Comprehensive evaluation of genes related to basement membrane in hepatocellular carcinoma.

In all mammals, the basement membrane serves as a pivotal extracellular matrix. Hepatocellular carcinoma (HCC) is a challenge among numerous cancer types shaped by basement membrane-related genes (BMGs). Our research established an innovative prognostic model that is highly accurate in its prediction of HCC prognoses and immunotherapy efficacy to summarize the crucial role of BMGs in HCC. We obtained HCC transcriptome analysis data and corresponding clinical data from The Cancer Genome Atlas (TCGA). To augment our dataset, we incorporated 222 differentially expressed BMGs identified from relevant literature. A weighted gene coexpression network analysis (WGCNA) of 10158 genes demonstrated four modules that were connected to HCC. Additionally, 66 genes that are found at the intersection of BMGs and HCC-related genes were designated as hub HCC-related BMGs. MMP1, ITGA2, P3H1, and CTSA comprise the novel model that was engineered using univariate and multivariate Cox regression analysis. Furthermore, the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) datasets encouraged the BMs model's validity. The overall survival (OS) of individuals with HCC may be precisely predicted in the TCGA and ICGC databases utilizing the BMs model. A nomogram based on the model was created in the TCGA database at similar time, and displayed a favorable discriminating ability for HCC. Particularly, when compared to the patients at an elevated risk, the patients with a low-risk profile presented different tumor microenvironment (TME) and hallmark pathways. Moreover, we discovered that a lower risk score of HCC patients would display a greater response to immunotherapy. Finally, quantitative real-time PCR (qRT-PCR) experiments were used to verify the expression patterns of BMs model. In summary, BMs model demonstrated efficacy in prognosticating the survival probability of HCC patients and their immunotherapeutic responsiveness.

Deep Learning Radiomics Model of Contrast-Enhanced CT for Differentiating the Primary Source of Liver Metastases.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CT) to identify the primary source of liver metastases. MATERIALS AND METHODS: In total, 657 liver metastatic lesions, including breast cancer (BC), lung cancer (LC), colorectal cancer (CRC), gastric cancer (GC), and pancreatic cancer (PC), from 428 patients were collected at three clinical centers from January 2018 to October 2023 series. The lesions were randomly assigned to the training and validation sets in a 7:3 ratio. An additional 112 lesions from 61 patients at another clinical center served as an external test set. A DLR model based on contrast-enhanced CT of the liver was developed to distinguish the five pathological types of liver metastases. Stepwise classification was performed to improve the classification efficiency of the model. Lesions were first classified as digestive tract cancer (DTC) and non-digestive tract cancer (non-DTC). DTCs were divided into CRC, GC, and PC and non-DTCs were divided into LC and BC. To verify the feasibility of the DLR model, we trained classical machine learning (ML) models as comparison models. Model performance was evaluated using accuracy (ACC) and area under the receiver operating characteristic curve (AUC). RESULTS: The classification model constructed by the DLR algorithm showed excellent performance in the classification task compared to ML models. Among the five categories task, highest ACC and average AUC were achieved at 0.563 and 0.796 in the validation set, respectively. In the DTC and non-DTC and the LC and BC classification tasks, AUC was achieved at 0.907 and 0.809 and ACC was achieved at 0.843 and 0.772, respectively. In the CRC, GC, and PC classification task, ACC and average AUC were the highest, at 0.714 and 0.811, respectively. CONCLUSION: The DLR model is an effective method for identifying the primary source of liver metastases.

Reniformin A suppresses non-small cell lung cancer progression by inducing TLR4/NLRP3/caspase-1/GSDMD-dependent pyroptosis.

Pyroptosis is an inflammatory form of programmed cell death that plays an important role in regulating tumor progression. Reniformin A (RA) is a natural compound isolated from the medicinal herb Isodon excisoides that has been applied as folk medicine in the treatment of esophageal cancer. However, whether RA has an individual function in cancer and the molecular mechanisms remain unclear. Here, we show that in non-small-cell lung cancer (NSCLC), RA inhibits tumor growth by functioning as a pyroptosis inducer to promote TLR4/NLRP3/caspase-1/GSDMD axis. Specially, RA treatment increased Toll-like receptor 4 (TLR4) protein expression level by enhancing the TLR4 stability. Based on the molecular docking, we identified that RA directly bound to TLR4 to activate the NLRP3 inflammasome and promote pyroptosis in A549 cells. Moreover, TLR4 is essential for RA-induced pyroptosis, and loss of TLR4 abolished RA-induced pyroptosis and further reduced the inhibitory effect of RA on NSCLC. In vivo experiments confirmed that RA inhibited the growth of lung tumors in mice by affecting pyroptosis in a dose-dependent manner. Furthermore, TLR4 knockdown abolished RA-induced pyroptosis and inhibited the effect of RA chemotherapy in vivo. In conclusion, we propose that RA has a significant anticancer effect in NSCLC by inducing TLR4/NLRP3/caspase-1/GSDMD-mediated pyroptosis, which may provide a potential strategy for the treatment of NSCLC.

Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study.

The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparametric MRI to differentiate the pathological subtypes of brain metastasis (BM) in lung cancer patients. This retrospective analysis collected 246 patients (456 BMs) from five medical centers from July 2016 to June 2022. The BMs were from small-cell lung cancer (SCLC, n = 230) and non-small-cell lung cancer (NSCLC, n = 226; 119 adenocarcinoma and 107 squamous cell carcinoma). Patients from four medical centers were assigned to training set and internal validation set with a ratio of 4:1, and we selected another medical center as an external test set. An attention-guided residual fusion network (ARFN) model for T1WI, T2WI, T2-FLAIR, DWI, and contrast-enhanced T1WI based on the ResNet-18 basic network was developed. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. Compared with models based on five single-sequence and other combinations, a multiparametric MRI model based on five sequences had higher specificity in distinguishing BMs from different types of lung cancer. In the internal validation and external test sets, AUCs of the model for the classification of SCLC and NSCLC brain metastasis were 0.796 and 0.751, respectively; in terms of differentiating adenocarcinoma from squamous cell carcinoma BMs, the AUC values of the prediction models combining the five sequences were 0.771 and 0.738, respectively. DL together with multiparametric MRI has discriminatory feasibility in identifying pathology type of BM from lung cancer.

Molecular basis and current insights of atypical Rho small GTPase in cancer.

Atypical Rho GTPases are a subtype of the Rho GTPase family that are involved in diverse cellular processes. The typical Rho GTPases, led by RhoA, Rac1 and Cdc42, have been well studied, while relative studies on atypical Rho GTPases are relatively still limited and have great exploration potential. With the increase in studies, current evidence suggests that atypical Rho GTPases regulate multiple biological processes and play important roles in the occurrence and development of human cancers. Therefore, this review mainly discusses the molecular basis of atypical Rho GTPases and their roles in cancer. We summarize the sequence characteristics, subcellular localization and biological functions of each atypical Rho GTPase. Moreover, we review the recent advances and potential mechanisms of atypical Rho GTPases in the development of multiple cancers. A comprehensive understanding and extensive exploration of the biological functions of atypical Rho GTPases and their molecular mechanisms in tumors will provide important insights into the pathophysiology of tumors and the development of cancer therapeutic strategies.

Spleen tyrosine kinase facilitates the progression of papillary thyroid cancer regulated by the hsa_circ_0006417/miR-377-3p axis.

Papillary thyroid cancer (PTC) is a prevalent malignancy worldwide. Spleen tyrosine kinase (SYK) is a crucial enzyme that participates in various biological processes, including cancer progression. This study aims to uncover the biological function of SYK in PTC. SYK expression patterns in PTC were evaluated using quantitative real time polymerase chain reaction (qRT-PCR), immunohistochemistry (IHC), and western blot. Cell function assays were performed to assess the effects of SYK on PTC. Bioinformatics analysis was conducted to identify intriguing microRNA (miRNA) and circular RNA (circRNA). Dual-Luciferase Reporter or RNA immunoprecipitation assays were used to investigate the correlation among SYK, miR-377-3p, and hsa_circ_0006417. SYK was upregulated in PTC. Overexpression of SYK exhibited a positive correlation with tumor size, lymph node metastasis, and unfavorable disease-free survival. Functional assays revealed that SYK exerted tumorigenic effect on PTC cells through mTOR/4E-BP1 pathway. Mechanistically, hsa_circ_0006417 and miR-377-3p regulated SYK expression, offering modulating its tumor-promoting effects. Collectively, SYK acts as an oncogene in PTC through mTOR/4E-BP1 pathway, which is regulated by the hsa_circ_0006417/miR-377-3p axis, thereby providing a potential alternative for PTC treatment.

NCOA5 Haploinsufficiency in Myeloid-Lineage Cells Sufficiently Causes Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma.

BACKGROUND & AIMS: The nuclear receptor coactivator 5 (NCOA5) is a putative type 2 diabetes susceptibility gene. NCOA5 haploinsufficiency results in the spontaneous development of nonalcoholic fatty liver disease (NAFLD), insulin resistance, and hepatocellular carcinoma (HCC) in male mice; however, the cell-specific effect of NCOA5 haploinsufficiency in various types of cells, including macrophages, on the development of NAFLD and HCC remains unknown. METHODS: Control and myeloid-lineage-specific Ncoa5 deletion (Ncoa5ΔM/+) mice fed a normal diet were examined for the development of NAFLD, nonalcoholic steatohepatitis (NASH), and HCC. Altered genes and signaling pathways in the intrahepatic macrophages of Ncoa5ΔM/+ male mice were analyzed and compared with those of obese human individuals. The role of platelet factor 4 (PF4) in macrophages and the underlying mechanism by which PF4 affects NAFLD/NASH were explored in vitro and in vivo. PF4 expression in HCC patient specimens and prognosis was examined. RESULTS: Myeloid-lineage-specific Ncoa5 deletion sufficiently causes spontaneous NASH and HCC development in male mice fed a normal diet. PF4 overexpression in Ncoa5ΔM/+ intrahepatic macrophages is identified as a potent mediator to trigger lipid accumulation in hepatocytes by inducing lipogenesis-promoting gene expression. The transcriptome of intrahepatic macrophages from Ncoa5ΔM/+ male mice resembles that of obese human individuals. High PF4 expression correlated with poor prognosis of HCC patients and increased infiltrations of M2 macrophages, regulatory T cells, and myeloid-derived suppressor cells in HCCs. CONCLUSIONS: Our findings reveal a novel mechanism for the onset of NAFLD/NASH and HCC initiated by NCOA5-deficient macrophages, suggesting the NCOA5-PF4 axis in macrophages as a potential target for developing preventive and therapeutic interventions against NAFLD/NASH and HCC.

Mechanism of regulating macrophages/osteoclasts in attenuating wear particle-induced aseptic osteolysis.

Joint replacement surgery is the most effective treatment for end-stage arthritis. Aseptic loosening caused by periprosthetic osteolysis is a common complication after joint replacement. Inflammation induced by wear particles derived from prosthetic biomaterials is a major cause of osteolysis. We emphasize that bone marrow-derived macrophages and their fusion-derived osteoclasts play a key role in this pathological process. Researchers have developed multiple intervention approaches to regulate macrophage/osteoclast activation. Aiming at wear particle-induced periprosthetic aseptic osteolysis, this review separately discusses the molecular mechanism of regulation of ROS formation and inflammatory response through intervention of macrophage/osteoclast RANKL-MAPKs-NF-κB pathway. These molecular mechanisms regulate osteoclast activation in different ways, but they are not isolated from each other. There is also a lot of crosstalk among the different mechanisms. In addition, other bone and joint diseases related to osteoclast activation are also briefly introduced. Therefore, we discuss these new findings in the context of existing work with a view to developing new strategies for wear particle-associated osteolysis based on the regulation of macrophages/osteoclasts.

Hyperpolarization-activated cyclic nucleotide-gated cation channel 3 promotes HCC development in a female-biased manner.

Sex differences in hepatocellular carcinoma (HCC) development are regulated by sex and non-sex chromosomes, sex hormones, and environmental factors. We previously reported that Ncoa5+/- mice develop HCC in a male-biased manner. Here we show that NCOA5 expression is reduced in male patient HCCs while the expression of an NCOA5-interacting tumor suppressor, TIP30, is lower in female HCCs. Tip30 heterozygous deletion does not change HCC incidence in Ncoa5+/- male mice but dramatically increases HCC incidence in Ncoa5+/- female mice, accompanied by hepatic hyperpolarization-activated cyclic nucleotide-gated cation channel 3 (HCN3) overexpression. HCN3 overexpression cooperates with MYC to promote mouse HCC development, whereas Hcn3 knockout preferentially hinders HCC development in female mice. Furthermore, HCN3 amplification and overexpression occur in human HCCs and correlate with a poorer prognosis of patients in a female-biased manner. Our results suggest that TIP30 and NCOA5 protect against female liver oncogenesis and that HCN3 is a female-biased HCC driver.

Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model.

PURPOSE: To assess the continuous-time random-walk (CTRW) model's diagnostic value in breast lesions and to explore the associations between the CTRW parameters and breast cancer pathologic factors. METHOD: This retrospective study included 85 patients (70 malignant and 18 benign lesions) who underwent 3.0T MRI examinations. Diffusion-weighted images (DWI) were acquired with 16b-values to fit the CTRW model. Three parameters (Dm, α, and ß) derived from CTRW and apparent diffusion coefficient (ADC) from DWI were compared among the benign/malignant lesions, molecular prognostic factors, and molecular subtypes by Mann-Whitney U test. Spearman correlation was used to evaluate the associations between the parameters and prognostic factors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) based on the diffusion parameters. RESULTS: All parameters, ADC, Dm, α, and ß were significantly lower in the malignant than benign lesions (P < 0.05). The combination of all the CTRW parameters (Dm, α, and ß) provided the highest AUC (0.833) and the best sensitivity (94.3%) in differentiating malignant status. And the positive status of estrogen receptor (ER) and progesterone receptor (PR) showed significantly lower ß compared with the negative counterparts (P < 0.05). The high Ki-67 expression produced significantly lower Dm and ADC values (P < 0.05). Additionally, combining multiple CTRW parameters improved the performance of diagnosing molecular subtypes of breast cancer. Moreover, Spearman correlations analysis showed that ß produced significant correlations with ER, PR and Ki-67 expression (P < 0.05). CONCLUSIONS: The CTRW parameters could be used as non-invasive quantitative imaging markers to evaluate breast lesions.

Comprehensive analysis of REST corepressors (RCORs) in pan-cancer.

REST corepressors (RCORs) are the core component of the LSD1/CoREST/HDACs transcriptional repressor complex, which have been revealed differently expressed in various cancers, but the therapeutic and prognostic mechanisms in cancer are still poorly understood. In this study, we analyzed expression, prognostic value, molecular subtypes, genetic alteration, immunotherapy response and drug sensitivity of RCORs in pan-cancer. Clinical correlation, stemness index, immune infiltration and regulatory networks of RCORs in hepatocellular carcinoma (HCC) were detected through TCGA and GSCA database. In-vitro experiments were conducted to explore the role of RCOR1 in HCC cells. The expression of RCORs varied among different cancers, and have prognostic values in several cancers. Cancer subtypes were categorized according to the expression of RCORs with clinical information. RCORs were significantly correlated with immunotherapy response, MSI, drug sensitivity and genetic alteration in pan-cancer. In HCC, RCORs were considered as potential predictor of stemness and also had association with immune infiltration. The ceRNA-TF-kinase regulatory networks of RCORs were constructed. Besides, RCOR1 acts as an oncogene in HCC and promotes the proliferation of HCC cells by inhibiting cell cycle arrest and cell apoptosis. Taken together, our study revealed the potential molecular mechanisms of RCORs in pan-cancer, offering a benchmark for disease-related research.

Targeting of Annexin A1 in Tumor-associated Macrophages as a therapeutic strategy for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common aggressive, malignant tumor with limited treatment options. Currently, immunotherapies have low success rates in the treatment of HCC. Annexin A1 (ANXA1) is a protein related to inflammation, immunity and tumorigenesis. However, the role of ANXA1 in liver tumorigenesis remains unknown. Therefore, we sought to explore the feasibility of ANXA1 as a therapeutic target for HCC. Here, we analyzed ANXA1 expression and localization by HCC microarray and immunofluorescence experiments. Using an in vitro culture system, monocytic cell lines and primary macrophages were employed to investigate the biological functions of cocultured HCC cells and cocultured T cells. In vivo, Ac2-26, human recombinant ANXA1 (hrANXA1), and cell depletion (macrophages or CD8 + T cells) experiments were further conducted to investigate the role of ANXA1 in the tumor microenvironment (TME). We found that ANXA1 was overexpressed in mesenchymal cells, especially macrophages, in human liver cancer. Moreover, the expression of ANXA1 in mesenchymal cells was positively correlated with programmed death-ligand 1 expression. Knockdown of ANXA1 expression inhibited HCC cell proliferation and migration by increasing the M1/M2 macrophage ratio and promoting T-cell activation. hrANXA1 promoted malignant growth and metastasis in mice by increasing the infiltration and M2 polarization of tumor-associated macrophages (TAMs), generating an immunosuppressive TME and suppressing the antitumor CD8 + T-cell response. Together, our findings reveal that ANXA1 may be an independent prognostic factor for HCC and demonstrate the clinical translational significance of ANXA1 for tumor immunotherapy in HCC.

Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm.

This study aims to develop and validate a deep learning (DL) model to differentiate glioblastoma from single brain metastasis (BM) using conventional MRI combined with diffusion-weighted imaging (DWI). Preoperative conventional MRI and DWI of 202 patients with solitary brain tumor (104 glioblastoma and 98 BM) were retrospectively obtained between February 2016 and September 2022. The data were divided into training and validation sets in a 7:3 ratio. An additional 32 patients (19 glioblastoma and 13 BM) from a different hospital were considered testing set. Single-MRI-sequence DL models were developed using the 3D residual network-18 architecture in tumoral (T model) and tumoral + peritumoral regions (T&P model). Furthermore, the combination model based on conventional MRI and DWI was developed. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. The attention area of the model was visualized as a heatmap by gradient-weighted class activation mapping technique. For the single-MRI-sequence DL model, the T2WI sequence achieved the highest AUC in the validation set with either T models (0.889) or T&P models (0.934). In the combination models of the T&P model, the model of DWI combined with T2WI and contrast-enhanced T1WI showed increased AUC of 0.949 and 0.930 compared with that of single-MRI sequences in the validation set, respectively. And the highest AUC (0.956) was achieved by combined contrast-enhanced T1WI, T2WI, and DWI. In the heatmap, the central region of the tumoral was hotter and received more attention than other areas and was more important for differentiating glioblastoma from BM. A conventional MRI-based DL model could differentiate glioblastoma from solitary BM, and the combination models improved classification performance.

Identification of fatty acid metabolism-related clusters and immune infiltration features in hepatocellular carcinoma.

Hepatocellular Carcinoma (HCC) is a type of liver cancer which is characterized by inflammation-associated tumor. The unique characteristics of tumor immune microenvironment in HCC contribute to hepatocarcinogenesis. It was also clarified that aberrant fatty acid metabolism (FAM) might accelerate tumor growth and metastasis of HCC. In this study, we aimed to identify fatty acid metabolism-related clusters and establish a novel prognostic risk model in HCC. Gene expression and corresponding clinical data were searched from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) portal. From the TCGA database, by unsupervised clustering method, we determined three FAM clusters and two gene clusters with distinct clinicopathological and immune characteristics. Based on 79 prognostic genes identified from 190 differentially expressed genes (DEGs) among three FAM clusters, five prognostic DEGs (CCDC112, TRNP1, CFL1, CYB5D2, and SLC22A1) were determined to construct risk model by least absolute shrinkage and selection operator (LASSO) and multivariate cox regression analysis. Furthermore, the ICGC dataset was used to validate the model. In conclusion, the prognostic risk model constructed in this study exhibited excellent indicator performance of overall survival, clinical feature, and immune cell infiltration, which has the potential to be an effective biomarker for HCC immunotherapy.

Identification of Prognosis-Related Oxidative Stress Model with Immunosuppression in HCC.

For hepatocellular carcinoma (HCC) patients, we attempted to establish a new oxidative stress (OS)-related prognostic model for predicting prognosis, exploring immune microenvironment, and predicting the immunotherapy response. Significantly differently expressed oxidative stress-related genes (DEOSGs) between normal and HCC samples from the Cancer Genome Atlas (TCGA) were screened, and then based on weighted gene coexpression network analysis (WGCNA), HCC-related hub genes were discovered. Based on the least absolute shrinkage and selection operator (LASSO) and cox regression analysis, a prognostic model was developed. We validated the prognostic model's predictive power using an external validation cohort: the International Cancer Genome Consortium (ICGC).Then a nomogram was determined. Furthermore, we also examined the relationship of the risk model and clinical characteristics as well as immune microenvironment. 434 DEOSGs, comprising 62 downregulated and 372 upregulated genes (p < 0.05 and |log2FC| ≥ 1), and 257 HCC-related hub genes were recognized in HCC. Afterward, we built a five-DEOSG (LOX, CYP2C9, EIF2B4, EZH2, and SRXN1) prognostic risk model. Using the nomogram, the risk model was shown to have good prognostic value. Compared to the low risk group, HCC patients with high risk had poorer outcomes, worse pathological grades, and advanced tumor stages (p < 0.05). There were significant increases in LOX, EIF2B4, EZH2, and SRXN1 expression in HCC samples, while CYP2C9 expression was decreased. Finally, Real-time PCR (RT-qPCR) confirmed the mRNA expressions of five genes (CYP2C9, EIF2B4, EZH2, SRXN1, LOX) in HCC cell lines. Our study constructed a prognostic OS-related model with strong predictive power and potential as an immunosuppressive biomarker for HCC leading to improving prediction and providing new insights for HCC immunotherapy.

Current and potential roles of RNA modification-mediated autophagy dysregulation in cancer.

Autophagy, a cellular lysosomal degradation and survival pathway, supports nutrient recycling and adaptation to metabolic stress and participates in various stages of tumor development, including tumorigenesis, metastasis, and malignant state maintenance. Among the various factors contributing to the dysregulation of autophagy in cancer, RNA modification can regulate autophagy by directly affecting the expression of core autophagy proteins. We propose that autophagy disorder mediated by RNA modification is an important mechanism for cancer development. Therefore, this review mainly discusses the role of RNA modification-mediated autophagy regulation in tumorigenesis. We summarize the molecular basis of autophagy and the core proteins and complexes at different stages of autophagy, especially those involved in cancer development. Moreover, we describe the crosstalk of RNA modification and autophagy and review the recent advances and potential role of the RNA modification/autophagy axis in the development of multiple cancers. Furthermore, the dual role of the RNA modification/autophagy axis in cancer drug resistance is discussed. A comprehensive understanding and extensive exploration of the molecular crosstalk of RNA modifications with autophagy will provide important insights into tumor pathophysiology and provide more options for cancer therapeutic strategies.

Emission characteristics and light absorption apportionment of carbonaceous aerosols: A tunnel test conducted in an urban with fully enclosed use of E10 petrol.

To reduce the heavy dependence on petroleum, bioethanol has been increasingly employed as an alternative and sustainable transportation fuel. However, the characteristics of black carbon (BC) emissions from E10 petrol vehicles (i.e., ethanol-gasoline containing 10% ethanol) are still unclear, especially under real driving conditions. Here, a tunnel test was conducted during a cold winter. This tunnel was characterized by heavy traffic comprising more than 98% E10-fueled gasoline vehicles (GVs). Real-time BC concentrations, traffic parameters and meteorological conditions were recorded during the sampling campaign. The average BC concentration inside the tunnel (10.94 ± 5.02 µg m-3) was almost twice the background concentration. Based on aethalometer AE33 in situ measurements and the minimum R-squared (MRS) method, real-time aerosol light absorption was apportioned. The light absorption proportions of BC, primary brown carbon (BrC1) and secondary brown carbon (BrC2) were 79.86%, 2.78% and 17.36%, respectively, at 370 nm. The BC emission factor (EFBC) of the E10-fueled vehicles was 1.09 ± 0.49 mg km-1·veh-1 and 15.24 ± 6.85 mg·(kg fuel)-1, lower than those of traditional gasoline fueled vehicles in previous studies. This study can support the compilation of vehicular BC emission inventories, provide recommendations for biofuel policies and contribute to comprehensively understanding the climatic impact of E10 petrol.

Pyroptosis in Periprosthetic Osteolysis.

Periprosthetic osteolysis (PPO) along with aseptic loosening (AL) caused by wear particles after artificial joint replacement is the key factor in surgical failure and subsequent revision surgery, however, the precise molecular mechanism underlying PPO remains unclear. Aseptic inflammation triggered by metal particles, resulting in the imbalance between bone formation by osteoblasts and bone resorption by osteoclasts may be the decisive factor. Pyroptosis is a new pro-inflammatory pattern of regulated cell death (RCD), mainly mediated by gasdermins (GSDMs) family, among which GSDMD is the best characterized. Recent evidence indicates that activation of NLRP3 inflammasomes and pyroptosis play a pivotal role in the pathological process of PPO. Here, we review the pathological process of PPO, the molecular mechanism of pyroptosis and the interventions to inhibit the inflammation and pyroptosis of different cells during the PPO. Conclusively, this review provides theoretical support for the search for new strategies and new targets for the treatment of PPO by inhibiting pyroptosis and inflammation.

Quantifying substantial carcinogenesis of genetic and environmental factors from measurement error in the number of stem cell divisions.

BACKGROUND: The relative contributions of genetic and environmental factors versus unavoidable stochastic risk factors to the variation in cancer risk among tissues have become a widely-discussed topic. Some claim that the stochastic effects of DNA replication are mainly responsible, others believe that cancer risk is heavily affected by environmental and hereditary factors. Some of these studies made evidence from the correlation analysis between the lifetime number of stem cell divisions within each tissue and tissue-specific lifetime cancer risk. However, they did not consider the measurement error in the estimated number of stem cell divisions, which is caused by the exposure to different levels of genetic and environmental factors. This will obscure the authentic contribution of environmental or inherited factors. METHODS: In this study, we proposed two distinct modeling strategies, which integrate the measurement error model with the prevailing model of carcinogenesis to quantitatively evaluate the contribution of hereditary and environmental factors to cancer development. Then, we applied the proposed strategies to cancer data from 423 registries in 68 different countries (global-wide), 125 registries across China (national-wide of China), and 139 counties in Shandong province (Shandong provincial, China), respectively. RESULTS: The results suggest that the contribution of genetic and environmental factors is at least 92% to the variation in cancer risk among 17 tissues. Moreover, mutations occurring in progenitor cells and differentiated cells are less likely to be accumulated enough for cancer to occur, and the carcinogenesis is more likely to originate from stem cells. Except for medulloblastoma, the contribution of genetic and environmental factors to the risk of other 16 organ-specific cancers are all more than 60%. CONCLUSIONS: This work provides additional evidence that genetic and environmental factors play leading roles in cancer development. Therefore, the identification of modifiable environmental and hereditary risk factors for each cancer is highly recommended, and primary prevention in early life-course should be the major focus of cancer prevention.