Search Results (575)

Black gay and bisexual older men face numerous barriers across the life course that can contribute to negative health and well-being as they age. Drawing on strengths-based social determinants discussed in the health literature and literature on intersectionality, justice, and critical consciousness, this study examines qualitative data from seventeen Black gay and bisexual older men about sources and strategies of resilience and thriving amidst intersecting systems of power and oppression that shape health inequities. The findings revealed an evolution of positive support networks across their life courses, including biological family and families of choice such as “houses” and support groups. Early and ongoing negative experiences relating to intersecting positionalities (e.g., race, gender, sexual orientation) also provided sources of strength and resilience. Participants identified three strategies for building resilience and thriving: naming external ignorance, acknowledging common struggles, and reconciling contradictions. These strategies reflected various levels of critical consciousness that helped them navigate complex and intersecting systems of power that they encountered as Black gay men across the life course. Overall, the findings underscore the importance of considering intersecting systems of power and critical consciousness when examining resilience and social determinants of health and contribute new insights on a vastly understudied population. Full article

Background: The candidate therapeutic peptide TnP demonstrates broad, system-level regulatory capacity, revealed through integrated network analysis from transcriptomic data in zebrafish. Our study primarily identifies TnP as a multifaceted modulator of drug metabolism, wound healing, proteolytic activity, and pigmentation pathways. Results: Transcriptomic profiling of TnP-treated larvae following tail fin amputation revealed 558 differentially expressed genes (DEGs), categorized into four functional networks: (1) drug-metabolizing enzymes (cyp3a65, cyp1a) and transporters (SLC/ABC families), where TnP alters xenobiotic processing through Phase I/II modulation; (2) cellular trafficking and immune regulation, with upregulated myosin genes (myhb/mylz3) enhancing wound repair and tlr5-cdc42 signaling fine-tuning inflammation; (3) proteolytic cascades (c6ast4, prss1) coupled to autophagy (ulk1a, atg2a) and metabolic rewiring (g6pca.1-tg axis); and (4) melanogenesis-circadian networks (pmela/dct-fbxl3l) linked to ubiquitin-mediated protein turnover. Key findings highlight TnP’s unique coordination of rapid (protease activation) and sustained (metabolic adaptation) responses, enabled by short network path lengths (1.6–2.1 edges). Hub genes, such as nr1i2 (pxr), ppara, and bcl6aa/b, mediate crosstalk between these systems, while potential risks—including muscle hypercontractility (myhb overexpression) or cardiovascular effects (ace2-ppp3ccb)—underscore the need for targeted delivery. The zebrafish model validated TnP-conserved mechanisms with human relevance, particularly in drug metabolism and tissue repair. TnP’s ability to synchronize extracellular matrix remodeling, immune resolution, and metabolic homeostasis supports its development for the treatment of fibrosis, metabolic disorders, and inflammatory conditions. Conclusions: Future work should focus on optimizing tissue-specific delivery and assessing genetic variability to advance clinical translation. This system-level analysis positions TnP as a model example for next-generation multi-pathway therapeutics. Full article

Person-centered navigation (PCN) in healthcare refers to a proactive collaboration among professionals, researchers, patients, and their families to guide individuals toward timely access to screening, treatment, follow-up, and psychosocial support. PCN—which includes professional, peer, and virtual guidance, is particularly crucial for rare cancers, where affected individuals face uncertainty, limited support, financial strain, and difficulties accessing relevant information, testing, and other services. The Canadian Cholangiocarcinoma Collaborative (C3) prioritizes PCN implementation to address these challenges in the context of Biliary Tract Cancers (BTCs). C3 uses a virtual PCN model and staffs a “C3 Research Navigator” who provides clinical and research navigation such as personalized guidance and support, facilitating access to molecular testing, clinical trials, and case reviews through national multidisciplinary rounds. C3 also supports a national network of BTC experts, a patient research registry, and advocacy activities. C3’s implementation strategies include co-design, timely delivery of support, and optimal outcomes across its many initiatives. Future priorities include expanding the C3 network, enhancing user engagement, and further integrating its innovative approach into routine care. Full article

This paper examines the farming systems and operational structures in the Region of Western Macedonia (RWM), Greece and constructs a typology of farms based on structural, operational, and socio-economic characteristics. Agriculture remains a vital pillar of the regional economy, particularly in the context of RWM’s ongoing transition to a post-lignite development model. Using farm-level data from the 2018 Farm Accountancy Data Network (FADN), Principal Component Analysis (PCA) identified four latent dimensions of farm heterogeneity—income and productivity, asset base, land size, and labour structure. Hierarchical and K-means cluster analysis revealed three distinct farm types: (1) medium-sized, high-efficiency farms with moderate reliance on subsidies (30% of the sample); (2) small-scale, family farms with modest productivity and limited capitalisation (48%); and (3) large, asset-rich farms exhibiting structural inefficiencies and lower output per hectare (22%). These findings highlight structural vulnerabilities, particularly the predominance of undercapitalised smallholdings, and provide a data-driven foundation for Thdesigning differentiated policies that support farm resilience, generational renewal, and sustainable rural development. Full article

Background and objectives: Adducins are cytoskeletal proteins essential for membrane stability, actin–spectrin network organization, and cell signaling. Mutations in the genes ADD1, ADD2, and ADD3 have been linked to hypertension, neurodevelopmental disorders, and cancer. However, no comprehensive in silico saturation mutagenesis study has systematically evaluated the pathogenic potential and structural consequences of all possible missense mutations in adducins. This study aimed to identify high-risk variants and their potential impact on protein stability and function. Methods: We performed computational saturation mutagenesis for all possible single amino acid substitutions across the adducin proteins family. Pathogenicity predictions were conducted using four independent tools: AlphaMissense, Rhapsody, PolyPhen-2, and PMut. Predictions were validated against UniProt-annotated pathogenic variants. Predictive performance was assessed using Cohen’s Kappa, sensitivity, and precision. Mutations with a prediction probability ≥ 0.8 were further analyzed for structural stability using mCSM, DynaMut2, MutPred2, and Missense3D, with particular focus on functionally relevant domains such as phosphorylation and calmodulin-binding sites. Results: PMut identified the highest number of pathogenic mutations, while PolyPhen-2 yielded more conservative predictions. Several high-risk mutations clustered in known regulatory and binding regions. Substitutions involving glycine were consistently among the most destabilizing due to increased backbone flexibility. Validated variants showed strong agreement across multiple tools, supporting the robustness of the analysis. Conclusions: This study highlights the utility of multi-tool bioinformatic strategies for comprehensive mutation profiling. The results provide a prioritized list of high-impact adducin variants for future experimental validation and offer insights into potential therapeutic targets for disorders involving ADD1, ADD2, and ADD3 mutations. Full article

Background/Objectives: Moso bamboo (Phyllostachys edulis), the most widely distributed bamboo species in China, is valued for both its shoots and timber. This species often faces challenges from high-temperature stress. To cope with this stress, Moso bamboo has evolved various adaptive mechanisms at the physiological and molecular levels. Although numerous studies have revealed that a large number of transcription factors (TFs) and genes play important roles in the regulatory network of plant heat stress responses, the regulatory network involved in heat responses remains incompletely understood. Methods: In this study, Moso bamboo was placed in a high-temperature environment of 42 °C for 1 h and 24 h, and transcriptome sequencing was carried out to accurately identify key molecules affected by high temperature and their related biological pathways. Results: Through a differential expression analysis, we successfully identified a series of key candidate genes and transcription factors involved in heat stress responses, including members of the ethylene response factor, HSF, WRKY, MYB, and bHLH families. Notably, in addition to traditional heat shock proteins/factors, multiple genes related to lipid metabolism, antioxidant enzymes, dehydration responses, and hormone signal transduction were found to play significant roles in heat stress responses. To further verify the changes in the expression of these genes, we used qRT-PCR technology for detection, and the results strongly supported their key roles in cellular physiological processes and heat stress responses. Conclusions: This study not only deepens our understanding of plant strategies for coping with and defending against extreme abiotic stresses but also provides valuable insights for future research on heat tolerance in Moso bamboo and other plants. Full article

This study investigates how demographic characteristics, severity of intimate partner violence (IPV), social support, gender equality awareness, and demographic factors (e.g., living with children at home) influence help-seeking behaviors among 2527 IPV-experienced women in Beijing, Shanghai, Guangzhou, and Shenzhen. Drawing on the help-seeking model and conservation of resource theory, the study distinguishes between formal (e.g., police, legal aid) and informal (e.g., family, friends) help-seeking. Logistic regression results reveal that greater violence severity, stronger perceived social support, and higher gender equality awareness significantly increase both formal and informal help-seeking. Notably, living with children is associated with a higher likelihood of seeking formal help, possibly due to increased concerns for children’s safety and the desire to change the abusive environment. While help-seeking behavior is on the rise overall, particularly among women with strong support networks and progressive gender attitudes, structural and cultural barriers remain. The findings underscore the need to improve public education, reduce stigma, and enhance accessibility of support systems. This study contributes to the growing literature on IPV in China and provides evidence for refining policy interventions and service delivery. Full article

Background/Objectives: Family self-care (FSC) is increasingly recognized as a vital aspect of caregiving in pediatric chronic conditions. However, its development in families of children with intellectual disabilities (IDs) remains underexplored. This study aimed to examine how families construct and sustain FSC, and to identify factors that shape its development across four domains: physical, cognitive, psychosocial, and behavioral. Methods: A qualitative study was conducted using an abductive approach, combining inductive thematic analysis with a deductively applied theoretical framework. Semi-structured interviews were carried out with nine families of children with ID in southern Portugal. The children ranged in age from 4 to 15 years, and the parents were aged between 29 and 53 years. The data was analyzed using Bardin’s content analysis, supported by NVivo software, and organized according to the FSC framework. This study followed COREQ guidelines. Results: The families described a range of self-care strategies, including environmental adaptations, experiential learning, emotional regulation, and long-term planning. These practices were shaped by contextual factors such as access to healthcare, relationships with professionals, emotional support networks, and socioeconomic conditions. Four emergent conclusions illustrate how structural and relational dynamics influence FSC in daily caregiving. Conclusions: FSC is a dynamic, multidimensional process shaped by lived experience, family interactions, and systemic support. The findings support inclusive, family-centered care models and inform clinical practice, training, and policy in pediatric IDs. Full article

Lycopene exhibits a broad spectrum of biological activities with potential therapeutic applications. Despite its established antioxidant and anti-inflammatory properties, the molecular basis for its pharmacological actions remains incompletely defined. Here we investigated the molecular targets, pharmacodynamic feasibility, and tissue-specific expression of lycopene targets using a computational pharmacology approach combined with affinity and protein–protein interaction (PPI) analyses. Lycopene-associated human protein targets were predicted using a Swiss target screening platform. Molecular docking was used to estimate binding affinities, and concentration-affinity (CA) ratios were calculated based on physiologically relevant plasma concentrations (75–210 nM). PPI networks of lycopene targets were constructed to identify highly connected targets, and tissue expression analysis was assessed for high-affinity targets using protein-level data from the Human Protein Atlas database. Of the 94 predicted targets, 37% were nuclear receptors and 18% were Family A G Protein Coupled Receptors (GPCRs). Among the top 15 high-affinity targets, nuclear receptors and GPCRs comprised 40% and 26.7%, respectively. Twenty targets had affinities < 10 μM, with six key targets (MAP2K2, SCN2A, SLC6A5, SCN3A, TOP2A, and TRIM24) showing submicromolar binding. CA ratio analysis identified MAP2K2, SCN2A, and SLC6A5 as pharmacodynamically feasible targets (CA > 1). PPI analysis revealed 32 targets with high interaction and 9 with significant network connectivity. Seven targets (TRIM24, GRIN1, NTRK1, FGFR1, NTRK3, CHRNB4, and PIK3CD) showed both high affinity and centrality in the interaction network. The expression profiling of submicromolar targets revealed widespread tissue distribution for MAP2K2 and SCN3A, while SCN2A, TOP2A, and TRIM24 showed more restricted expression patterns. This integrative analysis identifies a subset of lycopene targets with both high affinity and pharmacological feasibility, particularly MAP2K2, SCN2A, and TRIM24. Lycopene appears to exert its biological effects through modulation of interconnected signalling networks involving nuclear receptors, GPCRs, and ion channels. These findings support the potential of lycopene as a multi-target therapeutic agent and provide a rationale for future experimental and clinical validation. Full article

Background/Objectives: Cardiac aging involves the progressive structural and functional decline of the myocardium. Endurance training is a well-recognized non-pharmacological intervention that counteracts this decline, yet the molecular mechanisms driving exercise-induced cardiac rejuvenation remain inadequately elucidated. This study aimed to identify key effector genes and regulatory pathways by integrating human cardiac aging transcriptomic data with multi-omic exercise response datasets. Methods: A systems biology framework was developed to integrate age-downregulated genes (n = 243) from the GTEx human heart dataset and endurance-exercise-responsive genes (n = 634) from the MoTrPAC mouse dataset. Thirty-seven overlapping genes were identified and subjected to Enrichr for pathway enrichment, KEA3 for kinase analysis, and ChEA3 for transcription factor prediction. Candidate effector genes were ranked using ToppGene and ToppNet, with integrated prioritization via the FLAMES linear scoring algorithm. Results: Pathway enrichment revealed complementary patterns: aging-associated genes were enriched in mitochondrial dysfunction and sarcomere disassembly, while exercise-responsive genes were linked to protein synthesis and lipid metabolism. TTN, PDK family kinases, and EGFR emerged as major upstream regulators. NKX2-5, MYOG, and YBX3 were identified as shared transcription factors. SMPX ranked highest in integrated scoring, showing both functional relevance and network centrality, implying a pivotal role in mechano-metabolic coupling and cardiac stress adaptation. Conclusions: By integrating cardiac aging and exercise-responsive transcriptomes, 37 effector genes were identified as molecular bridges between aging decline and exercise-induced rejuvenation. Aging involved mitochondrial and sarcomeric deterioration, while exercise promoted metabolic and structural remodeling. SMPX ranked highest for its roles in mechano-metabolic coupling and redox balance, with X-inactivation escape suggesting sex-specific relevance. Other top genes (e.g., KLHL31, MYPN, RYR2) form a regulatory network supporting exercise-mediated cardiac protection, offering targets for future validation and therapy. Full article

Background: Chronic pain affects one in five youth globally and is frequently accompanied by mental health challenges that extend into adulthood. Caregivers play a vital role in supporting youth with chronic pain, yet their own mental and physical health needs are often overlooked. While caregiver well-being is linked to child outcomes, few interventions directly address caregivers’ health, especially among those facing systemic barriers. This study explored the lived experiences of caregivers to better understand their unmet needs and inform the co-design of a supportive digital health solution. Methods: We conducted a qualitative exploratory study involving 32 caregivers of youth with chronic pain across Canada and Australia. Semi-structured interviews were co-facilitated by caregiver partners. Thematic analysis was applied to interview data. Results: Two overarching themes were identified: (1) bearing the weight and sacrifice of caregiving and (2) deep interrelatedness and blurred boundaries. Caregivers reported profound emotional, physical, and financial burdens; strained relationships; and social isolation. Many struggled with self-neglect, prioritizing their child’s needs over their own. Fathers’ evolving caregiving roles challenged traditional gender norms, though mothers continued to bear a disproportionate load. Despite challenges, caregivers demonstrated resilience and recognized their well-being as interconnected with their child’s health. Conclusions: Findings underscore the need for systemic investment in caregiver well-being. Digital health solutions, including virtual peer networks, mental health resources, and tailored education, offer scalable, accessible pathways for support. These insights will inform the development of Power over Pain for Primary Caregivers, a digital solution and knowledge hub aimed at improving caregiver well-being and family outcomes, aligning with global efforts to enhance family-centred pediatric pain care. Full article

This paper explores the experiences of parents of children with autistic spectrum disorder (ASD) who have participated in parenting programmes in the UK. The parents attended generic programmes before they were able to access more specific programmes geared towards the needs of children with ASD. The parents found that the generic programmes were detrimental to the needs of their children and disruptive of family life, resulting in parental relationship breakdown in some instances. Whilst the ASD-specific programmes did provide some level of support, the most decisive factor was the sharing of experiences amongst those parents as well as the ongoing support that this fostered. The conclusion of this study is that the neoliberal responsibilisation of parents via parenting programmes is undermining the support networks of parents of children with ASD, and an asset-based community development approach would be more beneficial. Full article

Background: Accurate upfront risk stratification in suspected clinically significant prostate cancer (csPCa) may reduce unnecessary prostate biopsies. Integrating clinical and Magnetic Resonance Imaging (MRI) variables using deep learning could improve prediction. Methods: We retrospectively analysed 538 men who underwent MRI and biopsy between April 2019-September 2024. A fully connected neural network was trained using 5-fold cross-validation. Model 1 included clinical features (age, prostate-specific antigen [PSA], PSA density, digital rectal examination, family history, prior negative biopsy, and ongoing therapy). Model 2 used MRI-derived Prostate Imaging Reporting and Data System (PI-RADS) categories. Model 3 used all previous variables as well as lesion size, location, and prostate volume as determined on MRI. Results: Model 3 achieved the highest area under the receiver operating characteristic curve (AUC = 0.822), followed by Model 2 (AUC = 0.778) and Model 1 (AUC = 0.716). Sensitivities for detecting clinically significant prostate cancer (csPCa) were 87.4%, 91.6%, and 86.8% for Models 1, 2, and 3, respectively. Although Model 3 had slightly lower sensitivity than Model 2, it showed higher specificity, reducing false positives and avoiding 43.4% and 21.2% more biopsies compared to Models 1 and 2. Decision curve analysis showed M2 had the highest net benefit at risk thresholds ≤ 20%, while M3 was superior above 20%. Conclusions: Model 3 improved csPCa risk stratification, particularly in biopsy-averse settings, while Model 2 was more effective in cancer-averse scenarios. These models support personalized, context-sensitive biopsy decisions. Full article

With the development of higher education, college students have become a new and important group for environmentally sustainable development. How to evaluate and strengthen the practical effect of ecological education is of great significance. Based on the survey data of 1579 university students, this study constructed a systematic index system of ecological education by using a hierarchical evaluation method. Moreover, OLS (Ordinary Least Squares), Oprobit, and intermediary effect models were used to analyze the influence relationship and mechanism of the two empirically and IV-Oprobit was used to solve the endogeneity problem. The results show the following: (1) Ecological education can effectively promote the sustainable behavior of university students, and the probability of university students implementing sustainable behavior increases by 10.7% with each unit increase in the level of ecological education. (2) Environmental value perception such as in individual economic value perception, social value perception, and health value perception are all important mediating channels of ecological education, among which health value perception has the strongest mediating effect. (3) Particulate Matter 2.5 (PM2.5) exposure positively moderates the impact of university students’ environmental value perception on their sustainable behavior. (4) There is a significant correlation between university students’ household registration, participation in environmental associations and hometown social networks, and sustainable behaviors. (5) The influence of ecological education on students’ behaviors shows heterogeneity in family household registration. Students from rural families have a higher level of environmental behavior and value perception than those from urban families. Moreover, they are more likely to exhibit behaviors under the influence of ecological education. The above results provide reference suggestions for the ecological education policy system and offer theoretical support and policy inspiration for promoting sustainable behaviors among global college students and enhancing the efficiency of ecological education in universities. Full article

Neuropeptides (NPs) are a diverse group of signaling molecules involved in regulating key physiological processes such as pain perception, stress response, mood, appetite, and circadian rhythms. Acting as neurotransmitters, neuromodulators, or neurohormones, they play a critical role in modulating and fine-tuning neural signaling networks. Despite their biological significance, identifying NPs through experimental techniques remains time-consuming and resource-intensive. To support this effort, computational prediction tools have emerged as a cost-effective approach for prioritizing candidate sequences for experimental validation. In this study, we propose EnsembleNPPred, an ensemble learning framework that integrates traditional machine learning (ML) models with a deep learning (DL) component. By combining the complementary strengths of these approaches, the model aims to improve generalization and predictive robustness. EnsembleNPPred employs a majority voting mechanism to aggregate the outputs from three classifiers: Support Vector Machine (SVM), Extra Trees (ET), and a CNN-based DL model. When evaluated on independent datasets, EnsembleNPPred demonstrated consistently competitive performance, achieving improvements in both accuracy and sensitivity-specificity balance compared to several existing methods. Furthermore, testing on multiple neuropeptide families from the NeuroPep database yielded an average accuracy of 91.92%, suggesting the model’s potential to generalize across diverse peptide classes. These results suggest that EnsembleNPPred may be a useful tool for early-stage neuropeptide candidate identification and for supporting downstream experimental validation. Full article