Metabolic dysfunction-associated fatty liver disease increases the risk of complications after radical resection in patients with hepatocellular carcinoma.

BACKGROUND AND AIMS: The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) in hepatocellular carcinoma (HCC) patients is increasing, yet its association with postoperative complications of HCC remains unclear. The aim of this study was to investigate the impact of MAFLD on complications after radical resection in HCC patients. METHODS: Patients with HCC who underwent radical resection were included. Patients were stratified into MAFLD group and non-MAFLD group. Clinical features and post-hepatectomy complications were compared between the two groups, and logistic regression analysis was used to determine independent risk factors associated with post-hepatectomy complications. RESULTS: Among the 936 eligible patients with HCC who underwent radical resection, concurrent MAFLD was diagnosed in 201 (21.5%) patients. Compared to the non-MAFLD group, the MAFLD group exhibited a higher incidence of complications, including infectious and major complications after radical resection in HCC patients. The logistic regression analysis found that MAFLD was an independent risk factor for complications, including infectious and major complications in HCC patients following radical resection (OR 1.565, 95%CI 1.109-2.343, P = 0.012; OR 2.092, 95%CI 1.386-3.156, P < 0.001; OR 1.859, 95% CI 1.106-3.124, P = 0.019; respectively). Subgroup analysis of HBV-related HCC patients yielded similar findings, and MAFLD patients with type 2 diabetes mellitus (T2DM) exhibited a higher incidence of postoperative complications compared to those without T2DM (all P < 0.05). CONCLUSIONS: Concurrent MAFLD was associated with an increased incidence of complications after radical resection in patients with HCC, especially MAFLD with T2DM.

pH Dependence of a GPR4 Selective Antagonist Hampers Its Therapeutic Potential.

Inflammatory bowel disease (IBD) is characterized by chronic mucosal inflammation of the gastrointestinal tract and is associated with extracellular acidification of mucosal tissue. Several extracellular pH-sensing receptors, including G protein-coupled receptor 4 (GPR4), play an important role in the regulation of inflammatory and immune responses, and GPR4 deficiency has been shown to be protective in IBD animal models. To confirm the therapeutic potential of GPR4 antagonism in IBD, we tested Compound 13, a selective GPR4 antagonist, in the interleukin 10-/- mouse model of colitis. Despite good exposures and albeit there was a trend toward improvement for a few readouts, Compound 13 treatment did not improve colitis in this model, and there were no signs of target engagement. Interestingly, Compound 13 behaved as an "orthosteric" antagonist, i.e., its potency was pH dependent and mostly inactive at pH levels lower than 6.8 with preferential binding to the inactive conformation of GPR4. Mutagenesis studies confirmed Compound 13 likely binds to the conserved orthosteric binding site in G protein-coupled receptors, where a histidine sits in GPR4 likely preventing Compound 13 binding when protonated in acidic conditions. While the exact mucosal pH in the human disease and relevant IBD mice models is unknown, it is well established that the degree of acidosis is positively correlated with the degree of inflammation, suggesting Compound 13 is not an ideal tool to study the role of GPR4 in moderate to severe inflammatory conditions. SIGNIFICANCE STATEMENT: Compound 13, a reported selective GPR4 antagonist, has been widely used to assess the therapeutic potential of GPR4, a pH-sensing receptor, for numerous indications. Its pH dependence and mechanism of inhibition identified in this study clearly highlights the limitations of this chemotype for target validation.

Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign.

OBJECTIVES: To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs). MATERIALS AND METHODS: A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application. RESULTS: The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC65keV-AP = 0.92, AUC65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability. CONCLUSIONS: Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Zeff-AP was significantly superior to conventional model in the discrimination of SPSNs.

Mitigating the impact of bisphenol A exposure on mortality: Is diet the key? A cohort study based on NHANES.

Bisphenol A (BPA) is a widespread environmental pollutant linked to detrimental effects on human health and reduced life expectancy following chronic exposure. This prospective cohort study aimed to examine the association between BPA exposure and mortality in American adults and to explore the potential mitigating effects of dietary quality on BPA-related mortality. This study utilized data from 8761 American adults in the 2003-2016 National Health and Nutrition Examination Survey (NHANES). Urinary BPA levels were employed to assess BPA exposure, and dietary quality was evaluated using the Healthy Eating Index-2015 (HEI-2015). All-cause, cardiovascular disease (CVD), and cancer mortality statuses were determined until December 31, 2019, resulting in a cumulative follow-up of 80,564 person-years. The results showed that the highest tertile of urinary BPA levels corresponded to a 36% increase in all-cause mortality and a 62% increase in CVD mortality compared to the lowest tertile. In contrast, the highest tertile of HEI-2015 scores was associated with a 29% reduction in all-cause mortality relative to the lowest tertile. Although no significant interaction was found between HEI-2015 scores and urinary BPA levels concerning mortality, the association between HEI-2015 scores and both all-cause and CVD mortality was statistically significant at low urinary BPA levels. Continuous monitoring of BPA exposure is crucial for evaluating its long-term adverse health effects. Improving dietary quality can lower all-cause mortality and decrease the risk of all-cause and CVD mortality at low BPA exposure levels. However, due to the limited protective effect of dietary quality against BPA exposure, minimizing BPA exposure remains a vital goal.

The impact of metabolic dysfunction-associated fatty liver disease on the prognosis of patients with hepatocellular carcinoma after radical resection.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD) is recently proposed an entity by a group of international experts. However, the impact of MAFLD on the prognosis of patients with hepatocellular carcinoma (HCC) is not clear. The aim of this study was to explore the influence of MAFLD for the prognosis of HCC after radical resection. METHODS: HCC patients who received radical resection were enrolled. The recurrence-free survival (RFS) and overall survival (OS) were compared between MAFLD and non-MAFLD. RESULTS: A total of 576 HCC patients were included, and among them 114 (19.8%) met the diagnostic criteria of MAFLD. The median RFS was 34.0 months in the MAFLD group and 19.0 months in the non-MAFLD group. The 1-, 3-, and 5-year RFS rates were 64.9%, 49.1% and 36.1% in the MAFLD group, which were higher than those of the non-MAFLD group (59.4%, 35.3% and 26.5%, respectively, P = 0.01). The mean OS was 57.0 months in the MAFLD group and 52.2 months in the non-MAFLD group. There was no statistical difference in OS rate between the MAFLD group and non-MAFLD group. Similar results were found in HBV-related HCC patients in the subgroup analysis. Univariate analysis revealed that MAFLD was a protective factor for RFS in HCC patients after radical resection (P < 0.05), and there was no association between MAFLD and OS rate (P > 0.05). Multivariate analysis demonstrated that MAFLD was not an independent protective factor for HCC patients with radical resection. CONCLUSIONS: MAFLD improves RFS rate in HCC patients with radical resection, but is not an independent protective factor and not associated with OS rate.

CLSSL-ResNet: Predicting malignancy of solitary pulmonary nodules from CT images by chimeric label with self-supervised learning.

BACKGROUND: Pulmonary granulomatous nodules (GN) with spiculation or lobulation have a similar morphological appearance to solid lung adenocarcinoma (SADC) under computed tomography (CT). However, these two kinds of solid pulmonary nodules (SPN) have different malignancies and are sometimes misdiagnosed. OBJECTIVE: This study aims to predict malignancies of SPNs by a deep learning model automatically. METHODS: A chimeric label with self-supervised learning (CLSSL) is proposed to pre-train a ResNet-based network (CLSSL-ResNet) for distinguishing isolated atypical GN from SADC in CT images. The malignancy, rotation, and morphology labels are integrated into a chimeric label and utilized to pre-train a ResNet50. The pre-trained ResNet50 is then transferred and fine-tuned to predict the malignancy of SPN. Two image datasets of 428 subjects (Dataset1, 307; Dataset2, 121) from different hospitals are collected. Dataset1 is divided into training, validation, and test data by a ratio of 7:1:2 to develop the model. Dataset2 is utilized as an external validation dataset. RESULTS: CLSSL-ResNet achieves an area under the ROC curve (AUC) of 0.944 and an accuracy (ACC) of 91.3%, which was much higher than that of the consensus of two experienced chest radiologists (77.3%). CLSSL-ResNet also outperforms other self-supervised learning models and many counterparts of other backbone networks. In Dataset2, AUC and ACC of CLSSL-ResNet are 0.923 and 89.3%, respectively. Additionally, the ablation experiment result indicates higher efficiency of the chimeric label. CONCLUSION: CLSSL with morphology labels can increase the ability of feature representation by deep networks. As a non-invasive method, CLSSL-ResNet can distinguish GN from SADC via CT images and may support clinical diagnoses after further validation.

Humoral responses after inactivated COVID-19 vaccination in individuals with and without prior SARS-CoV-2 infection: A prospective cohort study.

We evaluated and compared humoral immune responses after inactivated coronavirus disease 2019 (COVID-19) vaccination among naïve individuals, asymptomatically infected individuals, and recovered patients with varying severity. In this multicenter, prospective cohort study, blood samples from 666 participants were collected before and after 2 doses of inactivated COVID-19 vaccination. Among 392 severe acute respiratory syndrome coronavirus 2-naïve individuals, the seroconversion rate increased significantly from 51.8% (median antispike protein pan-immunoglobulins [S-Igs] titer: 0.8 U/ml) after the first dose to 96% (median S-Igs titer: 79.5 U/ml) after the second dose. Thirty-two percent of naïve individuals had detectable neutralizing antibodies (NAbs) against the original strain but all of them lost neutralizing activity against the Omicron variant. In 274 individuals with natural infection, humoral immunity was significantly improved after a single vaccine dose, with median S-Igs titers of 596.7, 1176, 1086.5, and 1828 U/ml for asymptomatic infections, mild cases, moderate cases, and severe/critical cases, respectively. NAb titers also improved significantly. However, the second dose did not substantially increase antibody levels. Although a booster dose is needed for those without infection, our findings indicate that recovered patients should receive only a single dose of the vaccine, regardless of the clinical severity, until there is sufficient evidence to confirm the benefits of a second dose.

Enhancing remediation of PAH-contaminated soil through coupling electrical resistance heating using Na2S2O8.

Soil polycyclic aromatic hydrocarbons (PAHs) contamination caused by factory relocations is a serious environmental issue across the world. Electrical resistance heating (ERH) and chemical oxidation are two promising in-situ methods for treating volatile and semi-volatile organic pollutants in contaminated soil. Coupling of ERH and chemical oxidation technologies to improve the remediation efficiency for PAH-contaminated soil was estimated in this study. PAH removal ratio in contaminated soils using ERH treatment were significantly negatively correlated with the boiling point of the pollutants (P = 0.002), and 21.63% (DBA high boiling point) to 71.53% (Nap low boiling point) of PAHs in the contaminated soil were removed in 120 min. With oxidant Na2S2O8 coupling, the removal ratio were increased as more oxidant was added. For one Phe, 35.90% was removed by ERH treatment and increased to 52.90% and 79.42% when 0.05 or 2.5 mmol/g oxidant was added, respectively. PAHs with higher boiling points had more obvious removal ratio, such as Bap, which increased from 23.50% to 85.47% when coupling ERH with Na2S2O8, and Phe which increased from 35.90% to 79.42%. Relationships between boiling points and PAH removal ratio changed with coupled oxidants, indicating a change of mechanism from volatilization to coupling effects of volatilization and oxidation with the introduction of Na2S2O8. A dynamic experiment showed that Na2S2O8 can accelerate 45.50% of the treatment process. The results of this research demonstrated a novel, cost-effective coupling approach for remediating soil contaminated by organic pollutants.

Surface charge engineering of Thermomyces lanuginosus lipase improves enzymatic activity and biodiesel synthesis.

OBJECTIVES: This study was aimed at engineering charged residues on the surface of Thermomyces lanuginosus lipase (TLL) to obtain TLL variant with elevated performance for industrial applications. RESULTS: Site-directed mutagenesis of eight charged amino acids on the TLL surface were conducted and substitutions on the negatively charged residues D111, D158, D165, and E239 were identified with elevated specific activities and biodiesel yields. Synergistic effect was not discovered in the double mutants, D111E/D165E and D165E/E239R, when compared with the corresponding single mutants. One TLL mutant, D165E, was identified with increased specific activity (456.60 U/mg), catalytic efficiency (kcat/Km: 44.14 s-1 mM-1), the highest biodiesel conversion yield (93.56%), and comparable thermostability with that of the TLL. CONCLUSIONS: Our study highlighted the importance of surface charge engineering in improving TLL activity and biodiesel production, and the resulting TLL mutant, D165E, is a promising candidate for biodiesel industry.

Comparison of Postoperative Outcomes Between Traditional Longitudinal Incision and Bikini Incision in Total Hip Arthroplasty via Direct Anterior Approach: A Randomized Controlled Trial.

BACKGROUND: The purpose of this study is to compare a traditional longitudinal incision to an oblique "bikini" incision during total hip arthroplasty (THA) via direct anterior approach (DAA), in terms of the aesthetic appearance of the scar, postoperative functional recovery, and complications. METHODS: This study is a single-surgeon experience in the Chinese population. Patients who came to our institute needing a THA via DAA were enrolled in our randomized controlled trial and randomly allocated to undergo traditional longitudinal incision (control) or bikini incision. Primary outcomes were measured using the scar cosmesis assessment and rating scale, the visual analog scale for pain, Oxford hip score, and University of California Los Angeles activity-level rating. Secondary outcomes were postoperative serum markers of muscle damage, inflammation, hemoglobin drop, and implant stability. The occurrence of postoperative complications, such as nerve and wound healing, was also recorded. RESULTS: There were no differences in demographic or clinical characteristics before surgery. A greater proportion of patients in the bikini group were satisfied with the appearance of their scar, giving significantly better scar cosmesis assessment and rating scores. There was no difference in postoperative functional recovery, levels of serum markers, or positioning of the implant components. Incision type had no effect on duration of hospitalization. The incidence of complications did not differ significantly between groups. CONCLUSION: The bikini incision can improve patients' subjective satisfaction with scar aesthetics after THA via DAA and does not detract from a quick functional recovery. Studies with larger sample sizes should be conducted to further investigate associated complications. THE CLINICAL TRIAL REGISTRATION NUMBER: ChiCTR1900022870.

Surgical clipping of ophthalmic artery aneurysms: a single center series.

AIM: The purpose of this study was to summary the characteristics of ophthalmic artery (OphA) aneurysms and to obtain the independent risk factors for poor prognosis of microsurgical clipping treatment for OphA aneurysms. METHODS: The clinical and microsurgical clipping results of all 63 patients with ophthalmic aneurysm were investigated and reviewed. The OphA aneurysm patient's case records were reviewed including clinical characteristics, image findings, and clinical outcomes. Then, the risk factors of poor prognosis were analyzed retrospectively. RESULTS: Monocular blindness persisted in 4 patients (6.35%), 1 patient developed persistent vegetate state (PVS) (1.59%), while 4 patients (6.35%) died. The matching process constructed a cohort consisting of 9 poor outcome (Glasgow Outcome Scale, GOS 1-3) patients (14.3%), and 54 good outcome (GOS 4-5) patients (85.7%). Univariate analysis between the good outcome and poor outcome revealed statistical significance in age > 60 (p = 0.045), size (p = 0.016), and rupture before operation (p = 0.049). Further, multivariate logistic regression analysis identified age > 60 (odds ratio [OR], 5.877; 95% confidence interval [CI], 1.039-33.254; p = 0.045) and aneurysm size > 10mm (OR, 9.417; 95% CI, 1.476-60.072; p = 0.018) as the independent risk factors for poor outcome in microsurgical clipping treatment for OphA aneurysms. CONCLUSION: The significant independent risk factors associated with clipping OphA aneurysms are age (>60) and size (>10mm).

On the Use of Large Interactive Displays to Support Collaborative Engagement and Visual Exploratory Tasks.

Large interactive displays can provide suitable workspaces for learners to conduct collaborative learning tasks with visual information in co-located settings. In this research, we explored the use of these displays to support collaborative engagement and exploratory tasks with visual representations. Our investigation looked at the effect of four factors (number of virtual workspaces within the display, number of displays, position arrangement of the collaborators, and collaborative modes of interaction) on learners' knowledge acquisition, engagement level, and task performance. To this end, a user study was conducted with 72 participants divided into 6 groups using an interactive tool developed to support the collaborative exploration of 3D visual structures. The results of this study showed that learners with one shared workspace and one single display can achieve better user performance and engagement levels. In addition, the back-to-back position with learners sharing their view and control of the workspaces was the most favorable. It also led to improved learning outcomes and engagement levels during the collaboration process.

Association between NAFLD and risk of prevalent chronic kidney disease: why there is a difference between east and west?

BACKGROUNDS: There is a discrepancy between west and east on the relationship between non-alcoholic fatty liver disease (NAFLD) and chronic kidney disease (CKD). This study aimed to find out the possible reason for this and to clarify the association between NAFLD and CKD by analyzing two population-based datasets from the US and China. METHODS: Two health examination datasets from China and the US were used. CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73m2 or and/or abnormal albuminuria and/or overt proteinuria. Binary logistic regression was used to examine the association between NAFLD and CKD. RESULTS: A total of 60,965 participants were analyzed, including 11,844 from the US and 51,229 from China. The prevalence of NAFLD was 27.12% in the Chinese population and 36.08% in the US population (p < 0.001). The proportions of CKD and late stage CKD (stages 3-5) were higher in the US population than the Chinese one. NAFLD was independently associated with an increased risk of CKD in Chinese population, whereas in the US population, the NAFLD was not an independent risk factor of CKD. In subgroup analyses which excluded late stages CKD (stages 3-5), the risks of mild renal function decline became consistent: NAFLD was associated with early stages of CKD but not the late stages of CKD in both populations. CONCLUSION: NAFLD increased the risk of early stages of CKD in both Chinese and the US population. The conflicting results reported by previous studies might result from the different proportion of late stages of CKD.

Whole blood as an alternative to peripheral blood mononuclear cell for detection of total HIV-1 DNA.

BACKGROUND: A more time saving, convenient, reproducible, and scalable method is needed to assess total HIV-1 DNA levels. METHODS: Frozen whole blood and peripheral blood mononuclear cell (PBMC) samples both 200 µl at the same point were used to detect total HIV-1 DNA. Automatic extraction of total HIV-1 DNA was used to ensure the consistency of sample extraction efficiency. The detection reagent was HIV-1 DNA quantitative detection kit and real-time quantitative PCR was utilized. RESULTS: Of the 44 included patients, 42 were male and 2 were female, with a median age of 33 years. Thirty-three cases were collected after receiving antiviral treatment, with a median duration of treatment of 3 months, and the other 11 cases were collected before antiviral treatment. The median viral load was 1.83 log10 copies/mL, the median CD4 and CD8 count were 94 and 680 cells/µL, and the median CD4/CD8 ratio was 0.18. The results of the two samples were 3.02 ± 0.39 log10 copies/106 PBMCs in PBMC samples and 3.05 ± 0.40 log10 copies/106 PBMCs in whole blood samples. The detection results of the two methods were highly correlated and consistent by using paired t test (P = 0.370), pearson correlation (r = 0.887, P < 0.0001) and intra-group correlation coefficient (ICC = 0.887, P < 0.0001) and bland-altman [4.55% points were outside the 95% limits of agreement (- 0.340 ~ 0.390)]. CONCLUSIONS: The results of the whole blood sample test for total HIV-1 DNA are consistent with those of PBMC samples. In a clinical setting it is recommended to use whole blood samples directly for the evaluation of the HIV reservoir.

Identification of 2 Potential Core Genes for Influence of Gut Probiotics on Formation of Intracranial Aneurysms by Bioinformatics Analysis.

BACKGROUND Rupture of intracranial aneurysms (IA) is associated with high rates of mortality around the world. Use of intestinal probiotics can regulate the pathophysiology of aneurysms, but the details of the mechanism involved have been unclear. MATERIAL AND METHODS The GEO2R analysis website was used to detect the DEGs between IAs, AAAs, samples after supplementation with probiotics, and normal samples. The online tool DAVID provides functional classification and annotation analyses of associated genes, including GO and KEGG pathway. PPI of these DEGs was analyzed based on the STRING database, followed by analysis using Cytoscape software. RESULTS We found 170 intersecting DEGs (contained in GSE75240 and more than 2 of the 4 aneurysms datasets), 5 intersecting DEGs (contained in all datasets) and 1 intersecting DEG (contained in GSE75240 and all IAs datasets). GO analysis results suggested that the DEGs primarily participate in signal transduction, cell adhesion, immune response, response to drug, extracellular matrix organization, cell-cell signaling, and inflammatory response in the BP terms, and the KEGG pathways are mainly enriched in focal adhesion, cytokine-cytokine receptor interaction, ECM-receptor interaction, amoebiasis, chemokine signaling pathway, proteoglycans, and PI3K-Akt signaling pathway in cancer pathways. Through PPI network analysis, we confirmed 2 candidates for further study: CAV1 and MYH11. These downregulated DEGs are associated with the formation of aneurysms, and the change of these DEGs is the opposite in probiotics-treated animals. CONCLUSIONS Our study suggests that MYH11 and CAV1 are potential target genes for prevention of aneurysms. Further experiments are needed to verify these findings.

Tamoxifen attenuates reactive astrocyte-induced brain metastasis and drug resistance through the IL-6/STAT3 signaling pathway.

Brain metastasis affects approximately 20%-30% of patients with triple-negative breast cancers (TNBCs). Even small metastatic lesions in the brain can trigger severe neurological impairments and result in extremely short survival time. Recently, active astrocytes were reported to be associated with brain metastases. However, how activated astrocytes regulate the behaviors of disseminated breast cancer cells in the brain remains unknown. In this study, human primary astrocytes were stimulated with IL-1ß to form active astrocytes to study the cross-talk between stromal cells (astrocytes) and TNBC cells in brain metastases. Our results showed that active astrocytes significantly increase the malignancy of TNBC cells and prevent them from undergoing apoptosis caused by doxorubicin. We also found that the high level of IL-6 secreted by activated astrocytes was responsible for the drug resistance of breast cancer, which could be abolished by treatment of astrocytes with tamoxifen (TAM). The blockage of active astrocyte-derived IL-6 by a neutralizing antibody resulted in the attenuation of drug resistance, consequently enhancing the sensitivity of breast cancer cells to doxorubicin. Furthermore, the possible involved TAM-modulated drug resistance mechanism may be associated with a decrease in IL-6 expression in astrocytes and the downregulation of MAPK and JAK2/STAT3 signaling in cancer cells. Our data suggested that TAMs might reduce drug resistance through the IL-6/JAK2/STAT3 signaling pathway, providing a possible therapy to treat brain metastasis in TNBCs, as estrogen receptor inhibitors (TAMs, etc.) can cross the blood-brain barrier.

A Semantic-Based Belief Network Construction Approach in IoT.

Uncertainty is intrinsic in most of the complex systems, especially when the systems have to interact with the physical environment; therefore, handling uncertainty is critical in the Internet of Things (IoT). In this paper, we propose a semantic-based approach to build the belief network in IoT systems to handle the uncertainties. Semantics is the functionality description of any system component. Semantic Match mechanisms can construct the appropriate structures to compare the consistency between different sources of data based on the same functionality. In the approach, we define the belief property of every system component and develop the related algorithms to update the belief value. Furthermore, the related mechanisms and algorithms for data fusion and fault detection based on the belief property are described to explain how the approach works in the IoT systems. Several simulation experiments are used to evaluate the proposed approach, and the results indicate that the approach can work as expected. More accurate data are fused from the inaccurate devices and the fault in one node is automatically detected.

Single Cell Explorer, collaboration-driven tools to leverage large-scale single cell RNA-seq data.

BACKGROUND: Single cell transcriptome sequencing has become an increasingly valuable technology for dissecting complex biology at a resolution impossible with bulk sequencing. However, the gap between the technical expertise required to effectively work with the resultant high dimensional data and the biological expertise required to interpret the results in their biological context remains incompletely addressed by the currently available tools. RESULTS: Single Cell Explorer is a Python-based web server application we developed to enable computational and experimental scientists to iteratively and collaboratively annotate cell expression phenotypes within a user-friendly and visually appealing platform. These annotations can be modified and shared by multiple users to allow easy collaboration between computational scientists and experimental biologists. Data processing and analytic workflows can be integrated into the system using Jupyter notebooks. The application enables powerful yet accessible features such as the identification of differential gene expression patterns for user-defined cell populations and convenient annotation of cell types using marker genes or differential gene expression patterns. Users are able to produce plots without needing Python or R coding skills. As such, by making single cell RNA-seq data sharing and querying more user-friendly, the software promotes deeper understanding and innovation by research teams applying single cell transcriptomic approaches. CONCLUSIONS: Single cell explorer is a freely-available single cell transcriptomic analysis tool that enables computational and experimental biologists to collaboratively explore, annotate, and share results in a flexible software environment and a centralized database server that supports data portal functionality.

Genetic variants in IL-33/ST2 pathway with the susceptibility to hepatocellular carcinoma in a Chinese population.

Interleukin (IL)-33/ST2 pathway plays a pivotal role in tumorigenesis through influencing cancer stemness, tumor growth, metastasis, angiogenesis, and accumulation of regulatory T cells in tumor microenvironments. The aim of this study was to investigate the association of IL-33 rs7025417 and ST2 rs3821204 with the risk of hepatocellular carcinoma (HCC). Genotyping of IL-33 rs7025417 and ST2 rs3821204 was carried out using a Taqman assay. IL-33 and ST2 mRNA was examined using real-time PCR and plasma IL-33 and sST2 levels were measured using enzyme-linked immunosorbent assay. The ST2 rs3821204 CC genotype was associated with a significantly increased risk of HCC (CC vs. GG: adjusted OR = 2.29, 95% CI, 1.39-3.78; dominant model: adjusted OR = 1.58, 95% CI, 1.12-2.23; recessive model: adjusted OR = 1.88, 95% CI, 1.21-2.93; C vs. G: adjusted OR = 1.53, 95% CI, 1.20-1.95). Gene-environment interaction analysis showed that the risk effect of rs3821204 CG/CC genotypes was more evident in smokers (adjusted OR = 1.70, 95% CI, 1.13-2.55) and drinkers (adjusted OR = 1.57, 95% CI, 1.04-2.37). The increased risk was also observed in combined analysis. Moreover, HCC patients with ST2 rs3821204 CC genotype had higher levels of mRNA and protein expression (P < 0.05). These findings suggest that ST2 rs3821204 CC genotype may contribute to hepatocarcinogenesis by enhancing ST2 production at the transcriptional and translational level.

Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.

BACKGROUND: Lung segmentation constitutes a critical procedure for any clinical-decision supporting system aimed to improve the early diagnosis and treatment of lung diseases. Abnormal lungs mainly include lung parenchyma with commonalities on CT images across subjects, diseases and CT scanners, and lung lesions presenting various appearances. Segmentation of lung parenchyma can help locate and analyze the neighboring lesions, but is not well studied in the framework of machine learning. METHODS: We proposed to segment lung parenchyma using a convolutional neural network (CNN) model. To reduce the workload of manually preparing the dataset for training the CNN, one clustering algorithm based method is proposed firstly. Specifically, after splitting CT slices into image patches, the k-means clustering algorithm with two categories is performed twice using the mean and minimum intensity of image patch, respectively. A cross-shaped verification, a volume intersection, a connected component analysis and a patch expansion are followed to generate final dataset. Secondly, we design a CNN architecture consisting of only one convolutional layer with six kernels, followed by one maximum pooling layer and two fully connected layers. Using the generated dataset, a variety of CNN models are trained and optimized, and their performances are evaluated by eightfold cross-validation. A separate validation experiment is further conducted using a dataset of 201 subjects (4.62 billion patches) with lung cancer or chronic obstructive pulmonary disease, scanned by CT or PET/CT. The segmentation results by our method are compared with those yielded by manual segmentation and some available methods. RESULTS: A total of 121,728 patches are generated to train and validate the CNN models. After the parameter optimization, our CNN model achieves an average F-score of 0.9917 and an area of curve up to 0.9991 for classification of lung parenchyma and non-lung-parenchyma. The obtain model can segment the lung parenchyma accurately for 201 subjects with heterogeneous lung diseases and CT scanners. The overlap ratio between the manual segmentation and the one by our method reaches 0.96. CONCLUSIONS: The results demonstrated that the proposed clustering algorithm based method can generate the training dataset for CNN models. The obtained CNN model can segment lung parenchyma with very satisfactory performance and have the potential to locate and analyze lung lesions.