Assisted reproductive techniques (ARTs) may perturb the pre-/peri-conception microenvironments, which subsequently threaten the health of offspring. This study aimed to investigate the effects of superovulation, vitrification, in vitro culture, and embryo transfer on the expression of epigenetic modulators, imprinted genes, and pluripotency markers in expanded blastocysts and Day-9.5 (D9.5) concepti. Results revealed that 53.4% (8/15) and 86.7% (13/15) of genes in the fetus and placenta, respectively, have similar patterns of transcription in all D9.5 concepti, despite the perturbed mRNA expression observed at the blastocyst stage for each embryo-production technique. These observations indicate a counterbalancing of the abnormal expression pattern analyzed at the blastocyst stage during post-implantation development, particularly when the uterus of a naturally synchronized foster mother is employed. Superovulation resulted in the most abnormal expression patterns compared to other treatment groups, although these same blastocysts were able to develop in a synchronized uterus. Thus, superovulation creates a hormonal environment that negatively affected gene expression and impairs fetal growth more adversely during post-implantation development than other ART protocols, such as in vitro culture, vitrification, or embryo transfer-although each did contribute negatively to the implantation and development process. Together, these results may have implications for treating infertility in humans.

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ABSTRACT. We estimated the allele and genotype frequencies of IGF-I/SnaBI gene polymorphism and the concentration of this protein in Holstein dairy cows. We also examined the association with milk yield (305-day milk yield) and milk components (fat and protein percentage, and 305-day milk protein and fat yield). Blood IGF-I levels were measured and genotyping was performed on 250 Holstein cows of four different herds. In the association studies, traits of interest were analyzed using the GLM procedure of SAS; means of the IGF-I level among genotypes were compared by the LSMeans test. The AB and AA genotypes were the most (0.583-0.661) and least (0.083-0.192) frequent in the herds, respectively; the frequency of the BB genotype ranged from 0.201 to 0.333. The frequency of the A allele ranged from 0.375 to 0.495, while the frequency of the B allele ranged from 0.504 to 0.625, being the dominant allele. The mean level of IGF-I was 107 ± 22 ng/mL for all groups, without IGF-I gene and milk components any significant correlation with the production traits. Association of IGF-I/SnaBI genotypes with percentage of fat and protein in the milk was relatively high (P < 0.1 and P < 0.05, respectively); the AB genotype was superior to AA and BB genotypes. We concluded that this marker should be considered for milk component selection in Holstein dairy cattle.

Understanding the most relevant hematological/biochemical characteristics, pre-existing health conditions and complications in survivors and non-survivor will aid in predicting COVID-19 patient mortality, as well as intensive care unit (ICU) referral and death. A literature review was conducted for COVID-19 mortality in PubMed, Scopus, and various preprint servers (bioRxiv, medRxiv and SSRN), with 97 observational studies and preprints, consisting of survivor and non-survivor sub-populations. This meta/network analysis comprised 19,014 COVID-19 patients, consisting of 14,359 survivors and 4655 non-survivors. Meta and network analyses were performed using META-MAR V2.7.0 and PAST software. The study revealed that non-survivors of COVID-19 had elevated levels of gamma-glutamyl transferase and creatinine, as well as a higher number of neutrophils. Non-survivors had fewer lymphocytes and platelets, as well as lower hemoglobin and albumin concentrations. Age, hypertension, and cerebrovascular disease were shown to be the most influential risk factors among non-survivors. The most common complication among non-survivors was heart failure, followed by septic shock and respiratory failure. Platelet counts, creatinine, aspartate aminotransferase, albumin, and blood urea nitrogen levels were all linked to ICU admission. Hemoglobin levels preferred non-ICU patients. Lower levels of hemoglobin, lymphocytes, and albumin were associated with increased mortality in ICU patients. This meta-analysis showed that inexpensive and fast biochemical and hematological tests, as well as pre-existing conditions and complications, can be used to estimate the risk of mortality in COVID-19 patients.

Background: Understanding the most relevant hematological/biochemical characteristics, pre-existing health conditions and complications among survivors and non-survivor will help to predict the mortality in COVID-19 patients.Methods: A literature review was conducted in PubMed, Scopus, and various preprint servers (bioRxiv, medRxiv and SSRN) for COVID-19 mortality, with more than 97 reported clinical studies and preprints, consisting of survivor and non-survivor sub-populations. A total of 19014 patients including 14359 survivors and 4655 non-survivors were included in this meta-analysis. Outcome data was extracted and compared between survivors and non-survivors. Meta and network analyses were performed using META-MAR V2.7.0 and PAST software.Results: The finding showed higher concentrations of gamma-glutamyl transferase and creatinine and a higher number of neutrophils in non-survivors of COVID-19. A lower number of lymphocytes and platelets and a lower concentration of hemoglobin and albumin were observed in non-survivors. Data showed age, hypertension, and cerebrovascular disease as the most influential risk factors in non-survivors. Heart failure was the most common complication among non-survivors, accompanied by septic shock, and respiratory failure.Conclusions: Increased number of neutrophils and decreased number of platelets and lymphocytes, along with higher GGT concentration and lower hemoglobin levels were the best mortality indicators for COVID-19 patients. In addition, age, hypertension, and cerebrovascular disease were prevalent risk factors among non-survivors of COVID-19. Heart failure and septic shock were the most common complications among non-survivors. Data indicated that cheap and quick biochemical and hematological tests can be used to predict the risk of mortality in COVID-19 patients.