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BACKGROUND: Impaired semen quality and reproductive hormone levels were observed in patients during and after recovery from coronavirus disease 2019 (COVID-19), which raised concerns about negative effects on male fertility. Therefore, this study systematically reviews available data on semen parameters and sex hormones in patients with COVID-19. METHODS: Systematic search was performed on PubMed and Google Scholar until July 18th, 2022. We identified relevant articles that discussed the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on male fertility. RESULTS: A total number of 1,684 articles were identified by using a suitable keyword search strategy. After screening, 26 articles were considered eligible for inclusion in this study. These articles included a total of 1,960 controls and 2,106 patients. When all studies were considered, the results showed that the semen parameters and sex hormone levels of patients infected with SARS-CoV-2 exhibited some significant differences compared with controls. Fortunately, these differences gradually disappear as patients recover from COVID-19. CONCLUSION: While present data show the negative effects of SARS-CoV-2 infection on male fertility, this does not appear to be long-term. Semen quality and hormone levels will gradually increase to normal as patients recover.
Subject(s)
COVID-19 , Humans , Male , SARS-CoV-2 , Semen , Semen Analysis , Gonadal Steroid Hormones , HormonesABSTRACT
Oitline teaching arc facing drikmatic challenges due to the COVIDI9 pandemic requiring massive online education. Students are experiencing mental and physical isolation during this period. This research :Aims to find an efficient may to discover students emotion status through 1,;El: patient recognition (1'10. Traditional PR !method,' haie been applied eNtensikeh in 1":Ft;recognition including Artificial Neuron Networks iANNi, Support Vector Nlak'hinekSVNI Nearest Xeighhorc (KNN), and so on. In this paper, a association rule -based PR method has been introduced through incorporating clustering and Apriori association rube methods. The experimental results demonst rale that Ute tgdimized rule -based 1":F:t;PR model Can improve real-time recognition eflicienc. Tlic proposed model can Ike used for identifying students cognitive statuses and improve educational perfikrrnunce in (.0\11/19 period
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This paper examines Wellop discussion about 'hinese online education (luting the Cm id -19. Posts exit-acted from trending. topics of tte-learning vs. claNXIFOOM Irarning and tile-lesis vs. classroom tests are collected Ill explore the online public lieu touards clzinges liniughi In the nov teaching paradigm. We find that institutions of education are 1101 leading the online conversaolmi, uherras Ovate companies and social media influencers have a more powerful reach. Nlortaivrr, three thews ah0ut the common problems In distance education have surfaced from the posts and the overall attitude is far from positive.
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Background: During the coronavirus disease 2019 (COVID-19) lockdown, contact clustering in social bubbles may allow extending contacts beyond the household at minimal additional risk and hence has been considered as part of modified lockdown policy or a gradual lockdown exit strategy. We estimated the impact of such strategies on epidemic and mortality risk using the UK as a case study. Methods: We used an individual based model for a synthetic population similar to the UK, stratified into transmission risks from the community, within the household and from other households in the same social bubble. The base case considers a situation where non-essential shops and schools are closed, the secondary household attack rate is 20% and the initial reproduction number is 0.8. We simulate social bubble strategies (where two households form an exclusive pair) for households including children, for single occupancy households, and for all households. We test the sensitivity of results to a range of alternative model assumptions and parameters. Results: Clustering contacts outside the household into exclusive bubbles is an effective strategy of increasing contacts while limiting the associated increase in epidemic risk. In the base case, social bubbles reduced fatalities by 42% compared to an unclustered increase of contacts. We find that if all households were to form social bubbles the reproduction number would likely increase to above the epidemic threshold of R=1. Strategies allowing households with young children or single occupancy households to form social bubbles increased the reproduction number by less than 11%. The corresponding increase in mortality is proportional to the increase in the epidemic risk but is focussed in older adults irrespective of inclusion in social bubbles. Conclusions: If managed appropriately, social bubbles can be an effective way of extending contacts beyond the household while limiting the increase in epidemic risk.