Integrative analysis and risk model construction for super­enhancer­related immune genes in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer associated with poor prognosis, and accounts for the majority of RCC-related deaths. The lack of comprehensive diagnostic and prognostic biomarkers has limited further understanding of the pathophysiology of ccRCC. Super-enhancers (SEs) are congregated enhancer clusters that have a key role in tumor processes such as epithelial-mesenchymal transition, metabolic reprogramming, immune escape and resistance to apoptosis. RCC may also be immunogenic and sensitive to immunotherapy. In the present study, an Arraystar human SE-long non-coding RNA (lncRNA) microarray was first employed to profile the differentially expressed SE-lncRNAs and mRNAs in 5 paired ccRCC and peritumoral tissues and to identify SE-related genes. The overlap of these genes with immune genes was then determined to identify SE-related immune genes. A model for predicting clinical prognosis and response to immunotherapy was built following the comprehensive analysis of a ccRCC gene expression dataset from The Cancer Genome Atlas (TCGA) database. The patients from TCGA were divided into high- and low-risk groups based on the median score derived from the risk model, and the Kaplan-Meier survival analysis showed that the low-risk group had a higher survival probability. In addition, according to the receiver operating characteristic curve analysis, the risk model had more advantages than other clinical factors in predicting the overall survival (OS) rate of patients with ccRCC. Using this model, it was demonstrated that the high-risk group had a more robust immune response. Furthermore, 61 potential drugs with half-maximal inhibitory concentration values that differed significantly between the two patient groups were screened to investigate potential drug treatment of ccRCC. In summary, the present study provided a novel index for predicting the survival probability of patients with ccRCC and may provide some insights into the mechanisms through which SE-related immune genes influence the diagnosis, prognosis and potential treatment drugs of ccRCC.

Transformers-sklearn: a toolkit for medical language understanding with transformer-based models.

BACKGROUND: Transformer is an attention-based architecture proven the state-of-the-art model in natural language processing (NLP). To reduce the difficulty of beginning to use transformer-based models in medical language understanding and expand the capability of the scikit-learn toolkit in deep learning, we proposed an easy to learn Python toolkit named transformers-sklearn. By wrapping the interfaces of transformers in only three functions (i.e., fit, score, and predict), transformers-sklearn combines the advantages of the transformers and scikit-learn toolkits. METHODS: In transformers-sklearn, three Python classes were implemented, namely, BERTologyClassifier for the classification task, BERTologyNERClassifier for the named entity recognition (NER) task, and BERTologyRegressor for the regression task. Each class contains three methods, i.e., fit for fine-tuning transformer-based models with the training dataset, score for evaluating the performance of the fine-tuned model, and predict for predicting the labels of the test dataset. transformers-sklearn is a user-friendly toolkit that (1) Is customizable via a few parameters (e.g., model_name_or_path and model_type), (2) Supports multilingual NLP tasks, and (3) Requires less coding. The input data format is automatically generated by transformers-sklearn with the annotated corpus. Newcomers only need to prepare the dataset. The model framework and training methods are predefined in transformers-sklearn. RESULTS: We collected four open-source medical language datasets, including TrialClassification for Chinese medical trial text multi label classification, BC5CDR for English biomedical text name entity recognition, DiabetesNER for Chinese diabetes entity recognition and BIOSSES for English biomedical sentence similarity estimation. In the four medical NLP tasks, the average code size of our script is 45 lines/task, which is one-sixth the size of transformers' script. The experimental results show that transformers-sklearn based on pretrained BERT models achieved macro F1 scores of 0.8225, 0.8703 and 0.6908, respectively, on the TrialClassification, BC5CDR and DiabetesNER tasks and a Pearson correlation of 0.8260 on the BIOSSES task, which is consistent with the results of transformers. CONCLUSIONS: The proposed toolkit could help newcomers address medical language understanding tasks using the scikit-learn coding style easily. The code and tutorials of transformers-sklearn are available at https://doi.org/10.5281/zenodo.4453803 . In future, more medical language understanding tasks will be supported to improve the applications of transformers_sklearn.

Important scoring systems for assessing the severity of COVID-19 based on COVID-19-related deaths in Wuhan, China.

Background: This study aimed to investigate the clinical characteristics of 21 deaths and evaluate potential factors affecting disease severity and mortality risk in patients with coronavirus disease (COVID-19). Methods: This retrospective analysis assessed clinical data of 21 patients who died owing to COVID-19. Disease severity and mortality risk were assessed using Acute Physiology and Chronic Health Evaluation II (APACHE II); Sepsis-related Organ Failure Assessment (SOFA); multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension and age (MuLBSTA); and pneumonia severity index (PSI) scores. Results: The mean age of the patients was 66 ±â€Š14 years and 15 (71.4%) patients were men. Sixteen (76.2%) patients had chronic medical illnesses. Twelve (57.1%) patients were overweight. Decreased lymphocyte proportions were observed in 17 (81.0%) patients on admission. Elevated D-dimer levels were observed in 11 (52.4%) patients, and the levels significantly increased when pneumonia deteriorated. The initial APACHE II and SOFA scores demonstrated that 18 (85.7%) and 13 (61.9%) patients, respectively, were in the middle-risk level. MuLBSTA and PSI scores after admission were associated with higher risks of mortality in 13 (61.9%) patients. Most patients developed organ failure and subsequently died. Conclusions: Older, overweight, male patients with a history of chronic illnesses and continuously decreased lymphocyte proportions and increased D-dimer levels might have higher risks of death owing to COVID-19. The combination of general scoring (SOFA) and pneumonia-specific scoring (MuLBSTA and PSI) systems after admission might be sensitive in assessing the mortality risk of patients with COVID-19 who are in critical condition.

Aldehyde dehydrogenase 2 protects against sympathetic excitation-induced cardiac fibrosis.

Sympathetic stimulated-cardiac fibrosis imposes great significance on both disease progression and survival in the pathogenesis of many cardiovascular diseases. However, there are few effective therapies targeting it clinically. The cardioprotective effect of aldehyde dehydrogenase 2 (ALDH2) has been explored in many pathological conditions, whether it can exert benefit effects on chronic sympathetic stimulus-induced cardiac fibrosis remains unclear. In this study, we determined to explore the role of ALDH2 on isoproterenol (ISO)-induced cardiac fibroblasts (CF) proliferation and cardiac fibrosis. It was found that ALDH2 enzymatic activity was impaired in ISO-induced HCF proliferation and Aldh2 deficiency promoted mouse CF proliferation. Alda-1, an ALDH2 activator, exerted obvious suppressive effect on ISO-induced HCF proliferation, together with the induction of cell cycle arrest at G0/G1 phase and decreased expression of cyclin E1 and cyclin-dependent kinase 2 (CDK2). Mechanistically, the inhibitory role of Alda-1 on HCF proliferation was achieved by decreasing mitochondrial reactive oxygen species (ROS) production, which was partially reversed by rotenone, an inducer of ROS. In addition, wild-type mice treated with Alda-1 manifested with reduced fibrosis and better cardiac function after ISO pump. In summary, Alda-1 alleviates sympathetic excitation-induced cardiac fibrosis via decreasing mitochondrial ROS accumulation, highlighting ALDH2 activity as a promising drug target of cardiac fibrosis.

ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application.

BACKGROUND: The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians' healthcare practice, patients' health management and public health literacy. High-quality corpus containing cancer information is the necessary foundation of cancer education. Massive non-structural information resources exist in clinical narratives, electronic health records (EHR) etc. They can only be used for training AI models after being transformed into structured corpus. However, the scarcity of multilingual cancer corpus limits the intelligent processing, such as machine translation in medical scenarios. Thus, we created the cancer specific cross-lingual corpus and open it to the public for academic use. METHODS: Aiming to build an English-Chinese cancer parallel corpus, we developed a workflow of seven steps including data retrieval, data parsing, data processing, corpus implementation, assessment verification, corpus release, and application. We applied the workflow to a cross-lingual, comprehensive and authoritative cancer information resource, PDQ (Physician Data Query). We constructed, validated and released the parallel corpus named as ECCParaCorp, made it openly accessible online. RESULTS: The proposed English-Chinese Cancer Parallel Corpus (ECCParaCorp) consists of 6685 aligned text pairs in Xml, Excel, Csv format, containing 5190 sentence pairs, 1083 phrase pairs and 412 word pairs, which involved information of 6 cancers including breast cancer, liver cancer, lung cancer, esophageal cancer, colorectal cancer, and stomach cancer, and 3 cancer themes containing cancer prevention, screening, and treatment. All data in the parallel corpus are online, available for users to browse and download ( http://www.phoc.org.cn/ECCParaCorp/ ). CONCLUSIONS: ECCParaCorp is a parallel corpus focused on cancer in a cross-lingual form, which is openly accessible. It would make up the imbalance of scarce multilingual corpus resources, bridge the gap between human readable information and machine understanding data resources, and would contribute to intelligent technology application as a preparatory data foundation e.g. cancer-related machine translation, cancer system development towards medical education, and disease-oriented knowledge extraction.

A small-molecule activator of mitochondrial aldehyde dehydrogenase 2 reduces the severity of cerulein-induced acute pancreatitis.

Acute pancreatitis (AP) is one of the leading causes of hospital admission for gastrointestinal disorders. Although lipid peroxides are produced in AP, it is unknown if targeting lipid peroxides prevents AP. This study aimed to investigate the role of mitochondrial aldehyde dehydrogenase 2 (ALDH2), a critical enzyme for lipid peroxide degradation, in AP and the possible underlying mechanisms. Cerulein was used to induce AP in C57BL/6 J male mice and pancreatic acinar cells were used to elucidate underlying mechanisms in vitro. Pancreatic enzymes in the serum, lipid peroxidation products malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE), and Bcl-2, Bax and cleaved caspase-3 were measured. ALDH2 activation with a small-molecule activator, Alda-1, reduced the levels of the pancreatic enzymes in the serum and the lipid peroxidation products MDA and 4-HNE. In addition, Alda-1 decreased Bax and cleaved caspase-3 expression and increased Bcl-2 expression in vivo and in vitro. In conclusion, ALDH2 activation by Alda-1 has a protective effect in cerulein-induced AP by mitigating apoptosis in pancreatic acinar cells by alleviating lipid peroxidation.

TestIME: an application for evaluating the efficiency of Chinese input method engines in electronic medical record entry task.

BACKGROUND: With the wide application of Electronic Medical Record (EMR) systems, it has become a daily work for doctors using keyboards to input clinical information into the EMR system. Chinese Input Method Engine (IME) is essential for doctors to convert pinyin to Chinese characters, and an efficient IME would improve doctors' healthcare work. We developed a tool (called TestIME) to evaluating the efficiency of the current IMEs used in doctors' working scenario. The proposed TestIME consists of four major function modules: 1) Test tasks assignment, to ensure that participants using different IMEs to complete the same test task in a random order; 2) IME automatic switching, to automatically switch the input method engines without changing the experimental settings; 3) participants' behavior monitoring, to record the participants' keystrokes and timestamp during the typing process; 4) questionnaire, to collect the participants' subjective data. In addition, we designed a preliminary experiment to demonstrate the usability of TestIME. We selected three sentences from EMR corpus and news corpus as test texts respectively, and recruited four participants in a medical school to complete text entry tasks using the TestIME. RESULTS: Our TestIME was able to generate 72 files that record the detailed participants' keyboard behavior while transcribing test texts, and 4 questionnaires that reflect participants' psychological states. These profiles can be downloaded in a structured format (CSV) from the TestIME for further analysis. CONCLUSIONS: We developed a tool (TestIME) to evaluate Chinese input methods in the EMR entry tasks. In the given text input scenario in healthcare, the TestIME is capable to record doctors' keyboard behavior, frequently used Chinese terms, IME usability feedback etc. These user profiles are important to improve current IME tools for doctors and further improve healthcare service.

Appropriate dose of ethanol exerts anti-senescence and anti-atherosclerosis protective effects by activating ALDH2.

Moderate alcohol consumption has been shown to reduce atherosclerosis-associated diseases. As shown in our earlier works, ethanol has a dose-dependent protective effects against endothelial cellular senescence by activating aldehyde dehydrogenase 2 (ALDH2) in vitro. However, whether ethanol administration possesses anti-atherosclerosis properties and whether ALDH2 is involved in the underlying mechanisms are unknown. In the present study, we revealed that the appropriate dose of ethanol reduced atherosclerotic plaque formation, and upregulated ALDH2 expression and activity in ApoE-/- mice. ALDH2 deficiency blocked the protection of ethanol against atherosclerotic plaque formation by inhibiting endothelium senescence. In contrast, Alda-1, which is a specific enzymatic agonist of ALDH2, enhanced the anti-senescence and anti-atherosclerosis effects of the appropriate dose of ethanol. Furthermore, following ALDH2 knockdown, resveratrol (an anti-aging compound) recovered the beneficial effects of ethanol against endothelial senescence in vitro. Thus, these results suggest that the appropriate dose of ethanol has protective effects against endothelial senescence and atherosclerosis by activating ALDH2.

ALDH2 Activation Inhibited Cardiac Fibroblast-to-Myofibroblast Transformation Via the TGF-ß1/Smad Signaling Pathway.

Pathological stimulus-triggered differentiation of cardiac fibroblasts plays a major role in the development of myocardial fibrosis. Aldehyde dehydrogenase 2 (ALDH2) was reported to exert a protective role in cardiovascular disease, and whether ALDH2 is involved in cardiac fibroblast differentiation remains unclear. In this study, we used transforming growth factor-ß1 (TGF-ß1) to induce the differentiation of human cardiac fibroblasts (HCFs) and adopted ALDH2 activator Alda-1 to verify the influence of ALDH2 on HCF differentiation. Results showed that ALDH2 activity was obviously impaired when treating HCFs with TGF-ß1. Activation of ALDH2 with Alda-1 inhibited the transformation of HCFs into myofibroblasts, demonstrated by the decreased smooth muscle actin (α-actin) and periostin expression, reduced HCF-derived myofibroblast proliferation, collagen production, and contractility. Moreover, application of Smad2/3 inhibitor alleviated TGF-ß1-induced HCF differentiation and improved ALDH2 activity, which was reversed by the application of ALDH2 inhibitor daidzin. Finally, Alda-1-induced HCF alterations alleviated neonatal rat cardiomyocyte hypertrophy, supported by the immunostaining of α-actin. To summarize, activation of ALDH2 enzymatic activity inhibited the differentiation of cardiac fibroblasts via the TGF-ß1/Smad signaling pathway, which might be a promising strategy to relieve myocardial fibrosis of various causes.

Postinfarction Hearts Are Protected by Premature Senescent Cardiomyocytes Via GATA 4-Dependent CCN 1 Secretion.

Background Stress-induced cell premature senescence participates in a variety of tissue and organ remodeling by secreting such proteins as proinflammatory cytokines, chemokines, and growth factors. However, the role of cardiomyocyte senescence in heart remodeling after acute myocardial infarction has not been thoroughly elucidated to date. Therefore, we sought to clarify the impact of premature myocardial senescence on postinfarction heart function. Methods and Results Senescence markers, including p16 INK4a, p21 CIP1/WAF1, and SA -ß-gal staining, were analyzed in several heart disease models by immunostaining. Both postinfarction mouse hearts and ischemic human myocardium demonstrated increased senescence markers. Additionally, senescence-related secretory phenotype was activated after acute myocardial infarction, which upregulated senescence-related secretory phenotype factors, including CCN family member 1 ( CCN 1), interleukin-1α, tumor necrosis factor α, and monocyte chemoattractant protein-1. In vivo, a tail vein injection of AAV 9- Gata4-sh RNA significantly attenuated senescence-related secretory phenotype secretion and aggravated postinfarction heart dysfunction. Furthermore, among activated senescence-related secretory phenotype factors, CCN 1 administration reduced myofibroblast viability in vitro and rescued the deleterious effect of AAV 9- Gata4-sh RNA in vivo. Conclusions Myocardial premature senescence was observed in the ischemic hearts and improved postinfarction heart function, partly through the GATA-binding factor 4- CCN 1 pathway.

ALDH2 mediates the dose-response protection of chronic ethanol against endothelial senescence through SIRT1/p53 pathway.

Aldehyde dehydrogenase 2 (ALDH2) plays essential roles in drinking-associated diseases or effects. As we have previously reported, ALDH2 mediates acute ethanol-induced eNOS activation in vitro. However, whether chronic ethanol treatment has a dose-response endothelial protection, as well as the possible mediating role of ALDH2 involved, is unclear. Here, we show that appropriate dose of ethanol preserved the expression and activity of ALDH2 and eNOS, and alleviated senescence-associated phenotypes in human aortic endothelial cells. Furthermore, ALDH2 deficiency impairs the dose-response protection of ethanol against endothelial senescence by promoting the accumulation of 4-HNE, the formation of 4-HNE-SIRT1 protein adducts and the subsequent decrease in SIRT1-dependent p53 deacetylation. Collectively, our data indicate that ALDH2 mediates the protection of appropriate ethanol by modulating SIRT1/p53-dependent endothelial senescence.

Vaspin alleviates myocardial ischaemia/reperfusion injury via activating autophagic flux and restoring lysosomal function.

Visceral adipose tissue-derived serine protease inhibitor (vaspin), as a secretory adipokine, was reported to exert a protective role on insulin resistance. Recent studies showed that serum vaspin level was downregulated in patients with coronary artery disease. However, whether vaspin exerted specific effects on myocardial injury remains unknown. In this study, we determined to explore the role of vaspin overexpression in myocardial ischaemia/reperfusion (I/R) injury and the underlying mechanisms. Our results showed that the systemic delivery of adeno-associated virus-vaspin to mice reduced myocardial infarct size and apoptosis, and improved cardiac function after reperfusion, accompanied with upregulated autophagic flux and restored lysosomal function in the ischaemic heart. Blockage of the autophagic flux with choroquine mitigated the protection of vaspin on myocardial I/R injury. Moreover, we testified that administration of exogenous recombinant human vaspin on cultured cardiomyocytes suppressed hypoxia/reoxygenation-induced apoptosis, through the AMPK-mTOR-upregulated autophagic flux. Overall, we verified that vaspin functions as an adipokine which can alleviate I/R injury in the heart by suppressing myocardial apoptosis through AMPK-mTOR-dependent activation of autophagic flux, and then provided a potential breakthrough in the treatment of myocardial I/R injury and other ischaemic diseases.