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BackgroundUric acid is associated with noncommunicable diseases such as cardiovascular diseases, chronic kidney disease, coronary artery disease, stroke, diabetes, metabolic syndrome, vascular dementia, and hypertension. Therefore, uric acid is considered to be a risk factor for the development of noncommunicable diseases. Most studies on uric acid have been performed in developed countries, and the application of machine-learning approaches in uric acid prediction in developing countries is rare. Different machine-learning algorithms will work differently on different types of data in various diseases; therefore, a different investigation is needed for different types of data to identify the most accurate algorithms. Specifically, no study has yet focused on the urban corporate population in Bangladesh, despite the high risk of developing noncommunicable diseases for this population. ObjectiveThe aim of this study was to develop a model for predicting blood uric acid values based on basic health checkup test results, dietary information, and sociodemographic characteristics using machine-learning algorithms. The prediction of health checkup test measurements can be very helpful to reduce health management costs. MethodsVarious machine-learning approaches were used in this study because clinical input data are not completely independent and exhibit complex interactions. Conventional statistical models have limitations to consider these complex interactions, whereas machine learning can consider all possible interactions among input data. We used boosted decision tree regression, decision forest regression, Bayesian linear regression, and linear regression to predict personalized blood uric acid based on basic health checkup test results, dietary information, and sociodemographic characteristics. We evaluated the performance of these five widely used machine-learning models using data collected from 271 employees in the Grameen Bank complex of Dhaka, Bangladesh. ResultsThe mean uric acid level was 6.63 mg/dL, indicating a borderline result for the majority of the sample (normal range

Education is one of the most important factors in producing human resources. University education can be influenced by many factors that affect students' quality of academic performance. The main focus of this study is identifying the influencing factors that are significantly associated with the academic performance of universities students. Data were extracted from the various departments of two public universities. Data analysis by Contingency and logistic regression were used to identify the determinants of academic performance of the students. Among the students, 56.8% were male and 43.2% were female most of them are Muslims and unmarried. 75.1% of students came from rural areas, only 15% of students' mothers were higher educated and 65% of student's family status was middle class. Higher educated mother, HSC and SSC results, admitted to an expected university, admitted present department by their own choice, study environment in the department and use of the internet had significant effects on the results of 1st year of the students. The findings concluded that increase and improve students' academic performance are some crucial steps regarding securing admission first choice of the department and advising about peer influence should be taken into consideration.

BackgroundThe prevalence of non-communicable diseases is increasing throughout the world, including developing countries. ObjectiveThe intent was to conduct a study of a preventive medical service in a developing country, combining eHealth checkups and teleconsultation as well as assess stratification rules and the short-term effects of intervention. MethodsWe developed an eHealth system that comprises a set of sensor devices in an attaché case, a data transmission system linked to a mobile network, and a data management application. We provided eHealth checkups for the populations of five villages and the employees of five factories/offices in Bangladesh. Individual health condition was automatically categorized into four grades based on international diagnostic standards: green (healthy), yellow (caution), orange (affected), and red (emergent). We provided teleconsultation for orange- and red-grade subjects and we provided teleprescription for these subjects as required. ResultsThe first checkup was provided to 16,741 subjects. After one year, 2361 subjects participated in the second checkup and the systolic blood pressure of these subjects was significantly decreased from an average of 121 mmHg to an average of 116 mmHg (P

Aim: Calcium hydroxide (CH) has been considered as a direct pulp capping materials (DPC) for the last decades despite having some limitations. Phosphorylate pullulan (PPL) incorporated with CH (CHPPL) is a novel biomaterial that was introduced as a promising DPC material. Thus, the aim of the study was to evaluate the inflammatory response and mineralized tissue formation (MTF) ability of PPL‐based CH formulations on rat molars after DPC. Methodology: This study consisted of six groups: CH with 1% PPL (CHPPL‐1); 3% PPL (CHPPL‐3); 5% PPL (CHPPL‐5); Dycal and NEX MTA Cement (N‐MTA) as the positive control, and no capping materials (NC). One hundred twenty maxillary first molar cavities were prepared on Wistar rats. After capping, all the cavities were restored with 4‐META/MMA‐TBB resin and pulpal responses were evaluated at days 1, 7, and 28. Kruskal–Wallis followed by Mann–Whitney U‐test was performed with a significance level of 0.05. Immunohistochemical expression of IL‐6, Nestin, and DMP‐1 was observed. Results: At day 1, CHPPL‐1, N‐MTA, and Dycal exhibited no to mild inflammation, whilst CHPPL‐3, CHPPL‐5, and NC showed mild to moderate inflammation, and the results were significantly different (p <.05). At day 7, mild to moderate inflammation was observed in CHPPL‐1, N‐MTA, and Dycal, whereas CHPPL‐3, CHPPL‐5, and NC exhibited moderate to severe inflammation. Significant differences were observed between CHPPL‐1 and N‐MTA with NC (p <.05), CHPPL‐1 and CHPPL‐3 with CHPPL‐5 and Dycal (p <.05), and CHPPL‐3 with N‐MTA (p <.05). A thin layer of mineralized tissue formation (MTF) was observed in all groups. At day 28, CHPPL‐1, Dycal, and N‐MTA showed no to mild inflammation, whilst CHPPL‐3, CHPPL‐5, and NC exhibited mild to severe inflammation, and statistically significant difference was detected (p <.05). CHPPL‐1, Dycal, and N‐MTA exhibited continuous MTF, whilst CHPPL‐3, CHPPL‐5, and NC had thicker and interrupted MTF. Significant differences were observed between CHPPL‐1, CHPPL‐3, and N‐MTA with NC group (p <.05). Variable expressions of IL‐6, Nestin, and DMP‐1 indicated differences in the materials' impact on odontoblast‐like cell formation and tissue mineralization. Conclusions: These findings suggest that CHPPL‐1 has the potential to minimize pulpal inflammation and promote MTF and had similar efficacy as MTA cement. [ABSTRACT FROM AUTHOR]

Cinchona alkaloid-derived sulfonamides and ester dimers containing chiral hyperbranched polymers have been successfully synthesized and applied as catalysts in asymmetric reactions. Several hyperbranched polymers derived from cinchona alkaloids, incorporating sulfonamides and esters, were synthesized through Mizoroki--Heck coupling polymerization. These polymers were subsequently applied in enantioselective Michael addition reactions. As the prepared polymers are not soluble in frequently used organic solvents, they act as efficient catalysts in the enantioselective reaction of β-ketoesters to nitroolefins, achieving up to 99% enantioselectivity with good yields. The insoluble property allows them to better satisfy "green chemistry" requirements and be used several times without losing the enantioselectivity. [ABSTRACT FROM AUTHOR]

The present study aimed to identify novel biostimulatory compounds in boar seminal gel (SG), saliva and semen using Gas chromatography-mass spectrometry (GC-MS). The bio-stimulatory effect of SG, SG + saliva and SG + semen on young boar for semen collection as well were employed to study bio-stimulatory effects on gilts and sows. Distilled water (DW) exposure was kept as control. SG, saliva and semen were screened for total 105, 96 and 89 compounds. The highest concentration was of alkanes followed by sugar alcohols, then hydrocarbons, amino acids and fatty acids. Elaidic acid was the novel compound identified in pigs. Significantly higher (p < 0.05) number of males got trained in exposure to SG (80%), SG + saliva (75%) and SG + semen (75%) than control (0%). The time (hrs) taken by young boars to get trained on exposure to combination of SG + saliva (244 ± 22.19) and SG + semen (216 ± 13.14) was lesser (p < 0.05) than SG (356 ± 61.85) alone. Interval (hrs) from initiation of exposure for exhibition of different sexual behaviour by males on exposure to SG, saliva and semen was lesser (p < 0.05) than control. Significantly (p < 0.05) higher number of females showed estrus response to exposure of SG (72.72%), SG + saliva (69.23%) and SG + semen (76.92%) than control (0). Interval (hrs) taken to exhibit estrus was shorter (p < 0.05) in females exposed to SG + saliva (201.88 ± 12.66), SG + semen (198.20 ± 9.42) than SG (262.14 ± 20.06) alone. Interval (hrs) for exhibition of different sexual behaviour by females on exposure to SG + saliva and SG + semen was lesser (p < 0.05) than control. In conclusion, novel compounds were identified in boar seminal gel, saliva and semen with biostimulatory properties have been identified in boar SG, saliva and semen. The combined exposure of SG with saliva and semen has more intense biostimulation effect than SG alone for training of young boars and estrus induction in gilts and sows. Such compounds biostimulatory effects can be exploited for augmenting reproductive efficiency in pigs. [ABSTRACT FROM AUTHOR]

Objective: The purpose of the current study was to examine the effectiveness of green macroalgae as a novel, natural feed additive for broilers that have a greater concentration of active ingredients. Materials and Methods: Four experimental groups of 180-day-old male broiler chicks (Cobb-500) were randomly assigned, with three replicates in each group: the control group [T0, maintained only with basal diet] and three treatment groups supplemented with macroalgae for 35 days along with basal diet [T1 = 0.05% (w/w); T2 = 0.1% (w/w); T3 = 0.2% (w/w) macroalgae]. Live weight, carcass weight, and organs' weight were noted at the conclusion of the experiment. The meat quality was examined using the muscles of the thighs and breasts, and blood serum was obtained for biochemical assessment. Results: The results revealed that dietary supplementation of green macroalgae (0.1%) in broiler rations significantly (p < 0.05) improved the growth performance compared to other treated groups and controls. With increasing weight, it enhanced meat quality traits assessed by increased water holding capacity, ultimate pH, redness and yellowness, and decreased lightness of muscles in the thighs and breasts. Both the levels of serum cholesterol and abdominal fat decreased and showed no unwholesome effects on liver and kidney functions. Conclusions: For the production of safe and high-quality poultry meat, marine green macroalgae (Enteromorpha intestinalis) could be used as a potential feed additive. It enhanced the growth rate in broilers and improved meat quality and serum biochemical parameters for supplying healthy meat in the human food chain. [ABSTRACT FROM AUTHOR]

Brain tumors are critical neurological ailments caused by uncontrolled cell growth in the brain or skull, often leading to death. An increasing patient longevity rate requires prompt detection; however, the complexities of brain tissue make early diagnosis challenging. Hence, automated tools are necessary to aid healthcare professionals. This study is particularly aimed at improving the efficacy of computerized brain tumor detection in a clinical setting through a deep learning model. Hence, a novel thresholding-based MRI image segmentation approach with a transfer learning model based on contour (ContourTL-Net) is suggested to facilitate the clinical detection of brain malignancies at an initial phase. The model utilizes contour-based analysis, which is critical for object detection, precise segmentation, and capturing subtle variations in tumor morphology. The model employs a VGG-16 architecture priorly trained on the "ImageNet" collection for feature extraction and categorization. The model is designed to utilize its ten nontrainable and three trainable convolutional layers and three dropout layers. The proposed ContourTL-Net model is evaluated on two benchmark datasets in four ways, among which an unseen case is considered as the clinical aspect. Validating a deep learning model on unseen data is crucial to determine the model's generalization capability, domain adaptation, robustness, and real-world applicability. Here, the presented model's outcomes demonstrate a highly accurate classification of the unseen data, achieving a perfect sensitivity and negative predictive value (NPV) of 100%, 98.60% specificity, 99.12% precision, 99.56% F 1 -score, and 99.46% accuracy. Additionally, the outcomes of the suggested model are compared with state-of-the-art methodologies to further enhance its effectiveness. The proposed solution outperforms the existing solutions in both seen and unseen data, with the potential to significantly improve brain tumor detection efficiency and accuracy, leading to earlier diagnoses and improved patient outcomes. [ABSTRACT FROM AUTHOR]

Since the settlement of Rohingya people in Cox's Bazar, national and international NGO s have undertaken initiatives such as trust-building and community relationships for establishing social cohesion between the Rohingyas and host communities. However, cohabitation between the two communities is far-behind, and social conflict between the two communities has been a reality for the host society. By applying multiple approaches – perception survey among the local people, focus group discussion (FGD) among the Rohingyas and key informant interviews, this article finds that Rohingya settlement has resulted many challenges such as scarcity of resources, competition over livelihood options, price hikes, decaying of the physical environment, and security complexities. These challenges have been a source of generating conflict instead of building social cohesion in Cox's Bazar. Survey results outline that local people are anxious about population growth, social unrest, illicit business and drugs, and potential political conflict. The FGD among the Rohingyas explores the uncertain future of the refugee, frustration over livelihood, health, and education for their children. Overall results highlight that social, economic, environmental and political changes in the post-settlement phase post-2017 have been a potential source of conflict. Analysis suggests that the conflict potential for the host society stemming from the Rohingya displaced population is significant enough that the host government and international organisations should consider actions, policies, and diplomatic actions to address the social tension and remedy the emergent problems in the area. Such measures include those that strengthen efforts at repatriation initiatives for the refugee population, and those that can ensure livelihood opportunities for them without compromising such opportunities for the host population. [ABSTRACT FROM AUTHOR]

In the pursuit of Universal Health Coverage (UHC), developing countries with limited resources face significant hurdles. Traditional top-down approaches, spearheaded by governments, often entail lengthy planning periods and substantial costs to reach underserved communities. This paper proposes a bottom-up, cost-effective, and preventive approach aimed at empowering local human resources and using advanced technology. We call it the Micro Healthcare Entrepreneurship (MHE) model. The MHE model comprises four primary components: (1) utilization of local human resources, (2) disruptive healthcare technology, (3) continuous training, and (4) available funds. Extensive testing of the digital health and social business elements across diverse contexts underscores their efficacy. Furthermore, the viability of social business funds has been established. To solicit feedback and refine the MHE concept, three workshops, conducted in phases, engaged 60 community healthcare service providers. This paper elucidates both the potential advantages and the challenges inherent in implementing the MHE model. By shifting the paradigm toward grassroots empowerment and leveraging existing community assets, this approach offers promise in advancing healthcare accessibility and sustainability in resource-constrained settings to achieve UHC. [ABSTRACT FROM AUTHOR]

Rice cultivation in the low-lying basin-like wetlands, known as the Haor, is often affected by early flash floods during the first two weeks of April. The flooding is mainly caused by heavy rainfall and water surging downstream from the Meghalaya hills in India. This flash flood poses a significant threat to rice production, risking the country's food security. Dry winter (Boro) rice is the primary food source throughout the year in the Haor region. Flash floods are the most catastrophic, affecting about 80% or even the entire rice yield. In 2017, a loss of 0.88 million metric tons of Boro rice in Haor regions cost the nation USD 450 million. To escape flash floods, it is recommended to sow Boro rice earlier, between the last week of October and the first week of November, instead of around 15 November so rice may be harvested by the last week of March before the onset of flash floods. However, early sowing has a possibility of causing grain sterility due to cold spells when the booting and heading stages of rice inevitably coincide with the cold period between 15 January and 7 February. The minimum temperature in the Haor regions ranges from 11 to 15 °C during this time. Rice is especially susceptible to low average temperatures (<20 °C) during the reproductive stage, leading to pollen abortion and the malformation of immature microspores. Low temperatures mainly impact rice cultivation in Haor regions during the reproductive phase, resulting in the degeneration of the spikelets, partial panicle exertion, and increased spikelet sterility, leading to a decrease in grain yield. Over two million hectares of Boro rice have been damaged by extreme cold spells in recent years, resulting in partial or total yield loss. To overcome the threats of flash floods and cold injury, breeding short-duration and cold-tolerant rice varieties is crucial. We assume that an economic benefit of USD 230 million per year could be achieved through the development and adoption of short-duration and cold-tolerant high-yielding rice varieties in the Haor regions of the country. In this review article, the authors summarized the problems and outline a way forward to overcome the flash flood and cold injury of Boro rice cultivation in the Haor districts of the country. Furthermore, the authors discussed the various forms and scenarios of cold damage and the global existence of cold-tolerant rice cultivars. Based on the available data from earlier research, a potential way of mitigating flash floods and cold devastation was suggested. [ABSTRACT FROM AUTHOR]

New drugs for visceral leishmaniasis that are safe, low cost, and adapted to the field are urgently required. Despite concerted efforts over the last several years, the number of new chemical entities that are suitable for clinical development for the treatment of Leishmania remains low. Here, we describe the discovery and preclinical development of DNDI-6174, an inhibitor of Leishmania cytochrome bc1 complex activity that originated from a phenotypically identified pyrrolopyrimidine series. This compound fulfills all target candidate profile criteria required for progression into preclinical development. In addition to good metabolic stability and pharmacokinetic properties, DNDI-6174 demonstrates potent in vitro activity against a variety of Leishmania species and can reduce parasite burden in animal models of infection, with the potential to approach sterile cure. No major flags were identified in preliminary safety studies, including an exploratory 14-day toxicology study in the rat. DNDI-6174 is a cytochrome bc1 complex inhibitor with acceptable development properties to enter preclinical development for visceral leishmaniasis. Editor's summary: Chagas disease (CD) and visceral leishmaniasis are considered neglected tropical diseases and are responsible for ~30,000 fatalities annually. Current treatments for these vector-borne parasitic infections are inadequate, and there is a pressing need for better therapeutics. In companion articles, González et al. and Braillard et al. describe the development of closely related pyrrolopyrimidine compounds that target the cytochrome bc1 complex of the parasite electron transport chain and show promise for the treatment of both diseases. DNDI-6174 demonstrates potent activity in Leishmania models of infection and has a suitable profile for clinical development. For CD, the combination of pyrrolopyrimidine compounds with a subefficacious dose of benznidazole delivers rapid clearance of parasites in an animal model of chronic CD, offering the prospect of safer and shorter treatment regimens. Collectively, these studies represent advances in the development of potential treatments for some of the world's most neglected patient populations. —Christiana Fogg [ABSTRACT FROM AUTHOR]

Luteal steroidogenesis is critical to implantation and pregnancy maintenance in mammals. The role of androgen receptors (AR) in the progesterone (P4) producing luteal cells of porcine corpus luteum (CL) remains unexplored. The aim of the present study was to establish AR gene knock out (KO) porcine luteal cell culture system model by CRISPR/Cas9 genome editing technology and to study the downstream effects of AR gene deficiency on steroidogenic potential and viability of luteal cells. For this purpose, genomic cleavage detection assay, microscopy, RT-qPCR, ELISA, annexin, MTT, and viability assay complemented by bioinformatics analysis were employed. There was significant downregulation (p < 0.05) in the relative mRNA expression of steroidogenic marker genes STAR, CYP11A1, HSD3B1 in AR KO luteal cells as compared to the control group, which was further validated by the significant (p < 0.05) decrease in the P4 production. Significant decrease (p < 0.05) in relative viability on third passage were also observed. The relative mRNA expression of hypoxia related gene HIF1A was significantly (p < 0.05) downregulated in AR KO luteal cells. Protein-protein interaction analysis mapped AR to signaling pathways associated with luteal cell functionality. These findings suggests that AR gene functionality is critical to luteal cell steroidogenesis in porcine. [ABSTRACT FROM AUTHOR]

Objective: This study sought to determine the effectiveness of the cryodehydration technique in preserving the morphologic and morphometric attributes of the anatomical specimens of goats. Materials and Methods: Different anatomical parts of a goat, i.e., heart, lungs, spleen, liver, kidney, and musculoskeletal specimens, were collected and fixed in 15% formalin. Later on, the fixed specimens were cryodehydrated by fast freezing (burning process) and repeated freezing-thawing sessions, followed by wood glue coating. Finally, the macroscopic (i.e., weight, color, texture, odor, and durability) and microscopic characteristics (by routine hematoxylin and eosin staining) of the cryodehydrated specimens were studied. Results: The resultant specimens produced excellent color and texture and were lightweight (60%-80% weight loss), soft, dry, odorless, durable, and easy to handle. The histoarchitectural details of the heart and skeletal muscle were well preserved, while some distinctive alterations were observed in the parenchymatous organs, i.e., breach in cellular integrity, loss of cell cytoplasm, loss of cytoplasmic and nuclear clarity, increased sinusoidal space, dilatation of the renal tubules, and reduction in glomerular size. Nevertheless, the basic histoarchitecture of each specimen was yet to be distinctly identifiable. Conclusion: The current study findings suggest that the cryodehydration technique can preserve gross anatomical features as well as histoarchitectural details and can be an effective tool for facilitating veterinary education and research. [ABSTRACT FROM AUTHOR]

Chronic kidney disease (CKD) is a progressive condition characterized by the gradual deterioration of kidney functions, potentially leading to kidney failure if not promptly diagnosed and treated. Machine learning (ML) algorithms have shown significant promise in disease diagnosis, but in healthcare, clinical data pose challenges: missing values, noisy inputs, and redundant features, affecting early-stage CKD prediction. Thus, this study presents a novel, fully automated machine learning approach to tackle these complexities by incorporating feature selection (FS) and feature space reduction (FSR) techniques, leading to a substantial enhancement of the model's performance. A data balancing technique is also employed during preprocessing to address data imbalance issue that is commonly encountered in clinical contexts. Finally, for reliable CKD classification, an ensemble characteristics-based classifier is encouraged. The effectiveness of our approach is rigorously validated and assessed on multiple datasets, and the clinical relevancy of the strategy is evaluated on the real-world therapeutic data collected from Bangladeshi patients. The study establishes the dominance of adaptive boosting, logistic regression, and passive aggressive ML classifiers with 96.48% accuracy in forecasting unseen therapeutic CKD data, particularly in early-stage cases. Furthermore, the effectiveness of the FSR technique in reducing the prediction time significantly is revealed. The outstanding performance of the proposed model demonstrates its effectiveness in addressing the complexity of healthcare CKD data by incorporating the FS and FSR techniques. This highlights its potential as a promising computer-aided diagnosis tool for doctors, enabling early interventions and improving patient outcomes. [ABSTRACT FROM AUTHOR]