ID: 40665471
Title: Focused ultrasound-mediated APOE4 knockdown in mouse brain.
Abstract: The apolipoprotein E (APOE) ε4 allele is widely recognized as the strongest genetic risk factor for late-onset Alzheimer's disease. Therapeutic strategies to reduce apoE4 expression in APOE ε4 carriers hold promise to mitigate neuroinflammatory and neurodegenerative processes driving disease progression. Focused ultrasound (FUS) was employed to transiently open the blood-brain barrier (BBB) for efficient knockdown of humanized APOE ε4 in the mouse brain via gene editing. The all-in-one clustered regularly interspaced short palindromic repeats (CRISPR)-based adeno-associated virus (AAV) vectors were administered intravenously at a dose of 1.5×1012 vg per mouse to determine the gene-editing efficacy within the hippocampus. FUS-enhanced delivery of AAV resulted in a 12.6% knockdown of APOE ε4 gene expression in the targeted hippocampus, accompanied by an over 20% decrease in apoE4 protein levels and significant reductions in astrocyte and microglia levels. Our findings demonstrate a noninvasive, targeted approach for APOE ε4 knockdown, highlighting FUS-mediated brain-directed interventions as a promising therapeutic strategy for Alzheimer's disease. Focused ultrasound (FUS) enables noninvasive, transient blood-brain barrier (BBB) opening for enhanced adeno-associated virus (AAV) delivery. FUS-mediated gene editing achieves a 12.6% knockdown in APOE ε4 expression within the hippocampus of mouse brain. APOE ε4 knockdown significantly reduces apoE4 protein levels and astrocyte and microglia levels. No detectable gross toxicity was observed following the FUS-mediated gene editing.

ID: 40670663
Title: Long-read RNA sequencing unveils a novel cryptic exon in MNAT1 along with its full-length transcript structure in TDP-43 proteinopathy.
Abstract: Understanding the role of transcript isoforms is essential for elucidating disease mechanisms. TDP-43 regulates RNA splicing, and its dysfunction in neurons is a hallmark of some neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). While an association between TDP-43-dependent cryptic exons and disease pathogenesis has been suggested, an approach to investigate how cryptic exons disrupt transcript isoforms has yet to be established. In this study, we developed IsoRefiner, a novel method for identifying full-length transcript structures using long-read RNA-seq. Leveraging this method, we performed long-read RNA-seq, guided by prior short-read RNA-seq, to comprehensively determine the full-length structures of aberrant transcripts due to TDP-43 dysregulation in human iPSC-derived motor neurons. We identified a novel TDP-43-dependent cryptic exon in the MNAT1 gene, along with its full-length transcript structure. Furthermore, we confirmed the presence of the MNAT1 cryptic exon in patients with ALS and FTD. Our findings deepen understanding of TDP-43 proteinopathy and advance splicing research.

ID: 41174170
Title: TDP-43-dependent mis-splicing of KCNQ2 triggers intrinsic neuronal hyperexcitability in ALS/FTD.
Abstract: Motor neuron hyperexcitability is a broadly observed yet poorly understood feature of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Nuclear depletion and cytoplasmic aggregation of the RNA splicing protein TAR DNA-binding protein 43 (TDP-43) are observed in most ALS and FTD patients. Here we show that TDP-43 dysfunction causes mis-splicing of KCNQ2, which encodes a voltage-gated potassium channel (Kv7.2) that regulates neuronal excitability. Using iPSC-derived neurons and postmortem ALS/FTD brain and spinal cord tissue we find widespread, disease-specific and TDP-43-specific skipping of an exon encoding the KCNQ2 pore domain. The mis-spliced mRNA escapes degradation and is translated into a nonfunctional protein with severely reduced ion conductance that aggregates in the endoplasmic reticulum and causes intrinsic hyperexcitability in ALS neuronal models. This event, which correlates with higher phosphorylated TDP-43 levels and earlier age of disease onset in patients, can be rescued by splice-modulating antisense oligonucleotides that dampen hyperexcitability in induced pluripotent stem cell cortical neurons and spinal motor neurons with TDP-43 depletion. Our work reveals that nuclear TDP-43 maintains the fidelity of KCNQ2 expression and function and provides a mechanistic link between established excitability disruption in ALS/FTD patients and TDP-43 dysfunction.

ID: 41568513
Title: CRISPR in Alzheimer's Disease: Engineering Genetic Solutions for Neurodegenerative Resilience.
Abstract: Alzheimer's Disease (AD), the primary etiology of dementia, remains a considerable challenge owing to the limited availability of pharmacological interventions that effectively modify the course of the disease. This review evaluates CRISPR/Cas9 gene editing as a therapeutic strategy for AD, focusing on its capacity to target genetic drivers (e.g., APP, APOE, PSEN1/2, CD2AP) and modify disease pathology. CRISPR offers unprecedented precision in disrupting AD-associated pathogenic alleles, addressing the limitations of conventional Aβ/tau-targeted therapies that have failed in clinical trials. CRISPR corrects mutations in iPSC/organoid models, normalizing Aβ42/40 ratios and reducing tau hyperphosphorylation. Preclinical studies demonstrate reversal of amyloid accumulation and synaptic degeneration. Key challenges include off-target effects, blood-brain barrier (BBB) delivery limitations, and ethical concerns around permanent genome modifications. This study emphasizes that CRISPR/Cas9 holds transformative potential for AD therapy by targeting root genetic causes. Future success hinges on enhancing delivery systems (e.g., BBB-penetrant vectors) and integrating next-generation editors (base/prime editing) for clinical translation.

ID: 41573891
Title: Dual-targeting snRNA gene therapy rescues STMN2 and UNC13A splicing in TDP-43 proteinopathies.
Abstract: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder caused by the selective deterioration of motor neurons in the central nervous system (CNS). A key driver of this pathogenesis is nuclear loss of ALS-associated protein TDP-43, leading to mis-splicing of TDP-43 targets including important neuronal genes STMN2 and UNC13A . Here, we have developed a gene therapy strategy for ALS and related TDP-43 proteinopathies, to correct mis-splicing of both STMN2 and UNC13A cryptic exons using small nuclear RNAs (snRNAs) encoded from a single vector. We identified promoter sequence elements to increase therapeutic snRNA expression by 10-fold, then further optimized the expression cassette with combinatorial snRNA targeting to rescue multiple cryptic splicing targets. The engineered snRNAs restored normal pre-mRNA processing of both STMN2 and UNC13A transcripts despite TDP-43 loss of function, rescuing stathmin-2 protein levels in iPSC derived motor neurons, restoring their axonal regeneration capacity to wild-type levels. In addition, adeno-associated virus (AAV) delivery of the snRNAs to the murine central nervous system in the constitutive cryptic splicing model Stmn2 HumΔGU fully restored cortical Stmn2 pre-mRNA processing, highlighting the utility of snRNAs as a therapeutic modality in vivo . Together, this study demonstrates that snRNAs are a promising and versatile therapeutic strategy for the simultaneous correction of multiple aberrant transcripts affected by cryptic splicing in TDP-43 proteinopathies.

ID: 41720774
Title: A neurotoxic cryptic peptide arising from TDP-43-dependent cryptic splicing of PKN1.
Abstract: Dysfunction of transactive response DNA-binding protein 43 (TDP-43) drives neurodegeneration in amyotrophic lateral sclerosis (ALS) and Alzheimer's disease (AD), in part through inducing aberrant RNA splicing. However, whether such mis-splicing yields stable, pathogenic proteins remains unclear. Here, we identify a TDP-43-repressed cryptic exon in Protein kinase N1 (PKN1), designated PKN1-5a1, which is activated in ALS patient brains and introduces a premature termination codon. This aberrant transcript escapes nonsense-mediated decay and is translated into a truncated peptide, PKN1-N207 (PKN207), detectable in AD brains with TDP-43 pathology. In mice, PKN207 impairs cognition, memory, and synaptic plasticity. Our findings demonstrate that TDP-43 loss-induced cryptic splicing can generate stable neurotoxic polypeptides, revealing a peptide-mediated mechanism in TDP-43 proteinopathies.

ID: 41796799
Title: RNA-binding proteins TDP-43 and FUS promote R-loop resolution and regulate transcription termination.
Abstract: TDP-43 and FUS are RNA-binding proteins involved in the regulation of diverse RNA-processing events and have been strongly implicated in neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). We have previously demonstrated the role of symmetrical dimethylation (me2s) of a conserved arginine residue (R1810 in human POLR2A) in the C-terminal domain (CTD) of RNA polymerase II (RNAPII), which facilitates the recruitment of the Tudor domain-containing protein SMN to resolve R-loops at transcriptional termination sites. Here, we demonstrate that TDP-43 and FUS contribute to transcription termination through the R1810me2s-SMN pathway. Our data show that TDP-43-and to a lesser extent, FUS-are recruited to chromatin via this pathway, and that disruption of their recruitment leads to defective RNAPII termination. This impairment results in the accumulation of R-loops and elevated DNA damage to gene terminators. Using transcriptome-wide analyses, we further show that TDP-43 RNA-binding sites are highly correlated with regions of R-loop formation. Importantly, we find that the RNA-binding activity of TDP-43 is essential for its role in resolving R-loops and promoting efficient transcription termination. These findings establish a mechanistic link between TDP-43/FUS, R-loop resolution, and transcription termination, providing new insights into how their dysfunction may drive genome instability and contribute to the pathogenesis of ALS and FTD.

ID: 41835941
Title: The delivery challenge of adeno-associated virus vector-based gene therapies for neurological diseases.
Abstract: There is great anticipation that gene therapies can offer solutions to many neurological diseases. Already, much is known about therapeutic targets and how they would need to be manipulated to mitigate disease. For such gene therapies to move to the clinic, potent CNS delivery vehicles are needed. One line of investigation focuses on adeno-associated viruses (AAV) to address this need. In particular, blood-brain barrier (BBB)-penetrant AAV capsids are of interest due to the relative ease of their intravenous administration. This review will introduce this topic and provide an update on recent developments. First, we describe the physical barriers that must be overcome for AAV-delivered gene therapies to reach target cells in the CNS. We then put a spotlight on the natural AAV9 capsid's inherent propensity to cross the BBB and key lessons learned from its use for delivering a therapeutic payload for the treatment of spinal muscular atrophy. Next, we summarize methods for engineering recombinant AAV (rAAV) capsids with improved brain penetrance, and present in vitro paradigms for predicting their capacity to cross the human BBB. We also present strategies for side-stepping the delivery limitations of existing rAAV vectors. Finally, we point toward a few notable clinical studies whose outcomes may advance our understanding of what rAAV-delivered gene therapies can offer to people afflicted with CNS disorders.

ID: 41864145
Title: Emerging disease-modifying therapies for Angelman syndrome: A comprehensive review for pediatric neurologists.
Abstract: Angelman syndrome (AS), a rare neurogenetic disorder affecting approximately 1 in 15,000 live births, results from loss of functional UBE3A gene expression and manifests with severe developmental delay, intellectual disability, absent speech, ataxia, epilepsy, and distinctive behavioral features. Until recently, only symptomatic management was available. This review provides pediatric neurologists with a comprehensive, practice-oriented overview of emerging disease-modifying therapies for AS, focusing on therapeutic approaches advancing through clinical development. The molecular pathophysiology of AS, natural history considerations critical for trial interpretation, and the current evidence for antisense oligonucleotide (ASO) therapies (ION582, GTX-102/apazunersen, rugonersen), gene replacement approaches (MVX-220), and next-generation strategies including CRISPR-based gene editing, artificial transcription factors, small molecules, and novel delivery platforms are reviewed. ASO therapies targeting the UBE3A antisense transcript represent the most clinically advanced approach, with three candidates showing proof-of-concept efficacy in Phase 1/2 studies and two advancing to pivotal Phase 3 trials. Gene replacement therapy offers potential single-administration treatment but faces challenges regarding safety, immune responses, and durability. Next-generation approaches including CRISPR activation, epigenetic editing, and blood-brain barrier-penetrating delivery systems show preclinical promise. Critical challenges include outcome measurement limitations, genotype stratification, long-term safety monitoring, and ensuring equitable access. These advances herald a transformation in AS clinical care and represent a milestone in precision pediatric neurology.

ID: 41865126
Title: Recent Advances in the Non-viral Delivery of Genes to Central Nervous System Disorders.
Abstract: Disorders of the central nervous system (CNS), neurological disorders, neurodegenerative disorders, genetic disorders) constitute a significant burden on global health, and current treatment options remain challenging. As treatment for CNS disorders is primarily palliative, the underlying causes of disease progression are not addressed through conventional pharmacologic therapies. Gene therapy has the potential to address these root causes of disease progression; however, many of the vectors used in gene therapy (e.g., adeno-associated viruses (AAVs)) have limitations such as immunogenicity, low cargo capacity, and crossing the blood-brain barrier (BBB). These limitations have led to significant progress in the development of non-viral gene delivery systems. Compared with viral vectors, non-viral platforms offer improved safety profiles, greater design flexibility, lower production costs, and superior suitability for repeated administration. This review reports recent advancements in the development of non-viral platforms for CNS gene delivery and focuses on lipid-based nanoparticles, polymeric nanoparticles, exosome-based techniques, and new hybrid technologies. Particular emphasis is placed on nanoparticle modification approaches to enhance BBB penetration and enable delivery of genome-editing technologies (CRISPR/Cas systems). The review provides explanations of clinical trials, regulatory considerations, and manufacturing issues that result from the recent developments noted above. It also explores the emerging role of artificial intelligence in supporting carrier design and enhancing delivery efficiency. Both artificial intelligence and non-viral platforms have the potential to facilitate the advancement of safe, effective, and repeatably administered gene therapies for patients with CNS disorders.

ID: 41890591
Title: Axonal transport impairment as an upstream mechanism in amyotrophic lateral sclerosis pathogenesis.
Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive loss of upper and lower motor neurons. Despite marked genetic and pathological heterogeneity, a unifying pathogenic framework remains lacking. We propose that axonal transport impairment represents an early and convergent but genotype-modulated upstream vulnerability in ALS, contributing to distal synaptic failure, bioenergetic stress, protein aggregation, neuroinflammation, and neuronal death. Across many ALS models, including SOD1, TARDBP (TDP-43), FUS, and C9orf72, transport deficits are frequently detectable in presymptomatic stages, often preceding overt motor neuron loss or clinical manifestation, although temporal ordering varies by molecular subtype. Human data from induced pluripotent stem cell-derived motor neurons and neuroimaging in mutation carriers further support early transport dysfunction in both familial and sporadic ALS. We synthesize genetic, cellular, and systems-level evidence demonstrating that diverse ALS-associated mutations converge on intracellular trafficking machinery through distinct but interacting mechanisms, disrupting long-range cargo delivery and clearance in motor neurons. This framework provides a mechanistic basis for selective motor neuron vulnerability, the dying-back pattern of neuromuscular junction degeneration, and the emergence of downstream pathological hallmarks including mitochondrial dysfunction, excitotoxicity, aggregation, and inflammation. This model generates testable predictions regarding presymptomatic transport biomarkers and the timing of therapeutic intervention. We discuss implications for biomarker development and therapeutic strategy, proposing restoration of axonal transport as a central component of rational multimodal disease modification in ALS.

ID: 41909467
Title: Exosome-like nanovesicles from acerola for CRISPR-Cas9 ribonucleoprotein delivery to the central nervous system.
Abstract: An aberrant six-base repeat in intron 1 of C9orf72 is the most frequent cause of solitary and familial amyotrophic lateral sclerosis and frontotemporal dementia. This mutation is a potential target for CRISPR/Cas9-based genome editing. However, the blood-brain barrier and limitations of current viral or nanoparticle-based delivery systems to neurons significantly restrict the clinical application of CRISPR-Cas9 in the brain. To address these challenges, we developed a drug delivery system using acerola-derived exosome-like nanoparticles (AELNs), which may overcome several limitations associated with human exosomes. AELNs stably form complexes with ribonucleoproteins (RNPs) comprised of Cas9 proteins and guide RNAs (gRNAs). We improved the delivery efficiency and selectivity of AELN/RNP complexes in GLP2-receptor-expressing neurons by incorporating GLP2 peptides into the AELN/RNP complexes. Intranasal administration of peptide-tagged AELN/RNP complexes in vivo confirmed the successful genome editing of C9orf72, demonstrating the potential of this system for treating neurodegenerative diseases. This study presents a potentially innovative approach for in vivo genome editing using a noninvasive delivery system.

ID: 41919473
Title: Long non-coding RNAs in neurodegenerative diseases - Molecular mechanisms, liquid biopsy biomarkers, and therapeutic targets: A review.
Abstract: Neurodegenerative diseases (NDDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD), are age-related disorders characterized by progressive neuronal loss, cognitive decline, and limited options for disease-modifying treatments. Increasing evidence suggests that long non-coding RNAs (lncRNAs) play significant roles in neurodevelopment, neuronal homeostasis, and disease progression; however, their involvement in shared pathogenic pathways and clinical applications remains inadequately defined. This review consolidates recent experimental, transcriptomic, bioinformatic, and emerging clinical findings regarding the role of lncRNAs in NDDs. We examine how lncRNAs modulate common disease mechanisms, including protein misfolding and aggregation, neuroinflammation, mitochondrial dysfunction, ferroptosis, synaptic failure, and aging-related neurodegenerative processes. These regulatory functions occur through various mechanisms, including epigenetic modifications, transcriptional regulation, post-transcriptional processes, and RNA-protein interactions, as well as novel mechanisms such as liquid-liquid phase separation (LLPS), peptide coding, and exosome-mediated intercellular communication. Current evidence supports the potential of lncRNAs as minimally invasive liquid biopsy biomarkers, detectable in blood, cerebrospinal fluid (CSF), and extracellular vesicles. Additionally, lncRNAs may serve as therapeutic targets through antisense oligonucleotides (ASOs), gene editing, and engineered delivery platforms. Overall, lncRNAs have emerged as central molecular regulators and promising candidates for translation in NDDs. Nonetheless, challenges related to specificity, validation, delivery across the blood-brain barrier, and clinical standardization must be addressed before their routine application in precision neurology.

ID: 41931258
Title: CRISPR-Cas9 and next-generation gene editing strategies for therapeutic intervention of neurodegenerative pathways in Alzheimer's disease: a state-of-the-art review.
Abstract: Alzheimer's disease (AD) is a progressive and multifactorial neurodegenerative disorder and the leading cause of dementia worldwide, characterized by extracellular amyloid-β (Aβ) plaque deposition, intracellular neurofibrillary tangles composed of hyperphosphorylated tau, synaptic loss, mitochondrial dysfunction, oxidative stress, and chronic neuroinflammation. Despite major advances in understanding its molecular basis, currently approved therapies remain largely symptomatic and fail to halt or reverse neurodegeneration, emphasizing the urgent need for disease-modifying strategies. In this comprehensive state-of-the-art review, we examine the rapidly evolving landscape of CRISPR-Cas9 and next-generation gene-editing technologies, including base editors and prime editors, as innovative therapeutic platforms for precisely modulating AD-associated genetic and molecular pathways. We discuss targeting of critical genes such as APOE4, APP, PSEN1, PSEN2, and MAPT, which play central roles in amyloid processing, tau pathology, lipid metabolism, and neuroinflammatory cascades, and evaluate strategies for allele-specific correction, gene silencing, and transcriptional regulation using CRISPR interference/activation and epigenome editing tools. The review further explores multiplex editing approaches that simultaneously target interconnected pathogenic networks underlying Aβ accumulation, tau hyperphosphorylation, microglial activation, and synaptic dysfunction. A central focus is placed on overcoming delivery barriers to the central nervous system, particularly the blood-brain barrier (BBB), highlighting advances in engineered adeno-associated viral vectors, lentiviral systems, lipid nanoparticles, polymeric nanocarriers, exosome-based delivery, receptor-mediated transcytosis, immune-evasive vector design, and focused ultrasound-mediated BBB modulation. Review examines the integration of bioinformatics, multi-omics profiling, and artificial intelligence-guided design to enhance editing specificity, efficiency, and safety while minimizing off-target effects. Preclinical evidence demonstrating reductions in amyloid burden, attenuation of tau pathology, restoration of synaptic function, and improvement in cognitive performance is critically evaluated. This review discusses translational challenges, including immunogenicity, long-term genomic stability, ethical considerations, and regulatory frameworks. It outlines future directions, emphasizing personalized, precision-based, and durable gene-editing strategies that may redefine therapeutic intervention for AD.

ID: 41943580
Title: DCPS modulates TDP-43-linked neurodegeneration through P-body-mediated RNA decay.
Abstract: The proteinopathy of the RNA-binding protein TDP-43, characterized by nuclear clearance and cytoplasmic inclusion, is a hallmark of multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer's disease (AD). Through CRISPR interference (CRISPRi) screening in human neurons, we identified the decapping scavenger enzyme (DCPS) as a novel genetic modifier of TDP-43 loss-of-function (LOF)-mediated neurotoxicity. Our findings reveal that TDP-43 LOF leads to aberrant mRNA degradation via dysregulating the properties and activity of processing bodies (P-bodies). TDP-43 interacts with P-body component proteins, potentially influencing their dynamic equilibrium and assembly into ribonucleoprotein (RNP) granules. Loss of TDP-43 hyperactivates P-bodies, increasing mRNA association and RNA decay. Reducing DCPS restores P-body integrity and RNA turnover, ultimately improving neuronal survival. Overall, this study highlights a novel role of TDP-43 in RNA processing through P-body regulation and identifies DCPS as a potential therapeutic target for TDP-43 proteinopathy-related neurodegenerative diseases.

ID: 41964251
Title: RNA G-quadruplex-protein interactions: from nuclear RNA processing to cytoplasmic stress response and neurodegeneration.
Abstract: RNA G-quadruplexes (rG4s) are stable secondary structures formed by non-canonical Hoogsteen base-pairing of guanine-rich sequences in precursor and mature messenger and non-coding RNAs. We review evidence that rG4s exist in two functionally distinct worlds. In the nucleus, rG4s fold co-transcriptionally to regulate gene expression and RNA processing and organizing membraneless organelles through liquid-liquid phase separation. Splicing regulation by rG4s is restricted to vertebrates and co-evolved with transcriptome complexity. In the cytoplasm, rG4s are actively maintained in an unfolded state by dedicated helicases and RNA-binding proteins, but fold upon stress to nucleate stress granules, that sequester mRNAs and sustain cell survival. When compartmentalization of rG4-protein interactions fails, cells lose both nuclear RNA processing control and cytoplasmic translational regulation and proper stress response. The same biophysical properties that make rG4s effective scaffolds for reversible phase separation in RNA processing, proteostasis, and acute stress become liabilities under chronic conditions: in ageing neurons, failure of rG4-protein homoeostasis transforms protective condensates into irreversible aggregates associated with α-synuclein, tau, TDP-43, and FUS pathology. We discuss the implications of a dynamic equilibrium of folded and unfolded rG4s in health and disease, with particular focus on their emerging roles in neurodegeneration.

ID: 41987571
Title: QCatch: a framework for quality control assessment and analysis of single-cell sequencing data.
Abstract: Single-cell sequencing data analysis requires robust quality control (QC) to mitigate technical artifacts and ensure reliable downstream results. While tools like alevin-fry and simpleaf (and augmented execution context for the alevin-fry), offer flexibility and computational efficiency to process single-cell data, this ecosystem will further benefit from a standardized QC reporting tailored for its outputs. We introduce QCatch, a Python-based command-line tool that generates comprehensive and interactive HTML QC reports designed specifically for single-cell quantification results. Taking the output directory of alevin-fry or simpleaf as the input, QCatch is able to perform essential processing steps, like cell calling, and generate detailed QC reports that contain informative visualizations and statistics, including unique molecular identifier (UMI) count distributions, sequencing saturation estimates, and splicing status information, for QC assurance. Built for seamless integration into downstream analysis workflows, QCatch exports the processed results in a richly-annotated H5AD format file, a widely used data format common among many downstream single-cell data analysis tools. The source code and documentation of QCatch are available on GitHub at https://github.com/COMBINE-lab/QCatch. QCatch can be installed via both Bioconda and PyPI.

ID: 42010065
Title: Recent advances in lipid and biomimetic nanocarriers for nucleic acid delivery in glioblastoma.
Abstract: Glioblastoma (GBM) remains uniformly lethal due to diffuse invasion, extensive molecular heterogeneity, and a profoundly immunosuppressive microenvironment. Nucleic-acid therapeutics—including antisense oligonucleotides, RNA interference, messenger RNA, and CRISPR-based genome editing—offer programmable control over oncogenic drivers and immune pathways, yet their clinical translation is hindered by rapid nuclease degradation, systemic clearance, restricted blood–brain-barrier transport, inefficient cellular uptake, and endosomal entrapment. Recent progress in nanotechnology has enabled the rational design of nanoparticle platforms that overcome these multilayered biological obstacles. This review summarizes advances (2022–2025) in lipid and biomimetic nanocarriers engineered to enhance nucleic-acid delivery for GBM therapy. For instance, ionizable lipid nanoparticles with pH-responsive chemistry and optimized head-group design achieve efficient cytosolic release with improved biocompatibility, while biomimetic systems, such as cell-membrane-, lipoprotein-, virus-, DNA-, and exosome-mimicking platforms, leverage natural transport and recognition pathways for tumor-specific targeting and immune evasion. Finally, we discuss translational considerations, including GMP-compatible manufacturing, batch consistency, long-term safety and immunogenicity, and advanced model selection, and outline future opportunities in high-throughput lipid discovery, AI-assisted ligand design, hydrogel-mediated spatiotemporal release, and patient-tailored nanotherapies. Collectively, these emerging nanocarriers offer a convergent strategy to navigate physiological barriers and advance precision nucleic-acid therapeutics against glioblastoma.

ID: 42013476
Title: Cryptic Splicing in ALS: From Driving Disease Progression to Unlocking Novel Therapeutics.
Abstract: TDP-43 is an RNA-binding protein that regulates multiple aspects of RNA processing, and its mislocalization from the nucleus to the cytoplasm is a defining feature of amyotrophic lateral sclerosis (ALS). While both loss- and gain-of-function mechanisms contribute to disease, the discovery of cryptic splicing has shed light on the downstream consequences of TDP-43 nuclear clearance for neuronal health. Here, we highlight how loss of nuclear TDP-43 can drive a cascade of events that lead to the impairment of cellular proteostasis and result in a positive feedback loop that perpetuates neuronal dysfunction. This sustains the appearance of cryptic splicing events in genes that are involved in key pathways for the maintenance of axonal homeostasis and synaptic transmission. In contrast to their detrimental effects on neuronal health, cryptic splicing mechanisms may be harnessed to develop novel therapeutic strategies, unprecedentedly expanding the availability of therapeutic avenues for TDP-43 proteinopathies.

ID: 42041587
Title: Gene Editing Strategies for Neurological and Mental Disorders: Advances in Delivery, Methodology, and Clinical Translation.
Abstract: Neurological and mental disorders are among the main causes of disability worldwide, affecting over three billion people and increasing the socioeconomic burden. Advances in molecular genetics and genome engineering have led to gene-targeted therapies that address root causes rather than just symptoms. This review covers current genome-editing tools, including CRISPR/Cas, base editing, and prime editing. The focus is on the benefits of gene editing in the central nervous system, where post-mitotic neurons allow lasting effects after a single treatment. It also discusses emerging delivery platforms such as viral vectors, nanoparticles, and exosome systems, as well as methods to bypass the blood-brain barrier. Recent clinical progress in spinal muscular atrophy, Parkinson's disease, Huntington's disease, and Alzheimer's disease is highlighted, with promising preclinical results for autism, bipolar disorder, epilepsy, and other neurogenetic conditions. The review concludes with regulatory issues, market trends, and ongoing clinical trials, underscoring the potential of gene therapies to transform disease management and provide long-term solutions.

ID: 42083963
Title: Advances in Microneedle Technology for Targeted Therapy in Alzheimer's and Parkinson's Disease.
Abstract: The fourth major cause of death worldwide is Neurodegenerative Diseases (NDs), including Alzheimer's and Parkinson's disease. The existing therapies have only a small effect on alleviating symptoms, mainly because the therapeutic agents are difficult to cross the bloodbrain barrier. The purpose of the review is to discuss the potential of microneedle-based transdermal delivery systems to improve the delivery of drugs to the central nervous system and thereby manage neurodegenerative diseases effectively. The article summarizes and synthesizes the available literature that targets the strategies of microneedle-mediated drug delivery. The literature on the design, composition, pharmacokinetics, and mechanistic benefits of different microneedle platforms for surmounting central nervous system barriers was identified and thematically synthesized. Microneedle systems have emerged as non-invasive delivery systems with the potential for localized and sustained drug delivery, overcoming the stratum corneum and the blood-brain barrier. Micro-needles can be used to deliver small molecules, peptides, and nanoparticles to the brain, thereby avoiding systemic side effects and enhancing drug bioavailability. Some of those designs include dissolving, coated, hollow, hydrogel-forming, and stimuli-responsive microneedles, which have been shown to target the brain and exhibit higher therapeutic efficiency in preclinical models. Although technological advances have improved, the clinical translation of microneedlebased strategies remains limited. The future directions could include using microneedles with stem cell-based therapies, CRISPR/Cas9 gene editing, artificial intelligence-based delivery systems, and responsive release technology to facilitate customized treatment. The Microneedle-based drug delivery systems are promising in overcoming the current limitations in the treatment of neurodegenerative diseases. Nonetheless, a large-scale clinical validation is necessary to guarantee safety, efficacy, and scalability to be applied to real-life scenarios.

ID: 42086533
Title: Proteasomal-dependent CHK1 degradation leads to DNA damage accumulation in ALS cellular model systems.
Abstract: Amyotrophic lateral sclerosis (ALS) is characterised by the aggregation of TDP-43 and mutant FUS in the cytoplasm of affected motor neurons. Accumulation of DNA damage is emerging as a novel correlative trait of ALS. We recently showed that formation of TDP-43 and FUS cytoplasmic inclusions (CIs) lead to DNA damage accumulation through dysregulation of the DNA damage response (DDR). However, the multiple molecular mechanisms contributing to DNA damage accumulation in affected motor neurons in ALS have not been fully elucidated. In recent years, chemical inhibition of the serine/threonine kinase CHK1 was shown to lead to accumulation of DNA breaks as well as increased apoptosis, in differentiated cortical neurons. Notably, CHK1 has been involved in DNA double-strand break repair in non-dividing cells, by acting through the histone chaperone ASF1A. In this article, we show that cells bearing FUS and TDP-43 CIs show downregulation of the protein levels of CHK1 and ASF1A. We observe CHK1 protein downregulation in neuronal cell lines, as well as in patient-derived motor neurons progenitors and in the spinal cord of a FUS-ALS mouse model. Restoration of the nuclear levels of CHK1 and ASF1A via transient overexpression, is sufficient to reduce DNA damage signal accumulation and rescues DDR defects. Importantly, we show that the ubiquitin-proteasome pathway is responsible for CHK1 degradation in cells bearing FUS CI, since its inhibition restores CHK1 and ASF1A protein levels. Our study demonstrates that proteasomal-dependent CHK1 and ASF1A downregulation contributes to accumulation of DNA damage in cells affected by ALS-linked protein aggregates.

ID: 42096556
Title: Short RNA chaperones promote aggregation-resistant TDP-43 conformers to mitigate neurodegeneration.
Abstract: Aberrant aggregation of the prion-like RNA binding protein TDP-43 drives several fatal neurodegenerative proteinopathies, including amyotrophic lateral sclerosis (ALS). In this work, we define how short, specific RNAs solubilize TDP-43. These short RNAs engage and stabilize the TDP-43 RNA recognition motifs, which allosterically destabilizes a conserved helical region in the prion-like domain, thereby promoting aggregation-resistant conformers. Sequence-space mining identified short RNA chaperones with enhanced activity against TDP-43 and disease-linked variants. Enhanced short RNA chaperones mitigated aberrant TDP-43 phenotypes in optogenetic models and in ALS patient-derived and control motor neurons. In mice with cytoplasmic TDP-43 aggregation and motor neuron loss, an enhanced short RNA chaperone reduced pathological aggregation, restored TDP-43 function, and conferred neuroprotection. These results define a mechanistic and therapeutic framework for RNA-based strategies to counter TDP-43 proteinopathies.

ID: 42108387
Title: Rational Design and Optimisation of CRISPR-Cas9 Delivery Systems for Targeted Genomic Transformation.
Abstract: The CRISPR-Cas9 genome-editing technique offers a promising therapeutic strategy for genetic disorders, including neurodegenerative diseases like Alzheimer's disease (AD), characterised by inherited susceptibility and progressive cognitive decline, as well as other hallmarks such as amyloid beta (Aβ1-42) plaques and neurofibril tangles (NFTs). However, the blood-brain barrier (BBB) poses a significant challenge to the effectiveness of gene editing components in the affected brain region and impedes clinical translation. This comprehensive review compares various CRISPR-Cas9 delivery vectors, viral, nonviral and physical, with a focus on their efficacy in neurological diseases such as AD. Viral vectors viz., adeno-associated viruses (AAVs) and lentiviruses (LVs) demonstrate high transduction efficiency and BBB permeability. AAVs are preferred for their low immunogenicity, minimal toxicity, high neuronal tropism and episomal persistence, enabling sustained expression without insertional mutagenesis. LVs offer larger genetic payloads but raise concerns about genomic integration and potential oncogenesis, though integration-defective variants mitigate these risks. Nonviral vectors, including peptide and polymer-based nanoparticles, lipid nanoparticles (LNPs) and Inorganic carriers such as gold and silver nanoparticles, are less immunogenic and easier to handle but require further optimisation for in vivo BBB crossing and endosomal escape. Physical methods such as electroporation and microinjection are suitable for in vitro/ex vivo use, while novel CNS-targeted strategies, such as RVG-tagged particles, TfR-directed LNPs and engineered AAV variants, enhance brain penetration via receptor-mediated transcytosis. These preclinical studies show that these technologies can successfully edit genes and provide therapeutic benefits, including amyloid reduction and cognitive improvement in AD models. Yet off-target effects, immune responses and regulatory hurdles persist. Overall, continuous innovation in delivery vector design and safety profile-targeting strategies is crucial for advancing CRISPR-Cas9 towards clinical therapies for AD-based therapies and related neurological disorders.

ID: 42119563
Title: RegVelo: Gene-regulatory-informed dynamics of single cells.
Abstract: Cell fate transitions are driven by regulatory circuitry, yet RNA velocity models cellular dynamics without explicitly accounting for gene regulatory interactions, limiting mechanistic insight. Conversely, gene regulatory network (GRN) inference methods largely neglect the dynamic nature of biological systems. To overcome this conceptual disconnect, we present RegVelo, a bottom-up, actionable, and interpretable deep learning framework that jointly models splicing kinetics and gene regulatory interactions. Across diverse biological systems, RegVelo provides reliable predictive power for terminal states, gene interactions, and perturbation simulations. By applying RegVelo to zebrafish neural crest development using full-length Smart-seq3 and shared gene expression and chromatin accessibility measurements, we delineate regulatory programs underlying fate specification. Guided by in silico perturbations and validated by CRISPR-Cas9 knockout and single-cell Perturb-seq, we establish tfec as an early driver and elf1 as a regulator of pigment cell fate. RegVelo establishes a quantitative framework for bridging gene regulation and cell fate decisions.

ID: 42127163
Title: Analyzing the performance of deep learning splice prediction algorithms.
Abstract: SpliceAI is the leading tool for predicting splice-altering variants, but restrictive licensing limits clinical adoption. While open-source implementations have been published with author-reported comparisons, independent benchmarking across diverse datasets is needed to establish equivalence. We compared the original SpliceAI with two open-source implementations (OpenSpliceAI and CI-SpliceAI) and a legacy ensemble baseline across six datasets: a curated set of 1,316 validated variants, 213 variants with splice-assay data, 99,601 variants from the SPiP splicing prediction study, 242 manually curated deep intronic pathogenic variants, and two ClinVar-derived datasets comprising 53,600 intronic variants and 58,064 variants spanning all genomic contexts. The deep learning models were also evaluated against an ensemble of four legacy splice-prediction tools. Across all datasets, the deep learning algorithms outperformed the legacy ensemble. All three deep learning algorithms showed similar performance on the larger datasets dominated by canonical splice site variants (balanced accuracies 0.889-0.977). On the deep intronic benchmark, the original SpliceAI achieved the highest balanced accuracy (0.940), outperforming both CI-SpliceAI (0.890) and OpenSpliceAI (0.841). Critically, optimal thresholds for deep intronic variants were an order of magnitude lower than standard recommendations, indicating that default thresholds would miss the majority of pathogenic deep intronic variants. A correlation analysis showed that CI-SpliceAI maintained balanced concordance across event types, whereas OpenSpliceAI showed stronger correlation for loss events than gain events. Both implementations showed high positional agreement with SpliceAI, with exact splice-site match rates exceeding 90% across event types. Together, these results demonstrate that both open-source reimplementations of SpliceAI successfully reproduce the predictive behavior of the original algorithm across multiple evaluation contexts, while consistently outperforming traditional splice prediction methods. However, performance diverges on deeply intronic variants, and standard score thresholds are poorly calibrated for this variant class regardless of algorithm choice.

ID: 42131110
Title: Single cell Raman spectroscopic profiles predict treatment responses in patients with de novo acute myeloid leukemia.
Abstract: Leukemia is a clonal malignant proliferative disease originating from hematopoietic stem cells. Although its treatment strategy has gradually developed from traditional chemotherapy to a multimodal treatment system including novel targeted therapy and immunotherapy, primary drug resistance in particular remains the core clinical problem leading to poor patient prognosis. This clinical dilemma indicates that the traditional genotyping system based on genomics has not been able to fully resolve the molecular heterogeneity of acute myeloid leukemia (AML), and it is urgent to establish a precise stratified model that can dynamically reflect the functional status of tumor cells in the initial stage of treatment. In this study, Raman spectroscopy (RS) combined with machine learning algorithm was used to construct a metabolic prognosis prediction model for AML chemotherapy response. Bone marrow single cell Raman spectroscopy data of newly diagnosed AML patients were collected, and the molecular fingerprint was analyzed by principal component analysis linear discriminant analysis (PCA-LDA) and multivariate curve resolute alternating least square method (MCR-ALS). The results showed that the PCALDA model achieved complete remission or non-remission (CR/NR) classification through 24 principal components (cumulative variance contribution of 90.1%), the accuracy of external validation was 94.8% (sensitivity 97.9%, specificity 92.0%), and the AUC reached 96.27%. Protein, lipid, nucleic acid and mixed components were decomposed by MCR-ALS, and lipid and nucleic acid metabolic pathways were enriched in NR group (P < 0.001). Studies have shown that RS single-cell metabolic fingerprint can decode the metabolic reprogramming features associated with chemotherapy resistance in AML, providing a new marker-free and highly sensitive tool for real-time prognostic stratification and targeted intervention.

ID: 42135338
Title: Generation of spinal cord organoids from human induced pluripotent stem cells caudalised to a lumbar fate.
Abstract: Organoids offer a powerful platform to model human development and disease in vitro, while preserving key features of in vivo tissue architecture and complexity. In this study, we developed a protocol to generate human induced pluripotent stem cell (iPSC)-derived spinal cord organoids patterned to the lumbar region. Through immunofluorescent labelling and single-cell RNA sequencing analyses of these lumbar spinal cord organoids, we identified an enriched neuronal population complemented by a diverse array of glial subtypes that successfully recapitulate the ventral spinal cord, demonstrating greater anatomical relevance than conventional 2D motor neuron cultures. Notably, these organoids displayed functional neuronal properties, including spontaneous activity, indicative of integrated neural networks. This spinal cord organoid platform provides a physiologically relevant model for investigating human spinal cord development and presents a promising tool for studying neurodegenerative diseases and spinal cord injury in a controlled, human-specific context.

ID: 42135512
Title: Integrated single-cell and spatial transcriptomic profiling in ALS uncovers peripheral-to-central immune infiltration and reprogramming.
Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder marked by progressive motor neuron (MN) degeneration in the brain and spinal cord. Although neuroinflammation is increasingly recognized as a hallmark of ALS, the precise molecular programs linking immune responses to MN pathology remain poorly defined. Using an integrated approach that combines single-cell and bulk RNA sequencing with spatial proteogenomics, we characterized both shared and distinct immune dynamics in peripheral blood and spinal cord tissues from patients with sporadic ALS and those carrying C9orf72 repeat expansions. Our analysis revealed broad immune remodeling in C9orf72 ALS, ALS subtype-specific and progression-associated differences in monocyte activation and antigen-experienced CD8 effector memory T cells with clonal features consistent with antigen-driven responses. Spatial mapping revealed complement activation and lipid-programmed myeloid states converging at sites of MN loss and TDP-43 pathology. Together, these findings connect peripheral and central immune alterations to ALS heterogeneity and highlight stratified immunomodulation as a potential therapeutic strategy.

ID: 42135750
Title: Maintenance and disruption of the physiological dimer structure of TDP-43 in amyotrophic lateral sclerosis and frontotemporal lobar degeneration.
Abstract: Transactive response DNA-binding protein of 43 kDa (TDP-43) is an essential regulator of RNA metabolism, playing a pivotal role in splicing, transport, and stability. While its cytoplasmic aggregation is the pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), recent evidence suggests that the earliest pathogenic event is the disruption of its physiological homodimeric structure. Under healthy conditions, TDP-43 forms dimers via its N-terminal domain, a configuration that is crucial for its nuclear solubility and cooperative RNA binding. In this review, we propose the "Molecular Zipper" hypothesis to describe the maintenance of TDP-43 structural homeostasis. In this framework, the N-terminal domain acts as a stabilizing "NTD-mediated anchor" that keeps the protein in a functional, "zipped" dimeric state, effectively sequestering its aggregation-prone C-terminal regions. Pathogenic triggers-including genetic mutations, aberrant post-translational modifications such as phosphorylation and acetylation, and environmental stressors-can "unzip" this structure, leading to the formation of pathogenic monomers. These pathogenic monomers show increased propensity for cytoplasmic mislocalization and recruit wild-type protein into aggregates through a prion-like seeded aggregation mechanism, culminating in nuclear functional loss and cytoplasmic gain-of-toxicity. We further evaluate the emerging diagnostic landscape, focusing on methods to monitor the dimer-to-monomer ratio. Integrating prior biochemical data on TDP-43 dimerization with structural modeling enables a more coherent account of the transition from the physiological dimer to pathological conformers. The Molecular Zipper framework offers a conceptual foundation for reconciling existing experimental findings and for guiding future studies on early structural changes in TDP-43 proteinopathy.

ID: 42135847
Title: TDP-43: [GU]-ardian of the transcriptome.
Abstract: TDP-43 is a ubiquitously expressed, primarily nuclear DNA/RNA-binding protein implicated in neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer's disease (AD). In this review, we examine the structure and regulation of TDP-43, how these features influence its localization and functional activity, and how their disruption may contribute to disease. Among TDP-43's diverse functions, splicing repression of nonconserved RNA sequences termed cryptic exons has emerged as especially central to human disease. TDP-43 nuclear depletion and cytoplasmic aggregation are well-established pathological features in affected neurons and glia of neurodegenerative diseases, and accumulating evidence suggests that loss of TDP-43-mediated splicing repression occurs presymptomatically in disease. Advances in RNA-sequencing have enabled systematic identification of cryptic exon inclusion as a sensitive marker of TDP-43 dysfunction. Here, we synthesize current knowledge of TDP-43 biology and curate datasets from human tissues and experimental models, focusing on cryptic splicing to provide a resource for leveraging cryptic exon biology to better understand, detect, and target TDP-43 dysfunction.

ID: 42156927
Title: HELIX: a scalable model for predicting context-dependent regulation of RNA splicing and isoform usage.
Abstract: Context-dependent alternative splicing plays a critical role in disease pathogenesis and organ development, but its complex regulation remains challenging to predict. Here, to address this, we developed HELIX, a hierarchical deep learning framework that integrates pre-mRNA sequence and RNA-binding protein expression profiles to predict tissue- and condition-specific splicing patterns and transcript isoform usage simultaneously. By leveraging both short-read and long-read RNA sequencing data during training, HELIX achieves greater accuracy than existing splicing prediction models and conventional short-read-based methods in predicting differential splicing events, splicing strength at highly regulated splice sites, and isoform usage. The model enables systematic identification of tissue-specific splicing quantitative trait loci and their functional impacts. Furthermore, HELIX predicts patient-specific splicing dysregulation with quantitative attribution to genetic variants and abnormal RNA-binding protein expression in colon cancer cohorts. Through transfer learning, the HELIX model can be adapted to single-cell RNA sequencing data, thereby enabling the prediction of cell-type-specific isoforms.

ID: 42178983
Title: Protein Disulfide Isomerase Disassembles TDP-43/G3BP1 Condensates and Antagonizes TDP-43 Pathological Aggregates.
Abstract: Cytoplasmic mislocalization and aggregation of transactive response DNA-binding protein-43 (TDP-43) is a common pathological feature of amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration, and Alzheimer's disease with TDP-43 pathology (AD-TDP); the exact role of protein disulfide isomerase (PDI), an enzyme with chaperone activity, in modulating the pathological behavior of TDP-43 is unknown. In this study, we report that wild-type PDI, through its specific interaction with TDP-43, markedly attenuates phase separation of TDP-43, competitively displaces G3BP1 to disassemble TDP-43/G3BP1 condensates, and further counteracts the pathological mislocalization, abnormal phosphorylation, and pathological aggregation of TDP-43 through the b' domain of the enzyme. Ultimately, this alleviates mitochondrial damage and neuronal toxicity caused by TDP-43 aggregation and suppresses UNC13A cryptic splicing in stressed cells. In the presence of abnormal forms of PDI, however, PDI loses its activity, and stress granules containing TDP-43 are assembled into amyloid fibrils, resulting in mitochondrial impairment and neuronal cell death in ALS and AD-TDP patients. These findings not only provide new insights into the pathogenic mechanisms of TDP-43 in neurodegenerative diseases such as ALS and AD-TDP, but also propose PDI as a potential therapeutic target.

ID: 42183628
Title: CHCHD2 and CHCHD10 promoted autophagic clearance of protein aggregates via GABARAPs.
Abstract: Mutations in mitochondrial protein CHCHD2 and its paralog CHCHD10 were identified in patients with Parkinson disease (PD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD) or Alzheimer disease (AD). CHCHD2 and CHCHD10 mutations caused neurodegeneration in model animals as seen in patients, but their pathophysiological roles remain elusive. Here we reported a direct role of CHCHD2 and CHCHD10 in autophagy. We identified a protein complex composing of CHCHD2-CHCHD10-C1QBP/p32-Atg8-family proteins (ATG8s), in which each molecule interacted with another. CHCHD2, CHCHD10 and C1QBP/p32 associated with ATG8s, preferentially, GABARAPs. Disease-associated CHCHD2 and CHCHD10 mutations exhibited varied interaction with ATG8s. By binding to GABARAPs, CHCHD2 and CHCHD10 underwent autophagic degradation, and recruited the ULK1 complex. Autophagy initiation defects occurred upon transient knockdown of CHCHD2, and also in human iPSC-derived CHCHD2-/- or CHCHD2T61I dopaminergic neurons. Importantly, CHCHD2 and CHCHD10 promoted autophagy. CHCHD2 reduced protein aggregates in cells and toxic SNCA/α-synuclein species in mouse striatum. Our study thus revealed mitochondrial proteins CHCHD2 and CHCHD10 as both autophagy substrates and autophagy activators and laid groundwork for therapy targeting patients with neurodegeneration.Abbreviations: AA: amino acid; AD: Alzheimer disease; ALS: amyotrophic lateral sclerosis; ATG5: autophagy related 5; ATG7: autophagy related 7; ATG8: mammalian Atg8-family protein; ATG13: autophagy related 13; bafA1: bafilomycin A1; C1QBP/p32/gC1qR/HABP1: complement component 1, q subcomponent binding protein; CHCHD2/MNRR1/MIX17B: coiled-coil-helix-coiled-coil-helix domain containing 2; CHCHD10/MIX17A: coiled-coil-helix-coiled-coil-helix domain containing 10; CHX: cycloheximide; CMA: chaperone-mediated autophagy; CRISPR: clustered regularly interspaced short palindromic repeats; CQ, chloroquine; DA: dopaminergic; DMSO: dimethyl sulfoxide; EBSS: Earle's balanced salt solution; RB1CC1/FIP200: RB1 inducible coiled-coil 1; FTD: frontotemporal dementia; GABARAP: gamma-aminobutyric acid receptorbassociated protein; GABARAPL1: GABA type A receptor associated protein like 1; GABARAPL2: GABA type A receptor associated protein like 2; hESC: human embryonic stem cells; iPSC: induced pluripotent stem cell; KO: knockout; LAMP1: lysosomal-associated membrane protein 1; LAMP2A: lysosomal-associated membrane protein 2A; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; LIR: LC3-interacting region; PD: Parkinson disease; SQSTM1/p62: sequestosome 1; TARDBP/TDP-43: TAR DNA binding protein; TH: tyrosine hydroxylase; TMR, tetramethylrhodamine; WT: wild type; UB: ubiquitin; ULK1: unc-51 like kinase 1.

ID: 42192558
Title: Exosome-mediated gut-brain axis signaling in neurodegenerative diseases: Mechanisms, experimental evidence, and therapeutic perspectives-A narrative review.
Abstract: The stomach and the brain are connected by a sophisticated two-way communication mechanism called the gut-brain axis. Extracellular vesicles, particularly exosomes, that move bioactive substances between the stomach and the brain, such as proteins, lipids, metabolites, and microRNAs, may improve the gut-brain axis. In the past years, the role of exosome-mediated communication has been recognized as significant in relation to the etiology, continued progression, and potential treatment of neurodegenerative disorders. The authors of this review article present a summary of the current understanding of the relationship of gut microbiome, exosome biogenesis, and the pathophysiological development of neurodegenerative diseases. Evidence from laboratory studies, animal studies, and newly emerging human studies suggests that microbiome-based metabolites and inflammatory mediators may modulate how exosomes are produced, what they carry, and how they interact with the blood-brain barrier. These exosomal signals may impact neuroinflammation, neuronal signaling, and the spread of pathological proteins of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. In addition, they examine some possible ways to target the gut-brain axis from a therapeutic perspective, including manipulating the gut microbiome, providing probiotics and/or prebiotics, performing fecal microbiota transplantation, and/or using engineered extracellular vesicles as vehicles for drug delivery. The authors also outline some of the methodological differences that make it difficult to assess the effects of exosomes.

ID: 42199078
Title: Transforming surgical decisions: the rise of predictive and personalized digital tools.
Abstract: Artificial intelligence (AI) has the potential to profoundly transform surgical decision-making (SDM) by enabling more predictive, personalized, and data-driven care. Its integration across the surgical pathway can improve clinical outcomes, efficiency, and patient safety. This narrative review provides an overview of the current and emerging applications of AI in SDM. A structured search of electronic databases was conducted using PubMed, Scopus, Web of Science, and Google Scholar. The search primarily focused on peer-reviewed publications from 2015 to 2025. AI applications include radiologic image analysis for preoperative planning, electronic health record mining for individualized surgical strategies, risk and immunological response prediction, and genomic analysis to guide treatment selection. Intraoperative, AI-based video, image, and physiological data processing can support real-time decision-making by improving precision, identifying anatomical targets, and predicting complications earlier. Postoperatively, AI systems can monitor patient data to detect complications, evaluate outcomes, and tailor follow-up therapy. Despite these advantages, challenges remain, including data quality and availability, model explainability, and others. Overcoming these barriers requires explainable and secure AI models, scalable infrastructures, clinician engagement, and robust regulatory frameworks. Advances in AI-assisted robotics and interpretability are expected to support safer, more ethical, and more effective surgical decision-making.

ID: 42199099
Title: Activin A in the central nervous system: Mechanistic and therapeutic insights unveiled by emerging technologies.
Abstract: Activin A exhibits both protective and pathological roles in the central nervous system, reflecting a functional duality that complicates its therapeutic development. To decipher the underlying mechanisms responsible for these contradictions, we leverage emerging technologies that establish comprehensive cellular and spatiotemporal contexts for its signaling pathway. These approaches elucidate the mechanisms underlying central nervous system diseases and their potential therapeutic applications. In this review, we demonstrate how these advanced technologies enhance our understanding of the mechanism of activin A: CRISPR-based editing validates critical receptors such as ACVR1B in the process of remyelination; organoid and organ-on-a-chip systems model human-specific cellular interactions; spatial and single-cell multi-omics delineate expression and communication networks; and optogenetics/chemogenetics enable precise spatiotemporal control of signaling pathway activity. This technological toolkit provides a robust framework for elucidating the context-specific roles of activin A in conditions such as ischemic stroke, neurodegenerative diseases, glioma, epilepsy, and traumatic brain injury, encompassing key processes including neuroprotection, inflammation, and repair. Furthermore, these mechanistic insights inform next-generation interventions, including adeno-associated virus-mediated gene therapy for localized modulation and advanced nanodelivery systems for targeted biologic transport. Given these capabilities, artificial intelligence plays a crucial role in designing blood-brain barrier-permeable ligands and optimizing smart nanocarriers. By contrasting preclinical data with the clinical pipeline, which currently emphasizes peripheral diseases, we propose that integrating mechanism-decoding technologies with artificial intelligence-engineered delivery platforms is a critical pathway for advancement.

ID: 42208537
Title: Capturing multi-disease states on a spectrum with machine learning and routine clinical data.
Abstract: Diseases exist on spectra of risk factors, cellular perturbations, organ dysfunction, and clinical manifestations. It is unknown whether the analysis of routine laboratory tests and vitals using artificial intelligence presents a scalable and portable system for capturing the spectral nature of common diseases. We constructed and validated machine learning models targeting seven common diseases-atrial fibrillation, breast cancer, coronary artery disease, migraine, rheumatoid arthritis, schizophrenia, and type 2 diabetes-using routine clinical measurements from 394,957 electronic health records (EHRs) in the BioMe Biobank and UK Biobank. The Resulting model outputs, termed spectral health index from machine measurements of electronic records (SHIMMER), were assessed for association with disease diagnosis, risk factors, biomarkers, onset, survival, complications, and medications in two cohorts. SHIMMER was associated with disease diagnosis, known risk factors, and biomarkers in expected directions in both cohorts. With greater SHIMMER, the prevalence of risk factors, complications, and medications continuously increased; for instance, age and hypertension, stroke risk and cardiac arrest, and beta blockers increased, respectively, with atrial fibrillation SHIMMER. Biomarker levels for type 2 diabetes, such as glucose, hemoglobin A1c, C-reactive protein, and triglycerides, changed stepwise as SHIMMER increased. Rising SHIMMER also revealed gradations of earlier disease onset and decreased survival, particularly for coronary artery disease and schizophrenia. A holistic, non-invasive marker derived from machine learning trained on routine clinical measurements snapshots multiple common diseases on a spectrum, quantifying disease risk, severity, onset, survival, sequela, and treatment. This study was supported in part by the National Institutes of Health.

ID: 42234776
Title: Cryptic splicing in synaptic and membrane excitability genes links TDP-43 loss to neuronal dysfunction.
Abstract: TAR DNA binding protein 43 (TDP-43) pathology is a defining pathological hallmark of multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). A major feature of TDP-43 pathology is its nuclear depletion, leading to the aberrant inclusion of cryptic exons during RNA splicing. STMN2 and UNC13A have emerged as prominent TDP-43 splicing targets, but the broader impact of TDP-43-dependent cryptic splicing on neuronal function remains unclear. Here, we report previously unidentified TDP-43 splicing targets critical for membrane excitability and synaptic function, including KALRN, RAP1GAP, SYT7, and KCNQ2. Using human stem cell-derived neurons, we showed that TDP-43 reduction induces cryptic splicing and down-regulation of these genes, resulting in impaired excitability and synaptic transmission. In postmortem brains from patients with FTD, these cryptic splicing events occurred selectively in neurons with TDP-43 pathology. Suppressing individual cryptic splicing events using antisense oligonucleotides partially restored neuronal function, and combined targeting almost fully rescued the synaptic deficit caused by TDP-43 loss. Together, our findings provide evidence that cryptic splicing in these synaptic and membrane excitability genes is not only a downstream marker but instead a direct driver of neuronal dysfunction, establishing a mechanistic link between TDP-43 pathology and neurodegeneration in ALS and FTD.

ID: 42242212
Title: Agility training enhances motor temporal precision by reweighting spinal phase-locked commissural inhibition.
Abstract: Agile motor action requires rapid switching between motor states while maintaining stability. Because motor output combines fast and slow muscle fibers with distinct kinetics, prolonged slow-fiber activation can broaden burst envelopes and blur within-cycle transitions, limiting temporal precision. Here, we show that agility training improves locomotor timing by selectively compressing the activity of slow motor neurons through enhancing commissural inhibition. In adult zebrafish, training increased locomotor stability and reshaped cycle structure in vivo, shortening the contraction phase while extending relaxation. Ex vivo motor-nerve recordings revealed sharper burst envelopes and reduced temporal dispersion after training, explained by a selective narrowing of slow, but not fast, motor neuron discharge within each cycle. Training enhanced phase-locked commissural inhibition during locomotion, consistent with an inhibitory gate aligned to burst offset. Finally, electrophysiology and single-cell transcriptomics associated this plasticity with increased glycinergic receptor expression in slow motor neurons. Together, our findings identify a circuit and a molecular substrate for training-induced gains in agility and suggest that motor precision can be improved by inhibitory reformatting of slow motor output rather than by uniformly increasing excitation.

ID: 42242678
Title: Pathogenicity prediction for noncanonical splice-altering variants based on multimodal feature fusion.
Abstract: Splice-altering variants (SAVs) are the second most prevalent class of pathogenic genetic variants and are strongly associated with the occurrence and development of various diseases. However, current computational tools exhibit limited predictive capability beyond canonical GT-AG splice sites, making accurate assessment of noncanonical SAV pathogenicity a considerable challenge. To address this limitation, we developed MOSAIC (multimodal feature fusion for noncanonical splice-altering variants pathogenicity prediction), a deep learning framework designed for precise assessment of noncanonical SAV pathogenicity. MOSAIC integrates long-range contextual signals derived from a pretrained DNA language model, local sequence features captured from multi-scale convolutional neural networks, and functional annotations. By employing a transformer encoder and a gated fusion module, the model adaptively integrates these multimodal features. Benchmarking across multiple independent datasets demonstrated that MOSAIC consistently outperforms existing state-of-the-art methods, such as CADD and SpliceAI. It remains highly accurate and robust when evaluated on rare variants, gene-independent contexts, and the largest subset where all comparative methods yielded outputs. Furthermore, feature importance analysis revealed that long-range dependencies in DNA sequences and transformer-based integration were critical contributors to model performance. Interpretability analyses indicated that MOSAIC could identify key regulatory sequence motifs associated with transcription factors and RNA-binding proteins, offering mechanistic insight into how noncanonical SAVs disrupt splicing regulation and contribute to pathogenic processes. Overall, MOSAIC offers an accurate and interpretable framework for predicting the pathogenicity of noncanonical SAVs, thereby serving as a dependable computational tool for genetic diagnostics and precision medicine applications. MOSAIC source code and data are available at https://github.com/Lilab-genomics/MOSAIC.

ID: 42261185
Title: CRISPR-MBTF: a multi-branch transformer fusion framework for CRISPR-Cas9 off-target prediction.
Abstract: Clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR-Cas9) is a revolutionary genome editing technology derived from a bacterial adaptive immune system that uses a single guide RNA (sgRNA) to direct the Cas9 enzyme to specific DNA sequences for precise genetic modifications. Its ease of use and efficiency has accelerated advancements in genetic research and therapeutic development. However, unintended cleavage at off-target sites remains a significant concern, limiting the safety and broader applicability of CRISPR-based editing. Accurate computational prediction of off-target locations is therefore essential to mitigate potential risks and improve experimental design. In this study, we introduce CRISPR multi-branch transformer fusion (CRISPR-MBTF), a novel deep learning-based framework employing a multi-branch Transformer architecture combined with an attention-based fusion mechanism to model the intricate biological context influencing CRISPR activity. By capturing subtle sequence patterns and contextual dependencies, our model achieves enhanced predictive performance compared to existing approaches. Additionally, interpretability analyses uncover biologically meaningful patterns and highlight influential sequence regions, offering valuable insights into the determinants of CRISPR specificity. This work presents a robust and interpretable tool to support the design of safer and more effective genome editing strategies.

ID: 42314654
Title: S-acylation of TDP-43: PALMing down aggregation?
Abstract: S-acylation is well known for regulating protein stability and trafficking. In a recent issue of Molecular Cell, Xu et al.1 reveal a distinct, aggregation-suppressing function of this posttranslational lipid modification: S-acylation of the RNA-binding protein TDP-43 antagonizes poly(ADP-ribose)-driven condensation. Moreover, reduced S-acylation levels are linked to ALS pathogenesis.

ID: 42340456
Title: Viral Infections and Neurodegenerative Diseases: Reinterpreting the Crosstalk Through a Dual-Role Lens.
Abstract: Neurodegenerative diseases (NDDs) are multifactorial disorders with increasing evidence implicating viral infections in their pathogenesis. However, current reviews often catalog virus-disease associations without integrating this evidence into a unified conceptual model that also accounts for the therapeutic potential of viral platforms. This review investigates recent literature to propose a "dual-role" model for viruses in NDDs. We analyze how diverse viruses (e.g., HSV-1, HIV, EBV, and SARS-CoV-2) converge on shared pathogenic pathways, including protein misfolding, chronic neuroinflammation, and mitochondrial dysfunction, across different NDDs. Paradoxically, engineered viral vectors derived from neurotropic viruses are being investigated as tools for targeted gene therapy. To address these therapeutic applications of viruses, this review also provides an in-depth report of the various viral vector technologies developed. The approaches involved in designing rationally engineered viral vectors based on various adeno-associated virus serotypes through rational design, directed evolution and machine learning strategies, as well as the lentiviral and herpes simplex virus-based platform are described. Different strategies that have been used to incorporate large and/or small payloads such as gene replacement, RNA interference, microRNA cassettes, CRISPR-based gene editing (base editing, prime editing, CRISPRa and CRISPRi) and the double AAV systems to deliver larger transgene cassette have also been reviewed. This review further includes various routes of administration including intrathecal, intracerebroventricular and convection-enhanced delivery with the use of Focused Ultrasound. The constraints imposed by the Blood-Brain Barrier are discussed, especially the approach using receptor-mediated transcytosis for crossing. The review also critically evaluates obstacles toward clinical translation of viral vectors due to various factors including immunogenicity, the presence of pre-existing neutralising antibodies and dose-dependent toxicity, illustrated by the fatal outcome of ASPIRO and DMD trials. Finally, this review concludes with other promising non-viral approaches such as lipid nanoparticle and extracellular vesicles. Future research needs include long-term studies to investigate causality and extensive safety optimization of viral vectors.

ID: 42343570
Title: STMN2 protein depletion via translation deficits and stress granules in amyotrophic lateral sclerosis.
Abstract: STMN2 is an abundant neurospecific protein dysregulated in neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS). We previously reported that cellular stress can lead to STMN2 loss due to TDP-43 nuclear condensation. Here, using human and murine neuronal cell models, multiple pharmacological tools, in situ single-molecule analysis of translation and RNA localisation, and longitudinal analysis of neuronal fitness/survival, we establish TDP-43-independent mechanisms of STMN2 depletion under stress. We find that human STMN2 protein level is extremely labile under acute high-magnitude stress. Early in stress, STMN2 is suppressed via activated proteasomal degradation, phosphorylation and translation repression by stress granules, independently of TDP-43 loss of function in splicing. We further show that STMN2 protein level is highly sensitive to chronic translation deficits, such as those elicited by prolonged low-grade stress. We find that low pre-stress STMN2 sensitises neuronal cells to stress-induced apoptosis, whereas moderately increased STMN2 is protective under stress. Finally, we demonstrate that STMN2 mRNA is upregulated in non-TDP ALS (ALS-FUS) models, which may compensate for translation/stress granule defects in this disease subtype. Consistent with the compensation hypothesis, STMN2 mRNA is also upregulated in the relatively spared (cortex), but not severely affected (spinal cord), CNS regions in ALS-TDP. In conclusion, our study implicates two common denominators in neurodegeneration - dysregulation of translation and stress granules - in STMN2 depletion, independent of TDP-43 loss of function. It also describes an RNA-based compensatory mechanism in ALS underling the unique vulnerability of neurons with developing TDP-43 pathology.

ID: 42352457
Title: Engineered Exosomes in Precision Neuro-Oncology: Mechanisms, Therapeutics, and Translational Challenges.
Abstract: Exosomes are small vesicles released by cells that have attracted growing interest as drug delivery vehicles, particularly for brain diseases, where getting therapeutics across the BBB remains a fundamental problem. While conventional platforms such as liposomes, polymeric nanoparticles, and viral vectors often suffer from immune clearance and poor brain accumulation, engineered exosomes leverage natural cellular transport mechanisms to cross the BBB, protect cargo from degradation, and enable biocompatible interactions with target cells. This review takes a mechanistic and translational look at how exosomes are being engineered for CNS disorders, with a particular focus on glioblastoma. We cover exosome biogenesis through ESCRT-dependent and ESCRT-independent pathways, and how the competition between Rab27-driven secretion and Rab7-driven lysosomal degradation determines how many exosomes a cell releases, which has direct consequences for therapeutic production. We then discuss cargo loading strategies, from genetic approaches where donor cells are engineered to package specific molecules during biogenesis to physical methods like electroporation and sonication applied to isolated vesicles, alongside surface modification techniques for directing exosomes toward specific cell types. In glioblastoma, engineered exosomes have shown real promise for delivering chemotherapeutics across the BBB, targeting glioma stem cells, enabling CRISPR-based gene editing, and functioning as combined treatment and imaging tools. Applications in stroke and neurodegenerative diseases, where engineered exosomes carrying microRNAs and neuroprotective cargo have produced encouraging preclinical results, are also discussed. Scalable manufacturing and consistent targeting remain the hardest unsolved problems, and we outline emerging approaches including bioreactor-based production, programmable cargo loading, and patient-specific exosome design that are beginning to address these gaps. Overall, the progress reviewed here suggests that engineered exosomes are moving from an interesting biological concept toward a practically viable platform for CNS drug delivery.

ID: 42353201
Title: Machine Learning for CRISPR-Based Diagnostics.
Abstract: CRISPR-based diagnostics now detect viral, bacterial, and cancer-associated nucleic acids with sensitivities approaching quantitative PCR; however, their translation to decentralized care rests on computational design and interpretation that current datasets cannot sustain. Pandemic-era Cas12a assays reached 95% positive predictive agreement against reverse transcription quantitative PCR (RT-qPCR) at 10 copies/μL, and deep neural networks now design Cas13 detection assays spanning 1933 vertebrate-infecting viruses, ranking candidate guides at Spearman correlations of 0.69 to 0.84 across internal and external validation. Generative deep-learning systems improve single-nucleotide discrimination two- to three-fold, computer vision classifies lateral flow outputs at 96.5% accuracy, and multi-biomarker fusion reaches an area under the receiver operating characteristic curve (AUC) of 0.998 in lung cancer detection. These results mask a narrow data foundation. Cas13a guide prediction still draws from a single screening library of 19,209 guide-target pairs, Cas12a has one published diagnostic model, and signal classifiers almost uniformly validate on single-site cohorts. This review synthesizes mechanistic constraints, predictive and generative models, and point-of-care classifiers, and maps the path beyond this data ceiling. Evolutionary pretraining on RNA corpora and lab-in-the-loop agents that convert model failure into targeted data acquisition define the route forward.

ID: 42357271
Title: Folic Acid-Guided PLGA-Zein Core-Shell Nanoparticles for Co-Delivery of Temozolomide and Ellagic Acid to Overcome PARP-Mediated Chemoresistance in Glioblastoma.
Abstract: Background: Glioblastoma (GBM) remains a lethal malignancy due to temozolomide (TMZ) resistance and limited drug penetration across the blood-brain barrier, largely driven by hyperactive DNA damage repair mechanisms such as poly (ADP-ribose) polymerase (PARP). To address these challenges, we developed folic acid-targeted PLGA-zein hybrid core-shell nanoparticles for the codelivery of the alkylating agent TMZ and the natural PARP inhibitor Ellagic acid (FA-TMZ/EA-PZ-CS NPs), thereby enabling simultaneous enhancement of drug delivery and suppression of chemoresistance pathways. Methods and Results: The dual-drug nanoplatform was fabricated using a double-emulsion solvent evaporation method and functionalized via EDC/NHS-mediated folic acid conjugation to promote receptor-mediated uptake. Physicochemical characterisation confirmed uniform spherical morphology, high colloidal stability, efficient drug encapsulation, and sustained biphasic drug release consistent with a core-shell diffusion mechanism. In LN229 glioblastoma cells, folic acid conjugation significantly enhanced cellular internalisation and cytotoxic efficacy compared to free drugs and non-targeted nanoparticles. Combination index analysis revealed strong synergism between TMZ and ellagic acid, resulting in markedly reduced IC50 values. Mechanistic studies demonstrated apoptosis induction, increased DNA damage, inhibition of cell migration at sub-cytotoxic concentrations, and downregulation of PARP gene expression. Conclusion: Overall, this study establishes a targeted core-shell nanotherapeutic strategy that integrates chemotherapy with DNA repair inhibition to overcome TMZ resistance, offering a mechanistically sound strategy that serves as a foundational framework for future translational research.

ID: 42357281
Title: Tjap1/Pilt Is a cis-Golgi-Associated Protein Required for Golgi Integrity and Normal Drug Transporter Expression in Brain Microvascular Endothelial Cells In Vitro.
Abstract: Background: Brain microvascular endothelial cells (BMECs) form the blood-brain barrier (BBB), a highly selective interface that restricts paracellular diffusion and regulates the transport of nutrients and drugs into the central nervous system via specialized transporters and receptors. Tight junction-associated protein 1 (Tjap1), also termed protein incorporated later into tight junctions (Pilt), has been localized to tight junctions (TJs) in epithelial cells and to the trans-Golgi network in fibroblasts; however, its expression, subcellular localization, and functional significance in BMECs are still unknown. Methods: We characterized Tjap1 subcellular localization in mouse and human BMEC cell lines as well as primary mouse BMECs by immunofluorescence with and without pharmacological Golgi disruption by treatment with Brefeldin A, Golgicide A or Pitstop 2. CRISPR/Cas9-mediated Tjap1 knockout cells were generated and examined with regard to their Golgi morphology using immunostaining. Tjap1 mRNA localization was examined by RNAscope in situ hybridization. Quantitative real-time PCR and Western blot was performed to assess the expression of BBB-associated efflux transporters, solute carrier transporters, and cellular receptors in control and Tjap1 knockout cells. Results: Tjap1 predominantly localized to the cis-Golgi compartment, co-localizing with Gm130 rather than Tgn38, and was absent from TJs in BMECs. Tjap1 knockout induced pronounced Golgi fragmentation BMECs. Importantly, Tjap1 knockout significantly downregulated mRNA-expression of Abcb1a, Abcb1b, Abcc4, Slc2a1, Slc7a1, Slc7a5 and Tfrc, while Abcg2 was upregulated. At the protein level, a decrease in the protein levels of Abcb1, Abcc4, Slc2a1, Slc7a1, and Tfrc was observed in Tjap1 knockout cEND cells. Conclusions: In BMECs, Tjap1 is a cis-Golgi-associated protein required for the structural integrity of the Golgi apparatus. Its deletion is associated with Golgi fragmentation and significant alterations in the mRNA and protein expression of drug transporters and receptors at the BBB. These findings identify Tjap1 as a candidate regulator of both Golgi architecture and the BBB transporter profile in vitro, with potential implications for modulating drug transport across the BBB.

ID: 42358359
Title: Global research trends and hotspots of exosome-mediated drug delivery across the blood-brain barrier: a bibliometric study from 2015 to 2025.
Abstract: The blood-brain barrier (BBB) is a major obstacle to targeted drug delivery for central nervous system (CNS) diseases. Although liposomes and polymeric nanoparticles have improved brain drug delivery, limitations remain in BBB targeting, long-term biocompatibility, and in vivo clearance. Exosomes are endogenous nanoscale extracellular vesicles with favourable biocompatibility, low immunogenicity, and BBB-crossing potential. Therefore, this bibliometric study summarises the current research status, future research trends, and challenges in the more specific field of exosome-mediated BBB drug delivery. A comprehensive search was conducted across the Web of Science Core Collection (WoSCC), PubMed, and Embase databases for relevant English-language literature on exosome-mediated drug delivery across the blood-brain barrier from 2015 to 2025. WoSCC served as the primary source for bibliometric analysis. PubMed and Embase databases were used for supplementary validation. Software such as VOSviewer, CiteSpace, and R-bibliometrix was employed for literature visualisation analysis. This study included 1,365 relevant articles from the WoSCC database, and the annual publication volume showed a steady upward trend. China and the United States significantly lead in both the number of publications and the number of core contributing institutions in this field. Co-occurrence analysis of keywords showed that research hotspots are mainly focused on exosomes, the blood-brain barrier, drug delivery, and Alzheimer's disease. PubMed and Embase were used as supplementary validation databases, including 1,089 and 1,517 records, respectively. Their annual publication trends, major countries/regions, core journals, and keywords/themes were generally consistent with WoSCC, supporting the macro-level stability of the bibliometric findings. Unlike previous bibliometric analyses that mainly focused on overall trends in CNS exosome research, this study focuses specifically on the direction of exosome-mediated drug delivery across the BBB. The findings show a shift from basic vesicle characterisation toward engineered delivery systems, CNS disease applications, and translational evaluation. Mammalian-derived exosomes remain dominant, while plant-derived vesicles, AI-assisted design, biomimetic hybrid nanovesicles, and gut-brain axis strategies are emerging areas of focus. Future research should prioritise systematic platform comparisons, standardised evaluation, quality control, scalable production, long-term safety, and regulatory pathways.

ID: 42377669
Title: Is Technology Remaking Therapy: The Screen and the Self: Telepsychiatry, AI Therapy, and the Defense Against Intimacy.
Abstract: This paper examines several methods of technology that have challenged traditional expectations of the meaning of psychotherapy, from the widespread adoption of telepsychiatry to the subsequent emergence of AI-driven therapeutic agents (Therabots). Widespread usage of new technology that impacts the therapeutic process has outpaced an analysis of how that technology might affect the meaning and effectiveness of that process. Lawsuits assume such technology causes harm, while limited data and the literature has been more mixed. From Frankenstein to CRISPR, new technology always has its cheerleaders and its detractors. The more the technology seems to impact a topic especially connected to our humanity, the deeper the convictions will be on both sides. Certainly, when it comes to psychotherapy, the introduction of new technologies such as telepsychiatry to Therabots has provoked discussion. We argue that while new technologies offer practical advantages, they risk functioning as structural defenses against the vulnerability and authentic intimacy essential to transformative psychotherapy. Through analysis of the therapeutic alliance, relational dynamics, and the psychology of vulnerability, this paper contends that the structural form of telepsychiatry does not alter the inherent nature of the therapeutic experience, whereas AI-mediated therapy may collude with maladaptive defenses, fundamentally altering the nature of the therapeutic encounter.

ID: 42383305
Title: TDP-43 proteinopathy as a biomarker and therapeutic target in amyotrophic lateral sclerosis.
Abstract: Amyotrophic lateral sclerosis (ALS) is the most common form of adult-onset motor neuron disease, characterised by the degeneration of upper and lower motor neurons. The cytoplasmic aggregation of TDP-43 (TAR DNA-binding protein 43), an RNA-binding protein, is considered a hallmark of ALS pathology, found in nearly all postmortem cases of ALS. TDP-43 is normally primarily nuclear, where it has a widespread role in gene regulation. Mutations, extrinsic stressors, and alterations in RNA homeostasis in ALS lead to nuclear depletion of TDP-43 and the formation of cytosolic TDP-43 aggregates. This causes multiple downstream effects on neuronal function and degeneration as well as gene expression. TDP-43 is a promising target as a biomarker, as it is found to be elevated in the biofluids of ALS patients, and its cytoplasmic aggregation can also be observed in peripheral tissues; however, methodological variability and technical limitations currently preclude the establishment of TDP-43 as a standalone biomarker. There are also promising therapeutic strategies in development targeting TDP-43 pathology, but a critical challenge that remains is achieving a balance between eliminating toxic aggregates and preserving the essential functions of TDP-43. In summary, with further research, considering TDP-43 pathology in ALS gives hope for finding future novel diagnostics and therapeutics for ALS.

ID: 42387584
Title: SGK1-mediated deficits in microglial phagocytosis drive pathological progression in amyotrophic lateral sclerosis.
Abstract: Alterations in microglial function and transcriptomic profiles are major pathological hallmarks of amyotrophic lateral sclerosis (ALS). However, the dynamics and regulatory mechanisms underlying microglial phagocytic activity during disease progression remain unclear. In this study, we observed stage-dependent alterations in microglial phagocytic activity during disease progression in SOD1G93A mice. Single-cell RNA sequencing suggested that this change was associated with a reduced abundance of microglial subpopulations enriched for phagocytosis-related pathways. Transcriptomic analysis identified serum- and glucocorticoid-regulated kinase 1 (SGK1) as a potential mediator of this process. Notably, sgk1 knockout in SOD1G93A mice was associated with improved microglial clearance of myelin debris and reduced aberrant engulfment of neuronal material after disease onset. Our results further showed that, after disease onset, the accumulation of myelin debris and apoptotic neurons induced SGK1 upregulation in microglia from SOD1G93A mice. Mechanistically, SGK1 appeared to promote lipid accumulation in microglia by suppressing lipophagy, thereby impairing the ability of microglia to clear cellular debris. Moreover, pharmacological inhibition of SGK1 with GSK650394 attenuated motor deficits and prolonged survival in SOD1G93A mice. Together, our findings provide evidence for a previously unrecognized role of SGK1 in regulating microglial phagocytosis in ALS models and support SGK1 as a potential therapeutic target in SOD1 mutation-associated ALS models.

ID: 42392383
Title: Gingipains as macromolecular mediators at the periodontal-brain interface: Mechanistic, diagnostic, and therapeutic evidence in Alzheimer's and Parkinson's diseases.
Abstract: Chronic periodontitis, driven by Porphyromonas gingivalis, has emerged as a modifiable risk factor for Alzheimer's disease (AD) and Parkinson's disease (PD) the two most prevalent and socioeconomically burdensome neurodegenerative disorders through systemic dissemination of its signature cysteine proteases, gingipains (RgpA, RgpB, Kgp). This narrative critical review is explicitly scoped to AD and PD, the only neurodegenerative conditions for which postmortem detection of gingipains in affected brain regions, mechanistic evidence from cellular and animal models, and clinical epidemiological data currently exist in sufficient depth to support an integrated synthesis. Robust meta-analyses confirm that periodontitis is associated with elevated AD/PD risk (OR/HR 1.2-3.5), while gingipains have been detected in a high proportion (>85-90%) of postmortem AD/PD brains, correlating with tau/α-synuclein pathology, neuroinflammation, and neuronal loss. Mechanistic studies in cellular and animal models demonstrate that gingipains can disrupt blood-brain barrier integrity via tight-junction cleavage, trigger NF-κB/NLRP3-driven glial activation, catalyse amyloid-β/α-synuclein seeding, induce tau truncation/hyperphosphorylation, and precipitate mitochondrial oxidative damage, thereby generating self-amplifying neurotoxic cascades. Salivary gingipain activity offers a non-invasive, high-sensitivity biomarker candidate for early risk stratification that may outperform conventional fluid markers in prodromal cohorts. Therapeutically, small-molecule gingipain inhibitors have shown neuroprotective effects in preclinical models (e.g., atuzaginstat/COR388 failed primary endpoints in the Phase 2/3 GAIN trial but demonstrated subgroup benefits in P. gingivalis-positive participants; the next-generation inhibitor LHP588 is advancing in the Phase 2 SPRING trial). Emerging approaches including nanotechnology, CRISPR-based virulence gene disruption, and targeted delivery platforms aim to improve brain exposure and specificity. This review provides an integrated, isoform-resolved framework linking gingipain structure-function to neurodegeneration. While associative and mechanistic evidence is compelling, definitive causation in humans and disease-modifying efficacy require further validation through biomarker-guided clinical trials. Precision inhibition of gingipains represents a promising upstream strategy for addressing a potentially modifiable microbial contributor at the oral-brain interface.

ID: 42393685
Title: Structural-functional network decoupling in early stage amyotrophic lateral sclerosis reveals cell-type specific transcriptional signatures.
Abstract: Amyotrophic lateral sclerosis (ALS) involves widespread brain network dysfunction, yet the molecular mechanisms linked to these alterations remain poorly understood. We investigated macroscopic structural-functional coupling abnormalities in early-stage ALS (ALS-ES) and their underlying transcriptomic signatures. We analyzed multimodal MRI data from 73 patients with sporadic ALS-ES and 74 age- and sex-matched healthy controls. Structural-functional (SC-FC) coupling was quantified using diffusion tensor imaging and resting-state functional MRI. Machine learning models were constructed to distinguish patients from controls based on network features. Coupling alterations were spatially correlated with neurotransmitter receptor maps and gene expression profiles from the Allen Human Brain Atlas. Key transcriptomic findings were validated using independent single-cell RNA sequencing datasets. While structural connectivity remained largely preserved, functional connectivity was significantly reduced in the somatomotor network (SMN). This mismatch manifested as significant SC-FC network decoupling, particularly within the SMN (pFDR = 0.001). A gradient boosting machine model accurately classified patients, identifying SC-FC coupling in the left precentral gyrus as a primary statistical contributor to the classification model. Decoupling spatially correlated with 5-HT2A and mGluR5 receptor distributions. Imaging-transcriptomics linked network failure to a gene signature enriched for synaptic pathways and microglial markers. Single-cell analysis identified FMN1 as a candidate gene whose glial expression spatially associates with network decoupling. Early-stage ALS is characterized by significant structural-functional network decoupling, primarily in motor systems. This macroscopic failure is linked to specific microglial dysregulation, particularly FMN1 downregulation, providing a multiscale framework bridges statistical neuroimaging signatures with potential cellular pathology.

ID: 42397569
Title: RNA modifications as innovative pharmaceutical targets: emerging drug delivery strategies and precision therapeutics for cancer immunotherapy and metabolic diseases.
Abstract: RNA modifications have emerged as an important regulatory layer that influences gene expression beyond conventional genetic and epigenetic mechanisms. Among the various epitranscriptomic modifications, N6-methyladenosine (m6A), 5-methylcytosine (m5C), and pseudouridine (Ψ) have been extensively investigated for their roles in RNA stability, splicing, translation, immune regulation, and metabolic homeostasis. Increasing evidence suggests that dysregulation of these modifications contributes to cancer progression, immune evasion, therapeutic resistance, and metabolic disorders, suggesting their potential as therapeutic targets. This review summarizes recent advances in endogenous epitranscriptomic RNA modifications and discusses their relevance in cancer immunotherapy and metabolic diseases. In addition, emerging therapeutic approaches targeting RNA-modifying enzymes, including writers, erasers, and readers, are discussed along with the development of antisense oligonucleotides, RNA-based therapeutics, and delivery systems. Recent progress in lipid nanoparticles, polymeric carriers, and targeted delivery platforms has improved the stability, specificity, and translational potential of RNA-targeted therapies. The review also highlights current challenges associated with clinical translation, including delivery efficiency, therapeutic specificity, and patient heterogeneity. Overall, epitranscriptomic RNA modifications may provide new opportunities for the development of precision therapeutic strategies for cancer and metabolic diseases.

ID: 42412833
Title: A disentangled transformer-based transfer learning framework to predict patient drug response from tumor single-cell transcriptomics.
Abstract: Intratumoral cellular heterogeneity limits therapeutic efficacy in cancer patients. Although single-cell transcriptomics offers high-resolution profiling, translating these insights into clinical drug response prediction remains challenging. Recently, transfer learning approaches have attempted to predict patient drug response by leveraging pre-clinical data. However, these approaches operate at the bulk level, often masking the cellular heterogeneity essential for prediction. In this study, we propose scTAPE, a disentangled transfer learning framework to predict patient drug response using tumor single-cell transcriptomics. scTAPE follows a pre-training and fine-tuning paradigm. During the pre-training stage, scTAPE uses a disentangled learning strategy to extract intrinsic pharmacological signals masked by confounding factors from the matched bulk and single-cell expression profiles. Subsequently, a supervised drug response model is trained on labeled cell-line data to fine-tune the aligned common embedding, thereby achieving cross-domain generalization to unseen datasets. Experimental results demonstrate that scTAPE successfully predicts drug response across cell-line datasets and two independent clinical cohorts, outperforming state-of-the-art single-cell-based predictors. Furthermore, by analyzing tumor cell subpopulations, scTAPE not only predicts patient drug response to both single and combination treatments but also identifies potential therapeutic agents targeting drug-resistant subpopulations. The implementation of scTAPE is available via https://github.com/xinliangSun/scTAPE.