Continuous Monitoring Research Articles

Continuous High-Temperature Thermoelectric Power Monitoring of Thermal Embrittlement

Continuous High-Temperature Thermoelectric Power Monitoring of Thermal Embrittlement

Detecting cardiac states with wearable photoplethysmograms and implications for out-of-hospital cardiac arrest detection.

Out-of-hospital cardiac arrest (OHCA) is a global health problem affecting approximately 4.4million individuals yearly. OHCA has a poor survival rate, specifically when unwitnessed (accounting for up to 75% of cases). Rapid recognition can significantly improve OHCA survival, and consumer wearables with continuous cardiopulmonary monitoring capabilities hold potential to "witness" cardiac arrest and activate emergency services. In this study, we used an arterial occlusion model to simulate cardiac arrest and investigated the ability of infrared photoplethysmogram (PPG) sensors, often utilized in consumer wearable devices, to differentiate normal cardiac pulsation, pulseless cardiac (i.e., resembling a cardiac arrest), and non-physiologic (i.e., off-body) states. Across the classification models trained and evaluated on three anatomical locations, higher classification performances were observed on the finger (macro average F1-score of 0.964 on the fingertip and 0.954 on the finger base) compared to the wrist (macro average F1-score of 0.837). The wrist-based classification model, which was trained and evaluated using all PPG measurements, including both high- and low-quality recordings, achieved a macro average precision and recall of 0.922 and 0.800, respectively. This wrist-based model, which represents the most common form factor in consumer wearables, could only capture about 43.8% of pulseless events. However, models trained and tested exclusively on high-quality recordings achieved higher classification outcomes (macro average F1-score of 0.975 on the fingertip, 0.973 on the finger base, and 0.934 on the wrist). The fingertip model had the highest performance to differentiate arterial occlusion pulselessness from normal cardiac pulsation and off-body measurements with macro average precision and recall of 0.978 and 0.972, respectively. This model was able to identify 93.7% of pulseless states (i.e., resembling a cardiac arrest event), with a 0.4% false positive rate. All classification models relied on a combination of time-, power spectral density (PSD)-, and frequency-domain features to differentiate normal cardiac pulsation, pulseless cardiac, and off-body PPG recordings. However, our best model represented an idealized detection condition, relying on ensuring high-quality PPG data for training and evaluation of machine learning algorithms. While 90.7% of our PPG recordings from the fingertip were considered of high quality, only 53.2% of the measurements from the wrist passed the quality criteria. Our findings have implications for adapting consumer wearables to provide OHCA detection, involving advancements in hardware and software to ensure high-quality measurements in real-world settings, as well as development of wearables with form factors that enable high-quality PPG data acquisition more consistently. Given these improvements, we demonstrate that OHCA detection can feasibly be made available to anyone using PPG-based consumer wearables.

Patterns and trends in melanoma mortality in Spain (1999-2022).

To examine melanoma mortality trends in Spanish Autonomous Communities from 1999 to 2022, focusing on gender and age differences. Data from the National Statistics Institute were used to calculate age-standardized mortality rates (ASMRs). Joinpoint regression identified trend changes. Melanoma mortality varied significantly by region, gender, and age. Eastern Spain had higher male mortality, while western regions had lower rates. Asturias had higher female mortality, with lower rates in Andalusia, Extremadura, and Castilla-La Mancha. Men generally exhibited higher ASMRs than women, with variations across regions. While ASMRs remained stable in most areas, Madrid experienced a notable decline (AAPC: - 1.3%). A national trend reversal occurred in 2014 (AAPC: - 1.3%). For individuals aged 45-74 years, Catalonia saw a significant decrease (AAPC: - 1.1%, p < 0.05), whereas Andalusia experienced an increase (APC: 2.1% since 2007). Nationally, ASMRs for this age group declined (AAPC: - 0.7%). Among those aged 75 years and over, ASMRs varied considerably, with increases observed in Andalusia and Aragon. Nationally, male ASMRs rose (AAPC: 1.6% per year), while female rates were stable. Regional disparities were evident, with higher female mortality in the Balearic Islands and fluctuating rates in the Community of Madrid (an increase followed by a decrease after 2015). The gender gap in mortality varied across regions, with some areas showing a narrowing gap and others widening disparities. Continuous monitoring of melanoma mortality, especially among men and older adults, is crucial. Public health efforts should address regional disparities, improve early detection, and enhance treatment access to optimize outcomes nationwide.

Continuous digital cough monitoring during 6-month pulmonary tuberculosis treatment

Continuous digital cough monitoring during 6-month pulmonary tuberculosis treatment

A reduced carbohydrate diet improves glycemic regulation in hyperglycemic older people in a retirement home: The SAGE study.

Poor glucose regulation associated with gradual insulin resistance is a significant risk factor in several age-related chronic diseases. An eating plan that promotes a lower carbohydrate intake may have a beneficial effect on glucose metabolism. This study aimed to evaluate how a diet reduced carbohydrate by 32% (RCHO) over a 2-month period would influence the metabolic profile of older individuals (N = 24) living in a retirement home (RH). A continuous glucose monitor was used to measure blood glucose during four periods: the standard diet before (baseline) and after (washout) the intervention, during the 4 initial days of the RCHO diet (RCHO-early), and the final days of the 2-month intervention (RCHO-end). The blood metabolic profile was also measured (glucose, ketones, insulin, triglycerides and cholesterol). RCHO intake decreased average blood glucose compared to the standard diet in hyperglycemic participants: RCHO-early 7.8 ± 1.0 vs 7.5 ± 1.1 mM (p = 0.012) and RCHO-end 7.8 ± 1.0 vs 7.0 ± 0.9 mM (p = 0.050). In the hyperglycemic participants, the percentage of time spent in hyperglycemia (> 10.0 mM) decreased by 50% during the RCHO-early (p = 0.012) and by 66% at RCHO-end (p = 0.021) compared to baseline. Glycated hemoglobin was significantly lower at RCHO-end in both hyperglycemic and normoglycemic participants compared to baseline (p < 0.008). Plasma ketones increased 3-fold in hyperglycemic participants at RCHO-end compared to baseline (p < 0.028). This study shows that an RCHO diet has metabolic health benefits in an older population and confirms its safety, tolerability, and acceptability in a RH. (NCT06022094).

High frequency of acquired virulence factors in carbapenemase-producing Klebsiella pneumoniae isolates from a large German university hospital, 2013-2021.

Carbapenemase-producing Klebsiella pneumoniae (CP-Kp) isolates are a public health concern as they can cause severe hospital-acquired infections that are difficult to treat. It has recently been shown that CP-Kp can take up virulence factors from hypervirulent K. pneumoniae lineages. In this study, 109 clinical CP-Kp isolates from the University Hospital Cologne were examined for the presence of acquired virulence factors using whole-genome sequencing and phenotypic tests, and results were linked to clinical data. The virulence factor iuc was present in 18/109 of the CP-Kp isolates. Other acquired virulence factors, such as ybt, cbt, iro, rmpA/rmpA2, peg-344, and hypervirulence-associated capsule types were detected in various combinations among these isolates. The iuc-positive isolates produced OXA-232 (n = 7), OXA-48 (n = 6), OXA-48+NDM (n = 3), NDM, and KPC (each n = 1), and 7/18 isolates were resistant to ceftazidime-avibactam, colistin, and/or cefiderocol. Four isolates carried hybrid plasmids that harbored acquired virulence factors alongside the carbapenemase genes blaNDM-1/5 or blaOXA-48. In 15/18 patients, iuc-positive CP-Kp were isolated from a clinically manifest infection site. Among these, four patients had osteomyelitis, and four patients died from pneumonia with OXA-232-producing ST231 isolates, three of them as part of an outbreak. In conclusion, acquired virulence factors are frequently detected in various combinations in carbapenemase-producing K. pneumoniae isolates in Germany, warranting continuous monitoring of infections caused by these strains.

Posterior fossa decompression in patients with Chiari malformation type 1: effect on sleep apnea and follow-up outcomes.

Sleep apnea, posing significant health risks, is frequently associated with Chiari malformation (CM), characterized by cerebellar tonsil herniation through the foramen magnum. Central sleep apnea (CSA) in CM results from impaired brain-to-muscle signaling and requires treatment. Conversely, obstructive sleep apnea (OSA), arising from throat muscle relaxation, typically unrelated to CM, often coexists. This study evaluates the effectiveness of posterior fossa decompression (PFD) on sleep apnea. A retrospective chart review was conducted of pediatric patients with CM-1 and sleep apnea who underwent PFD between April 1, 2004, and September 30, 2022. Data collected included demographics, clinical characteristics, adenotonsillectomy status, PFD details, and sleep study parameters like the apnea-hypopnea index and respiratory disturbance index. Statistical analysis assessed the surgery's impact on sleep apnea severity. The study included eleven patients, predominantly male (63.6%). All had OSA (100%), with 63.6% also having CSA. Preoperative sleep studies classified OSA severity as 36.4% mild, 18.2% moderate, and 45.5% severe, with no change post-surgery. CSA severity initially included seven mild cases, which became three mild, one moderate, and three resolved cases post-surgery. Among seven patients who had adenotonsillectomy before decompression, five showed no improvement in OSA severity post-surgery. This study elucidates the complex relationship between CM-1, sleep apnea, and PFD. The findings show the persistence of sleep apnea in some patients and highlight the need for continuous monitoring of these patients in order to optimize their care after surgery.

Fully Integrated Biosensing System for Dynamic Monitoring of Sweat Glucose and Real-Time pH Adjustment Based on 3D Graphene MXene Aerogel.

The development of noninvasive glucose sensors capable of continuous monitoring without restricting user mobility is crucial, particularly for managing diabetes, which demands consistent and long-term observation. Traditional sensors often face challenges with accuracy and stability that curtail their practical applications. To address these issues, we have innovatively applied a three-dimensional porous aerogel composed of Ti3C2Tx MXene and reduced graphene oxide (MX-rGO) in electrochemical sensing. It significantly reduces the electron-transfer distance between the enzyme's redox center and the electrode surface while firmly anchoring the enzyme layer to effectively prevent any leakage. Another pivotal advancement in our study is the integration of the sensor with a real-time adaptive calibration mechanism tailored specifically for analyzing sweat glucose. This sensor not only measures glucose levels but also dynamically monitors and adjusts to pH fluctuations in sweat. Such capabilities ensure the precise delivery of physiological data during physical activities, providing strong support for personalized health management.

Ability of Heart Rate Recovery and Gait Kinetics in a Single Wearable to Predict Frailty: Quasiexperimental Pilot Study.

Aging is a risk factor for falls, frailty, and disability. The utility of wearables to screen for physical performance and frailty at the population level is an emerging research area. To date, there is a limited number of devices that can measure frailty and physical performance simultaneously. The aim of this study is to evaluate the accuracy and validity of a continuous digital monitoring wearable device incorporating gait mechanics and heart rate recovery measurements for detecting frailty, poor physical performance, and falls risk in older adults at risk of falls. This is a substudy of 156 community-dwelling older adults ≥60 years old with falls or near falls in the past 12 months who were recruited for a fall prevention intervention study. Of the original participants, 22 participants agreed to wear wearables on their ankles. An interview questionnaire involving demographics, cognition, frailty (FRAIL), and physical function questions as well as the Falls Risk for Older People in the Community (FROP-Com) was administered. Physical performance comprised gait speed, timed up and go (TUG), and the Short Physical Performance Battery (SPPB) test. A gait analyzer was used to measure gait mechanics and steps (FRAIL-functional: fatigue, resistance, and aerobic), and a heart rate analyzer was used to measure heart rate recovery (FRAIL-nonfunctional: weight loss and chronic illness). The participants' mean age was 74.6 years. Of the 22 participants, 9 (41%) were robust, 10 (46%) were prefrail, and 3 (14%) were frail. In addition, 8 of 22 (36%) had at least one fall in the past year. Participants had a mean gait speed of 0.8 m/s, a mean SPPB score of 8.9, and mean TUG time of 13.8 seconds. The sensitivity, specificity, and area under the curve (AUC) for the gait analyzer against the functional domains were 1.00, 0.84, and 0.92, respectively, for SPPB (balance and gait); 0.38, 0.89, and 0.64, respectively, for FRAIL-functional; 0.45, 0.91, and 0.68, respectively, for FROP-Com; 0.60, 1.00, and 0.80, respectively, for gait speed; and 1.00, 0.94, and 0.97, respectively, for TUG. The heart rate analyzer demonstrated superior validity for the nonfunctional components of frailty, with a sensitivity of 1.00, specificity of 0.73, and AUC of 0.83. Agreement between the gait and heart rate analyzers and the functional components of the FRAIL scale, gait speed, and FROP-Com was significant. In addition, there was significant agreement between the heart rate analyzer and the nonfunctional components of the FRAIL scale. The gait and heart rate analyzers could be used in a screening test for frailty and falls in community-dwelling older adults but require further improvement and validation at the population level.

Clinical analysis of abnormal muscle response monitoring for hemifacial spasm during microvascular decompression: a retrospective study.

Microvascular decompression (MVD) is a widely recognized therapeutic approach for the treatment of hemifacial spasm (HFS). Abnormal muscle response (AMR) is a distinctive electromyographic finding exclusively in patients with HFS. The purpose of our investigation was to determine the correlation between changes in intraoperative AMR and surgical efficacy, as well as the incidence of postoperative complications in patients with HFS after undergoing MVD. In this retrospective study, we evaluated 145 patients with HFSs treated with MVD, which was maintained for 1year postoperatively. The subjects were divided into two groups based on the persistence or disappearance of AMR. Continuous monitoring of AMR during surgery provided data on persistence. All patients were followed up 1day, 30days, and 1year after MVD. A range of potential predictive factors, such as patient demographics, symptom duration, and morphology and latency of AMR, were analyzed using binary logistic regression to assess their relationship with postoperative non-cure and delayed cure rates. The 1day postoperative cure rate was 77.9%, with a 1year postoperative cure rate of 94.59% and 1day postoperative relief rate of 87.6%. A marked distinction was noted between preoperative and 1year postoperative Cohen grades (P < 0.05). Moreover, 1day after surgery, the outcome demonstrated significant variability, as shown by the binary logistic regression model (χ2 = 62.913, P < 0.05). The results suggested that factors such as age, symptom duration, disappearance of AMR, and preoperative carbamazepine treatment markedly influence outcomes 1day after surgery. The binary logistic regression model for delayed cure at 1year showed significant variability (χ2 = 54.883, P < 0.05). Furthermore, analysis using generalized estimating equations revealed that the duration of postoperative follow-up significantly impacted Cohen grades, as did the disappearance of AMR, with the grade of AMR disappearance being only 10% of that of non-AMR disappearance (P < 0.05). Our findings suggest that MVD is an effective intervention for HFS. Our findings also indicate that factors such as patient age, duration of symptoms, disappearance of AMR, and preoperative carbamazepine therapy are significant predictors of 1day postoperative cure rate. Major predictors for delayed cure at 1year include age, symptom duration, AMR disappearance, preoperative carbamazepine and botulinum neurotoxin administration, single morphology AMR, and offending vertebral artery.

Smart watch applications in atrial fibrillation detection: Current state and future directions.

Atrial fibrillation (Afib) is a prevalent chronic arrhythmia associated with severe complications, including stroke, heart failure, and increased mortality. This review explores the use of smartwatches for Afib detection, addressing the limitations of current monitoring methods and emphasizing the potential of wearable technology in revolutionizing healthcare. Current Afib detection methods, such as electrocardiography, have limitations in sensitivity and specificity. Smartwatches with advanced sensors offer continuous monitoring, improving the chances of detecting asymptomatic and paroxysmal Afib. The review meticulously examines major clinical trials studying Afib detection using smartwatches, including the landmark Apple Heart Study and ongoing trials such as the Heart Watch, Heartline, and Fitbit Heart Study. Detailed summaries of participant numbers, smartwatch devices used, and key findings are presented. It also comments on the cost-effectiveness and scalability of smartwatch-based screening, highlighting the potential to reduce healthcare costs and improve patient outcomes. The integration of wearable technology into healthcare can lead to earlier diagnosis, improved patient engagement, and enhanced cardiac health monitoring. Despite ethical considerations and disparities, the potential benefits outweigh the challenges. This review calls for increased awareness, collaboration with insurance companies, and ongoing research efforts to optimize smartwatch accuracy and encourage widespread adoption of Afib detection. With insights from major trials, this review serves as a comprehensive reference for healthcare professionals and policymakers, guiding future strategies in the early diagnosis and management of atrial fibrillation.

An uncertainty‐based evaluation of sulphuric compounds transport in reservoirs considering sensitivity analysis

AbstractDeepwater bodies such as dam reservoirs are among the most prominent water resources that supply societies' water demand. Hence, water quality in these resources requires continuous and meticulous monitoring. This study evaluated the water quality of Changuleh Dam, a dam under construction in western Iran, using the CE‐QUAL‐W2 model to predict fluctuations in sulphate (SO42−) and hydrogen sulphide (H2S) concentrations. A sensitivity analysis was conducted to assess the dependence of model outputs on input variables. Additionally, an uncertainty analysis was performed using MATLAB to address the inherent uncertainties of the input variables through an ARIMA (2, 2, 1) time series model and Monte Carlo simulations. The results indicated a high sulphate concentration averaging 955.6 mg/l, considerably exceeding the drinking water standard of 400 mg/l, identifying the reservoir as a sulphate‐rich water resource. Seasonal fluctuations of H2S concentrations were also observed in the reservoir's anaerobic bed sediments, peaking at 87 mg/l. The sensitivity analysis showed that nitrate and total dissolved solids (TDS) varied more noticeably than dissolved oxygen (DO) at different depths, with the greatest variation at 50 m. This study highlights the critical need for continuous and meticulous monitoring of water quality in dam reservoirs to meet water supply standards.

Impact of Continuous Glucose Monitoring on Glycemic Control and Lifestyle Changes among Diabetes Patients: Evidence from a Diverse Indian Cohort

Abstract Background: Continuous glucose monitoring (CGM) has emerged as a pivotal technology in diabetes management, offering real-time insights into glucose fluctuations. This study aims to assess the impact of CGM on glycemic control and lifestyle changes among diabetes patients in India. Methodology: A retrospective observational study was conducted on a cohort of 556 diabetes patients from 3 diabetes centers across India. Data were collected using a structured questionnaire focusing on demographics, CGM usage patterns, lifestyle changes, and glycemic outcomes, particularly hemoglobin A1c (HbA1c) levels. The analysis included descriptive statistics and inferential methods, such as paired t-tests and regression analysis, to evaluate the relationship between CGM usage and changes in glycemic control and lifestyle behaviors. Results: The study revealed a significant reduction in HbA1c levels, with an average decrease of 0.85% across the cohort. A higher frequency of CGM use was associated with greater improvements in glycemic control. Patients who made dietary improvements and managed stress levels effectively, as guided by real-time CGM feedback, exhibited more pronounced reductions in HbA1c. The study also identified that demographic factors such as age and gender had minimal influence on glycemic outcomes. A clustering analysis grouped patients based on their HbA1c improvement, identifying distinct patterns of lifestyle changes and CGM usage. Conclusion: CGM significantly improves glycemic control and promotes positive lifestyle changes among diabetes patients in India. The findings underscore the importance of frequent CGM usage and patient engagement in achieving optimal outcomes. Despite the challenges related to cost and accessibility in the Indian context, CGM presents a valuable tool for enhancing diabetes management. Future research should focus on optimizing CGM usage patterns and addressing barriers to its widespread adoption.

A-092 Siemens Healthineers Commitment to Quality - A Focus on Continuous Improvement and Customer Experience

Abstract Background It is necessary that each step of in vitro diagnostic assay development and manufacturing processes be documented and executed in alignment with established quality management systems. Here, we describe how Siemens Healthineers (SHS) maintains assay traceability and focus on continuous improvement using the Atellica® CH A-LYTE® Integrated Multisensor Technology (IMT) assays measuring electrolytes sodium (Na), potassium (K), and chloride (Cl) as a prime example. Methods Establishing an unbroken chain of comparison from the National Institute of Standards and Technology (NIST) higher standard references to the product calibrators ensures accurate value assignment within stated measurement uncertainties. Traceability and standardization are achieved by creating a panel of 10 serum anchor pools spanning the analytical measuring interval for each electrolyte: Na, K, and Cl. The concentrations of the anchor pools are determined at a reference laboratory using methods calibrated with standard solutions derived from NIST reference material. These serum anchor pools are used by SHS, assigning values to product calibrator material which maintains the chain of traceability to the primary reference methods. In addition to traceability, onboard stability for the A-LYTE® IMT multisensor is continuously monitored and evaluated against allowable drift limits for each electrolyte. Although observed drift was within allowable limits, a design change was implemented to improve recovery drift over the use life of the sensor. Results To ensure consistent, robust, and accurate performance of the A-LYTE IMT, a strict set of testing procedures are used to verify the accuracy of value assignments for each manufactured lot of master standards. The recovery of the NIST standard reference material must fall within manufacturer established acceptable bias limits. Consistency over nine master lots is shown with bias ranging from -0.9% to +1.9%, -2.4% to +1.8% and -1.8 to +0.5%, for Na, K and Cl, respectively. By further optimizing the amount of Na ionophore and the polymer matrix of the Na sensor, drift over the use life was minimized and onboard stability improved. Prior to making the sensor change, customer Na QC data at 116 mmol/L showed an SD of 1.1 mmol/L (n=585), whereas the precision improved to an SD of 0.6 mmol/L (n=470) post-optimization. As Manufacturers optimize assay performance, it may become necessary for laboratories to re-evaluate reference intervals for their patient populations. For example, one large integrated delivery network established a new reference interval for patient anion gap (AG). A re-evaluation of the historical AG reference interval which was 5-15 mmol/L identified the need for an update. AG values were calculated from 16,948 healthy patients and used to establish a new reference interval of 2-10 mmol/L. Conclusions Accurate clinical laboratory measurements are critical for diagnosing, monitoring, and treating diseases. A-LYTE assays have an unbroken chain of traceability to NIST reference material and minimal drift over the life of the multisensor. Continuous monitoring to identify improvement projects and rigorous control systems ensure sensor performance over time. This provides confidence that the patient results produced by the laboratory are accurate and consistent over time and across different laboratory locations.

Detection of Volcanic Ash Using Goes-16 Satellite Imagery: Case Study of Popocatépetl Volcano, Mexico

Objective: The objective of this study is to investigate the accuracy of volcanic ash detection using satellite imagery, to improve existing monitoring tools to adapt them to the Popocatépetl volcano in Mexico. Theoretical Framework: Volcanic ash detection via remote sensing employs Pavolonis' algorithms that compare radiances in the thermal and mid-infrared spectrum. This approach differentiates ash from clouds and water vapor by leveraging its differential absorption. Satellites such as GOES-16, which capture multispectral data, optimize the continuous detection and monitoring of ash dispersion, even in areas of low concentration. Method: Three volcanic ash detection algorithms were compared using images from the Popocatépetl eruption event on May 21, 2023: two developed by Pavolonis, which combine thermal and mid-infrared bands, and a third, a spectral adaptation designed to enhance precision at the edges of the ash cloud, tailored to the study area. Results were validated with an RGB ash image provided by NOAA. Results and Discussion: Pavolonis' algorithms provided a solid foundation for general detection, but the third algorithm, specifically designed for this study, significantly improved edge detection where classification conditions are more complex. This improvement was reflected in a higher agreement with the RGB ash image used as a reference. However, limitations related to atmospheric interference were identified, which require further adjustments in low ash concentration scenarios. Research Implications: The findings of this research have significant practical and theoretical implications for volcanic risk management and environmental protection. Enhanced accuracy in volcanic ash detection can optimize monitoring and early warning strategies, reducing risks to public health and infrastructure. Originality/Value: This study contributes to the literature by introducing a specific spectral adaptation to improve edge detection of volcanic ash, a novel approach not previously addressed. The research's relevance lies in its ability to refine monitoring methodology, providing more effective tools for volcanic risk management and offering a model applicable to other areas facing similar remote sensing challenges.

Development of an artificial intelligence-enabled non-invasive digital stethoscope for monitoring the heart condition of athletes in real-time

This study investigates the efficacy of AI-enabled digital stethoscopes in enhancing physical performance, increasing student engagement and motivation, and improving psychological well-being among physical culture students. The experimental design involved two groups of 40 students each: the experimental group used AI-enabled stethoscopes for real-time cardiovascular monitoring, while the control group relied on traditional heart rate monitoring methods. The results indicated significant improvements in physical performance, engagement, and psychological well-being for the experimental group. Real-time monitoring facilitated personalized training adjustments, optimizing training loads and preventing overexertion, leading to superior performance outcomes. Additionally, the use of innovative monitoring tools significantly increased student motivation and engagement in physical culture classes, as reflected in higher attendance rates and more enthusiastic participation. Psychological assessments revealed that continuous health monitoring reduced anxiety levels and enhanced overall mental well-being, providing students with a sense of security and proactive health management. These findings underscore the transformative potential of integrating advanced monitoring technologies into physical education and rehabilitation programs, offering precise, real-time data that supports individualized and responsive interventions. The study concludes with a call for further research to explore the long-term impacts and broader applications of AI-enabled health monitoring tools in diverse educational and clinical settings, aiming to maximize their benefits and improve overall student and patient outcomes. Keywords: Sports therapy, Physical culture education, Health monitoring technology, Personalized training, Student engagement, Real-time cardiovascular monitoring, AI-enabled stethoscope.

An Invisible Dermal Nanotattoo-Based Smart Wearable Sensor for eDiagnostics of Jaundice.

Despite substantial progress in the diagnosis of jaundice/hyperbilirubinemia as the most common disease and cause of hospitalization of newborns, on the eve of Industry/Healthcare 5.0, the development of accurate and reliable wearable diagnostic sensors for noninvasive smart monitoring of bilirubin (BIL) is still in high demand. Aiming to fabricate a smart wearable sensor for early diagnosis of neonatal jaundice and its therapeutic monitoring, we here report a fluorescent dermal nanotattoo that further coupled with an IoT-integrated wearable optoelectronic reader for minimally invasive, continuous, and real-time monitoring of BIL in interstitial fluid. Selective recovery of quenched fluorescence of the dermal tattoo sensor, composed of biocompatible dissolving/hydrogel microneedles loaded with fluorescent carbon quantum dots, upon blue light exposure used for jaundice phototherapy was utilized for highly selective BIL sensing. The fascinating features of our developed smart wearable tattoo sensor and its successful results with high correlation with blood BIL results make it a highly promising sensor for easy, minimally invasive, reliable, and smart eDiagnostics and continuous therapeutic eMonitoring of jaundice and other BIL-induced diseases at the point of care. We envision that the developed nanotattoo sensing bioplatform will inspire the development of future smart tattoo sensors in various diagnostic and monitoring scenarios.

Assessment of groundwater quality in the eastern part of tehran plain: Implications for human health.

Groundwater quality is a critical concern for human health, particularly in urban areas like the eastern part of Tehran Plain, where geological features and anthropogenic activities contribute to contamination risks. This study aimed to assess the quality of groundwater in this region, focusing on its implications for public health. The objectives of the study were to identify factors influencing hydrogeochemistry, evaluate environmental risk based on metal(loid)s using water quality indices, and conduct a health risk assessment. Groundwater samples were collected and analyzed for chemistry, water quality, heavy metal contamination, and associated health risks. The results indicated a relatively stable pH condition and a wide variation in the concentration of dissolved solids. The Water Quality Index (WQI) was employed to evaluate the overall water quality, revealing that approximately 50% of the samples fell into the poor and very poor quality categories, with two samples deemed unsuitable for drinking. Heavy metal contamination varied across different metals, with some indicating low levels while others showed moderate to very high levels. Priority pollutants such as mercury and arsenic were identified as having a greater potential impact on water quality deterioration. Exposure and health risk assessments indicated a negligible risk associated with aluminum exposure but high risks associated with arsenic, chromium, and mercury exposure. Carcinogenic risk assessments for arsenic, chromium, and mercury exceeded acceptable thresholds, emphasizing the urgent need for further investigation into contamination sources and strategies for mitigation. These findings highlight the importance of continuous monitoring and sustainable groundwater management practices, providing valuable insights for other regions facing similar challenges in groundwater quality and public health.

A systematic review on the impact of SARS-CoV-2 viral infection on precocious puberty

Precocious puberty is defined as the onset of sexual characteristics before age 8 in girls and 9 in boys, with serious physical and psychological implications, including advanced bone maturation, early growth cessation, and increased behavioral issues. As per the studies done by Gupta et al precocious puberty cases have risen during the pandemic, prompting inquiries into the potential link between SARS-CoV-2 and early pubertal onset. PubMed, Scopus Web of Science, Google Scholar, and other electronic databases were used for the literature search. The search was restricted to studies published between January 2020 and July 2024. The study has shown a concerning increase in precocious puberty cases during the pandemic, with reports of a significant rise ranging from 9.8% to 93%. The increase clearly shows the concern of having a massive impact on the puberty timing in girls. The data reveal a consistent increase in the incidence of precocious puberty during the pandemic, with relative increases ranging from 0.2 average incidence per month pre-pandemic to 5.9 average per month pandemic incidence. These findings underscore the need for localized public health strategies and further research to fully understand the long-term implications of early puberty in the context of the COVID-19 pandemic. This review emphasizes the importance of continued monitoring and research to mitigate the potential long-term health risks associated with precocious puberty, including metabolic, cardiovascular, and psychological disorders.

Development and deployment of a mid-cost CO2 sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO2 emissions in Paris

Abstract. To effectively monitor highly heterogeneous urban CO2 emissions using atmospheric observations, there is a need to deploy cost-effective CO2 sensors at multiple locations within the city with sufficient accuracy to capture the concentration gradients in urban environments. These dense measurements could be used as input of an atmospheric inversion system for the quantification of emissions at the sub-city scale or to separate specific sectors. Such quantification would offer valuable insights into the efficacy of local initiatives and could also identify unknown emission hotspots that require attention. Here we present the development and evaluation of a mid-cost CO2 instrument designed for continuous monitoring of atmospheric CO2 concentrations with a target accuracy of 1 ppm for hourly mean measurements. We assess the sensor sensitivity in relation to environmental factors such as humidity, pressure, temperature and CO2 signal, which leads to the development of an effective calibration algorithm. Since July 2020, eight mid-cost instruments have been installed within the city of Paris and its vicinity to provide continuous CO2 measurements, complementing the seven high-precision cavity ring-down spectroscopy (CRDS) stations that have been in operation since 2016. A data processing system, called CO2calqual, has been implemented to automatically handle data quality control, calibration and storage, which enables the management of extensive real-time CO2 measurements from the monitoring network. Colocation assessments with the high-precision instrument show that the accuracies of the eight mid-cost instruments are within the range of 1.0 to 2.4 ppm for hourly afternoon (12:00–17:00 UTC) measurements. The long-term stability issues require manual data checks and instrument maintenance. The analyses show that CO2 measurements can provide evidence for underestimations of CO2 emissions in the Paris region and a lack of several emission point sources in the emission inventory. Our study demonstrates promising prospects for integrating mid-cost measurements along with high-precision data into the subsequent atmospheric inverse modeling to improve the accuracy of quantifying the fine-scale CO2 emissions in the Paris metropolitan area.