PTPRO-related CD8⁺ T-cell signatures predict prognosis and immunotherapy response in patients with breast cancer

Background: Poor immunogenicity and extensive immunosuppressive T-cell infiltration in the tumor immune microenvironment (TIME) have been identified as potential barriers to immunotherapy success in “immune-cold” breast cancers. Thus, it is crucial to identify biomarkers that can predict immunotherapy efficacy. Protein tyrosine phosphatase receptor type O (PTPRO) regulates multiple kinases and pathways and has been implied to play a regulatory role in immune cell infiltration in various cancers. Methods: ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) were performed to uncover the TIME landscape. The correlation analysis of PTPRO and immune infiltration was performed to characterize the immune features of PTPRO. Univariate and multivariate Cox analyses were applied to determine the prognostic value of various variables and construct the PTPRO-related CD8+ T-cell signatures (PTSs). The Kaplan–Meier curve and the receiver operating characteristic (ROC) curve were used to estimate the performance of PTS in assessing prognosis and immunotherapy response in multiple validation datasets. Results: High PTPRO expression was related to high infiltration levels of CD8+ T cells, as well as macrophages, activated dendritic cells (aDCs), tumor-infiltrating lymphocytes (TILs), and Th1 cells. Given the critical role of CD8+ T cells in the TIME, we focused on the impact of PTPRO expression on CD8+ T-cell infiltration. The prognostic PTS was then constructed using the TCGA training dataset. Further analysis showed that the PTS exhibited favorable prognostic performance in multiple validation datasets. Of note, the PTS could accurately predict the response to immune checkpoint inhibitors (ICIs). Conclusion: PTPRO significantly impacts CD8+ T-cell infiltration in breast cancer, suggesting a potential role of immunomodulation. PTPRO-based PTS provides a new immune cell paradigm for prognosis, which is valuable for immunotherapy decisions in cancer patients

A meta-analysis of cognitive and functional outcomes in severe brain trauma cases

BackgroundSevere traumatic brain injuries (TBIs) are an important health issue worldwide, which are associated with harmful side effects. This meta-analysis investigates the cognitive and functional outcomes in severe brain trauma cases. It assesses the impact on memory, verbal and visual abilities, attention, learning, and the presence of depression. The study provides a comprehensive overview of the consequences of severe brain trauma injury on cognitive and functional domains.ObjectiveThe main objective of the current comprehensive meta-analysis study is to assess and analyze the impact of severe TBI on functional and cognitive outcomes, including verbal, visual, attention, learning, memory, and emotional stability.MethodsWe collected data from three online databases, including PubMed, Cochrane Library, and Embase. Case–control trials related to severe TBI association with cognitive and functional outcomes were included. Verbal strength, visual functions, learning abilities, attention, memory, and depression were considered primary outcomes.ResultsWe have included 13 case–control studies with 1,442 subjects in this meta-analysis, which provide adequate data to determine the pooled effect size for targeted outcomes. The effect of severe TBI on the inducement of depression and impairment of memory, verbal, visual, attention, and learning abilities compared to the control group showed statistically significant outcomes (p < 0.05).ConclusionSevere TBI is strongly associated with impaired cognitive and functional abilities, including visual and verbal disabilities, impaired memory, depression inducement, attention deficits, and learning disabilities

Research Progress on Extraction and Detection Technologies of Flavonoid Compounds in Foods

Flavonoid compounds have a variety of biological activities and play an essential role in preventing the occurrence of metabolic diseases. However, many structurally similar flavonoids are present in foods and are usually in low concentrations, which increases the difficulty of their isolation and identification. Therefore, developing and optimizing effective extraction and detection methods for extracting flavonoids from food is essential. In this review, we review the structure, classification, and chemical properties of flavonoids. The research progress on the extraction and detection of flavonoids in foods in recent years is comprehensively summarized, as is the application of mathematical models in optimizing experimental conditions. The results provide a theoretical basis and technical support for detecting and analyzing high-purity flavonoids in foods

Application of FME Deterministic Model in the Calculation of a Reservoir Arch Dam

At present, the analysis of monitoring data for the stress of dam is mostly based on statistical models. However, the monitoring data of the stress on some arch dams have considerably large error, it is hard to build a reasonable statistic model based on the monitoring data. In order to solve the practical application problem of the project, this paper calculates the elastic modulus of the dam by using finite element analysis based on the displacement of the hydraulic component separated from the statistical model of horizontal displacement. Then according to the reversed elastic modulus, this paper has calculated the dam stress under different water levels and temperature conditions. Finally, it has built a stress-deterministic model of the dam

Étude de la préparation et des propriétés photoluminescentes de luminophores utilisés avec des LEDs ultraviolettes et / ou bleues

Parce que les diodes blanches peuvent être bénéfiques en terme de rendement lumineux, d économie d énergie, de durée de vie, de respect de l environnement, de petites volumes et de l absence de mercure, elles sont considérées comme la prochaine génération de système d éclairage. Différentes approches ont été explorées pour obtenir ces qualités le systèmes à base de LEDs. Aujourd hui, le design le plus commun pour les diodes blanches utilise une diode bleue ou proche UV pour exciter des luminophores qui émettent à longueurs d onde plus grandes où les performances de la LED sont faibles. Dans cette thèse, les oxyapatites dopés et leurs oxynitrures, le luminophore, ont été préparés par voie céramique hautes températures. Leur structure et leurs propriétés photoluminescentes ont été étudiées en détail...White light emitting diodes (WLEDS) have attracted many attention of researcher in recent years due to high luminous efficiency, energy savings, long persistence, environmental friendliness, small volume and lack of toxic mercury. Two basic approaches can be used to fabricate white LEDs. The conventional approach is the combination of near ultraviolet or blue light LED chips with photo convert phosphors. In this thesis, the phosphors have been summarized in detail. Because of some disadvantages of present phosphors, such as poor chemical stability, low efficiency or critical synthesis conditions, novel phosphors or preparation methods have to be developed...RENNES1-BU Sciences Philo (352382102) / SudocSudocFranceF

Odd-even effects in charge transport through self-assembled monolayer of alkanethiolates

10.1021/jp5116146Journal of Physical Chemistry C119105657-566

Equalized shape feature enhancement method for multiple ferromagnetic objects

When magnetic measuring instruments are used to measure the shape of ferromagnetic objects, the objects far away from the observation plane are likely to have blurred shape features because the magnetic field decays rapidly with distance. A bigger challenge is to measure multiple objects at the same time. When the relative positions of multiple measured objects and the observation plane are inappropriate, it is easy to have problems that the shape features of the deeper measured objects are not obvious and the magnetic signals of multiple measured objects are aliased, which usually leads to shape feature measurement failed. To address this issue, we propose an equalized shape feature enhancement method for multiple ferromagnetic objects. The method enhances shape features by evaluating the trends of the total horizontal derivative and vertical derivative of the magnetic field within the measurement area using the standard deviation. Meanwhile, the method combines the theory of ratio equalization and normalization to improve the shape features convergence of deeper objects and balance the signal aliasing interference between objects of different depths. Model simulation and experimental results show that the shape feature measurement results of the proposed method are clear and in good agreement with the ideal model. The method can effectively balance the magnetic anomaly amplitudes of the measured objects with different depths, and improve the accuracy and stability of shape feature measurement. We compare and analyze the processing effects of the proposed method and the traditional normalized standard deviation method (NSTD). It is calculated that the standard deviations of the results obtained by the proposed method and the NSTD method are 0.146 and 0.136, and the average peak-to-trough differences are 0.368 and 0.352, respectively. Therefore, the proposed method can better enhance the shape characteristics of ferromagnetic objects and has more practical application value