Neuroscience

Background: For early detection of Alzheimer's disease, it is essential to identify individuals showing cognitive performance consistent with the mild cognitive impairment (MCI) range during preliminary screening, ideally using methods that extend beyond conventional cognitive assessments. Non-invasive, easily accessible screening tools applicable in daily life are increasingly needed. Facial expressions, particularly during rest, may offer promising biomarkers for MCI level detection. This study aimed to identify specific facial features associated with MCI level during rest to inform development of facial expression-based screening tools. Methods: Participants were classified into an MCI level group and a healthy control (HC) group based on the Montreal Cognitive Assessment (MoCA) scores. Facial Action Units (AUs) were extracted from video recordings of resting-state facial expressions in 31 individuals with MCI level and 14 HC. Two statistical models were employed: a multilevel zero-inflated beta regression model for intensity of 17 AUs and a multilevel logistic regression model for presence or absence of 18 AUs. Results: In the zero-inflated beta regression, the AU relates to upper lip raiser showed a significant group effect (MCI level vs. HC; p <0.001), remaining significant after multiple comparison correction. The logistic regression revealed significant group differences for the AUs related to lip tightener (p <0.001) and lip suck (p <0.001), both remained significant after multiple comparison correction. Conclusions: Distinctive facial action patterns during rest were observed in individuals with MCI level. These findings highlight the potential of resting-state facial expressions as a basis for novel, unobtrusive screening tools for early MCI level detection.

A central question in psycholinguistics in visual word recognition is whether morphologically complex words are obligatorily decomposed into stems and affixes during visual word recognition or whether whole-word access can occur when forms are frequent and familiar. The present study investigated how morphological complexity and lexical frequency jointly shape neural responses by leveraging Korean nominal inflection, whose transparent stem-suffix structure permits a clean dissociation between base (stem) frequency and surface (whole-word) frequency. Twenty-five native Korean speakers completed a rapid event-related fMRI lexical decision task involving simple and inflected nouns that varied parametrically in both frequency measures. Representational similarity analysis (RSA) revealed robust encoding of surface frequency--but not base frequency--in the inferior frontal gyrus (IFG) pars opercularis and supramarginal gyrus (SMG), with significantly stronger correlations for inflected than simple nouns. Univariate analyses converged with this result: surface frequency selectively increased activation for inflected nouns in inferior parietal regions, whereas base frequency showed no reliable effects in any ROI. These findings challenge models positing obligatory pre-lexical decomposition, instead supporting accounts in which morphological processing is shaped by post-lexical, usage-driven lexical statistics. Taken together, our findings shed light on a distributed perspective on morphological processing, suggesting that structural and statistical factors jointly constrain access to morphologically complex forms.

BackgroundDespite scale-up of antiretroviral therapy (ART), children living with HIV (CLHIV) and children who are HIV-exposed-but-uninfected (CHEU) are at an increased risk of poor growth outcomes compared to children HIV-unexposed-and-uninfected (CHUU). Few studies quantify the magnitude of growth deficits extending into school age in sub-Saharan Africa (SSA). This study examined the impact of perinatal HIV exposure and infection on the growth trajectory of school-aged children in Nigeria. MethodsWithin a prospective cohort, 569 children aged 3-11 years were recruited from pediatric clinics in Nigeria and matched by age and sex based on their exposure or infection status. School-aged children were observed across three time-points at 6-month intervals, during which anthropometric measures, CD4 count, and maternal factors were collected. Z-scores for height-for-age (HAZ), weight-for-age (WAZ), and body-mass-index-for-age (BAZ) were calculated using WHO standards. Longitudinal linear regression analyses using generalized estimating equations (GEE), adjusted for maternal and child covariates, were conducted to compare growth outcomes across groups. ResultsGrowth Z-scores declined until approximately age 8, after which they gradually increased. Across all visits, CLHIV consistently and independently demonstrated lower Z-scores (WAZ ({beta} = -1.04, p <0.001); HAZ ({beta} = -0.67, p <0.001)), followed by CHEU with intermediate but significant impairments (WAZ ({beta} = -0.35, p <0.01); HAZ ({beta} = -0.38, p <0.01)) compared to CHUU. ConclusionStunting remains unacceptably high in CLHIV and CHEU in SSA. The findings suggest a need for immediate paradigm shifts to address persistent growth deficits despite ART and beyond infancy.

Brain activity comprises both rhythmic (periodic) and arrhythmic (aperiodic) components. These signal elements vary across healthy aging, and disease, and may make distinct contributions to conscious perception. Despite pioneering techniques to parameterize rhythmic and arrhythmic neural components based on power spectra, the methodology for quantifying rhythmic activity remains in its infancy. Previous work has relied on parametric estimates of rhythmic power extracted from specparam, or estimates of rhythmic power obtained after detrending neural spectra. Variation in analytical choices for isolating brain rhythms from background arrhythmic activity makes interpreting findings across studies difficult. Whether these current approaches can accurately recover the independent contribution of these neural signal elements remains to be established. Here, using simulation and parameter recovery approaches, we show that power estimates obtained from detrended spectra conflate these two neurophysiological components, yielding spurious correlations between spectral model parameters. In contrast, modelled rhythmic power obtained from specparam, which detrends the power spectra and parametrizes brain rhythms, independently recovers the rhythmic and arrhythmic components in simulated neural time series, minimising spurious relationships. We validate these methods using resting-state recordings from a large cohort. Based on our findings, we recommend modelled rhythmic power estimates from specparam for the robust independent quantification of rhythmic and arrhythmic signal components for cognitive neuroscience.

Clonal hematopoiesis of indeterminate potential (CHIP) is an age-associated condition linked to chronic inflammation and an increased risk of cardiovascular diseases and hematological malignancies. People with HIV (PWH) exhibit a higher prevalence of CHIP than the general population, but the mechanisms underlying this association remain unclear. In particular, it is unknown whether the excess burden of CHIP reflects earlier emergence of mutant clones, altered clonal expansion dynamics, or differences in selective pressures acting on hematopoietic stem cells. We reconstructed longitudinal trajectories of CHIP variant allele frequency (VAF) in 52 PWH using serial peripheral blood samples spanning up to 25 years from the Swiss HIV Cohort Study. We used spline-based modelling to estimate clone size and growth dynamics, and dynamic time warping to identify common trajectory patterns. Associations between clonal dynamics and longitudinal immune parameters were assessed using linear mixed-effects models. Trajectories in PWH were compared with publicly available longitudinal CHIP data from the SardiNIA population cohort. We identified heterogeneous clonal dynamics consistent with known gene-specific fitness patterns. Larger clone size was associated with lower CD4 T-cell count and lower CD4/CD8 ratio. Compared with the general population cohort, PWH showed higher VAF across the observed age range and steeper early trajectory increases, while long-term expansion rates were broadly similar. Greater variability in clonal dynamics among PWH suggests a stronger contribution of host environmental factors to clonal fitness. These findings support a model in which HIV-associated immune dysregulation alters the hematopoietic fitness landscape, contributing to earlier detectable clonal expansion and increased burden of CHIP in PWH.

Study ObjectivesIdiopathic hypersomnia (IH) is a central nervous system hypersomnia frequently accompanied by autonomic symptoms, yet objective physiological data are limited. We sought to characterize autonomic nervous system (ANS) dysfunction in IH using nocturnal heart rate variability (HRV) and diurnal autonomic reflex testing (ART), compared to individuals with type 1 narcolepsy (NT1) and healthy controls (HCs). MethodsTwenty-four adults with IH, 10 with NT1, and 14 HCs underwent overnight video polysomnography with HRV analyses in time and frequency domains during stable slow-wave sleep and REM sleep. Comprehensive ART included sympathetic adrenergic (head-up tilt (HUT), Valsalva BP responses), parasympathetic cardiovagal (HRV to deep breathing, Valsalva ratio), and sudomotor (Q-Sweat) measures. ResultsIH participants were predominantly female, with over half reporting long sleep duration. Compared to NT1 and HC, participants with IH demonstrated a greater magnitude of orthostatic tachycardia on tilt ({Delta}HR 41.0 {+/-} 16.3 vs. 26.3 {+/-} 9.3 vs. 30.8 {+/-} 9.3 bpm, p = 0.0086), as well as frequent sudomotor dysfunction (64.3%). IH participants demonstrated greater nocturnal and REM HR with reduced parasympathetic indices during REM, indicating diminished vagal modulation compared with HCs ConclusionsIH is characterized by a distinct pattern of autonomic dysfunction, including pronounced orthostatic tachycardia, frequent sudomotor abnormalities, and reduced parasympathetic activity during sleep. These findings provide objective physiological evidence of ANS involvement in IH and delineate features that distinguish IH from NT1 and HCs.

Dystonia treatment evaluation in cerebral palsy (CP) is limited by the lack of clinician-assessed scales linking dystonia severity to functional impact. We asked 7 pediatric movement disorder specialists to review videos of 27 children with CP while performing an upper extremity task and while walking. Experts rated arm and leg dystonia severity using the Global Dystonia Severity Rating Scale (GDRS) and task-specific functional impact on a five-point scale adapted from the Dyskinetic Cerebral Palsy Functional Impact Scale. Arm GDRS scores correlated with functional impact on the upper extremity task (linear regression R^2=0.48, p=0.0005). Leg GDRS scores correlated with gait impact (R^2=0.43, p=0.001). A four-point increase in total GDRS corresponded to a one-point worsening in combined functional impact. By demonstrating how expert-rated limb dystonia severity correlates with task-specific functional impact in children with CP, these results could help clinically identify functionally-meaningful differences in dystonia severity.

ObjectivesEpidural spinal cord stimulation (SCS) is an emerging therapy for motor rehabilitation following spinal cord injury (SCI) and other motor disorders. Conventionally, SCS leads are placed along the dorsal spinal cord (SCSD), where stimulation activates large diameter afferent fibers, which indirectly activate motoneurons through reflex pathways. This leads to broad activation of flexor and extensor muscles and limited fine-tuned control of motor output. Targeting the ventral spinal cord (SCSV) may enable more direct activation of motoneuron pools, potentially improving the specificity of muscle activation; however, there is currently no established method to place leads ventrally. To address this, we evaluated the feasibility of four modified percutaneous implantation techniques to target the ventrolateral thoracolumbar spinal cord. Materials and methodsPercutaneous SCSV implantation was performed in three human cadaver torso specimens under fluoroscopic guidance. The following approaches were evaluated: sacral hiatus, transforaminal, interlaminar contralateral, and interlaminar ipsilateral. The leads in the latter 3 approaches were inserted between L1 and L5. Eighteen implants were attempted, with nine leads retained for analysis. Lead and electrode position were assessed using computed tomography (CT) with three-dimensional reconstruction, along with anatomical dissection to verify lead and electrode placement within the epidural space. ResultsSuccessful ventral epidural lead placement was achieved using all four implantation approaches. The sacral hiatus (16/16 electrodes) and transforaminal (8/8 electrodes) approaches resulted in exclusively ventrolateral placement. The interlaminar contralateral approach led to 27/32 electrodes positioned ventrolaterally and 5/32 dorsally. The interlaminar ipsilateral implantation approach led to 14/32 electrodes positioned ventrolaterally and 18/32 positioned ventromedially. ConclusionsThese findings demonstrate that ventral epidural SCS lead placement can be achieved using modified percutaneous implant techniques. The four approaches outlined here provide a clinically feasible pathway to SCSV and establishes a foundation for future clinical studies investigating SCSV for motor rehabilitation following SCI.

PurposePrevious research has demonstrated effects of head impact exposure on cortical neurophysiology, which may help with understanding variability in clinical sequelae. In separate lines of research, neurochemical and gene transcription markers of vulnerability to traumatic brain injury (TBI) have been established. The purpose of this study was to examine whether these cortical neurochemical and gene transcription gradients are spatially aligned with neurophysiological effects. Methods and MaterialsMagnetoencephalography (MEG) data was collected at a total of 278 pre- and post-season timepoints from 91 high school football players across up to four seasons of play. Of the 91 football players, 10 experienced a concussion, and of the remaining 81 non-concussed players, 71 met the criteria for complete imaging and kinematic data, with post-season evaluations less than six weeks after the end of the season. Head impacts were tracked over the course of the season with helmet-mounted sensors. MEG data underwent source-imaging, frequency-transformation, spectral parameterization, and linear modeling to examine the effects of concussive and non-concussive head impact exposure on pre-to-post-season changes in rhythmic and arrhythmic neurophysiological activity. To determine clinical effects, parent reported Post-Concussive Symptom Inventory scores related to cognitive symptoms were correlated with cortical neurophysiological changes. Multi-atlas data of neurochemical system densities from neuromaps and gene expression from the Allen Human Brain Atlas were examined for alignment with head impact-related alterations in neurophysiology via nonparametric spin-tests with autocorrelation-preserving null models (5,000 Hungarian spins; pFDR <.05). ResultsConcussion-related reductions in cortical excitability (i.e., aperiodic exponent slowing) were aligned with atlas-based norepinephrine transporter (NET) and alpha-4 beta-2 nicotinic receptor (4{beta}2) densities, and with apolipoprotein E (APOE) and brain-derived neurotrophic factor (BDNF) expression levels. More severe cognitive symptoms associated with concussion-related slowing of aperiodic neurophysiology were also aligned with atlas-based NET and 4{beta}2 receptor densities. Similar changes in cortical excitability related to non-concussive head impact exposure were colocalized with serotonin receptor (5-HT1A) density maps and APOE and BDNF expression. Rhythmic alpha activity was reduced by concussion and colocalized with histamine (H3) and mu-opioid (MOR) receptors, among others, as well as with gene transcription atlases of APOE and C-C chemokine receptor 5 (CCR5). ConclusionsThese findings extend our previous work to show that the effects of head impact exposure on neurophysiology are strongest in cortical areas with specific neurochemical and genetic profiles that are known to signal vulnerability to traumatic brain injury, and that these spatial alignments are also associated with self-reported symptom severity. Clinical Relevance / ApplicationChange in cortical excitability, as measured here by MEG, has potential value as a clinical tool for concussion diagnosis and prognosis. We provide genetic and neurochemical contextualization for these changes that may extend their clinical applications, for example to concussion risk assessment and pharmacotherapies.

Digital pathology, coupled with advanced image recognition algorithms, represents a transformative frontier in histopathological diagnosis. This sub-Saharan African laboratorys exploratory study investigates the application of a Convolutional Neural Network (CNN) model, specifically leveraging the VGG16 architecture with transfer learning, for automated analysis and classification of selected gastrointestinal (GIT) and liver tissue samples, incorporating both routine and specialized staining protocols. The study utilized a dataset comprising 114 samples (18 liver, 96 GIT images) derived from archival formalin-fixed paraffin-embedded tissue blocks at University College Hospital, Ibadan, Nigeria. Specialized staining techniques included Alcian Yellow for GIT mucin visualization and Massons Trichrome for liver fibrosis assessment, alongside conventional H&E staining. Model performance was evaluated using statistical methodologies including Wilson Score confidence intervals (CI), Bayesian probability assessment, and effect size analysis. Results reveal a striking dichotomy in model performance. The GIT tissue model achieved perfect classification accuracy (100% test accuracy) with exceptional statistical significance (Z=10.0, p<0.0001), Wilson CI [96.29%, 99.99%], Cohens h=1.571, and Bayesian probability >99.99%. Conversely, the liver tissue model demonstrated diagnostic failure (42.86% test accuracy), with Z=-1.428, p=0.9236, Wilson CI [33.59%, 52.65%], Cohens h=-0.144, and Bayesian probability of 7.64%. This performance divergence correlates with training data availability, as the liver dataset fell far below empirically established thresholds (>100-200 samples) for reliable classification. The liver models failure reveals limitations in transfer learning with insufficient data. These findings underscore critical implications for AI-enhanced digital pathology, demonstrating potential deployment of the GIT model as a promising one that supports tissue-specific model development.

BackgroundRespiration is a key central nervous system rhythm that modulates sensorimotor function in healthy individuals, but the neurophysiological mechanisms of volitional breathing-mediated sensorimotor modulation and its preservation in stroke patients remain unclear. This study aimed to characterize the effects of volitional fast inspiration on sensorimotor pathway excitability in healthy and stroke populations, and provide a mechanistic basis for respiratory-integrated post-stroke rehabilitation. MethodsA multimodal case-control neurophysiology study was conducted in 52 healthy volunteers (26 {+/-} 3 years, 30 males) and 44 first-ever subacute stroke patients (66 {+/-} 10 years, 30 males). Three complementary experiments assessed transcranial magnetic stimulation-induced motor-evoked potentials (MEPs), peripheral nerve stimulation-induced somatosensory-evoked potentials (SEPs), and functional electrical stimulation -evoked muscle force under three breathing conditions: volitional fast inspiration (IN), fast expiration (EX), and spontaneous breathing (CON). Two-way and one-way repeated measures ANOVA with Bonferroni post hoc tests were used for statistical analysis. ResultsVolitional fast inspiration significantly enhanced sensorimotor pathway excitability and muscle force generation in both groups. Volitional fast inspiration increased MEP amplitudes relative to spontaneous breathing and fast expiration (p {inverted exclamation} 0.05), with further amplification during active muscle contraction (p {inverted exclamation} 0.05). It also elevated SEP amplitudes in healthy parietal/frontal cortical regions and the stroke parietal cortex (p {inverted exclamation} 0.05). Synchronizing volitional fast inspiration with voluntary finger contraction increased muscle force evoked by functional electrical stimulation by 16-18% relative to spontaneous breathing (p {inverted exclamation} 0.05), with non-significant force gains at rest. ConclusionsVolitional fast inspiration bidirectionally enhances corticospinal transmission, somatosensory integration, and functional force generation in both healthy individuals and stroke patients, with preserved respiratory modulation in stroke-damaged neuropathways. By demonstrating preserved respiratory modulation in stroke-damaged neuropathways, our results provide mechanistic support for integrating controlled breathing into low-cost, non-invasive post-stroke rehabilitation paradigms.

Patterns of locus coeruleus (LC) activity and norepinephrine (NE) release during non-rapid-eye-movement (NREM) sleep suggest a critical role for the LC-NE system in offline modulation of forebrain circuits. NE transmission promotes synaptic plasticity and is required for memory consolidation, but the field has only begun to uncover how LC activity contributes to coordinated forebrain network dynamics. Hippocampal ripples, a hallmark of memory replay, are temporally coupled with thalamocortical oscillations; however, the circuit mechanisms underlying systems-level consolidation across larger brain networks remain incompletely understood. Here, using multi-site electrophysiology, we examined LC firing in relation to hippocampal ripples in freely behaving rats. LC activity and ripple occurrence were state-dependent and inversely related: heightened arousal was associated with increased LC firing and reduced ripple rates. At finer timescales, LC spiking decreased {approx}1-2 seconds before ripple onset, with the strongest modulation during awake ripples but minimal change during ripple- spindle coupling. These findings reveal state-dependent dynamics of LC-hippocampal interactions, positioning the LC as a key component of a cortical-subcortical network supporting systems-level memory consolidation.

Although several ancillary tests are available in limited laboratories, diagnosis of microphthalmia (MiT)/TFE family translocation renal cell carcinoma (tRCC) could be challenging due to diverse and overlapping tumor morphology and the lack of reliable biomarkers. GPNMB has been recently identified as a diagnostic marker for various renal neoplasms with FLCN/TSC/mTOR-TFE alterations. However, the sensitivity and specificity of GPNMB immunostain are suboptimal and the result interpretation in ambiguous cases could be difficult. To search additional biomarkers that could improve the screening sensitivity and predict genetic aberrations in FLCN/TSC/mTOR-TFE pathway in renal tumors, we performed bioinformatic analysis of publicly available cancer databases and found GPR143, a transmembrane protein regulated by MiT transcription factors, was highly expressed in a subset of renal cell carcinomas (RCCs). In two the Cancer Genome Atlas (TCGA) kidney cancer cohorts, RCCs with high levels of GPR143 expression were enriched for renal neoplasms with FLCN/TSC/mTOR-TFE alterations. Similar to GPNMB labeling, GPR143 immunostain was positive in the majority of tRCC cases and renal tumors with FLCN/TSC/mTOR alterations, suggesting that GPR143 could function as another surrogate marker for FLCN/TSC/mTOR-TFE alterations in certain renal tumors. Interestingly, despite the concordant GPR143 and GPNMB immunoreactivity in most renal neoplasms with FLCN/TSC/mTOR-TFE alterations, diffuse GPR143 immunostain was observed in some cases with negative or focal GPNMB labeling. Taken together, our results indicate GPR143 could serve as a useful adjunct marker to improve the sensitivity for screening renal tumors with FLCN/TSC/mTOR-TFE alterations.

Background: Deep brain stimulation (DBS) is a treatment option for Parkinson disease (PD). However, the effect of DBS on the arterial pressure (AP) remains unexplored. We aimed to develop an artificial baroreflex system for treating orthostatic hypotension (OH) due to central baroreflex failure in patients with PD. To achieve this, we developed an appropriate algorithm after estimating the dynamic responses of the AP to DBS using a white noise system identification method. Methods: We randomly performed DBS while measuring the AP tonometrically in 3 trials involving 3 patients with PD treated with DBS. We calculated the frequency response of the AP to the DBS using a fast Fourier transform algorithm. Finally, the feedback correction factors were determined via numerical simulation. Results: The frequency responses of the systolic AP to random DBS were identifiable in all 3 trials, and the steady state gain was 8.24 mmHg/STM. Based on these results, the proportional correction factor was set to 0.12, and the integral correction factor was set to 0.018. The computer simulation revealed that the system could quickly and effectively attenuate a sudden AP drop induced by external disturbances such as head-up tilting. Conclusion: An artificial baroreflex system with DBS may be a novel therapeutic approach for OH caused by central baroreflex failure.

Objective Cerebral palsy (CP) affects approximately 1 million Americans and 18 million individuals worldwide, yet contemporary US epidemiologic data remains limited. We aimed to use Cerebral Palsy Research Network (CPRN) clinical registry to describe demographics and clinical characteristics of individuals with CP across the US and determine associations with gross motor function and genetic etiology. Methods Registry subjects were included if they had clinician-confirmed CP and prospectively entered data for Gross Motor Function Classification System (GMFCS) Level, gestational age, genetic etiology, CP distribution, and tone/movement types. Logistic regression was used to determine which of these variables plus race, sex, ethnicity, and age were associated with GMFCS level and genetic etiology. Results A total of 9,756 children and adults with CP from 22 CPRN sites met inclusion criteria. Participants were predominantly White (73.0%), male (57.3%), non-Hispanic (87.8%), and younger than 18 years (73.7%). Most were classified as GMFCS levels I-III (55.6%), born preterm (52.8%), had spasticity (83.8%), and had quadriplegia (41.9%); 12.2% were identified as having a genetic etiology. Tone/movement types, CP distribution, and gestational age were significantly associated with both GMFCS level and genetic etiology (p<0.001). Compared to White individuals, Black individuals were more likely to have greater gross motor impairment (p<0.001). Conclusion In this large US cohort, clinical and demographic factors, including race, were associated with gross motor function and genetic etiology in CP. These findings highlight persistent disparities and demonstrate the value of a national clinical registry for informing prognostication, quality improvement efforts, and targeted genetic testing strategies.

Walking impairments in Parkinsons disease (PD), including reduced speed, cadence, and stride length, and increased variability, impair mobility and raise fall risk. Conventional treatments may fail to address these deficits, underscoring the need for complementary non-invasive alternatives. This study examined whether combining rhythmic auditory cueing with transcranial direct current stimulation (tDCS) over the supplementary motor area (SMA), a critical region for internally-generated movement, would enhance gait performance in PD. Thirty-three participants with PD and thirty-two healthy controls completed two sessions (anodal vs. sham tDCS) with gait assessed during stimulation, immediately after stimulation, and 15 minutes after stimulation under two auditory conditions: walking in silence and walking to music paced 10% faster than baseline cadence. Spatiotemporal, variability, and stability gait parameters were analyzed using linear mixed-effects models. Rhythmic auditory cueing significantly increased cadence and speed during, immediately after, and especially 15 minutes after stimulation, suggesting sustained effects of rhythmic entrainment. Anodal tDCS produced faster cadence, as well as lower stride time variability and stride width, particularly in individuals with PD. Although both music and anodal tDCS affected gait, no interaction was observed, indicating independent effects. Individuals with PD had greater gait variability overall, and adjusted temporal gait parameters less to music than healthy controls did. Anodal stimulation reduced walking variability in PD, reducing the group differences observed under sham conditions. These findings suggest that rhythmic cueing and SMA stimulation target complementary mechanisms, highlighting the promise of combined tDCS-music interventions for gait rehabilitation in PD.

This study investigated retirement adjustment in retired police officers in the UK (N = 289), examining how time since leaving the service moderates the relationship between perceived organisational support and retirement adjustment while accounting for resilience. Results indicated a developmental trend: organisational support remains stable initially but becomes increasingly influential in later life. Using Johnson-Neyman analysis, a threshold of 32.07 years was identified, after which the association reaches statistical significance. These findings suggest an organisational legacy effect; for the older generation, the retrospective perception of being valued by the service acts as a durable psychological resource. This study offers a novel conceptualisation of long-term organisational influence by identifying a temporally delayed legacy effect that extends beyond existing models of retirement adjustment. The study advocate for lifelong wellbeing strategies that extend, recognising that the organisational relationship continues to shape adjustment outcomes decades after the conclusion of active duty.

Predicting response to induction chemotherapy (IC) and overall survival (OS) is critical for optimizing treatment in patients with locally advanced nasopharyngeal carcinoma (LANPC). This study aimed to develop and validate a multi-task deep learning model integrating pretreatment MRI and whole slide images (WSIs) to predict IC response and OS in LANPC. Pretreatment MRI and WSIs from 404 patients with LANPC were retrospectively collected to construct a multi-task model (MoEMIL) for the simultaneous prediction of early IC response and OS. MoEMIL employed multi-instance learning to process WSIs, PyRadiomics and a convolutional neural network (ResNet50) to extract MRI features, and fused multimodal features through a multi-gate mixture-of-experts architecture. Clustering-constrained attention multiple instance learning and gradient-weighted class activation mapping were applied for visualization and interpretation. MoEMIL effectively stratified patients into good and poor IC response groups, achieving areas under the curve of 0.917, 0.869, and 0.801 in the train, validation, and test sets, respectively, and outperformed the deep learning radiomics model, the pathomics model and TNM staging. The model also stratified patients into high- and low-risk OS groups (P < 0.05). MoEMIL shows promise as a decision-support tool for early IC response prediction and prognostication in LANPC. Author SummaryWe have developed a deep learning model that integrates two types of medical images, including magnetic resonance imaging (MRI) and digital pathological slices, to simultaneously predict response to induction chemotherapy and prognosis in patients with locally advanced nasopharyngeal carcinoma. Current treatment decisions primarily rely on traditional tumor staging (TNM), which often fails to comprehensively reflect the complexity of the disease. Our model, named MoEMIL, was trained and tested on data from 404 patients across two hospitals and consistently outperformed both single-model approaches and TNM staging methods. By identifying patients who exhibit poor response to induction chemotherapy or higher prognostic risk, our tool can assist clinicians in achieving personalized treatment, enabling intensified management for high-risk patients and avoiding unnecessary side effects for low-risk patients. Additionally, we visualize the models reasoning process through heat map generation, which highlights the image regions exerting the greatest influence on prediction outcomes. This work represents a step toward more precise treatment for nasopharyngeal carcinoma; however, larger-scale prospective studies are required before the model can be integrated into routine clinical practice.

Objective: Skin sympathetic nerve activity (SKNA) has emerged as a promising non-invasive surrogate measure of sympathetic drive, but its relevant physiological characteristics remain ill-defined. This observational study aims to investigate its regulatory patterns during rest and Valsalva maneuver (VM) in healthy participants. Method: Using a two-layer strategy integrating signal analysis and physiological modelling, we analyzed data recorded from 41 subjects performing repeated VMs. The observational layer includes time-domain feature comparisons using linear mixed-effect models, and time-varying spectral coherence analysis. The mechanistic layer proposes a mathematical model to investigate whether baroreflex and respiratory modulation are sufficient to reproduce the observed HR and average SKNA (aSKNA) dynamics. Main Results: Mean integrated SKNA (iSKNA) showed more significant change than HRV for VM induced effects. We also found mean iSKNA increase during VM varies with BMI and sex. The coherence analysis indicated that iSKNA strongly synchronized with EDR under resting conditions. The proposed model successfully reproduced main characteristics of aSKNA dynamics, yielding a high median Pearson correlation coefficient of 0.80 ([Q1, Q3] = [0.60, 0.91]). In contrast, HR dynamics were only partially captured, with a median PCC of 0.37 ([Q1, Q3] = [0.16, 0.55]). These results likely suggest SKNA provides a more direct representation of sympathetic burst dynamics during VM in healthy subjects. Significance: This study provides convergent evidence that SKNA reflects known autonomic regulatory influences in healthy subjects. These findings strengthen the physiological interpretability of SKNA while clarifying its appropriate use as a practical biomarker of sympathetic function.

Neural excitability fluctuates with sensory events, creating windows of opportunity to enhance brain stimulation. Repetitive transcranial magnetic stimulation (TMS), including intermittent theta burst stimulation (iTBS), is a promising treatment for neurological and psychiatric disorders, but does not account for fluctuations in neural excitability, likely contributing to variable outcomes. Sensory Entrained TMS (seTMS) leverages sensorimotor oscillations to enhance corticospinal responses, but the sustained effects as a repetitive protocol are unknown. We extend seTMS to iTBS, measuring motor-evoked potentials (MEPs) as a physiological readout. In a randomized crossover study comparing standard iTBS with sensory entrained iTBS (se-iTBS; n=20), we found that se-iTBS more than doubled the MEP effect (55% vs 26% MEP enhancement) and persisted for at least 30 minutes. Notably, at least 80% of participants showed larger responses with se-iTBS at all time points. se-iTBS may provide a robust and practical framework for optimizing TMS that bridges electrophysiological mechanisms and clinical applications.