Construction of T cell exhaustion model for predicting survival and immunotherapy effect of bladder cancer based on WGCNA

IntroductionThe prognosis of bladder cancer (BLCA) and response to immune checkpoint inhibitors (ICIs) are determined by multiple factors. Existed biomarkers for predicting the effect of immunotherapy cannot accurately predict the response of BLCA patients to ICIs.MethodsTo further accurately stratify patients’ response to ICIs and identify potential novel predictive biomarkers, we used the known T cell exhaustion (TEX)-related specific pathways, including tumor necrosis factor (TNF), interleukin (IL)-2, interferon (IFN)-g, and T- cell cytotoxicpathways, combined with weighted correlation network analysis (WGCNA) to analyze the characteristics of TEX in BLCA in detail, constructed a TEX model.ResultsThis model including 28 genes can robustly predict the survival of BLCA and immunotherapeutic efficacy. This model could divide BLCA into two groups, TEXhigh and TEXlow, with significantly different prognoses, clinical features, and reactivity to ICIs. The critical characteristic genes, such as potential biomarkers Charged Multivesicular Body Protein 4C (CHMP4C), SH2 Domain Containing 2A (SH2D2A), Prickle Planar Cell Polarity Protein 3 (PRICKLE3) and Zinc Finger Protein 165 (ZNF165) were verified in BLCA clinical samples by real-time quantitative chain reaction (qPCR) and immunohistochemistry (IHC).DiscussionOur findings show that the TEX model can serve as biological markers for predicting the response to ICIs, and the involving molecules in the TEX model might provide new potential targets for immunotherapy in BLCA

Inducible miR-145 expression by HIF-1a protects cardiomyocytes against apoptosis via regulating SGK1 in simulated myocardial infarction hypoxic microenvironment

   Background: Myocardial infarction (MI) is partly due to myocardial cell damage caused by hypoxia. MicroRNAs (miRNAs) have been proved to be closely related to the development and progression of many cardiovascular diseases. This study investigated the role of miR-145 in cardiomyocytes under hypoxic condition. Methods: The quantitative real-time polymerase chain reaction (qRT-PCR) was performed to test miR-145 expression in H9c2 cells with hypoxia-inducible factor (HIF)-a abnormal expression under hypoxic condition. The 3-(4, 5-dimethyl-2-thiazolyl)-2, 5-diphenyltetrazolium bromide (MTT), Tran­swell assay and flow cytometry were used to investigate the effects of miR-145 on cell viability, migration and apoptosis under normoxic or hypoxic condition, respectively. Meanwhile, reactive oxygen species (ROS) content in hypoxic H9c2 cells was analyzed. Western blotting was used to explore the potential mechanism of miR-145 protective effects on cardiomyocytes. Expression levels of miR-145 and SGK1 in rat MI model were also assessed. Results: Results showed that miR-145 was upregulated in H9c2 and HL-1 cells under hypoxic condi­tion, which was promoted by HIF-1a. MiR-145 overexpression enhanced cell viability and migration under normoxic condition. Under hypoxic condition, miR-145 overexpression promoted cell viability, inhibited apoptosis and ROS activity. Western blotting results proved that miR-145 overexpression inhibited the activation of apoptotic related factors, and promoted activation of PI3K/AKT signaling pathway via SGK1 upregulation. Expression levels of miR-145 and SGK1 were both upregulated in rat MI models. Conclusions: HIF-1a could induce miR-145 upregulation in hypoxic H9c2 and HL-1 cells. MiR-145 protected H9c2 cells against hypoxic damage. SGK1 upregulation and activated PI3K/AKT may have participated in the protective effects of miR-145 on cardiomyocytes

Anger Weakens Behavioral Inhibition Selectively in Contact Athletes

Studies have increasingly found that the aggression level of contact athletes is higher than that of non-athletes. Given that higher aggression levels are associated with worse behavioral inhibition and that athletes show better behavioral inhibition than non-athletes, it is unclear why contact athletes would exhibit higher aggression levels. Emotion, especially anger, is an important factor in the generation of aggressive behavior, and anger has been shown to affect behavioral inhibition. Thus, the present study examined the influence of anger on behavioral inhibition in contact athletes. An implicit emotional Go/No-go task was used that contained 50 anger-associated words and 50 neutral words as stimuli. Participants were asked to execute a key press depending on the explicit color of word and to ignore any (implicit) emotional information associated with the word. The results showed a significant interaction in performance accuracy on the No-go task between emotion (i.e., anger-associated words versus neutral words) and group (athlete versus non-athlete). The performance accuracy of the contact athletes on anger-associated stimuli was significantly lower than that for neutral stimuli. Evoked delta and theta oscillations were analyzed at the time windows 200–600 and 200–400 ms respectively in both groups. A time-frequency analysis indicated a significant interaction between group, emotion and task for both evoked delta and theta oscillations. Post hoc analyses showed that stronger evoked delta and theta oscillations were evoked during the presentation of anger-associated stimuli compared with neutral stimuli on the No-go task in athletes. By contrast, no other significant effect was found in the control group or between the control and athlete groups. These results indicate that time-frequency analysis can effectively distinguish conventional ERP components and that implicit anger significantly weakens behavioral inhibition in contact athletes but not in non-athletes

Development and Validation of a 6-Gene Hypoxia-Related Prognostic Signature For Cholangiocarcinoma

Cholangiocarcinoma (CHOL) is highly malignant and has a poor prognosis. This study is committed to creating a new prognostic model based on hypoxia related genes. Here, we established a novel tumor hypoxia-related prognostic model consisting of 6 hypoxia-related genes by univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) algorithm to predict CHOL prognosis and then the risk score for each patient was calculated. The results showed that the patients with high-risk scores had poor prognosis compared with those with low-risk scores, which was verified as an independent predictor by multivariate analysis. The hypoxia-related prognostic model was validated in both TCGA and GEO cohorts and exhibited excellent performance in predicting overall survival in CHOL. The PPI results suggested that hypoxia-related genes involved in the model may play a central role in regulating the hypoxic state. In addition, the presence of IDH1 mutations in the high-risk group was high, and GSEA results showed that some metabolic pathways were upregulated, but immune response processes were generally downregulated. These factors may be potential reasons for the high-risk group with worse prognosis. The analysis of different immune regulation-related processes in the high- and low-risk groups revealed that the expression of genes related to immune checkpoints would show differences between these two groups. We further verified the expression of the oncogene PPFIA4 in the model, and found that compared with normal samples, CHOL patients were generally highly expressed, and the patients with high-expression of PPFIA4 had a poor prognosis. In summary, the present study may provide a valid prognostic model for bile duct cancer to inform better clinical management of patients

Lidar based map construction fusion method for underground coal mine shaft bottom

Intellectualization of coal mine is the technical support for high-quality development of coal industry, and robot replacement of key posts is the development trend of realizing efficient mining of coal with few people and no people. Simultaneous localization and mapping (SLAM) is one of the key technologies for autonomous movement and navigation of coal mine robots. The environment of underground coal mine is a typical unstructured environment, with narrow space, complex and changeable structure and uneven lighting, posing a severe challenge to the realization of SLAM in the underground coal mine. The research status of the map construction of the underground coal mine is summarized. In view of the shortcomings of the loopback detection of the LeGO-LOAM algorithm, the SegMatch algorithm is used to improve the loopback detection module of the LeGO-LOAM, the ICP algorithm is used to optimize the global map, and an improved algorithm integrating LeGO-LOAM and SegMatch is proposed, and the principle and implementation of the algorithm are discussed. The underground simulation scene experiments of coal mine were carried out, the mapping effect and accuracy of SLAM algorithm before and after the improvement were compared and analyzed, and the results showed that the map loopback effect constructed by the improved algorithm was better, and the estimated trajectory was smoother and more accurate. The construction method of two-dimensional occupied grid map is studied aiming at the navigation requirements, and the accuracy of the grid map constructed by this method is verified through experiments. The results show that the grid map after effectively filtering outliers such as dynamic obstacles has a mapping accuracy of 0.01 m, and the required storage space is 3 orders of magnitude lower than that of the point cloud map. The research results are helpful to the realization of SLAM and real-time positioning and autonomous navigation of the coal mine robot under the unstructured environment of the underground coal mine

Exploiting Code Diversity to Enhance Code Virtualization Protection

Code virtualization built upon virtual machine (VM)technologies is emerging as a viable method for implementing code obfuscation to protect programs against unauthorized analysis. State-of-the-art VM-based protection approaches use a fixed set of virtual instructions and bytecode interpreters across programs. This, however, exposes a security vulnerability where an experienced attacker can use knowledge extracted from other programs to quickly uncover the mapping between virtual instructions and native code for applications protected under the same scheme. In this paper, we propose a novel VM-based code obfuscation system to address this problem. The core idea of our approach is to obfuscate the mapping between the opcodes of bytecode instructions and their semantics. We achieve this by partitioning each protected code region into multiple segments where the mapping of opcodes and their semantics is randomized in different ways in different segments. In this way, each bytecode instruction will be translated into different native code in different sections of the obfuscated code. This significantly increases the diversity of the program behavior. As a result, the knowledge of bytecode to native code mappings obtained from other programs will be less useful when targeting a new program. We evaluate our approach on a set of real-world applications and compare it against two state-of-the-art VM-based code obfuscation approaches. Experimental results show that our approach is effective, which provides stronger protection with comparable runtime overhead and code size

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data