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Metabolic-dysfunction associated steatotic liver disease (MASLD) affects 1 out of every 3 individuals in the adult population and the disease prevalence is predicted to increase worldwide. Patients with MASLD are also burdened by cardiovascular disease, which is the leading cause of mortality in this population. Complex metabolic derangements such as insulin resistance and atherogenic dyslipidemia affect patients with MASLD. In patients with MASLD, treatment such as pharmacotherapy may be best directed towards improving the adverse concomitant metabolic disorders associated with MASLD, particularly the ones that may contribute to MASLD. Herein, we discuss conventional therapies that target cardiometabolic risk factors which have the potential to improve hepatic injury, and summarize emerging therapies that target hepatic receptors, fibrosis, and fatty acid oxidation in patients with MASLD. Given the relationship between hepatic injury which leads to MASLD, insulin resistance, and ultimately atherogenic dyslipidemia our review uniquely delves into the effects of conventional and emerging therapies for MASLD on plasma lipid parameters.

INTRODUCTION: Granulocyte transfusion is one of the best therapeutic modalities in prolonged neutropenic patients with severe bacterial/fungal infections. Granulocyte harvest using conventional acid citrate dextrose (ACD) anticoagulant (ACD-A) by apheresis is not satisfactory in comparison to the use of hydroxyethyl starch (HES), but the latter is associated with various adverse events, especially with high-molecular-weight HES. AIMS AND OBJECTIVE: This study aimed to assess the beneficial impact of the use of medium-molecular-weight (MMW)-HES and trisodium citrate combination over ACD-A in granulocyte apheresis when using Spectra Optia. MATERIALS AND METHODS: This was a retrospective study comparing granulocyte harvest results with the use of ACD or HES and trisodium citrate combination. All the donors in both the groups received single 600 μg of granulocyte colony-stimulating factor subcutaneous injection followed by 8 mg of dexamethasone tablet 10–12 h and omnacortil 60 mg orally 3 h before harvest. A number of adverse incidents, if any, were observed and noted. Donor/procedure parameters were compared using Mann–Whitney U-test/unpaired t-test. RESULTS: Granulocyte yield (mean: 3.29 × 1010/unit vs. 4.5 × 1010/unit in the ACD and HES groups, respectively, P ≤ 0.0001) was significantly better in the HES group. The collection efficiency was also better in the HES group (mean: 15.86% vs. 26.70% in the ACD and HES groups, respectively, P ≤ 0.0001) in the ACD and HES groups, respectively. There was no significant adverse event noted in any of these two groups. CONCLUSION: In our study, granulocytes with optimum yield can be easily harvested with Spectra Optia cell separator using 6% HES (MMW) and trisodium citrate combination with standard 12-h interval gap between mobilization and harvest. This strategy can also have no or minimal extra cost burden to patients.

Abstract Cardiac rhythm regulated by micro-macroscopic structures of heart. Pacemaker abnormalities or disruptions in electrical conduction, lead to arrhythmic disorders may be benign, typical, threatening, ultimately fatal, occurs in clinical practice, patients on digitalis, anaesthesia or acute myocardial infarction. Both traditional and genetic animal models are: In-vitro: Isolated ventricular Myocytes, Guinea pig papillary muscles, Patch-Clamp Experiments, Porcine Atrial Myocytes, Guinea pig ventricular myocytes, Guinea pig papillary muscle: action potential and refractory period, Langendorff technique, Arrhythmia by acetylcholine or potassium. Acquired arrhythmia disorders: Transverse Aortic Constriction, Myocardial Ischemia, Complete Heart Block and AV Node Ablation, Chronic Tachypacing, Inflammation, Metabolic and Drug-Induced Arrhythmia. In-Vivo: Chemically induced arrhythmia: Aconitine antagonism, Digoxin-induced arrhythmia, Strophanthin/ouabain-induced arrhythmia, Adrenaline-induced arrhythmia, and Calcium-induced arrhythmia. Electrically induced arrhythmia: Ventricular fibrillation electrical threshold, Arrhythmia through programmed electrical stimulation, sudden coronary death in dogs, Exercise ventricular fibrillation. Genetic Arrhythmia: Channelopathies, Calcium Release Deficiency Syndrome, Long QT Syndrome, Short QT Syndrome, Brugada Syndrome. Genetic with Structural Heart Disease: Arrhythmogenic Right Ventricular Cardiomyopathy/Dysplasia, Dilated Cardiomyopathy, Hypertrophic Cardiomyopathy, Atrial Fibrillation, Sick Sinus Syndrome, Atrioventricular Block, Preexcitation Syndrome. Arrhythmia in Pluripotent Stem Cell Cardiomyocytes. Conclusion: Both traditional and genetic, experimental models of cardiac arrhythmias’ characteristics and significance help in development of new antiarrhythmic drugs.

The scarcity of freshwater is one of the biggest issues in the world, as a result of which more attention is given to the thermal distillation process for seawater and as well as brackish water distillation which removes almost all types of contaminants. Multiple effect distillation makes the process economical by recycling the latent heat of vaporization. In this paper a vertical tube evaporator is designed for a small scale thermal driven MED system comprising six effects and one condenser and a boiler that can produce 20–25 kg/hr of steam. VTE dimensions are calculated by estimating the outside diameter for different configurations. Heat transfer coefficient was estimated by using the developed correlations of the Bell method, Kandlikar and Kutateladze, compared with previous experiments and then used for calculating the heat transfer area for different distillate flow rates. An appropriate vertical tube evaporator is designed with the developed model to condense 25–30 kg/hr steam for producing 50–75 lt/hr freshwater. The result shows good agreement with previous work and reliability in design. The Developed model can also be used to design the vertical tube evaporator for different sizes (micro scale to large scale) MED plant. HIGHLIGHTS A vertical tube evaporator was designed for six effect small scale thermal-driven multiple effect distillation.; Vertical tube evaporator dimensions were calculated by estimating outside diameter for different configurations.; The vertical tube evaporator was designed for thermal driven multiple effect distillation for different capacities with low cost and high efficiency.;

Introduction: Fumarate hydratase (FH) deficient uterine leiomyomas account for only 0.4 % of all uterine leiomyomas. They are characterized by some distinct histological features and may be associated with Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome. Methods: Herein we present a series of five cases of FH deficient uterine leiomyomas in patients with a mean age of 30 years. All five patients underwent myomectomy. Three of these cases had an outside histopathologic diagnosis ranging from Smooth muscle tumor of uncertain malignant potential (STUMP) to Leiomyosarcoma while two cases were operated at our centre. All five cases were reported as suggestive of FH deficient leiomyomas and were advised germline testing along with genetic counselling. Results: Immunohistochemically four of the cases showed moderate to strong positivity for 2-SC with a complete loss or reduced expression of FH while one case showed absence of 2-SC staining. Discussion: Mutations in FH lead to reduced enzyme activity and accumulation of fumarate leading to a complete loss or aberrant reduced expression seen on immunohistochemistry, which confirms the diagnosis. It is important to differentiate it from a leiomyosarcoma or other malignant spindle cell tumors as these tumors follow a benign course. Their association with HLRCC also needs to be established for a suitable follow up since HLRCC-associated RCCs are often aggressive. Conclusion: Management of such leiomyomas is myomectomy or hysterectomy with advice of genetic testing to rule out HLRCC. Histomorphology and immunohistochemistry are imperative for a correct and timely diagnosis.

Background Literature suggests a bidirectional association between advanced hepatic fibrosis (AHF) and coronary artery disease (CAD). We evaluated the association of AHF with immune activation, systemic inflammation, and adverse outcomes in patients with CAD. Methods and Results A fibrosis‐4 index cutoff value ≥2.67 was used to define AHF. Circulating levels of soluble urokinase plasminogen activator receptor and hsCRP (high‐sensitivity C‐reactive protein) were measured as markers for immune activation and systemic inflammation, respectively. The relationship of AHF with soluble urokinase plasminogen activator receptor, hsCRP, and adverse cardiovascular outcomes was evaluated. Among 3406 participants with CAD, 479 had AHF. Participants with AHF were older; were less likely to be Black individuals; and had a lower body mass index, worse renal function, and a prior history of heart failure. In multivariable linear regression models adjusted for clinical and demographic confounders, participants with AHF had 15.6% higher soluble urokinase plasminogen activator receptor and 24.0% higher hsCRP levels. They were more likely to experience the following adverse outcomes: all‐cause death (adjusted hazard ratio [HR], 1.57 ([95% CI, 1.29–1.92]; P

Evapotranspiration is one of agricultural water management's most significant and impactful hydrologic processes. A new multi-decomposition deep learning-based technique is proposed in this study to forecast weekly reference evapotranspiration (ETo) in western coastal regions of Australia (Redcliffe and Gold Coast). The time-varying filter-based empirical mode decomposition (TVF-EMD) technique was used to first break down the original meteorological variables/signals into intrinsic mode decomposition functions (IMFs), which included maximum and minimum temperature, relative humidity, wind speed, and solar radiation. Using a partial autocorrelation function (PACF), the significant lagged values were then calculated from the decomposed sub-sequences (i.e., IMFs). A novel Extra Tree- Boruta feature selection algorithm was used to extract important features from the decomposed IMFs. Four machine learning approaches, including bidirectional recurrent neural network (Bi-RNN), multi-layer perceptron neural network (MLP), random forest (RF), and extreme gradient boosting (XGBoost), were used to forecast weekly evapotranspiration using the TVF-EMD-based decomposed meteorological data. Different statistical metrics were applied to evaluate the model performances. The results showed that the decomposition of the input data by TVF-EMD significantly improved the accuracy compared with the non-decomposed inputs (single models without decomposition). The findings indicate that the TVF-BiRNN model, as presented, achieved the highest level of accuracy in simulating weekly ET0 at both the Redcliffe and Gold Coast stations (Redcliffe: R=0.9281, RMSE=3.8793 mm/week, MAPE = 9.2010%; Gold Coast: R=0.8717, RMSE=4.1169 mm/week, MAPE = 11.5408%). The novel hybrid modeling technique can potentially improve agricultural water management through its ability to generate more accurate ETo estimates weekly. The proposed methodology exhibits potential applicability to various other environmental and hydrological modeling issues.

Hybridization of electrodialysis (ED) and batch reverse osmosis (BRO) process is used to reduce the brine volume and water production cost. The ED process has the benefit of high water volume recovery in brackish water desalination, while reverse osmosis can produce pure water at a low production cost. Here, a simple hybrid process layout is preferred in which the ED process is kept in the reject stream of the BRO process and permeate from both ED and BRO is mixed. Recovery of the ED process is kept at 70% which can decide the blending ratio of ED and BRO permeates. The capital cost and operating cost of ED and BRO processes are used to calculate water production cost. The water production cost from the hybrid ED–BRO process is found to be 0.22 $ m−3 of freshwater when the feed concentration is 1,100 ppm. The cost increases from 0.20 to 0.34 $ m−3 with feed concentration from 1,000 to 2,000 ppm. In the cost, a major portion comes from the capital equipment in which the highest contributor is the membrane for both ED and BRO processes. HIGHLIGHTS Designing hybrid electrodialysis and batch reverse osmosis process for brackish water desalination.; Effect of feed concentration on the freshwater cost of the hybrid ED–BRO process.; The hybrid process increases water recovery and has 0.22 $ m−3 freshwater cost at 1,100 ppm feed concentration.;

A polyherbal formulation consisting of Withania somnifera, Tinospora cordifolia, Moringa oleifera, Adhatoda vasica, Pipper longum, Glycyrrhiza glabra, Ocimum sanctum and Curcuma longa has been used for Covid-19 treatment empirically, which was found effective. However, toxicity data were not available for this polyherbal formulation. This study aims to assess the polyherbal formulation's oral acute and subchronic toxicity in rats. The fixed-dose approach was used to conduct the acute toxicity investigation on 6 female Wistar rats for the treatment group and 5 female Wistar rats for the control group. A single dosage of this polyherbal formulation weighing 2,000 mg/kg was administered orally to the test group. At the end of the investigation, no fatalities or major toxic effects were noted, and it was determined that the lethal dose 50% (LD50) of the polyherbal formulation was greater than 2,000 mg/kg. Vital organs underwent macroscopic and microscopic inspection, neither of which revealed any toxicity signs. The polyherbal formulation was given orally for 91 days during the subchronic toxicity research in dose variations: 250 mg/kg, 500 mg/kg, 1,000 mg/kg, 2,000 mg/kg, and 4,000 mg/kg. The daily dose for a human is the same at the lowest level of 250 mg/kg. On physical signs and symptoms, weight growth, food intake, haematological parameters, biochemical parameters, and macroscopic and microscopic examination of organs, no major harmful effects were seen at any of these doses. These results demonstrated that the oral administration of this polyherbal formulation over the short- and long-term is safe when taken as suggested. Keywords: Ayurvedic, Polyherbal, COVID­19, Acute toxicity, Sub­chronic Oral Toxicity

Introduction Mission Thrombectomy, established in 2016 by the Society of Vascular and Interventional Neurology, aims to enhance global accessibility to mechanical thrombectomy surgery for strokes caused by large vessel occlusion in the brain. High school students interested in exposure to global health have limited access to get exposure in this rapidly expanding area of public health. The MT2020+ student internship was designed in collaboration with MT2020+ to provide such an experience to US High School students. Students designed and carried out projects to raise stroke awareness among other high school students and communities while studying the barriers to stroke treatment. We report on this novel internship program's methodology, results, and outcomes. Methods The MT2020+ internship program followed a comprehensive framework. Three phases were implemented: Phase A involved secondary research, stakeholder identification, and the formation of a detailed survey and interview questions. Stakeholders included neurologists, neuro‐interventionalists, neuro‐radiologists, and members of stroke societies. Countries in the region of interest were categorized into three groups based on stroke and COVID‐19 data. A survey template was created in Phase B, and stakeholders were contacted for data collection. Interviews were conducted to delve deeper into survey responses. Phase C focused on analyzing the collected data, articulating the key barriers, and generating a written report. Interns also developed interventions to address key barriers identified during the research. Results The first cohort (2020) comprised 8 interns who investigated barriers to stroke treatment across different regions. The interns received survey responses and conducted interviews with stakeholders. Their research covered the U.S. & North America, Latin America, Europe, Africa, Asia, and Australia. The outcomes varied, with different levels of engagement. One student developed an app in Peru to address transportation, educational, and rehabilitation barriers. The second cohort (2021) had 2 interns who focused on Latin America and Asia, working on rehabilitation apps. The third cohort (2022) included 4 interns studying Asia, Australia/New Zealand, North America/US, and Latin America. Their interventions ranged from creating stroke awareness clubs to organizing virtual conferences. Conclusion The MT2020+ student internship provided a novel opportunity for high school students to get exposure to global health implementation. The student research in this internship has contributed valuable insights into stroke treatment barriers and raised awareness among high school students worldwide.

Therapeutic Area: ASCVD/CVD in Special Populations Background: Association between socioeconomic status and cardiovascular diseases (CVD) is well-documented. Racial disparities in prevalence and outcomes of CVD have also been extensively studied. The intersection of income, race, and CVD is relatively underexplored. Hence, we aimed to study the prevalence of CVD and associated risk factors among different races/ethnicities across different income groups. Methods: This retrospective analysis included data from participants from the National Health and Nutrition Examination Survey from 2005-2018. Adults ≥20 years who identified as non-Hispanic (NH) White, NH Black, or Hispanic (Mexican-American and other Hispanics) were included. Family income to poverty ratio (PIR) was calculated by dividing family (or individual) income by poverty guidelines specific to the survey year and used as a measure of socioeconomic status. The participants were divided into four quartiles based on PIR 3.9 (highest income). Weighted logistic regression was performed to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association of race/ethnicity and CVD and associated risk factors in each quartile. Models were adjusted for age, sex, race, health insurance, marital status, citizenship status, and level of education and PIR. Results: We included 31,884 unweighted participants that corresponded to 191,307,167 weighted, nationally representative participants. Of these, 8,009 (weighted 16.3%), 7,967 (weighted 19.2%), 7,944 (weighted 26.9%), and 7,964 (weighted 37.5%) participants belonged to 1st, 2nd, 3rd, and 4th quartiles respectively. The proportion of NH-Whites increased with increasing PIR quartiles whereas the proportion of NH-Blacks and Hispanics decreased with increasing PIR quartiles. In adjusted analyses, the prevalence odds of diabetes mellitus (DM), hypertension, coronary artery disease (CAD), congestive heart failure (CHF), and stroke decreased in a step-wise manner from 1st to 4th PIR quartile. Overall, NH Blacks had higher prevalence odds of DM, hypertension, obesity, CHF, and stroke compared to NH Whites, whereas NH Whites had higher prevalence odds of CAD and dyslipidemia compared to NH Blacks (Figure 1). The model testing for PIR-race/ethnicity interaction revealed that PIR-race/ethnicity interaction was significant for obesity (P-interaction 0.002) and diabetes mellitus (P-interaction 0.027) (Figure 2). The difference in prevalence odds between NH White adults and NH Black adults was greater for obesity and diabetes mellitus in the highest PIR quartile compared to the lowest PIR quartile. PIR-race/ethnicity interaction for stroke was 0.053 with the difference in prevalence odds between NH White adults and NH Black adults being greater in the higher PIR quartiles compared to the lowest PIR quartile. Conclusions: The difference in prevalence between NH White and NH Black adults was greater for diabetes mellitus, obesity and stroke in the highest PIR quartile compared to the lowest PIR quartile. These data suggest a complex interplay between race/ethnicities and income inequalities resulting in disparities in CVD.

Therapeutic Area: ASCVD/CVD in Special Populations Background: Association between socioeconomic status and cardiovascular diseases (CVD) is well-documented. Racial disparities in prevalence and outcomes of CVD have also been extensively studied. The intersection of income, race, and CVD is relatively underexplored. Hence, we aimed to study the prevalence of CVD and associated risk factors among different races/ethnicities across different income groups. Methods: This retrospective analysis included data from participants from the National Health and Nutrition Examination Survey from 2005-2018. Adults ≥20 years who identified as non-Hispanic (NH) White, NH Black, or Hispanic (Mexican-American and other Hispanics) were included. Family income to poverty ratio (PIR) was calculated by dividing family (or individual) income by poverty guidelines specific to the survey year and used as a measure of socioeconomic status. The participants were divided into four quartiles based on PIR 3.9 (highest income). Weighted logistic regression was performed to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association of race/ethnicity and CVD and associated risk factors in each quartile. Models were adjusted for age, sex, race, health insurance, marital status, citizenship status, and level of education and PIR. Results: We included 31,884 unweighted participants that corresponded to 191,307,167 weighted, nationally representative participants. Of these, 8,009 (weighted 16.3%), 7,967 (weighted 19.2%), 7,944 (weighted 26.9%), and 7,964 (weighted 37.5%) participants belonged to 1st, 2nd, 3rd, and 4th quartiles respectively. The proportion of NH-Whites increased with increasing PIR quartiles whereas the proportion of NH-Blacks and Hispanics decreased with increasing PIR quartiles. In adjusted analyses, the prevalence odds of diabetes mellitus (DM), hypertension, coronary artery disease (CAD), congestive heart failure (CHF), and stroke decreased in a step-wise manner from 1st to 4th PIR quartile. Overall, NH Blacks had higher prevalence odds of DM, hypertension, obesity, CHF, and stroke compared to NH Whites, whereas NH Whites had higher prevalence odds of CAD and dyslipidemia compared to NH Blacks (Figure 1). The model testing for PIR-race/ethnicity interaction revealed that PIR-race/ethnicity interaction was significant for obesity (P-interaction 0.002) and diabetes mellitus (P-interaction 0.027) (Figure 2). The difference in prevalence odds between NH White adults and NH Black adults was greater for obesity and diabetes mellitus in the highest PIR quartile compared to the lowest PIR quartile. PIR-race/ethnicity interaction for stroke was 0.053 with the difference in prevalence odds between NH White adults and NH Black adults being greater in the higher PIR quartiles compared to the lowest PIR quartile. Conclusions: The difference in prevalence between NH White and NH Black adults was greater for diabetes mellitus, obesity and stroke in the highest PIR quartile compared to the lowest PIR quartile. These data suggest a complex interplay between race/ethnicities and income inequalities resulting in disparities in CVD.

Therapeutic Area: Heart Failure Background: Several studies have shown that most patients who are eligible for an Sodium-glucose Cotransporter-2 inhibitor (SGLT2i) are not receiving them and the proportion of prescriptions from cardiologists was very low (

Forecasting accurately suspended sediment load (SSL) in the basin is one of the most critical issues for river engineering, environment, and water resources management which effectively reduces flood damages. In this study, a new multi-criteria hybrid expert system comprised of empirical wavelet decomposition (EWT) integrated with Encoder-Decoder Bidirectional long short-term memory (EDBi-LSTM), supported by five feature selection (FS) methods was developed for the first time to forecast daily SSL at two study sites (Bamini and Ashti) of Godavari river basin, India. The employed FS schemes are including Boruta-Random forest (BRF), simulated annealing (SA), Relief algorithm, Ridge regression (RR), and Mutual information (MI) where the BRF coupled with EWT and EDBi-LSTM (i.e., EWT-EDBi-LSTM-Boruta) is identified as the main forecasting paradigm. Here the original SSL signals in the monsoon season (2001–2015) as the only input information were considered to forecast SSL events at a daily time scale in both study zones. The SSL signals were decomposed using the EWT technique considering the significant antecedent time-lagged inputs based on partial auto-correlation function (PACF). In the next stage, five FS strategies were addressed to specify the significant sub-sequences to reduce computational cost and enhance forecasting accuracy. Besides, the extreme gradient boosting (XGB) approach was implemented to compare the potential of the hybrid EDBi-LSTM and standalone counterpart models for both study sites. According to several goodness-of-fit indices and validation tools, the outcomes at the Bamini and Ashti sites demonstrated that the EWT-EDBi-LSTM-Boruta as the main model, achieved the best accuracy, followed by EWT-XGB-Boruta, EWT-EDBi-LSTM-SA, and EWT-XGB-SA, respectively. Comparing all the hybrid models showed that the BRF, SA, and RR strategies performed better in integration with machine learning (ML) models.

Total phosphorus (T-P) refers to the concentration of phosphorus in water and is one of the important parameters for eutrophication in lakes and rivers. In current research, neuroscience dependent (i.e., singular and double-platform synthetic) approaches were employed to predict the river T-P concentration. Singular techniques were developed utilizing machine learning based (support vector machines (SVMs), stochastic gradient boosting (SGB)), and deep learning based multilayer perceptron (DMLP) models. Besides, double-platform synthetic techniques were developed by integrating a prior data-processing (Discrete-wavelet) algorithm with the singular techniques. Six input scenarios conditional on different water quantity and quality parameters acquired from two stations (Hwangji and Toilchun), South Korea, were employed for appraising singular and double-platform synthetic techniques. The various promoted models were evaluated using four statistical standards viz., mean absolute error (MAE), root mean square error (RMSE), scatter index (SI), and Pearson correlation coefficient (CCp), and four visual references viz., scatter diagram, box-and-whisker plot, violin plot, and Taylor diagram. It can be indicated from the outcomes that the double-platform synthetic techniques did not always lead to more accurate predictions than the singular techniques. Further, results also supplied that the SGB with the 6th input (MAE = 0.012 mg/L, RMSE = 0.014 mg/L, and CCp = 0.650 for Hwangji; MAE = 0.011 mg/L, RMSE = 0.017 mg/L, and CCp = 0.963 for Toilchun) scenario model demonstrated the best accuracy for predicting river T-P concentration by the singular techniques for both stations, whereas the discrete-wavelet SVMs with the 4th input (MAE = 0.007 mg/L, RMSE = 0.011 mg/L, and CCp = 0.765 for Hwangji) and discrete-wavelet SGB with the 5th input (MAE = 0.012 mg/L, RMSE = 0.017 mg/L, and CCp = 0.953 for Toilchun) scenario models provided the best predictive accuracy among double-platform synthetic techniques, respectively.

Due to the COVID-19 pandemic’s rapid expansion, the creation of vaccines is crucial for lowering disease transmission. Therefore, to determine the safety and efficacy of the vaccine against symptomatic illness and to evaluate breakthrough infections, those who received single or both the doses of vaccine against COVID-19 infection. A retrospective observational study was carried out on vaccine efficacy and the incidence of the breakthrough infections among the heath care workers, support staff and administrative staff. Out of 599 fully vaccinated health care workers, those who tested COVID-19 positive post-vaccination only 1.16% developed a severe illness that necessitates hospitalization. This study reflects a significant vaccine efficacy of 81.3% after a complete dose of vaccination and protection of 76.9% after one standard dose against symptomatic disease. The frequency of COVID-19 vaccine breakthrough is very low, which means that COVID-19 vaccines are highly effective at preventing COVID-19, particularly when it comes to severity.

Bottle gourd, a common vegetable in the human diet, has been valued for its medicinal and energetic properties. In this experiment, the time-resolved analysis of the changes in the proteins’ electrophoretic patterning of the seed development at different crossing periods was studied in bottle gourd using label-free quantitative proteomics. Hybrid HBGH-35 had the highest observed protein levels at the 4th week of the crossing period (F4) compared to the parental lines, viz. G-2 (M) and Pusa Naveen (F). The crossing period is significantly correlated with grain filling and reserve accumulation. The observed protein expression profile after storage was related to seed maturation and grain filling in bottle gourds. A total of 2517 proteins were identified in differentially treated bottle gourd fruits, and 372 proteins were differentially expressed between different crossing periods. Proteins related to carbohydrate and energy metabolism, anthocyanin biosynthesis, cell stress response, and fruit firmness were characterized and quantified. Some proteins were involved in the development, while others were engaged in desiccation and the early grain-filling stage. F4 was distinguished by an increase in the accumulation of low molecular weight proteins and enzymes such as amylase, a serine protease, and trypsin inhibitors. The seed vigor also followed similar patterns of differential expression of seed storage proteins. Our findings defined a new window during seed production, which showed that at F4, maximum photosynthetic assimilates accumulated, resulting in an enhanced source–sink relationship and improved seed production. Our study attempts to observe the protein expression profiling pattern under different crossing periods using label-free quantitative proteomics in bottle gourd. It will facilitate future detailed investigation of the protein associated with quality traits and the agronomic importance of bottle gourd through selective breeding programs.

Abstract Background KRAS, although a common variant of occurrence (~20% of non‐small‐cell lung carcinoma [NSCLC]) has been untargetable, owing to the molecular structure which inherently prevents drug binding. KRAS mutations in NSCLC are associated with distinct clinical profiles including smokers and mucinous histology. KRAS G12C mutations account for ~40% KRAS altered NSCLC, but NSCLC being a geographically diverse disease, the features may be distinct in this part of the world. This is a single‐center experience of KRAS‐mutated NSCLC including clinical, imaging, pathologic features, and treatment patterns and outcomes. Methods This is a single‐center retrospective study of KRAS‐mutated NSCLC. The clinicopathological features and outcomes were retrieved and collated from the medical record archives of the hospital. Results Fifty (30.6%) patients with advanced‐stage NSCLC with alterations in the KRAS gene were enrolled in the 163 patients who were tested for KRAS alterations. The median age was 61 years. Molecular detection revealed three main types of KRAS mutations viz‐a‐vis: G12C in 17 (34%), G12V in 9 (18%), and G12D in 6 (12%) patients. Comparing G12C versus the non‐G12C mutated cases, co‐mutations were common in the non‐G12C subgroup (p

Background: Rapid-onset obesity with hypoventilation, hypothalamic dysfunction, and autonomic dysregulation (ROHHAD) syndrome is a rare cause of obesity, characterized by early and rapid onset of obesity, hypoventilation, hypothalamic dysfunction, and autonomic dysfunction. When there is an associated neuroendocrine tumor, (NET) it becomes ROHHAD NET. Hypothalamic dysfunction causes endocrine problems, respiratory dysfunction, and autonomic alterations. It is difficult to distinguish this clinically from other obesity syndromes of genetic origin unless an individualized strategic approach is used. Clinical Description: We present a case of a 5-year-old developmentally normal girl with excessive weight gain starting in early childhood and the development of a squint. The clinical phenotype of central hypoventilation and autonomic dysfunction, central hypothyroidism, and central precocious puberty satisfied the criteria for ROHHAD syndrome. Management: A right-sided paraspinal supradiaphragmatic mass was identified that was excised and diagnosed as neuroblastoma on histopathology. Since there was no evidence of metastases, chemotherapy was not indicated. Alpha and beta-blockers were started for autonomic dysfunction and high catecholamine levels. Lack of improvement in behavioral manifestations prompted a trial of immunosuppressive therapy, but yielded no results. She ultimately succumbed to a probable cardiorespiratory arrest during sleep. Conclusions: ROHHAD syndrome should be considered a differential diagnosis in rapid-onset monogenic obesity and should be managed with a multidisciplinary approach. Prognosis is guarded due to sudden life-threatening events secondary to autonomic dysfunction.

Automatic liver cancer detection (ALCD) is very crucial in automatic biomedical image analysis and diagnosis as it is the largest organ in the body and plays a significant role in the metabolic process as well as the elimination of toxins. In the last decade, various machine and deep learning schemes have been investigated for automatic ALCD using computed tomography (CT) images. However, ALCD in CT images is challenging because of the noise, intricate structure of abdominal computed tomography (CT) images, and textural changes throughout the CT images making liver segmentation a vital challenge that may result in both under-segmentation (u-seg) and over-segmentation ( o-seg) of the organ. This paper presents liver segmentation based on the proposed Edge Strengthening Parallel UNet (ESP-UNet) for liver segmentation to avoid the u-seg and o-seg of the liver in CT images. Further, it offered ALCD based on lightweight sequential Deep Convolution Neural Networks (DCNN). The consequences of ESP-UNet DCNN-based ALCD are evaluated based on accuracy, recall, precision, and F1-score. The suggested approach provides a noteworthy improvement in ALCD over the traditional state of arts.

Lung cancer (LC) is one of the leading causes of cancer deaths worldwide. In India, the incidence of LC is increasing rapidly, and a majority of the patients are diagnosed at advanced stages of the disease when treatment is less likely to be effective. Recent therapeutic developments have significantly improved survival outcomes in patients with LC. Prompt specialist referral remains critical for early diagnosis for improved patient survival. In the Indian scenario, distinguishing LC from benign and endemic medical conditions such as tuberculosis can pose a challenge. Hence, awareness regarding the red flags—signs and symptoms that warrant further investigations and referral—is vital. This review is an effort toward encouraging general physicians to maintain a high index of clinical suspicion for those at risk of developing LC and assisting them in refering patients with concerning symptoms to specialists or multidisciplinary teams as early as possible.

Abstract Socioeconomic status is an overlooked risk factor for cardiovascular disease (CVD). Low family income is a measure of socioeconomic status and may portend greater CVD risk. Therefore, we assessed the association of family income with cardiovascular risk factor and disease burden in American adults. This retrospective analysis included data from participants aged ≥ 20 years from the National Health and Nutrition Examination Survey (NHANES) cycles between 2005 and 2018. Family income to poverty ratio (PIR) was calculated by dividing family (or individual) income by poverty guidelines specific to the survey year and used as a measure of socioeconomic status. The association of PIR with the presence of cardiovascular risk factors and CVD as well as cardiac mortality and all-cause mortality was examined. We included 35,932 unweighted participants corresponding to 207,073,472 weighted, nationally representative participants. Participants with lower PIR were often female and more likely to belong to race/ethnic minorities (non-Hispanic Black, Mexican American, other Hispanic). In addition, they were less likely to be married/living with a partner, to attain college graduation or higher, or to have health insurance. In adjusted analyses, the prevalence odds of diabetes mellitus, hypertension, coronary artery disease (CAD), congestive heart failure (CHF), and stroke largely decreased in a step-wise manner from highest (≥ 5) to lowest PIR (

Abstract Dinesh Chandra Doval Background Circulating tumor cells (CTCs) in the peripheral blood may play a major role in the metastatic spread of breast cancer. This study was conducted to assess the role of CTCs to determine the prognosis in terms of survival in metastatic breast cancer patients. Methods This prospective study of 36 patients was conducted at the Hospital from April 2016 to May 2018. Details of each patient related to the demographic profile, tumor type, treatment, and follow-up information were recorded. The number of CTCs in the peripheral blood was measured by Celsee PREP 400 sample processing system and Celsee Analyzer imaging station. Results There was a positive correlation between the number of site of metastasis with number of CTCs (p-value

In the present study, two innovative techniques namely, Deep Learning (DL) and Gradient boosting Machine (GBM) models are developed based on a maximum air temperature ‘univariate modeling scheme’ for modeling the monthly pan evaporation (Epan) process. Monthly air temperature and pan evaporation are used to build the predictive models. These models are used for evaluating the evaporation prediction for the Kiashahr meteorological station located in the north of Iran and Ranichauri station positioned in Uttarakhand State of India. Findings indicated that the deep learning model was found best at Kiashahr station for testing datasets MAE (0.5691, mm/month), RMSE (0.7111, mm/month), NSE (0.7496), and IOA (0.9413). It can be concluded that in the semi-arid climate of Iran both of the used methods had the good capability in modeling of monthly Epan. However, DL predicted monthly Epan better than GBM. Moreover, the highest accuracy of the deep learning model was also observed for the Ranichauri station in terms of MAE = 0.3693 mm/month, RMSE = 0.4357 mm/month, NSE = 0.8344, & IOA = 0.9507 in testing stage. Overall, results expose the superior performance of DL-based models for both study stations and can also be utilized for various other environmental modeling.

Covalent organic frameworks (COFs) have attracted attention due to their ordered pores leading to important industrial applications like storage and separation. Combined with their modular synthesis and pore engineering, COFs could become ideal candidates for nanoseparations. However, the fabrication of these microcrystalline powders as continuous, crack‐free, robust films remains a challenge. Herein, we report a simple, slow annealing strategy to construct centimeter‐scale COF films (Tp‐Azo and Tp‐TTA) with micrometer thickness. The as‐synthesized films are porous (SABET=2033 m2 g−1 for Tp‐Azo) and chemically stable. These COFs have distinct size cut‐offs (ca. 2.7 and ca. 1.6 nm for Tp‐Azo and Tp‐TTA, respectively), which allow the size‐selective separation of gold nanoparticles. Unlike, other conventional membranes, the durable structure of the COF films allow for excellent recyclability (up to 4 consecutive cycles) and easy recovery of the gold nanoparticles from the solution. [ABSTRACT FROM AUTHOR]

Follicular lymphoma (FL) is a mature B-cell lymphoma that can transform into a more aggressive disease such as diffuse large B-cell lymphoma, Burkitt lymphoma, or precursor B-lymphoblastic leukaemia/lymphoma. The process of transformation of FL occurs by the acquisition of additional genetic alterations, e.g. c-MYC rearrangement, TP53, and cyclin D1 inactivation. Herein, we describe four such cases of FL that transformed into more aggressive B-cell non-Hodgkin lymphomas within six months of their initial diagnosis. Subsequent testing of c-myc, P53 and cyclin D1 by immunohistochemistry and fluorescence in situ hybridization was done to further analyse their role in the process of transformation.

Background/Aims Response to vaccine in patients with inflammatory bowel disease is lower than in the general population. We aimed to evaluate the efficacy of hepatitis B virus (HBV) vaccination in patients with ulcerative colitis (UC) versus controls. Methods We prospectively compared antibody response to HBV vaccination in 100 patients with UC versus controls. HBV vaccination was given to all the cases and controls at 0, 1 and 6 months. Anti-hepatitis B surface (anti-HBs) titers were then measured 4 weeks after the first and the third dose. Adequate immune response (AIR) was considered if the anti-HBs titer was >10 IU/L and effective immune response (EIR) if the anti-HBs titer was >100 IU/L. Results Median anti-HBs titer was lower in patients with UC than controls (67 IU/L vs. 105 IU/L, P2 IU/L and non-exposure to corticosteroids, azathioprine and biologicals were predictors of AIR in patients with UC (P

Background: Inappropriate broad-spectrum antibiotic use targeting methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa can result in increased adverse events, antibiotic resistance, and Clostridioides difficile infection. In 2019, revised ATS/IDSA community-acquired pneumonia (CAP) guidelines removed healthcare-associated pneumonia (HCAP) as a clinical entity and modified patient factors warranting empiric broad-spectrum antibiotic (BSA) use. As a result, most patients hospitalized with CAP should receive empiric antibiotics targeting standard CAP pathogens. Based on revised guidelines, we evaluated predictors and outcomes associated with inappropriate BSA use among hospitalized patients with CAP. Methods: Between November 2019 and July 2022, trained abstractors collected data on non-ICU adult medical patients admitted with CAP at 67 Michigan hospitals who received either an inappropriate empiric BSA on hospital day 1 or 2 or a standard CAP regimen. Inappropriate empiric BSA use was defined as use of an anti-MRSA or anti-pseudomonal antibiotic in a patient eligible for standard CAP coverage per IDSA guidelines. Patients with immune compromise, moderate or severe chronic obstructive pulmonary disease (COPD), pulmonary complication, or guideline-concordant treatment with BSA were excluded. Data collected included comorbidities, antibiotic use and hospitalizations in the preceding 90 days, cultures in the preceding year, signs or symptoms of pneumonia, hospital characteristics, and 30-day postdischarge patient outcomes. Data were collected through chart review and patient phone calls. Predictors of inappropriate empiric BSA were evaluated using logistic general estimating equation (GEE) models, accounting for hospital-level clustering. We assessed the effect of inappropriate empiric BSA (vs standard CAP therapy) on 30-day patient outcomes using logistic GEE models controlling for predictors associated with the outcome and probability of treatment. Results: Of 8,286 included patients with CAP, 2,215 (26.7%) were empirically treated with inappropriate BSA. The median BSA treatment was 3 days (IQR, 2.5). After adjustments, factors associated with inappropriate empiric BSA treatment included hospitalization or treatment with high-risk antibiotics in preceding 90 days, transfer from a postacute care facility, hemodialysis, support with ≥3 L supplemental oxygen, severe sepsis, leukocytosis, and higher pneumonia severity index (Fig. 1). After adjustments, patients with inappropriate empiric BSA treatment had higher readmissions 30 days after discharge, more transfers to the intensive care unit, more antibiotic-associated adverse events, and longer hospitalizations (Fig. 2). Conclusions: Patients hospitalized with CAP often received inappropriate BSA as empiric coverage, and this inappropriate antibiotic selection was associated with worse patient outcomes. To improve patient outcomes, stewardship efforts should focus on reducing inappropriate BSA use in patients hospitalized for CAP with historic HCAP risk factors or severe CAP without other guideline-directed indications for BSA.

Background: Antibiotic overuse and the resulting patient outcomes span all hospitals. However, although antibiotic stewardship can improve antibiotic use, effective stewardship programs require expertise and an infrastructure that are not present in all hospitals. Rural hospitals have less access to resources, infectious disease expertise, and participation in academic research. Thus, we compared antibiotic overuse at discharge between rural and nonrural hospitals for patients diagnosed with community-associated pneumonia (CAP) or urinary tract infection (UTI)—the 2 most common hospital infections. Methods: To determine whether antibiotic overuse at discharge was higher among rural versus nonrural hospitals, we analyzed data from a 41-hospital prospective cohort of patients treated for CAP or UTI between July 1, 2017, and July 30, 2019, in Michigan. Antibiotic overuse was defined as treatment that was unnecessary (ie, patient did not have an infection), excessive (ie, duration >4 days for CAP), or included suboptimal fluoroquinolone use (ie, safer alternative available). Overuse was determined based on patient risk factors, symptoms, allergies, diagnostic results, and time to stability. Hospital rurality was defined using the Rural–Urban Continuum Codes (RUCC) score. We defined rural as a score ≥4 and very rural as a score of 7–9. We used t tests to compare the mean percentage of patients with antibiotic overuse at discharge between nonrural and rural (and very rural) hospitals. Results: Across 41 hospitals, we included 23,449 patients with CAP or UTI. There were 5 rural (and 3 very rural) hospitals with 2,039 (and 1,082) patients. Antibiotic overuse at discharge was present in 43.1% of patient cases in nonrural hospitals, 52.5% in rural hospitals (P = .04 vs nonrural) and 58.1% in very rural hospitals (P = .007 vs nonrural). Compared to nonrural hospitals, the mean percentage of cases with antibiotic overuse at discharge in rural hospitals was 9.4% higher (15.1% higher in very rural hospitals). Results were similar in a subgroup analysis of only patients with UTI (47.0% in rural vs 37.5% in nonrural, mean difference, 9.5%; P = .03) but were not statistically significant in patients with CAP (53.8% vs 48.0%, respectively; mean difference, 5.8%; P = 0.23). Conclusions: In this retrospective study, rural hospitals—especially very rural hospitals, had higher rates of antibiotic overuse at discharge than nonrural hospitals. Our findings suggest that antibiotic stewardship interventions tailored toward the unique differences in infrastructure, resources, and needs of rural hospitals are essential to community health.

Background: IDSA guidelines recommend withholding treatment in patients with asymptomatic bacteriuria in the absence of systemic signs of infection. However, some patients with bacteriuria may not be able to express symptoms either due to presence of indwelling catheter, underlying complicated urologic anatomy, dementia, or altered mental status (AMS). Clinicians frequently treat bacteriuria in this population with antimicrobial therapy due to concern for sepsis. To determine treatment need, we aimed to review prevalence and risk factors for bacteremic urinary tract infection (UTI) in a cohort of hospitalized inpatients without definitive signs and symptoms of a UTI. Methods: This retrospective cohort study of inpatients with a positive urine culture who presented without definitive signs or symptoms of a UTI was conducted between July 1, 2017, and June 30, 2022, in 68 academic and community hospitals (Michigan Hospital Medicine Safety Consortium). Signs and symptoms were obtained from medical record review 3 days before and after urine-culture collection. Bacteremic UTI was defined as any positive blood culture growing at least 1 organism matching the urine culture. Risk factors for bacteremic UTI were assessed using multivariable logistic regression models with results expressed as odds ratios (ORs) for dichotomous variables and relative risks (RRs) for continuous variables. Results: Of 11,793 patients meeting study criteria, 73.6% were female with a median age of 78.2 years. Overall, 41.8% had AMS, 33.8% had dementia, 15.6% had an indwelling urinary catheter, and 54.6% had complicated urologic history (eg, urologic surgery). Of these, 166 patients (1.4%) developed bacteremic UTI. On adjusted analysis, male sex, hypotension, heart rate >90, urinary retention, fatigue, log of serum leukocytosis [1 log increase in serum WBC = 2.718 × serum white blood cell count (WBC)], and pyuria with >25 WBC per high-powered field (WBC/hpf) on urinalysis were associated with bacteremic UTI (Table). Older age, presence of an indwelling catheter, complicated urologic history, functional decline, AMS, dementia, and change in urine were not associated with higher odds for bacteremic UTI (Table). Of patients with AMS and no definitive signs or symptoms of a UTI, only 89 (1.8%) of 4,932 developed a bacteremic UTI. Conclusions: Bacteremic UTI is relatively rare in hospitalized inpatients presenting with bacteriuria without symptoms of UTI. Predictors of bacteremic UTI included male sex, hypotension, tachycardia, urinary retention, fatigue, serum leukocytosis, and higher levels of pyuria (>25 WBC/hpf) on urinalysis. Our findings provide stewards a framework to risk stratify inpatients of older age who present with positive urine cultures but without (or are unable to express) signs or symptoms of UTI.

Background: Since 2019, community-acquired pneumonia (CAP) guidelines have recommended hospitalized patients be treated until clinical “stability and for no less than 5 days.” However, randomized trials have reported that, in patients who stabilize by hospital day 3, very short antibiotic durations (eg, 3 days) are noninferior to longer durations. How these trial results relate to real-world practice is unknown. Methods: Using a 68-hospital cohort study of hospitalized, general-care adults with CAP, we aimed to (1) quantify the percentage of patients who—according to trial criteria—qualify for a 3-day antibiotic duration, (2) quantify the percentage who actually received a 3-day duration, and (3) assess 30-day outcomes. Patients were considered to have CAP if they had a pneumonia discharge diagnosis and met clinical criteria for CAP. Patients with concomitant infections (including COVID-19), admission to intensive care, or severe immunocompromise were not included. Results: Between February 23, 2017, and August 3, 2022, 36,064 patients with CAP were included. Of those, 48.2% (9,826 of 36,064) were excluded due to a condition or organism ineligible for the 3-day treatment (Fig. 1). Of the 18,690 patients remaining, 52.6% (9,826) were unstable on day 3 and thus were ineligible for the 3-day treatment. Therefore, of all 36,064 patients, only 8,864 (24.6%) would be eligible under trial criteria for a 3-day treatment. Notably, 5,493 (55.9%) of 9,826 patients unstable on day 3 would be eligible for 5 days of treatment under national guidelines. In practice, use of 3–4-day treatment was rare, occurring in 599 (6.8%) of 8,864 patients eligible for a 3-day treatment versus 660 (6.7%) of 9,826 patients unstable on day 3 (P = .945). Use of 3–4-day treatment increased over time and comorbidities that could mimic CAP or a negative procalcitonin were more common in patients who received a 3–4-day treatment whereas specific symptoms of CAP were less common (Fig. 2). After adjustments, patients eligible for a 3-day duration who received a 3–4 day treatment versus a ≥5-day treatment had higher 30-day mortality (aOR, 1.87; 95% CI, 1.32–2.64) and readmission (aOR, 1.35; 95% CI, 1.17–1.56). Conclusions: Across 68 hospitals,

As an agricultural state, Haryana (India) produces about six million metric tons (mt) of rice straw every year from rice cultivation. Currently, rice straw is either burned or ploughed into the field without being turned into a functional product. Burning of paddy straw release green house gases and particulate matter (2.5 and 10 μm), which leads to air pollution and considerable loss of soil property viz. nutrients, organic matter, productivity and biodiversity, and on and off-farm humans and animals’ health. The biochemically and functionally specified potential for optimal alternative use of the rice straw of 13 most widely produced rice varieties from Haryana’s eastern and western agro-climate zones was undertaken. Pusa-1401 variety had the highest cellulose (46.55%) and silica content (13.70%), while Pusa-1718 had hemicellulose (28.25%) and lignin (11.60%), respectively. Maximum nitrogen (0.81%), phosphorus (0.32%) and potassium (2.78%) were found in rice variety Pusa-1509, Pusa-1401 and Rice-6129. The findings seemed to be statistically significant (p

Because of its excellent ability to non-invasively assess left ventricular (LV) systolic function, two-dimensional speckle tracking echocardiography (STE) is increasingly being used in echocardiographic laboratories worldwide. Two-dimensional STE is the most sought-after method to evaluate LV strain, rotation, twist and torsion. Two dimensional, three-dimensional and four-dimensional (4D) deformation estimation by STE has several intrinsic limitations. For better appraisal of LV contractile properties, a recently introduced updated version of 4D XStrain STE has been used to analyse the various complex multidimensional LV mechanics. This novel technology is a reliable, economical and simple tool for estimating regional and global myocardial function. Furthermore, 4D XStrain STE can accurately quantify the 4D LV ejection-fraction, LV volume and sphericity index. However, this technology has not been extensively implemented, and its assessment remains limited primarily to research applications. Hence, we aim to promote this innovative technology by comprehensively addressing its technique, advantages and limitations, so that it can be better applied in cardiovascular disease.

This study investigates the spatio-temporal distribution and trends of seasonal rainfall for different meteorological sub-divisions (MSDs) of India using statistical analysis and the innovative trend analysis (ITA) method. The gridded dataset of daily rainfall for 120 years from 1901 to 2020 was obtained from the India Meteorological Department (IMD) and analysed using statistical results of mean rainfall, standard deviation, coefficient of variation, skewness, kurtosis, maximum seasonal rainfall, percent deviation of rainfall, number of rainy days, rainfall intensity, rainfall categorization, trend detection, and cross-correlation coefficients. The period was divided into three quad-decadal times (QDT) of 40 years each (i.e., 1901–1940: QDT1, 1941–1980: QDT2, and 1981–2020: QDT3). A general decrease in the number of rainfall events was observed in all the seasons except for a few MSDs of northwest India showing a rise throughout the pre-monsoon season in recent times (QDT3). Significant trends were detected using the ITA method in seasonal rainfall in nearly all the MSDs of India. Our findings are highlighting the qualitative and quantitative characteristics of seasonal rainfall dynamics at the MSDs level which will be useful for comprehending the rainfall dynamics as impacted by climate change and climate variability in India, and may further lead the policymakers and stakeholders for making the best use of available water resources. HIGHLIGHTS Spatio-temporal distribution and performance of rainfall was explored.; Spatial variability in timeseries was identified.; Innovative trend analysis on rainfall was performed for each season to see the impact of climate change and climate variablity.; Number of rainy days and rainfall intensity was analysed for each season.; Findings highlight the qualitative and quantitative aspects of seasonal rainfall dynamics.;

Abstract The rising salinity trend in the country’s coastal groundwater has reached an alarming rate due to unplanned use of groundwater in agriculture and seawater seeping into the underground due to sea-level rise caused by global warming. Therefore, assessing salinity is crucial for the status of safe groundwater in coastal aquifers. In this research, a rigorous hybrid neurocomputing approach comprised of an Adaptive Neuro-Fuzzy Inference System (ANFIS) hybridized with a new meta-heuristic optimization algorithm, namely Aquila optimization (AO) and the Boruta-Random forest feature selection (FS) was developed for estimating the salinity of multi-aquifers in coastal regions of Bangladesh. In this regard, 539 data samples, including ten water quality indices, were collected to provide the predictive model. Moreover, the individual ANFIS, Slime Mould Algorithm (SMA), and Ant Colony Optimization for Continuous Domains (ACOR) coupled with ANFIS (i.e., ANFIS-SMA and ANFIS-ACOR) and LASSO regression (Lasso-Reg) schemes were examined to compare with the primary model. Several goodness-of-fit indices, such as correlation coefficient (R), the root mean squared error (RMSE), and Kling-Gupta efficiency (KGE) were used to validate the robustness of the predictive models. Here, the Boruta-Random Forest (B-RF), as a new robust tree-based FS, was adopted to identify the most significant candidate inputs and effective input combinations to reduce the computational cost and time of the modeling. The outcomes of four selected input combinations ascertained that the ANFIS-OA regarding the best accuracy in terms of (R = 0.9450, RMSE = 1.1253 ppm, and KGE = 0.9146) outperformed the ANFIS-SMA (R = 0.9406, RMSE = 1.1534 ppm, and KGE = 0.8793), ANFIS-ACOR (R = 0.9402, RMSE = 1.1388 ppm, and KGE = 0.8653), Lasso-Reg (R = 0.9358), and ANFIS (R = 0.9306) models. Besides, the first candidate input combination (C1) by three inputs, including Cl− (mg/l), Mg2+ (mg/l), Na+ (mg/l), yielded the best accuracy among all alternatives, implying the role importance of (B-RF) feature selection. Finally, the spatial salinity distribution assessment in the study area ascertained the high predictability potential of the ANFIS-OA hybrid with B-RF feature selection compared to other paradigms. The most important novelty of this research is using a robust framework comprised of the non-linear data filtering technique and a new hybrid neuro-computing approach, which can be considered as a reliable tool to assess water salinity in coastal aquifers.