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Background: Non-small cell lung cancer (NSCLC), including the lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) subtypes, is a malignant tumor type with a poor 5-year survival rate. The identification of new powerful diagnostic biomarkers, prognostic biomarkers, and potential therapeutic targets in NSCLC is urgently required. Methods: The UCSC Xena, UALCAN, and GEO databases were used to screen and analyze differentially expressed genes, regulatory modes, and genetic/epigenetic alterations in NSCLC. The UCSC Xena database, GEO database, tissue microarray, and immunohistochemistry staining analyses were used to evaluate the diagnostic and prognostic values. Gain-of-function assays were performed to examine the roles. The ESTIMATE, TIMER, Linked Omics, STRING, and DAVID algorithms were used to analyze potential molecular mechanisms. Results: NR3C2 was identified as a potentially important molecule in NSCLC. NR3C2 is expressed at low levels in NSCLC, LUAD, and LUSC tissues, which is significantly related to the clinical indexes of these patients. Receiver operating characteristic curve analysis suggests that the altered NR3C2 expression patterns have diagnostic value in NSCLC, LUAD, and especially LUSC patients. Decreased NR3C2 expression levels can help predict poor prognosis in NSCLC and LUAD patients but not in LUSC patients. These results have been confirmed both with database analysis and real-world clinical samples on a tissue microarray. Copy number variation contributes to low NR3C2 expression levels in NSCLC and LUAD, while promoter DNA methylation is involved in its downregulation in LUSC. Two NR3C2 promoter methylation sites have high sensitivity and specificity for LUSC diagnosis with clinical application potential. NR3C2 may be a key participant in NSCLC development and progression and is closely associated with the tumor microenvironment and immune cell infiltration. NR3C2 co-expressed genes are involved in many cancer-related signaling pathways, further supporting a potentially significant role of NR3C2 in NSCLC. Conclusions: NR3C2 is a novel potential diagnostic and prognostic biomarker and therapeutic target in NSCLC.
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OBJECTIVE: A novel Proximal Femoral Bionic Nail (PFBN) has been developed by a research team for the treatment of femoral neck fractures. This study aims to compare the biomechanical properties of the innovative PFBN with those of the conventional Inverted Triangular Cannulated Screw (ITCS) fixation method through biomechanical testing. METHODS: Sixteen male femoral specimens preserved in formalin were selected, with the donors' age at death averaging 56.1 ± 6.3 years (range 47-64 years), and a mean age of 51.4 years. The femurs showed no visible damage and were examined by X-rays to exclude diseases affecting bone quality such as tumors, severe osteoporosis, and deformities. The 16 femoral specimens were randomly divided into an experimental group (n = 8) and a control group (n = 8). All femurs were prepared with Pauwels type III femoral neck fractures, fixed with PFBN in the experimental group and ITCS in the control group. Displacement and stress limits of each specimen were measured through cyclic compression tests and failure experiments, and vertical displacement and strain values under a 600 N vertical load were measured in all specimens through vertical compression tests. RESULTS: In the vertical compression test, the average displacement at the anterior head region of the femur was 0.362 mm for the PFBN group, significantly less than the 0.480 mm for the ITCS group (p < 0.001). At the fracture line area, the average displacement for the PFBN group was also lower than that of the ITCS group (0.196 mm vs. 0.324 mm, p < 0.001). The difference in displacement in the shaft area was smaller, but the average displacement for the PFBN group (0.049 mm) was still significantly less than that for the ITCS group (0.062 mm, p = 0.016). The situation was similar on the posterior side of the femur. The average displacements in the head area, fracture line area, and shaft area for the PFBN group were 0.300 mm, 0.168 mm, and 0.081 mm, respectively, while those for the ITCS group were 0.558 mm, 0.274 mm, and 0.041 mm, with significant differences in all areas (p < 0.001). The average strain in the anterior head area for the PFBN group was 4947 µm/m, significantly less than the 1540 µm/m for the ITCS group (p < 0.001). Likewise, in the fracture line and shaft areas, the average strains for the PFBN group were significantly less than those for the ITCS group (p < 0.05). In the posterior head area, the average strain for the PFBN group was 4861 µm/m, significantly less than the 1442 µm/m for the ITCS group (p < 0.001). The strain conditions in the fracture line and shaft areas also showed the PFBN group was superior to the ITCS group (p < 0.001). In cyclic loading experiments, the PFBN fixation showed smaller maximum displacement (1.269 mm vs. 1.808 mm, p < 0.001), indicating better stability. In the failure experiments, the maximum failure load that the PFBN-fixated fracture block could withstand was significantly higher than that for the ITCS fixation (1817 N vs. 1116 N, p < 0.001). CONCLUSION: The PFBN can meet the biomechanical requirements for internal fixation of femoral neck fractures. PFBN is superior in biomechanical stability compared to ITCS, particularly showing less displacement and higher failure resistance in cyclic load and failure experiments. While there are differences in strain performance in different regions between the two fixation methods, overall, PFBN provides superior stability.
Subject(s)
Bone Nails , Bone Screws , Femoral Neck Fractures , Fracture Fixation, Intramedullary , Humans , Femoral Neck Fractures/surgery , Femoral Neck Fractures/diagnostic imaging , Middle Aged , Male , Biomechanical Phenomena , Fracture Fixation, Intramedullary/methods , Fracture Fixation, Intramedullary/instrumentation , Bionics/methodsABSTRACT
BACKGROUND: Accurately identifying the risk level of drug combinations is of great significance in investigating the mechanisms of combination medication and adverse reactions. Most existing methods can only predict whether there is an interaction between two drugs, but cannot directly determine their accurate risk level. METHODS: In this study, we propose a multi-class drug combination risk prediction model named AERGCN-DDI, utilizing a relational graph convolutional network with a multi-head attention mechanism. Drug-drug interaction events with varying risk levels are modeled as a heterogeneous information graph. Attribute features of drug nodes and links are learned based on compound chemical structure information. Finally, the AERGCN-DDI model is proposed to predict drug combination risk level based on heterogenous graph neural network and multi-head attention modules. RESULTS: To evaluate the effectiveness of the proposed method, five-fold cross-validation and ablation study were conducted. Furthermore, we compared its predictive performance with baseline models and other state-of-the-art methods on two benchmark datasets. Empirical studies demonstrated the superior performances of AERGCN-DDI. CONCLUSIONS: AERGCN-DDI emerges as a valuable tool for predicting the risk levels of drug combinations, thereby aiding in clinical medication decision-making, mitigating severe drug side effects, and enhancing patient clinical prognosis.
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Neural Networks, Computer , Humans , Drug Interactions , Drug Combinations , Risk Assessment , Drug-Related Side Effects and Adverse Reactions , Reproducibility of Results , Computer GraphicsABSTRACT
To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.
Subject(s)
Deep Learning , Metabolomics , Wine , Wine/analysis , Metabolomics/methods , Neural Networks, Computer , Chromatography, High Pressure Liquid/methods , Mass Spectrometry/methodsABSTRACT
BACKGROUND: Drug-drug interaction events influence the effectiveness of drug combinations and can lead to unexpected side effects or exacerbate underlying diseases, jeopardizing patient prognosis. Most existing methods are restricted to predicting whether two drugs interact or the type of drug-drug interactions, while very few studies endeavor to predict the specific risk levels of side effects of drug combinations. METHODS: In this study, we propose MathEagle, a novel approach to predict accurate risk levels of drug combinations based on multi-head attention and heterogeneous attribute graph learning. Initially, we model drugs and three distinct risk levels between drugs as a heterogeneous information graph. Subsequently, behavioral and chemical structure features of drugs are utilized by message passing neural networks and graph embedding algorithms, respectively. Ultimately, MathEagle employs heterogeneous graph convolution and multi-head attention mechanisms to learn efficient latent representations of drug nodes and estimates the risk levels of pairwise drugs in an end-to-end manner. RESULTS: To assess the effectiveness and robustness of the model, five-fold cross-validation, ablation experiments, and case studies were conducted. MathEagle achieved an accuracy of 85.85 % and an AUC of 0.9701 on the drug risk level prediction task and is superior to all comparative models. The MathEagle predictor is freely accessible at http://120.77.11.78/MathEagle/. CONCLUSIONS: The experimental results indicate that MathEagle can function as an effective tool for predicting accurate risk of drug combinations, aiding in guiding clinical medication, and enhancing patient outcomes.
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Drug Interactions , Humans , Algorithms , Neural Networks, Computer , Drug-Related Side Effects and Adverse Reactions , Machine LearningABSTRACT
BACKGROUND: Total knee arthroplasty (TKA) is a mature procedure recommended for correcting knee osteoarthritis deformity, relieving pain, and restoring normal biomechanics. Although TKA is a successful and cost-effective procedure, patient dissatisfaction is as high as 50%. Knee pain after TKA is a significant cause of patient dissatisfaction; the most common location for residual pain is the anterior region. Between 4% and 40% of patients have anterior knee pain (AKP). AIM: To investigate the effect of various TKA procedures on postoperative AKP. METHODS: We searched PubMed, EMBASE, and Cochrane from January 2000 to September 2022. Randomized controlled trials with one intervention in the experimental group and no corresponding intervention (or other interventions) in the control group were collected. Two researchers independently read the title and abstract of the studies, preliminarily screened the articles, and read the full text in detail according to the selection criteria. Conflicts were resolved by consultation with a third researcher. And relevant data from the included studies were extracted and analyzed using Review Manager 5.4 software. RESULTS: There were 25 randomized controlled trials; 13 were comparative studies with or without patellar resurfacing. The meta-analysis showed no significant difference between the experimental and control groups (P = 0.61). Six studies were comparative studies of circumpatellar denervation vs non-denervation, divided into three subgroups for meta-analysis. The two-subgroup meta-analysis showed no significant difference between the experimental and the control groups (P = 0.31, P = 0.50). One subgroup meta-analysis showed a significant difference between the experimental and control groups (P = 0.001). Two studies compared fixed-bearing TKA and mobile-bearing TKA; the results meta-analysis showed no significant difference between the experimental and control groups (P = 0.630). Two studies compared lateral retinacular release vs non-release; the meta-analysis showed a significant difference between the experimental and control groups (P = 0.002); two other studies compared other factors. CONCLUSION: Patellar resurfacing, mobile-bearing TKA, and fixed-bearing TKA do not reduce the incidence of AKP. Lateral retinacular release can reduce AKP; however, whether circumpatellar denervation can reduce AKP is controversial.
Subject(s)
Genital Neoplasms, Male , Paget Disease, Extramammary , Scrotum , Humans , Male , Scrotum/surgery , Paget Disease, Extramammary/surgery , Paget Disease, Extramammary/pathology , Paget Disease, Extramammary/diagnosis , Genital Neoplasms, Male/surgery , Genital Neoplasms, Male/pathology , Genital Neoplasms, Male/diagnosis , Treatment Outcome , AgedABSTRACT
There are few effective treatments for small cell lung cancer (SCLC) underscoring the need for innovative therapeutic approaches. This study focuses on exploiting telomerase, a critical SCLC dependency as a therapeutic target. A prominent characteristic of SCLC is their reliance on telomerase activity, a key enzyme essential for their continuous proliferation. Here we utilize a nucleoside analog, 6-Thio-2'-deoxyguanosine (6TdG) currently in phase II clinical trials, that is preferentially incorporated by telomerase into telomeres leading to telomere dysfunction. Using preclinical mouse and human derived models we find low intermittent doses of 6TdG inhibit tumor growth and reduce metastatic burden. Anti-tumor efficacy correlates with a reduction in a subpopulation of cancer initiating like cells (CICs) identified by their expression of L1CAM/CD133 and highest telomerase activity. 6TdG treatment also leads to activation of innate and adaptive anti-tumor responses. Mechanistically, 6TdG depletes CICs and induces type-I interferon signaling leading to tumor immune visibility by activating tumor cell STING signaling. We also observe increased sensitivity to irradiation after 6TdG treatment in both syngeneic and humanized SCLC xenograft models both of which are dependent on the presence of host immune cells. This study underscores the immune-enhancing and metastasis-reducing effects of 6TdG, employing a range of complementary in vitro and in vivo SCLC preclinical models providing a potential therapeutic approach to SCLC.
Subject(s)
Deoxyguanosine/analogs & derivatives , Lung Neoplasms , Small Cell Lung Carcinoma , Telomerase , Thionucleosides , Humans , Animals , Mice , Small Cell Lung Carcinoma/drug therapy , Lung Neoplasms/drug therapy , Drug Delivery Systems , TelomereABSTRACT
BACKGROUND: The consolidation tumor ratio (CTR) is a predictor of invasiveness in peripheral T1N0M0 lung adenocarcinoma. However, its association with spread through air spaces (STAS) remains largely unexplored. We aimed to explore the correlation between the CTR of primary tumors and STAS in peripheral T1N0M0 lung adenocarcinoma. METHODS: We collected data from patients who underwent surgery for malignant lung neoplasms between January and November 2022. Univariate and multivariate analyses following propensity-score matching with sex, age, BMI, were performed to identify the independent risk factors for STAS. The incidence of STAS was compared based on pulmonary nodule type. A smooth fitting curve between CTR and STAS was produced by the generalized additive model (GAM) and a multiple regression model was established using CTR and STAS to determine the dose-response relationship and calculate the odds ratio (OR) and 95% confidence interval (CI). RESULTS: 17 (14.5%) were diagnosed with STAS. The univariate analysis demonstrated that the history of the diabetes, size of solid components, spiculation, pleural indentation, pulmonary nodule type, consolidation/tumor ratio of the primary tumor were statistically significant between the STAS-positive and STAS-negative groups following propensity-score matching(p = 0.047, 0.049, 0.030, 0.006, 0.026, and < 0.001, respectively), and multivariate analysis showed that the pleural indentation was independent risk factors for STAS (with p-value and 95% CI of 0.043, (8.543-68.222)). Moreover, the incidence of STAS in the partially solid nodule was significantly different from that in the solid nodule and ground-glass nodule (Pearson Chi-Square = 7.49, p = 0.024). Finally, the smooth fitting curve showed that CTR tended to be linearly associated with STAS by GAM, and the multivariate regression model based on CTR showed an OR value of 1.24 and a p-value of 0.015. CONCLUSIONS: In peripheral stage IA lung adenocarcinoma, the risk of STAS was increased with the solid component of the primary tumor. The pleural indentation of the primary tumor could be used as a predictor in evaluating the risk of the STAS.
Subject(s)
Adenocarcinoma of Lung , Lung Neoplasms , Humans , Propensity Score , Radiography , Multivariate AnalysisABSTRACT
BACKGROUND: Diabetes is a chronic disease that can lead to a variety of complications and even cause death. The signal characteristics of the photoplethysmography signals (PPG) and electrocardiogram signals (ECG) can reflect the autonomic and vascular aspects of the effects of diabetes on the body. OBJECTIVE: Based on the complex mechanism of interaction between PPG and ECG, a set of ensemble empirical mode decomposition-independent component analysis (EEMD-ICA) fusion multi-scale percussion entropy index (MSPEI) method was proposed to analyze cardiovascular function in diabetic patients. METHODS: Firstly, the original signal was decomposed into multiple Intrinsic Mode Function (IMFs) by ensemble empirical mode decomposition EEMD, principal components of IMF were extracted by independent component analysis (ICA), then the extracted principal components were reconstructed to eliminate the complex high and low frequency noise of physiological signals. In addition, the MSPEI was calculated for the ECG R-R interval and PPG amplitude sequence.(RRI and Amp) The results showed that, compared with EEMD method, the SNR of EEMD-ICA method increases from 2.1551 to 11.3642, and the root mean square error (RMSE) decreases from 0.0556 to 0.0067. This algorithm can improve the performance of denoising and retain more feature information. The large and small scale entropy of MSPEI (RRI,Amp) was significantly different between healthy and diabetic patients (p< 0.01). RESULTS: Compared with arteriosclerosis index (AI) and multi-scale cross-approximate entropy (MCAE): MSPEISS (RRI,Amp) indicated that diabetes can affect the activity of human autonomic nervous system, while MSPEILS (RRI,Amp) indicated that diabetes can cause or worsen arteriosclerosis. CONCLUSION: Multi-scale Percussion Entropy algorithm has more advantages in analyzing the influence of diabetes on human cardiovascular and autonomic nervous function.
Subject(s)
Arteriosclerosis , Diabetes Mellitus , Humans , Signal Processing, Computer-Assisted , Entropy , Percussion , AlgorithmsABSTRACT
The development of animal early embryos commences with the reprogramming of terminally differentiated gametes into totipotent zygotes following fertilization. During the initial stages of embryonic development, the transcriptional levels of zygotic genome remain silent and maternal gene products dominate the regulation of development. As embryonic development progresses, the maternal gene products undergo phased degradation while the zygotic genome gradually activates transcription, marking the transition from the maternal regulation to the zygotic genome regulation in early embryonic development, which is also referred to as the maternal-zygotic transition (MZT). Zygotic genome activation (ZGA) is a critical turning process in this transition, and its accurate occurrence is crucial for early embryonic development and cell fate decisions. However, the regulatory factors and molecular mechanisms of ZGA remain poorly understood. Studies have shown that ZGA varies greatly among different species and may be affected by a variety of regulatory factors such as DNA methylation, histone modification, non-coding RNA, chromatin remodeling and ZGA related factors. Here, we review the research progress of the above regulatory factors affecting ZGA, which can provide valuable insights for further investigations into the ZGA related mechanisms of early embryos.
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BACKGROUND: Immunosenescence occurs as people age, leading to an increased incidence of age-related diseases. The number of senescent T cells also rises with age. T cell senescence and immune response dysfunction can result in a decline in immune function, especially in anti-tumor immune responses. Metformin has been shown to have various beneficial effects on health, such as lowering blood sugar levels, reducing the risk of cancer development, and slowing down the aging process. However, the immunomodulatory effects of metformin on senescent T cells still need to be investigated. METHODS: PBMCs isolation from different age population (n = 88); Flow Cytometry is applied to determine the phenotypic characterization of senescent T lymphocytes; intracellular staining is applied to determine the function of senescent T cells; Enzyme-Linked Immunosorbent Assay (ELISA) is employed to test the telomerase concentration. The RNA-seq analysis of gene expression associated with T cell senescence. RESULTS: The middle-aged group had the highest proportion of senescent T cells. We found that metformin could decrease the number of CD8 + senescent T cells. Metformin affects the secretion of SASP, inhibiting the secretion of IFN-γ in CD8 + senescent T cells. Furthermore, metformin treatment restrained the production of the proinflammatory cytokine IL-6 in lymphocytes. Metformin had minimal effects on Granzyme B secretion in senescent T cells, but it promoted the production of TNF-α in senescent T cells. Additionally, metformin increased the concentration of telomerase and the frequency of undifferentiated T cells. The results of RNA-seq showed that metformin promoted the expression of genes related to stemness and telomerase activity, while inhibiting the expression of DNA damage-associated genes. CONCLUSION: Our findings reveal that metformin could inhibit T cell senescence in terms of cell number, effector function, telomerase content and gene expression in middle-aged individuals, which may serve as a promising approach for preventing age-related diseases in this population.
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The role of tumor mutational burden (TMB) in shaping tumor immunity is a key question that has not been addressable using genetically engineered mouse models (GEMMs) of lung cancer. To induce TMB in lung GEMMs, we expressed an ultra-mutator variant of DNA polymerase-E (POLE)P286R in lung epithelial cells. Introduction of PoleP286R allele into KrasG12D and KrasG12D; p53L/L (KP) models significantly increase their TMB. Immunogenicity and sensitivity to immune checkpoint blockade (ICB) induced by Pole is partially dependent on p53. Corroborating these observations, survival of NSCLC patients whose tumors have TP53truncating mutations is shorter than those with TP53WT with immunotherapy. Immune resistance is in part through reduced antigen presentation and in part due to mutational heterogeneity. Total STING protein levels are elevated in Pole mutated KP tumors creating a vulnerability. A stable polyvalent STING agonist or p53 induction increases sensitivity to immunotherapy offering therapeutic options in these polyclonal tumors.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Mice , Animals , Humans , Lung Neoplasms/drug therapy , Proto-Oncogene Proteins p21(ras)/genetics , Tumor Suppressor Protein p53/genetics , Carcinoma, Non-Small-Cell Lung/therapy , Carcinoma, Non-Small-Cell Lung/drug therapy , MutationABSTRACT
Azulene-based conjugated systems are of great interests due to their unusual structures and photophysical properties. Incorporation of a transition metal into azulene skeleton presents an intriguing opportunity to combine the dπ-pπ and pπ-pπ conjugated properties. No such metallaazulene skeleton however has been reported to date. Here, we describe our development of an efficient [5 + 2] annulation reaction to rapid construction of a unique metal-containing [5-5-7] scaffold, termed metalla-dual-azulene (MDA), which includes a metallaazulene and a metal-free organic azulene intertwined by sharing the tropylium motif. The two azulene motifs in MDA exhibit distinct reactivities. The azulene motif readily undergoes nucleophilic addition, leading to N-, O- and S-substituted cycloheptanetrienyl species. Demetalation of the metallaazulene moiety occurs when it reacts with nBu4NF, which enables highly selective recognition of fluoride anion and a noticeable color change. The practical [5 + 2] annulation methodology, facile functional-group modification, high and selective fluoride detection make this new π-conjugated polycyclic system very suitable for potential applications in photoelectric and sensing materials.
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In the past 4 decades, many articles have reported on the effects of the piezoelectric effect on bone formation and the research progress of piezoelectric biomaterials in orthopedics. The purpose of this study is to comprehensively evaluate all existing research and latest developments in the field of bone piezoelectricity, and to explore potential research directions in this area. To assess the overall trend in this field over the past 40 years, this study comprehensively collected literature reviews in this field using a literature retrieval program, applied bibliometric methods and visual analysis using CiteSpace and R language, and identified and investigated publications based on publication year (1984-2022), type of literature, language, country, institution, author, journal, keywords, and citation counts. The results show that the most productive countries in this field are China, the United States, and Italy. The journal with the most publications in the field of bone piezoelectricity is the International Journal of Oral & Maxillofacial Implants, followed by Implant Dentistry. The most productive authors are Lanceros-Méndez S, followed by Sohn D.S. Further research on the results obtained leads to the conclusion that the research direction of this field mainly includes piezoelectric surgery, piezoelectric bone tissue engineering scaffold, manufacturing artificial cochleae for hearing loss patients, among which the piezoelectric bone tissue engineering scaffold is the main research direction in this field. The piezoelectric materials involved in this direction mainly include polyhydroxybutyrate valerate, PVDF, and BaTiO3.
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OBJECTIVE: To explore the patterns and correlates of insight among patients with schizophrenia in a large Chinese population. METHOD: A multi-center cross-sectional study was conducted in Guangdong province, China. Patients with schizophrenia were included. Basic socio-demographic and clinical characteristics were collected in this study. Univariate analyses, multivariate logistic regression, and network analysis were conducted. RESULTS: A total of 6090 participants (58.8% were male, and 41.2% were female) met the study criteria and completed all the assessments. 63.5% (n = 3869) patients with schizophrenia had impaired insight. Fewer drug sides effect, higher psychological and environment domains scores in quality of life have a positive significant impact on insight in patients with schizophrenia. Younger age, higher BPRS scores have a negative significant impact on insight in patients with schizophrenia. The node ITAQ 8 (strength=1.17) was the most central node within the ITAQ network, while node ITAQ 3 was the least central node (strength=0.69). The edge ITAQ 1-ITAQ 2 was the thickest and most saturated edge in network model. CONCLUSIONS: Considering patterns and correlation of insight, it is necessary to ensure adherence to medications and engagement with mental health services for patients with schizophrenia, which could also improve their quality of life. Taking medication actively is more central to identify ITAQ and might be the potential targets for future interventions.
Subject(s)
Antipsychotic Agents , Schizophrenia , Humans , Male , Female , Schizophrenia/epidemiology , Schizophrenia/drug therapy , Cross-Sectional Studies , Quality of Life , China/epidemiology , Antipsychotic Agents/therapeutic useABSTRACT
PURPOSE: To explore the role of quantitative plaque analysis and fractional flow reserve (CT-FFR) derived from coronary computed angiography (CCTA) in evaluating plaque progression (PP). METHODS: A total of 248 consecutive patients who underwent serial CCTA examinations were enrolled. All patients' images were analyzed quantitatively by plaque analysis software. The quantitative analysis indexes included diameter stenosis (%DS), plaque length, plaque volume (PV), calcified PV, noncalcified PV, minimum lumen area (MLA), and remodeling index (RI). PP is defined as PAV (percentage atheroma volume) change rate >1%. CT-FFR analysis was performed using the cFFR software. RESULTS: A total of 76 patients (30.6%) and 172 patients (69.4%) were included in the PP group and non-PP group, respectively. Compared with the non-PP group, the PP group showed greater %DS, smaller MLA, larger PV and non-calcified PV, larger RI, and lower CT-FFR on baseline CCTA (all P <0.05). Logistic regression analysis showed that RI≥1.10 (odds ratio [OR]: 2.709, 95% CI: 1.447-5.072), and CT-FFR≤0.85 (OR: 5.079, 95% CI: 2.626-9.283) were independent predictors of PP. The model based on %DS, quantitative plaque features, and CT-FFR (area under the receiver-operating characteristics curve [AUC]=0.80, P <0.001) was significantly better than that based rarely on %DS (AUC=0.61, P =0.007) and that based on %DS and quantitative plaque characteristics (AUC=0.72, P <0.001). CONCLUSIONS: Quantitative plaque analysis and CT-FFR are helpful to identify PP. RI and CT-FFR are important predictors of PP. Compared with the prediction model only depending on %DS, plaque quantitative markers and CT-FFR can further improve the predictive performance of PP.
Subject(s)
Coronary Artery Disease , Coronary Stenosis , Fractional Flow Reserve, Myocardial , Plaque, Atherosclerotic , Humans , Computed Tomography Angiography/methods , Plaque, Atherosclerotic/diagnostic imaging , Coronary Stenosis/diagnostic imaging , Predictive Value of Tests , Severity of Illness Index , Tomography, X-Ray Computed , Coronary Angiography/methods , Coronary Artery Disease/diagnostic imagingABSTRACT
Objective: To observe the characteristics of the evolution of liver indexes in patients with relapsed/refractory multiple myeloma (RRMM) treated with CAR-T-cells based on BCMA. Methods: Retrospective analysis was performed of patients with RRMM who received an infusion of anti-BCMA CAR-T-cells and anti-BCMA combined with anti-CD19 CAR-T-cells at our center between June 1, 2019, and February 28, 2023. Clinical data were collected to observe the characteristics of changes in liver indexes such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and direct bilirubin (DBIL) in patients, and its relationship with cytokine-release syndrome (CRS) . Results: Ninety-two patients were included in the analysis, including 41 patients (44.6%) in the group receiving a single infusion of anti-BCMA CAR-T-cells, and 51 patients (55.4%) in the group receiving an infusion of anti-BCMA combined with anti-CD19 CAR-T-cells. After infusing CAR-T-cells, 31 patients (33.7%) experienced changes in liver indexes at or above grade 2, which included 20 patients (21.7%) with changes in one index, five patients (5.4%) with changes in two indexes, and six patients (6.5%) with changes in three or more indexes. The median time of peak values of ALT and AST were d17 and d14, respectively, and the median duration of exceeding grade 2 was 5.0 and 3.5 days, respectively. The median time of peak values of TBIL and DBIL was on d19 and d21, respectively, and the median duration of exceeding grade 2 was 4.0 days, respectively. The median time of onset of CRS was d8, and the peak time of fever was d9. The ALT, AST, and TBIL of patients with CRS were higher than those of patients without CRS (P=0.011, 0.002, and 0.015, respectively). CRS is an independent factor that affects ALT and TBIL levels (OR=19.668, 95% CI 18.959-20.173, P=0.001). The evolution of liver indexes can be reversed through anti-CRS and liver-protection treatments, and no patient died of liver injury. Conclusions: In BCMA-based CAR-T-cell therapy for RRMM, CRS is an important factor causing the evolution of liver indexes. The evolution of liver indexes after CAR-T-cell infusion is transient and reversible after treatment.
Subject(s)
Humans , Antigens, CD19 , B-Cell Maturation Antigen/therapeutic use , Bilirubin , Immunotherapy, Adoptive , Liver , Multiple Myeloma/drug therapy , Retrospective Studies , T-LymphocytesABSTRACT
OBJECTIVE@#To investigate the safety and efficacy of novel CD19-KIRS2/Dap12-BB chimeric antigen receptor T cells (CAR-T cells) in the treatment of relapsed/refractory B-cell malignancy (R/R BCM).@*METHODS@#Three patients with R/R BCM treated with novel CD19-KIRS2/Dap12-BB CAR-T cells from June 2020 to November 2020 were enrolled, including 1 case of B-cell acute lymphoblastic leukaemia (B-ALL) and 2 cases of non-Hodgkin's lymphoma (NHL), and the efficacy and adverse reactions were observed.@*RESULTS@#After CAR-T cells infusion, patient with B-ALL achieved complete remission (CR) and minimal residual disease (MRD) turned negative, and 2 patients with NHL achieved partial remission (PR). Grade 2 cytokine release syndrome (CRS) occurred in B-ALL patient, grade 1 CRS occurred in 2 NHL patients, and grade II to IV hematologic adverse reactions occurred in 3 patients, all of which were controllable and reversible. The progression-free survival (PFS) of the 3 patients was 143, 199, and 91 days, and overall survival (OS) was 282, 430, and 338 days, respectively.@*CONCLUSION@#The novel CD19-KIRS2/Dap12-BB CAR-T cells in treatment of 3 patients with R/R BCM have significant short-term efficacy and controllable adverse reactions, but the long-term efficacy needs to be further improved.
Subject(s)
Humans , Receptors, Chimeric Antigen , Immunotherapy, Adoptive , Burkitt Lymphoma , Antigens, CD19 , Neoplasm, Residual , Adaptor Proteins, Signal TransducingABSTRACT
Objective:To investigate the influence of DTAS gene mutations (DNMT3A, TET2, ASXL1, SRSF2) on survival of newly diagnosed acute myeloid leukemia (AML) patients.Methods:A retrospective analysis of 163 patients with next-generation sequencing(NGS)data in the hematology Department of Affiliated Hospital of Xuzhou Medical University from January 1, 2018 to October 31, 2021 was performed. Clinical data of patients were collected and analyzed including patient′s height, weight, gender, age, bone marrowblast ratio, induction chemotherapy regimen, transplantation or not, complete blood count, etc. There were 88 males and 75 females with a median age of 48 (4-81) years. According to the next-generation sequencing data, patients with any mutation of the above four genes were divided into the DTAS gene mutation group, and vice versa, they were divides into non-DTAS gene mutation group.The Kaplan-Meier method and Cox proportional risk model were used to analyze survival and prognosis.Results:Among 163 patients, DTAS gene mutation was detected in 50 patients (30.7%), and not in 113patients(69.3%). Among the 50 patients with DTAS genemutations, 8 cases(16%) had≥2 mutations and 42 cases(84%) had any gene mutation in DTAS. In the DTAS gene mutation group, the patients were older, the stratification of the European leukemia network(ELN) was poor, the duration of remission was shorter, the proportion of sever myelosuppression degree was higher (61.8% vs 34.8%) at day28 after induction chemotherapy, and the lymphocyte-monocyte ratio was lower than that of the healthy control group when CR was reached after treatment.The results of K-M survival analysis showed that the overall survival(OS)time ( P=0.003) and event-free survival(EFS) ( P=0.008) time of the DTAS gene mutant were significantly shorter than those of the non-DTAS gene mutated group.The medianOS timein theh DTAS gene mutations was significantly shorter than that in the non-DTAS gene mutated group ( P=0.003, HR=2.041) [21(95% CI 16.63-25.37) months vs 43 (95% CI 33.01-52.99) months].The results of multivariate COX analysis revealed that DTAS gene mutations was an independent risk facror forOS time(HR=2.041, 95% CI: 1.285-3.244, P=0.003) in AML patients. Conclusion:DTAS gene mutation does not affect the hematopoietic recovery time after induction chemotherapy, but the duration of remission is shorter in the DTAS gene mutations group. DTAS gene mutations indicate a poor prognosis, which is an independent risk factor for OS.