Hepatocellular carcinoma (HCC) is a highly heterogeneous kind of malignant tumor with a high recurrence rate and low five-year survival rate, which has become one of the major public health issues in China. Currently, HCC is the only solid tumor that can be solely diagnosed based on epidemiological history and typical imaging features without preoperative pathological confirmation. The paradigm for HCC imaging diagnosis has shifted in recent years from anatomy to function, from macroscopic to microscopic, and from diagnosis to prediction in the context of precision medicine, making it possible to study the microscopic processes such as HCC genes and their metabolic laws from the perspective of qualitative and quantitative imaging, thereby providing more accurate biological and imaging information for elucidating the occurrence, development, and clinical treatment decisions of HCC.This paper reviews the research progress of HCC imaging in recent years, demonstrating the rapid horizontal development and enormous potential of imaging in the vertical follow-up of HCC precision diagnosis and treatment. Simultaneously, it also puts forward the shortcomings of current HCC imaging research and looks forward to future development directions in order to be more accurately used in clinical decision support systems.

Uridine diphosphate glycosyltransferase(UGT) is a highly conserved protein in plants, which usually functions in secondary metabolic pathways. This study used the Hidden Markov Model(HMM) to screen out members of UGT gene family in the whole genome of Dendrobium officinale, and 44 UGT genes were identified. Bioinformatics was used to analyze the structure, phylogeny, and promoter region components of D. officinale genes. The results showed that UGT gene family could be divided into four subfamilies, and UGT gene structure was relatively conserved in each subfamily, with nine conserved domains. The upstream promoter region of UGT gene contained a variety of cis-acting elements related to plant hormones and environmental factors, indicating that UGT gene expression may be induced by plant hormones and external environmental factors. UGT gene expression in different tissues of D. officinale was compared, and UGT gene expression was found in all parts of D. officinale. It was speculated that UGT gene played an important role in many tissues of D. officinale. Through transcriptome analysis of D. officinale mycorrhizal symbiosis environment, low temperature stress, and phosphorus deficiency stress, this study found that only one gene was up-regulated in all three conditions. The results of this study can help understand the functions of UGT gene family in Orchidaceae plants and provide a basis for further study on the molecular regulation mechanism of polysaccharide metabolism pathway in D. officinale.
Dendrobium/genetics* ; Plant Growth Regulators ; Glycosyltransferases/metabolism* ; Gene Expression Profiling ; Mycorrhizae ; Phylogeny ; Plant Proteins/metabolism*

This study aimed to identify subtypes of genomic variants associated with the efficacy of immune checkpoint inhibitors (ICIs) by conducting systematic literature search in electronic databases up to May 31, 2021. The main outcomes including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and durable clinical benefit (DCB) were correlated with tumor genomic features. A total of 1546 lung cancer patients with available genomic variation data were included from 14 studies. The Kirsten rat sarcoma viral oncogene homolog G12C (KRAS^G12C) mutation combined with tumor protein P53 (TP53) mutation revealed the promising efficacy of ICI therapy in these patients. Furthermore, patients with epidermal growth factor receptor (EGFR) classical activating mutations (including EGFR^L858R and EGFR^Δ19) exhibited worse outcomes to ICIs in OS (adjusted hazard ratio (HR), 1.40; 95% confidence interval (CI), 1.01‍‒‍1.95; P=0.0411) and PFS (adjusted HR, 1.98; 95% CI, 1.49‍‒‍2.63; P<0.0001), while classical activating mutations with EGFR^T790M showed no difference compared to classical activating mutations without EGFR^T790M in OS (adjusted HR, 0.96; 95% CI, 0.48‍‒‍1.94; P=0.9157) or PFS (adjusted HR, 0.72; 95% CI, 0.39‍‒‍1.35; P=0.3050). Of note, for patients harboring the Usher syndrome type-2A(USH2A) missense mutation, correspondingly better outcomes were observed in OS (adjusted HR, 0.52; 95% CI, 0.32‍‒‍0.82; P=0.0077), PFS (adjusted HR, 0.51; 95% CI, 0.38‍‒‍0.69; P<0.0001), DCB (adjusted odds ratio (OR), 4.74; 95% CI, 2.75‍‒‍8.17; P<0.0001), and ORR (adjusted OR, 3.45; 95% CI, 1.88‍‒‍6.33; P<0.0001). Our findings indicated that, USH2A missense mutations and the KRAS^G12Cmutation combined with TP53 mutation were associated with better efficacy and survival outcomes, but EGFR classical mutations irrespective of combination with EGFR^T790M showed the opposite role in the ICI therapy among lung cancer patients. Our findings might guide the selection of precise targets for effective immunotherapy in the clinic.
Humans ; Carcinoma, Non-Small-Cell Lung/genetics* ; ErbB Receptors/genetics* ; Extracellular Matrix Proteins/genetics* ; Immune Checkpoint Inhibitors/therapeutic use* ; Lung Neoplasms/genetics* ; Mutation ; Protein Kinase Inhibitors/therapeutic use* ; Proto-Oncogene Proteins p21(ras)/genetics* ; Treatment Outcome

Glucose transporter 1(GLUT1)overexpression in tumor cells is a potential target for drug therapy,but few studies have reported screening GLUT1 inhibitors from natural or synthetic compounds.With cur-rent analysis techniques,it is difficult to accurately monitor the GLUT1 inhibitory effect of drug molecules in real-time.We developed a cell membrane-based glucose sensor(CMGS)that integrated a hydrogel electrode with tumor cell membranes to monitor GLUT1 transmembrane transport and screen for GLUT1 inhibitors in traditional Chinese medicines(TCMs).CMGS is compatible with cell membranes of various origins,including different types of tumors and cell lines with GLUT1 expression knocked down by small interfering RNA or small molecules.Based on CMGS continuous monitoring technique,we inves-tigated the glucose transport kinetics of cell membranes with varying levels of GLUT1 expression.We used CMGS to determine the GLUT1-inhibitory effects of drug monomers with similar structures from Scutellaria baicalensis and catechins families.Results were consistent with those of the cellular glucose uptake test and molecular-docking simulation.CMGS could accurately screen drug molecules in TCMs that inhibit GLUT1,providing a new strategy for studying transmembrane protein-receptor interactions.

Objective:To investigate the feasibility and effectiveness of the blended teaching model for diagnostic radiology based on BOPPPS classroom reconstruction, i.e., bridge-in, objective, pre-assessment, participatory-learning, post-assessment, and summary.Methods:The undergraduate students in the classes of 2017 and 2018 in Department of Medical Imaging were selected as research subjects. The students in the class of 2018 were established as observation group and received the innovative blended teaching model based on BOPPPS classroom reconstruction, and those in the class of 2017 were established as control group and received teaching with traditional theoretical lectures. At the end of the course, 80 students were randomly selected from the observation group and the control group for performance analysis and teaching evaluation. SPSS 26.0 was used to perform the t-test. Results:The observation group had a total score of (82.66±6.18), while the control group had a total score of (76.47±5.42), and compared with the control group, the observation group had significantly higher scores of homework score, course discussion, and final examination ( P<0.05). Compared with the control group, the observation group had significantly higher scores of "understanding of the basic knowledge of imaging", "improvement of comprehensive diagnostic thinking ability", "stimulating the interest in learning and expanding horizons", and "cultivating clinical competence" in the self-evaluation survey ( P<0.05). Conclusion:The blended teaching model based on BOPPPS classroom reconstruction is suitable for the teaching of radiology diagnostics. It not only enriches teaching means and methods and enhances classroom participation and interaction, but also expands teaching space and teaching content.

This study aimed to identify subtypes of genomic variants associated with the efficacy of immune checkpoint inhibitors (ICIs) by conducting systematic literature search in electronic databases up to May 31, 2021. The main outcomes including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and durable clinical benefit (DCB) were correlated with tumor genomic features. A total of 1546 lung cancer patients with available genomic variation data were included from 14 studies. The Kirsten rat sarcoma viral oncogene homolog G12C (KRASG12C) mutation combined with tumor protein P53 (TP53) mutation revealed the promising efficacy of ICI therapy in these patients. Furthermore, patients with epidermal growth factor receptor (EGFR) classical activating mutations (including EGFRL858R and EGFRΔ19) exhibited worse outcomes to ICIs in OS (adjusted hazard ratio (HR), 1.40; 95％ confidence interval (CI), 1.01?1.95; P=0.0411) and PFS (adjusted HR, 1.98; 95％ CI, 1.49?2.63; P<0.0001), while classical activating mutations with EGFRT790M showed no difference compared to classical activating mutations without EGFRT790M in OS (adjusted HR, 0.96; 95％ CI, 0.48?1.94; P=0.9157) or PFS (adjusted HR, 0.72; 95％ CI, 0.39?1.35; P=0.3050). Of note, for patients harboring the Usher syndrome type-2A (USH2A) missense mutation, correspondingly better outcomes were observed in OS (adjusted HR, 0.52; 95％ CI, 0.32?0.82; P=0.0077), PFS (adjusted HR, 0.51; 95％ CI, 0.38?0.69; P<0.0001), DCB (adjusted odds ratio (OR), 4.74; 95％ CI, 2.75?8.17; P<0.0001), and ORR (adjusted OR, 3.45; 95％ CI, 1.88?6.33; P<0.0001). Our findings indicated that, USH2A missense mutations and the KRASG12C mutation combined with TP53 mutation were associated with better efficacy and survival outcomes, but EGFR classical mutations irrespective of combination with EGFRT790M showed the opposite role in the ICI therapy among lung cancer patients. Our findings might guide the selection of precise targets for effective immunotherapy in the clinic.

Air pollution has always been an important factor threatening population health, and with the acceleration of urbanization in China, the adverse health effects associated with air pollution is becoming more and more serious. Numerous scientific studies have shown that chemical components of fine particulate matter are closely related to human health damage. This paper elaborated reported human health outcomes of PM_2.5 chemical components, including fatality, morbidity, reproduction & development, and physiological indexes or biomarkers, reviewed the research progress of PM_2.5 chemical constituents on human health in China, and summarized the deficiencies of current research, aiming to provide useful clues for future relevant studies.

Air pollution is a major environmental threat to human health, and skin, as the largest organ of the human body, is a major exposure route of air pollutants, so the correlations between air pollutants and skin diseases are noteworthy to study. This paper reviewed the acute effects of air pollutants on the risks of dermatosis outpatient and emergency visits at home and abroad, especially on dermatitis, eczema, urticaria, acne, psoriasis, and other skin diseases with high prevalence rates and heavy disease burdens. The effects of air pollutants on skin diseases are affected by exposure characteristics of air pollutants (such as composition, concentration, and exposure time), environmental factors (such as temperature, humidity, and ultraviolet), and population characteristics. In view of insufficient evidence on the long-term effects of air pollutants on skin diseases and the interaction of environmental factors, future research directions were prospected, aiming to provide new ideas for further study on the effects of air pollutants on skin diseases and the formulation of relevant prevention and control strategies.

Since the outbreak of coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) discovered in December 2019, the disease has emerged as a global pandemic (Shi et al., 2020; World Health Organization, 2020). Several studies have shown a higher incidence of COVID-19, as well as related poor outcomes in patients with malignancies as compared with those without them (Liang et al., 2020; Tian et al., 2020). The impact of cancer on COVID-19 may be attri‑buted to the use of antitumor treatments that may disturb the host response to SARS-CoV-2 infection (Wang et al., 2020), while the current studies on this topic have drawn controversial conclusions. Some implied that anticancer treatments might elevate the risk of death (García-Suárez et al., 2020; Liu et al., 2020). On the contrary, others pointed out that this association is not significant (Brar et al., 2020; Lee et al., 2020a). Although previous systematic reviews have investigated this important issue (Wang and Huang, 2020), the heterogeneity of findings is obvious and the general conclusion has remained unclear. Considering this ambiguity, it is difficult for clinicians to make therapeutic decisions when facing patients with both cancer and COVID-19; therefore, a high-quality and accurate evaluation of the impact of anticancer treatments on COVID-19 patients is necessary. Accordingly, we conducted a pooled analysis with the original data of each patient for the first time to provide a comprehensive perspective into the association between anticancer regimens and the outcomes of cancer patients with COVID-19.
Adult ; Aged ; Aged, 80 and over ; COVID-19/complications* ; Female ; Humans ; Male ; Middle Aged ; Neoplasms/therapy* ; SARS-CoV-2

Objective:To explore the risk factors for early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH), and construct a clinical-radiomics combined model to predict HE after sICH.Methods:From April 2014 to September 2020, 339 patients with sICH who underwent plain CT scans in Radiology Department of our hospital were recruited. Patients were divided into HE group and non-HE group according to whether HE occurred (HE was defined as an increase in hematoma volume>33% or 6 mL on the follow-up CT within 24 h). The clinical data of non-HE group and HE group were compared, and multivariate Logistic regression analysis was used to detect independent risk factors for HE. The radiomics features were extracted from the regions of interest of the hematoma in the first CT scan images; the optimal radiomics features were selected using least absolute shrinkage and selection operator (LASSO) regression model and 10-fold cross-validation method, and then, the radiomics scores (R-score) were calculated; the risk factors for HE (clinical data) and R-score (radiomics data) were used to construct the clinical model, R-score model, and clinical-radiomics combined model; receiver operating characteristic (ROC) curve was performed to evaluate the prediction performance of clinical model, R-score model, and clinical-radiomics combined model; the best model was visualized as a nomogram and a calibration curve was drawn to evaluate the prediction accuracy of this model.Results:As compared with patients in the non-HE group, patients in the HE group had shorter time from sICH onset to first CT, higher percentage of patients with diabetes, lower platelet count, lower Glasgow Coma Scale (GCS) scores, and larger baseline hematoma volume in CT image, with significant differences ( P<0.05). Multivariate Logistic regression analysis showed that baseline hematoma volume ( OR=1.015, 95%CI: 1.000-1.030, P=0.046), GCS scores ( OR=0.914, 95%CI: 0.839-0.995, P=0.039), time from sICH onset to first CT ( OR=0.855, 95%CI: 0.741-0.987, P=0.032), and diabetes ( OR=0.522, 95%CI: 0.311-0.875, P=0.014) were independent risk factors for HE. By using LASSO regression and 10-fold cross-validation method, 20 optimal radiomics features were finally selected. The area under ROC curve of clinical model, R-score model, and clinical-radiomics combined model were 0.650, 0.860, and 0.870, respectively. The calibration curve showed that the prediction accuracy of clinical-radiomics combined model in early HE had good consistency with the actual occurrence probability. Conclusion:The clinical-radiomics combined model could effectively predict early HE with good calibration, which is helpful in individualized clinical assessment of risk of early HE in SICH patients.