Search

Immune checkpoint inhibitors restart and maintain cancer-immunity circulation to normalize the anti-tumor immunity. Currently, anti-PD-1/PD-L1 antibodies, as new milestone in immunotherapy, have significantly improved the prognosis of patients with various malignant tumors. However, anti-PD-1/PD-L1 antibody alone exhibited a low response rate, and the combination of anti-PD-1/PD-L1 antibody with traditional therapies such as surgery, chemotherapy, radiotherapy and targeted therapy have shown great potential. As new immune checkpoint inhibitors or in combination therapy are on the way, tumor immunotherapy is entering the era of post-anti-PD-1/PD-L1 antibody. The methodology of combination therapy and biomarker screening remain the focus. This paper reviews the current status of immune checkpoint inhibitor therapy and makes a perspective for the future of post-anti-PD-1/PD-L1 antibody era.

BackgroundUterine corpus endometrial carcinoma (UCEC) belongs to a group of epithelial malignant tumors. Icaritin is the main active compound of Epimedii Folium. Icaritin has been utilized to induce UCEC cells to death.MethodsWe wished to identify potential targets for icaritin in the treatment of UCEC, as well as to provide a groundwork for future studies into its pharmacologic mechanism of action. Network pharmacology was employed to conduct investigations on icaritin. Target proteins were chosen from the components of icaritin for UCEC treatment. A protein–protein interaction (PPI) network was established using overlapping genes. Analyses of enrichment of function and signaling pathways were undertaken using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively, to select “hub genes”. Finally, experiments were carried out to ascertain the effect of icaritin on endometrial cancer (HEC-1-A) cells.ResultsWe demonstrated that icaritin has bioactive components and putative targets that are therapeutically important. Icaritin treatment induced sustained activation of the phosphoinositide 3-kinase/protein kinase B (PI3K/Akt pathway) and inhibited growth of HEC-1-A cells.ConclusionOur data provide a rationale for preclinical and clinical evaluations of icaritin for UCEC therapy.

Objective To investigate the effect of IFN-γ on the proliferation and migration of esophageal squamous cell carcinoma cell line Eca9706 and related mechanism. Methods Cells were cultured in vitro and treated with interferon-γ. Cell morphology changes were observed under microscope, cell proliferation ability was detected by CCK-8 experiment, and cell migration ability was detected by cell scratch experiment and Transwell experiment. Real-time PCR method was used to detect the expression efficiency of chemokine CXCL8 (interleukin 8), and the ELISA experiment was used to detect the change of CXCL8 secretion. Results Compared with the blank control group, Eca9706 cells treated with different concentrations of interferon-γ did not change significantly in cell morphology. CCK8 experiment confirmed that the proliferation ability of Eca9706 cells after IFN-γ treatment was significantly reduced (P < 0.01). Cell scratch experiment found that IFN-γ significantly decreased the migration ability of Eca9706 cells (P < 0.01). Transwell experiment showed that after IFN-γ treatment, the migration ability of Eca9706 cells was significantly inhibited (P < 0.01). CXCL8 gene expression level in Eca9706 cells treated with interferon-γ was significantly down-regulated (P < 0.01), and the amount of CXCL8 secretion significantly reduced (P < 0.05). Conclusion Interferon-γ can inhibit the proliferation and migration of esophageal cancer cell line Eca9706, which may be related to its inhibition of the expression and secretion of CXCL8.

Many computer experiments involve a large number of input factors, but many of them are inert and only a subset are important. This paper develops a new sequential design framework that can accommodate multiple responses and quickly screen out inert factors so that the final design is space-filling with respect to the active factors. By folding over Latin hypercube designs with sliced structure, this sequential design can have flexible sample size in each stage and also ensure that each stage, as well as the whole combined design, are all approximately Latin hypercube designs. The sequential framework does not require prescribing the total sample size and, under the presence of inert factors, can lead to substantial savings in simulation resources. Even if all factors are important, the proposed sequential design can still achieve a similar overall space-filling property compared to a maximin Latin hypercube design optimized in a single stage. [ABSTRACT FROM AUTHOR]

Objective To systematically evaluate the efficacy and safety of immune checkpoint inhibitors in the treatment of advanced gastric cancer or gastroesophageal junction cancer (GC/GEJC). Methods CNKI, Wanfang, PubMed, EMBASE, ClinicalTrials, Cochrane Library and other databases were searched to collect the clinical trials of immune checkpoint inhibitors in the treatment of advanced GC/GEJC. The retrieval time was from the inception to Nov. 2019. Outcome measures mainly included ORR, DCR, PFS, OS and toxicities. The adoption rate difference and hazard ratio were effect measures. Meta-analysis was performed using RevMan 5.3 software. Results We included seven literatures with a total of 1949 patients. Meta-analysis showed that for the patients with advanced GC/GEJC, the second-line or later immune checkpoint inhibitor therapy improved the overall survival rate at 12 and 18 months; the OS of the patients was prolonged, compared with chemotherapy/placebo therapy (all P < 0.05). The incidence of adverse reactions of any grade or ≥grade 3 caused by immune checkpoint inhibitor therapy was lower than that caused by chemotherapy/placebo. Conclusion Immune checkpoint inhibitor treatment could improve survival endpoints in some patients with advanced GC/GEJC, and the incidence of common adverse reactions is low.

Objective To analyze the screening results of colorectal cancer in urban area of Hebei Province from 2018 to 2019. Methods According to the screening process of early diagnosis and treatment of colorectal cancer in urban area of Hebei Province, we enrolled local residents aged 40-74 years from the selected communities in Shijiazhuang and Tangshan City. The high-risk populations were evaluated by national unified evaluation model after the questionnaires. The early colorectal lesions were detected by colonoscopy, and further confirmed pathologically if necessary. Results From 2018 to 2019, a total of 37849 urban residents were involved in the risk assessment of colorectal cancer, and 6938 (18.33%) cases were evaluated as the high risk population of colorectal cancer, among which 1230 cases received colonoscopy examination and 37.8%(465/1230) received pathological examination. The age of the residents who received pathological diagnosis was mainly distributed in the age group of 50-64 years. A total of 6 (0.49%) patients with colorectal cancer were diagnosed, including 4 (0.33%) cases of colon cancer and 2 (0.16%) cases of rectum cancer. The detection rates of colorectal precancerous lesion, non-advanced adenoma/polyp and inflammatory intestinal disease were 15.45%, 20.22% and 13.66%, respectively. Conclusion Colonoscopy screening could effectively detect colorectal cancer and precancerous lesions, and achieve early detection, early diagnosis and early intervention of colorectal cancer.

Abstract Implication By understanding Matrix Metalloprotease (MMP) dysregulation from a pan-cancer perspective, this study sheds light on the diagnostic potentials of MMPs across multiple neoplasms. Background MMPs are intriguing genes related to cancer disease progression, functional promotion of angiogenesis, invasion, metastasis, and avoidance of immune surveillance. Many studies have noted these genes are frequently upregulated in cancer. However, expression patterns of all MMPs and their diagnostic and prognostic potential have not been investigated in a pan-cancer perspective. Methods The Cancer Genome Atlas (TCGA) data were used to evaluate diagnostic and prognostic potential of 24 MMPs in fifteen different cancer types. Gene expression measured by RNA-seq was analyzed by differential expression, hierarchical clustering, and ROC analysis for individual genes and in combination. Results MMP1, MMP9, MMP10, MMP11, and MMP13 were almost universally upregulated across all cancers, with significant (p 2) in ten of fifteen cancers. MMP3, MMP7, MMP12 and MMP14) are significantly up-regulated in at least 10 cancer types. Interestingly, MMP2, MMP7, MMP23B, MMP27 and MMP28) are significantly down-regulated in seven to nine cancer types. Multiple MMPs possess AUC’s > 0.9 in more than one cancer. However, survival analyses suggest that the prognostic value of MMPs is limited to clear cell renal carcinoma. Conclusions Most MMPs have consistently increased gene expression across cancers, while several MMPs have consistently decreased expression in several cancer types. Many MMPs have diagnostic value individually or in combination, while the prognostic value of MMPs is restricted to one subtype of kidney cancer.

At intersections, road features related to different maneuvers, such as left-turn, right-turn, and central channelization (i.e., guidelines and channelized islands), are widely used to decrease the traffic conflicts and improve the safety and mobility of traffic. However, there are several main problems related to channelization design at intersections, including poor recognizability, unreasonable entering speed, insufficient sight distance, and relatively low merging speed. To address these problems, this paper focused on developing a method to assess how to design intersection features by dividing the driving process through intersections into four stages: “appearance of channelization,” “beginning of channelization,” “middle of channelization,” and “end of channelization.” Drivers' visual lane models were established based on the Catmull-Rom spline to quantify visual road information perceived by drivers. Shape parameters and three characteristic regions were extracted from these models. The naturalistic driving experiments and 3D mobile mapping experiments were conducted at intersections with channelized islands or guidelines. Driving speed distributions in the four stages were found to obey normal distributions and could be calculated by shape parameters with Bayesian inference. Then, 3D mobile mapping was used as a substitute for extensive naturalistic driving experiments to obtain drivers' visual perception from all possible visual angles. An evaluation method on intersection design was built and used to identify which stage of channelization needs to be modified. This new method helps to enhance the safety and efficiency of intersections.

Interleukin-8 (IL-8), a member of the CXC chemokine family, is an important mediator of immune responses in the innate immune system. Recent studies have confirmed that IL-8 is significantly elevated in a variety of tumor tissues, including breast, nasopharyngeal, colorectal and gastric tumors, and also in the serum of patients suffering from these cancers. The level of IL-8 is correlated to the TNM staging and prognosis of cancer patients. Researches have shown that IL-8 is an indispensable inflammatory and immunosuppressive factor in the tumor microenvironment, capable of promoting tumor progression, angiogenesis and the recruitment of immune suppressor cells, as well as suppressing immune responses against tumor growth. It is also closely related to the drug resistance of tumors. This article provides a review on the application of targeted therapies related to IL-8 and the progress in combining these therapies with other anti-tumor treatments.

Vehicle automation promises to improve safety. However, it also raises concerns about human performance. Many current research and policy efforts address automation effects on operational levels of driving control. However, the driving task encompasses more than just operational control. So, in this paper, we ask whether a more holistic view of the driving task should be considered. Would such a framework imply that the human role is more than just a “fallback” mechanism for automation systems, especially for partial automation systems? If the human role were conceptualized more as a “commander role” (than an “operator”), would it enable system-level performance to be optimized more effectively? If so, would this lead to changes in design of the vehicle and interface—as well as in skills needed by human users? New skills like strategic planning, delegation of control responsibility, tactical avoidance, and effective mediation of hazardous situations could become important. A more holistic approach for integrating automation may facilitate role change for human users while also improving safety.

Chronic low-grade inflammation is involved in the pathogenesis of type-1 diabetes (T1D) and its complications. In this cross-section study design, we investigated association between serum levels of soluble cytokine receptors with presence of peripheral neuropathy in 694 type-1 diabetes patients. Sex, age, blood pressure, smoking, alcohol intake, HbA1c and lipid profile, presence of DPN (peripheral and autonomic), retinopathy and nephropathy was obtained from patient’s chart. Measurement of soluble cytokine receptors, markers of systemic and vascular inflammation was done using multiplex immunoassays. Serum levels were elevated in in DPN patients, independent of gender, age and duration of diabetes. Crude odds ratios were significantly associated with presence of DPN for 15/22 proteins. The Odds ratio (OR) remained unchanged for sTNFRI (1.72, p=0.00001), sTNFRII (1.45, p=0.0027), sIL2Rα (1.40, p=0.0023), IGFBP6 (1.51, p=0.0032) and CRP (1.47, p=0.0046) after adjusting for confounding variables, HbA1C, hypertension and dyslipidemia. Further we showed risk of DPN is associated with increase in serum levels of sTNFRI (OR=11.2, p

Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised learning in the discovery dataset (97.8% accuracy) with density based UMAP (DBU). The top 30 genes were identified by univariate gene expression analysis and ROC analysis, to create a gene signature called COGS. COGS, combined with DBU, was able to differentiate chRCC from RO in the discovery dataset with an accuracy of 97.8%. The classification accuracy of COGS was validated in an independent meta-dataset consisting of TCGA-KICH and GSE12090, where COGS could differentiate chRCC from RO with 100% accuracy. The differentially expressed genes were involved in carbohydrate metabolism, transcriptomic regulation by TP53, beta-catenin-dependent Wnt signaling, and cytokine (IL-4 and IL-13) signaling highly active in cancer cells. Using multiple datasets and machine learning, we constructed and validated COGS as a tool that can differentiate chRCC from RO and complement histology in routine clinical practice to distinguish these two tumors.

Combining actual conditions, power demand forecasting is affected by various uncertain factors such as meteorological factors, economic factors, and diversity of forecasting models, which increase the complexity of forecasting. In response to this problem, taking into account that different time step states will have different effects on the output, the attention mechanism is introduced into the method proposed in this paper, which improves the deep learning model. Improved models of convolutional neural networks (CNN) and long short-term memory (LSTM) that combine the attention mechanism are proposed respectively. Finally, according to the verification results of actual examples, it is proved that the proposed method can obtain a smaller error and the prediction performance are better compared with other models.

By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles' deployment, and provide employment. It is becoming clear that fully driverless vehicles will not be able to handle "edge" cases in the near future, suggesting that new methods are needed to monitor remotely driverless vehicles' safe deployment. While the remote operations concept is not new, a super-human driver is needed to handle sudden, critical events. We envision that the remote operators do not directly drive the vehicles, but provide input on high level tasks such as path-planning, object detection and classification. This can be achieved via input from multiple individuals, coordinated around a task at a moment's notice. Assuming a 10% penetration rate of driverless vehicles, we show that one remote driver can replace 14,840 human drivers. A comprehensive nationwide interoperability standard and procedure should be established for the remote monitoring and operation of driverless vehicles. The resulting system has potential to be an order of magnitude safer than today's ground transportation system. We articulate a research and policy roadmap to launch this nationwide system. Additionally, this hybrid human-AI system introduces a new job category, likely a source of employment nationwide.