REVIEW OF PAST AND PRESENT EBOLA HEMORRHAGIC FEVER OUTBREAKS IN THE DEMOCRATIC REPUBLIC OF CONGO 1976 -2014

Background: Ebola Hemorrhagic Fever (EHF) has become well known all over the world, especially following the West African outbreak in Guinea, Sierra Leone and Liberia (December 2013). The Ebola virus was first discovered in the Democratic Republic of Congo (DRC), an African country that has continued to register Ebola outbreaks. This study aims to summarize old and new experiences of Ebola in the DRC, in order to propose strategies for better prevention. Materials and Methods: Information was taken from databases such as PubMed and Cochrane library. A total of eleven full text and three abstracts were identified for the data extraction. Results: Since its discovery in the DRC, there have been seven Ebola outbreaks, accounting for a total of 1032 cases and 795 deaths. The presence of Non-Human Primates, also considered as the natural reservoir and susceptible host of Ebola virus, can be one major factor that has contributed to the increased number of Ebola outbreaks and cases in the Equatorial region. The existence of rumors and legends related to Ebola in DRC obscure the the viral nature of the disease, and lead to difficulty for health workers, to easily accomplish their tasks. Conclusion :It is important ,to scale up community education campaigns designed to give more details on the viral nature of the EHF, establish national agencies and institutions specialized in controlling hunting in the Equatorial region, for better prevention, since there is not yet a specific drug or vaccine to the Ebola Virus

A Historical Review of Ebola Outbreaks

Ebola Virus Disease (EVD) is a severe, often fatal illness in humans caused by the Ebola virus. Since the first case was identified in 1976, there have been 36 documented outbreaks with the worst and most publicized recorded in 2014 which ravaged three West African Countries, Guinea, Liberia and Serial Leone. The West African outbreak recorded 28,616 human cases, 11,310 deaths (CFR: 57–59%) and left about 17,000 survivors, many of whom have to grapple with Post-Ebola syndrome. Historically, ZEBOV has the highest virulence. Providing a historical perspective which highlights key challenges and progress made toward detecting and responding to EVD is a key to charting a path towards stronger resilience against the disease. There have been remarkable shifts in diagnostics, at risk populations, impact on health systems and response approaches. The health sector continues to gain global experiences about EVD which has shaped preparedness, prevention, detection, diagnostics, response, and recovery strategies. This has brought about the need for stronger collaboration between international organizations and seemingly Ebola endemic countries in the areas of improving disease surveillance, strengthening health systems, development and establishment of early warning systems, improving the capacity of local laboratories and trainings for health workers

Mental Health Consequences of being Raped in the Eastern Region of the Democratic Republic of Congo

Rape has been used as a weapon of war in a lot of countries, including the Democratic Republic of Congo (DRC). In eastern Congo, the prevalence and intensity of rape and other acts of sexual violence are described as the worst in the world. Considered as a public health problem, rape in this region has a lot of impact on the mental health of the population. A convenient sampling method was used to identify female rape victims who reported to Heal Africa hospital in Goma (Eastern DRC) and had developed mental disorders from July 2012 to March 2013. The DSM IV Scale was used to assess the mental state of the victims and after diagnosis, three groups of mental responses were considered: Post Traumatic Syndrome Disorder (PTSD), Major Depressive Disorder (MDD), comorbid PTSD/depression. Chi-square test was used to ascertain if any association existed between socio-demographic characteristics of the victims, types of rape, social rejection and the mental response of the victims. A total of 69 subjects met these criteria and were enrolled for the study. Results from the single factor analysis revealed that Social rejection (p=0.00), the type of rape (p=0.03) and residential area (p=0.04) were significantly related to the mental disorders of the victims. The findings of this study suggest strategies for better health care of women who are victims of sexual violence in the eastern DRC

Construction of a prognostic model based on eight ubiquitination-related genes via machine learning and potential therapeutics analysis for cervical cancer

Introduction: Ubiquitination is involved in many biological processes and its predictive value for prognosis in cervical cancer is still unclear.Methods: To further explore the predictive value of the ubiquitination-related genes we obtained URGs from the Ubiquitin and Ubiquitin-like Conjugation Database, analyzed datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases, and then selected differentially expressed ubiquitination-related genes between normal and cancer tissues. Then, DURGs significantly associated with overall survival were selected through univariate Cox regression. Machine learning was further used to select the DURGs. Then, we constructed and validated a reliable prognostic gene signature by multivariate analysis. In addition, we predicted the substrate proteins of the signature genes and did a functional analysis to further understand the molecular biology mechanisms. The study provided new guidelines for evaluating cervical cancer prognosis and also suggested new directions for drug development.Results: By analyzing 1,390 URGs in GEO and TCGA databases, we obtained 175 DURGs. Our results showed 19 DURGs were related to prognosis. Finally, eight DURGs were identified via machine learning to construct the first ubiquitination prognostic gene signature. Patients were stratified into high-risk and low-risk groups and the prognosis was worse in the high-risk group. In addition, these gene protein levels were mostly consistent with their transcript level. According to the functional analysis of substrate proteins, the signature genes may be involved in cancer development through the transcription factor activity and the classical P53 pathway ubiquitination-related signaling pathways. Additionally, 71 small molecular compounds were identified as potential drugs.Conclusion: We systematically studied the influence of ubiquitination-related genes on prognosis in cervical cancer, established a prognostic model through a machine learning algorithm, and verified it. Also, our study provides a new treatment strategy for cervical cancer