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Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related deaths worldwide. Dendritic cells (DCs) constitute a heterogeneous group of antigen-presenting cells that are important for initiating and regulating both innate and adaptive immune responses. As a crucial component of the immune system, DCs have a pivotal role in the pathogenesis and clinical treatment of CRC. DCs cross-present tumor-related antigens to activate T cells and trigger an antitumor immune response. However, the antitumor immune function of DCs is impaired and immune tolerance is promoted due to the presence of the tumor microenvironment. This review systematically elucidates the specific characteristics and functions of different DC subsets, as well as the role that DCs play in the immune response and tolerance within the CRC microenvironment. Moreover, how DCs contribute to the progression of CRC and potential therapies to enhance antitumor immunity on the basis of existing data are also discussed, which will provide new perspectives and approaches for immunotherapy in patients with CRC.

Abstract Background Combining antitumor proprietary Chinese medicine (pCm) with radiotherapy and chemotherapy can effectively improve tumor cure rates and enhance patients’ quality of life. Gastric cancer (GC) severely endangers public health. Despite satisfactory therapeutic effects achieved by using antitumor pCm to treat GC, its underlying mechanism remains unclear. Objective To integrate existing research data, construct a database of antitumor pCm, and study the intervention mechanisms in GC by focusing on their monomer components. Methods We constructed an antitumor pCm database based on China’s medical insurance catalog, and employed network pharmacology, molecular docking methods, cell experiments, transcriptomics, and bioinformatics to investigate the intervention mechanisms of effective pCm components for GC. Results The study built an antitumor pCm database including 55 pCms, 171 Chinese herbal medicines, 1955 chemical components, 2104 targets, and 32 disease information. Network pharmacology and molecular docking technology identified norcantharidin as an effective component of antitumor pCm. In vitro experiments showed that norcantharidin effectively inhibited GC cell proliferation, migration, and invasion; blocked the G2/M cell cycle phase; and induced GC cell apoptosis. Transcriptomic results revealed that norcantharidin affected biological processes, such as cell adhesion, migration, and inflammatory responses by influencing PI3K-AKT, NF-κB, JAK-STAT, TNF-α signaling pathways, and EMT-related pathways. Core molecules of norcantharidin involved in GC intervention include SERPINE1, SHOX2, SOX4, PRDM1, TGFR3, TOX, PAX9, IL2RB, LAG3, and IL15RA. Additionally, the key target SERPINE1 was identified using bioinformatics methods. Conclusion Norcantharidin, as an effective component of anti-tumor pCm, exerts its therapeutic effects on GC by influencing biological processes such as cell adhesion, migration, and inflammation. This study provides a foundation and research strategy for the post-marketing re-evaluation of antitumor pCms.

ABSTRACT While the link between plant species diversity and biomass has been well‐studied, the impact of evolutionary diversity on community biomass across long timescales or ongoing change remains a subject of debate. We elucidated the association between evolutionary diversity and community aboveground biomass (AGB) using an ideal experimental system with over 150‐year history of natural vegetation regeneration. Higher phylogenetic diversity facilitated the sampling effect under the influence of environmental filtering, and caused an increase in AGB. Phylogenetic structure varied from aggregation to dispersion during the later period of vegetation recovery (70–150 years), which was correlated with increases in niche complementarity and increasing AGB. Woody plant evolutionary diversity was used as a key to predict the relationship between vegetation recovery and AGB, with a total explanatory power of ~84.7%. Mixed forests composed of evergreen conifers and deciduous broadleaf forests had higher carbon sequestration potential than that of pure forests, which is advantageous for increasing top‐stage AGB. This research expands our knowledge of the causes and effects of biodiversity and ecosystem function dynamics over time and space, which is important for accurately predicting future climate change effects.

Abstract Background Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data. The aim of this paper is to develop a prediction model of the incidence rate of infectious diseases that integrates multiple methods and multisource data, realizing ground-breaking research. Results The infectious disease dataset is from an official release and includes four national and three regional datasets. The Baidu index platform provides internet data. We choose a single model (seasonal autoregressive integrated moving average (SARIMA), nonlinear autoregressive neural network (NAR), and long short-term memory (LSTM)) and a deep evolutionary fusion neural network (DEFNN). The DEFNN is built using the idea of neural evolution and fusion, and the DEFNN + is built using multisource data. We compare the model accuracy on reference group data and validate the model generalizability on external data. (1) The loss of SA-LSTM in the reference group dataset is 0.4919, which is significantly better than that of other single models. (2) The loss values of SA-LSTM on the national and regional external datasets are 0.9666, 1.2437, 0.2472, 0.7239, 1.4026, and 0.6868. (3) When multisource indices are added to the national dataset, the loss of the DEFNN + increases to 0.4212, 0.8218, 1.0331, and 0.8575. Conclusions We propose an SA-LSTM optimization model with good accuracy and generalizability based on the concept of multiple methods and multiple data fusion. DEFNN enriches and supplements infectious disease prediction methodologies, can serve as a new benchmark for future infectious disease predictions and provides a reference for the prediction of the incidence rates of various infectious diseases.

[Objective] The changes in plant community composition and vertical structure under natural restoration were studied in order to provide a reference for vegetation construction and high-quality development of the Loess Plateau. [Methods] Using the method of space instead of time, species composition and diversity characteristics of vegetation from abandoned cropland to top community in the Ziwuling forest area were investigated and analyzed. A vegetation vertical structure index was constructed to study the vertical structure of the vegetation community and its changing trend in the succession sequence. [Results] ① A total of 115 species of vegetation in 42 families, 98 genera, and 115 species appeared in the Ziwuling forest zrea, and a total of 32 families, 77 genera, and 88 species of vegetation appeared in the succession sequence. ② In succession, the species diversity index and richness index of the community showed a significant increasing trend, The diversity and richness index values were 0.901 and 1.702 at the beginning of the succession, and 1.998 and 2.665 at the end of the succession. The middle stage showed a unimodal trend, and the two indices were 2.21 and 3.05. The evenness index did not change significantly. ③ During the succession process, each tree factor showed an increasing trend. The DBH was 12.13 cm at the initial stage of succession and increased to 22.19 cm at the end; the crown width increased from 11.64 m2 to 41.54 m2; and the tree biomass increased from 54.07 t/hm2 to 175.13 t/hm2. However, the indicators of shrubs did not change significantly during the succession process. Shrub biomass showed significant peaks in the middle of succession (highest value of 9.56 t/hm2), but showed a rapid fluctuation and declining trend in the subsequent succession process. At the end of succession, shrub biomass was only 1.82 t/hm2. The thickness of the litter layer increased significantly when the shrub community was succeeded by the tree community, but the litter coverage was not significantly different between the succession stages. ④ The overall vertical structure index in the early stage of succession was low and similar, ranging from 0.086 to 0.104, and rapidly increased to 0.349 in the middle stage of succession, reaching a maximum value of 0.477 near the end of the succession. The vertical structure index of understory vegetation was highest in the middle of the succession (0.342), thereafter decreasing and tending to be stable at the end of succession (0.195~0.246). [Conclusion] With natural succession, species diversity and community richness significantly improved, and a single peak appeared in the middle of the succession. The overall vertical structure of the community became more complex, and the vertical structure of understory vegetation degraded during late succession.

Abstract Background Pancreatic cancer is one of the most lethal cancers worldwide. Aidi injection (ADI) is a representative antitumor medication based on Chinese herbal injection, but its antitumor mechanisms are still poorly understood. Materials and methods In this work, the subcutaneous xenograft model of human pancreatic cancer cell line Panc-1 was established in nude mice to investigate the anticancer effect of ADI in vivo. We then determined the components of ADI using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS) and explored the possible molecular mechanisms against pancreatic cancer using network pharmacology. Results In vivo experiments, the volume, weight, and degree of histological abnormalities of implanted tumors were significantly lower in the medium and high concentration ADI injection groups than in the control group. Network pharmacology analysis identified four active components of ADI and seven key targets, TNF, VEGFA, HSP90AA1, MAPK14, CASP3, P53 and JUN. Molecular docking also revealed high affinity between the active components and the target proteins, including Astragaloside IV to P53 and VEGFA, Ginsenoside Rb1 to CASP3 and Formononetin to JUN. Conclusion ADI could reduce the growth rate of tumor tissue and alleviate the structural abnormalities in tumor tissue. ADI is predicted to act on VEGFA, P53, CASP3, and JUN in ADI-mediated treatment of pancreatic cancer.

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BackgroundThe Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown.MethodsWe collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (Cr). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (Rt). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses.Results(1) The overall level of Rt in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, Rt decreased rapidly, and the overall Rt level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage.ConclusionEffective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

Introduction: Systematic evaluation of the clinical efficacy and safety of Brucea javanica oil emulsion injection (BJOEI) in combination with chemotherapy in the treatment of malignant pleural effusion (MPE).Methods: The study searched CNKI, Wanfang database, VIP database, SinoMed, PubMed, Embase, the Cochrane Library, and the Web of Science database and retrieved randomized controlled trials (RCTs) on the treatment of MPE with BJOEI in combination with chemotherapy from seven electronic databases from inception to 31 March 2022. Meta-analysis and sensitivity analysis were performed using Revman 5.4 and Stata 13.0 software.Results: Ultimately, 30 RCTs with 2035 patients were included, including 1002 cases in the control group and 1033 cases in the treatment group. The results of the meta-analysis showed that the overall efficacy rate of BJOEI combined with chemotherapy was higher in the treatment of MPE compared with chemotherapy alone (RR = 1.45, 95%CI: 1.36–1.54, p < 0.00001). And it could improve the Karnofsky (KPS) score (RR = 1.54, 95%CI: 1.41–1.68, p < 0.00001), reduce adverse reactions such as fever (RR = 0.82, 95%CI:0.60–1.12), chest pain (RR = 0.90, 95%CI: 0.67–1.21), gastrointestinal reactions (RR = 0.70, 95%CI: 0.57–0.87, p < 0.005), and leukopenia (RR = 0.51, 95%CI: 0.43–0.61, p < 0.00001).Conclusion: BJOEI combined with chemotherapy has better clinical efficacy than chemotherapy alone in the treatment of MPE. It can further improve KPS score, improve patients’ quality of life, and reduce the occurrence of adverse reactions. However, the conclusions of this study need to be confirmed by further randomized, double-blind, controlled trials with large sample size, reasonable design, and strict implementation.

Aim: The detection and segmentation of cerebral microbleeds (CMBs) images are the focus of clinical diagnosis and treatment. However, segmentation is difficult in clinical practice, and missed diagnosis may occur. Few related studies on the automated segmentation of CMB images have been performed, and we provide the most effective CMB segmentation to date using an automated segmentation system.Materials and Methods: From a research perspective, we focused on the automated segmentation of CMB targets in susceptibility weighted imaging (SWI) for the first time and then constructed a deep learning network focused on the segmentation of micro-objects. We collected and marked clinical datasets and proposed a new medical micro-object cascade network (MMOC-Net). In the first stage, U-Net was utilized to select the region of interest (ROI). In the second stage, we utilized a full-resolution network (FRN) to complete fine segmentation. We also incorporated residual atrous spatial pyramid pooling (R-ASPP) and a new joint loss function.Results: The most suitable segmentation result was achieved with a ROI size of 32 × 32. To verify the validity of each part of the method, ablation studies were performed, which showed that the best segmentation results were obtained when FRN, R-ASPP and the combined loss function were used simultaneously. Under these conditions, the obtained Dice similarity coefficient (DSC) value was 87.93% and the F2-score (F2) value was 90.69%. We also innovatively developed a visual clinical diagnosis system that can provide effective support for clinical diagnosis and treatment decisions.Conclusions: We created the MMOC-Net method to perform the automated segmentation task of CMBs in an SWI and obtained better segmentation performance; hence, this pioneering method has research significance.

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Household food consumption is the associative link between ecosystems and anthropogenic activities. In grassland areas, inappropriate food consumption patterns will cause irreversible damage to vulnerable local ecosystems. For this study, we selected three typical transitional grassland areas of Inner Mongolia, China (i.e., meadow steppe, typical steppe, and desert steppe), to analyze spatial heterogeneity in household food consumption and nutritional characteristics. Results showed that: (a) Food consumption structures exhibited zonal gradients from east to west alongside a reduction in grassland conditions. Additionally, the average food consumption quantity also decreased. Available food supplies altered household preferences for vegetables and fruits, meat, dairy products, and other food consumption category types. (b) The nutritional structure implied that grains provided the main source of energy, proteins, and fat for local rural households, while meat, dairy products, beans (including bean byproducts), and oils caused a fluctuation in the nutritional structure of residents. (c) Local food supplies affect short-term local food consumption patterns, while socioeconomic development affects long-term food consumption patterns. This study is intended to provide a reference for the development of sustainable strategies for regional resource management.

Abstract Background Yuzhi Zhixue Granule (YZG) is a traditional Chinese patent medicine for treating excessive menstrual flow caused by ovulatory dysfunctional uterine bleeding (ODUB) accompanied by heat syndrome. However, the underlying molecular mechanisms, potential targets, and active ingredients of this prescription are still unknown. Therefore, it is imperative to explore the molecular mechanism of YZG. Methods The active compounds in YZG were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The putative targets of YZG were collected via TCMSP and Search Tool for Interacting Chemicals (STITCH) databases. The Therapeutic Target Database (TTD) and Pharmacogenomics Knowledgebase (PharmGKB) databases were used to identify the therapeutic targets of ODUB. A protein–protein interaction (PPI) network containing both the putative targets of YZG and known therapeutic targets of ODUB was built. Furthermore, bioinformatics resources from the database for annotation, visualization and integrated discovery (DAVID) were utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking was performed to verify the binding effect between the YZG screened compounds and potential therapeutic target molecules. Results The study employed a network pharmacology method, mainly containing target prediction, network construction, functional enrichment analysis, and molecular docking to systematically research the mechanisms of YZG in treating ODUB. The putative targets of YZG that treat ODUB mainly involved PTGS1, PTGS2, ALOX5, CASP3, LTA4H, F7 and F10. The functional enrichment analysis suggested that the produced therapeutic effect of YZG against ODUB is mediated by synergistical regulation of several biological pathways, including apoptosis arachidonic acid (AA) metabolism, serotonergic synapse, complement and coagulation cascades and C-type lectin receptor signaling pathways. Molecular docking simulation revealed good binding affinity of the seven putative targets with the corresponding compounds. Conclusion This novel and scientific network pharmacology-based study holistically elucidated the basic pharmacological effects and the underlying mechanisms of YZG in the treatment of ODUB.

Abstract Background Javanica oil emulsion injection (JOEI) is an effective therapeutic option for patients with non-small cell lung cancer (NSCLC), but its mechanisms have not been fully elucidated. Methods In this study, we utilized network pharmacology to systematically investigate the bioactive components and targets of JOEI, identify common targets in NSCLC, and understand and evaluate the underlying mechanism of JOEI in the treatment of NSCLC through expression level, correlation, enrichment, Cox, survival and molecular docking analyses. The results indicated that five compounds of JOEI interact with five pivotal targets (LDLR, FABP4, ABCB1, PTGS2, and SDC4) that might be strongly correlated with the JOEI-mediated treatment of NSCLC. Results The expression level analysis demonstrated that NSCLC tissues exhibit low expression of FABP4, ABCB1, LDLR and PTGS2 and high SDC4 expression. According to the correlation analysis, a decrease in FABP4 expression was strongly correlated with decreases in LDLR and ABCB1, and a decrease in LDLR was strongly correlated with decreased PTGS2 and increased in SDC4 expression. Cox and survival analyses showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group (p = 0.00388). In the survival analysis, the area under the curve (AUC) showed that the pivotal gene model exhibited the best predictive capacity over 4 years (AUC = 0.613). Moreover, the molecular docking analysis indicated that LDLR, FABP4, ABCB1, PTGS2 and SDC4 exhibit good binding activity with the corresponding compounds. Conclusion In conclusion, this study predicted and verified that the mechanism of JOEI against NSCLC involves multiple targets and signaling pathways. Furthermore, this study provides candidate targets for the treatment of NSCLC, lays a good foundation for further experimental research and promotes the reasonable application of JOEI in clinical treatment.

Background: An outbreak of coronavirus disease 2019 (COVID-19) occurred in Wuhan, China; the epidemic is more widespread than initially estimated, with cases now confirmed in multiple countries. Aims: The aim of this meta-analysis was to assess the prevalence of comorbidities in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected patients and the risk of underlying diseases in severe patients compared to non-severe patients. Methods: A literature search was conducted using the databases PubMed, EMBASE, and Web of Science through February 25, 2020. Odds ratios (ORs) and 95% confidence intervals (CIs) were pooled using random-effects models. Results: Seven studies were included in the meta-analysis, including 1 576 infected patients. The results showed the most prevalent clinical symptom was fever (91.3%, 95% CI: 86–97%), followed by cough (67.7%, 95% CI: 59–76%), fatigue (51.0%, 95% CI: 34–68%) and dyspnea (30.4%, 95% CI: 21–40%). The most prevalent comorbidities were hypertension (21.1%, 95% CI: 13.0–27.2%) and diabetes (9.7%, 95% CI: 7.2–12.2%), followed by cardiovascular disease (8.4%, 95% CI: 3.8–13.8%) and respiratory system disease (1.5%, 95% CI: 0.9–2.1%). When compared between severe and non-severe patients, the pooled OR of hypertension, respiratory system disease, and cardiovascular disease were 2.36 (95% CI: 1.46–3.83), 2.46 (95% CI: 1.76–3.44) and 3.42 (95% CI: 1.88–6.22) respectively. Conclusion: We assessed the prevalence of comorbidities in the COVID-19 patients and found that underlying disease, including hypertension, respiratory system disease and cardiovascular disease, may be risk factors for severe patients compared with non-severe patients.

Mobile edge computing (MEC) is a promising paradigm for providing computing and storage capabilities in close proximity to mobile devices. To solve the scenario in which massive mobile devices have tasks to be processed at the same time, this paper proposes an assisted mechanism for the MEC system. When the primary MEC server is unable to meet the delay requirements of the mobile devices within its coverage area, a portion of the tasks can be offloaded to secondary MEC servers to obtain extra resources for processing. This MEC framework effectively reduces the computing and communication burden of the primary MEC server and improves the resource utilization of the secondary MEC servers. To maximize the system offloading utility in terms of latency, we formulated an optimization problem that jointly optimizes the task assignment, computing resource allocation and offloading decision of all mobile devices. Since the formulated problem is a mixed integer nonlinear problem, we use the decomposition method to convert the optimization problem into several subproblems. In addition, a heuristic algorithm based on the priorities of mobile devices and the MEC servers is proposed to obtain the suboptimal device offloading strategy. The numerical results show that the assisted mechanism can effectively reduce system latency and improve system reliability. In addition, the performance of our proposed algorithm is close to the optimal solution.

A new practical automatic planning method for MV distribution network considering complementation of load characteristic and division of power supply is presented to solve the problems of large network size and low equipment utilization ratio caused by the lack of consideration of complementation of load characteristic in distribution network planning. First, based on the existing research results on load clustering and grid planning, the concepts of MV distribution network feeder block and power supply unit are redefined and the technical framework of MV distribution network planning considering division of power supply is designed. Then, the evaluation indexes of feeder block partitioning and power supply unit partitioning considering complementation of load characteristic are set up, and rotation center line distance weighting alternate location algorithm is proposed to divide the feeder block. Further, the MV distribution network planning model based on power supply unit partitioning is proposed, which takes the minimum value of the sum of interruption cost based on reliability index and line integrated cost of the planning year. Combining ant colony algorithm, automatic planning algorithm is proposed to get the combinatorial solution of trunk line and branch line. Finally, the scientificalness and practicability of the model and method in this paper was verified through the case study.

With the rapid development of society and economy, people’s demand for ecosystem services is constantly increasing. All countries support this demand by vigorously developing green finance. The coordinated development of green finance and ecosystem service demand is of great significance for sustainable development. Most of the existing studies separately study green finance or ecosystem service demand, separating the relationship between the two. At present, there is still a lack of clear understanding of the coupling relationship between green finance and ecosystem service demand. In addition, in the existing coupling relationship calculation models, the setting of relevant parameters is subjective. Therefore, based on the green finance and ecosystem service demand database of 30 provinces in China from 2010 to 2017, this paper firstly evaluates the green finance and ecosystem service demand quantitatively, and then analyzes the coupling coordination relationship between them by using an improved coupling coordination degree model. The results show that: (1) compared with the traditional coupling coordination degree model, the contribution coefficient of each subsystem in the improved coupling coordination degree model has a more sufficient basis, and more objective evaluation results; (2) from 2010 to 2017, the level of green finance in China’s provinces increased significantly, showing a spatial pattern of “high in the east and low in the west”; the ecosystem services demand increased first and then decreased, with an increase in nearly two-thirds of provinces; (3) the coupling coordination relationship between green finance and ecosystem service demand in China’s provinces was optimized continuously from 2010 to 2017, showing the spatial differentiation of “eastern China > central China > northeast China > western China”; (4) in 2017, the coupling coordination degree of green finance and ecosystem service demand in Guangdong Province was the highest, reaching a high level of coordination, while Qinghai Province was the lowest, as a result of a serious level of incoordination. It is worth noting that the comprehensive development level of green finance in China is still low and seriously lags behind the development level of ecosystem services demand. In the future, green and low-carbon transformation should be accelerated to promote the sustainable development of financial ecology.

Introduction: As non-small cell lung cancer (NSCLC) seriously threatens human health, several clinical studies have reported that Chinese herbal injections (CHIs) in combination with and gemcitabine plus cisplatin (GP) are beneficial. This multidimensional network meta-analysis aimed to compare the clinical efficacy and safety of different CHIs in combination with GP against NSCLC.Methods: Randomized controlled trials (RCTs) for the treatment of NSCLC were retrieved from seven electronic databases from inception to April 30, 2020. Study selection and data extraction were based on a priori criteria. Data analysis was performed using Stata 13.0, WinBUGS 14.0 software. Multidimensional cluster analysis was performed using the “scatterplot3d” package in R 3.6.1 software.Results: This network meta-analysis included 71 eligible RCTs and 10 Chinese herbal injections. Delisheng injection and Kangai injection had the highest probability in terms of clinical effectiveness rate (94.60%) and gastrointestinal reactions (82.62%) when combined with GP compared with the other interventions. Compound Kushen injection combined with GP ranked ahead of the other interventions in terms of performance status (73.36%) and abnormal liver function (87.17%). Shenmai injection combined with GP had the highest probability in terms of leukopenia (94.59%) and thrombocytopenia (99.18%).Conclusion: The current evidence revealed that CHIs combined with GP have a better impact on patients with NSCLC than GP alone. Aidi injection, Compound kushen injection, and Kanglaite injection deserve more attention of clinicians when combined with GP in patients with NSCLC. Additionally, due to the limitations of this network meta-analysis, further well-designed, large-sample, multicenter RCTs are required to support our findings adequately.

BackgroundAlthough notable therapeutic and prognostic benefits of compound kushen injection (CKI) have been found when it was used alone or in combination with chemotherapy or radiotherapy for triple-negative breast cancer (TNBC) treatment, the effects of CKI on TNBC microenvironment remain largely unclear. This study aims to construct and validate a predictive immunotherapy signature of CKI on TNBC.MethodsThe UPLC-Q-TOF-MS technology was firstly used to investigate major constituents of CKI. RNA sequencing data of CKI-perturbed TNBC cells were analyzed to detect differential expression genes (DEGs), and the GSVA algorithm was applied to explore significantly changed pathways regulated by CKI. Additionally, the ssGSEA algorithm was used to quantify immune cell abundance in TNBC patients, and these patients were classified into distinct immune infiltration subgroups by unsupervised clustering. Then, prognosis-related genes were screened from DEGs among these subgroups and were further overlapped with the DEGs regulated by CKI. Finally, a predictive immunotherapy signature of CKI on TNBC was constructed based on the LASSO regression algorithm to predict mortality risks of TNBC patients, and the signature was also validated in another TNBC cohort.ResultsTwenty-three chemical components in CKI were identified by UPLC-Q-TOF-MS analysis. A total of 3692 DEGs were detected in CKI-treated versus control groups, and CKI significantly activated biological processes associated with activation of T, natural killer and natural killer T cells. Three immune cell infiltration subgroups with 1593 DEGs were identified in TNBC patients. Then, two genes that can be down-regulated by CKI with hazard ratio (HR) > 1 and 26 genes that can be up-regulated by CKI with HR < 1 were selected as key immune- and prognosis-related genes regulated by CKI. Lastly, a five-gene prognostic signature comprising two risky genes (MARVELD2 and DYNC2I2) that can be down-regulated by CKI and three protective genes (RASSF2, FERMT3 and RASSF5) that can be up-regulated by CKI was developed, and it showed a good performance in both training and test sets.ConclusionsThis study proposes a predictive immunotherapy signature of CKI on TNBC, which would provide more evidence for survival prediction and treatment guidance in TNBC as well as a paradigm for exploring immunotherapy biomarkers in compound medicines.

Introduction: Given the wide utilization of Chinese herbal injections in the treatment of nasopharyngeal carcinoma (NPC), this network meta-analysis (NMA) was devised to compare the clinical efficacy and safety of different Chinese herbal injections combined with concurrent chemoradiotherapy (CCRT) against NPC.Methods: Randomized controlled trials (RCTs) were retrieved from seven electronic databases from the date of database establishment to October 5, 2020. Study selection and data extraction conformed to a priori criteria. Focusing on clinical effective rate, performance status, grade ≥3 oral mucositis, nausea and vomiting, leukopenia, and thrombopenia, this NMA was performed with Review Manager 5.3.5, Stata 13.1, WinBUGS 1.4.3, and R 4.0.3 software.Results: Ten inventions from 37 RCTs involving 2,581 participants with NPC that evaluated the clinical effective rate, nausea and vomiting, leukopenia, thrombopenia, and grade ≥3 oral mucositis were included. Compared with CCRT alone, Elemene injection and Compound Kushen injection were associated with significantly improved clinical effective rates, and Elemene injection plus CCRT had the highest probability in terms of clinical effective rate (78.07%) compared with the other interventions. Shenqifuzheng injection, Xiaoaiping injection, and Shenmai injection ranked the best in terms of performance status (79.02%), nausea and vomiting (86.35%), and grade ≥3 oral mucositis (78.14%) when combined with CCRT. Kangai injection combined with CCRT ranked ahead of the other injections in terms of leukopenia (90.80%) and thrombopenia (91.04%), and had a better impact on improving performance status and reducing leukopenia, thrombopenia, grade ≥3 oral mucositis, and nausea and vomiting in the multidimensional cluster analysis.Conclusion: Current clinical evidence indicates that Elemene injection combined with CCRT has the best clinical effective rate and that Kangai injection might have a comprehensively better impact on improving performance status and reducing adverse reactions against NPC. Additionally, due to the limitations of this NMA, more multicenter, high-quality, and head-to-head RCTs are needed to properly support our findings.

Background: As non-small cell lung cancer (NSCLC) seriously threatens human health, several clinical studies have reported that Chinese herbal injections (CHIs) combined with vinorelbine and cisplatin (NP) are beneficial. This multidimensional network meta-analysis was performed to explore the preferable options among different CHIs for treating NSCLC.Methods: A literature search was performed in several databases to identify randomized controlled trials (RCTs) of CHIs in the treatment of NSCLC from inception to January 31, 2019. Final included studies met the eligibility criteria and methodological quality recommendations. Data analysis was performed using Stata 13.0 and WinBUGS 14.0 software. Each outcome was presented as an odds ratio and the surface under the cumulative ranking curve value (SCURA). The “scatterplot3d” package in R 3.6.1 software was used to perform multidimensional cluster analysis.Results: Ultimately, 97 eligible RCTs involving 7,440 patients and 14 CHIs were included in this network meta-analysis. Combined with NP chemotherapy, Kanglaite injection plus NP exhibited a better impact on the clinical effectiveness rate (SCURA probability: 78.34%), and Javanica oil emulsion injection plus NP was better in the performance status (95.44%). Huachansu injection plus NP was dominant in reducing thrombocytopenia (92.67%) and gastrointestinal reactions (92.52%). As to multidimensional cluster analysis, Shenmai injection plus NP was superior considering improving the clinical effectiveness rate, performance status and relieving leukopenia.Conclusions: The combination of CHIs and NP has a better impact on patients with NSCLC than NP alone. Among them, Shenmai injection plus NP, Kanglaite injection plus NP and Javanica oil emulsion injection plus NP were notable. Nevertheless, more multicenter and better designed RCTs are needed to validate our findings.

Background: Given the limitations of chemotherapy for the treatment of breast cancer (BC) and the wide exploration of Chinese herbal injections (CHIs), this network meta-analysis (NMA) was conducted to analyze the comparative efficacy and safety of nine CHIs combined with CF (Cyclophosphamide and 5-Fluorouracil) chemotherapy regimens in the treatment of BC.Methods: Several electronic databases were searched to identify randomized controlled trials (RCTs) from inception to January 6, 2020. RCTs were screened by pre-established eligibility criteria, and the quality of which was assessed using the Cochrane risk of bias tool. Outcomes such as the clinical effectiveness rate, performance status, peripheral hemogram, and detection of T-lymphocyte subsets were analyzed using the Winbugs 1.4.3 and Stata 13.0 software. Surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the examined treatments. Cluster analysis was performed to compare the effect of CHIs between two or three different outcomes.Results: A total of 84 RCTs involving 7855 patients and nine CHIs were included. The results showed that compared to CF chemotherapy regimens alone, the ones injected along with Aidi, Shenmai, Shenqi Fuzheng, Kangai, Kanglaite, or Shengmai combined with CF can improve the clinical effectiveness rate. Aidi, Shenmai, Shenqi Fuzheng, Compound Kushen, Kangai, and Kanglaite injection combined with CF can improve the performance status. Shenqi Fuzheng injection was considered as a favorable choice for relieving adverse reactions. According to the results of cluster analysis, Aidi injection and Compound Kushen injection plus CF were more favorable for the clinical effectiveness rate and performance status.Conclusion: In conclusion, Shenqi Fuzheng, Compound Kushen, Aidi, and Kangai injection combined with CF chemotherapy regimen have more significant effects for patients with BC. However, more high-quality clinical RCTs, especialy which correctly use blinding and allocation concealment, are required to support the conclusions.

BackgroundGiven the severity of pulmonary heart disease and the wide utilization of Chinese herbal injections, this network meta-analysis was devised to assess the comparative efficacy of seven Chinese herbal injections (Ciwujia injection, Dazhuhongjingtan injection, Huangqi injection, Shenfu injection, Shengmai injection, Shenmai injection, and Shenqi Fuzheng injection) that were combined with Western medicines in the treatment of pulmonary heart disease.MethodsA literature search was performed in PubMed, Cochrane Library, EMBASE, Chinese Biological Medicine Database, China National Knowledge Infrastructure, Wanfang Database, and the Chinese Scientific Journal Database from their inception to July14, 2019. This network meta-analysis was conducted in accordance with a priori eligibility criteria and methodological quality recommendations. Data analysis was performed with WinBUGS 1.4.3 and Stata 13.0 software focusing on clinical effectiveness rate, arterial blood gas analysis, hemorheology and hemodynamic indexes and right ventricular dimensions. In addition to the odds ratio or mean difference in various outcomes, the ranking probability of interventions calculated by the surface under the cumulative ranking area curve was demonstrated. The surface under the cumulative ranking area was equal to the rank of the intervention and was aimed to assess the best intervention.ResultsUltimately, 118 randomized controlled trials including 10,085 patients were included. Integrating the outcome results, all eligible Chinese herbal injections plus Western medicines were superior to Western medicines alone, especially Shenfu injection+ Western medicines, Shenmai injection+ Western medicines, and Shenqi Fuzheng injection+ Western medicines. Regarding safety, the drip rate was an essential element for clinicians to consider during treatment.ConclusionsIn conclusion, Shenfu injection+ Western medicines, Shenmai injection+ Western medicines and Shenqi Fuzheng injection+ Western medicines may be potential optimal treatments for pulmonary heart disease. A larger sample size and high-quality randomized controlled trials are needed to confirm and support this network meta-analysis.

BackgroundConsidering the limitations of broad-spectrum antiviral drugs for the treatment of herpangina and the extensive exploration of Chinese herbal injections (CHIs), systematic evaluation of the efficacy of different CHIs in the treatment of herpangina is a key imperative. In this study, we performed a network meta-analysis to investigate the efficacy of CHIs, including Reduning injection (RDN), Shuanghuanglian injection (SHL), Tanreqing injection (TRQ), Xiyanping injection (XYP), and Yanhuning injection (YHN), in the treatment of herpangina.MethodsA systematic literature review including studies published before December 17, 2018, was conducted in several databases. The quality of the included studies was assessed using the Cochrane risk of bias tool. Data were analyzed using STATA 13.0 and WinBUGS 1.4.3 software. Surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the examined treatments. Clustering analysis was performed to compare the effects of CHIs between two different outcomes.ResultsA total of 72 eligible randomized controlled trials involving 8,592 patients and five CHIs were included. All patients were under the age of 15 years, and most were under 7 years. The results of the network meta-analysis showed that RDN, XYP, and YHN had significantly better treatment performance than ribavirin. SHL (OR: 0.18; 95% CI: 0.09–0.34) and TRQ (OR: 0.18; 95% CI: 0.10–0.31) were obviously superior to ribavirin with respect to total clinical effectiveness. The results of SUCRA and cluster analysis indicated that RDN is the best intervention with respect to total clinical effectiveness, antipyretic time, and blebs disappearing time. Fifty-four studies described adverse drug reactions/adverse drug events (ADRs/ADEs), and 32 studies reported ADRs/ADEs in detail.ConclusionsCHIs were found to be superior to ribavirin in terms of treatment performance and may be beneficial for patients with herpangina. RDN had the potential to be the best CHI with respect to all outcome measures. More evidence is needed to assess the safety aspects of CHIs.

Objective This study compared Chinese herbal injections (CHIs) plus chemotherapy with chemotherapy alone in terms of clinical efficacy and safety for treating patients with esophageal cancer (EC). Methods Randomized controlled trials (RCTs) of CHIs combined with chemotherapy for treating EC published in English and Chinese databases were identified. The main outcomes were clinical efficacy, performance status, and adverse reactions. Random-effects models were fitted to calculate the odds ratios and 95% confidence intervals for all pair-wise comparisons. Results In total, 29 RCTs of eight CHIs were included in this study. The results of cluster analysis demonstrated that Compound Kushen injection plus chemotherapy was the optimal choice for improving the clinical efficacy rate. Shenfu injection was associated with a relatively high performance status. Compound Kushen injection and Shenfu injection were inferior to other CHIs in terms of preventing leukopenia and gastrointestinal side effects. Conclusions The combination of Compound Kushen injection with chemotherapy could improve efficacy and reduce adverse drug reactions versus chemotherapy alone in patients with EC.

The tumor suppressor protein p53 plays an important role in the development and progression of colon cancer, and the subcellular organelle localization directly affects its function. Wogonin (5,7-dihydroxy-8-methoxyflavone), a mono-flavonoid extracted from root of Scutellaria baicalensis Georgi, possesses acceptable toxicity and has been used in colorectal cancer (CRC) chemoprevention in pre-clinical trials by oncologist. However, the underlying anti-colon cancer mechanisms of wogonin are not yet fully understood. In the present study, the effect of wogonin on the initiation and development of colitis-associated cancer through p53 nuclear translocation was explored. AOM-DSS CRC animal model and human CRC HCT-116 cell model were used to evaluate the in vivo and in vitro anti-colon cancer action of wogonin. We observed that wogonin showed a dramaticlly preventive effect on colon cancer. Our results showed that wogonin caused apoptotic cell death in human CRC HCT-116 cell through increased endoplasmic reticulum (ER) stress. Meanwhile, excessive ER stress facilitated the cytoplasmic localization of p53 through increasing phosphor-p53 at S315 and S376 sites, induced caspase-dependent apoptosis and inhibited autophagy. Furthermore, we verified the chemoprevention effect and toxicity of wogonin in vivo by utilizing an AOM-DSS colon cancer animal model. We found that wogonin not only reduced tumor multiplicity, preserved colon length to normal (6.79 ± 0.34 to 7.41 ± 0.56, P < 0.05) but also didn’t induce side effects on various organs. In conclusion, these results explain the anti-tumor effect of wogonin in CRC and suggest wogonin as a potential therapeutic candidate for the therapeutic strategy in CRC treatment.

Lung adenocarcinoma (LAC), predominant subclassfication of lung cancer, leads high incidence and mortality annually worldwide. During the premalignant transition from lung adenomas to LAC, cellular senescence is regard as a critical physiological barrier against tumor progression. Nevertheless, the role of senescence in tumorigenesis is controversial and few senescence inducers are extensively determined. In this study, we used two classical cell lines A549 and H1299 and two NSCLC xenograft models on Balb/c-nude mice to reveal the pro-senescence effects of shikonin and the corresponding underlying mechanism in LAC. Shikonin, a pure compound isolated from the herbal medicine Lithospermum erythrorhizon, remarkably stimulated cellular senescence including increased SAHF formation, enlarged cellular morphology, and induced SA-β-Gal positive staining. Further mechanism study revealed that the pro-senescence effect of shikonin was dependent on the increased intercellular ROS generation, which subsequently triggered DNA damage-p53/p21waf axis without activating oncogenes such as Ras and MEK-1. Meanwhile, Kdm2b, an H3K36me2-specific demethylase effectively suppressed ROS generation, was also notably suppressed by shikonin treatment. Moreover, shikonin at 10 mg/kg significantly inhibited tumor weights by 55.84% and 50.98% in A549 and H1299 xenograft model, respectively (P < 0.05) through activating cellular senescence. Our study suggested that shikonin, a ROS-dependent senescence inducer, could serve as a promising agent for further lung cancer treatment.