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The necessity of digital management of teaching cases is mainly reflected in the aspects of improving teaching quality, facilitating retrieval and storage, achieving cross-platform sharing, conducting real-time updating, saving resources, and carrying out data analysis and evaluation. However, there are still some defects in the existing management models or methods, which lead to difficulties in data storage and retrieval, and affect the utilization efficiency of teaching resources. To this end, this article takes the Chinese language and literature major as an example, and studies the digital management of teaching cases in colleges and universities based on cluster analysis. First of all, it quantifies the quality of digital management of teaching cases, enables resource demanders to accurately select digital resources of teaching cases that meet their teaching or learning needs through the evaluation index of service quality when faced with diversified digital resources of teaching cases in colleges and universities. The clustering algorithm is used to mine potential topics and patterns in teaching cases, which improves the classification efficiency of teaching cases and enables educators to have a deeper understanding of teaching content and educational needs. It uses "absolute index", "incremental index" and "fluctuation index" to construct the similarity measurement distance function of the basic attributes of teaching cases in colleges and universities and uses the Ward method based on variance analysis to classify the characteristics of teaching cases in colleges and universities. Experimental results verify the effectiveness of the proposed method.

Crown roots are the main components of the fibrous root system in cereal crops and play critical roles in plant adaptation; however, the molecular mechanisms underlying their formation in wheat (Triticum aestivum) have not been fully elucidated. In this study, we identified a wheat basic helix-loop-helix (bHLH) protein, TabHLH123, that interacts with the essential regulator of crown root initiation, MORE ROOT in wheat (TaMOR). TabHLH123 is expressed highly in shoot bases and roots. Ectopic expression of TabHLH123 in rice resulted in more roots compared with the wild type. TabHLH123 regulates the expression of genes controlling crown-root development and auxin metabolism, responses, and transport. In addition, we analysed the nucleotide sequence polymorphisms of TabHLH123s in the wheat genome and identified a superior haplotype, TabHLH123-6B, that is associated with high root dry weight and 1000-grain weight, and short plant height. Our study reveals the role of TabHLH123 in controlling the formation of crown roots and provides beneficial insights for molecular marker-assisted breeding in wheat.

Schematic of red emissive carbon dots with an ultra-large Stokes shift for the multi-channel detection of pesticides.

Mild hypothermia has been identified to reduce brain injury following intracerebral hemorrhage (ICH) by protecting neuron cells through several pathways. However, the role of hypothermia in brain function following ICH and the related mechanisms have not been well identified. Ubiquitination-mediated inflammation plays important roles in the pathogenesis of immune diseases. The experiment analyzed anti-inflammatory effects of mild hypothermia following ICH.The model of ICH was induced by injecting autologous blood. Neuregulin receptor degradation protein-1 (Nrdp1) and downstream molecule were analyzed. In addition, brain inflammatory response, brain edema, and neurological functions of ICH mice were also assessed.We found that mild hypothermia attenuated proinflammatory factors production after ICH. Mild hypothermia significantly inhibited BBB injury, water content, and neurological damage following ICH in vivo. Moreover, mild hypothermia also increased Nrdp1/MyD88 levels and thus affect neuronal apoptosis and inflammation.Taken together, these results suggest that mild hypothermia can attenuate the neuroinflammatory response and neuronal apoptosis after ICH through the regulation of the Nrdp1 levels.

The power generation industry needs to adopt renewable energy so as to reduce the utilization of fossil energy and pollution emission. In renewable energy power generation, microgrid operation optimization needs to consider multiple objectives such as economy and environmental protection, which is a multi-objective optimization problem. Aiming at the multi-objective optimization problem, based on the Pareto optimal concept, a hybrid crossover multi-agent multi-objective evolutionary algorithm is proposed and applied to the multi-objective optimization problem of microgrid systems, in which the economical cost and environmental protection are considered. The simulation results under three operating conditions show that compared with the classical NSGA-Ⅱ algorithm, the proposed algorithm can obtain higher quality Pareto optimal solution in a shorter time. The efficiency of the proposed algorithm in this problem is higher than that of the classical NSGA-Ⅱ algorithm. It can provide a higher quality solution for the optimal operation of a microgrid.

In this article, I advance a recent epigraphic approach to historical study by foregrounding steles as a medium that functions both to communicate information and project authority publicly. Scholars taking this approach have explored distinctive genres of steles to transform our understanding of north China under Mongol rule. Through a case study, I show how a set of steles installed in the fifteenth-century rural world of north China transmitted authority and power not just through the content of their inscriptions but also through other written and unwritten information they stored. I give particular attention to the ways in which the inscriptions were materialized and visualized. In doing so, I argue that emphasizing the public communication function of steles challenges us to think beyond primary sources strictly in terms of their textual value to reflect more broadly on modes of transmission and the power dynamics contained within them.

Sea-level rise integrates the responses of several components (ocean thermal expansion, mass loss from glaciers and ice sheets, terrestrial water storage). Before the satellite era, global sea-level reconstructions depend on tide-gauge records and ocean observations. However, the available global mean sea level (GMSL) reconstructions using different methods indicate a spread in sea-level trend over 1900-2008 (1.3~2.0 mm yr-1). With the improved understanding of the causes of sea-level change, here we update the original Church and White (2011) reconstruction by using the latest observations, taking the time-evolving sea-level fingerprint, sterodynamic sea level (SDSL) climate change pattern and local vertical land motion (VLM) into account. The updated trend of GMSL of 1.6 ± 0.2 mm yr-1 (90% confidence level) over 1900-2019 is consistent with the sum of contributions of 1.5 ± 0.2 mm yr-1, slightly lower than 1.8 ± 0.2 mm yr-1 from original reconstruction. The lower trend from the updated reconstruction is mainly due to including residual VLM correction. The trends at tide gauge locations from updated reconstruction agree better with the tide gauge observations, with comparable mean trend of 1.7 mm yr-1 (standard deviation; STD of 2.0 mm yr-1) from observation and 1.7 mm yr-1 (STD of 1.2 mm yr-1) from the updated reconstruction. The inclusion of sea-level fingerprint and SDSL climate change pattern are the dominant contributors for improved reconstruction skill on regional scales at tide gauge locations. This update leads to GMSL solution that are consistent with other reconstructions in terms of long-term trend and 30-year running rate.

Linear local tangent space alignment (LLTSA) is a classical dimensionality reduction method based on manifold. However, LLTSA and all its variants only consider the one-way mapping from high-dimensional space to low-dimensional space. The projected low-dimensional data may not accurately and effectively “represent” the original samples. This paper proposes a novel LLTSA method based on the linear autoencoder called LLTSA-AE (LLTSA with Autoencoder). The proposed LLTSA-AE is divided into two stages. The conventional process of LLTSA is viewed as the encoding stage, and the additional and important decoding stage is used to reconstruct the original data. Thus, LLTSA-AE makes the low-dimensional embedding data “represent” the original data more accurately and effectively. LLTSA-AE gets the recognition rates of 85.10, 67.45, 75.40 and 86.67% on handwritten Alphadigits, FERET, Georgia Tech. and Yale datasets, which are 9.4, 14.03, 7.35 and 12.39% higher than that of the original LLTSA respectively. Compared with some improved methods of LLTSA, it also obtains better performance. For example, on Handwritten Alphadigits dataset, compared with ALLTSA, OLLTSA, PLLTSA and WLLTSA, the recognition rates of LLTSA-AE are improved by 4.77, 3.96, 7.8 and 8.6% respectively. It shows that LLTSA-AE is an effective dimensionality reduction method.

Comparison of CART19 levels in different groups. A, Levels of CART19 cells in PB were shown as assessed by means of qPCR assay at serial time points before and after infusion of CART19 respectively. B, CAR DNA copies in BM and PB on day 7 to 9 after CART19 infusion were compared. CAR DNA copies in BM (Patient 2, 6, 11, 13) were higher than in PB. C, Paired measurements of CAR DNA copies in BM and PB on day 7 to 9 after CART19 infusion, percentage of leukemia cells after FC chemotherapy shows strong correlations (CAR DNA copies in BM VS in PB, Spearman r=0.956, p

Relapsed leukemia cells analysis by FACS.A, leukemia cells with bright CD19 expression obtained CR with MRD negative after CART19 therapy and relapsed with CD19 + leukemia cells (Patient 1). B, leukemia cells with dim CD19 expression obtained CR with MRD negative after CART19 therapy but relapsed with 2 subsets of CD19 + and - leukemia cells (Patient 2 and 3).

Supplementary Tables including Table 1, Table 2 and Table 3

CRS complication after CART19 therapy. A, the peak serum concentration of IL-6, IFN-γ, IL-10, CRP, D-dimer and ferritin of a representative patient (Patient 15) during CRS at the indicated time-points after CART19 infusion are showed. B, D, Peak serum levels of CRP, ferritin and D-dimer in patients who developed grade 3 CRS (n=6) compared with those without CRS or with 1 or 2 CRS (n=10). Data represented the mean{plus minus}SEM. The Mann-Whitney U test was used for statistical analysis. C, Paired measurements of peak serum IL-6, CRP, ferritin and D-dimer showed strong correlations (IL-6 VS CRP, Spearman r=0.617, p=0.014; IL-6 VS ferritin, Spearman r=0.574, p=0.028; IL-6 VS D-dimer, Spearman r=0.789, p

CART19 identification and quantification

The cumulative incidence of non-relapse mortality are shown.

Supplementary materials

A, A representative diagram of the transduction efficiency evaluation of CART19s 5 days after lentivirus infection. B, Specific target cell lysis by CART19s. T cells or CART19s were co-cultured with K562-RFP cells or CD19-RFP-K562 cells at the indicated E:T ratio for overnight co-culture (24 hours). C, IFN-γ secretion measurements in supernatants in T cells or CART19 cells co-cultured with K562-RFP cells or CD19-RFP-K562 cells at the indicated E:T ratios for 24 hours.

Patient 13 with extramedullary leukemia relapse compromising testis obtained CR after CART19 infusion. A, Ultrasound showed complete elimination of extramedullary relapsed masses involved in testis (red arrows). Images are from before treatment and 90 days after CART19 infusion. B, Pathology showed complete elimination of extramedullary relapsed masses involved in testis. Images are from before treatment and 30 days after CART19 infusion. Left: 10×10, right: 10×40.

Purpose: Patients with relapsed/refractory acute lymphocytic leukemia (R/R ALL) have a poor prognosis. Chimeric antigen receptor–modified T cells against CD19 (CART19) have displayed anti-leukemia activities. However, data from systemic trials in Chinese patients are limited.Experimental Design: T cells transduced with CD19-directed CAR lentiviral vectors were infused in patients with R/R ALL under fludarabine- and cyclophosphamide-based lymphodepletion. The postinfusion responses, toxicities, expansion, and persistence of CART19s in enrolled patients were observed and monitored.Results: We enrolled 15 patients with R/R ALL. The median transduction efficiency of CART19s was 33%. In vitro cytotoxicity assays were conducted and showed prominent antileukemia activities with CART19s. The patients received CART19s infusion at doses of 1.1 × 106/kg to 9.8 × 106/kg. Twelve patients achieved complete remission 1 month after CART19s infusion. CART19s expanded and persisted in peripheral blood and bone marrow. At 150 days, the overall survival rate and leukemia-free survival rate were 65.5% and 37.8%, respectively. The cumulative incidence of relapse and the nonrelapse mortality rate were 54.5% and 7.7%, respectively. Four patients underwent subsequent haploidentical hematopoietic stem cell transplantation. In this trial, 10 patients experienced cytokine release syndrome (CRS). Grade 3 CRS developed in 40% of patients and was associated with a higher disease burden on day −1 and a higher number of previous relapses.Conclusions: This trial demonstrated potent antileukemia activities of CART19s in Chinese patients with R/R ALL. Disease relapse remained the main obstacle. However, patients with a high risk of relapse after CART19s might benefit from subsequent haploidentical hematopoietic stem cell transplantation. Clin Cancer Res; 23(13); 3297–306. ©2016 AACR.

Background This study aimed to develop cardiovascular disease (CVD) risk equations for Chinese patients with newly diagnosed type 2 diabetes (T2D) to predict 10-, 20-, and 30-year of risk. Methods Risk equations for forecasting the occurrence of CVD were developed using data from 601 patients with newly diagnosed T2D from the Da Qing IGT and Diabetes Study with a 30-year follow-up. The data were randomly assigned to a training and test data set. In the training data set, Cox proportional hazard regression was used to develop risk equations to predict CVD. Calibration was assessed by the slope and intercept of the line between predicted and observed probabilities of outcomes by quintile of risk, and discrimination was examined using Harrell’s C statistic in the test data set. Using the Sankey flow diagram to describe the change of CVD risk over time. Results Over the 30-year follow-up, corresponding to a 10,395 person-year follow-up time, 355 of 601 (59%) patients developed incident CVD; the incidence of CVD in the participants was 34.2 per 1,000 person-years. Age, sex, smoking status, 2-h plasma glucose level of oral glucose tolerance test, and systolic blood pressure were independent predictors. The C statistics of discrimination for the risk equations were 0.748 (95%CI, 0.710–0.782), 0.696 (95%CI, 0.655–0.704), and 0.687 (95%CI, 0.651–0.694) for 10-, 20-, and 30- year CVDs, respectively. The calibration statistics for the CVD risk equations of slope were 0.88 (P = 0.002), 0.89 (P = 0.027), and 0.94 (P = 0.039) for 10-, 20-, and 30-year CVDs, respectively. Conclusions The risk equations forecast the long-term risk of CVD in patients with newly diagnosed T2D using variables readily available in routine clinical practice. By identifying patients at high risk for long-term CVD, clinicians were able to take the required primary prevention measures.

Atherosclerosis (AS), mainly caused by the changed immune system functions and inflammation, is the central pathogenesis of cardiovascular disease, which is a leading cause of death in the world. In modern medicine, the development of carriers precisely delivering the therapeutic agents to the target sites is the primary goal, which could minimize the potential adverse effects and be more effective in treating lesions. Due to the precise location, real-time monitoring, AS microenvironment response, and low toxicity, stimuli-responsive nano-based drug delivery systems (NDDSs) have been a promising approach in AS treatments. Herein, we will systematically summarize the recent advances in stimuli-responsive NDDSs for AS treatment, including internal stimuli (reactive oxygen species, enzyme, shear stress, and pH) and external stimuli (light, ultrasound, and magnetism) responsive NDDSs. Besides, we will also summarize in detail the classification of stimuli-responsive NDDSs for AS, such as organic NDDSs (e.g., lipid-based and polymer-based nanomaterials), inorganic NDDSs (e.g., metal-based nanoparticles and nonmetallic nanomaterials), and composite multifunctional NDDSs. Finally, the critical challenges and prospects of this field will also be proposed and discussed.

ADHD in children is one of the most common neurodevelopmental disorders. It is manifested as inattention, hyperactivity, impulsiveness, and other symptoms that are inconsistent with the developmental level in different occasions, accompanied by functional impairment in social, academic, and occupational aspects. At present, the treatment for children with ADHD is mainly based on psychological nursing intervention combined with drug therapy. Therefore, the actual efficacy evaluation of this treatment regimen is very important. Neural networks are widely used in smart medical care. This work combines artificial intelligence with the evaluation of clinical treatment effects of ADHD children and designs an intelligent model based on neural networks for evaluating the clinical efficacy of psychological nursing intervention combined with drug treatment of children with ADHD. The main research is that, for the evaluation of clinical treatment effect of ADHD in children, this paper proposes a 1D Parallel Multichannel Network (1DPMN), which is a convolutional neural network. The results show that network models can extract different data features through different channels and can achieve high accuracy evaluation of clinical efficacy of ADHD in children. On the basis of the model, performance is improved through the study of Adam optimizer to speed up the model convergence, adopts batch normalization algorithm to improve stability, and uses Dropout to improve the generalization ability of the network. Aiming at the problem of too many parameters, the 1DPMN is optimized through the principle of local sparseness, and the model parameters are greatly reduced.

OBJECTIVE To investigate the association of potential cardiovascular disease (CVD) biomarkers in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We enrolled 120 participants (aged 61.5–69.5 years) with type 2 diabetes and 60 (aged 62.5–73.5 years) with normal glucose tolerance in the discovery group from the original Da Qing Diabetes Study. Their diabetes status was confirmed in 1986; then, the participants were followed over 23 years to collect CVD outcome data. Untargeted and targeted metabolomics analyses based on ultra-high-performance liquid chromatography–tandem mass spectrometry were used to identify potential markers. Multivariable regression analysis was used to evaluate the association between metabolites and CVD outcomes. An independent group of 335 patients (aged 67.0–77.0 years) with diabetes was used for biomarker validation. RESULTS In the discovery group, untargeted metabolomics analysis found 16 lipids and fatty acids metabolites associated with CVD risk in patients with diabetes, with palmitoyl sphingomyelin (PSM) having the strongest association. Plasma PSM concentrations were significantly higher in cases of diabetes with CVD than without (41.68 ± 10.47 vs. 9.69 ± 1.47 μg/mL; P < 0.0001). The odds ratio (OR) of CVD for 1 µg/mL PSM change was 1.19 (95% CI 1.13–1.25) after adjustment of clinical confounders. The validation study confirmed that PSM was significantly associated with increased CVD risk in diabetes (OR 1.22 [95% CI 1.16–1.30]). CONCLUSIONS Changes in lipid and fatty acid content were significantly associated with CVD risk in the Chinese population with diabetes. PSM is a potential biomarker of increased CVD risk in diabetes.

Objective Nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) frequently coexist and can act synergistically to drive adverse outcomes of one another. This study aimed to unravel the metabolomic changes in patients with NAFLD and T2DM, to identify potential noninvasive biomarkers, and to provide insights for understanding the link between NAFLD and T2DM. Methods Three hundred participants aged 35 to 70 years who were diagnosed with NAFLD (n = 100), T2DM (n = 100), or a comorbidity of NAFLD and T2DM (n = 100) were included in this study. Anthropometrics and routine blood chemistry were assessed after overnight fast. The global serum metabolomic analysis was performed by ultra-performance liquid chromatography-Orbitrap mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Results A set of serum biomarkers that could effectively separate NAFLD from NAFLD + T2DM and T2DM from NAFLD + T2DM were identified. We found that patients with coexisting NAFLD and T2DM had significantly higher levels of total protein (TP), triglycerides (TG), glucose in urine, and gamma-hydroxybutyric acid than those with NAFLD and had significant increased levels of TP, albumin, alanine aminotransferase, aspartate aminotransferase, total cholesterol, cholinesterase, TG, low-density lipoprotein, and apolipoprotein A when compared to patients with T2DM. Conclusion The metabolomics results provide evidence that the comorbidity of NAFLD and T2DM considerably altered patients’ metabolomics patterns compared to those of patients with only NAFLD or T2DM.