MuCoCP: a priori chemical knowledge-based multimodal contrastive learning pre-trained neural network for the prediction of cyclic peptide membrane penetration ability.

MOTIVATION: There has been a burgeoning interest in cyclic peptide therapeutics due to their various outstanding advantages and strong potential for drug formation. However, it is undoubtedly costly and inefficient to use traditional wet lab methods to clarify their biological activities. Using artificial intelligence instead is a more energy-efficient and faster approach. MuCoCP aims to build a complete pre-trained model for extracting potential features of cyclic peptides, which can be fine-tuned to accurately predict cyclic peptide bioactivity on various downstream tasks. To maximize its effectiveness, we use a novel data augmentation method based on a priori chemical knowledge and multiple unsupervised training objective functions to greatly improve the information-grabbing ability of the model. RESULTS: To assay the efficacy of the model, we conducted validation on the membrane-permeability of cyclic peptides which achieved an accuracy of 0.87 and R-squared of 0.503 on CycPeptMPDB using semi-supervised training and obtained an accuracy of 0.84 and R-squared of 0.384 using a model with frozen parameters on an external dataset. This result has achieved state-of-the-art, which substantiates the stability and generalization capability of MuCoCP. It means that MuCoCP can fully explore the high-dimensional information of cyclic peptides and make accurate predictions on downstream bioactivity tasks, which will serve as a guide for the future de novo design of cyclic peptide drugs and promote the development of cyclic peptide drugs. AVAILABILITY AND IMPLEMENTATION: All code used in our proposed method can be found at https://github.com/lennonyu11234/MuCoCP.

Linc01588 deletion inhibits the malignant biological characteristics of hydroquinone-induced leukemic cells via miR-9-5p/SIRT1.

Leukemia caused by environmental chemical pollutants has attracted great attention, the malignant leukemic transformation model of TK6 cells induced by hydroquinone (HQ) has been previously found in our team. However, the type of leukemia corresponding to this malignant transformed cell line model needs further study and interpretation. Furthermore, the molecular mechanism of malignant proliferation of leukemic cells induced by HQ remains unclear. This study is the first to reveal the expression of aberrant genes in leukemic cells of HQ-induced malignant transformation, which may correspond to chronic lymphocytic leukemia (CLL). The expression of Linc01588, a long non-coding RNA (lncRNA), was significantly up-regulated in CLL patients and leukemic cell line model which previously described. After gain-of-function assays and loss-of-function assays, feeble cell viability, severe apoptotic phenotype and the increased secretion of TNF-α were easily observed in malignant leukemic TK6 cells with Linc01588 deletion after HQ intervention. The tumors derived from malignant TK6 cells with Linc01588 deletion inoculated subcutaneously in nude mice were smaller than controls. In CLL and its cell line model, the expression of Linc01588 and miR-9-5p, miR-9-5p and SIRT1 were negative correlation respectively in CLL and cell line model, while the expression of Linc01588 and SIRT1 were positive correlation. The dual-luciferase reporter assay showed that Linc01588 & miR-9-5p, miR-9-5p & SIRT1 could bind directly, respectively. Furthermore, knockdown of miR-9-5p successfully rescued the severe apoptotic phenotype and the increased secretion of TNF-α caused by the Linc01588 deletion, the deletion of Linc01588 in human CLL cell line MEC-2 could also inhibit malignant biological characteristics, and the phenotype caused by the deletion of Linc01588 could also be rescued after overexpression of SIRT1. Moreover, the regulation of SIRT1 expression in HQ19 cells by Linc01588 and miR-9-5 P may be related to the Akt/NF-κB pathway. In brief, Linc01588 deletion inhibits the malignant biological characteristics of HQ-induced leukemic cells via miR-9-5p/SIRT1, and it is a novel and hopeful clue for the clinical targeted therapy of CLL.

Induction of zinc finger protein RNF6 auto-ubiquitination for the treatment of myeloma and chronic myeloid leukemia.

The zinc finger ubiquitin ligase RNF6 has been proposed as a potential therapeutic target in several cancers, but understanding its molecular mechanism of degradation has been elusive. In the present study, we find that RNF6 is degraded via auto-ubiquitination in a manner dependent on its Really Interesting New Gene (RING) domain. We determine that when the RING domain is deleted (ΔRING) or the core cysteine residues in the zinc finger are mutated (C632S/C635S), the WT protein, but not the ΔRING or mutant RNF6 protein, undergoes polyubiquitination. We also identify USP7 as a deubiquitinase of RNF6 by tandem mass spectrometry. We show that USP7 interacts with RNF6 and abolishes its K48-linked polyubiquitination, thereby preventing its degradation. In contrast, we found a USP7-specific inhibitor promotes RNF6 polyubiquitination, degradation, and cell death. Furthermore, we demonstrate the anti-leukemic drug Nilotinib and anti-myeloma drug Panobinostat (LBH589) induce RNF6 K48-linked polyubiquitination and degradation in both multiple myeloma (MM) and leukemia cells. In agreement with our hypothesis on the mode of RNF6 degradation, we show these drugs promote RNF6 auto-ubiquitination in an in vitro ubiquitination system without other E3 ligases. Consistently, reexpression of RNF6 ablates drug-induced MM and leukemia cell apoptosis. Therefore, our results reveal that RNF6 is a RING E3 ligase that undergoes auto-ubiquitination, which could be abolished by USP7 and induced by anti-cancer drugs. We propose that chemical induction of RNF6 auto-ubiquitination and degradation could be a novel strategy for the treatment of hematological malignancies including MM and leukemia.

iASMP: An interpretable in-silico predictive tool focusing on species-specific antimicrobial peptides.

Antimicrobial peptides (AMPs), a crucial part of the innate immune system, have been exploited as promising candidates for antibacterial agents. Many researchers have been devoting their efforts to develop novel AMPs in recent decades. In this term, many computational approaches have been developed to identify potential AMPs accurately. However, finding peptides specific to a particular bacterial species is challenging. Streptococcus mutans is a pathogen with an apparent cariogenic effect, and it is of great significance to study AMP that inhibit S. mutans for the prevention and treatment of caries. In this study, we proposed a sequence-based machine learning model, namely iASMP, to exactly identify potential anti-S. mutans peptides (ASMPs). After collecting ASMPs, the performances of models were compared by utilizing multiple feature descriptors and different classification algorithms. Among the baseline predictors, the model integrating the extra trees (ET) algorithm and the hybrid features exhibited optimal results. The feature selection method was utilized to remove redundant feature information to improve the model performance further. Finally, the proposed model achieved the maximum accuracy (ACC) of 0.962 on the training dataset and performed on the testing dataset with an ACC of 0.750. The results demonstrated that iASMP had an excellent predictive performance and was suitable for identifying potential ASMP. Furthermore, we also visualized the selected features and rationally explained the impact of individual features on the model output.

Safety and efficacy of a humanized CD19 chimeric antigen receptor T cells for relapsed/refractory acute lymphoblastic leukemia.

CD19-targeted chimeric antigen receptor T (CAR-T) cells using murine single-chain variable fragment (scFv) has shown substantial clinical efficacy in treating relapsed/refractory acute lymphoblastic leukemia (R/R ALL). However, potential immunogenicity of the murine scFv domain may limit the persistence of CAR-T cells. In this study, we treated 52 consecutive subjects with R/R ALL with humanized CD19-specific CAR-T cells (hCART19s). Forty-six subjects achieved complete remission (CR) (N = 43) or CR with incomplete count recovery (CRi) (N = 3) within 1 month post infusion. During the follow-up with a median time of 20 months, the 1-year cumulative incidence of relapse was 25% (95% confidence interval [CI] 13-46), and 1-year event-free survival was 45% (95% CI 29-60). To the cutoff date, 20 patients presented CD19+ relapse and 2 had CD19- relapse. Among the 22 relapsed patients, 14 had treatment-mediated and treatment-boosted antidrug antibodies (ADA) as detected in a sensitive and specific cell-based assay. ADA positivity was correlated with the disease relapse risk. ADA-positive patients had a significantly lower CAR copy number than ADA-negative patients at the time of recurrence (p < .001). In conclusion, hCART19s therapy is safe and highly active in R/R ALL patients, and the hCART19s treatment could induce the emergence of ADA, which is related to the recurrence of the primary disease.

GM-Pep: A High Efficiency Strategy to De Novo Design Functional Peptide Sequences.

Although peptides are regarded as ideal therapeutic agents, only a small proportion of the marketed drugs are peptides. In the past decade, pharmacists have paid great attention to the development of peptide therapeutics. Except a few approved chemically/rationally designed peptides, most attempts failed due to unsatisfactory efficacy or safety. Luckily, computation methods, such as artificial intelligence, have been utilized to accelerate the discovery of therapeutic peptides by predicting the activity, toxicity, and absorption, distribution, metabolism, and excretion of polypeptides. Usually, a specific biological activity of a peptide could be accurately determined by an interest-oriented binary classification constructed of a positive set and another un-experimentally validated negative set regardless of other characteristics, which suggests that it could be challenging to realize the comprehensive evaluation of the research object in the early stage of drug research and development. Herein, we proposed an integrated method (GM-Pep) that contained a conditional variational autoencoder model (CVAE) and a positive sample training multiclassifier (Deep-Multiclassifier) to effectively generate a single bioactive peptide sequence without toxicity and referential side effects. The results showed that our Deep-Multiclassifier model gave a sequence accuracy of up to 96.41% [toxicity (94.48%), antifungal (96.58%), antihypertensive (97.18%), and antibacterial (96.91%), respectively]. The properties of Deep-Multiclassifier and CVAE were validated through 12 first synthesized antibacterial peptides or compared to random peptides. The source code and data sets are available at https://github.com/TimothyChen225/GM-Pep.

Hsa_circRNA_0017620 regulated cell progression of non-small-cell lung cancer via miR-520a-5p/KRT5 axis.

BACKGROUND: CircRNA is a very important functional RNA that plays an important role in the development and metabolism of cancer. However, the study of circRNA in NSCLC has not been fully elucidated. METHODS: The expression of hsa_circ_0017620, SFMBT2, miR-520a-5p, and KRT5 was determined using qRT-PCR. KRT5, Twist1, E-cadherin, and Ki67 protein expression were measured with western blot. The positive expression rates of Ki67 and Vimentin were determined by immunohistochemistry assay. 5-Ethynyl-2'-deoxyuridine (EdU), colony formation, and MTT assays were used to assess cell proliferation. Transwell migration and invasion assay were applied to determine cell migration and invasion. Dual-luciferase reporter and RNA immunoprecipitation assays were used to verify the relationship among hsa_circ_0017620, miR-520a-5p, and KRT5. The animal experiment was used to ensure the effects of hsa_circ_0017620 on tumor growth in vivo. RESULTS: Hsa_circ_0017620 was upregulated in NSCLC cells and tissues. MiR-520a-5p had been verified to be a target miRNA of hsa_circ_0017620 and KRT5 had been verified to be a target mRNA of miR-520a-5p in NSCLC cells. Knockdown of hsa_circ_0017620 inhibited cell proliferation, migration, and invasion in NSCLC cells, which was reversed by downregulating miR-520a-5p or upregulating KRT5 in NSCLC. Overexpression of hsa_circ_0017620 had opposite effects in NSCLC. Moreover, hsa_circ_0017620 silencing inhibited tumor growth in vivo of NSCLC. CONCLUSION: In this study, we found that hsa_circ_0017620 played an important role in NSCLC progression. Hsa_circ_0017620 regulated cell proliferation, invasion, and migration through targeting miR-520a-5p/KRT5 axis in NSCLC, providing a potential new target for the treatment and diagnosis of NSCLC.

Correlation Between Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio with Risk Stratification Indicators and Thrombus Burden in Patients with Moderate-to-High Risk Acute Pulmonary Embolism, and Changes After Treatment.

OBJECTIVE: To investigate the correlation between neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and risk stratification indicators as well as thrombus burden in patients with moderate-to-high risk acute pulmonary embolism (APE), and to assess the changes in these parameters following interventional therapy. METHODS: This study retrospectively included patients with moderate-to-high risk APE who were admitted to the Department of Interventional Vascular Surgery at Putian First Hospital from May 2020 to May 2024. All patients received anticoagulation therapy, pulmonary artery catheter-directed thrombolysis, and/or mechanical thrombectomy. Patients were further divided into subgroup A if they did not present with any of the following conditions at admission: a) acute inflammatory diseases (including lung infections); b) malignant tumors; c) history of trauma or surgery within the past 2 months. Patients with any of the aforementioned conditions were classified as subgroup B. Additionally, 50 healthy individuals were randomly selected as the healthy control group. RESULTS: The NLR and PLR in subgroup A were significantly lower than those in subgroup B (P < .01). Compared with the healthy control group, the NLR in the APE group and subgroup A was significantly higher (P < .001). There were no significant differences in NLR and PLR between the troponin I-negative and troponin I-positive groups (P > .05), or between the N-terminal pro-B-type natriuretic peptide (NT-proBNP)-negative and NT-proBNP-positive groups (P > .05). There were no significant correlations between NLR and PLR with risk stratification indicators and pulmonary artery embolism index (P > .05). Compared with before treatment, NLR, troponin I, NT-proBNP, right ventricular diameter/left ventricular diameter ratio, and pulmonary artery embolism index were significantly reduced after treatment (P < .05), while there was no significant difference in PLR before and after treatment (P > .05). CONCLUSION: Elevated NLR in patients with APE, which decreases after effective treatment, may be used for assessing disease status and treatment efficacy. However, there is no correlation between NLR and risk stratification indicators or thrombus burden. PLR does not demonstrate significant value in assessing APE.

Organocatalytic enantio- and diastereoselective synthesis of trifluoro-ethylamine allenoate derivatives containing axial and central chiralities.

Herein, we report an example of a stereoselective γ-addition reaction of trifluoromethyl ketimines to 1-alkynyl ketones mediated by an isothiourea, BTM, under mild conditions, which afforded tetrasubstituted allenes with central chiralities in high yields (up to 94% yield), good enantioselectivities (up to 91% ee), and excellent diastereoselectivities (all >20 : 1 dr). In addition, the BTM-catalyzed γ-addition reaction was successfully applied to the gram-scale reaction, and an unexpected benzopyrrolothiazine derivative was successfully converted, albeit racemic.

Apatinib plus hepatic arterial infusion of oxaliplatin and raltitrexed for hepatocellular carcinoma with extrahepatic metastasis: phase II trial.

Most patients with advanced hepatocellular carcinoma (HCC) ultimately experience tumor progression after first-line systemic therapies. Systemic therapy is generally recommended as second-line treatment for advanced HCC in the major guidelines. Combining apatinib with hepatic arterial infusion chemotherapy (HAIC) likely drives synergistic activity on advanced HCC with extrahepatic metastasis. This phase II trial (ChiCTR2000029082) aimed to assess efficacy and safety of this combination in patients with HCC with extrahepatic metastasis who have progressed after first-line systemic therapies. The primary end point was the objective response rate (ORR). The secondary endpoints were progress-free survival (PFS), disease control rate (DCR), 6- and 12-month survival rates, overall survival (OS), and adverse events (AEs). Thirty-nine patients received oral treatment with apatinib, and hepatic artery infusion oxaliplatinplus raltitrexed. Per RECIST v1.1, the ORR and DCR was 53.8% and 89.7% in the patients population, respectively. The median PFS and OS was 6.2 months and 11.3 months, respectively. The 6- and 12-month survival rates were 81.7% and 44.1%, respectively. All AEs were manageable by medication or dose modifications. Apatinib plus HAIC for second-line therapy in advanced HCC with extrahepatic metastasis shows promising efficacy and manageable toxicities.

Discovery of AMPs from random peptides via deep learning-based model and biological activity validation.

The ample peptide field is the best source for discovering clinically available novel antimicrobial peptides (AMPs) to address emerging drug resistance. However, discovering novel AMPs is complex and expensive, representing a major challenge. Recent advances in artificial intelligence (AI) have significantly improved the efficiency of identifying antimicrobial peptides from large libraries, whereas using random peptides as negative data increases the difficulty of discovering antimicrobial peptides from random peptides using discriminative models. In this study, we constructed three multi-discriminator models using deep learning and successfully screened twelve AMPs from a library of 30,000 random peptides. three candidate peptides (P2, P11, and P12) were screened by antimicrobial experiments, and further experiments showed that they not only possessed excellent antimicrobial activity but also had extremely low hemolytic activity. Mechanistic studies showed that these peptides exerted their bactericidal effects through membrane disruption, thus reducing the possibility of bacterial resistance. Notably, peptide 12 (P12) showed significant efficacy in a mouse model of Staphylococcus aureus wound infection with low toxicity to major organs at the highest tested dose (400 mg/kg). These results suggest deep learning-based multi-discriminator models can identify AMPs from random peptides with potential clinical applications.

Platelet dropping, bleeding and new treatment requirements in ITP patients after inactivated COVID-19 vaccination.

Significant decreases in platelet counts and ITP relapses have been documented in ITP patients receiving COVID-19 mRNA vaccines; however, the effect of the inactivated COVID-19 vaccine on ITP patients remains unclear. The present study aimed to investigate the impact of inactivated COVID-19 vaccines on ITP patients, with a focus on platelet dropping events, bleeding events/scores, and the requirement of a new round of treatment. A total of 118 ITP patients, with 97 chronic ITP and 21 persistent ITP, who received inactivated COVID-19 immunization were investigated retrospectively. Following vaccination (within 1 month), ITP patients reported platelet dropping (31.36 %), new bleeding events (22.88 %), increases in bleeding scores (23.73 %), and new treatment requirements (22.03 %). Among them, persistent ITP patients with disease duration of 3-12 months had higher ratios of the above adverse events (71.43 %, 57.14 %, 61.90 % and 71.43 %, respectively) than chronic ITP patients with duration > 1 year (22.68 %, 15.46 %, 15.46 % and 11.34 %, respectively); patients' disease duration was negatively correlated with platelet dropping events and new treatment requirements. Furthermore, logistic regression analysis also supported the above findings, revealing that persistent ITP patients had 9.40-9.70, 7.24-10.08, and 27.17-28.51 times incidence of having platelet dropping events, new bleeding events, and new treatment requirements after vaccination, respectively, when compared to chronic ITP patients. In conclusion, the present study demonstrates that after receiving inactivated COVID-19 vaccines, ITP patients may experience platelet dropping, which may lead to new bleeding events and the requirement of a new round of treatment for ITP recurrence. As a result, platelet level monitoring is crucial for ITP patients during the vaccination, especially those with persistent ITP.

An FPGA-based system for generalised electron devices testing.

Electronic systems are becoming more and more ubiquitous as our world digitises. Simultaneously, even basic components are experiencing a wave of improvements with new transistors, memristors, voltage/current references, data converters, etc, being designed every year by hundreds of R &D groups world-wide. To date, the workhorse for testing all these designs has been a suite of lab instruments including oscilloscopes and signal generators, to mention the most popular. However, as components become more complex and pin numbers soar, the need for more parallel and versatile testing tools also becomes more pressing. In this work, we describe and benchmark an FPGA system developed that addresses this need. This general purpose testing system features a 64-channel source-meter unit, and [Formula: see text] banks of 32 digital pins for digital I/O. We demonstrate that this bench-top system can obtain [Formula: see text] current noise floor, [Formula: see text] pulse delivery at [Formula: see text] and [Formula: see text] maximum current drive/channel. We then showcase the instrument's use in performing a selection of three characteristic measurement tasks: (a) current-voltage characterisation of a diode and a transistor, (b) fully parallel read-out of a memristor crossbar array and (c) an integral non-linearity test on a DAC. This work introduces a down-scaled electronics laboratory packaged in a single instrument which provides a shift towards more affordable, reliable, compact and multi-functional instrumentation for emerging electronic technologies.

Circ_0016760 accelerates non-small-cell lung cancer progression through miR-646/AKT3 signaling in vivo and in vitro.

BACKGROUND: Currently, the prognosis of non-small-cell lung cancer (NSCLC) patients remains dismal due to recurrence and metastasis. The purpose of our study was to explore the role of circular RNA_0016760 (circ_0016760) in NSCLC progression and its associated mechanism. METHODS: Quantitative real-time polymerase chain reaction (qRT-PCR) was implemented to measure the expression of circ_0016760, microRNA-646 (miR-646) and AK strain thymoma serine/threonine kinase 3 (AKT3). The protein level of AKT3 was examined by Western blot assay. Cell Counting Kit 8 assay, transwell assays, and flow cytometry were conducted to analyze cell proliferation, metastasis, and apoptosis. Dual-luciferase reporter assay was used to confirm the interactions that were predicted by bioinformatics software (Circular RNA Interactome and TargetScan). A xenograft tumor model was built to investigate the role of circ_0016760 in vivo. RESULTS: Circ_0016760 and AKT3 were highly expressed in NSCLC tissue specimens and cell lines. Circ_0016760 interference suppressed cell proliferation, migration, and invasion and promoted the apoptosis of NSCLC cells. Circ_0016760 interacted with miR-646 and negatively regulated its expression. MiR-646 silencing partly counteracted circ_0016760 knockdown-mediated influences in NSCLC cells. MiR-646 bound to the AKT3 3' untranslated region in NSCLC cells, and miR-646 overexpression-induced effects in NSCLC cells were partly overturned by the addition of AKT3 overexpression plasmid. Circ_0016760 silencing reduced the expression of AKT3 through enhancing miR-646 expression. Circ_0016760 knockdown suppressed NSCLC tumor growth in vivo. CONCLUSION: Circ_0016760 played an oncogenic role to promote the proliferation, migration, and invasion and restrained the apoptosis of NSCLC cells via miR-646/AKT3 signaling.

Δ133p53/FLp53 Predicts Poor Clinical Outcome in Esophageal Squamous Cell Carcinoma.

BACKGROUND: p53 isoform Δ133p53 is directly transactivated by p53 and antagonizes p53 activities in cancer progression. However, its correlation with prognosis and cancer recurrence in esophageal squamous cell carcinoma (ESCC) is still unclear. PATIENTS AND METHODS: Expression of Δ133p53 and Δ133p53/full-length p53 (FLp53) in tissues and serums of 180 ESCC patients was evaluated using qRT-PCR. Patients were divided into high- and low-expression groups according to the cutoff value determined by X-tile 3.6.1 software. Survival analysis was performed by the Kaplan-Meier method. Univariate and multivariate Cox survival analyses were applied to assess the hazard ratios (HRs). RESULTS: Tissue Δ133p53 expression and Δ133p53/FLp53 ratio were significantly increased in ESCC tissue compared with adjacent normal tissue. Pre-operative Δ133p53 expression and Δ133p53/FLp53 ratio in tissue or serum samples were positively associated with TNM stage and post-operative recurrence. Kaplan-Meier curve and multivariate cox regression analyses revealed that the tissue and serum Δ133p53/FLp53 ratios (cutoff value: 2.9160) were independent prognostic factors for overall survival (OS) and progression-free survival (PFS) in ESCC patients and showed no statistical difference in receiver-operating characteristic curve (ROC) analysis, while serum Δ133p53 showed no significant prognostic value. More importantly, the serum Δ133p53/FLp53 ratio in ESCC patients was significantly decreased within 72 h post tumor resection and patients with a consistently high serum Δ133p53/FLp53 ratio (≥2.9160) had higher recurrence rates than those with consistently low ratio values. In addition, dynamic detection in each follow-up timepoint showed that serum Δ133p53/FLp53 ratios were higher than 2.9160 upon recurrence, and they even increased prior to radiologic progression. CONCLUSION: The serum Δ133p53/FLp53 ratio can be a novel predictor for survival outcome and may serve as a real-time parameter for monitoring recurrence in ESCC patients after surgery.

m6A RNA Methylation Regulators Contribute to Malignant Progression and Have Clinical Prognostic Impact in Gastric Cancer.

N6-methyladenosine (m6A) is the most common form of mRNA modification, and is dynamically regulated by the m6A RNA methylation regulators. However, little is known about m6A in gastric cancer. The aim of this work is to investigate the effects of m6A RNA methylation regulators in gastric cancer. Here, we found that most of the 13 main m6A RNA methylation regulators are higher expressed in 375 patients with gastric cancer. We identified two subgroups of gastric cancer (cluster1 and 2) by applying consensus clustering to m6A RNA methylation regulators. Compared with the cluster1 subgroup, the cluster2 subgroup correlates with a poorer prognosis, and most of the 13 main m6A RNA methylation regulators are higher expressed in cluster2. Moreover, the cancer-specific pathways are also significantly enriched in the cluster2 subgroup. This finding indicates that m6A RNA methylation regulators are closely associated with gastric cancer. Based on this finding, we derived a risk signature, using 3 m6A RNA methylation regulators (FTO, RBM15, ALKBH5), that is not only an independent prognostic marker but can also predict the clinicopathological features of gastric cancer. Moreover, FTO is higher expressed in high risk scores subtype in gastric cancer. Thus, this first finding provide us clues to understand epigenetic modification of RNA in gastric cancer.

Correction: Unique CDR3 epitope targeting by CAR-T cells is a viable approach for treating T-cell malignancies.

In the original version of this article the author name Xiaolei Chen was published incorrectly. This has been corrected to Xiao Lei Chen.

The increase in sympathetic nerve density in the atrium facilitates atrial fibrillation in patients with rheumatic heart disease.

BACKGROUND: Atrial fibrillation (Af) is frequently observed in patients with rheumatic heart disease (RHD). The hyperactivity of autonomic nervous system is known to contribute to the occurrence of Af in RHD patients. This study investigated the association between the autonomic density and the risk of Af in RHD patients. METHODS: Seventy-five patients were enrolled: (1) RHD patients with Af (N = 25, Group 1); (2) RHD patients without Af (N = 25, Group 2); (3) congenital heart disease patients without Af (N = 25, Group 3). The baseline characteristics and the blood concentrations of renin, C-reaction protein and angiotensin II were collected from all patients. The tissues were obtained from the right atrial appendage during the open-heart surgery and then stained using immunohistochemical methods with autonomic antibodies. RESULTS: The sympathetic nerve density was significantly higher in RHD patients with Af than RHD patients without Af and congenital heart disease patients, both endocardially and epicardially. The parasympathetic nerve density did not show significant difference among the three groups. The left atrial diameter was larger in RHD patients with Af than the other two groups. The blood concentrations of renin and angiotensin II were higher in RHD patients with Af than the other two groups. The erythrocyte sedimentation rate and blood concentrations of C-reaction protein did not show significant change among the three groups. CONCLUSION: This study provided direct evidence of the increase in sympathetic nerve density in atrium in patients with RHD. This phenomenon may be associated with the development of Af in RHD patients.