Biochimica et Biophysica Acta (BBA) - Molecular Cell Research

Drug resistance to the androgen receptor (AR) antagonist is a critical obstacle in the clinic for advanced prostate cancers. Especially, AR antagonist treatment-induced neuroendocrine progression represents a lethal and therapy-resistant subtype. Although transcriptional and epigenetic lineage plasticity have been extensively implicated in treatment-induced neuroendocrine progression, the contribution of metabolic adaptation remains incompletely understood. Here, we identified a previously unrecognized metabolic reprogramming mechanism induced by AR antagonists in castration-resistant prostate cancer (CRPC) models. AR antagonist treatment markedly enhanced glycolytic activity and induced glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression. Genetic depletion of GAPDH suppressed AR antagonist-induced glycolytic activation, altered transcriptomic and metabolic programs, reduced neuroendocrine-associated marker expression, and inhibited xenograft tumor growth. Mechanistically, GAPDH promoter pulldown coupled with mass spectrometry, siRNA screening, and chromatin immunoprecipitation assays identified myeloid zinc finger-1 (MZF1) as a key transcription factor for Enzalutamide-induced GAPDH gene expression. Pharmacological inhibition of GAPDH using koningic acid (KA) or penta-O-galloyl-{beta}-D-glucopyranose (PGG) significantly suppressed tumor growth and attenuated neuroendocrine-associated molecular programs in CRPC cell-derived xenograft and patient-derived t-NEPC xenograft models. Collectively, our findings identify an AR antagonist-induced MZF1-GAPDH signaling axis that promotes glycolytic activation and neuroendocrine-associated metabolic adaptation during treatment resistance. These results support targeting GAPDH-dependent metabolic reprogramming as a potential therapeutic strategy for treatment-resistant prostate cancer. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/729867v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@180c5feorg.highwire.dtl.DTLVardef@146c015org.highwire.dtl.DTLVardef@1ece2f4org.highwire.dtl.DTLVardef@12819c0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Prestin (SLC26A5), a membrane protein in cochlear outer hair cells, drives electromechanical transduction essential for mammalian hearing. Unlike other SLC26 anion transporters, prestin functions as a voltage-dependent molecular motor, transitioning between compact and expanded conformations. How this transition relates to the transporter cycle of SLC26 family members remains unclear. Here, multi-microsecond molecular dynamics simulations starting from the compact state reveal a rapid, spontaneous transition to an expanded state that resembles the inward-facing conformation of the anion exchanger pendrin (SLC26A4 from mouse). An accompanying transmembrane area expansion is localized to the inner membrane leaflet, likely leading to membrane bending. In line with this observation, reduced unitary sensor charge movement accompanies neutralization of charged residues localized near the inner leaflet. Simulations also uncover a previously uncharacterized compact conformation resembling outward-facing pendrin and predict an extracellular anion-binding site in prestin. In fact, in the presence of thiocyanate anions, we observe a previously unresolved binding site in a 3.27-[A] cryo-electron microscopy structure of prestin. Furthermore, like prestin, pendrin exhibits a non-linear capacitance, an indication of voltage-dependent conformational switching. Together, these findings suggest that prestin and pendrin share core structural and functional properties, notably parallels between expansion-contraction states and transporter function, though transition speeds may differ.

The rapid accumulation of single-cell RNA-Seq (scRNA-seq) data across multiple repositories presents major challenges for data accessibility, integration, and reproducibility. While primary repositories provide raw data, they rarely include structured cell-type annotations or descriptions of analytical workflows, limiting the ability to reuse and integrate datasets in a FAIR (Findable, Accessible, Interoperable, Reusable) manner. Here we present scFAIR, a consortium of single-cell data resources that has developed a unified metadata schema and common curation framework to improve the FAIRness of scRNA-seq data. Building on and extending the CZ CELLxGENE Discover metadata schema, the scFAIR consortium has been instrumental in driving key schema improvements, including the expansion of supported organisms, richer biological context, and structured reporting of computational workflows. To provide unified access to decentralized datasets, the consortium developed the sc-fair.org portal, which currently aggregates 2,346 datasets across partner resources through ontology-aware semantic search. We demonstrate the practical value of FAIR-compliant datasets through a cross-species validation between human and mouse Allen Brain Atlases, showing that standardized ontology annotations enable reliable annotation transfer across species, with 90% of neuronal clusters receiving an exact or equivalent label. Together, the scFAIR schema, validator, and portal constitute a community-driven framework that advances single-cell data standardization and lays the foundation for reproducible, large-scale integration of single-cell datasets.

The Doberman Pinscher population has undergone strong artificial selection for morphology and behavior, which can reduce genomic diversity and increase autozygosity. Here, we characterized the genome structure and identified selection signatures in Doberman Pinschers using complementary within- and between-population approaches. Genotypes from 3,226 Dobermans Dogs (Illumina CanineHD; 216,184 SNPs) provided by the Doberman Diversity Project were analyzed after purpose-specific quality control. Genomic inbreeding was quantified using four allele-frequency-based metrics and the runs of homozygosity (FROH) approach. Selection signatures were detected using intrapopulation (i.e., Runs of Homozygosity--ROH; Integrated Haplotype Score--iHS; and Number of Segregating Sites by Length--nSL) and interpopulation methods (i.e., Fixation Index--FST; Cross-Population Extended Haplotype Homozygosity--XP-EHH; and Cross-Population Number of Segregating Sites by Length--XP-nSL) comparing the Doberman Pinscher breed to Labrador Retriever (n=237). Dobermans showed high overall inbreeding, with a mean FROH of 0.42 (range 0.22-0.68), whereas the allele-frequency-based inbreeding estimators had similar means ([~]0.04). The partitioning of the ROH indicated high contributions from medium-to-long ROHs, consistent with recent inbreeding. The ROH scans identified 39,512 SNPs in ROH islands ([≥]50% frequency across individuals), with notable concentrations on CFA2, CFA3, and CFA31. Haplotype-based scans identified 2,820 candidate iHS SNPs and 2,173 candidate nSL SNPs (|score|>2). A common set of 310 SNPs was shared among ROH, iHS, and nSL, mapping near 279 genes that were mostly enriched for developmental pathways, particularly neurodevelopment and neuron-related cellular components. Between breeds, 349 highly differentiated SNPs were detected by FST, while XP-EHH and XP-nSL highlighted over 1,000 of Doberman-specific haplotype signals. A total of seven SNPs overlapped across FST, XP-EHH, and XP-nSL, which were located mainly on CFA8 ([~]59.48-60.61 Mb) near the KCNK10, SPATA7, PTPN21, NEGR1, and BTG1 genes. These genes are mainly linked to neural development and signaling, but BTG1 has also been associated with cardiomyocyte cell-cycle regulation, and KCNK10 with cardiac excitability and remodeling. Overall, the Doberman Pinscher breed exhibits high genome-wide autozygosity and levels of inbreeding. In addition, our results showed consistent, multi-method evidence of selection at loci associated with neurodevelopmental and regulatory pathways. These findings provide prioritized targets for follow-up studies that integrate phenotypes relevant to breed health and performance.

In plant breeding, it is often necessary to improve a target trait while maintaining other essential traits within desirable ranges. When genetic relationships exist among these traits, improvements in the target trait may lead to undesirable changes in essential traits, complicating cross selections. In such cases, it is critical to select cross-pairs that are expected to produce progeny that satisfy the requirements for all traits. The progeny distribution of each crossing pair can be predicted using the estimated genotypic values and genetic (co)variances of the target and essential traits. By utilizing this distribution, the probability of generating progeny that satisfy predefined trait requirements can be evaluated, allowing a direct comparison of alternative crosses. In this study, we developed Cross Potential Selection for Multiple Traits (CPS-MT), a breeding strategy designed to improve a target trait while maintaining one or more essential traits within desirable ranges. CPS-MT extends the original Cross Potential Selection (CPS) framework to explicitly handle trade-offs between traits under genetic correlations. We evaluated the performance of CPS-MT through simulations involving four types of genetic relationships and two genetic causal factors between traits, resulting in seven scenarios. Across all scenarios, CPS-MT consistently improved the likelihood of obtaining desirable progeny, indicating that CPS-MT provides a practical and effective framework for cross selection under multi-trait constraints in breeding programs. Article SummaryThis study developed Cross Potential Selection for Multiple Traits (CPS-MT), a new breeding strategy designed to improve a target trait while maintaining one or more essential traits within desirable ranges. CPS-MT evaluates crossing pairs by predicting progeny distributions based on estimated genotypic values and genetic covariances, enabling direct comparison of alternative crosses under multi-trait constraints. Through simulations incorporating four types of genetic relationships and two causal factors (seven scenarios), CPS-MT consistently increased the likelihood of obtaining progeny that satisfied the predefined trait requirement. These results indicate that CPS-MT provides a practical, robust framework for target trait improvement under trait constraints.

Species distribution forecasts commonly overlook intraspecific genetic variation, missing a potentially important mechanism of ecosystem change: climate-driven range shifts among lineages within a species native range. Here we integrate population genomic analysis of 495 individuals, multi-site common garden experiments, and species distribution modeling based on 837 occurrence records for three major genetic lineages of the foundation grass Phragmites australis in China. The octoploid FEAU lineage (haplotype P) exhibits superior heat tolerance (critical temperature Tcrit and T50) and produces significantly greater total biomass in three of four common gardens compared to the cold-adapted CN lineage (tetraploid, haplotypes O/M), which occupies a climatic niche with lower annual mean temperature (Bio1) and mean temperature of the wettest quarter (Bio8). Genomic analyses further reveal bidirectional but asymmetric introgression, with admixed individuals showing a systematic bias toward FEAU ancestry. Under the high-emission scenario (SSP5-8.5) by 2070, projected highly suitable habitat for the FEAU lineage expands by 18.6%, while the CN lineage shows a smaller relative increase. By contrast, the subtropical SW lineage (haplotypes U/I) exhibits limited and stable suitable habitat. These results demonstrate that climate change interacts with intraspecific variation rooted in polyploidy, thermal tolerance, and asymmetric gene flow to drive potential lineage replacement within a native range, a process already suggested by field observations of FEAU expansion in a plateau lake. Our findings argue for integrating evolutionary history and genetic identity into ecological forecasting to better anticipate ecosystem responses under ongoing climate warming.

Huntingtin-associated protein 40 (HAP40) is an obligate structural subunit of huntingtin (HTT) and is rapidly degraded when unbound, yet has been conserved across eukaryotes for over a billion years. Combining interactomics, quantitative respirometry, and transcriptomics, we show that the HTT-HAP40 complex functions as a bidirectional stoichiometric rheostat: unbuffered apo-HAP40 activates the Integrated Stress Response via ATF4 and DDIT3/CHOP, whereas unbuffered apo-HTT reciprocally drives cholesterol and fatty-acid biosynthesis through SREBF1/2. We identify the ER-mitochondria tether RMDN3 (PTPIP51) as a key HAP40 interactor, placing mitochondria-associated ER membranes (MAMs) at the rheostats convergence point, and demonstrate that HAP40 depletion specifically impairs respiratory complexes II/IV. Loss of rheostat balance reproduces transcriptional signatures of Huntingtons disease patient tissues, supporting a "dual failure" model in which collapse of stoichiometric buffering -- rather than aggregation toxicity alone -- drives pathogenesis. To our knowledge, this is the first obligate complex in which both unbound partners carry out distinct essential functions, defining stoichiometric buffering as a generalizable regulatory principle that couples complex assembly to metabolic and stress-response control across eukaryotes.

Salmonella enterica serovars Typhimurium (STM) and Paratyphi A (SPA) cause clinically distinct diseases, yet the molecular bases for their different lifestyles remain incompletely understood. Genome degradation, a hallmark of typhoidal Salmonella, results in extensive pseudogenization across multiple functional pathways. Here, we investigate how such gene inactivation rewires cyclic-di-GMP (c-di-GMP) signaling and flagellar motility regulation in SPA vs. STM. We show that YhjH, a conserved phosphodiesterase (PDE), is required for motility in STM but not in SPA, despite retaining PDE activity in both serovars. We demonstrate that this functional divergence is caused by pseudogenization of ycgR in SPA, which truncates the flagellar brake protein YcgR to a nonfunctional peptide, severing the link between c-di-GMP levels and flagellar motor control. Site directed mutagenesis in the YhjH active site and ectopic expression of intact YcgR from STM that restored YhjH-dependent motility regulation in SPA, confirmed this molecular mechanism. Additionally, using a bacterial two-hybrid (BACTH) genetic screen, we identified a serovar-specific interaction between YhjH and the general stress protein YciG in SPA, but not in STM. Computational RNA folding analysis predicted substantial differences in mRNA secondary structure and stability between the SPA and STM yhjH alleles, suggesting a potential role for synonymous mutations in this serovar-specific interaction. Together, these findings reveal how genome degradation can rewire regulatory networks, uncovering a fundamental difference in motility control between typhoidal and non-typhoidal Salmonella and suggest that these differences allow SPA motility under conditions that suppress motility in STM. IMPORTANCESalmonella enterica serovars Typhimurium (STM) and Paratyphi A (SPA) cause fundamentally different diseases in humans, yet the molecular basis for their distinct lifestyles and pathogenicity remains poorly understood. Genome degradation is a hallmark of typhoidal Salmonella, but its functional consequences for regulatory networks are largely unexplored. Here, we demonstrate that pseudogenization of ycgR in SPA dismantles c-di-GMP-mediated flagellar motor control, liberating SPA from an inhibitory brake that suppresses motility in STM. Additionally, we uncover a serovar-specific interaction between the phosphodiesterase YhjH and the general stress protein YciG in SPA, demonstrating that genome degradation can drive regulatory network rewiring beyond simple gene loss. These differences in motility regulation may facilitate the systemic pathogenesis and unique lifestyle of SPA.

Auditory stimuli have been known to elicit neural responses in visual cortical areas, but such responses are partly associated with sound-evoked orofacial movements. However, it remains unclear to what extent neural correlates of movement can be dissociated from non-motor correlates. Here we developed a paradigm with a forced delayed-response mechanism by means of a moving reward apparatus in order to test whether this results in low amounts of movement-related neural activity shortly after stimulus onset. Animals performed a multisensory detection task, while we recorded neural activity from V1 and measured orofacial motion. During the delay, when only the stimulus was present, orofacial motion was relatively low. Reward-related motion increased after the delay, with a concomitant increase in motor-related spiking activity. Visual stimulation did neither elicit considerable motion nor corresponding neural responses in the delay period. Conversely, salient auditory stimuli led to modest, but increased orofacial motion and related neuronal activity during the delay. We identified a subpopulation of visually responsive V1 neurons that did not show correlations with orofacial movement, with only the stimulus being represented. These results present a forced delayed-response window as a method to help disentangle motor-related activity from visual (but not auditory) processing and show that motor-related activity only affects a fraction of visually selective neurons.

Neurobiological models of emotion have proposed the existence of multiple direct subcortical pathways in humans, often referred to as "low roads", linking the thalamus to the amygdala and implicated in affective function. Among these, pulvinar-amygdala structural connectivity has been associated with individual differences in anxiety and anxiety-related conditions. However, whether distinct thalamo-amygdala pathways across thalamic subnuclei differentially relate to anxiety remains unknown. Using diffusion MRI in 34 healthy participants, we reconstructed four candidate subcortical "low roads" bilaterally from the medial geniculate body (MGB), as well as the medial, inferior and lateral pulvinar to the basolateral amygdala (BLA). We then tested whether their structural connectivity strength was associated with individual differences in state and trait anxiety. Linear regression analyses revealed that fiber density in three left thalamo-amygdala pathways predicted state, but not trait, anxiety. Importantly, our results showed a functional dissociation across pathways. While fiber density in MGB-BLA and medial pulvinar-BLA pathways was negatively related to state anxiety, the inferior pulvinar-BLA tract showed the opposite association. These findings support differentiated contributions across thalamo-amygdala pathways in humans to state anxiety. The results highlight these subcortical pathways as potentially relevant neurobiological substrates for understanding anxiety and affective function. Key pointsO_LIFiber density of three left thalamo-amygdala pathways explained 24.1% of the variance in state anxiety across 34 healthy individuals C_LIO_LIFiber density in the left medial geniculate body and left medial pulvinar-amygdala pathways was negatively associated with state anxiety C_LIO_LIFiber density in the left inferior pulvinar-amygdala pathway was positively associated with state anxiety C_LI

The structural and functional organization of the brain can be studied across multiple scales, yielding richly detailed topographic brain maps of biological features. What are the underlying forces that shape their spatial patterning? Here we introduce a simple generative model of multiscale brain maps based on the concept of inter-regional homophily: the tendency for regions that are proximal in a given physical, molecular or functional space to display similar biological features. We evaluate the model with respect to six definitions of inter-regional homophily, including physical proximity, structural and functional connectivity, and laminar, receptor and transcriptional similarity, and across 43 empirical brain maps estimated using multiple imaging, electrophysiological and histological technologies. We show that homophilic principles are sufficient to accurately reconstruct many maps, with biological similarity and functional connectivity often contributing more than the brains geometry. We also identify consistent patterns of unexplained variation in maps with low homophily, revealing axes of cortical organization not captured by canonical inter-regional relationships. Finally, we show that homophily-informed generative models can be used to disentangle complex relationships between brain features and make new inferences on how they fit together. Collectively, this work highlights the fundamental contribution of homophily to the topographic layout of numerous biological features of the brain.

The large diversity of neuronal and glial cell types in the human brain is underpinned by foundational cell populations known as neural progenitor cells (NPCs). The dentate gyrus (DG) of the hippocampus, a key structure in learning and memory, maintains a tightly organized NPC population into adulthood across many mammalian species. However, the emergence, organization and persistence of NPCs in the human hippocampus remain poorly characterized. Reports of NPCs in the juvenile, adult, and aged periods have been variable, reflecting differences in identification criteria and highlighting the need for a unified framework across development. In this study, we provide a spatial and molecular map of the developmental trajectory of NPCs in the human DG, combining multimodal transcriptomic analysis within a neuroanatomical context. At mid-gestation, we observed changes in the structural and cellular arrangement of the hippocampus, coinciding with the emergence of a multicellular NPC layer within the DG, herein named the granular-hilar progenitor zone (GHPZ). Neurogenic transcriptomic signatures in the GHPZ were diminished by early infancy, coinciding with a reduction in NPC number as they progressed toward an astrocytic program. At childhood, the GHPZ dissolved with only sparse radial NPCs remaining in the DG. Lastly, we validated WNT signaling pathway-associated genes as NPC identity markers in the developing human DG, observing a decline in their expression after infancy. Our study defines the steep decline of NPCs from gestation to the postnatal period, identifies their progression to an astrocytic nature, and sets the molecular blueprint for NPC identification in the human DG. HighlightsO_LIMultimodal mapping of neural progenitor cells from gestational to postnatal stages in the human hippocampus C_LIO_LIFormation of the granular-hilar progenitor zone within the dentate gyrus at mid-gestation C_LIO_LINeurogenic potential declines sharply from the prenatal period to childhood, with radial glia cells progressively acquiring astrocytic features C_LIO_LIDevelopmental modulation of the WNT signaling pathway accompanies radial glia cell transitions C_LI

DNA methylation is the foundational layer of epigenetic regulation underlying mammalian tissue specification. During synaptogenesis, neurons accumulate high levels of a unique type of methylation in which a cytosine precedes a C, A, or T (mCH) instead of the canonical guanine (mCG). Disruption of the mCH reader methyl-CpG binding protein 2 (MECP2) causes the devastating neurodevelopmental disorder Rett syndrome, yet the role of mCH in neurodevelopment remains unclear. In this study, we generated the first large-scale single-cell methylation atlas of the early postnatal mouse brain and resolved subtype-specific trajectories of canonical and noncanonical methylation changes underlying neuronal subtype specification. Each identified population undergoes a rapid maturation event of the noncanonical methylome occurring between the first and second postnatal weeks, with highly subtype-specific changes concentrated at genes involved in synaptic partner establishment. Trajectory analysis resolved that subtype diversification, such as the separation of parvalbumin and somatostatin-positive GABAergic interneurons, is further facilitated by a hierarchical sequence of methylation changes in genes involved in regulation of membrane potential. In parallel, we applied single-cell methylation analysis to a mouse model of Rett syndrome that recapitulates severe human symptoms. We show that while noncanonical methylation accumulation proceeds in each subtype in the absence of MECP2, populations that have been consistently implicated in Rett pathology such as GABAergic interneurons have an increasing number of differentially methylated regions with age and fail to accumulate typical global levels of mCH. Together, our study defines the methylation dynamics that facilitate neuronal subtype specification and resolves subtype-specific, global disruptions of noncanonical methylation in Rett syndrome.

Computing the direction of a moving object requires integrating motion signals from its component edges into coherent patterns. The representation of pattern motion in visual cortex has been extensively studied, yet its underlying neural circuitry remains unknown. Using high-density recordings in macaque area MT, we show that selectivity to pattern motion emerges from a functionally and anatomically distinct cortical circuit. We demonstrate that neurons specialized for encoding component and pattern motion comprise distinct cell types arranged in a hierarchical circuit in which pattern neurons integrate inputs from a range of component neurons. Furthermore, we show that component and pattern neurons are spatially segregated into modules arranged systematically across cortical columns encoding direction of motion. This architecture and circuit align with a classic solution to the problem of computing the motion of objects.

Whether language and mathematics rely on shared or distinct neural representations remains an unresolved question in cognitive neuroscience. Here we combine latent features from a large language model (LLM) with vertex-wise encoding models to examine cross-domain generalization between language and mathematics. Thirty-two participants performed sentence comprehension and calculation tasks during fMRI, and encoding models were trained using features embedded in a common latent space. Cross-domain prediction identified cortical regions associated with partially shared representations, most prominently the left 55b, while control analyses suggested that these effects could not be fully explained by low-level visual processing or simple task-general factors. Task-specificity contrasts revealed stronger language-related prediction in the left anterior superior temporal and angular gyri and math-related prediction in the left precentral and intraparietal sulci. Model-weight analyses further showed that shared and domain-specific prediction patterns were reflected in distinct weight profiles across cortical regions. Connectivity analyses showed task-dependent functional coupling between cross-domain regions and language- or math-related networks. Together, these findings suggest that language and mathematics involve partially shared neural representations alongside domain-specific cortical organization, helping reconcile previous contrasting views on their neural basis.

Early life adversity is associated with increased risk for psychopathology and shifts in life history (LH) strategies, but the psychological mechanisms underlying these associations remain unclear. Drawing on evolutionary-developmental theory, we examined whether short-term mindsets mediate associations between dimensions of childhood adversity and mental health and LH-related outcomes. In a UK-representative sample of 877 adults, we assessed threat, deprivation, and unpredictability, alongside internalizing and externalizing symptoms, borderline features, and a latent factor capturing reproductive versus somatic maintenance effort. Structural equation models showed that adversity predicted poorer mental health and faster LH strategies. Short-term mindsets, indexed by lower future orientation and higher affective impulsivity, mediated effects of adversity, particularly unpredictability. Further decomposition of unpredictability into short-timescale and long-timescale forms revealed dissociable effects, with short-timescale unpredictability primarily linked to psychopathology and long-timescale unpredictability to reproductive-oriented LH strategies.

Vertebrate evolution has driven adaptive remodeling of brain regions impacted by changing sensorimotor demands. The cerebellum--a hindbrain area mediating associative learning and predictive coding--is thought to participate in diverse motor and non-motor behaviors across vertebrate species by duplicating and repurposing a conserved cortical circuit. Yet, few studies systematically compare circuit architecture across cerebellar evolution. We recently found that human Purkinje cells (PCs, the principal neuron of the cerebellar cortex) almost universally have multiple primary dendrites, a structural motif that confers distinct signaling properties, as shown by experiments in mice where this motif is present but less common. Seeking evolutionary insight, we developed a framework to parameterize and compare PC morphology across 11 simiiform (anthropoid) primates representing 40 million years of evolution, and mice as an outgroup. Dendritic architecture shifts profoundly from single primary dendrites with vertical orientation in mice and monkeys to multiple horizontally oriented primary dendrites in apes and, particularly pronounced, in humans. Increasing dendritic compartmentalization in the human lineage is produced by monotonic, stepwise, or human-specific trends across individual morphological traits. PC morphology is high-dimensional, with most features varying widely and independently, yet clade identity can be readily predicted from multivariate morphospace profiles. Phylogenetic patterns are not well explained by tissue foliation or allometric scaling, supporting the hypothesis that morphological variation is constrained by functional demands. Echoing a core principle of brain evolution that selection pressure drives fine-tuning of circuit elements rather than total circuit rearrangement, PC dendrite morphology may serve as a key node for cerebellar adaptation amid a conserved circuit architecture.

Sympathetic preganglionic neurons (SPNs) provide the sole spinal output to the peripheral sympathetic nervous system. Although sympathetic control is traditionally attributed to synaptic integration within the spinal cord and ganglia, the reliability of spike propagation along SPN axons themselves has received little attention. Here, and in companion papers, we show that axonal conduction in adult mouse thoracic SPNs is highly modifiable and constitutes a critical site of sympathetic gain control. Using an ex vivo preparation preserving intact paravertebral and splanchnic pathways while blocking synaptic transmission, we recorded compound action potentials evoked across multiple ganglia. Slower-conducting, unmyelinated SPN axons, particularly those with branching axons traversing the interganglionic nerve (IGN), exhibited pronounced, temperature-dependent conduction failures. Elevation of temperature produced membrane hyperpolarization and loss of conduction, consistent with activation of temperature-sensitive K2P leak channels, as supported by pharmacological evidence. Pharmacological activation of TREK-family channels with riluzole or arachidonic acid preferentially suppressed conduction in these axons. In contrast, blockade of voltage-gated K+ channels with 4-aminopyridine (4-AP) robustly facilitated conduction, recruited previously silent axons, and restored propagation under conditions of temperature-induced failure. Surprisingly, tetraethylammonium (TEA) block of K+ channels were without effect or depressant. Transmitter systems further shaped axonal reliability: agonists and antagonists of GABAA receptors, as well as cholinergic manipulations, selectively depressed conduction in slow, branching axons. Together, these findings establish SPN axons, particularly slow-conducting branching fibers, as an active and dynamically regulated substrate for sympathetic output control, revealing a presynaptic mechanism with implications for autonomic physiology and disease. SIGNIFICANCESympathetic output is commonly viewed as being regulated primarily through synaptic integration within spinal and autonomic circuits, while axons are often treated as passive transmission elements. Emerging evidence suggests this assumption is incomplete, particularly in slowly conducting and highly branched sympathetic preganglionic neuron (SPN) axons that may operate near the limits of conduction reliability. This study identifies branch point conduction as a dynamic and pharmacologically modifiable control mechanism governing sympathetic signal transmission. By demonstrating selective vulnerability of distinct SPN populations and revealing strong modulation by potassium channel mechanisms, these findings establish axonal conduction security as an underappreciated site of autonomic gain control. These mechanisms may represent novel therapeutic targets for restoring autonomic function after spinal cord injury and related disorders.

Mainland Southeast Asia (MSEA) remains under-represented in global immunogenomic references despite its extensive genetic heterogeneity. We present the first single-cell immune atlas of an MSEA population, utilizing Thai individuals from the Asian Immune Diversity Atlas (AIDA) as a representative cohort. We demonstrate that the Thai population is highly genetically diverse, reflecting its history as a geographic nexus for Asian admixture. By integrating single-cell transcriptomics with high-resolution genotyping, we show that genetic ancestry significantly shapes innate immune profiles, specifically CD14+ monocytes, highlighting potential evolutionary adaptations to regional pathogens. We identify specific sex-by-ancestry interactions that may drive the baseline activation of pro-inflammatory pathways in females, providing a long-sought cellular rationale for the high prevalence of autoimmune disorders observed in Southeast Asian populations. Ultimately, our study reveals that population-specific genetic architecture dictates immune heterogeneity often missed by self-reported ethnicity or country of origin, providing a critical immunogenomic reference for precision medicine in MSEA regions.

Length and time constants are foundational to the study of conduction in neurons and other biological cables but are exactly defined only for passive membranes. Here we define and derive exact length and time constants for propagating action potentials in unmyelinated axons. This derivation exploits specific instants during action potential conduction when the net transmembrane ionic current is zero, but axial current remains non-zero. At these instants, we define a curvature parameter,{kappa} , explore its determinants using computer modelling, demonstrate that it is the local real Laplace exponent of the action potential upstroke, and suggest practical approaches for its experimental measurement. From{kappa} , we define action potential length and time constants, {lambda}AP = 1/{surd}({kappa}racm) and {tau}AP = 1/{kappa}, and show that action potential propagation velocity is exactly {lambda}AP/{tau}AP.