The antihyperglycemic potential of pyrazolobenzothiazine 1, 1-dioxide novel derivative in mice using integrated molecular pharmacological approach.

Diabetes Mellitus is a metabolic disease characterized by elevated blood sugar levels caused by inadequate insulin production, which subsequently leads to hyperglycemia. This study was aimed to investigate the antidiabetic potential of pyrazolobenzothiazine derivatives in silico, in vitro, and in vivo. Molecular docking of pyrazolobenzothiazine derivatives was performed against α-glucosidase and α-amylase and compounds were selected based on docking score, bonding interactions and low root mean square deviation (RMSD). Enzyme inhibition assay against α-glucosidase and α-amylase was performed in vitro using p-nitrophenyl-α-D-glucopyranoside (PNPG) and starch substrate. Synthetic compound pyrazolobenzothiazine (S1) exhibited minimal conformational changes during the 100 ns MD simulation run. S1 also revealed effective IC50 values for α-glucosidase (3.91 µM) and α-amylase (8.89 µM) and an enzyme kinetic study showed low ki (- 0.186 µM, - 1.267 µM) and ki' (- 0.691 µM, - 1.78 µM) values with the competitive type of inhibition for both enzymes α-glucosidase and α-amylase, respectively. Moreover, studies were conducted to check the effect of the synthetic compound in a mouse model. A low necrosis rate was observed in the liver, kidney, and pancreas through histology analysis performed on mice. Compound S1 also exhibited a good biochemical profile with lower sugar level (110-115 mg/dL), increased insulin level (25-30 µM/L), and low level of cholesterol (85 mg/dL) and creatinine (0.6 mg/dL) in blood. The treated mice group also exhibited a low % of glycated haemoglobin (3%). This study concludes that S1 is a new antidiabetic-agent that helps lower blood glucose levels and minimizes the complications associated with type-II diabetes.

Optimizing Wireless Connectivity: A Deep Neural Network-Based Handover Approach for Hybrid LiFi and WiFi Networks.

A Hybrid LiFi and WiFi network (HLWNet) integrates the rapid data transmission capabilities of Light Fidelity (LiFi) with the extensive connectivity provided by Wireless Fidelity (WiFi), resulting in significant benefits for wireless data transmissions in the designated area. However, the challenge of decision-making during the handover process in HLWNet is made more complex due to the specific characteristics of electromagnetic signals' line-of-sight transmission, resulting in a greater level of intricacy compared to previous heterogeneous networks. This research work addresses the problem of handover decisions in the Hybrid LiFi and WiFi networks and treats it as a binary classification problem. Consequently, it proposes a handover method based on a deep neural network (DNN). The comprehensive handover scheme incorporates two sets of neural networks (ANN and DNN) that utilize input factors such as channel quality and the mobility of users to enable informed decisions during handovers. Following training with labeled datasets, the neural-network-based handover approach achieves an accuracy rate exceeding 95%. A comparative analysis of the proposed scheme against the benchmark reveals that the proposed method considerably increases user throughput by approximately 18.58% to 38.5% while reducing the handover rate by approximately 55.21% to 67.15% compared to the benchmark artificial neural network (ANN); moreover, the proposed method demonstrates robustness in the face of variations in user mobility and channel conditions.

Phase Engineered Composite Phase Change Materials for Thermal Energy Manipulation.

Phase change materials (PCMs) present a dual thermal management functionality through intrinsic thermal energy storage (TES) capabilities while maintaining a constant temperature. However, the practical application of PCMs encounters challenges, primarily stemming from their low thermal conductivity and shape-stability issues. Despite significant progress in the development of solid-solid PCMs, which offer superior shape-stability compared to their solid-liquid counterparts, they compromise TES capacity. Herein, a universal phase engineering strategy is introduced to address these challenges. The approach involves compositing solid-liquid PCM with a particulate-based conductive matrix followed by surface reaction to form a solid-solid PCM shell, resulting in a core-shell composite with enhanced thermal conductivity, high thermal storage capacity, and optimal shape-stability. The core-shell structure designed in this manner not only encapsulates the energy-rich solid-liquid PCM core but also significantly enhances TES capacity by up to 52% compared to solid-solid PCM counterparts. The phase-engineered high-performance PCMs exhibit excellent thermal management capabilities by reducing battery cell temperature by 15 °C and demonstrating durable solar-thermal-electric power generation under cloudy or no sunshine conditions. This proposed strategy holds promise for extending to other functional PCMs, offering a compelling avenue for the development of high-performance PCMs for thermal energy applications.

Risk of infection with arboviruses in a healthy population in Pakistan based on seroprevalence.

Infectious diseases caused by arboviruses are a public health concern in Pakistan. However, the studies on data prevalence and threats posed by arboviruses are limited. This study investigated the seroprevalence of arboviruses in a healthy population in Pakistan, including severe fever with thrombocytopenia syndrome virus (SFTSV), Crimean-Congo hemorrhagic fever virus (CCHFV), Tamdy virus (TAMV), and Karshi virus (KSIV) based on a newly established luciferase immunoprecipitation system (LIPS) assays, and Zika virus (ZIKV) by enzyme-linked immunosorbent assays (ELISA). Neutralizing activities against these arboviruses were further examined from the antibody positive samples. The results showed that the seroprevalence of SFTSV, CCHFV, TAMV, KSIV, and ZIKV was 17.37%, 7.58%, 4.41%, 1.10%, and 6.48%, respectively, and neutralizing to SFTSV (1.79%), CCHFV (2.62%), and ZIKV (0.69%) were identified, as well as to the SFTSV-related Guertu virus (GTV, 0.83%). Risk factors associated with the incidence of exposure and levels of antibody response were analyzed. Moreover, co-exposure to different arboviruses was demonstrated, as thirty-seven individuals were having antibodies against multiple viruses and thirteen showed neutralizing activity. Males, individuals aged ≤40 years, and outdoor workers had high risk of exposure to arboviruses. All these results reveal the substantial risks of infection with arboviruses in Pakistan, and indicate the threat from co-exposure to multiple arboviruses. The findings raise the need for further epidemiologic investigation in expanded regions and populations and the necessity to improve health surveillance in Pakistan.

Cardiovascular Health and Disease in the Pakistani American Population.

PURPOSE OF REVIEW: This narrative review seeks to elucidate clinical and social factors influencing cardiovascular health, explore the challenges and potential solutions for enhancing cardiovascular health, and identify areas where further research is needed to better understand cardiovascular issues in native and American Pakistani populations. RECENT FINDINGS: The prevalence of cardiometabolic disease is high not only in Pakistan but also among its global diaspora. This situation is further complicated by the inadequacy of current cardiovascular risk assessment tools, which often fall short of accurately gauging the risk among Pakistani individuals, underscoring the urgent need for more tailored and effective assessment methodologies. Moreover, social determinants play a crucial role in shaping cardiovascular health. The burden of cardiovascular disease and upstream risk factors is high among American Pakistani individuals. Future research is needed to better understand the heightened risk of cardiovascular disease among Pakistani individuals.

Multitarget Mechanisms of Monocarbonyl Curcuminoid Analogues against HL-60 Cancer Cells: In Vitro and Network Pharmacology-Based Approach.

This study addressed the cytotoxic potential of four compounds: monocarbonyl curcuminoid, ethyl (2E)-2-benzylidene-3-oxobutanoate 1, 1,2-dimethoxy-12-methyl-13H- [1,3] benzodioxolo[5,6-c] phenanthridine 2, 3,5-dibenzyloxybenzyl bromide 3, and (E)-4-(4-chlorobenzylidene)-1-(4-nitrophenyl)hexan-3-one 4. In vitro cytotoxic assays were carried out in HL-60 and BJ cells using the MTT assay along with analysis of apoptosis with the annexin V detection kit. Additional network pharmacology and docking analyses were carried out. In the in vitro assays, compounds 2 and 4 displayed significant antiproliferative effects in HL-60 cells, exhibiting IC50 values of 5.02 and 9.50 µM, respectively. Compound 1 showed no activity, and compound 3 displayed toxicity in BJ cells. In addition, both compounds 2 and 4 induced apoptosis in HL-60 cells. Network pharmacology and docking analyses indicated that compounds 2 and 4 had synergistic effects targeting the CASP3 and PARP1 proteins. Notably, these proteins play pivotal roles in cancer-related pathways. Thus, by modulating these proteins, monocarbonyl curcuminoid has the potential to influence various cancer-related pathways. In summary, our novel findings provide valuable insights into the potential of these compounds to serve as novel anticancer therapeutic agents, warranting further mechanistic studies and clinical exploration.

High-Efficiency Thermal-Shock Resistance Enabled by Radiative Cooling and Latent Heat Storage.

Radiative cooling technology is well known for its subambient temperature cooling performance under sunlight radiation. However, the intrinsic maximum cooling power of radiative cooling limits the performance when the objects meet the thermal shock. Here, a dual-function strategy composed of radiative cooling and latent heat storage simultaneously enabling the efficient subambient cooling and high-efficiency thermal-shock resistance performance is proposed. The electrospinning and absorption-pressing methods are used to assemble the dual-function cooler. The high sunlight reflectivity and high mid-infrared emissivity of radiative film allow excellent subambient temperature of 5.1 °C. When subjected the thermal shock, the dual-function cooler demonstrates a pinning effect of huge temperature drop of 39 °C and stable low-temperature level by isothermal heat absorption compared with the traditional radiative cooler. The molten phase change materials provide the heat-time transfer effect by converting thermal-shock heat to the delayed preservation. This strategy paves a powerful way to protect the objects from thermal accumulation and high-temperature damage, expanding the applications of radiative cooling and latent heat storage technologies.

A Novel Thermal Interface Material Composed of Vertically Aligned Boron Nitride and Graphite Films for Ultrahigh Through-Plane Thermal Conductivity.

The relentless drive toward miniaturization in microelectronic devices has sparked an urgent need for materials that offer both high thermal conductivity (TC) and excellent electrical insulation. Thermal interface materials (TIMs) possessing these dual attributes are highly sought after for modern electronics, but achieving such a combination has proven to be a formidable challenge. In this study, a cutting-edge solution is presented by developing boron nitride (BN) and graphite films layered silicone rubber composites with exceptional TC and electrical insulation properties. Through a carefully devised stacking-cutting method, the high orientation degree of both BN and graphite films is successfully preserved, resulting in an unprecedented through-plane TC of 23.7 Wm-1 K-1 and a remarkably low compressive modulus of 4.85 MPa. Furthermore, the exceptional properties of composites, including low thermal resistance and high resilience rate, make them a reliable and durable option for various applications. Practical tests demonstrate their outstanding heat dissipation performance, significantly reducing CPU temperatures in a computer cooling system. This research work unveils the possible upper limit of TC in BN-based TIMs and paves the way for their large-scale practical implementation, particularly in the thermal management of next-generation electronic devices.

A Deep Dive into Cu2 ZnSnS4 (CZTS) Solar Cells: A Review of Exploring Roadblocks, Breakthroughs, and Shaping the Future.

Renewable energy is crucial for sustainable future, and Cu2 ZnSnS4 (CZTS) based solar cells shine as a beacon of hope. CZTS, composed of abundant, low-cost, and non-toxic elements, shares similarities with Cu(In,Ga)Se2 (CIGS). However, despite its promise and appealing properties for solar cells, CZTS-based solar cells faces performance challenges owing to inherent issues with CZTS material, and conventional substrate structure complexities. This review critically examines these roadblocks, explores ongoing efforts and breakthroughs, providing insight into the evolving landscape of CZTS-based solar cells research. Furthermore, as an optimistic turn in the field, the review first highlights the crucial need to transition to a superstrate structure for CZTS-based single junction devices, and summarizes the substantial progress made in this direction. Subsequently, dive into the discussion about the fascinating realm of CZTS-based tandem devices, providing an overview of the existing literature as well as outlining the possible potential strategies for enhancing the efficiency of such devices. Finally, the review provides a useful outlook that outlines the priorities for future research and suggesting where efforts should concentrate to shape the future of CZTS-based solar cells.

MXene-Integrated Solid-Solid Phase Change Composites for Accelerating Solar-Thermal Energy Storage and Electric Conversion.

The high thermal storage density of phase change materials (PCMs) has attracted considerable attention in solar energy applications. However, the practicality of PCMs is often limited by the problems of leakage, poor solar-thermal conversion capability, and low thermal conductivity, resulting in low-efficiency solar energy storage. In this work, a new system of MXene-integrated solid-solid PCMs is presented as a promising solution for a solar-thermal energy storage and electric conversion system with high efficiency and energy density. The composite system's performance is enhanced by the intrinsic photo-thermal behavior of MXene and the heterogeneous phase transformation properties of PCM molecular chains. The optimal composites system has an impressive solar thermal energy storage efficiency of up to 94.5%, with an improved energy storage capacity of 149.5 J g-1 , even at a low MXene doping level of 5 wt.%. Additionally, the composite structure shows improved thermal conductivity and high thermal cycling stability. Furthermore, a proof-of-concept solar-thermal-electric conversion device is designed based on the optimized M-SSPCMs and commercial thermoelectric generators, which exhibit excellent energy conversion efficiency. The results of this study highlight the potential of the developed PCM composites in high-efficiency solar energy utilization for advanced photo-thermal systems.

Regenerative Medicine and Nanotechnology approaches against Cardiovascular Diseases: Recent Advances and Future Prospective.

Regenerative medicine refers to medical research focusing on repairing, replacing, or regenerating damaged or diseased tissues or organs. Cardiovascular disease (CVDs) is a significant health issue globally and is the leading cause of death in many countries. According to the Centers for Disease Control and Prevention (CDC), one person dies every 34 seconds in the United States from cardiovascular diseases, and according to a World Health Organization (WHO) report, cardiovascular diseases are the leading cause of death globally, taking an estimated 17.9 million lives each year. Many conventional treatments are available using different drugs for cardiovascular diseases, but these treatments are inadequate. Stem cells and nanotechnology are promising research areas for regenerative medicine treating CVDs. Regenerative medicines are a revolutionary strategy for advancing and successfully treating various diseases, intending to control cardiovascular disorders. This review is a comprehensive study of different treatment methods for cardiovascular diseases using different types of biomaterials as regenerative medicines, the importance of different stem cells in therapeutics, the expanded role of nanotechnology in treatment, the administration of several types of stem cells, their tracking, imaging, and the final observation of clinical trials on many different levels as well as it aims to keep readers up to pace on emerging therapeutic applications of some specific organs and disorders that may improve from regenerative medicine shortly.

Performance evaluation of various techniques in estimating precipitation record of a sparsely gauged mountainous watershed.

Comprehensive precipitation data is essential for hydrological, agricultural, and climatological studies. Yet, gaps and sparse rain gauge distribution pose challenges, requiring imputation algorithms to fill data gaps. The aim of this research is to evaluate the performance of several approaches for estimating incomplete precipitation data in the Upper Indus Basin (UIB). Eight various imputation approaches were used on sparsely gauged mountainous UIB on a monthly time series of twenty-four meteorological observatories. Following that, the estimation approaches were evaluated using a rank-based approach comprising four different statistical indicators. The results indicate that multiple linear regression is the best-performing strategy for most of the stations regardless of season or orography, followed by the arithmetic average method and inverse distance weighing method.

Bio-net dataset: AI-based diagnostic solutions using peripheral blood smear images.

Peripheral blood smear examination is one of the basic steps in the evaluation of different blood cells. It is a confirmatory step after an automated complete blood count analysis. Manual microscopy is time-consuming and requires professional laboratory expertise. Therefore, the turn-around time for peripheral smear in a health care center is approximately 3-4 hours. To avoid the traditional method of manual counting under the microscope a computerized automation of peripheral blood smear examination has been adopted, which is a challenging task in medical diagnostics. In recent times, deep learning techniques have overcome the challenges associated with human microscopic evaluation of peripheral smears and this has led to reduced cost and precise diagnosis. However, their application can be significantly improved by the availability of annotated datasets. This study presents a large customized annotated blood cell dataset (named the Bio-Net dataset from healthy individuals) and blood cell detection and counting in the peripheral blood smear images. A mini-version of the dataset for specialized WBC-based image processing tasks is also equipped to classify the healthy and mature WBCs in their respective classes. An object detection algorithm called You Only Look Once (YOLO) with a refashion disposition has been trained on the novel dataset to automatically detect and classify blood cells into RBCs, WBCs, and platelets and compare the results with other publicly available datasets to highlight the versatility. In short the introduction of the Bio-Net dataset and AI-powered detection and counting offers a significant potential for advancement in biomedical research for analyzing and understanding biological data.

Deciphering Multi-target Pharmacological Mechanism of Cucurbita pepo Seeds against Kidney Stones: Network Pharmacology and Molecular Docking Approach.

BACKGROUND: Urolithiasis is a prevalent condition with significant morbidity and economic implications. The economic burden associated with urolithiasis primarily stems from medical expenses. Previous literature suggests that herbal plants, including Cucurbita pepo, have lithotriptic capabilities. C. pepo is an annual, herbaceous, widely grown, and monoecious vegetative plant known for its antioxidants, fibers, and fatty acids. Recent studies on C. pepo seeds have shown therapeutic potential in reducing bladder stones and urodynamic illnesses, like kidney stones. However, the precise molecular and pharmacological mechanisms are unclear. OBJECTIVE: In this research, we employed network pharmacology and molecular docking to examine the active compounds and biological mechanisms of Cucurbita pepo against kidney stones. METHODS: Active constituents were obtained from previous studies and the IMPPAT database, with their targets predicted using Swiss target prediction. Kidney stone-associated genes were collected from DisGeNET and GeneCards. The active constituent-target-pathway network was constructed using Cytoscape, and the target protein-protein interaction network was generated using the STRING database. Gene enrichment analysis of C. pepo core targets was conducted using DAVID. Molecular docking was performed to identify potential kidney stone-fighting agents. RESULTS: The findings revealed that Cucurbita pepo contains 18 active components and has 192 potential gene targets, including AR, EGFR, ESR1, AKT1, MAPK3, SRC, and MTOR. Network analysis demonstrated that C. pepo seeds may prevent kidney stones by influencing disease-related signaling pathways. Molecular docking indicated that key kidney stone targets (mTOR, EGFR, AR, and ESR1) effectively bind with active constituents of C. pepo. CONCLUSION: These findings provide insight into the anti-kidney stone effects of Cucurbita pepo at a molecular level. In conclusion, this study contributes to understanding the potential of Cucurbita pepo in combating kidney stones and lays the foundation for further research.

Measures of quality of life of people with neurogenic overactive bladder: A systematic review of psychometric properties.

OBJECTIVE: To identify psychometrically robust quality-of-life (QOL) outcome measures for evaluating QOL among people with neurogenic overactive bladder (OAB). STUDY DESIGN: Electronic databases (CINAHL, EMBASE, MEDLINE, Scopus and Web of Science) were searched from inception to January 2023. Two independent reviewers participated in study screening, data extraction and quality appraisal. Studies were included if they validated at least one psychometric property of a QOL outcome measure among adults (age ≥ 18 years) with neurogenic OAB. The COnsensus-based Standards for selecting health status Measurement INstruments (COSMIN) checklist and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool were used to evaluate the methodological quality and quality of evidence, respectively, for each included study. RESULTS: Database searches identified 47 studies that tested the psychometric properties of 15 QOL measures in a total of 19,994 participants with stroke, spinal cord injury, Parkinson's disease or multiple sclerosis. The Incontinence Quality of Life Questionnaire (I-QOL), King's Health Questionnaire, Overactive Bladder Questionnaire and Qualiveen were the best validated measures, with strong reliability, validity and responsiveness. I-QOL was the most robust, cross-culturally administered and psychometrically strong measure. The COSMIN checklist indicated sufficient methodological quality for 70% of measures, and the modified GRADE tool indicated quality of evidence ranging from moderate (67%) to high (33%). CONCLUSIONS: This review identified the I-QOL as a culturally diverse measure with robust reliability, validity and responsiveness for assessing QOL among people with neurogenic OAB. These findings are supported by studies with good methodological quality (COSMIN) and high-quality evidence (GRADE).

Intravascular imaging guided versus coronary angiography guided percutaneous coronary intervention: systematic review and meta-analysis.

OBJECTIVE: To assess the absolute treatment effects of intravascular imaging guided versus angiography guided percutaneous coronary intervention in patients with coronary artery disease, considering their baseline risk. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed/Medline, Embase, and Cochrane Library databases up to 31 August 2023. STUDY SELECTION: Randomized controlled trials comparing intravascular imaging (intravascular ultrasonography or optical coherence tomography) guided versus coronary angiography guided percutaneous coronary intervention in adults with coronary artery disease. MAIN OUTCOME MEASURES: Random effect meta-analysis and GRADE (grading of recommendations, assessment, development, and evaluation) were used to assess certainty of evidence. Data included rate ratios and absolute risks per 1000 people for cardiac death, myocardial infarction, stent thrombosis, target vessel revascularization, and target lesion revascularization. Absolute risk differences were estimated using SYNTAX risk categories for baseline risks at five years, assuming constant rate ratios across different cardiovascular risk thresholds. RESULTS: In 20 randomized controlled trials (n=11 698), intravascular imaging guided percutaneous coronary intervention was associated with a reduced risk of cardiac death (rate ratio 0.53, 95% confidence interval 0.39 to 0.72), myocardial infarction (0.81, 0.68 to 0.97), stent thrombosis (0.44, 0.27 to 0.72), target vessel revascularization (0.74, 0.61 to 0.89), and target lesion revascularization (0.71, 0.59 to 0.86) but not all cause death (0.81, 0.64 to 1.02). Using SYNTAX risk categories, high certainty evidence showed that from low risk to high risk, intravascular imaging was likely associated with 23 to 64 fewer cardiac deaths, 15 to 19 fewer myocardial infarctions, 9 to 13 fewer stent thrombosis events, 28 to 38 fewer target vessel revascularization events, and 35 to 48 fewer target lesion revascularization events per 1000 people. CONCLUSIONS: Compared with coronary angiography guided percutaneous coronary intervention, intravascular imaging guided percutaneous coronary intervention was associated with significantly reduced cardiac death and cardiovascular outcomes in patients with coronary artery disease. The estimated absolute effects of intravascular imaging guided percutaneous coronary intervention showed a proportional relation with baseline risk, driven by the severity and complexity of coronary artery disease. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42023433568.

Frontiers in nonviral delivery of small molecule and genetic drugs, driven by polymer chemistry and machine learning for materials informatics.

Materials informatics (MI) has immense potential to accelerate the pace of innovation and new product development in biotechnology. Close collaborations between skilled physical and life scientists with data scientists are being established in pursuit of leveraging MI tools in automation and artificial intelligence (AI) to predict material properties in vitro and in vivo. However, the scarcity of large, standardized, and labeled materials data for connecting structure-function relationships represents one of the largest hurdles to overcome. In this Highlight, focus is brought to emerging developments in polymer-based therapeutic delivery platforms, where teams generate large experimental datasets around specific therapeutics and successfully establish a design-to-deployment cycle of specialized nanocarriers. Three select collaborations demonstrate how custom-built polymers protect and deliver small molecules, nucleic acids, and proteins, representing ideal use-cases for machine learning to understand how molecular-level interactions impact drug stabilization and release. We conclude with our perspectives on how MI innovations in automation efficiencies and digitalization of data-coupled with fundamental insight and creativity from the polymer science community-can accelerate translation of more gene therapies into lifesaving medicines.

Systematic elucidation of the multi-target pharmacological mechanism of Terminalia arjuna against congestive cardiac failure via network pharmacology and molecular modelling approaches.

Congestive cardiac failure (CCF) is a pathophysiologic state when the heart is not able to maintain its cardiac output to meet the demand of metabolising tissues. CCF is responsible for approximately 2.9 million deaths worldwide. The heterogeneous nature of CCF draws the attention of researchers to find more enthralling and promising diagnostic and treatment options. Terminalia arjuna (Arjuna) is an evergreen, deciduous tree exhibited various astringent, anti-bacterial, and anti-microbial properties. T. arjuna is being used in various regions for anginal pain, hypertension, congestive heart failure, and dyslipidemia. Although previous in vitro studies have demonstrated the therapeutic potential of T. arjuna, the exact molecular mechanism underlying its protective effect on the heart remains unclear. In this study, a network pharmacology technique was used to explore the active ingredients, potential targets in T. arjuna for the treatment of CCF. In the framework of this study, we explored the active ingredient-target-pathway network and figured out that oleanolic acid, arjunolic acid, luteolin, kaempferol, cholesterol, ellagic acid 4-O-xylopyranoside 3,3'-dimethyl ether, and cyclohexyl (2,4-dimethyl phenyl) methanone contributed significantly to the development of CCF by affecting AKT1, MAPK14, TNF, IL6, ESR1, and HSP90AA1 genes. Molecular docking analysis further validated the activities of these compounds against potential targets. To sum up, integrated network pharmacology and docking analysis revealed that T. arjuna exerts its cardioprotective effect by acting on various signalling pathways, including the thyroid hormone, VEGF signalling pathway, AGE-RAGE signalling pathway in diabetic complications, HIF signalling pathway, sphingolipid signalling pathway, and oestrogen signalling pathways. Overall, this study provides valuable insights into the molecular mechanism of T. arjuna in CCF and highlights its potential as a promising preventive treatment for this condition.

Physician-scientists or celebrities? Kardashian-index of gastroenterologists.

BACKGROUND: The coronavirus disease 2019 pandemic unleashed a flood of untrustworthy information on social media platforms, resulting in the unfortunate consequence of expert scientists' opinions getting lost amidst the chaotic sea of misinformation. The question of how much influence these esteemed scientists hold on social media platforms remains elusive. To address this scientific quandary, we sought to explore the concept of the Kardashian index (K-index), a term introduced by Hall in 2014. This metric provides a rudimentary means of evaluating whether a physician scientist's popularity on social media aligns with their significant scientific contributions. AIM: To evaluate if a Gastroenterologist physician's popularity on social media is at par with their scientific contributions (research articles and publications). METHODS: We conducted an extensive search to identify all gastroenterologists actively practicing and associated with the top 100 hospitals as reported by the United States News. We collected specific data on a sub-group including their names, affiliations, degrees, and sub-specializations. To gauge their social media popularity, we utilized the K-index calculation which is determined by dividing the actual number of Twitter followers by the number of researcher's citations. The expected number of followers (F) is calculated using the formula F = 43.3 C ^ 0.32, where C represents the number of citations. RESULTS: Physicians affiliated with the Mayo Clinic emerged as the most prominent presence on Twitter, constituting 16% of the total. They were followed closely by physicians from Mount Sinai Hospital (9%) and the University of Michigan Hospital (9%). Surprisingly, 76% of the physicians evaluated exhibited a low K-index, falling within the range of 0 to less than 2. This suggests that a significant number of highly influential physician-scientists are not receiving due recognition, as indicated by their relatively low number of followers. On the other hand, 24% of the physicians had an inflated K-index, exceeding 5, which positioned them as the "Kardashians". These individuals enjoyed greater social media popularity than their actual scientific contributions. Interestingly, our analysis revealed no discernible association between sex and K-index (P value of 0.92). CONCLUSION: In the gastroenterology field, our study estimated that a majority (76%) of highly researched physicians are undervalued despite their significant scientific contributions.

Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective.

Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases, such as skin, breast, and lung cancer. AI is an advanced form of technology that uses mathematical-based algorithmic principles similar to those of the human mind for cognizing complex challenges of the healthcare unit. Cancer is a lethal disease with many etiologies, including numerous genetic and epigenetic mutations. Cancer being a multifactorial disease is difficult to be diagnosed at an early stage. Therefore, genetic variations and other leading factors could be identified in due time through AI and machine learning (ML). AI is the synergetic approach for mining the drug targets, their mechanism of action, and drug-organism interaction from massive raw data. This synergetic approach is also facing several challenges in data mining but computational algorithms from different scientific communities for multi-target drug discovery are highly helpful to overcome the bottlenecks in AI for drug-target discovery. AI and ML could be the epicenter in the medical world for the diagnosis, treatment, and evaluation of almost any disease in the near future. In this comprehensive review, we explore the immense potential of AI and ML when integrated with the biological sciences, specifically in the context of cancer research. Our goal is to illuminate the many ways in which AI and ML are being applied to the study of cancer, from diagnosis to individualized treatment. We highlight the prospective role of AI in supporting oncologists and other medical professionals in making informed decisions and improving patient outcomes by examining the intersection of AI and cancer control. Although AI-based medical therapies show great potential, many challenges must be overcome before they can be implemented in clinical practice. We critically assess the current hurdles and provide insights into the future directions of AI-driven approaches, aiming to pave the way for enhanced cancer interventions and improved patient care.