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In chronic kidney disease (CKD), hyperuricemia is a common phenomenon, presumably due to reduced renal clearance of uric acid. This study investigated the effect of xanthine oxidase (XO) inhibitors allopurinol and febuxostat to prevent oxidative stress in the kidney of two-kidney, one-clip (2K1C) rats. In this investigation, 2K1C rats were used as an experimental animal model for kidney dysfunction. 2K1C rats were provided with food and drinking water and received febuxostat at a dose of 10 mg/kg or allopurinol at 100 mg/kg, respectively. After the treatment completion, all rats were sacrificed, and tissue samples were collected. 2K1C rats exhibited increased plasma creatinine, uric acid level, and glomerular injury assessed based on microscopic findings. Both allopurinol and febuxostat significantly normalized creatinine and uric acid levels. Furthermore, 2K1C rats showed increased lipid peroxidation (LPO), nitric oxide (NO), and advanced oxidation protein products (AOPP) alongside decreased superoxide dismutase (SOD) and catalase activity. Again, both drug treatments ameliorated these elevated oxidative stress parameters in 2K1C rats. The antioxidant genes such as Nrf-2, HO-1, and SOD were also restored in the kidneys of 2K1C rats by allopurinol and febuxostat treatment. 2K1C rats also showed increased IL-1β, IL-6, TNF-α, and NF-кB mRNA expression in the kidneys which were normalized by allopurinol and febuxostat treatment. Thus, the data suggest that XO inhibition protects kidney function potentially by restoring antioxidant enzyme function and suppressing inflammation.

To improve medical care and rehabilitation algorithms for patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is important to evaluate and summarize the available data on the effect of coronavirus infection (COVID-19) on the endocrine system. The purpose of this review was to study the effect of COVID-19 on the endocrine system. The scientific novelty of this study is the evaluation of the effect of coronavirus infection on the endocrine system and the potential effect of hormones on susceptibility to COVID-19. The results of this review show that the endocrine system is vulnerable to disorders caused by COVID-19, mainly thyroid dysfunction and hyperglycemia. The information in the published literature mentioned here contains some unclear aspects and contradictory data, but much remains to be studied and clarified regarding the impact of COVID-19 on the endocrine system. In particular, this concerns the study of the hyperglycemic status of patients who have had coronavirus infection, which is extremely important for the future metabolic health of COVID-19 survivors. This review contributes to the scientific discourse by systematically synthesizing disparate studies to identify patterns, gaps, and emerging trends in the literature concerning the effects of COVID-19 on the endocrine system. By integrating these findings, this study offers a novel perspective on potential hormonal interactions influencing COVID-19 susceptibility and outcomes, proposing new hypotheses and frameworks for future research.

Although glucosamine (GlcN) exhibits antitumor effects, its mechanism of action remains controversial. Additionally, its impact on hepatocellular carcinoma (HCC) is not well understood. This study aimed to investigate the antitumor effects of GlcN and its underlying mechanism in a mouse HCC cell line, Hepa1-6. GlcN treatment significantly inhibited Hepa1-6 cell proliferation. Gene expression analysis revealed that GlcN upregulated Chop and Bax while downregulating Bcl2, indicating the involvement of endoplasmic reticulum (ER) stress-induced apoptosis in the antiproliferative effects of GlcN. GlcN also increased the expression of FoxO1 and FoxO3, known tumor suppressors in various cancers. Furthermore, GlcN treatment elevated the levels of LC3II (an autophagy marker) and AMP-activated protein kinase activity, suggesting intracellular energy shortage. Indeed, GlcN treatment significantly suppressed glycolytic flux, lactate, and ATP production. Supplementing GlcN treatment with a high glucose concentration (20 mM) significantly attenuated its effect. We postulate that GlcN inhibits Hepa1-6 cell growth by inducing ER stress-induced apoptosis and autophagy and by inhibiting aerobic glycolysis (the Warburg effect), a key hallmark of cancer metabolism. Given that glucose transporter 2 (GLUT2), which is abundantly expressed in hepatocytes, has a high affinity for GlcN, these effects may result from GlcN competing with glucose for hepatocyte uptake by GLUT2. Our novel findings have potential implications for HCC treatment.

Tobacco, being a globally cultivated crop, holds significant social and economic importance. Tobacco plants are susceptible to the adverse effects of heavy metals (HMs), particularly cadmium (Cd), which hinders root development, disrupts water balance, and impedes nutrient absorption. Higher concentrations of HMs, especially Cd, naturally accumulate in tobacco leaves due to complex interactions within the plant-soil continuum. The uptake of Cd by plants from the soil is influenced by several factors, including soil type, pH, irrigation water quality, and the chemical composition of the metal involved. Different techniques, such as bioremediation, phytoremediation, and mycoremediation, have been employed to tackle the issue of HMs. The use of biochar offers a practical solution to mitigate this problem. With its large surface area and porous nature, biochar can effectively alleviate HMs contamination. Under biochar application, metal adsorption primarily occurs through physical adsorption, where metal ions are trapped within the pores of the biochar. Additionally, electrostatic attraction, in which negatively charged biochar surfaces attract positively charged metal ions, is another major mechanism of metal remediation facilitated by biochar. In this review, we documented, compiled, and interpreted novel and recent information on HMs stress on tobacco plants and explored biochar's role in alleviating HMs toxicity. By providing a comprehensive review of the persistent threat posed by Cd to tobacco crops and exploring biochar's potential as a remediation measure, this work aims to enhance our understanding of HMs stress in tobacco and contribute to the development of sustainable agricultural practices.

Sangihe nutmeg is an important crop because of its usefulness in the pharmacology, spices and cosmetics industries. Sangihe is the oldest active subduction zone island in the Indonesia-Philippines region, where frequent tectonic earthquakes and the geographic and reproductive isolation of Sangihe nutmeg occur. This isolation results in adaptation and speciation because of increasing variability. Using morphological and molecular approaches, we aimed to assess the genetic variety of Sangihe nutmeg based on morphological and intersimple sequence repeat (ISSR) markers. In total, 31 morphological characteristics were examined, and molecular data of ISSR markers using five primers were analysed based on numerical taxonomy using the unweighted pair group method with arithmetic mean (UPGMA) and principal component analysis (PCA) methods. Results showed five major groups of Sangihe nutmeg based on seed variation, that is, thick round, thin round, thick oval, thin oval, and twin seeds, whereas the presence of variation in molecular characters was indicated by DNA polymorphisms between 0% and 33.33%. The phenetic relationships within Sangihe nutmeg, based on morphological and ISSR markers, exhibit two groups with different member compositions. The major morphological characteristics influencing the phenetic relationship pattern were tree shape, leaf shape, fruit shape, number of fractions when ripe, fruit size index, number of fruit indentations, indentation, aryl density, seed shell, and number of seeds.

For sustainable genetic improvement of crops like sorghum, assessing genetic variability and knowing the nature and extent of the association between grain yield and yield-related traits is a prerequisite. However, there needs to be sufficient information about the genetic variability study as well as yield-related trait correlation and path coefficient analysis for sorghum accessions, especially those from southern Ethiopia. Hence, this field experiment assessed genetic variability, determined the nature and extent of phenotypic-genetic correlation, and analyzed the path coefficients among 17 quantitative traits. A total of 225 sorghum genotypes were tested using a simple lattice design with two replications at the Jinka Agricultural Research Center during the 2021 cropping season. Based on the analysis of variance, most traits showed highly significant (P 0.001) differences, suggesting genetic diversity between the genotypes. High estimates of GCV and PCV were noted for leaf width (3924.50% and 3924.50%), while the lowest GCV and PCV estimates were obtained for days to flowering and days to maturity. High heritability coupled with high GAM estimates was recorded for plant height, leaf number, leaf length, leaf width, and leaf area. The magnitudes of genotypic correlations were higher than those of phenotypic correlations for most of the studied traits, implying that the traits under study were genetically controlled. Grain yield was positively and significantly correlated with most of the traits at phenotypic and genotypic levels, indicating the presence of a strong inherent association between grain yield and other traits. Phenotypic path coefficient analysis showed that grain filling period and biomass yield exerted a high positive direct effect on grain yield. Genotypic path coefficient analysis revealed that biomass yield, grain filling period, leaf width, and days to flowering had a relatively high positive direct effect on grain yield. However, days to maturity, plant height, leaf number, leaf area, yield per panicle, straw weight, and harvest index exerted a negative direct effect on grain yield. Almost for all the studied traits, genotypic direct and indirect effects were higher than the phenotypic direct and indirect effects, indicating that the studied traits had a genetically inherited relationship with grain yield. Grain yield in sorghum can be improved through indirect selection for traits such as plant height, leaf number, leaf length, leaf width, and biomass yield. In general, the observed variability and the information obtained from this study can be used for the genetic enhancement of sorghum thereby developing high-yielding varieties.

Pseudomonas aeruginosa is a critical-class pathogen that shows great resistance to most conventional antibiotics. Hence, it is of utmost importance to search for novel drugs to fight infections caused by this bacterium. This study aimed to evaluate the antibacterial activity of Lippia multiflora, Terminalia mollis, and Cinchona officinalis extracts alone and in combination with antibiotics against multidrug-resistant (MDR) P. aeruginosa. Phytochemical analysis was performed using standard qualitative and quantitative assays. The microdilution method was used to assess the antibacterial and antibiotic-resistance modulatory activity of the extracts. The interaction between antibiotics and Cinchona officinalis leaf extract was carried out using the checkerboard broth microdilution method. Phenols and flavonoids were detected in all extracts, whereas other phytochemical classes were selectively distributed. T. mollis leaf extract demonstrated the highest phenolic content (151.59 mg GAE/g), while L. multiflora leaf (LML) extract showed the highest flavonoid content (24.51 mg QE/g). These extracts exhibited antibacterial activity, with minimum inhibitory concentrations (MICs) ranging from 128 to 2048 μg/mL. LML extract displayed the best antipseudomonal activity, with MIC of 128 μg/mL against ATCC 27853 and 256 μg/mL against some MDR isolates (PA1, PA2, and PA7). Moreover, C. officinalis leaf extract (MIC/8), although weakly active, had improved by 2 to 64-fold the activity of imipenem, streptomycin, kanamycin, and ceftriaxone against MDR P. aeruginosa. It also showed synergy (ΣFIC ≤ 0.5) with streptomycin, ampicillin, tetracycline, and vancomycin against P. aeruginosa PA3. The overall results indicate that the tested extracts, especially those from L. multiflora and C. officinalis leaves, necessitate further exploration for the development of natural drugs to treat infections caused by MDR P. aeruginosa.

The goal of the research was to use BBD, a productive RSM approach, to enhance the HPLC separation and validation of astilbin in Lysiphyllum strychnifolium stems. The percentage of acetonitrile (ACN), flow rate, and temperature were among the independent parameters that determined how much the chromatographic condition chosen from factor-level screens lowered the t _R of astilbin. The six dependent variables were t _R , PA, k', Rs, N, and As. The following HPLC settings were optimal for astilbin separation: 19% ACN at t ₀-t ₁₅, 0.8 mL/min flow rate, and 25°C temperature, resulting in a 26-min reduction in working time. This resulted in a separation success rate of 68.57%. Findings revealed the following sequence for t _R , PA, k', Rs, N, and As: 12.108 ± 0.010 min, 78,845,108 ± 420,267, 2.510 ± 0.003, 2.141 ± 0.024, 10,945 ± 80, and 0.991 ± 0.005. The limit of detection was 0.10 μg/mL, while the limit of quantitation was 0.20 μg/mL. The calibration curve was constructed using concentrations ranging from 0.39 to 50 μg/mL, with an R ² value of 0.9991, indicating excellent linearity. The intraday and interday precision RSD values were 0.069%-1.892% and 0.993%-3.229%, respectively. Recovery values were between 95.56% and 105.57%, confirming the method's accuracy. Astilbin was found at 175.51 ± 7.80 μg in L. strychnifolium stem extracts; its actual concentration was 3.51 ± 0.16%. The usefulness of astilbin as a chemical marker in L. strychnifolium stems may therefore be determined based on the criteria that have been established using this information.

It is crucial to prioritize research and development as part of rural revitalization efforts to promote balanced economic growth, preserve cultural heritage, and reduce urban migration. This ensures sustainability and encourages equal access to opportunities, resources, and a healthy environment for people in both rural and urban areas. For the first time, this study explores the interplay between sustainability (Factor A) and health-related environment (Factor B) under the background of rural revitalization in the eight towns (Chengguan, Haocheng, Liacheng, Renqiao, Hugou, Xinmaqiao, Liuji, and Wangzhuang) located in Guzhen County, Bengbu City, China. The towns of Guzhen County were not studied under these two factors before. This study evaluates the sustainability and health-related environmental needs by gathering data from 100 residents in eight towns, totaling 800 residents from the targeted study area. Sustainability highlights town-specific priorities; however, health-related needs (Factor B) emphasize the mutual needs of all residents. Similar results in different towns highlight the critical significance of health-related environment. Statistical analysis reveals a significant correlation between sustainability and health-related environmental factors. This stimulates further exploration of nuanced dynamics in rural revitalization. A higher agreement percentage (80%-100%) on health-related aspects underscores the importance of prioritizing policies to overcome these issues in the study area.

The development of a model is highly crucial in cases where there are intricate geographical features, and conducting a forest inventory is both time-consuming and expensive, requiring significant manual effort for measurement. Acquiring reliable data regarding the forest's condition and future progression is essential for making informed decisions about its management. Therefore, this research aimed to create an individual tree diameter growth model specifically for Terminalia alata (B. Heyne. ex Roth). This study was conducted in Terai Arc Landscape of Nepal, encompassing 14 districts in the Terai and Chure regions of Nepal. Individual tree data (diameter at breast height, tree height, crown height, crown cover, longitude, and latitude) from three different time periods (2011, 2017, and 2022) were obtained with 673 sample plots maintained for forest research assessment by Government of Nepal, and annual diameter growth was estimated. Multiple linear, linear mixed, and generalized additive models were employed to fit the growth modeling for individual tree diameter growth of T. alata. We observed higher mean diameter growth rates in 0-25 cm and 101-125 cm tree diameter classes (0.318 cm·yr^-1). There were significant differences in diameter growth across tree quality classes, but no significant differences due to crown classes were observed. Although the generalized additive model (Adj. R ² = 0.32) performed better than the linear mixed model (adj. R ² = 0.23) and the multiple linear model (adj. R ² = 0.03), it still explained only a small proportion of the variance in diameter growth. This suggests that other factors, such as unmeasured environmental variables, biotic interactions, or complex nonlinear relationships, may play a significant role in explaining the variation. In addition, the low R ² values indicate that the models may need further refinement, possibly by incorporating interaction terms, random effects, or other possible nonlinear approaches. Future research should also consider the potential influence of spatial or temporal heterogeneity on the growth dynamics.