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• The in-hospital mortality for AMI in the training, testing, and validation sets were 5.7 %, 5.6 %, and 6.0 %, respectively. • The top 8 predictors were D-Dimer, brain natriuretic peptide, cardiogenic shock, neutrophil, prothrombin time, blood urea nitrogen, cardiac arrest, and phosphorus. • Bagging has good predictive value and certain clinical value in external validation with AUROC 0.893. Persistent efforts are required to further reduce the in-hospital mortality of patients suffering from acute myocardial infarction (AMI), even in the face of a global trend of declining AMI-related fatalities. We investigated deep machine learning models for in-hospital death prediction in patients on their first AMI. In this 2-center retrospective analysis, first AMI patients from Hospital I and Hospital II were included; 4783 patients from Hospital 1 were split in a 7:3 ratio between the training and testing sets. Data from 1053 AMI patients in Hospital II was used for further validation. 70 clinical information and laboratory examination parameters as predictive indicators were included. Logistic Regression Classifier (LR), Random Forests Classifier (RF), eXtreme Gradient Boosting (XGB), Support Vector Machine Classifier (SVM), Multilayer Perceptron (MLP), Gradient Boosting Machine (GBM), Bootstrapped Aggregation (Bagging) models with AMI patients were developed. The importance of selected variables was obtained through the Shapley Additive exPlanations (SHAP) method. The performance of each model was shown using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (Average Precision; AP). Result: The in-hospital mortality for AMI in the training, testing, and validation sets were 5.7 %, 5.6 %, and 6.0 %, respectively. The top 8 predictors were D-dimer, brain natriuretic peptide, cardiogenic shock, neutrophil, prothrombin time, blood urea nitrogen, cardiac arrest, and phosphorus. In the testing cohort, the models of LR, RF, XGB, SVM, MLP, GBM, and Bagging yielded AUROC values of 0.929, 0.931, 0.907, 0.868, 0.907, 0.923, and 0.932, respectively. Bagging has good predictive value and certain clinical value in external validation with AUROC 0.893. In order to improve the forecasting accuracy of the risk of AMI patients, guide clinical nursing practice, and lower AMI inpatient mortality, this study looked into significant indicators and the optimal models for predicting AMI inpatient mortality. [ABSTRACT FROM AUTHOR]

The Regorafenib is a broad-spectrum kinase inhibitor that has been approved to treat colorectal cancer (CRC). However, evidences have shown that the agent is also implicated in drug interaction with microRNA-21 (miR-21), an oncogenic miRNA which plays a key role in resisting programmed cell death in CRC cells. Here, we supposed that, instead of kinase inhibition, Regorafenib can directly bind to and then stabilize miR-21 pre-element, thus preventing RNase Dicer-meditated cleavage of the pre-element to mature miR-21. In order to verify the notion, an in silico-in vitro integrated investigation of the direct intermolecular interaction between Regorafenib and miR-21 pre-element was performed by using active pocket identification, RNA–ligand docking, molecular dynamics (MD) simulation, binding energetic analysis, and fluorescence-based assay. It was revealed that the Regorafenib can bind at the major groove-like stem region of miR-21 pre-element through three geometrically satisfactory hydrogen bonds (H-bonds) as well as a number of hydrophobic forces and π-π stacking, conferring strong specificity and high stability to the RNA–ligand complex system ( K d = 0.73 μM). Separate inversion mutation of two base pairs (G6C, C12G) and (A13U, U4A) that are involved in the H-bonding can considerably impair the affinity of Regorafenib to miR-21 pre-element, with K d increase to 27 and 96 μM, respectively. All these supported that Regorafenib can directly bind to miR-21 pre-element at molecular level and the binding mode can be properly modeled by using the proposed integrated strategy. This study would provide a potential, alternative mechanism for anti-colorectal cancer chemotherapy with Regorafenib. [ABSTRACT FROM AUTHOR]

The long noncoding RNAs MEG3 is involved in the pathogenesis and metastasis of cancer, which has been found to target the distal regulatory elements (DREs) of TGF‐β pathway genes TGFBR1, TGFB2, and SMAD2 by forming DNA‐RNA triplex. Here, the molecular mechanism of MEG3 binding to its cognate or noncognate DNA partners is investigated systematically via an integrative chemometric approach. Here, we apply a spatial information characterization technique to capture the structural and energetic features of DNA‐RNA triplex architecture and then to correlate the extracted features with binding potency of the triplex complexes. A genome‐wide statistical analysis strategy is used to quantitatively evaluate the intermolecular interaction between DNA with RNA in a high‐throughput manner. The strategy is then employed to examine the binding potency and recognition specificity of MEG3 with its interacting DRE partners TGFBR1, TGFB2, and SMAD2. As might be expected, the abundance of GA nucleotide residues in DNA core motif exhibits a positive correlation with the affinity of MEG3 binding to the DREs of TGF‐β pathway, while the MEG3 possesses a moderate specificity for its known cognate DNA partners on the background of numerous random decoys. Therefore, it is suggested that the MEG3 has a broad spectrum of potential targets in the human genome and may regulate diverse cell biological events. The sequence‐specific recognition in intermolecular interaction between cancer MEG3 lncRNA and its cognate or noncognate TGF‐β pathway DNA is investigated in a genome‐wide background via an integrative chemometric approach. It is revealed that the GA abundance of DNA exhibits a positive correlation with the affinity of MEG3 binding to TGF‐β genes and the MEG3 possesses a moderate specificity for its cognate DNA partners. [ABSTRACT FROM AUTHOR]

Papillary Thyroid Cancer (PTC) represents a commonly encountered type of thyroid malignancy whose occurrence and development is influenced by long non-coding RNA (LncRNA). A novel lncRNA (LncRNA AK023507), known to have tumor suppressive functions, was shown to prevent breast cancer cells from proliferating and metastasizing, but its mechanism in PTC is unclear. Using PTC tissues and cell lines, the expression of LncRNA AK023507 was investigated by quantitative Real-time Polymerase Chain Reaction (qRT-PCR). The effects of knockdown or overexpression of LncRNA AK023507 on cell growth and movement were investigated through various cell experiments in vitro. The presence of important functional proteins was determined by Western blotting, with the recovery experiment used for verification. LncRNA AK023507 was found to have low expression in both the PTC cell lines and tissue samples. Knockdown of LncRNA AK023507 in PTC cells significantly promoted cell proliferation, migration, and invasion, while overexpression of LncRNA AK023507 resulted in the opposite effects. Furthermore, LncRNA AK023507 could regulate the expression of β-catenin/Wnt signaling pathway as confirmed by recovery experiment. By acting through the β-catenin/Wnt signaling pathway, LncRNA AK023507 prevented PTC cells from proliferating and metastasizing. These novel findings indicate that LncRNA AK023507 could be of prognostic and diagnostic value as a potential biomarker of PTC. • LncRNA AK023507 was found to have low expression in both the PTC cell lines and tissue samples. • LncRNA AK023507 inhibits cell metastasis and proliferation in Papillary Thyroid Cancer. • LncRNA AK023507 prevented PTC cells from metastasizing through the β-catenin/Wnt signaling pathway. [ABSTRACT FROM AUTHOR]

Background: Palbociclib was the only available cyclin‐dependent kinase 4/6 inhibitor in China until very recently, and its effect has not been systemically evaluated among Chinese patients. This study aims to assess the efficacy, safety and patient‐reported outcomes (PROs) of palbociclib plus endocrine therapy (ET) in real‐world China. Methods: An ambispective cohort study was conducted on patients with advanced HR+HER2− breast cancer who received palbociclib between July 2018, and November 2020 and were enrolled from 12 hospitals. Treatment patterns, survival outcomes, and safety events were documented, and PROs (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire‐Core 30 items [EORTC QLQ‐C30] and EuroQoL 5 dimensions [EQ‐5D]) were analyzed. The Kaplan–Meier method was used to visualize and estimate the median progression‐free survival (mPFS). Log‐rank tests, Cox regressions, t tests, and chi‐square tests were performed for comparison. Results: A total of 190 patients (median follow‐up of 18.0 months) were enrolled. Palbociclib was mostly combined with aromatase inhibitors (66.3%), fulvestrant (32.6%), and tamoxifen (1.1%). The mPFS values were 21.0, 14.0, and 7.0 months with palbociclib administered in first‐ (n = 83), second‐ (n = 41) and subsequent‐line settings (n = 66), respectively. Endocrine sensitivity was significantly associated with patient prognosis (mPFS: 23.0, 12.0, and 6.0 months for endocrine naïve, acquired, and primary resistant patients, respectively, p < 0.01). The outcome was worse for patients who failed to meet the inclusion criteria of PALOMA‐3 than for those who met the criteria (later‐line: 6.0 months vs. 9.0 months). The most common adverse events (AEs) were neutropenia (74.2%; grade 3/4: 30.0%), fatigue (48.4%), anemia (32.6%), and thrombocytopenia (22.1%). PRO data suggested that palbociclib plus ET significantly improved cognitive and emotional function, pain symptoms, and overall quality of life. Conclusions: Palbociclib is effective for front‐line use and for treating endocrine‐sensitive patients in real‐world China and is generally well tolerated. The prevalence of AEs in the Chinese population is different from that reported in the PALOMA‐2/3 trials. [ABSTRACT FROM AUTHOR]

Autoimmune thyroid diseases (AITDs) including Graves' disease (GD) and Hashimoto's thyroiditis (HT) are common autoimmune endocrine disorders. Interleukin-4 (IL-4), a cytokine secreted by T cells, plays a critical role in antigen-specific Th2 responses. The IL-4 gene is highly polymorphic and it has been reported that the polymorphism at -590 (T/C, rs2243250) in the promoter region of IL-4 may contribute to the development of AITDs. Recently, several case-control studies have examined the association of genetic variants of IL-4 with AITDs. However, the results of these studies remain conflicting. To systematically study the role of IL-4 in the pathogenesis of AITDs, we conducted a meta-analysis including 11 eligible studies (1847 cases and 2068 healthy controls). Fixed-effect or random-effect models were used to calculate pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Our results revealed a significant association between the IL-4 genetic variant (−590, T/C, rs2243250) and the risk of developing AITDs (TC + TT versus TT genotype: OR = 1.83, 95% CI = 1.083-3.091, p = 0.024). These findings demonstrate that the IL-4 rs2243250 genetic variant might play a key role in the development of AITDs. [ABSTRACT FROM AUTHOR]

Gastric cancer remains the second most common cause of cancer-related death worldwide. Because of the poor prognosis of late-stage gastric cancer patients, it is imperative to develop new strategies to improve the survival rate of this disease. Currently, immunotherapy is considered as an innovative approach for cancers such as lung cancer, gastric cancer and breast cancer. In fact, previous works have revealed promising results in this field. With further understanding of immunogenomics of gastric cancer, new immune checkpoint regulators could become more important. In addition, whole-genome sequencing and genome editing provide us with more information on the heterogeneity of gastric cancer, showing helpful tools to identify new predictive biomarkers and to achieve personalized treatment. Further research and better understanding of the functions of immune system will enhance immunotherapy treatment in the future. [ABSTRACT FROM AUTHOR]