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The current study investigated and optimized key process parameters affecting mushroom hydrolysis with crude enzymatic extract. The crude enzyme was prepared by solid-state fermentation of pineapple peels using Aspergillus niger. The reaction parameters viz. time, temperature, pH and enzyme concentration were optimized using the central composite design of the response surface methodology. The model predicted glucose yield of 1.49 mg/mL at optimal pH of 6.5, temperature of 50 °C, enzyme loading of 5 % (v/v), and reaction time of 12 h. Mushroom hydrolysis at the same optimal model conditions, increased glucose yield by 10%. More so supplementing SSF media with 0.2% (w/v) Tween-80 and 0.08% (w/v) yeast extract at moisture level of 70–75% significantly (p value < 0.05) improved hydrolytic efficiency of the crude enzyme extract by 2.2-fold. This study provides baseline data that will be useful in developing a low-cost enzyme-based process for hydrolyzing mushrooms to recover high-value products.

Tsetse flies are the sole vectors of human African trypanosomiasis throughout sub-Saharan Africa. Both sexes of adult tsetse feed exclusively on blood and contribute to disease transmission. Notable differences between tsetse and other disease vectors include obligate microbial symbioses, viviparous reproduction, and lactation. Here, we describe the sequence and annotation of the 366-megabase Glossina morsitans morsitans genome. Analysis of the genome and the 12,308 predicted protein-encoding genes led to multiple discoveries, including chromosomal integrations of bacterial (Wolbachia) genome sequences, a family of lactation-specific proteins, reduced complement of host pathogen recognition proteins, and reduced olfaction/chemosensory associated genes. These genome data provide a foundation for research into trypanosomiasis prevention and yield important insights with broad implications for multiple aspects of tsetse biology.

The profound advances in the biomolecular sciences over the last decades have enabled similar advances in biomedicine. These advances have increasingly challenged our abilities to deploy them in an equitable and ethically acceptable manner. As such, it has become necessary and important to teach biomedical and scientific ethics to our students who will become the researchers, medical professionals, and global citizens of the future. As advances in the biosciences and medicine are made, developed, and used across the globe, our survival on an endangered planet requires global dialog and consensual action. To that end, a group of us from around the world have come together to describe the differing foundations of our ethical beliefs, and how ethical issues in biomedicine and in science are described and confronted in our countries. We hope to show the commonality in our beliefs and practices and to encourage readers from around the world to contribute to a continuing discussion through a new section of the journal, The Global Ethics Corner.

Background: Staphylococcus aureus cause diseases both in humans and animals. These diseases range from mild to fatal infections thus necessitating development of a specific molecular method for detection of pathogenic S. aureus. Objectives: To identify and analyze genetic profile of pathogenic S. aureus using bacteriophage based genetic biomarkers. Methods: Using culture and biochemical methods, 148 S. aureus (87 %) were isolated from 170 raw milk samples taken from 10 dairy farms in Marsabit and Isiolo counties in Northern Kenya between June 2016 and February 2017. The samples were collected directly from dairy lactating cows previously diagnosed with S. aureus in a follow‐up study. The isolates were analyzed by PCR and sequencing of beta hemolysin (hlb) gene. The genetic relationship between five Kenyan S. aureus isolates and five isolates previously identified was inferred. Results: From the 96 isolates screened for hlb gene, 75 (78.1%) tested positive. Some of the positive isolates yielded a band size of 975 bp, while others 1100 bp. Through Basic Local Alignment Search Tool (BLAST) search analysis, the two different band sizes (975 bp and 1100 bp) were both confirmed to be hlb gene from S. aureus isolates indicating that the difference in band size may have been due to deletions that were detected in the 975 bp hlb gene. Some S. aureus isolates from Kenya appeared to be closely related to isolates from other parts of the world, while some showed a distant relationship. Conclusions: Phage‐derived hlb gene is a suitable molecular marker for detection of pathogenic S. aureus. [ABSTRACT FROM AUTHOR]

Yam (Dioscorea spp.) is an economically important crop grown in the tropical and subtropical regions, producing tuberous roots that serve as a staple food, an income source, and an excellent source of various pharmaceutical precursors. Yam production is constrained by disease and pest infestations and a range of abiotic stresses. Genetic improvement can significantly mitigate these challenges, improve productivity, expand the yam markets, and increase economic gains. However, several intrinsic attributes of the crop have curtailed progress in yam breeding. Advanced genetic engineering such as genome editing by sequence‐specific nucleases has emerged as complementary approaches to conventional breeding techniques. Mainly, the clustered regularly interspaced short palindromic repeats/CRISPR‐associated protein (CRISPR/Cas) system for genome editing has provided robust platforms for gene function analysis and crop improvement in the post‐genomic era. Despite its significance, research towards improving the yam species remains under‐represented compared to other staple tuber crops such as cassava and sweet potato. Thus, it is critical to explore avenues for increasing the genetic gains from this under‐exploited crop. The present review focuses on the progress and prospects for applying the CRISPR/Cas technology for yam improvement. The study elaborates on the currently available CRISPR/Cas tool for yam genome engineering and explores the potential applications of this toolkit in mitigating the various challenges encountered in yam production and consumption. Furthermore, we have delved into the challenges associated with this technology and the improvements made to minimize these challenges. The insights presented herein provide a guide for yam improvement to increase genetic gains from this under‐researched and under‐utilized resource. [ABSTRACT FROM AUTHOR]

Background: HIV/AIDS remains one of the major global human health challenges, especially in resource-limited environments. By 2017, over 77.3 million people were infected with the disease, and approximately 35.4 million individuals had already died from AIDS-related illnesses. Approximately 21.7 million people were accessing ART with significant clinical outcomes. However, numerous challenges are experienced in the delivery and accurate interpretation of data on patients with HIV data by various health care providers at different care levels. Mobile health (mHealth) technology is progressively making inroads into the health sector as well as medical research. Different mobile devices have become common in health care settings, leading to rapid growth in the development of downloadable software specifically designed to fulfill particular health-related purposes. Objective: We developed a mobile-based app called ARVPredictor and demonstrated that it can accurately define HIV-1 drug-resistance mutations in the HIV pol gene for use at the point of care. Methods: ARVPredictor was designed using Android Studio with Java as the programming language and is compatible with both Android and iOS. The app system is hosted on Nginx Server, and network calls are built on PHP’s Laravel framework handled by the Retrofit Library. The Digital Ocean offers a high-performance and stable cloud computing platform for ARVPredictor. This mobile app is enlisted in the Google Play Store as an “ARVPredictor” and the source code is available under MIT permissive license at a GitHub repository. To test for agreement between the ARVPredictor and Stanford HIV Database in detecting HIV subtype and NNRT and NRTI mutations, a total of 100 known HIV sequences were evaluated. Results: The mobile-based app (ARVPredictor) takes in a set of sequences or known mutations (protease, reverse transcriptase and integrase). It then returns inferred levels of resistance to selected nucleoside, nonnucleoside protease, and integrase inhibitors for accurate HIV/AIDS management at the point of care. The ARVPredictor identified similar HIV subtypes in 98/100 sequences compared with the Stanford HIV Database (κ=0.98, indicating near perfect agreement). There were 89/100 major NNRTI and NRTI mutations identified by ARVPredictor, similar to the Stanford HIV Database (κ=0.89, indicating near perfect agreement). Eight mutations classified as major by the Stanford HIV Database were classified as others by ARVPredictor. Conclusions: The ARVPredictor largely agrees with the Stanford HIV Database in identifying both major and minor proteases, reverse transcriptase, and integrase mutations. The app can be conveniently used robustly at the point of care by HIV/AIDS care providers to improve the management of HIV infection. [ABSTRACT FROM AUTHOR]