Search

Context: Repeated pregnancy loss is causing great distress to couples and undermining their confidence in achieving reproductive success in the future. A doctor can usually diagnose the cause and manage it directly, but in some cases, the cause is not known. Aim: This study aims to investigate whether there is a correlation between recurrent miscarriage and the level of protein S, C, age and blood groups in women who have experienced recurrent miscarriage without identifying a cause for this condition. Material and methods: one hundred twenty from infected women by recurrent abortion for unknown causes were classified according to age groups. Diagnosed blood group by using a specific kit for Biorex diagnostic Limited (the United Kingdom, 2016). The concentration of protein S and C were calculated by using the equipment produced by the AESKU.DIAGNOSTIC (Germany) Statistical analysis: the statistical analyses of the data were performed by using the (SPSS) 20.0 software package. We used the following analyses, frequencies, percentage, mean, stander diversion and Pearson correlation to identify the potential correlation between the miscarriage and the level of protein S, C, age and blood groups, the p-value of less than 0.05 was considered significant. Results: The study showed that out of a total of 120 women, who suffer from recurrent abortion, 82/120 have a decrease in the level of C protein, 96/120 have a decrease in the level of S protein and 74\120 have low level of both proteins C&S. The results were statistically significant (P=0.000, P=0.000 and p=0.000), There was an intermediate direct correlation between recurrent abortion and the level of proteins C and S (rp= 0.545, rp= 0.643), also there was correlation between the level of protein S and the level of protein C (rp=0.713). It was also found that there was no correlation between age and blood groups with cases of recurrent abortion in women the results was statistically non-significant (rp= - 0.084, p= 0.279; rp= 0.108, p=0.159). Conclusion: There are several reasons for the occurrence of recurrent abortion, including what is caused by microbial infections, or it may be caused by certain abnormalities in the reproductive system, etc., also appear to the results of this research, the low level of one of the proteins S, C or both may be a cause in the case of recurrent abortion.

In recent years, substitution at the third position on phthalides has been proven a valuable synthetic intermediate for developing active molecules. We reported a direct and efficient onepot method for the synthesis of 3-aryl Phthalides performed by adding organo-zinc reagent on methyl-2-formylbenzoate; reagent formed in-situ by the reaction between diethylzinc and different aryl boronic acid derivatives without using any ligand. The possible mechanism involved a coordinated zinc carbonyl transition state, arylation, and followed by the intramolecular cyclization. The substituents groups in boronic having different electronic and steric properties played an important role in the reaction completion time and yield. The structure elucidation and confirmation of the synthesized compounds were done by using H-NMR analytical data. The method can be useful for synthesizing various scaffolds and intermediates in search of potentially active compounds.

Making predictions robust is an important challenge. A separate challenge in federated learning (FL) is to reduce the number of communication rounds, particularly since doing so reduces performance in heterogeneous data settings. To tackle both issues, we take a Bayesian perspective on the problem of learning a global model. We show how the global predictive posterior can be approximated using client predictive posteriors. This is unlike other works which aggregate the local model space posteriors into the global model space posterior, and are susceptible to high approximation errors due to the posterior's high dimensional multimodal nature. In contrast, our method performs the aggregation on the predictive posteriors, which are typically easier to approximate owing to the low-dimensionality of the output space. We present an algorithm based on this idea, which performs MCMC sampling at each client to obtain an estimate of the local posterior, and then aggregates these in one round to obtain a global ensemble model. Through empirical evaluation on several classification and regression tasks, we show that despite using one round of communication, the method is competitive with other FL techniques, and outperforms them on heterogeneous settings. The code is publicly available at https://github.com/hasanmohsin/FedPredSpace_1Round., Comment: 7 pages, 1 figure. Code is publicly available at https://github.com/hasanmohsin/FedPredSpace_1Round