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As the textile industry expands, more industrial waste effluents are released into natural water streams, prompting the research and development of innovative materials for the remediation of environmental issues. In this research, a direct precipitation and hydrolysis method were used to synthesize ZnO and TiO2 nanoparticles, respectively that were utilized to investigate the photocatalytic activity of Congo Red (CR) dye. Afterward, the crystallite size was computed from the data of the X-ray diffractometer (XRD), and utilizing several models (Scherrer equation, LSLMSE, Monshi-Scherrer equation, Williamson-Hall model, Size-strain plot method, Halder-Wagner model, Sahadat-Scherrer model). Among these models, the size-strain plot model yields the most accurate crystal size (45.31 nm) for ZnO nanoparticles and the Halder-Wagner model (2.44 nm) for TiO2 nanoparticles. Scanning Electron Microscope exhibited the spherical shape of nanoparticles (ZnO, and TiO2) with particle size (less than 151 nm). The absorption spectrum from Fourier transform infrared (FTIR) spectroscopy confirmed the formation of nanoparticles (ZnO, and TiO2). Thereafter, the photocatalytic activity of the ZnO-TiO2 nanocomposite was evaluated by using Congo Red (CR) dye under different process variables, such as catalyst dose, time, initial dye concentration, pH, radical scavenging ability, and reusability. The best degradation (90 %) was recorded at 180 min time intervals using a 0.2 g catalyst dose with a 20 ppm CR concentration at pH 9.

This research investigates the effectiveness of using a smart ternary-hybrid nanofluid to enhance the melting rate and convective behavior of electrically conducting tin (Sn) in a rectangular enclosure under the influence of a uniform magnetic field. The enclosure has adiabatic vertical walls with hot and cold temperatures on the bottom and top walls. The finite element method (FEM) is used to solve the governing equations with appropriate boundary conditions using Galerkin's weighted residual approach. The study focuses on applying tin as the phase change material (PCM), with the highest temperature of 508 K, the lowest temperature of 503 K, and the melting interface temperature of 505 K. To enhance the heat transfer performance, tin-based ternary (graphene (G), silicon carbide (SiC), and nickel (Ni)) hybrid smart coolant is applied into the system. To investigate the mechanism of the melting and convective thermal transfer process, the results of the present study are reported with time for various values of the magnetic field (Ha) and solid concentration of ternary hybrid nanoparticle (ϕ). This study represents the streamlines, isothermal lines, melting interface, melting fraction, and heat transfer for the above-mentioned parameters. The results show that increasing the magnetic field reduces the rate of thermal transport by 38.96 % at t = 4000s. However, at a particular time of 2500s, increasing the solid volume fraction of nanoparticles enhances the melting fraction by approximately 8.34 %. Two regression equations are derived for the Nusselt number and melting fraction, with multiple response variables. This article improves understanding of natural convective heat transport during phase change processes for various coolants in different engineering applications.

In exploring nature's potential in addressing liver-related conditions, this study investigates the therapeutic capabilities of flavonoids. Utilizing in silico methodologies, we focus on flavone and its analogs (1–14) to assess their therapeutic potential in treating liver diseases. Molecular change calculations using density functional theory (DFT) were conducted on these compounds, accompanied by an evaluation of each analog's physiochemical and biochemical properties. The study further assesses these flavonoids' binding effectiveness and locations through molecular docking studies against six target proteins associated with human cancer. Tropoflavin and taxifolin served as reference drugs. The structurally modified flavone analogs (1–14) displayed a broad range of binding affinities, ranging from -7.0 to -9.4 kcal mol⁻¹, surpassing the reference drugs. Notably, flavonoid (7) exhibited significantly higher binding affinities with proteins Nrf2 (PDB:1 × 2 J) and DCK (PDB:1 × 2 J) (-9.4 and -8.1 kcal mol⁻¹) compared to tropoflavin (-9.3 and -8.0 kcal mol⁻¹) and taxifolin (-9.4 and -7.1 kcal mol⁻¹), respectively. Molecular dynamics (MD) simulations revealed that the docked complexes had a root mean square deviation (RMSD) value ranging from 0.05 to 0.2 nm and a root mean square fluctuation (RMSF) value between 0.35 and 1.3 nm during perturbation. The study concludes that 5,7-dihydroxyflavone (7) shows substantial promise as a potential therapeutic agent for liver-related conditions. However, further validation through in vitro and in vivo studies is necessary.Key insights from this study include: • Screening of flavanols and their derivatives to determine pharmacological and bioactive properties using ADMET, molinspiration, and pass prediction analysis. • Docking of shortlisted flavone derivatives with proteins having essential functions. • Analysis of the best protein-flavonoid docked complexes using molecular dynamics simulation to determine the flavonoid's efficiency and stability within a system.

Social media has become integral to contemporary society, with online behaviors impacting individual experiences and the wider community. In Bangladesh, a developing country, SNS have played a pivotal role in the nation's digitalization efforts. This study explores the relationship between social capital theory, D&M Information System Model, subjective well-being, and SNS Citizenship Behavior (SCB) among active social media users in Bangladesh. Data was collected from 418 participants through an online survey, and hypotheses were tested using structural equation modeling. The findings indicate that the items of the D&M model positively influenced the aspects of social capital theory, excluding service quality. In contrast, social interaction ties and shared values were positively associated with SCB, although social trust did not exhibit a significant relationship. Additionally, subjective well-being mediated the connection between social capital and SCB. This research offers valuable insights into the factors influencing online prosocial behavior and provides practical implications for cultivating a positive communication culture in the digital era. The model proposed in this study holds significant implications for Bangladesh's policymakers and social networking site authorities, guiding their efforts in implementing technology-based initiatives.

The mitogen-activated protein kinase (MAPK) signaling pathway, particularly the p38 MAPK and ERK1/2, has been implicated in the pathogenesis of Parkinson's disease (PD). Recent studies have shown that MAPK signaling pathway can influence the expression of matrix metalloproteinase 9 (MMP-9), known for its involvement in various physiological and pathological processes, including neurodegenerative diseases. This study explores the modulation of MMP-9 expression via the MAPK/ERK signaling cascade and its potential therapeutic implications in the context of PD-associated motor dysfunction. Here, tolperisone hydrochloride (TL), a muscle relaxant that blocks voltage-gated sodium and calcium channels, was used as a treatment to observe its effect on MAPK signaling and MMP-9 expression. Rotenone (RT) exposure in mice resulted in a significant reduction in substantia nigra and primary motor cortex neurons, which were further evidenced by impairments in motor function. When TL was administered, neuron count was restored (89.0 ± 4.78 vs 117.0 ± 4.46/mm2), and most of the motor dysfunction was alleviated. Mechanistically, TL reduced the protein expression of phospho-p38MAPK (1.06 fold vs 1.00 fold) and phospho-ERK1/2 (1.16 fold vs 1.02 fold), leading to the inhibition of MAPK signaling, as well as reduced MMP-9 concentrations (2.76 ± 0.10 vs 1.94 ± 0.10 ng/mL) in the process of rescuing RT-induced neuronal cell death and motor dysfunction. Computational analysis further revealed TL’s potential inhibitory properties against MMP-9 along with N and L-type calcium channels. These findings shed light on TL's neuroprotective effects via MMP-9 inhibition and MAPK signaling downregulation, offering potential therapeutic avenues for PD-associated motor dysfunction.

This study aimed to explore whether Nypa juice collection as an alternative income-generating activity (AIGA) influenced the life and livelihood of the coastal communities of Bangladesh. Following a cross-sectional survey method, this study was conducted in four unions of Kalapara and Taltoli Upazila (sub-district) of Patuakhali and Barguna districts, where data were collected using a multistage stratified random sampling from 208 participants, including both Nypa juice collectors and no-collectors by administering a semi-structured interview schedule (SSIS). Findings indicated that Nypa juice collectors were older (p = 0.032) and mostly Hindu (p

Due to the Covid-19 pandemic more than 6 million people have died, and it has bought unprecedented challenges to our lives. The recent outbreak of monkeypox virus (MPXV) has brought out new tensions among the scientific community. Currently, there is no specific treatment protocol for MPXV. Several antivirals, vaccinia immune globulin (VIG) and smallpox vaccines have been used to treat MPXV. Ginseng, one of the more famous among traditional medicines, has been used for infectious disease for thousands of years. It has shown promising antiviral effects. Ginseng could be used as a potential adaptogenic agent to help prevent infection by MPXV along with other drugs and vaccines. In this mini review, we explore the possible use of ginseng in MPXV prevention based on its antiviral activity.

In this study, several aspects of autogenous and autonomous healing concrete are discussed, including their characterization, processes, and performances. Mineral admixtures, fibers, and autonomous methods like shape memory alloys, capsules, and microbial technologies have been found effective in repairing cracks. Based on this review, autonomous approaches heal cracks better than autogenous methods also geometry and size of cracks have an important role in selecting self-healing techniques and agents. The effectiveness of biomimetic materials such as shape memory alloys, capsules, and bacteria-based self-healing concrete is also being carefully considered. Lastly, future research scope and present gaps are recognized and discussed.

A typical study has been performed for synthesizing Ag2O and ZnO nanoparticles. In our case, aloe vera extract was used as a reducing agent for synthesizing Ag2O. This green synthesis of silver oxide used silver nitrate (AgNO3) as a precursor material. On the other hand, the direct precipitation method was used for synthesizing zinc oxide nanoparticles, in which the precursor materials used were zinc nitrate hexahydrate (Zn(NO3)2·6H2O) and potassium hydroxide (KOH). Afterward, the characterization of these synthesized nanoparticles was done by the X-ray diffraction (XRD) method. Then, the crystal size, lattice strain, stress, and energy density of synthesized ZnO and Ag2O were determined by using XRD peak profile analysis. Among the various available models for determining these microstructural parameters, we explored the Scherrer model, the linear straight-line method of the Scherrer equation, the Monshi-Scherrer model, the Sahadat-Scherrer model, the Williamson-Hall model (including the uniform deformation model, the uniform stress deformation model, the uniform deformation energy density model), the size-strain plot method, the Halder-Wagner model, etc. By employing the crystal size values from these models, the accuracy and validity of crystals were also performed. The synthesized products were also characterized by the exploration of functional groups (by FTIR) and optical band gaps (by UV technique).

The presence of trace metals in aquatic ecosystems can have detrimental effects on fish survival. The Tanguar haor, a Ramsar conservation wetland, receives sediment and water from multiple transboundary rivers. However, there have been limited studies on the metal concentrations in fish species in this sediment-rich wetland. This study aimed to analyze the concentrations of iron (Fe), manganese (Mn), chromium (Cr), copper (Cu), zinc (Zn), cadmium (Cd), and lead (Pb) in water, sediment, and fish tissues. Higher concentrations of Cd and Pb were found in the water and sediment. All these metals were detected in eight fish species, including benthic and pelagic species. Among them, Systomus sarana, a pelagic fish that also consumes benthic organisms, exhibited a higher metal pollution index than other fish, particularly benthic species. The release of higher metal concentrations from sediment into the water has the potential to impact the accumulation of metals in fish. Synopsis: This study on metal concentrations in fish species will aid policymaking on ecotoxicology research for transboundary river-connected wetlands.

This work highlights the development of a conductive elastomer (CE) based electrophoretic platform that enables the transfer of charged molecules from a solid-state CE electrode directly to targeted tissues. Using an elastomer-based electrode containing poly (3,4-ethylenedioxythiophene) nanowires, controlled electrophoretic delivery of methylene blue (MB) and fluorescein (FLSC) was achieved with applied voltage. Electroactive release of positively charged MB and negatively charged FLSC achieved 33.19 ± 6.47 μg release of MB and 22.36 ± 3.05 μg release of FLSC, a 24 and 20-fold increase in comparison to inhibitory voltages over 1 h. Additionally, selective, and sequential release of the two oppositely charged molecules from a single CE device was demonstrated, showing the potential of this device to be used in multi-drug treatments.

Since the beginning of the COVID-19 pandemic, the use and manufacture of alcohol-based hand sanitizers increased exponentially. Efficacy of hand sanitizers mainly depends on active ingredients like ethanol and isopropanol (IPA). Even though methanol is extremely hazardous to people, it is still illegally used in hand sanitizers in Bangladesh. Developing a quick and simple analytical method for detecting and quantifying ethanol/IPA/methanol is crucial. Here, Fourier transform infrared spectroscopy (FTIR) was used to identify and quantify alcohol content in commercially available hand sanitizers in a quick and easy way. Comparing the FTIR and GC data, provided quite similar results. Unlike previous studies by FTIR, C–H, CH3–C–CH3 stretching, and C–H bending vibrational modes were employed to construct analytical calibration curves to detect and quantify alcohol in hand sanitizers. According to FTIR and GC findings, ethanol and IPA content were found to be 43–82% and 40–69%, and 56–64% and 61–66%, respectively, whereas ethanol was labeled at 66–80% and IPA at 65–70%. FTIR and GC revealed methanol content ranging from 37 to 98 and 19 to 81%, respectively. Also, the FTIR was significantly faster than the GC. Therefore, FTIR can be used to commercially analyze the quality of hand sanitizers. • FTIR was used to identify and quantify alcohol content in commercially available hand sanitizers in a quick and easy way. • Comparing the FTIR and GC data, provided quite similar results. • Out of ten samples, five contained ethanol, three IPA, and two methanol.

Background: Few studies have examined detailed features of pregnancy and the postpartum period as potential risk factors for early onset breast cancer (BC) by molecular subtype. These data may have value for improving risk assessment and prevention. Methods: We surveyed parous enrollees in the prospective Mayo Clinic Breast Disease Registry (MCBDR) who had been diagnosed with BC at age

Bangladesh, a coastal developing nation with a diverse sustainable biodiversity of natural resources is currently focused upon by international communities as a result of its high potential of the coastal zone (CZ) with natural gas. Sustainable Coastal Zone Management (SCZM) is key to its national development. SCZM refers to the management of coastal resources in order to provide secure and alternative livelihoods, as well as to manage all types of coastal hazards and social and cultural well-being in order to ensure long-term productivity and minimize environmental impact. This paper aims to delineate the current initiatives and status of coastal management in Bangladesh, highlighting key issues such as climate changes, sea level rise, tropical cyclones, coastal and marine pollution, coastal erosions, saltwater intrusions, and mangrove degradations as well as the future trend in Bangladesh which will facilitate sustainable development by emphasizing the social, ecological, and economic pillars of sustainability. Unsustainable coastal development practices in Bangladesh are going to damage the coastal ecosystems, particularly mangrove forests and coral reefs, which provide protection against tropical cyclones caused by global climate change and coastal erosions. The paper concludes by outlining a roadmap toward achieving SCZM in Bangladesh. The road to achieving SCZM requires collaboration, integration of scientific research, policy frameworks, community engagement, capacity building, and long-term commitment from all stakeholders involved. So, it is required to address all kinds of coastal issues and reframes all existing coastal management practices to ensure a healthy productive ecosystem to achieve SCZM as well as the sustainable development of the country.

Background: Cervical cancer (CC) is the second most common type of female malignancy in Bangladesh. Polymorphisms in the CYP1A1 gene have been reported to be associated with CC in different populations. This case-control study with meta-analysis was undertaken to assess the relation of CYP1A1 rs4646903 and rs1048943 polymorphisms with the susceptibility of CC. Methods: A total of 185 CC patients and 220 controls were recruited, and the PCR-RFLP (Polymerase chain reaction-restriction fragment length polymorphism) technique was applied for genotyping. Again, 42 eligible studies (24 with rs4646903 and 18 with rs1048943) were included for meta-analysis, and RevMan 5.3 and the MetaGenyo web-based tool were used. Results: The rs4646903 polymorphism was significantly linked with CC in all association models, namely, additive 1, additive 2, dominant, recessive, overdominant, and allele models (OR = 2.41, 4.75, 2.67, 3.61, 2.13, and 2.44 with corresponding 95% CI = 1.55–3.76, 1.81–12.45, 1.75–4.07, 1.39–9.35, 1.38–3.30, and 1.71–3.48, respectively). On the contrary, rs1048943 showed no association (p > 0.05) with CC. Haplotype analysis revealed AT and AC haplotypes significantly decreased (OR = 0.45) and increased (OR = 4.86) CC risk, respectively, and SNPs are in strong linkage disequilibrium (D’ = 0.912, r2 = 0.448). Again, rs4646903 carriers with a contraception history and >5 years of taking contraceptives showed an enhanced risk of CC (OR = 2.39, OR = 3.05). Besides, rs1048943 carriers aged >40 years (OR = 0.44), conceived first child aged ≤18 years (OR = 3.45), and history of contraceptives (OR = 2.18) were significantly linked with CC. Our meta-analysis found that for CYP1A1 rs4646903 codominant 1 (COD 1), codominant 2 (COD 2), codominant 3 (COD 3), dominant model (DM), recessive model (RM), and allele model (AM) in Caucasians and overdominant model (OD) in the overall population are associated with an elevated risk of CC, whereas rs1048943 is also associated with CC in overall, Caucasians and Asians in some genetic models. Conclusion: Our case-control study and meta-analysis summarize that CYP1A1 rs4646903 and rs1048943 polymorphisms may be correlated with cervical cancer.

Safety experts and transportation departments are focused on reducing road accidents and their societal and economic effects. The most crucial step in establishing a successful road safety practice is identifying dangerous highway zones through the study of crashes and looking at how the location of accidents relates to surrounding geography and other factors. Using the latest cutting-edge GIS analytical methods, this study aims to map the locations of accident hot spots and evaluate the severity and spatial extent of crash occurrences in Ohio. Road traffic crash (RTC) data has been analyzed using sophisticated GIS-based hot spot analysis for decades by safety researchers. Using four years' worth of crash data from the state of Ohio and spatial autocorrelation analysis, this study aims to show how a GIS technique can be used to find places where accidents are likely to happen (2017–2020). The study analyzed and ranked crash hotspot areas using the matching severity levels of RTCs. Cluster zones of high and low crash severity were discovered using the spatial autocorrelation tool and the Getis Ord Gi* statistics tool to evaluate the distribution of RTCs. The analysis used Getis Ord Gi*, the crash severity index, and Moran's I spatial autocorrelation of accident events. The findings indicated that these techniques were useful for identifying and rating crash hotspot locations. Since the sites of the identified accident hotspots are located in significant cities in the state of Ohio, such as Cleveland, Cincinnati, Toledo, and Columbus, the organizations in charge of traffic management should make it their top priority to minimize the negative socioeconomic impact that RTCs have and should also conduct a thorough investigation. This study's contribution is the incorporation of crash severity into hot spot analysis using GIS, which could lead to better-informed decision-making in the realm of highway safety.

The current Covid-19 pandemic has changed the entire world and bought so many unprecedented challenges to the scientific community. More than 5 million people died due to the SARS-COV-2 outbreak. For many thousands of years, ginseng, the traditional herb has been used for various infectious diseases by traditional healers. Ginseng showed promising antiviral effects by modulating both natural and acquired immunity. Ginseng might be used as a potential therapeutic agent to prevent SARS-CoV-2 infection along with the vaccine. In this current review, we offer an alternative approach for SARS-COV-2 prevention during this unprecedented pandemic.

This research aims to extract essential oils from the peel of two varieties of Citrus maxima- White pomelo and Red pomelo of Bangladeshi origin by hydrodistillation (HD) method and characterization of the extracted oils. The study also looked into the effect of different conditions, such as type of peels, and extraction time, on the yield amount. To determine the chemical components of oil, the Gas Chromatography-mass spectrum (GC-MS) technique has been used. The three major components were, for white pomelo, limonene (67.58%), β-linalool (7.53%) and Neral (6.61%), and for red pomelo, limonene (73.82%), β-linalool (5.42%) and Neral (4.11%). The morphological changes in the oil glands of the peels of both varieties were compared to understand changes before and after the extraction. The result showed that white pomelo (WP) provides a slightly higher yield percentage in similar extraction time than red pomelo (RP), 1.09 and 0.96%, respectively. GC-MS results showed that the presence of limonene is the highest for both pomelos, although the amount is higher in RP than that of WP. However, the digital microscopy showed the drawbacks of the hydrodistillation process. The pressure in the oil glands during the distillation is too low to rupture the oil glands fully. This study will be able to broaden the path for future studies on related physicochemical and biochemical properties of pomelo varieties of Bangladesh.

Graphene oxide (GO) and reduced graphene oxide (rGO) were synthesized from graphite powder to compare the adsorption capacity of GO and rGO towards a cationic dye-methylene blue (MB). These synthesized nanomaterials were analyzed by Fourier Transform-Infrared Spectroscopy (FTIR), Brunauer-Emmett-Teller (BET), and Field Emission Scanning Electron Microscope (FESEM). FTIR results indicated the presence of larger number of oxygenated functional groups in the GO as compared to rGO surface suggests the conversion of GO to rGO. Scattered layers of graphite sheets with chunks of pores present in the GO surface were marked by FESEM. The effect of contact time and adsorbent dosage have been studied to make an efficient comparison between the adsorption capacity of GO and rGO for removing MB. GO showed an excellent adsorption capacity by removing 98.67% of MB dye within 4 h, while rGO could remove 93.47% of MB within 7 h from the aqueous solution. The maximum adsorption capacities of GO and rGO were 3333 mg/g and 2000 mg/g, respectively. The findings reveal the contribution of electrostatic interaction, H-bonds, and π–π interactions for the sorption of MB onto GO and rGO. The abundance of oxygen-containing functional groups substantially raised the sorption capacity of GO compared to rGO by at least 60%. The higher specific surface area of GO (9.10 m2/g) compared to rGO (0.60 m2/g) was another contributing factor to higher MB sorption. The sorption process was well described by a pseudo-second-order kinetics model, suggesting that the adsorption of MB by GO and rGO was mostly controlled by chemisorption. The Langmuir isotherm model fitted best (R2 > 0.9) for both adsorbents indicating monolayer sorption on a uniform surface with a finite number of adsorption sites. These results suggest that GO can be preferred over rGO for removing cationic pollutants from wastewater.

Background: Low Birth Weight (LBW) continues to be a prominent universal cause of various short- and long-term health hazards throughout infancy and adulthood. However, no study has revealed the socioeconomic inequalities in LBW among South Asian countries. This study assesses the socioeconomic inequalities among under-five South Asian children with LBW. Methods: Secondary data were derived from six (Afghanistan, Bangladesh, India, Maldives, Nepal, and Pakistan) nationally representative South Asian Demographic and Health Surveys conducted between 2015 and 2021, and included 170,547 under-five years of age children. The study employed the concentration curve and concentration index to assess the socioeconomic inequalities of those with LBW. Additionally, mixed-effect logistic regression was applied to determine the factors associated with LBW. Results: A significant negative concentration index indicates the wealth-related and education-related inequalities of LBW among under-five South Asian children. LBW is highly concentrated in the socio-economically poor section of the society. Our study found statistically significant negative concentration index in all South Asian countries: Afghanistan (Education: -0.108), Bangladesh (wealth: -0.070 & education: -0.083), India (wealth: -0.059 & education: -0.052), Nepal (by wealth: -0.064 & by education: -0.080), and Pakistan (by wealth: -0.080 & by education: -0.095). Findings from the mixed-effects logistic regression model also show that children from the poorest quintiles (AOR: 1.53, 95% CI: 1.41–1.67) and illiterate mothers (AOR: 1.39, 95% CI: 1.29–1.51) had higher odds of being afflicted with LBW compared to the wealthiest quintiles and educated mothers respectively. Women's pregnancy assessments, such as antenatal care utilisation, iron supplementation intake, and normal delivery mode, are significantly correlated with decreased odds of children's LBW. Conclusion: There exists a strong association between LBW cases and socioeconomic inequalities among South-Asian children below five years of age. This indicates the urgent need for health education and prenatal care services for women from Afghanistan, Bangladesh, India, Nepal, and Pakistan, especially those with lower socioeconomic status.

One of the most promising aspects of lactic acid bacteria (LAB) in foodstuffs with probiotic characteristics is cholesterol-lowering action. This study aimed to examine the bile salt hydrolase (BSH) positive strains; out of 50 LAB isolates, Lactiplantibacillus plantarum Lpb01 and Lpb02 were selected. Both Lpb01 and Lpb02 were more bile-tolerant strains, surviving in 1% bile for 3 h at up to 7.27 and 7.14 log CFU/mL, respectively. Lactiplantibacillus plantarum Lpb01 and Lpb02 deconjugated considerably more sodium glycocholate, releasing 5.50 ± 0.12 mM and 5.23 ± 0.41 mM cholic acid, respectively, compared with 4.32 ± 0.17 mM cholic acid released by ATCC 8014. In addition, Lpb. plantarum Lpb01 and Lpb02 deconjugated a considerably higher quantity of sodium glycocholate than ATCC 8014. Compared to ATCC 8014, Lactiplantibacillus plantarum Lpb01 and Lpb02 demonstrated a higher level of BSH activity. The tested strains Lactiplantibacillus plantarum Lpb01 and Lpb02 resulted in a 63–68% reduction in the cholesterol level in broth media, whereas the commercial strain Lpb. plantarum ATCC 8014 showed a 51% reduction. In the case of survivability during in vitro gastrointestinal (GI) digestion, they did not lyse in the presence of lysozyme, and they survived more than 96% of the time when exposed to pepsin and low acidity (pH 3) for 1.5 h. Finally, the LAB strains were resistant to bile salts and pancreatin, with an overall viability rate of 94.0–99.4% after exposure to small intestinal conditions. This suggests that the isolates can survive severe environment in the GI tract. As a result, these strains with demonstrated in vitro capabilities are promising candidates for novel probiotic-containing formulations and could be incorporated into functional dairy foods.

Study objective: To compare the characteristics and outcomes of COVID-19 patients with a hyperdynamic LVEF (HDLVEF) to those with a normal or reduced LVEF. Design: Retrospective study. Setting: Rush University Medical Center. Participants: Of the 1682 adult patients hospitalized with COVID-19, 419 had a transthoracic echocardiogram (TTE) during admission and met study inclusion criteria. Interventions: Participants were divided into reduced (LVEF

Natural vegetation is a critical component of ecosystem change models and conservation efforts. Over nineteen years, this study explores the spatiotemporal dynamics of normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) with atmospheric, biological, and soil indicators, and to determine whether a significant correlation exists between these indices in Bangladesh. We used the Google earth engine (GEE) for geospatial analysis using moderate resolution imaging spectroradiometer (MODIS) datasets to perform the study. Vegetation indices are positively correlated with land surface temperature (LST), Humidity, and Evapotranspiration. From 2000 to 2019, the average increase in vegetation cover (NDVI) was 0.1 to 0.3. LST changes from −6°C to +5°C in numerous places over the previous 19 years (increased in urban areas and mostly decreased in the north-eastern part). Due to increased human activity, LST in the northern part of the country has dropped and increased during the last nineteen years in the center and eastern parts. In the future, new studies on vegetation cover and its relationship to other factors, protection of nature, and resource allocation may benefit from the findings of this study.

This article presents dataset on agromorphogenic traits of Aloe vera treated by foliar application of Zn (zinc) and vermicompost. Data from yield and yield related characters with morphological traits were collected to assess the effect of vermicompost and Zn. The data showed in this dataset article contained 17 agronomic and morphological traits. The collected data were analyzed using excel, statistix 10.0 and STAR software. The analyzed data presented with the help of ANOVA (analysis of variance), mean comparison, correlation co-efficient and principal component analysis (PCA). Data of microclimate, correlation co-efficient and biplot distribution of principal components were presented graphically. The aim of the article is to ensure the data easily accessible and as a brief source of agricultural management information for crop development and production for researcher.

Background: Although studies have investigated the association between alcohol use and violent behaviors such as weapon carrying, few studies have examined the association between age at first alcohol use and weapon-carrying among adolescents. The objective of this study was to investigate the association between age at first alcohol use and weapon carrying among adolescents. Methods: Data for this study came from the 2019 Youth Risk Behavior Survey. An analytic sample of 13,442 adolescents aged 14–18 years old (51% female) was analyzed using binary logistic regression. The outcome variable investigated in this study was weapon carrying during the past 30 days, and the main explanatory variable investigated was age at first alcohol use. Results: Of the 13,442 adolescents, 13.5% carried a weapon during the past 30 days, and 15.4% reported having their first alcoholic drink before age 13. In the multivariable logistic regression, adolescents who reported having alcohol before age 13 had more than double the odds of carrying a weapon when compared to those who never had alcohol before age 13 (AOR = 2.32, p < .001, 95% CI = 1.87-2.89). Other significant factors associated with weapon carrying include male gender, victim of bullying, teen dating violence, sexual violence, suicidal ideation, and history of substance use. Adolescents who self-identified as Black/African American or Hispanic were significantly less likely to carry a weapon when compared to adolescents who self-identified as non-Hispanic White. Conclusion: The findings of this study underscore the importance of developing age appropriate intervention strategies to curb early initiation of alcohol use and weapon carrying among adolescents.

Background: A high prevalence of disability has been previously observed in developed countries. Identifying trends in its prevalence and risk, as well as protective factors of disability, are essential to establish effective prevention strategies. Objective: The purposes of this study are to outline trends in the prevalence of disability among Australian adults and to analyse the relationship between obesity, and physical activity with disability. Design: A retrospective longitudinal research design. Methods: The study utilized the most recent 14 waves (wave 6 through 19) of the nationally-representative Household, Income and Labour Dynamics in Australia (HILDA) survey (2006–2019). The Generalized Estimating Equation (GEE) with the logistic link function model was employed to estimate the relationships between obesity and physical activity with disability. The final study sample consisted of 189,519 person-year observations from 26,208 participants. Results: The pooled prevalence of disability in adults is 28%. The prevalence of disability among older adults (65 and above years) is more than 50%, irrespective of gender. Further, it identifies obesity and physical activity as risk and protective factors of disability for adults, respectively. The odds of acquisition of a disability was 1.33 times (Odds Ratios [OR]: 1.33, 95% Confidence Interval [CI]: 1.28–1.39) higher among obese adults than healthy weight counterparts. However, adults undertaking recommended level of physical activity (more than thrice a week to everyday) per week have 17% (OR: 0.83, 95% CI: 0.81–0.85) lower chances of disability acquisition. Conclusions: Obesity imposes a significant toll on adult Australians' health. This risk factor of disability can be reduced through public health interventions.

The outbreak of new coronavirus disease (COVID-19) has triggered a global panic, affecting the mental well-being of people of all ages, including students. The aim of this study was to explore the relationship between self-reported mental health concerns and subjective sleep quality of the Bangladeshi university students during the COVID-19 pandemic. A web-based cross-sectional study was conducted to maintain the social distancing recommended by the World Health Organization. There were 1,317 student responses from 49 universities across Bangladesh. Data was analyzed by executing both bi-variate and multivariate analysis. Findings indicate that 27.1%, 51.0%, 45.9%, and 86.0% of students had poor subjective sleep quality, anxiety, depression, and fear of COVID-19, respectively. Anxiety (AOR = 1.09, 95% CI: 1.06–1.12, p < 0.001) was a risk factor for increasing the poor subjective sleep quality of university students. In contrast, the odds of poor subjective sleep quality were lower with increasing the score of depression (AOR = 0.88, 95% CI: 0.86–0.90, p < 0.001) and fear of COVID-19 (AOR = 0.97, 95% CI: 0.94–0.99, p < 0.05). Compared to public university students, private university students were more likely to report poor subjective sleep quality since the pandemic began. Therefore, it is strongly recommended that psychiatric conditions of university students should be monitored during the COVID-19 epidemic, and necessary strategies, such as allocation of resources, implementation of awareness programs, establishment of psychological counselling unit, should carefully be devised.

Background: In the coronavirus disease 2019 (COVID-19) global pandemic, patients with cardiovascular disease represent a vulnerable population with higher risk for contracting COVID-19 and worse prognosis with higher case fatality rates. However, the relationship between COVID-19 and heart failure (HF) is unclear, specifically whether HF is an independent risk factor for severe infection or if other accompanying comorbidities are responsible for the increased risk. Methods: This is a retrospective analysis of 1331 adult patients diagnosed with COVID-19 infection between March and June 2020 admitted at Rush University System for Health (RUSH) in metropolitan Chicago, Illinois, USA. Patients with history of HF were identified by International Classification of Disease, Tenth Revision (ICD-10) code assignments extracted from the electronic medical record. Propensity score matching was utilized to control for the numerous confounders, and univariable logistic regression was performed to assess the relationship between HF and 60-day morbidity and mortality outcomes. Results: The propensity score matched cohort consisted of 188 patients in both the HF and no HF groups. HF patients did not have lower 60-day mortality (OR 0.81; p = 0.43) compared to patients without HF. However, those with HF were more likely to require readmission within 60 days (OR 2.88; p

The erratic nature of the novel coronavirus disease (COVID-19) forced the Bangladeshi government to shut down all the educational institutions since March 18, 2020. This prolonged closure not only detached the students from their study but also increased anxiety among them regarding their future academic as well as professional careers. The present study aimed to explore the perception and understanding of the students and teachers regarding the impact of COVID-19 on the academic life and career pursuit of university students in Bangladesh. With a semi-structured interview schedule, data for this qualitative study were collected from 8 purposively selected participants, using telephone interviews, affiliated with a public university in Bangladesh. Students argued that the extended closure is responsible for the delayed graduation of the senior students, thereby, mounting mental stress and frustration among them. The informants unequivocally opposed the online education platform, as a solution for the ongoing gap, due to scarcity of the resources, and unequal accesses and opportunities for all. It has been suggested that the education gap can be reduced by shortening the term, curtailing the preparatory leave, and taking extra classes over the weekends when the universities re-open together with enforced collective health hygiene.

The coronavirus family has been infecting the human population for the past two decades, but the ongoing coronavirus called SARS-CoV-2 has posed an enigmatic challenge to global public health security. Since last year, the mutagenic quality of this virus is causing changes to its genetic material. To prevent those situations, the FDA approved some emergency vaccines but there is no assurance that these will function properly in the complex human body system. In point of view, a short but efficient effort has made in this study to develop an immune epitope-based therapy for the rapid exploitation of SARS-CoV-2 by applying in silico structural biology and advancing immune information strategies. The antigenic epitopes were screened from the Surface, Membrane, Envelope proteins of SARS-CoV-2 and passed through several immunological filters to determine the best possible one. According to this, 7CD4+, 10CD8+ and 5 B-cell epitopes were found to be prominent, antigenic, immunogenic, and most importantly, highly conserved among 128 Bangladeshi and 110 other infected countries SARS-CoV-2 variants. After that, the selected epitopes and adjuvant were linked to finalize the multi-epitope vaccine by appropriate linkers. The immune simulation disclosed that the engineered vaccine could activate both humoral and innate immune responses. For the prediction of an effective binding, molecular docking was carried out between the vaccine and immunological receptors (TLRs). Strong binding affinity and good docking scores clarified the stringency of the vaccines. Furthermore, MD simulation was performed within the highest binding affinity complex to observe the stability. Codon optimization and other physicochemical properties revealed that the vaccine would be suitable for a higher expression at cloning level. So, monitoring the overall in silico assessment, we anticipated that our engineered vaccine would be a plausible prevention against COVID-19.

Mixed hepatocellular carcinoma-neuroendocrine carcinomas (HCC-NECs)11 HCC-NECs: hepatocellular carcinoma-neuroendocrine carcinomas. are rare, and they usually carry a poor prognosis. We report a fascinating case of mixed HCC-NEC — the neuroendocrine component of the tumor was diagnosed retrospectively after discovery of the metastatic neuroendocrine carcinoma (NEC).22 NEC: neuroendocrine carcinoma. A 50-year-old man with cirrhosis underwent resection of a 2.7 cm hepatocellular carcinoma (HCC)33 HCC: hepatocellular carcinoma. at the segment II of the liver. Thirteen months after the surgery he had local recurrence in the liver that was treated with radio-embolization. Eighteen months after the initial diagnosis, he was found to have metastatic NEC in the left shoulder. Later, re-evaluation of the previously resected liver tumor revealed a small focus of tumor cells with neuroendocrine morphology within the tumor, which were negative for HepPar1 and positive for synaptophysin, whereas the majority of the tumor cells were positive for HepPar1 and negative for synaptophysin that reclassified the liver tumor as a combined type of mixed HCC-NEC tumor. Upon discovery of the metastatic NEC, the patient was treated with eight cycles of cisplatin and etoposide with a partial response. Nonetheless, his disease progressed two months after finishing chemotherapy, and he was treated with nivolumab for two cycles. In addition, he received palliative radiation to different skeletal metastases. The patient died of sepsis thirty-three months after the initial diagnosis of liver tumor. In conclusion, mixed HCC-NECs are rare and aggressive— an accurate diagnosis may require a high degree of clinical suspicion and re-evaluation of the pathological specimen, especially when one of the components is scarce. Strategic use of multiple modalities of treatment may prolong the life of patients with this type of aggressive tumor.

The global prevalence of hyperlipidaemia is increasing rapidly and high dietary fat intake is a major risk factor for developing hyperlipidaemia. An in-vivo biological investigation was carried out on ethanolic extract of Momordica charantia, a plant belonging to the family Cucurbitaceae for the evaluation of antihyperlipidemic activity and serum uric acid reducing potential. In our study, 25 healthy male mice were selected randomly and grouped into 5 groups (5 animals in each group). Lipid and uric acid profile were estimated after 21 days of treatment by using the enzymatic colourimetric GPO-PAP method. Results showed that ethanolic extract of M. charantia at a dose of 200 mg/kg body weight showed significant (p < 0.05) cholesterol and triglyceride level reduction profile when co-administrated with 20% fat and normal feed respectively. Atorvastatin was used as standard. Data from pathological examination showed that the average weight of the heart of the mice was normal for every group when compared with control. Gr-2 (normal and extract feed) showed significant (p ˂ 0.05) increased of liver and kidney weight rather than experimental groups; however, these values were lower than the values for the control group. Uric acid level determination revealed that the ethanolic extract of M. charantia reduced serum uric acid level both in experimental groups (Gr-2 and Gr-3). Thus a considerable correlation was found between serum uric acid reducing potentials of the present plant extract with a lipid-lowering profile. This plant can be further investigated thoroughly as a potential source of chemically interesting and biologically important drug candidates.

The article identifies the relationship among different agile software development approaches such as response extensiveness, response efficiency, team autonomy, team diversity, and software functionality that software teams face difficult challenges in associating and achieving the right balance between the two agility dimensions. This research strategy, in terms of quantity, is descriptive and correlational. Statistical analysis of the data was carried out, using SmartPLS 3.0. Statistical population, consist of employees of software industries in Bangladesh, who were engaged in 2017 and their total number is about 100 people. The data show that the response extensiveness, response efficiency, team autonomy, team diversity, and software functionality have impact on software development agility and software development performance.

Permeability is the most important petrophysical characteristic for determining how fluids pass through reservoir rocks. This study aims to develop and assess intelligent computer-based models for predicting permeability. The research focuses on three novel models—Decision Tree, Bagging Tree, and Extra Trees—while also investigating previously applied techniques such as random forest, support vector regressor (SVR), and multiple variable regression (MVR). The primary dataset consists of 197 data points from a heterogeneous petroleum reservoir in the Jeanne d'Arc Basin, including laboratory-derived permeability (K), oil saturation (SO), water saturation (SW), grain density (ρgr), porosity (φ), and depth. The most effective machine learning models are identified by a thorough analysis that makes use of a variety of statistical metrics, such as the coefficient of the determinant (R2), mean squared error (MSE), mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), maximum error (maxE), and minimum error (minE). Additionally, core features are ranked based on their importance in permeability modeling. This study deviates from conventional approaches by proposing an efficient means of forecasting permeability, reducing reliance on labor-intensive and time-consuming laboratory work. The findings reveal that MVR is unsuitable for permeability prediction, with all developed models outperforming it. Extra Trees emerges as the most accurate model, with an R2 of 0.976, while random forest and bagging tree exhibit slightly lower R2 values of 0.961 and 0.964, respectively. The ranking of these algorithms based on performance criteria is as follows: extra trees, bagging tree, random forest, SVR, decision tree, and MVR. The study also presents a detailed analysis of the impact of input parameters, highlighting porosity (φ) and water saturation (SW) as the most influential, while grain density (ρgr), oil saturation (SO), and depth are considered less important. This study contributes to the petroleum industry's knowledge by showcasing the inadequacy of MVR and highlighting the superior performance of machine learning models, particularly Extra Trees. The proposed models employed in this study can help engineers and researchers determine reservoir permeability quickly and accurately by using a few core attributes, reducing the dependency on resource-intensive and time-consuming laboratory work.

The calorific value of any fuel is one of the crucial parameters to grade fuel's burning capability. The bomb calorimeter has historically been used to calculate coal's gross calorific value (GCV). However, for many years, engineers and scientists were trying to measure coal's GCV without a bomb calorimeter, using only laboratory-derived ultimate and/or proximate analyses to eliminate tedious and time-consuming laboratory analyses. In this study, Extra trees, Bagging, Decision tree, and Adaptive boosting are developed for the first time in coal's GCV modeling. In addition, the prediction and computational efficiency of previously applied decision tree-based algorithms, such as Random forest, Gradient boosting, and XGBoost are investigated. Well-established empirical models, namely Schuster, Mazumdar, Channiwala and Parikh, Parikh et al. and Central Fuel Research Institute of India are examined to compare their efficiency with newly developed algorithms. Proximate and ultimate analysis parameters are ranked based on their significance in GCV modeling. The studied models are tuned using an exhaustive grid search technique. Statistical indexes, such as explained variance (EV), mean absolute error (MAE), coefficient of determinant (R2), mean squared error (MSE), maximum error, minimum error, and mean absolute percentage error (MAPE) are used to critique these models. To accomplish the goals, 7430 data points containing ten coal features, such as ash, moisture, fixed carbon, volatile matter, hydrogen, carbon, sulfur, nitrogen, oxygen, and GCV are selected from the U.S. Geological Survey Coal Quality (COALQUAL) database. It has been found that, due to simplicity and location-specific constraints, empirical models could not correlate proximate and/or ultimate analyses with GCV. Bagging and boosting techniques tested here performed well with the coefficient of determinant (R2) of over 0.97. The XGBoost model outperforms other tree-based algorithms with the most significant coefficient of determinant (R2 of 0.9974) and lowest error values (MSE of 14703.3, max_error of 1027.2, MAE of 89.2, MAPE of 0.009). The studied models' ranking (highest to lowest) based on their performance are XGBoost, Extra trees, Random forest, Bagging, Gradient boosting, Decision tree, and Adaptive boosting. The correlation heatmap and scatterplots used here clearly indicate that oxygen and carbon are the utmost significant, whereas volatile matter and sulfur are the least essential rank parameters for GCV modeling. The strategy suggested in this research can aid engineers/operators in obtaining a rapid and accurate determination of the GCV with a few coal features, thus lessening complicated, tedious, expensive, and time-consuming laboratory efforts.