Search Results (2,518)

Chronic wound healing disorders are closely associated with microenvironmental imbalance, while traditional dressings fail to meet dynamic therapeutic demands due to limited functionality, poor responsiveness, and lack of controlled drug release. In this study, a smart hydrogel dressing was developed by integrating curcumin/Cu²⁺ co-loaded UiO-66-NH₂ metal–organic frameworks into a dynamically cross-linked oxidized hyaluronic acid/carboxymethyl chitosan (OHA-CMCS) network via Schiff base bonding. The MOFs served as a “one-carrier-dual-function” platform, enabling simultaneous delivery of Cu²⁺ and curcumin. The resulting Cur/Cu-MOF@OHA-CMCS hydrogel exhibited a porous structure, excellent self-healing ability, injectability, and favorable rheological and mechanical properties. Additionally, it showed pH-responsive degradation behavior and sustained drug release (~71% within 7 days). The hydrogel demonstrated effective anti-bacterial activity against both Escherichia coli and Staphylococcus aureus, along with good cytocompatibility (>70% cell viability). These results highlight its potential as a multifunctional and responsive dressing for chronic wound management. Full article

As new energy vehicles and energy storage systems become more common, safety accidents caused by lithium-ion batteries overheating have become more of a concern. Early detection based on distinctive gases (such as H₂ and CO) can give an earlier warning than typical monitoring methods like temperature, voltage, or impedance. Nonetheless, attaining high-precision identification in intricate mixed-gas settings continues to be difficult because of the considerable cross-sensitivity of metal oxide semiconductor (MOS) gas sensors. This research presents an ISA-LSTM-TCN multi-task learning model utilizing an enhanced spatial attention mechanism for the swift identification and concentration forecasting of distinctive gases during lithium-ion battery thermal runaway. The model improves key feature extraction and anti-noise performance by combining the long-term temporal modeling ability of the Long Short-Term Memory (LSTM) network with the multi-scale feature extraction ability of the Temporal Convolutional Network (TCN). It also adds an Improved Spatial Attention (ISA) module with a residual multiplication structure. Moreover, in a multi-task learning framework, joint optimization of gas categorization and concentration regression is facilitated using a hard parameter-sharing method. Tests using a built MOS sensor array dataset show that the model is 99.23% accurate at classifying gases and that the $R^2$ values for predicting H₂ and CO concentrations are 0.9510 and 0.8400, respectively. Tests on public datasets and in different noisy environments show that the model is even better at generalizing and is more robust. The results show that the suggested method allows for quick, accurate detection of thermal runaway gases. This makes it an effective and smart way to monitor battery safety warning systems. Full article

Phyllanthus emblica L. is a nutraceutically important medicinal plant; however, the relationship between genetic variation and bioactive potential remains poorly understood. This study integrates genome-wide SNP analysis, phytochemical profiling, and functional bioassays to investigate cross-scale differentiation among fourteen cultivars. Genotyping-by-sequencing (GBS) identified 5644 high-quality SNPs from an initial dataset of 9018 SNPs, revealing moderate but structured genomic divergence (0.0275–0.0845). Phytochemical analysis of five commercial cultivars demonstrated significant variation (p < 0.05) in total phenolic content (6.58–15.53 mg GAE/gDW) and tannin content (284.52–333.81 mg TAE/gDW). Functional assays revealed strong anti-obesity potential, with crude extracts exhibiting superior α-glucosidase inhibition (up to 98.75%), while tannin-enriched extracts showed enhanced pancreatic lipase inhibition (up to 46.26%). Importantly, enzyme inhibition did not correlate directly with total phenolic or tannin content, indicating compound-specific bioactivity. LC-MS/QTOF analysis identified flavonoids (e.g., quercetin and kaempferol), phenolic acids, and other candidate metabolites potentially associated with enzyme inhibitory activity. These findings demonstrate a non-proportional association among genomic variation, metabolite composition, and functional bioactivity, suggesting that bioactivity may be influenced more strongly by compound-specific metabolite composition than by genome-wide similarity alone. Full article

Background: Recurrent pregnancy loss (RPL) remains etiologically unexplained in 40–50% of cases following standard diagnostic workup. Non-criteria antiphospholipid antibodies (non-criteria aPL) are increasingly considered potential markers of seronegative obstetric antiphospholipid syndrome (APS); however, their diagnostic value in this clinical setting requires further investigation. Objective: To assess the diagnostic value of non-criteria aPL in women with RPL and to construct an exploratory immunological scoring model for diagnostic stratification. Methods: Antiphospholipid antibody detection was performed using a single-measurement semi-quantitative line immunoblot assay (Anti-Phospholipid 10 Dot, Generic Assays, Germany). Statistical analysis included χ², Fisher’s exact test, Mann–Whitney U test, binary logistic regression, and ROC analysis. Results: Statistically significant associations with RPL were observed for anti-prothrombin antibodies (OR = 11.1; 95% CI 1.8–68.0; p = 0.022 [Haldane–Anscombe correction]), anti-annexin V (OR = 4.28; 95% CI 1.18–15.6; p = 0.023), and anti-β₂GP I (OR = 3.31; 95% CI 1.18–9.28; p = 0.019). The exploratory composite immunological score demonstrated moderate discriminatory performance (AUC = 0.701; 95% CI 0.588–0.814; p = 0.005). The overall logistic regression model was statistically significant (χ² = 8.564; p = 0.036), although none of the individual predictors retained independent significance, indicating a contribution of cumulative immunological burden rather than any single marker. Conclusions: In this single-center cross-sectional study, non-criteria aPL were frequently detected in women with RPL and were statistically associated with the condition. The findings should be interpreted as hypothesis-generating only, given the cross-sectional design, single-measurement immunoblot, small control group, and absence of external validation. Confirmation in larger prospective multicenter cohorts using ELISA-based assays with the internationally recommended 12-week repeat measurement is required before any clinical implementation. Full article

Background: Hepatitis A (HA) and E (HE) represent a significant global health burden. Despite the development of effective vaccines against hepatitis A virus (HAV) and hepatitis E virus (HEV), outbreaks of acute HA and HE continue to occur worldwide. This study aimed to assess the seroprevalence of anti-HAV and anti-HEV IgG antibodies (Abs) in the population of Belgrade and to analyze their association with socio-demographic and clinical factors. Materials and Methods: A cross-sectional study was conducted on a sample of 2533 healthy volunteers in Serbia in May 2024. Participation was voluntary and web-based, leading to an overrepresentation of women and middle-aged adults, while children were underrepresented. Due to this non-probabilistic recruitment, the absolute seroprevalence estimates have limited generalizability to the entire population of Belgrade. Serum samples were tested for anti-HAV and anti-HEV IgG using commercial ELISA kits. The anti-HEV estimate is based on a single ELISA without confirmatory testing and should be interpreted with this limitation in mind. Statistical analysis included confidence interval estimation, chi-square tests, and Spearman’s correlation. Results: Overall seroprevalence was 20.5% (95% CI: 18.9–22.1) for anti-HAV and 22.6% (95% CI: 21.0–24.3) for anti-HEV. A strong, non-linear increase in anti-HAV seroprevalence with age was observed, rising sharply from 2.8% in the 18–29 group to 78.3% in those aged 70+. Anti-HEV seroprevalence also featured a significant positive correlation with age (rs = 0.99, p < 0.0001), increasing from 4.2% in children (1–17 years) to 49.2% in the 70+ group. Men had significantly higher anti-HAV seroprevalence than women (23.1% vs. 19.3%, p = 0.029). Individuals with a history of surgical interventions or blood transfusions had significantly higher odds of being anti-HEV positive (OR = 1.41, p = 0.0005). Vaccination coverage against HAV was low (1.8%), and Abs were detected in only 28.6% of vaccinated individuals. Conclusions: This study suggests high HEV seroprevalence and an age-polarized HAV seroprevalence in Serbia, indicating a significant shift in the epidemiological landscape while acknowledging the sampling and assay limitations stated above. The findings underscore a growing population susceptible to HAV and highlight the need for reinforced vaccination strategies, improved diagnostics, and targeted public health interventions. Full article

Aiming at the challenges of class imbalance, tiny defect scales, and complex brushed background interference in the surface defect detection of electrical commutators, this paper proposes a high-precision and lightweight improved instance segmentation algorithm named WG-YOLOv11. Firstly, to overcome the barrier of highly imbalanced positive and negative samples in actual industrial data collection, a Balanced Defect Synthesis (BDS) data augmentation strategy is introduced to effectively enrich the morphological diversity of tiny defects. Secondly, a Wavelet Transform Convolution (WTConv) module is collaboratively integrated into the feature extraction network to expand the receptive field while preserving the high-frequency edge details of hairline cracks. Thirdly, a Group CBAM Enhancer (GCE) module is introduced to filter out high-reflection and brushed background noise through grouped attention and weight re-calibration mechanisms. Finally, addressing the difficulty of pixel-level alignment for tiny defects, an $\alpha$-IoU loss function is utilized to improve the high-precision segmentation and localization capabilities by dynamically adjusting the gradient distribution. Comprehensive evaluations are conducted on two real-world electrical commutator surface defect datasets: KolektorSDD2 and KolektorSDD. Experimental results show that on the KolektorSDD2 dataset, compared to the YOLOv11 baseline, the Mask mAP@50 of WG-YOLOv11 increases from 85.2% to 89.2%, and the stringent metric Mask mAP@50:95 improves from 52.7% to 56.9%. Additional computational analysis on the same dataset validates that the proposed method maintains high efficiency, matching the baseline computational cost without compromising real-time inference speed. Furthermore, evaluations on the public MSD dataset confirm the model’s cross-domain generalization capabilities. The proposed framework effectively achieves a balance between detection accuracy, anti-interference robustness, and a lightweight architecture. Full article

Introduction: Chronic non-specific neck pain (CNSNP) is a prevalent condition where active myofascial trigger points (A-MTrPs) are commonly detected in cervical muscles and may be associated with altered electromyographic activity (EMGact). However, their association with EMGact during functional tasks remains unclear. Objectives: This study aimed to explore this relationship, hypothesizing that A-MTrPs in cervical muscles would be associated with altered EMGact. Methods: An analytical cross-sectional exploratory study was conducted in 52 patients with CNSNP. Surface EMGact of the sternocleidomastoid (SCM), anterior scalene (AS), and upper trapezius (UT) muscles was recorded during the craniocervical flexion test (CCFT) and an isometric shoulder abduction task (ABD-90). Linear mixed-effects models were constructed to identify factors associated with EMGact. Age, pain intensity, pain duration, analgesic dose, anti-inflammatory dose, and kinesiophobia score were included as covariates, while gender, physical activity level, and the presence or absence of A-MTrPs were included as categorical factors. Results: At the 22 mmHg CCFT level, analgesic consumption was positively associated with peak EMGact and average AS activation (B = 0.791 and B = 0.223, respectively) and with SCM peak EMG act (B = 0.510). At the same level, kinesiophobia was associated with average SCM EMGact (B = 0.231). At the 26 mmHg CCFT level, average AS activation remained positively associated with analgesic consumption (B = 0.148) and SCM without A-MTrPs was associated with lower EMGact compared to SCM with A-MTrPs. At the 30 mmHg CCFT level, kinesiophobia was negatively associated with average EMGact of AS. In the UT muscle, during ABD-90, kinesiophobia was negatively associated with both peak (B = −0.378) and average EMGact (B = −0.132). Conclusions: The presence of A-MTrPs may be related to SCM EMGact during CCFT in individuals with CNSNP, while analgesic consumption and kinesiophobia also could be associated with cervical muscles EMGact during functional tasks. Full article

The acetic acid corrosion resistance of silver electrodes is critical for ensuring photovoltaic (PV) module reliability. Ethylene-vinyl acetate (EVA) is the most widely used encapsulant material in photovoltaic modules. Under exposure to light, heat, and moisture, EVA decomposes to generate acetic acid, which corrodes the silver electrodes, leading to energy conversion efficiency degradation of the module. To address this problem, the lead-free paste was formulated and evaluated in this paper to improve the anti-acetic acid performance. The contact resistivity of the front and the rear side of the solar cells have been measured before and after acetic acid exposure, and greater degradation is shown in the front electrode than in the rear side. Furthermore, the lead-free paste demonstrates lower efficiency degradation compared to the lead-containing paste after acetic acid exposure. In addition, top-view and cross-sectional scanning electron microscopy was performed to analyze the mechanism of the acetic acid corrosion resistance, in which the silver acetate particles were observed. Our experimental results demonstrate that the lead-free paste exhibits superior acetic acid corrosion resistance, which is due to its higher glass acidity and the absence of lead oxide that causes enhanced chemical reactivity with acetic acid. Based on these findings, the acetic acid corrosion model is proposed to attribute the conversion efficiency degradation of reactions between acetic acid and silver, as well as the glass of the silver electrodes. Full article

Background: Traumatic brain injury (TBI) affects millions of individuals annually and remains a major global cause of neurological disability and death. Tau protein hyperphosphorylation, particularly in its cis conformation, is a major pathological hallmark contributing to neurodegeneration following TBI. Single-chain variable fragments (scFvs), despite their diagnostic potential, suffer from rapid renal clearance and short circulation half-lives, which limit their in vivo performance. PEGylation is therefore employed to prolong systemic circulation and improve the pharmacokinetic behavior of scFvs, enabling more effective brain retention and target engagement. Methods: In this study, we utilized a previously validated anti-cis p-tau scFv antibody fragment, radiolabeled with technetium-99m tricarbonyl (^99mTc(CO)₃), as a diagnostic tracer to detect tau pathology in TBI rat models. The antibody was conjugated with polyethylene glycol (PEG, 20 kDa); PEGylation efficiency was determined by quantifying the products on SDS-PAGE, and the products were subsequently radiolabeled. Results: Radiochemical purity (RCP) was ~95.4% for the non-PEGylated tracer (^99mTc-AININ20) and ~92.7% for the PEGylated form (^99mTc-AININ20-PEG), with both showing >90% radiochemical purity consistently. Upon systemic administration, PEGylated scFv was able to cross the blood–brain barrier (BBB) and selectively accumulated in injured regions, as confirmed by single-photon emission computed tomography (SPECT) imaging. Both PEGylated and non-PEGylated scFv tracers showed significantly higher brain uptake in TBI rats compared to healthy controls (p < 0.0001). At 24 h, the PEGylated form exhibited a significantly higher brain signal than the non-PEGylated version (p < 0.0001), indicating improved tracer retention. Biodistribution analysis at 2 h post-injection showed significantly reduced renal clearance for the PEGylated tracer and increased hepatic uptake compared to the non-PEGylated form. At 24 h, in vivo imaging confirmed sustained brain retention, highlighting improved pharmacokinetics and imaging potential. Conclusions: These results support PEGylated scFv as a promising SPECT imaging agent for early detection of tauopathy in TBI, offering enhanced brain retention and improved pharmacokinetics. Full article

In response to the problems of high energy consumption and difficulty in precise regulation of electric tracing anti-icing systems for polar marine engineering equipment in low-temperature, strong-wind, and high-humidity environments, this paper conducts experimental measurement and predictive modeling research on the convective heat transfer characteristics of electric heat-traced circular cylinders in cross-flow. First, a controllable environmental experimental system was set up to obtain 144 sets of steady-state convective heat transfer data under different combinations of wind speed, temperature, humidity, and heat flux density. Based on this, a Nusselt number (Nu) prediction model using a fully connected Deep Neural Network (DNN) was constructed, and its performance was evaluated through five-fold cross-validation. The results show that the DNN model can effectively capture nonlinear mapping relationships among multiple factors, and its prediction accuracy ($R^2$ = 0.9828) is superior to that of traditional machine learning models. Furthermore, the Shapley Additive Explanations (SHAP) method was introduced to analyze the multi-factor coupling mechanisms, quantify the contribution of each input variable to the Nu prediction, and provide a data-driven reference for the optimization of engineering parameters under extreme polar conditions. Full article

Mucosal immunity, including antibodies like immunoglobulin A (IgA), function as the body’s first line of defense in the respiratory tract, particularly against viruses. An anti-rS protein IgA enzyme-linked immunosorbent assay (ELISA) was developed using the Omicron XBB.1.5 subvariant of SARS-CoV-2 and was validated to demonstrate the suitability of the method for testing saliva from SARS-CoV-2 vaccine clinical trials. This assay successfully met acceptance criteria for inter-/intra-assay precision, specificity, selectivity, linearity, lower/upper limits of quantitation, and assay robustness. The IgA in saliva was stable for up to 7 freeze/thaw cycles, for up to 48 h at 24 °C, up to 7 days at 4 °C, up to 3 weeks at −20 °C, and up to 1 year at −80 °C. After validation using Omicron XBB.1.5 rS protein, cross-reactivity was demonstrated with the SARS-CoV-2 variant JN.1. This validated IgA assay can be a valuable tool to assess mucosal IgA levels in SARS-CoV-2 clinical trials. Full article

Tomatoes are the major dietary source of lycopene, a carotenoid that crosses the blood–brain barrier and exerts antioxidant and anti-inflammatory effects. However, the impact of tomato consumption on cognitive function in healthy adults remains unclear. This study assessed the effects of concentrated tomato paste on cognitive performance and explored potential mechanisms, including brain-derived neurotrophic factor (BDNF) and functional brain connectivity. A randomized, two-period crossover trial (ClinicalTrials.gov: NCT05891977) was conducted in 47 healthy adults aged 40–55 years assigned to two 3-month interventions separated by a 1-month washout: (a) daily consumption of concentrated tomato paste (0.5 g/kg body weight) and (b) a lycopene-restricted control diet. Cognitive performance was evaluated using validated neuropsychological tests (d2-R, Face-Name Associative Memory Exam, Modified Wisconsin Card Sorting Test), alongside plasma lycopene and BDNF, and resting-state functional magnetic resonance imaging (fMRI). Forty-two participants completed the study. Tomato intake improved selective attention (concentration performance: +7.2 points; processing speed: +8.3 points) and associative memory (face-name matching: +0.8 points). Plasma BDNF showed a borderline increase with tomato intake (mean difference 15.2 ng/mL). Resting-state fMRI revealed changes in brain networks, including reduced connectivity in frontoparietal and auditory networks, contrasting with reductions in the dorsal attention network during the control period. These findings provide evidence that tomato consumption may support cognitive function and modulate brain connectivity in healthy middle-aged adults. Full article

Narrative extraction algorithms construct storylines by finding coherent paths through document collections. The Narrative Trails algorithm frames this as maximum-capacity path optimization, where path quality depends on a coherence function measuring document relationships. We introduce quantum kernels as coherence functions for narrative extraction—to the best of our knowledge, the first systematic characterisation of quantum kernel methods for storyline extraction—and compare them against classical baselines on two corpora using a multi-seed protocol. The sweep covers 93 method evaluations (54 quantum kernels across three encoder families—R_Y+CNOT-ring, IQP/ZZ-feature-map, and a projected quantum kernel—and 39 classical kernels—cosine, RBF, and the cluster-aware Narrative Trails baseline). On 11,215 human navigation paths from Wikispeedia, evaluation metrics divide into two clusters that disagree with each other: alignment-based metrics (length-normalised DTW and per-step DTW similarity) favour methods that produce long alignment-rich paths, while set-overlap metrics (Jaccard and F1) favour methods that produce shorter paths with higher article overlap. On LLM-judged coherence for Cuban news storylines, evaluated under a 12-method × 5-seed × 30-endpoint-pair × 2-judge design (Claude Sonnet 4.5 and GPT-4o, both at $T=0$ via structured tool calling), the cluster-aware classical baseline is the top method in terms of mean overall coherence; the 5-method quantum-kernel pool and the 7-method classical-kernel pool on matched projection input show no significant differences after Holm correction. Cross-task analysis reveals that LLM coherence rank correlates with alignment-cluster Wikispeedia metrics (Spearman $\rho \approx +0.70$) and anti-correlates with overlap-cluster metrics ($\rho \approx -0.62$). A closed-form theoretical analysis shows that the depth-1 R_Y+CNOT-ring kernel reduces to a classical product-of-cosines kernel order equivalent to RBF, explaining the absence of empirical separation at low depth; deeper encoders break the cancellation but exponentially concentrate kernel values, eroding inter-pair distinguishability. Our results characterise quantum coherence kernels as competitive with classical kernels on the same projected input rather than decisively superior, with the cluster-aware classical baseline retaining a modest advantage attributable to its explicit topical structure. Full article

Human metapneumovirus (HPMV) is a significant pathogen that causes lower respiratory tract infections. Given the weak immunogenicity thereof, and the few relevant studies, the utility of the viral membrane protein G as a vaccine remains controversial. In this study, the G extracellular domain (RMG) of HMPV was expressed either alone or fused with the cholera toxin B subunit (CTB) and “cross-reacting material 197” (CRM197) carrier proteins (giving G-CTB/G and CRM197), to enhance immunogenicity. The non-glycosylated G protein (REG) expressed in Escherichia coli served as a control. SDS-PAGE and anti-His tag Western blotting verified that each protein was successfully expressed and correctly identified. BALB/c mice were immunized with each protein and subjected to challenge with HMPV. The results showed that, although immunization with RMG alone failed to induce potent neutralizing antibodies, it modestly reduced viral loads in the lungs of mice. However, the pathological damage caused by lung inflammation was more aggravated than that of the control challenge group. The level of specific IgG antibody induced by the recombinant G-CTB was significantly higher than that elicited by RMG. Compared to the RMG group, the viral load in the lungs of the G-CTB group tended to be reduced. Also, the damage caused by lung inflammation was significantly alleviated. Our study proves that HMPV G may be a valuable antigen in terms of HMPV vaccine development and offers a promising strategy for modulating the immunogenicity and safety thereof. Full article

Background. The highly mutable influenza virus causes severe annual infections worldwide and results in substantial socioeconomic losses. The spread of infection could be effectively controlled by cross-protective vaccines and universal diagnostic test systems based on the nucleoprotein (NP) as one of the most conserved viral antigens. However, NP also undergoes slow evolutionary changes, and little is known about the influence of these mutations on its antigenicity and immunogenicity. Methods. We expressed the full-length recombinant 6xHis-tagged NPs of ten evolutionary distant influenza A strains of different subtypes in E. coli BL21(DE3) cells and purified these proteins by immobilized metal affinity chromatography. The obtained antigens were identified by mass spectrometry and serological methods. NPs served as antigens for three immunizations of BALB/c mice (15 µg/animal at 14-day interval) and as capturing proteins in ELISA at 2 µg/mL, in order to study the effect of adaptive mutations on the antigenic and immunogenic properties of NPs. Results. A pronounced cross-reactivity of anti-NP antibodies induced in mice by immunization with different NPs was revealed. At the same time, we observed the differences in the humoral immunogenicity of NP, which are in line with the accumulation of evolutionarily driven NP mutations. In general, antibody affinity to heterologous NPs was reduced, indicating the differences in the specificity of anti-NP immunoglobulins, which may be caused by evolutionarily determined variability of immunogenic epitopes leading to the emergence of escape mutations. Conclusions. Overall, our results reflect the slightly evolving nature of the NP antigen, which influences the specificity spectrum of anti-NP antibodies and should be considered as a limitation for the development of NP-based cross-protective vaccines and test systems. Full article