BMC Genomics - Growth resilience to weather variation in commercial free-ranging chickens in Ethiopia
Chicken farming is a growing industry in Ethiopia and demand is expected to increase by over 200% in the next 25 years. The majority of flocks are made up of indigenous breeds that are adapted to local conditions. However, a growing portion is made up of imported high-productivity breeds that fail to thrive due to increasing extremes of temperature and other climate-change induced environmental stressors.
This paper aimed to investigate the effects of changing weather conditions on the growth of commercially raised chickens by looking at both growth resistance phenotypes and associated genomic architecture. Over 1,500 cross-bred chickens were weighed weekly and were genotyped for this study. Weekly growth was compared to weather patterns to determine resilience phenotypes and genetic markers were identified for these phenotypes.
The authors found that growth was significantly impacted by temperature, humidity, and precipitation. They also found significant genomic variance between resilience phenotypes and identified specific candidate genes associated with lipid metabolism and adipocyte homeostasis. These results could be used to breed chickens that are both highly productive and adapted to local weather conditions.
Anemia in women of reproductive age is a prevalent problem worldwide, and India has one of the highest rates at 57%. Efforts to reduce the prevalence of anemia have focused on ways to increase the availability and distribution of supplements to prevent and treat anemia. However, there has not been much focus on interventions to increase consumption of supplements and understanding of medical guidelines.
In this longitudinal cluster randomized controlled trial, an intervention package that focused on changing social norms was tested as a way to increase iron folic acid consumption among women of reproductive age. The intervention package comprised community-based education sessions, health communication videos, and hemoglobin testing. Over 4,000 women were recruited for the trial and were randomized by geographical cluster to either the intervention or the control.
The results showed that the intervention improved social norms around supplement consumption compared with the control as well as increased consumption more in intervention communities. This highlights a potentially useful way to increase uptake of important micronutrient supplements and reduce the burden of anemia.
BMC Primary Care - Exploring the relationship between cultural and structural workforce issues and retention of nurses in general practice (GenRet): a qualitative interview study
Nurses are a vital part of healthcare services, but current shortfalls in the nursing workforce are expected to worsen in the coming decade. In England, the shortage of nurses is especially acute in general practice, with up to 28% of nurses considering leaving general practice within one year.
In order to understand the factors that both encourage and discourage nurses to stay in general practice, the authors of this paper conducted a qualitative study. They interviewed 41 current and former general practice nurses and nurse leaders in England and Wales to explore how general practice culture and structure support or challenge workforce retention.
The findings indicate that a range of cultural and structural issues affect nurses’ intention to remain in general practice in both positive and negative ways. These issues include recognition of the value of nurses in general practice, limited input into decision-making, and access to professional development and representation. These insights suggest ways that stakeholders, including policy makers, employers, and professional organizations, can support nurses to remain and flourish in general practice.
BMC Gastroenterology - An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas
Gastric stromal tumors (GSTs) are a subtype of gastrointestinal submucosal tumors (SMTs) that have high malignant potential and often need aggressive surgical and pharmaceutical intervention. Gastric leiomyomas (GLs) are a less-common subtype of SMTs that are usually benign and require treatment only if they grow or cause other symptoms. Differentiating between these two subtypes is crucial during the diagnostic process, but accurately distinguishing them using endoscopic ultrasonography is challenging, especially for smaller tumors (<2.0 cm).
To address this challenge, the authors of this paper created an artificial intelligence (AI) model trained on images of confirmed GSTs and GLs. The model was then validated on a different set of images.
The AI model was able to accurately differentiate between GSTs and GLs smaller than 2.0 cm. When multiple images of each tumor were used in the AI model, its diagnostic efficiency was better than that of clinical prediction models and endoscopists. This model could offer valuable support to clinicians to accurately diagnose and treat small SMTs.