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Dyslipidemia may be a potential mechanism linking fine particulate matter (PM

Background. A rising amount of data demonstrates that the epithelial-mesenchymal transition (EMT) in clear cell renal cell carcinomas (ccRCC) is connected with the advancement of the cancer. In order to understand the role of EMT in ccRCC, it is critical to integrate molecules involved in EMT into prognosis prediction. The objective of this project was to establish a prognosis prediction model using genes associated with EMT in ccRCC. Methods. We acquired the mRNA expression profiles and clinical information about ccRCC from TCGA database. In this study, we measured differentially expressed EMT-related genes (DEEGs) by two comparison groups (tumor versus normal tissues; “stages I-II” versus “stages III-IV” tumor tissues). Based on classification and regression random forest models, we identified the most important DEEGs in predicting prognosis. Afterwards, a risk-score model was created using the identified important DEEGs. The prediction ability of the risk-score model was calculated by the area under the curve (AUC). A nomogram for prognosis prediction was built using the risk-score in combination with clinical factors. Results. Among the 72 DEEGs, the classification and regression random forest models identified six hub genes (DKK1, DLX4, IL6, KCNN4, RPL22L1, and SPDEF), which exhibited the highest importance values in both models. Through the expression of these six hub genes, a novel risk-score was developed for the prognosis prediction of ccRCC. ROC curves showed the risk-score performed well in both the training (0.749) and testing (0.777) datasets. According to the survival analysis, individuals who were separated into high/low-risk groups had statistically different outcomes in terms of prognosis. Besides, the risk-score model also showed outstanding ability in assessing the progression of ccRCC after treatment. In terms of nomogram, the concordance index (C-index) was 0.79. Additionally, we predicted the differences in response to chemotherapy drugs among patients from low- and high-risk groups. Conclusion. Gene signatures related to EMT could be useful in predicting ccRCC prognosis.

Although single image dehazing has been widely studied as a common low-level computer vision task, it still faces serious challenges such as limited ability to dehaze real foggy pictures. We propose an efficient end-to-end self-adaptation feature attention (SAFA) network with multi-step fusion for this purpose. The proposed SAFA module can adaptively expand the receptive field to obtain the key structure information in space and extract more comprehensive and accurate features. In addition, considering the lack of connection between features acquired at low and high levels in the network, we also implement a multi-step fusion module, which makes the features of different layers in the network complementary effectively in the process of image recovery. The network structure is simplified, and the required computing resources are significantly reduced by decreasing network parameters. For multiple datasets and photographs with real haze, our method demonstrates better efficiency and availability, both quantitatively and qualitatively.

Background Recent studies indicate exosomes play an important role in cell-to-cell communication, cancer metastasis, neovascularization, the regulation of the tumor immune microenvironment, and drug resistance in various tumors. However, the prognostic and therapeutic value of exosome-related genes in bladder cancer (BCa) remains to be determined. Hence, the goal of this study was to identify and validate a novel prognostic model based on exosome-associated genes for BCa patients Methods Differentially expressed exosome-related genes (DEGs) were analyzed using the Cancer Genome Atlas (TCGA) databases. DEGs closely associated with BCa patient survival prognosis were identified using Cox regression; and these genes are used for molecular typing. Moreover, we constructed a 17 multigene model using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The five external cohorts (i.e., GSE13507, GSE32894, GSE31684, GSE48075, and IMvigor210) of BCa patients were used to validate the accuracy by KM plot, ROC and calibration curves. Subsequently, we assessed immune infiltration using seven published algorithms: TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL, and EPIC. Furthermore, the correlation results between risk groups (scores) and overall survival, recognised immunoregolatory cells or common chemotherapeutic agents, clinicopathological data and immune checkpoint-related genes of BCa patients, were analyzed based on wilcox rank test, chi-square test, cox regression and spearman's correlation method. Additionally, we also preformed that the expression level of partial modeled genes was significantly associated with objective responses to anti-PD-1/PD-L1 treatment in the IMvigor210, GSE111636, GSE176307 or our Truce01 cohort. Results In BC patients, 156 exosome-related prognostic DEGs were identified, and were clustered into three classes. Subtypes C3 predicts worse OS, DSS, and PFS in patients with BCa. The prognostic model of 17 exosome-related genes showed good prediction performance by the TCGA training set, internal test set and five external verification sets. Our study also additionally confirmed that model riskscore was closely related with drug susceptibility, immune cell infiltration, and the prediction of immunotherapy efficacy. The high-risk group was characterized by a higher number of infiltrating macrophages M2 cells, and cancer-associated fibroblasts (CAFs). Lastly, we verified the protein and mRNA expression of six interested model-related genes (including AKR1B1, CGB5, CSPG4, P4HB, POLR3G and RAC3) from the Human Protein Atlas (HPA) and 10 paired BCa tissues collected by us. Conclusions In summary, the exosome-associated gene signature established by us exhibited a high predictive performance for the prognosis, immunotherapeutic responsiveness, and chemotherapeutic sensitivity of BCa. And, The model also might function as a chemotherapy and immune checkpoint inhibitor (ICI) treatment guidance.

Hydrogel-based microfluidics offer an in vivo-relevant micro-environments for construction of organs-on-chips. However, the fabrication of heterogeneous microchannels using hydrogels is challenging and fails to mimic the complex structures of organs in vivo. Here we present a new methodology called “layer-by-layer adhesion” for the construction of complex microfluidic chips. A hydrosoluble and photo-crosslinkable adhesive, chitosan methacryloyl (CS-MA), was used to stitch various hydrogels together layer-by-layer to form perfusable microchannels. Our results show that CS-MA can bond different types of hydrogels with adhesion energy ranging from 1.2-140 N/m. Using the layer-by-layer adhesion approach, we constructed heterogeneous hydrogel-based microchannels with various morphologies of snail, spiral, vascular-like, and bilayer. Based on this methodology, liver-on-a-chip was established by entrapping hepatic cells inside a biocompatible Gel-MA layer and covering it with the perfusable microchannels in tough F127-DA layer. The “layer-by-layer adhesion” provides a facile and cytocompatible approach for engineering user-defined hydrogel-based chips potentially for organs-on-chips.

Background In cancer, exosomes play an important role in cell-to-cell communication, cancer metastasis,neovascularization, and drug resistance. Due to the lack of mechanistic studies regarding exosomes in bladder cancer (BCa), the goal of this study was to identify the significance of exosome-related genes in BCa.Methods Differentially expressed genes (DEGs) were analyzed using the Cancer Genome Atlas (TCGA) databases. DEGs closely associated with BCa patient survival were identified using Cox regression, least absolute shrinkage, and selection operator analyses. A prognostic model about exosomes was then developed and validated. To predict survival, a nomogram was developed.Results A prediction model was constructed using seventeen of the six hundred and fifty-six DEGs related to exosomes. A low-risk and high-risk group was then established for patients with BCa. Patients at high-risk group had a significantly worse prognosis than those at low-risk group. Further analysis showed a lower risk score was associated with higher expression of immune cell infiltration, including T cells regulatory (Tregs) and Mast cells activated, and immune checkpoint genes, including LGALS9 and TNFRSF14.Conclusions Using exosome-related genes, this study identified a novel biomarker that may be used to predict the outcome of BCa in the future.

Modeling the global dynamics of emerging infectious diseases (EIDs) like COVID-19 can provide important guidance in the preparation and mitigation of pandemic threats. While age-structured transmission models are widely used to simulate the evolution of EIDs, most of these studies focus on the analysis of specific countries and fail to characterize the spatial spread of EIDs across the world. Here, we developed a global pandemic simulator that integrates age-structured disease transmission models across 3,157 cities and explored its usage under several scenarios. We found that without mitigations, EIDs like COVID-19 are highly likely to cause profound global impacts. For pandemics seeded in most cities, the impacts are equally severe by the end of the first year. The result highlights the urgent need for strengthening global infectious disease monitoring capacity to provide early warnings of future outbreaks. Additionally, we found that the global mitigation efforts could be easily hampered if developed countries or countries near the seed origin take no control. The result indicates that successful pandemic mitigations require collective efforts across countries. The role of developed countries is vitally important as their passive responses may significantly impact other countries.

Aims LDL cholesterol (LDL-C) is a well-established risk factor for coronary artery disease (CAD). However, the optimal LDL-C level with regard to efficacy and safety remains unclear. We aimed to investigate the causal relationships between LDL-C and efficacy and safety outcomes. Methods and results We analyzed 353 232 British from the UK Biobank and 41 271 Chinese from the China-PAR project. Linear and non-linear Mendelian randomization (MR) analyses were performed to evaluate the causal relation between genetically proxied LDL-C and CAD, all-cause mortality, and safety outcomes (including haemorrhagic stroke, diabetes mellitus, overall cancer, non-cardiovascular death, and dementia). No significant non-linear associations were observed for CAD, all-cause mortality, and safety outcomes (Cochran Q P > 0.25 in British and Chinese) with LDL-C levels above the minimum values of 50 and 20 mg/dL in British and Chinese, respectively. Linear MR analyses demonstrated a positive association of LDL-C with CAD [British: odds ratio (OR) per unit mmol/L increase, 1.75, P = 7.57 × 10−52; Chinese: OR, 2.06, P = 9.10 × 10−3]. Furthermore, stratified analyses restricted to individuals with LDL-C levels less than the guideline-recommended 70 mg/dL demonstrated lower LDL-C levels were associated with a higher risk of adverse events, including haemorrhagic stroke (British: OR, 0.72, P = 0.03) and dementia (British: OR, 0.75, P = 0.03). Conclusion In British and Chinese populations, we confirmed a linear dose–response relationship of LDL-C with CAD and found potential safety concerns at low LDL-C levels, providing recommendations for monitoring adverse events in people with low LDL-C in the prevention of cardiovascular disease.

Haemorrhagic stroke (HS) is a devastating form of stroke with a high fatality rate. The lack of rapid lesion detection limits early diagnosis of HS. Several susceptibility genes of HS found in genome-wide association studies (GWAS) warrant transcriptional-level biomarkers for useful utility. 13 GWAS level loci with minor allele frequency ≥ 0.05 were selected out of 95 loci related to HS. After validation, the mRNA expression in peripheral leukocytes of 11 genes (PMF1, SLC25A44, CASZ1, NINJ2, WNK1, DYRK1A, LRCH1, LDLR, SMARCA4, AQP9, and LIPC) were measured in the HS case-control study (64 HS cases vs. 128 controls), and then verified in an ischemic stroke (IS) case-control study (67 IS cases vs. 61 controls). LIPC (P=0.002) and CASZ1 (P=0.040) were downregulated in HS patients, while SLC25A44 was upregulated (P=0.009). In the IS case-control study, the differential expression of LIPC (P=0.034) and SLC25A44 (PCASZ1 expression was not different between IS cases and controls (P=0.419) with fold change (FC) of 1.205, the direction of expression was opposite to that in HS case-control study (FC=0.747). The ROCtrfgs of traditional risk factors and gene score which was estimated by combining LIPC, CASZ1, and SLC25A44 expression weights, improved the utility for HS identification by 14.1% compared with ROC (P=0.001). Expression of LIPC, CASZ1, and SLC25A44 could serve as potential biomarkers for identifying HS. CASZ1 might be a cause-specific indicator for differentiating HS from IS. Transcriptional score of these three genes could improve performance of the traditional risk model for HS identification.

Background and Aims We explored the associations among fruit consumption, physical activity and their dose-response relationship with all-cause and cardiovascular disease (CVD) mortality in type 2 diabetic patients. Methods and Results We prospectively followed 20,340 community-dwelling type 2 diabetic patients aged 21-94 years. Information on diets and physical activity was collected using standardized questionnaires. All-cause and CVD mortality were assessed. Hazard ratios (HRs) for all-cause mortality were estimated with Cox regression models, and HRs for CVD mortality were derived from a competing risk model. Restricted cubic spline regression was used to analyse dose-response relationships. We identified 1,362 deaths during 79,844 person-years. Compared to non-consumption, fruit consumption >42.9 g/d was inversely associated with all-cause mortality (HR 0.76; 95% CI 0.64-0.88), CVD mortality (HR 0.69, 0.51-0.94) and stroke mortality (HR 0.57, 0.36-0.89), but not with heart disease mortality (HR 0.93, 0.56-1.52). The HRs comparing the top vs bottom physical activity quartiles were 0.44 (0.37-0.53) for all-cause mortality, 0.46 (0.33-0.64) for CVD mortality, 0.46 (0.29-0.74) for stroke mortality and 0.51 (0.29-0.88) for heart disease mortality. Lower fruit consumption combined with a lower physical activity level was associated with a greater mortality risk. A nonlinear threshold of 80 g fruit/day was identified, all-cause mortality risk was reduced by approximately 24% at this value. A physical activity threshold of 8 metabolic equivalents (MET) h/day was also identified, after which the risk of mortality did not decrease. Conclusions Fruit consumption and physical activity may reduce all-cause, CVD and stroke mortality in type 2 diabetic patients.

In recent years, the bionic polarized light compass has been widely studied for the unmanned aerial vehicle navigation. However, it is found from the obtained investigation results that a polarized light compass with a sensitive and high dynamic range polarimeter still provides inferior output precision of the heading angle due to the presence of the noise generating from the compass. The noise is existed not only in the angle of the polarization image acquired by polarimeters but also in the output heading data, which leads to a sharp reduction in the accuracy of a polarized light compass. Herein, we present noise analysis and a novel multiscale transform denoising method of a polarized light compass used for the unmanned aerial vehicle navigation. Specifically, a multiscale principle component analysis utilizing one-dimensional image entropy as classification criterion is directly implemented to suppress the noise in the acquired polarization image. Subsequently, a multiscale time–frequency peak filtering method using the sample entropy as classification criterion is applied for the output heading data so as to further increase the heading measurement accuracy from the denoised image above. These two approaches are combined to significantly reduce the heading error affected by different types of noises. Our experimental results indicate the proposed multiscale transform denoising method exhibits high performance in suppressing the noise of a polarized light compass used for the unmanned aerial vehicle navigation compared to existing prior arts.

One of the most important results in domain theory is the Hofmann-Mislove Theorem, which reveals a very distinct characterization for the sober spaces via open filters. In this paper, we extend this result to the d-spaces and well-filtered spaces. We do this by introducing the notions of Hofmann-Mislove-system (HM-system for short) and $\Psi$ -well-filtered space, which provide a new unified approach to sober spaces, well-filtered spaces, and d-spaces. In addition, a characterization for $\Psi$ -well-filtered spaces is provided via $\Psi$ -sets. We also discuss the relationship between $\Psi$ -well-filtered spaces and H-sober spaces considered by Xu. We show that the category of complete $\Psi$ -well-filtered spaces is a full reflective subcategory of the category of $T_0$ spaces with continuous mappings. For each HM-system $\Psi$ that has a designated property, we show that a $T_0$ space X is $\Psi$ -well-filtered if and only if its Smyth power space $P_s(X)$ is $\Psi$ -well-filtered.

Immiscible and incompressible liquid–liquid flows are considered in a Taylor–Couette geometry and analysed by direct numerical simulations coupled with the volume-of-fluid method and a continuum surface force model. The system Reynolds number $Re \equiv r_i \omega _i d / \nu$ is fixed to $960$ , where the single-phase flow is in the steady Taylor vortex regime, whereas the secondary-phase volume fraction $\varphi$ and the system Weber number $We \equiv \rho r_i^2 \omega _i^2 d / \sigma$ are varied to study the interactions between the interface and the Taylor vortices. We show that different Weber numbers lead to two distinctive flow regimes, namely an advection-dominated regime and an interface-dominated regime. When $We$ is high, the interface is easily deformed because of its low surface tension. The flow patterns are then similar to the single-phase flow, and the system is dominated mainly by advection (advection-dominated regime). However, when $We$ is low, the surface tension is so large that stable interfacial structures with sizes comparable to the cylinder gap can exist. The background velocity field is modulated largely by these persistent structures, thus the overall flow dynamics is governed by the interface (interface-dominated regime). The effect of the interface on the global system response is assessed by evaluating the Nusselt number $Nu_{\omega }$ based on the non-dimensional angular velocity transport. It shows non-monotonic trends as functions of the volume fraction $\varphi$ for both low and high $We$ . We explain how these dependencies are closely linked to the velocity and interfacial structures.

Ultrafiltration membranes can intercept oil particles smaller than 10 μm, but the membranes are easily contaminated by oil due to their hydrophobicity. To treat various oily wastewaters, we prepared a hydrophilic hollow fiber membrane (HFM) with anti-fouling property by grafting sulfobetaine methacrylate (SBMA) onto polysulfone (PSU). For six simulated wastewaters containing emulsified oil at 1,000 mg/L, the PSU-g-SBMA HFM was able to remove 98.5–99.7% of oil, higher than that of PSU HFM at 91.1–98.9%. The oil concentration in filtrate was less than 15 mg/L, which could meet the discharge standard of wastewater. The water flux of PSU-g-SBMA HFM can be completely recovered after being washed by rhamnolipid and alkali solution, while the same cleaning process could not recover the PSU HFM. As found, the contact angles of oil droplets on the PSU-g-SBMA membrane were larger than those on PSU membrane, which indicated the improved hydrophilicity by PSU-g-SBMA. For 48 h of filtration to soybean and diesel oil/water emulsion, the effect of PSU-g-SBMA HFM was stable and the flux could be completely recovered by cleaning. Therefore, we provided a new method for oily wastewater treatment, which can efficiently and energy-saving remove various oil substances in wastewater. HIGHLIGHTS PSU-g-SBMA hollow fiber membrane could well remove >98.5% of various oil form wastewaters.; RHA + NaOH solution could completely recover the water flux of the oil-contaminated PSU-g-SBMA hollow fiber membrane.; Oil contamination on membranes was partly determined by the contact angles of oil.

Background Stroke is the leading cause of mortality in China. DNA methylation has essential roles in multiple diseases, but its association with stroke was barely studied. We hereby explored the association between blood-based HTRA serine protease 1 (HTRA1) methylation and the risk of stroke. Results The association was discovered in a hospital-based case–control study (cases/controls = 190:190) and further validated in a prospective nested case–control study including 139 cases who developed stroke within 2 years after recruitment and 144 matched stroke-free controls. We observed stroke-related altered HTRA1 methylation and expression in both case–control study and prospective study. This blood-based HTRA1 methylation was associated with stroke independently from the known risk factors and mostly affected the older population. The prospective results further showed that the altered HTRA1 methylation was detectable 2 years before the clinical determination of stroke and became more robust with increased discriminatory power for stroke along with time when combined with other known stroke-related variables [onset time ≤ 1 year: area under the curve (AUC) = 0.76]. Conclusions In our study, altered HTRA1 methylation was associated with stroke at clinical and preclinical stages and thus may provide a potential biomarker in the blood for the risk evaluation and preclinical detection of stroke.