Undernutrition and low dietary quality remain widespread issues in Africa. As most rural households in the region are involved in farming, the diversification of own farm production could improve their access to nutritious foods. Here we use representative panel data from six African countries to estimate this effect across different scales. We show that farm production diversity is positively associated with household dietary diversity-yet the average magnitude of the association is small, depends on the specific measure of production diversity and increases with distance from urban centres. In all countries, markets and market access are more important for dietary diversity than own production. Because village-, town- and district-level production diversity are often positively associated with dietary diversity, higher diversity on each individual farm may not be required. The appropriate spatial scale should be considered when designing diversification strategies.
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http://dx.doi.org/10.1038/s43016-024-01096-6 | DOI Listing |
Sci Rep
January 2025
Department of Respiratory and Critical Care Medicine, Changhai Hospital, The Second Military Medical University, Shanghai, People's Republic of China.
In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common disease, and PE remains a clinical challenge because of its high mortality, high disability, high missed and high misdiagnosed rates. To address this, we employed an artificial intelligence-based machine learning algorithm (MLA) to construct a robust predictive model for PE. We retrospectively analyzed 1480 suspected PE patients hospitalized in West China Hospital of Sichuan University between May 2015 and April 2020.
View Article and Find Full Text PDFBioData Min
January 2025
School of Computer Science, Fudan University, Shanghai, China.
This survey explores the transformative impact of foundation models (FMs) in artificial intelligence, focusing on their integration with federated learning (FL) in biomedical research. Foundation models such as ChatGPT, LLaMa, and CLIP, which are trained on vast datasets through methods including unsupervised pretraining, self-supervised learning, instructed fine-tuning, and reinforcement learning from human feedback, represent significant advancements in machine learning. These models, with their ability to generate coherent text and realistic images, are crucial for biomedical applications that require processing diverse data forms such as clinical reports, diagnostic images, and multimodal patient interactions.
View Article and Find Full Text PDFJ Anim Sci Biotechnol
January 2025
College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, China.
Background: The diverse types and processing methods of grains intricately influence the sites and digestibility of starch digestion, thereby impacting energy utilization. This study aimed to explore the impact of grain variety and processing methods on the net energy (NE) in dairy goats, analyzing these effects at the level of nutrient digestion and metabolism.
Methods: Eighteen castrated Guanzhong dairy goats (44.
BMC Public Health
January 2025
Department of Health Management, Policy & Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Background: Diabetes mellitus, particularly Type 2 diabetes (T2D), represents a significant global health challenge, with its prevalence steadily rising over the past few decades. This study was conducted with the aim of estimating the economic burden of T2D in Iran.
Methods: This study employed a prevalence-based approach to estimate the economic burden of T2D and its attributable complications in adults above 20 years old in Iran for 2022.
Antiviral Res
January 2025
INSERM, Research Center for Respiratory Diseases, UMR 1100, University of Tours, France. Electronic address:
The respiratory tract hosts a diverse microbial community whose composition varies with anatomical location and throughout life. Rothia mucilaginosa, a common commensal of the upper respiratory tract and oral cavity, has recently been recognized for its ability to inhibit bacteria-triggered pro-inflammatory responses. However, its role in modulating the immune response to viral infections such as influenza A virus (IAV) pneumonia, remains unknown.
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