Controlled Porosity in Thermochromic Coatings

Vanadium dioxide is a promising thermochromic material, seemed as the great candidate for smart window applications. The real application of VO2 requires high visible transmission (Tlum) as well as large solar modulating abilities (∆Tsol), which could not be achieved by pristine VO2 materials due to the trade-off between Tlum and ∆Tsol. Here in, the porosity design is thoroughly reviewed from the effect on modulating the thermochromic performance to the porous control and preparation. To begin with, the history, advantages, challenges and approaches to tackle the issues comprised of antireflection multilayer structure, nanothermochromism, patterning and porous design is introduced in detail. Then, the effect of porosity on improving the thermochromic performance of VO2 thin films is demonstrated using the newest experimental and simulation results. In the following, the porous control and structural synthesis, including the polymer-assisted deposition (PAD), freeze-drying, colloidal lithography as well as the dual phase transformation is summarized. Fourthly, the characterization methods, composed of scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), X-ray diffraction (XRD), Raman spectroscopy as well as UV-Vis-NIR spectroscopy are demonstrated. Finally, the challenges that the porous design faces and possible approaches to optimize the performance are presented

Multiobjective Transmission Network Planning considering the Uncertainty and Correlation of Wind Power

In order to consider the uncertainty and correlation of wind power in multiobjective transmission network expansion planning (TNEP), this paper presents an extended point-estimation method to calculate the probabilistic power flow, based on which the correlative power outputs of wind farm are sampled and the uncertain multiobjective transmission network planning model is transformed into a solvable deterministic model. A modified epsilon multiobjective evolutionary algorithm is used to solve the above model and a well-distributed Pareto front is achieved, and then the final planning scheme can be obtained from the set of nondominated solutions by a fuzzy satisfied method. The proposed method only needs the first four statistical moments and correlation coefficients of the output power of wind farms as input information; the modeling of wind power is more precise by considering the correlation between wind farms, and it can be easily combined with the multiobjective transmission network planning model. Besides, as the self-adaptive probabilities of crossover and mutation are adopted, the global search capabilities of the proposed algorithm can be significantly improved while the probability of being stuck in the local optimum is effectively reduced. The accuracy and efficiency of the proposed method are validated by IEEE 24 as well as a real system

Zero-shot Skeleton-based Action Recognition via Mutual Information Estimation and Maximization

Zero-shot skeleton-based action recognition aims to recognize actions of unseen categories after training on data of seen categories. The key is to build the connection between visual and semantic space from seen to unseen classes. Previous studies have primarily focused on encoding sequences into a singular feature vector, with subsequent mapping the features to an identical anchor point within the embedded space. Their performance is hindered by 1) the ignorance of the global visual/semantic distribution alignment, which results in a limitation to capture the true interdependence between the two spaces. 2) the negligence of temporal information since the frame-wise features with rich action clues are directly pooled into a single feature vector. We propose a new zero-shot skeleton-based action recognition method via mutual information (MI) estimation and maximization. Specifically, 1) we maximize the MI between visual and semantic space for distribution alignment; 2) we leverage the temporal information for estimating the MI by encouraging MI to increase as more frames are observed. Extensive experiments on three large-scale skeleton action datasets confirm the effectiveness of our method. Code: https://github.com/YujieOuO/SMIE.Comment: Accepted by ACM MM 202

In vitro inhibitory and pro-apoptotic effect of Stellera Chamaejasme L Extract on human lung cancer cell line NCI-H157

AbstractObjectiveTo investigate the inhibitory and pro-apoptotic effect of Stellera Chamaejasme L extract (ESC) in vitro.MethodsESC was first extracted with ethanol, and then washed using a polyamide column with 60% ethanol. ESC was then decompressively recycled and vacuum dried at room temperature to obtain active fractions. Subsequently, the cytotoxic and apoptotic effects of ESC on NCI-H157 human lung cancer cells were determined.ResultsThe results showed that ESC was rich in isomers of Chamaejasminor, neochamaejasmine and Sikokianin. ESC had significant cytotoxicity against NCI-H157 cells, with an IC50 of approximately 18.50 μg · mL−1. ESC caused significant increase in total apoptotic rate, the activity of caspase 3 and 8, and Fas protein expression (P<0.05).ConclusionThe inhibitory effect of ESC on NCI-H157 tumor cells might partly be attributed to its apoptotic induction through activation of the Fas death receptor pathway

Comparison of the major cell populations among osteoarthritis, Kashin-Beck disease and healthy chondrocytes by single-cell RNA-seq analysis

Chondrocytes are the key target cells of the cartilage degeneration that occurs in Kashin-Beck disease (KBD) and osteoarthritis (OA). However, the heterogeneity of articular cartilage cell types present in KBD and OA patients and healthy controls is still unknown, which has prevented the study of the pathophysiology of the mechanisms underlying the roles of different populations of chondrocytes in the processes leading to KBD and OA. Here, we aimed to identify the transcriptional programmes and all major cell populations in patients with KBD, patients with OA and healthy controls to identify the markers that discriminate among chondrocytes in these three groups. Single-cell RNA sequencing was performed to identify chondrocyte populations and their gene signatures in KBD, OA and healthy cells to investigate their differences as related to the pathogenetic mechanisms of these two osteochondral diseases. We performed immunohistochemistry and quantitative reverse-transcription PCR (qRT-PCR) assays to validate the markers for chondrocyte population. Ten clusters were labelled by cell type according to the expression of previously described markers, and one novel population was identified according to the expression of a new set of markers. The homeostatic and mitochondrial chondrocyte populations, which were identified by the expression of the unknown markers MT1X and MT2A and MT-ND1 and MT-ATP6, were markedly expanded in KBD. The regulatory chondrocyte population, identified by the expression of CHI3L1, was markedly expanded in OA. Our study allows us to better understand the heterogeneity of chondrocytes in KBD and OA and provides new evidence of differences in the pathogenetic mechanisms between these two diseases

Особенности вазомоторной функции эндотелия у больных стабильной стенокардией с факторами риска (артериальной гипертензией, гиперхолестеринемией, курением)

ВАЗОМОТОРНАЯ СИСТЕМАЭНДОТЕЛИЙ /ФИЗИОЛЭПИТЕЛИЙСТЕНОКАРДИЯКОРОНАРНАЯ БОЛЕЗНЬГРУДНАЯ КЛЕТКА, БОЛИФАКТОРЫ РИСКАГИПЕРТЕНЗИЯКРОВЕНОСНЫХ СОСУДОВ БОЛЕЗНИГИПЕРХОЛЕСТЕРИНЕМИЯГИПЕРЛИПИДЕМИЯКУРЕНИЕ /ВРЕД ВОЗДТАБАКА УПОТРЕБЛЕНИЕ, РАССТРОЙСТВА ЗДОРОВЬ

Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

Background Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence. Methods The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database. Results Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group. Conclusions Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients

Differential expression of cyclins CCNB1 and CCNG1 is involved in the chondrocyte damage of kashin-beck disease

The purpose of this study was clarify the relationship between the differential expression of cyclins CCNB1 and CCNG1 and chondrocyte damage in Kashin-Beck disease. Systematic review and high-throughput sequencing of chondrocytes derived from Kashin-Beck disease patients were combined to identify the differentially expressed cyclins and cyclin-dependent kinase genes. In parallel, weaned SD rats were treated with low selenium for 4 weeks and then T-2 toxin for 4 weeks. Knee cartilage was collected to harvest chondrocytes for gene expression profiling. Finally, the protein expression levels of CCNB1 and CCNG1 were verified in knee cartilage tissue of Kashin-Beck disease patients and normal controls by immunohistochemical staining. The systematic review found 52 cartilage disease-related cyclins and cyclin-dependent kinase genes, 23 of which were coexpressed in Kashin-Beck disease, including 15 upregulated and 8 downregulated genes. Under the intervention of a low selenium diet and T-2 toxin exposure, CCNB1 (FC = 0.36) and CCNG1 (FC = 0.73) showed a downward expression trend in rat articular cartilage. Furthermore, compared to normal controls, CCNB1 protein in Kashin-Beck disease articular cartilage was 71.98% and 66.27% downregulated in the superficial and middle zones, respectively, and 12.06% upregulated in the deep zone. CCNG1 protein was 45.66% downregulated in the superficial zone and 12.19% and 9.13% upregulated in the middle and deep zones, respectively. The differential expression of cyclins CCNB1 and CCNG1 may be related to articular cartilage damage in Kashin-Beck disease

Metabolic syndrome and metastatic prostate cancer correlation study, a real-world study in a prostate cancer clinical research center, Xinjiang, China

ObjectiveThe aim of this study was to investigate the relevance of metabolic syndrome (MetS) and metabolic scores to the occurrence, progression and prognosis of metastatic prostate cancer (mPCA), assessing the definition of the variables of metabolic syndrome, and the potential mechanisms of MetS and mPCA.MethodsData were obtained from the database of prostate cancer follow-up at the Urology Centre of the First Affiliated Hospital of Xinjiang Medical University (N=1303). After screening by inclusion and exclusion criteria, clinical data of 190 patients diagnosed with mPCA by pathology and imaging from January 2010 to August 2021 were finally included, including 111 cases in the MetS group and 79 cases in the Non-MetS group.ResultsThe MetS group was higher than the Non-MetS group: T stage, Gleasson score, initial PSA, tumor load, PSA after 7 months of ADT (P&lt;0.05),with a shorter time to progression to CRPC stage(P&lt;0.05)[where the time to progression to CRPC was relatively shorter in the high metabolic score subgroup of the MetS group than in the low subgroup (P&lt;0.05)].Median survival time was significantly shorter in the MetS group than in the Non-MetS group (P&lt;0.05),and there was a correlation with metabolic score, with the higher metabolic score subgroup having a lower survival time than the lower metabolic score subgroup (P&lt;0.05).ConclusionThose with mPCA combined with MetS had lower PSA remission rates, more aggressive tumors, shorter time to progression to CRPC and shorter median survival times than those with mPCA without MetS.Tumour progression and metabolic score showed a positive correlation, predicting that MetS may promote the progression of mPCA, suggesting that MetS may be a risk factor affecting the prognosis of mPCA