Hesperetin protects against rotenone-induced motor disability and neurotoxicity via the regulation of SIRT1/NLRP3 signaling.

Rotenone is a pesticide that causes complex I inhibition and is widely known to induce motor disability and experimental Parkinson's disease (PD) in rodents. Evidence suggests a crucial role for sirtuin/nuclear factor-kappaB/nod-like receptor family, pyrin domain-containing 3 (SIRT1/NFκB/NLRP3) signaling and inflammation in PD and rotenone neurotoxicity. Hesperetin (C16H14O6) is a citrus flavonoid with documented anti-inflammatory activity. We investigated the value of hesperetin in delaying rotenone-induced PD in mice and the possible modulation of inflammatory burden. PD was induced in mice via rotenone injections. Groups were assigned as a vehicle, PD, or PD + hesperetin (50 or 100 mg/kg) and compared for the motor function, protein level (by ELISA), and gene expression (by real-time PCR) of the target proteins, histopathology, and immunohistochemistry for tyrosine hydroxylase enzyme. Hesperetin (50 or 100 mg/kg) alleviated the motor disability and the striatal dopamine level and decreased the expression of NLRP3 and NF-κB but increased SIRT1 expression (p < 0.05). Further, it enhanced the neural viability and significantly decreased neural degeneration in the substantia nigra, hippocampus, and cerebral cortex (p < 0.05). Taken together, we propose that hesperetin mediates its neuroprotective function via alleviating modulation of the SIRT1/NFκB/NLRP3 pathway. Therefore, hesperetin might delay the PD progression.

Reproductive Outcomes of Infertile Males With Novel Genetic Defects.

Various chromosomal structural aberrations and genetic mutations have been discovered in infertile couples. Some have no obvious loss of genetic material; they are usually phenotypically normal people with reproductive issues. Males with these illnesses may have infertility and abnormal sperm analysis. However, positive sperm have also been detected in the ejaculation of some patients. As a result, knowing about these problems and how common they are can influence the fertility treatment that couples receive to achieve pregnancy and the birth of healthy newborns.

Population modifiable risk factors associated with neonatal mortality in 35 sub-Saharan Africa countries: analysis of data from demographic and health surveys.

Background: Sub-Saharan Africa (SSA) has the highest burden of neonatal mortality in the world. Identifying the most critical modifiable risk factors is imperative for reducing neonatal mortality rates. This study is the first to calculate population-attributable fractions (PAFs) for modifiable risk factors of neonatal mortality in SSA. Methods: We analysed the most recent Demographic and Health Surveys data sets from 35 SSA countries conducted between 2010 and 2022. Generalized linear latent and mixed models were used to estimate odds ratios (ORs) along with 95% confidence intervals (CIs). PAFs adjusted for communality were calculated using ORs and prevalence estimates for key modifiable risk factors. Subregional analyses were conducted to examine variations in modifiable risk factors for neonatal mortality across Central, Eastern, Southern, and Western SSA regions. Findings: In this study, we included 255,891 live births in the five years before the survey. The highest PAFs of neonatal mortality among singleton children were attributed to delayed initiation of breastfeeding (>1 h after birth: PAF = 23.88%; 95% CI: 15.91, 24.86), uncleaned cooking fuel (PAF = 5.27%; 95% CI: 1.41, 8.73), mother's lacking formal education (PAF = 4.34%; 95% CI: 1.15, 6.31), mother's lacking tetanus vaccination (PAF = 3.54%; 95% CI: 1.55, 4.92), and infrequent antenatal care (ANC) visits (PAF = 2.45; 95% CI: 0.76, 3.63). Together, these five modifiable risk factors were associated with 39.49% (95% CI: 21.13, 48.44) of neonatal deaths among singleton children in SSA. Our subregional analyses revealed some variations in modifiable risk factors for neonatal mortality. Notably, delayed initiation of breastfeeding consistently contributed to the highest PAFs of neonatal mortality across all four regions of SSA: Central, Eastern, Southern, and Western SSA. Interpretation: The PAF estimates in the present study indicate that a considerable proportion of neonatal deaths in SSA are preventable. We identified five modifiable risk factors that accounted for approximately 40% of neonatal deaths in SSA. The findings have policy implications. Funding: None.

A novel spectrofluorimetric method using optical sensor Eu3+-ACAC as a highly selective photo probe to determine Pregabalin in biological samples and pharmaceutical form.

A novel spectrofluorimetric method with high selectivity and sensitivity was created to determine Pregabalin (PG) in pharmaceutical form, human serum, and urine. This method relies on detecting quenching in the intensity of luminescence of the europium acetylacetone complex (Eu3+-ACAC) at emission wavelength λem = 616 nm, which results from interaction with various concentrations of PG after excitation at λex = 395 nm and pH 6.5 in dimethylformamide (DMF). The calibration curve was generated using concentrations ranging from 7.6 × 10-8 to 6.3 × 10-6 mol/L. The plot showed a high correlation coefficient (r2) of 0.994 with a detection limit (LOD) of 2.81 × 10-8 mol/L and a quantification limit (LOQ) of 8.5 × 10-8 mol/L. The remarkable luminescence intensity quenching of the Eu3+-ACAC by ranged concentrations of PG was effectively employed as a photo probe to determine PG in marketable form and different body fluids. Spectroscopic characterization, such as absorption and emission spectra, confirmed the obtained sensor. The improved method is verified using a range of characteristics, such as accuracy, precision, selectivity, linearity, and robustness.

The Effect of Genetic Variants of SLC22A2 (rs662301 and rs315978) on the response to Metformin in type 2 Saudi diabetic patients.

PURPOSE: To investigate the allelic and genotypic frequencies of the two genetic variations, NC_000006.12: g.160275887C > T (rs662301) and NC_000006.12:g.160231826 T > C (rs315978), in the SLC22A2 gene among the Saudi population. The primary goal is to elucidate potential associations with these genetic variations and the response to metformin therapy over 6 months to enhance our knowledge of the genetic basis of Type 2 Diabetes Mellitus (T2DM) and its clinical management in the Saudi population. MATERIALS/METHODS: 76 newly diagnosed T2DM patients, aged 30 to 60, of both sexes and Saudi origin, were treated with metformin monotherapy. Blood samples were collected before and after 6 months of therapy,80 healthy individuals were included as controls. Genomic DNA was extracted. Genotyping of the SLC22A2 genetic variations was performed using TaqMan® SNP Genotyping Assays. Binary logistic regression was utilized to evaluate how certain clinical parameters influence T2DM concerning the presence of SLC22A2 gene variants. RESULTS: Among these patients, 73.3 % were responders, and 26.7 % were non-responders. For these variants, no statistically significant differences in genotype or allele frequencies were observed between responders and non-responders (p = 0.375 and p = 0.384 for rs662301; p = 0.473 and p = 0.481 for rs315978, respectively). For the SLC22A2 variant rs662301, the C/C genotype was significantly associated with increased T2DM risk with age and elevated HbA1c levels. Similarly, rs315978 revealed higher T2DM susceptibility and HbA1c elevation in C/C genotype carriers, specifically with advancing age compared to individuals with C/T and T/T genotypes. CONCLUSION: The study offers insights into the genetic landscape of T2DM in Saudi Arabia. Despite the absence of significant associations with treatment response, the study suggests potential age-specific associations, this highlights the complexity of the disease. This research underscores the necessity for expanded research, considering diverse populations and genetic factors, to develop personalized treatment approaches. This study serves as a foundation for future investigations into the Saudi population, recognizing the need for a larger sample size.

Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network.

In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimensional bioinformatics data often challenge classical survival models, which are either infeasible to fit or produce low prediction accuracy due to overfitting. To address this issue, the focus has shifted towards introducing a novel approaches for feature selection and survival prediction. In this article, we propose a new hybrid feature selection approach that handles high-dimensional bioinformatics datasets for improved survival prediction. This study explores the efficacy of four distinct variable selection techniques: LASSO, RSF-vs, SCAD, and CoxBoost, in the context of non-parametric biomedical survival prediction. Leveraging these methods, we conducted comprehensive variable selection processes. Subsequently, survival analysis models-specifically CoxPH, RSF, and DeepHit NN-were employed to construct predictive models based on the selected variables. Furthermore, we introduce a novel approach wherein only variables consistently selected by a majority of the aforementioned feature selection techniques are considered. This innovative strategy, referred to as the proposed method, aims to enhance the reliability and robustness of variable selection, subsequently improving the predictive performance of the survival analysis models. To evaluate the effectiveness of the proposed method, we compare the performance of the proposed approach with the existing LASSO, RSF-vs, SCAD, and CoxBoost techniques using various performance metrics including integrated brier score (IBS), concordance index (C-Index) and integrated absolute error (IAE) for numerous high-dimensional survival datasets. The real data applications reveal that the proposed method outperforms the competing methods in terms of survival prediction accuracy.

A new family of distributions using a trigonometric function: Properties and applications in the healthcare sector.

Probability distributions play a pivotal and significant role in modeling real-life data in every field. For this activity, a series of probability distributions have been introduced and exercised in applied sectors. This paper also contributes a new method for modeling continuous data sets. The proposed family is called the exponent power sine-G family of distributions. Based on the exponent power sine-G method, a new model, namely, the exponent power sine-Weibull model is studied. Several mathematical properties such as quantile function, identifiability property, and rth moment are derived. For the exponent power sine-G method, the maximum likelihood estimators are obtained. Simulation studies are also presented. Finally, the optimality of the exponent power sine-Weibull model is shown by taking two applications from the healthcare sector. Based on seven evaluating criteria, it is demonstrated that the proposed model is the best competing distribution for analyzing healthcare phenomena.

Hormonal, liver, and renal function associated with electronic waste (e-waste) exposure in Dhaka, Bangladesh.

Electronic waste (e-waste) contains numerous metals and organic pollutants that have detrimental impacts on human health. We studied 199 e-waste recycling workers and 104 non-exposed workers; analyzed blood, urine, and hair samples to measure heavy metals, hormonal, liver, and renal function. We used quantile regression models to evaluate the impact of Pb, Cd, and Hg on hormonal, liver and renal function, and the role of DNA oxidative damage in mediating the relationship between exposures and outcomes. Exposed workers had higher blood lead (Pb) (median 11.89 vs 3.63 µg/dL), similar blood cadmium (Cd) (1.04 vs 0.99 µg/L) and lower total mercury (Hg) in hair (0.38 vs 0.57 ppm) than non-exposed group. Exposed workers also had elevated median concentrations of total triiodothyronine (TT3), aspartate aminotransferase (AST), alanine aminotransferase (ALT), urinary albumin, albumin creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) were significantly higher than non-exposed group (p≤0.05). Sex hormones including luteinizing hormone, follicle stimulating hormone, estrogen, progesterone and testosterone concentrations were not significantly different between exposed and non-exposed (all p≥0.05). The median concentration of ALT was 4.00 (95% CI: 0.23, 7.77), urinary albumin was 0.09 (95% CI: 0.06, 0.12) and ACR was 1.31 (95% CI: 0.57, 2.05) units higher in the exposed group compared to non-exposed group. Pb was associated with a 3.67 unit increase in the ALP (95% CI: 1.53, 5.80), 0.01 unit increase in urinary albumin (95% CI: 0.002, 0.01), and 0.07 unit increase in ACR (95% CI: 0.01, 0.13). However, no hormonal, renal, and hepatic parameters were associated with Cd or Hg. Oxidative DNA damage did not mediate exposure-outcome relationships (p≥0.05). Our data indicate e-waste exposure impairs liver and renal functions secondary to elevated Pb levels. Continuous monitoring, longitudinal studies to evaluate the dose-response relationship and effective control measure are required to protect workers from e-waste exposure.

Sequence based model using deep neural network and hybrid features for identification of 5-hydroxymethylcytosine modification.

RNA modifications are pivotal in the development of newly synthesized structures, showcasing a vast array of alterations across various RNA classes. Among these, 5-hydroxymethylcytosine (5HMC) stands out, playing a crucial role in gene regulation and epigenetic changes, yet its detection through conventional methods proves cumbersome and costly. To address this, we propose Deep5HMC, a robust learning model leveraging machine learning algorithms and discriminative feature extraction techniques for accurate 5HMC sample identification. Our approach integrates seven feature extraction methods and various machine learning algorithms, including Random Forest, Naive Bayes, Decision Tree, and Support Vector Machine. Through K-fold cross-validation, our model achieved a notable 84.07% accuracy rate, surpassing previous models by 7.59%, signifying its potential in early cancer and cardiovascular disease diagnosis. This study underscores the promise of Deep5HMC in offering insights for improved medical assessment and treatment protocols, marking a significant advancement in RNA modification analysis.

Assessment of Patient Satisfaction and Functional Outcomes in Orthognathic Surgery.

Background: Orthognathic surgery is a surgical procedure performed to correct severe jaw misalignments that can affect a patient's facial aesthetics and functional occlusion. While the primary goal of orthognathic surgery is to improve functional outcomes and facial appearance, it is essential to assess patient satisfaction as a crucial aspect of overall treatment success. Materials and Methods: Patient selection: We conducted a prospective study involving 50 patients who underwent orthognathic surgery. All patients had a confirmed diagnosis of severe jaw misalignment, as determined by clinical and radiographic assessments. The surgical procedures performed included maxillary advancement, mandibular setback, or a combination of both, depending on the patient's specific diagnosis. Preoperative orthodontic treatment was provided to align the teeth and prepare the patient for surgery. Patients were evaluated preoperatively and at postoperative intervals of 3 months, 6 months, and 1 year. Results: Patient satisfaction scores and functional outcomes were as follows: aesthetics of facial profile (1-year post-op): mean score = 4.6, chewing function (1-year post-op): mean score = 4.4, speech function (1-year post-op): mean score = 4.3, and overall satisfaction with surgical outcome (1-year post-op): mean score = 4.5. Objective assessments revealed a significant improvement in occlusion and facial aesthetics. The mean reduction in overjet was 4.8 mm, and the mean reduction in overbite was 3.2 mm. Additionally, the mean postoperative ANB angle improved by 3.7°, indicating a better facial balance. Conclusion: Orthognathic surgery in our cohort of 50 patients resulted in high levels of patient satisfaction with both functional outcomes and facial aesthetics. Objective measurements also indicated significant improvements in occlusion and facial balance.

The Effect of Early Orthodontic Treatment on Long-Term Stability of Class II Malocclusions.

Background: Class II malocclusions are a common dental issue characterized by the misalignment of the upper and lower teeth. Early orthodontic treatment is often considered to correct these malocclusions, but its long-term effectiveness remains unclear. Materials and Methods: In this study, we examined the impact of early orthodontic treatment on the long-term stability of Class II malocclusions. We conducted a retrospective analysis of dental records from a sample of 150 patients who had received early orthodontic treatment for Class II malocclusions. The treatment involved braces and other orthodontic appliances. We compared their dental measurements before and after treatment, with a follow-up period of 5 years. Results: Our analysis revealed that the early orthodontic treatment led to a significant improvement in the alignment of upper and lower teeth, as indicated by a reduction in the overjet (the horizontal distance between upper and lower incisors). The mean overjet reduction was 3.2 millimeters. Furthermore, the Angle's Class II molar relationship was corrected in 80% of the cases. Conclusion: Early orthodontic treatment for Class II malocclusions demonstrated positive long-term stability, as evidenced by a reduction in overjet and improvement in molar relationships.

Effectiveness of Early Intervention with Palatal Expansion Versus Late Orthodontic Treatment for Correcting Maxillary Crowding.

Background: Maxillary crowding is a common orthodontic issue that can impact a patient's oral health and overall well-being. The timing of orthodontic treatment plays a crucial role in achieving optimal results. Materials and Methods: Thirty patients who received early intervention with palatal expansion (Group A) and 30 patients who underwent late orthodontic treatment (Group B) were included in this study. The age range for Group A was 8-10 years, while Group B had an age range of 16-18 years. Pretreatment and posttreatment records, including dental models and cephalometric radiographs, were analyzed to assess the effectiveness of the respective treatments. Results: In Group A, the mean duration of treatment was 12 months, and the maxillary crowding was corrected by an average of 4.5 mm. In Group B, the mean treatment duration was 24 months, and maxillary crowding was corrected by an average of 3.2 mm. The early intervention group (Group A) exhibited a statistically significant reduction in treatment duration and greater correction of maxillary crowding compared to the late orthodontic treatment group (Group B) (P < 0.05). Conclusion: Early intervention with palatal expansion is an effective approach for correcting maxillary crowding, leading to shorter treatment duration and greater improvement compared to late orthodontic treatment.

Prognostic Value of Hyperglycemia and Insulin Resistance Among Patients with Confirmed COVID-19 Infections at Admission to the Alexandria Fever Hospital, Egypt.

Background: The interaction between COVID-19 infection, hyperglycemia, and insulin resistance (IR) may lead to poor outcome. Methods: This prospective study included 100 adult participants without diabetes attending Alexandria Fever Hospital with confirmed COVID-19 infections. They were classified into four groups according to disease severity using World Health Organization (WHO) criteria. Demographic and clinical parameters were collected. Laboratory investigations were obtained. Another follow-up fasting plasma glucose (FPG) value was measured after 3 months in cured patients. Results: Admission FPG, follow-up FPG, lipid profile, markers of IR, and inflammation were significantly higher in severe and critical cases than in mild and moderate cases with increasing values with increased severity. Furthermore, these parameters were significantly higher in died cases compared with cured cases. Admission FPG, TyG index, and homeostatic model assessment (HOMA)-IR showed significant positive correlations with follow-up FPG. Admission FPG was the only independent mortality predictor in multivariate analysis (P = 0.027) with 1.7-folds increased mortality risk with each 10 mg/dL increments. Values exceeding 117 mg/dL, 2.2, and 6.33 for admission FPG, HOMA-IR, and Fasting Insulin Resistance Index, respectively, were able to predict mortality in the studied sample. Conclusions: These results will help in identifying patients at high risk of severe infection and death at admission and take early actions to improve outcome.

Chemotherapeutic potential of betanin/capecitabine combination targeting colon cancer: experimental and bioinformatic studies exploring NFκB and cyclin D1 interplay.

Introduction: Betanin (C24H26N2O13) is safe to use as food additives approved by the FDA with anti-inflammatory and anticancer effects in many types of cancer cell lines. The current experiment was designed to test the chemotherapeutic effect of the combination of betanin with the standard chemotherapeutic agent, capecitabine, against chemically induced colon cancer in mice. Methods: Bioinformatic approach was designed to get information about the possible mechanisms through which the drugs may control cancer development. Five groups of mice were assigned as, (i) saline, (ii) colon cancer, (iii) betanin, (iv) capecitabine and (v) betanin/capecitabine. Drugs were given orally for a period of six weeks. Colon tissues were separated and used for biological assays and histopathology. Results: In addition, the mRNA expression of TNF-α (4.58-fold), NFκB (5.33-fold), IL-1ß (4.99-fold), cyclin D1 (4.07-fold), and IL-6 (3.55-fold) and protein levels showed several folds increases versus the saline group. Tumor histopathology scores in the colon cancer group (including cryptic distortion and hyperplasia) and immunostaining for NFκB (2.94-fold) were high while periodic-acid Schiff staining demonstrated poor mucin content (33% of the saline group). These pathologic manifestations were reduced remarkably in betanin/capecitabine group. Conclusion: Collectively, our findings demonstrated the usefulness of betanin/capecitabine combination in targeting colon cancer and highlighted that betanin is a promising adjuvant therapy to capecitabine in treating colon cancer patients.

Enhancement of cellulolytic enzyme production from intrageneric protoplast fusion of Aspergillus species and evaluating the hydrolysate scavenging activity.

BACKGROUND: Lignocellulosic biomass provides a great starting point for the production of energy, chemicals, and fuels. The major component of lignocellulosic biomass is cellulose, the employment of highly effective enzymatic cocktails, which can be produced by a variety of microorganisms including species of the genus Aspergillus, is necessary for its utilization in a more productive manner. In this regard, molecular biology techniques should be utilized to promote the economics of enzyme production, whereas strategies like protoplast fusion could be employed to improve the efficacy of the hydrolytic process. RESULTS: The current study focuses on cellulase production in Aspergillus species using intrageneric protoplast fusion, statistical optimization of growth parameters, and determination of antioxidant activity of fermentation hydrolysate. Protoplast fusion was conducted between A. flavus X A. terreus (PFFT), A. nidulans X A. tamarii (PFNT) and A. oryzae X A. tubingensis (PFOT), and the resultant fusant PFNT revealed higher activity level compared with the other fusants. Thus, this study aimed to optimize lignocellulosic wastes-based medium for cellulase production by Aspergillus spp. fusant (PFNT) and studying the antioxidant effect of fermentation hydrolysate. The experimental strategy Plackett-Burman (PBD) was used to assess how culture conditions affected cellulase output, the best level of the three major variables namely, SCB, pH, and incubation temperature were then determined using Box-Behnken design (BBD). Consequently, by utilizing an optimized medium instead of a basal medium, cellulase activity increased from 3.11 U/ml to 7.689 U/ml CMCase. The following medium composition was thought to be ideal based on this optimization: sugarcane bagasse (SCB), 6.82 gm; wheat bran (WB), 4; Moisture, 80%; pH, 4; inoculum size, (3 × 106 spores/ml); and incubation Temp. 31.8 °C for 4 days and the fermentation hydrolysate has 28.13% scavenging activities. CONCLUSION: The results obtained in this study demonstrated the significant activity of the selected fusant and the higher sugar yield from cellulose hydrolysis over its parental strains, suggesting the possibility of enhancing cellulase activity by protoplast fusion using an experimental strategy and the fermentation hydrolysate showed antioxidant activity.

Disease prognosis and therapeutic strategies in patients with advanced non-small cell lung cancer (NSCLC): a 6-year epidemiological study between 2015-2021.

Background: Lung cancer is the top cause of mortality in males and the second largest cause of cancer-related fatalities in women worldwide. Non-small cell lung cancer (NSCLC) cases are discovered at an advanced stage, raising major challenges in disease management and survival outcomes. This study aimed to investigate the clinical findings and management of stage IIIB and IV NSCLC patients for better decision-making, disease management, and understanding of this fatal disease. Methods: In this cohort study of 340 patients, a total of 140 (41.2%) were diagnosed with advanced-stage NSCLC at a mean age of 64 years. The electronic data of patients from 2015 to 2021 who met the inclusion criteria were retrieved from two tertiary hospitals in Riyadh, Saudi Arabia, and an Excel sheet was used to record the variables. Patients' data including all categorical variables such as gender, stage, metastasis, ALK, EGFR, and ROS, etc., and continuous variables such as age and body mass index (BMI) were retrieved and analyzed. Results: The multivariate Cox-regression model indicated that smoking was the significant risk factor of death for two-thirds of male smokers (37.9%), with a median survival time of 123 days. Disease progression was higher with pleural and brain metastasis, and localized metastasis was the highest in 75% of patients. The intent of treatment was mainly palliative, however, a statistically significant association was found with the simultaneous use of chemotherapy and immunotherapy. Patients' response to first-line treatment revealed a significant improvement if chemotherapy treatment was maintained at the same dose without interruption of dosage. Conclusions: The overall cure and survival rates for NSCLC remain low, particularly in metastatic disease. Therefore, continued research into new drugs and combination therapies is required for better decision-making to expand the clinical benefit to a broader patient population and to improve outcomes in NSCLC.

Adjustment of model misspecification in estimation of population total under ranked set sampling through balancing.

In the model-based approach, researchers assume that the underlying structure, which generates the population of interest, is correctly specified. However, when the working model differs from the underlying true population model, the estimation process becomes quite unreliable due to misspecification bias. Selecting a sample by applying the balancing conditions on some functions of the covariates can reduce such bias. This study aims at suggesting an estimator of population total by applying the balancing conditions on the basis functions of the auxiliary character(s) for the situations where the working model is different from the underlying true model under a ranked set sampling without replacement scheme. Special cases of the misspecified basis function model, i.e. homogeneous, linear, and proportional, are considered and balancing conditions are introduced in each case. Both simulation and bootstrapped studies show that the total estimators under proposed sampling mechanism keep up the superiority over simple random sampling in terms of efficiency and maintaining robustness against model failure.

Perceived Neighborhood Characteristics and Sleep in Australian Adults.

BACKGROUND: Poor sleep can contribute to poorer health and socioemotional outcomes. Sleep health can be influenced by a range of individual and other socioecological factors. Perceptions of neighborhood physical and social characteristics reflect broader social-level factors that may influence sleep, which have not been well studied in the Australian context. This study examined the association between perceived neighborhood characteristics and sleep in a large sample of Australians. METHODS: Data were from 9,792 people aged 16 years or older, from Waves 16 and 17 of the nationally representative Household, Income and Labour Dynamics in Australia Survey. Associations between perceived neighborhood characteristics (neighborly interaction and support, environmental noise, physical condition, and insecurity) and self-reported sleep duration, sleep disturbance, and napping were examined using multiple logistic regression models. RESULTS: "Neighborhood interaction and support" and "neighborhood physical condition" were not significantly associated with any sleep outcomes after adjusting for relevant covariates. However, "environmental noise" and "neighborhood insecurity" remained significantly associated with sleep duration and sleep disturbance. None of the neighborhood characteristics were associated with napping. Furthermore, associations did not significantly vary by gender. CONCLUSIONS: This study highlights the potential benefit of public health policies to address noise and safety in neighborhoods to improve sleep.

Uncovering the impact of mega-scale shipbreaking yards on soil and crop quality in Bangladesh: A spatiotemporal dynamics and associated health risks of metal/loid contamination.

The uncontrolled release of harmful metal/loids from mega-scale shipbreaking activities in Bangladesh is a significant concern. This study investigated the impact of shipbreaking activities on soil and crop quality and human health in relation to metal/loid contamination. This work covered an area of 1221 km2 surrounding the shipbreaking yards in Chittagong during the wet and dry seasons between 2019 and 2020. Amongst the sixteen elements measured, the concentrations of Pb, Cd, As, V, Cr, Mn, Cu, Zn, Fe, Co, Ni, and Sn in the soil, rice, and vegetables from the four exposure sites were significantly higher compared to the control site in both seasons. Soil pollution indices indicated moderate to higher contamination levels of Pb, Zn, Cd, As, and Se in 30-50% of soil, supporting their accumulation in food crops. Source apportionment analysis identified uncontrolled shipwrecking operations as the primary anthropogenic activity mainly contributing to metal/loid pollution. Health risk analysis showed inorganic arsenic (estimated), Cd, and Pb in food crops could pose potential health threats to the general population. Spinach leaf and gourd were identified as the highest-risk contributing vegetables in the dry and wet seasons. These findings help to inform management strategies to protect agroecosystems and public health.