Heritable symbionts in a world of varying temperature

Heritable microbes represent an important component of the biology, ecology and evolution of many plants, animals and fungi, acting as both parasites and partners. In this review, we examine how heritable symbiont–host interactions may alter host thermal tolerance, and how the dynamics of these interactions may more generally be altered by thermal environment. Obligate symbionts, those required by their host, are considered to represent a thermally sensitive weak point for their host, associated with accumulation of deleterious mutations. As such, these symbionts may represent an important determinant of host thermal envelope and spatial distribution. We then examine the varied relationship between thermal environment and the frequency of facultative symbionts that provide ecologically contingent benefits or act as parasites. We note that some facultative symbionts directly alter host thermotolerance. We outline how thermal environment will alter the benefits/costs of infection more widely, and additionally modulate vertical transmission efficiency. Multiple patterns are observed, with symbionts being cold sensitive in some species and heat sensitive in others, with varying and non-coincident thresholds at which phenotype and transmission are ablated. Nevertheless, it is clear that studies aiming to predict ecological and evolutionary dynamics of symbiont–host interactions need to examine the interaction across a range of thermal environments. Finally, we discuss the importance of thermal sensitivity in predicting the success/failure of symbionts to spread into novel species following natural/engineered introduction

Rural-urban differentials of premature mortality burden in south-west China

BACKGROUND: Yunnan province is located in south western China and is one of the poorest provinces of the country. This study examines the premature mortality burden from common causes of deaths among an urban region, suburban region and rural region of Kunming, the capital of Yunnan. METHODS: Years of life lost (YLL) rate per 1,000 and mortality rate per 100,000 were calculated from medical death certificates in 2003 and broken down by cause of death, age and gender among urban, suburban and rural regions. YLL was calculated without age-weighting and discounting rate. Rates were age-adjusted to the combined population of three regions. However, 3% discounting rate and a standard age-weighting function were included in the sensitivity analysis. RESULTS: Non-communicable diseases contributed the most YLL in all three regions. The rural region had about 50% higher premature mortality burden compared to the other two regions. YLL from infectious diseases and perinatal problems was still a major problem in the rural region. Among non-communicable diseases, YLL from stroke was the highest in the urban/suburban regions; COPD followed as the second and was the highest in the rural region. Mortality burden from injuries was however higher in the rural region than the other two regions, especially for men. Self-inflicted injuries were between 2–8 times more serious among women. The use of either mortality rate or YLL gives a similar conclusion regarding the order of priority. Reanalysis with age-weighting and 3% discounting rate gave similar results. CONCLUSION: Urban south western China has already engaged in epidemiological pattern of developed countries. The rural region is additionally burdened by diseases of poverty and injury on top of the non-communicable diseases

Developments in AI and Machine Learning for Neuroimaging

This paper reviews guidelines on how medical imaging analysis can be enhanced by Artificial Intelligence (AI) and Machine Learning (ML). In addition to outlining current and potential future developments, we also provide background information on chemical imaging and discuss the advantages of Explainable AI. We hypothesize that it is a matter of AI to find an invariably recurring parameter that has escaped human attention (e.g. due to noisy data). There is great potential in AI to illuminate the feature space of successful models

Antibiotic Resistance Genes in the Bacteriophage DNA Fraction of Environmental Samples

Antibiotic resistance is an increasing global problem resulting from the pressure of antibiotic usage, greater mobility of the population, and industrialization. Many antibiotic resistance genes are believed to have originated in microorganisms in the environment, and to have been transferred to other bacteria through mobile genetic elements. Among others, β-lactam antibiotics show clinical efficacy and low toxicity, and they are thus widely used as antimicrobials. Resistance to β-lactam antibiotics is conferred by β-lactamase genes and penicillin-binding proteins, which are chromosomal- or plasmid-encoded, although there is little information available on the contribution of other mobile genetic elements, such as phages. This study is focused on three genes that confer resistance to β-lactam antibiotics, namely two β-lactamase genes (blaTEM and blaCTX-M9) and one encoding a penicillin-binding protein (mecA) in bacteriophage DNA isolated from environmental water samples. The three genes were quantified in the DNA isolated from bacteriophages collected from 30 urban sewage and river water samples, using quantitative PCR amplification. All three genes were detected in the DNA of phages from all the samples tested, in some cases reaching 104 gene copies (GC) of blaTEM or 102 GC of blaCTX-M and mecA. These values are consistent with the amount of fecal pollution in the sample, except for mecA, which showed a higher number of copies in river water samples than in urban sewage. The bla genes from phage DNA were transferred by electroporation to sensitive host bacteria, which became resistant to ampicillin. blaTEM and blaCTX were detected in the DNA of the resistant clones after transfection. This study indicates that phages are reservoirs of resistance genes in the environment

Estrogen receptor transcription and transactivation: Estrogen receptor alpha and estrogen receptor beta - regulation by selective estrogen receptor modulators and importance in breast cancer

Estrogens display intriguing tissue-selective action that is of great biomedical importance in the development of optimal therapeutics for the prevention and treatment of breast cancer, for menopausal hormone replacement, and for fertility regulation. Certain compounds that act through the estrogen receptor (ER), now referred to as selective estrogen receptor modulators (SERMs), can demonstrate remarkable differences in activity in the various estrogen target tissues, functioning as agonists in some tissues but as antagonists in others. Recent advances elucidating the tripartite nature of the biochemical and molecular actions of estrogens provide a good basis for understanding these tissue-selective actions. As discussed in this thematic review, the development of optimal SERMs should now be viewed in the context of two estrogen receptor subtypes, ERα and ERβ, that have differing affinities and responsiveness to various SERMs, and differing tissue distribution and effectiveness at various gene regulatory sites. Cellular, biochemical, and structural approaches have also shown that the nature of the ligand affects the conformation assumed by the ER-ligand complex, thereby regulating its state of phosphorylation and the recruitment of different coregulator proteins. Growth factors and protein kinases that control the phosphorylation state of the complex also regulate the bioactivity of the ER. These interactions and changes determine the magnitude of the transcriptional response and the potency of different SERMs. As these critical components are becoming increasingly well defined, they provide a sound basis for the development of novel SERMs with optimal profiles of tissue selectivity as medical therapeutic agents

Contribution of Exogenous Genetic Elements to the Group A Streptococcus Metagenome

Variation in gene content among strains of a bacterial species contributes to biomedically relevant differences in phenotypes such as virulence and antimicrobial resistance. Group A Streptococcus (GAS) causes a diverse array of human infections and sequelae, and exhibits a complex pathogenic behavior. To enhance our understanding of genotype-phenotype relationships in this important pathogen, we determined the complete genome sequences of four GAS strains expressing M protein serotypes (M2, M4, and 2 M12) that commonly cause noninvasive and invasive infections. These sequences were compared with eight previously determined GAS genomes and regions of variably present gene content were assessed. Consistent with the previously determined genomes, each of the new genomes is ∼1.9 Mb in size, with ∼10% of the gene content of each encoded on variably present exogenous genetic elements. Like the other GAS genomes, these four genomes are polylysogenic and prophage encode the majority of the variably present gene content of each. In contrast to most of the previously determined genomes, multiple exogenous integrated conjugative elements (ICEs) with characteristics of conjugative transposons and plasmids are present in these new genomes. Cumulatively, 242 new GAS metagenome genes were identified that were not present in the previously sequenced genomes. Importantly, ICEs accounted for 41% of the new GAS metagenome gene content identified in these four genomes. Two large ICEs, designated 2096-RD.2 (63 kb) and 10750-RD.2 (49 kb), have multiple genes encoding resistance to antimicrobial agents, including tetracycline and erythromycin, respectively. Also resident on these ICEs are three genes encoding inferred extracellular proteins of unknown function, including a predicted cell surface protein that is only present in the genome of the serotype M12 strain cultured from a patient with acute poststreptococcal glomerulonephritis. The data provide new information about the GAS metagenome and will assist studies of pathogenesis, antimicrobial resistance, and population genomics

A systematic review of frameworks for the interrelationships of mental health evidence and policy in low- and middle-income countries

Background: The interrelationships between research evidence and policy-making are complex. Different theoretical frameworks exist to explain general evidence–policy interactions. One largely unexplored element of these interrelationships is how evidence interrelates with, and influences, policy/political agenda-setting. This review aims to identify the elements and processes of theories, frameworks and models on interrelationships of research evidence and health policy-making, with a focus on actionability and agenda-setting in the context of mental health in low- and middle-income countries (LMICs). Methods: A systematic review of theories was conducted based on the BeHeMOTh search method, using a tested and refined search strategy. Nine electronic databases and other relevant sources were searched for peer-reviewed and grey literature. Two reviewers screened the abstracts, reviewed full-text articles, extracted data and performed quality assessments. Analysis was based on a thematic analysis. The included papers had to present an actionable theoretical framework/model on evidence and policy interrelationships, such as knowledge translation or evidence-based policy, specifically target the agenda-setting process, focus on mental health, be from LMICs and published in English. Results: From 236 publications included in the full text analysis, no studies fully complied with our inclusion criteria. Widening the focus by leaving out ‘agenda-setting’, we included ten studies, four of which had unique conceptual frameworks focusing on mental health and LMICs but not agenda-setting. The four analysed frameworks confirmed research gaps from LMICs and mental health, and a lack of focus on agenda-setting. Frameworks and models from other health and policy areas provide interesting conceptual approaches and lessons with regards to agenda-setting. Conclusion: Our systematic review identified frameworks on evidence and policy interrelations that differ in their elements and processes. No framework fulfilled all inclusion criteria. Four actionable frameworks are applicable to mental health and LMICs, but none specifically target agenda-setting. We have identified agenda-setting as a research theory gap in the context of mental health knowledge translation in LMICs. Frameworks from other health/policy areas could offer lessons on agenda-setting and new approaches for creating policy impact for mental health and to tackle the translational gap in LMICs