A Critical Investigation of Sick Euthyroid Syndrome in Chronic Heart Failure Patients: Addressing the Need for Accurate Thyroid Assessment.

Background The body undergoes numerous metabolic changes during severe illness or physiological stress to protect itself by lowering metabolism and reducing overall demands. This evolutionary adaptation dates back to early human development, long before the advent of ICU facilities and advanced treatments. One such protective mechanism is Sick Euthyroid Syndrome (SES), also known as Non-thyroidal Illness Syndrome (NTIS). SES commonly occurs in critically ill patients and is frequently observed in conditions such as heart failure, chronic kidney disease, and severe sepsis. This syndrome is characterized by abnormal thyroid function tests in patients with acute or chronic systemic illnesses who do not have intrinsic thyroid disease. Typically, these patients exhibit low serum levels of triiodothyronine (T3), normal or low levels of thyroxine (T4), and normal or low thyroid-stimulating hormone (TSH) levels. SES is believed to be an adaptive response to illness, aimed at reducing the body's metabolic rate and conserving energy during severe physiological stress. This original article delves into SES's prevalence and clinical impact in these settings. Materials and methods The study aims to determine the prevalence of SES in patients with long-standing heart failure, elucidate the relationship between thyroid function and heart failure severity, and assess its impact on various hematological and clinical parameters. This observational, cross-sectional study was conducted at Dr. D. Y. Patil Medical College, Hospital and Research Centre, Pune, India, a 2011-bed hospital, over one and a half years. This study included 70 patients with chronic heart failure, aged 18 years and above, defined by a left ventricular ejection fraction of 40% or less and a Boston criteria score of 8 or more. Patients were excluded if they had a history of thyroid dysfunction, clinical sepsis, or were taking thyroid-affecting drugs.  Results The study provides important insights into the prevalence and impact of SES in long-standing heart failure patients. It found that a significant 44.29% of these patients exhibited low T3 levels, highlighting the substantial occurrence of SES in this population. Additionally, the study revealed a negative correlation between N-terminal pro-b-type natriuretic peptide (NT-proBNP) levels, Boston score, and total T3, suggesting that as indicators of heart failure severity worsen, total T3 levels may decrease further. Another key finding is the high prevalence of anemia among heart failure patients, with a notable gender disparity: 92.11% of male patients were affected compared to 50% of female patients.  Conclusion The study concluded that SES is significantly prevalent among long-standing heart failure patients, further indicating that thyroid suppression increases with the severity of heart failure. Recognizing SES can guide tailored treatments, prompting intensive monitoring and optimized heart failure management. Additionally, the study found a high prevalence of anemia, particularly among male patients, highlighting the need for gender-specific considerations in managing heart failure. These findings underscore the importance of routine thyroid function assessments and regular monitoring of anemia in heart failure patients. Future research should focus on improving clinical outcomes through comprehensive management of both thyroid function and anemia in these patients.

Assessment of poly(diallyl dimethyl ammonium chloride) and lime for surface water treatment (pond, river, and canal water): seasonal variations and correlation analyses.

The present study deals with the assessment of different physicochemical parameters (pH, electrical conductivity (E.C.), turbidity, total dissolved solids (TDS), and dissolved oxygen) in different surface water such as pond, river, and canal water in four different seasons, viz. March, June, September, and December 2023. The research endeavors to assess the impact of a cationic polyelectrolyte, specifically poly(diallyl dimethyl ammonium chloride) (PDADMAC), utilized as a coagulation aid in conjunction with lime for water treatment. Employing a conventional jar test apparatus, turbidity removal from diverse water samples is examined. Furthermore, the samples undergo characterization utilizing X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The study also conducts correlation analyses on various parameters such as electrical conductivity (EC), pH, total dissolved solids (TDS), turbidity of raw water, polyelectrolyte dosage, and percentage of turbidity removal across different water sources. Utilizing the Statistical Package for Social Science (SPSS) software, these analyses aim to establish robust relationships among initial turbidity, temperature, percentage of turbidity removal, dosage of coagulant aid, electrical conductivity, and total dissolved solids (TDS) in pond water, river water, and canal water. A strong positive correlation could be found between the percentage of turbidity removal and the value of initial turbidity of all surface water. However, a negative correlation could be observed between the polyelectrolyte dosage and raw water's turbidity. By elucidating these correlations, the study contributes to a deeper understanding of the effectiveness of PDADMAC and lime in water treatment processes across diverse environmental conditions. This research enhances our comprehension of surface water treatment methodologies and provides valuable insights for optimizing water treatment strategies to address the challenges posed by varying water sources and seasonal fluctuations.

A Cross-Sectional Study to Evaluate Work-Life Balance Among Indian Medical Students.

Introduction The concept of work-life balance is a complex, multidimensional intertwinement of the roles an individual plays in their professional and personal life. Work-life balance is crucial for every profession, and doctors have no exemption not exempted from it. Medical students and young graduates face numerous challenges that potentially impact their work (study)-life balance. Objectives of the study The aim is to assess the hours spent in study and the hours spent in non-study activities by medical students and graduates in India and to assess the study-life balance among them. Methodology A cross-sectional observational study employing a predefined web-based survey to investigate the study-life balance among medical students and graduates across India. A predesigned questionnaire was designed and made accessible through Google Forms, which was distributed among doctors across India via popular social media platforms. Data management was conducted using Microsoft Excel and Data analysis was done using SPSS (IBM Corp., Armonk, NY). Results A total of 416 responses were included in the study. The study participants were predominantly female (64.2%). Most of the study participants were from the State of Telangana (63.9%). The time spent studying was < 10 hours/week for 43.8% students and 10-25 hours/week for 27.2% students. Around 24% students reported spending 10-25 hours/week in hospital. While 47.4% reported spending less than one to two hours per day with their family, 26% of the participants answered "yes" to the question "Do you feel that your study-life is stressful?." Conclusions Self-care and study-life balance is a multi-factorial focal area that is based on balancing stress and happiness, with completing the tasks of the medical school. Medical students need to receive proper guidelines to transition into medical school for better study-life balance.

On topological indices and entropy measures of beryllonitrene network via logarithmic regression model.

Chemical graph theory, a subfield of graph theory, is used to investigate chemical substances and their characteristics. Chemical graph analysis sheds light on the connection, symmetry, and reactivity of molecules. It supports chemical property prediction, research of molecular reactions, drug development, and understanding of molecular networks. A crucial part of computational chemistry is chemical graph theory, which helps researchers analyze and manipulate chemical structures using graph algorithms and mathematical models. Beryllonitrene , a compound of interest due to its potential applications in various fields, is examined through the lens of graph theory and mathematical modeling. The study involves the calculation and interpretation of topological indices and graph entropy measures, which provide valuable insights into the structural and energetic properties of Beryllonitrene's molecular graph. Logarithmic regression models are employed to establish correlations between these indices, entropy, and other relevant molecular attributes. The results contribute to a deeper understanding of Beryllonitrene's complex characteristics, facilitating its potential applications in diverse scientific and technological domains. In this study, degree-based topological indices TI are determined, as well as the entropy of graphs based on these TI .

Coastal groundwater quality prediction using objective-weighted WQI and machine learning approach.

The water quality index (WQI) is a globally accepted guideline to indicate the water quality standard of any groundwater resource. Water levels in existing groundwater sources are declining in several coastal zones. Therefore, for monitoring water quality and improving water management, the prediction and identification of groundwater status by an effective technique with higher accuracy is urgently needed. Therefore, this research aims to find an effective model for WQI prediction by comparing entropy and critic weight-based WQI (ENW-WQI and CRITIC-WQI) with multi-layer perceptron artificial neural network (MLP-ANN) technique and also to identify contaminated zones using GIS. Initially, 1000 water sampling datasets with concentrations of several water quality parameters of different coastal blocks of eastern India during 2018 to 2022 are considered for the estimation of ENW-WQI and CRITIC-WQI. It shows 65% and 67% of the samples are excellent to good for drinking. ENW-WQI and CRITIC-WQI-based MLP-ANN models have been established considering different data portioning and hidden neuron numbers. Input variables and appropriate dataset partitioning with hidden neurons for models obtained from correlation and trial-error analysis. Spatial distribution maps are also produced for calculated WQIs using inverse distance weighted interpolation approaches. Three fitting models are obtained: ENW-WQI-MLP-ANN, CRITIC-WQI-MLP-ANN-I and CRITIC-WQI-MLP-ANN-II. CRITIC-WQI-MLP-ANN-II model (data ratio 85:15, network structure 6-12-1, R2 = 0.986, NSE = 0.98, and error rate 0.49%) provides the best accuracy in WQI prediction. The GIS-based WQI maps record several areas related to drinking water quality. The results of this research can help in planning the provision of safe drinking water in the future.

Exploring how IP marketing (media marketing) influences consumer shopping psychology through quantitative and empirical analysis.

As the concepts of intellectual property and media marketing have gained popularity, media marketing has gradually become an integral part of intellectual property marketing, and its use has become more widespread. However, the field of intellectual property marketing (media marketing) has become confused and faces challenges such as loss of uniqueness and weak consumer connections. Existing research efforts have focused on marketing strategies for branded intellectual property, but have neglected the important perspective of consumer psychology and behaviour. In this study, we use the AISAS model to segment digital marketing and delve into consumer psychology and behavioural factors that influence intellectual property marketing (media marketing). This exploration covers intellectual property content at the attention stage, intellectual property value at the interest stage, emotional trust at the search stage, mental consumption at the purchase stage and fan interaction at the sharing stage. We conducted a comprehensive analysis of the data using SPSS and AMOS, and integrated a consumer attitude questionnaire. The final findings confirm that intellectual property content, value, emotional trust, spiritual consumption and fan interaction all positively influence consumer psychology and behaviour. In addition, we make consumer-centric recommendations to extend the life cycle of intellectual property and promote sustainable brand development.

Evaluation of groundwater quality by adopting a multivariate statistical approach and indexing of water quality in Sagar Island, West Bengal, India.

In the vicinity of the coast, predominantly groundwater is the sole reliable resource for potable purposes as the surface water sources are highly saline and unfit for human consumption. However, the groundwater in Sagar Island is highly vulnerable to saltwater intrusion. The majority of drinking water comes from government-owned hand pump-equipped tube wells. But during the summer season, many of these tube wells yield significantly less water. Hence, in the current scenario, water quality assessment has become important to the quantity available. Total of 31 samples of deep tube wells (groundwater) are collected at variegated locations during pre-monsoon season throughout Sagar, and then, the physical and chemical quality parameters of these water samples are analysed. Furthermore, a multivariate statistical technique is executed with the aid of the SPSS program. The hydro-chemical parameters that are taken into account for the quality analysis are pH, salinity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, aluminium, arsenic, bi-carbonate, cadmium, iron, chloride, copper, chromium, cobalt, lead, magnesium, manganese, nickel, potassium, sulphate, zinc, and sodium. Then, the analysed data evaluates the water quality index (WQI). Five components are identified through the principal component analysis (PCA) technique, and 82.642% total variance is found. The outcomes of the quality assessment study illustrate that about 54.84% of collected samples come in the "excellent" water quality class when calculated by the "weighted arithmetic WQI method," and 90.32% of collected groundwater samples come in the "good" water quality class when computed using the "modified weighted arithmetic WQI method." This study helps for the interpretation of WQI to assess groundwater quality.

Factors Affecting Adherence to Hemodialysis Therapy Among Patients With End-Stage Renal Disease Attending In-Center Hemodialysis in Al-Ahsa Region, Saudi Arabia.

Background Chronic kidney disease (CKD) and end-stage renal disease (ESRD) are global health concerns, with ESRD requiring renal replacement therapy (RRT). Hemodialysis is a prevalent modality for RRT. However, access to hemodialysis is challenging for rural patients due to geographical barriers and limited nephrology services. This research aims to identify factors influencing adherence to hemodialysis sessions among rural ESRD patients, addressing travel, healthcare infrastructure, and socioeconomic factors. Materials and methods A cross-sectional study of 154 participants was conducted from July 06 to September 10, 2023 at Al-Jaber Dialysis Center in Al-Ahsa, Saudi Arabia. It included adult CKD patients on hemodialysis who were interviewed to assess factors influencing hemodialysis adherence using a structured questionnaire. Results Our study assessed hemodialysis adherence in 154 patients in Al-Ahsa, Saudi Arabia. Gender distribution was nearly equal (male = 54.5%), with the majority aged 41-60, married, and residing in downtown areas. Hypertension (43.9%) and diabetes (32.3%) were the prevalent comorbidities. Most patients received thrice-weekly dialysis (96.15%), with family cars as the primary transportation mode (55.2%). Hypertension (43.3%) and diabetic nephropathy (40.9%) were the leading causes of CKD. Approximately 26% missed dialysis, with health issues and transportation difficulties being common reasons. Notably, adherence correlated with female gender, lower education, and family car transportation mode. Social support significantly influenced adherence, highlighting its importance in maintaining hemodialysis adherence. Conclusion Our study identified various sociodemographic and dialysis-related factors influencing adherence among hemodialysis patients in the Al-Ahsa region, Saudi Arabia. Notably, factors such as gender, education level, and transportation means significantly influenced adherence. Adequate family and social support were associated with better adherence. These findings highlight the importance of tailored interventions addressing these factors to enhance hemodialysis adherence and ultimately improve patient outcomes in this population.

Dietary fat types consumption association with obesity and coronary indices.

This article aims to study the different dietary fat types associated with obesity and coronary indices. A sample of 491 healthy adults was included in a cross-sectional manner. Dietary fats intake, obesity indices (conicity index (CI), body adiposity index (BAI), abdominal volume index (AVI), body roundness index (BRI), and weight-adjusted-waist index (WWI)), and cardiovascular indices (cardiometabolic index (CMI), lipid accumulation product (LAP), and atherogenic index of plasma (AIP)) were calculated and studied. Participants with an acceptable intake of omega-3 had a higher BRI score (1⋅90 ± 0⋅06 v. 1⋅70 ± 0⋅06). Participants with an unacceptable intake of cholesterol had a higher CI (1⋅31 ± 0⋅11 v. 1⋅28 ± 0⋅12; P = 0⋅011), AVI (20⋅24 ± 5⋅8 v. 18⋅33 ± 6⋅0; P < 0⋅001), BRI (2⋅00 ± 1⋅01 v. 1⋅70 ± 1⋅00; P = 0⋅003), WWI (11⋅00 ± 0⋅91 v. 10⋅80 ± 0⋅97; P = 0⋅032), and lower AIP (0⋅46 ± 0⋅33 v. 0⋅53 ± 0⋅33; P = 0⋅024). Total fat, saturated fat (SFA), and polyunsaturated fat (PUFA) intake had a significant moderate correlation with AVI and BRI. The monounsaturated fat (MUFA) intake had a significantly weak correlation with CI, AVI, BRI, WWI, and AIP. Cholesterol and omega-6 had weak correlations with all indices. Similar correlations were seen among male and female participants. The different types of fat intake significantly affected obesity and coronary indices, especially SFA and PUFA, as well as omega-3 and cholesterol. Gender and the dietary type of fat intake have a relationship to influence the indicators of both obesity and coronary indices.

Lead Exposure Survey Tool (LEST): A methodological approach to highlight the invisible lead poisoning.

Lead is the most common heavy metal found in the Earth's crust. Lead has been widely dispersed and incorporated in the natural world since prehistoric times. In the majority of wealthy countries, the amount of lead entering the atmosphere has been significantly reduced. Acute lead exposure becomes relatively low, but chronic lead exposure remains a substantial public health hazard. Disadvantaged people, are developing and industrializing countries in the Middle East and North Africa (MENA). Between 1981 and 2018, a comprehensive literature search was undertaken in the PubMed and Scopus databases. All studies were evaluated equally based on predetermined inclusion and exclusion criteria. The Delphi method was used to identify numerous resources of lead pollutants. The Mixed Method Appraisal Tool (MMAT) was used to evaluate the quality of identified papers for inclusion in the systematic review synthesis. The studies and sources of lead toxicology were further evaluated using a scale of evidence to establish the degree of evidence based on SIGN & GRADE standards. There were 14 genres and 82 subgenres identified. Through a comprehensive analysis, our cohort developed an exposure survey tool that takes into account the local sociocultural aspects of MENA countries, which will serve as a resource forresearchers, medical toxicologists, and public health professionals in the MENA region to enhance early detection of potential subjects, conduct further studies and implement exposure prevention strategies.•There is no single tool available to detect the invisible lead poison. Lead poisoning is a serious public health problem that can have devastating consequences.•The tool, called the Lead Exposure Survey Tool (LEST), uses a combination of but not limited to data sources, including blood lead levels, environmental lead levels, and demographic information, to identify subjects who are at risk of lead poisoning. LEST is a powerful tool that can help to improve early detection and prevention of lead poisoning.•The development of LEST is a major breakthrough in the fight against lead poisoning. This tool has the potential to save lives and improve the health of high risk subjects around the world.

Different origins and processing methods affect the intrinsic quality of ginger: a novel approach to evaluating ginger quality.

Introduction: Ginger (Zingiber officinale Roce.) is a widely consumed food item and a prominent traditional Chinese medicinal herb. The intrinsic quality of ginger may differ due to variations in its origin and processing techniques. To evaluate the quality of ginger, a straightforward and efficient discriminatory approach has been devised, utilizing 6-gingerol, 8-gingerol, and 10-gingerol as benchmarks. Methods: In order to categorize ginger samples according to their cultivated origins with different longitude and latitude (Shandong, Anhui, and Yunnan provinces in China) and processing methods (liquid nitrogen pulverization, ultra-micro grinding, and mortar grinding), similarity analysis (SA), hierarchical cluster analysis (HCA), and principal component analysis (PCA) were employed. Furthermore, there was a quantitative determination of the significant marker compounds gingerols, which has considerable impact on maintaining quality control and distinguishing ginger products accurately. Moreover, discrimination analysis (DA) was utilized to further distinguish and classify samples with unknown membership degrees based on the eigenvalues, with the aim of achieving optimal discrimination between groups. Results: The findings obtained from the high-performance liquid chromatography (HPLC) data revealed that the levels of various gingerols present in all samples exhibited significant variations. The study confirmed that the quality of ginger was primarily influenced by its origin and processing method, with the former being the dominant factor. Notably, the sample obtained from Anhui province and subjected to liquid nitrogen pulverization demonstrated the highest content of gingerols. Conclusion: The results obtained from the analysis of SA, HCA, PCA, and DA were consistent and could be employed to evaluate the quality of ginger. As such, the combination of HPLC fingerprints and chemo metric techniques provided a dependable approach for comprehensively assessing the quality and processing of ginger.

Clinical role of CYP1B1 gene polymorphism in prediction of postoperative chemotherapy efficacy in NSCLC based on individualized health model.

Non-small cell lung cancer (NSCLC) is one of the most common cancers worldwide, and chemotherapy is one of its main treatment methods. However, there are significant differences in patients' reactions to chemotherapy, leading to unsatisfactory treatment outcomes. Therefore, identifying relevant factors that affect the efficacy of chemotherapy can help doctors better develop personalized treatment plans, improve the treatment effectiveness, and quality of life of patients. This article aims to understand the specific clinical role of CYP1B1 gene in NSCLC. Therefore, based on the individualized health model of CYP1B1 gene polymorphism, this article analyzes the prediction of postoperative chemotherapy efficacy for NSCLC. Through a study on the control variables of postoperative recovery of stage III NSCLC in a hospital, according to the findings of this study, 14 of the 32 patients in the EGFR mutation-positive group relapsed. In the EGFR-negative group, 13 of the 36 patients relapsed. It can be considered that CYP1B1 gene polymorphism has a good curative effect in postoperative chemotherapy of NSCLC, and it can effectively control the recurrence rate of cancer.

MLR index-based principal component analysis to investigate and monitor probable sources of groundwater pollution and quality in coastal areas: a case study in East India.

Identifying groundwater contamination sources and supervising groundwater quality conditions are urgently needed to protect the groundwater resources of coastal areas like Contai of India, as communities here are heavily relying on groundwater which deteriorates progressively. So current research aims to address in detail about origins and influencing factors of groundwater contamination, status, and monitoring water quality by employing extremely useful leading technologies like principal component and factor analyses (PCA/FA), groundwater quality index (GWQI), and multiple linear regression (MLR) that helps to simplify complicated works instead of the conventional methods. Eight groundwater quality parameters were evaluated here, such as pH, TH (total hardness), Tur (turbidity), EC (electrical conductivity), TDS (total dissolved solids), Mn (manganese), Fe (iron), and Cl (chloride) for 38 sites. Three principal components with ~ 81% of the total variance were extracted from the PCA/FA analysis. The origin of maximum loadings of each factor is identified as a result of saline water, disintegration and leaching process, organic or else biogenic activities, and lithogenic or otherwise non-lithogenic links through percolating water. GWQI results show that ~ 87% of the samples fall into the good category and ~ 13% of the samples fall into the poor to very poor category. A model consisting of Tur, Fe, EC, Mn, TH, and Cl as independent parameters is more feasible and is proposed to predict GWQI obtained from MLR analysis. This MLR model also suggests that turbidity with the highest beta coefficient (0.820) is a key contributor relative to the entire groundwater class in this affected area. The findings relating to this research may support the designer and officials in monitoring and protecting coastal groundwater resources like selected areas.

Integrating computational skills in undergraduate Microbiology curricula in developing countries.

The employability of young graduates has gained increasing significance in the labour market of the 21st century. Universities turn out millions of graduates annually, but at the same time, employers highlight their lack of the requisite skills for sustainable employment. We live today in a world of data, and therefore courses that feature numerical and computational tools to gather and analyse data are to be sourced for and integrated into life sciences' curricula as they provide a number of benefits for both the students and faculty members that are engaged in teaching the courses. The lack of this teaching in undergraduate Microbiology curricula is devastating and leaves a knowledge gap in the graduates that are turned out. This results in an inability of the emerging graduates to compete favourably with their counterparts from other parts of the world. There is a necessity on the part of life science educators to adapt their teaching strategies to best support students' curricula that prepare them for careers in science. Bioinformatics, Statistics and Programming are key computational skills to embrace by life scientists and the need for training beginning at undergraduate level cannot be overemphasized. This article reviews the need to integrate computational skills in undergraduate Microbiology curricula in developing countries with emphasis on Nigeria.

Minimum acceptable diet and its associated factors among children aged 6-23 months in Lalibela, northeast Ethiopia: a community-based cross-sectional study.

The first 2 years of life are a critical window of opportunity for ensuring optimal child growth and development. In Ethiopia, the magnitude of the minimum acceptable diet ranges from 7 to 74⋅6 %. The evidence revealed the variation and unrelated data on the prevalence of minimum acceptable diet. Therefore, the present study aimed to assess the minimum acceptable diet and its associated factors among children aged 6-23 months in Lalibela town administration, northeast Ethiopia. A community-based cross-sectional study was conducted in Lalibela town administration, northeast Ethiopia among 387 mothers/caregivers with children aged 6-23 months from May 1 to 30, 2022. The data were entered by Epidata version 3.1 and analysed by SPSS version 25.0. A multivariable binary logistic regression model was fitted to identify factors associated with minimum acceptable diet. The degrees of association were assessed using an adjusted odds ratio with a 95 % confidence interval and P-value of 0⋅05. The magnitude of minimum acceptable diet in the study area was 16⋅7 % (95 % confidence interval: 12⋅8-20⋅6 %). Sex of child, getting infant and young child feeding counselling at antenatal care, infant feeding practice-related knowledge and childhood illness are the variables that were found to be an independent predictor of minimum acceptable diet. Health facilities should strengthen infant feeding counselling starting from antenatal care visits during pregnancy for the recommended minimum acceptable diet is crucial.

Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases.

Sensitivity analyses of rate constants for chemical kinetics of the pyrolysis reaction are essential for the efficient valorization of plastic waste into combustible liquids and gases. Finding the role of individual rate constants can provide important information on the process conditions, quality, and quantity of the pyrolysis products. The reaction temperature and time can also be reduced through these analyses. For sensitivity analysis, one possible approach is to estimate the kinetic parameters using MLRM (multiple linear regression model) in SPSS. To date, no research reports on this research gap are documented in the published literature. In this study, MLRM is applied to kinetic rate constants, which slightly differ from experimental data. The experimental and statistically predicted rate constants varied up to 200% from their original values to perform sensitivity analysis using MATLAB software. The product yield was examined after 60 min of thermal pyrolysis at a fixed temperature of 420 °C. The predicted rate constant "k(8)" with a slight difference of 0.02 and 0.04 from the experiment revealed 85% oil yield and 40% light wax after 60 min of operation. The heavy wax was missing from the products under these conditions. This rate constant can be utilized to maximize the commercial-scale extraction of liquids and light waxes from thermal pyrolysis of plastics.

Perceptions and practices of urban slum-dwelling women concerning soil-transmitted helminths infections in Bangladesh: A cross-sectional study.

Introduction: Soil-transmitted helminths (STH) infections are still attributed to a significant part of mortality and disabilities in developing nations. This study aimed at exploring the perceptions and practices concerning STH and to assess the associated risk of infections among slum-dwelling women of Dhaka South City Corporations (DSCC), Bangladesh. Materials and methods: A cross-sectional study was conducted in two selected slums (Malibagh and Lalbagh) of DSCC, Bangladesh, from September 2020 to February 2021. A total of 206 women participants were requested to provide stool samples, followed by a semi-structured questionnaire survey. Parasitological assessment was done by the formol-ether concentration (FEC) technique. Data were analyzed using descriptive statistics, and p-value < 0.05 was considered as statistically significant. An adjusted odds ratio (AOR) with a 95% confidence interval (95% CI) was estimated using logistic regression analysis to examine the association between explanatory and outcome factors. Results: In total, 36 (17.5%) STH infections were observed out of 206 examined participants. Among the STH, Trichuris trichiura showed the highest prevalence (10.7%), followed by Ascaris lumbricoides (5.3%). Lack of formal education, overcrowded living, large family sizes, and using shared toilets were significantly associated with STH infections. Irregular nail cutting (AOR = 3.12), irregular soap usage after toilet (AOR = 2.98), wearing no shoes (AOR = 4.64), and failing to teach kids to wash their hands (AOR = 3.87) were revealed as practice concerns linked to high STH prevalence. Women, who had never heard about STH (AOR = 2.42) and had no misconceptions regarding STH (AOR = 1.94) were positively related to STH infection in this study. Conclusion: Slum-dwelling women in Bangladesh still had a substantial infection of STH. Most of the communities under study were unaware of parasite infection and its negative effects on health. Revision of the policy of ongoing anthelmintic distribution programs and widespread health education programs are recommended aimed at controlling STH.

Adoption of novel climate-smart farming systems for enhanced carbon stock and carbon dioxide equivalent emission reduction in cattle corridor areas of Uganda.

Climate change remains the single major threat to the realization of increased livestock production because of its impact on the quantity and quality of feed crops and forages, water availability, animal reproduction, and biodiversity. To minimize the negative impacts of climate change on livestock, an agroforestry project was implemented in the cattle corridor areas of Uganda. Predominant agroforestry tree species and improved grass were planted. At the age of 1.5 years, the aboveground biomass, aboveground carbon stock, and carbon dioxide equivalent emissions sequestrated by each sapling species strand and grass species were determined. From the results, the aboveground biomass (F = 92.21, p = 0.020), aboveground carbon stock (F = 101.01, p = 0.035), and the carbon dioxide equivalent emissions sequestrated (F = 71.02, p = 0.0401) varied significantly among the studied species. Among the agroforestry saplings, Calliandra callothyrus (10.0 ± 0.7 ton/acre) had the highest aboveground biomass, while Markhamia lutea (4.3 ± 0.3 tons/acre) and Albizia chinense (4.1 ± 0.2 tons/acre) had the lowest aboveground biomass. Similarly, the aboveground carbon stock was the highest in Calliandra callothyrus strand (4.70 ± 0.1 tons/acre) and lowest in the Albizia chinense strand (1.94 ± 0.2 tons/acre). At a strand level, Calliandra callothyrus (17 ± 0.4 ton/acre) sequestrated the highest quantities of carbon dioxide equivalent emissions, followed by Maesopsis eminii (10 ± 0.2 ton/acre) and Grevillea robusta (9 ± 0.5 ton/acre) species strands. Markhamia lutea (7 ± 0.2 ton/acre) and Albizia Chinense (7 ± 0.1 ton/acre) strands sequestrated the lowest quantities of carbon dioxide equivalent emissions. At the age of 1.5 years, the grass species were fully grown but only stored 0.51 ± 0.0 and 0.47 ± 0.0 tons/acre of Aboveground carbon for Chloris gayana and Centrosema pubescens, respectively. The carbon dioxide equivalent emissions sequestrated by the grass: Chloris gayana (1.9 ± 0.0 ton/acre) and Centrosema pubescens (1.7 ± 0.0 ton/acre) were also less than that of the agroforestry saplings. From this study, the agroforestry species with higher wood biomass and fast growth rate are recommended for carbon dioxide emission sequestration.

Covid-19 related factors to food security and dietary diversity among urban households in western Oromia, Ethiopia.

Background: This study aims to assess factors associated with food security and dietary diversity among poor urban households of western Oromia, Ethiopia, after the outbreak of the Covid-19 pandemic. Method: A cross-sectional, community-based study was conducted in May to June 2021 with 361 poor urban households in the Horo Guduru Wollega zone, western Oromia, Ethiopia. A pre-tested structured questionnaire was used to collect primary data. Twenty-four hour reminder points were used to assess household dietary diversity, and household food security was assessed using the Household Food Insecurity Access Scale tool. Data were evaluated using the statistical software SPSS version 25.0. Results: This study showed a prevalence of food insecurity in households of 59.6%. The mean and standard deviation of household dietary diversity values were 4.19 ± 1.844. Family size (AOR = 8.5; 95% CI:3.295-21.92), monthly income (AOR = 3.52; 95% CI; 1.771-6.986), dietary diversity (AOR = 8.5; 95% CI; 3.92-18.59), knowledge (AOR = 3.0, 95% CI = 1.08-)8.347), attitude (AOR = 8.35, 95% CI:3.112-22.39) and practices against Covid-19 (AOR = 2.12; 95% CI:1.299-11.4) were factors significantly associated with food insecurity. Variables like educational status (AOR = 3.46; 95% CI:1.44-8.312), increased family size after the Covid-19 pandemic (AOR = 2.26; 95% CI:1.02-5.04), food security (AOR = 6.7; 95% CI:4.01-19.01), knowledge (AOR = 3.96; 95% CI:1.57-10.0), attitude (AOR = 3.9; 95% CI:1.75-8.82) and practices toward coronavirus (AOR = 2.23; 95% CI:2.18-23.95) were predictors significantly associated with dietary diversity. Conclusion: This study concluded that family size, monthly income, and dietary diversity were factors contributed to household food security. On the other hand, variables such as educational status, family size, and food security were highly relevant factors for dietary diversity after the outbreak of the Covid-19 pandemic. Knowledge, attitudes, and practices were also variables related to both household food security and dietary diversity. Therefore, immediate interventions such as nutrition-specific interventions can be suggested to address food insecurity and problems of inadequate food intake in poor urban households. In addition, governmental and non-governmental organizations should raise awareness and policies to support those at higher risk by developing affordable, sustainable and targeted social protection systems that ensure food security and adequate dietary intake at the household level.

Assessment of patients' satisfaction with the postanesthesia care unit service at University Hospital in Al Khobar, KSA.

Objectives: The quality of health care is individually and subjectively reflected through patients' level of satisfaction, as well as the optimality and effectiveness of the provided postoperative pain management. The provision of postanesthesia care unit (PACU) service in hospitals has led to overall positive outcomes, in addition to the enhancement of patients' satisfaction with the provided pain management service. This study assessed patients' level of satisfaction with PACU service at a university hospital and discussed different factors that might have contributed to the level of satisfaction. Methods: A prospective cross-sectional study was carried out among patients after being discharged from PACU. The study took place at King Fahad Hospital of the University in Al Khobar, KSA between November 2021 and February 2022. The data were collected using a three-section predesigned questionnaire. Results: Two hundred patients were included in this study. Nearly all patients (95.5%) were satisfied with the provided pain management service. Almost all patients (99.5%) indicated that the PACU staff was courteous and professional during the entire pain management service. More patients complained about pain before using analgesia and this difference was statistically significant (Z = 8.642; p < 0.001). The satisfaction rate was significantly higher in the older age group (>45 years) (Z = 2.114; p = 0.035), in patients with American Society of Anesthesiology (ASA) 3 physical status (H = 13.130; p = 0.001), and those with a previous surgical history (Z = 2.139; p = 0.032). Conclusion: This study concluded that the level of patients' satisfaction with PACU service was high, and established a statistically significant association with age, ASA score, and previous surgical history. Healthcare providers should consider patient education and effective communication to increase patients' satisfaction level and improve the overall quality of care.