Antileishmanial potentials of azacitidine and along with meglumine antimoniate on Leishmania major: In silico prediction and in vitro analysis.

This study aimed to investigate the in vitro and in silico antileishmanial activity of azacitidine (AZA) on Leishmania major promastigotes and amastigotes. The in silico method was used to evaluate the possibility of the interaction of AZA into the binding pocket of inducible nitric oxide synthase (iNOS), a leading defensive oxidative metabolite. Following that, in vitro anti-promastigote, and anti-amastigote activity of AZA was determined using an MTT assay and a macrophage model, respectively. Cytotoxic effects of AZA and meglumine antimoniate (MA) were also assessed by MTT assay on murine macrophages. All experiments were performed in triplicate. The results showed that AZA interacted with Ser133, Gln134, and Lys13 amino acids of iNOS, and the molecular docking score was obtained at -241.053 kcal/mol. AZA in combination with MA significantly (P<0.001) inhibited the growth rate of nonclinical promastigote (IC50 247.6±7.3 µM) and 8.5-fold higher of clinical intramacrophage amastigote stage (29.8±5.3 µM), compared to the untreated group. A significant upsurge of Th1 subsets and transcription genes and a meaningful decline in Th2 cytokines subclasses at the equivalent concentrations of AZA and MA was observed (P<0.001). The apoptosis effect of AZA along with MA was significantly induced on L. major in a dose-dependent manner (P<0.001). The present study demonstrated that AZA possesses antileishmanial activity in in vitro and in silico models. However, AZA combined with MA was more effective than AZA alone in inhibiting the growth rate of promastigotes and amastigotes of L. major. This study indicates that AZA in combination with MA demonstrated a potent antileishmanial mechanism, promoting immune response and enhancing an immunomodulatory role toward the Th1 pathway. This experimental study is a basic study for applying more knowledge about the mechanisms of AZA along with MA in animal models in the future.

The association between exposure to polycyclic aromatic hydrocarbons and birth outcomes: A systematic review and meta-analysis of observational studies.

Exposure to polycyclic aromatic hydrocarbons (PAHs) has been linked to adverse birth outcomes; however, to date, the available studies on such relations, with the exception of birth weight, has not been systematically synthesized. We conducted a systematic review and meta-analysis of the available observational studies on the association of maternal exposure to PAHs and their metabolites during pregnancy with indicators of fetal growth and gestational age at delivery. We searched Web of Science, PubMed and Scopus systematically for all relevant published papers in English until 13 January 2023. Random effects meta-analysis was applied to synthesize the association estimates. Publication bias was assessed using Egger's regression. A total of 31 articles were included in our review (n = 703,080 participants). Our quality assessment of reviewed papers showed that 19 research had excellent, nine had good, and three had fair quality. Most of the reviewed studies on exposure to PAHs and their metabolites with gestational age and preterm birth (seven studies) reported no statistically significant association. Eight studies were eligible for our meta-analysis. Results of the meta-analysis indicated that higher levels of maternal urinary 1-OHP was associated with lower birth weight, birth length and head circumference and a higher risk of low birth weight (LBW). However, these associations were not statistically significant. Similarly, the combined association between maternal urinary 1-OHP and newborn's Ponderal index (PI) and Cephalization index were not statistically significant. Overall, our systematic review and meta-analysis suggested a potential adverse impact of exposure to PAHs on LBW, HC, and CC; however, further studies are required to be able to draw concrete conclusions on such associations.

Fabrication and characterization of lipopeptide biosurfactant-based electrospun nanofibers for use in tissue engineering.

Nanofibers are a class of nanomaterial with specific physicochemical properties and characteristics making them quite sought after and investigated by researchers. Lipopeptide biosurfactant (LPB) formulation properties were previously established in wound healing. LPB were isolated from in vitro culture of Acinetobacter junii B6 and loaded on nanofibers formulation produced by electrospinning method with different ratios of carboxymethylcellulose (CMC), polyvinyl alcohol (PVA), and Poloxamer. Numerous experimental control tests were carried out on formulations, including physicochemical properties which were evaluated by using dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FT-IR), morphology study by scanning electron microscopy (SEM), and thermal stability. The best nanofibers formulation was obtained by the electrospinning method, with a voltage of 19.8 volts, a discharge capacity of 1cm/h, a cylindrical rotating velocity of 100rpm, and a needle interval of 7cm from the cylinder, which continued for 7hours. The formulation contained 2% (w/v) CMC, 10% (w/v) poloxamer, 9% (w/v) PVA, and 5% (w/v) LPB. This formula had desirable physicochemical properties including spreadability, stability, and uniformity with the particle size of about 590nm.

A study on exposure to greenspace during pregnancy and lipid profile in cord blood samples.

Although evidence reporting the beneficial associations of prenatal greenspace exposure with pregnancy outcomes is increasing, there is still a lack of evidence on the potential association of such exposure to greenspace on fetal lipid profile. We aimed to first-time investigate the associations between prenatal exposure to greenspace and lipid levels in the cord blood. The present study was based on data from 150 expectant mothers, residents of Sabzevar city in Iran (2018). For each participant, we identified exposure to greenspace in residential surroundings, residential accessibility to green space, use of green spaces, and the number of plant pots inside the home. Measures of levels of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and TC/HDL-C and TG/HDL-C ratios in samples of cord blood were applied to identify the lipid profile. We developed adjusted linear regression models to estimate the associations of each indicator of greenspace exposure with each cord blood lipid. We found increased greenspace in residential surroundings across a 100 m buffer, higher residential accessibility to green space, and more use of green spaces were associated with decreased cord blood lipid levels. The remainder findings regarding the greenspace in residential surroundings across 300 m and 500 m buffers and the number of plant pots were null. Some suggestions were observed for a potential mediatory role of air pollution. This study suggests that greenspace exposure during pregnancy may influence positively fetal lipid levels in the cord blood.

Impact of HSP90α, CEA, NSE, SCC, and CYFRA21-1 on Lung Cancer Patients.

Lung cancer is a lethal disease, and early diagnosis with the aid of biomarkers such as HSP90α protein can certainly assist the doctors to start treatment of patient at the earliest and can save their lives. To analyse the diagnostic value of HSP90α expression in lung cancer patients by collecting data of patients through IoT devices to avoid delay in treatments, a study has been presented in this paper where the significance of HSP90α biomarker is highlighted in early diagnosis of patients suffering from lung cancer. The second objective of the research study is to examine the correlation between the appearance level of HSP90α biomarker and the clinicopathological features of lung cancer. It is also evaluated whether the changes in HSP90α index are indicative or noteworthy before and after surgery of lung cancer patients. An observatory study of 78 patients with lung cancer in Qinhuangdao Hospital is presented in this paper where the samples were collected from June 2018 to March 2020. Their data were collected through IoT devices used in the latest healthcare facilities of the hospital. The ELISA method was utilized to identify the level of plasma HSP90 and to analyse HSP90 levels between the lung cancer group and healthy group of people. The relationship between HSP90 and the clinical pathological features of 78 patients suffering from lung cancer was analysed. An electrochemical luminescence method was used to detect CEA, NSE, SCC, and CYFRA21-1 levels. ROC curve and box plots were used to determine the analytic value of HSP90 and other biomarkers used in lung cancer diagnosis. Forty-two patients with moderate to early stage lung cancer with surgical correction were selected, and paired sample T test was used to analyse HSP90 levels before and after surgery. The plasma HSP90 level of lung cancer patients was quite higher as compared to the group of healthy people as per the values depicted in the research study. Second, HSP90 levels are substantially higher in pathologic type, differentiation degree, stage, and the existence of the lung, liver, and bone metastases (P < 0.05). The level of HSP90 expression was largely impacted by a few factors such as sex, age, smoking, and tumour location (P > 0.05). The ROC value for HSP90 was 0.599, while the area under the curve of HSP90 combined with other four tumour markers was 0.915 in the presented case study, indicating the presence of lung cancer. Patients with lung cancer had statistically significant differences in HSP90 expression levels before and after surgery (P < 0.05). It is concluded that the expression level of plasma HSP90α in lung cancer patients increases remarkably; therefore, HSP90 can be used to monitor presence of lung cancer before and after surgery in the patients.

Machine Learning-Based Ensemble Model for Zika Virus T-Cell Epitope Prediction.

Zika virus (ZIKV), the causative agent of Zika fever in humans, is an RNA virus that belongs to the genus Flavivirus. Currently, there is no approved vaccine for clinical use to combat the ZIKV infection and contain the epidemic. Epitope-based peptide vaccines have a large untapped potential for boosting vaccination safety, cross-reactivity, and immunogenicity. Though many attempts have been made to develop vaccines for ZIKV, none of these have proved to be successful. Epitope-based peptide vaccines can act as powerful alternatives to conventional vaccines due to their low production cost, less reactogenic, and allergenic responses. For designing an effective and viable epitope-based peptide vaccine against this deadly virus, it is essential to select the antigenic T-cell epitopes since epitope-based vaccines are considered safe. The in silico machine-learning-based approach for ZIKV T-cell epitope prediction would save a lot of physical experimental time and efforts for speedy vaccine development compared to in vivo approaches. We hereby have trained a machine-learning-based computational model to predict novel ZIKV T-cell epitopes by employing physicochemical properties of amino acids. The proposed ensemble model based on a voting mechanism works by blending the predictions for each class (epitope or nonepitope) from each base classifier. Predictions obtained for each class by the individual classifier are summed up, and the class with the majority vote is predicted upon. An odd number of classifiers have been used to avoid the occurrence of ties in the voting. Experimentally determined ZIKV peptide sequences data set was collected from Immune Epitope Database and Analysis Resource (IEDB) repository. The data set consists of 3,519 sequences, of which 1,762 are epitopes and 1,757 are nonepitopes. The length of sequences ranges from 6 to 30 meter. For each sequence, we extracted 13 physicochemical features. The proposed ensemble model achieved sensitivity, specificity, Gini coefficient, AUC, precision, F-score, and accuracy of 0.976, 0.959, 0.993, 0.994, 0.989, 0.985, and 97.13%, respectively. To check the consistency of the model, we carried out five-fold cross-validation and an average accuracy of 96.072% is reported. Finally, a comparative analysis of the proposed model with existing methods has been carried out using a separate validation data set, suggesting the proposed ensemble model as a better model. The proposed ensemble model will help predict novel ZIKV vaccine candidates to save lives globally and prevent future epidemic-scale outbreaks.

Dietary pattern and telomere length in preschool children in a middle-income country.

Telomere length (TL) has been associated with lifestyle and dietary pattern. However, the available evidence on this association in children is scarce, especially in low- and middle-income countries (LMICs). Therefore, this study aimed to evaluate the association of dietary pattern and leukocyte TL (LTL) in preschool children, Sabzevar, Iran (2017). This cross-sectional study was based on 187 preschool children (aged 5 to 7) recruited from 27 kindergartens. Nutrition information including amounts of consumed dairy products, meat and processed meat products, nuts and seeds, white bread and refined grains, fruits, vegetables, simple sugars, fats and drinks was obtained through a questionnaire. Linear mixed-effects models were fitted with polymerase chain reaction (PCR) plate ID and kindergartens as random effects to estimate the association of each food group consumption with LTL, controlled for relevant covariates. Higher consumption of dairy products and sugar was associated with shorter LTL (ß = -0.180, 95% confidence interval [CI]: -0.276, -0.085, P value <0.001 and ß = -0.139, 95% CI: -0.193, -0.086, P value <0.001, respectively). An increase in consumption of fish, nuts and seeds, coloured fruits, green leafy vegetables, cruciferous vegetables and olive was significantly associated with the increase in relative LTL. The associations for the consumption of legumes, other fruits, yellow and orange vegetables, red meat, egg, white bread and refined grains, solid and liquid fats, processed meats, potato chips, carbonated drinks, tea (black) and soft drinks groups were not statistically significant. Our findings showed that there was an association between the consumption of certain food groups with LTL.

Polycyclic aromatic hydrocarbons exposures and telomere length: A cross-sectional study on preschool children.

Exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with shorter telomere length (TL), a marker of ageing at cellular level. However, the available evidence on this association among children is still scarce. We therefore aimed to assess, the relationship between urinary 1-hydroxipayrene (1-OHP), a marker of exposure to PAHs, and relative leukocyte TL (LTL) in children at preschool age. Our study was based on 200 children enrolled from 27 randomly-selected kindergartens in the city of Sabzevar, Iran (2017). 1-OHP levels in the participants' urine samples were measured using solid phase extraction (SPE) method and high-performance liquid chromatography (HPLC). Moreover, real-time PCR was used to measure the LTL in the participants' blood samples. Linear mixed effects models, controlled for relevant covariates, were applied to investigate the association of 1-OHP concentration and LTL. The median (interquartile range (IQR)) of relative LTL and urinary 1-OHP were 0.83 (0.7) and 257 (375.5) ng/L, respectively. In the fully adjusted model, an IQR increase in urinary 1-OHP was related to -0.05 (95% confidence interval (CI): 0.09, -0.01, P-value = 0.02) decrease in relative LTL. This association was similar among boys and girls; however, we observed indications for a stronger association for those children whose parents had university education. Our study suggested an inverse relationship between urinary 1-OHP and LTL in children at preschool age. However, further longitudinal research with repeated measures of PAHs and LTL are needed to confirm these findings.

Maternal exposure to air pollution and umbilical asprosin concentration, a novel insulin-resistant marker.

Air pollution exposure during pregnancy has been associated with abnormal glucose hemostasis in the fetus, which may result in the programming of type 2 diabetes mellitus (T2DM) development in future life. Therefore, we investigated the association of maternal exposure to particulate matters (PMs) and traffic indicators with umbilical asprosin concentration, a novel insulin-resistant inducing adipokine, in newborns. Accordingly, 759 mother-newborn pairs from Sabzevar, Iran (2018-2019) participated in our study. Maternal exposure to PM1, PM2.5 and PM10 concentrations was estimated using spatial-temporal models developed for the study area. The associations of exposure to traffic indicators (total street length in 100, 300 and 500 m buffers around home and proximity of mothers to nearest major roads) and air pollution with umbilical asprosin concentration were estimated using linear regression models, adjusted for potential confounders. The median (interquartile range (IQR)) of umbilical asprosin concentration was 30.4 (19.1) ng/mL. In fully adjusted models, each one IQR increase in PM10 and PM2.5 were associated with 26.43 ng/mL (95% CI: 10.97, 41.88) and 31.76 ng/mL (95% CI: 15.66, 47.86) increase in umbilical asprosin concentration, respectively. A similarity result was observed for total street length in 100 m buffer. An increase in proximity to major roads was associated with a decrease of -21.48 ng/mL (95% CI: 33.29, -9.67) in umbilical asprosin concentration. Our results suggested that maternal exposure to air pollution during pregnancy could increase the umbilical asprosin concentration. These novel findings may improve our understanding of the mechanisms whereby air pollutants impaired glucose hemostasis during the fetal period.

Effects of Salvia miltiorrhiza and Radix astragali on the TGF-ß/Smad/Wnt pathway and the pathological process of liver fibrosis in rats.

Traditional Chinese medicine has made some progress in the study of liver fibrosis, and provides valuable experience for clinical treatment of liver fibrosis. The aim of this study was to investigate the rationality of compatibility use of Salvia miltiorrhiza and Radix astragali on liver fibrosis in rats. For this purpose, the rat model of liver fibrosis was treated with single or different compatibilities of herbals extracts for 4 weeks. Saline and colchicine were set as a negative and positive control, respectively. Liver histopathology, liver function, and expressions of key proteins in the TGF-ß/Smad/Wnt pathway were assessed. Results showed that compared with colchicine, herbal extracts showed better ability to reduce deposition of α-SMA and type I collagen, and improve liver function. The effect of R. astragali extracts and 1:1 compound on improving liver fibrosis and liver function was relatively better than other treatment options. The compound groups showed a particularly significant effect on reducing Cyclin D1 expression. It was concluded that the 1:1 compatibility use of S. miltiorrhiza extracts and R. astragali extracts can preferably attenuate liver fibrosis by regulating the expression of TGF-ß1 and Cyclin D1.