Climate change and rapid population ageing are significant public health challenges. Understanding which health problems are affected by temperature is important for preventing heat and cold-related ...deaths and illnesses, particularly in the elderly. Here we present a systematic review and meta-analysis on the effects of ambient hot and cold temperature (excluding heat/cold wave only studies) on elderly (65+ years) mortality and morbidity.
Time-series or case-crossover studies comprising cause-specific cases of elderly mortality (n=3,933,398) or morbidity (n=12,157,782) were pooled to obtain a percent change (%) in risk for temperature exposure on cause-specific disease outcomes using a random-effects meta-analysis.
A 1°C temperature rise increased cardiovascular (3.44%, 95% CI 3.10–3.78), respiratory (3.60%, 3.18–4.02), and cerebrovascular (1.40%, 0.06–2.75) mortality. A 1°C temperature reduction increased respiratory (2.90%, 1.84–3.97) and cardiovascular (1.66%, 1.19–2.14) mortality. The greatest risk was associated with cold-induced pneumonia (6.89%, 20–12.99) and respiratory morbidity (4.93% 1.54–8.44). A 1°C temperature rise increased cardiovascular, respiratory, diabetes mellitus, genitourinary, infectious disease and heat-related morbidity.
Elevated risks for the elderly were prominent for temperature-induced cerebrovascular, cardiovascular, diabetes, genitourinary, infectious disease, heat-related, and respiratory outcomes. These risks will likely increase with climate change and global ageing.
•Heat and cold exposure elevates elderly risk of cardiovascular and cerebrovascular deaths and respiratory deaths and morbidity.•Climate change and ageing will likely increase the risk of diabetes, renal, infectious disease and heat-induced morbidity.•Temperature risks for elderly populations in Africa, Middle East, Asia and South America are under-represented.
We applied a rigorous search strategy on three relevant databases following the PRISMA protocol. The search retrieved 18 mortality, and 30 morbidity publications eligible for meta-analysis, representing 3,933,398 deaths and 12,157,782 morbidity cases. Robust risk estimates were calculated for a wide range of temperature-sensitive health outcomes in the elderly. Temperature was found to significantly elevate cerebrovascular, cardiovascular, diabetes, genitourinary, and especially respiratory mortality or morbidity risks in the elderly. This study highlights considerable adverse health risks from temperature exposure in a large vulnerable population and provides impetus for climate change policy to address these risks.
Combinations of antibiotics are commonly used in medicine to broaden antimicrobial spectrum and generate synergistic effects. Alternatively, combination of nonantibiotic drugs with antibiotics offers ...an opportunity to sample a previously untapped expanse of bioactive chemical space. We screened a collection of drugs to identify compounds that augment the activity of the antibiotic minocycline. Unexpected synergistic drug combinations exhibited in vitro and in vivo activity against bacterial pathogens, including multidrug-resistant isolates.
Genetics aims to understand the relation between genotype and phenotype. However, because complete deletion of most yeast genes (~80%) has no obvious phenotypic consequence in rich medium, it is ...difficult to study their functions. To uncover phenotypes for this nonessential fraction of the genome, we performed 1144 chemical genomic assays on the yeast whole-genome heterozygous and homozygous deletion collections and quantified the growth fitness of each deletion strain in the presence of chemical or environmental stress conditions. We found that 97% of gene deletions exhibited a measurable growth phenotype, suggesting that nearly all genes are essential for optimal growth in at least one condition.
Cells respond to DNA double-strand breaks by recruiting factors such as the DNA-damage mediator protein MDC1, the p53-binding protein 1 (53BP1), and the breast cancer susceptibility protein BRCA1 to ...sites of damaged DNA. Here, we reveal that the ubiquitin ligase RNF8 mediates ubiquitin conjugation and 53BP1 and BRCA1 focal accumulation at sites of DNA lesions. Moreover, we establish that MDC1 recruits RNF8 through phosphodependent interactions between the RNF8 forkhead-associated domain and motifs in MDC1 that are phosphorylated by the DNA-damage activated protein kinase ataxia telangiectasia mutated (ATM). We also show that depletion of the E2 enzyme UBC13 impairs 53BP1 recruitment to sites of damage, which suggests that it cooperates with RNF8. Finally, we reveal that RNF8 promotes the G₂/M DNA damage checkpoint and resistance to ionizing radiation. These results demonstrate how the DNA-damage response is orchestrated by ATM-dependent phosphorylation of MDC1 and RNF8-mediated ubiquitination.
The structure of genetic interaction networks predicts that, analogous to synthetic lethal interactions between non-essential genes, combinations of compounds with latent activities may exhibit ...potent synergism. To test this hypothesis, we generated a chemical-genetic matrix of 195 diverse yeast deletion strains treated with 4,915 compounds. This approach uncovered 1,221 genotype-specific inhibitors, which we termed cryptagens. Synergism between 8,128 structurally disparate cryptagen pairs was assessed experimentally and used to benchmark predictive algorithms. A model based on the chemical-genetic matrix and the genetic interaction network failed to accurately predict synergism. However, a combined random forest and Naive Bayesian learner that associated chemical structural features with genotype-specific growth inhibition had strong predictive power. This approach identified previously unknown compound combinations that exhibited species-selective toxicity toward human fungal pathogens. This work demonstrates that machine learning methods trained on unbiased chemical-genetic interaction data may be widely applicable for the discovery of synergistic combinations in different species.
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•A chemical-genetic interaction matrix (CGM) of compounds against genotypes•A systematic chemical interaction matrix between genotype-specific inhibitors•Machine learning models of structural features and CGM interactions that predict synergism•Synergistic combinations that exhibit species-selective effects against pathogenic fungi
A general experimental and machine learning strategy is developed to predict synergistic compound combinations from chemical-genetic interaction data and chemical structural features.
This work presents a MATLAB-based software package for high-throughput microscopy image analysis development, making such development more accessible for a large user community. The toolbox provides ...a GUI and a number of analysis workflows, and can serve as a general framework designed to allow for easy extension. For a new application, only a minor part of the object-oriented code needs to be replaced by new components, making development efficient. This makes it possible to quickly develop solutions for analysis not available in existing tools. We show its use in making a tool for quantifying intracellular transport of internalized peptide-drug conjugates. The code is freely available as open source on GitHub (https://github.com/amcorrigan/ia-lab).
Genome integrity is jeopardized each time DNA replication forks stall or collapse. Here we report the identification of a complex composed of MMS22L (C6ORF167) and TONSL (NFKBIL2) that participates ...in the recovery from replication stress. MMS22L and TONSL are homologous to yeast Mms22 and plant Tonsoku/Brushy1, respectively. MMS22L-TONSL accumulates at regions of ssDNA associated with distressed replication forks or at processed DNA breaks, and its depletion results in high levels of endogenous DNA double-strand breaks caused by an inability to complete DNA synthesis after replication fork collapse. Moreover, cells depleted of MMS22L are highly sensitive to camptothecin, a topoisomerase I poison that impairs DNA replication progression. Finally, MMS22L and TONSL are necessary for the efficient formation of RAD51 foci after DNA damage, and their depletion impairs homologous recombination. These results indicate that MMS22L and TONSL are genome caretakers that stimulate the recombination-dependent repair of stalled or collapsed replication forks.
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► Loss of MMS22L or TONSL results in spontaneous DNA double-strand breaks ► MMS22L forms an interdependent complex with TONSL ► MMS22L and TONSL accumulate at lesions containing RPA-bound single-stranded DNA ► MMS22L-TONSL promotes RAD51 nucleofilament formation and homologous recombination
Increased nuclear size correlates with lower survival rates and higher grades for prostate cancer. The short-chain dehydrogenase/reductase (SDR) family member DHRS7 was suggested as a biomarker for ...use in prostate cancer grading because it is largely lost in higher-grade tumors. Here, we found that reduction in DHRS7 from the LNCaP prostate cancer cell line with normally high levels of DHRS7 increases nuclear size, potentially explaining the nuclear size increase observed in higher-grade prostate tumors where it is lost. An exogenous expression of DHRS7 in the PC3 prostate cancer cell line with normally low DHRS7 levels correspondingly decreases nuclear size. We separately tested 80 compounds from the Microsource Spectrum library for their ability to restore normal smaller nuclear size to PC3 cells, finding that estradiol propionate had the same effect as the re-expression of DHRS7 in PC3 cells. However, the drug had no effect on LNCaP cells or PC3 cells re-expressing DHRS7. We speculate that separately reported beneficial effects of estrogens in androgen-independent prostate cancer may only occur with the loss of DHRS7/ increased nuclear size, and thus propose DHRS7 levels and nuclear size as potential biomarkers for the likely effectiveness of estrogen-based treatments.
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