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Rare earth elements (REEs) in surface sediments and the soft tissues of bivalve mollusks (mussels and oysters) from the coast of Korea were investigated to evaluate their degrees of pollution and bioaccumulation. REE concentrations in surface sediments, mussels, and oysters showed a general sawtooth pattern. Surface sediments were not contaminated with REEs and were mainly influenced by REEs of natural rather than of anthropogenic origin. None of the REEs in sediments posed a potential ecological risk to marine biota. The mean REE concentrations were up to 1.6 times higher in oysters than in mussels, and a moderate correlation between the REEs in sediments and oysters was determined. The REE distribution patterns and biota-sediment accumulation factor suggested that, in assessments of REE bioavailability in marine environments, oysters are a better environmental monitoring organism than mussels.
There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to ∼300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq™ PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.
Pelvic organ prolapse (POP) significantly impacts women's physical and mental health. Although current research primarily focuses on the analysis of extracellular matrix (ECM) components, the underlying pathological imbalances of POP remain incompletely understood. The functional roles and phenotypic changes of fibroblasts within the complex microenvironment of prolapsed tissue warrant further investigation. To decipher the pathological basis of pelvic organ prolapse (POP) at single-cell resolution through analyzing the heterogeneity of fibroblasts, exploring prolapse-specific fibroblast subtypes and their functional characteristics. A total of 6 full-thickness prolapsed vaginal wall tissue samples were collected from patients with stage III or IV pelvic organ prolapse (POP group), along with 3 control tissue samples from patients with stage 0-I prolapse who underwent total hysterectomy for benign gynecological diseases (CTRL group). Nuclei were isolated from frozen tissues and processed into single-nucleus suspensions for snRNA-seq. The sequencing data were subjected to dimensionality reduction, clustering, cell type annotation, and subpopulation identification to construct a single-nucleus transcriptome atlas of the anterior vaginal wall, with a focused exploration of fibroblast heterogeneity. Gene Ontology Biological Process (GO BP) enrichment analysis was performed to investigate dysregulated cellular functions and the functional characteristics of fibroblast subpopulations. Pseudotime trajectory analysis was performed to construct fibroblast differentiation trajectories and investigate fibroblast subpopulation specific differentiation aberrations. The main findings of bioinformatics analysis were validated by immunofluorescence staining and in vitro functional assays. The transcriptomes of 96,622 vaginal wall cell nuclei isolated from POP and CTRL group were profiled. Fibroblasts, endothelial cells, and epithelial cells were the major cell populations in the anterior vaginal wall. Fibroblasts exhibited significantly higher enrichment scores for extracellular matrix (ECM) and related gene sets compared to other cell types, underscoring their critical role in regulating ECM homeostasis in pelvic floor tissues. In the POP group, we observed an increased proportion of pro-inflammatory (IL6ST+_FIB) and matrix-degrading (MMP2+_FIB) fibroblast subpopulations, alongside a decreased proportion of ECM-synthesis (COL1A1+_FIB) and mesenchymal (POSTN+_FIB) fibroblast subpopulations. Pseudotime trajectory analysis further revealed that fibroblast differentiation in POP samples shifted away from an ECM-synthesis phenotype toward pro-inflammatory and matrix-degradating phenotypes. Functional enrichment analysis of fibroblasts showed that biological processes related to ECM remodeling and negative regulation of cell migration and growth were upregulated. Consistently, fibroblasts isolated from prolapsed tissue exhibited impaired proliferation and migration capabilities. Fibroblasts in prolapsed vaginal wall exhibited marked heterogeneity compared to non-prolapsed tissue, comprising 6 functionally distinct subpopulations, including those involved in ECM synthesis, pro-inflammatory, and matrix degradation. In the prolapse microenvironment, an aberrant phenotypic shift was observed that fibroblasts transitioned from an ECM-stable phenotype predominantly characterized by COL1A1+_FIB toward pro-inflammatory (IL6ST+_FIB) and matrix-degrading (MMP2+_FIB) phenotypes, which contributes to extracellular matrix disorganization and impaired tissue repair capacity. These findings further enhance the understanding of the fibroblast phenotype imbalance underlying POP and provide novel therapeutic strategies targeted at modulating fibroblast function to restore pelvic floor.
The accurate prediction of particulate matter concentrations serves as the foundation for effective air quality management. Hisar City, which resides in north-west India, experiences high levels of PM2.5 and PM10 pollution because of vehicular and industrial emissions, construction and farming activities, and weather conditions. The research tests machine learning models to forecast PM2.5 and PM10 levels in Hisar City. Historical air quality data together with weather data for a period of 2020-2024 were gathered and an exploratory data analysis was performed to study the seasonal behaviour of particulate matter for the representative location. For modelling analysis, the periodic data from the year 2020 to 2023 was used for model training and the data from the year 2024 was used for testing. The research used Support Vector Regression (SVM), Random Forest (RF), Gradient Boosting, AdaBoost and M5 regression to create and test multiple machine learning models. For model explainability, SHAP analysis along with the sensitivity were performed to study the role and contribution of weather variables on the PM concentration estimation. The researchers used correlation coefficient (CC), root mean squared error (RMSE), and mean absolute error (MAE) as statistical indicators to assess the model performance. The study results showed that ensemble-based models (Gradient Boosting and RF) provide better results than the other regression models for predicting PM concentrations of the city. Correlation coefficient of 0.73 and 0.668 was achieved by Gradient Boosting model for PM2.5 and PM10 prediction along with the least RMSE values during testing. The RF model achieved CC values of 0.724 and 0.674 for PM2.5 and PM10 prediction, respectively, during testing. The proposed method shows that machine learning techniques can be used to predict air quality reliably, which helps policymakers develop effective emergency response plans.
Land use types and elevation gradients are key determinants of soil environment, thereby shaping the composition and diversity of soil bacterial communities. Nevertheless, our understanding of how the composition, diversity, and functions of soil bacterial communities vary among land use types along elevation gradients remains limited. The present study was conducted in the biodiversity-rich Gaoligong Mountains, where soil samples were collected from shrublands (SL), coffee fields (CF), maize fields (MF), and orange fields (OF) along an elevation gradient spanning 900-1800 m (i.e., 900-1200 m, 1200-1500 m, and 1500-1800 m). A 16 S rRNA amplicon sequencing was applied to assess the composition of soil bacterial community. In addition, we employed FAPROTAX to perform functional classification based on the 16 S sequencing data. The results showed that land use types, elevation, and their interactions had significant affected on soil chemical properties, α diversity and functions of soil bacterial communities. PERMANOVA analysis further revealed that both land use types (R2 = 0.21) and elevation (R2 = 0.09) both had significant effects on the bacterial β diversity. The nine measured soil chemical properties explained 86.35%, 86.88%, and 83.75% of the variation in soil bacterial community composition at low, medium, and high elevation, respectively, suggesting that soil chemical conditions were major determinants of bacterial community composition across elevation gradients. Among these factors, soil nitrogen variables including NO3--N, TN, NO4་-N played particularly role in shaping soil bacterial community composition. Overall, land use types and elevation gradients jointly shape the composition, diversity, and function of soil bacterial communities in the Gaoligong Mountains. This study can help enhance our understanding of how anthropogenic and natural factors interact to influence soil microbial communities in mountain ecosystems, and provides a scientific basis for soil health management and the conservation of microbial ecosystem functions under global environmental change.
Individuals reliably differ in how they look at complex visual scenes, with the most prominent variation in their propensity to fixate faces and text. Here we tested the hypothesis that these differences in gaze are linked to representational properties of the individual visual system in 61 adults. Eye-tracking captured each observer's characteristic gaze tendencies during naturalistic scene viewing, and independent functional magnetic resonance imaging recorded category-selective responses to faces, words and other stimuli when participants were instructed to fixate centrally. We find that the propensity to fixate faces or text goes along with enhanced distinctiveness and enlarged functional regions of corresponding categorical representations in the ventral stream. These in turn predicted performance on reading and face recognition tasks. Thus, active vision appears linked to the precision of category-selective encoding and corresponding neural resources in the individual brain.
Acute kidney injury (AKI) is a common and serious complication in critically ill patients receiving extracorporeal membrane oxygenation (ECMO), significantly affecting mortality and long-term renal function. However, risk factors and clinical course of AKI across different ECMO modalities remain poorly understood. Herein, our study identified independent risk factors for AKI in ECMO patients and evaluated the effect of AKI severity on 30-day mortality. This multicenter retrospective cohort study enrolled patients from three ECMO centers (September 2019-June 2024). AKI was defined and staged according to KDIGO serum creatinine criteria within 7 days after ECMO initiation. Multivariate stepwise logistic regression identified predictors of moderate-to-severe AKI (stages 2-3). Cox proportional-hazards models assessed the association between AKI stage and 30-day mortality. Among 210 patients, 110 (52.4%) developed AKI stages 2-3 within 7 days. Serial monitoring showed a progressive increase in stage 2, while stage 3 plateaued. Moderate-to-severe AKI was independently associated with 30-day mortality. In the overall cohort, VA-ECMO modality and norepinephrine use were independent risk factors for AKI stages 2-3, while high fibrinogen (FIB) level and a history of cardiovascular disease (CVD) were protective. In the VV-ECMO subgroup, elevated lactate, bicarbonate, FIB, procalcitonin, and blood urea nitrogen levels, along with decreased total bilirubin and white blood cell counts were significantly associated with increased moderate-to-severe AKI risk. Herein, our study indicated that severe AKI independently predicts 30-day mortality in ECMO patients. VA-ECMO modality and NE use increase moderate-to-severe AKI risk, while high FIB level and CVD provide protection.
Detecting natural selection operating at the amino acid sequence level of proteins is essential for understanding the functional importance of amino acid sites and substitutions. Relatively large number of sequences are required for detecting natural selection using statistical methods including the parsimony method. However, applicability of the parsimony method declines as the number of sequences increases, partly due to the difficulty in inferring ancestral sequences at interior nodes of the phylogenetic tree. Here, an attempt was demonstrated to detect natural selection by the parsimony method without inferring ancestral sequences, through estimating the numbers of synonymous and nonsynonymous substitutions utilizing the minimum numbers of nucleotide and amino acid substitutions along the phylogenetic tree. In the analysis of 19,949 sequences for hemagglutinin of influenza A virus A(H1N1)pdm09, recurrent positive selection was detected at the amino acid sites in B cell and T cell epitopes. In addition, episodic positive selection was detected for the amino acid substitution giving rise to N-linked glycosylation at position 162. These results suggested a possibility that the parsimony method may remain applicable to large-scale sequence analyses for detecting natural selection.
Collective cognition, in which groups display enhanced problem-solving abilities compared with individuals, is a hallmark of ant behaviour. For instance, in navigation tasks, such as the piano movers' problem, a short-term memory-like directional persistence emerges in large enough ant groups and aids them in implementing an effective wall-following heuristic. Here, we investigate the collective problem-solving abilities of Paratrechina longicornis by presenting groups of varying sizes with an array of piano movers' puzzles. We find that increasingly complex puzzles reveal performance differences between small and large groups. To benchmark these results, we compare the performance of the ants to a simulated physics-based null model incorporating gravity and noise. Although the null model performs comparably with ants in simple puzzles, it fails in more challenging ones. Introducing ant-inspired mechanisms, including attachment along edges or transient leadership, enables the simulated solver to match ant performance across group sizes and tasks. Beyond these features, we show that ants solve a broad spectrum of puzzles without prior knowledge of geometry, whereas the simulated solver requires parameter adjustments tailored to each puzzle. Our findings highlight the flexibility and robustness of collective cognition in ant groups and provide a framework for integrating biological strategies into artificial problem-solving systems.
This study investigates the regulatory role of p21-activated protein kinase 1 (PAK1) in estrogen secretion during ovulation induction in Bactrian camels, along with the associated molecular mechanisms. We evaluated the morphological differences of follicles between ovulatory and non-ovulatory camels through rectal examinations and B-ultrasound imaging. Using iTRAQ quantitative proteomics, we identified a significant upregulation of PAK1 protein in the ovarian tissues of the ovulatory group, followed by a bioinformatics analysis to explore its biological functions. Our results revealed distinct tissue-specific expression and distribution patterns of PAK1 within the hypothalamic-pituitary-gonadal (HPG) axis. In in vitro cultured ovarian granulosa cells, FTY720-induced activation of PAK1 significantly increased cell viability, reduced apoptosis rates, and decreased the expression of apoptosis-related molecules. Additionally, PAK1 activation enhanced the expression of key enzymes and receptors involved in estrogen synthesis, promoting estradiol secretion. Conversely, inhibiting PAK1 with IPA-3 resulted in opposing effects, exacerbating granulosa cell apoptosis and reducing estrogen synthesis. Overall, this study demonstrates that PAK1 is essential for regulating estrogen secretion by modulating granulosa cell apoptosis and the expression of key steroidogenic enzymes, ultimately influencing ovulation induction in Bactrian camels. These findings improve our understanding of the reproductive regulatory mechanisms in camels and provide a molecular framework for further investigations into ovulation induction and enhancements in reproductive performance.
The aim of this study was to evaluate pattern visual evoked potential (PVEP) and pattern electroretinography (PERG) parameters during the attack-free period in patients with multiple sclerosis (MS) with and without a history of optic neuritis (ON), as well as in individuals with non-MS demyelinating diseases and healthy controls. This cross-sectional study included 71 patients with demyelinating diseases (95 eyes) and 44 healthy volunteers (88 eyes). This study was prospectively designed to evaluate clinical and electrophysiological data obtained during the routine diagnostic work-up and follow-up in our Neuro-ophthalmology Unit. Patients were classified into three groups: MS with ON (MS + ON), MS without ON (MS-ON), and non-MS demyelinating disorders with ON (non-MS + ON). All participants underwent a comprehensive ophthalmological examination followed by PVEP and PERG testing. Tests were conducted using the Metrovision Monpack system. The peak latencies and amplitudes of the PVEP N75 and P100 waves, as well as the peak latencies and amplitudes of the PERG P50 and N95 waves, were analyzed and compared with control subjects. To account for inter-eye dependency, we employed Generalized Estimating Equations (GEE), specifying a Gaussian family with an identity link function and an exchangeable working correlation structure. Results are reported as median (range) and Mean Differences (MD) with 95% CI. In the MS + ON group, a significant prolongation of P100 latency along with marked reductions in both P100 and N95 amplitudes was observed (p < 0.001), indicating demyelination accompanied by axonal damage. Additionally, the MS - ON group demonstrated a significant prolongation of P100 latency (p = 0.02) and a reduction in N95 amplitude (p = 0.005), suggestive of subclinical retinal ganglion cell dysfunction in the absence of ON. In the non-MS + ON group, although P100 latency was prolonged (p = 0.01), P100 amplitude was preserved (p = 0.28); however, a significant reduction in N95 amplitude was detected (p = 0.002). Effect sizes were expressed as Mean Differences (MD) with 95% Confidence Intervals (CI) to emphasize clinical magnitude over binary p-values. In combination with PVEP, PERG enhances neuro-ophthalmological evaluation by revealing optic nerve and retinal ganglion cell involvement across both acute and chronic stages of demyelinating diseases.
Health inequality remains a persistent challenge in rural areas, where limited healthcare accessibility is often associated with lower levels of health capital. In China, traditional Chinese medicine (TCM) service accessibility constitutes an important component of the rural healthcare system. However, whether and to what extent TCM service accessibility is associated with health capital and health inequality remains insufficiently understood. This study investigates whether, and through which mechanisms, TCM service accessibility is associated with health capital among rural residents and whether it is associated with lower health inequality. This study uses micro-level survey data from 12860 rural residents across six provinces in China, combined with county-level healthcare resource statistics. The empirical strategy includes multivariate regression, instrumental variable estimation, mediation analysis, heterogeneity analysis, and inequality decomposition. Health capital is measured using a composite index constructed from four standardized dimensions: self-rated health, activities of daily living, chronic disease status, and objective physiological indicators (including blood pressure and fasting blood glucose). These indicators are aggregated using principal component analysis (PCA), with the first principal component used as the health capital index. TCM service accessibility is operationalized along three dimensions: supply availability, geographical accessibility, and individual utilization. The results show that greater TCM service accessibility is significantly associated with higher levels of health capital among rural residents. Specifically, a 0.1-unit increase in TCM service accessibility corresponds to an increase of approximately 0.021 units in the health capital index. The estimated effects exhibit significant heterogeneity, with larger magnitudes among individuals with poorer baseline health and lower income levels, and in settings with higher levels of social support. From an equity perspective, TCM service accessibility shows an equalizing association with the distribution of health capital, with a contribution share of -0.10 and an estimated contribution corresponding to approximately 0.030 of the health capital Gini coefficient. This represents the largest equalizing association among all examined factors, including income, education, and Western medical resources. Quantile regression results further indicate that the estimated effect at the 10th percentile of the health capital distribution is four times larger than that at the 90th percentile, suggesting larger estimated associations for disadvantaged groups. Mediation analysis suggests that healthcare utilization and health behavior are key potential pathways linking TCM service accessibility to health capital, with the total mediating effect accounting for 47.6% of the overall association. The findings suggest that TCM service accessibility is associated with higher health capital and a more equitable distribution of health capital among rural residents. These findings highlight the equity-enhancing potential of traditional medicine within pluralistic healthcare systems and provide important policy implications for addressing persistent health disparities in resource-constrained rural settings.
Alcohol consumption and depression frequently co-occur, but little is known about how alcohol and antidepressant medication interact along the gut-brain axis. We examined the independent and combined effects of chronic alcohol exposure and fluoxetine on gut microbiota, intestinal structure, peripheral endotoxin-related and inflammatory markers, and neuroinflammatory gene expression in male rats. Animals received alcohol for 14 days and fluoxetine for 7 days, resulting in four groups: control-vehicle, control-fluoxetine, alcohol-vehicle, and alcohol-fluoxetine. Fecal microbiota was analyzed using 16S rRNA sequencing, functional prediction, and culturable bacteria under antibiotic selection. Ileal morphology, extracellular matrix organization, plasma LPS and cytokines, and neuroinflammation-related gene expression in the amygdala and medial prefrontal cortex (mPFC) were also evaluated. Both alcohol and fluoxetine modified the gut microbiota, with their combination producing the most pronounced alterations, including the loss of several short-chain fatty acid-producing taxa. Fluoxetine alone increased alpha diversity and altered the abundance of genera linked to metabolic activity. Alcohol impaired intestinal integrity by reducing villus width, increasing goblet cell density, and decreasing collagen content. In animals with prior alcohol exposure, reduced plasma LPS and TNF-α levels were observed at the time of sample collection. Neuroimmune gene expression changes differed between the amygdala and mPFC, indicating region-specific central responses. Together, these findings reveal that fluoxetine treatment can modulate the gut-brain axis differently depending on prior alcohol exposure, supporting further investigation of microbiota-related mechanisms in alcohol use and psychiatric comorbidity.
Hyperactivity of the adductor pollicis muscle in upper motor neuron lesions can cause a thumb-in-palm deformity, which can be treated with botulinum toxin injection to reduce spasticity. This study aimed to identify reliable surface landmarks for localizing the motor entry point to administer botulinum toxin. A total of 21 formalin-fixed adult cadaveric hands were dissected. The anatomical landmarks of the hand, such as the styloid process of the radius, first metacarpophalangeal joint, and the longitudinal axis of the shaft of the third metacarpal, were used to create a grid divided into four zones. Morphometric measurements of the hand and adductor pollicis muscle, and distances from the anatomical landmarks to the motor entry point, were recorded using a digital caliper. In 13 hand specimens, the motor entry point was located between zones 1 and 2 along the longitudinal axis of the shaft of the third metacarpal; in 8 specimens, it was in zone 2, medial to the third metacarpal. The mean distances of the motor entry point from the first metacarpophalangeal joint, styloid process of the radius, midpoint of the two, and the third metacarpal were 13.74 ± 6.56mm, 48.51 ± 8.23mm, 17.59 ± 7.18mm, and 2.61 ± 3.63mm, respectively. Both the first metacarpophalangeal joint and the midpoint between it and the styloid process of the radius showed comparable proximity to the motor entry point. They remained consistent despite variations in the length of the hand and the muscle. These observations provide reference anatomical points that may help guide botulinum toxin injections, nerve blocks, and reconstructive procedures; however, their applicability to broader populations requires further validation.
To address the problem of strong mine pressure caused by ultra-thick overlying strata (UTOS), this paper analyzes the distribution law of mining stress field in different layers of UTOS, and the expression of mining stress concentration coefficient of UTOS is given. The law of hydraulic fracture propagation in stress concentration area and original stress area of stope roof is expounded. The stress-oriented fracturing mechanism of UTOS is revealed. The results show that: (1) Along the advacned direction, the stress concentration value in the UTOS increases first and then decreases, exhibiting a "core" distribution pattern. As the buried depth of the roof increases, the range of the stress concentration core gradually decreases; (2) When hydraulic fracturing is carried out in the stress concentration area and the original stress area respectively, vertical hydraulic fractures and horizontal hydraulic fractures will be formed in the roof respectively; (3) The fracture propagation pressure in the stress concentration area is significantly greater than that in the original stress area. After the stress-oriented fracturing of the UTOS, the support resistance of the working face is significantly reduced, which is beneficial to the mine pressure management of the working face.
The neocortex has a remarkable capacity to alter its functional organization and connectivity in response to sensory loss, particularly if this loss occurs early in life. A key question is whether this cross-modal reorganization is driven by sensory deprivation or by enhanced use of the spared senses. We investigated how different rearing environments shape neural responses in primary somatosensory cortex (S1) of short-tailed opossums (Monodelphis domestica), following elimination of visual inputs through bilateral enucleation in early development. Early blind and sighted littermates of either sex were reared in enriched environments to promote active tactile exploration in three-dimensional (3D) space, or in standard laboratory cages. In adulthood, both enriched groups showed adaptive changes in exploration patterns and gap crossing behaviors relative to standard-reared counterparts. Thus, early blind animals showed behavioral compensation when challenged by complex environments. Enriched rearing increased selectivity of S1 neural responses to whisker touch and altered receptive field shapes such that they were less horizontally anisotropic. This shift was strongest in enriched early blind animals, enhancing tuning along the behaviorally relevant horizontal axis more than in standard-reared early blind animals. Thus, alterations in receptive fields of neurons in S1 following early blindness were amplified by environmental complexity. Sighted opossums reared with enrichment also showed similar whisker receptive field plasticity, though to a slightly lower degree. These results demonstrate that the rearing environment strongly influences the reorganization of cortex that processes inputs from the spared senses, underscoring the role of experience in directing compensatory plasticity following early sensory loss.Significance statement Enhanced perceptual abilities following early sensory loss are often attributed to cross-modal recruitment of cortex linked to the deprived sense. However, plasticity also occurs in cortical areas representing spared modalities. It remains unresolved whether deprivation alone is sufficient to induce such reorganization, or whether experience using the spared sense is required. We show that enriched rearing amplifies neural coding changes in primary somatosensory cortex after early blindness, shaping receptive field geometry and promoting adaptive behavioral strategies aligned with environmental demands. Comparable changes in sighted animals reared under the same conditions reveal that reliance on touch-rather than visual deprivation alone-drives this neural and behavioral plasticity, supporting the critical role of experience in enhancing functional outcomes after early sensory impairment.
Mangrove ecosystems, renowned as coastal protectors, also serve as major sinks of plastic debris. The study assessed size-partitioned plastic pollution in water, sediment, and two edible mollusc species, Telescopium telescopium and Crassostrea madrasensis, from the Ayiramthengu Mangrove Forest (AMF), an ecologically significant environmental hotspot along the southwest coast of India. The distinct habitats, contrasting feeding strategies, and prominence of these edible molluscs in local diets highlight their ecological and dietary significance, making them suitable sentinel species for cross-matrix microplastic (MP) assessment. MP contamination assessed following the NOAA protocols in AMF revealed a high abundance of macro-, meso-, and microplastics in the sediments of Site 1. All analyses were performed using procedural blanks and rigorous contamination controls. The evident spatial variations observed in MP distribution resulted from differences in anthropogenic activities and hydrodynamic transport. Polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), and polystyrene (PS) were the major MP contaminants. The pronounced spatial variation in MP distribution, as reflected by the particle abundance, indicated that mangrove sediments act as the primary reservoir, retaining more particles than the surrounding water, thereby enhancing their bioavailability to molluscs and dietary exposure. However, direct implications of MP on human health were not evaluated in this study. The high Polymer Hazard Index and Pollution Load Index of each site indicate the intensity of MP pollution in AMF. Overall, the results of the study provide season-specific patterns and baseline information for future monitoring and management of plastic pollution, prioritizing targeted debris removal and restoration along with implementation of proper dietary guidelines.
Migraine is a highly disabling disorder with a high prevalence, significantly impairing quality of life. Emerging evidence suggests that circulating endogenous peptides play critical roles in neurovascular regulation and nociceptive signaling. However, the contribution of blood-derived endogenous peptides to the activation of meningeal afferents and the pathophysiology of migraine remains poorly understood. Therefore, investigating the role of these peptides in the meninges is crucial for elucidating the mechanisms underlying migraine. To elucidate the role of endogenous peptides in activating meningeal afferents during migraine, we established a chronic migraine mouse model using nitroglycerin (NTG). Serum peptidomic analysis was performed to identify differentially expressed peptides between the Negative Group (NEG) and NTG group. Functional enrichment analysis revealed significant upregulation of pathways associated with prolactin signaling and hypoxia-inducible factor-1 (HIF-1) signaling. Subsequently, peptidomic profiling of the meninges was conducted in both groups. Integration of meningeal and serum peptidomic datasets, together with a curated set of endogenous secreted proteins, enabled cross-comparative analysis to identify circulating peptides with potential effects on the meninges. This analysis revealed a marked increase in both pituitary adenylate cyclase-activating polypeptide (PACAP) and calcitonin gene-related peptide (CGRP), two key mediators critically implicated in migraine pathophysiology.In addition, several PACAP-related short peptide fragments were identified, some of which exhibited sequence homology to known bioactive domains. Collectively, these findings suggest that PACAP and CGRP, along with their derived peptide fragments, may contribute to the activation of meningeal nociceptive fibers and thereby participate in the initiation and maintenance of migraine. Peptidomics sequencing of the TNC region was performed, and functional enrichment analysis of the differentially expressed proteins indicated the dysregulation of diverse biological pathways. These findings reveal that CGRP and PACAP may play a key role in the activation of meningeal afferents in a chronic migraine mouse model. Several protein modification sites are thought to be crucial mechanisms in endogenous peptides-mediated meningeal activation.
Well-characterized cohorts are essential for advancing neuroimaging biomarkers and refining models of brain aging and dementia across diverse populations. Despite growing neuroimaging research in Latin America, additional multimodal cohorts integrating imaging, genomic, and environmental data are needed to capture population diversity. We present GeNED.ar (Genetics and Neuroimaging of Aging and Dementia in Argentina), a multimodal cohort established in the Metropolitan Area of Buenos Aires to investigate brain aging in a population with genetic admixture and socioeconomic heterogeneity. The dataset combines two complementary recruitment strategies, community-based healthy participants and Memory Clinic attendees, including 3T MRI, genome-wide genotyping, and detailed sociodemographic data from 367 individuals aged 18-94 years. Participants comprise healthy individuals (n=235) and Memory Clinic attendees classified as cognitively unimpaired (n=65), mild cognitive impairment (n=37), Alzheimer's or mixed dementia (n=24), and vascular dementia (n=6). Genetic ancestry analysis (n=191) indicated a predominantly admixed population (65% European, 28.3% Native American) with significant differences across recruitment sources. Brain age gap (BAG), estimated from T1-weighted MRI, increased progressively along the clinical continuum, where people with dementia exhibited older-appearing brains relative to cognitively unimpaired participants, and intermediate values were observed in mild cognitive impairment. No independent associations were observed between BAG and individual genetic or environmental risk factors. By integrating multimodal MRI and genomic data across complementary recruitment settings, GeNED.ar provides a unique regional resource to evaluate neuroimaging biomarkers, facilitate cross-cohort validation, and strengthen the generalizability of aging and dementia models in genetically and socially diverse populations.
Physical activity among adults with disabilities is influenced by functional limitations, health status, and socioeconomic conditions; yet, the relative predictive importance of these factors remains insufficiently understood. This study compared multiple machine learning approaches for predicting exercise participation and used explainable artificial intelligence to identify the most influential predictors. Using the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System data, we modeled self-reported exercise participation from 5 disability indicators-blindness, deafness, cognitive disability, self-care disability, and mobility disability, along with demographic, socioeconomic, behavioral, psychosocial, and self-rated health factors. Five machine learning models were compared: logistic regression, LASSO, support vector machine, random forest, and XGBoost. Performance was evaluated with AUC, accuracy, F1 score, sensitivity, specificity, and Cohen kappa. Exercise participation was also summarized across disability types by income and education. Model explainability for the best performing model was assessed using SHAP plots. XGBoost demonstrated the strongest overall performance (AUC = 0.83, accuracy = 0.79, F1 = 0.78, sensitivity = 0.77, specificity = 0.80, κ = .54), followed by random forest (AUC = 0.80). Exercise participation showed a pronounced socioeconomic gradient within disability groups. Among respondents with cognitive disability, exercise participation declined from 75.2% in the high-income group to 40.7% in the low-income group, while among those with mobility disability, it declined from 51.7% to 29.9%. SHAP analyses identified mobility status, education attainment, income, physical health, and age as the top 5 contributors to exercise participation. Explainable machine learning may improve identification of individuals at elevated risk of inactivity and highlights the combined importance of disability type and socioeconomic context in shaping exercise participation.