Search

Raoul Emeric Guetiya Wadoum,1,&ast; Stephen Sevalie,2,&ast; Maurice Baimba Kargbo,3 Andrew Clarke,4,5 Sherry Bangura,6 Mariatu Kargbo,6 Hawa Mariama Sesay,7 Abdul H Kamara,6 Jamil Bangura,6 Alie F Kamara,6 Sophie Allieu,1 Hassan Rogers,1 Maurizio Mattei,8 Vittorio Colizzi,9 Carla Montesano,8 Edwin JJ Momoh1,3 1Department of Public Health, Microbiology and Immunology, Ernest Bai Koroma University of Science and Technology, Makeni, Sierra Leone; 2 34th Military Hospital, The Republic of Sierra Leone Armed Forces, Freetown, Sierra Leone; 3Department of Agriculture and Food Security; Ernest Bai Koroma University of Science and Technology, Makeni, Sierra Leone; 4Global Programs Division, Save the Children UK, London, UK; 5Department/Division of Health Research, Lancaster University, Lancaster, UK; 6Sierra Leone Association of Ebola Survivors, Freetown, Sierra Leone; 7Department of Public Health, University of Makeni, Makeni, Sierra Leone; 8Department of Biology, University of Rome Tor Vergata, Rome, Italy; 9Department of Sciences and Technology, Evangelical University of Cameroon, Bandjoun, Cameroon&ast;These authors contributed equally to this workCorrespondence: Raoul Emeric Guetiya Wadoum; Edwin JJ Momoh, Email ergwadoum@ebkustsl.edu.sl; raoulemeric@gmail.com; emomoh@ebkust.edu.slBackground: The clinical management of persistent medical conditions affecting Ebola survivors, generally described as a post-Ebola syndrome, remains a public health concern. We aimed to analyze Ebola survivors’ laboratory biomarkers as compared to their non-infected household relatives to identify biomarkers that could guide the identification of survivors at increased risk of developing severe at odds with the non-severe post-Ebola syndrome.Materials and Methods: Data were extracted from medical records of the Ebola survivors clinic, and we included only Ebola survivor’s parameters recorded during the first baseline follow-up visit 2 weeks interval after their second negative PCR result. Moreover, household non-infected family contacts of survivors visiting the clinic during the same period were recruited as community control.Results: The mean age of survivors was 32.65 (IQR: 15.5, 38.25) years, and Ebola IgG immunoglobulin was detected in all, thus confirming their status. The statistical significance (all p < 0.05) observed in monocyte percentage (MONO%), cluster of differentiation 4 percentage (CD4%), alanine aminotransferase (ALT), creatinine (CREA), and creatinine kinase (C-kinase) proved to be clinically significant as compared to the household relatives’ group. Interestingly, the linear regression analysis indicated that the duration at ETU was negatively associated with lymphocyte percentage with a 5% lymphocyte decrease per day spent at ETU. Finally, there was a significant (p < 0.05) association between hematological (Hb, PCV, MCV, MCH), biochemical (ALT, CREA, C-kinase, T-cholesterol, triglycerides) parameters and the risk of developing severe complications.Conclusion: We recommend clinicians closely monitor Hb, PCV, MCV, MCH, ALT, CREA, C-kinase, T-cholesterol, triglycerides and lymphocytes as clinically relevant laboratory biomarkers to identify survivors at higher risk of developing severe post-acute syndrome upon discharge from Ebola treatment unit including headache, abdominal pain, chest pain, ocular complication, arthralgia, hearing difficulty and erectile dysfunction which can impact health-related quality of life among Ebola survivors.Keywords: Ebola virus disease, hematological, immunological, biochemical, biomarkers, post-acute syndrome

Raoul Emeric Guetiya Wadoum,1 Stephen Sevalie,2 Antonella Minutolo,3 Andrew Clarke,4,5 Gianluca Russo,6 Vittorio Colizzi,7 Maurizio Mattei,8 Carla Montesano8 1Department of Public Health, Microbiology and Immunology, Ernest Bai Koroma University of Science and Technology, Makeni, Sierra Leone; 2 34th Regimental Military Hospital, The Republic of Sierra Leone Armed Forces, Freetown, Sierra Leone; 3Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy; 4Global Programs Division, Save the Children United Kingdom, London, UK; 5Division of Health Research, Lancaster University, Lancaster, UK; 6Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy; 7Department of Biomedical Sciences, Faculty of Science and Technology, Evangelical University of Cameroon, Bandjoun, Cameroon; 8Department of Biology, School of Mathematics, Physics and Natural Sciences, University of Rome Tor Vergata, Rome, ItalyCorrespondence: Raoul Emeric Guetiya Wadoum Tel +232 78425924Email ergwadoum@ebkustsl.edu.sl; raoulemeric@gmail.comAbstract: The Ebola virus disease, formerly known as Ebola hemorrhagic fever, is a severe and often fatal zoonosis in humans. The 2013– 2016 West African Ebola outbreak had distinctive characteristics, and it was the largest and most complex epidemic since the virus discovery in 1976. Although the 2018– 2020 Ebola outbreak in the Democratic Republic of the Congo had many similarities, there were additional challenges due to the presence of armed rebel groups at the epicenters of the epidemic. Despite these challenges, the extraordinary commitment of the World Health Organization (WHO) regional office for Africa, in collaboration with Africa Union (AU) member states through the Africa Centres for Disease Control and Prevention (Africa CDC), and WHO’s prompt declaration of a Public Health Emergency of International Concern (PHEIC) shepherded an effective coordinated response to contain the epidemic. Learning from previous Ebola virus epidemics and the current Coronavirus disease 2019 (COVID-19) pandemic, the AU member states should strengthen inter-state coordination towards the development and implementation of a preparedness and readiness plan which will enable the continent to build and sustain resilient capacities to prevent, detect, and respond to future outbreaks following the International Health Regulations (IHR).Keywords: United Nations, Africa Union, WHO, Africa CDC, Ebola virus disease, COVID-19

Béatrice Dambaya,1,2 Céline Nguefeu Nkenfou,1,3 Linda Mekue,1,4 Georges Této,1 Nicole Ngoufack,1,2 Georgia Ambada,1,2 Njiokou Flobert,1 Vittorio Colizzi,5 Ndjolo Alexis1,6 1Chantal BIYA International Reference Centre for Research on HIV/AIDS Prevention and Management (CBIRC), Yaoundé, Cameroon; 2Department of Animal Biology, Faculty of Sciences, University of Yaounde I, Yaoundé, Cameroon; 3Department of Biological Sciences, Higher Teachers’ Training College, University of Yaounde I, Yaoundé, Cameroon; 4Department of Biochemistry, Faculty of Sciences, University of Dschang, Dschang, Cameroon; 5Department of Immunology, University of Rome Tor Vergata, Rome, Italy; 6Department of Ear, Nose and Throat, Faculty of Medicine and Biomedical Sciences, University of Yaounde I, Yaoundé, CameroonCorrespondence: Céline Nguefeu NkenfouHigher Teacher Training College, University of Yaounde I, P.O. BOX 47, Yaounde, CameroonTel +675573519Email nkenfou@yahoo.comBackground: Children show various degrees of vulnerability regarding HIV infection and disease progression. This disparity presents challenges for the follow-up of infected children. Here we investigated reasons behind this variability focusing on some host-related HIV genes.Methods: We screened 570 Cameroonian children and adolescents, aged 1 to 19 years old. Among them, 137 were followed over 4 years, from 2010 to 2015. Upon signing a proxy consent, children and adolescents were classified according to their age, CD4 count, viral load and clinical symptoms as long-term non-progressors (LTNP), slow progressors (SP) and rapid progressors (RP). Their blood was collected every 6 months and used for biological and host genetic polymorphism analyses. Five genes were genotyped: Trim5α (R136Q), CCR5 promoter 59029G, CCR2-64I, SDF 3ʹA and CCR5-Δ32. Exposed non-infected (HEU) and unexposed HIV negative children (HNEU) were recruited as control groups.Results: Among the 5 genes studied, the protective allele of Trim5α (R136Q) was present in all LTNP and in 72.34% and 2.56% of SP and RP, respectively (p

Luciano Giacò,1 Massimo Amicosante,2 Maurizio Fraziano,1 Pier Federico Gherardini,1 Gabriele Ausiello,1 Manuela Helmer-Citterich,1 Vittorio Colizzi,1 Andrea Cabibbo11Department of Biology, 2Department of Internal Medicine, University of Rome "Tor Vergata", Rome, ItalyAbstract: The ability to predict immunogenic regions in selected proteins by in-silico methods has broad implications, such as allowing a quick selection of potential reagents to be used as diagnostics, vaccines, immunotherapeutics, or research tools in several branches of biological and biotechnological research. However, the prediction of antibody target sites in proteins using computational methodologies has proven to be a highly challenging task, which is likely due to the somewhat elusive nature of B-cell epitopes. This paper proposes a web-based platform for scoring potential immunological reagents based on the structures or 3D models of the proteins of interest. The method scores a protein's peptides set, which is derived from a sliding window, based on the average solvent exposure, with a filter on the average local model quality for each peptide. The platform was validated on a custom-assembled database of 1336 experimentally determined epitopes from 106 proteins for which a reliable 3D model could be obtained through standard modeling techniques. Despite showing poor sensitivity, this method can achieve a specificity of 0.70 and a positive predictive value of 0.29 by combining these two simple parameters. These values are slightly higher than those obtained with other established sequence-based or structure-based methods that have been evaluated using the same epitopes dataset. This method is implemented in a web server called B-Pred, which is accessible at http://immuno.bio.uniroma2.it/bpred. The server contains a number of original features that allow users to perform personalized reagent searches by manipulating the sliding window's width and sliding step, changing the exposure and model quality thresholds, and running sequential queries with different parameters. The B-Pred server should assist experimentalists in the rational selection of epitope antigens for a wide range of applications.Keywords: B-cell epitopes, immunoinformatics, bioinformatics, web server, epitope prediction