Wearable sweat chloride sensors: materials, fabrication and their applications.

Chloride is a crucial anion required for multiple functions in the human body including maintaining acid-base balance, fluid balance, electrical neutrality and supporting muscles and nerve cells. Low-chloride levels can cause nausea, diarrhoea, etc. Chloride levels are measured in different body fluids such as urine, serum, sweat and saliva. Sweat chloride measurements are used for multiple applications including disease diagnosis, sports monitoring, and geriatric care. For instance, a sweat chloride test is performed for cystic fibrosis screening. Further, sweat also offers continuous non-invasive access to body fluids for real-time monitoring of chloride that could be used for sports and geriatric care. This review focuses on wearable chloride sensors that are used for periodic and continuous chloride monitoring. The multiple sections in the paper discuss the clinical significance of chloride, detection methods, sensor fabrication methods and their application in cystic fibrosis screening, sports and geriatric care. Finally, the last section discusses the limitation of current sensors and future directions for wearable chloride sensors.

Correlation of serum uric acid levels with certain anthropometric parameters in prediabetic and drug-naive diabetic subjects.

Introduction: Uric acid is produced during the metabolism of nucleotide and adenosine triphosphate and contains the final product of human purine metabolism. It acts both as an antioxidant and pro-inflammatory marker and has a positive association with visceral fat in overweight subjects. The aim of the present study is to find an association of uric acid level with certain anthropometric parameters in subjects having type 2 diabetes. Materials and Methods: The study included 124 urban drug-naive diabetic Indian subjects above 18 years of age from the general population of the city of North India. Uric acid concentrations were estimated by the uricase method. Fasting plasma glucose (FPG) concentrations were estimated by the glucose oxidase-peroxidase method. Anthropometric measurements and information on lifestyle factors and disease history were collected through in-person meeting. Results: All participants of the study subjects had a body mass index (BMI) of more than 23.5. BMI, waist-to-hip ratio (WHR), waist-to-height ratio, waist circumference, neck circumference, weight, age, sagittal abdominal diameter (SAD), skinfold thickness, and body roundness index were positively correlated with the serum uric acid level. The correlation of weight, BMI, SAD, and WHR was statistically significant. Conclusion: We found that serum uric acid level increases as body fat content increases. Statistical data show remarkable results for a significant correlation of uric acid level with BMI, WHR, SAD, and FPG. Hypertrophy occurs as a result of inflammatory processes and oxidative stress when the supply of energy starts to exceed the storage capacity of adipocytes, as a result, adipokines such as interleukin (IL)-1, IL-6, and tumor-necrosis factor-alpha are released more frequently which lead to low-grade chronic inflammation. Uric acid levels are much lean toward visceral obesity than overall body fat content.

Résumé Introduction: L'acide urique est produit lors du métabolisme des nucléotides et de l'adénosine triphosphate, et il représente le produit final du métabolisme des purines chez l'homme. Il agit à la fois comme un antioxydant et un marqueur pro-inflammatoire, et il est positivement associé à la graisse viscérale chez les sujets en surpoids. L'objectif de la présente étude est de rechercher une association entre le taux d'acide urique et certains paramètres anthropométriques chez des sujets atteints de diabète de type 2. Matériels et méthodes: L'étude a inclus 124 sujets diabétiques urbains indiens, naïfs aux médicaments, âgés de plus de 18 ans, issus de la population générale de la ville du nord de l'Inde. Les concentrations d'acide urique ont été estimées par la méthode de l'uricase. Les concentrations de glucose plasmatique à jeun (FPG) ont été estimées par la méthode glucose oxydase-peroxydase. Les mesures anthropométriques et les informations sur les facteurs de mode de vie et les antécédents médicaux ont été recueillies lors de rencontres en personne. Résultats: Tous les participants de l'étude présentaient un indice de masse corporelle (IMC) supérieur à 23,5. L'IMC, le rapport taille-hanche (WHR), le rapport taille-hauteur, la circonférence de taille, la circonférence du cou, le poids, l'âge, le diamètre abdominal sagittal (SAD), l'épaisseur des plis cutanés et l'indice de rondeur corporelle étaient corrélés positivement avec le taux d'acide urique sérique. La corrélation du poids, de l'IMC, du SAD et du WHR était statistiquement significative. Conclusion: Nous avons constaté que le taux d'acide urique sérique augmente avec l'augmentation de la teneur en graisse corporelle. Les données statistiques montrent des résultats remarquables pour une corrélation significative du taux d'acide urique avec l'IMC, le WHR, le SAD et le FPG. L'hypertrophie se produit en raison de processus inflammatoires et de stress oxydatif lorsque l'apport d'énergie dépasse la capacité de stockage des adipocytes. Par conséquent, des adipokines telles que l'interleukine (IL)-1, l'IL-6 et le facteur alpha de nécrose tumorale sont libérées plus fréquemment, ce qui entraîne une inflammation chronique de bas grade. Les niveaux d'acide urique sont davantage associés à l'obésité viscérale qu'à la teneur globale en graisse corporelle. Mots-clés: Anthropométrique, syndrome métabolique, microalbuminurie, acide urique sérique.

Ensuring the quality of medicines in India: An update on the development, modernization, and harmonization of drug standards in the Indian Pharmacopoeia.

India has a sparkling pharmaceutical sector that holds a distinguished place by producing and supplying high-quality and affordable medicines across the globe. Ensuring the quality and safety of the marketed medicinal products is one of the most important components of the drug regulatory framework and assessment of the quality of medicines is usually achieved by referring to the public standards of the official Pharmacopoeia. In India, the Indian Pharmacopoeia (IP) is published at regular intervals to fulfill the requirements of the Drugs and Cosmetics Act, 1940 to ensure the quality of medicines being manufactured and/or marketed in India. The present article aims to provide an overview of the history of the IP, its standards-setting process, and the current status of monographs in the 9th edition of the IP 2022. Special focus is placed on the newly added and upgraded general chapters and monographs within the IP 2022. There are a total of 223 general chapters and 3152 drug monographs available under various categories in the IP 2022. This study also highlights a total of 92 new drug monograph additions and 412 monograph revisions in the IP 2022. It is anticipated that the standards laid down in the IP 2022 will play an imperative role in delivering quality medicines to patients within and outside India.

Comprehensive chemo-profiling of coumarins enriched extract derived from Aegle marmelos (L.) Correa fruit pulp, as an anti-diabetic and anti-inflammatory agent.

Aegle marmelos (L.) Correa is an Indian medicinal plant known for its vast therapeutic activities. In Ayurveda, the plant is known to balance "vata," "pitta," and "kapha" dosh. Recent studies suggest anti-inflammatory, anti-microbial, and anti-diabetic potential but lack in defining the dosage over the therapeutic activities. This study aims to determine the chemical profile of Aegle marmelos fruit extract; identification, enrichment, and characterization of the principal active component(s) having anti-inflammatory and anti-diabetic potential. Targeted enrichment of total coumarins, focusing on marmelosin, marmesin, aegeline, psoralen, scopoletin, and umbelliferone, was done from Aegle marmelos fruit pulp, and characterized using advanced high-throughput techniques. In vitro and in silico anti-diabetic and anti-inflammatory activities were assessed to confirm their efficacy and affinity as anti-diabetic and anti-inflammatory agents. The target compounds were also analysed for toxicity by in silico ADMET study and in vitro MTT assay on THP-1 and A549 cell lines. The coumarins enrichment process designed, was found specific for coumarins isolation as it resulted into 48.61% of total coumarins enrichment, which includes 31.2% marmelosin, 8.9% marmesin, 4% psoralen, 2% scopoletin, 1.7% umbelliferone, and 0.72% aegeline. The quantification with HPTLC and qNMR was found to be correlated with the HPLC assay results. The present study validates the potential use of Aegle marmelos as an anti-inflammatory and anti-diabetic agent. Coumarins enriched from the plant fruit have good therapeutic activity and can be used for Phytopharmaceutical ingredient development. The study is novel, in which coumarins were enriched and characterized by a simple and sophisticated methodology.

Comparison of frequency domain parameters of heart rate variability between women with polycystic ovarian disease and apparently healthy women.

Background: Polycystic ovary syndrome (PCOS) patients shows common features like increased insulin resistance and adiposity, which have been known to correlate with sympathetic hyperactivity. Objective: The aim of this study is to analyze the characteristics of heart rate variability in women with PCOS. To compare frequency domain parameters of heart rate variability (HRV) between women with PCOS and apparently healthy women. To study the impact of cardiometabolic parameters such as BMI and blood pressure on frequency-domain HRV parameters. Methods: A total of 30 women with PCOS aged 20 to 40 years (as per Rotterdam criteria) were enrolled as cases and 30 age-matched women having normal ovulatory cycles were enrolled as controls. HRV was recorded using an electrocardiography machine (ECG) machine. The following frequency-domain parameters were assessed: Total power, Very low frequency (VLF), VLF%, Low Frequency (LF), LF%, LF nu, High frequency (HF), HF%, HF nu, LF/HF ratio, short-term variability (SD1), and long-term variability (SD2), respectively. Results: Mean age of cases was 28.03 ± 5.33 years. Mean BMI of PCOS women was 25.39 ± 2.69 kg/m2. A total of 18 (60%) had BMI >25 kg/m2. Cases had significantly higher BMI, waist hip ratio, and blood pressure as compared with controls. None of the controls had BMI >25 kg/m2. Majority of cases (66.7%) had systolic blood pressure/diastolic blood pressure (SBP/DBP) >130/85 mmHg as compared with only 6 (20%) of controls (P < 0.001). For different frequency domain parameters, no statistically significant difference between two groups was observed for VLF and LF. Mean VLF%, LF%, LF (nu), and LF/HF were significantly higher in cases as compared with controls. For all, the other mean value was significantly lower in cases as compared with that of controls (P < 0.05). Conclusions: Autonomic nervous system is affected by PCOS status of women, and sympathetic hyperactivity is seen.

Evaluation of Salivary Lactate Dehydrogenase as a Prognostic Biomarker in Tobacco Users with and without Potentially Malignant Disorders of the Oral Cavity.

Background Oral squamous cell carcinoma (OSCC) is a deadly disease that develops in a multistage process and is often preceded by oral potentially malignant disorders (PMDs), of which many are caused by tobacco usage. It is associated with a shift from an aerobic to anaerobic glycolytic pathway, and hence an increase in lactate dehydrogenase (LDH) levels is seen. The objective of this study was to estimate and correlate the level of salivary LDH in healthy individuals with tobacco users (with or without PMDs). Methods A total of 78 patients were selected from the Department of Oral Medicine and Radiology, Dayananda Sagar College of Dental Sciences, Bengaluru, Karnataka, India, and were divided into three groups of 26 patients each, namely controls, tobacco users without PMD, and tobacco users with PMD. A total of 1 mL of unstimulated saliva was collected from each patient using the spit method. Sample was subjected to centrifugation at 2,500 rpm, and salivary LDH was quantified by a standard kit (LDH-P kit, DIALAB, Neudorf, Austria) using an autoanalyzer. Results There was a statistically significant ( p < 0.001) gradual increase in the level of LDH in controls (267 ± 27.64 U/L), tobacco users without PMD (391 ± 80.53 U/L), and tobacco users with PMD (706.1 ± 199 U/L). Increase in the LDH level was also noted with increased duration and frequency of the habit. Conclusion LDH can potentially be used as a promising biomarker in the very early stages of progression toward oral cancer caused by tobacco use.

Synthetic image augmentation with generative adversarial network for enhanced performance in protein classification.

Proteins are complex macromolecules accountable for the biological processes in the cell. In biomedical research, the images of protein are extensively used in medicine. The rate at which these images are produced makes it difficult to evaluate them manually and hence there exists a need to automate the system. The quality of images is still a major issue. In this paper, we present the use of different image enhancement techniques that improves the contrast of these images. Besides the quality of images, the challenge of gathering such datasets in the field of medicine persists. We use generative adversarial networks for generating synthetic samples to ameliorate the results of CNN. The performance of the synthetic data augmentation was compared with the classic data augmentation on the classification task, an increase of 2.7% in Macro F1 and 2.64% in Micro F1 score was observed. Our best results were obtained by the pretrained Inception V4 model that gave a fivefold cross-validated macro F1 of 0.603. The achieved results are contrasted with the existing work and comparisons show that the proposed method outperformed.

A comprehensive evaluation for the prediction of mortality in intensive care units with LSTM networks: patients with cardiovascular disease.

Intensive care units (ICUs) are responsible for generating a wealth of useful data in the form of electronic health records. We aimed to build a mortality prediction model on a Medical Information Mart for Intensive Care (MIMIC-III) database and to assess whether the use of deep learning techniques like long short-term memory (LSTM) can effectively utilize the temporal relations among clinical variables. The models were built on clinical variable dynamics of the first 48 h of ICU admission of 12,550 records from the MIMIC-III database. A total of 36 variables including 33 time series variables and three static variables were used for the prediction. We present the application of LSTM and LSTM attention (LSTM-AT) model for mortality prediction with such a large number of clinical variables dataset. For training and validation purpose, we have used International Classification of Diseases, 9th edition (ICD-9) codes for extracting the patients with cardiovascular disease, and infections and parasitic disease, respectively. The effectiveness of the LSTM model is achieved over non-recurrent baseline models like naïve Bayes, logistic regression (LR), support vector machine and multilayer perceptron (MLP) by generating state of the art results (area under the curve [AUC], 0.852). Next, by providing attention at each time stamp, we developed a model, LSTM-AT, which exhibits even better performance (AUC, 0.876).

Assessment of serum copper, iron and immune complexes in potentially malignant disorders and oral cancer.

Potentially malignant disorders (PMDs) of oral cavity and oral cancer remain a cause of serious concern despite intensive research and development. Diet and immunity have been identified to play a crucial role as modifying factors in these diseases. Our study intended to explore this relationship by estimating and comparing the serum levels of copper, iron and circulating immune complexes (CICs) in patients diagnosed with PMDs and oral cancer and normal healthy individuals. In this study, 40 histopathologically diagnosed cases of PMDs and oral cancer were included along with 30 healthy controls and 5 ml of venous blood was drawn using venipuncture. Serum estimation of copper, iron and CIC then followed using the colorimetric and spectrophotometric methods. The data obtained was subjected to statistical analysis using one way ANOVA and Pearson's Product-Moment Correlation Test. The mean serum copper level was measured as 138.98 ± 10.13µg/100ml in the PMD group and 141.99 ± 21.44 µg/100ml in the oral cancer as compared to 105.5 + 18.81µ/100ml in the controls. The mean serum CIC levels was highest in the oral cancer (9.65 ± 0.16OD470) followed by the PMD group (0.18 + 0.21 OD470) and least in the control group (0.048 ± 0.02OD470). Whereas, the serum levels of iron showed a significant decrease in the PMD group (110.9 ± 10.54 µg/100ml) and the oral cancer group (114.29 ± 25.83 µg/100ml) as compared with the control group (136.85 ± 14.48 µg/100ml). There was no positive correlation obtained between the three groups with respect to the chosen parameters indicating that the variables were independent of each other. It can be thus be ascertained that trace elements like copper and iron as well as humoral responses (CICs) have a close relationship with PMDs and oral cancers.

Assessment of serum copper, iron and immune complexes in potentially malignant disorders and oral cancer

Abstract Potentially malignant disorders (PMDs) of oral cavity and oral cancer remain a cause of serious concern despite intensive research and development. Diet and immunity have been identified to play a crucial role as modifying factors in these diseases. Our study intended to explore this relationship by estimating and comparing the serum levels of copper, iron and circulating immune complexes (CICs) in patients diagnosed with PMDs and oral cancer and normal healthy individuals. In this study, 40 histopathologically diagnosed cases of PMDs and oral cancer were included along with 30 healthy controls and 5 ml of venous blood was drawn using venipuncture. Serum estimation of copper, iron and CIC then followed using the colorimetric and spectrophotometric methods. The data obtained was subjected to statistical analysis using one way ANOVA and Pearson's Product-Moment Correlation Test. The mean serum copper level was measured as 138.98 ± 10.13µg/100ml in the PMD group and 141.99 ± 21.44 µg/100ml in the oral cancer as compared to 105.5 + 18.81µ/100ml in the controls. The mean serum CIC levels was highest in the oral cancer (9.65 ± 0.16OD470) followed by the PMD group (0.18 + 0.21 OD470) and least in the control group (0.048 ± 0.02OD470). Whereas, the serum levels of iron showed a significant decrease in the PMD group (110.9 ± 10.54 µg/100ml) and the oral cancer group (114.29 ± 25.83 µg/100ml) as compared with the control group (136.85 ± 14.48 µg/100ml). There was no positive correlation obtained between the three groups with respect to the chosen parameters indicating that the variables were independent of each other. It can be thus be ascertained that trace elements like copper and iron as well as humoral responses (CICs) have a close relationship with PMDs and oral cancers.