Search Results (5,832)

Background: India accounts for one-fifth of global cervical cancer deaths, yet Human Papillomavirus (HPV) vaccination coverage remains low despite the World Health Organization (WHO) recommendations to initiate vaccination at age 9. With the national HPV vaccination campaign in 2026 and its approval for integration into India’s Universal Immunization Programme (UIP), strengthening physician knowledge, beliefs, and confidence in recommending the vaccine is critical. Methods: In 2023, the American Cancer Society and Cancer Foundation of India catalyzed two national medical societies, the Federation of Obstetric and Gynaecological Societies of India and the Indian Academy of Pediatrics, to educate physicians on HPV vaccination using a train-the-trainer (ToT) model. A mixed-methods evaluation, using the RE-AIM Framework, included pre- and post-training surveys assessing changes in knowledge, beliefs, confidence, and intent, as well as monthly engagement surveys and project reports analyzed using descriptive and inferential statistics. A fidelity assessment evaluated consistency of training delivery. Twenty in-depth interviews explored physician reactions and implementation of learnings, analyzed using a rapid approach. Results: A total of 18,206 physicians were trained. The post-training respondent group demonstrated higher HPV vaccination knowledge scores and more favorable responses in confidence, beliefs, and intent than the pre-training respondent group. The fidelity assessment demonstrated consistent delivery overall, with some variability in role play facilitation. Interviews highlighted increased physician confidence, peer knowledge sharing, and community engagement following the training. Medical societies reported strong program adoption and plans for continued efforts. Conclusions: A ToT physician training cascaded through medical societies is a feasible strategy to prepare physicians to recommend the HPV vaccine and address parental concerns at scale. Full article

Cardiopulmonary bypass (CPB) during heart surgery provokes an inflammatory response that can cause post-operative organ injury, yet how CPB shapes key neutrophil effector programs is unclear. We investigated whether CPB differentially regulates neutrophil degranulation versus neutrophil extracellular trap (NET) formation and whether pre-operative neutrophil phenotypes associate with organ dysfunction. In a prospective cohort (n = 39) of children (1 day–4 years) undergoing CPB, blood samples were obtained before CPB and 24 h post-operatively. Purified neutrophils were analyzed for elastase activity and NET formation, alongside phenotypic markers of activation and neutrophil–platelet aggregation. Findings were correlated with acute kidney injury, respiratory failure, and cardiovascular dysfunction. CPB induced marked neutrophilia (4.5-fold rise; p < 0.0001). Elastase release was robustly enhanced after CPB and showed limited augmentation with secondary stimulation but did not predict organ dysfunction. In contrast, NET formation was significantly reduced after CPB. Importantly, diminished pre-operative responsiveness to low-dose NET priming was observed in patients who developed organ injury. Pediatric CPB uncouples neutrophil effector programs, priming degranulation while suppressing NETosis. Pre-operative NET “reserve” may define a clinically relevant innate immune endotype at risk for post-operative organ dysfunction and supports development of biomarker-driven treatment strategies in patients undergoing CPB. Full article

Histone-modifying enzymes and histone post-translational modifications (PTMs) play key roles in the organization (euchromatin versus heterochromatin) and function (active versus silenced genes) of chromatin. The abundance and activity of these enzymes, along with their associated histone PTMs, are often altered in cancer cells, leading to deregulated gene expression. The expression of the KMT2A-MLLT3 protein, resulting from a chromosomal translocation in mixed-lineage leukemia (MLL), a subtype of acute myeloid leukemia, augments transcription elongation, promoting the expression of HOXA9 and MEIS1, genes that play critical roles in MLL development. Bortezomib, a proteasome inhibitor, has been effective at treating various cancers. In this study, we compared the impact of bortezomib on histone PTMs in the MLL cell line MOLM-13 and the chronic myeloid leukemic (CML) cell line K562. We report that MOLM-13 had a greater level of histone H2B monoubiquitinated at lysine 120 (H2BK120ub) and histone H3 dimethylated at lysine 79 (H3K79me2) (modifications involved in elongation) and similar levels of histone H2A monoubiquitinated at lysine 119 (H2AK119ub). Bortezomib treatment resulted in significant reductions in H2BK120ub and H2AK119ub levels, as well as in transcript levels of genes involved in MLL development. Full article

Re-establishing native plant communities is critical for restoring post-mine influenced sites. A major challenge is that mining activity can result in poor soil quality that is not conducive to plant growth. Various soil amendments can provide organic material and nutrients that assist plant growth. Biosolids, treated solids recovered from municipal wastewater, can be used as a soil amendment to improve soil quality of mine-influenced landscapes and provide the nutrients for plant growth. The objectives of this study were (1) to determine an appropriate rate of biosolid application to promote the colonization of native plants and (2) to determine the effects of the biosolids on soil properties. In 2021, a field study was devised that tested four biosolid application rates (0, 125, 250, and 375 dry Mg/ha). The site was located in a mining area in the southern interior of British Columbia, Canada, with six replicates per experimental combination. This study demonstrated that biosolids significantly increased the productivity and diversity of the plant community. Biosolids reduced soil pH and increased soil organic matter, carbon and nitrogen concentrations. Receiving soils were either similar to or marginally high in arsenic (As) and molybdenum (Mo). In contrast, biosolids tended to significantly increase Cu levels compared to the control soils. Higher rates of biosolids did not lead to significantly higher plant productivity or diversity than the lower rates. The results of this study suggest that biosolids may significantly help restore sustainable grassland ecosystems in post-mining environments even at a lower application rate of 125 dry Mg/ha. Full article

Highway–rail grade crossing (HRGC) incidents in the United States declined substantially for several decades before stabilizing in recent years. Understanding this persistence is important because future safety improvements may depend on identifying locations where incident occurrence remains resistant to further reduction. This study developed an integrated framework to characterize persistent HRGC incident environments using 50 years (1976–2025) of Federal Railroad Administration incident records. Trend, structural-break, variance, and stationarity tests were first applied to determine whether the historical decline transitioned into a distinct persistence regime. A county-level persistence index (PI) was then developed to quantify the combined effects of incident burden and resistance to decline during the plateau period. Distributional analysis characterized the statistical behavior of the PI, while global and local Moran’s I statistics evaluated its spatial organization. Explainable machine learning methods were subsequently used to identify incident characteristics associated with elevated persistence. The results identified a statistically significant regime change around 2010. Prior to 2010, incidents exhibited a strong declining trend, whereas the subsequent period displayed a statistically significant but substantially weaker decline, lower variance, and behavior consistent with a persistence regime characterized by a markedly attenuated rate of improvement. The PI followed a strongly right-skewed distribution that was best represented by a bounded heavy-tailed unit log-logistic model, indicating that persistence is concentrated within a relatively small subset of counties. Spatial analysis revealed significant positive spatial autocorrelation (Moran’s I = 0.180, p = 0.001) and geographically coherent clusters concentrated primarily in the southeastern United States and several major freight-oriented regions. Explainable machine learning models identified train-operating characteristics, warning device contexts, movement patterns, and temporal conditions as key attributes associated with high-persistence counties. The findings demonstrate that the post-2010 incident plateau is sustained disproportionately by a limited number of geographically concentrated environments and provide a framework for supporting more targeted safety interventions. Full article

Deep neural networks (DNNs) have significantly advanced machine perception and reasoning; however, their lack of transparency in decision-making continues to pose a major challenge, particularly in high-stakes domains such as healthcare, finance, and law. This is especially concerning with the black-box nature of convolutional neural networks (CNNs), where the rationale for making a decision can be as important as the decision itself. This paper is driven by a question that is easier to ask than to answer: how can CNNs be made to explain themselves? To answer the question, we wrote a PRISMA-compliant systematic review of 154 studies published between 2017 and 2025. These studies were selected from 4421 studies retrieved through Web of Science, Scopus, IEEE Xplore, and ACM Digital Library. CNN-specific taxonomy was developed. This taxonomy organizes explainable artificial intelligence (XAI) methods on four axes: explanation timing, model dependency, output type, and target component. We found that there is a huge bias in the field regarding post hoc visual methods. Grad-CAM is the most widely cited visual explanation methodology, and within the model-agnostic framework, LIME and SHAP prevail. This research was also the first to analyze standard assessment methods. It was found that out of the 154 studies in the review, 98 used objective methods to evaluate fidelity, stability, or sensitivity. Conversely, fewer than ten of them used human-centered methods to evaluate how tasks were performed, how the users trusted the method, or how the users were prepared to interact with the system. We argue for a dual-reporting convention under which metrics should be reported together at least once, as per the family of metrics. The third contribution is an evidence-based challenge map, where we outline four issues: absence of standardized benchmarks, post hoc mechanism scalability limitations, vulnerability to adversarial perturbations, and the persistent gap between the technical descriptions and human understanding. For each challenge, we propose concrete directions: integrating causal reasoning, adopting participatory evaluation design, and building hybrid transparent architectures. We offer this review as a practical roadmap for researchers and practitioners working toward more explainable deep neural networks. Full article

Background: Prenatal maternal stress is increasingly recognized as a critical determinant of fetal programming, with potential consequences for early physical growth and neurodevelopment. Although a growing body of evidence links maternal psychological stress to adverse perinatal and developmental outcomes, most studies originate from high-income Western settings, rely predominantly on self-reported stress measures, and rarely incorporate biological stress markers. Evidence from post-Soviet regional contexts remains limited. Methods: A two-phase study was conducted in Tbilisi, Georgia. Phase I employed a cross-sectional observational design involving 398 pregnant women recruited from maternity homes and women’s consultations. Maternal psycho-emotional stress was assessed using a study-specific pregnancy stress questionnaire, and salivary cortisol was measured in a subsample of women reporting chronic stress (N = 95). Phase II used a prospective cohort design to follow infants born to stress-exposed mothers (N = 95) and non-stressed controls (N = 95) from birth to 12 months. Infant outcomes included anthropometric measurements evaluated using World Health Organization Child Growth Standards and neurodevelopmental screening using the Ages & Stages Questionnaires, Third Edition (ASQ-3), at 1–3, 5–7, and 11–13 months. Statistical analyses were made by SPSS 23.0. Results: Salivary cortisol assessment in the stress-exposed subsample provided supportive biological evidence of elevated stress levels but was not used for direct comparison with the control group. Children born to stress-exposed mothers showed significantly poorer physical growth and lower ASQ-3 scores across all developmental domains during the first year of life (all p < 0.05). Conclusions: This study provides novel evidence from an underrepresented regional context and supports early developmental surveillance and preventive strategies to improve maternal and child health outcomes. Full article

Background/Objectives: Whole exome sequencing (WES) has emerged as a clinically valuable second-tier test following abnormal biochemical newborn screening (NBS). However, population-specific data on diagnostic yield, secondary findings (SFs), and exome-wide carrier burden remain scarce in East Asian neonates, particularly since the release of the ACMG SF v3.3 gene list. We aimed to characterize these metrics in a Taiwanese neonatal cohort. Methods: We retrospectively analyzed 118 consecutive neonates referred to Taipei Veterans General Hospital between August 2021 and August 2022 following abnormal biochemical NBS. WES was performed on the Illumina NovaSeq 6000 platform; variants were classified per the 2015 ACMG/AMP framework and re-evaluated under ACMG SF v3.3. Referral categories comprised lysosomal storage diseases (n = 61), amino acid disorders (n = 38), fatty acid oxidation disorders (n = 13), and organic acid disorders (n = 6). Results: Fifty neonates (42.4%) received confirmed molecular diagnoses and 45 (38.1%) were carriers (combined molecular resolution 80.5%). Five participants (4.2%) harbored pathogenic/likely pathogenic variants in ACMG SF v3.3 genes (TTN, LDLR, PTEN, RYR1, TP53). Incidental findings occurred in 51.7%, and at least one recessive-carrier variant was detected in 99.2% (mean 4.15 per individual; median 4). The Taiwanese-specific c.639+919G>A cardiac Fabry variant accounted for 24/25 confirmed male Fabry cases, and the p.Gly576Ser pseudodeficiency allele confounded all suspected Pompe cases. Conclusions: Second-tier WES substantially improves diagnostic precision, discriminating confirmed diagnoses from carrier, pseudodeficiency, and biochemical false-positive states. The high carrier burden and incidental-finding rate underscore the importance of comprehensive pre- and post-test genetic counseling in East Asian neonatal genomic programs. Full article

Myocardial ischemia and reperfusion initiate spatially organized injury–repair programs that subsequently shape ventricular remodeling. Although cardiac fibroblasts are indispensable for scar formation, single-cell and spatial transcriptomic studies reveal temporally dynamic and regionally distinct fibroblast-lineage states. This critical narrative review integrates direct evidence from myocardial ischemia–reperfusion (I/R) with model-labeled evidence from permanent myocardial infarction, clinically heterogeneous human infarction, fibroblast-specific ubiquitin biology, cell-cycle regulation, and cardiac fibroblast atlases. A direct fibroblast I/R study identifies an HSP47–USP10–SMAD4 deubiquitination axis, whereas most other fibroblast ubiquitin–proteasome system (UPS) mechanisms derive from permanent infarction, non-ischemic cardiac stress, or in vitro systems. We propose that CCNB1-associated, G2/M-enriched cycling fibroblast-lineage states may impose heightened proteostatic demands within defined post-ischemic niches. The conceptual novelty is not that CCNB1 turnover or UPS activity is cardiac-specific; both are general features of proliferating cells. Rather, the framework asks whether fibroblast lineage, injury-model provenance, anatomical niche, temporal window, cell state, and substrate-specific UPS nodes jointly define proteostatic dependencies during post-ischemic remodeling. RNA-based ubiquitin-related signatures remain transcriptional proxies and do not directly quantify ubiquitinated substrates, ubiquitin-chain topology, enzyme activity, or proteasome flux. Resolving the proposed relationships will require spatial colocalization, protein-level and ubiquitin-remnant profiling, proteasome and ribosome assays, fibroblast-specific perturbation, and validation in human infarct tissue. Full article

Kombucha is a functional beverage produced through the fermentation of Camellia sinensis by a symbiotic culture of bacteria and yeast (SCOBY). Incorporating cashew (Anacardium occidentale L.) and Cajá (Spondias mombin L.) pulps represents a value-addition strategy to mitigate the post-harvest perishability of native Cerrado fruits. This study evaluated physicochemical kinetics, 21-day refrigerated shelf life, consumer acceptance, and biological effects in Caenorhabditis elegans of flavored kombuchas. During a 9-day primary fermentation, the pH decreased to 2.95 while total acidity reached 5.38%. Following flavoring (10% v/v pulp/juice), cashew kombucha exhibited the highest total phenolic content (4.19 mg GAE/mL) and ferric reducing power (FRAP), whereas Cajá kombucha showed superior DPPH scavenging activity (1236 µM TroloxE/mL). Refrigerated storage (4 °C) maintained high counts of viable microorganisms (>10⁵ CFU/mL), though active residual fermentation induced ongoing sugar cleavage and a transient yeast proliferation peak on day 7 (8.15 log CFU/mL in Cajá kombucha). Toxicity assays using C. elegans revealed the initial mortality (31.5–62.5%); however, adjusting the pH to near-neutrality restored high organism viability (<10% mortality), confirming that mortality was acidity-driven. In pH-adjusted media, cashew kombucha promoted a modest extension of nematode lifespan, whereas Cajá kombucha reduced lipid accumulation. Sensory testing revealed moderate consumer acceptance, with cashew kombucha achieving a higher Acceptance Index (72.92%) than Cajá (67.26%). Overall, fruit supplementation enriches the bioactive potential of green tea kombucha, provided that post-fermentation acidity is appropriately managed. Full article

Obesity and type 2 diabetes mellitus (T2DM) are multifactorial disorders characterized by insulin resistance, chronic low-grade inflammation, adipose tissue dysfunction, and multi-organ metabolic impairment. MicroRNAs (miRNAs) act as post-transcriptional gene regulators and play critical roles in metabolic homeostasis, the modulation of insulin signaling, adipogenesis, inflammatory pathways, and energy balance in key insulin-target tissues, including liver, skeletal muscle, and adipose tissue. This review summarizes mechanistic and translational insights into miRNA regulation in obesity, insulin resistance, and T2DM, integrating data from human studies and experimental models on miRNA sequence codes and extracellular vesicle sorting pathways. We focus on the tissue-specific and systemic roles of miRNAs, highlighting their contribution to inter-organ communication and metabolic network regulation. In addition, we emphasize their emerging roles as predictive biomarkers, modulators of treatment response, and promising targets for RNA-based interventions. Advances in sequence-specific miRNA sorting and extracellular vesicle-mediated delivery may provide avenues for therapeutic intervention. However, challenges related to delivery efficiency, tissue specificity, off-target effects, and variability in miRNA quantification remain important barriers to clinical translation. Addressing these limitations may help define the clinical utility of miRNAs as biomarkers and therapeutic targets in metabolic disorders. Full article

Background: In 2022, we adapted the World Health Organization Digital Adaptation Kit (DAK) for antenatal care (ANC) into the BornFyne digital health platform. Because ANC services in many facilities relied on fragmented paper-based guidance, the DAK represented the first exposure for many providers to a structured, comprehensive ANC guideline framework integrated into a digital system. Understanding providers’ motivation, capabilities, and readiness to adopt guideline-driven digital care was essential to inform implementation strategies. We therefore conducted a workshop to explore healthcare providers’ expectations, perceived challenges, and readiness to integrate a comprehensive digital ANC system into routine practice. Methods: A prospective mixed-methods pre–post implementation pilot workshop was conducted between June and August 2023 across four districts. The 5-h workshop targeted ANC providers and included exposure to the WHO ANC DAK and demonstration of its integration into the BornFyne platform. Survey tools assessed perceived knowledge, attitudes, perceived behavioural control, intention, and social norms using Likert scales. Constructs were mapped to the COM-B framework. Paired student’s t-tests assessed pre–post changes (p < 0.05), and Cohen’s d estimated effect sizes. Qualitative responses were thematically analysed. Results: Nineteen participants, including doctors, nurses, midwives, and data managers from public, private, and faith-based facilities, completed the surveys. Most participants were women (90%). Following the workshop, perceived knowledge of behaviour change and digital guideline use significantly increased (t(19) = 3.22, p = 0.004, d = 0.78). Although no statistically significant changes were observed in attitudes, perceived behavioural control, intentions, or social norms, descriptive trends suggested improved confidence and openness toward digital ANC systems. Qualitative findings identified increased knowledge as the most important outcome, with 80% of participants emphasizing its role in strengthening capability. Participants also reported greater confidence in integrating digital tools into routine care but highlighted contextual and motivational barriers as ongoing challenges. Acceptability was high: 90% expressed satisfaction, and all participants rated the workshop as useful, relevant, engaging, and worth their time. Conclusions: The workshop improved providers’ perceived knowledge and demonstrated high acceptability of DAK-aligned digital ANC systems. While changes in attitudes and behavioural control were not statistically significant, the findings support the feasibility of behaviour change-based digital ANC interventions. Addressing contextual and motivational barriers will be essential for sustained adoption in resource-limited settings. Full article

Green finance has become a key component of sustainability transitions by supporting the alignment of financial systems with environmental and climate-related objectives. As discussions on sustainable investments and climate finance increasingly take place in digital environments, analyzing large-scale user-generated content has become important for understanding online discussions and emerging discourse patterns. This study investigates green finance discourse in the digital public sphere using a multi-method Natural Language Processing (NLP) framework. A dataset of 23,452 posts collected from the platform X was analyzed using TF-IDF-based word frequency analysis, FinBERT-based sentiment analysis, Latent Dirichlet Allocation (LDA) topic modelling, and keyword co-occurrence network analysis. The results indicate that green finance discourse is dominated by positive (44.61%) and neutral (45.85%) sentiment, suggesting a generally favorable and institutionalized public perception. Topic modelling identified three dominant themes: climate finance and sustainability transition, digital finance and speculative investment narratives, energy investments and financial infrastructure. Network analysis revealed that sustainability, climate, energy, investment, and finance constitute the core conceptual structure of discourse. These findings demonstrate the effectiveness of NLP-based approaches for analyzing large-scale digital discussions and provide insights for policymakers, financial institutions, and organizations seeking to better understand online discussions surrounding green finance and support more effective sustainability communication strategies. Full article

The European crafts ecosystem faces critical structural threats, declining practitioner numbers, weakening intergenerational transmission, limited digital literacy, and competition from industrial imitation. Existing online craft communities are narrowly material-specific and structurally ill-suited to the cross-disciplinary dialogue required for systemic sector transformation. This paper presents the design, iterative development, and pilot evaluation of the Craeft Community, a multi-stakeholder Virtual Community of Practice (VCoP) developed within the Horizon Europe CRAEFT project. Three research questions guided the study: how a multi-stakeholder VCoP should be structured to overcome disciplinary fragmentation; to what extent a stewarded digital forum can operationalize Situated Learning and Communities of Practice theory; and what factors facilitate or inhibit engagement and post-funding sustainability. Using design-based research, the platform evolved through four iterative phases, culminating in restructuring from a material-based architecture into five transversal thematic pillars, driven by survey evidence from 151 European craft professionals and systematic stakeholder feedback. The pilot phase yielded 86 registered members, 31 posts, and 27 interactions, with Transmission & Training as the most engaged pillar. Qualitative analysis reveals substantive cross-disciplinary discourse alongside a structural Effort-Engagement Gap, a persistent tension between forum participation demands and the gravitational pull of mainstream social media. The study demonstrates that a thematically organized, stewarded VCoP can meaningfully operationalize apprenticeship-based learning in digital settings, advancing craft heritage preservation, economic resilience, and hybrid professional identity formation at the intersection of craft and technology. Full article

Fake social media profiles increasingly resemble ordinary accounts, combining believable images, fluent biographies, copied posts, and selective engagement, which makes single signal detection unreliable. This study develops and evaluates a forensic natural language processing (NLP) framework that treats profile text as digital evidence rather than raw model input. Profiles were collected from Facebook, Instagram, X, Truth Social, and LinkedIn through network expansion and vocabulary guided scraping, then anonymized, merged, cleaned, and organized into structured text and profile records. Ground truth came from human eye annotation (referred to throughout as human eye review, human review, or manual review) supported by three LLM reviewers (referred to throughout as LLM assisted review), OpenAI GPT-4o, Anthropic Claude 3.5 Sonnet, and Google Gemini 1.5 Pro, with strict agreement logic producing confidence-tiered labels across platform-specific label spaces covering scam, fraud, harmful, and legitimate behavior. Each model received a defined set of label categories, was instructed to return a single label with a one sentence rationale, and worked independently with no cross-model communication. Multidimensional features, including TF-IDF representations, sentence embeddings, scam lexicon counts, sentiment and emotion scores, and behavioral indicators, were extracted through a pipeline built to keep links, hashtags, contact markers, and repeated phrasing as forensic signals rather than noise. Traditional classifiers, transformer models, and ensembles were trained on verified labels, and the best model per platform was applied to the full dataset of over 309,108 records under confidence filtered classification, with predictions below a 0.70 probability threshold flagged for human review. The framework links classification outputs to textual indicators through explainable AI, achieving weighted F1 scores between 0.86 and 0.96 across five platforms. These results show that profile text alone provides strong, production-relevant evidence for detecting fake and harmful accounts, even though the framework treats this as one evidence stream to be weighed alongside image and behavioral signals rather than as a final determination on its own. The accompanying evidence trail means an investigator or a trust and safety team can see why a profile was flagged rather than being handed a bare score, which is what turns a classifier into a tool that can be checked, challenged, and used directly in an investigation. Full article