Institut Supérieur de Technique Médicale

L’accès à une eau de boisson salubre demeure un défi majeur de santé publique dans de nombreux pays africains, notamment en République Démocratique du Congo. A Mbujimayi, la faiblesse du réseau public de distribution, la dépendance aux sources alternatives et les déficiences d’assainissement exposent les populations à des risques sanitaires importants. Cette étude a été conduite dans le but de déterminer la qualité physico-chimique et microbiologique de différentes eaux de boisson issues de différentes sources selon les saisons et d’en estimer les risques sanitaires associés, et ce, par rapport aux normes de l’Organisation Mondiale de la Santé (OMS). C’est une étude descriptive analytique transversale réalisée sur 62 échantillons d’eau collectés dans 31 sites représentant sept types de sources d’approvisionnement. Les analyses ont été effectuées selon des méthodes normalisées et des procédures opérationnelles validées. Les risques sanitaires ont été évalués par une matrice OMS et une approche QMRA. Les résultats montrent une forte variabilité saisonnière. La saison sèche est marquée par une minéralisation accrue et des dépassements de certaines valeurs guides chimiques, tandis que la saison des pluies est caractérisée par une contamination microbiologique élevée. La convergence des analyses physico-chimiques, microbiologiques et de l’évaluation quantitative du risque microbiologique (QMRA) indique que plus de 70 % des sources étudiées présentent un niveau de risque infectieux modéré à critique, incompatible avec une consommation directe sans traitement préalable. La qualité des eaux de boisson à Mbujimayi est donc globalement non conforme aux normes OMS, justifiant la mise en oeuvre urgente de stratégies intégrées de gestion du risque.

Sickle cell disease (SCD) is a common and potentially life-threatening haematological disorder. In high-income countries, universal newborn screening and timely interventions have markedly reduced infant mortality. In contrast, in low-resource settings, diagnosis often occurs only in late childhood, once clinical manifestations have developed. The high cost, technical complexity, and limited availability of conventional diagnostic methods remain major barriers to implementing neonatal screening programmes in sub-Saharan Africa and other resource-constrained regions. We assessed the diagnostic performance of Sickle SCAN®, a prototype rapid immunoassay designed to qualitatively detect HbA, HbS, and HbC. The test is based on a lateral flow immunoassay format and provides results at the point of care. Cord blood samples from 365 newborns were analysed with Sickle SCAN® and results were compared against the reference standard of capillary electrophoresis. Sickle SCAN® accurately identified haemoglobin phenotypes in 97.3% of cases (95% CI: 95.0%-98.7%). For HbAA, sensitivity was 97.8% (95% CI: 94.9%-99.3%) and specificity was 96.5% (95% CI: 92.0%-98.9%). For HbAS, sensitivity was 95.8% (95% CI: 90.5%-98.6%) and specificity 98.0% (95% CI: 95.3%-99.3%). Importantly, no false-positive or false-negative results were observed for HbSS and HbAC, yielding 100% sensitivity and specificity for these phenotypes. Our findings demonstrate that Sickle SCAN® is a highly accurate, rapid, and low-cost tool for neonatal SCD screening. Its use could substantially reduce diagnostic delays, lower programme costs, and improve accessibility to early detection in resource-limited settings, thereby contributing to improved child survival.

Le cancer de la prostate constitue l’un des principaux problèmes de santé publique chez l’homme à l’échelle mondiale. Le diagnostic précoce et précis demeure un défi majeur, en particulier pour la détection des lésions de faible volume et des récidives précoces. L’imagerie par tomographie par émission de positons (TEP) utilisant des radiopharmaceutiques ciblant l’antigène de membrane spécifique de la prostate (PSMA) a considérablement amélioré la prise en charge diagnostique. Dans cette étude, une approche de modélisation moléculaire in silico a été employée afin d’analyser et de comparer les interactions entre deux radiopharmaceutiques marqués au fluor-18, le Piflufolastat F-18 et le Flotufolastat F-18, et plusieurs cibles biologiques impliquées dans le cancer de la prostate, notamment le récepteur des androgènes (AR), HIF-1α, HER2 et le PSMA. Le docking moléculaire a permis d’évaluer les affinités de liaison et d’identifier les interactions stabilisantes au niveau atomique. Les résultats montrent que les deux radiopharmaceutiques présentent une forte affinité pour le PSMA, avec des énergies de liaison particulièrement favorables, confirmant leur pertinence en imagerie diagnostique. Par ailleurs, le Piflufolastat F-18 est un ligand multi-cible, ce qui peut limiter sa sélectivité, tandis que le Flotufolastat F-18 est très sélectif. Cette étude met en évidence l’intérêt de la modélisation moléculaire comme outil complémentaire pour la compréhension des interactions ligand-récepteur et pour l’optimisation future des radiotraceurs PSMA-ciblés.

To enhance carp production, four experimental diets formulated from locally available raw materials and incorporating varying proportions of banana flour were evaluated. Each diet was standardized to contain 36% crude protein and 8% lipids. The feeds were administered to common carp (Cyprinus carpio) fingerlings with an initial mean weight of 9 g. After a 50-day feeding trial conducted in both pond and tank rearing systems, comparable growth performances were observed across treatments. Final weight gain (WG) ranged from 120.88 g to 125.08 g, while daily weight gain (DWG) varied between 2.21 g/day and 2.31 g/day. The specific growth rate (SGR) remained consistent across treatments, ranging from 2.46% to 2.49%. Feed conversion ratios (FCR) were similarly efficient in both systems, ranging from 1.15 to 1.16, and survival reached 100% in all cases. Although ponds demonstrated a marginal advantage in DWG, tank systems compensated through tighter control of feeding regimes and water quality. Overall, the findings demonstrate that effective management can ensure similar levels of performance across both rearing environments. These results also highlight the potential of incorporating banana flour into carp feed formulations as a viable strategy within sustainable aquaculture systems.

Aquaculture in Madagascar is experiencing significant growth, although its potential remains largely underexploited. Between 2021 and 2023, national production increased from 16,000 to 37,000 tons, mainly thanks to the development of rice cultivation and marine algoculture. This increase partially contributes to the nutritional needs of the 28 million inhabitants, in a context where nearly 45% of children suffer from malnutrition, especially in rural areas of the Highlands. Rice cultivation, combining rice cultivation and fish farming on the same plot, increases household incomes by about 30%, while reducing water consumption and supporting biodiversity. The expansion of 17 emergence fish farming areas and the support of 1,000 fish farming families reflect this positive dynamic. At the same time, the shrimp sector remains fragile, affected by overfishing and recent pathological episodes. Economically, aquaculture contributes about $140 million in exports, while national consumption reaches 8 kg/inhabitant/year, a level below the regional average. Compared to East African countries, Madagascar is distinguished by the efficiency of its extensive systems, but is lagging behind in the modernization of infrastructure, particularly in rural areas. The outlook for 2030 envisages the extension to 70 fish areas, the adoption of innovative processes such as biofloc and artificial intelligence, as well as the strengthened establishment of marine protected areas, in order to respond to the challenges of drought, fishing overloads and food security. Overall, Madagascar appears as an emerging model of sustainable aquaculture in southern Africa, gradually transforming its structural constraints into opportunities for food resilience, agro-ecological innovation and rural employment.

The aim of this study was to investigate the perception of climate change and its impact on agriculture in the Ubanguienne eco-region of the Democratic Republic of Congo. The stratified probability sampling method was used. The majority of respondents were men (64.0%) with secondary education, of whom 59.5% were farmers, most of whom were married (74.5%). The majority of respondents were Ngbandi (23.0%). 59.0% of respondents felt that the impact was high. The majority (96.5%) of respondents were aware of the effects of the change. 59% of respondents felt that the impact of climate change on agriculture was high. Of these changes, 52.7% of respondents had modified the crops grown. Respondents' main concerns included degradation of agri-cultural land (35.5%), loss of farm income (34.0%), and food security (30.0%), while 0.5% mentioned other concerns.

Background:Obstetric fistula (OF) is a severe and debilitating complication of childbirth that primarily affects women in developing countries, particularly the Democratic Republic of the Congo. It results in chronic urinary and/or fecal incontinence, often accompanied by social isolation, stigma, and psychological distress, thereby having a profound negative impact on the quality of life of affected women.Objectives:This study aims to evaluate the level of awareness and knowledge regarding OF among Congolese women of reproductive age in the North Kivu Province.Design:This is a community-based, cross-sectional study.Methods:A two-stage cluster random sampling method was employed to select a sample of 500 women aged 15–49 years. Data were collected using a pretested, semi-structured questionnaire administered through face-to-face interviews. The questionnaire gathered information on sociodemographic characteristics, reproductive history, and knowledge of OF. Data were analyzed using descriptive statistics and binary logistic regression to identify factors associated with a good OF knowledge.Results:The mean age of respondents was 33.7 ± 10.4 years. Among the 467 surveyed, 22.7% demonstrated good OF knowledge. Urban residence (adjusted odds ratio, aOR = 2.8, 95% CI [1.6–4.6]; p < 0.0001), being single (aOR = 2.6, 95% CI [1.3–4.6]; p = 0.0078), lack of professional occupation (aOR = 1.7, 95% CI [1.0–2.7]; p = 0.0407), use of family planning services (aOR = 1.9, 95% CI [1.2–3.2]; p = 0.0111), and personally knowing someone who had suffered from OF (aOR = 9.6, 95% CI [2.0–46.9]; p = 0.0052) were independently associated with good OF knowledge.Conclusion:The study revealed that a substantial proportion of women in North Kivu province have limited knowledge about OF. Strengthening awareness and education efforts, particularly in rural settings, is essential to promote early recognition of symptoms and timely care-seeking behavior. Targeted health education programs and community-based interventions are crucial to improving understanding and reducing the burden of this preventable condition. Moreover, identifying the determinants of good OF knowledge can inform the design of more effective prevention and intervention strategies at the elimination of this condition.

La présente étude a pour objectif d’évaluer les connaissances sur les moyens de prévention et de dépistage du VIH/sida des para médicaux de l’hôpital général de référence de N’djili dans la ville de Kinshasa en RDC. Il s’agit d’une étude descriptive transversale, réalisée durant la période allant du 01 Janvier au 30 juin 2012. Les résultats obtenus avaient montré dans plus de la moitié des enquêtés que l’acquisition des connaissances sur le VIH/sida, la part de l’institution de formation étaient très remarquée chez les enquêtés. La variante école et séminaire a été mis en évidence chez 23,6 % de la population interviewée. Cette étude nous a permis de déterminer le niveau des connaissances des paramédicaux de l’Hôpital Général de Référence de N’djili/ Kinshasa, elle nous a permis également de voir comment ces enquêtés ne sont pas suffisamment informés sur les mesures de prévention de VIH/sida qui est la pandémie du siècle.

Les violences sexuelles basées sur le genre est un réel problème de santé publique et qui a des conséquences incalculables sur les survivantes. Cet article vise à décrire les aspects épidémiologiques et de prise en charge des abus sexuels à l’Hôpital Général de Référence (HGR) de N’djili. Il s’agit d’une étude transversale descriptive réalisée auprès de 483 victimes des abus sexuels reçues pour les soins à l’HGR de N’djili durant la période du 1er Janvier au 31 Décembre 2021. Les données étaient analysées à l’aide du logiciel SPSS 21. Les variables qualitatives ont été exprimées en pourcentage et les quantitatives en moyenne accompagné de l’écart type. Les victimes d’abus avaient un âge moyen de 15,1±5,4 ans et 99,2 % étaient de sexe féminin. Les agresseurs avaient un âge moyen estimé à 24,3 ± 10,2 ans et parmi eux 96% étaient de sexe masculin dont 82,4 % étaient des agresseurs bien connus (39,9 % étaient des copains, 20,1 % étaient des voisins, 6,8 % étaient des membres de famille). En conclusion, on peut dire que les agressions sexuelles constituent un véritable problème de santé publique au vu de l’ampleur du phénomène et des conséquences qui en découlent sur la santé principalement des femmes.

The topics covered in this article include the creation of a bootstrap learning model for depression predictions based on the Random Forest technique. Depression is a severe mental illness that affects millions of people worldwide. This condition causes great pain and affects quality of life, and in the most severe cases, the person takes their own life. Depression has a high incidence, but diagnosis is always complex and often delayed. It is made on the basis of clinical assessment, which is subjective, and questionnaires, which are often inaccurate and cannot identify people at risk early enough because a person's subjective perception can often be distorted. In this context, and to illustrate our point, we aim to show how AI, and more specifically machine learning, can provide innovative applications that can be used to improve early detection cf. prevention of depression risk. Instead of stupidly defining score intervals for a child, we can train a model on a dataset to identify patterns and correlations that escape simple regression analyses. Then, we can anticipate the first signs of log-in with depression, or we can identify which combinations of self and family history are most concerning. To complement our study, we chose the decision tree ensemble algorithm. The article highlights the need for more objective and effective prediction tools for depression, and proposes a machine learning-based solution to achieve this, potentially leading to earlier intervention and better patient care.