Diabetes-related chronic wounds are difficult to heal due to persistent bacterial infection, disrupted pH homeostasis, and prolonged excessive inflammation. Consequently, effective wound monitoring and treatment integrated platforms are an urgent unmet demand to enable real-time assessment of wound progression and healing status. Herein, a bilayer theranostic hydrogel was developed as a wound dressing to achieve simultaneous infection monitoring and pathological micro-niche regulation. The therapeutic lower layer employed gelatin methacryloyl (GelMA), which incorporated quercetin-loaded liposomes (QLs) to sustain the suppression of inflammatory stress and improvement of glycemic regulation. The coordination interactions between copper ions and sodium alginate (SA) constituted a secondary network within the hydrogel, enhancing its antibacterial potential and mechanical strength. Monitoring pH alterations in wound niches can predict early infection and inflammation risk, thereby facilitating the optimization of wound management. Hence, the monitoring layer integrated bromothymol blue (BTB) as a pH indicator, enabling visual detection of pH variations and providing real-time feedback during healing. In a diabetic rat full-thickness wound model, the bilayer hydrogel significantly accelerated chronic wound closure. By integrating wound monitoring with antibacterial and anti-inflammatory dual functions, this multifunctional dressing provides insights into efficient healing and comprehensive assessment of diabetes-related chronic wounds.
Physical activity is associated with improved clinical outcomes across the cancer continuum. However, adherence to recommended activity levels among cancer survivors remains low. Digital health technologies such as smartwatches may support patients and survivors in achieving sufficient daily activity through continuous monitoring and feedback. Patients with head and neck cancer (HNC) often experience persistent functional limitations, yet evidence regarding the utility of wearable-based monitoring in this population remains limited. Therefore, the MOVE-1 study evaluated the feasibility of smartwatch-based monitoring in HNC survivors. MOVE-1 was a cross-sectional study investigating smartwatch use in HNC survivors. Participants were instructed to wear a smartwatch continuously for seven days (24 hours per day, 168 hours in total). Heart rate and step count were recorded and visible to participants via the smartwatch display. Feasibility parameters evaluated included recruitment rate, adherence assessed by heart rate data availability, frequency of display use (4-point Likert scale) and usability (System Usability Scale, SUS). Demographic and clinical characteristics were collected. Screened individuals who declined participation were analyzed separately regarding age, sex and reasons for refusal. The recruitment rate was 50%. There were no significant differences between participants and non-participants regarding sex or age. Common reasons for non-participation included lack of interest, sufficient self-reported physical activity, time constraints and low affinity for technology. Thirty-five HNC survivors were enrolled (median age 63 ± 6 years). Median smartwatch wearing time was 111 hours, out of a total of 168 hours (67%). Display functions were used "often" or "very often" by 60% of participants. Perceived usability was rated as good, with a mean SUS score of 74 (percentile rank 69, grade B). Reported dissatisfaction mainly concerned wristband handling, while three participants experienced difficulties operating the smartwatch. The median daily step count was 7,298 steps. Moderate-to-good adherence and good usability suggest that smartwatch-based monitoring of physical activity and vital parameters is feasible in HNC survivors, although alternative wristband designs may improve usability. The observed step counts indicate that included individuals were more physically active than average. These findings support future interventional studies using smartwatches to promote physical activity in this patient cohort.
MXenes, a rapidly expanding family of two-dimensional transition-metal carbides and nitrides, have emerged as a key material of self-powered wearable electronics and therapeutics owing to their metallic conductivity, mechanical flexibility, and highly tunable surface chemistry. Their integration into piezoelectric nanogenerators and triboelectric nanogenerators (PENGs and TENGs) has substantially advanced mechanical-to-electrical energy conversion in flexible, skin-conformal devices. This review critically examines recent progress in MXene-enabled nanogenerators, covering material synthesis, device architectures, charge-generation mechanisms, and system-level integration. Emphasis is placed on emerging MXene-based composites, including hydrogels, aerogels, nanofibers, and smart textiles, that synergistically integrate energy harvesting, sensing, and mechanical robustness for continuous physiological monitoring, human-machine interfaces, sports analytics, wearable therapeutics and in vivo applications. Key challenges limiting practical deployment, such as oxidation instability, mechanical fatigue, biocompatibility, and scalable manufacturing, are systematically analyzed alongside state-of-the-art mitigation strategies. Finally, future perspectives are outlined, highlighting the convergence of MXene nanogenerators with artificial intelligence, the Internet of Things, and sustainable materials systems to enable autonomous, intelligent, and next-generation, personalized monitoring and therapeutic technologies.
Enhanced Recovery After Surgery (ERAS) pathways in thoracic oncology emphasize early mobilization and objective discharge readiness, but perioperative functional recovery is often assessed intermittently. Wearable devices may provide continuous, objective recovery metrics. We conducted a PRISMA 2020-based systematic review registered in PROSPERO (CRD420261325339). PubMed, Scopus, and Web of Science Core Collection were searched for English-language studies published between February 2, 1996 and February 2, 2026. Eligible reports included adults undergoing lung cancer surgery or clinically relevant pulmonary resection and evaluated wearable-based activity, physiologic monitoring, or rehabilitation support across the preoperative, in-hospital, or post-discharge phases. Risk of bias was assessed using RoB 2, ROBINS-I, or design-appropriate feasibility and measurement appraisal. Certainty of evidence was qualitatively informed by GRADE principles, and findings were synthesized narratively because of clinical and methodological heterogeneity. Eight reports representing seven independent cohorts were included: two randomized trials, one nonrandomized trial with historical controls, two prospective observational studies, two companion single-arm preoperative feasibility/effectiveness reports, and one development/usability agreement study. In the Move For Surgery RCT, wearable-enhanced preconditioning reduced prolonged hospital stay >5 days from 24% to 7% (12/50 vs 3/45; p=0.021). A digital chest drainage RCT reported shorter postoperative length of stay and chest tube duration in the intervention group, although the cohort was not restricted to lung cancer. Observational studies showed weak but significant associations between perioperative step counts and recovery outcomes. Feasibility studies supported device use and data transmission, while a smartwatch-ePRO study showed close agreement with electronic health record measurements. Wearable-based perioperative monitoring appears feasible and may provide objective recovery signals in lung cancer surgery. However, current evidence remains sparse, heterogeneous, and often indirect. Findings should be interpreted as hypothesis-generating rather than sufficient to support routine clinical implementation. https://www.crd.york.ac.uk/PROSPERO/view/CRD420261325339, identifier CRD420261325339.
In the progression of Alzheimer's disease (AD), the levels of butyrylcholinesterase (BChE) increase significantly, making it a promising biomarker and therapeutic target. To investigate the functional role of BChE in AD pathogenesis, it is essential to develop diagnostic tools capable of visualizing its activity in a structure-function context. Herein, we designed and synthesized a series of fluorescent probes by conjugating environment-sensitive fluorophores to potent BChE inhibitors via rationally designed amine-functionalized linkers. Among these, the optimal probe LY36 integrates a naphthalimide-based fluorophore as the responsive unit and a selective BChE inhibitor pharmacophore as the recognition and therapeutic moiety. LY36 exhibits high selectivity for BChE over acetylcholinesterase (AChE), demonstrating a distinct "turn-on" fluorescence response upon binding to BChE while effectively inhibiting BChE enzymatic activity. Molecular dynamics simulations confirmed a highly stable and specific binding mode within the BChE active site. Furthermore, LY36 displays excellent in situ imaging performance in both cellular and animal models, and successfully visualizes elevated BChE levels. These findings suggest that LY36 holds promise as a simple and effective visualization tool for AD diagnosis, progression monitoring, and therapeutic evaluation.
Thyroid hormones have a crucial impact on all physiological systems. Diagnosis of thyroid diseases using salivary biomarkers is an emerging discipline and requires consolidation of existing information. This systematic review is aimed at identifying and analyzing salivary biomarkers that are associated with thyroid diseases and evaluate their potential as diagnostic applicability as non-invasive indicators of thyroid dysfunction. Literature search was conducted in PubMed, Cochrane, EBSCO, ProQuest, and Google Scholar from date of inception to May 2025. Human observational studies, clinical trials, and diagnostic accuracy studies published in the English language, that related biomarkers in saliva to thyroid diseases were collected and analyzed for relevant information. The search resulted in 35 records, followed by PRISMA 2020 compliant screening which resulted in 9 records included for data synthesis. Data extraction, tabulation and Risk of Bias assessment was carried out by 2 independent reviewers. Included studies suggest that FT3, amino acids, salivary metabolic profiling, glycan profiles, microbiome, and thyroid antibodies present in saliva could be putative and noninvasive biomarkers of diagnostic and prognostic importance. Heterogeneity in study design and analytical techniques has limited definitive conclusions about said markers, necessitating future well-designed clinical studies for validation of these biomarkers for noninvasive thyroid screeing and diagnosis. Hormones produced by thyroid glands have a role to play in all systems of the body. Hence abnormal thyroid function needs to be detected and treated earlier. Currently tests require blood samples that are invasive to collect requiring exploration of non invasive samples from the body. saliva is one such source and is being currently explored. This review searched studies that analyzed various substances in saliva that could indicate disorders in thyroid function. The analysis pointed at some compounds in saliva, viz. free T3 hormone, thyroid-related antibodies, certain amino acids, oral microbiomes to reflect thyroid problems. Among these, free T3 and thyroid antibodies are apparently the most promising variables in saliva that help diagnose and monitor thyroid diseases.
Low-dose computed tomography screening plays a pivotal role in early lung cancer detection. This narrative review aims to evaluate nodule characteristics, especially volume doubling time (VDT), and their relevance to lung cancer suspicion, staging, and clinical outcomes, to support more accurate risk stratification in screening programs for lung cancer. A literature search was conducted in PubMed, Scopus, and Web of Science, covering studies published from January 2012 to August 2024. A total of 27 studies (23 original and 4 reviews) were included. Key nodule features (VDT, size, attenuation, margins, histology, and stage) were extracted, reclassified, and analyzed to ensure standardized graphical comparison. Diagnostic performance metrics such as sensitivity, specificity, and predictive values of VDT were also assessed. Findings revealed that all malignant nodules had a VDT under 200 days, with the shortest VDTs observed in aggressive histological subtypes and advanced disease stages. PET-CT positivity correlated with shorter VDTs, and never-smokers exhibited faster nodule growth than ever-smokers. Stage-specific growth patterns showed a trend of decreasing VDT with disease progression. However, variability in study designs and classification criteria made it necessary to implement standardization. Digital tools in the field of lung imaging may be valuable assets in early detection and risk prediction and could minimize inter-reader variability and thus overdiagnosis. VDT is a valuable indicator for assessing nodule malignancy risk but should be integrated into multifactorial risk models. Standardizing VDT reporting and incorporating it into personalized lung cancer screening algorithms could enhance early detection and reduce overtreatment. Digital tools can support this integration by enabling accurate, automated VDT calculations, improving measurement consistency, and facilitating the incorporation of volumetric and attenuation data into advanced risk prediction models, provided that healthcare professionals receive proper training to use these tools effectively.
Forchlorfenuron (FCF), a widely utilized cytokinin-type plant growth regulator, poses a considerable threat to human health and ecological stability when overapplied. This issue has consequently driven an escalating demand for real-time, on-site monitoring technologies capable of detecting FCF residues in agricultural products and environmental matrices. Herein, computational quantum chemical analyses were conducted to elucidate the 3D structures of FCF and four designed haptens, thereby enabling the systematic evaluation of potential epitope masking sites. On the basis of these analyses, two structurally reliable haptens were screened out, which further facilitated the successful development of a highly matrix-tolerant and specific anti-FCF monoclonal antibody (mAb). Based on mAb, the AuNP-labeled double-T immunochromatographic assay was firstly developed to detect FCF in orange, grape, and soil samples. The limits of detection (LOD) were 2.640 µg kg-1, 1.069 µg kg-1, and 3.628 µg kg-1, respectively, with linear ranges of 3.55-296.25 µg kg-1, 1.44-231.37 µg kg-1, and 5.28-438.03 µg kg-1, respectively. Method validation confirmed that the obtained results were in good agreement with those derived from LC-MS/MS, thus verifying that the established double-T immunochromatographic assay is well suited for the rapid, quantitative, and on-site monitoring of FCF residues in food and environmental samples.
Axial spondyloarthritis (axSpA) is an inflammatory disease in which, despite expanding therapeutic options, a substantial proportion of patients do not achieve the desired treatment target, highlighting the emerging concept of difficult-to-manage (D2M) axSpA. To identify characteristics and predictive factors of D2M axSpA and to develop machine learning models for early identification. Longitudinal observational cohort study with external validation. Patients with axSpA from the SpA-Paz cohort initiating a first biological or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) between 2004 and 2019 were included. D2M was defined as failure of ⩾2 b/tsDMARDs, and very good responders (GR) as retention of the first b/tsDMARD ⩾3 years or discontinuation due to improvement. Baseline clinical data and baseline/6-month disease activity measures were collected. Factors associated with D2M were assessed using descriptive, comparative, and logistic regression analyses. Classification and Regression Tree (CART) models were developed and externally validated with the REGISPONSERBIO registry. Of 311 patients initiating b/tsDMARDs, 101 were included (42 D2M, 59 GR), with a D2M prevalence of 13.5%. D2M patients were more often smokers, Human Leukocyte Antigen B27 (HLA-B27) negative, and had higher rates of enthesitis and comorbidities. Baseline Axial Spondyloarthritis Disease Activity Score (ASDAS) and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) did not differ between groups, but after 6 months D2M patients showed higher disease activity (ASDAS 2.8 vs 1.6, BASDAI 5.4 vs 3.3; both p < 0.001). Multivariable models identified ASDAS, or BASDAI plus C-reactive protein (all at 6 months), as predictors of D2M. CART models achieved areas under the receiver operating characteristic curve of 0.70 (95% confidence interval (CI) 0.46-0.93; ASDAS model) and 0.76 (95% CI 0.55-0.97; BASDAI model), with external validation confirming discrimination. D2M axSpA affects approximately 1 in 8 patients initiating advanced therapy and is associated with smoking, HLA-B27 negativity, enthesitis, comorbidities, and poor 6-month response to first-line b/tsDMARDs. CART models using routine clinical data may support early identification. Identifying difficult-to-manage axial spondyloarthritis patients early in routine care: using clinical information and early treatment response to flag people more likely to need several advanced treatments Why was this study done? Axial spondyloarthritis is a long-term inflammatory condition that mainly affects the spine, but it can also involve other joints and cause symptoms involving the gut, eyes, and skin. Although several advanced treatments are available, some people do not improve enough and may need to change treatments more than once (“difficult-to-manage” disease). Early clues could help plan closer monitoring and earlier care decisions. What did the researchers do? Patients with axial spondyloarthritis from a hospital in Madrid, Spain, who started a first advanced treatment between 2004 and 2019 were studied. Two groups were compared: those who stopped at least two advanced treatments for any reason (difficult-to-manage) and those who did very well on the first treatment for ⩾3 years or stopped due to major improvement (very good responders). Clinical information was collected at the start and at 6 months. The researchers also developed clinical classification tools and tested them in an external Spanish registry. What did they find? Of 311 patients starting advanced treatment, 101 met the study definitions (42 difficult-to-manage and 59 very good responders). Difficult-to-manage disease affected about 1 in 8 patients. These patients were more often smokers, less often carriers of a genetic marker linked to the disease, and more likely to have inflammation of entheses and other health conditions. The clearest early warning sign was poor improvement after 6 months on the first advanced treatment; a standard disease activity score at 6 months was the strongest predictor. In the external registry, the classification tools showed acceptable performance in classifying patients as difficult-to-manage. What do these findings mean? Everyday clinic measures (especially the 6-month response to the first advanced treatment) may help identify patients at higher risk earlier, so care teams can monitor them more closely and adjust treatment sooner when needed.
Photothermal biomodulation is used to precondition platelet-rich plasma, but standardized laboratory workflows for monitoring associated physicochemical changes remain limited. This article describes a paired ex vivo protocol for assessing selected physicochemical parameters of platelet-rich plasma before and after photothermal preconditioning.•Platelet-rich plasma is prepared from donor blood, pooled per donor, and divided into paired control and photothermally preconditioned aliquots.•The protocol enables time-course monitoring of density/turbidity, pH, and temperature from baseline to 60 min.•Application in samples from three healthy donors showed that the workflow can detect small time-dependent differences between paired aliquots.
Dissolved organic carbon (DOC) is a major and dynamic carbon pool regulating carbon cycling in freshwater systems. Over the past two decades, research on freshwater DOC has moved beyond simple concentration monitoring to examine its sources, molecular composition, degradation potential, and interactions with climate change. Lake studies increasingly focus on DOC processing, long-term storage, and its role in greenhouse gas production, while river studies emphasize DOC mobilization, transport, and connectivity between terrestrial landscapes, inland waters, and downstream coastal environments. Long-term observations reveal increases in DOC concentrations in lakes and rivers, with mean growth rates of 0.042 and 0.015 mg L-1 per year, respectively. These trends are driven by multiple factors, including recovery from acid deposition, climate warming, extreme precipitation, and intensified human activities such as land-use change and wastewater discharge. Rising DOC concentrations lead to water browning, degraded water quality, biodiversity loss, and increased greenhouse gas emissions, with consequent socioeconomic impacts, particularly in fisheries and tourism. Addressing these challenges requires integrated strategies combining source control, long-term monitoring, and ecosystem restoration. Future research should prioritize global spatiotemporal dynamics of DOC concentration and composition by integrating field observations, remote sensing, and modeling to better understand and mitigate its ecological and socioeconomic impacts.
Cattle ranching is a sustainability challenge worldwide, and in the Amazon, the planet's largest tropical forest, it remains the main driver of deforestation. Yet, cattle numbers have typically been estimated from coarse census data or indirect proxies, limiting our ability to monitor land-use change at finer scales. Here, we introduce a novel approach that applies deep learning-based density estimation to very high-resolution satellite imagery to detect individual animals across the Brazilian Amazon. Our cattle data set covers over 12,000 km² in four states and is integrated with pasture maps to analyze property-level stocking rates. We find patterns of extensive land use, deriving conservative stocking rate estimates of 0.73 head per hectare in 2018-2019, with lower cattle stocking rates on properties with higher recent deforestation and properties further away from slaughterhouses. While the use of VHR imagery presents challenges of coverage and detection, our framework establishes a foundation for advancing livestock monitoring and supports strategies to address deforestation and promote sustainable resource management.
Surgical site infections (SSIs) remain among the most frequent healthcare-associated infections worldwide and are associated with significant morbidity, mortality, and healthcare costs. Despite availability of evidence-based guidelines, adherence to SSI prevention measures varies substantially across countries and institutions. In Ukraine, reliable data describing SSI prevention practices remain limited due to absence of nation-wide monitoring of infection prevention and control practices. We conducted two rounds of a national survey among surgeons and anaesthesiologists in Ukraine in 2021 and 2025. The survey was based on the World Health Organization (WHO) Global Guidelines for the Prevention of Surgical Site Infection (2018 edition) and assessed knowledge, attitudes, and self-reported adherence to recommended and non-recommended SSI prevention practices. Both surveys were distributed online via professional societies' platforms, targeting practicing surgeons and anaesthesiologists across different levels of healthcare facilities. In 2021, a total of 294 responses were received, followed by 145 responses in 2025. Across both survey periods, respondents represented a wide range of clinical specialties and geographic regions, with anaesthesiologists comprising the majority. In the 2025 survey, perioperative antimicrobial prophylaxis was reported as universally practiced (100%). In addition, active intraoperative warming was implemented by 82.6% of respondents and goal-directed fluid therapy by 93.8%. Despite these encouraging figures, several evidence-based measures were only partially adopted. For instance, alcohol-based chlorhexidine for skin preparation was used by 51%, surgical hand preparation with antiseptic soap by 60%, and intensive perioperative blood glucose control by 71.7% of respondents. Conversely, certain non-recommended practices, such as extended antimicrobial prophylaxis after surgery, remained prevalent, with 82.6% of respondents reporting its use. Although self-rated knowledge of WHO guidelines was generally high, notable gaps between awareness and actual practice were observed. This national survey, conducted in two rounds (2021 and 2025), was instrumental in understanding which SSI prevention practices are currently used in Ukraine. The continued use of non-recommended practices remains evident. These results underscore the need for targeted educational interventions, systematic monitoring, and strengthened institutional support to improve adherence to evidence-based guidelines and ultimately reduce the burden of SSIs nationwide.
The objective was to determine the test-retest reliability and concurrent validity of a drone system in comparison to a radar device. Seventeen male collegiate soccer players participated in two maximal 30-meter sprint runs. The test-retest reliability of the drone system was evaluated using intraclass correlation coefficients (ICC3,1), coefficient of variation (CV%), and standard error of measurement (SEM). Subsequently, the systematic bias and consistency of the two devices on various force-velocity (F-V) variables (e.g., maximal velocity [Vmax], theoretical maximal velocity [V0], theoretical maximal horizontal force [F0], the slope of the F-V relationship [SFV]) were evaluated using linear mixed model (LMM) and Bland-Altman analysis. The drone system demonstrated moderate to excellent test-retest reliability across all variables (0.59 ≤ ICC ≤ 0.95; CV% < 10%). While LMM analysis detected significant systematic differences for Vmax (p = 0.013) and V0 (p = 0.012), Bland-Altman analysis confirmed high practical agreement with minimal bias (≤ 1.12%) and narrow limits of agreement (LoA < 10%). Pmax, split times (T5m-T20m) and average accelerations (A10m-A20m) demonstrated greater consistency (%Bias ≤ 0.76%) with no significant systematic bias (p > 0.05). Conversely, early-acceleration and model-derived metrics (Tau, Amax, F0, SFV) exhibited significant bias (p ≤ 0.028) and wide LoA exceeding 10% (e.g., F0: -13.37% to 8.56%; SFV: -11.54% to 18.18%). In conclusion, although the drone system exhibits high monitoring value in the maximum speed phase, early-acceleration metrics (Amax, F0, and T5m) should be interpreted with caution for individual-level monitoring. The tracking instability during the early acceleration phase necessitates further algorithm optimization.
In light of the growing global trend toward health awareness, wearable technologies like smartwatches have become essential for monitoring physiological indicators such as heart rate (HR). However, their utility faces two critical challenges: a technical disparity between premium and affordable devices and a conceptual gap where objective HR may fail to capture the true subjective strain experienced by diverse populations. Consequently, this study has a dual objective: to evaluate the HR accuracy of four commercially available watches and examine how measurement variations propagate through a standardized HR-derived energy expenditure model; and to investigate the dissociation between objective HR and subjective perceived exertion (RPE) in individuals with elevated central adiposity. Forty healthy adults ( n = 40 ) participated in a 45 min multi-stage exercise protocol consisting of stretching, cycling, and running. Participants were stratified into two groups based on their waist-to-height ratio (WHtR): normal ( ≤ 0.5) and elevated (>0.5). Data were synchronized using a temporal alignment procedure, and calorie expenditure was calculated through a standardized heart-rate-based regression model to ensure fair comparisons across all devices. Premium smartwatches, specifically the Apple Watch and Garmin, demonstrated superior HR precision across all activity phases, maintaining high correlations ( r ≥ 0.98 ) with the clinical reference. While the low-cost Xiaomi and ThaiSook watches exhibited higher HR errors during motion-intensive activities, their derived calorie expenditure estimates remained remarkably stable and consistent with the reference standard. Notably, individuals with elevated WHtR reported significantly higher Ratings of Perceived Exertion (RPE) during running and recovery phases ( p < 0.05 ), despite showing no significant difference in heart rate responsiveness compared to leaner participants. This study confirms that while higher-end sensors offer greater heart rate precision, affordable wearables can provide sufficient HR data to yield consistent energy expenditure estimates when using a standardized mathematical model, supporting their potential utility in large-scale health monitoring. The divergence between objective heart rate and subjective exertion in participants with central adiposity indicates that heart rate alone is an insufficient gauge of exercise intensity. Consequently, personalized weight-management programs should integrate wearable-derived metrics with perceived effort to better account for the unique physiological and psychological strain associated with higher body mass.
Kawasaki disease (KD) is a leading cause of acquired heart disease in children. Although intravenous immunoglobulin (IVIG) therapy significantly reduces coronary complications, long-term management of these patients as they transition into adulthood remains a clinical challenge. We report a rare case of a 52-year-old patient from the first generation of IVIG-treated survivors of KD who required emergency surgical intervention for acute coronary syndrome (ACS). A 52-year-old man presented with persistent chest pain and dyspnea. He had been diagnosed with KD at the age of 5 and was treated with IVIG. Although he was monitored for coronary aneurysms until the age of 18, he had been lost to medical follow-up for 34 years and did not receive antiplatelet therapy during this period. Coronary angiography revealed complete occlusion of the proximal left anterior descending and right coronary arteries, with calcified aneurysms at both coronary orifices. Emergency off-pump coronary artery bypass grafting (OPCABG) was performed using an all-arterial anaortic technique. The left internal thoracic artery was grafted to the left anterior descending artery, and the right gastroepiploic artery was grafted to the posterior descending artery. The calcified aneurysms were left intact to avoid complex reconstruction requiring cardiopulmonary bypass. The postoperative course was uneventful, and coronary CT confirmed excellent graft patency. The patient was discharged on POD 14. As early generations of patients with KD reach their 50s, the combination of pre-existing vascular vulnerability and age-related atherosclerosis may increase the risk of acute coronary events. This case demonstrates that anaortic OPCABG using all-arterial grafts is a safe and effective strategy for managing ACS in this specific clinical scenario. It also highlights the need for standardized transitional care protocols to ensure continuous cardiovascular monitoring from childhood to adulthood.
Driver fatigue is a critical factor in traffic accidents and is strongly influenced by sleep deprivation and prolonged driving. This study examines physiological and subjective fatigue responses by combining Heart Rate Variability (HRV) indicators with the Karolinska Sleepiness Scale (KSS) and Rating of Fatigue (ROF) in a controlled driving simulation. Forty participants completed four driving sessions under normal sleep and sleep-deprived conditions, with HRV recorded in each session. The results show that increased driving duration was associated with autonomic imbalance, as reflected in lower mean RR, mean HR, RMSSD, and HF, which were associated with increased fatigue levels. In contrast, sleep duration did not significantly affect most HRV indices, although it had robust effects on subjective fatigue measures (ROF and KSS). Significant correlations were observed between HRV parameters and ROF, indicating that physiological changes aligned with subjective perceptions. To complement the statistical analysis, Logistic Regression and ensemble learning models were applied to classify fatigue-related conditions. XGBoost achieved the highest performance, with an accuracy of 77%, and identified Mean RR, mean HR, and LF as the most influential predictors. These findings indicate that combining HRV metrics with machine learning improves fatigue pattern detection and offers strong potential for developing real-time fatigue monitoring systems. The study highlights the importance of integrating objective and subjective measures to evaluate driver fatigue, particularly in conditions of sleep restriction and extended driving duration.
Ipilimumab is the first cytotoxic T lymphocyte protein-4 (CTLA-4) inhibitor approved in the United States. However, there is insufficient data on the safety of this drug in elderly patients. This study aimed to identify adverse events (AEs) associated with ipilimumab in elderly patients through the Adverse Event Reporting System (FAERS) database. This study retrieved adverse event reports related to ipilimumab in elderly patients (≥65 years) from the first quarter of 2011 to the first quarter of 2025 in the FAERS database. Multiple disproportionality analysis methods were used to detect adverse event signals associated with ipilimumab. A total of 18,698 adverse event reports were included. We identified 245 positive signals using four disproportionality methods. Common AEs included malignant neoplasm progression, diarrhea, colitis, pyrexia, rash, adrenal insufficiency, hypophysitis, and immune-mediated enterocolitis. In addition, we also identified some signals not listed on the drug label, such as orchitis, dropped head syndrome, and alopecia areata. Approximately 40% of AEs related to ipilimumab in elderly patients occurred within one month of medication use, with a median onset time of 42 days (interquartile range[IQR] 18-80days). Among these, AEs related to skin and subcutaneous tissue disorders had the shortest median time to onset, while those related to endocrine disorders had the longest median time to onset and continued to occur over time. The weight subgroup analysis indicated a statistically significant difference in the median time to AEs between the <70 kg and ≥70 kg populations (P<0.001). This study provides safety data on the use of ipilimumab in elderly patients and suggests prioritizing monitoring for gastrointestinal events and endocrine toxicities in elderly patients during treatment.
Associations between sleep duration and cognitive decline are inconsistent, and the value of longitudinal changes versus static measurements remains unclear. We identified longitudinal sleep patterns in 4780 older adults from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) using K-means clustering. Linear mixed-effects models and Cox models assessed cognitive decline and incident dementia risk over 10 years. The "Consistently Long" pattern showed the fastest cognitive decline (β = -0.027 standard deviation/year; p < 0.001) and highest cumulative dementia incidence. Conversely, patterns trending toward healthy duration slowed decline. However, adjusted Cox models found no significant association between sleep patterns and incident dementia risk. The trajectory of sleep duration, particularly the direction of change, is a powerful correlate of cognitive decline. Monitoring long-term dynamics outperforms static assessments for identifying high-risk older adults.
Acquired long QT syndrome (aLQTS) is a disorder of delayed myocardial repolarization induced by medications, electrolyte disturbances, and other factors, with a significantly higher risk in females than in males. Various perioperative factors can trigger aLQTS, which may lead to cardiac arrest in severe cases, yet clinical recognition remains challenging. This article reports a 38-year-old female patient who underwent laparoscopic combined hysteroscopic tubal lavage under general anesthesia for "bilateral tubal obstruction." During the procedure, the patient suddenly developed a heart rate of 40 beats per minute, followed by torsade de pointes (TdP) that rapidly progressed to cardiac arrest. The patient was successfully resuscitated after timely cardiopulmonary resuscitation, defibrillation, and pharmacological interventions. Postoperative electrocardiogram and 24-h Holter monitoring showed progressive prolongation of the QTc interval, reaching a maximum of 581 ms. Follow-up electrocardiogram at 1 month post-surgery showed that the QTc interval had returned to normal (421 ms). Based on a review of the literature, the final diagnosis was aLQTS. aLQTS is one of the important causes of perioperative cardiac arrest. Female sex, electrolyte disturbances, bradycardia, and QT-prolonging medications can act synergistically as triggers. Comprehensive interventions including early recognition of abnormal electrocardiographic signals, timely resuscitation, and correction of precipitating factors are key to improving prognosis.