to seek healthcare for childhood illness. To reduce childhood mortalities and morbidities in Ghana, we recommend educating women such as those who take healthcare decisions alone, older women and women from deprived regions like the Northern and Upper West regions on the need to seek healthcare for childhood illnesses. In December 2019, the COVID-19 outbreak began in China and quickly spread throughout the world and was reclassified as a pandemic in March 2020. The first case of COVID-19 was declared in Togo on March 5. Two months later, few data were available to describe the circulation of the new coronavirus in the country. This survey aimed to estimate the prevalence of SARS-CoV-2 in high-risk populations in Lomé. From April 23, 2020, to May 8, 2020, we recruited a sample of participants from five sectors health care, air transport, police, road transport and informal. We collected oropharyngeal swabs for direct detection through real-time reverse transcription polymerase chain reaction (rRT-PCR) and blood for antibody detection by serological tests. The overall prevalence (current and past) of infection was defined by positivity for both tests. A total of 955 participants with a median age of 36 (IQR 32-43) were included, and 71.6% (n = 684) were men. Approximately 22.1% (n = 212) were from the air transport sector, 20.5% (n = 196) were from the police sector, and 38.7% (n = 370) were from the health sector. Seven participants (0.7%, 95% CI 0.3-1.6%) had a positive rRT-PCR test result at the time of recruitment, and nine (0.9%, 95% CI 0.4-1.8%) were seropositive for IgM or IgG against SARS-CoV-2. We found an overall prevalence of 1.6% (n = 15), 95% CI 0.9-2.6%. The prevalence of SARS-CoV-2 infection among high-risk populations in Lomé was relatively low and could be explained by the various measures taken by the Togolese government. Therefore, we recommend targeted screening. The prevalence of SARS-CoV-2 infection among high-risk populations in Lomé was relatively low and could be explained by the various measures taken by the Togolese government. Therefore, we recommend targeted screening.Minimizing the toxicity of radiotherapy is challenging. We investigated the effects of a phosphodiesterase type-5 inhibitor (PDE5I) on the urinary bladder after pelvic radiotherapy. Eight rats were assigned to each group (group 1 control; group 2 radiation; group 3 radiation plus PDE5I). Radiation dose was 10 Gy/one fraction. Udenafil (20 mg/kg, daily for 4 weeks) was administered in group 3. Cystometry was performed 4 weeks after treatment, followed by real-time PCR for PDE5, vascular endothelial growth factor (VEGF), and endothelial nitric oxide synthase (eNOS) mRNA, western blotting for PDE5, cyclic GMP-dependent protein kinase (PRKG), VEGF164, Akt, eNOS and NADPH oxidase (NOX)-2 proteins, and immunohistochemistry for eNOS. The expression of both VEGF mRNA and eNOS mRNA was higher in group 3 than in group 2. VEGF and eNOS protein expression improved with PDE5I treatment. Akt protein phosphorylation was higher in group 3 than in group 2, but NOX-2 protein expression was lower in group 3 than in group 2. Immunohistochemistry showed that the mean density of arterioles expressing eNOS was higher in group 3 than in group 2. Cystometry revealed that the intercontraction interval was remarkably longer in group 3 than in group 2 but that the maximal voiding pressure was higher in group 2 than in group 3. Daily treatment with a PDE5I after radiotherapy may prevent bladder storage dysfunction, potentially due to its effects on vasodilation and angiogenesis and through minimizing tissue oxidative damage by means of the VEGF/Akt/eNOS pathway.Biomedical question answering (QA) represents a growing concern among industry and academia due to the crucial impact of biomedical information. When mapping and ranking candidate snippet answers within relevant literature, current QA systems typically refer to information retrieval (IR) techniques specifically, query processing approaches and ranking models. However, these IR-based approaches are insufficient to consider both syntactic and semantic relatedness and thus cannot formulate accurate natural language answers. Recently, deep learning approaches have become well-known for learning optimal semantic feature representations in natural language processing tasks. https://www.selleckchem.com/products/protac-tubulin-degrader-1.html In this paper, we present a deep ranking recursive autoencoders (rankingRAE) architecture for ranking question-candidate snippet answer pairs (Q-S) to obtain the most relevant candidate answers for biomedical questions extracted from the potentially relevant documents. In particular, we convert the task of ranking candidate answers to several siness and effectiveness of rankingRAE.The aim of time-varying heart rate variability spectral analysis is to detect and quantify changes in the heart rate variability spectrum components during nonstationary events. Of the methods available, the nonparametric short-time Fourier Transform and parametric time-varying autoregressive modeling are the most commonly employed. The current study (1) compares short-time Fourier Transform and autoregressive modeling methods influence on heart rate variability spectral characteristics over time and during an experimental ozone exposure in mature adult spontaneously hypertensive rats, (2) evaluates the agreement between short-time Fourier Transform and autoregressive modeling method results, and (3) describes the advantages and disadvantages of each method. Although similar trends were detected during ozone exposure, statistical comparisons identified significant differences between short-time Fourier Transform and autoregressive modeling analysis results. Significant differences were observed between methods for LF power (p ≤ 0.014); HF power (p ≤ 0.011); total power (p ≤ 0.027); and normalized HF power (p = 0.05). Furthermore, inconsistencies between exposure-related observations accentuated the lack of agreement between short-time Fourier Transform and autoregressive modeling overall. Thus, the short-time Fourier Transform and autoregressive modeling methods for time-varying heart rate variability analysis could not be considered interchangeable for evaluations with or without interventions that are known to affect cardio-autonomic activity.