Contextual Similarity is More Valuable than Character Similarity: Curriculum Learning for Chinese Spell Checking

Chinese Spell Checking (CSC) task aims to detect and correct Chinese spelling errors. In recent years, related researches focus on introducing the character similarity from confusion set to enhance the CSC models, ignoring the context of characters that contain richer information. To make better use of contextual similarity, we propose a simple yet effective curriculum learning framework for the CSC task. With the help of our designed model-agnostic framework, existing CSC models will be trained from easy to difficult as humans learn Chinese characters and achieve further performance improvements. Extensive experiments and detailed analyses on widely used SIGHAN datasets show that our method outperforms previous state-of-the-art methods

Preventive Effect of Chimonanthus praecox Flower Extract on High-fat Diet-induced Obesity in Mice

Objective: To study the preventive effect of ethanolic extract from Chimonanthus praecox flower on obesity induced by high-fat diet in mice. Methods: A total of 50 C57BL/6 mice were divided into five groups of blank control, model control, low-, medium- and high-dose Chimonanthus praecox flower extract (CPFE) treatment. The mice in the blank control group were provided with a basal diet whereas those in the other groups were given a high-fat diet. The mice in the low-, medium- and high-dose groups were orally administered with CPFE at doses of 0.2, 0.4 and 0.8 g/(kg mb·d), containing 24.81, 49.62 and 99.25 mg/(kg mb·d) of Chimonanthus praecox flower polyphenols, respectively. The blank control, model control groups were administered with 0.9% NaCl. The administration lasted for 4 weeks. Then, body weight, serum biochemical indicators, organ antioxidant capacity were measured and pathological sections of liver tissue were examined. Results: The body weight, liver coefficient, serum levels of TC, LDL-C, organ levels of MDA in the model control group were significantly higher than those in the blank control group (P<0.05). The levels of organ GSH-Px, CAT, SOD, GSH in the model control group were significantly lower than those in the blank control group (P<0.05). Pathological examination showed that compared with the blank control group, the structure of liver lobules was irregular, the cell morphology was destroyed, vacuolar degeneration occurs, and the hepatic cord was not clear, and the hepatic sinuses were squeezed and deformed, indicating successful obesity induction in mice. In addition, compared with the model control group, the CPFE especially at the high dose lowered serum TC, LDL-C, TG, organ MDA in obese mice (P<0.05) and increased serum HDL-C levels, organ GSH-Px, CAT, SOD, GSH levels, and the effect was dose-effective with the concentration of CPFE. Pathological status of the organ were improved compared to the model control group, as evidenced by a more intact liver histomorphology and structure. The extract also reduced the body weight and liver index of obese mice and the effect was more pronounced in the high dose group. Conclusion: The CPFE have the effects of lowering serum cholesterol, enhancing antioxidant capacity and protecting the functional morphology of liver tissue cells in mice

Comparative transcriptome analysis reveals gene network regulation of TGase-induced thermotolerance in tomato

Transglutaminase (TGase), the ubiquitous protein in plants, catalyzes the post-translational transformation of proteins and plays a vital role in photosynthesis. However, its role and mechanism in tomato subjected to heat stress still remain unknown. Here, we carried out a transcriptomic assay to compare the differentially expressed genes (DEGs) between wild type (WT) and TGase overexpression (TGaseOE) plants employed to high-temperature at 42 °C and samples were collected after 0, 6, and 12 h, respectively. A total of 11,516 DEGs were identified from heat-stressed seedlings, while 1,148 and 1,353 DEGs were up-and down-regulated, respectively. The DEGs upon high-temperature stress were closely associated with the pathways encompassing protein processing in the endoplasmic reticulum, carbon fixation, and photosynthetic metabolism. In addition, 425 putative transcription factors (TFs) were identified, and the majority of them associated with the bHLH, HSF, AP2/ERF, MYB, and WRKY families. RNA-seq data validation further confirmed that 8 genes were linked to protein processing and photosynthesis, and the mRNA level of these genes in TGaseOE was higher than that in WT plants, which is consistent in transcriptome results. In conclusion, these results reveal the transcriptional regulation between WT and TGaseOE in tomato under heat stress and shed light on a new dimension of knowledge of TGase-mediated thermotolerance mechanism at the molecular level

A COVID-19 Risk Score Combining Chest CT Radiomics and Clinical Characteristics to Differentiate COVID-19 Pneumonia From Other Viral Pneumonias

With the continued transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world, identification of highly suspected COVID-19 patients remains an urgent priority. In this study, we developed and validated COVID-19 risk scores to identify patients with COVID-19. In this study, for patient-wise analysis, three signatures, including the risk score using radiomic features only, the risk score using clinical factors only, and the risk score combining radiomic features and clinical variables, show an excellent performance in differentiating COVID-19 from other viral-induced pneumonias in the validation set. For lesion-wise analysis, the risk score using three radiomic features only also achieved an excellent AUC value. In contrast, the performance of 130 radiologists based on the chest CT images alone without the clinical characteristics included was moderate as compared to the risk scores developed. The risk scores depicting the correlation of CT radiomics and clinical factors with COVID-19 could be used to accurately identify patients with COVID-19, which would have clinically translatable diagnostic and therapeutic implications from a precision medicine perspective

Transcriptional Activation of OsDERF1 in OsERF3 and OsAP2-39 Negatively Modulates Ethylene Synthesis and Drought Tolerance in Rice

The phytohormone ethylene is a key signaling molecule that regulates a variety of developmental processes and stress responses in plants. Transcriptional modulation is a pivotal process controlling ethylene synthesis, which further triggers the expression of stress-related genes and plant adaptation to stresses; however, it is unclear how this process is transcriptionally modulated in rice. In the present research, we report the transcriptional regulation of a novel rice ethylene response factor (ERF) in ethylene synthesis and drought tolerance. Through analysis of transcriptional data, one of the drought-responsive ERF genes, OsDERF1, was identified for its activation in response to drought, ethylene and abscisic acid. Transgenic plants overexpressing OsDERF1 (OE) led to reduced tolerance to drought stress in rice at seedling stage, while knockdown of OsDERF1 (RI) expression conferred enhanced tolerance at seedling and tillering stages. This regulation was supported by negative modulation in osmotic adjustment response. To elucidate the molecular basis of drought tolerance, we identified the target genes of OsDERF1 using the Affymetrix GeneChip, including the activation of cluster stress-related negative regulators such as ERF repressors. Biochemical and molecular approaches showed that OsDERF1 at least directly interacted with the GCC box in the promoters of ERF repressors OsERF3 and OsAP2-39. Further investigations showed that OE seedlings had reduced expression (while RI lines showed enhanced expression) of ethylene synthesis genes, thereby resulting in changes in ethylene production. Moreover, overexpression of OsERF3/OsAP2-39 suppressed ethylene synthesis. In addition, application of ACC recovered the drought-sensitive phenotype in the lines overexpressing OsERF3, showing that ethylene production contributed to drought response in rice. Thus our data reveal that a novel ERF transcriptional cascade modulates drought response through controlling the ethylene synthesis, deepening our understanding of the regulation of ERF proteins in ethylene related drought response

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research

Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke

Importance It is uncertain whether intravenous methylprednisolone improves outcomes for patients with acute ischemic stroke due to large-vessel occlusion (LVO) undergoing endovascular thrombectomy. Objective To assess the efficacy and adverse events of adjunctive intravenous low-dose methylprednisolone to endovascular thrombectomy for acute ischemic stroke secondary to LVO. Design, Setting, and Participants This investigator-initiated, randomized, double-blind, placebo-controlled trial was implemented at 82 hospitals in China, enrolling 1680 patients with stroke and proximal intracranial LVO presenting within 24 hours of time last known to be well. Recruitment took place between February 9, 2022, and June 30, 2023, with a final follow-up on September 30, 2023.InterventionsEligible patients were randomly assigned to intravenous methylprednisolone (n = 839) at 2 mg/kg/d or placebo (n = 841) for 3 days adjunctive to endovascular thrombectomy. Main Outcomes and Measures The primary efficacy outcome was disability level at 90 days as measured by the overall distribution of the modified Rankin Scale scores (range, 0 [no symptoms] to 6 [death]). The primary safety outcomes included mortality at 90 days and the incidence of symptomatic intracranial hemorrhage within 48 hours. Results Among 1680 patients randomized (median age, 69 years; 727 female [43.3%]), 1673 (99.6%) completed the trial. The median 90-day modified Rankin Scale score was 3 (IQR, 1-5) in the methylprednisolone group vs 3 (IQR, 1-6) in the placebo group (adjusted generalized odds ratio for a lower level of disability, 1.10 [95% CI, 0.96-1.25]; P = .17). In the methylprednisolone group, there was a lower mortality rate (23.2% vs 28.5%; adjusted risk ratio, 0.84 [95% CI, 0.71-0.98]; P = .03) and a lower rate of symptomatic intracranial hemorrhage (8.6% vs 11.7%; adjusted risk ratio, 0.74 [95% CI, 0.55-0.99]; P = .04) compared with placebo. Conclusions and Relevance Among patients with acute ischemic stroke due to LVO undergoing endovascular thrombectomy, adjunctive methylprednisolone added to endovascular thrombectomy did not significantly improve the degree of overall disability.Trial RegistrationChiCTR.org.cn Identifier: ChiCTR210005172

Bayesian analysis of series system with dependent causes of failure

Most studies of series system assume the causes of failure are independent, which may not hold in practice. In this paper, dependent causes of failure are considered by using a Marshall–Olkin bivariate Weibull distribution. We derived four reference priors based on several grouping orders. Gibbs sampling combined with the rejection sampling algorithm and Metropolis–Hastings algorithm is developed to obtain the estimates of the unknown parameters. The proposed approach is compared with the maximum-likelihood method via simulation. We find that the root-mean-squared errors of the Bayesian estimates are much smaller for the case of small sample size, and that the coverage probabilities of the Bayesian estimates are much closer to the nominal levels. Finally, a real data-set is analysed for illustration

Research on three-step accelerated gradient algorithm in deep learning

Gradient descent (GD) algorithm is the widely used optimisation method in training machine learning and deep learning models. In this paper, based on GD, Polyak's momentum (PM), and Nesterov accelerated gradient (NAG), we give the convergence of the algorithms from an initial value to the optimal value of an objective function in simple quadratic form. Based on the convergence property of the quadratic function, two sister sequences of NAG's iteration and parallel tangent methods in neural networks, the three-step accelerated gradient (TAG) algorithm is proposed, which has three sequences other than two sister sequences. To illustrate the performance of this algorithm, we compare the proposed algorithm with the three other algorithms in quadratic function, high-dimensional quadratic functions, and nonquadratic function. Then we consider to combine the TAG algorithm to the backpropagation algorithm and the stochastic gradient descent algorithm in deep learning. For conveniently facilitate the proposed algorithms, we rewite the R package ‘neuralnet’ and extend it to ‘supneuralnet’. All kinds of deep learning algorithms in this paper are included in ‘supneuralnet’ package. Finally, we show our algorithms are superior to other algorithms in four case studies