Search Results (8,496)

Radiographic imaging remains a cornerstone of diagnostic practice. However, accurate interpretation faces challenges from subtle visual signatures, anatomical variability, and inter-observer inconsistency. Conventional deep learning approaches, such as convolutional neural networks and vision transformers, deliver strong predictive performance but often lack anatomical grounding and interpretability, limiting their trustworthiness in imaging applications. To address these challenges, we present SpineNeuroSym, a neuro-geometric imaging framework that unifies geometry-aware learning and symbolic reasoning for explainable medical image analysis. The framework integrates weakly supervised keypoint and region-of-interest discovery, a dual-stream graph–transformer backbone, and a Differentiable Radiographic Geometry Module (dRGM) that computes clinically relevant indices (e.g., slip ratio, disc asymmetry, sacroiliac spacing, and curvature measures). A Neuro-Symbolic Constraint Layer (NSCL) enforces monotonic logic in image-derived predictions, while a Counterfactual Geometry Diffusion (CGD) module generates rare imaging phenotypes and provides diagnostic auditing through counterfactual validation. Evaluated on a comprehensive dataset of 1613 spinal radiographs from Sunpasitthiprasong Hospital encompassing six diagnostic categories—spondylolisthesis (n = 496), infection (n = 322), spondyloarthropathy (n = 275), normal cervical (n = 192), normal thoracic (n = 70), and normal lumbar spine (n = 258)—SpineNeuroSym achieved 89.4% classification accuracy, a macro-F1 of 0.872, and an AUROC of 0.941, outperforming eight state-of-the-art imaging baselines. These results highlight how integrating neuro-geometric modeling, symbolic constraints, and counterfactual validation advances explainable, trustworthy, and reproducible medical imaging AI, establishing a pathway toward transparent image analysis systems. Full article

The green sunfish, Lepomis cyanellus, is a common centrarchid that has been previously reported to harbor several myxosporeans. In May 2022, six L. cyanellus were collected from the Caddo River, Montgomery County, Arkansas, USA, and had their gills, gall bladders, urinary bladders, fins, integument, other major organs, and musculature examined for myxosporeans. A single individual was found to harbor a new species of Myxobolus infecting the soft dorsal fin. A qualitative and quantitative morphological description was based on fresh plasmodia and myxospores. Elliptoid to obovoid myxospores of Myxobolus picassoi sp. n. are asymmetrical, 12.2 µm long × 9.1 µm wide, with two broadly pyriform to broadly ovoid subequal polar capsules. Molecular data consisted of a 2042 base pair sequence of the partial small subunit rRNA gene (SSU). Phylogenetic analysis revealed that M. picassoi sp. n. is a member of a clade of myxosporean species that predominately infect centrarchid sunfishes from North America. This is the fifth report of a Myxobolus from L. cyanellus, but the first report of a species infecting the soft dorsal fin. This article was registered in the Official Register of Zoological Nomenclature (ZooBank) as urn:lsid:zoobank.org:pub:146D21D1-E416-41C7-A1F6-8AB2AC6D9260. Full article

This study examines clinician interactions with a Knowledge Graph (KG)-enhanced Large Language Model (LLM) for diagnostic support, with an emphasis on the rare condition pseudohypoparathyroidism (PHP). Ten medical professionals engaged with simulated diagnostic scenarios, using the KG-enhanced LLM to support reasoning and validate differential diagnoses. Evaluation included basic model performance (RAGAS = 0.85; F1 = 0.79) and clinician-centered outcomes, such as diagnostic conclusions, confidence, adherence, and efficiency. Results show the tool was most valuable for rare or uncertain cases, increasing clinician confidence and supporting reasoning, while familiar cases elicited selective adoption with minimal AI engagement. Participant feedback indicated generally high usability, accuracy, and relevance, with most reporting improved efficiency and trust. Statistical analysis confirmed that AI assistance significantly reduced time-to-diagnosis ($t\left(8\right)=4.99$, $p=0.001$, Cohen’s $d_z=1.66$, 95% CI [73.8, 197.2]; Wilcoxon $W=0.0$, $p=0.0039$). These findings suggest that KG-enhanced LLMs can effectively augment clinician judgment in complex cases, serving as reasoning aids or educational tools while preserving clinician control over decision-making. The study emphasizes evaluating AI not only for accuracy, but also for practical utility and integration into real-world clinical workflows. Full article

Generative Adversarial Networks (GANs) have emerged as powerful tools for medical image synthesis and clinical outcome prediction. In ophthalmology, accurate forecasting of Optical Coherence Tomography (OCT) images and best-corrected visual acuity (BCVA) values can significantly enhance patient monitoring and personalized treatment planning. We introduce a multimodal GAN inspired by the StyleGAN architecture, featuring super-resolution modules, a multi-scale patch discriminator, and temporal attention mechanisms. To predict logMAR values, a hybrid deep–shallow LSTM model was jointly trained alongside the image pipeline. Synthesized scans were processed through an EfficientNet-based classifier to predict 16 retinal biomarkers. To ensure subject independence, we employed a 3-fold patient-level cross-validation strategy. The proposed multimodal GAN achieved an SSIM of 0.9264, an FID of 11.9, and a PSNR of 38.1 dB for OCT forecasting. The logMAR module delivered an MAE of 0.052, while the biomarker classifier attained a macro-F1 score of 0.81. Based on logMAR change forecasting, patients were further categorized into Winner, Stabilizer, and Loser outcome groups using a threshold of $\Delta =0.05$, achieving an overall F1 score of 0.84. Our approach effectively forecasts retinal morphology and functional outcomes, providing valuable predictive insights for proactive clinical decision-making in retinal health management. Full article

Aim: This study compared the effects of standard evening smartphone restriction with an adapted intervention combining progressive restriction, psychoeducational guidance, and pre-sleep relaxation on sleep, psychological state, cognitive performance, and physical performance in physically active physical education students with moderate-to-high nomophobia. Methods: Thirty participants (age 21.9 ± 1.2 years; intermediate chronotype) completed a randomized controlled trial consisting of a 7-day baseline period, a 14-day intervention phase, and post-intervention assessments. The standard group (n = 15) implemented a 2-h pre-bedtime smartphone restriction combined with general sleep hygiene guidance. The adapted group (n = 15) followed a progressive restriction protocol (30→60→120 min) supplemented with psychoeducational guidance targeting smartphone-related anxiety and a nightly slow-paced breathing routine. Objective sleep parameters were quantified using wrist-worn actigraphy. Subjective sleep quality, pre-sleep anxiety, and stress were assessed using visual analog scales. Cognitive performance (psychomotor vigilance task and choice reaction time) and physical performance (vertical jumps and agility) were evaluated at both morning and afternoon time points. Results: The adapted intervention produced significantly greater improvements in sleep efficiency (time × group: F(1,28) = 6.84, p = 0.014, ηp² = 0.20; d = 0.78) and sleep onset latency (F(1,28) = 5.97, p = 0.021, ηp² = 0.18; d = 0.72) compared with standard restriction. Significant reductions were also observed in pre-sleep anxiety (F(1,28) = 7.12, p = 0.012, ηp² = 0.20; d = 0.81) and stress (F(1,28) = 6.45, p = 0.017, ηp² = 0.19; d = 0.74). Cognitive performance showed significant time × group × time-of-day interactions, with improvements during afternoon assessments in psychomotor vigilance (F(1,28) = 7.48, p = 0.011; d = 0.83) and choice reaction time (F(1,28) = 6.89, p = 0.014; d = 0.79) exclusively in the adapted group. Physical performance outcomes remained stable across interventions. Conclusions: Progressive smartphone restriction combined with psychoeducational strategies and pre-sleep relaxation yields clinically meaningful improvements in sleep continuity, psychological arousal, and afternoon cognitive performance, exceeding the benefits achieved through behavioral restriction alone. Full article

The flowers of Panax ginseng C. A. Mey. (PG) and Panax notoginseng (Burkill) F. H. Chen ex C. H. Chow (PN) are morphologically indistinguishable after drying, leading to prevalent adulteration that compromises product quality and consumer safety. To address this issue, we developed a rapid, closed-tube molecular authentication method based on high-resolution melting (HRM) analysis. Species-specific primer pairs were designed to target the conserved ITS and rbcL-accD regions, with PNG-2 selected as the optimal candidate owing to its stable genotyping performance and moderate GC content. Our results established GC content, rather than amplicon length, as the primary determinant of the melting temperature (Tm). Notably, the experimentally measured Tm values were consistently 0.7–1.5 °C higher than theoretical predictions, a discrepancy attributable to the stabilizing effect of the saturated fluorescent dye. To ensure maximum diagnostic reliability, the HRM results were cross-validated through a three-tier system comprising ITS2 phylogenetic analysis, agarose gel electrophoresis, and Sanger sequencing. The practical utility and matrix robustness of the assay were further verified using a diversified validation cohort of 30 commercial samples, including 24 floral batches and 6 root-derived products (root slices and ultramicro powders). The HRM profiles demonstrated 100% concordance with DNA barcoding results, effectively identifying mislabeled products across different botanical matrices and processing forms. This methodology, which can be completed within 3 h, provides a significantly more cost-effective and rapid alternative to traditional sequencing-based methods for large-scale market surveillance and industrial quality control. Full article

Objective: Based on our previous findings, we designed new molecules by extending functionalized pyrazole derivatives containing iodine atoms, which are linked via an amino bond to halogen-substituted phenyl groups. In addition, these newly developed pyrazole compounds exhibit anti-tumor, antibacterial, and anti-biofilm activities. Methods: Three new series of pyrazole compounds were designed. Fifteen novel pyrazole derivatives, distributed across three series (4a–d, 5a–d, and 6a–g), were synthesized and structurally characterized by ¹H-NMR, ¹³C-NMR, FTIR, UV-Vis spectroscopy, and elemental analysis. Results: Among them, compound 4c, which exhibited notable anti-tumor activity, crystallized in a monoclinic system and was further analyzed via single-crystal X-ray diffraction. All synthesized compounds were evaluated in vitro on NCTC normal fibroblast cells and HEp-2 tumor epithelial cells. Compound 4c demonstrated significant anti-tumor activity while displaying no cytotoxic effects on normal cells. The antibacterial and anti-biofilm activities of the compounds were also assessed against four bacterial strains. Compounds 5a and 5c exhibited the highest antibacterial activity against Staphylococcus aureus ATCC 25923, both with a minimum inhibitory concentration (MIC) of 0.023 μg/mL. Additionally, compounds 4a, 5a, 6a, 6e, and 6f showed the strongest anti-biofilm effects, each presenting a minimum biofilm inhibition concentration (MBIC) of 0.023 μg/mL. ADME and ADMET in silico predictions indicated that all compounds exhibit generally favorable, drug-like physicochemical properties. Conclusions: The study reinforces the applicability of these compounds as promising anticancer, antibacterial, and anti-biofilm drugs. Full article

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne zoonotic pathogen of significant public health concern in South Korea, where human cases continue to occur at high levels; however, information on the molecular epidemiology and genotype diversity of SFTSV in goats—an increasingly important livestock species—remains limited. In this study, blood samples were collected from 750 clinically healthy goats during nationwide surveillance in 2024. Viral RNA was detected by RT-PCR targeting the S and M genomic segments. Epidemiological characteristics were analyzed according to season, region, farm size, breed, and sex. Positive samples were subjected to sequencing and phylogenetic analysis to determine SFTSV genotypes. SFTSV RNA was detected in 10 of 750 goats (1.3%), with significantly higher detection rates in autumn compared with summer, in southern regions compared with northern regions, and in female goats compared with males, while no significant association was observed with farm size or breed. Phylogenetic analysis showed that goat-derived SFTSV strains belonged to genotypes B2, D, and F; notably, genotypes D and F were identified in goats for the first time in South Korea. These findings indicate that goats are exposed to genetically diverse SFTSV strains circulating in tick populations and exhibit epidemiological patterns consistent with tick ecology and human SFTS incidence, supporting the role of goats as incidental or sentinel hosts. Continuous molecular surveillance of goats, integrated with vector monitoring programs, may enhance understanding of regional SFTSV transmission dynamics and facilitate early detection of emerging genotypes with public health implication. Full article

Background: Innovative training strategies aimed at improving physiological efficiency are of growing interest in kinesiology and sports performance. Elevation training masks (ETMs) offer a practical means of inducing hypoxia-like stress. However, evidence of their effectiveness in recreationally active populations remains limited. This pilot study examined the efficiency of a five-week progressive ETM protocol combined with high-intensity interval training (HIIT) in eliciting physiological, hematological, and body-composition adaptations relevant to endurance performance. Methods: Nine recreationally active men completed a five-week intervention consisting of three treadmill-based sessions per week: one weekly incremental Conconi test and two structured aerobic–anaerobic HIIT sessions performed with an ETM. Mask resistance was progressively increased to simulate altitudes of approximately 900–3600 m. Hematological variables (erythrocytes, hemoglobin, hematocrit, erythrocyte indices, leukocytes, and platelets), body composition, maximal heart rate (HRmax), and peripheral oxygen saturation (SpO₂) were assessed pre- and post intervention. Data were analyzed using paired-sample t-tests and repeated-measures ANOVA, with effect sizes reported (Cohen’s d, ω²). Results: A significant main effect of time on SpO₂ was observed (F(1, 8) = 130.61, p < 0.001, ω² = 0.69), along with a significant effect of training week (F(4, 32) = 17.41, p < 0.001, ω² = 0.43), and a significant Time × Week interaction (F(4, 32) = 15.20, p < 0.001, ω² = 0.42), indicating progressively greater post-exercise oxygen desaturation with increasing simulated altitude. Significant post-intervention increases were found in erythrocyte count, hemoglobin concentration, and hematocrit (p ≤ 0.009, d = 1.15–1.55), alongside increases in mean corpuscular volume and mean corpuscular hemoglobin. Platelet count increased significantly (p = 0.001, d = 1.68), while leukocyte values remained unchanged (p > 0.05). Body mass index (p = 0.049, d = 0.77) and body fat percentage (p = 0.012, d = 1.08) decreased following the intervention. HRmax tended to be lower at higher simulated altitudes. Conclusions: A five-week progressive ETM-HIIT protocol efficiently induced hematological and body-composition adaptations associated with improved oxygen transport and metabolic efficiency in recreationally active men. These findings support ETM-based training as an accessible strategy for enhancing physiological efficiency in endurance-oriented kinesiology practice, warranting confirmation in larger randomized controlled studies. Full article

This paper presents a low-power high-precision Discrete-Time Delta–Sigma (DT-DS) analog-to-digital converter (ADC) for a Battery Management System (BMS), which is critical for monitoring key battery parameters such as voltage, current, and temperature. This design employs a second-order Cascade of Integrators FeedForward (CIFF) architecture using a hybrid chopping technique to effectively suppress 1/f noise and offset. Fabricated in a 180 nm Bipolar-CMOS-DMOS (BCD) process, the ADC achieves a peak signal-to-noise ratio (SNR) of 91.2 dB and a peak signal-to-noise-and-distortion ratio (SNDR) of 90.6 dB within a 600 Hz bandwidth, while consuming only 35 µA from a 1.8 V supply. This corresponds to a figure-of-merit (FoM) of 160.4 dB, calculated based on the SNDR, bandwidth, and power dissipation. Full article

Millimeter-wave (mmWave)/terahertz (THz) devices relying on conventional semiconductor technologies face significant performance bottlenecks, constraining their use in next-generation electronic systems. To address these challenges, this work demonstrates high-performance THz Schottky barrier diodes (SBDs) based on aligned carbon nanotube (ACNT) arrays, and the realization of a D-band second-harmonic frequency multiplier. The ACNT-SBDs exhibit superior electrical and radio-frequency (RF) characteristics, achieving a forward current density of 0.14 mA·μm⁻¹ at −1.3 V and an intrinsic cutoff frequency (f_C) of 506 GHz. The developed small-signal model of diodes shows close agreement with measurements, with S-parameter relative errors below 0.7% from 100 MHz to 67 GHz. The implemented 154 GHz D-band multiplier achieved a maximum output power of −18.97 dBm and a minimum conversion loss of 27.92 dB, outperforming previously reported frequency multipliers based on carbon nanotubes or two-dimensional (2D) materials. This study not only establishes the outstanding high-frequency response, nonlinear efficiency, and integration potential of ACNT-based devices but also provides a promising technical pathway for future THz communication and sensing applications. Full article

The continued performance scaling of AI gigafactories requires the development of energy-efficient devices to meet the rapidly growing global demand for AI services. Emerging materials offer promising opportunities to reduce energy consumption in such systems. In this work, we propose an electro-optic microring modulator that exploits a graphene (Gr) and transition-metal dichalcogenide (TMD) interface for phase modulation of data-bit signals. The interface is configured as a capacitor composed of a top Gr layer and a bottom WSe${}_2$ layer, separated by a dielectric Al${}_2$O${}_3$ film. This multilayer stack is integrated onto a silicon (Si) waveguide such that the microring is partially covered, with coverage ratios varying from 10% to 100%. In the design with the lowest power consumption, the device operates at 26.3 GHz and requires an energy of 5.8 fJ/bit under 10% Gr–TMD coverage while occupying an area of only 20 $\mathsf{\mu }$m${}^2$. Moreover, a modulation efficiency of $V_{\pi }L=$ 0.203 V$·$cm and an insertion loss of 6.7 dB are reported for the 10% coverage. The Gr-TMD-based microring modulator can be manufactured with standard fabrication techniques. This work introduces a compact microring modulator designed for dense system integration, supporting high-speed, energy-efficient data modulation and positioning it as a promising solution for sustainable AI gigafactories. Full article

Sweet corn (Zea mays var. saccharata) is a widely cultivated crop valued for its sweet flavor and high nutritional content. Over the past decade, the area devoted to sweet corn grain production has increased substantially, driven by both its nutritional qualities and its economic value. In this context, we aimed to evaluate the impact of three genotypes (Royalty F₁, Hardy F₁ and Deliciosul de Bacau,) under two fertilization types (chemical and organic) compared with a control version on yield, biometrical, biochemical, and quality parameters. This research was carried out between 2022 and 2023 at an experimental station situated in the North-East region of Romania. The results revealed significant influences of cultivar, fertilization method, and the interaction between these two experimental factors on most of the analyzed indicators. Regardless of the fertilization type, the genotype Hardy F₁ showed higher levels of photosynthetic activity, polyphenols (2.22 mg/g d.w.) and sucrose (6.7 g/100 g d.w.), leading to greater yield (13,995 kg/ha) than that of Deliciosul de Bacau and Royalty F₁. Research on fertilization has shown that sweet corn grains under an organic method have higher levels of lycopene, chlorophyll a, chlorophyll b, total phenolic content (TPC), and fructose. In contrast, chemical fertilization more effectively supported growth, photosynthetic activity, yield, and the content of antioxidants and tannins. Regarding the combined influence of these factors, most of the nutritional characteristics of Royalty F1 were enhanced by organic fertilization, whereas those of the Hardy F1 genotype were improved by chemical fertilization. These findings provide practical guidance for selecting appropriate genotype–fertilization combinations to optimize the yield and nutritional quality of sweet corn and highlight key priorities for further research on sustainable fertilization strategies under climate change conditions. Full article

Background/Objectives: Pseudomonas aeruginosa is one of the leading causes of ventilator-associated pneumonia (VAP) and ventilator-associated tracheobronchitis (VAT), with a worldwide spread of difficult-to-treat high-risk clones. This study aimed to investigate the virulence potential and to characterize phenotypic and genotypic antimicrobial resistance (AMR) in P. aeruginosa causing VAP/VAT in the Intensive Care Unit (ICU), University Hospital of Split, Croatia. Methods: The study included P. aeruginosa isolates obtained from ICU patients who met the criteria for VAP or VAT, between January 2023 and January 2024. Isolates were identified using MALDI-TOF MS and tested for antimicrobial susceptibility (AST). A subset of phenotypically multidrug-resistant (MDR) isolates was further analyzed using whole-genome sequencing (WGS) and multilocus sequence typing. Results: A high rate of resistance was detected to ceftazidime (23.4%), imipenem (39.6%), and meropenem (43.8%). WGS confirmed the presence of multiple AMR genes, including the bla_VIM-2 gene, whose genetic environment highlights a complex MDR locus integrating multiple AMR determinants and mobile genetic elements. All tested isolates possessed genes for class C (bla_PDC34, bla_PDC374 or bla_PDC16) and class D (bla_OXA-2, bla_OXA-10 or bla_OXA-50) β-lactamases, fosA, aph(3′)-IIb and crpP genes. Additionally, WGS analysis revealed the presence of numerous virulence genes including those for adherence (Type IV pili and Fap protein production), motility (such as flgF), biofilm formation (e.g., algE and mucE), quorum sensing (lasI, lasR, rhlI and rhlR), exotoxin (toxA and plcH) and exoenzyme activity (exoU, exoT, exoS, exoY, pcrV, hcp1 and lasA). The isolates belonged to four different sequence types: ST235, ST446, the high-risk ST253 and the widely distributed ST395. Phylogenomic comparison demonstrated that the isolates from this study do not originate from a single clonal source, but instead represent multiple globally distributed high-risk P. aeruginosa lineages introduced into the clinical setting. Conclusions: Due to the emergence of high-risk clones with broad AMR and strong virulence potential, ineffectiveness of standard empirical therapy may be anticipated, highlighting the urgent need for new therapeutic approaches (including those targeting major virulence factors). Full article

Orbea is a morphologically diverse lineage within the subtribe Stapeliinae, yet plastome evolution in Arabian taxa remains insufficiently characterized. This study reports the first complete chloroplast genomes of Orbea sprengeri subsp. commutata and O. wissmannii var. eremastrum and investigates plastome structure, sequence variability, and phylogenetic relationships across tribe Ceropegieae. Chloroplast genomes were assembled, annotated, and compared with 13 published plastomes representing major Ceropegieae lineages. Both Arabian plastomes displayed the typical quadripartite structure and identical gene content of 114 unique genes, including 80 protein-coding genes, 30 transfer RNA genes, and four ribosomal RNA genes. However, O. wissmannii var. eremastrum exhibited pronounced structural divergence, possessing the largest plastome recorded for the tribe (170,054 bp), an 8.9 kb expansion of the inverted repeat regions, and an 8.4 kb inversion spanning the ndhG–ndhF region. Comparative analyses revealed conserved gene order across Ceropegieae but identified six highly variable loci (accD, clpP, ndhF, ycf1, psbM–trnD, and rpl32–trnL) as potential DNA barcodes. Selection pressure analyses indicated strong purifying selection across most genes, with localized adaptive signals in accD, ndhE, ycf1, and ycf2. Phylogenomic reconstruction consistently resolved the two Arabian Orbea taxa as a distinct clade separate from the African O. variegata. This study fills a gap in Ceropegieae plastid genomics and underscores the importance of sequencing additional Orbea species to capture the full extent of genomic variation within this diverse genus. Full article