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Design of a fault‑tolerant‑metric‑aware, reversible n‑bit quantum arithmetic logic unit using IBM Qiskit
Association between serum 25-hydroxyvitamin D levels and Early Vascular Aging in young and middle-aged adults
Background Cardiovascular disease (CVD) remains the leading cause of mortality and morbidity worldwide. Early vascular aging (EVA) is an independent predictor of cardiovascular risk in young and middle-aged adults. The plausible association between EVA and vitamin D warrants further investigation. Methods This study examined the relationship between serum 25-hydroxyvitamin D [25(OH)D] levels and EVA in young and middle-aged healthy adults.This cross-sectional study included 2047 eligible participants who underwent physical examinations at the Health Management Center of the Affiliated Hospital of Qingdao University between May 2023 and May 2025. Participants were categorized into EVA group (n = 687) and control group (n = 1360) based on brachial ankle pulse wave velocity (baPWV). Logistic regression and restricted cubic splines assessed the association between 25(OH)D and EVA, with an inflection point identified using two-piecewise linear regression. Subgroup analyses and interaction tests were conducted by age, sex, blood collection month, smoking status, alcohol drinking status, hypertension, diabetes, and body mass index (BMI). Results The prevalence of EVA was 33.56%. Each 10 ng/mL increase in 25(OH)D was associated with a 19% decrease in the likelihood of EVA (OR = 0.81, 95% CI: 0.70–0.94, P = 0.008).Compared with Q1, Q4 had a significantly lower risk (OR = 0.55, 95% CI: 0.40–0.76, P < 0.001), while Q2 and Q3 did not differ (both P > 0.05). Restricted cubic spline analysis showed a nonlinear L-shaped association (P for non linearity = 0.015) with a threshold at 17.90 ng/mL: below this level, higher 25(OH)D was linked to a lower EVA risk (OR=0.90，95%CI: 0.85–0.96), whereas no significant association was observed above it. Subgroup analyses indicated a particularly significant inverse association between 25(OH)D levels and EVA in men and overweight/obese individuals. Significant interactions were observed for sex, BMI, and age (all P < 0.05), while interactions with other factors, such as blood collection month, hypertension, diabetes, smoking status, drinking status were not statistically significant. Conclusion This study suggests an inverse association between 25(OH)D levels and EVA, with a more pronounced association possibly observed in men and individuals with overweight/obesity, and further indicates a threshold at 17.9 ng/mL below which this inverse association is significantly enhanced.
Enhancing image retrieval via Siamese network-based hashing with gated residual connections
Relationship between lightning and ice hydrometeors in thunderstorms over northern India from polarimetric weather radar observations
Abstract In this study we have investigated the relationship between lightning and ice-hydrometeors for thunderstorms over norther India. we have implemented a hydrometeor identification (HID) algorithm on a C-band polarimetric Doppler Weather Radar (DWR) data to get information on the ice-hydrometeors and utilized lightning flash data of both cloud-to-ground (CG) and intracloud (IC) type lightnings, from Indian Lightning Location Network (ILLN). Seven prominent thunderstorm events, comprising a total of 385 radar volume scans, have been used in this study. The study reveals a good spatial association between graupel and lightning flashes. Time evolution of ice-hydrometeors and lightning flashes during thunderstorms are in tandem. It is revealed that, decrease in cloud-top brightness temperature (from INSAT-3DR satellite) precedes lightning occurrence by more than an hour. Event-wise correlations between ice hydrometeor related parameters and lightning flash rates show higher values for IC than CG flashes, but less correlations when all the data are pooled across events, signifying higher inter-storm variability in the relationship for IC. Graupel Count (GC), i.e., the number of radar grid points identified as graupel, showed the highest pooled correlation coefficient value of 0.87 for CG lightning. For IC lightning also, GC has the highest correlation coefficient value (0.74). The pooled correlations are higher for CG lightning for all ice-hydrometeor parameters. The findings support the non-inductive collision mechanism of thunderstorm charging. Lag-correlation analysis (up to 60 min of lag) has been performed. Lag correlation coefficient values greater than 0.65 (for CG lightning at 30 min of lag) in case of certain ice-hydrometeor parameters, strongly indicate that they are potential precursors for lightning and could be used for nowcasting of lightning.
A blockchain-enabled scalable and secure architecture for cloud big data storage using sharding and swarming
The CAPTCHA protocol
Phenomenological study of the lived experiences of pregnant women following the diagnosis of fetal abnormalities in the second half of pregnancy
Directionally factorized light field reconstruction with cross-epipolar and spatial modeling
Antibacterial and anticancer properties of Streptomyces microflavus BA2 isolated from brackish waters
Abstract The increasing incidence of cancer and the rapid emergence of antibiotic-resistant pathogens represent two of the greatest global health threats and necessitate safe, multifunctional agents. In the present study, the brackish water actinomycete Streptomyces microflavus BA2 was isolated from sediments of Lake Burullus (Egypt). Morphological and molecular analyses, including 16 S rRNA sequencing, confirmed its membership in the family Streptomycetaceae with 100% agreement to S. microflavus NRRL B-2156. The culture filtrate showed potent antibacterial activity against Staphylococcus aureus , Klebsiella pneumoniae , Proteus mirabilis , Salmonella typhi and Escherichia coli , with the aqueous diethyl ether fraction exhibiting the highest inhibition. GC-MS analyses identified seven bioactive compounds, including five fatty acids with antibacterial and anticancer properties, as well as phenolic derivatives. The diethyl ether extract showed moderate antitumor activity against HepG-2 liver cancer cells (IC₅₀ = 189.66 µg/ml), moderate antioxidant potential (IC₅₀ = 74.15 ± 3.27 mg/ml), and safe to moderate toxicity to normal WI-38 lung fibroblasts. These results underscore the high biomedical potential of S. microflavus BA2 as a promising source of natural agents for combating cancer and antibiotic resistance.
MultiTask learning AI system to assist BCC diagnosis with dual explanation
Abstract Basal cell carcinoma (BCC) accounts for 75% of all skin cancers. Currently, all major public hospitals in Spain have a dermatology care protocol that includes teledermatology. This has created an overload for hospital dermatologists, which could be alleviated with an AI tool for prioritization. Several AI systems have been proposed for this purpose, but the lack of transparent diagnostic explanations limits their clinical acceptance and implementation. This fact motivates the present study, which aims to develop an AI tool focused on detecting BCC from dermoscopic images incorporating dermatologist diagnostic criteria to enhance reliability. Specifically, the BCC diagnostic criterium is that a lesion is not considered BCC if it exhibits pigment network pattern, and that a lesion is considered BCC if it exhibits at least one of these BCC patterns: ulceration, ovoid nest, multi globules, maple-leaf, spoke wheel, arborizing telangiectasia. We analyzed 1,559 dermoscopic images collected from 60 primary care centers in Andalusia. Four dermatologists annotated the images as exhibiting or not each of the seven possible BCC patterns. As there is no established Ground Truth to determine the BCC patterns present in a lesion, we propose an Expectation-Maximization consensus algorithm to consolidate the multi-rater annotations into a unified standard reference (SR). As an additional novelty, the system incorporates the symbolic reasoning of dermatologists, who base their diagnoses on BCC patterns shown in lesions. To this end, a multitask learning (MTL) system based on MobileNet-V2 was designed. This system can rapidly triage BCC and non-BCC lesions while providing clinical information justifying this classification. This system also provides GradCAM-based maps to dermatologists to improve its reliability and confidence. Three evaluations were performed on the AI system. First, a performance analysis was conducted to evaluate the AI tool’s ability to classify lesions as BCC or non-BCC. In this analysis, the model achieved 90% accuracy (precision=0.90, recall=0.89). The second evaluation analyzed whether the detected patterns agreed with dermoscopic criteria. Notably, at least one clinically relevant BCC pattern was correctly identified in 99% of BCC-positive cases, and the pigment-network negative criterion was met in 95% of non-BCC cases. A comparison of the GradCAM maps with the dermatologist’s manual delineation demonstrated strong colocalization with dermatologist-segmented regions (mean foreground density 0.57 vs. background 0.16), confirming alignment of the visual focus of experts. This work introduces the first clinically validated dual-explanation AI system that combines high-accuracy BCC detection with transparent, pattern-based explanations. This approach closes the critical gap between AI performance and clinical trust in teledermatology, positioning the system for immediate deployment in primary care. Future work will focus on determining the extent to which this dual explanation system improves dermatologists’ confidence.