BMC Nutrition - Perceived motivators and barriers to consuming a plant-based diet: a qualitative research study
Evidence suggests that adopting a plant-based diet may reduce the risk of developing cardiometabolic diseases such as cardiovascular disease and type II diabetes. It may also support environmental sustainability, given the burden that large-scale agricultural production and processing of animal products places on land use and food systems.
However, the reasons individuals choose to adopt a plant-based diet vary widely and are often shaped by social, cultural, and socioeconomic factors. From a public health perspective, it is therefore important to understand the motivators and barriers to adopting such diets across different populations – particularly in regions where meat remains the most popular source of protein.
In a qualitative study published in BMC Nutrition, researchers conducted a series of semi-structured interviews with participants from the Baltimore area in the US who had either adopted a plant-based diet or were considering it. Through thematic analysis, the authors found that motivations included animal welfare, environmental concerns, cultural influences, and awareness of potential health benefits. However, participants also identified several barriers, including limited availability of plant-based products, a lack of nutritional awareness, and the perceived lack of inclusiveness in social settings.
These findings may help inform future policies and interventions aimed at promoting plant-based diets, and highlight the need for further research in other populations and cultural contexts to better understand the factors influencing dietary choices.
BMC Genomics - Molecular adaptations in MMP genes support lung elasticity and diving adaptations in cetaceans
Cetaceans, including whales, dolphins, and porpoises, evolved from a terrestrial mammalian ancestor, requiring a series of physiological adaptations for life in the marine environment. Although they have adapted to remain submerged and hold their breath for extended periods, diving still presents unique challenges, such as an increased risk of decompression-related injuries, sickness, and hypoxia.
It has been observed that the anatomy of shallow-diving and deep-diving cetaceans differs significantly. In deep-diving species, enhanced lung elasticity is thought to enable flexible lung collapse and efficient gas exchange during deep dives under pressure. This elasticity is supported by the presence of elastic fibres, which are formed, maintained, and remodelled with the help of matrix metalloproteinases (MMPs).
In a recent publication in BMC Genomics, a comprehensive evolutionary analysis of the MMP gene family was conducted across 46 mammalian genomes, supported by protein expression analyses and functional assays. This analysis focused on the genomes of cetaceans and other marine mammals, with terrestrial mammals included for comparison. The authors found that the MMP gene family underwent positive selection in cetaceans, identifying nine genes that showed signs of accelerated evolution. These findings provide new molecular insights into the role of MMPs in supporting the diving physiology of marine mammals, particularly in enhancing lung flexibility and enabling reversible lung collapse during dives.
BMC Oral Health - Associations between cumulative exposure to potentially traumatic events and self-reported oral health in the Tromsø Study: Tromsø7
Potentially Traumatic Events, such as accidents, abuse, or childhood neglect, are known to affect both mental and physical health, but their impact on oral health has been relatively unexplored. A recent study published in BMC Oral Health explored this link using data from the Tromsø Study, a large population health survey involving over 21,000 adults aged 40 and above in Tromsø, Norway.
The authors found that people who had experienced more traumatic events were more likely to report poor oral health. This association remained even after accounting for factors such as stress, dental anxiety, and oral hygiene habits. The authors’ analysis also assessed the type and timing of trauma, distinguishing between interpersonal events, such as abuse or bullying, and impersonal events, such as accidents or natural disasters.
Here, adverse dental experiences were most strongly linked to poor oral health, especially when they happened in childhood, as these experiences may lead to dental anxiety and the avoidance of care which may worsen oral health outcomes over time. Other types of trauma, particularly impersonal events in early life, were also associated with poorer outcomes.
The findings highlight how trauma, especially early in life, can have lasting effects on oral health. They also point to the importance of trauma-informed care in dentistry, particularly for children and those with a history of difficult experiences.
BMC Medical Genomics - Genome-to-genome analysis reveals associations between human and mycobacterial genetic variation in tuberculosis patients from Tanzania
Through the recent popularity of genome-wide association studies (GWAS) in medical genomic research, the heritable nature of tuberculosis (TB) susceptibility and the interplay between human and bacterial genetic factors in influencing TB risk and prognosis have been increasingly characterised through the identification of relevant genetic loci.
However, there are limitations to this approach. Associations identified by GWAS may not always be transferable across different populations, and the role of bacterial genetic variation in disease progression is often overlooked. This is particularly important given that Mycobacterium tuberculosis lineages and sub-lineages vary in pathogenicity and are geographically distributed, having adapted to different human populations with distinct genetic backgrounds.
In BMC Medical Genomics, a genome-to-genome study addressed this gap by using paired human and M. tuberculosis genomic data from 1,000 adult patients in Tanzania. The study identified two genetic loci with significant host–pathogen interactions, with one showing a particularly strong association with the severity of disease.
This work contributes valuable insight by investigating a large cohort from a region typically underrepresented in genomic research and highlights the potential for more tailored treatment approaches for a disease still closely linked to poverty.
BMC Artifical Intelligence - Developing Amharic text-based chatbot model for HIV/AIDS awareness and care using deep learning approaches
The use of chatbots for providing medical information and knowledge in healthcare settings is being increasingly explored in recent years as a means of delivering timely and accessible support. Due to advancements in machine learning and artificial intelligence, chatbots are becoming more effective at providing personalised responses based on learned patterns and large datasets, potentially improving patient outcomes in diverse settings where barriers and stigma may preclude timely guidance being provided by healthcare professionals.
A research article published in our new journal, BMC Artificial Intelligence, outlines a workflow to develop a text-based chatbot that provides accurate guidance for the prevention and awareness of HIV/AIDS in the Amharic language, with the authors identifying limitations in existing chatbot models based on the English language that do not provide sufficient transferability to the linguistic and cultural nuances of Amharic. By compiling a comprehensive dataset of medical information related to HIV/AIDS and comparing several deep learning algorithms, the authors developed a BiGRU-based model that achieved a testing accuracy of 95.01%, meaning the chatbot gave correct responses in the vast majority of test cases. The model also recorded a loss score of 0.372, indicating a strong level of predictive accuracy.
This work contributes to the alleviation of the insufficient accessibility of healthcare information for Amharic speakers living with or at risk of HIV/AIDS, and establishes a workflow for researchers in other cultural contexts to develop similar models. The authors propose developing speech capabilities in the chatbot for improved accessibility in the future.