University of Nouakchott Al Aasriya

Genetic polymorphisms within the tumor necrosis factor (TNF) cluster have been implicated in several diseases. This exploratory study aimed to assess the role of two polymorphisms (− 308G > A and − 857 C > T) in the TNF-α gene in the risk of developing chronic Hepatitis B virus (CHB) infection in a cohort of Mauritanian patients. We selected 160 subjects, including 82 patients with CHB and 78 spontaneously cured controls. Following PCR amplification, the targeted DNA regions were sequenced using the Sanger method. The TNF-α-308 G > A (rs1800629) wild-type GG genotype was significantly associated with decreased susceptibility to CHB (OR = 0.13 (0.045–0.379), p < 0.001). In contrast, the A mutant allele was identified as a risk factor for HBV persistence (OR = 0.310 (0.132–0.728), p = 0.007). The TNF-α-857 C > T (rs1799724) polymorphism was not associated with CHB, although the minor allele T was linked with a high viral load (OR = 0.14(0.03–0.76), p = 0.022). Our results suggest a possible association between TNF-α-308 G > A (rs1800629) variation and the evolution of HBV infection to a chronic state in Mauritanian patients.

The northern coast of Mauritania presents a strategic opportunity for clean energy investment due to its remarkable potential for green hydrogen production through wind energy. To determine the best location for wind-based green hydrogen production, this paper established a Multi-Criteria Decision-Making framework (MCDM) that combines the Analytic Hierarchy Process (AHP) and Evidential Reasoning (ER) to assess five coastal sites: Nouakchott, Nouamghar, Tasiast, Boulanoir, and Nouadhibou. Four main criteria (i.e., economic, technical, environmental, and social) and twelve sub-criteria were taken into account in the assessment. To ensure reliability and contextual accuracy, the data used in this study were obtained from geographic databases, peer-reviewed literature, and structured expert questionnaires. The results indicate that site 5 (Nouadhibou) is the most suitable location for green hydrogen generation using wind energy. Sensitivity analysis confirms the robustness of the ranking results, validating the reliability of the proposed hybrid framework. The findings of this study provide critical, data-driven decision-support insights for investors and policymakers, guiding the strategic development of sustainable wind-based green hydrogen projects along Mauritania’s coastline.

Gastric cancer (GC) remains a significant global health challenge with high mortality rates, often due to late-stage diagnosis. We hypothesize that Raman spectroscopy (RS) (a modern minimally invasive technique that uses light to analyze the molecular composition of tissue, generating a unique "fingerprint" that reveals biochemical details, distinguishing between normal and diseased tissues.) when combined with Machine learning (ML) would provide accurate and expedite approach of detecting GC. We aim to meta-analyze the diagnostic accuracy of ML-enhanced RS in differentiating GC component from normal tissue.This study was conducted following PRISMA-DTA guidelines. We searched PubMed, Scopus, Web of Science, VHL, and Google Scholar up to the end of February 2025. with an updated search conducted on 14 July 2025. We included any peer-reviewed manuscript that assessed ML-based RS technique for detecting GC components against normal control during endoscopy and reported sufficient data to construct 2 × 2 contingency table for assessing basic diagnostic metrics such as the sensitivity and specificity were included. Methodological quality of studies deemed eligible was assessed using QUADAS-2 risk of bias tool. Data on true positives, true negatives, false positives, and false negatives were extracted to calculate pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (AUC) using R software. Heterogeneity was assessed with I2 statistics and Deeks' funnel plot was employed to examine potential publication bias. Moreover, we further subgrouped individual study metrics based on source of sample, RS technique, AI model, and the experimental context to assess their role in solidify results by controlling several confounders for heterogeneity.A total of 28 studies were enrolled comprising 2,392 patients and 8861 gastric spectra. Twenty-one studies (75%) applied per-spectra approach to analyze the diagnostic utility for GC tissue detection from non-pathological tissue. On the other hand, seven studies (25%) approached analysis as of per-patient stratification evaluating GC patients from healthy subjects. The pooled estimates of the sensitivity and specificity of per spectra approach yielded 92% (95% CI: 88-95%) and 93% (95% CI: 89-96%), respectively, and the AUC was 0.955. On the other hand, the pooled analysis of studies implemented per patient assessment approach yielded excellent sensitivity, specificity, and AUC as well with 95% (95% CI: 87-98%), 93% (95% CI: 89-95%), 0.928, respectively. Subgroup analyses showed that studies using the KNN model demonstrated the highest diagnostic accuracy. Conventional Raman spectroscopy also achieved superior performance across most metrics. Serum-based samples yielded higher sensitivity and specificity than tissue samples, though the limited number of serum studies warrants cautious interpretation. In vitro studies showed slightly better diagnostic accuracy than in vivo studies, although the difference was not statistically significant. Substantial heterogeneity was observed across per-spectra studies (I² = 82.1% for sensitivity and 91.2% for specificity), but no significant between-study variation was observed in per-patient analyses (I² = 27.3% for sensitivity and I² = 0% for specificity). No substantial publication bias was detected based on Deeks' funnel plot asymmetry test, with p = 0.394 for the per-spectra analysis and p = 0.858 for the per-patient analysis.Our meta-analyses' results provide strong evidence that ML-enabled RS from different body sources and across various ML algorithms subtypes significantly improve the GC detection rate and is superior at differentiating GC from healthy tissue during upper GI endoscopy. This approach led to a more precise and real-time decision-making regarding biopsy and excision, given our excellent diagnostic accuracy and low between-study heterogeneity that we obtained, integrating ML-enhanced detection of significant spectra into clinical workflows as valuable diagnostic adjunct particularly during the endoscopy will optimize false negative rate and overall patient outcomes.

In many countries, population growth, rapid urbanization, industrialization, and the irrational use of fertilizers and pesticides are severely disrupting natural environments, leading to an imbalance in ecosystems and generating physico-chemical and biological pollutants in receiving aquatic environments, and changing their uses, such as drinking water collection, livestock watering, and bathing. The objective of our study is to analyze the spatial and temporal variations in the physicochemical properties of Lake Kankossa waters. The study is based on four sampling campaigns conducted over a two-year period, between 2017 and 2021, covering seven representative sampling points: Exploitation, ElVak, ElHakem, Essak, Harth Ewlad Emin, ElHachya, and ElBir. The parameters analyzed are: pH, temperature, turbidity, suspended solids, conductivity, major ions, calcium, magnesium, sodium, potassium, nitrate, nitrite, sulfate, and chloride. Recorded temperatures range from 24 to 25.1 °C in March and October, and from 32 to 38.7°C in September and April. The pH is slightly neutral to very alkaline, varying between 7.28 and 10.93, sometimes reaching 11. Recorded conductivity values fluctuate between 158 and 460 μS/cm during humid periods and decrease to between 210 and 377 μS/cm during dry periods. Average turbidity and suspended solids (SS) levels peak during winter (134–148 mg/L and 317.5 NTU).

This study was conducted with a profound sense of urgency and has provided significant results that will complement previous studies carried out in Mauritania-a country with unique socio-economic and healthcare characteristics-to monitor the epidemiological situation of coronavirus disease 2019 (COVID-19). The study aimed to comprehensively and rigorously investigate the epidemiological profile of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains circulating in Mauritanian patients. This descriptive study was carried out on 84 patients at the Cheikh Mohamed Ben Zayed Hospital and the National Institute of Hepato-Virology in Nouakchott. The samples were sequenced by next-generation sequencing (NGS) of the Illumina NextSeq 2000 type. The data were analyzed by the EPI Info 7 and SPSS 21 software. The average age of the patients was 51 years, and the distribution of cases by age showed that the virus did not select a specific age group. The results indicated that the most frequent variant was Delta (33.33%). The death rate was very high (34.52%) compared to the national death rate, with a peak in the 58-69 years age group. This study provides an overview of the epidemiological characteristics of COVID-19 in Mauritania. These findings not only help identify what policies or strategies should be designed to combat the COVID-19 pandemic, but also pave the way for a more effective response to similar pandemics in the future.

Background: Placenta accreta spectrum (PAS) represents an increasingly prevalent global health concern, associated with significant maternal morbidity and mortality. The burden is particularly critical in low-income countries. This study reports the experience of Mauritania in the management of PAS.Methodology: A retrospective cross-sectional observational study was conducted at the Mother-Child Hospital Center of Nouakchott (CHME), the national referral center for gynecological, obstetric, and pediatric pathologies, between January 1, 2023, and December 31, 2024. All cases of PAS diagnosed and managed during this period were included.Results: A total of 25 cases of PAS were identified among 16,658 deliveries, corresponding to an incidence of 1.50 per 1,000 births (0.15%). The mean maternal age was 35.3 years. The main risk factors observed were previous cesarean section, high multiparity, and advanced maternal age. Blood transfusion was a cornerstone of management. Most patients underwent primary radical surgical treatment with cesarean hysterectomy. Surgical complications represented the main adverse outcomes.Conclusions: PAS is an emerging and challenging reality in Mauritania. The high prevalence of risk factors and the frequent need for transfusion emphasize the importance of establishing dedicated referral centers. Planned, multidisciplinary, and early management in specialized facilities is crucial to improving maternal and perinatal outcomes.

This three-dimensional numerical study investigates the combined effects of magnetic fields, carrier collection velocity at the p-n junction, and base thickness on the photogenerated current density in bifacial polycrystalline silicon solar cells. The model uses a columnar geometry centered on a single grain with front, rear, or dual-side illumination, representing realistic configurations of modern photovoltaic systems. The results demonstrate that the applied magnetic field reduces carrier mobility, degrading transport properties by lowering both the diffusion coefficient and diffusion length, which impacts the overall efficiency of the solar cell. Carrier collection velocity plays a crucial role as a key parameter, determining the transition between open-circuit (zero current) and short-circuit (maximum current) operating modes, and is highly sensitive to changes in the cell structure. Additionally, the base thickness significantly influences carrier collection efficiency: thinner bases show better performance under magnetic field conditions, as they reduce the path length for carrier diffusion. Bifacial illumination enhances the overall photocurrent by utilizing both the front and rear surfaces of the cell, but remains sensitive to the combined effects of magnetic fields, recombination, and geometry. This study provides valuable insights into how the physical configuration of solar cells can be optimized, suggesting that adjusting the base thickness and controlling recombination mechanisms can significantly improve the performance of photovoltaic systems in environments disturbed by magnetic fields or other external factors. The findings are relevant for designing more efficient bifacial solar cells in real-world applications.