In the next century, global warming, due to changes in climatic factors, is expected to have an enormous influence on the interactions between pathogens and their hosts. Over the years, the rate at which vector-borne diseases and their transmission dynamics modify and develop has been shown to be highly dependent to a certain extent on changes in temperature and geographical distribution. Schistosomiasis has been recognized as a tropical and neglected vector-borne disease whose rate of infection has been predicted to be elevated worldwide, especially in sub-Saharan Africa; the region currently with the highest proportion of people at risk, due to changes in climate. This review not only suggests the need to develop an efficient and effective model that will predict Schistosoma spp. population dynamics but seeks to evaluate the effectiveness of several current control strategies. The design of a framework model to predict and accommodate the future incidence of schistosomiasis in human population dynamics in sub-Saharan Africa is proposed. The impact of climate change on schistosomiasis transmission as well as the distribution of several freshwater snails responsible for the transmission of Schistosoma parasites in the region is also reviewed. Lastly, this article advocates for modelling several control mechanisms for schistosomiasis in sub-Saharan Africa so as to tackle the re-infection of the disease, even after treating infected people with praziquantel, the first-line treatment drug for schistosomiasis.

Presently, many studies have focused on exploring in silico approaches in the identification and development of alternative therapy for the treatment and management of cancer. Solute carrier family-2-member-4-gene (Slc2a4) which encodes glucose transporter 4 protein (GLUT4), has been identified as a promising therapeutic target for cancer. Though Slc2a4 is known to play a major regulatory role in the pathophysiology of type 2 diabetes, emerging evidence suggests that successful pharmacological inhibition of this protein may lead to the development of a novel drug candidate for the treatment of cancer. In this study, Slc2a4 protein sequence was retrieved and analysed using in silico approaches, and we identified seven putative antimicrobial peptides (AMPs; RAB1-RAB7) as anti-cancer. The structures of the protein and AMPs were modelled using I-TASSER server, and the overall quality of the Slc2a4 model was validated using PROCHECK. Subsequently, the probable motifs and active site of the protein were forecasted. Also, the molecular interaction between the AMPs and Slc2a4 was ascertained using PatchDock. The result revealed that, all the AMPs are good Slc2a4 inhibitors with RAB1 having the highest binding affinity of 12,392 and binding energy of −39.13 kcal/mol. Hence, this study reveals that all the generated AMPs can serve as therapeutic drug in treating cancer by inhibiting Slc2a4 which is responsible for the production of energy for cancer cells during angiogenesis. This is the first report on AMPs as inhibitors of Slc2a4 for the treatment of cancer.

As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, and surveillance. Meanwhile, fast and efficient point-of-care (POC) testing and self-testing kits have become necessary in the fight against COVID-19 and to assist healthcare personnel and governments curb the spread of the virus. This paper presents a review of the various types of COVID-19 detection methods, diagnostic technologies, and surveillance approaches that have been used or proposed. The review provided in this article should be beneficial to researchers in this field and health policymakers at large.

With the exponential increase in new cases coupled with an increased mortality rate, cancer has ranked as the second most prevalent cause of death in the world. Early detection is paramount for suitable diagnosis and effective treatment of different kinds of cancers, but this is limited to the accuracy and sensitivity of available diagnostic imaging methods. Breast cancer is the most widely diagnosed cancer among women across the globe with a high percentage of total cancer deaths requiring an intensive, accurate, and sensitive imaging approach. Indeed, it is treatable when detected at an early stage. Hence, the use of state of the art computational approaches has been proposed as a potential alternative approach for the design and development of novel diagnostic imaging methods for breast cancer. Thus, this review provides a concise overview of past and present conventional diagnostics approaches in breast cancer detection. Further, we gave an account of several computational models (machine learning, deep learning, and robotics), which have been developed and can serve as alternative techniques for breast cancer diagnostics imaging. This review will be helpful to academia, medical practitioners, and others for further study in this area to improve the biomedical breast cancer imaging diagnosis.

Schistosomiasis is one of the major parasitic diseases and second most prevalent among the group of neglected diseases. The prevalence of schistosomiasis may be due to environmental and socio-economic factors, as well as the unavailability of vaccines for schistosomiasis. To date, current treatment; mainly the drug praziquantel (PZQ), has not been effective in treating the early forms of schistosome species. The development of drug resistance has been documented in several regions globally, due to the overuse of PZQ, rate of parasitic mutation, poor treatment compliance, co-infection with different strains of schistosomes and the overall parasite load. Hence, exploring the schistosome tegument may be a potential focus for the design and development of targeted anti-schistosomal therapy, with higher bioavailability as molecular targets using nanotechnology. This review aims to provide a concise incursion on the use of various advance approaches to achieve targeted anti-schistosomal therapy, mainly through the use of nano-enabled drug delivery systems. It also assimilates the molecular structure and function of the schistosome tegument and highlights the potential molecular targets found on the tegument, for effective specific interaction with receptors for more efficacious anti-schistosomal therapy.

An important driving force for precision and individualized medicine is the provision of tailor-made care for patients on an individual basis, in accordance with best evidence practice. Liquid biopsy(LB) has emerged as a critical tool for the early diagnosis of cancer and for treatment monitoring, but its clinical utility for oral squamous cell carcinoma (OSCC) requires more research and validation. Hence, in this review, we have discussed the current applications of LB and the practicality of its routine use in Africa; the potential advantages of LB over the conventional “gold-standard” of tissue biopsy; and finally, practical considerations were discussed in three parts: pre-analytic, analytic processing, and the statistical quality and postprocessing phases. Although it is imperative to establish clinically validated and standardized working guidelines for various aspects of LB sample collection, processing, and analysis for optimal and reliable use, manpower and technological infrastructures may also be an important factor to consider for the routine clinical application of LB for OSCC. LB is poised as a non-invasive precision tool for personalized oral cancer medicine, particularly for OSCC in Africa, when fully embraced. The promising application of different LB approaches using various downstream analyses such as released circulating tumor cells (CTCs), cell free DNA (cfDNA), microRNA (miRNA), messenger RNA (mRNA), and salivary exosomes were discussed. A better understanding of the diagnostic and therapeutic biomarkers of OSCC, using LB applications, would significantly reduce the cost, provide an opportunity for prompt detection and early treatment, and a method to adequately monitor the effectiveness of the therapy for OSCC, which typically presents with ominous prognosis.