Hepatic recruitment of myeloid-derived suppressor cells upon liver injury promotes both liver regeneration and fibrosis.

BACKGROUND: The liver regeneration is a highly complicated process depending on the close cooperations between the hepatocytes and non-parenchymal cells involving various inflammatory cells. Here, we explored the role of myeloid-derived suppressor cells (MDSCs) in the processes of liver regeneration and liver fibrosis after liver injury. METHODS: We established four liver injury models of mice including CCl4-induced liver injury model, bile duct ligation (BDL) model, concanavalin A (Con A)-induced hepatitis model, and lipopolysaccharide (LPS)-induced hepatitis model. The intrahepatic levels of MDSCs (CD11b+Gr-1+) after the liver injury were detected by flow cytometry. The effects of MDSCs on liver tissues were analyzed in the transwell co-culture system, in which the MDSCs cytokines including IL-10, VEGF, and TGF-ß were measured by ELISA assay and followed by being blocked with specific antibodies. RESULTS: The intrahepatic infiltrations of MDSCs with surface marker of CD11b+Gr-1+ remarkably increased after the establishment of four liver injury models. The blood served as the primary reservoir for hepatic recruitment of MDSCs during the liver injury, while the bone marrow appeared play a compensated role in increasing the number of MDSCs at the late stage of the inflammation. The recruited MDSCs in injured liver were mainly the M-MDSCs (CD11b+Ly6G-Ly6Chigh) featured by high expression levels of cytokines including IL-10, VEGF, and TGF-ß. Co-culture of the liver tissues with MDSCs significantly promoted the proliferation of both hepatocytes and hepatic stellate cells (HSCs). CONCLUSIONS: The dramatically and quickly infiltrated CD11b+Gr-1+ MDSCs in injured liver not only exerted pro-proliferative effects on hepatocytes, but also accounted for the activation of profibrotic HSCs.

Research progress of human key DNA and RNA methylation-related enzymes assay.

Gene methylation-related enzymes (GMREs) are disfunction and aberrantly expressed in a variety of cancers, such as lung, gastric, and pancreatic cancers and have important implications for human health. Therefore，it is critical for early diagnosis and therapy of tumor to develop strategies that allow rapid and sensitive quantitative and qualitative detection of GMREs. With the development of modern analytical techniques and the application of various biosensors, there are numerous methods have been developed for analysis of GMREs. Therefore, this paper provides a systematic review of the strategies for level and activity assay of various GMREs including methyltransferases and demethylase. The detection methods mainly involve immunohistochemistry, colorimetry, fluorescence, chemiluminescence, electrochemistry, etc. Then, this review also addresses the coordinated role of various detection probes, novel nanomaterials, and signal amplification methods. The aim is to highlight potential challenges in the present field, to expand the analytical application of GMREs detection strategies, and to meet the urgent need for future disease diagnosis and intervention.

Vitamin D May Play a Vital Role in Alleviating Type 2 Diabetes Mellitus by Modulating the Ferroptosis Signaling Pathway.

Ferroptosis is an iron-dependent death mode mediated by the aggregation of lipid peroxides and lipid-reactive oxygen species. It is characterized by iron-dependent lipid peroxide accumulation accompanied by oxidoreductase deficiency. Pancreatic beta cell dysfunction and insulin resistance are two major causes of type 2 diabetes mellitus (T2DM). Iron accumulation and metabolism may play a role in the development of T2DM. The molecular mechanism of ß cell apoptosis and iron death in T2DM were reviewed. In addition, we discuss recent insights on the relationship between the trace element iron and apoptosis of ß cells in T2DM.

Transcranial Acoustic Metamaterial Parameters Inverse Designed by Neural Networks.

Objective: The objective of this work is to investigate the mapping relationship between transcranial ultrasound image quality and transcranial acoustic metamaterial parameters using inverse design methods. Impact Statement: Our study provides insights into inverse design methods and opens the route to guide the preparation of transcranial acoustic metamaterials. Introduction: The development of acoustic metamaterials has enabled the exploration of cranial ultrasound, and it has been found that the influence of the skull distortion layer on acoustic waves can be effectively eliminated by adjusting the parameters of the acoustic metamaterial. However, the interaction mechanism between transcranial ultrasound images and transcranial acoustic metamaterial parameters is unknown. Methods: In this study, 1,456 transcranial ultrasound image datasets were used to explore the mapping relationship between the quality of transcranial ultrasound images and the parameters of transcranial acoustic metamaterials. Results: The multioutput parameter prediction model of transcranial metamaterials based on deep back-propagation neural network was built, and metamaterial parameters under transcranial image evaluation indices are predicted using the prediction model. Conclusion: This inverse big data design approach paves the way for guiding the preparation of transcranial metamaterials.

Real-world efficacy and safety of pyrotinib in patients with HER2-positive metastatic breast cancer: A prospective real-world study.

Background: Pyrotinib, a novel irreversible EGFR/HER2 dual tyrosine kinase inhibitor, shows encouraging anticancer activity and acceptable tolerability in multiple phase II and phase III randomized clinical trials, but the real-world data of pyrotinib, especially the outcomes in HER2-positive metastatic breast cancer, have been rarely reported. Here, we evaluated the treatment outcomes of pyrotinib in real-world practice in patients with HER2-positive metastatic breast cancer (MBC). Methods: This was a prospective, real-world, observational cohort study. Through the Breast Cancer Information Management System, HER-2 positive MBC patients treated with pyrotinib between 2017/06 and 2020/09 were included. Provider-reported objective response rate, progression-free survival (PFS), and overall survival (OS) were considered in the assessment of treatment outcomes. Tumor responses to pyrotinib treatment were calculated using RECIST 1.1. Adverse events were evaluated using clinical records. Results: The trial involved 113 individuals who were receiving pyrotinib treatment, with an average age of 51 years. Complete response, partial response and stable disease were observed in 9 (8.0%), 66 (58.4%), and 17 (15.0%) patients, respectively, while progressive disease was recorded in 20 (17.7%) patients. After a median follow-up of 17.2 months, the median PFS was 14.1. The most common adverse events of any grade were diarrhea (87.6%), vomiting (31.9%), and palmar-plantar erythrodysesthesia (26.6%). Among the patients with brain metastases, the median PFS and OS were 15.2 and 19.8 months, respectively. In addition, pyrotinib has similar efficacy in various subtypes of HER2-positive MBC patients, as shown by the lack of a significant difference of PFS and OS among pyrotinib-treated patients with or without brain metastases, or patients using pyrotinib as first-line, second-line, third-line or beyond therapies. Conclusion: Our real-world results demonstrated equivalent clinical efficacy in HER-2 positive MBC patients compared to phase II and phase III clinical trials with pyrotinib, and promising outcomes in patients with brain metastases.

Comparative and Functional Analysis of miRNAs and mRNAs Involved in Muscle Fiber Hypertrophy of Juvenile and Adult Goats.

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate several pathway intermediates and affect the skeletal muscle development in mice, pigs, sheep, and cattle. However, to date, only a small number of miRNAs have been reported in the muscle development of goats. In this report, the longissimus dorsi transcripts of one- and ten-month-old goats were analyzed by sequencing RNAs and miRNAs. The results showed that the ten-month-old Longlin goats had 327 up- and 419 down-regulated differentially expressed genes (DEGs) compared with the one-month-old. In addition, 20 co-up-regulated and 55 co-down-regulated miRNAs involved in the muscle fiber hypertrophy of goats were identified in ten-month-old Longlin and Nubian goats compared with one-month-old. Five miRNA-mRNA pairs (chi-let-7b-3p-MIRLET7A, chi-miR193b-3p-MMP14, chi-miR-355-5p-DGAT2, novel_128-LOC102178119, novel_140-SOD3) involved in the goat skeletal muscle development were identified by miRNA-mRNA negative correlation network analysis. Our results provided new insight into the functional roles of goat muscle-associated miRNAs, allowing a deeper understanding of the transformation of miRNA roles during mammalian muscle development.

[Application Value of Plasma vWF and ADAMTS-13 in Evaluating Postoprative Vascular Endothelial Injury and Prognosis in Children with VSD].

OBJECTIVE: To dynamically observe the levels and activities of von Willebrand factor (vWF) and ADAMTS-13 (a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13) in plasma of children with congenital ventricular septal defect (VSD) during perioperative period, and explore the value of plasma vWF antigen (vWF:Ag) and ADAMTS-13 activity (ADAMTS-13: AC) in evaluating vascular endothelial injury and prognosis in children with VSD. METHODS: In this cross-sectional study, a total of 74 children with VSD who underwent surgical treatment in TEDA International Cardiovascular Hospital from September 2018 to March 2019 were enrolled in the observation group. Among them, there were 28 cases of pure VSD, 32 cases of VSD combined with pulmonary hypertension, and 14 cases of VSD combined with valvular heart disease. 31 healthy children who underwent physical examination in Tianjin Children's Hospital during the same period were collected as the control group. The biochemical indexes of the children at admission were recorded. Peripheral plasma was collected at admission, postsurgery day 0 and day 1, respectively, and the levels of vWF activity (vWF:AC), vWF:Ag, ADAMTS-13 antigen (ADAMTS-13:Ag) and ADAMTS-13:AC were detected. RESULTS: The level of plasma vWF:Ag and vWF:AC in the observation group before surgery were significantly lower than those in the control group (P<0.001), and increased continuously, on postsurgery day 0 and day 1 (P<0.001). The level of ADAMTS-13:Ag in the observation group before surgery was significantly higher than that in the control group (P<0.001), which decreased significantly on postsurgery day 0 (P<0.001), and increased significantly on postsurgery day 1 compared with postsurgery day 0 (P=0.033). The level of ADAMTS-13:AC in the observation group before surgery was significantly lower than that in the control group (P=0.015), which decreased significantly on postsurgery day 0 (P=0.037), and increased on postsurgery day 1, but the difference was not statistically significant (P=0.051). The changes of vWF and ADAMTS-13 in the three subgroups were basically similar to the observation group. vWF: Ag/ADAMTS-13: AC ratio on postsurgery day 0 and day 1 had high diagnostic value in vascular endothelial injury (AUC=0.80, P<0.001; AUC=0.93, P<0.001). Preoperative vWF and ADAMTS-13 levels, and related baseline indicators were not correlated with postoperative infection, bleeding, thrombosis,etc. CONCLUSION: Preoperative vWF: Ag, vWF: AC and ADAMTS-13: AC levels in children with VSD are low, while the level of ADAMTS-13: Ag is high. After surgery, the levels of vWF: Ag and vWF: AC are increased and the level of ADAMTS-13: Ag is decreased. The postoperative vWF: Ag/ADAMTS-13: AC ratio shows high diagnostic value in evaluating vascular endothelial injury. There is no correlation between preoperative vWF and ADAMTS-13 levels with perioperative clinical events.

The mediating role of specific coping styles in the relationship between perceived social support and depressive symptoms in adolescents.

BACKGROUND: Depressive symptoms are one of the most common mental health problems in adolescence, and the relationship between perceived social support and depressive symptoms has been well-studied. However, little research has been conducted on the mediating role of specific coping styles in the relationship. Therefore, the primary purpose of this study was to examine the mediating role of specific coping styles in perceived social support and depressive symptoms in adolescents. METHODS: A questionnaire was administered to 3887 Chinese junior and senior high school adolescents (mean age = 15.72 years, SD = 1.43) using a multistage stratified and cluster sampling method. The PROCESS model 4 was used to conduct a multiple mediation analysis. RESULTS: Problem solving, seeking help, venting, fantasy and endurance mediated the relationship between internal family support or external family support and depressive symptoms. The problem solving coping style mediated the largest amount of effect, accounting for 22.32 % and 19.05 %, respectively. LIMITATIONS: This study used a cross-sectional survey and self-reported information, which may be the main research limitation. CONCLUSIONS: The findings suggest that higher social support not only directly reduces the likelihood of adolescent depression, but also influences depressive symptoms through specific coping styles. This may help further develop targeted prevention and interventions for at-risk adolescents for specific coping styles.

Towards reliable head and neck cancers locoregional recurrence prediction using delta-radiomics and learning with rejection option.

PURPOSE: A reliable locoregional recurrence (LRR) prediction model is important for the personalized management of head and neck cancers (HNC) patients who received radiotherapy. This work aims to develop a delta-radiomics feature-based multi-classifier, multi-objective, and multi-modality (Delta-mCOM) model for post-treatment HNC LRR prediction. Furthermore, we aim to adopt a learning with rejection option (LRO) strategy to boost the reliability of Delta-mCOM model by rejecting prediction for samples with high prediction uncertainties. METHODS: In this retrospective study, we collected PET/CT image and clinical data from 224 HNC patients who received radiotherapy (RT) at our institution. We calculated the differences between radiomics features extracted from PET/CT images acquired before and after radiotherapy and used them in conjunction with pre-treatment radiomics features as the input features. Using clinical parameters, PET radiomics features, and CT radiomics features, we built and optimized three separate single-modality models. We used multiple classifiers for model construction and employed sensitivity and specificity simultaneously as the training objectives for each of them. Then, for testing samples, we fused the output probabilities from all these single-modality models to obtain the final output probabilities of the Delta-mCOM model. In the LRO strategy, we estimated the epistemic and aleatoric uncertainties when predicting with a trained Delta-mCOM model and identified patients associated with prediction of higher reliability (low uncertainty estimates). The epistemic and aleatoric uncertainties were estimated using an AutoEncoder-style anomaly detection model and test-time augmentation (TTA) with predictions made from the Delta-mCOM model, respectively. Predictions with higher epistemic uncertainty or higher aleatoric uncertainty than given thresholds were deemed unreliable, and they were rejected before providing a final prediction. In this study, different thresholds corresponding to different low-reliability prediction rejection ratios were applied. Their values are based on the estimated epistemic and aleatoric uncertainties distribution of the validation data. RESULTS: The Delta-mCOM model performed significantly better than the single-modality models, whether trained with pre-, post-treatment radiomics features or concatenated BaseLine and Delta-Radiomics Features (BL-DRFs). It was numerically superior to the PET and CT fused BL-DRF model (nonstatistically significant). Using the LRO strategy for the Delta-mCOM model, most of the evaluation metrics improved as the rejection ratio increased from 0% to around 25%. Utilizing both epistemic and aleatoric uncertainty for rejection yielded nonstatistically significant improved metrics compared to each alone at approximately a 25% rejection ratio. Metrics were significantly better than the no-rejection method when the reject ratio was higher than 50%. CONCLUSIONS: The inclusion of the delta-radiomics feature improved the accuracy of HNC LRR prediction, and the proposed Delta-mCOM model can give more reliable predictions by rejecting predictions for samples of high uncertainty using the LRO strategy.

Verification of the Mandarin Chinese version of Advance Care Planning Engagement Survey Scale in community-dwelling older people.

BACKGROUND: Advance care planning (ACP) has become increasingly critical for older people. The Advance Care Planning Engagement Survey (ACPES) develops targeted interventions for older people by measuring ACP-related behaviours, while previous studies focus only on advance directives. Moreover, while ACPES has English and Dutch versions, it does not yet have a Mandarin Chinese version (ACPES-MC) that can be used for Chinese populations. OBJECTIVES: To translate the ACPES into Mandarin Chinese and test its reliability and validity in community-dwelling older people with chronic diseases. METHODS: The English version of the ACPES was translated into Mandarin Chinese using Functional Assessment of Chronic Illness Therapy. Four communities were recruited in central China (N = 450) by convenience sampling. Internal consistency and construct validity were used to evaluate the reliability and validity of the ACPES-MC. RESULTS: The ACPES-MC consists of 34 items across five domains, with good internal consistency (0.817), with each dimension ranging from 0.606 to 0.881; exploratory factor analysis was distributed to four different factors and the total variance explained was 63.537%; and confirmatory factor analysis results showed that χ2  = 3791.131 (p < .001), χ2 /df = 1.106, CFI = 0.980, IFI = 0.980, NFI = 0.827 and RMR = 0.027, indicating a good model fit to previous factor structures. CONCLUSIONS: The ACPES-MC is an effective and reliable tool that can measure the ACP-related behaviour stage of community-dwelling older people and evaluate the effect of ACP intervention. IMPLICATIONS FOR PRACTICE: The ACPES-MC can be used in healthcare to identify potential ACP-related behaviours in community-dwelling older people with chronic diseases, including native and ethnic Chinese, evaluate their behaviour change stages and promote the application of ACP.

Predicting local persistence/recurrence after radiation therapy for head and neck cancer from PET/CT using a multi-objective, multi-classifier radiomics model.

Objectives: Accurate identifying head and neck squamous cell cancer (HNSCC) patients at high risk of local persistence/recurrence (P/R) is of importance for personalized patient management. Here we developed a multi-objective, multi-classifier radiomics model for early HNSCC local P/R prediction based on post-treatment PET/CT scans and clinical data. Materials and methods: We retrospectively identified 328 individuals (69 patients have local P/R) with HNSCC treated with definitive radiation therapy at our institution. The median follow-up from treatment completion to the first surveillance PET/CT imaging was 114 days (range: 82-159 days). Post-treatment PET/CT scans were reviewed and contoured for all patients. For each imaging modality, we extracted 257 radiomic features to build a multi-objective radiomics model with sensitivity, specificity, and feature sparsity as objectives for model training. Multiple representative classifiers were combined to construct the predictive model. The output probabilities of models built with features from various modalities were fused together to make the final prediction. Results: We built and evaluated three single-modality models and two multi-modality models. The combination of PET, CT, and clinical data in the multi-objective, multi-classifier radiomics model trended towards the best prediction performance, with a sensitivity of 93%, specificity of 83%, accuracy of 85%, and AUC of 0.94. Conclusion: Our study demonstrates the feasibility of employing a multi-objective, multi-classifier radiomics model with PET/CT radiomic features and clinical data to predict outcomes for patients with HNSCC after radiation therapy. The proposed prediction model shows the potential to detect cancer local P/R early after radiation therapy.

Different nutrient compositions in diet and taking hypoglycemic drugs can modulate gut microbial flora.

The diet structure of diabetic patients is different from that of normal people. Diabetic patients also need to take hypoglycemic drugs to regulate blood sugar. Both dieting and drugs affect the gut microbiota of diabetic patients. In this letter, we discuss that different dietary patterns and the use of hypoglycemic agents may have an impact on changes in gut microbiota in diabetic patients.

CDC6 is a prognostic biomarker and correlated with immune infiltrates in glioma.

BACKGROUND: Cell division cycle 6 (CDC6) has been proven to be associated with the initiation and progression of human multiple tumors. However, it's role in glioma, which is ranked as one of the common primary malignant tumor in the central nervous system and is associated with high morbidity and mortality, is unclear. METHODS: In this study, we explored CDC6 gene expression level in pan-cancer. Furthermore, we focused on the relationships between CDC6 expression, its prognostic value, potential biological functions, and immune infiltrates in glioma patients. We also performed vitro experiments to assess the effect of CDC6 expression on proliferative, apoptotic, migrant and invasive abilities of glioma cells. RESULTS: As a result, CDC6 expression was upregulated in multiple types of cancer, including glioma. Moreover, high expression of CDC6 was significantly associated with age, IDH status, 1p/19q codeletion status, WHO grade and histological type in glioma (all p < 0.05). Meanwhile, high CDC6 expression was associated with poor overall survival (OS) in glioma patients, especially in different clinical subgroups. Furthermore, a univariate Cox analysis showed that high CDC6 expression was correlated with poor OS in glioma patients. Functional enrichment analysis indicated that CDC6 was mainly involved in pathways related to DNA transcription and cytokine activity, and Gene Set Enrichment Analysis (GSEA) revealed that MAPK pathway, P53 pathway and NF-κB pathway in cancer were differentially enriched in glioma patients with high CDC6 expression. Single-sample gene set enrichment analysis (ssGSEA) showed CDC6 expression in glioma was positively correlated with Th2 cells, Macrophages and Eosinophils, and negative correlations with plasmacytoid dendritic cells, CD8 T cells and NK CD56bright cells, suggesting its role in regulating tumor immunity. Finally, CCK8 assay, flow cytometry and transwell assays showed that silencing CDC6 could significantly inhibit proliferation, migration, invasion, and promoted apoptosis of U87 cells and U251 cells (p < 0.05). CONCLUSION: In conclusion, high CDC6 expression may serve as a promising biomarker for prognosis and correlated with immune infiltrates, presenting to be a potential immune therapy target in glioma.

Ultrasonic Methods for Brain Imaging: Techniques and Implications.

Brain imaging technology is widely used in the diagnosis of brain diseases. Computed tomography and magnetic resonance imaging are the most common imaging modalities used for clinical brain imaging, whereas ultrasound is rarely used because the skull substantially reduces the incident energy of ultrasonic waves to levels too low for imaging. However, remarkable developments of novel technologies in ultrasound brain imaging have been achieved recently, including Doppler-based imaging, contrast agent imaging, ultrasound elastography, and phase compensation imaging. Doppler-based imaging, including ultrafast Doppler imaging and functional ultrasound, is able to obtain reliable cerebral blood volume changes and has the best penetration depth and a better spatiotemporal resolution. Contrast agent brain imaging, including ultrasound localization microscopy, can obtain super spatial resolution vasculature maps over a large region within a few minutes of acquisition and reconstruction time. Ultrasound elastography reflects the stiffness of brain tissues. Phase correction imaging, such as time reversal mirror and spatiotemporal inverse filter, aims at focusing smoothly in the skull. These methods have been widely performed on animal models, newborn children, and adults in preclinical studies, with results demonstrating great potential in the diagnosis and treatment of brain diseases. This review discusses the ultrasound methods developed in recent years for brain imaging and highlights the promising future they hold.

Advance Care Planning Engagement Among Family Members of Community-Dwelling Elderly Patients With Chronic Diseases in China: A Mixed-Methods Study.

In China, traditional culture advocates family consensus, and the advance care planning (ACP) engagement of family members is crucial to the implementation of ACP. However, there is still a lack of research on family members' engagement in ACP in mainland China. This study investigated the ACP engagement of family members of community-dwelling elderly patients with chronic diseases and provided evidence for further ACP intervention research. We conducted a mixed-methods sequential explanatory study, 273 family members were surveyed, and semistructured interviews were conducted. Following that, 12 family members were selected after statistical analysis to supplement the quantitative results. The results showed that the ACP engagement of family members of elderly patients with chronic diseases in the community was low, but the self-efficacy was higher. The age of family members, severity, and duration of patients' diseases were the main influencing factors for family members' ACP engagement. Traditional cultural, clinical decision-making mode, lack of understanding of ACP, and factors within the family may impede family members' engagement. This study showed that family-centered ACP practice has significant advantages in China and that future research should focus on the Chinese culture and medical system and highlight the role of families.

Parent-Child Discrepancies in Perceived Parent-Child Communication and Depressive Symptoms in Early Adolescents in China.

Although recent studies demonstrated that parent-child discrepancies in the perceived family processes were associated with children's developmental outcomes, few studies have addressed this issue in different types of families in mainland China. The present study investigated that how discrepancies in parents' and adolescents' perceptions of parent-adolescent communication were associated with early adolescent depressive symptoms in a nationally representative sample (N = 15,377) with 7010 father-adolescent dyads (adolescents: Mage = 14.24 years, SD = 1.25 years; 5960 adolescents from two-parent families, 443 adolescents from single-father families) and 8367 mother-adolescent dyads (adolescents: Mage = 14.02 years, SD = 1.18 years; 6670 adolescents from two-parent families, 1362 adolescents from single-mother families) in China. Adolescent respondents completed a measure of depressive symptoms and all informants reported on the perceived levels of parent-adolescent communication. Results indicated that adolescents reported parent-child communication more negatively than did their parents. Father-adolescent discrepancies were also greater in intact families than non-intact families. Polynomial regression analyses indicated that while there was a significant interactive effect of father-reported and adolescent-reported father-adolescent communication in Chinese two-parent families, no significant interaction was found for mother-adolescent dyad. Besides, adolescent-reported mother-child communication interacted with mother-reported communication in Chinese single-mother families only. The findings clarify parent-adolescent discrepancies in parent-child communication in different types of families in China and they have theoretical and practical implications on the role of discrepancies in parents and adolescent children on perceived parent-adolescent communication in early adolescent depressive symptoms.

Parent-Adolescent Communication and Early Adolescent Depressive Symptoms: The Roles of Gender and Adolescents' Age.

Positive parent-adolescent communication has been found to be negatively related to adolescent depressive symptoms; however, few studies have investigated the moderating effects of adolescent gender and age on this relationship, especially during early adolescence in China. The present study investigated the joint moderating effects of adolescent gender and age on the linkage of father-adolescent and mother-adolescent communication with adolescents' depressive symptoms. A total of 11,455 Chinese junior high school students (M age = 14.15 years, SD = 1.22 years; 49.86% boys; N grade7 = 5712, N grade9 = 5743) completed ad hoc questionnaires of parent-adolescent communication and depressive symptoms. Multiple linear regression analyses were conducted. Results indicated that gender and age jointly moderated the association between parental communication and adolescent depressive symptoms. Specifically, for girls, the negative effects of both father-adolescent and mother-adolescent communication on depressive symptoms were stronger in 9th grade students than in 7th grade students, while for boys, the negative effects were not different between 7th grade students and 9th grade students. These findings suggest that in China, the protective effects of positive parent-adolescent communication on adolescents' depressive symptoms may be most salient among senior-grade girls in junior high school.

A multi-objective radiomics model for the prediction of locoregional recurrence in head and neck squamous cell cancer.

PURPOSE: Locoregional recurrence (LRR) is the predominant pattern of relapse after nonsurgical treatment of head and neck squamous cell cancer (HNSCC). Therefore, accurately identifying patients with HNSCC who are at high risk for LRR is important for optimizing personalized treatment plans. In this work, we developed a multi-classifier, multi-objective, and multi-modality (mCOM) radiomics-based outcome prediction model for HNSCC LRR. METHODS: In mCOM, we considered sensitivity and specificity simultaneously as the objectives to guide the model optimization. We used multiple classifiers, comprising support vector machine (SVM), discriminant analysis (DA), and logistic regression (LR), to build the model. We used features from multiple modalities as model inputs, comprising clinical parameters and radiomics feature extracted from X-ray computed tomography (CT) images and positron emission tomography (PET) images. We proposed a multi-task multi-objective immune algorithm (mTO) to train the mCOM model and used an evidential reasoning (ER)-based method to fuse the output probabilities from different classifiers and modalities in mCOM. We evaluated the effectiveness of the developed method using a retrospective public pretreatment HNSCC dataset downloaded from The Cancer Imaging Archive (TCIA). The input for our model included radiomics features extracted from pretreatment PET and CT using an open source radiomics software and clinical characteristics such as sex, age, stage, primary disease site, human papillomavirus (HPV) status, and treatment paradigm. In our experiment, 190 patients from two institutions were used for model training while the remaining 87 patients from the other two institutions were used for testing. RESULTS: When we built the predictive model using features from single modality, the multi-classifier (MC) models achieved better performance over the models built with the three base-classifiers individually. When we built the model using features from multiple modalities, the proposed method achieved area under the receiver operating characteristic curve (AUC) values of 0.76 for the radiomics-only model, and 0.77 for the model built with radiomics and clinical features, which is significantly higher than the AUCs of models built with single-modality features. The statistical analysis was performed using MATLAB software. CONCLUSIONS: Comparisons with other methods demonstrated the efficiency of the mTO algorithm and the superior performance of the proposed mCOM model for predicting HNSCC LRR.

Government Intervention, Risk Perception, and the Adoption of Protective Action Recommendations: Evidence from the COVID-19 Prevention and Control Experience of China.

This study examines the relationships between government interventions, risk perception, and the public's adoption of protective action recommendations (PARs) during the COVID-19 coronavirus disease emergency in mainland China. We conducted quota sampling based on the proportion of the population in each province and gender ratios in the Sixth Census and obtained a sample size of 3837. Government intervention was divided into government communication, government prevention and control, and government rescue. We used multiple regression and a bootstrap mediation effect test to study the mechanism of these three forms of government intervention on the public's adoption of PARs. The results show that government prevention and control and government rescue significantly increased the likelihood of the public adopting PARs. Risk perception was significantly associated with the public's adoption of PARs. The effects of government interventions and risk perception on the public's adoption of PARs was not found to vary by region. Risk perception is identified as an important mediating factor between government intervention and the public's adoption of PARs. These results indicate that increasing the public's risk perception is an effective strategy for governments seeking to encourage the public to adopt PARs during the COVID-19 pandemic.

Combining many-objective radiomics and 3D convolutional neural network through evidential reasoning to predict lymph node metastasis in head and neck cancer.

Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential to optimizing treatment. Positron emission tomography (PET) and computed tomography (CT) imaging are routinely used to identify LNM. Although large or highly active lymph nodes (LNs) have a high probability of being positive, identifying small or less reactive LNs is challenging. The accuracy of LNM identification strongly depends on the physician's experience, so an automatic prediction model for LNM based on CT and PET images is warranted to assist LMN identification across care providers and facilities. Radiomics and deep learning are the two promising imaging-based strategies for node malignancy prediction. Radiomics models are built based on handcrafted features, while deep learning learns the features automatically. To build a more reliable model, we proposed a hybrid predictive model that takes advantages of both radiomics and deep learning based strategies. We designed a new many-objective radiomics (MaO-radiomics) model and a 3D convolutional neural network (3D-CNN) that fully utilizes spatial contextual information, and we fused their outputs through an evidential reasoning (ER) approach. We evaluated the performance of the hybrid method for classifying normal, suspicious and involved LNs. The hybrid method achieves an accuracy (ACC) of 0.88 while XmasNet and Radiomics methods achieve 0.81 and 0.75, respectively. The hybrid method provides a more accurate way for predicting LNM using PET and CT.