The association of in-utero exposure to air pollution and atherogenic index of plasma in newborns.

BACKGROUND: Prenatal exposure to particulate matter (PM) and traffic was associated with the programming of cardiovascular diseases (CVDs) in early life. However, the exact underlying mechanisms are not fully understood. Therefore, we aimed to evaluate the association between in-utero exposure to PMs and traffic indicators with the atherogenic index of plasma (AIP) in newborns, which is a precise index reflecting an enhancement of lipid risk factors for CVDs. METHODS: In this cross-sectional study, a total of 300 mother-newborn pairs were enrolled in Sabzevar, Iran. Spatiotemporal land-use regression models were used to estimate the level of PM1, PM2.5 and PM10 at the mother's residential address. The total length of streets in different buffers (100,300 and 500m) and proximity to major roads were calculated as indicators of traffic. The AIP of cord blood samples was calculated using an AIP calculator. Multiple linear regression models were used to examine the association of PM concentrations as well as traffic indicators with AIP controlled for relevant covariates. RESULTS: PM2.5 exposure was significantly associated with higher levels of AIP in newborns. Each interquartile range (IQR) increment of PM2.5 concentration at the mothers' residential addresses was associated with a 5.3% (95% confidence interval (CI): 0.0, 10.6%, P = 0.04) increase in the AIP. Associations between PM1, PM10 and traffic indicators with cord blood level of AIP were positive but not statistically significant. CONCLUSION: Our findings showed that in utero exposure to PM2.5 may be associated with CVDs programming through the increase of atherogenic lipids.

Distribution incidence, mortality of tuberculosis and human development index in Iran: estimates from the global burden of disease study 2019.

BACKGROUND: Tuberculosis is one of the most serious challenges facing the global healthcare system. This study aims to investigate the incidence and mortality of tuberculosis in Iran from 2010 to 2019 as well as its relationship with the human development index (HDI). METHODS: The present study is an ecological study aiming at investigating the incidence and mortality of tuberculosis in Iran during the years 2010 to 2019. The related data were extracted from the Global Burden of Disease (GBD) website. The spatial pattern attributed to tuberculosis in the provinces of Iran was analyzed using ArcGIS software. In this study, the two-variable correlation method was used to analyze the data extracted to study the correlation between Tuberculosis and HDI. RESULT: Based on the results recorded in GBD, the incidence of tuberculosis in 2010, that is, 14.61 (12.72, 16.74), declined compared to 2019, namely 12.29 (10.71, 14.09). The age-standardized mortality rate which was 1.63 (1.52, 1.73) in 2010, has decreased compared to 2019: 1.17 (1.07, 1.32). The incidence and mortality rates of tuberculosis in Iran in all age groups have decreased in 2019 compared to 2010. The highest incidence and mortality among tuberculosis patients were recorded in Sistan and Baluchistan and Golestan provinces. The results indicated that there was a negative and significant correlation between the mortality rate of tuberculosis and the human development index in 2010 (r = -0.509, P-value = 0.003) and 2019 (r = -0.36, P-value = 0.001); however, this correlation between incidence and human development index was not significant (p > 0.05). CONCLUSION: Since mortality is mostly observed in areas with low HDI, health system policymakers must pay more attention to these areas in order to improve care and perform screenings to diagnose and treat patients thus reducing the mortality rate of tuberculosis and preventing an increase in its incidence in Iran.

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.

The association of in-utero exposure to polycyclic aromatic hydrocarbons and umbilical liver enzymes.

BACKGROUND: The adverse health influences of polycyclic aromatic hydrocarbons (PAHs) exposures have been examined in several previous research. However, the evidence on the health influences of PAHs exposure during pregnancy and childhood is scarce, with no study on the infant's liver function. Therefore, in this study, the association of in-utero exposure to particulate matter-bound PAHs (PM-bound PAHs) on the umbilical liver enzymes was investigated. METHODS: A total of 450 mother-pair samples were assessed in this cross-sectional study in Sabzevar, Iran (2019-2021). The concentrations of PM-bound PAHs were estimated based on spatiotemporal models at residential addresses. The umbilical cord blood alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and gamma-glutamyl transferase (GGT) were measured as indicators of infant's liver function. The association of PM-bound PAHs with umbilical liver enzymes was evaluated using multiple linear regression, controlled for relevant covariates. The quantile g-computation (g-comp) was used to investigate the combined impact of the 15 PAHs on liver function biomarkers. RESULTS: Higher levels of total 4-ring PAHs, Dibenzo[a,h]anthrancene, Anthracene, Pyrene, Benzo[a]anthracene, Phenanthrene, Fluorene, Acenaphthylene and Naphthalene were associated with higher umbilical ALP. An increase in total 5-ring PAHs, Benzo[g,h,i]perylene, Benzo[a]pyrene and Chrysene was associated with higher umbilical AST levels. Each 1 ng/m3 increase in exposure to Benzo[g,h,i]perylene was related with 182.21 U/L (95 % CI: 116.11, 248.31, P < 0.01) increase in umbilical GGT. PAHs mixture exposure was positively associated with higher umbilical AST and ALT, while no significant associations were noted for ALP and GGT. We observed a potentially stronger association for girls compared to boys based on umbilical ALT and AST. However, for GGT and ALP, these associations were stronger for boys compared to girls. CONCLUSION: Overall our findings suggested that exposure to PAHs during pregnancy had adverse effects on infant's liver function.

The association between prenatal exposure to polycyclic aromatic hydrocarbons and childhood intelligence: a systematic review of observational studies.

Exposure to polycyclic aromatic hydrocarbons (PAHs) during pregnancy has been associated with many adverse child health. However, the evidence on such associations with child brain development was not reviewed systemically. Therefore, in this study, we systemically reviewed the observational studies on prenatal exposure to PAHs and childhood intelligence quotient (IQ). The Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines were applied to perform this review. We systematically searched Scopus, PubMed, and Web of Science for all relevant articles published in English until 15 October 2022. The quality of retrieved studies was evaluated based on the Gascon et al. method. We retrieved a total of 351 citations through the initial search, of which an overall of six articles ([Formula: see text] participants) were included in our final review. The quality assessment indicated that four studies had excellent and two studies had good quality. Three reviewed studies reported a significant negative association between prenatal exposure to PAHs and children's IQ. One study reported that exposure to PAHs combined with material hardship was associated with lower child IQ and one study indicated lower child IQ through lower LINE1 DNA methylation-related maternal exposure to PAHs. However, another study did not observe a significant association between prenatal PAH exposure and child IQ. Overall, our review indicated that exposure to PAHs during pregnancy has an adverse impact on childhood IQ.

The association of exposure to air pollution and depression in women; a cross-sectional study of a middle-income country.

Air pollution exposure has been related with mental disorders, especially depression; however, the available evidence on these associations in Low and Middle-Income Countries (LMICs) is scarce. Therefore, we aimed to assess the relationship between particulate matter (PM) exposure and indicators of traffic with depressive symptoms in women of Sabzevar, Iran. This cross-sectional study was based on 741 women aged 15-45 years (adults) in 2019. The annual average of PM10, PM2.5 and PM1 at home was estimated using land use regression (LUR) models. Street map of Sabzevar was used to calculate the indicators of traffic, i.e., the proximity to major roads and total street length buffers with 100, 300 and 500 m radii around the participants' homes. We used the Center for Epidemiological Studies- Depression (CESD-20) Scale in the general population to measure depression scores. Quasi-Poisson models and logistic regression were used to examine the association and odds ratios of exposure to air pollution and depression scores adjusted for relevant covariates. Exposure to PM10, PM2.5 and PM1 and total street length in 100 m buffer were significantly associated with higher depression scores. In fully adjusted model, an interquartile range (IQR) increase in PM10, PM2.5 and PM1 concentration as well as total street length in 100 m buffer was associated with 1.25 (95% CI:1.03, 1.52, P-value = 0.02), 1.16 (95% CI: 1.06, 1.26, P-value< 0.01), 1.16 (95% CI: 1.03, 1.29, P-Value = 0.01) and 1.15 (95% CI: 1.06, 1.25, P-value< 0.01) odds of clinical depression, respectively. For street length in 300 and 500 m buffers and proximity to major roads, no statistically significant increased risk of clinical depression were observed. Overall, our findings recommended that air pollution exposure has increased the risk of clinical depression in women.

The relationship between the serotonergic system and COVID-19 disease: A review.

COVID-19 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which led to a pandemic started in Wuhan, China, in 2019. The rapid spread of the disease in the world, unprecedented mortality rate, and lack of definitive treatment for the disease have led to a global effort to develop effective vaccines as well as new therapeutic interventions. Immune cells activation with excessive inflammation is an important pathophysiological feature of COVID-19 that may impair the various organs functions. Accordingly, these could cause dysfunction in the brain with some symptoms such as respiratory failure, headache, impaired consciousness, olfactory and taste disorders, and severe neurological disorders such as encephalitis. It was found that there is a two-way communication between the immune system and the nervous system through classical neurotransmitters, hormones, and cytokines. Among neurotransmitters, serotonin plays important roles in the immune system and in regulating inflammatory responses by central and peripheral mechanisms. This article aimed to review the two-way relationship between the immune and the nervous systems by focusing on the serotonergic system and the emerging COVID-19 disease.

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.

Uses of Natural Honey in Cancer: An Updated Review.

Cancer was predicted as the leading cause of death and the most important obstacle to the increased life expectancy in the 21st century worldwide. The World Health Organization (WHO) estimated number of new cases of cancers in 2020 about 19 million, and this number is estimated to be more than 295300000 people up to 2040 (more than 55% increase during next 20 years). Standard treatments for cancer include surgery, radiotherapy, and chemotherapy. However, all of these methods have dangerous side effects, so researchers are more interested in finding novel and less risky therapies. In recent years, there has been a great deal of interest in the development of anticancer agents obtained from foods or natural products. The relative safety of natural and food-derived compounds makes them attractive alternatives to conventional cancer treatment drugs. As a result, the majority of people are advised to use complementary and alternative medicine to treat and prevent cancer. In recent years, honey, as a natural product, has attracted many researchers' attention as an alternative to conventional anticancer drugs. Natural honey has long been used as a medicine and nutrient and its beneficial effects on various diseases in animal and human models have been studied. It was found that it has a wide range of therapeutic properties, including antioxidant, antibacterial, antiviral, anti-fungal, anti-diabetic, anti-inflammatory, anti-hypertensive, antiarrhythmic, wound healing, and liver protection benefits. This article aimed to review the role of natural honey in the prevention and treatment of a number of important cancers and their subsequent complications.

Green space exposure during pregnancy and umbilical cord blood levels of liver enzymes.

Evidence has suggested better pregnancy outcomes due to exposure to greenspace; however, the studies on such an association with the level of liver enzymes in the cord blood are still nonexistent. Hence, this study investigated the relationship between exposure to greenspace during the entire pregnancy and gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels in cord blood samples. We selected 150 pregnant women from our pregnancy cohort in Sabzevar, Iran (2018). Greenspace exposure was characterized based on (i) residential distance to green space, (ii) time spent in public/private green spaces, (iii) residential surrounding greenspace, (iv) visual access to greenspace, and (v) number of indoor natural pot plants at home. We developed linear regression models to investigate the adjusted associations of greenspace exposure with enzyme levels. Each one interquartile range (IQR) increase in the residential surrounding greenspace (100 m buffer) was related to a reduction of -12.58 (U/L) (95% CI -22.86, -2.29), -3.35 (U/L) (95% CI -5.50, -1.20), and -0.57 (U/L) (95% CI -1.12, -0.02) in the levels of GGT, AST, and ALT, respectively. Moreover, a similar association was observed for the time the participants spent in green spaces. A decrease in the residential distance to large green spaces was related with lower cord blood levels of AST, ALT, and GGT. Having a window with greenspace view at home was significantly related to lower AST level. The results for the indoor plant pots were not conclusive. Our findings suggested an inverse relationship between greenspace exposure during pregnancy and cord blood levels of liver enzymes. Further studies in other settings and populations are needed to confirm our findings.

Determinants of carbon load in airway macrophages in pregnant women.

The airway macrophages carbon loading (AMCL) has been suggested to be a biomarker of the long-term exposure to air pollution; however, to date no study has characterized AMCL for the pregnancy period. Therefore, this study aimed to assess the determinants of AMCL during pregnancy in Iran, a middle-income country. This study was based on a sample of 234 pregnant women with term and normal vaginal delivery who were residing in Sabzevar, Iran (2019). We characterized 35 potential determinants of personal exposure to air pollution for each participant, including six personal, nine indoor, and 20 home-outdoor factors. We applied Deletion/Substitution/Addition algorithm to identify the most relevant determinants that could predict AMCL levels. The median (IQR) of AMCL level was 0.12 (0.30) µm2 with a successful sputum induction in 82.9% (194) of participants. Ambient residential PM2.5 levels were positively associated with higher AMCL levels. On the other hand, increased residential distance to the traffic lights, squares and ring-roads, the duration of opening window per day, and opening window during cooking were inversely associated with AMCL levels. Our findings provide novel insights on the different personal, indoor, and outdoor determinants of personal exposure to air pollution during pregnancy in a middle-income country.

Bioaccumulation and health risk assessment of exposure to potentially toxic elements by consuming agricultural products irrigated with wastewater effluents.

Potentially toxic elements (PTEs) have many adverse health effects due to bioaccumulation capability and their long persistence in the environment. As a renewable water source, the effluents of municipal wastewater treatment systems have been used to irrigate agricultural products widely. However, the evidence on the bioaccumulation of PTEs in crops irrigated with these effluents is still scarce, with no available study in low and middle-income countries. Therefore, this study aimed to assess the PTEs concentration in the soil and crops irrigated with effluents of Sabzevar wastewater treatment plant and the related health risk by that. The clustered method was used to determine the soil and craps samples. Seventy cumulative samples were randomly prepared in summer and autumn 2016 and 2017 from crops, soil and effluent. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure PTEs. The health risk of exposure to PTEs was assessed using Monte Carlo simulation technique. Kruskal Wallis test and Posthoc Tukey HSD test were used to assess the mean difference of PTEs between soil, effluent and crops as well as between crops together. The bioaccumulation factor (BAF) magnitude order in different crop samples was Cd > Sr > Cu > Pb > Zn > Co > As > Cr > Ni, respectively. The Cd accumulation in Sugar beet plant was significantly higher than in other samples. The highest hazard quotient (HQ) based on single PTEs was observed for As (mineral) (mean: 5.62 × 10-1 and percentile 95th: 2.13) in Okra. Regarding total HQ (THQ), the highest and lowest mean (percentile 95th) values were 1.50 (3.22) and 2.40 × 10-1 (4.01 × 10-1) for Okra and Watermelon, respectively. The mean concentrations of Co, Cr, Ni and Zn were significantly higher in crops compared to soil and influent samples. Posthoc tests indicated that the concentration of PTEs between investigated crop samples were not statistically significant different (p > 0.05). Overall, our study suggested that irrigation with the effluent of stabilization pond wastewater treatment system exerts a potential health risk due to bioaccumulation of PTEs in crops.

Probabilistic risk assessment of soil contamination related to agricultural and industrial activities.

Soil contamination related to industrial and agricultural activities were associated with many adverse health effects and climate change could exacerbate this effect. However, the evidence on this topic in low and middle-income countries (LMICs) is still scarce. We, therefore, aimed to investigate the heavy metals (HMs) concentrations in topsoil around Lake Urmia (which dried about 50 % of it in recent years). Accordingly, 96 surface soil samples were collected from an area of about 4000 km2 in 2019. An inductively coupled plasma-atomic emission spectrometry (ICP-AES) was used to measure the HMs concentrations, including cadmium (Cd), arsenic (As), chromium (Cr), cobalt (Co), nickel (Ni), copper (Cu), lead (Pb) and zinc (Zn). Health risk assessment of exposure to HMs was performed using Monte Carlo simulations technique. The mean concentrations of Zn, Cu, Ni, Co, Pb, Cr, As and Cd were 68.66, 35, 31.66, 15, 14.4, 11.2, 7.04, and 0.26 mg/kg, respectively, which was in the allowable range of USEPA guideline. The mean enrichment factor (EF) values for Zn, Cd, Cu, Cr, Ni, Pb, Co and As were1.3, 1.9, 1, 1.2, 1.7, 2.8, 1.8 and 2, respectively. Carcinogenic risks of exposure to HMs for inhalation, dermal and ingestion exposure pathways were at safe level. Similarly, the hazard index (HI) was at safe level (HI < 1). The sensitivity analysis indicated that the exposure duration (ED) for As, exposure frequency (EF) for Cd and Ni, concentration (Csoi) for Cr and Pb had the highest impact on ELCR values. Our finding confirmed that HMs concentrations around Lake Urmia had no health risk for inhabitants.

Association of traffic-related air pollution with Newborn's anthropometric indexes at birth.

An emerging body of evidence has associated exposure to traffic-related air pollution (TRAP) during pregnancy with birth outcomes. However, the evidence on the association of TRAP exposure and neonatal anthropometric measurements (NAPM) in low and middle-income countries is very scarce yet. Therefore, we investigate the association of prenatal exposure to indicators of traffic and ambient particulate matter (PM) with NAPM. This cross-sectional study was based on hospital medical records of 4053 mother-neonate pairs between May 16, 2016, and December 5, 2018. PMs were estimated at residential addresses based on validated spatiotemporal models. Moreover, total street length in 100, 300 and 500m buffers around the home, residential distance to the ring road, major roads, heavy-traffic lights, gas station, motorway junction, bank, square, bus terminal, public parking and industrial land-use were calculated as indicators of traffic. The head circumference (HC), birth weight (BW) and birth length (BL) of neonates were collected as NAPM. Multivariate regression models were applied to evaluate the relationship between PMs and indicators of traffic with NAPM, controlled for relevant covariates. The median (IQR) of BW, BL, and HC of newborns were 3250 (592) gr, 51.0 (3.5) cm, 35 (2) cm, respectively. The adjusted models revealed that higher exposure to PM2.5 and PM10 was significantly related with lower BW and BL. Similar results were observed for total street length in a 100 m buffer around maternal home with BW and BL. Moreover, higher distance to heavy traffic lights was significantly associated with higher BW and BL. An IQR increase in PM10 was significantly related to lower HC (95% CI: 0.11, -0.01, P-value = 0.03). An increase in distance from residential address to heavy traffic lights, ring roads, bus terminal, and transportation land-use was associated with higher HC. Overall, our findings suggested that higher prenatal exposure to TRAP was related with lower BW, BL and HC.

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.

Medicine storage, wastage, and associated determinants among urban households: a systematic review and meta-analysis of household surveys.

BACKGROUND: Irrational household storage of medicines is a world-wide problem, which triggers medicine wastage as well as its associated harms. This study aimed to include all available evidences from literature to perform a focused examination of the prevalence and factors associated with medicine storage and wastage among urban households. This systematic review and meta-analysis mapped the existing literature on the burden, outcomes, and affective socio-economic factors of medicine storage among urban households. In addition, this study estimated pooled effect sizes for storage and wastage rates. METHODS: Household surveys evaluating modality, size, costs, and affective factors of medicines storage at home were searched in PubMed, EMBASE, OVID, SCOPUS, ProQuest, and Google scholar databases in 2019. Random effect meta-analysis and subgroup analysis were used to pool effect sizes for medicine storage and wastage prevalence among different geographical regions. RESULTS: From the 2604 initial records, 20 studies were selected for systematic review and 16 articles were selected for meta-analysis. An overall pooled-prevalence of medicine storage and real wastage rate was 77 and 15%, respectively. In this regard, some significant differences were observed between geographical regions. Southwest Asia region had the highest storage and wastage rates. The most common classes of medicines found in households belonged to the Infective agents for systemic (17.4%) and the Nervous system (16.4%). Moreover, income, education, age, the presence of chronic illness, female gender, and insurance coverage were found to be associated with higher home storage. The most commonly used method of disposal was throwing them in the garbage. CONCLUSIONS: Factors beyond medical needs were also found to be associated with medicine storage, which urges effective strategies in the supply and demand side of the medicine consumption chain. The first necessary step to mitigate home storage is establishing an adequate legislation and strict enforcement of regulations on dispensing, prescription, and marketing of medicines. Patient's pressure on excessive prescription, irrational storage, and use of medicines deserve efficient community-centered programs, in order to increase awareness on these issues. So, hazardous consequences of inappropriate disposal should be mitigated by different take back programs, particularly in low and middle income countries.