Table_1_Genetic predisposition of the gastrointestinal microbiome and primary biliary cholangitis: a bi-directional, two-sample Mendelian randomization analysis.xlsx

BackgroundThe gut-liver axis indicates a close relationship between the gastrointestinal microbiome (GM) and primary biliary cholangitis (PBC). However, the causality of this relationship remains unknown. This study investigates the causal relationship between the GM and PBC using a bidirectional, two-sample Mendelian randomization (MR) analysis.MethodsGenome-wide association data for GM and PBC were obtained from public databases. The inverse-variance weighted method was the primary method used for MR analysis. Sensitivity analyses were conducted to assess the stability of the MR results. A reverse MR analysis was performed to investigate the possibility of reverse causality.ResultsThree bacterial taxa were found to be causally related to PBC. Class Coriobacteriia (odds ratio (OR) = 2.18, 95% confidence interval (CI): 1.295-3.661, PConclusionPreviously unrecognized taxa that may be involved in the pathogenesis of PBC were identified in this study, confirming the causality between the GM and PBC. These results provide novel microbial targets for the prevention and treatment of PBC.</p

Synthesis and Characterization of Hydrazide-Linked and Amide-Linked Organic Polymers

Four kinds of either hydrazide-linked or amide-linked polymers were facilely synthesized by using hydrazine, tetrakis­(4-aminophenyl)­methane (TAPM), terephthaloyl chloride (TPC), and trimesoyl chloride (TMC) as building blocks. The morphology, porosity, composition, and surface property of polymers were characterized by scanning electron microscopy, transmission electron microscopy, nitrogen adsorption–desorption measurement, ¹³C/CP-MAS NMR, X-ray photoelectron spectroscopy, etc. The results indicated that building blocks had important effects on morphology and porosity. Poly­(TMC–TAPM) synthesized with TMC and TAPM showed the highest surface area of 241.9 m² g^–1. In addition, note that a hollow structure with ∼20 nm wall thickness was formed in poly­(TMC–hydrazine) prepared with TMC and hydrazine. Further study indicated that both carboxyl groups (−COOH) and hydrazide groups (−CONH–NH₂) existed on the surface of poly­(TMC–hydrazine), besides the mainly hydrazide linkage (−CONH–NHOC−). Taking advantages of good hydrophilicity and special functional groups on the surface, we finally adopted poly­(TMC–hydrazine) to enrich glycopeptides from tryptic digest via both hydrophilic interaction chromatography method with identification of 369 unique N-glycosylation sites and hydrazide chemistry method with identification of 88 unique N-glycosylation sites, respectively

Chinese Systemic Lupus Erythematosus Treatment and Research Group Registry VI: Effect of Cigarette Smoking on the Clinical Phenotype of Chinese Patients with Systemic Lupus Erythematosus

<div><p>Objectives</p><p>Our study aimed to investigate the effect of cigarette smoking on the clinical phenotype of patients registered in the Chinese Systemic Lupus Erythematosus (SLE) Treatment and Research (CSTAR) group registry database, the first online registry of Chinese patients with SLE.</p><p>Methods</p><p>A prospective cross-sectional study of Chinese SLE patients was conducted using the CSTAR. Our case-control analysis was performed on age- and gender-matched subjects to explore the potential effect of cigarette smoking on the clinical manifestation of SLE.</p><p>Results</p><p>Smokers comprised 8.9% (65/730) of patients, and the ratio of females/males was 19/46. Thirty-nine patients were current smokers, and 26 were ex-smokers. Data showed significant differences between smokers and nonsmokers in the following areas: nephropathy (58.5% vs. 39.2%; p = 0.003), microscopic hematuria (30.8% vs. 19.1%; p = 0.025), proteinuria (53.8% vs. 34.4%; p = 0.002), and SLE Disease Activity Index(DAI) scores (12.38±8.95 vs. 9.83±6.81; p = 0.028). After adjusting for age and gender, significant differences between smokers and nonsmokers were found with photosensitivity (35.9% vs. 18%; p = 0.006), nephropathy (59.4% vs. 39.8%; p = 0.011), and proteinuria (54.7% vs. 35.2%). Although smokers tended to have greater disease severity compared with nonsmokers (SLEDAI scores: 12.58±8.89 vs.10.5±7.09), the difference was not significant (p = 0.081).</p><p>Conclusions</p><p>Cigarette smoking triggers the development and exacerbation of SLE, especially with respect to renal involvement. Chinese smokers with SLE should be advised to discontinue cigarette use.</p></div

Comparison of clinical manifestations between smokers and nonsmokers in SLE patients.

<p>F, female; M, male</p><p>Comparison of clinical manifestations between smokers and nonsmokers in SLE patients.</p

Life cycle of soybean biodiesel produced in Brazil, highlighting GHG emission sources within the four stages: agriculture, extraction, biodiesel production and distribution.

<p>Life cycle of soybean biodiesel produced in Brazil, highlighting GHG emission sources within the four stages: agriculture, extraction, biodiesel production and distribution.</p

Life cycle GHG emission of biodiesel production, considering a domestic B100 scenario (MT-PA) and an exported B100 scenario (MT-EU).

<p>Life cycle GHG emission of biodiesel production, considering a domestic B100 scenario (MT-PA) and an exported B100 scenario (MT-EU).</p

Summary of conversion factors used in this study.

<p>Summary of conversion factors used in this study.</p

Comparison of laboratory findings and SLEDAI scores between smokers and nonsmoker SLE patients in the case-control study.

<p>SLE, systemic lupus erythematosus; SLEDAI, SLE disease activity index; ANA, antinuclear antibody; Sm, Smith; RNP, ribonucleoprotein; rRNP, ribosomal RNP; APL antiphospholipid.</p><p>Comparison of laboratory findings and SLEDAI scores between smokers and nonsmoker SLE patients in the case-control study.</p

Schematic representation of the four pathways for distribution of final B100.

<p>Schematic representation of the four pathways for distribution of final B100.</p

Main inputs and yield per hectare of soybean in Mato Grosso state, Brazil (growing season of 2007/08, 2008/09 and 2009/10).

<p>Main inputs and yield per hectare of soybean in Mato Grosso state, Brazil (growing season of 2007/08, 2008/09 and 2009/10).</p