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Abstract Background Functional alveolar regeneration is essential for the restoration of normal lung homeostasis after acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Lung is a relatively quiescent organ and a variety of stem cells are recruited to participate in lung repair and regeneration after lung tissue injury. However, there is still no effective method for promoting the proliferation of endogenous lung stem cells to promote repair and regeneration. Methods Using protein mass spectrometry analysis, we analyzed the microenvironment after acute lung injury. RNA sequencing and image cytometry were used in the alveolar epithelial type 2 cells (AEC2s) subgroup identification. Then we used Sftpc+AEC2 lineage tracking mice and purified AEC2s to further elucidate the molecular mechanism by which CTGF regulates AEC2s proliferation both in vitro and in vivo. Bronchoalveolar lavage fluid (BALF) from thirty ARDS patients who underwent bronchoalveolar lavage was collected for the analysis of the correlation between the expressing of Krt5 in BALF and patients’ prognosis. Results Here, we elucidate that AEC2s are the main facultative stem cells of the distal lung after ALI and ARDS. The increase of connective tissue growth factor (CTGF) in the microenvironment after ALI promoted the proliferation of AEC2s subpopulations. Proliferated AEC2s rapidly expanded and differentiated into alveolar epithelial type 1 cells (AEC1s) in the regeneration after ALI. CTGF initiates the phosphorylation of LRP6 by promoting the interaction between Krt5 and LRP6 of AEC2s, thus activating the Wnt signaling pathway, which is the molecular mechanism of CTGF promoting the proliferation of AEC2s subpopulation. Conclusions Our study verifies that CTGF promotes the repair and regeneration of alveoli after acute lung injury by promoting the proliferation of AEC2s subpopulation.

Abstract Background Sepsis is a life‐threatening organ dysfunction caused by a dysregulated host response to infection and progressive immunosuppression with high mortality. HLA‐DR, CD64, and PD‐1 were assumed to be useful biomarkers for sepsis prediction. However, the ability of a combination of these biomarkers has not been clarified. Methods An observational case‐control study was conducted that included 30 sepsis patients, 30 critically ill patients without sepsis admitted to the intensive care unit (ICU), and 32 healthy individuals. The levels of HLA‐DR, CD64, and PD‐1 expression in peripheral blood immune cells and subsets was assayed on Days 1, 3, and 5, and the clinical information of patients was collected. We compared these biomarkers between groups and evaluated the predictive validity of single and combined biomarkers on sepsis mortality. Results The results indicate that PD‐1 expression on CD4−CD8−T (PD‐1+CD4−CD8−T) (19.19% ± 10.78% vs. 9.88% ± 1.79%, p = .004) cells and neutrophil CD64 index (nCD64 index) (9.15 ± 5.46 vs. 5.33 ± 2.34, p = .001) of sepsis patients were significantly increased, and HLA‐DR expression on monocytes (mHLA‐DR+) was significantly reduced (13.26% ± 8.06% vs. 30.17% ± 21.42%, p = 2.54 × 10−4) compared with nonsepsis critically ill patients on the first day. Importantly, the expression of PD‐1+CD4−CD8−T (OR = 0.622, 95% CI = 0.423–0.916, p = .016) and mHLA‐DR+ (OR = 1.146, 95% CI = 1.014–1.295, p = .029) were significantly associated with sepsis mortality. For sepsis diagnosis, the mHLA‐DR+, PD‐1+CD4−CD8−T, and nCD64 index showed the moderate individual performance, and combinations of the three biomarkers achieved greater diagnostic value (AUC = 0.899, 95% CI = 0.792–0.962). When adding PCT into the combined model, the AUC increased to 0.936 (95% CI = 0.840–0.983). For sepsis mortality, combinations of PD‐1+CD4−CD8−T and mHLA‐DR+, have a good ability to predict the prognosis of sepsis patients, with an AUC = 0.921 (95% CI = 0.762–0.987). Conclusion These findings indicate that the combinations of HLA‐DR, CD64, and PD‐1 outperformed each of the single indicator in diagnosis and predicting prognosis of sepsis.

Alveolar type II (AT2) cells are key effector cells for repairing damaged lungs. Direct differentiation into AT2 cells from bone marrow mesenchymal stem cells (BMSCs) is a promising approach to treating acute lung injury (ALI). The mechanisms of BMSC differentiation into AT2 cells have not been determined. The Sonic Hedgehog (Shh) pathway is involved in regulating multiple differentiation of MSCs. However, the role of the Shh pathway in mediating the differentiation of BMSCs into AT2 cells remains to be explored. The results showed that BMSCs significantly ameliorated lung injury and improved pulmonary function in mice with ALI. These improvements were accompanied by a relatively high proportion of BMSCs differentiate into AT2 cells and an increase in the total number of AT2 cells in the lungs. Lung tissue extracts from mice with ALI (ALITEs) were used to mimic the injured lung microenvironment. The addition of ALITEs significantly improved the differentiation efficiency of BMSCs into AT2 cells along with activation of the Shh pathway. The inhibition of the Shh pathway not only reduced the differentiation rate of BMSCs but also failed to mitigate lung injury and regenerate AT2 cells. The results confirmed that promoting AT2 cell regeneration through the differentiation of BMSCs into AT2 cells is one of the important therapeutic mechanisms for the treatment of ALI with BMSCs. This differentiation process is highly dependent on Shh pathway activation in BMSCs in the injured lung microenvironment.

Abstract Heparanase (HPA) is the predominant enzyme that cleaves heparan sulfate and plays a critical role in a variety of pathophysiological processes. HPA activity has been traditionally correlated with tumor metastasis due to participation in the cleavage and remodeling of the extracellular matrix (ECM). Apart from its well-characterized catalytic properties, HPA was noticed to exert biological functions not rely on its enzymatic activity. This feature is supported by studies showing induction of signaling events, such as Src and AKT, by nonenzymatic HPA mutant. We provide evidence here that active HPA and inactive HPA mutant proteins enhance gastric cancer cell growth, possibly attributed to TFEB-mediated autophagy. Similarly, HPA gene silencing resulted in decreased gastric cancer cell proliferation and autophagy. Besides, TFEB inhibition reduced cell growth and autophagy induced by nonenzymatic HPA. Notably, HPA and TFEB were significantly elevated in gastric carcinomas compared with the adjacent gastric tissue. Moreover, the elevation of HPA gene expression and upregulation of TFEB levels have been associated with advanced clinical stage and poor prognosis of gastric cancer, providing strong clinical support for a connection between TFEB and HPA. Thus, neutralizing the nonenzymatic function of HPA and the related TFEB-driven autophagy may profoundly impact gastric cancer progression.

PurposeCXC chemokines are mediators which mediate immune cells migration to sites of inflammation and injury. Chemokine C-X-C motif ligand 16 (CXCL16) plays an important role in the occurrence and development of sepsis through leukocyte chemotaxis, leukocyte adhesion and endotoxin clearance. In this study, we selected a set of tagging single nucleotide polymorphisms (tag SNPs) in the CXCL16 gene and investigated their clinical relevance to the development of sepsis and multiple organ dysfunction syndrome (MODS) in patients with major trauma in three independent Chinese Han populations.MethodsA total of 1,620 major trauma patients were enrolled in this study. Among these patients, 920 came from Chongqing in western China, 350 came from Zhejiang Province in eastern China, and 350 came from Guizhou Province in southwestern China. The improved multiplex ligation detection reaction (iMLDR) method was employed in the genotyping and genetic association analyses to determine the associations between CXCL16 haplotypes and sepsis morbidity rate and higher MOD scores in three cohorts.ResultsOnly CXCL16 T123V181 haplotype was associated with an increased risk for sepsis morbidity and higher MOD scores in the three cohorts (OR = 1.89, P = 0.001 for the Chongqing cohort; OR = 1.76, P = 0.004 for the Zhejiang cohort; OR = 1.55, P = 0.012 for the Guizhou cohort). The effect of T123V181 haplotype on the chemotaxis, migration and endotoxin clearance of immune cells were further observed. Protein modeling analysis showed that T123 and V181 might alter the structure of the CXCL16 active center. Thus it enhanced the chemotaxis and adhesion ability of immunocytes.ConclusionWe demonstrate the mechanism of CXCL16 T123V181 haplotype which regulates the sepsis morbidity rate and thus provide a new biomarker for early diagnosis of sepsis and MODS.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier NCT01713205 (https://www.clinicaltrials.gov/ct2/results?cond=&term=+NCT01713205&cntry=&state=&city=&dist=).

Abstract Background Peroxisome proliferator-activated receptor gamma (PPARγ) is a major regulator in sepsis. Our previous study identified the enhancer polymorphism rs10865710C/G to be associated with susceptibility to sepsis in trauma patients. We performed two-stage cohort studies integrating biological experiments of potential functional variants that modify susceptibility to traumatic sepsis. Methods Improved multiplex ligation detection reaction (iMLDR) was used to genotype rs10865710 in 797 Han Chinese trauma patients in Chongqing. Clinical relevance was validated in 334 patients in Guizhou. The potential function of rs10865710 in transcriptional regulation was explored through a dual luciferase reporter assay and electrophoretic mobility shift assay (EMSA). Expression of PPARγ was assessed by expression quantitative trait locus (e-QTL) and western blot analyses. Results The association results confirmed rs10865710 to be significantly strongly associated with sepsis risk in trauma patients of the Chongqing and Guizhou cohorts (OR = 1.41 (1.11–1.79), P = 0.004 and OR = 1.45 (1.01–2.09), P = 0.046, both for allele-dose effect, respectively). A meta-analysis of both cohorts and a previous study indicated strong evidence for this association (OR = 1.41 (1.17–1.71), P = 0.0004 for the dominant model, OR = 1.78 (1.34–2.36), P

BackgroundIncreasing genetic variants associated with sepsis have been identified by candidate-gene and genome-wide association studies, but single variants conferred minimal alterations in risk prediction. Our aim is to evaluate whether a weighted genetic risk score (wGRS) that aggregates information from multiple variants could improve risk discrimination of traumatic sepsis.MethodsSixty-four genetic variants potential relating to sepsis were genotyped in Chinese trauma cohort. Genetic variants with mean decrease accuracy (MDA) > 1.0 by random forest algorithms were selected to construct the multilocus wGRS. The area under the curve (AUC) and net reclassification improvement (NRI) were adopted to evaluate the discriminatory and reclassification ability of weighted genetic risk score (wGRS).ResultsSeventeen variants were extracted to construct the wGRS in 883 trauma patients. The wGRS was significantly associated with sepsis after trauma (OR = 2.19, 95% CI = 1.53–3.15, P = 2.01 × 10–5) after being adjusted by age, sex, and ISS. Patients with higher wGRS have an increasing incidence of traumatic sepsis (Ptrend = 6.81 × 10–8), higher SOFA (Ptrend = 5.00 × 10–3), and APACHE II score (Ptrend = 1.00 × 10–3). The AUC of the risk prediction model incorporating wGRS into the clinical variables was 0.768 (95% CI = 0.739–0.796), with an increase of 3.40% (P = 8.00 × 10–4) vs. clinical factor-only model. Furthermore, the NRI increased 25.18% (95% CI = 17.84–32.51%) (P = 6.00 × 10–5).ConclusionOur finding indicated that genetic variants could enhance the predictive power of the risk model for sepsis and highlighted the application among trauma patients, suggesting that the sepsis risk assessment model will be a promising screening and prediction tool for the high-risk population.

Abstract Background Published data revealed that host genetic variants have a substantial influence on sepsis susceptibility. However, the results have been inconsistent. We aimed to systematically review the published studies and quantitatively evaluate the effects of these variants on the risk of sepsis. Methods We searched the PubMed, EMBASE, Medline, Web of Knowledge, and HuGE databases to identify studies that investigated the associations between genetic variants and sepsis risk. Then, we conducted meta-analyses of the associations for genetic variants with at least three study populations and applied the Venice criteria to assess the association result credibility. Results A literature search identified 349 eligible articles that investigated 405 variants of 172 distinct genes. We performed 204 primary and 185 subgroup meta-analyses for 76 variants of 44 genes. The results showed that 29 variants of 23 genes were significantly associated with the risk of sepsis, including 8 variants of pattern recognition receptors (PRRs), 14 variants of cytokines, one variant of an immune-related gene and 6 variants of other genes. Furthermore, the cumulative epidemiological evidence of a significant association between each variant and the risk of sepsis was classified as strong or moderate for 18 variants. For the 329 variants with fewer than three study populations, 63 variants of 48 genes have been reported to be significantly associated with the risk of sepsis in a systematic review. Conclusion We identified several genetic variants that could influence the susceptibility to sepsis by systematic review and meta-analysis. This study provides a comprehensive overview of the genetic architecture of variants involved in sepsis susceptibility and novel insight that may affect personalized targeted treatment in the future clinical management of sepsis.