Search Results (83,491)

Background and Clinical Significance: Prader–Willi syndrome (PWS) is an imprinting disorder not typically associated with severe congenital sensorineural hearing loss (SNHL). When profound SNHL is present in an infant with a known syndrome, an independent monogenic etiology should be considered. We report the first molecularly confirmed case of PWS co-occurring with biallelic pathogenic TMC1 variants causing congenital SNHL, outlining diagnostic challenges, cochlear implant (CI) outcomes, and implications for blended phenotypes. Case Presentation: A male infant with PWS due to a paternal 15q11.2–q13 deletion failed newborn hearing screening. Diagnostic auditory brainstem response and auditory steady-state response confirmed bilateral severe-to-profound SNHL. Temporal bone CT/MRI were normal. Comprehensive genetic testing identified compound heterozygous TMC1 variants consistent with autosomal recessive DFNB7/11 hearing loss, plus two variants of uncertain significance in SERPINB6 and EPS8L2. Sequential bilateral cochlear implantation was performed (left ear at 14 months, right at 20 months), followed by auditory–verbal therapy. Over four years, the child showed steady improvements in hearing and early-speech development. Conclusions: Early genomic evaluation is essential when clinical features appear atypical for a known syndrome. Identifying TMC1-related deafness enabled timely cochlear implantation and measurable gains. This case highlights that severe congenital SNHL in a syndromic infant may reflect a distinct monogenic disorder rather than phenotypic expansion of the primary syndrome, emphasizing the importance of recognizing blended phenotypes to guide precision-care strategies in rare disorders. Full article

Liver cancer, also known as hepatocellular carcinoma (HCC), remains a major global health concern, with high mortality driven by late-stage diagnosis, limited treatment efficacy, and frequent therapeutic resistance. Matrix metalloproteinases (MMPs), a large family of zinc-dependent endopeptidases, are central to the biological processes that drive liver tumor initiation and progression. By degrading and reorganizing extracellular matrix components, MMPs facilitate tumor expansion, tissue invasion, and metastatic dissemination. In addition, these enzymes regulate the availability of growth factors, cytokines, and chemokines, thereby influencing angiogenesis, inflammation, immune cell recruitment, and the development of an immunosuppressive tumor microenvironment. Aberrant expression or activity of multiple MMP family members is consistently associated with aggressive clinicopathologic features, including vascular invasion, increased metastatic potential, and reduced patient survival, highlighting their promise as prognostic markers and actionable therapeutic targets. Past attempts to modulate MMP activity were hindered by broad inhibition profiles and dose-limiting toxicities, underscoring the need for improved specificity and delivery strategies. Recent advances in molecular design, biologics engineering, and nanotechnology have revitalized interest in MMP targeting by enabling more selective, context-dependent modulation of proteolytic activity. Preclinical studies demonstrate that carefully tuned MMP inhibition can limit tumor invasion, enhance anti-angiogenic responses, and potentially improve the efficacy of existing systemic therapies, including immuno-oncology agents. This review synthesizes current knowledge on the multifaceted roles of MMPs in HCC pathobiology and evaluates emerging therapeutic strategies that may finally unlock the clinical potential of targeting these proteases. Full article

Personality traits are well-established predictors of safety behavior in construction, yet the cognitive mechanisms through which these traits influence such behavior remain poorly understood. In particular, hazard recognition and risk perception are underexamined cognitive mediators that elucidate how personality traits shape safety behavior. Moreover, the mediating effects of these cognitive processes are likely to vary across individuals, reflecting heterogeneity in background characteristics. Neglecting these mediating processes and their differentiated effects not only limits theoretical understanding of the pathways linking personality traits to safety behavior but also undermines the effectiveness of safety interventions. To address this gap, this study develops a framework incorporating cognitive mediators to examine how personality traits influence safety behavior (safety compliance and participation). The hypothesized cognitive-mediation pathways were tested using structural equation modeling based on offline questionnaire data collected from 213 site managers and workers. The findings reveal distinct cognitive pathways through which personality traits shape safety behavior. Extraversion and openness indirectly reduced safety compliance and safety participation by weakening hazard recognition and risk perception, either independently or sequentially. In contrast, agreeableness and conscientiousness enhanced safety behavior by strengthening these same cognitive processes. Higher education levels positively moderated certain mediating effects, whereas extensive work experience exerted mixed influences on specific pathways, facilitating some and inhibiting others depending on context. These findings deepen understanding of the internal mechanisms through which personality traits influence safety behavior via risk cognition. By identifying differentiated pathways across groups, this study further refines the theoretical framework explaining construction workers’ safety behavior. In addition, the theoretical insights generated by this study offer proactive and effective directions for safety practice, including improving person–job fit, designing targeted risk cognition training, and implementing stratified safety management strategies. Full article

Background and Objectives: Cognitive disorders are a significant health problem in patients undergoing peritoneal dialysis and can profoundly impair both quality of life and treatment outcomes. Early identification of risk factors for the development of cognitive disorders in this population is therefore essential. This study aimed to (1) determine the prevalence of cognitive dysfunction in patients on peritoneal dialysis, (2) examine its association with sociodemographic characteristics, and (3) assess whether anaemia is associated with cognitive dysfunction in these patients. Materials and Methods: A cross-sectional study was conducted in November 2024 at the University Clinical Centre of Vojvodina, Clinic for Nephrology and Clinical Immunology, and included 36 patients on peritoneal dialysis. The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive function, while a structured questionnaire was used to collect sociodemographic data. Anaemia was determined based on haemoglobin levels. Results: Cognitive dysfunction was present in 69.4% of patients on peritoneal dialysis, while anaemia, as indicated by haemoglobin values, was present in 58.3% of the sample. Older age, rural residence, and lower haemoglobin levels were significantly associated with cognitive dysfunction in patients on peritoneal dialysis. Conclusions: Preserved cognitive function is a key prerequisite for the adequate implementation of peritoneal dialysis and for maintaining patients’ quality of life. The findings indicate the need for further research to identify effective strategies for preventing and treating anaemia, a factor associated with cognitive dysfunction in this patient population. Full article

This study aimed to assess the effect of mulberry leaf fortification with a probiotic (Enterococcus faecium and rosemary) on larval development, feed utilization efficiency, digestive performance, and cocoon-related traits in two Bombyx mori breeds. The results showed that a probiotic addition to the silkworms’ diet, particularly at a 2% inclusion level, enhances key productive traits such as larval weight, silk gland weight, cocoon weight, digestibility, and feed efficiency, while reducing excreta. Breed-specific differences were evident, with Kahuri/T exhibiting superior nutrient intake, assimilation, and overall productivity compared to AO/T (p < 0.0001). Productive traits during the 5th instar increased significantly over time, with both larval growth and silk gland development following rapid, exponential patterns. The Kahuri/T breed and the probiotic-supplemented groups—particularly at a 2% concentration—showed the most notable improvements compared with the AO/T breed and the control diet. Pearson correlation analyses identified strong positive relationships between feed efficiency, protein intake, and silk yield, underscoring probiotics as a viable strategy for sustainable productivity gains in sericulture. In conclusion, mulberry leaf fortification with Enterococcus faecium and rosemary, especially at a 2% inclusion level, significantly improved performance and nutrient utilization, with the strongest responses observed in the Kahuri/T breed. These findings highlight probiotic supplementation as an effective and sustainable strategy for enhancing sericulture. Full article

Convolutional Neural Networks (CNNs) generally suffer from excessive computational overhead, high resource consumption, and complex network structures, which severely restrict the deployment on microprocessor chips. Existing related accelerators only have an energy efficiency ratio of 2.32–6.5925 GOPs/W, making it difficult to meet the low-power requirements of embedded application scenarios. To address these issues, this paper proposes a low-power and high-energy-efficiency CNN accelerator architecture based on a central processing unit (CPU) and an Application-Specific Integrated Circuit (ASIC) heterogeneous computing architecture, adopting an operator-fused systolic array algorithm with the YOLOv5n target detection network as the application benchmark. It integrates a 2D systolic array with Conv-BN fusion technology to achieve deep operator fusion of convolution, batch normalization and activation functions; optimizes the RISC-V core to reduce resource usage; and adopts a locking mechanism and a prefetching strategy for the asynchronous platform to ensure operational stability. Experiments on the Nexys Video development board show that the architecture achieves 20.6 GFLOPs of computational performance, 1.96 W of power consumption, and 10.46 GOPs/W of energy efficiency ratio, which is 58–350% higher than existing mainstream accelerators, thus demonstrating excellent potential for embedded deployment. Full article

Background/Objectives: Our previous study showed that the dietary structure is imbalanced in a majority of colorectal cancer patients receiving chemotherapy. These patients had higher risk of developing malnutrition. In the present study, we aimed to identify factors associated with nutritional risk in this cohort of patients. Methods: We performed a secondary analysis of a dataset that was originally collected to identify the factors that are associated with an imbalanced dietary structure in patients receiving chemotherapy for colorectal cancer. Nutritional risk was evaluated by using an NRS-2002 form. Binary logistic regression was used for multivariate analysis. Results: Among the 178 CRC patients enrolled in this study, 60 (33.7%) had nutritional risk. Patients with nutritional risk exhibited lower intake of grains, potatoes, vegetables, fruits, beans, nuts, and oils compared to those without risk. Multivariate analysis showed that non-surgery (95% CI: 0.130–0.914, p = 0.032) and high dietary structure score (95% CI: 0.808–0.944, p = 0.001) are associated with lower nutritional risk in CRC patients receiving chemotherapy. Conclusions: CRC patients receiving chemotherapy have moderate risk of developing malnutrition. Dietary structure score and surgery are associated with malnutrition in CRC patients receiving chemotherapy. Education on proper dietary structure is a potential strategy to mitigate nutritional risk in CRC patients undergoing chemotherapy. These findings highlight the need for personalized nutritional support to optimize patient outcomes. Full article

Predicting neoadjuvant chemotherapy response in breast cancer remains critical for optimizing treatment strategies, yet robust predictive biomarkers are lacking. This study implemented an ensemble machine learning approach to identify a gene expression signature predicting pathological complete response (pCR) versus residual disease (RD) using bulk RNA-sequencing data from GSE163882 (138 RD, 80 pCR). We employed TMM normalization with differential expression analysis (250 genes, FDR < 0.05, |log2FC| ≥ 1), ensemble feature selection across five classifiers (Random Forest, Gradient Boosting, SVM, k-NN, and Neural Network) with 10-fold repeated cross-validation, and stacked ensemble development. Consensus selection identified a 17-gene signature consistently ranked across algorithms. The stacked ensemble achieved 0.97 AUC post-testing on hold-out test data. External validation on the independent GSE240671 cohort (37 pCR, 25 RD) following ComBat batch correction achieved ROC AUC of 0.78 and PR AUC of 0.85 with isotonic calibration, demonstrating balanced accuracy of 0.71 and 0.86 sensitivity for pCR detection. Pathway enrichment revealed associations with cell cycle regulation (E2F3, MKI67), DNA repair (BRCA2), and transcriptional control (MED1), with six priority genes (MED1, BRCA2, E2F3, PITPNB, H1-1, and FARP2) showing established breast cancer relevance. This externally validated 17-gene signature provides a biologically grounded tool for NAC response prediction in precision oncology. Full article

Objectives: We aimed to develop expert-informed recommendations for colleges and universities to support students with celiac disease (CeD) managing a gluten-free (GF) diet. Methods: A multidisciplinary panel of 40 stakeholders, including physicians, dietitians, a disability rights attorney, university staff, and students, was convened by the Celiac Disease Foundation to create expert-based and experience-informed recommendations. Over a 6-month period, the group conducted literature reviews, stakeholder interviews, and expert consensus discussions to identify common barriers and accommodations aligned with federal disability law. The expert panel collaboratively developed and revised an initial set of recommendations. Two rounds of structured voting were held during which panelists provided feedback to refine content and ensure clarity. All final recommendations were adopted with at least 90% of panelists voting in support. Results: The panel identified 24 accommodations across four domains: academics, housing, dining, and campus life. Academic recommendations include flexibility for illness-related absences, support for remote learning, and classroom modifications. Housing recommendations emphasize access to priority placement, appropriate appliances, and proximity to safe dining. Dining accommodations address GF food availability, ingredient transparency, staff training, and meal plan flexibility. Campus life recommendations ensure full participation in athletics, study abroad, social events, and internships, with supports for psychosocial well-being. Conclusions: This manuscript presents the first expert-informed recommendations focused specifically on the needs of college students with CeD. These recommendations are intended to support institutions as they develop strategies to enhance access to GF food, quality of life, educational supports, and student experience for those living with this chronic autoimmune condition. Full article

High electrostrain, excellent thermal stability, and low hysteresis are critical requirements for advanced high-precision actuators. However, simultaneously achieving these synergistic properties in lead-free ferroelectric ceramics remains a significant challenge. In this work, a targeted B-site doping strategy was employed to develop novel lead-free (0.99-x)BaTiO₃-xBaZrO₃-0.01Bi(Zn_2/3Nb_1/3)O₃ (BT-xBZ-BZN, x = 0–0.2) ceramics. Systematic investigation identified optimal Zr⁴⁺ substitution at x = 0.1, which yielded an outstanding combination of electromechanical properties. For this optimal composition, a high unipolar electrostrain (S_max = 0.11%) was achieved at 50 kV/cm, accompanied by an ultra-low hysteresis (H_S = 1.9%). Concurrently, a large electrostrictive coefficient (Q₃₃ = 0.0405 m⁴/C²) was determined, demonstrating excellent thermal robustness with less than 10% variation across a broad temperature range of 30–120 °C. This superior comprehensive performance is attributed to a composition-driven evolution from a long-range ferroelectric to a pseudocubic relaxor state. In this state, the dominant electrostrictive effect, propelled by reversible dynamics of polar nanoregions (PNRs), minimizes irreversible domain switching. These findings not only present BT-xBZ-BZN (x = 0.1) as a highly promising lead-free candidate for high-precision, low-loss actuator devices, but also provide a viable design strategy for developing high-performance electrostrictive materials with synergistic large strain and superior thermal stability. Full article

Pod corn (Zea mays var. tunicata) bears leafy glumes that enclose kernels, resembling a partial reversion to wild-forms, yet remains poorly characterized in situ in Mexico. We evaluated Mexican accessions at two contrasting locations to quantify morphological/phenological diversity and to assess functional traits via proximate kernel composition. Standard descriptors captured variation in plant architecture, tassel/ear traits (including glume length), and reproductive timing. Accessions showed strong plasticity and significant accession × environment effects on ear morphology and maturation. Grain yield ranged from 6.32 to 10.78 t ha⁻¹, with peak values comparable to commercial hybrids and above-typical yields reported for native Mexican races (2.7–6.6 t ha⁻¹). Proximate analysis showed that milling with the tunic increased moisture/ash (up to 3.07% vs. 1.80% in dehulled grain), tended to lower fat and protein, and yielded lower crude fiber than dehulled samples (0.78–0.96% vs. 1.59–1.77%); protein varied widely (1.05–6.64%). Thus, the tunic modulates elemental composition, informing processing choices (with vs. without tunic). Our results document a spectrum of morphotypes and highlight developmental diversity and field adaptability. The observed accession × environment responses provide a practical baseline for comparisons with native and improved varieties, and help guide product development strategies. Collectively, these data underscore the high productive potential of pod corn (up to 10.78 t ha⁻¹ under optimal management) and show that including the tunic substantially alters proximate composition, establishing a quantitative foundation for genetic improvement and food applications. Overall, pod corn’s distinctive ear morphology and context-dependent composition reinforce its value for conservation, developmental genetics, and low-input systems. Full article

Due to complex underwater environments characterized by severe scattering, absorption, and color distortion, accurate restoration remains challenging. This paper proposes a hybrid approach combining dual transmission estimation, adaptive ambient light estimation with color correction, and a U-Net Transformer (Uformer) for underwater image enhancement. Our method estimates transmission maps by integrating boundary constraints and local contrast, which effectively address visibility degradation. An adaptive ambient light estimation and color correction strategy are further developed to correct color distortion robustly. Subsequently, a Uformer network enhances the restored image by capturing global and local contextual features effectively. Experiments conducted on publicly available underwater image datasets validate our approach. Performance is quantitatively evaluated using widely adopted non-reference image quality metrics, especially Underwater Image Quality Measure (UIQM) and Underwater Color Image Quality Evaluation (UCIQE). The results demonstrate that our proposed method achieves superior enhancement performance over several state-of-the-art methods. Full article

Long bone formation in vertebrates proceeds via endochondral ossification, a sequential process that begins with mesenchymal condensation, advances through cartilage anlage formation, and culminates in its replacement by mineralized bone. Recent advances in inducible lineage tracing and single-cell genomics have revealed that, rather than being a uniform event, mesenchymal condensation rapidly segregates into progenitor pools with distinct fates. Centrally located Sox9⁺/Fgfr3⁺ chondroprogenitors expand into the growth plate and metaphyseal stroma, peripheral Hes1⁺ boundary cells refine condensation via asymmetric division, and outer-layer Dlx5⁺ perichondrial cells generate the bone collar and cortical bone. Concurrently, dorsoventral polarity established by Wnt7a–Lmx1b and En1 ensures that dorsal progenitors retain positional identity throughout development. These lineage divergences integrate with signaling networks, including the Ihh–PTHrP, FGF, BMPs, and WNT/β-catenin networks, which impose temporal control over chondrocyte proliferation, hypertrophy, and vascular invasion. Perturbations in these programs, exemplified by mutations in Fgfr3, Sox9, and Dlx5, underlie region-specific skeletal dysplasias, such as achondroplasia, campomelic dysplasia, and split-hand/foot malformation, demonstrating the lasting impacts of embryonic patterning errors. Based on these insights, regenerative strategies are increasingly drawing upon developmental principles, with organoid cultures recapitulating ossification centers, biomimetic hydrogels engineered for spatiotemporal morphogen delivery, and stem cell- or exosome-based therapies harnessing developmental microRNA networks. By bridging developmental biology with biomaterials science, these approaches provide both a roadmap to unravel skeletal disorders and a blueprint for next-generation therapies to reconstruct functional bones with the precision of the embryonic blueprint. Full article

Accurate perception of dynamic carbon intensity is a prerequisite for low-carbon demand-side response. However, traditional grid-average carbon factors lack the spatio-temporal granularity required for real-time regulation. To address this, this paper proposes a “Prediction-Optimization” closed-loop framework for electric vehicle (EV) fleets. First, a hybrid forecasting model (VMD-BSLO-CTL) is constructed. By integrating Variational Mode Decomposition (VMD) with a CNN-Transformer-LSTM network optimized by the Blood-Sucking Leech Optimizer (BSLO), the model effectively captures multi-scale features. Validation on the UK National Grid dataset demonstrates its superior robustness against prediction horizon extension compared to state-of-the-art baselines. Second, a multi-objective Model Predictive Control (MPC) strategy is developed to guide EV charging. Applied to a real-world station-level scenario, the strategy navigates the trade-offs between user economy and grid stability. Simulation results show that the proposed framework simultaneously reduces economic costs by 4.17% and carbon emissions by 8.82%, while lowering the peak-valley difference by 6.46% and load variance by 11.34%. Finally, a cloud-edge collaborative deployment scheme indicates the engineering potential of the proposed approach for next-generation low-carbon energy management. Full article

Whole-genome sequencing is a powerful approach for exploring genomic diversity in livestock species. Chickens (Gallus gallus) are an important food source worldwide, and in Taiwan, poultry production contributes substantially to the livestock industry. Taiwan’s commercial red- and black-feathered country chickens dominate this category and play a crucial role in local poultry production. However, fundamental genomic information on their population structure remains limited. To address this gap, this study generated whole-genome sequencing data from red-feathered country chickens originating from four major breeding farms. Genetic diversity analyses revealed uniformly low genetic diversity across all farms. Runs of homozygosity (ROH) analyses indicated predominantly historical inbreeding, with farm-specific differences in recent inbreeding patterns. Population structure analyses revealed clear clustering of individuals according to farm origin, indicating distinct line structures among breeding farms. These results provide the first comprehensive genomic overview of Taiwan’s commercial red-feather country chickens and offer valuable reference information for future breeding strategies and the development of new lines. Full article