The long arm of childhood socioeconomic deprivation on mid- to later-life cognitive trajectories: a cross-cohort analysis

Introduction Earlier studies of the effects of childhood socioeconomic status (SES) on later-life cognitive function consistently report a social gradient in later-life cognitive function. Evidence for their effects on cognitive decline is, however, less clear. Methods The sample consists of 5324 participants in the Whitehall II study, 8572 in the Health and Retirement Study (HRS), and 1413 in the Kame Project, who completed self-report questionnaires on their early life experiences and underwent repeated cognitive assessments. We characterized cognitive trajectories using latent class mixed models, and explored associations between childhood SES and latent class membership using logistic regressions. Results We identified distinct trajectories classes for all cognitive measures examined. Childhood socioeconomic deprivation was associated with an increased likelihood of being in a lower trajectory class. Discussion Our findings support the notions that cognitive aging is a heterogeneous process and early life circumstances may have lasting effects on cognition across the life-course

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

A review of the distribution of particulate trace elements in urban terrestrial environments and its application to considerations of risk

We review the evolution, state of the art and future lines of research on the sources, transport pathways, and sinks of particulate trace elements in urban terrestrial environments to include the atmosphere, soils, and street and indoor dusts. Such studies reveal reductions in the emissions of some elements of historical concern such as Pb, with interest consequently focusing on other toxic trace elements such as As, Cd, Hg, Zn, and Cu. While establishment of levels of these elements is important in assessing the potential impacts of human society on the urban environment, it is also necessary to apply this knowledge in conjunction with information on the toxicity of those trace elements and the degree of exposure of human receptors to an assessment of whether such contamination represents a real risk to the city’s inhabitants and therefore how this risk can be addressed

Regulation of microRNA biogenesis and turnover by animals and their viruses

Item does not contain fulltextMicroRNAs (miRNAs) are a ubiquitous component of gene regulatory networks that modulate the precise amounts of proteins expressed in a cell. Despite their small size, miRNA genes contain various recognition elements that enable specificity in when, where and to what extent they are expressed. The importance of precise control of miRNA expression is underscored by functional studies in model organisms and by the association between miRNA mis-expression and disease. In the last decade, identification of the pathways by which miRNAs are produced, matured and turned-over has revealed many aspects of their biogenesis that are subject to regulation. Studies in viral systems have revealed a range of mechanisms by which viruses target these pathways through viral proteins or non-coding RNAs in order to regulate cellular gene expression. In parallel, a field of study has evolved around the activation and suppression of antiviral RNA interference (RNAi) by viruses. Virus encoded suppressors of RNAi can impact miRNA biogenesis in cases where miRNA and small interfering RNA pathways converge. Here we review the literature on the mechanisms by which miRNA biogenesis and turnover are regulated in animals and the diverse strategies that viruses use to subvert or inhibit these processes

Development of a modified Cambridge Multimorbidity Score for use with SNOMED CT:an observational English primary care sentinel network study

Background People with multiple health conditions are more likely to have poorer health outcomes and greater care and service needs; a reliable measure of multimorbidity would inform management strategies and resource allocation. Aim To develop and validate a modified version of the Cambridge Multimorbidity Score in an extended age range, using clinical terms that are routinely used in electronic health records across the world (Systematized Nomenclature of Medicine — Clinical Terms, SNOMED CT). Design and setting Observational study using diagnosis and prescriptions data from an English primary care sentinel surveillance network between 2014 and 2019. Method In this study new variables describing 37 health conditions were curated and the associations modelled between these and 1-year mortality risk using the Cox proportional hazard model in a development dataset (n = 300 000). Two simplified models were then developed — a 20-condition model as per the original Cambridge Multimorbidity Score and a variable reduction model using backward elimination with Akaike information criterion as the stopping criterion. The results were compared and validated for 1-year mortality in a synchronous validation dataset (n = 150 000), and for 1-year and 5-year mortality in an asynchronous validation dataset (n = 150 000). Results The final variable reduction model retained 21 conditions, and the conditions mostly overlapped with those in the 20-condition model. The model performed similarly to the 37- and 20-condition models, showing high discrimination and good calibration following recalibration. Conclusion This modified version of the Cambridge Multimorbidity Score allows reliable estimation using clinical terms that can be applied internationally across multiple healthcare settings

Adverse events after first and second doses of COVID-19 vaccination in England: a national vaccine surveillance platform self-controlled case series study

Objectives: To estimate the incidence of adverse events of interest (AEIs) after receiving their first and second doses of coronavirus disease 2019 (COVID-19) vaccinations, and to report the safety profile differences between the different COVID-19 vaccines. Design: We used a self-controlled case series design to estimate the relative incidence (RI) of AEIs reported to the Oxford-Royal College of General Practitioners national sentinel network. We compared the AEIs that occurred seven days before and after receiving the COVID-19 vaccinations to background levels between 1 October 2020 and 12 September 2021. Setting: England, UK. Participants: Individuals experiencing AEIs after receiving first and second doses of COVID-19 vaccines. Main outcome measures: AEIs determined based on events reported in clinical trials and in primary care during post-license surveillance. Results: A total of 7,952,861 individuals were vaccinated with COVID-19 vaccines within the study period. Among them, 781,200 individuals (9.82%) presented to general practice with 1,482,273 AEIs. Within the first seven days post-vaccination, 4.85% of all the AEIs were reported. There was a 3–7% decrease in the overall RI of AEIs in the seven days after receiving both doses of Pfizer-BioNTech BNT162b2 (RI = 0.93; 95% CI: 0.91–0.94) and 0.96; 95% CI: 0.94–0.98), respectively) and Oxford-AstraZeneca ChAdOx1 (RI = 0.97; 95% CI: 0.95–0.98) for both doses), but a 20% increase after receiving the first dose of Moderna mRNA-1273 (RI = 1.20; 95% CI: 1.00–1.44)). Conclusions: COVID-19 vaccines are associated with a small decrease in the incidence of medically attended AEIs. Sentinel networks could routinely report common AEI rates, which could contribute to reporting vaccine safety

Positive association between increased popliteal artery vessel wall thickness and generalized osteoarthritis: is OA also part of the metabolic syndrome?

This is the final version of the article. Available from Springer Verlag via the DOI in this record.PURPOSE: The purpose of the study was to determine if a positive association exists between arterial vessel wall thickness and generalized osteoarthritis (OA). Our hypothesis is that generalized OA is another facet of the metabolic syndrome. MATERIALS AND METHODS: The medical ethical review board of our institution approved the study. Written informed consent was obtained from each patient prior to the study. Magnetic resonance (MR) images of the knee were obtained in 42 patients who had been diagnosed with generalized OA at multiple joint sites. Another 27 MR images of the knee were obtained from a matched normal (non-OA) reference population. Vessel wall thickness of the popliteal artery was quantitatively measured by dedicated software. Linear regression models were used to investigate the association between vessel wall thickness and generalized OA. Adjustments were made for age, sex, and body mass index (BMI). Confidence intervals (CI) were computed at the 95% level and a significance level of alpha = 0.05 was used. RESULTS: Patients in the generalized OA population had a significant higher average vessel wall thickness than persons from the normal reference population (p < or = alpha), even when correction was made for sex, age, and BMI. The average vessel wall thickness of the popliteal artery was 1.09 mm in patients with generalized OA, and 0.96 mm in the matched normal reference population. CONCLUSION: The association found between increased popliteal artery vessel wall thickness and generalized osteoarthritis suggests that generalized OA might be another facet of the metabolic syndrome

A miRNA-Target Prediction Case Study

Giansanti, V., Castelli, M., Beretta, S., & Merelli, I. (2019). Comparing Deep and Machine Learning Approaches in Bioinformatics: A miRNA-Target Prediction Case Study. In V. V. Krzhizhanovskaya, M. H. Lees, P. M. A. Sloot, J. J. Dongarra, J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, ... R. Lam (Eds.), Computational Science – ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part III (pp. 31-44). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11538 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-22744-9_3MicroRNAs (miRNAs) are small non-coding RNAs with a key role in the post-transcriptional gene expression regularization, thanks to their ability to link with the target mRNA through the complementary base pairing mechanism. Given their role, it is important to identify their targets and, to this purpose, different tools were proposed to solve this problem. However, their results can be very different, so the community is now moving toward the deployment of integration tools, which should be able to perform better than the single ones. As Machine and Deep Learning algorithms are now in their popular years, we developed different classifiers from both areas to verify their ability to recognize possible miRNA-mRNA interactions and evaluated their performance, showing the potentialities and the limits that those algorithms have in this field. Here, we apply two deep learning classifiers and three different machine learning models to two different miRNA-mRNA datasets, of predictions from 3 different tools: TargetScan, miRanda, and RNAhybrid. Although an experimental validation of the results is needed to better confirm the predictions, deep learning techniques achieved the best performance when the evaluation scores are taken into account.authorsversionpublishe

Women Have Higher Protein Content of β-Oxidation Enzymes in Skeletal Muscle than Men

It is well recognized that compared with men, women have better ultra-endurance capacity, oxidize more fat during endurance exercise, and are more resistant to fat oxidation defects i.e. diet-induced insulin resistance. Several groups have shown that the mRNA and protein transcribed and translated from genes related to transport of fatty acids into the muscle are greater in women than men; however, the mechanism(s) for the observed sex differences in fat oxidation remains to be determined. Muscle biopsies from the vastus lateralis were obtained from moderately active men (N = 12) and women (N = 11) at rest to examine mRNA and protein content of genes involved in lipid oxidation. Our results show that women have significantly higher protein content for tri-functional protein alpha (TFPα), very long chain acyl-CoA dehydrogenase (VLCAD), and medium chain acyl-CoA dehydrogenase (MCAD) (P<0.05). There was no significant sex difference in the expression of short-chain hydroxyacyl-CoA dehydrogenase (SCHAD), or peroxisome proliferator activated receptor alpha (PPARα), or PPARγ, genes potentially involved in the transcriptional regulation of lipid metabolism. In conclusion, women have more protein content of the major enzymes involved in long and medium chain fatty acid oxidation which could account for the observed differences in fat oxidation during exercise