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FRED enables standardized FAIR metadata generation and management for omics research
Abstract Scientific research relies on transparent dissemination of data and its associated interpretations, including raw data, metadata, experimental design, and data processing details. Production and handling of research data represents an ongoing challenge, extending beyond publication into individual facilities, institutes and research groups, often termed Research Data Management (RDM). It is foundational to scientific discovery and aligned with the FAIR principles. Although the majority of peer-reviewed journals require raw data deposition in public repositories in alignment with FAIR principles, metadata frequently lacks standardization, hindering effective utilization and sharing of research findings. Here we present FRED, a generalized toolkit for FAIR metadata management in omics research based on a flexible, machine-readable YAML format. FRED enables (i) guided, dialog-based creation of metadata files, (ii) structured semantic validation, (iii) logical cross-file search, (iv) API-based integration with external systems, and (v) self-hosted web deployment. We demonstrate the utility of FRED through a complete annotation workflow applied to a published single-nucleus RNA-seq dataset, covering metadata generation, validation, repository-based discovery, and export to NCBI GEO submission format. FRED is designed for non-computational scientists and specialized facilities alike, and integrates into existing RDM infrastructure without requiring dedicated IT resources.
Sleep satisfaction and problematic smartphone use among adolescents in the Republic of Korea: The mediating roles of anxiety and loneliness
Problematic smartphone use (PSU) has become a growing public health concern among adolescents, with global prevalence estimates ranging from 10% to 30%. Sleep dissatisfaction has been identified as a potential risk factor for PSU. However, the psychological mechanisms underlying this association remain unclear. This study examined the relationship between sleep satisfaction and PSU among Korean adolescents, and investigated the mediating roles of anxiety and loneliness. Data were collected from 48,829 adolescents who were categorized into three groups: general users (72.1%), potential-risk users (24.8%), and high-risk users (3.1%). Group differences were examined using chi-square tests and one-way analysis of variance (ANOVA). Multivariate logistic regression analyses were conducted to identify the factors associated with PSU risk. Mediation analyses were conducted using a counterfactual framework to estimate the total, natural direct, and natural indirect effects of sleep satisfaction on PSU risk through anxiety and loneliness. Increased PSU risk was significantly associated with being female, high smartphone usage time (≥4 hours/day), and reporting poor perceived health. High-risk users reported markedly longer daily smartphone use (7.01 ± 0.12 hours) and significantly higher anxiety and loneliness scores compared to other groups ( p < .001). Poor sleep satisfaction and insufficient physical activity were also significantly associated with higher PSU risk. Mediation analyses indicated significant natural indirect effects through anxiety and loneliness, with proportions mediated of 30.0% and 15.2%, respectively. Sleep dissatisfaction is significantly associated with problematic smartphone use among adolescents, and this relationship is partly explained by heightened anxiety and loneliness. Interventions aimed at improving sleep satisfaction and addressing emotional vulnerability may be effective strategies for reducing the PSU risk in this population.
Classification of bacterial biological warfare agent simulants through 2D Py-GC/MS data coupled with deep learning
Unspoken cycles: A qualitative study exploring the lived experiences of women’s menstruation in the urban informal settlements of Bangladesh
Background Menstrual health and hygiene (MHH) is a critical component of public health and gender equity. However, limited research has explored the everyday experiences of women and adolescent girls managing menstruation within the constrained environment of urban informal settlements. This study explores the lived experiences of menstruation among women and girls in the Khulna Railway Slum in Bangladesh. Methods Guided by a Feminist Political Ecology framework, this qualitative study employed a combined inductive and deductive thematic approach. Data were collected between September and October 2025 through in-depth interviews with 18 women and adolescent girls aged 15–45 years living in urban informal settlements in Khulna. Five key informant interviews were also conducted with relevant stakeholders. Data were analyzed thematically using both pre-defined conceptual domains and emergent codes. Findings Findings revealed that menstrual experiences are shaped by three interrelated conceptual domains: structural-environmental constraints, socio-cultural stigma, and gendered inequities in access to resources. Inadequate WASH facilities, poor waste management, and lack of affordable menstrual products hinder safe and dignified menstrual practices. Stigma and taboos reinforced shame, exclusion, and silence, while gendered inequalities limited autonomy and resource access, especially among adolescents. Conclusion The study highlights menstruation as a socially and structurally shaped experience influenced by infrastructural constraints, cultural norms, and gendered inequalities. It contributes to scholarship on menstrual health by emphasizing the need to address menstrual inequities as part of broader efforts to improve gender equity and WASH services in urban informal settlement.
Upper extremity muscle thickness, handgrip strength, manual dexterity and cognitive functions in older adults living in community and nursing homes : a cross-sectional study
Abstract This study aims to compare upper extremity muscle thickness, hand grip strength, manual dexterity, and cognitive functions in elderly individuals living in the community and nursing homes. A total of 85 older adults with similar demographic characteristics, aged 65–80 years, 39 living in nursing homes and 46 community-dwelling older adults, were included in a cross-sectional study. Hand grip strength (HGS) was assessed via the Jamar hand dynamometer, and pinch strength was assessed via the Jamar digital pinch gauge. The Purdue Pegboard Test (PPT) was used to assess manual dexterity, and the Stroop T-Bag Test was used to assess cognitive function. In addition, upper extremity muscle thickness was assessed via ultrasonography. The forearm, biceps brachii, triceps brachii and deltoid muscle thicknesses were lower in elderly people living in nursing homes than in adults living in the community (p < 0.05). HGS and pinch strength were greater in adults living in the community than in adults living in nursing homes (p < 0.05). The total PPT score was higher in adults living in the community than in adults living in nursing homes (p < 0.05). The MOCA score and Stroop test composite score of elderly individuals living in nursing homes were worse than those of adults living in the community (p < 0.05). In this study, older adults living in nursing homes were observed to have lower upper extremity muscle thickness, handgrip strength, pinch strength, manual dexterity, and cognitive performance compared with community-dwelling older adults. This may be related to differences in living conditions, social resources, and environmental factors between the two groups. These findings suggest that maintaining upper extremity muscle thickness and strength, manual dexterity, and cognitive functions may be important for older adults living in nursing homes.
Pattern of family dynamics and treatment-seeking behaviour of caregivers of under-five children with uncomplicated malaria in a tertiary hospital in Ilesa, southwestern Nigeria
Background The morbidity and possible consequent mortality resulting from malaria in children are either due to delayed treatment-seeking or preceded by an inappropriate treatment-seeking process. This study aimed to assess the relationship between the pattern of family dynamics and treatment-seeking behaviour of caregivers of under-five children with uncomplicated malaria. Methods This was a hospital-based cross-sectional study that recruited 350 child-caregiver pairs. An interviewer-administered questionnaire was used for data collection, and it was analysed using the Statistical Package for the Social Sciences (SPSS) software version 25. A p-value of < 0.05 was taken as statistically significant. Results The family dynamics of the caregivers revealed that 82.3% of them had strong family support, four-fifths (80.3%) had functional families, and a little over half of them (58.3%) had monthly family incomes that fell below the defined household poverty line. Only 41.7% of the caregivers had appropriate treatment-seeking behaviour. Caregivers from lower-income families had 2.5 times higher odds of exhibiting inappropriate treatment-seeking behaviour compared to those from higher-income families (OR, 2.494; 95% CI, 1.486–4.184; p = 0.001). Caregivers with dysfunctional families were about four times more likely to have inappropriate treatment-seeking behaviour compared to their counterparts with functional families (OR, 3.766; 95% CI, 1.445–9.813, p = 0.007). Conclusion Significant inappropriate treatment-seeking behaviour existed among caregivers of under-five children with uncomplicated malaria. Family factors related to inappropriate treatment-seeking behaviour were family income and family functioning. Strengthening the family and counselling on appropriate treatment-seeking is crucial to reducing malaria morbidity and mortality among under-five children.
A fourier neural operator-based subband-BTE solver for sub-10 nm ultra-scaled devices
FetalADM: a double-layer ensemble model based on SMOTE_KM and RF-RFE for fetal trisomy 21, 18, and 13 detections
Abstract Noninvasive prenatal testing (NIPT), which utilizes high-throughput sequencing technology to analyze cell-free DNA fragments from maternal peripheral plasma, has been widely adopted in clinical practice. However, accurately detecting fetal trisomy remains a challenge. To address this issue, we propose a novel double-layer ensemble model designed for detecting fetal trisomy13, 18 and 21. Firstly, we integrate the Synthetic Minority Oversampling Technique with K-Means clustering to augment positive samples, effectively balancing the training dataset. Subsequently, we implement feature selection algorithms to identify the optimal feature combination. Leveraging these enhancements, we develop a fast and accurate multi-class classification model FetalADM based on machine learning. Evaluate its performance on three independent test datasets: T54, T210, and T136. Notably, on the T54 dataset, FetalADM achieved a perfect 100% accuracy in detecting trisomy 21, 18, and 13. On the T210/T136 dataset, the model misclassified only 2/1 out of 210/136 samples (accuracy = 99.0%/99.3%), respectively, compared to 31/12 misclassifications by traditional bioinformatics methods. Specially, as a four-class classifier, FetalADM enables direct prediction of specific trisomy types, distinguishing itself from most binary-class models while maintaining high efficiency and accuracy. These results demonstrate that it outperforms conventional bioinformatics methods, underscoring its potential to improve the clinical diagnostic accuracy of fetal aneuploidies.
An efficient serialized hardware implementation of the ASCON algorithm
Abstract The era of the Internet of Things (IoT) introduces new technologies alongside challenges in hardware and data transfer security. This work presents the hardware implementation of the Lightweight Cryptography (LWC) algorithm ASCON-128, specifically targeting IoT applications and edge devices with stringent power and area constraints. The proposed design utilizes a serialized hardware architecture that minimizes logic usage, resulting in a compact area and low power consumption. It maintains adequate throughput through a sponge-based construction in authenticated mode. On FPGA, the design operates on the ultra-low-power platform, Lattice iCE40, achieving maximum frequency (Fmax) of 228.8 MHz with only 582 Lookup Tables (LUTs), 418 flip-flops, and 2.28 mW at 13.7 MHz. The Application-Specific Integrated Circuit (ASIC) implementation using 16 nm TSMC FinFET technology achieves a power consumption of 0.254 mW and an area of 1.341 kilo gate-equivalents (kGE), delivering an energy efficiency of 0.106 nJ/bit and a throughput of 2.381 Mbps at 100 MHz. These results highlight the effectiveness of the proposed ASCON-128 architecture for secure, low-power IoT and RFID applications.
The use of cocoa pod shells as a bio-based concrete retarder
Low-level hydrogen co-firing in turkish thermal power plants: thermodynamic, environmental, and economic impacts
Computational exploration of urethane formation in the presence of amine catalysts
Abstract Polyurethanes are highly versatile polymers widely used in industry to produce a broad range of materials. Their synthesis from diisocyanates and polyols under industrial conditions typically requires a catalyst—or a combination of catalysts—which plays a critical role in determining reaction efficiency and selectivity. In this study, we examined a diverse set of amine catalysts to identify key properties relevant to selecting the most suitable species for specific applications. To this end, we evaluated both structural and energetic descriptors, namely steric parameters (expressed as %Vbur) and proton affinities (PA). The results show that 1-(3-aminopropyl)imidazole (APIM) possesses the lowest calculated proton affinity (905.8 kJ mol − 1 ) among the studied compounds, indicating a greater tendency of its conjugate acid to donate a proton. In contrast, steric analysis revealed that tertiary amines generally exhibit higher buried volumes than primary and secondary amines. Notably, the differences in %VBur values between 2,2’-dimorpholinodiethylether (DMDEE) (67.0%), dimethylaminoethylether (DMAEM-1 N*) (66.4%), and N -Ethylmorpholine (NEM*) (65.8%) are relatively small; these values indicate similar steric environments, rather than a strictly greater steric effect for one catalyst over the others. However, given the small numerical differences, these catalysts can be considered to exhibit comparable steric profiles. Overall, this work provides deeper insight into how electronic and steric factors influence urethane formation and offers a rational basis for selecting appropriate catalysts tailored to specific applications.
Relationship between motor reserve, general cognitive functioning and brain atrophy in older adults
Diabetes–TyG interaction and mortality in critical cerebrovascular disease: a retrospective cohort study
Changes in public perceptions of wild boar presence and management in Flanders
A high-performance dataflow-driven 2-D transform architecture for versatile video coding
Validation of portable, semi-dry electrode-based electroencephalography device for its application in brain–computer interface solutions
Abstract In recent years, commercial lightweight electroencephalography (EEG) headsets are gaining popularity in neuroscience. These devices commonly utilize only a few dry electrodes in specific locations and signal quality is often inferior compared to that of their traditional counterparts. In this study, we wanted to assess the feasibility of portable, paste-less, passive electrode-based EEG headset MindRove vision (VSN) for laboratory use. Three paradigms were implemented for acquiring visual evoked potential (VEP), P300 event-related potential and motor execution task (ME) related cortical patterns. Measurements were taken by using VSN, with wet-electrode system mBrainTrain SMARTING applied as reference. The performance of the devices was assessed by using signal-to-noise ratio (SNR) for VEP and P300 while support vector machine, random forest and convolutional neural network-based classifiers were fit to ME data. The SNRdB (i.e. SNR expressed in decibels) of VSN was greater for both VEP and P300, by a margin of 1.998 and 2.845 dB, respectively. There was a significant difference between VEP signal amplitude levels and SNRdB, P300 SNR and SNRdB in favor of VSN. Average accuracy of the sorters were 78.8% for VSN and 80.9% for SMARTING; the difference was not significant. The application of VSN is feasible for use in research besides qualitative exploration.
Correlation between NRS-2002 scores and PD-1/CTLA-4 expression levels in patients with community-acquired pneumonia
Dermoscopy guided high-frequency ultrasound features of basal cell carcinoma subtypes compared with histopathology: a multicenter study
Abstract Accurate non-invasive differentiation of basal cell carcinoma (BCC) subtypes is crucial for guiding treatment; however, current imaging tools have limitations in accessibility, depth resolution, and interpretability. To describe sonographic features of distinct BCC subtypes using dermoscopy-guided high-frequency ultrasound (DG-HFUS), and assess its potential as a non-invasive subtyping modality. In this multicenter cross-sectional study, 87 histologically confirmed BCCs (nodular, superficial, infiltrative, and micronodular) were imaged using a portable 33 MHz DG-HFUS device. Morphological features were evaluated independently by blinded observers, and statistical associations with histologic subtypes were analyzed using univariate logistic regression. Hypoechoic mass was the most common sonographic feature of BCCs, seen in 92% of cases. Distinct DG-HFUS features correlated with specific subtypes: ribbon-like shape (OR = 86.3, p < 0.0001), homogeneous internal echoes (OR = 22.5, p = 0.003), and well-defined margins (OR = 9, p = 0.04) were strongly associated with superficial BCC; oval shape (OR = 3.8, p = 0.003) and prominent hyperechoic spots (OR = 3.5, p = 0.005) with nodular BCC; and acoustic shadowing (OR = 7.5, p = 0.001) with infiltrative BCC. Micronodular BCCs were underrepresented. Mixed subtypes were excluded, and vascular patterns were not evaluated. DG-HFUS reveals subtype-specific sonographic features and offers a promising, accessible, and interpretable tool for non-invasive BCC classification in clinical settings.