Search Results (212)

Background and Clinical Significance: Human Herpesvirus 8-associated multicentric Castleman disease is a rare, lymphoproliferative disorder characterized by recurrent episodes of systemic inflammation. The disease is predominantly observed in human immunodeficiency virus-positive patients, but there is evidence of its occurrence in negative individuals. Its pathogenesis is driven by dysregulated cytokine activity, particularly interleukin 6. Additionally, these individuals have an increased risk of developing Kaposi Sarcoma, which may present simultaneously. Case Presentation: The current paper presents a case of a 58-year-old male patient admitted to the Hematology Department of the Emergency City Hospital in Timisoara, Romania, in October 2024, accusing fever, night sweats, palpitations, weight loss and general deterioration, approximately three months prior, with gradual progression. Clinical examination revealed bilateral lymphadenopathy in the cervical and inguinal regions. No cutaneous lesions were observed initially. Laboratory tests showed elevated inflammatory markers, pancytopenia, hypergammaglobulinemia and hyponatremia. HIV serology had negative results. CT imaging revealed extensive lymphadenopathy and splenomegaly. Further excisional biopsy of the inguinal and cervical lymphadenopathies was performed. Following the microscopic examination, the final diagnosis of Human Herpesvirus 8-associated multicentric Castleman disease concurrent with Kaposi Sarcoma was established. Conclusions: Human Herpesvirus 8-associated multicentric Castleman disease is predominantly observed in HIV-positive patients, but there is evidence of its occurrence in human immunodeficiency virus-negative individuals, presenting distinct epidemiological and pathological characteristics. Early and precise diagnosis is essential, as the disease can progress rapidly and may lead to severe or fatal outcomes. Full article

As a promising class of catalysts for enzymatic glucose sensors, Prussian blue analogues (PBAs) exhibit exceptional biomimetic activity. However, their performance is often constrained by poor intrinsic conductivity, which typically limits their sensitivity. To address this limitation, this study presents an effective approach using direct in situ growth of PBAs on the electrode substrates, which enables the effective integration of PBA-based electrochemical systems. A porous Ni framework was first electrodeposited onto a screen-printed gold electrode substrate, followed by the reduction of Pt onto the porous Ni. Subsequently, NiFe PBA was synthesized in situ using the porous Pt/Ni structure as a sacrificial template. Functionalized with glucose oxidase (GO_x), the PBA/Pt/Ni biosensor exhibited excellent performance for glucose detection in buffer solution, with a high sensitivity of 262.6 μA mM⁻¹·cm⁻² and an ultra-low detection limit of 1.45 μM (calculated at a signal-to-noise ratio of 3, S/N = 3). Notably, its sensitivity corresponds to a two-fold enhancement relative to the electrodes modified with commercial Prussian blue using the conventional drop-casting method. Even when tested in human sweat samples, the biosensor achieved a high sensitivity of 236.4 μA mM⁻¹·cm⁻² and a linear detection range of 20–1000 μM, with the broad sensing range fully encompassing the typical physiological concentrations of glucose in human sweat. This excellent performance arises from the high specific surface area of the porous Pt/Ni structure and the tight connection between PBA and the sacrificial Ni anode. This research presents a promising design strategy for advanced, wearable, and non-invasive health-monitoring platforms. Full article

The increasing demand for continuous physiological monitoring has accelerated the development of high-sensitivity wearable electrochemical platforms. This study reports the fabrication of a multi-analyte electrochemical sensor based on single-walled carbon nanotubes (SWCNTs) for the detection of sweat-associated metabolites. To facilitate efficient heterogeneous electron transfer, glucose oxidase (Gox), lactate oxidase (Lox), and urease (Ure) were immobilized onto the SWCNT network through π–π interaction using 1-pyrenebutanoic acid succinimidyl ester (PBSE), followed by additional stabilization via 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) coupling. The developed platform exhibited concentration-dependent resistance responses within the ranges of 0.02–0.20 mM for glucose, 20–100 mM for lactate, and 50–400 mM for urea under controlled experimental conditions. The resistance-based configuration enabled stable and reproducible signal modulation across these concentration intervals. Although direct testing with human sweat was not performed, the electrochemical behavior of key sweat-related metabolites was systematically evaluated as a preparatory step toward future wearable integration. Full article

The Green Oasis (GRO) Project is a targeted urban greening intervention designed to evaluate the environmental and health impacts of compact, high-density plantings in dense built environments. Initiated in downtown Louisville, the project transformed Founders Square, a 0.64-acre sparsely planted park, into a microforest (“Trager Microforest”), a multilayered planting of 119 trees and more than 200 shrubs. The impact of this intervention is being assessed through a randomized crossover study in which participants walk in the microforest and a nearby impervious parking lot. Physiological outcomes include heart rate, heart rate variability, arterial stiffness, and stress biomarkers measured in saliva, urine, and sweat. Environmental conditions are continuously monitored by fixed and mobile weather stations, air pollution sensors, and biodiversity surveys. Baseline assessments were conducted in 2023 and 2024, with post-planting evaluations now underway (2025–). Power calculations indicate adequate sensitivity (n ≈ 40–50) to detect changes in cardiovascular stress responses in participants. Complementary ecological measurements include soil microbiome composition, greenhouse gas fluxes, and avian diversity. This study addresses critical gaps in understanding how small-scale, high-density greening interventions affect cardiovascular resilience, stress physiology, and microclimatic regulation. By integrating environmental, biological, and human health data, GRO establishes a comprehensive framework for evaluating the efficacy of urban microforests as nature-based solutions. The results are expected to inform urban planning, public health strategies, and climate adaptation policies, demonstrating how compact greening interventions can simultaneously mitigate heat, reduce pollution, enhance biodiversity, and promote human wellbeing in dense urban cores. Full article

Background/Objectives: The COVID-19 pandemic has emphasized the urgent need for non-invasive diagnostic strategies. While breath analysis has been widely investigated, sweat and sebum remain largely unexplored, despite being abundant, chemically diverse, and easily collected. This exploratory study presents a proof-of-concept workflow to evaluate their potential for infection biomarker discovery. Methods: Samples from 51 subjects were analyzed by headspace solid-phase microextraction coupled with gas chromatography and time-of-flight mass spectrometry (HS-SPME-GC/ToF-MS). Over 8000 untargeted volatile compounds were detected, reflecting the high complexity of these matrices. Results: Data refinement and chemometric modelling using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) revealed robust separation between SARS-CoV-2-positive Patients and Controls. Classification accuracies consistently exceeded 95%, demonstrating the robust discriminative performance of the approach. Among the detected volatiles, 2-methylbenzenemethanol acetate emerged as the most informative compound, representing a potential biomarker candidate. Conclusions: This work shows that the sweat and sebum volatilome can be exploited for clinical applications. The workflow integrates non-invasive sampling, comprehensive chromatographic profiling, and advanced statistical modelling, representing a methodological contribution to analytical chemistry. Beyond COVID-19, the strategy provides a potential framework for volatile organic compound (VOC)-based diagnostics across different diseases and supports future development of sensor technologies for translation into healthcare practice. Full article

Deployed armed forces and the public engaged in outdoor activities are at high risk for mosquito bites and the diseases they transmit. Current mosquito bite-resistant garments prevent blood-feeding with slow-release insecticide formulations. Many people today want to avoid contact with pesticides, especially in their clothing. Insecticide treated clothing also is costly and requires regulatory agency approvals. Using mosquito bite-resistant mathematical textile models and a WholeGarment^® knitting technique, a seamless garment was constructed with military-compliant, no-melt, no-drip flame retardant yarns using an AiryPique knit architecture. The garment was 99.5% bite proof in walk-in cage bioassays with 200 Aedes aegypti host-seeking mosquitoes where the human subjects did not move for 20 min. A standard flame test and a PyroMan^TM flammability study validated the garment’s fire protection, a requirement for military uniforms. The thermal physiological comfort tests (air permeability, wetting time/radius, thermal resistance, evaporative resistance, and sweating thermal manikin test) were similar to current army combat uniforms and appropriate for use in everyday clothing. Bite prevention occurred by physically blocking the insect mouth parts from obtaining a blood meal. The knitting technique is well-suited for mass production of bite-resistant clothing through automation, significantly reducing labor, time, and cost by optimizing “fit on demand” for different body types compared to traditional manufacturing methods. This innovation provides a non-insecticidal, safe, scalable, and efficient solution for protecting individuals against mosquito bites. Full article

Heat exposure during strenuous exercise increases core temperature and cardiovascular strain, impairing performance and elevating the risk of heat illness. Standard countermeasures include heat acclimation, cooling, and hydration/electrolyte planning. Taurine is a sulfur-containing amino acid present in excitable tissues and widely used as an oral supplement; emerging human trials suggest it can augment thermoregulation, primarily by enhancing eccrine sweating and evaporative heat loss. This narrative review synthesizes mechanistic and applied evidence on taurine during exercise in hot environments and evaluates potential interactions with acclimation, cooling strategies (pre- and per-cooling), and hydration practices. Across a small number of randomized, mostly double-blind crossover studies, acute (~50 mg/kg) or short-term multi-day supplementation has been associated with earlier sweat onset, higher sweat production, modestly lower core temperature (~0.3–0.4 °C), and, in one multi-arm trial, a large standardized reduction in core temperature (d ≈ 1.9), with improved exercise capacity or performance. Benefits appear to be context-dependent and may be attenuated when sweating is constrained (e.g., impermeable protective clothing) or when heat acclimation is already optimized. Because taurine may increase sweat losses, its use should be paired with individualized fluid and sodium replacement. Current evidence is promising but remains constrained by small samples and heterogeneous protocols; adequately powered field trials are required to establish dose–response, safety and efficacy across populations, and additive value when combined with established heat-mitigation strategies. Full article

Pharmacological modulators of CFTR have significantly changed the cystic fibrosis (CF) phenotype of subjects affected by this multi-organ disease. Here, we evaluated the CFTR function analysis (short-circuit chamber in colonoids) in response to Elexacaftor/Tezacaftor/Ivacaftor (ETI) with the clinical benefits of in vivo treatment with ETI in ten CF subjects. We found that the functional response of ETI-corrected PDROS significantly correlated with the absolute change in the sweat chloride test. Thus, our work reinforces the use of organoid-derived human intestinal monolayers to guide clinicians in selecting CFTR-targeted therapies. Full article

Background: Artificial Intelligence (AI) and Machine Learning (ML) are increasingly integrated into sport and exercise through wearable biosensing systems that enable continuous monitoring and data-driven training adaptation. However, their practical value for coaching depends on the validity of biosensor data, the robustness of analytical models, and the conditions under which these systems have been empirically evaluated. Methods: A structured narrative review was conducted using Scopus, PubMed, Web of Science, and Google Scholar (2010–2026), synthesising empirical and applied evidence on wearable biosensing, signal processing, and ML-based adaptive training systems. To enhance transparency, an evidence map of core empirical studies was constructed, summarising sensing modalities, cohort sizes, experimental settings (laboratory vs. field), model types, evaluation protocols, and key outcomes. Results: Evidence from field and laboratory studies indicates that wearable biosensors can reliably capture physiological (e.g., heart rate variability), biomechanical (e.g., inertial and electromyographic signals), and biochemical (e.g., sweat lactate and electrolytes) markers relevant to training load, fatigue, and recovery, provided that signal quality control and calibration procedures are applied. ML models trained on these data can support training adaptation and recovery estimation, with improved performance over traditional workload metrics in endurance, strength, and team-sport contexts when evaluated using athlete-wise or longitudinal validation schemes. Nevertheless, the evidence map also highlights recurring limitations, including sensitivity to motion artefacts, inter-session variability, distribution shift between laboratory and field settings, and overconfident predictions when contextual or psychosocial inputs are absent. Conclusions: Current empirical evidence supports the use of AI-driven biosensor systems as decision-support tools for monitoring and adaptive training, but not as autonomous coaching agents. Their effectiveness is bounded by sensor reliability, appropriate validation protocols, and human oversight. The most defensible model emerging from the evidence is human–AI collaboration, in which ML enhances precision and consistency in data interpretation, while coaches retain responsibility for contextual judgement, ethical decision-making, and athlete-centred care. Full article

Human axillary malodor negatively influences impression-related appearance, confidence, and hygiene, and ultimately decreases quality of life. Malodor formation involves three steps: vesiculation of odorless precursors within the human body, influx of these precursors into the intracellular space of bacteria, such as Corynebacterium striatum and Staphylococcus hominis, and efflux of malodorous metabolites into the axilla after conversion by axillary malodor-releasing enzymes (AMREs). Malodor deodorants are currently in use, and their formulation strategies, based on the ingredients, can be classified as follows: anti-sweating, antiproliferation of malodor-forming bacteria, masking (neutralizing) effects against malodor, and deodorization. However, current deodorants have several adverse effects. To reduce such effects while enhancing malodor suppression, a strategy targeting the specific step in malodor formation should be developed, such as the use of ABCC11 pump inhibitors, specific bacterial active pump controllers, and AMRE blockers. Full article

Reliable methods for the isolation and culture of human eccrine sweat gland cells (SGCs) are essential for studying glandular biology and developing tissue-engineered skin substitutes (TESs) that restore full skin function. However, maintaining the glandular phenotype of SGCs in vitro remains a major challenge. In this study, we present an optimized isolation protocol combining enzymatic digestion with mechanical separation to improve SGC yield and purity, while also enabling keratinocyte isolation from a single human skin biopsy. We then evaluated two culture strategies, 2D monolayers and 3D spheroids, to determine their impact on SGC identity and proliferation. While 2D culture supported cell expansion, SGCs and keratinocytes exhibited highly similar marker expression profiles, with the absence of functional SGC markers (AQP5, α-SMA) reflecting a shift toward less differentiated phenotypes. In contrast, SGCs cultured in 3D spheroids preserved the expression of SGC-specific markers (AQP5, K18, α-SMA), distinguishing them from keratinocytes; however, their growth and structural organization were suboptimal under these 3D conditions. Moreover, SGCs expanded in 2D did not regain their glandular features when reintroduced into 3D culture, suggesting potential limitations in phenotype recovery. These results highlight the need for improved culture systems that maintain SGC identity while supporting expansion. Advancing such methods is a critical step toward integrating functional sweat glands into TESs and achieving complete skin regeneration for clinical applications. Full article

Human herpesvirus-8 (HHV-8)-associated multicentric Castleman disease (MCD) is a rare lymphoproliferative disorder with systemic and cutaneous manifestations that can be diagnostically challenging, especially in immunocompromised patients. We report the case of a 68-year-old man with HIV and biopsy-proven Kaposi sarcoma (KS), who developed progressive fevers, night sweats, weight loss, and fatigue, accompanied by diffuse lymphadenopathy, splenomegaly, and new erythematous and hyperpigmented lesions shortly after intravenous immunoglobulin therapy for Guillain–Barré syndrome. A laboratory evaluation revealed that the patient had elevated total protein and polyclonal hypergammaglobulinemia, without monoclonality. Imaging demonstrated widespread lymphadenopathy and splenomegaly. A core lymph node biopsy showed polytypic plasmacytosis, but was non-diagnostic. Given the ongoing symptoms, an excisional biopsy was performed, revealing regressed germinal centers with increased interfollicular vascularity, mantle zone “onion skinning,” and HHV-8 LANA-1 nuclear positivity, establishing the diagnosis of HHV-8-associated MCD. Rituximab monotherapy was initiated, resulting in clinical improvement, resolution of the constitutional symptoms, and stabilization of ascites. This case highlights the importance of maintaining a high index of suspicion for MCD in patients with KS who develop new systemic or cutaneous findings, the limitations of a core biopsy, and the value of a timely excisional biopsy in guiding diagnosis and treatment. Full article

Heat stress (HS), a pervasive environmental stressor, significantly disrupts systemic physiological homeostasis, posing substantial threats to human and animal health. Sheng Mai San (SMS), a classic Traditional Chinese Medicine (TCM) formula, exerts its therapeutic effects by replenishing qi (the vital energy governing physiological functions) and nourishing yin (the material basis responsible for moistening and cooling actions). This formula demonstrates significant efficacy in astringing sweating and preventing collapse. However, its precise molecular mechanisms against HS-induced myocardial injury remain incompletely elucidated. This study initially employed physicochemical analytical methods to determine the contents of total polysaccharides, saponins, and flavonoids in SMS and evaluated its antioxidant activity. Subsequently, both in vitro and in vivo rat models of HS were established to systematically assess the alterations in reactive oxygen species (ROS), antioxidant enzymes (GSH, SOD, CAT), and heat shock proteins (HSP70, HSP90) following SMS intervention, thereby investigating HS-induced myocardial injury and the protective effects of SMS. Furthermore, Western blot, immunofluorescence, and qRT-PCR techniques were utilized to quantitatively analyze key molecules in the Keap1-Nrf2-HO-1 and Stub1-HSF1 signaling pathways. The results demonstrated that total polysaccharides were the most concentrated in SMS, followed by total saponins. This formula exhibited potent free radical scavenging capacity against DPPH, ABTS, and OH⁻, along with significant reducing activity. HS-induced myocardial injury reached its peak severity at 6-12 h post-stress exposure. SMS intervention effectively suppressed excessive ROS generation, enhanced the activities of antioxidant enzymes (GSH, SOD, and CAT), and downregulated HSP70 and HSP90 mRNA expression levels, thereby significantly mitigating cardiomyocyte damage. Mechanistic investigations revealed that SMS conferred cardioprotection through dual modulation of the Keap1-Nrf2-HO-1 and Stub1-HSF1 signaling pathways. This study not only provides a novel TCM-based therapeutic strategy for preventing and treating HS-related cardiovascular disorders but also establishes a crucial theoretical foundation for further exploration of SMS’s pharmacological mechanisms and clinical applications. Full article

In the context of mounting mobility issues in Latin American cities, bicycles are emerging as a vital sustainable solution. However, their widespread adoption is hindered by various obstacles. This study aimed to identify and prioritize human factors inhibiting bicycle use in Colombia to support the development of effective public policies, given that research in this area mainly focuses on designing and developing road infrastructure for cyclists. An artificial intelligence classification methodology was applied to data from a self-administered online survey of 2068 participants. An objective variable was constructed to classify respondents as “potential users” or “non-potential users,” and three models (Logistic Regression, Random Forest, and XGBoost) were used to analyze the predictive power of different barriers. The results from the three models consistently show that personal, convenience, and safety perception barriers are significantly more important predictors than infrastructure factors. Specifically, inconvenience due to subsequent activities, perceived insecurity when cycling, and concern about sweating were consistently ranked as the most critical barriers. Therefore, to effectively promote cycling, public policies should address not only infrastructure development but also the mitigation of subjective and logistical barriers. Thus, these results can inform the design of more holistic mobility programs and serve as a foundation for future research on sustainable mobility. Full article

Blood lactate (BLa) concentration is a pivotal biomarker of exercise intensity and physiological stress, which provides insights into athletic performance and recovery. However, traditional lactate measurement requires invasive blood sampling, which presents significant limitations, including procedural discomfort, infection risks, and impracticality for continuous monitoring. Though non-invasive measurements of BLa concentration have emerged, most rely on a single physiological indicator like heart rate and sweat rate, and their accuracy and reliability remain limited. To address these limitations, this study proposes an innovative multi-sensor fusion framework for non-invasive estimation of BLa. By leveraging the inherent multisystem and multidimensional coordination of human physiology during exercise, the framework integrates a range of physiological signals (e.g., heart rate variability and respiratory entropy) and biomechanical signals (e.g., motion data). We proposed a stacking ensemble model that leverages the complementary strengths of these signals and achieved exceptional predictive performance with near-perfect correlation (R² = 0.9661) while maintaining high precision (MAE = 0.1816 mmol/L) and robustness (RMSE = 0.5891 mmol/L). Furthermore, the model’s exceptional capability extends to blood lactate threshold detection with 98.15% classification accuracy, which is a critical metric for training intensity optimization. This approach provides a robust, non-invasive solution for continuous exercise intensity monitoring, demonstrating significant potential for optimizing athletic performance through real-time physiological assessment and data-driven training modulation. Full article