No abstract

Data from the Personal Software Process (PSP) courses indicate that the PSP improves the quality of the developed programs. However, since the programs (exercises of the course) are in the same application domain, the improvement could be due to programming repetition. In this research we try to eliminate this threat to validity in order to confirm that the quality improvement is due to the PSP. In a previous study we designed and performed a controlled experiment with software engineering undergraduate students at the Universidad de la República. The students performed the same exercises of the PSP course but without applying the PSP techniques. Here we present a replication of this experiment. The results indicate that the PSP and not programming repetition is the most plausible cause of the important software quality improvements.

There is pressing urgency to better understand the immunological underpinnings of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) in order to identify potential therapeutic targets and drugs that allow treating patients effectively. To fill in this gap, we performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19. As results, the high-confidence protein interactome network was conformed by 1,588 nodes between immune system proteins and human proteins physically associated with SARS-CoV-2. Subsequently, we screened all these nodes in ACE2 and TMPRSS2 co-expressing cells according to the Alexandria Project, finding 75 potential therapeutic targets significantly overexpressed (Z score > 2) in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs for 25 of the 75 aforementioned proteins. On one hand, we obtained 45 approved drugs, 16 compounds under investigation, and 35 experimental compounds with the highest area under the receiver operating characteristic (AUROCs) for 15 immune system proteins. On the other hand, we obtained 4 approved drugs, 9 compounds under investigation, and 16 experimental compounds with the highest multi-target affinities for 9 immune system proteins. In conclusion, computational structure-based drug discovery focused on immune system proteins is imperative to select potential drugs that, after being effectively analyzed in cell lines and clinical trials, these can be considered for treatment of complex symptoms of COVID-19 patients, and for co-therapies with drugs directly targeting SARS-CoV-2.

No abstract

Rice cultivation on paddy soil is commonly associated with emissions of methane, a greenhouse gas, but rice varieties may differ in their actual level of emissions. This study analysed methane emissions associated with 22 distinct rice genotypes, using gas chromatography, and identified the cultivar Heijing 5 from northern China as a potential low-methane rice variety. To confirm this and to examine whether Heijing 5 can perform similarly at higher latitudes, Heijing 5 was cultivated in field trials in China (lat. 32° N) and Sweden (lat. 59° N) where (i) methane emissions were measured, (ii) methanogen abundance in the rhizosphere was determined using quantitative PCR, and (iii) the concentrations of nutrients in water and of heavy metals in rice grain and paddy soil were analysed. The results demonstrated that the low-methane rice cultivar Heijing 5 can successfully complete an entire growth period at high-latitude locations such as central Sweden. Massively parallel sequencing of mRNAs identified candidate genes involved in day length and cold acclimatisation. Cultivation of Heijing 5 in central Sweden was also associated with relatively low heavy metal accumulation in rice grains and lowered nutrient losses to neighbouring water bodies.