Globally, more than 30 million people suffer from diabetes mellitus type 1 (T1DM) characterized by pancreas producing little or no insulin hormone to facilitate glucose entering cells for energy production. T1DM patients tend to suffer a higher overall rate of atherosclerosis, cancer, and end-stage renal failure. No drug or surgical therapy seems to halt its annual upward trend amongst children and young adults. Consequently, a significant number of sufferers turn to complementary or alternative therapies for help to arrest this chronic endocrine condition. This paper discusses how a well-designed evidence-based dietary and nutritional therapy with some lifestyle modifications might offer a solution for this highly complex autoimmune disorder. The treatment outcome demonstrated a partial regeneration of pancreatic islet beta cells with substantial improvement for all relevant serum and urine markers tested.

Ethiopia is a country characterized by a wide range of climate and ecological condition which helped to have high diversity of medicinal plants and up to 80% of the population use traditional medicine for primary health care. Studies on the current practices of the communities in the area are vital to document the basic information in these regards. Therefore, this study was aimed in assessing the practices of traditional plant medicine use among communities of Wonchi District. Results: The most widely used route of administration in the study area was oral accounted for (56.67%) followed by dermal (29.63%) This is the reason that oral and dermal routes permit rapid physiological reaction of the prepared medicines with the pathogens and increase its curative power. The prepared traditional medicines were applied in a number of ways, among which drinking (37.57%), creaming (16.76%), and eating (10.40%) were mentioned frequently.

Background: Pyrimidine molecules biological and chemotherapeutic importance in the medicinal world has been overlooked in many reports. We have previously synthesized new series of pyrrolo [3,2-d]pyrimidine derivatives (4a-4f) and here, we evaluate the antibacterial activity of these derivatives against Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli and Salmonella bacteria. Materials and Methods: The agar well diffusion and agar dilution methods were used for determining inhibition zone diameter and minimum inhibitory concentration during preliminary evaluation of antimicrobial activity against gram-positive and gram-negative bacteria. Statistical analysis using Microsoft Excel 2010 was based on three independent experiments and the results were expressed as mean. Results: Some of the synthesized compounds exhibited antibacterial activity against the tested bacteria. Conclusion: Our findings indicate the antibacterial potential of the six novel synthetic pyrrolo[3,2-d]pyrimidine compounds.

Interests remain in searching for cofactor regeneration system with higher efficiency at lower substrate cost. Glucose dehydrogenase (GDH) system has been dominant in NADH regeneration, but it only has a theoretical yield of one NADH per glucose molecule. This work sought to explore the utility of a two-step ethanol utilization pathway (EUP) in pathway-based NADH regeneration. The pathway runs from ethanol to acetaldehyde and to acetyl-CoA with each step generating one NADH, that together results in a higher theoretical yield of two NADH per ethanol molecule. In this project, anaerobic biotransformation of ketone (acetophenone or butanone) to alcohol by cpsADH from Candida parapsilosis was used as readout for evaluating relative efficacy and operating modes for EUP cofactor regeneration in Escherichia coli BL21 (DE3). Experiment tests validated that EUP was more efficient than GDH in NADH regeneration. Further, growing cell delivered higher biotransformation efficiency compared to resting cell due to the driving force generated by cell growth. Finally, preculture or cultivation in M9 + 10 g/L ethanol medium delivered higher biotransformation efficiency compared to LB medium. Overall, EUP could help regenerate NADH in support of a biocatalytic reaction, and is more efficient in cofactor regeneration than GDH.

Successful engineering of a microbial host for efficient production of a target product from a given substrate can be viewed as an extensive optimization task. Such a task involves the selection of high activity enzymes as well as their gene expression regulatory control elements (i.e., promoters and ribosome binding sites). Finally, there is also the need to tune expression of multiple genes along a heterologous pathway to relieve constraints from rate-limiting step and help reduce metabolic burden on cells from unnecessary over-expression of high activity enzymes. While the aforementioned tasks could be performed through combinatorial experiments, such an approach incurs significant cost, time and effort, which is a handicap that can be relieved by application of modern machine learning tools. Such tools could attempt to predict high activity enzymes from sequence, but they are currently most usefully applied in classifying strong promoters from weaker ones as well as combinatorial tuning of expression of multiple genes. This perspective reviews the application of machine learning tools to aid metabolic pathway optimization through identifying challenges in metabolic engineering that could be overcome with the help of machine learning tools.