Search Results (3,931)

The adaptive immune system plays a vital role in protecting individuals against invading pathogens primarily through its ability to discern self- versus non-self-antigens. Conditions leading to the breakdown of such immune surveillance can have devastating consequences, one of them being erroneous recognition and immune response against self-antigens, resulting in autoimmunity. Autoimmune diseases (AID) are widespread and span multiple organ systems and cellular functions. Historically, the etiology of AID is multifarious and complex owing to a mix of genetic predisposition and environmental conditions. However, in recent years the study of somatic mutations has gained traction in understanding the basis of AID. Somatic mutations commonly result from elevated DNA damage and inefficient DNA repair and have been linked to cancer. Moreover, the hyper-inflammatory microenvironment is highly conducive to the accumulation of DNA damage in immune cells. Thus, understanding the mutational burden and landscape of somatic mutagenesis in the context of AID can illuminate the basis of disease development and progression. In this review, we summarize past and current research on genome instability in AID, focusing on the nexus between inflammation, immune response, DNA damage, and mutagenesis, and discuss the possible link between AID and cancer development. We provide examples of autoimmune disorders that have been studied from a mutational standpoint and outline results from key studies highlighting the extent of DNA damage and mutagenesis in cells from AID patients. Lastly, we provide our perspective on the key challenges and future directions to understand the role of somatic mutagenesis in autoimmunity and cancer. Full article

The lack of reliable sensory input from prosthetic limbs limits transfemoral amputees’ ability to perceive limb movement without visual monitoring. This study evaluated design parameters of a proposed forearm-based vibrotactile system in a pre-clinical, design-level perceptual evaluation, conveying prosthetic joint positions through patterned vibrations to provide non-invasive proprioceptive feedback. Healthy participants completed two experiments assessing detection of tactile cues from dual-actuator bands on the wrist and elbow representing assumed ankle and knee positions. The effects of temporal structuring (sequential vs. simultaneous stimulation), actuator configuration, amplitude and frequency settings, and signal duration on response accuracy were examined. Sequential vibrations produced significantly higher recognition accuracy than simultaneous presentation (72.4% vs. 42.7%, p < 0.001) in a variety of vibration signal parameter values. Actuator placement also influenced performance: simultaneous stimulation on opposite forearm sides yielded significantly lower accuracy (p < 0.001) than same-side configurations, whereas this directional effect was not significant for sequential presentation. Accuracy did not differ significantly between equal and unequal amplitude or frequency levels across actuators. Longer stimulus durations improved accuracy, increasing from 82.3% at 60 ms to 92.5% at 240 ms, though the results indicated a saturation point, suggesting an optimal temporal window. These findings inform the design of forearm-based sensory feedback systems for improved prosthetic limb control. Full article

Neurodegenerative diseases, such as Parkinson’s and Alzheimer’s, are becoming an increasingly serious challenge for modern medicine because of the significant increase in incidence and the narrow range of effective therapeutic strategies. In recent years, the kynurenine pathway, which is one of the main pathways of tryptophan metabolism, responsible for the synthesis of products that act oppositely in the CNS including neurotoxic (quinolinic acid) and neuroprotective products, has gained increasing recognition as a potential therapeutic target. Abnormalities in the production of these metabolites, causing a disruption of homeostasis in the CNS, often lead to the development of inflammation, which can cause oxidative stress or neuronal death. This paper aims to discuss strategies useful in modulation of the kynurenine pathway, based on increasing the production of neuroprotective metabolites and reducing the synthesis of neurotoxic compounds, as well as to outline the progress in preclinical and clinical studies and the challenges encountered in these studies, among others, in the search for new KP inhibitors. The pharmacological (IDO and KMO inhibitors) and non-pharmacological (physical activity, diet) strategies are discussed, as well as new approaches from combination and targeted therapies. Together with the results of preclinical studies, they demonstrate the high utility of this target in the treatment of neurodegeneration. Despite its promising activity, further key studies are needed to fully understand the mechanisms involved in metabolism, which may translate into increased efficacy of developed therapies in the future. Full article

Background: Rapid and accurate fracture detection is critical in emergency departments (EDs), where high patient volume and time pressure increase the risk of diagnostic error, particularly in radiographic interpretation. Multimodal large language models (LLMs) with image-recognition capability have recently emerged as general-purpose tools for clinical decision support, but their diagnostic performance within routine emergency department imaging workflows in orthopedic trauma remains unclear. Methods: In this retrospective diagnostic accuracy study, we included 1136 consecutive patients referred from the ED to orthopedics between 1 January and 1 June 2025 at a single tertiary center. Given the single-center, retrospective design, the findings should be interpreted as hypothesis-generating and may not be fully generalizable to other institutions. Emergency radiographs and clinical data were processed by a multimodal LLM (2025 version) via an official API using a standardized, deterministic prompt. The model’s outputs (“Fracture present”, “No fracture”, or “Uncertain”) were compared with final diagnoses established by blinded orthopedic specialists, which served as the reference standard. Diagnostic agreement was analyzed using Cohen’s kappa (κ), sensitivity, specificity, accuracy, and 95% confidence intervals (CIs). False-negative (FN) cases were defined as instances where the LLM reported “no acute fracture” but the specialist identified a fracture. The evaluated system is a general-purpose multimodal LLM and was not trained specifically on orthopedic radiographs. Results: Overall, the LLM showed good diagnostic agreement with orthopedic specialists, with concordant results in 808 of 1136 patients (71.1%; κ = 0.634; 95% CI: 68.4–73.7). The model achieved balanced performance with sensitivity of 76.9% and specificity of 66.8%. The highest agreement was observed in knee trauma (91.7%), followed by wrist (78.8%) and hand (69.6%). False-negative cases accounted for 184 patients (16.2% of the total cohort), representing 32.4% of all LLM-negative assessments. Most FN fractures were non-displaced (82.6%), and 17.4% of FN cases required surgical treatment. Ankle and foot regions showed the highest FN rates (30.4% and 17.4%, respectively), reflecting the anatomical and radiographic complexity of these areas. Positive predictive value (PPV) and negative predictive value (NPV) were 69.4% and 74.5%, respectively, with likelihood ratios indicating moderate shifts in post-test probability. Conclusions: In an emergency department-to-orthopedics consultation cohort reflecting routine clinical workflow, a multimodal LLM demonstrated moderate-to-good diagnostic agreement with orthopedic specialists, broadly within the range reported in prior fracture-detection AI studies; however, these comparisons are indirect because model architectures, training strategies, datasets, and endpoints differ across studies. However, its limited ability to detect non-displaced fractures—especially in anatomically complex regions like the ankle and foot—carries direct patient safety implications and confirms that specialist review remains indispensable. At present, such models may be explored as hypothesis-generating triage or decision-support tools, with mandatory specialist confirmation, rather than as standalone diagnostic systems. Prospective, multi-center studies using high-resolution imaging and anatomically optimized algorithms are needed before routine clinical adoption in emergency care. Full article

Background: Severe lower urinary tract dysfunction (LUTD) in neurologically and anatomically normal children is uncommon and frequently underdiagnosed. When severe, functional voiding disorders may closely mimic obstructive or reflux pathology, leading to diagnostic errors, unnecessary invasive procedures, and potential risk to the upper urinary tract. Case presentation: We present three pediatric cases (aged 3–10 years) referred for recurrent febrile urinary tract infections, incontinence, or acute urinary retention in the absence of neurological or structural abnormalities. Urodynamic evaluation identified three distinct severe functional phenotypes: detrusor overactivity with reduced bladder capacity, poor compliance with detrusor–sphincter dyssynergia and secondary high-grade vesicoureteral reflux (Hinman syndrome), and detrusor underactivity with significant post-void residual volumes. All patients demonstrated marked bladder wall remodeling on cystoscopy, including trabeculation and pseudopolypoid mucosal changes. Case discussion: Despite similar clinical severity, the cases illustrated substantial functional heterogeneity and differing risks of upper urinary tract involvement. Urodynamic phenotyping proved central to diagnosis, differentiation from structural disease, and treatment planning. Multimodal conservative management—including urotherapy, pelvic floor biofeedback, targeted pharmacologic therapy, and, when indicated, clean intermittent catheterization or antibiotic prophylaxis—led to resolution of recurrent infections and meaningful improvement in bladder function during medium-term follow-up, although symptom recurrence occurred in one patient after treatment withdrawal. Conclusions: These cases highlight the heterogeneity and potential reversibility of severe functional LUTD in otherwise healthy children. Early functional recognition based on urodynamic assessment is essential to avoid misdiagnosis, prevent unnecessary surgical intervention, and protect renal function. Conservative, function-oriented management remains the cornerstone of effective treatment. The findings are discussed in the context of the existing literature on severe non-neurogenic LUTD and Hinman syndrome. Full article

Satellite image recognition increasingly relies on data collected by geographically distributed institutions, but centralizing geospatial imagery is often infeasible due to policy and privacy constraints. Federated learning enables collaborative training, yet standard aggregation (e.g., FedAvg) degrades under strong geographic non-IID shifts, and adding client-level differential privacy (DP) can further reduce utility—especially for rare land-cover classes—due to gradient clipping and injected noise. We propose FL-SPDP, a spatially modulated DP federated framework that leverages coarse spatial priors to reweight and aggregate client updates among geographically related clients, improving robustness to heterogeneity while preserving formal privacy guarantees. Experiments on SEN12MS and BigEarthNet show that FL-SPDP improves accuracy and macro-F1 at a fixed privacy budget ($\epsilon \le 3.5$, $\delta ={10}^{-5}$) and strengthens rare-class performance, demonstrating an effective privacy–utility trade-off for satellite image analysis. Full article

This paper examines the measures available to improve operational energy efficiency from the perspective of onboard crew, the barriers associated with implementing those measures and how crew behaviour can be nudged using incentives. A total of 25 semi-structured interviews and subsequent surveys with 42 onboard crew were carried out to gather qualitative information on two main domains: operational efficiency and incentive schemes. In-depth thematic analysis of interviews showed the central and recurring themes such as stakeholder hierarchy, autonomy and accountability, temporal restrictions, profitability and type of charter. Due to the heterogeneity in interview responses on the topic of incentives, online surveys were conducted. The findings of the study show that whilst speed reduction was seen as the single most important measure to optimise, it was also the most difficult to implement in practice due to several barriers. These include contractual obligations, a complex web of accountability and perverse incentives to increase speed. Other measures such as trim–draft optimisation and auxiliary engine load optimisation have smaller efficiency gains but were found to have more potential for increasing implementation through behavioural changes and encouraged through incentives. Both monetary and non-monetary incentives were perceived to be important and going beyond the status quo of incentivising captains so that rewards are shared equitably amongst the crew. Whilst not generalisable, preliminary findings suggest that there is room to consider alternatives to the current approaches on incentives, which do not take advantage of the importance of acknowledgment and recognition, as well as fostering positive interpersonal relationships. Full article

Humidity sensing is essential in medical fields such as respiratory support, neonatal care, sterilization, and pharmaceutical storage. However, current sensors face limitations, including slow response/recovery, low sensitivity, and poor long-term stability. To address these challenges, we developed borophene-multiwalled carbon nanotube (MWCNT) heterostructures using a stepwise in situ thermal decomposition method. The resulting humidity sensor exhibits an ultrabroad detection range (11–97% RH), ultra-high sensitivity (55,000% at 97% RH), and fast response/recovery times (10.04 s/4.8 s). Through interfacial charge-transfer engineering, the system facilitates rapid electron migration, enhances Schottky barrier modulation, and provides abundant active adsorption sites for water molecules, thereby achieving comprehensive improvement in sensing performance. It also demonstrates excellent selectivity, mechanical flexibility, and operational stability. Notably, the sensor’s sensitivity at 97% RH surpasses that of sensors based on pure borophene or MWCNT by 37–462 times, highlighting the advantages of heterostructure engineering. The multifunctionality of the device suggests its potential in areas beyond conventional sensing, including non-contact voice recognition, skin humidity mapping, and real-time breath monitoring. These results lay a solid foundation for developing borophene-MWCNT heterostructures into a high-performance platform for next-generation medical diagnostics and intelligent health monitoring. Full article

The accurate detection and non-contact weight estimation of zucchini fruits are crucial for automated harvesting systems. This study presents a novel weakly supervised oriented object detection method for zucchini fruit recognition and weight prediction in complex greenhouse environments. Our approach, termed H2RBox-v2-SF, introduces three key enhancements to the original H2RBox-v2 model. First, the Swin Transformer V2 (SwinV2) is adopted as the backbone network to replace 50-layer Residual Networks (ResNet-50), significantly strengthening feature extraction capabilities. Second, the Bi-directional Feature Pyramid Network (BiFPN) is employed instead of the original Feature Pyramid Network (FPN) to achieve more efficient multi-scale feature fusion. Third, the FPDIoU loss is introduced to replace the CircumIoU loss, enhancing the accuracy and efficiency of bounding box regression. Furthermore, we propose a Morphology-based Fruit Weight Estimation (MFWE) algorithm that leverages depth information for non-contact weight estimation. Experimental results demonstrate that the improved model achieves an AP@0.75 of 87.8%, a precision of 69.8%, and a recall of 91.5%, representing improvements of 9.6%, 5.0%, and 4.7% respectively over the original model. Additionally, the weight estimation achieves a mean absolute error (MAE) of 55.05 g, a coefficient of determination ($R^2$) of 0.899, and a root mean square error (RMSE) of 63.59 g. The proposed method achieves high accuracy for ‘Jinghu No. 43’ zucchini fruit detection and weight estimation under greenhouse conditions, offering an effective technical solution for automated zucchini harvesting. Full article

The recent recognition of the Neotropical otter (Lontra annectens) as a distinct species highlights the need to evaluate its genetic status and connectivity across fragmented tropical habitats. We analyzed genetic diversity, population structure, and recent demographic patterns of L. annectens from two contrasting regions in northern Costa Rica—Tortuguero National Park (TNP) and the Sarapiquí River Basin (SRB). Non-invasive fecal and anal-gland secretion samples collected during 2021–2022 were genotyped at ten nuclear DNA microsatellite loci. Genetic diversity was moderate across regions (mean allelic richness [AR] = 3.98–4.03, observed heterozygosity [Ho] = 0.52–0.58), expected heterozygosity [He] = 0.62–0.65) with no significant inter-regional differences. Bayesian clustering, principal component analysis, and pairwise F_ST (0.002) supported a near-panmictic population. Kinship analyses detected localized clusters of related individuals, suggesting weak but non-random structuring, while contemporary migration estimates indicated low-frequency, asymmetric gene flow from SRB to TNP. Bottleneck tests revealed signatures of recent demographic contraction in both regions, particularly in TNP. These findings demonstrate limited yet ongoing connectivity among riverine subpopulations and emphasize that increasing habitat fragmentation could erode this exchange. Maintaining hydrological corridors and monitoring genetically vulnerable subpopulations should be conservation priorities to preserve gene flow and long-term viability of L. annectens in northern Costa Rica. Full article

Background: Salt-sensitive blood pressure (SSBP) represents a prevalent yet underrecognized hypertensive phenotype, in which blood pressure (BP) and volume status are disproportionately influenced by dietary sodium intake. Beyond BP elevation alone, salt sensitivity reflects a convergence of renal sodium handling abnormalities, neurohormonal activation, vascular dysfunction, and inflammatory pathways that link excessive sodium exposure to progressive kidney injury and adverse cardiac remodeling. Given its association with chronic kidney disease (CKD) and the association of heart failure with preserved ejection fraction (HFpEF), improved recognition of SSBP has direct clinical relevance. Objective: This narrative review aims to synthesize current mechanistic and clinical evidence on SSBP, focusing on pathophysiology, cardiorenal interactions, diagnostic challenges, and phenotype-guided therapeutic strategies with practical applicability. Methods: A narrative literature review was conducted using PubMed, Scopus, and Web of Science from inception through January 2026. Experimental, translational, and clinical studies, along with relevant guideline documents, were integrated to provide conceptual and clinical interpretation rather than quantitative analysis. Key Findings: Impaired renal sodium excretion, intrarenal RAAS activation, sympathetic overactivity, endothelial dysfunction, and immune-mediated inflammation contribute to sodium retention, microvascular dysfunction, and fibrotic remodeling across the kidney–heart axis. These pathways are strongly supported by experimental and translational data, but direct interventional clinical validation remains limited for several mechanisms. Clinically, salt-sensitive individuals often exhibit non-dipping BP patterns, albuminuria, salt-induced edema, and a predisposition to HFpEF. Dynamic BP monitoring combined with targeted laboratory assessment improves identification of this phenotype and supports individualized management. Conclusions: Early recognition of SSBP enables targeted interventions beyond uniform sodium restriction. Phenotype-guided strategies integrating lifestyle modification, RAAS blockade, thiazide-like diuretics, mineralocorticoid receptor antagonists, and sodium-glucose co-transporters 2 inhibitors (SGLT2i) may improve cardiorenal outcomes. Emerging precision tools (e.g., wearable blood-pressure sensors, digital sodium tracking technologies, etc.) remain exploratory but may further refine individualized management. Full article

Background/Objectives: Teacher burnout represents a complex cognitive-emotional syndrome characterized by the interplay between mental exhaustion and emotional dysregulation, threatening educational sustainability during crisis periods. This study employed comprehensive behavioral data analysis to investigate burnout syndrome patterns among Greek teachers during the COVID-19 educational crisis, aiming to identify risk factors and resilience patterns through multiple analytical approaches that capture the syndrome’s multidimensional nature. Methods: A cross-sectional study examined primary and secondary school teachers in Western Greece during the autumn of 2021. Stratified random sampling ensured representativeness across school levels, geographic locations, and employment types. Participants completed the Greek-adapted Maslach Burnout Inventory for Educators, which measured emotional exhaustion, depersonalization, and personal accomplishment. Behavioral data analysis integrated traditional statistical methods with advanced pattern recognition techniques, including classification trees for non-linear relationships, association analysis for behavioral patterns, and cluster analysis for profile identification. Results: The majority of teachers experienced high stress with inadequate coping capabilities. Classification analysis achieved high accuracy in predicting burnout severity, identifying emotional exhaustion as the primary predictor. Deputy teachers demonstrated severe cognitive-emotional strain compared to permanent colleagues across all dimensions, with dramatically reduced personal accomplishment and minimal resources. Association analysis revealed that combined low support and high workload more than doubled burnout risk. Three distinct profiles emerged: Resilient teachers, characterized by older age and permanent employment; At-Risk teachers, showing early warning signs; and Burned Out teachers, predominantly young and in precarious employment. Remote teaching, exceeding half of the workload, significantly increased strain. Multiple regression confirmed emotional exhaustion as the dominant syndrome predictor. Conclusions: Behavioral data analysis revealed complex cognitive-emotional patterns constituting burnout syndrome during educational crisis. Employment precarity emerged as the fundamental vulnerability factor, with young deputy teachers facing dramatically higher syndrome probability compared to supported senior permanent teachers. The syndrome manifests through cascading processes where cognitive overload triggers emotional exhaustion, subsequently reducing personal accomplishment. These findings provide an evidence-based framework for early syndrome identification and targeted interventions addressing both cognitive and emotional dimensions of teacher burnout. Full article

This study investigates the genomic basis of immune adaptation in the transparent glass catfish (Kv: Kryptopterus vitreolus), focusing on the loss of the Toll-like receptor 21 (TLR21) gene. Comparative genomic analysis with closely related non-transparent North African catfish (Cg: Clarias gariepinus) revealed 11 TLR genes in the latter, while only 8 TLR genes (KvTLR1, 2, 3, 5, 7, 9, 13, and 20) were retained in the glass catfish, with TLR21 specifically absent. Collinearity analysis confirmed that the genomic region containing TLR21 is conserved across eight siluriform species, with loss exclusively in the glass catfish, supporting its lineage-specific absence. Structural expansion was notable in KvTLR5, KvTLR7, and KvTLR20. Molecular docking indicated that binding stability between CpG oligonucleotides and TLR21 varies significantly, with CpG-B 1681 showing the strongest interaction, which highlights sequence-dependent ligand recognition. Interestingly, absence of the TLR1 gene in another transparent teleost, the X-ray tetra (Pristella maxillaris), suggests that transparent fishes may share an evolutionary trend of lineage-specific TLR gene loss. Together, these findings reveal a distinctive evolutionary trajectory in the innate immune receptor family of transparent fishes and provide new molecular insights into their adaptive immune strategies. These insights will benefit the academic community by improving comparative frameworks for fish innate immunity, and they may inform disease prevention and health management strategies in aquaculture and the ornamental fish trade. Full article

Background: Non-small cell lung carcinoma (NSCLC) is the most prevalent form of lung cancer, and its progression is closely associated with constitutive activation of signal transducer and activator of transcription 3 (STAT3). This study used surface plasmon resonance (SPR) technology to develop a STAT3-targeting recognition system and identify natural STAT3-targeting compounds from the traditional Chinese medicine Psoralea corylifolia and to evaluate their anti-NSCLC activities, with particular attention to reactive oxygen species (ROS) regulation. Methods: The SPR biosensor immobilized with STAT3 was used to screen and enrich STAT3-binding constituents of Psoralea corylifolia, and to determine ligand-STAT3 affinities. Molecular docking was performed to characterize interactions within the STAT3 SH2 domain. Functional effects were assessed in A549 cells using proliferation and scratch migration assays. Antioxidant capacity was evaluated via hydroxyl radical and superoxide anion scavenging assays, and intracellular ROS levels were measured in hydrogen peroxide (H₂O₂)-induced oxidative stress models in human umbilical vein endothelial cells (HUVECs) and A549 cells. Results: SPR analysis showed that psoralen and isopsoralen bind to STAT3, with equilibrium dissociation constants (KD) of 80.92 µM and 28.11 µM, respectively. Molecular docking further confirmed their interaction with the STAT3 SH2 domain. Both compounds inhibited A549 proliferation and reduced migration. Beyond direct STAT3 inhibition, both compounds demonstrated notable free radical scavenging activity. In a H₂O₂-induced oxidative stress model, pretreatment with psoralen or isopsoralen significantly reduced ROS levels in HUVECs, while increasing ROS accumulation in A549 lung cancer cells. Conclusions: This work identifies psoralen and isopsoralen as novel dual-function STAT3 inhibitors that exert anti-NSCLC effects through combined STAT3 suppression and context-dependent ROS modulation, and demonstrates the utility of SPR for screening bioactive natural products. Full article

This study investigates the evolution of public sentiment and discourse surrounding artificial intelligence through a comprehensive multi-method analysis of 28,819 Reddit comments spanning March 2015 to May 2024. Addressing three research questions—(1) what dominant topics characterize AI discourse, (2) how has sentiment changed over time, particularly following ChatGPT 5.2’s release, and (3) what linguistic patterns distinguish positive from negative discourse—we employ 28 distinct analytical techniques to provide validated insights into public AI perception. Methodologically, the study integrates VADER sentiment analysis, Linguistic Inquiry and Word Count (LIWC) analysis with regression validation, dual topic modeling using Latent Dirichlet Allocation and Non-negative Matrix Factorization for cross-validation, four-dimensional tone analysis, named entity recognition, emotion detection, and advanced NLP techniques including sarcasm detection, stance classification, and toxicity analysis. A key methodological contribution is the validation of LIWC categories through linear regression (R² = 0.049, p < 0.001) and logistic regression (61% accuracy), moving beyond the descriptive statistics typical of prior linguistic analyses. Results reveal a pronounced decline in positive sentiment from +0.320 in 2015 to +0.053 in 2024. Contrary to expectations, sentiment decreased following ChatGPT’s November 2022 release, with negative comments increasing from 31.9% to 35.1%—suggesting that direct exposure to powerful AI capabilities intensifies rather than alleviates public concerns. LIWC regression analysis identified negative emotion words (β = −0.083) and positive emotion words (β = +0.063) as the strongest sentiment predictors, confirming that affective rather than technical engagement drives public AI attitudes. Topic modeling revealed nine coherent themes, with facial recognition, algorithmic bias, AI ethics, and social media misinformation emerging as dominant concerns across both LDA and NMF analyses. Network analysis identified regulation as a central hub (degree centrality = 0.929) connecting all major AI concerns, indicating strong public appetite for governance frameworks. These findings contribute to theoretical understandings of technology risk perception, provide practical guidance for AI developers and policymakers, and demonstrate validated computational methods for tracking public opinion toward emerging technologies. Full article