Search Results (749)

Background/Objectives: Polymyalgia rheumatica (PMR) is a relatively common inflammatory rheumatic disease of the elderly. The role of vitamin D remains unclear in this condition. The endpoints of this study were to assess 25-hydroxyvitamin D [25(OH)D] serum concentrations in PMR patients with active disease compared to elderly controls and to determine if baseline levels or changes following supplementation [delta 25-hydroxyvitamin D, Δ25(OH)D] were associated with improved clinical outcomes. Methods: In this retrospective, case–control study, 29 PMR patients (55% males, 75.24 ± 9.6 years old, disease duration of 3.8 ± 3 months) were included, meeting the 2012 EULAR/ACR classification criteria, with 29 age- and sex-matched controls without systemic inflammatory rheumatic diseases. We assessed demographic, clinical and laboratory features for PMR patients, including baseline 25(OH)D serum concentrations, disease activity (polymyalgia rheumatica activity score), and serum inflammatory biomarkers. A subgroup of them (n = 25) was followed longitudinally, for an average period of 21.1 ± 17.7 months, to evaluate the association between Δ25(OH)D and clinical outcomes at follow-up using multivariate logistic regression. Results: Although lower than the normal reference values, baseline 25(OH)D concentrations did not differ significantly between PMR patients and controls (21.6 ± 9.2 vs. 22.7 ± 11.3 ng/mL, p = 0.66) and did not predict long-term clinical outcomes. However, after only 3 months of supplementation, the increase in 25(OH)D concentrations was significantly associated with a remission status, and patients in remission showed a significant increase in 25(OH)D compared to those with persistent disease activity (+22.02 vs. +1.33 ng/mL, respectively; p = 0.044). Notably, in the multivariate model, this Δ25(OH)D was the strongest independent predictor of remission (OR = 2.89; 95% CI [1.60–4.11]), an effect independent of prednisone dosage prescribed at first visit (p = 0.32) and glucocorticoid exposure at third month (p = 0.12). Conclusions: Individual’s response of PMR patients to supplementation of vitamin D seems to be a robust independent predictor of early clinical remission achievement. Interestingly, optimizing vitamin D supplementation based on individual responsiveness may represent a valuable adjunctive strategy in PMR management. Full article

Many patients experience unique or persistent symptoms several months following the onset of infection with severe acute respiratory syndrome coronavirus 2, the causative agent of COVID-19. While this condition is commonly referred to as long COVID, no universally accepted definition exists; therefore, many patients go underrecognized and underreported. Long COVID can involve almost any major organ system and is characterized by widely heterogeneous persistent or recurrent symptoms including fatigue, headache, cough, dyspnea, chest pain, cognitive dysfunction, anxiety, and depression. In line with the wide array of symptoms, numerous potential underlying pathophysiologic pathways, including viral persistence, prolonged inflammation, autoimmune reactions, endothelial dysfunction, and dysbiosis of the microbiome of the gut, may contribute to the symptomology of long COVID. Therapy is directed at symptomatic control; however, no pharmacologic treatments are specifically approved for the management of symptoms associated with long COVID. Several common symptoms of long COVID may be managed with nonprescription treatments (pharmacologic and nonpharmacologic). The goal of this review is to provide clinicians with a better understanding of long COVID and review the latest recommendations for managing common mild-to-moderate symptoms with nonprescription treatment options. Full article

Background/Objectives: Malnutrition is a common but underrecognized complication in colorectal cancer (CRC), contributing to poor treatment outcomes and reduced quality of life. Regional data from the Gulf remains limited. This study assessed the prevalence of malnutrition and nutrition impact symptoms (NISs) among CRC patients in Kuwait. It evaluated the diagnostic performance of the PG-SGA Short Form (PG-SGA SF) in comparison to the full PG-SGA and the Malnutrition Screening Tool (MST). Methods: A cross-sectional study was conducted among 65 CRC outpatients at the Kuwait Cancer Control Center. Nutritional status was assessed using the full PG-SGA, PG-SGA SF, and MST. Dietary intake, anthropometry, biochemical parameters, and NISs were collected. Logistic regression identified independent predictors of malnutrition, and the performance of the tool was evaluated using kappa statistics and diagnostic accuracy metrics. Results: Malnutrition (PG-SGA B/C) was identified in 61.4% of patients. Loss of appetite, dry mouth, and nausea were significantly associated with malnutrition (p < 0.00385); dry mouth independently predicted malnutrition (OR: 17.65, 95% CI: 2.02–154.19, p = 0.009). BMI was not predictive, but reduced mid-arm circumference was significantly associated. PG-SGA SF showed strong agreement with the full PG-SGA (κ = 0.75), with high sensitivity (87.2%) and specificity (88.5%), outperforming MST (κ = 0.38). Only 23.5% of moderately malnourished patients were referred to a dietitian. Conclusions: Malnutrition and NIS are highly prevalent among Kuwaiti CRC patients. PG-SGA SF is a valid and efficient screening tool that should replace MST in oncology settings. Symptom-informed screening and structured referral protocols are crucial for enhancing nutrition care. Full article

Control valves are the main throttling resistance components in industries such as chemical engineering, nuclear power, aerospace, hydrogen energy, natural gas transportation, marine engineering, and energy systems. Flow-induced vibration fatigue failure is a common failure mode. To provide engineers and researchers with a reference for reliable design analysis of control valves and to predict and prevent potential failures, this article reviews and categorizes vibration-induced failure in control valves by integrating numerous engineering cases and research articles. The vibration failures of control valves are mainly divided into categories such as jet flow, vortex flow, cavitation, and acoustic cavity resonance. This paper reviews control valve vibration research from three aspects: theoretical models, numerical simulations, and experimental methods. It highlights the mechanisms by which internal unstable flow, jet flow, vortex shedding, cavitation, and acoustic resonance lead to vibration-induced fractures in valve components. Additionally, it examines the influence of valve geometry, component constraints, and damping on flow-induced valve failures and summarizes research on vibration and noise reduction in control valves. This paper aims to serve as a reference for the analysis of vibration-induced failures in control valves, helping identify failure mechanisms under different operating conditions and proposing effective solutions to enhance structural reliability and reduce the occurrence of vibration failures. Full article

Accurate normalization is crucial for reliable gene expression quantification and depends on stably expressed housekeeping genes (HKGs) as internal controls. However, HKGs expression varies with developmental stage, tissue type, and treatments, potentially introducing bias and compromising data accuracy. Thus, validating candidate reference genes under defined conditions is essential. Reynoutria, also known as giant Asian knotweeds, is a Polygonaceae family genus of several medicinal plants producing a diverse array of specialized metabolites of pharmacological interest. Outside their native range, these plants are also noxious invasive weeds, causing significant environmental and economic threats. Research on stable reference genes in these species is limited, with a primary focus on R. japonica. To enable accurate gene expression analysis related to specialized metabolism and natural product biosynthesis, we aimed to identify the most stable reference genes across the most common species: R. japonica Houtt., R. sachalinensis (F. Schmidt) Nakai, and their hybrid—R. × bohemica Chrtek & Chrtková. In this study, we evaluated twelve candidate HKGs (ACT, TUA, TUB, GAPDH, EF-1γ, UBQ, UBC, 60SrRNA, eIF6A, SKD1, YLS8, and NDUFA13) across three tissue types (rhizomes, leaves, and flowers) from three Reynoutria species sampled at peak flowering. Primer specificity and amplification efficiency were confirmed through standard-curve analysis. We assessed expression stability using ΔCt, geNorm, NormFinder, and BestKeeper, and generated comprehensive rankings with RefFinder. Our integrated analysis revealed organ- and species-dependent stability differences, yet identified up to three reference genes suitable for interspecific normalization in Reynoutria. This represents the first systematic, comparative validation of HKGs across closely related knotweed species, providing a robust foundation for future transcriptomic and functional studies of their specialized metabolism and other biological processes. Full article

Soil–groundwater pollution is a complex environmental phenomenon formed by the coupling of multiple processes. Due to the concealment of pollution, the persistence of harm, and the complexity of the system, soil–groundwater pollution has become a major environmental issue of increasing concern. The simulation and prediction of different types of models, different pollutants, and different scales in soil and groundwater have always been the research hotspots for pollution prevention and control. Starting from the mathematical mechanism of pollutant transport in soil and groundwater, this study reviews the method models represented by empirical models, analytical models, statistical models, numerical models, and machine learning, and expounds the characteristics and applications of the various representative models. Our Web of Science analysis (2015–2025) identifies 3425 relevant studies on soil–groundwater pollution models. Statistical models dominated (n = 1155), followed by numerical models (n = 878) and machine learning (n = 703). Soil pollution studies (n = 1919) outnumber groundwater research (n = 1506), with statistical models being most prevalent for soil and equally common as numerical models for groundwater. Then this study summarizes the research status of soil–groundwater pollution simulation and prediction at the level of multi-scale numerical simulation and the pollutant transport mechanism. It also discusses the development trend of artificial intelligence innovation applications such as machine learning in soil–groundwater pollution, looks forward to the challenges and measures to cope with them, and proposes to systematically respond to core challenges in soil and groundwater pollution simulation and remediation through new technology development, multi-scale and multi-interface coupling, intelligent optimization algorithms, and pollution control collaborative optimization methods for pollution management, so as to provide references for the future simulation, prediction, and remediation of soil–groundwater pollution. Full article

Methyl CpG-binding protein 2 (MeCP2) is an epigenetic reader of DNA methylation with high abundance in the brain. While genetic mutations occur across different protein domains of MeCP2, the T158M mutation is amongst the most frequent MeCP2 mutations. MeCP2 is encoded by the MECP2/Mecp2 gene located on the X chromosome. In humans, MECP2 mutations cause Rett Syndrome, a debilitating neurodevelopmental disorder in females, with very rare cases presenting in males. Despite the generation of different transgenic mouse lines with MeCP2 mutations, the sex-dependent phenotypic and molecular impact of common MeCP2 mutations in mouse models of disease remains largely unexplored. Here, we focus on the MeCP2 T158M mutation using Mecp2^tm4.1Bird/J transgenic mice (referred to as Mecp2^T158M), and report that Mecp2^T158M mutant mice display sex-specific molecular, behavioural, and phenotypic characteristics when compared to wild-type controls. Our data indicates sex- and brain-region-dependent impacts on the expression of MeCP2, synaptic proteins, cytoskeletal markers, and autophagy factors. Our findings demonstrate that the phenotypic and molecular characteristics of this mouse model may relate to the clinical manifestation in human patients with Rett Syndrome. Full article

The paper presents an FPGA-based, hardware-accelerated IEC 61850-9-2 Sampled Measured Values (SMV) subscriber—termed the high-speed SMV subscriber (HS3)—by integrating real-time energy-quality (EQ) analytics directly into the subscriber pipeline while preserving a deterministic, microsecond-scale operation under high stream counts. Building on a prior hardware decoder that achieved sub-3 μs SMV parsing for up to 512 subscribed svIDs with modest logic utilization (<8%), the proposed design augments the pipeline with fixed-point RTL modules for single-bin DFT frequency estimation, windowed true-RMS computation, and per-sample active power evaluation, all operating in a streaming fashion with configurable windows and resolutions. A lightweight software layer performs only residual scalar combinations (e.g., apparent power, form factor) on pre-aggregated hardware outputs, thereby minimizing CPU load and memory traffic. The paper’s aim is to bridge the gap between software-centric analytics—common in toolkit-based deployments—and fixed-function commercial firmware, by delivering an open, modular architecture that co-locates SMV subscription and EQ pre-processing in the same hardware fabric. Implementation on an MPSoC platform demonstrates that integrating EQ analytics does not compromise the efficiency or accuracy of the primary decoding path and sustains the latency targets required for protection-and-control use cases, with accuracy consistent with offline references across representative test waveforms. In contrast to existing solutions that either compute PQ metrics post-capture in software or offer limited in-FPGA analytics, the main contributions lie in a cohesive, resource-efficient integration that exposes continuous, per-channel EQ metrics at microsecond granularity, together with an implementation-level characterization (latency, resource usage, and error against reference calculations) evidencing suitability for real-time substation automation. Full article

In loop-powered 4–20 mA transmitter systems, sensors like temperature, pressure, flow, and gas sensors are chosen based on specific application requirements. These systems are widely adopted in high-precision measurement scenarios, including industrial automation, process control, and environmental monitoring. The transmitter requires a high-performance analog front end (AFE) for precise amplification and signal conditioning. This paper presents a low-noise instrumentation amplifier (IA) for high-precision transmitter front ends, featuring a Successive Approximation Register (SAR)-assisted offset calibration architecture. The proposed structure integrates a chopper current-feedback instrumentation amplifier (CFIA) with an automatic offset calibration loop (AOCL), significantly suppressing internal offset errors and enabling high-accuracy signal acquisition under stringent power and environmental temperature constraints. The designed amplifier provides four selectable gain settings, covering a range from ×32 to ×256. Fabricated in a 0.18 μm CMOS process, the CFIA operates at a 1.8 V supply voltage, consumes a static current of 182 μA, and achieves an input-referred noise as low as 20.28 nV/√Hz at 1 kHz, with a common-mode rejection ratio (CMRR) up to 122 dB and a power-supply rejection ratio (PSRR) up to 117 dB. Experimental results demonstrate that the proposed amplifier exhibits excellent performance in terms of input-referred noise, offset voltage, PSRR, and CMRR, making it well-suited for front-end detection in field instruments that require direct interfacing with measured media. Full article

This paper introduces a novel strategy for the diagnosis and fault-tolerant control (FTC) of inter-turn short-circuit (ITSC) faults in the stator windings of Doubly Fed Induction Generator (DFIG)-based wind turbines. ITSC faults are among the most common electrical issues in rotating machines: early detection is therefore essential to reduce maintenance costs and prevent severe damage to the wind turbine system. To address this, a Fault Detection and Diagnosis (FDD) approach is proposed to identify and assess the severity of ITSC faults in the stator windings. A state-space model of the DFIG under ITSC fault conditions is first developed in the (d,q) reference frame. Based on this model, an Unknown Input Observer (UIO) structured using Takagi–Sugeno (T-S) fuzzy models is designed to estimate the fault level. To mitigate the impact of the fault and ensure continued operation under degraded conditions, a T-S fuzzy fault-tolerant controller is synthesized. This controller enables natural decoupling and optimal power extraction across a wide range of rotor speed variations. Since the effectiveness of the FTC relies on accurate fault information, a Proportional-Integral Observer (PIO) is employed to estimate the ITSC fault level. The proposed diagnosis and compensation strategy is validated through simulations performed on a 3 kW wind turbine system, demonstrating its efficiency and robustness. Full article

Large language models (LLMs) now match or exceed human performance on many open-ended language tasks, yet they continue to produce fluent but incorrect statements, which is a failure mode widely referred to as hallucination. In low-stakes settings this may be tolerable; in regulated or safety-critical domains such as financial services, compliance review, and client decision support, it is not. Motivated by these realities, we develop an integrated mitigation framework that layers complementary controls rather than relying on any single technique. The framework combines structured prompt design, retrieval-augmented generation (RAG) with verifiable evidence sources, and targeted fine-tuning aligned with domain truth constraints. Our interest in this problem is practical. Individual mitigation techniques have matured quickly, yet teams deploying LLMs in production routinely report difficulty stitching them together in a coherent, maintainable pipeline. Decisions about when to ground a response in retrieved data, when to escalate uncertainty, how to capture provenance, and how to evaluate fidelity are often made ad hoc. Drawing on experience from financial technology implementations, where even rare hallucinations can carry material cost, regulatory exposure, or loss of customer trust, we aim to provide clearer guidance in the form of an easy-to-follow tutorial. This paper makes four contributions. First, we introduce a three-layer reference architecture that organizes mitigation activities across input governance, evidence-grounded generation, and post-response verification. Second, we describe a lightweight supervisory agent that manages uncertainty signals and triggers escalation (to humans, alternate models, or constrained workflows) when confidence falls below policy thresholds. Third, we analyze common but under-addressed security surfaces relevant to hallucination mitigation, including prompt injection, retrieval poisoning, and policy evasion attacks. Finally, we outline an implementation playbook for production deployment, including evaluation metrics, operational trade-offs, and lessons learned from early financial-services pilots. Full article

Background: Peripherally inserted central catheters (PICCs) are becoming an increasingly utilised alternative to traditional central venous access devices. Their uptake, particularly among oncology patients, is due to their growing ease of access, suitability for medium-term use and perceived safety profile. However, PICCs can be a source of severe and life-threatening complications such as central line-associated bloodstream infection (CLABSI), deep vein thrombosis (DVT), pulmonary embolism (PE), malpositioning, dislodgement, and occlusion. Methods: This narrative was constructed from a literature review of the PubMed database, utilising MESH terms for peripherally inserted central catheters, percutaneous central catheters, PICC, and complications. Randomised controlled trials, systematic reviews, and meta-analyses published between 2015 and 2025 were included. Additional articles were obtained through targeted PubMed searches or from references within previous articles. Results: Major periprocedural complications were seen in 1.1% of PICC insertions, CLABSI in 1.4–1.9%, venous thrombosis embolism (including PE) in 2.3–5.9%, and malpositioning in 7.87%. The overall PICC complication incidence was 9.5–38.6%, which is greater than that of centrally inserted central venous access. A higher BMI, diabetes mellitus, chronic renal failure, and malignancy were the most significant predictive factors for PICC-associated complications. Conclusions: PICC complications are common, occurring more frequently than other forms of central venous access, and may lead to significant morbidity and mortality. Appropriate assessment of patient risk factors and optimisation strategies may reduce complication rates. Full article

The olive industry is transitioning from traditional to super-high-density (SHD) systems to optimize production costs and address labor shortages. This shift coincides with increasing challenges from soil salinization and deteriorating irrigation water quality. This study evaluated salinity tolerance in three novel olive cultivars (Lecciana, Coriana, and Sikitita) against the established SHD references Arbequina and Arbosana under controlled greenhouse conditions over five months with increasing NaCl concentrations (25, 50, and 75 mM). The analysis revealed distinct adaptation mechanisms among cultivars. Arbosana exhibited balanced tolerance across parameters, with minimal biomass reduction and remarkable photosynthetic resilience. Lecciana demonstrated superior ion regulation, maintaining the highest K⁺/Na⁺ ratios across all salinity levels despite pronounced shoot growth sensitivity at high salinity. Sikitita showed moderate tolerance through biomass maintenance but with significant photosynthetic sensitivity under stress. Arbequina displayed effective chloride exclusion and consistent shoot growth despite biomass sensitivity, whereas Coriana presented notable biomass increases at moderate salinity but poor ion discrimination. Tissue-specific analysis revealed common compartmentalization patterns across cultivars, with roots accumulating the highest Na⁺ and Cl⁻ concentrations. These data identify Arbosana and Lecciana as promising candidates for salinized SHD orchards. Full article

This paper refers to fast and accurate electric servo control in the presence of position and velocity constraints. This problem, one of the most common nowadays in industrial automation, is often addressed by controllers derived using barrier Lyapunov functions (BLFs). This popular and effective technique is burdened with several difficulties, such as complex feasibility conditions and the inapplicability of the derived controller because of control constraints. In this contribution, we propose a novel, BLF-based, adaptive controller for an electric servo (linear or rotational) with modeling uncertainties, solving a tracking problem. The controller derivation is completed by the tuning procedure, which enables safe system operation in the presence of active control constraints, measurement errors, and noise. The selection of the best combination of BLFs is a part of this procedure. Also, all feasibility issues are solved by the proposed approach. The derivation is completed by extensive numerical simulations and real-life implementation using two different servo systems—the first with a linear permanent magnet motor and the second with a rotational PMSM. Full article

Introduction: Mycobacterium tuberculosis (Mtb), the most common co-infection among people living with HIV (PLWH), aggravates the associated morbidity and mortality in these individuals; however, the immune-modulatory role of Mtb in the pathogenesis of HIV infection remains incompletely understood. Methods: We investigated the role of Mtb infection in regulating adaptive immune responses with reference to the expression of five immune checkpoint molecules (ICMs) in co-infected individuals in a cross-sectional study conducted on treatment-naïve human cohorts from North India, including PLWH, people with Mtb infection, people with HIV-Mtb co-infection, and healthy volunteers as controls. Results: The data revealed a significantly increased gene expression of TIM-3 (p = 0.0058), LAG-3 (p < 0.0001), PD-1 (p = 0.0090), and CTLA-4 (p = 0.0008). It also revealed a higher frequency of CD4⁺ and CD8⁺ T-cells surface-expressing TIM-3⁺, CTLA-4⁺, LAG-3⁺. Finally, it showed cells co-expressing two ICMs together (p < 0.05) in individuals with HIV–Mtb co-infection as compared to HIV mono-infected ones. Interestingly, the frequency of these cells correlated inversely with the absolute CD4⁺ T-cell count and positively with the plasma viral load (p < 0.05), indicating direct association with HIV disease progression. Conclusions: These findings suggest that Mtb co-infection exacerbates immune exhaustion in co-infected individuals. Targeting ICMs with pharmacological immune checkpoint inhibitors (ICIs) offers a promising approach for better clinical management of co-infected individuals. Full article