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ObjectiveTo explore the construction and application in the practice of green channel in No. 971 Naval Hospital of PLA (No. 971 Hospital mode) for the treatment of acute ischemic stroke (AIS).MethodsThis retrospective study involved a cohort of 694 suspected stroke patients from December 2022 to November 2023 undergoing emergency treatment for stroke at our institution. Among them, 483 patients were treated with standard green channel (the control group), and 211 patients adopted the No. 971 Hospital mode for treatment (the study group). The biggest difference between the two groups was that the treatment process started before admission. We compared the effectiveness of the emergency treatment between the two groups and the thrombolysis treatment.ResultsCompared with control group, the accuracy rate of determining stroke and the rate of thrombolysis were significantly higher (p = 0.002, 0.039) and the door to doctor arrival time (DAT) and the door to CT scan time (DCT) of the study group was significantly shorter (all p

Scientific literacy is a key factor of personal competitiveness, and reading is the most common activity in daily learning life, and playing the influence of reading on individuals day by day is the most convenient way to improve the level of scientific literacy of all people. Reading engagement is one of the important student characteristics related to reading literacy, which is highly malleable and is jointly reflected by behavioral, cognitive, and affective engagement, and it is of theoretical and practical significance to explore the relationship between reading engagement and scientific literacy using reading engagement as an entry point. In this study, we used PISA2018 data from China to explore the relationship between reading engagement and scientific literacy with a sample of 15-year-old students in mainland China. 36 variables related to reading engagement and background variables (gender, grade, and socioeconomic and cultural status of the family) were selected from the questionnaire as the independent variables, and the score of the Scientific Literacy Assessment (SLA) was taken as the outcome variable, and supervised machine learning method, the XGBoost algorithm, to construct the model. The dataset is randomly divided into training set and test set to optimize the model, which can verify that the obtained model has good fitting degree and generalization ability. Meanwhile, global and local personalized interpretation is done by introducing the SHAP value, a cutting-edge machine model interpretation method. It is found that among the three major components of reading engagement, cognitive engagement is the more influential factor, and students with high reading cognitive engagement level are more likely to get high scores in scientific literacy assessment, which is relatively dominant in the model of this study. On the other hand, this study verifies the feasibility of the current popular machine learning model, i.e., XGBoost, in a large-scale international education assessment program, with a better model adaptability and conditions for global and local interpretation.

Tripartite-motif 56 (TRIM56) is a member of the TRIM family, and was shown to be an interferon-inducible E3 ubiquitin ligase that can be overexpressed upon stimulation with double-stranded DNA to regulate stimulator of interferon genes (STING) to produce type I interferon and thus mediate innate immune responses. Its role in tumors remains unclear. In this study, we investigated the relationship between the expression of the TRIM56 gene and its prognostic value in pan-cancer, identifying TRIM56 expression as an adverse prognostic factor in glioma patients. Therefore, glioma was selected as the primary focus of our investigation. We explored the differential expression of TRIM56 in various glioma subtypes and verified its role as an independent prognostic factor in gliomas. Our research revealed that TRIM56 is associated with malignant biological behaviors in gliomas, such as proliferation, migration, and invasion. Additionally, it can mediate M2 polarization of macrophages in gliomas. The results were validated in vitro and in vivo. Furthermore, we utilized single-cell analysis to investigate the impact of TRIM56 expression on cell communication between glioma cells and non-tumor cells. We constructed a multi-gene signature based on cell markers of tumor cells with high TRIM56 expression to enhance the prediction of cancer patient prognosis. In conclusion, our study demonstrates that TRIM56 serves as a reliable immune-related prognostic biomarker in glioma.

Background: Cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CARASIL) is an autosomal recessive disorder characterized by baldness, recurrent ischemic stroke, lumbago, headache, and dementia which is closely related to homozygous mutations of the high-temperature requirement serine peptidase A1 (HTRA1) gene. Heterozygous mutations of HTRA1 are usually considered to be non-pathogenic. Although it has been revealed that only a few patients with heterozygous mutations could present some manifestations, their clinical symptoms were atypical, milder, and always with a lower frequency of extra-neurological features. Here, a rare patient with heterozygous mutation of HTRA1 who had all typical features of CARASIL as well as severe clinical symptoms and rapid progression was initially reported in our study.Case presentation: A 43-year-old female patient presented with a gradual onset of headache and cognitive decline. As time progressed, her headache intensified and symptoms of dementia began to manifest gradually. During her early years, she had thinning hair and subsequently experienced two occurrences of ischemic strokes in her thirties. Furthermore, she also had a history of lumbago and urinary retention before visiting our hospital. The patient’s magnetic resonance imaging revealed the presence of widespread white matter lesions, infarctions, and microbleeds, in addition to lumbar disc herniation and degenerative lesions. The observed clinical characteristics had a strong correlation with CARASIL, and the patient was diagnosed with a heterozygous missense mutation of 905G>A (Arg302Gln) in the HTRA1 gene. The patient has been under continuous follow-up for a duration exceeding 3 years subsequent to her release from the hospital. She underwent cystostomy, and symptoms of bulbar paralysis developed in a progressive way. Currently, there has been a notable decrease in motor function and activities of daily living, resulting in the individual being confined to bed for a duration exceeding 1 year.Conclusion: This case suggests that patients carrying a heterozygous mutation in G905A may also have typical clinical features of CARASIL, which allows us to have a more comprehensive understanding of CARASIL.

ObjectiveTo evaluate the efficacy and safety of combined traditional Chinese medicine in the adjuvant treatment of proliferative diabetic retinopathy (PDR) by Meta-analysis.MethodsPubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang databases were searched by computer. Random controlled clinical trials (RCTS) using traditional Chinese medicine as adjuvant therapy for proliferative diabetic retinopathy were screened, and Stata16.0 software was used to perform meta-analysis on the final included literatures.ResultsA total of 18 studies involving 1392 patients were included. Meta-analysis showed that the clinical effective rate OR=2.99 (CI: 2.18-4.10, I2 = 42.7%, P

BackgroundNon-small cell lung cancer (NSCLC) is the most common histological type of lung cancer, and brain metastasis (BM) is the most lethal complication of NSCLC. The predictive biomarkers and risk factors of asynchronous BM are still unknown.Materials and methodsA total of 203 patients with NSCLC were enrolled into our cohort and followed up. The clinicopathological factors such as tumor size, T stage, lymphatic invasion, metastasis and asynchronous BM were investigated. CCKAR expression in NSCLC and resected BM was assessed by IHC, and CCKAR mRNAs in NSCLC and para-tumor tissues were estimated by qRT-PCR. The correlations between CCKAR expression, BM and other clinicopathological factors were assessed by chi-square test, and prognostic significance of CCKAR was estimated by univariate and multivariate analyses.ResultsCCKAR was highly expressed in NSCLC tissues compared with para-tumor tissues. CCKAR expression in NSCLC was significantly associated with asynchronous BM. The BM percentages for NSCLC patients with low and high CCKAR were surprisingly 5.2% and 66.6%, respectively. CCKAR expression and BM were unfavorable factors predicting unfavorable outcome of NSCLC. Moreover, CCKAR expression in NSCLC was an independent risk factor of asynchronous BM.ConclusionsCCKAR is a prognostic biomarker of NSCLC. CCKAR expression in NSCLC is positively associated with asynchronous BM, and is a risk factor of asynchronous BM from NSCLC.

This study focuses on the measurement of mathematical ability in the Chinese Compulsory Education Qualification Monitoring (CCEQM) framework using bifactor theory. First, we propose a full-information item bifactor (FIBF) model for the measurement of mathematical ability. Second, the performance of the FIBF model is empirically studied using a data set from three representative provinces were selected from CCEQM 2015–2017. Finally, Monte Carlo simulations are conducted to demonstrate the accuracy of the model evaluation indices and parameter estimation methods used in the empirical study. The obtained results are as follows: (1) The results for the four used model selection indices (AIC, SABIC, HQ, BIC) consistently showed that the fit of the FIBF model is better than that of the UIRT; (2) All of the estimated general and domain-specific abilities of the FIBF model have reasonable interpretations; (3) The model evaluation indices and parameter estimation methods exhibit excellent accuracy, indicating that the application of the FIBF model is technically feasible in large-scale testing projects.

BackgroundNeutrophil extracellular traps (NETs) have been found to play an important role in several nervous system diseases. However, their role in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis remains unclear. The purpose of this study was to examine the possible role of NETs in anti-NMDAR encephalitis.Materials and methodsEleven patients with anti-NMDAR encephalitis and ten healthy participants were enrolled. Plasma NETs levels were detected using an immunofluorescence assay and enzyme-linked immunosorbent assay. Additionally, we examined 10 plasma cytokines in patients with anti-NMDAR encephalitis and analyzed the correlation between citrullinated histone 3 levels and cytokine release. ResultsPeripheral blood neutrophils from patients with anti-NMDAR encephalitis were more susceptible to NET generation. When compared with controls, cases of anti-NMDAR encephalitis showed elevated levels of IL-1 α, IL-6, IL-8, IL-13, MCP-1, and TNF-α (p < 0.05). Moreover, IL-6, IL-8, and TNF-α levels were positively correlated with H3Cit levels.ConclusionWe provide evidence that NETs may play a role in anti-NMDAR encephalitis, providing clues for elucidation of the pathogenesis of this disease.

Cuproptosis is the most recently discovered type of regulated cell death and is mediated by copper ions. Studies show that cuproptosis plays a significant role in cancer development and progression. Lower-grade gliomas (LGGs) are slow-growing brain tumors. The majority of LGGs progress to high-grade glioma, which makes it difficult to predict the prognosis. However, the prognostic value of cuproptosis-related genes (CRGs) in LGG needs to be further explored. mRNA expression profiles and clinical data of LGG patients were collected from public sources for this study. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model were used to build a multigene signature that could divide patients into different risk groups. The differences in clinical pathological characteristics, immune infiltration characteristics, and mutation status were evaluated in risk subgroups. In addition, drug sensitivity and immune checkpoint scores were estimated in risk subgroups to provide LGG patients with precision medication. We found that all CRGs were differentially expressed in LGG and normal tissues. Patients were divided into high- and low-risk groups based on the risk score of the CRG signature. Patients in the high-risk group had a considerably lower overall survival rate than those in the low-risk group. According to functional analysis, pathways related to the immune system were enriched, and the immune state differed across the two risk groups. Immune characteristic analysis showed that the immune cell proportion and immune scores were different in the different groups. High-risk group was characterized by low sensitivity to chemotherapy but high sensitivity to immune checkpoint inhibitors. The current study revealed that the novel CRG signature was related to the prognosis, clinicopathological features, immune characteristics, and treatment perference of LGG.

ObjectiveTo validate the clinical reliability of an individualized CT image-guided‘ free-hand catheter technique (CTGFC) for basal ganglia hematoma (BGH) evacuation.MethodsFrom January 2017 to December 2020, 58 cases of patients with BGH who underwent catheter evacuation were enrolled. The surgery was conducted using the CTGFC (n = 31) or stereotactic catheter technique (STC, n = 27). The authors evaluated the baseline characteristics, operation-related indicators, postoperative complications, hospitalization-related indicators, short-term and long-term functional outcomes, and mortality rate 1 year after surgery.ResultsAll patients underwent BGH evacuation under non-general anesthesia in the CTGFC group. The operative time (p < 0.01) and operation costs (p < 0.05) were significantly shorter in the CTGFC group than that in the STC group (p < 0.01). Comparable results were found in the catheter indwelling duration, residual hematoma volume, hematoma evacuation rate, incidence of postoperative complications, hospital ICU stay, and hospital costs between these two groups (p > 0.05). The duration of hospital stay was remarkably shorter in the CTGFC group than that in the STC group (p < 0.01). There were no differences in terms of the short-time functional outcomes score at discharge, including the Glasgow outcome scale (GOS) score, the activities of daily living (ADL) score, and the Karnofsky performance score (KPS). Moreover, comparable findings were also found in the 1-year postoperative GOS score, ADL score, KPS score, and mortality rate between these two groups.ConclusionThe simple CTGFC-assisted surgery was a safe and reliable option for BGH evacuation, especially in primary medical institutes and emergency situations with limited medical resources.

Rac1 is critically involved in the regulation of the actin cytoskeleton, neuronal structure, synaptic plasticity, and memory. Rac1 overactivation is reported in human patients and animal models of Alzheimer’s disease (AD) and contributes to their spatial memory deficits, but whether Rac1 dysregulation is also important in other forms of memory deficits is unknown. In addition, the cell types and synaptic mechanisms involved remain unclear. In this study, we used local injections of AAV virus containing a dominant-negative (DN) Rac1 under the control of CaMKIIα promoter and found that the reduction of Rac1 hyperactivity in ventral hippocampal excitatory neurons improves social recognition memory in APP/PS1 mice. Expression of DN Rac1 also improves long-term potentiation, a key synaptic mechanism for memory formation. Our results suggest that overactivation of Rac1 in hippocampal excitatory neurons contributes to social memory deficits in APP/PS1 mice and that manipulating Rac1 activity may provide a potential therapeutic strategy to treat social deficits in AD.

Glioma, one of the most common malignant tumors in the nervous system, is characterized by limited treatment, high mortality and poor prognosis. Numerous studies have shown that lncRNAs play an important role in the onset and progression of glioma by acting on various classical signaling pathways of tumors through signaling, trapping, guiding, scaffolding and other functions. LncRNAs contribute to the malignant progression of glioma via proliferation, apoptosis, epithelial-mesenchymal transformation, chemotherapy resistance, ferroptosis and other biological traits. In this paper, relevant lncRNA signaling pathways involved in glioma progression were systematically evaluated, with emphasis placed on the specific molecular mechanism of lncRNAs in the process of ferroptosis, in order to provide a theoretical basis for the application of lncRNAs in the anticancer treatment of glioma.

This study aimed to investigate the features of only child status related to physical health, mathematics achievement, and school feelings and expectations from a different perspective. A representative sample of 91,619 Grade 4 students with an average age of 10.4 ± 0.7, among which 28,631 were only children, were assessed. We used propensity score matching (PSM) and the average treatment effects on the treatment to analyze data. The treatment was the only child of a family. The results indicated that only children have better academic achievement and school feelings (only for urban only child girls), while non-only children have better physical status and anaerobic fitness (AF). In addition, gender and rural vs. urban areas differences were also explored. The adverse situation for rural only boys is emphasized for families, researchers, and governments to focus on. Some suggestions are given under the Two- and Three-Child Policy.

Although classification accuracy is a critical issue in cognitive diagnostic computerized adaptive testing, attention has increasingly shifted to item exposure control to ensure test security. In this study, we developed the binary restrictive threshold (BRT) method to balance measurement accuracy and item exposure. In addition, a simulation study was conducted to evaluate its performance. The results indicated that the BRT method performed better than the restrictive progressive (RP) and stratified dynamic binary searching (SDBS) approaches but worse than the restrictive threshold (RT) method in terms of classification accuracy. With respect to item exposure control, the BRT method exhibited noticeably stronger performance compared with the RT method, even though its performance was not as high as that of the RP and SDBS methods.

BackgroundGlioma is one of the highly fatal primary tumors in the central nervous system. As a major component of tumor microenvironment (TME), immune cell has been proved to play a critical role in the progression and prognosis of the diffuse lower-grade gliomas (LGGs). This study aims to screen the key immune-related factors of LGGs by investigating the TCGA database.MethodsThe RNA-sequencing data of 508 LGG patients were downloaded in the TCGA database. ESTIMATE algorithm was utilized to calculate the stromal, immune, and ESTIMATE scores, based on which, the differentially expressed genes (DEGs) were analyzed by using “limma” package. Cox regression analysis and the cytoHubba plugin of Cytoscape software were subsequently applied to screen the survival-related genes and hub genes, the intersection of which led to the identification of SERPINE1 that played key roles in the LGGs. The expression patterns, clinical features, and regulatory mechanisms of SERPINE1 in the LGGs were further analyzed by data mining of the TCGA database. What’s more, the above analyses of SERPINE1 were further validated in the LGG cohort from the CGGA database.ResultWe found that stromal and immune cell infiltrations were strongly related to the prognosis and malignancy of the LGGs. A total of 54 survival-related genes and 46 hub genes were screened out in the DEGs, within which SERPINE1 was identified to be significantly overexpressed in the LGG samples compared with the normal tissues. Moreover, the upregulation of SERPINE1 was more pronounced in the gliomas of WHO grade III and IDH wild type, and its expression was correlated with poor prognosis in the LGG patients. The independent prognostic value of SERPINE1 in the LGG patients was also confirmed by Cox regression analysis. In terms of the functions of SERPINE1, the results of enrichment analysis indicated that SERPINE1 was mainly enriched in the immune‐related biological processes and signaling pathways. Furthermore, it was closely associated with infiltrations of immune cells in the LGG microenvironment and acted synergistically with PD1, PD-L1, PD-L2.ConclusionThese findings proved that SERPINE1 could serve as a prognostic biomarker and potential immunotherapy target of LGGs.

Bayesian networks (BNs) can be employed to cognitive diagnostic assessment (CDA). Most of the existing researches on the BNs for CDA utilized the MCMC algorithm to estimate parameters of BNs. When EM algorithm and gradient descending (GD) learning method are adopted to estimate the parameters of BNs, some challenges may emerge in educational assessment due to the monotonic constraints (greater skill should lead to better item performance) cannot be satisfied in the above two methods. This paper proposed to train the BN first based on the ideal response pattern data contained in every CDA and continue to estimate the parameters of BN based on the EM or the GD algorithm regarding the parameters based on the IRP training method as informative priors. Both the simulation study and realistic data analysis demonstrated the validity and feasibility of the new method. The BN based on the new parameter estimating method exhibits promising statistical classification performance and even outperforms the G-DINA model in some conditions.

Calibration errors are inevitable and should not be ignored during the estimation of item parameters. Items with calibration error can affect the measurement results of tests. One of the purposes of the current study is to investigate the impacts of the calibration errors during the estimation of item parameters on the measurement accuracy, average test length, and test efficiency for variable-length cognitive diagnostic computerized adaptive testing. The other purpose is to examine the methods for reducing the adverse effects of calibration errors. Simulation results show that (1) calibration error has negative effect on the measurement accuracy for the deterministic input, noisy “and” gate (DINA) model, and the reduced reparameterized unified model; (2) the average test lengths is shorter, and the test efficiency is overestimated for items with calibration errors; (3) the compensatory reparameterized unified model (CRUM) is less affected by the calibration errors, and the classification accuracy, average test length, and test efficiency are slightly stable in the CRUM framework; (4) methods such as improving the quality of items, using large calibration sample to calibrate the parameters of items, as well as using cross-validation method can reduce the adverse effects of calibration errors on CD-CAT.

How to effectively evaluate students’ essays based on a series of relatively objective writing criteria has always been a topic of discussion. With the development of automatic essay scoring, a key question is whether the writing quality can be evaluated systematically based on the scoring rubric. To address this issue, we used an innovative set of graph-based features to predict the quality of Chinese middle school students’ essays. These features are divided into four sub-dimensions: basic characteristics, main idea, essay content, and essay development. The results show that graph-based features were significantly better at predicting human essay scores than the baseline features. This indicates that graph-based features can be used to reliably and systematically evaluate the quality of an essay based on the scoring rubric, and it can be used as an alternative tool to replace or supplement human evaluation.

BackgroundFamily with sequence similarity 111 member A (FAM111A), as a replication factor required for proliferating cell nuclear antigen (PCNA) loading, has been demonstrated a possible association with carcinogenesis. However, the role of FAM111A in lower-grade glioma (LGG) remains unclear. We aim at investigating the expression and function of FAM111A in lower-grade glioma at the molecular and clinical levels.MethodsIn total, 711 lower-grade glioma samples were analyzed in our research, including 182 RNA-seq data from the Chinese Glioma Genome Atlas (CGGA) dataset and 529 RNA-seq data from The cancer Genome Atlas (TCGA) dataset. R language and the GraphPad software were used for the majority of statistical analysis and graphical work.ResultsFAM111A expression was overexpressed in WHO grade III and IDH-wildtype lower-grade glioma. FAM111A was significantly downregulated in the IDHmut-Codel molecular subtype. Univariate and multivariate Cox analysis demonstrated that FAM111A was an independent prognostic factor in LGG patients. Functional characterization of FAM111A revealed that it was associated with inflammatory response and immune response to tumor cells. FAM111A could also act as an indicator of the stromal and immune population, especially for monocytic lineage, myeloid dendritic cells and fibroblasts. It was positively correlated with macrophages, especially the M2 macrophage cells. Furthermore, FAM111A revealed predictive value for the immune subtypes and immune checkpoint blockade therapy.ConclusionFAM111A expression was closely related to the malignant phenotype, molecular pathology and immune response of lower-grade glioma. It might be a promising target for LGG immunotherapeutic strategies.

As previous researchers have found, like other parts of the world, depression is prevalent among middle school teachers in China. The Beck Depression Inventory-II (BDI-II) has been widely used to detect depression among workers in different careers all over the world and has shown good scale properties but inconsistent factor structures. To examine the psychometric properties of the BDI-II among middle school teachers, a nationally representative sample of 4,672 valid cases from 688 middle schools were included. We first generated a new bifactor model based on exploratory factor analysis and agglomerate cluster analysis of the residual item correlations and then validated the modes and examined measurement invariance across gender and school location with multiple-group confirmatory factor analysis (CFA). Results indicated that (1) a new bifactor model with a general factor and two group factors (cognitive–affective group factor and somatic group factor) fitted well to the data [WLSMV χ2 = 745.651, df = 173, P < 0.001, CFI = 0.983, TLI = 0.979, RMSEA = 0.037; 90% CI (0.035, 0.040)]; Omega values for the three factors varied from 0.88 to 0.92; (2) measurement invariance tests indicated that the BDI-II could equally measure depression of middle school teachers across gender and school location groups. All the findings suggest that the BDI-II is a self-report inventory with good psychometric properties for measuring depression among middle school teachers in China.

We propose a new method that balances attribute coverage for short-length cognitive diagnostic computerized adaptive testing (CD-CAT). The new method uses the attribute discrimination index (ADI-based method) instead of the number of items that measure each attribute [modified global discrimination index (MGDI)-based method] to balance the attribute coverage. Therefore, the information that each attribute provides can be captured. The purpose of the simulation study was to evaluate the performance of the new method, and the results showed the following: (a) Compared with uncontrolled attribute-balance coverage method, the new method produced a higher mastery pattern correct classification rate (PCCR) and attribute correct classification rate (ACCR) with both the posterior-weighted Kullback–Leibler (PWKL) and the modified PWKL (MPWKL) item selection method. (b) Equalization of ACCR (E-ACCR) based on the ADI-based method leads to better results, followed by the MGDI-based method. The uncontrolled method leads to the worst results regardless of item selection methods. (c) Both the ADI-based and MGDI-based methods produced acceptable examinee qualification rates, regardless of item selection methods, although they were relatively low for the uncontrolled condition.

The overexpressed soluble fms-like tyrosine kinase 1 (sFLT-1) in placenta is considered to be a potential therapeutic target for preeclampsia (PE). How to achieve efficient intervention of sFLT1 expression in the placenta is an urgent problem to be solved. PEG-PLA nanoparticle generated by double-emulsion methods is a novel siRNA delivery system. Synthetic placental CSA binding peptide (P-CSA-BP) is effective for targeting lipid-polymer nanoparticle to the placenta. We conjugated P-CSA-BP to the surface of PEG-PLA nanoparticle to create a novel placenta specific sFLT1 siRNA delivery system for the therapy of PE. Nanoparticles were synthesized using double emulsion method and characterized by dynamic light scattering and transmission electron microscopy (TEM). RT-PCR was employed to evaluate mRNA level and protein level was analyzed by ELISA kit. The tissue distribution of nanoparticles was observed through ex vivo images. The concentrations of nanoparticles in organs were measured using high-performance liquid chromatography. T-NPsisFLT1 had higher efficiency than NPsisFLT1 in accumulating in HTR-8/SVneo cells and significantly decreased the expression of sFLT1. Intravenously administered T-NPsisFLT1 specifically accumulated in placentas of mice. sFLT1 mRNA level in placenta and protein level in serum were declined by T-NPsisFLT1. T-NPsisFLT1 shown no obvious toxic effect on both mother and fetus. The utility of T-NPsisFLT1 nanoparticles as a sFLT1 siRNA placenta specific delivery system significantly silenced sFLT1 in mice and is safe for both mother and fetus. This nanoparticle is a novel potential therapeutic strategy for PE.

The study examined the dimensionality and psychometric properties of Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for heroin use disorder in a clinical sample of Chinese adolescents using item response theory approach. We examined 168 adolescents aged 14.8–17.9 years, who were in treatment for heroin use disorder. A two-parameter logistic item response theory model was conducted to examine the severity and discrimination of DSM-5 criteria for heroin use disorder. Differential item functioning across age and ethnicity was assessed. Results supported the hypothesis that the DSM-5 criteria for heroin use disorder were arrayed an underlying unitary dimension of severity in clinical adolescents. All the items exhibited good discriminatory power in distinguishing between clinical adolescent heroin users. Although three criteria exhibited measurement non-invariance at the item level, the overall DSM-5 heroin use disorder diagnostic criteria set appears to achieve measurement invariance at the scale level.

This study investigated the effects of social-emotional competency on pupils’ academic achievement, academic emotions and attitudes, and interpersonal relationships. Participants were 7106 fourth-grade and fifth-grade students in western China. The results were: (1) social-emotional competency positively predicted pupils’ academic achievement (including reading, mathematics, and science); (2) social-emotional competency predicted pupils’ academic emotions and attitudes, including learning anxiety and interest, and academic emotions and attitudes played a mediating role in the relation between social-emotional competency and academic achievement; and (3) social-emotional competency positively predicted pupils’ interpersonal relationships, including peer relationships and teacher–student relationships, and interpersonal relationships played a mediating role in the relation between social-emotional competency and academic achievement. These findings highlighted the importance of social-emotional competency to child development in western China, where many children might lack their parents’ company.

As a class of discrete latent variable models, cognitive diagnostic models have been widely researched in education, psychology, and many other disciplines. Detecting and eliminating differential item functioning (DIF) items from cognitive diagnostic tests is of great importance for test fairness and validity. A Monte Carlo study with varying manipulated factors was carried out to investigate the performance of the Mantel-Haenszel (MH), logistic regression (LR), and Wald tests based on item-wise information, cross-product information, observed information, and sandwich-type covariance matrices (denoted by Wd, WXPD, WObs, and WSw, respectively) for DIF detection. The results showed that (1) the WXPD and LR methods had the best performance in controlling Type I error rates among the six methods investigated in this study and (2) under the uniform DIF condition, when the item quality was high or medium, the power of WXPD, WObs, and WSw was comparable with or superior to that of MH and LR, but when the item quality was low, WXPD, WObs, and WSw were less powerful than MH and LR. Under the non-uniform DIF condition, the power of WXPD, WObs, and WSw was comparable with or higher than that of LR.

The performance of the limited-information statistic M2 for diagnostic classification models (DCMs) is under-investigated in the current literature. Specifically, the investigations of M2 for specific DCMs rather than general modeling frameworks are needed. This article aims to demonstrate the usefulness of M2 in hierarchical diagnostic classification models (HDCMs). The performance of M2 in evaluating the fit of HDCMs was investigated in the presence of four types of attribute hierarchies. Two simulation studies were conducted to examine Type I error rates and statistical power of M2 under different simulation conditions, respectively. The findings suggest acceptable Type I error rates control of M2 as well as high statistical power under the conditions of a Q-matrix misspecification and the DINA model misspecification. The data of Examination for the Certificate of Proficiency in English (ECPE) were used to empirically illustrate the suitability of M2 in practice.

In the past decades, the longitudinal approach has been remarkably and increasingly used in the investigations of children's cognitive development. Recently, many researchers have started to realize the importance and necessity of examining measurement invariance for any further longitudinal analysis. However, there are few empirical studies demonstrating how to conduct further analysis when the assumption of measurement invariance of an instrument is violated. The primary purpose of this study is to explore how a newly-developed calibrated projection method can be applied to reduce the impact of lack of parameter invariance in a longitudinal study of preschool children's cognitive development. The sample consisted of 882 children from China who participated in two waves of the cognitive tests when they were 4 and 5 years old. Before this study was conducted, the IRT method was used to examine the measurement invariance of the instrument. The results showed that five items presented difficulty parameter drift and three items presented discrimination/slope parameter drift. In the study, the invariant items were treated as “common items” and calibrated projection linking was used to establish a comparable scale across two time points. Then the linking method was evaluated by three properties: grade-to-grade growth, grade-to-grade variability, and the separation of distributions. The results showed that the grade-to-grade growth across two waves was larger and exhibited a larger effect size; the grade-to-grade variability showed less scale shrinkage, which indicated a smaller measurement error; the separation of distributions showed a larger growth as well.

In spite of the growing interest in the methods of evaluating the classification consistency (CC) indices, only few researches are available in the field of applying these methods in the practice of large-scale educational assessment. In addition, only few studies considered the influence of practical factors, for example, the examinee ability distribution, the cut score location and the score scale, on the performance of CC indices. Using the newly developed Lee's procedure based on the item response theory (IRT), the main purpose of this study is to investigate the performance of CC indices when practical factors are taken into consideration. A simulation study and an empirical study were conducted under comprehensive conditions. Results suggested that with negatively skewed distribution, the CC indices were larger than with other distributions. Interactions occurred among ability distribution, cut score location, and score scale. Consequently, Lee's IRT procedure is reliable to be used in the field of large-scale educational assessment, and when reporting the indices, it should be treated with caution as testing conditions may vary a lot.

Writing assessments are an indispensable part of most language competency tests. In our research, we used cross-classified models to study rater effects in the real essay rating process of a large-scale, high-stakes educational examination administered in China in 2011. Generally, four cross-classified models are suggested for investigation of rater effects: (1) the existence of sequential effects, (2) the direction of the sequential effects, and (3) differences in raters by their individual characteristics. We applied these models to the data to account for possible cluster effects caused by the application of multiple rating strategies. The results of our research showed that raters demonstrated sequential effects during the rating process. In contrast to many other studies on rater effects, our study found that raters exhibited assimilation effects. The more experienced, lenient, and qualified raters were less susceptible to assimilation effects. In addition, our research demonstrated the feasibility and appropriateness of using cross-classified models in assessing rater effects for such data structures. This paper also discusses the implications for educators and practitioners who are interested in reducing sequential effects in the rating process, and suggests directions for future research.

We report the development and validation of a scale to measure online shopping addiction. Inspired by previous theories and research on behavioral addiction, the Griffiths's widely accepted six-factor component model was referred to and an 18-item scale was constructed, with each component measured by three items. The results of exploratory factor analysis, based on Sample 1 (999 college students) and confirmatory factor analysis, based on Sample 2 (854 college students) showed the Griffiths's substantive six-factor structure underlay the online shopping addiction scale. Cronbach's alpha suggested that the resulting scale was highly reliable. Concurrent validity, based on Sample 3 (328 college students), was also satisfactory as indicated by correlations between the scale and measures of similar constructs. Finally, self-perceived online shopping addiction can be predicted to a relatively high degree. The present 18-item scale is a solid theory-based instrument to empirically measure online shopping addiction and can be used for understanding the phenomena among young adults.

Automatic speech emotion recognition (SER) is a challenging component of human-computer interaction (HCI). Existing literatures mainly focus on evaluating the SER performance by means of training and testing on a single corpus with a single language setting. However, in many practical applications, there are great differences between the training corpus and testing corpus. Due to the diversity of different speech emotional corpus or languages, most previous SER methods do not perform well when applied in real-world cross-corpus or cross-language scenarios. Inspired by the powerful feature learning ability of recently-emerged deep learning techniques, various advanced deep learning models have increasingly been adopted for cross-corpus SER. This paper aims to provide an up-to-date and comprehensive survey of cross-corpus SER, especially for various deep learning techniques associated with supervised, unsupervised and semi-supervised learning in this area. In addition, this paper also highlights different challenges and opportunities on cross-corpus SER tasks, and points out its future trends. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effects of Physical Therapies (PTs) on improvement in psychosomatic symptoms and quality of life (QOL) in breast cancer patients. Data Sources: Seven databases (MEDLINE, EMBASE, Cochrane CENTRAL, China National Knowledge Infrastructure, Wangfang, VIP, and China Biology Medicine disc databases) were systematically searched from the database inception through May 18, 2021. Study Selection: Randomized controlled trials (RCTs) which compared acupuncture or exercise with a sham control or usual care for the treatment of aromatase inhibitors (AIs)-related psychosomatic symptoms and QOL. Data Extraction and Synthesis: Data were screened and extracted independently using predesigned forms. The quality of RCTs was assessed with the Cochrane Handbook for Systematic Reviews of Interventions. The effect size was calculated via random-effects modeling. The quality of evidence was evaluated with the Grading of Recommendations Assessment, Development and Evaluation approach. Main Outcomes and Measures: The score of pain was measured with BPI scale and Western Ontario and the McMaster Universities Index (WOMAC) scale. Emotional state was measured with Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Scale (HADS-A), and Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatigue). The QOL score was measured by self-reported measurements, including the Functional Assessment of Cancer Therapy-General (FACT-G) scale and 36-Item Short Form Survey (SF-36) scale. Results: Eleven RCTs (with 830 patients) were included in the systematic review, and data from 10 RCTs (with 798 patients) were used in the meta-analysis. Results showed acupuncture significantly reduced worst pain scores (P < 0.00001, I 2 = 83.5%) [SMD = −0.81, 95% CI (−1.51, −0.11)], but the effect of exercise therapies was not significant in overall change in worst pain scores (P =0.006, I 2 = 72.3%) [SMD = −0.30, 95% CI (−0.76, 0.16)]. Both acupuncture and exercise resulted in little to no difference in overall change in HADS-A subscale (P = 0.026<0.05, I 2 = 79.8%) [WMD = −0.21, 95% CI (−3.44, 3.03)], PSQI subscale (P = 0.488, I 2 = 0%) [WMD = 0.98, 95% CI (−0.57, 2.53)], and FACIT-Fatigue subscale (P = 0.022<0.05, I 2 = 81.0%) [WMD = 1.6, 95% CI (−5.75, 8.94)]. Exercise (compared with usual care) was associated with improving overall change in health-related QOL (subscales of SF-36 tool) (P = 0, I 2 = 72.1%) [WMD = 7.97, 95% CI (5.68, 10.25)] and cancer-specific QOL (subscales of FACT-G tool) (P = 0.304, I 2 = 16%) [WMD = 1.16, 95% CI (0.34, 1.97)]. Conclusions and Relevance: This systematic review and meta-analysis suggested that based on moderate-level evidence, acupuncture was associated with significant reductions in pain intensity, and exercise might improve QOL in breast cancer patients treated with AIs. However, in psychosomatic symptoms such as anxiety, sleep disturbance, and fatigue, acupuncture and exercise training did not result in significant improvements. [ABSTRACT FROM AUTHOR]

Low protein diets are commonly used in the growing-finishing pig stage of swine production; however, the effects of low dietary protein on the intestinal microbiota and their metabolites, and their association with pig sex, remain unclear. The present study aimed to assess the impact of a low crude protein (CP) diet on the gut microbiome and metabolome, and to reveal any relationship with sex. Barrows and gilts (both n = 24; initial body = 68.33 ± 0.881 kg) were allocated into two treatments according to sex. The four groups comprised two pairs of gilts and barrows fed with a high protein diet (CP 17% at stage I; CP 13% at stage II) and a low protein diet (CP 15% at stage I; CP 11% at stage II), respectively, for 51 d. Eight pigs in each group were slaughtered and their colon contents were collected. Intestinal microbiota and their metabolites were assessed using 16S rRNA sequencing and tandem mass spectrometry, respectively. The low protein diet increased intestinal microbiota species and richness indices (P < 0.05) in both sexes compared with the high protein diet. The sample Shannon index was different (P < 0.01) between barrows and gilts. At the genus level, unidentified Clostridiales (P < 0.05), Neisseria (P < 0.05), unidentified Prevotellaceae (P < 0.01) and Gracilibacteria (P < 0.05) were affected by dietary protein levels. The relative abundance of unidentified Prevotellaceae was different (P < 0.01) between barrows and gilts. The influence of dietary protein levels on Neisseria (P < 0.05), unidentified Prevotellaceae (P < 0.01) and Gracilibacteria (P < 0.05) were associated with sex. Metabolomic profiling indicated that dietary protein levels mainly affected intestinal metabolites in gilts rather than barrows. A total of 434 differentially abundant metabolites were identified in gilts fed the two protein diets. Correlation analysis identified that six differentially abundant microbiota communities were closely associated with twelve metabolites that were enriched for amino acids, inflammation, immune, and disease-related metabolic pathways. These results suggested that decreasing dietary protein contents changed the intestinal microbiota in growing-finishing pigs, which selectively affected the intestinal metabolite profiles in gilts. [ABSTRACT FROM AUTHOR]

Most herbal polysaccharides possess multiple benefits against metabolic disorders, such as non-alcoholic fatty liver disease (NAFLD) and obesity. However, the underlying mechanisms are largely unknown. Here, male C57BL/6J mice were fed with chow or high-fat diet (HFD) with or without Astragalus polysaccharides (APS) supplementation, and gut microbial profile and metabolite profile were studied by metagenomic sequencing and untargeted metabolomics, respectively. APS was effective in alleviating HFD-induced metabolic disorders, with the alteration of gut microbiota composition and function. A total of 188 species, which mainly from Bacteroidetes, Actinobacteria, Firmicutes, and Proteobacteria phyla, and 36 metabolites were markedly changed by HFD and revered by APS. Additionally, the altered glutathione metabolism and purine metabolism pathways were identified by both metagenomic function analysis and metabolite pathway enrichment analysis. Furthermore, the gut microbial alteration was associated with the changes of key intestinal metabolites. We found 31 and 20 species were correlated with purine metabolism and glutathione metabolism, respectively. Together, our results showed significant metagenomic and metabolomic changes after HFD feeding and APS intervention, revealed the potential correlation between gut microbial species and metabolites, and highlighted mechanisms of herb-derived polysaccharides by modulating gut microbiome and host metabolism underlying their benefits on metabolic disorders. [ABSTRACT FROM AUTHOR]

Shiraia bambusicola has long been used as a traditional Chinese medicine and its major medicinal active metabolite is hypocrellin, which exhibits outstanding antiviral and antitumor properties. Here we report the 32 Mb draft genome sequence of S. bambusicola S4201, encoding 11,332 predicted genes. The genome of S. bambusicola is enriched in carbohydrate-active enzymes (CAZy) and pathogenesis-related genes. The phylogenetic tree of S. bambusicola S4201 and nine other sequenced species was constructed and its taxonomic status was supported (Pleosporales , Dothideomycetes). The genome contains a rich set of secondary metabolite biosynthetic gene clusters, suggesting that strain S4201 has a remarkable capacity to produce secondary metabolites. Overexpression of the zinc finger transcription factor zftf , which is involved in hypocrellin A (HA) biosynthesis, increases HA production when compared with wild type. In addition, a new putative HA biosynthetic pathway is proposed. These results provide a framework to study the mechanisms of infection in bamboo and to understand the phylogenetic relationships of S. bambusicola S4201. At the same time, knowledge of the genome sequence may potentially solve the puzzle of HA biosynthesis and lead to the discovery of novel genes and secondary metabolites of importance in medicine and agriculture. [ABSTRACT FROM AUTHOR]