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Background: Immune checkpoint inhibitor (ICI) plus chemotherapy is effective in advanced gastric or gastroesophageal junction (G/GEJ) cancer. This study aims to evaluate the clinical effect of first-line immunotherapy in combination with chemotherapy for advanced G/GEJ cancer. Methods: PubMed, Web of Science, Embase and Cochrane databases were systematically searched from the inception of the databases to December 2021. Randomized trials comparing ICI plus chemotherapy with chemotherapy in first-line treatment for advanced G/GEJ cancer were included. The outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and adverse events (AEs). Analyses were performed in Stata 14.0 software. The study protocol was registered with PROSPERO, number CRD42022300907. Results: Five trials were included for analysis, involving 2, 814 patients. ICI plus chemotherapy can significantly improve OS (hazards ratio [HR], 0.86; 95% CI 0.78-0.94; P = .002), PFS (HR, 0.79; 95% CI 0.63-0.99; P ï¼ .001) and ORR (relative ratio [RR], 1.20; 95% CI 1.11-1.30; P < .001). In safety analyses, there were no significant differences in incidence of all AEs, treatment-related adverse event (TRAE), TRAE of grade 3 or higher, serious TRAE and TRAE leading to death between two arms (P > .05). Conclusions: ICI plus chemotherapy is more effective first-line treatment for advanced G/GEJ cancer in contrast to chemotherapy regrading to improving OS, PFS and ORR, without increasing TRAE risk. This study will redefine the role of ICI in combination with chemotherapy in the first-line setting for G/GEJ cancer, and provide reference for clinical treatment.
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Protocolos de Quimioterapia Combinada Antineoplásica , Neoplasias Esofágicas , Junção Esofagogástrica , Inibidores de Checkpoint Imunológico , Neoplasias Gástricas , Humanos , Inibidores de Checkpoint Imunológico/uso terapêutico , Inibidores de Checkpoint Imunológico/efeitos adversos , Neoplasias Gástricas/tratamento farmacológico , Neoplasias Gástricas/mortalidade , Junção Esofagogástrica/patologia , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Protocolos de Quimioterapia Combinada Antineoplásica/efeitos adversos , Neoplasias Esofágicas/tratamento farmacológico , Neoplasias Esofágicas/mortalidade , Resultado do Tratamento , Estadiamento de NeoplasiasRESUMO
BACKGROUND: TMPRSS2, a key molecule for SARS-CoV-2 invading human host cells, has an association with cancer. However, its association with lung cancer remains insufficiently unexplored. METHODS: In five bulk transcriptomics datasets, one single-cell RNA sequencing (scRNA-seq) dataset and one proteomics dataset for lung adenocarcinoma (LUAD), we explored associations between TMPRSS2 expression and immune signatures, tumor progression phenotypes, genomic features, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we performed experimental validation of the bioinformatics findings. RESULTS: TMPRSS2 expression levels correlated negatively with the enrichment levels of both immune-stimulatory and immune-inhibitory signatures, while they correlated positively with the ratios of immune-stimulatory/immune-inhibitory signatures. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor progression, and worse survival in LUAD. We further validated that TMPRSS2 was downregulated with tumor progression in the LUAD cohort we collected from Jiangsu Cancer Hospital, China. In vitro and in vivo experiments verified the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1. CONCLUSIONS: TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a potential link between lung cancer and pneumonia caused by SARS-CoV-2 infection.
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Adenocarcinoma de Pulmão , Regulação para Baixo , Neoplasias Pulmonares , Serina Endopeptidases , Humanos , Adenocarcinoma de Pulmão/imunologia , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/patologia , Adenocarcinoma de Pulmão/metabolismo , Neoplasias Pulmonares/imunologia , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/metabolismo , Serina Endopeptidases/genética , Serina Endopeptidases/metabolismo , Animais , Camundongos , COVID-19/imunologia , Imunoterapia/métodos , Regulação Neoplásica da Expressão Gênica , Masculino , Genes Supressores de Tumor , Feminino , Camundongos Nus , Linhagem Celular Tumoral , SARS-CoV-2RESUMO
One of the primary challenges for autonomous vehicle (AV) is planning a collision-free path in dynamic environment. It is a tricky task for achieving high-performance obstacle avoidance with velocity-varying obstacle. To solve this problem, a highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle (HSPI-OAM) is presented in this work. The proposed method uses the virtual collision point model to accurately design the desired acceleration, which makes the obtained path highly smooth. At the same time, the method gets rid of the dependence on parameter adjustment and has strong adaptability to different environments. The simulation is implemented on the Matlab-Carsim co-simulation platform, and the simulation results show that the path planned by HSPI-OAM has good performance for obstacle with acceleration.
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Acidentes de Trânsito , Acidentes de Trânsito/prevenção & controle , Simulação por Computador , Condução de Veículo , Algoritmos , Aceleração , Humanos , Modelos Teóricos , AutomóveisRESUMO
Many computational methods have been proposed to identify potential drug-target interactions (DTIs) to expedite drug development. Graph neural network (GNN) methods are considered to be one of the most effective approaches. However, shallow GNN methods can only aggregate local information from nodes. Also, deep GNN methods may result in over-smoothing while obtaining long-distance neighbourhood information. As a result, existing GNN methods struggle to extract the complete features of the graph. Additionally, the number of known DTIs is insufficient, and there are far more unknown drug-target pairs than known DTIs, leading to class imbalance. This article proposes a model that combines graph autoencoder and self-supervised learning to accurately encode multilevel features of graphs using only a small number of labelled samples. We introduce a positive sample compensation coefficient to the objective function to mitigate the impact of class imbalance. Experiments on two datasets demonstrated that our model outperforms the four baseline methods, and the new DTIs predicted by the SSLDTI model were verified by the DrugBank database.
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Desenvolvimento de Medicamentos , Redes Neurais de Computação , Bases de Dados Factuais , Aprendizado de Máquina SupervisionadoRESUMO
Human pluripotent stem cell (hPSC)-derived neurons have shown promise in treating spinal cord injury (SCI). We previously showed that hPSC-derived dorsal spinal γ-aminobutyric acid (GABA) neurons can alleviate spasticity and promote locomotion in rats with SCI, but their long-term safety remains elusive. Here, we characterized the long-term fate and safety of human dorsal spinal GABA neural progenitor cells (NPCs) in naive rats over one year. All grafted NPCs had undergone differentiation, yielding mainly neurons and astrocytes. Fully mature human neurons grew many axons and formed numerous synapses with rat neural circuits, together with mature human astrocytes that structurally integrated into the rat spinal cord. The sensorimotor function of rats was not impaired by intraspinal transplantation, even when human neurons were activated or inhibited by designer receptors exclusively activated by designer drugs (DREADDs). These findings represent a significant step toward the clinical translation of human spinal neuron transplantation for treating SCI.
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When the autonomous vehicle (AV) is under various road friction and speed, emergency collision avoidance is extremely difficult. In this situation, the AV may encounter severe understeering problem, so it is hard to achieve collision avoidance, even under the control of active safety system. To tackle this problem, an adaptive collision avoidance strategy (ACAS) is proposed for AV under various road friction and speed. The adaptive performance of the ACAS is realized via three aspects. (1) An adaptive reference path planning method is proposed to provide desired evasive speed and reference path for the AV according to various road friction and reduces the turning burden of AV. (2) A predictive-based fuzzy controller is designed to realize the speed control, and it improves the tracking accuracy of various desired evasive speed. (3) A novel turning enhanced method built with a direct yaw turning controller and a torque distribution method can enhance the turning capability of AV. Finally, the proposed strategy is verified on AV via simulation experiments. The code can be found online here: https://github.com/wangjinlei-hnu/ACAS.
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We propose PreCanCell, a novel algorithm for predicting malignant and non-malignant cells from single-cell transcriptomes. PreCanCell first identifies the differentially expressed genes (DEGs) between malignant and non-malignant cells commonly in five common cancer types-associated single-cell transcriptome datasets. The five common cancer types include renal cell carcinoma (RCC), head and neck squamous cell carcinoma (HNSCC), melanoma, lung adenocarcinoma (LUAD), and breast cancer (BC). With each of the five datasets as the training set and the DEGs as the features, a single cell is classified as malignant or non-malignant by k-NN (k = 5). Finally, the single cell is determined as malignant or non-malignant by the majority vote of the five k-NN classification results. We tested the predictive performance of PreCanCell in 19 single-cell datasets, and reported classification accuracy, sensitivity, specificity, balanced accuracy (the average of sensitivity and specificity) and the area under the receiver operating characteristic curve (AUROC). In all these datasets, PreCanCell achieved above 0.8 accuracy, sensitivity, specificity, balanced accuracy and AUROC. Finally, we compared the predictive performance of PreCanCell with that of seven other algorithms, including CHETAH, SciBet, SCINA, scmap-cell, scmap-cluster, SingleR, and ikarus. Compared to these algorithms, PreCanCell displays the advantages of higher accuracy and simpler implementation. We have developed an R package for the PreCanCell algorithm, which is available at https://github.com/WangX-Lab/PreCanCell.
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OBJECTIVE: To evaluate the efficacy of NAHAO® oral mucosal antibacterial care solution (NAHAO® spray) on attenuating oral mucositis (OM) symptoms and related mechanisms investigation. MATERIAL AND METHODS: Experimental OM models were established by acetic acid and 5-fluorouracil combined with mechanical trauma. We investigated spontaneous pain of conscious OM rats after using NAHAO®. The expression of NF-κB in affected trigeminal ganglion was measured by western blot. In clinical study, 60 patients who developed post-treatment OM of grade 2 or above or persistent mucosal pain with a score equal to or greater than 4 points were selected. All patients were required to receive NAHAO® spray 8 times a day and were examined for OM degrees and oral mucosal pain scores before and after application. RESULTS: Experimental data from experimental model suggested that clinical efficacy of NAHAO® spray was involved in inflammation inhibition via NF-κB pathway. The results of clinical study showed that NAHAO® spray improved the symptoms of OM, there is statistically significant difference in oral mucosal pain scores after treated with NAHAO, and the dietary restrictions were also improved. CONCLUSION: NAHAO® spray alleviates pain and improves the diet situation in OM patients, which is partly mediated through the inhibition of NF-κB pathway.
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Hidrogéis , Estomatite , Humanos , Ratos , Animais , Hidrogéis/efeitos adversos , NF-kappa B/uso terapêutico , Estomatite/tratamento farmacológico , Estomatite/induzido quimicamente , Dor/tratamento farmacológico , Quimiorradioterapia/métodosRESUMO
A number of vaccines have been developed and deployed globally to restrain the spreading of the coronavirus disease 2019 (COVID-19). The adverse effect following vaccination is an important consideration. Acute myocardial infarction (AMI) is a kind of rare adverse event after COVID-19 vaccination. Herein, we present a case of an 83-year-old male who suffered cold sweat ten minutes after the first inactivated COVID-19 vaccination and AMI one day later. The emergency coronary angiography showed coronary thrombosis and underlying stenosis in his coronary artery. Type II Kounis syndrome might be a potential mechanism, which is manifested as coronary thrombosis secondary to allergic reactions in patients with underlying asymptomatic coronary heart disease. We also summarize the reported AMI cases post COVID-19 vaccination, as well as overview and discuss the proposed mechanisms of AMI after COVID-19 vaccination, thus providing insights for clinicians to be aware of the possibility of AMI following COVID-19 vaccination and potential underlying mechanisms.
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Poly(ADP-ribose) polymerase inhibitors (PARPis) induce DNA lesions that preferentially kill homologous recombination (HR)-deficient breast cancers induced by BRCA mutations, which exhibit a low incidence in breast cancer, thereby limiting the benefits of PARPis. Additionally, breast cancer cells, particularly triple-negative breast cancer (TNBC) cells, exhibit HR and PARPi resistance. Therefore, targets must be identified for inducing HR deficiency and sensitizing cancer cells to PARPis. Here, we reveal that CXorf56 protein increased HR repair in TNBC cells by interacting with the Ku70 DNA-binding domain, reducing Ku70 recruitment and promoting RPA32, BRCA2, and RAD51 recruitment to sites of DNA damage. Knockdown of CXorf56 protein suppressed HR in TNBC cells, specifically during the S and G2 phases, and increased cell sensitivity to olaparib in vitro and in vivo. Clinically, CXorf56 protein was upregulated in TNBC tissues and associated with aggressive clinicopathological characteristics and poor survival. All these findings indicate that treatment designed to inhibit CXorf56 protein in TNBC combined with PARPis may overcome drug resistance and expand the application of PARPis to patients with non-BRCA mutantion.
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Oiltea-camellia (C. oleifera) is a widely cultivated woody oil crop in Southern China and Southeast Asia. The genome of oiltea-camellia was very complex and not well explored. Recently, genomes of three oiltea-camellia species were sequenced and assembled, multi-omic studies of oiltea-camellia were carried out and provided a better understanding of this important woody oil crop. In this review, we summarized the recent assembly of the reference genomes of oiltea-camellia, genes related to economic traits (flowering, photosynthesis, yield and oil component), disease resistance (anthracnose) and environmental stress tolerances (drought, cold, heat and nutrient deficiency). We also discussed future directions of integrating multiple omics for evaluating genetic resources and mining key genes of important traits, and the application of new molecular breeding and gene editing technologies to accelerate the breeding process of oiltea-camellia.
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The selection of different examination sequences of painless gastroscopy in patients with difficult airway risk was explored in this study. A total of 45 patients undergoing painless gastroscopy with Mallampati airway score of III-IV were randomly assigned into two groups (A group and B group) according to the sequence of colonoscopy and gastroscopy. Group A was first examined by gastroscopy after anesthesia, and then by colonoscopy. Group B was examined in the opposite order, first by colonoscopy, and then by gastroscopy. Ramsay Sedation scores were evaluated every five minutes when gastroscopy was performed in the two groups. The dosage of propofol, blood pressure, heart rate, blood oxygen saturation, recovery time, hospital leaving time, and adverse reactions after induction and endoscopy were recorded. The dosage of propofol and change of vital signs in B group was less than that in A group. Operation time, recovery time, hospital leaving time and postoperative adverse reactions have no significant difference between two groups. For patients at risk of difficult airway, colonoscopy followed by gastroscopy has more stable intraoperative vital signs and less propofol consumption.
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Spinal cord injury (SCI) leads to permanent neural dysfunction without effective therapies. We previously showed that human pluripotent stem cell (hPSC)-derived spinal GABA neurons can alleviate spasticity and promote locomotion in rats after SCI, but whether this strategy can be translated into the clinic remains elusive. Here, a nonhuman primate (NHP) model of SCI was established in rhesus macaques (Macaca mulatta) in which the T10 spinal cord was hemisected, resulting in neural conduction failure and neural dysfunction, including locomotion deficits, pain, and spasms. Grafted human spinal GABA neurons survived for up to 7.5 months in the injured monkey spinal cord and retained their intrinsic properties, becoming mature and growing axons and forming synapses. Importantly, they are functionally alive, as evidenced by designer receptors exclusively activated by designer drug (DREADD) activation. These findings represent a significant step toward the clinical translation of human spinal neuron transplantation for treating SCI.
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Traumatismos da Medula Espinal , Medula Espinal , Humanos , Ratos , Animais , Macaca mulatta , Traumatismos da Medula Espinal/terapia , Coluna Vertebral , Neurônios GABAérgicos , Recuperação de Função Fisiológica/fisiologiaRESUMO
Objective: Peritoneal metastasis is difficult to diagnose using traditional imaging techniques. The main aim of the current study was to develop and validate a nomogram for effectively predicting the risk of peritoneal metastasis in colorectal cancer (PMCC). Methods: A retrospective case-control study was conducted using clinical data from 1284 patients with colorectal cancer who underwent surgery at the First Affiliated Hospital of Guangxi Medical University from January 2010 to December 2015. Least absolute shrinkage and selection operator (LASSO) regression was applied to optimize feature selection of the PMCC risk prediction model and multivariate logistic regression analysis conducted to determine independent risk factors. Using the combined features selected in the LASSO regression model, we constructed a nomogram model and evaluated its predictive value via receiver operating characteristic (ROC) curve analysis. The bootstrap method was employed for repeated sampling for internal verification and the discrimination ability of the prediction models evaluated based on the C-index. The consistency between the predicted and actual results was assessed with the aid of calibration curves. Results: Overall, 96 cases of PMCC were confirmed via postoperative pathological diagnosis. Logistic regression analysis showed that age, tumor location, perimeter ratio, tumor size, pathological type, tumor invasion depth, CEA level, and gross tumor type were independent risk factors for PMCC. A nomogram composed of these eight factors was subsequently constructed. The calibration curve revealed good consistency between the predicted and actual probability, with a C-index of 0.882. The area under the curve (AUC) of the nomogram prediction model was 0.882 and its 95% confidence interval (CI) was 0.845-0.919. Internal validation yielded a C-index of 0.868. Conclusion: We have successfully constructed a highly sensitive nomogram that should facilitate early diagnosis of PMCC, providing a robust platform for further optimization of clinical management strategies.
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Access Control Lists (ACL) are critical to protecting network and cyber-physical systems. Traditional firewalls mostly use reactive methods to enforce ACLs, so that new ACL updates cannot take effect immediately. In this paper, based on our previous work, we propose CPACK, an intelligent cyber-physical access control kit, which uses a smart algorithm to upgrade the ACL list. CPACK adopts a proactive way to enforce ACL and reacts to a new ACL update and network view update in real time. We implement CPACK on both Floodlight and ONOS controller. We then conduct a large number of experiments to compare CPACK with the Floodlight firewall application. The experimental results show that CPACK has a better performance than the existing Floodlight firewall application. CPACK is also integrated into the new version of Floodlight and ONOS controller.
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Algoritmos , Redes de Comunicação de ComputadoresRESUMO
Background: Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored. Methods: This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients. Results: This analysis identified 13 genes significantly upregulated in COVID-19 patients' leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes' downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes. Conclusions: A strong antiviral immune response is essential in reducing severity of COVID-19.
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COVID-19 , Transcriptoma , Antivirais , COVID-19/genética , Perfilação da Expressão Gênica , Humanos , SARS-CoV-2RESUMO
The roles of the microbiome in human beings have become clearer with the development of next-generation sequencing techniques. Several pieces of evidence showed strong correlations between the microbiome and human health and disease, such as metabolic disorders, infectious diseases, digestive system diseases, and cancers. Among these diverse microbiomes, the role of bacteria in human cancers, especially in cancer cells, has received extensive attention. Latest studies found that bacteria widely existed in cancers, mainly in cancer cells and immune cells. In this review, we summarize the latest advances in understanding the role of bacteria in human cancer cells. We also discuss how bacteria are transported into cancer cells and their physiological significance in cancer progression. Finally, we present the prospect of bacterial therapy in cancer treatment.
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Vaccination is considered as the ultimate weapon to end the pandemic. However, the role of vaccines in the pandemic remains controversial. To explore the impact of vaccination on the COVID-19 pandemic, we used logistic regression models to predict numbers of population-adjusted confirmed cases, deaths, intensive care unit (ICU) cases, case fatality rates and ICU admission rates of COVID-19 in the 50 U.S. states, based on 17 related variables. The logistic regression analysis showed that percentages of people vaccinated correlated inversely with the numbers of COVID-19 deaths and case fatality rates but showed no significant correlation with numbers of confirmed cases or ICU cases, or ICU admission rates. The Spearman correlation analysis showed that the percentages of people vaccinated correlated inversely with the numbers of COVID-19 deaths, ICU cases, ICU case rates, and case fatality rates but showed no significant correlation with numbers of confirmed cases. The number of deaths and mortality in the group after the vaccine usage were significantly lower than those in the group before the vaccine usage. However, after delta became the dominant strain, there were no longer significant differences in the number of deaths and the mortality rate between before and after delta became the dominant strain, although vaccines were used in both periods. Vaccination can significantly reduce COVID-19 deaths and mortality, while it cannot reduce the risk of COVID-19 infection. In addition to vaccination, other measures, such as social distancing, remain important in containing COVID-19 transmission and lower the risk of COVID-19 severe outcomes.
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Colorectal cancer (CRC) is one of the most common tumors and ranks second in tumor mortality. N6-methyladenosine (m6A) modification is the most prevalent RNA modification in eukaryotes. As the critical m6A methyltransferase, the role of METTL3 in the metastasis regulation of CRC might be controversial and need to be further explored. In this study, we confirmed that METTL3 could promoted CRC metastasis in vitro and in vivo. METTL3 was upregulated in CRC tissues and led to poor survival in CRC metastasis. We found METTL3 upregulated PLAU mRNA in an m6A-dependent manner, and then participated in MAPK/ERK pathway to promote angiogenesis and metastasis in CRC. Our study provided new therapeutic targets in CRC metastasis treatment.
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Neoplasias Colorretais , Proteínas de Membrana/genética , Metiltransferases/metabolismo , RNA Mensageiro/metabolismo , Adenosina/metabolismo , Linhagem Celular Tumoral , Neoplasias Colorretais/patologia , HumanosRESUMO
HER2 positive BC is heterogeneous. But few studies discussed the classification of HER2-positive BC based on immune-related signatures. Using three publicly BC genomics datasets, we classified HER2 positive BC based on 33 immune-related signatures and used unsupervised machine learning methods to predict and perform the classification. We grouped three HER2-positive BC subtypes that we called Immune-High (IM-H), Immune-Medium (IM-M), and Immune-Low (IM-L), and manifested this categorization was predictable, duplicable and reliable by analyzing another dataset. Compared to other subtypes, IM-H had a higher immune cell infiltration level and stronger anti-tumor immune activities, as well as better clinical survival outcome. Besides these signatures, there were some cancer-related pathways which were hyperactivated in IM-H, including cytokine-cytokine receptor interactions, antigen processing and presentation pathways, natural killer cell-mediated cytotoxicity, Th1 and Th2 cell differentiation, chemokine signaling pathway, Th17 cell differentiation, B and T cell receptor signaling, NF-kappa B signaling, PD-L1 expression and PD-1 checkpoint pathway in cancer, TNF signaling, IL-17 signaling, NOD-like receptor signaling and Toll-like receptor signaling. By contrast, IM-L showed depressed immune-related signatures and enhanced activation of lycosylphosphatidylinositol-anchor biosynthesis and mismatch repair. Moreover, we discovered a gene co-expression network focused on eight transcription factor genes (EOMES, TBX21, GFI1, IRF4, POU2AF1, CIITA, FOXP3 and TOX) and one tumor suppress gene (PRF1), which were closely related with tumor immune. We identified three HER2-positive BC subtypes based on immune-related signatures, which had potential clinical implications and promoted the optimal stratification of HER2-positive BC responsive to immunotherapy.