No abstract

Recent studies of the microbiome proposed that resident microbes play a beneficial role in maintaining human health. Although lower respiratory tract disease is a leading cause of sickness and mortality, how the lung microbiome interacts with human health remains largely unknown. Here we assessed the association between the lung microbiome and host gene expression, cytokine concentration, and over 20 clinical features. Intriguingly, we found a stratified structure of the active lung microbiome which was significantly associated with bacterial biomass, lymphocyte proportion, human Th17 immune response, and COPD exacerbation frequency. These observations suggest that the microbiome plays a significant role in lung homeostasis. Not only microbial composition but also active functional elements and host immunity characteristics differed among different individuals. Such diversity may partially account for the variation in susceptibility to particular diseases.

Developing a universal strategy to design piezochromic luminescent materials with desirable properties remains challenging. Here, we report that insertion of a non-emissive molecule into a donor (perylene) and acceptor (1,2,4,5-tetracyanobezene) binary cocrystal can realize fine manipulation of intermolecular interactions between perylene and 1,2,4,5-tetracyanobezene (TCNB) for desirable piezochromic luminescent properties. A continuous pressure-induced emission enhancement up to 3 GPa and a blue shift from 655 to 619 nm have been observed in perylene-TCNB cocrystals upon THF insertion, in contrast to the red-shifted and quenched emission observed when compressing perylene-TCNB cocrystals and other cocrystals reported earlier. By combining experiment with theory, it is further revealed that the inserted non-emissive THF forms blue-shifting hydrogen bonds with neighboring TCNB molecules and promote a conformation change of perylene molecules upon compression, causing the blue-shifted and enhanced emission. This strategy remains valid when inserting other molecules as non-emissive component into perylene-TCNB cocrystals for abnormal piezochromic luminescent behaviors.

Introduction Diabetes is a well‐established risk factor for dementia, but its impact on the prodromal phase of dementia is unclear. Methods Cohorts of older adults who were cognitively healthy (n = 1840) or had cognitive impairment‐no dementia (CIND; n = 682) were followed over 12 years to detect incident CIND and dementia, respectively. Results Poorly controlled diabetes (glycated hemoglobin [HbA1c] ≥7.5%; reference = normoglycemia) was associated with double the risk of CIND (Cox regression multi‐adjusted hazard ratio [HR] 2.01, 95% confidence interval [CI] 1.13‐3.58) and triple the risk CIND progressing to dementia (HR 2.87, 95% CI 1.20‐6.85). Co‐morbid diabetes and heart disease doubled the risk of incident CIND and dementia, although neither disease conferred a significant risk of either outcome alone. Elevated systemic inflammation contributed to the diabetes‐associated increased dementia risk. Conclusions Diabetes characterized by poor glycemic control or cardiovascular complications is related to a greater risk of the development and progression of cognitive impairment. Inflammation may play a role in these relationships.

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Introduction:The effect of comorbid cardiometabolic diseases (CMDs), including diabetes, heart diseases, and stroke, on dementia remains unclear. Methods:A cohort of 2648 dementia-free adults aged ≥60 years was followed up for 12 years. An active lifestyle was defined in accordance with the engagement in leisure activities and/or a social network. Cox models were used in data analysis. Results:The multiadjusted hazard ratio (HR, 95% confidence interval) of dementia was 1.41 (1.07-1.86) for one, 2.38 (1.58-3.59) for two, and 4.76 (2.04-11.13) for three CMDs. In joint exposure analysis, the HR of dementia was 3.36 (2.14-5.30) for participants with CMDs plus an inactive lifestyle and 1.32 (0.95-1.84) for those with CMDs plus an active lifestyle (reference: no CMDs plus active lifestyle). An active lifestyle delayed dementia onset by 3.50 years in people with CMDs.Discussion: CMDs, especially when comorbid, are associated with increased dementia risk; however, leisure activities and social integration mitigate this risk.

BackgroundThe natural history of prediabetes in older adults remains unknown.ObjectivesTo assess the rate at which prediabetes progresses to diabetes, leads to death or reverts to normoglycaemia in older adults and to identify prognostic factors related to different outcomes of prediabetes.MethodsIn the Swedish National Study on Aging and Care‐Kungsholmen, 2575 diabetes‐free participants aged ≥60 years were examined at baseline and followed for up to 12 years. At each wave, diabetes was diagnosed via medical examination, antidiabetic drug use, medical records or glycated haemoglobin (HbA1c) ≥6.5%. Prediabetes was defined as HbA1c ≥5.7% and normoglycaemia as HbA1c <5.7% in diabetes‐free participants. Data were analysed with multinomial logistic regression.ResultsAt baseline, 918 (36%) individuals had prediabetes. Of them, 204 (22%) reverted to normoglycaemia (3.4/100 person‐years, 95% CI 5.6–12.3), 119 (13%) developed diabetes (2.0/100 person‐years, 95% CI 1.7–2.4) and 215 (23%) died (13.0/100 person‐years, 95% CI 11.4–14.9) during the 12‐year follow‐up. The rates of reversion, progression and mortality were higher in the first 6‐year than in the second 6‐year follow‐up, albeit not statistically significant. Lower systolic blood pressure (SBP), absence of heart diseases and weight loss promoted the reversion from prediabetes to normoglycaemia, whilst obesity accelerated its progression to diabetes.ConclusionsDuring a 12‐year follow‐up, most of older adults with prediabetes remained stable or reverted to normoglycaemia, whereas only one‐third developed diabetes or died. Lower SBP, no heart diseases and weight management may promote reversion to normoglycaemia, suggesting possible strategies for achieving normoglycaemia in older adults with prediabetes.

Background With the unprecedented rapid growth rate (up to 2.75 cm/day), velvet antler is an invaluable model for the identification of potent growth factors and signaling networks for extremely fast growing tissues, mainly cartilage. Antler growth center (AGC) locates in its tip and consists of five tissue layers: reserve mesenchyme (RM), precartilage (PC), transition zone (TZ), cartilage (CA) and mineralized cartilage (MC). The aim of this study was to investigate the transcription dynamics in the AGC using RNA-seq technology. Results Five tissue layers in the AGC were collected from three 3-year-old male sika deer using our previously reported sampling method (morphologically distinguishable). After sequencing (15 samples; triplicates/tissue layer), we assembled a reference transcriptome de novo and used RNA-seq to measure gene expression profiles across these five layers. Nine differentially expressed genes (DEGs) were selected from our data and subsequently verified using qRT-PCR. The results showed a high consistency with the RNA-seq results (R 2 = 0.80). Nine modules were constructed based on co-expression network analysis, and these modules contained 370 hub genes. These genes were found to be mainly involved in mesenchymal progenitor cell proliferation, chondrogenesis, osteogenesis and angiogenesis. Combination of our own results with the previously published reports, we found that Wnt signaling likely plays a key role not only in stimulating the antler stem cells or their immediate progeny, but also in promoting chondrogenesis and osteogenesis during antler development. Conclusion We have successfully assembled a reference transcriptome, generated gene expression profiling across the five tissue layers in the AGC, and identified nine co-expressed modules that contain 370 hub genes and genes predorminantly expressed in and highly relevant to each tissue layer. We believe our findings have laid the foundation for the identification of novel genes for rapid proliferation and chondrogenic differentiation of antler cells. Electronic supplementary material The online version of this article (10.1186/s12864-019-5560-1) contains supplementary material, which is available to authorized users.