Introduction: Cancer is a major public health problem and a global leading cause of death where the screening, diagnosis, prediction, survival estimation, and treatment of cancer and control measures are still a major challenge. The rise of Artificial Intelligence (AI) and Machine Learning (ML) techniques and their applications in various fields have brought immense value in providing insights into advancement in support of cancer control. Methods: A systematic and thematic analysis was performed on the Scopus database to identify the top 100 cited articles in cancer research. Data were analyzed using RStudio and VOSviewer.Var1.6.6. Results: The top 100 articles in AI and ML in cancer received a 33 920 citation score with a range of 108 to 5758 times. Doi Kunio from the USA was the most cited author with total number of citations (TNC = 663). Out of 43 contributed countries, 30% of the top 100 cited articles originated from the USA, and 10% originated from China. Among the 57 peer-reviewed journals, the “Expert Systems with Application” published 8% of the total articles. The results were presented in highlight technological advancement through AI and ML via the widespread use of Artificial Neural Network (ANNs), Deep Learning or machine learning techniques, Mammography-based Model, Convolutional Neural Networks (SC-CNN), and text mining techniques in the prediction, diagnosis, and prevention of various types of cancers towards cancer control. Conclusions: This bibliometric study provides detailed overview of the most cited empirical evidence in AI and ML adoption in cancer research that could efficiently help in designing future research. The innovations guarantee greater speed by using AI and ML in the detection and control of cancer to improve patient experience.

Indigenous Sudanese cattle are mainly indicine/zebu (humped) type. They thrive in the harshest dryland environments characterised by high temperatures, long seasonal dry periods, nutritional shortages, and vector disease challenges. Here, we sequenced 60 indigenous Sudanese cattle from six indigenous breeds and analysed the data using three genomic scan approaches to unravel cattle adaptation to the African dryland region. We identified a set of gene-rich selective sweep regions, detected mostly on chromosomes 5, 7 and 19, shared across African and Gir zebu. These include genes involved in immune response, body size and conformation, and heat stress response. We also identified selective sweep regions unique to Sudanese zebu. Of these, a 250 kb selective sweep on chromosome 16 spans seven genes, including PLCH2, PEX10, PRKCZ, and SKI, which are involved in alternative adaptive metabolic strategies of insulin signalling, glucose homeostasis, and fat metabolism. Our results suggest that environmental adaptation may involve recent and ancient selection at gene-rich regions, which might be under a common regulatory genetic control, in zebu cattle.

Background: Dengue fever (DF) is an arthropod-borne disease caused by dengue virus (DENV). DENV is a member of the genus Flavivirus in the family Flaviviridae. Recently, DENV has been reported as an important emerging infectious viral pathogen in Sudan. Multiple outbreaks and sporadic cases of DF have been frequently reported in the eastern region of Sudan. The present study was conducted to confirm DENV outbreak in Kassala State, eastern Sudan, 2019, and to provide some information on the molecular characterization of the DENV isolate associated with the disease outbreak. Methods: A hundred serum samples were collected during the outbreak from residents of Kassala State, Sudan, 2019. ELISA was used to detect DENV non structural protein NS1 (DENV-NS1) in acute phase sera sampled during the disease outbreak. RT-PCR assays were used to amplify a fragment of the capsid/pre-membrane region (CprM) of the viral polyprotein gene. The PCR products of the amplified CprM region of the viral polyprotein gene were purified and partial sequences were generated and used to confirm the specificity of DENV sequences and to identify the virus serotype. Phylogenetic tree was constructed to determine the genotype of DENV associated with the outbreak. Results: Using DENV-NS1 ELISA assay, DENV infection was confirmed in 23% sampled sera. The detection of DENV RNA was made possible using group-specific RT-PCR assay. The virus was serotyped as DENV serotype 3 (DENV-3) using DENV serotype-specific RT-PCR assay. Phylogenetic analysis of the partial CprM sequences of the viral polyprotein gene indicates that the virus belonged to genotype III of DENV-3. Conclusion: The scientific data presented in this investigation confirmed that genotype III of DENV-3 was associated with the disease outbreak in eastern Sudan, 2019. The study represents the first report on molecular characterization of DENV-3 in Sudan.

Adipose-derived mesenchymal stem cells (AdMSC) are multipotent adult mesenchymal cells isolated and cultured from the stromal vascular fraction derived from adipose tissue. The present study was conducted to analyze the global trends in AdMSC research using bibliometric and visual analysis tools. The literature search was done on February 13, 2022, using appropriate keywords and inclusion-exclusion criteria from the Scopus database. The extracted data were retrospectively analyzed and visualized using Bibliometrics and R packages and VOSviewer. Preliminary analysis identified 1569 documents from the Scopus database published between 2005 and 2021. The average citations received per document was 26.51, whereas the average citations per year per document was 3.347. In addition, the selected documents had an h-index value of 90. China was the most productive country, whereas Seoul National University (South Korea) was identified as the most productive institute/university in AdMSC research. In addition, the National Natural Science Foundation of China funded the most research studies in AdMSC research. The findings from this study indicate a progressive increase in interest among the research community towards AdMSC, suggesting promising prospects in the coming years.

Objective. The rise of zoonotic diseases has become a global health issue around the world. The present study is aimed at assessing the global status and the trends in scrub typhus (ST) research. Methods. Publications related to ST studies from 1945 to 21^st July 2020 were retrieved from the Scopus database. The search for the ST literature was conducted using the entry terms of the MeSH (Medical Subject Headings) database. Full research articles and reviews were included in the analysis, and no limitation to the language was specified. Key bibliometric indicator analysis was performed using Microsoft Excel, Bibliometrix (an R package), GraphPad Prism 5, and VOSviewer (version 1.6.6). Results. A total of 1567 publications were retrieved. The results revealed a significant increase in the number of ST publications over time. The documents received an average of 11.22 citations per document. Mahidol University in Thailand (258, 16.46%) was the most productive institution, while the American Journal of Tropical Medicine and Hygiene published the most ST articles (88, 5.62%). Korea (195, 12.44%) was the most productive country, followed by India (178, 11.36%) and China (106, 6.76%). Richards AL was the most productive author with 36 articles. Conclusions. The study findings provide useful insights into the global efforts and works related to the progress of ST research, which can be used to identify future research areas, such as vaccine development.