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BACKGROUND: Mother-to-child transmission is the primary cause of HIV cases among children. Antiretroviral therapy (ART) plays a critical role in preventing mother-to-child transmission and reducing HIV progression, morbidity, and mortality among mothers. However, after more than two decades of ART during pregnancy, the comparative effectiveness and safety of ART medications during pregnancy are unclear, and existing evidence is contradictory. This study aimed to assess the effectiveness and safety of different ART regimens among pregnant women living with HIV at preconception or during pregnancy. METHODS: We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Web of Science. We included randomized trials that enrolled pregnant women living with HIV and randomized them to receive ART for at least four weeks. Pairs of reviewers independently completed screening for eligible studies, extracted data, and assessed the risk of bias using the Cochrane risk of bias tool. Our outcomes of interest included low birth weight, stillbirth, preterm birth, mother-to-child transmission of HIV, neonatal death, and congenital anomalies. Network meta-analysis was performed using a random-effects frequentist model, and the certainty of evidence was evaluated using the GRADE approach. RESULTS: We found 14 eligible randomized trials enrolling 9,561 pregnant women. The median duration of ART uptake ranged from 6.0 to 17.4 weeks. No treatment was statistically better than a placebo in reducing the rate of neonatal mortality, stillbirth, congenital defects, preterm birth, or low birth weight deliveries. Compared to placebo, zidovudine (ZDV)/lamivudine (3TC) and ZDV monotherapy likely reduce mother-to-child transmission (odds ratio (OR): 0.13; 95% CI: 0.05 to 0.31, high-certainty; and OR: 0.50; 95% CI: 0.33 to 0.74, moderate-certainty). Moderate-certainty evidence suggested that ZDV/3TC was associated with decreased odds of stillbirth (OR: 0.47; 95% CI: 0.09 to 2.60). CONCLUSIONS: Our analysis provides high- to moderate-certainty evidence that ZDV/3TC and ZDV are more effective in reducing the odds of mother-to-child transmission, with ZDV/3TC also demonstrating decreased odds of stillbirth. Notably, our findings suggest an elevated odds of stillbirth and preterm birth associated with all other ART regimens.

Ensuring the correct operation of electrical equipment in tandem is a critical engineering concern, particularly when addressing the issue of electromagnetic compatibility (EMC). In satellite systems, EMC considerations must be addressed from the initial design phases, as methods such as shielding or the addition of suitable filters are not always feasible or optimal. This article examines the necessity of shielding the LVDS (Low-Voltage Differential Signaling) bus cabling of the satellite's camera, which is located on the satellite's exterior. The study begins with the simulation of the LVDS bus cabling to assess the need for shielding, and the results are subsequently validated through electromagnetic compatibility testing. The research findings indicate that, while shielding the LVDS bus cable of the camera can improve protection by a factor of ten thousand in the worst-case scenario during Radiated Emission (RE) and Radiated Susceptibility (RS) tests, the low level of interference radiation in RE (approximately E7–8 V/m or E4/1–11 A/m) and the small amplitude of the interference signal in RS (approximately 0.001 V) suggest that shielding is not necessary. Shielding would only increase the satellite's mass and complicate the connection without significant benefits. It is evident from this study that simulating Conducted Emission (CE) and Conducted Susceptibility (CS) tests in subsequent design phases is essential to ensure comprehensive EMC assessment.

Background. Brain stroke is the second most common cause of death and the first cause of disability in Iran. Most stroke-related deaths occur in low- and middle-income countries. This epidemiological study was conducted due to insufficient studies and generally with a small sample size in the country, aiming at identifying the main risk factors for stroke in East Azarbaijan province. Methods. This cross-sectional study was performed using data gathered from 5430 patients with a definite diagnosis of brain stroke registered in the Tabriz Stroke Registration System (TSR) between February 2015 and June 2021 in the referral hospitals of East Azerbaijan. Analyses were performed using STATA software (version 17). Descriptive statistics were calculated, and a chi-square test was run. It is worth mentioning that any was considered statistically significant. Results. The epidemiological profile of the main risk factors was presented in the framework of clinical trials and findings, clinical risk factors, and behavioral risk factors associated with brain stroke. The mean age of the patients was 69.52±15.72 years; 47.15% were female and 52.85% were male. The most common risk factors include: having high blood pressure (67.81%), snoring (32.06%), diabetes mellitus (22.23%), familial history of stroke (18.78%), ischemic heart disease (17.55%), aspiration pneumonia (15.32%), smoking (13.65%), atrial fibrillation (10.15%), and hyperlipidemia (8.42%). Ischemic brain stroke (68.20%) was more common than hemorrhagic brain stroke (31.80%). Smoking was significantly higher in men than women. The prevalence of hypertension, atrial fibrillation (P=0.001), and hyperlipidemia was significantly higher in women than men. There was a direct and significant relationship between atrial fibrillation and age and female gender (P=0.001). Conclusion. The main risk factors for brain stroke include high blood pressure, snoring, diabetes mellitus, ischemic heart disease, aspiration pneumonia, smoking, atrial fibrillation, and hyperlipidemia, respectively. Hypertension is the most common risk factor among patients, so screening for asymptomatic cases is recommended. Educating people about common clinical manifestations can help expedite their early referral and treatment.

Light olefins are critical chemical materials with high global demand. The syngas-to-olefins (STO) process offers a promising pathway for light olefin production due to the versatility of syngas production technologies from various energy sources. However, achieving high carbon monoxide (CO) conversion and selectivity for olefins remains a challenge in catalytic development. This review categorizes STO catalysts into conventional Fischer-Tropsch catalysts, including unsupported and supported metal-based catalysts (with supports such as carbon, graphene, graphene oxide, zeolites, and metal oxides), as well as bifunctional, hybrid, and emerging core@shell structured catalysts. Another type of catalyst is core@shell structure catalyst, which is a developing method widely used for FT reactions. The performance of these catalysts is influenced by their materials, chemical compositions, operating conditions, and synthesis techniques. Unsupported catalysts, especially Fe-based and Co-based, exhibit high CO conversion but face issues like rapid deactivation and complex processing requirements. Supported catalysts enhance surface area, metal dispersion, and stability, with promoters such as Na, Mg, K, Mn, Zn, V, Zr, and Cu oxides improving catalytic activity through better CO adsorption and bond modulation. Zeolites, due to their acidic properties, significantly impact reactant adsorption and activation. Catalyst preparation methods, including impregnation, co-precipitation, sol-gel, and hydrothermal synthesis, alongside post-synthesis treatments like calcination and reduction, critically affect catalyst performance. This review provides a comprehensive overview of the light olefin production from syngas, detailing the roles of various catalysts and the impact of material types, operating conditions, and synthesis techniques on catalyst activity, and selectivity. The insights aim to guide future research and development towards more efficient and sustainable light olefin production processes.

Lung cancer is one of the leading causes of death among all cancer deaths. This cancer is classified into two different histological subtypes: non-small cell lung cancer (NSCLC), which is the most common subtype, and small cell lung cancer (SCLC), which is the most aggressive subtype. Understanding the molecular characteristics of lung cancer has expanded our knowledge of the cellular origins and molecular pathways affected by each of these subtypes and has contributed to the development of new therapies. Traditional treatments for lung cancer include surgery, chemotherapy, and radiotherapy. Advances in understanding the nature and specificity of lung cancer have led to the development of immunotherapy, which is the newest and most specialized treatment in the treatment of lung cancer. Each of these treatments has advantages and disadvantages and causes side effects. Today, combination therapy for lung cancer reduces side effects and increases the speed of recovery. Despite the significant progress that has been made in the treatment of lung cancer in the last decade, further research into new drugs and combination therapies is needed to extend the clinical benefits and improve outcomes in lung cancer. In this review article, we discussed common lung cancer treatments and their combinations from the most advanced to the newest.

Background: Many studies have assessed the effect of music on driving. However, their results are very scattered and contradictory. Therefore, this systematic review is conducted to determine the effect of music on driving performance and drivers’ physiological and psychological indicators. Methods: Scopus, PubMed, and Web of Science databases were searched until July 2023. A manual search in Google Scholar for gray literature was conducted. The Simulation Research Rubric (SRR) tool was used to assess the reporting quality of the studies. Stata software (StataCorp, version 16) was used to perform a meta-analysis. Results: A total of 2650 records were identified. The findings of 19 studies were analyzed. Most of them were carried out in high-income countries (HICs) using simulators. The most frequently used music style was classic rock. The meta-analysis results indicated that music with high and medium volume increases the average driving speed, and music with low volume decreases it. Although music in every mood reduces the average reaction time, it positively reduces response delay and increases coherence. Music with high volume decreases the heart rate, but music with medium and low volume increases it. Listening to music increases the level of arousal and mental load. Conclusion: It was concluded that, in some indicators, listening to music has adverse effects on driving. However, in many indicators, music has a positive impact on improving driving safety. It is better to choose appropriate music for different driving conditions and to train the drivers about it.

Background. In vitro studies have shown some effects for Hydroxychloroquine (HCQ) against SARS-CoV-2 virus. Despite effective vaccination program, relatively large proportion of population remains unvaccinated. So, there still remains a need for other prophylactic measures. The present study aims to evaluate whether HCQ can prevent severe COVID-19 outcomes among health-care workers. Materials and methods. In this randomized, double blind placebo-controlled clinical trial 334 healthcare workers aged 18–65 years old were included of whom 278 individuals completed the study. Participants were randomly assigned to the HCQ group (800 mg at day one, followed by 400 mg weekly for the next 7 weeks); or the placebo group. Participants were followed three weeks after the last dose of drug or placebo (10 weeks from the first dose of drug or placebo). The primary outcome was hospitalization or death from COVID-19. Results. Of 148 people who received HCQ, none were hospitalized or died from COIVD-19, while of 130 people who received the placebo, 2 (1.5%) were hospitalized for COIVD-19 (p-value: 0.26). And, 22 (14.9%) people in the HCQ group and 15 (11.6%) people in the placebo group contracted COVID-19 (p-value: 0.99). Adverse reactions were reported by 5 (3.4%) of participants in the HCQ group and 5 (3.9%) of participants in the placebo group (p-value: 0.99). Conclusion. We found that HCQ has no significant prevention effect on the incidence of mild COVID-19. However, the low rate of hospitalization (the primary outcome) in this trial like most of the other clinical trials with HCQ would have required increasing the sample size considerably to be able to comment on the effectiveness of HCQ in prevention of severe forms including death rate. This justifies systematic reviews to include similar studies to further investigate the issue.

Abstract Background Accurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation helps clinicians to better diagnose and evaluation of any treatment risks. However, manual segmentation of brain lesions relies on the experience of neurologists and is also a very tedious and time-consuming process. So, in this study, we proposed a novel deep convolutional neural network (CNN-Res) that automatically performs the segmentation of ischemic stroke lesions from multimodal MRIs. Methods CNN-Res used a U-shaped structure, so the network has encryption and decryption paths. The residual units are embedded in the encoder path. In this model, to reduce gradient descent, the residual units were used, and to extract more complex information in images, multimodal MRI data were applied. In the link between the encryption and decryption subnets, the bottleneck strategy was used, which reduced the number of parameters and training time compared to similar research. Results CNN-Res was evaluated on two distinct datasets. First, it was examined on a dataset collected from the Neuroscience Center of Tabriz University of Medical Sciences, where the average Dice coefficient was equal to 85.43%. Then, to compare the efficiency and performance of the model with other similar works, CNN-Res was evaluated on the popular SPES 2015 competition dataset where the average Dice coefficient was 79.23%. Conclusion This study presented a new and accurate method for the segmentation of MRI medical images using a deep convolutional neural network called CNN-Res, which directly predicts segment maps from raw input pixels.