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Abstract Background Previous studies from the US and UK suggest that neighbourhood ethnic composition is associated with health, positive or negative, depending on the health outcome and ethnic group. We examined the association between neighbourhood ethnic composition and self-reported health in these groups in Amsterdam, and we aimed to explore whether there is spatial variation in this association. Methods We used micro-scale data to describe the ethnic composition in buffers around the home location of 2701 Turks and 2661 Moroccans. Multilevel regression analysis was used to assess the association between three measures of ethnic composition (% co-ethnics, % other ethnic group, Herfindahl index) and three measures of self-reported health: self-rated health, Physical and Mental Component Score (PCS, MCS). We adjusted for socioeconomic position at individual and area level. We used geographically weighted regression and spatially stratified regression analyses to explore whether associations differed within Amsterdam. Results Ethnic heterogeneity and own ethnic density were not related to self-rated health for both ethnic groups. Higher density of Turks was associated with better self-rated health among Moroccans at all buffer sizes, with the most significant relations for small buffers. Higher heterogeneity was associated with lower scores on PCS and MCS among Turks (suggesting worse health). We found spatial variation in the association of the density of the other ethnic group with self-rated health of Moroccans and Turks. We found a positive association for both groups, spatially concentrated in the sub-district Geuzenveld. Conclusions Our study showed that the association of ethnic composition with self-reported health among Turks and Moroccans in Amsterdam differed between the groups and reveals mainly at small spatial scales. Among both groups, an association of higher density of the other group with better self-rated health was found in a particular part of Amsterdam, which might be explained by the presence of a relatively strong sense of community between the two groups in that area. The study suggests that it is important to pay attention to other-group density, to use area measurements at small spatial scales and to examine the spatial variation in these associations. This may help to identify neighbourhood characteristics contributing to these type of area effects on urban minority health.

BackgroundTo integrate immigrants into their societies, European countries have adopted different types of policies, which may influence health through both material and psychosocial determinants. Recent studies have suggested poorer health outcomes for immigrants living in countries with poorly rated integration policies.ObjectiveTo analyse mortality differences of immigrants from the same country of origin living in countries with distinct integration policy contexts.MethodsFrom the mortality dataset collected in the Migrant Ethnic Health Observatory (MEHO) project, we chose the Netherlands (linked data from 1996-2006), France (unlinked; 2005-2007) and Denmark (linked; 1992-2001) as representatives of the inclusive, assimilationist and exclusionist policy models, respectively, based on the Migrant Integration Policy Index. We calculated for each country sex- and age-standardized mortality rates for Turkish-, Moroccan- and local-born populations aged 20-69 years. Poisson regression was used to estimate the mortality rate ratios (MRRs) for cross-country and within-country comparisons. The analyses were further stratified by age group and cause of death.ResultsCompared with their peers in the Netherlands, Turkish-born immigrants had higher all-cause mortality in Denmark (MRR men 1.92; 95% CI 1.74-2.13 and women 2.11; 1.80-2.47) but lower in France (men 0.64; 0.59-0.69 and women 0.58; 0.51-0.67). A similar pattern emerged for Moroccan-born immigrants. The relative differences between immigrants and the local-born population were also largest in Denmark and lowest in France (e.g., Turkish-born men MRR 1.52; 95% CI 1.38-1.67 and 0.62; 0.58-0.66, respectively). These patterns were consistent across all age groups, and more marked for cardiovascular diseases.ConclusionsAlthough confounders and data comparability issues (e.g., French cross-sectional data) may affect the findings, this study suggests that different macro-level policy contexts may influence immigrants' mortality. Comparable mortality registration systems across Europe along with detailed socio-demographic information on immigrants may help to better assess this association.

Abstract Green synthesis is an easy, safe, and environmentally beneficial nanoparticle creation method. It is a great challenge to simultaneously improve the capping and stabilizing agent carrier separation efficiency of photocatalysts. Herein, Zn-doped Titanium dioxide (TiO2) nanoparticles with high exposure of 360 nm using a UV/visible spectrophotometer were prepared via a one-step hydrothermal decomposition method. A detailed analysis reveals that the electronic structures were modulated by Zn doping; thus, the responsive wavelength was extended to 600 nm, which effectively improved the visible light absorption of TiO2. We have optimized the different parameters like concentration, time, and temperature. The peak for TiO2 is located at 600 cm-1 in FTIR. A scanning electron microscope revealed that TiO2 has a definite shape and morphology. The synthesized Zn-doped TiO2NPs were applied against various pathogens to study their anti-bacterial potentials. The anti-bacterial activity of Zn-doped TiO2 has shown robust against two gram-ve bacteria (Salmonella and Escherichia coli) and two gram + ve bacteria (Staphylococcus epidermidis and Staphylococcus aureus). Synthesized Zn-doped TiO2 has demonstrated strong antifungal efficacy against a variety of fungi. Moreover, doping TiO2 nanoparticles with metal oxide greatly improves their characteristics; as a result, doped metal oxide nanoparticles perform better than doped and un-doped metal oxide nanoparticles. Compared to pure TiO2, Zn-doped TiO2 nanoparticles exhibit considerable applications including antimicrobial treatment and water purification.

Cola nitida, also known as Kola nut, is a tropical plant native to West Africa and has a rich history of traditional medicinal use. In this narrative review, we aim to provide an overview of the protective effects of Cola nitida in various health and disease states. Cola nitida has been traditionally used for its medicinal properties, and its bioactive compounds include caffeine, alkaloids, tannins, flavonoids, and phenolics. These compounds contribute to its potential therapeutic effects. Here, we examine the potential benefits of Cola nitida in several areas of health, discussing its role in cognitive function, cardiovascular health, immune system function, gastrointestinal health, and metabolic and endocrine health. Relevant original articles available from PubMed, African Journals Online (AJOL), SCOPUS, and Google Scholar were retrieved using the keywords “cola” AND “nitida” without date restriction until July 17, 2023. Evidence suggests that Cola nitida may have positive effects on health, with indications of adverse effects only from its chronic usage. However, more research is needed to establish its efficacy and safety. Cola nitida holds promise as a natural remedy for various health conditions. Understanding the benefits and limitations of Cola nitida will contribute to its effective utilization in health and disease management.

The tropical dry forests (TDF) have an enormously rich flora and fauna that offer various ecological services to the surrounding human societies. Biodiversity assessment is mandatory for implementing any sustainable forest management policy, which is why it is one of the important criteria and indicators currently used. Threats to TDF biodiversity are the primary challenges arising from environmental concerns caused by anthropogenic activity leading to global warming issues. The study aimed to investigate the vegetation assessment and several environmental and anthropogenic variables influencing forest biodiversity from 5 threatened forest sites of District Sialkot (Ghalotian, Kishan Garh, Daburgi Chanda Singh, Pir Kot, and Ghulab Garh), Pakistan. We collected 170 distinct plant species, including 135 dicots, 27 monocots, seven pteridophytes, and one bryophyte, categorized into 138 genera and 62 families, divided into 114 herbs, 32 trees, and 24 shrubs. The phytosociological analysis described the quantitative characteristics, including % frequency, % density, % cover, and importance Value Index (IVI) of all forest areas. Gulab Garh forest has the richest biodiversity forest area, and herbs are the dominant species that have been documented. Environmental factors such as temperature, precipitation, organic matter, soil pH, Ca+2, Mg+2, Na+, Cl−, and electric conductivity (EC) strongly affect forest vegetation investigated by principal coordinate analysis. Shannon and Simpson’s diversity indexes reveal that all sites contain loamy and sandy soil and display a significant relationship between alpha diversity and richness. Increasing trends in temperature and decreasing trends in rainfall suggested that climate significantly affects the Sialkot region’s plant biodiversity. SWOT analysis highlighted that population growth leads to increasing anthropogenic activities such as constructing housing societies and roads, inadequate farming, and excessive grazing, impacting the forest vegetation and altering TDF ecosystem properties/services and functioning. Our findings reinforce the vegetational assessment and importance of local forest biodiversity and significant environmental drivers that influence the plant species diversity in TDF areas. Future conservation strategies are suggested to reduce unlawful resource consumption, restore plant biodiversity in designated protected areas, and conserve rare species locally.

Continuous consumption of sachet and tap water in Nigeria is of public health significance as the potential bacterial water contaminants could develop resistance to commonly used antimicrobials. This study was carried out to assess the bacteriological quality and TLC-Bio autographic profile of water samples using M. oleifera leaf extract. One hundred samples comprising 50 sachets and 50 tap water were collected from five different locations in Katsina metropolis. Most probable number (MPN) was used to identify indicator bacteria and characterized using biochemical tests followed by 16S rRNA gene sequencing identification. The results showed that the pH and temperature level of all the samples were significantly different. Turbidity (0.2-0.47NTU), dissolved oxygen (1.34-2.03mg/L and 0.85-2.45mg/L) and biological oxygen demand (0.49-1.09mg/L and 0.19-0.59mg/L) were below the minimum permissible limits set by WHO and NAFDAC (=5). Total coliform counts exceeded limits of 2 MPN/100ml and Escherichia coli was detected from tap water of Kofar Marusa, Kofar Durbi and Kofar Kaura as well as the sachet water of Kofar Marusa and Kofar Keke. However, there was no statistically significant difference (P=0.05) between the total coliform counts of both sachet and tap water. The 16S rRNA gene identification showed the presence of Escherichia marmotae and Enterobacter kobei in both sachet and tap water. The GC-MS demonstrated that M. oleifera leaf extract contained 9,12,15-Octadecatrienoic acid, ethyl ester, Octadec-9-enoic acid and Hexadecanoic acid, The TLC-bioautography result indicate antibacterial activity, with inhibition zones ranging from 15±0.00 to 19.5±4.95mm (E. coli) to 23.5±6.36mm (E. faecalis) and 20±0.00 to 22±1.41mm (E. faecium). Waterborne faecal bacterial contaminants were found associated with the sachet and tap water analyzed. M. oleifera leaf has bioactive principles with nobility to be used as candidate for drug development. [ABSTRACT FROM AUTHOR]

This study delves into the application of Logistic Regression through a Voting Classifier to predict liver disease prevalence within the Indian demographic, specifically analyzing data from the NorthEast of Andhra Pradesh. Employing a dataset encompassing 584 patient records, the research utilizes a 5-fold cross-validation approach to evaluate the model's performance across accuracy, precision, recall, and F1-Score metrics. The findings reveal accuracy rates ranging from 69.23% to 74.14%, with variable precision and recall, indicating a promising yet improvable predictive capability of the model. The study significantly contributes to the existing body of knowledge by demonstrating the potential of Logistic Regression in medical diagnostics, especially in the context of liver disease, and highlighting the critical role of machine learning models in enhancing diagnostic processes. Through a detailed discussion, the research aligns with previous studies on the efficacy of machine learning in healthcare, advocating for the integration of more comprehensive data and suggesting further exploration into the model's applicability across diverse populations. The study's implications extend to healthcare professionals and policymakers, underscoring the necessity for advanced diagnostic tools in the early detection of liver diseases.

Abstract Objectives This study investigated whether exosomes from LPS pretreated bone marrow mesenchymal stem cells (LPS pre-MSCs) could prolong skin graft survival. Methods The exosomes were isolated from the supernatant of MSCs pretreated with LPS. LPS pre-Exo and rapamycin were injected via the tail vein into C57BL/6 mice allografted with BALB/c skin; graft survival was observed and evaluated. The accumulation and polarization of macrophages were examined by immunohistochemistry. The differentiation of macrophages in the spleen was analyzed by flow cytometry. For in vitro, an inflammatory model was established. Specifically, bone marrow-derived macrophages (BMDMs) were isolated and cultured with LPS (100 ng/ml) for 3 h, and were further treated with LPS pre-Exo for 24 h or 48 h. The molecular signaling pathway responsible for modulating inflammation was examined by Western blotting. The expressions of downstream inflammatory cytokines were determined by Elisa, and the polarization of macrophages was analyzed by flow cytometry. Results LPS pre-Exo could better ablate inflammation compared to untreated MSC-derived exosomes (BM-Exo). These loaded factors inhibited the expressions of inflammatory factors via a negative feedback mechanism. In vivo, LPS pre-Exo significantly attenuated inflammatory infiltration, thus improving the survival of allogeneic skin graft. Flow cytometric analysis of BMDMs showed that LPS pre-Exo were involved in the regulation of macrophage polarization and immune homeostasis during inflammation. Further investigation revealed that the NF-κB/NLRP3/procaspase-1/IL-1β signaling pathway played a key role in LPS pre-Exo-mediated regulation of macrophage polarization. Inhibiting NF-κB in BMDMs could abolish the LPS-induced activation of inflammatory pathways and the polarization of M1 macrophages while increasing the proportion of M2 cells. Conclusion LPS pre-Exo are able to switch the polarization of macrophages and enhance the resolution of inflammation. This type of exosomes provides an improved immunotherapeutic potential in prolonging graft survival.

Abstract Background Vascular malformations are common but complicated types of disease in infants, with unclear causes and lack of effective prevention. The symptoms usually do not disappear and tend to progress without medical intervention. It is extremely necessary to choose correct treatment options for different types of vascular malformations. A large number of studies have confirmed that sclerotherapy has a tendency to become the first-line treatment in near future, but it is also associated with mild or severe complications. Furthermore, to our knowledge, the serious adverse event of progressive limb necrosis has not been systematically analyzed and reported in the literature. Case presentation Three cases (two females and one male) were presented who were all diagnosed as vascular malformations and were treated by several sessions of interventional sclerotherapy. Their previous medical records showed the use of several sclerosants in different sessions including Polidocanol and Bleomycin. The sign of limb necrosis did not occur during the first sclerotherapy, but after the second and third sessions. Furthermore, the short-term symptomatic treatment could improve the necrosis syndrome, but could not change the outcome of amputation. Conclusion Sclerotherapy undoubtedly tends to be the first-line treatment in near future, but the adverse reactions still remain major challenges. Awareness of progressive limb necrosis after sclerotherapy and timely management by experts in centers of experience of this complication can avoid amputation.

Ensuring water potability is paramount for public health and safety. This research aimed to assess the efficacy of the Decision Tree classification algorithm in predicting water potability using the Water Quality and Potability dataset. Employing a 5-fold cross-validation technique, the model showcased a moderate performance with an average accuracy of approximately 54.33%. While the Decision Tree provides a baseline and interpretable mechanism for classification, the results emphasize the need for further exploration using more intricate models or ensemble methods. This study contributes to the broader effort of leveraging machine learning techniques for water quality assessment and provides insights into the potential and limitations of such models in predicting water safety