Based on the data provided, the Panel concluded that this food enzyme does not give rise to safety concerns under the intended conditions of use.Alzheimer's disease (AD) is a common neurodegenerative dementia in the elderly. Although there is no effective drug to treat AD, proteins associated with AD have been discovered in related studies. One of the proteins is mitochondrial fusion protein 2 (Mfn2), and its regulation presumably be related to AD. However, there is no specific drug for Mfn2 regulation. In this study, a three-tunnel deep neural network (3-Tunnel DNN) model is constructed and trained on the extended Davis dataset. In the prediction of drug-target binding affinity values, the accuracy of the model is up to 88.82% and the loss value is 0.172. By ranking the binding affinity values of 1,063 approved drugs and small molecular compounds in the DrugBank database, the top 15 drug molecules are recommended by the 3-Tunnel DNN model. After removing molecular weight less then 200 and topical drugs, a total of 11 drug molecules are selected for literature mining. The results show that six drugs have effect on AD, which are reported in references. Meanwhile, molecular docking experiments are implemented on the 11 drugs. The results show that all of the 11 drug molecules could dock with Mfn2 successfully, and 5 of them have great binding effect. Whole-exome sequencing is a valuable tool to determine genetic variations that are associated with rare and common health conditions. A limited number of studies demonstrated that mitochondrial DNA can be captured using whole-exome sequencing. Previous studies have suggested that mitochondrial DNA variants and haplogroup lineages are associated with obesity. Therefore, we investigated the role of mitochondrial variants and haplogroups contributing to the risk of obesity in Arabs in Kuwait using exome sequencing data. Indirect mitochondrial genomes were extracted from exome sequencing data from 288 unrelated native Arab individuals from Kuwait. The cohort was divided into obese [body mass index (BMI) ≥ 30 kg/m ] and non-obese (BMI < 30 kg/m ) groups. Mitochondrial variants were identified, and haplogroups were classified and compared with other sequencing technologies. Statistical analysis was performed to determine associations and identify mitochondrial variants and haplogroups affecting obesity. Haplogroup R showed a protective effect on obesity [odds ratio (OR) = 0.311; = 0.006], whereas haplogroup L individuals were at high risk of obesity (OR = 2.285; = 0.046). VVD-130037 Significant differences in mitochondrial variants between the obese and non-obese groups were mainly haplogroup-defining mutations and were involved in processes in energy generation. The majority of mitochondrial variants and haplogroups extracted from exome were in agreement with technical replica from Sanger and whole-genome sequencing. This is the first to utilize whole-exome data to extract entire mitochondrial haplogroups to study its association with obesity in an Arab population.This is the first to utilize whole-exome data to extract entire mitochondrial haplogroups to study its association with obesity in an Arab population.Prader-Willi Syndrome (PWS) is a rare neurodevelopmental disorder that affects approximately 1 in 20,000 individuals worldwide. Symptom progression in PWS is classically characterized by two nutritional stages. Stage 1 is hypotonia characterized by poor muscle tone that leads to poor feeding behavior causing failure to thrive in early neonatal life. Stage 2 is followed by the development of extreme hyperphagia, also known as insatiable eating and fixation on food that often leads to obesity in early childhood. Other major features of PWS include obsessive-compulsive and hoarding behaviors, intellectual disability, and sleep abnormalities. PWS is genetic disorder mapping to imprinted 15q11.2-q13.3 locus, specifically at the paternally expressed SNORD116 locus of small nucleolar RNAs and noncoding host gene transcripts. SNORD116 is processed into several noncoding components and is hypothesized to orchestrate diurnal changes in metabolism through epigenetics, according to functional studies. Here, we review the current status of epigenetic mechanisms in PWS, with an emphasis on an emerging role for SNORD116 in circadian and sleep phenotypes. We also summarize current ongoing therapeutic strategies, as well as potential implications for more common human metabolic and psychiatric disorders.It is known that cancer onset and development arise from complex, multi-factorial phenomena spanning from the molecular, functional, micro-environmental, and cellular up to the tissular and organismal levels. Important advances have been made in the systematic analysis of the molecular (mostly genomic and transcriptomic) within large studies of high throughput data such as The Cancer Genome Atlas collaboration. However, the role of the microbiome in the induction of biological changes needed to reach these pathological states remains to be explored, largely because of scarce experimental data. In recent work a non-standard bioinformatics strategy was used to indirectly quantify microbial abundance from TCGA RNA-seq data, allowing the evaluation of the microbiome in well-characterized cancer patients, thus opening the way to studies incorporating the molecular and microbiome dimensions altogether. In this work, we used such recently described approaches for the quantification of microbial species alongside with gene expression. With this, we will reconstruct bipartite networks linking microbial abundance and gene expression in the context of colon cancer, by resorting to network reconstruction based on measures from information theory. The rationale is that microbial communities may induce biological changes important for the cancerous state. We analyzed changes in microbiome-gene interactions in the context of early (stages I and II) and late (stages III and IV) colon cancer, studied changes in network descriptors, and identify key discriminating features for early and late stage colon cancer. We found that early stage bipartite network is associated with the establishment of structural features in the tumor cells, whereas late stage is related to more advance signaling and metabolic features. This functional divergence thus arise as a consequence of changes in the organization of the corresponding gene-microorganism co-expression networks.