Abdifetah Ibrahim Omar

Withania somnifera seeds remain understudied compared with roots despite increasing nutraceutical use. This study evaluated safety, metabolic effects, and potential DPP‐4 activity of seed extract (WSS‐E) and powder (WSS‐P) in rats. Twenty male Wistar rats were assigned to five groups ( n = 4/group): control, 0.25% WSS‐E, 0.5% WSS‐E, 0.5% WSS‐P, and 1% WSS‐P for 56 days. Biochemical, hematological, and histopathological outcomes were assessed, whereas major seed phytochemical–DPP‐4 interactions were examined by molecular docking. Data were analyzed by ANOVA and Duncan's test ( p < 0.05). The 0.5% WSS‐E group showed the strongest metabolic response. At Day 56, glucose (85.73 vs. 105.69 mg/dL), triglycerides (78.40 vs. 108.84 mg/dL), total cholesterol (90.55 vs. 104.03 mg/dL), LDL (37.69 vs. 48.53 mg/dL), VLDL (15.70 vs. 21.78 mg/dL), and atherogenic index (2.13 vs. 3.24) were significantly lower than control, whereas HDL was higher (37.19 vs. 33.76 mg/dL; p < 0.05). Creatinine and urea were also significantly lower than control. No overt hepatic, renal, hematological, or histopathological toxicity was observed. Withanone showed strongest predicted DPP‐4 binding (−10.0 kcal/mol), comparable to sitagliptin (−8.4 kcal/mol). Thus, 0.5% WSS‐E provided the most favorable metabolic profile without overt toxicity; long‐term safety and mechanistic studies are warranted.

Diabetes mellitus is characterized by persistent hyperglycemia accompanied by dyslipidemia, oxidative stress, and progressive hepatic, renal, and hematological disturbances. This study evaluated the compositional, antioxidant, and preclinical antidiabetic potential of Trigonella foenum‐graecum (fenugreek) and Nigella sativa (black seed) powders, administered individually or combined, in alloxan‐induced diabetic rats. Fenugreek powder contained high crude fiber (22.1%) and moderate protein (20.5%), whereas black seed powder showed high crude fat (38.9%) and appreciable protein (20.9%). Total phenolic content was substantially higher in black seed powder (185.3 mg ± 7.6 mg GAE/g) than in fenugreek powder (47.1 mg ± 2.0 mg GAE/g), although both exhibited comparable DPPH radical scavenging activity (63.8%–63.9%). Diabetic rats received fenugreek, black seed, or their combination (100 mg/kg body weight) for 28 days alongside healthy and untreated diabetic controls. All treatments improved glycemic status, with the combined treatment producing the greatest HbA1c reduction (8.9% to 5.1%) compared with fenugreek (6.4%), black seed (6.2%), and untreated diabetic rats (8.1%). Treatments also improved dyslipidemia, hematological indices, and hepatic and renal biomarkers, with the combined treatment consistently showing superior efficacy. These findings support fenugreek and black seed powders as bioactive‐rich functional ingredients with complementary glucose‐lowering and organ‐protective effects, highlighting their promise as a multi‐target dietary adjunct against diabetes. Practical Applications: This study demonstrates that the combined use of Trigonella foenum‐graecum (fenugreek) and Nigella sativa (black seed) powders has potential as a functional food ingredient or nutraceutical formulation for dietary management of diabetes. Their complementary bioactive composition improved glycemic control, lipid metabolism, and liver and kidney function in a preclinical model, supporting their application in developing value‐added functional foods, health supplements, and plant‐based therapeutic diets aimed at reducing diabetes‐associated metabolic complications.

Background: Antimicrobial resistance (AMR) constitutes a profound global health crisis, with profoundly disproportionate impacts in low-resource settings (LRS) and conflict-affected regions like Somalia. Traditional laboratory-based surveillance is largely unfeasible in these environments due to resource constraints. This study proposes and preliminarily evaluates an Artificial Intelligence (AI)-driven surveillance framework to predict multidrug resistance (MDR) using minimal, routinely available clinical metadata. Methods: A retrospective cross-sectional analysis was conducted using 262 curated clinical bacterial isolates from Mogadishu, Somalia. A Random Forest machine learning algorithm was trained using five basic variables (patient age, sex, isolated organism, ward, and specimen source) to predict MDR against five sentinel antibiotics. Phenotypic co-resistance was further evaluated using an undirected weighted network analysis. Results: The predictive model achieved an overall accuracy of 66.7% (95% CI: 52.1– 79.2%) and an Area Under the Curve (AUC) of 0.607. Prioritizing its utility as an early-warning triage tool, the model demonstrated an exceptionally high sensitivity (recall) of 91.4%, effectively flagging the vast majority of MDR cases, with a specificity of 12.5%, a precision of 69.6%, an F1-score of 0.79, and a Matthews Correlation Coefficient (MCC) of 0.06. The low MCC indicates that, despite high sensitivity, overall discriminative agreement beyond chance was weak. Variable importance analysis revealed that microbiological factors (organism and specimen source) were the strongest predictors of resistance. Conversely, spatial features (hospital ward) lacked predictive value, indicating widespread transmission. Network analysis identified a fully connected co-resistance topology (degree centrality = 4) among all sentinel antibiotics. Conclusion: High-sensitivity AI models utilizing minimal metadata offer a potentially scalable triage-support approach for MDR surveillance in deeply resource-constrained health systems. Given the modest discriminatory performance, low specificity, small final analytical sample, and the absence of external validation, these findings should be interpreted as a preliminary proof-of-concept rather than evidence of a deployment-ready tool. The findings underscore critical, hospital-wide infection prevention and control (IPC) vulnerabilities and highlight the necessity of implementing digital epidemiological tracking, alongside external validation and benchmarking against alternative algorithms, to guide empiric therapy in East Africa.

Artificial intelligence (AI) is promptly changing the nature of food production and processing to increase safety, efficiency, quality assurance, and sustainability throughout the farm‐to‐fork chain. This review discusses the recent developments in AI in the food manufacturing industry, such as machine learning (ML), deep learning (Dl), computer vision (CV), hyperspectral imaging (HSI), robotics, Internet‐of‐Things (IoT) integration, and natural language processing. These technologies allow detecting contamination and fraud in real‐time, near‐perfect predictive maintenance less 30% unplanned downtime, automated quality checks with up to 96%–100% accuracy, AI‐enabled predictive maintenance (PdM) has demonstrated its effectiveness by decreasing unplanned downtime in industrial case studies through a reduction rate that reaches 30% of total downtime, resource‐efficient smart factories, and creative AI‐driven formulation of products. New paradigms include digital twins, explainable AI, computational gastronomy, and cultured meat production, highlighting the transformative power of AI. Some of the solutions include standardized datasets, lightweight architectures, federated learning, and scalable deployment training programs. When used responsibly, AI can help create food systems that meet regulatory requirements while achieving sustainable development goals and circular economy standards, and all three Sustainable Development Goals, like Zero Hunger (SDG 2), Responsible Consumption and Production (SDG 12), and Climate Action (SDG 13).

Background: Neonatal mortality remains high in Somalia, and inadequate postnatal care (PNC) contributes substantially to preventable maternal and newborn deaths. Although PNC is critical during the first days after childbirth, both access to services and the content of care remain limited. This study examined access to postnatal care and the determinants of receiving appropriate-quality PNC among Somali women. Methods: This cross-sectional study analyzed data from the 2020 Somalia Demographic and Health Survey. The analysis included 2813 women aged 15– 49 years who had a live birth within the five years preceding the survey. Access to PNC was defined as receiving any postnatal check after delivery. Among women who received PNC, appropriate-quality care was defined as receiving all six essential postnatal care components within 48 hours of delivery. Weighted descriptive statistics and multivariable Poisson regression were used to identify factors associated with receiving appropriate-quality PNC. Results: Most women had no formal education and delivered at home. Access to postnatal care was limited, and among women who received PNC, only 3% obtained appropriate-quality care. Coverage of individual postnatal components was consistently low. Husband’s education and adequate antenatal care attendance were strongly associated with higher likelihood of receiving appropriate-quality PNC, while substantial regional disparities were observed. Conclusion: Both access to and quality of postnatal care in Somalia are extremely limited. Expanding skilled maternal services, strengthening antenatal care utilization, and improving community-based postnatal outreach are essential to improve maternal and newborn outcomes.

Lathyrus sativus L. (grass pea) has been receiving growing interest because of its drought resistance and its adaptation to low‐input farming systems, but the biochemical adaptations of L. sativus to divergent environmental conditions are poorly comprehended. The work assessed the consequences of local and climatic differences in proximate composition, phenolic and flavonoid content, antioxidants, antibacterial, and anti‐inflammatory action, and untargeted LCMS/MS metabolomic profiles of L. sativus seeds grown in two Algerian systems: a semi‐arid highland, Ain Defla, and a sub‐humid plain, Sidi Bel Abbès. Ain Defla seeds contained more dry matter (89.2%), crude protein (28.5%), and crude fiber (6.1%) than Sidi Bel Abbès (88.1%, 26.9%, and 5.4%), and the lipid content in Ain Defla was a bit higher (2.8% vs. 2.3%). The total phenols were more in Ain Defla (8.64 ± 0.31 mg GAE g ⁻¹ DW), and flavonoids and condensed tannins were more in Sidi Bel Abbès. Extracts of Ain Defla had greater antioxidant potential in DPPH, ABTS, FRAP, and TBARS, whereas Sidi Bel Abbès extracts were observed to have better antibacterial strength, especially against Staphylococcus aureus and Listeria monocytogenes . LCMS/MS analysis showed the presence of 42 major metabolites, which occupy different regional chemotypes dominated by phenolic acids in Ain Defla, and flavanols and procyanidins in Sidi Bel Abbès. These results support the notion that L. sativus is biochemically flexible and a promising multifunctional legume in agri‐food systems.

Background: Despite global advancements in reproductive healthcare, the utilization of modern contraceptives in Somalia remains critically low, marked by significant regional and sociodemographic disparities. This study assessed the prevalence and identified key predictors of modern contraceptive use among Somali women of reproductive age using data from the 2020 Somali Health and Demographic Survey (SHDS). Methods: A nationally representative cross-sectional analysis was conducted on a sample of 2,704 women aged 15–49 years. Descriptive statistics and multivariable logistic regression were employed to identify factors associated with the use of modern contraceptives. Results: The majority of participants were aged 26 years or older (57.6%), resided in urban areas (85.1%), and belonged to the highest wealth quintile (62.4%). The prevalence of modern contraceptive use among the study participants was exceptionally low at 1.8%. The most commonly reported methods were oral contraceptive pills (0.6%) and implants (0.2%), while the use of intrauterine devices (IUDs) was minimal (0.04%). A significant gap in exposure to family planning information was observed, with only 13.6% of women reported to have received it at health facilities. Key predictors for modern contraceptive use included the age of the women and exposure to family planning education at a health facility. Women aged 26 years and older demonstrated significantly higher odds of using contraception compared to their younger counterparts [adjusted odds ratio (AOR): 10.13; 95% confidence interval (CI): 2.39–42.97]. Furthermore, women who received family planning information from health facilities were twice as likely to use modern contraceptive methods (AOR: 1.99; 95% CI: 1.02–3.88). Conclusion: The findings underscore an urgent need to enhance both the accessibility and knowledge of modern contraceptives in Somalia. Targeted interventions focusing on health facility-based education and expanding the limited variety of available contraceptive methods are crucial to improving uptake and addressing the reproductive health needs of Somali women.

Background: Henoch-Schönlein Purpura (HSP), also known as IgA vasculitis (IgAV), is a common childhood vasculitis that frequently involves the gastrointestinal tract. Its occurrence in adults, particularly in association with Giardia lamblia infection, is exceptionally rare. Case Presentation: We report the case of an 18-year-old female, who presented with severe abdominal pain, hematemesis, and a palpable purpuric rash on her lower limbs. Investigations revealed leukocytosis (WBC: 15.5× 10³/μL), microscopic hematuria, and elevated serum IgA (3.5 g/L). An upper gastrointestinal endoscopy showed diffuse hemorrhagic mucosa consistent with vasculitis. Stool microscopy identified Giardia lamblia trophozoites. A diagnosed of IgA vasculitis with severe gastrointestinal involvement and concurrent giardiasis was established. The patient was treated with intravenous methylprednisolone and metronidazole, resulting in significant clinical improvement. Discussion and conclusion: This case highlights a rare association between IgA vasculitis and an active Giardia lamblia infection, and to our knowledge, is the first such case reported from Somalia. It underscores the presence of IgAV in adults and emphasizes the importance of investigating for co-infections in patients presenting with sever GI symptoms. A comprehensive evaluation is vital for ensuring timely and appropriate management.