ANALGESIC EFFECT OF ROPIVACAINE AFTER ARTHROSCOPIC RECONSTRUCTION OF THE LIGAMENT IN ATHLETES

ABSTRACT After arthroscopic ligament reconstruction, athletes still need to go through a postoperative rehabilitation training period and suffer the possible pain that can go from moderate to severe. Commonly used analgesic medications, ropivacaine and fentanyl have the effect of relieving athletes’ pain. To study the analgesic effect of ropivacaine on arthroscopic reconstruction of the knee ligament, the steps of reconstruction and pharmacology of ropivacaine were first introduced. Next, the analgesic effects of ropivacaine and fentanyl in 86 athletes were compared on muscle strength recovery, patient satisfaction, and pain score. The results showed that the satisfaction of patients with ropivacaine was 95.35%, and the incidence of postoperative adverse reactions was only 9.30%. These results indicate that ropivacaine has a better analgesic effect in arthroscopic reconstruction of the knee ligament in athletes, which is suitable for postoperative rehabilitation.</div

Efficient and Deterministic Propagation of Mixed Quantum-Classical Liouville Dynamics

We propose a highly efficient mixed quantum-classical molecular dynamics scheme based on a solution of the quantum-classical Liouville equation (QCLE). By casting the equations of motion for the quantum subsystem and classical bath degrees of freedom onto an approximate set of coupled first-order differential equations for <i>c</i>-numbers, this scheme propagates the composite system in time deterministically in terms of independent classical-like trajectories. To demonstrate its performance, we apply the method to the spin-boson model, a photoinduced electron transfer model, and a Fenna–Matthews–Olsen complex model, and find excellent agreement out to long times with the numerically exact results, using several orders of magnitude fewer trajectories than surface-hopping solutions of the QCLE. Owing to its accuracy and efficiency, this method promises to be very useful for studying the dynamics of mixed quantum-classical systems

Quantum Nondemolition Photon Counting With a Hybrid Electromechanical Probe

Quantum nondemolition (QND) measurements of photons is a much pursued endeavor in the field of quantum optics and quantum information processing. Here we propose a novel hybrid optoelectromechanical platform that integrates a cavity system with a hybrid electromechanical probe for QND photon counting. Building upon a mechanical-mode-mediated nonperturbative electro-optical dispersive coupling, our protocol performs the QND photon counting measurement by means of the current-voltage characteristics of the probe. In particular, we show that the peak voltage shift of the differential conductance is linearly dependent on the photon occupation number, thus providing a sensitive measure of the photon number, especially in the strong optomechanical coupling regime. Given that our proposed hybrid system is compatible with state-of-the-art experimental techniques, we discuss its implementations and anticipate applications in quantum optics and polariton physics

DataSheet_3_CTNNB1 Alternation Is a Potential Biomarker for Immunotherapy Prognosis in Patients With Hepatocellular Carcinoma.pdf

BackgroundThe emergence of immune checkpoint inhibitors (ICIs) marks the beginning of a new era of immunotherapy for hepatocellular carcinoma (HCC), however, not all patients respond successfully to this treatment. A major challenge for HCC immunotherapy is the development of ways to screen for those patients that would benefit from this type of treatment and determine the optimal treatment plan for individual patients. Therefore, it is important to find a biomarker which allows for the stratification of HCC patients, which distinguishes responders from non-responders, thereby further improving the clinical benefits for those undergoing immunotherapy.MethodsWe used univariate and multivariate Cox risk proportional regression models to evaluate the relationship between non-synonymous mutations with a mutation frequency greater than 10%. We made a prognosis of an immunotherapy HCC cohort using mutation and prognosis data. An additional three HCC queues from the cbioportal webtool were used for further verification. The CIBERSORT, IPS, quanTIseq, and MCPcounter algorithms were used to evaluate the immune cells. PCA and z-score algorithm were used to calculate immune-related signature with published gene sets. Gene set enrichment analysis (GSEA) was used to compare the differences in the pathway-based enrichment scores of candidate genes between mutant and wild types.ResultsUnivariate and multivariate Cox results showed that only CTNNB1-Mutant(CTNNB1-MUT) was associated with progression-free survival (PFS) of HCC patients in the immunotherapy cohort. After excluding the potential bias introduced by other clinical features, it was found that CTNNB1-MUT served as an independent predictor of the prognosis of HCC patients after immunotherapy (P 1). The results of the tumor immune microenvironment (TIME) analysis showed that patients with CTNNB1-MUT had significantly reduced activated immune cells [such as T cells, B cells, M1-type macrophages, and dendritic cells (DCs)], significantly increased M2-type macrophages, a significantly decreased expression of immunostimulating molecules, low activity of the immune activation pathways (cytokine pathway, immune cell activation and recruitment) and highly active immune depletion pathways (fatty acid metabolism, cholesterol metabolism, and Wnt pathway).ConclusionsIn this study, we found CTNNB1-MUT to be a potential biomarker for HCC immunotherapy patients, because it identified those patients are less likely to benefit from ICIs.</p

Can carbon dioxide be a good indicator for formaldehyde in residences?—Monte Carlo modeling for a whole year

Indoor air quality (IAQ) plays a significant role in human health, and CO2 has a long history of use as an IAQ indicator. Formaldehyde is one of the most ubiquitous indoor pollutants with proven adverse health effects. However, formaldehyde sensors are generally expensive, and they are not as accurate as CO2 sensors. Thus, it is important to determine whether CO2 could be used as an indicator for formaldehyde in engineering applications. In this study, indoor CO2 and formaldehyde concentrations in actual Chinese residences under natural and mechanical ventilation were simulated by the Monte Carlo method. The Pearson correlation analyses were also performed. It was found that when emission rate of CO2 is constant, CO2 can act as a good indicator for formaldehyde when the formaldehyde emission rate (mg/h) divided by the emission rate of CO2 (L/h) is smaller than 0.14 and positive correlation occurred between them. However, when the emission rate of CO2 is varied, CO2 may not be used as an indicator for formaldehyde despite their positive correlation.</p

DataSheet_4_CTNNB1 Alternation Is a Potential Biomarker for Immunotherapy Prognosis in Patients With Hepatocellular Carcinoma.pdf

BackgroundThe emergence of immune checkpoint inhibitors (ICIs) marks the beginning of a new era of immunotherapy for hepatocellular carcinoma (HCC), however, not all patients respond successfully to this treatment. A major challenge for HCC immunotherapy is the development of ways to screen for those patients that would benefit from this type of treatment and determine the optimal treatment plan for individual patients. Therefore, it is important to find a biomarker which allows for the stratification of HCC patients, which distinguishes responders from non-responders, thereby further improving the clinical benefits for those undergoing immunotherapy.MethodsWe used univariate and multivariate Cox risk proportional regression models to evaluate the relationship between non-synonymous mutations with a mutation frequency greater than 10%. We made a prognosis of an immunotherapy HCC cohort using mutation and prognosis data. An additional three HCC queues from the cbioportal webtool were used for further verification. The CIBERSORT, IPS, quanTIseq, and MCPcounter algorithms were used to evaluate the immune cells. PCA and z-score algorithm were used to calculate immune-related signature with published gene sets. Gene set enrichment analysis (GSEA) was used to compare the differences in the pathway-based enrichment scores of candidate genes between mutant and wild types.ResultsUnivariate and multivariate Cox results showed that only CTNNB1-Mutant(CTNNB1-MUT) was associated with progression-free survival (PFS) of HCC patients in the immunotherapy cohort. After excluding the potential bias introduced by other clinical features, it was found that CTNNB1-MUT served as an independent predictor of the prognosis of HCC patients after immunotherapy (P 1). The results of the tumor immune microenvironment (TIME) analysis showed that patients with CTNNB1-MUT had significantly reduced activated immune cells [such as T cells, B cells, M1-type macrophages, and dendritic cells (DCs)], significantly increased M2-type macrophages, a significantly decreased expression of immunostimulating molecules, low activity of the immune activation pathways (cytokine pathway, immune cell activation and recruitment) and highly active immune depletion pathways (fatty acid metabolism, cholesterol metabolism, and Wnt pathway).ConclusionsIn this study, we found CTNNB1-MUT to be a potential biomarker for HCC immunotherapy patients, because it identified those patients are less likely to benefit from ICIs.</p

Image_1_CTNNB1 Alternation Is a Potential Biomarker for Immunotherapy Prognosis in Patients With Hepatocellular Carcinoma.pdf

BackgroundThe emergence of immune checkpoint inhibitors (ICIs) marks the beginning of a new era of immunotherapy for hepatocellular carcinoma (HCC), however, not all patients respond successfully to this treatment. A major challenge for HCC immunotherapy is the development of ways to screen for those patients that would benefit from this type of treatment and determine the optimal treatment plan for individual patients. Therefore, it is important to find a biomarker which allows for the stratification of HCC patients, which distinguishes responders from non-responders, thereby further improving the clinical benefits for those undergoing immunotherapy.MethodsWe used univariate and multivariate Cox risk proportional regression models to evaluate the relationship between non-synonymous mutations with a mutation frequency greater than 10%. We made a prognosis of an immunotherapy HCC cohort using mutation and prognosis data. An additional three HCC queues from the cbioportal webtool were used for further verification. The CIBERSORT, IPS, quanTIseq, and MCPcounter algorithms were used to evaluate the immune cells. PCA and z-score algorithm were used to calculate immune-related signature with published gene sets. Gene set enrichment analysis (GSEA) was used to compare the differences in the pathway-based enrichment scores of candidate genes between mutant and wild types.ResultsUnivariate and multivariate Cox results showed that only CTNNB1-Mutant(CTNNB1-MUT) was associated with progression-free survival (PFS) of HCC patients in the immunotherapy cohort. After excluding the potential bias introduced by other clinical features, it was found that CTNNB1-MUT served as an independent predictor of the prognosis of HCC patients after immunotherapy (P 1). The results of the tumor immune microenvironment (TIME) analysis showed that patients with CTNNB1-MUT had significantly reduced activated immune cells [such as T cells, B cells, M1-type macrophages, and dendritic cells (DCs)], significantly increased M2-type macrophages, a significantly decreased expression of immunostimulating molecules, low activity of the immune activation pathways (cytokine pathway, immune cell activation and recruitment) and highly active immune depletion pathways (fatty acid metabolism, cholesterol metabolism, and Wnt pathway).ConclusionsIn this study, we found CTNNB1-MUT to be a potential biomarker for HCC immunotherapy patients, because it identified those patients are less likely to benefit from ICIs.</p

DataSheet1_Regulation of Long Non-coding RNA KCNQ1OT1 Network in Colorectal Cancer Immunity.XLSX

Over the past few decades, researchers have become aware of the importance of non-coding RNA, which makes up the vast majority of the transcriptome. Long non-coding RNAs (lncRNAs) in turn constitute the largest fraction of non-coding transcripts. Increasing evidence has been found for the crucial roles of lncRNAs in both tissue homeostasis and development, and for their functional contributions to and regulation of the development and progression of various human diseases such as cancers. However, so far, only few findings with regards to functional lncRNAs in cancers have been translated into clinical applications. Based on multiple factors such as binding affinity of miRNAs to their lncRNA sponges, we analyzed the competitive endogenous RNA (ceRNA) network for the colorectal cancer RNA-seq datasets from The Cancer Genome Atlas (TCGA). After performing the ceRNA network construction and survival analysis, the lncRNA KCNQ1OT1 was found to be significantly upregulated in colorectal cancer tissues and associated with the survival of patients. A KCNQ1OT1-related lncRNA-miRNA-mRNA ceRNA network was constructed. A gene set variation analysis (GSVA) indicated that the expression of the KCNQ1OT1 ceRNA network in colorectal cancer tissues and normal tissues were significantly different, not only in the TCGA-COAD dataset but also in three other GEO datasets used as validation. By predicting comprehensive immune cell subsets from gene expression data, in samples grouped by differential expression levels of the KCNQ1OT1 ceRNA network in a cohort of patients, we found that CD4+, CD8+, and cytotoxic T cells and 14 other immune cell subsets were at different levels in the high- and low-KCNQ1OT1 ceRNA network score groups. These results indicated that the KCNQ1OT1 ceRNA network could be involved in the regulation of the tumor microenvironment, which would provide the rationale to further exploit KCNQ1OT1 as a possible functional contributor to and therapeutic target for colorectal cancer.</p

Image5_Regulation of Long Non-coding RNA KCNQ1OT1 Network in Colorectal Cancer Immunity.TIF

Over the past few decades, researchers have become aware of the importance of non-coding RNA, which makes up the vast majority of the transcriptome. Long non-coding RNAs (lncRNAs) in turn constitute the largest fraction of non-coding transcripts. Increasing evidence has been found for the crucial roles of lncRNAs in both tissue homeostasis and development, and for their functional contributions to and regulation of the development and progression of various human diseases such as cancers. However, so far, only few findings with regards to functional lncRNAs in cancers have been translated into clinical applications. Based on multiple factors such as binding affinity of miRNAs to their lncRNA sponges, we analyzed the competitive endogenous RNA (ceRNA) network for the colorectal cancer RNA-seq datasets from The Cancer Genome Atlas (TCGA). After performing the ceRNA network construction and survival analysis, the lncRNA KCNQ1OT1 was found to be significantly upregulated in colorectal cancer tissues and associated with the survival of patients. A KCNQ1OT1-related lncRNA-miRNA-mRNA ceRNA network was constructed. A gene set variation analysis (GSVA) indicated that the expression of the KCNQ1OT1 ceRNA network in colorectal cancer tissues and normal tissues were significantly different, not only in the TCGA-COAD dataset but also in three other GEO datasets used as validation. By predicting comprehensive immune cell subsets from gene expression data, in samples grouped by differential expression levels of the KCNQ1OT1 ceRNA network in a cohort of patients, we found that CD4+, CD8+, and cytotoxic T cells and 14 other immune cell subsets were at different levels in the high- and low-KCNQ1OT1 ceRNA network score groups. These results indicated that the KCNQ1OT1 ceRNA network could be involved in the regulation of the tumor microenvironment, which would provide the rationale to further exploit KCNQ1OT1 as a possible functional contributor to and therapeutic target for colorectal cancer.</p