Search Results (5,136)

Background: SARS-CoV-2 infection has been associated with metabolic disturbances and endocrine alterations, including effects on pancreatic β-cell function and thyroid hormone regulation. However, the relationship between thyroid function and β-cell compensatory capacity in the post-COVID state remains unclear. Methods: In this cross-sectional study, we evaluated β-cell compensation (HOMA-B/HOMA-IR) and thyroid parameters in three groups: patients with active COVID-19, individuals with post-COVID metabolic disturbances, and a COVID-negative metabolic syndrome reference group. Thyroid status was assessed using both comprehensive clinical classification and biochemical criteria. Associations between thyroid hormones and β-cell function were analyzed using Spearman correlation. Results: β-cell compensatory capacity differed significantly across groups, with the lowest values observed during active COVID-19 and intermediate impairment in the post-COVID cohort compared with the metabolic syndrome group. FT3 concentrations and the FT3/FT4 ratio were significantly reduced during active infection and were positively associated with β-cell compensation in the post-COVID group (ρ = 0.421, p = 0.018 and ρ = 0.382, p = 0.031, respectively). Although thyroid dysfunction appeared more prevalent in the post-COVID cohort when defined by overall clinical classification, no significant differences were observed when thyroid status was evaluated based solely on biochemical criteria, excluding clinical history and euthyroid sick syndrome. Conclusions: Post-COVID metabolic disturbances are characterized by impaired β-cell compensatory capacity and alterations in peripheral thyroid hormone dynamics. The apparent increase in thyroid dysfunction is largely driven by pre-existing thyroid disease and non-thyroidal illness effects rather than intrinsic thyroid pathology. These findings are consistent with the hypothesis of a potential post-COVID immunometabolic phenotype involving both pancreatic and thyroid-related mechanisms. Full article

The Internet of Vehicles (IoV) is reshaping intelligent transportation through pervasive connectivity, real-time data exchange, cooperative perception, and vehicle–edge–cloud services, while also expanding cybersecurity and privacy risks across heterogeneous cyber–physical environments. This paper presents a PRISMA 2020-informed systematic review of IoV security and privacy protection research. A cross-layer and lifecycle-oriented analytical framework is developed by integrating a four-layer IoV architecture—sensing layer, network access layer, coordinative computing layer, and application layer—with a five-stage data lifecycle covering data collection, transmission, storage, usage, and disposal. Based on this framework, the paper examines representative threat surfaces, vehicle-to-everything (V2X) communication security, public key infrastructure (PKI) based authentication, trust management, privacy-preserving data sharing, intrusion detection, active defense, and AI-assisted security analytics. Privacy-preserving mechanisms, including differential privacy, federated learning, blockchain, homomorphic encryption, and secure multi-party computation, are further compared in terms of deployment layer, lifecycle stage, real-time suitability, and representative performance evidence. In addition, the review discusses the engineering relevance of UNECE WP.29 R155/R156, ISO/SAE 21434, and related national standards, with emphasis on compliance evidence, over-the-air (OTA) governance, supply-chain coordination, and lifecycle cybersecurity management. The review shows that no single protection mechanism can simultaneously satisfy the requirements of real-time performance, scalability, privacy preservation, trustworthiness, and regulatory compliance in dynamic IoV environments. Future research should emphasize lightweight and adaptive protection, cross-layer trust coordination, privacy–utility co-optimization, trustworthy AI-assisted security operations, and evidence-based lifecycle governance. This review provides a structured reference for researchers and a practical basis for secure and privacy-aware IoV system design. Full article

2-Ethylhexyl-4-methoxycinnamate (EHMC) is among the most widely adopted organic UVB filters in commercial sunscreens. Nevertheless, its practical application potential is limited by unfavorable formulation compatibility and safety risks stemming from systemic exposure after topical administration. In this study, an oil-continuous structured gel matrix consisting of EHMC, disteardimonium hectorite (DDH) and dextrin palmitate (DP) was constructed to enhance UVB photoprotection and modulate the plasma exposure profile of EHMC following topical application. Comprehensive characterizations including rheology, XRD, Raman spectroscopy, FTIR spectroscopy, TGA and SEM collectively revealed that the combined incorporation of DDH and DP facilitates matrix structural rearrangement, enables EHMC to bind within the structured network, and promotes the formation of more intact continuous surface films. In vitro SPF assays demonstrated that the finished topical formulation SC-4 delivered superior UVB blocking efficacy compared with the EHMC-only control SC-1; furthermore, SC-4 exhibited improved short-term physical stability under the preset thermal and centrifugal acceleration test conditions. Follow-up skin safety assessments, mass spectrometry imaging (MSI) and pharmacokinetic assays verified that SC-4 elicited no remarkable acute skin irritation across all experimental conditions. Relative to SC-1, the reference formulation with EHMC as the sole UV filter, SC-4 displayed weaker EHMC-related distribution signals in skin tissues, accompanied by lower early plasma EHMC concentrations and a slightly lower AUC_0–48h trend. Collectively, these findings indicate that DDH/DP co-assembly serves as a viable matrix-structuring strategy to modulate EHMC-related skin distribution and early plasma exposure. Further research into UVA blocking performance, photostability, skin retention and transdermal permeation profiles, as well as long-term storage stability, is required to advance the development of broad-spectrum sunscreen formulations built on this novel matrix platform. Full article

Background: The continued evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) created ongoing challenges for molecular diagnostics and variant surveillance. Assays capable of maintaining diagnostic sensitivity across emerging variants while providing variant-related information remain essential for clinical and public health applications. This study evaluated the performance of the GXT96 X3 extraction kit in combination with the FluoroType^® SARS-CoV-2 varID Q version 1.0 assay (Hain LifeScience SA (Pty) Ltd., South Africa) for the detection, semi-quantitative assessment, and variant characterization of SARS-CoV-2 under laboratory conditions. Methods: A total of 220 samples were evaluated, including residual nasopharyngeal clinical specimens (n = 183), reference materials, and cultured SARS-CoV-2 virus dilutions. Residual specimens collected during multiple COVID-19 waves in South Africa (wild-type, Beta, Delta, and Omicron) were compared against standard-of-care (SOC) molecular assays used for routine diagnosis. RNA extraction was performed using the automated GXT96 X3 platform, followed by amplification on the FluoroCycler^® XT using the FluoroType^® SARS-CoV-2 varID Q assay targeting RdRp and N genes, with additional spike gene mutation detection for variant detection. Diagnostic accuracy, agreement (Cohen’s kappa), precision, linearity, and limit of detection (LoD) were assessed. Results: The assay demonstrated a sensitivity of 98.4% (95% CI: 94.2–99.8) and specificity of 100% (95% CI: 95.9–100.0) compared with SOC assays, with an overall agreement of κ = 0.981. Precision analysis showed acceptable reproducibility with a standard deviation of ≤1.49 and a coefficient of variation of ≤3.83%. Regression analysis demonstrated linearity across the dilution series (R² = 0.9882 for RdRp and 0.994 for N genes). The LoD was ≤100 copies/mL for the RdRp gene and 250 copies/mL for the N gene. Variant-associated spike mutations corresponded broadly with epidemiological wave patterns observed in South Africa. Conclusions: Under the evaluated laboratory conditions, the GXT96 X3 extraction platform combined with the FluoroType^® SARS-CoV-2 varID Q assay demonstrated high diagnostic accuracy and reproducibility for SARS-CoV-2 detection across a range of viral loads with additional spike gene mutation detection as an adjunct feature. Full article

Abandoned slopes often encounter problems such as compacted soil and lack of nutrients. Biochar, as a promising soil amendment agent, can effectively enhance soil fertility. Moreover, evaluating the nutrient and microbial characteristics during the improvement process is of great significance for revealing its mechanism of action in improving abandoned land. This study analyzed the characteristics of soil nutrients, microbial community structure, and co-occurrence network after reclamation under different application rates (0%, 1%, 2.5%, 4%, 5.5%, hereinafter referred to as CK, T1, T2, T3, T4) of corn straw biochar. The results showed that biochar significantly increased soil organic carbon (by 60.74–164.82%), total nitrogen (11.31–27.73%), and total phosphorus (13.32–56.03%) content, and the effect was best at a rate of 4% (T3). With the increase in biochar application rate, soil bulk density generally showed a downward trend, and pH generally showed an upward trend. Significant levels (p < 0.05) were reached from T2 to T4. There was a strong linear correlation between biochar application rate and soil organic matter, total nitrogen, and pH in the fitted model, with R² values reaching 0.753, 0.601, and 0.706, respectively. Microbial community analysis showed that biochar application changed the bacterial community structure. With the increase in soil depth, the Shannon index and Chao index of each treatment generally increased, indicating that soil depth is one of the key factors regulating the community structure. Biochar application promoted the proliferation of beneficial bacterial groups such as Pseudomonadota and Acidobacteriota, by increasing the number of co-occurrence network nodes and edges enhancing the complexity and stability of the microbial network. Full article

Fusing spatial observations from sensors with heterogeneous error characteristics is a persistent challenge in geostatistics. Classical kriging assumes a Gaussian likelihood for all observations, an assumption that fails when sensors exhibit one-sided or asymmetric noise. We present a Variable Rank Kriging (VRK) formulation that supports per-observation heterogeneous likelihoods where each observation may define its own likelihood function, thus enabling principled fusion of sensors whose noise structures are significantly different in terms of distribution family and magnitude. Within this framework, we use the exponential (one-sided) likelihood as a case study to demonstrate the method and compare it with sampling-based numerical alternatives for general likelihoods without closed forms. A non-collocated RTK calibration workflow uses kriging predictions from a sparse high-accuracy reference to characterise sensor-specific likelihood parameters without requiring co-located paired observations. Synthetic 1-D and 2-D experiments show that correct per-point likelihood specification reduces RMSE by up to 92% (1-D) and 57% (2-D) relative to a misspecified Gaussian model while also eliminating systematic positive bias. A demonstration using NEON Airborne Observation Platform lidar data at Harvard Forest confirms these findings in a practical, real-world scenario. Across multiple subsamples of the lidar dataset, the exponential likelihood reduces vegetated-zone RMSE by $20.6\%$ (open zone: $18.6\%$) and mean absolute bias by $26.5\%$ relative to a heteroscedastic Gaussian baseline. The open-source vrk Python ($>=$3.10) package provides a reproducible implementation that can be applied to any spatial domain that requires multi-sensor spatial fusion with heterogeneous error structures. Full article

The digitization of existing building stock often depends on legacy 2D raster floor plans (scanned drawings, PDF exports, or photographs) because structured building information models are frequently unavailable for older properties. Manual measurement and visual inspection of such documents are time consuming and error prone. This paper presents an integrated deep learning pipeline that extracts semantic information from unstructured two-dimensional floor plan images of existing structures and supports preliminary compliance screening via locally deployed large language models. The pipeline employs YOLOv8 for the localization and classification of 18 architectural symbols and furniture items, and a U-Net with a ResNet34 encoder for the semantic segmentation of walls and interior room spaces. To translate pixel-level predictions into physical metrics, we implement an area calculation module based on user-defined reference scale calibration. An LLM evaluation module, deployed locally via Ollama with a retrieval-augmented generation pipeline, interprets extracted room metrics and flags potential non-compliance against referenced residential design guidelines; it is intended for the assessment of existing layouts rather than generative co-design. We expand a core dataset of 101 manually annotated source floor plans to 303 augmented instances using label-aligned geometric transformations, while reporting generalization in terms of the 101 unique source plans. On the held-out validation split (10 source plans), YOLOv8 achieves 92.3% mAP50 versus 87.2% for a Faster R-CNN reference model on the same data split (detection baselines differ in training epochs and pretraining; see Experiments); U-Net achieves 95.71% mIoU, surpassing DeepLabv3+ (93.2%) under matched segmentation training settings. The system is deployed as an interactive web application for legacy building survey and preliminary regulatory review when only two-dimensional documentation is available. Full article

Introduction: Establishing baseline descriptions of inorganic elements in the early life stages of sharks and in their respective nursery areas is essential for assessing anthropogenic impacts and supporting conservation strategies. Objectives: This study presents the first baseline of plasma trace element concentrations (Al, Zn, As, Cu, Cr, Cd, Co, Mn, Ti, Ni, Hg, Pb) for four juvenile shark species (Carcharhinus limbatus, Paragaleus pectoralis, Rhizoprionodon acutus, and Sphyrna lewini) from Sal Rei Bay, Boa Vista Island, Cabo Verde—the first multi-species shark nursery area described in Atlantic Africa. Methodology: Seawater and sediment samples were collected from eight sites and analyzed along with plasma samples using total reflection X-ray fluorescence spectroscopy (TXRF). Sediment granulometry and pollution indices, including the enrichment factor (EF), ecological risk index (RI), and metal pollution index (MPI), were used to characterize habitat contamination. Data were analyzed using statistical models to explore spatial and element-specific patterns. Results: Overall, environmental contamination was low, with slight increases in Cd, Co, and Hg at sites 1 and 2, near the fishing port, and at site 5, likely reflecting natural transport, sediment redistribution, and enhanced nearshore deposition. Juvenile sharks exhibited generally low plasma trace element concentrations, although species-specific elemental signatures were evident: elevated levels of Al and Cu in C. limbatus, Zn in S. lewini, and As in R. acutus and P. pectoralis. Conclusions: These findings establish critical baseline reference values for trace elements in juvenile sharks from a key Atlantic nursery area. The results provide an essential framework for future biomonitoring efforts and contribute to the management and conservation of Cabo Verdean shark nursery habitats. Full article

Chronic overlapping pain conditions (COPCs) refer to a set of chronic pain disorders that frequently co-occur and may involve partially overlapping mechanisms. The U.S. National Institutes of Health currently recognizes ten COPCs: fibromyalgia, painful temporomandibular disorders, chronic low back pain, chronic migraine headache, chronic tension-type headache, irritable bowel syndrome, endometriosis, interstitial cystitis/bladder pain syndrome, vulvodynia, and myalgic encephalomyelitis/chronic fatigue syndrome. When multiple COPCs coexist, they are associated with a disproportionate multimorbidity burden, including greater pain, poorer psychological well-being, functional limitations, disability, fatigue, sleep disturbances, diminished quality of life, and increased healthcare utilization. Despite their impact, COPCs remain under-recognized, underdiagnosed, and undertreated. Combining structured literature searches and citation tracking with narrative syntheses, this review examines comorbid relationships, the burden of multimorbidity, and potentially overlapping nociplastic mechanisms. By adopting a multimorbidity-based perspective rather than a one-disease, one-treatment approach, it highlights barriers to care—including limited clinical awareness, under-recognition of additional COPCs, limited mechanistic understanding, and fragmented care—and proposes integrated strategies emphasizing prevention, systematic screening, mechanism-informed assessment, and coordinated, patient-centered multimodal management. Full article

Background/Objectives: With the increasing incidence of drug counterfeiting and the emergence of personalized medicine, the need for unique marking of solid dosage forms, e.g., tablets, has attracted considerable interest in the current research and development landscape. Besides traditional printing methods, laser marking offers several advantages, as it eliminates the need for organic solvents and enables the generation of precise patterns. However, laser exposure may raise safety concerns regarding the stability of photosensitive drugs in the irradiated dosage forms. Therefore, the aim of the present study was to test the photoprotective effect of titanium dioxide (TiO₂) and its various alternatives, e.g., talc, calcium carbonate (CaCO₃), zinc oxide (ZnO), and black iron oxide (Fe₃O₄), alongside a ready-to-use reference formulation, Opadry^® Brown, which contains TiO₂ (titanium-containing, TC) on nifedipine, a light-sensitive model drug. Methods: Laser marking or short-term laser ablation at different wavelengths (193 nm, 248 nm, 532 nm, and 781 nm) was applied to different coating formulations. As a positive control, prolonged exposure to daylight was applied. The properties and photostability of these formulations were evaluated using several analytical methods (i.e., surface profilometry, Raman spectroscopy, and high-performance liquid chromatography (HPLC)). Results: The TiO₂, ZnO, Fe₃O₄, and Opadry^® TC Brown coatings maintained their color during the long-term study under all conditions. Furthermore, the prepared formulations exhibited different ablation depths and morphological changes depending on the coating and laser type. HPLC measurements confirmed significant differences in the protective ability of various pigments against sunlight and different types of lasers. Nevertheless, the obtained Raman spectra were not in complete agreement with HPLC results, which can be attributed to spectral overlap between key nifedipine degradation markers and excipient signals in the tablet core. Conclusions: Overall, laser treatment of tablets containing photosensitive drugs may induce API decomposition; however, this effect can be minimized or avoided by careful selection of the appropriate combination of laser type and photoprotective pigment. Under the applied experimental conditions, Ti:Sa laser treatment was associated with the lowest degree of nifedipine degradation among all formulations, while ZnO-containing coatings demonstrated the most consistent photoprotective performance against the majority of the tested laser types, while Fe₃O₄-containing coatings provided superior protection during prolonged sunlight exposure and Nd:YAG laser irradiation. Full article

Reliable air pollution monitoring remains a major challenge in Sub-Saharan Africa (SSA), limiting the assessment of population exposure and the development of effective mitigation strategies. Recent advances in low-cost (LC) sensors offer promising opportunities, but their deployment in low-infrastructure settings still faces significant technical and logistical challenges. This study presents the experience gained from deploying LC sensor networks in Burkina Faso, Niger, and the Republic of Guinea, focusing on the practical challenges of installing and maintaining these systems under demanding conditions. In Burkina Faso, an LC station was co-located with a reference-grade instrument, enabling field calibration. In Niger, factory-calibrated LC sensors were deployed across urban, semi-urban, and rural settings, while in Guinea they were installed in a remote area. Several practical issues and challenges emerged, including unstable power supplies, limited internet connectivity, safety, and logistical constraints. Careful planning and involvement of local expertise proved essential for the long-term sustainability of LC sensors. Knowledge transfer to local partners supported ongoing maintenance and strengthened data ownership. Overall, this study demonstrated that the reliability of LC air quality networks in SSA depends not only on technology, but also on adaptive strategies, robust calibration, and strong local engagement, offering practical guidance for future scalable and sustainable implementations in resource-limited settings. Full article

The vertebrate mitochondrial genome (mitogenome) is a small, circular DNA molecule typically ~16–17 kb in length, encoding 37 genes that are essential for the electron transport chain, the mechanism that drives mostly all the ATP synthesis in cells. Owing to its central role in energy metabolism, its structure is highly conserved across vertebrate lineages in both the number and relative position of each gene in the genome. Nevertheless, different variations have been found in several teleost lineages, including antarctic fishes (Nototheniidae), gadiforms, hatchetfishes (Sternoptychidae), and Batrachoidiformes. The explanation for these phenomena remains unknown yet may reflect shifts in functional constraints and can provide insights into lineage-specific and/or coevolutionary processes. This raises the possibility that mitogenome structure is related to habitat selection, potentially reflecting environmental influences on energetic regulation. To further test this hypothesis, we studied more than 400 teleost species across all major teleost lineages. The mitogenome sequences were downloaded from NCBI and annotated using two independent algorithms (MITOZ and MITOS) and then compared with a reference (Danio rerio) to find any deviation from the standard structure. Similarly, ecological data was downloaded from FishBase using the R Package “rfishbase” 5.0.3. Two independent ancestral reconstruction analyses were carried out for both traits, “Mitogenome” and “Habitat”, using a reference evolutionary tree for teleosts to unravel both evolutionary histories. The possible association between mitogenome and habitat was then assessed using a suite of phylogenetic comparative methods, including Pagel’s correlation test (corHMM) to evaluate whether both traits evolved in a correlated fashion, branch-level co-transition analysis to identify lineages where structural changes and habitat shifts co-occurred, and node-by-node comparisons of ancestral state probabilities across the phylogeny. Preliminary results suggest a correlation between some deep-sea environments and a modified mitogenome structure, with structural deviations tending to cluster in lineages inhabiting greater depths. These exploratory findings raise the possibility that changes in mitogenome architecture may be linked to adaptations in energetic metabolism required for life in extreme low-energy environments. Further analyses are underway to clarify the functional significance of these genomic changes and their relationship to ecological and metabolic pressures in teleost evolution. Full article

Large-scale dense-phase carbon dioxide (CO₂) injection is an energy-intensive process in the carbon capture, utilization, and storage (CCUS) value chain. To address insufficient utilization of inlet pressure potential energy and sealing/friction losses of conventional reciprocating pumps under high-base-pressure dense-phase CO₂ transport conditions, this study develops a dense-phase CO₂-oriented structural optimization scheme for a hydraulically driven opposed-piston reciprocating pump based on force-coupling. A dynamic model was established to clarify the in situ recovery mechanism by which inlet pressure potential energy is converted into auxiliary thrust, enabling the drive load to shift from absolute pressure to net pressure difference. Simulation results show that under the rated 8 MPa inlet and 25 MPa discharge condition, the optimized opposed-piston configuration reduces peak driving oil pressure by 31.39% compared with the non-opposed reference configuration. Field reliability operation data show an average normalized specific energy consumption of 0.422 kWh/(MPa·m³) during the selected 24 h continuous operating period. The optimized configuration improves inlet-pressure utilization and reduces hydraulic power demand under high-base-pressure dense-phase CO₂ injection conditions, providing theoretical support and engineering reference for low-energy CCUS injection systems. Full article

Kadsura heteroclita (Roxb.) Craib, commonly known as “Xuetong”, is a traditional Tujia ethnomedicine with anti-rheumatoid arthritis (RA) activity, and schizanlactone E (Xuetongsu) is its major bioactive component whose biosynthetic pathway remains uncharacterized. As a cycloartane-type tetracyclic triterpenoid, Xuetongsu’s biosynthesis is likely to involve multiple oxidation steps. Cytochrome P450 (CYP450) is a versatile monooxygenase encoded by a large and diverse gene superfamily and plays a critical role in various oxidation reactions in plants’ secondary metabolism. In this study, 367 KhCYP450s were identified and systematically analyzed for their physicochemical properties, phylogenetic analysis, conserved motifs, gene structures, collinearity, and cis-acting elements. Weighted gene co-expression network analysis (WGCNA) revealed a turquoise module strongly associated with Xuetong root tissue, which had the highest Xuetongsu accumulation; 32 candidate KhCYP450s within this module were screened via correlation analysis between gene expression and xuetongsu content and partially validated by qRT-PCR. Five of these candidates showed significant homology with known triterpenoid biosynthetic genes via protein structure analyses. This study deepened our comprehension of the CYP450 superfamily in Xuetong and provided a valuable reference for further research on the biosynthesis of Xuetongsu. Full article

COVID-19, caused by the SARS-CoV-2 virus, has become a global public health crisis with diverse clinical manifestations affecting multiple organ systems, including the integumentary system. One notable cutaneous manifestation, referred to as “COVID toes,” involves the development of pernio-like chilblains, characterized by red-to-violet macules, plaques, or nodules, primarily on toes and fingers. This characteristic clinical feature gained significant attention due to its apparent association with COVID-19, especially during the early stages of the pandemic when individuals with mild or asymptomatic cases exhibited these symptoms. Concurrently, digital platforms such as Google Trends have emerged as tools for tracking public interest in health-related topics, offering insights into real-time patterns of disease awareness. Previous research has demonstrated that Google Trends data may correlate with the incidence of infectious diseases, suggesting that search interest can be a proxy for disease outbreaks. In this study, we sought to explore the potential relationship between public interest in COVID toes, as reflected in Google Trends, and the incidence and mortality rates of COVID-19. Specifically, we examined whether peaks in search interest for “COVID toes” corresponded with surges in COVID-19 cases and deaths. By analyzing trends in search data, we aimed to assess the utility of digital platforms as an epidemiological tool for monitoring disease progression and public awareness. Our findings provide insights into the potential role of digital search data in forecasting outbreaks and highlight the interplay between public perception and the clinical burden of COVID-19, emphasizing the importance of real-time data in public health surveillance and response. Full article