Search Results (9)

Background: SGLT2 inhibitors (SGLT-2i) and GLP1 receptor agonists (GLP-1 RA) are recommended as the first line therapy for the management of type 2 diabetes mellitus (T2DM), particularly in patients with chronic kidney disease (CKD), cardiovascular disease (CVD), and heart failure (HF). Despite their established efficacy, there is limited evidence available to predict which subset of patients will respond favorably to them. We conducted this study to identify baseline characteristics to predict the response to therapy with SGLT-2i and GLP-1 RA. Methods: A retrospective analysis of the medical records was conducted at the Veteran Affairs Medical Center (VAMC) in Omaha, Nebraska, USA. Veterans who had completed 6–12 months of treatment with SGLT-2i or GLP-1 RA were included. Favorable treatment outcomes were a ≥0.5% reduction in glycosylated hemoglobin (HbA1c) or a ≥5% reduction in body weight; and those who achieved both outcomes were classified as adequate responders. Results: Patients in the GLP-1 RA group had 2.11 (95% CI: 1.45, 3.07) times the odds of achieving an adequate response as compared to patients in the SGLT-2i group in the unadjusted analysis, p < 0.001. HbA1c > 8% and older age was significantly associated with achieving an adequate response. Conclusions: Treatment with GLP-1 RA should be considered in Veterans with these characteristics. Full article

The identification of gas leakages is a significant factor to be taken into consideration in various industries such as coal mines, chemical industries, etc., as well as in residential applications. In order to reduce damage to the environment as well as human lives, early detection and gas type identification are necessary. The main focus of this paper is multimodal gas data that were obtained simultaneously by using multiple sensors for gas detection and a thermal imaging camera. As the reliability and sensitivity of low-cost sensors are less, they are not suitable for gas detection over long distances. In order to overcome the drawbacks of relying just on sensors to identify gases, a thermal camera capable of detecting temperature changes is also used in the collection of the current multimodal dataset The multimodal dataset comprises 6400 samples, including smoke, perfume, a combination of both, and neutral environments. In this paper, convolutional neural networks (CNNs) are trained on thermal image data, utilizing variants such as bidirectional long–short-term memory (Bi-LSTM), dense LSTM, and a fusion of both datasets to effectively classify comma separated value (CSV) data from gas sensors. The dataset can be used as a valuable source for research scholars and system developers to improvise their artificial intelligence (AI) models used for gas leakage detection. Furthermore, in order to ensure the privacy of the client’s data, this paper explores the implementation of federated learning for privacy-protected gas leakage classification, demonstrating comparable accuracy to traditional deep learning approaches. Full article

The dropout rate is one of the determinants of immunization coverage and program performance, program continuity, and follow-up. The dropout rate refers to the proportion of vaccine recipients who did not finish their vaccination schedules, and it is determined by comparing the number of infants who started the schedule to the number who completed it. It is the rate difference between the first and final dosage or the rate difference between the first vaccination and the last vaccine dropout; thus, it denotes that the first recommended dose of vaccine was received, but that the subsequently recommended dose was missed. In India, immunization coverage has shown significant improvements over the last two decades, but full immunization coverage has remained stagnant at 76.5%, of which 19.9% are partially immunized, and 3.6% are children who have been left out. In India, the Universal Immunization Programme (UIP) is challenged with cases related to dropout in immunization. Although immunization coverage in India is improving, the program is challenged by vaccination dropouts. This study provides an analysis of the determinants of vaccination dropout in India using data from two rounds of the National Family Health Survey. The finding shows that the mother’s age, education, family wealth, antenatal care visit, and place of delivery were some of the variables that significantly contributed to reducing the dropout rate of immunization among children. The findings of this paper show that the dropout rate has reduced over a certain period of time. The overall improvement in the rates of dropout and increase in full immunization coverage could be attributed to various policy measures taken in the last decade in India, which brought structural changes with a positive impact on full immunization coverage and its components. Full article

The world is grappling with the coronavirus disease 2019 (COVID-19) pandemic, the causative agent of which is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 symptoms are similar to the common cold, including fever, sore throat, cough, muscle and chest pain, brain fog, dyspnoea, anosmia, ageusia, and headache. The manifestation of the disease can vary from being asymptomatic to severe life-threatening conditions warranting hospitalization and ventilation support. Furthermore, the emergence of mutecated variants of concern (VOCs) is paramount to the devastating effect of the pandemic. This highly contagious virus and its emergent variants challenge the available advanced viral diagnostic methods for high-accuracy testing with faster result yields. This review is to shed light on the natural history, pathology, molecular biology, and efficient diagnostic methods of COVID-19, detecting SARS-CoV-2 in collected samples. We reviewed the gold standard RT-qPCR method for COVID-19 diagnosis to confer a better understanding and application to combat the COVID-19 pandemic. This comprehensive review may further develop awareness about the management of the COVID-19 pandemic. Full article

Mycobacterium tuberculosis is a human pathogen that can thrive inside the host immune cells for several years and cause tuberculosis. This is due to the propensity of M. tuberculosis to synthesize a sturdy cell wall, shift metabolism and growth, secrete virulence factors to manipulate host immunity, and exhibit stringent response. These attributes help M. tuberculosis to manage the host response, and successfully establish and maintain an infection even under nutrient-deprived stress conditions for years. In this review, we will discuss the importance of mycobacterial stringent response under different stress conditions. The stringent response is mediated through small signaling molecules called alarmones “(pp)pGpp”. The synthesis and degradation of these alarmones in mycobacteria are mediated by Rel protein, which is both (p)ppGpp synthetase and hydrolase. Rel is important for all central dogma processes—DNA replication, transcription, and translation—in addition to regulating virulence, drug resistance, and biofilm formation. Rel also plays an important role in the latent infection of M. tuberculosis. Here, we have discussed the literature on alarmones and Rel proteins in mycobacteria and highlight that (p)ppGpp-analogs and Rel inhibitors could be designed and used as antimycobacterial compounds against M. tuberculosis and non-tuberculous mycobacterial infections. Full article

As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic since the 1918 flu. The main challenges in mitigating COVID-19 are effective vaccination, treatment, and agile containment strategies. In this review, we focus on the potential of Artificial Intelligence (AI) in COVID-19 surveillance, diagnosis, outcome prediction, drug discovery and vaccine development. With the help of big data, AI tries to mimic the cognitive capabilities of a human brain, such as problem-solving and learning abilities. Machine Learning (ML), a subset of AI, holds special promise for solving problems based on experiences gained from the curated data. Advances in AI methods have created an unprecedented opportunity for building agile surveillance systems using the deluge of real-time data generated within a short span of time. During the COVID-19 pandemic, many reports have discussed the utility of AI approaches in prioritization, delivery, surveillance, and supply chain of drugs, vaccines, and non-pharmaceutical interventions. This review will discuss the clinical utility of AI-based models and will also discuss limitations and challenges faced by AI systems, such as model generalizability, explainability, and trust as pillars for real-life deployment in healthcare. Full article

Numerous publications have reported the significant pharmacodynamic activity of Curcumin (CRM) despite low or undetectable levels in plasma. The objective of the present study was to perform a detailed pharmacokinetic evaluation of CRM after the oral administration of a highly bioavailable lipidic formulation of CRM (CRM-LF) in human subjects. C_max, T_max and AUC_0–¥ were found to be 183.35 ± 37.54 ng/mL, 0.60 ± 0.05 h and 321.12 ± 25.55 ng/mL respectively, at a dose of 750 mg. The plasma profile clearly showed three distinct phases, viz., absorption, distribution and elimination. A close evaluation of the primary pharmacokinetic parameters provided valuable insight into the behavior of the CRM after absorption by CRM-LF. CRM-LF showed a lag time (T_lag) of 0.18 h (around 12 min). Pharmacokinetic modeling revealed that CRM-LF followed a two-compartment model with first order absorption, lag time and first order elimination. A high absorption rate constant (K₀₁, 4.51/h) signifies that CRM-LF ensured rapid absorption of the CRM into the central compartment. This was followed by the distribution of CRM from the central to peripheral compartment (K₁₂, 2.69/h). The rate of CRM transfer from the peripheral to central compartment (K₂₁, 0.15/h) was slow. This encourages higher tissue levels of CRM as compared with plasma levels. The study provides an explanation of the therapeutic efficacy of CRM, despite very low/undetectable levels in the plasma. Full article