Browse Articles

Action-guilt, survivor-guilt, and depression in combat-related PTSD

Identifying the role of guilt in post-traumatic stress disorder (PTSD) has important implications for understanding the development and treatment of PTSD. The present study is a secondary analysis of data collected on veterans with combat-related PTSD (N = 61) who enrolled in a clinical trial. Hierarchical regression analyses were used to explore associations between action- and survivor-guilt on the Clinician Administered PTSD Scale (CAPS), PTSD symptom severity on the CAPS, and depression on the Quick Inventory of Depressive Symptomatology (QIDS). Action- and survivor-guilt independently predicted PTSD total symptom severity, but in examining PTSD symptom cluster severity, only action-guilt independently predicted avoidance and numbing severity in PTSD. However, depression symptom severity on QIDS also mediated the association between action-guilt and PTSD total symptom severity and avoidance and numbing severity. Thus, action- and survivor-guilt appear to have independent contributions to PTSD symptom severity, and action-guilt, more specifically, appears to affect avoidance and numbing severity in PTSD through depression. The findings are discussed in terms of the potential role of guilt in PTSD and in relation to previous research on guilt and depression in PTSD and PTSD treatment.

Neural CDE-GAT framework for spatio-temporal air pollution prediction

De novo design of quasisymmetric two-component protein cages

Siderophore production by the lichen fungus Xanthoria parietina supports its algal symbiont

Abstract Lichens are symbiotic associations between a fungal mycobiont and a photosynthetic photobiont. They thrive in nutrient-poor environments; yet the mechanisms underlying their adaptation to iron limitation remained largely unknown. Here, we characterize the iron acquisition system of Xanthoria parietina , a globally distributed lichen-forming fungus associated with the microalgal photobiont Trebouxia decolorans . We demonstrate that the mycobiont produces the siderophore ferrichrome and possesses the full genetic repertoire not only for siderophore biosynthesis, but also reductive iron assimilation, iron detoxification, and regulation. The ferrichrome-synthesizing non-ribosomal peptides synthetase exhibits a lichen-specific compact architecture but retains functionality when heterologously expressed in a non-lichenized ascomycete. Transcriptomic analysis and ferrichrome quantification reveal substrate-dependent regulation of the siderophore system. Importantly, ferrichrome promotes photobiont growth independent of extracellular iron reduction, indicating direct utilization. These findings provide the functional evidence of siderophore-mediated iron acquisition in a lichen symbiosis and highlight ferrichrome as a key mediator of mutualistic nutrient exchange.

Biogenic Silver–Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus

The rapid emergence of multi-drug resistant (MDR) pathogenic bacteria as well as the continued burden of malignant diseases requires the safe development of novel and multifunctional therapeutic agents. The WHO designated vancomycin-resistant Staphylococcus aureus (VRSA) as “high priority” AMR pathogen. Thus, this study aimed to ecofriendly synthesis of silver–selenium nanocomposite (Ag–Se NC) and evaluate its in vitro anticancer effect and inhibitory activity against VRSA clinical isolates. Biogenic Ag–Se NC was successfully synthesized using the aqueous peel extract of Cucumis melo ( C. melo ) through an eco-friendly green synthesis approach. Following visual color transformation of the preparation mixture, nanocomposite formation was validated based on comprehensive physicochemical characterization using different spectroscopic analyses. The greenly synthesized Ag–Se NC revealed the Ag and Se specific surface plasmon resonance (SPR) peaks, high crystallinity, and predominantly spherical morphology with an average particle size of ~35 nm. Biological evaluations revealed that Ag–Se NC possesses selective cytotoxicity, displaying low toxicity toward WI-38 normal lung fibroblasts (IC₅₀ = 203.4 µg/mL) while exerting a potent, concentration-reliant inhibitory effect towards malignant cell lines, including hepatocellular carcinoma (Hep-G2) and breast adenocarcinoma (MCF-7) with IC50 90.97 and 38.18 μg/mL respectively. Furthermore, the Ag–Se NC demonstrated appreciated antibacterial activity, in comparison with the linezolid standard antimicrobial agent, against 11 VRSA clinical isolates, with MIC values ranging from 64 to 512 µg/mL and a mean MIC of 203.64 µg/mL. The marked NC bactericidal effects were indicated by their minimum inhibitory concentration index (MICi) values of 1–4, rapid time-kill kinetics, and significant membrane disruption evidenced by the protein leakage assay. The obtained NC also exhibited a respected inhibitory effect against VRSA biofilm development, in the range of 34.68 ± 2.4–72.89 ± 1.87%, as well as a strain-dependent partial eradication effect on the fully formed bacterial biofilm, ranging from 16.81 ± 0.96 to 42.59 ± 0.78%. Notably, variable interactions were observed when Ag–Se NC was combined with vancomycin against VRSA isolates; one isolate showed synergistic interaction with fractional inhibitory concentration index (FICi) = 0.5 and three isolates exhibited additive effects (FICi ranged from 0.5 to 1). In conclusion, these findings highlight Ag–Se NC as a promising green-synthesized nanoplatform with combined anticancer and bacterial inhibitory effects in both planktonic and biofilm growth forms and antimicrobial–potentiating activities.

Adaptive learning rate methodologies and clipping mechanisms based upon gradient entropy

Abstract Serving as a pivotal parameter during deep learning training processes, learning rate plays a crucial role regarding training efficiency. Traditional optimizers confront challenges such as sluggish convergence and unstable precision; particularly across large-scale datasets, solitary adaptive mechanisms easily lead to premature learning rate decay and training instability, thereby undermining model generalization capabilities. Present research proposes an optimizer enhancement method based upon entropy-modulated mechanisms and multi-strategy integration, improving adaptive capacity of learning rate regulation across diverse training phases through introduction of entropy-aware learning rate scheduling mechanisms while effectively bolstering optimizer responsiveness toward training dynamics and structural complexity. Constructing entropy-modulated optimizers incorporates dual factors of gradient perturbation rate and information entropy to achieve real-time response toward training dynamics, while multi-scale entropy-aware clipping mechanisms are designed to alleviate gradient explosion and structural instability within deep networks. Validated through experiments across multiple public datasets, results demonstrate that present method effectively enhances model robustness and convergence stability.

Improvement of the tensile strength of carbon nanotube fibers to 12.5 GPa by fluidics-induced alignment and densification

Key molecular mechanisms of mitochondrial metabolic pathways in specific cell subpopulations of pancreatic cancer based on scRNA-seq and bulk RNA-seq

Background Pancreatic cancer (PC) is a highly malignant tumor with increasing incidence, mortality, and a low five-year survival rate. Mitochondrial metabolic reprogramming plays a crucial role in tumor development, but the molecular mechanisms in different cell subpopulations of PC remain unclear. This study aims to integrate single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq to explore mitochondrial metabolism in PC. Methods Transcriptome datasets (GSE183795, GSE16515, GSE197177, and TCGA-PAAD) were downloaded from the GEO and TCGA databases. Differentially expressed genes (DEGs) were identified using the limma package for bulk RNA-seq and the Seurat package for scRNA-seq. Weighted gene co-expression network analysis (WGCNA) was performed to identify key modules and hub genes. Machine learning algorithms screened key genes, and functional enrichment analysis was conducted using clusterProfiler. PPI, ceRNA, and transcription factor networks explored gene regulation. Immune infiltration analysis, drug prediction, and molecular docking were conducted on key genes. The prognostic value of the key genes was evaluated using clinical data from TCGA. Results A total of 1238 bulk RNA-DEGs and 8231 scRNA-DEGs in fibroblasts were identified. Integration of both datasets revealed 536 DEGs. WGCNA identified 6 modules associated with PC. By intersecting DEGs, hub genes, and mitochondrial metabolism-related genes, 18 candidate genes were obtained. These genes were enriched in glucose metabolism and mitochondrial outer membrane pathways. Three key genes (IFI27, PKM, and RSAD2) were selected using machine learning. PPI, ceRNA, and transcription factor networks provided regulatory insights. Immune infiltration analysis showed significant differences in immune cells, particularly in T cells CD4 memory resting and macrophages M2. Drug prediction and molecular docking identified potential drugs for these genes. Survival analysis indicated that high expression of these genes correlated with poor prognosis. Conclusion This study integrates scRNA-seq and bulk RNA-seq data to identify three key genes (IFI27, PKM, and RSAD2) and their immune-related mechanisms in PC. These findings offer new insights into the pathogenesis and potential therapeutic targets for PC.

Correction: Sphingosine-1-phosphate receptor 1/5 selective agonist alleviates ocular vascular pathologies

Near-unity charge readout signal in a nonlinear resonator without matching the sensor dissipation

Abstract Dissipative sensors typically use linear resonators with impedance matching to achieve maximal signal and fast operation. The impedance matching, however, sets an upper limit to the bandwidth of the readout. In this paper, we present a nonlinear resonator performing the readout of a double quantum dot charge state via a charge-sensing quantum dot. We show that by driving the resonator in the nonlinear regime, we achieve a near-unity signal for a dissipative sensor. This despite not satisfying the sensor impedance matching requirements necessary for such large signals in the linear regime. Our experiments, supported by numerical calculations, demonstrate that the signal increase stems from the sensor dissipation shifting the onset of the nonlinear resonator response. By lifting the matching requirement, we open up an avenue to ultra-fast charge detectors as the resonator input-output coupling - setting the detector bandwidth - does not have to match to the typically much slower sensor dissipation rate.

Muscle strength characteristics and the predictive value of handgrip strength in young obese males: A multi‑joint isokinetic and LASSO regression analysis

Obesity is a primary global public health concern, often associated with impaired muscle function and an increased risk of exercise-related injuries. This cross-sectional study aimed to elucidate the associations among muscular strength, body load, and functional capacity in young adults with obesity. A total of 75 male university students were recruited, including a normal-weight group (n = 47, BMI 18.5–24.99) and an obese group (n = 28, BMI ≥ 30). Assessments included handgrip strength, one-repetition maximum (1RM) for squat, deadlift, and bench press, as well as isokinetic strength evaluations across four major joints (shoulder, elbow, hip, and knee), yielding 32 strength-related variables. After normalizing all strength measures to body weight, the obese group demonstrated significantly lower relative strength across all parameters compared to the normal-weight group ( P  < 0.001), indicating a distinct “strength-to-load imbalance.” To identify key predictors of handgrip strength while addressing potential overfitting, we employed least absolute shrinkage and selection operator (LASSO) regression with cross-validation. The final model retained five predictors: elbow flexion maximum work at 180°/s (EF180°Wmax), elbow flexion peak torque at 180°/s (EF180°Fmax), elbow extension peak torque at 60°/s (EE60°Fmax), shoulder flexion peak torque at 60°/s (SF60°Fmax), and group (obese vs. normal), together explaining 63.3% of the variance in handgrip strength (adjusted R² = 0.606), although this finding should be interpreted with caution due to the sample size and requires validation in larger cohorts. Notably, group membership remained a significant independent predictor (β = −0.23, P = 0.014), underscoring the persistent deficit in relative strength associated with obesity even after accounting for joint-specific strength. By incorporating a multidimensional assessment of strength across multiple joints, this study moves beyond the limitations of single-joint evaluations and offers theoretical support for the potential use of handgrip strength as a practical indicator of overall muscle function in obese populations. Further research with larger samples and longitudinal designs is needed to validate its utility as a screening tool. These findings have important implications for designing function-oriented, precision-based exercise interventions for obese populations.

Design and synthesis of a novel polyoxovanadate–zeolite nanocomposite membrane for efficient desalination and heavy metal removal via forward osmosis

The Bipartisan infrastructure law’s impact on drinking water funding for disadvantaged communities

Siphonophore genome structure and the evolution of functional specialization

Siphonophores (Cnidaria: Hydrozoa) are pelagic colonial marine invertebrates with many highly specialized bodies (zooids) within a single colony. Their unique biology and ecological importance have made them of particular interest, and motivate questions on their genomic structure, organization and content. To investigate siphonophores’ genome biology and develop resources for future studies, we sequenced the genome of a single Nanomia septata to chromosome scale. The haploid genome is 1.7 GB across 8 chromosomes. Relative to closely related hydrozoan genomes, this is an expansion in length but a reduction, from 15, in chromosome number, indicating multiple chromosomal fusion events. We found no genomic features clearly associated with siphonophores’ exceptional colony-level complexity. Gene families that play critical roles in cnidarian development have not expanded, and gene proximity was not generally correlated to their expression across zooids, except in male gonophores. To contextualize these observations, we sequenced 20 additional Nanomia specimens across the globe and mapped them to our chromosome-scale reference. Population genomic analyses support three previously recognized species of Nanomia , and at least one additional undescribed species. Present day overlapping geographic distribution of some Nanomia species raises the possibility of reproductive isolation in sympatry. Phylogenetic analyses of genome size indicate Nanomia septata and Nanomia cara have similarly large genomes around 1.7 GB, while Nanomia bijuga and an undescribed species show a secondary reduction to 0.7 GB. These results highlight how genomic factors have shaped colony organization and genome diversity within Nanomia.

Geospatial and Statistical Analysis of Natural Radionuclides in the Soil of Kirkuk Province, Iraq

Comparative analysis of Cdc48-dependent proteolysis at the ER, mitochondria and chloroplasts

Abstract The ubiquitin-proteasome system (UPS) is the preeminent proteolytic system in eukaryotes. While soluble nucleocytosolic proteins are readily accessed by the UPS, organelle-localised proteins present major, membrane-related accessibility challenges. Cells overcome this problem by employing the conserved AAA+ ATPase Cdc48 to extract organellar proteins to the cytosol, thereby enabling proteasomal degradation. Major Cdc48-dependent proteolytic systems exist at the endoplasmic reticulum, mitochondria and chloroplasts, and are uniquely adapted to deliver protein homeostasis within the respective organelles. We provide a focused comparison of these systems, analysing similarities and differences between them. Better understanding of underlying principles has important implications spanning human health and agriculture.

Delayed health-seeking behavior and its associated factors among cancer patients in Ethiopia: A systematic review and meta-analysis, 2025

Background Delayed Health-seeking behavior among cancer patients is a major contributor to late diagnosis, poor prognosis, and high mortality, particularly in low-resource settings like Ethiopia. However, evidence on the magnitude and determinants of delayed care-seeking remains fragmented. Objective This systematic review and meta-analysis aimed to estimate the pooled prevalence of delayed Health-seeking behavior among cancer patients in Ethiopia and to identify associated factors influencing delays. Methods This study employed a systematic review and meta-analysis design to assess delayed Health-seeking behavior and its influencing factors among cancer patients in Ethiopia. A systematic search was conducted in PubMed, Scopus, Web of Science, CINAHL, AJOL, Google Scholar, and Ethiopian University repositories until April 27, 2025. The data were extracted from March 10–20 and analyzed from March 21–30, with report generation till April 27, 2025, using R software. Meta-analysis was performed using a random-effects model, with forest plots illustrating pooled prevalence and associated factors. Heterogeneity was assessed using the I² statistic, and study quality was evaluated using a validated tool. Results Seven studies conducted across multiple regions of Ethiopia were included in the final analysis with a total of 2,641 participants. The pooled prevalence of delayed Health-seeking behavior among cancer patients was 54% (95% CI: 39%–68%). Meta-analysis of associated factors showed that rural residence was significantly associated with delayed Health-seeking behavior, with patients residing in rural areas having more than threefold higher odds of delay (AOR = 3; 95% CI: 1.81–4.19), poor knowledge about cancer was strongly associated with delay, with nearly seven times higher odds among patients with poor knowledge compared to those with adequate knowledge (AOR = 6.63; 95% CI: 2.21–11.05), lack of cancer awareness was also a significant predictor of delayed Health-seeking behavior (AOR = 2.63; 95% CI: 1.75–3.51), and patients without pain were over three times more likely to delay Healthcare(AOR = 3.38; 95% CI: 2.44–4.67) were factors associated with delayed Health-seeking behavior. Conclusions Our review showed that half of the cancer patients in Ethiopia experienced delayed health-seeking behavior. Delayed care-seeking was associated with rural residence, poor knowledge, limited awareness of cancer, and absence of pain symptoms. Targeted interventions, including public awareness campaigns, expansion of healthcare services in rural areas, and financial support initiatives, are urgently needed to reduce delays and improve early cancer diagnosis and outcomes. Prospero Registration Number CRD420251037845

Clinical and physiological outcomes of peroral endoscopic myotomy in Thailand, with a comparative review of Southeast Asian cohorts

A low-temperature, water-free fabrication route to Mg-based micro thermoelectric coolers for thermal management

Emotional understanding in Japanese children 3–6 years: Language ability mediates the relations between theory of mind and executive function

Previous research has documented associations between children’s emotional understanding (EU) and social-cognitive abilities such as theory of mind (ToM) and executive function (EF); however, findings in preschool-aged children remain inconsistent. One potential explanation is that language ability, which develops rapidly during early childhood, has often not been examined concurrently with these abilities. The present study focused on individual differences in EU and examined how ToM, EF, and language ability relate to EU in Japanese preschool children, with particular attention to the mediating role of language. Participants were 90 children aged 3–6 years (M = 60.34 months, SD = 10.82). Children completed a false belief task, emotional understanding tasks, executive function tasks assessing cognitive flexibility and working memory, and a receptive vocabulary test. Correlational analyses, hierarchical multiple regression analyses, and bootstrapped mediation analyses were conducted. EU was positively associated with ToM, EF, and language ability. Language ability accounted for significant variance in EU beyond age and gender. When language ability was included in the model, the association between ToM and EU was no longer significant, whereas the association between EF and EU remained significant but was attenuated. Mediation analyses revealed significant indirect effects of both ToM and EF on EU through language ability, indicating that the association between ToM and EU was accounted for by language ability, whereas EF showed both direct and indirect associations with EU. These findings suggest that language ability plays a central role in linking social-cognitive abilities to emotional understanding in early childhood. Theory of mind was associated with emotional understanding primarily through language, whereas executive function showed both direct and indirect associations via language ability. By modeling multiple predictors simultaneously, this study provides an integrated account of individual differences in emotional understanding and elucidates the distinct pathways through which cognitive and social-cognitive skills are associated with emotional development.