Ahmed Khairy

Nanoscale materials can support vaccine delivery, antigen display and immune stimulation, but successful platform function or enhanced immunogenicity does not necessarily establish meaningful or durable clinical protection. This narrative review examines evidence published from January 2016 through April 2026, with selected foundational studies, for nanotechnology-enabled vaccines against malaria, tuberculosis, human immunodeficiency virus (HIV) and dengue, focusing on their relevance to the Global South. These diseases were selected for their substantial public-health burden, distinct biological barriers to vaccination and contrasting stages of translational development, enabling comparison across preclinical research, human immunogenicity, clinical efficacy and implementation evidence. The synthesis distinguishes the functional contribution of nanoscale carriers, antigen-display scaffolds and adjuvants from the performance of complete vaccine formulations. Malaria has the most advanced clinical and implementation evidence among the reviewed platforms. Tuberculosis has disease-prevention evidence in a defined infected adult population, and HIV and dengue platforms remain predominantly at preclinical or early clinical stages. Clinical efficacy of a nano-enabled formulation does not, by itself, quantify the incremental benefit attributable to its nanoscale component. Across diseases, translational value depends on antigen suitability, disease-relevant immune function, durability, formulation-specific safety and applicability to the intended population. Evidence from selected trial cohorts cannot automatically be generalized across heterogeneous Global South settings. Manufacturing readiness, storage requirements, affordable complete schedules, regulatory capacity and equitable access must therefore be assessed alongside biological performance. The review identifies where links between platform function, clinical benefit and feasible implementation are supported and where they remain unestablished.

Background: Tobacco use is a major risk factor for ischemic heart disease (IHD), substantially increasing the likelihood of myocardial infarction, stroke, and premature mortality. This study examined U.S. trends in IHD mortality with documented tobacco use disorder from 1999 to 2023. Methods: CDC mortality data for adults aged ≥ 25 years with IHD (ICD-10 codes: I20–I25) and documented tobacco use (ICD-10 code: F17) listed as contributing causes of death were analyzed. Age-adjusted mortality rates (AAMRs) per 100,000 population were calculated. Joinpoint regression was used to estimate annual percent change (APC) and average annual percent change (AAPC). Results: From 1999 to 2023, 1,497,919 deaths were reported. The AAMR rose from 3.90 to 32.37 (AAPC: 10.71; p < 0.01). Males had a higher AAMR (39.68; AAPC: 10.72) than females (14.05; AAPC: 10.77). Non-Hispanic (NH) Whites had the highest AAMR (26.86), followed by American Indians (25.43), NH Blacks (19.77), and Hispanics (10.38). The Midwest had the highest regional AAMR (32.96). Most deaths occurred in inpatient facilities (27.9%). Adults aged ≥ 65 years had the highest mortality rate (CMR: 92.16). Rural areas exceeded urban (35.73 vs. 22.95). Conclusion: IHD mortality with documented tobacco use has risen sharply, disproportionately affecting older adults, males, rural areas, the Midwest, and NH Whites.

Background: Radiology underpins diagnosis and treatment across pediatrics, yet most artificial intelligence (AI) tools are developed for adults and validated on adult datasets only. Of more than 200 AI systems cleared by the United States (U.S.) Food and Drug Administration (FDA), only about 3% include pediatric validation. Because children differ from adults in anatomy, physiology, pathology, epidemiology, and imaging protocols, adult-trained models often perform sub-optimally in pediatric settings. Methods: A narrative review of peer-reviewed literature from 2000 to 2025 was conducted using PubMed, MEDLINE, Google Scholar, and Scopus. Studies involving AI applications in pediatric X-ray, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), echocardiography, and point-of-care ultrasound with quantitative performance metrics were included. Findings were synthesized by imaging modality, clinical task, and differences between high-income countries (HICs) and low- and middle-income countries (LMICs). Results: AI demonstrated strong performance across multiple pediatric imaging tasks. In X-ray interpretation, AI detected fractures with area under the curve (AUC) values up to 0.96 (sensitivity, 90.8%; specificity, 88.7%). Pneumonia classification achieved 76.5% accuracy, and foreign body aspiration detection showed 95.3% specificity in HICs. In ultrasound, AI improved junior sonographers’ detection of intussusception (AUC 0.857 to 0.966) and reduced scan time by more than 50%. AI-assisted bone age estimation achieved a mean error of 0.39 years. In echocardiography, AI-derived ejection fraction showed excellent agreement with experts’ interclass correlation coefficient (ICC 0.983), and AI support improved atrioventricular septal defect detection (84.4% to 86.5%). In MRI, the use of AI enhanced lesion detection and supported quantitative analysis. Deep-learning models trained on routine T1- and T2-weighted sequences predicted liver stiffness across multi-site datasets, while advanced neuroimaging pipelines improved the identification of subtle epileptogenic lesions that are often missed on conventional pediatric MRI. However, adult-trained models showed limited generalizability to children. Still, excluding children under the age of two years improved the reading accuracy of pediatric chest X-rays (CXRs) by adult-trained models from 88% to 97%. AI faces challenges beyond the development of age-specific models. Substantial heterogeneity, limited pediatric-specific datasets, and unresolved medicolegal responsibility further restrict adoption worldwide. Challenges are amplified in LMICs, where unstable electricity, limited radiology resources, weak digital infrastructure, and scarce pediatric providers limit implementation. Additionally, many large language models underperform and lack inclusive algorithms suitable for pediatric radiology in many LMICs. Conclusions: AI can enhance diagnostic accuracy, efficiency, and access to pediatric imaging, particularly in resource-limited settings, through task-shifting and decision support. However, it cannot replace pediatric radiologists as of today. Safe adoption requires pediatric-specific model development, standardized validation metrics, diverse datasets that include LMIC populations, stronger digital infrastructure, robust radiologist training in AI capabilities, and the establishment of clear guidelines and medicolegal policies.

Background: Multiple Myeloma (MM) is the second most common hematological cancer, with chronic kidney disease (CKD) representing a major complication. This study aims to analyze national mortality trends, demographic differences, and geographic variation related to MM and CKD. Methods: Nationwide mortality records were obtained from the CDC-WONDER database from 1999 to 2023 among U.S. adults aged ≥45 with MM (C90.0) and CKD (N18); Deaths recorded anywhere on the death certificate (multiple-cause). Age-adjusted mortality rates (AAMRs) per 100,000 populations were calculated for variables. Joinpoint regression analysis was utilized to evaluate annual percent changes (APCs). Results: From 1999 to 2023, a total of 24,606 deaths occurred among adults with MM and CKD in the U.S. The overall AAMR increased from (0.65) in 1999 to (0.86) in 2023 (AAPC: 1.22; 95% CI: 0.54 to 2.00; p<0.001). Males had a higher overall AAMR (1.09) and a more rapid increase (AAPC: 1.40; p<0.001) compared to females (AAMR: 0.60; AAPC: 0.71; p=0.027). Racially, NH Blacks had the highest AAMR (2.14). Regionally, the highest AAMRs were in the South (0.83). Metropolitan areas had a higher overall AAMR 0.81 than Non-metropolitan areas 0.77 (available 1999–2020 only). Most deaths occurred in inpatient medical facilities (46.27%). Among adults aged ≥65 years, overall CMR was 1.80 per 100,000. Conclusion: Mortality from MM and CKD is increasing in the U.S from 1999 to 2023. NH Blacks, males, urban areas and the South region face high burden of death, underscoring the need for targeted strategies to reduce these substantial disparities.