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HighlightsThe classification of 2D perovskite is summarized, and the preparation methods of 2D perovskite according to the requirements of X-ray detection materials are introduced.We analyzed the advantages and insufficiency of different devices and introduced improvement measures, including ion migration, charge transfer performance, stability, and 2D/3D heterojunctions.Finally, we introduced the potential preponderances of 2D perovskite in the scintillation detection field; meanwhile, the main challenges facing the practical application of 2D perovskite X-ray detectors are analyzed.Metal halide perovskites have recently emerged as promising candidates for the next generation of X-ray detectors due to their excellent optoelectronic properties. Especially, two-dimensional (2D) perovskites afford many distinct properties, including remarkable structural diversity, high generation energy, and balanced large exciton binding energy. With the advantages of 2D materials and perovskites, it successfully reduces the decomposition and phase transition of perovskite and effectively suppresses ion migration. Meanwhile, the existence of a high hydrophobic spacer can block water molecules, thus making 2D perovskite obtain excellent stability. All of these advantages have attracted much attention in the field of X-ray detection. This review introduces the classification of 2D halide perovskites, summarizes the synthesis technology and performance characteristics of 2D perovskite X-ray direct detector, and briefly discusses the application of 2D perovskite in scintillators. Finally, this review also emphasizes the key challenges faced by 2D perovskite X-ray detectors in practical application and presents our views on its future development.

The application of chimeric antigen receptor (CAR) T-cell therapy as a tumor immunotherapy has received great interest in recent years. This therapeutic approach has been used to treat hematological malignancies solid tumors. However, it is associated with adverse reactions such as, cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), off-target effects, anaphylaxis, infections associated with CAR-T-cell infusion (CTI), tumor lysis syndrome (TLS), B-cell dysplasia, hemophagocytic lymphohistiocytosis (HLH)/macrophage activation syndrome (MAS) and coagulation disorders. These adverse reactions can be life-threatening, and thus they should be identified early and treated effectively. In this paper, we review the adverse reactions associated with CAR-T cells, the mechanisms driving such adverse reactions, and strategies to subvert them. This review will provide important reference data to guide clinical application of CAR-T cell therapy.

An increasing number of studies have shown that immunotherapy serves a significant role in treating colorectal cancer (CRC) and has become a hotspot. However, few studies used the bibliometric method to analyze this field comprehensively. This study collected 1,899 records of CRC immunotherapy from 2012 to October 31, 2021, and used CiteSpace to analyze regions, institutions, journals, authors, and keywords to predict the latest trends in CRC immunotherapy research. The United States and China, contributing more than 60% of publications, were the main drivers in this field. Sun Yat-sen University was the most active institution, while the National Cancer Institute had the highest frequency of citations. Most publications were published in the Journal for Immunotherapy of Cancer. Adam E Snook was the most prolific writer, while Dung T. Le was the most commonly co-cited author. “T cell”, “MMI” and “PD-1blocked” were the most widely studied aspects of CRC immunotherapy. “Immune checkpoint inhibitor”, “combination therapy”, “drug therapy” and “liver metastases” were current research hotspots. “Tumor microenvironment”, “neutrophils”, “tumor-associated macrophages”, and “suppressor cell” have emerged as research hotspots in recent years. “Gut microbiota”, “nanoparticle” and “tumor mutational burden” as recently emerged frontiers of research that should be closely monitored.

Chimeric antigen receptor (CAR) T-cell immunotherapy refers to an adoptive immunotherapy that has rapidly developed in recent years. It is a novel type of treatment that enables T cells to express specific CARs on their surface, then returns these T cells to tumor patients to kill the corresponding tumor cells. Significant strides in CAR-T cell immunotherapy against hematologic malignancies have elicited research interest among scholars in the treatment of solid tumors. Nonetheless, in contrast with the efficacy of CAR-T cell immunotherapy in the treatment of hematologic malignancies, its general efficacy against solid tumors is insignificant. This has been attributed to the complex biological characteristics of solid tumors. CAR-T cells play a better role in solid tumors, for instance by addressing obstacles including the lack of specific targets, inhibition of tumor microenvironment (TME), homing barriers of CAR-T cells, differentiation and depletion of CAR-T cells, inhibition of immune checkpoints, trogocytosis of CAR-T cells, tumor antigen heterogeneity, etc. This paper reviews the obstacles influencing the efficacy of CAR-T cell immunotherapy in solid tumors, their mechanism, and coping strategies, as well as economic restriction of CAR-T cell immunotherapy and its solutions. It aims to provide some references for researchers to better overcome the obstacles that affect the efficacy of CAR-T cells in solid tumors.

A bibliometric and knowledge-map analysis is used to explore hotspots' evolution and development trends in the CAR-T cell field. By looking for research hotspots and new topics, we can provide new clues and ideas for researchers in this field. The articles and reviews regarding CAR-T cells were retrieved and obtained from the Web of Science Core Collection (WOSCC) on October 28th, 2021. CtieSpace [version 5.8.R3 (64-bit)] and VOSviewer (version 1.6.17) were used to conduct the bibliometric and knowledge-map analysis. 660 authors from 488 institutions in 104 countries/regions published 6,867 papers in 1,212 academic journals. The United States was absolutely in the leading position in this research field. The institution that contributed the most publications was the University of Pennsylvania. Carl H June published the most articles, while Shannon L Maude had the most co-citations. However, there was little cooperation between countries. After 2012, cooperation among various institutions was also small. The journals that published the most CAR-T cell-related papers were and . Nevertheless, and were the most commonly co-cited journals. The most influential research hotspots were the research of CAR-T cells in hematological malignancies, the related research of cytokine release syndrome (CRS), CD19, and the anti-tumor activity and efficacy of CAR-T cells. The latest hotspots and topics included the study of CAR-T cells in solid tumors, universal CAR-T cells, CAR-NK cells, CD22, and anakinra (the IL-1 receptor antagonist). The research of CAR-T cells in solid tumors was a rapidly developing hot field. Emerging topics in this field mainly included the study of CAR-T cells in glioblastoma (related targets: IL13Rα2, EGFRvIII, and HER2), neuroblastoma (related target: GD2), sarcoma (related target: HER2), and pancreatic cancer (related target: mesothelin), especially glioblastoma. As an anti-tumor therapy with great potential and clinical application prospects, CAR-T cell therapy is still in a stage of rapid development. The related field of CAR-T cells will remain a research hotspot in the future.

Background When the health administration department re-assumed the responsibilities for occupational safety and health supervision and management in 2018, the Chinese government allocated special funds annually to the Centers for Disease Control and Prevention (CDCs) at all levels to enhance their capacity to monitor occupational diseases and hazardous factors. Thus, the CDCs’ technical support capacity for occupational disease surveillance and assessment (TSCODSA) has garnered increasing attention. Against this backdrop, we aimed to develop a comprehensive evaluation model to assess the CDCs’ TSCODSA, taking the municipal and county-level CDCs in Sichuan Province as an example. Methods In 2023, a survey was conducted on the municipal and county-level CDCs across 21 cities (including three autonomous prefectures) in Sichuan Province. Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was used to evaluate the TSCODSA of these CDCs, combined with the Rank Sum Ratio (RSR) method for classification. The obstacle degree model was used to analyze the primary factors influencing their capacity. Results Among the 21 cities of Sichuan Province, only 4 cities (19.05%) had a “good” rating for the TSCODSA, while the remaining 17 cities (80.95%) were classified as either “medium” or “poor”. Cities with “good” ratings for the TSCODSA of CDCs were predominantly concentrated in the Chengdu Plain Economic Zone, while cities with “poor” ratings were mainly concentrated in the Northeast Sichuan Economic Zone. Obstacle degree analysis revealed that core capacity building and human resources constitute significant barriers impacting the capacity levels of CDCs across cities. Conclusion The overall TSCODSA level of CDCs in Sichuan Province is relatively low, with pronounced disparities in support capability across different economic zones, indicating imbalanced development. The evaluation system proposed in this study effectively reflects the level of TSCODSA of CDCs in various cities of Sichuan Province.

Accurate prediction of lymph node metastasis (LNM) is critical for the staging and treatment planning of gastric cancer (GC). This study aimed to develop and validate a multi-module prediction model that integrates clinicopathological features and hematological biomarkers to enhance the preoperative assessment of GC-LNM. A retrospective analysis was conducted on GC patients treated at a single medical center. Clinical variables were categorized into five modules: basic demographic information, tumor characteristics, inflammation-related indicators, coagulation parameters, and nutritional-immune markers. An XGBoost machine learning model was constructed using 19 selected features, and model interpretability was assessed using SHapley Additive exPlanations (SHAP). Model performance was evaluated using the area under the curve (AUC), sensitivity, and specificity across training (80%) and testing (20%) cohorts. Among 1580 patients included in the analysis, 984 (62.3%) had confirmed LNM. The optimized XGBoost model demonstrated excellent predictive performance, achieving an AUC of 0.883 (95% CI 0.864–0.902) in the training set and 0.815 (95% CI 0.767–0.863) in the testing set. SHAP analysis revealed distinct biomarker contribution patterns across different T-stages, Lauren classifications, and histological differentiation grades. In multivariate logistic regression, T4 stage (odd ratio [OR] = 16.091, P  < 0.001) and poorly differentiated tumors (OR = 5.891, P  < 0.05) were confirmed as independent risk factors for LNM. This interpretable, multi-module machine learning model offers a robust and convenient tool for predicting LNM in GC, facilitating precise risk stratification and individualized treatment decision-making. The observed heterogeneity in biomarker predictive patterns across pathological subtypes also provides novel insights into metastatic mechanisms and supports the development of personalized therapeutic strategies.

Background Both incidence and mortality of gastric cancer in Gansu rank first in china, this study aimed to describe the recent prevalence of gastric cancer and explore the social and environmental determinants of gastric cancer in Gansu Province. Methods The incidence of gastric cancer in each city of Gansu Province was calculated by utilizing clinical data from patients with gastric cancer (2013–2021) sourced from the medical big data platform of the Gansu Province Health Commission, and demographic data provided by the Gansu Province Bureau of Statistics. Subsequently, we conducted joinpoint regression analysis, spatial auto-correlation analysis, space–time scanning analysis, as well as an exploration into the correlation between social and environmental factors and GC incidence in Gansu Province with Joinpoint_5.0, ArcGIS_10.8, GeoDa, SaTScan TM _10.1.1 and GeoDetector_2018. Results A total of 75,522 cases of gastric cancer were included in this study. Our findings suggested a significant upward trend in the incidence of gastric cancer over the past nine years. Notably, Wuwei, Zhangye and Jinchang had the highest incidence rates while Longnan, Qingyang and Jiayuguan had the lowest. In spatial analysis, we have identified significant high-high cluster areas and delineated two high-risk regions as well as one low-risk region for gastric cancer in Gansu. Furthermore, our findings suggested that several social and environmental determinants such as medical resource allocation, regional economic development and climate conditions exerted significant influence on the incidence of gastric cancer. Conclusions Gastric cancer remains an enormous threat to people in Gansu Province, the significant risk areas, social and environmental determinants were observed in this study, which may improve our understanding of gastric cancer epidemiology and help guide public health interventions in Gansu Province.

In recent years, chimeric antigen receptor T cells (CAR-T cells) have been faced with the problems of weak proliferation and poor persistence in the treatment of some malignancies. Researchers have been trying to perfect the function of CAR-T by genetically modifying its structure. In addition to the participation of T cell receptor (TCR) and costimulatory signals, immune cytokines also exert a decisive role in the activation and proliferation of T cells. Therefore, genetic engineering strategies were used to generate cytokines to enhance tumor killing function of CAR-T cells. When CAR-T cells are in contact with target tumor tissue, the proliferation ability and persistence of T cells can be improved by structurally or inductively releasing immunoregulatory molecules to the tumor region. There are a large number of CAR-T cells studies on gene-edited cytokines, and the most common cytokines involved are interleukins (IL-7, IL-12, IL-15, IL-18, IL-21, IL-23). Methods for the construction of gene-edited interleukin CAR-T cells include co-expression of single interleukin, two interleukin, interleukin combined with other cytokines, interleukin receptors, interleukin subunits, and fusion inverted cytokine receptors (ICR). Preclinical and clinical trials have yielded positive results, and many more are under way. By reading a large number of literatures, we summarized the functional characteristics of some members of the interleukin family related to tumor immunotherapy, and described the research status of gene-edited interleukin CAR-T cells in the treatment of malignant tumors. The objective is to explore the optimized strategy of gene edited interleukin-CAR-T cell function.

According to the WHO, the number of mental disorder patients, especially depression patients, has overgrown and become a leading contributor to the global burden of disease. With the rising of tools such as artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and recordings of spoken language data from clinically depressed patients and matching normal controls, who were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes data collected using a traditional 128-electrodes mounted elastic cap and a wearable 3-electrode EEG collector for pervasive computing applications. The 128-electrodes EEG signals of 53 participants were recorded as both in resting state and while doing the Dot probe tasks; the 3-electrode EEG signals of 55 participants were recorded in resting-state; the audio data of 52 participants were recorded during interviewing, reading, and picture description.Measurement(s)Human Brainwave • spoken languageTechnology Type(s)EEG collector • audio recorderSample Characteristic - OrganismHomo SapiensSample Characteristic - LocationChina