Kidney fibrosis is the hallmark of chronic kidney disease progression; however, at present no antifibrotic therapies exist1-3. The origin, functional heterogeneity and regulation of scar-forming cells that occur during human kidney fibrosis remain poorly understood1,2,4. Here, using single-cell RNA sequencing, we profiled the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys to map the entire human kidney. This analysis enabled us to map all matrix-producing cells at high resolution, and to identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibroblasts during human kidney fibrosis. We used genetic fate-tracing, time-course single-cell RNA sequencing and ATAC-seq (assay for transposase-accessible chromatin using sequencing) experiments in mice, and spatial transcriptomics in human kidney fibrosis, to shed light on the cellular origins and differentiation of human kidney myofibroblasts and their precursors at high resolution. Finally, we used this strategy to detect potential therapeutic targets, and identified NKD2 as a myofibroblast-specific target in human kidney fibrosis.
  Few reports have investigated the association between metabolic abnormalities (obesity and related metabolic syndrome) and total serum IgE concentrations.
 
  This cross-sectional study included a random sample of 1,516 adult individuals (44.7% men, aged 18-91 years, median 52 years) from a single municipality in Spain. Serum IgE was measured in the ADVIA Centaur system. Atopy was defined by the presence of positive skin prick tests to a panel of common aeroallergens in the area. Body mass index and data related to the definition of metabolic syndrome were obtained from all participants. Alcohol consumption, smoking, and regular physical exercise were assessed by a questionnaire.
 
  Atopy (present in 21.9% of 1,514 evaluable individuals) was the strongest factor determining serum IgE concentrations. Male sex and heavy alcohol drinking were independently associated with higher IgE concentrations, particularly in the non-atopic individuals. Body mass index was positively associated with IgE concentrations, independent of potential confounders, although the effect was only evident among non-atopic individuals. In that group, median IgE concentrations in normal-weight and obese individuals were 15 and 24 kU/L, respectively (p < 0.001); likewise, obesity was associated with high (>100 kU/L) IgE concentrations after adjusting for potential confounders (odds ratio 1.79, 95% confidence interval 1.26-2.56, p = 0.001). The presence of metabolic syndrome and its components, particularly abdominal obesity and hyperglycaemia, was also positively and independently associated with higher IgE concentrations in non-atopic individuals.
 
  Obesity and metabolic syndrome components are associated with high total serum IgE concentrations, particularly in non-atopic individuals.
 Obesity and metabolic syndrome components are associated with high total serum IgE concentrations, particularly in non-atopic individuals.
  Alveolar development and lung parenchymal simplification are not well characterized in vivo in neonatal patients with respiratory morbidities, such as bronchopulmonary dysplasia (BPD). Hyperpolarized (HP) gas diffusion magnetic resonance imaging (MRI) is a sensitive, safe, nonionizing, and noninvasive biomarker for measuring airspace size in vivo but has not yet been implemented in young infants.
 
  This work quantified alveolar airspace size via HP gas diffusion MRI in healthy and diseased explanted infant lung specimens, with comparison to histological morphometry.
 
  Lung specimens from 8 infants were obtained 7 healthy left upper lobes (0-16 months, post-autopsy) and 1 left lung with filamin-A mutation, closely representing BPD lung disease (11 months, post-transplantation). Specimens were imaged using HP 3He diffusion MRI to generate apparent diffusion coefficients (ADCs) as biomarkers of alveolar airspace size, with comparison to mean linear intercept (Lm) via quantitative histology.
 
  Mean ADC and Lm wlmonary disease.This study investigated the impact of estimated age, anatomical location, and the presence of wear facets on the susceptibility of enamel to develop caries-like lesions. Extracted human premolars (n = 261) had their age estimated between 10 and 93 years old, using established forensic methods. Specimens of enamel (4 × 4 mm) were prepared from the middle of the buccal surfaces, preserving the outer surface layer. The central area of the block (4 × 1 mm) was protected with nail polish and used as an internal control. The specimens were demineralized for 8 days (with 0.1 M acetic acid, 1.28 mM Ca, 0.74 mM Pi, and 0.03 µg F/mL, pH 5.0), to simulate caries-like lesion development. They were then scanned individually using microtomography, and digital 2D images were used to calculate the outcomes of integrated mineral concentration loss (ΔZ in µm/g/cm3) and lesion depth (LD in µm) at 3 locations, i.e., the cervical, middle, and occlusal thirds. The presence of natural surface wear facets was considered in the analysis. Data were evaluated using a linear mixed-effects models (α = 0.05). ΔZ increased significantly as a function of estimated tooth age at all 3 locations, and this increase was greater after the age of 30 years (p 0.15). The presence of wear facets significantly increased ΔZ and LD (p less then 0.001 for both). Overall, we concluded that the susceptibility of enamel to developing caries-like lesions increased with estimated dental age.  https://www.selleckchem.com/products/ly333531.html  This effect was more pronounced after the estimated age of 30 years and in the presence of natural tooth wear facets.Oral microbiota are among the most diverse in the human body. More than 700 species have been identified in the mouth, and new sequencing methods are allowing us to discover even more species. The anatomy of the oral cavity is different from that of other body sites. The oral cavity has mucosal surfaces (the tongue, the buccal mucosa, the gingiva, and the palate), hard tissues (the teeth), and exocrine gland tissue (major and minor salivary glands), all of which present unique features for microbiota composition. The connection between oral microbiota and diseases of the human body has been under intensive research in the past years. Furthermore, oral microbiota have been associated with cancer development. Patients suffering from periodontitis, a common advanced gingival disease caused by bacterial dysbiosis, have a 2-5 times higher risk of acquiring any cancer compared to healthy individuals. Some oral taxa, especially Porphyromonas gingivalis and Fusobacterium nucleatum, have been shown to have carcinogenic potential by several different mechanisms.