CATAD: exploring topologically associating domains from an insight of core-attachment structure.

Identifying topologically associating domains (TADs), which are considered as the basic units of chromosome structure and function, can facilitate the exploration of the 3D-structure of chromosomes. Methods have been proposed to identify TADs by detecting the boundaries of TADs or identifying the closely interacted regions as TADs, while the possible inner structure of TADs is seldom investigated. In this study, we assume that a TAD is composed of a core and its surrounding attachments, and propose a method, named CATAD, to identify TADs based on the core-attachment structure model. In CATAD, the cores of TADs are identified based on the local density and cosine similarity, and the surrounding attachments are determined based on boundary insulation. CATAD was applied to the Hi-C data of two human cell lines and two mouse cell lines, and the results show that the boundaries of TADs identified by CATAD are significantly enriched by structural proteins, histone modifications, transcription start sites and enzymes. Furthermore, CATAD outperforms other methods in many cases, in terms of the average peak, boundary tagged ratio and fold change. In addition, CATAD is robust and rarely affected by the different resolutions of Hi-C matrices. Conclusively, identifying TADs based on the core-attachment structure is useful, which may inspire researchers to explore TADs from the angles of possible spatial structures and formation process.

AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification.

MOTIVATION: Dropout events bring challenges in analyzing single-cell RNA sequencing data as they introduce noise and distort the true distributions of gene expression profiles. Recent studies focus on estimating dropout probability and imputing dropout events by leveraging information from similar cells or genes. However, the number of dropout events differs in different cells, due to the complex factors, such as different sequencing protocols, cell types, and batch effects. The dropout event differences are not fully considered in assessing the similarities between cells and genes, which compromises the reliability of downstream analysis. RESULTS: This work proposes a hybrid Generative Adversarial Network with dropouts identification to impute single-cell RNA sequencing data, named AGImpute. First, the numbers of dropout events in different cells in scRNA-seq data are differentially estimated by using a dynamic threshold estimation strategy. Next, the identified dropout events are imputed by a hybrid deep learning model, combining Autoencoder with a Generative Adversarial Network. To validate the efficiency of the AGImpute, it is compared with seven state-of-the-art dropout imputation methods on two simulated datasets and seven real single-cell RNA sequencing datasets. The results show that AGImpute imputes the least number of dropout events than other methods. Moreover, AGImpute enhances the performance of downstream analysis, including clustering performance, identifying cell-specific marker genes, and inferring trajectory in the time-course dataset. AVAILABILITY AND IMPLEMENTATION: The source code can be obtained from https://github.com/xszhu-lab/AGImpute.

Metrics for evaluating differentially methylated region sets predicted from BS-seq data.

Investigating differentially methylated regions (DMRs) presented in different tissues or cell types can help to reveal the mechanisms behind the tissue-specific gene expression. The identified tissue-/disease-specific DMRs also can be used as feature markers for spotting the tissues-of-origins of cell-free DNA (cfDNA) in noninvasive diagnosis. In recent years, many methods have been proposed to detect DMRs. However, due to the lack of benchmark DMRs, it is difficult for researchers to choose proper methods and select desirable DMR sets for downstream studies. The application of DMRs, used as feature markers, can be benefited by the longer length of DMRs containing more CpG sites when a threshold is given for the methylation differences of DMRs. According to this, two metrics ($Qn$ and $Ql$), in which the CpG numbers and lengths of DMRs with different methylation differences are weighted differently, are proposed in this paper to evaluate the DMR sets predicted by different methods on BS-seq data. DMR sets predicted by eight methods on both simulated datasets and real BS-seq datasets are evaluated by the proposed metrics, the benchmark-based metrics, and the enrichment analysis of biological data, including genomic features, transcription factors and histones. The rank correlation analysis shows that the $Qn$ and $Ql$ are highly correlated to the benchmark metrics for simulated datasets and the biological data enrichment analysis for real BS-seq data. Therefore, with no need for additional biological data, the proposed metrics can help researchers selecting a more suitable DMR set on a certain BS-seq dataset.

Drug repositioning based on multi-view learning with matrix completion.

Determining drug indications is a critical part of the drug development process. However, traditional drug discovery is expensive and time-consuming. Drug repositioning aims to find potential indications for existing drugs, which is considered as an important alternative to the traditional drug discovery. In this article, we propose a multi-view learning with matrix completion (MLMC) method to predict the potential associations between drugs and diseases. Specifically, MLMC first learns the comprehensive similarity matrices from five drug similarity matrices and two disease similarity matrices based on the multi-view learning (ML) with Laplacian graph regularization, and updates the drug-disease association matrix simultaneously. Then, we introduce matrix completion (MC) to add some positive entries in original association matrix based on low-rank structure, and re-execute the multi-view learning algorithm for association prediction. At last, the prediction results of the above two operations are integrated as the final output. Evaluated by 10-fold cross-validation and de novo tests, MLMC achieves higher prediction accuracy than the current state-of-the-art methods. Moreover, case studies confirm the ability of our method in novel drug-disease association discovery. The codes of MLMC are available at https://github.com/BioinformaticsCSU/MLMC. Contact: jxwang@mail.csu.edu.cn.

Identifying the tissues-of-origin of circulating cell-free DNAs is a promising way in noninvasive diagnostics.

Advances in sequencing technologies facilitate personalized disease-risk profiling and clinical diagnosis. In recent years, some great progress has been made in noninvasive diagnoses based on cell-free DNAs (cfDNAs). It exploits the fact that dead cells release DNA fragments into the circulation, and some DNA fragments carry information that indicates their tissues-of-origin (TOOs). Based on the signals used for identifying the TOOs of cfDNAs, the existing methods can be classified into three categories: cfDNA mutation-based methods, methylation pattern-based methods and cfDNA fragmentation pattern-based methods. In cfDNA mutation-based methods, the SNP information or the detected mutations in driven genes of certain diseases are employed to identify the TOOs of cfDNAs. Methylation pattern-based methods are developed to identify the TOOs of cfDNAs based on the tissue-specific methylation patterns. In cfDNA fragmentation pattern-based methods, cfDNA fragmentation patterns, such as nucleosome positioning or preferred end coordinates of cfDNAs, are used to predict the TOOs of cfDNAs. In this paper, the strategies and challenges in each category are reviewed. Furthermore, the representative applications based on the TOOs of cfDNAs, including noninvasive prenatal testing, noninvasive cancer screening, transplantation rejection monitoring and parasitic infection detection, are also reviewed. Moreover, the challenges and future work in identifying the TOOs of cfDNAs are discussed. Our research provides a comprehensive picture of the development and challenges in identifying the TOOs of cfDNAs, which may benefit bioinformatics researchers to develop new methods to improve the identification of the TOOs of cfDNAs.

AlzCode: a platform for multiview analysis of genes related to Alzheimer's disease.

MOTIVATION: Alzheimer's disease (AD) is a complex brain disorder with risk genes incompletely identified. The candidate genes are dominantly obtained by computational approaches. In order to obtain biological insights of candidate genes or screen genes for experimental testing, it is essential to assess their relevance to AD. A platform that integrates different types of omics data and approaches would facilitate the analysis of candidate genes and is in great need. RESULTS: We report AlzCode, a platform for multiview analysis of genes related to AD. First, this platform integrates a rich collection of functional genomic data, including expression data of AD samples (gene expression, single-cell RNA-seq data and protein expression), AD-specific biological networks (co-expression networks and functional gene networks), neuropathological and clinical traits (CERAD score, Braak staging score, Clinical Dementia Rating, cognitive function and clinical severity) and general data such as protein-protein interaction, regulatory networks, sequence similarity and miRNA-target interactions. These data provide basis for analyzing genes from different views. Second, the platform integrates multiple approaches designed for the various types of data. We implement functions to analyze both individual genes and gene sets. We also compare AlzCode with two existing platforms for AD analysis, which are Agora and AD Atlas. We pinpoint the features of each platform and highlight their differences. This platform would be valuable to the understanding of AD genetics and pathological mechanisms. AVAILABILITY AND IMPLEMENTATION: AlzCode is freely available at: http://www.alzcode.xyz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High carbon emissions from thermokarst lakes and their determinants in the Tibet Plateau.

Thermokarst lakes are potentially important sources of methane (CH4 ) and carbon dioxide (CO2 ). However, considerable uncertainty exists regarding carbon emissions from thermokarst lakes owing to a limited understanding of their patterns and motivators. In this study, we measured CH4 and CO2 diffusive fluxes in 163 thermokarst lakes in the Qinghai-Tibet Plateau (QTP) over 3 years from May to October. The median carbon emissions from the QTP thermokarst lakes were 1440 mg CO2 m-2 day-1 and 60 mg CH4 m-2 day-1 , respectively. The diffusive rates of CO2 and CH4 are related to the catchment land cover type. Sediment microbial abundance and hydrochemistry explain 51.9% and 38.3% of the total variance in CH4 diffusive emissions, respectively, while CO2 emissions show no significant relationship with environmental factors. When upscaling carbon emissions from the QTP thermokarst lakes, the annual average CH4 release per lake area is equal to that of the pan-Arctic region. Our findings highlight the importance of incorporating in situ observation data with different emission pathways for different land cover types in predicting carbon emissions from thermokarst lakes in the future.

Linear and non-linear relationships between sulfur dioxide and semen quality: A longitudinal study in Anhui, China.

Existing evidence indicates that ambient air pollutants pose a threat to human semen quality; however, these findings are sparse and controversial. Besides, their non-linear dose-response relationship has not yet been well investigated. This study aimed to explore the linear and non-linear associations of gaseous air pollutants exposure with semen quality based on a large longitudinal cohort. A total of 15,112 males (with 28,267 semen tests) from the Anhui prospective assisted reproduction cohort were analyzed. Individual air pollutants exposure before semen tests in four exposure windows (i.e., 0-9, 10-14, 70-90, and 0-90 days) were estimated by inverse distance weighting interpolation. Linear mixed-effects models, cubic spline analysis and piecewise regression were used to test the potential linear and non-linear dose-response relationships. Ambient SO2 exposure was negatively associated with all semen quality parameters (all p values < 0.05), except for the progressive motility in the 0-90 and 70-90 days exposure windows. There were 'J' or 'U' shaped dose-response relationships of ambient SO2 exposure with total sperm count, progressive motility, total motility, progressively motile sperm count, and total motile sperm count (p values for non-linearity < 0.05), but not sperm concentration. Piecewise regression analysis also indicated a negative association of SO2 exposure with semen quality only when SO2 exposure was below the cut-off points identified by cubic spline analyses, which were all smaller than 40 µg/m3, the 2021 updated WHO air quality guideline level for SO2 exposure. Overall, we found that SO2 exposure was negatively associated with semen quality. Ambient SO2 exposure could reach the maximum hazardous dose even below the WHO air quality guideline level for SO2 exposure, suggesting a refinement to the current guideline.

Frailty predicts knee pain trajectory over 9 years: results from the Osteoarthritis Initiative.

OBJECTIVE: Frailty is a multisystem syndrome and its relationship with symptomatic osteoarthritis has been reported. We aimed to identify trajectories of knee pain in a large prospective cohort and to describe the effect of frailty status at baseline on the pain trajectories over 9 years. METHODS: We included 4419 participants (mean age 61.3 years, 58% female) from the Osteoarthritis Initiative cohort. Participants were classified as "no frailty," "pre-frailty," or "frailty" at baseline, based on 5 characteristics (ie, unintentional weight loss, exhaustion, weak energy, slow gait speed, and low physical activity). Knee pain was evaluated annually using the Western Ontario and McMaster Universities Osteoarthritis Index pain subscale (0-20) from baseline to 9 years. RESULTS: Of the participants included, 38.4%, 55.4%, and 6.3% were classified as "no frailty," "pre-frailty," and "frailty," respectively. Five pain trajectories were identified: "No pain" (n = 1010, 22.8%), "Mild pain" (n = 1656, 37.3%), "Moderate pain" (n = 1149, 26.0%), "Severe pain" (n = 477, 10.9%), and "Very Severe pain" (n = 127, 3.0%). Compared to participants with no frailty, those with pre-frailty and frailty were more likely to have more severe pain trajectories (pre-frailty: odds ratios [ORs] 1.5 to 2.1; frailty: ORs 1.5 to 5.0), after adjusting for potential confounders. Further analyses indicated that the associations between frailty and pain were mainly driven by exhaustion, slow gait speed, and weak energy. CONCLUSIONS: Approximately two-thirds of middle-aged and older adults were frail or pre-frail. The role of frailty in predicting pain trajectories suggests that frailty may be an important treatment target for knee pain.

Circular RNA CircCDKN2B-AS_006 Promotes the Tumor-like Growth and Metastasis of Rheumatoid Arthritis Synovial Fibroblasts by Targeting the miR-1258/RUNX1 Axis.

Rheumatoid arthritis (RA) is an autoimmune polyarthritis in which synovial fibroblasts (SFs) play a major role in cartilage and bone destruction through tumor-like proliferation, migration, and invasion. Circular RNAs (circRNAs) have emerged as vital regulators for tumor progression. However, the regulatory role, clinical significance, and underlying mechanisms of circRNAs in RASF tumor-like growth and metastasis remain largely unknown. Differentially expressed circRNAs in synovium samples from patients with RA and patients with joint trauma were identified via RNA sequencing. Subsequently, in vitro and in vivo experiments were performed to investigate the functional roles of circCDKN2B-AS_006 in RASF proliferation, migration, and invasion. CircCDKN2B-AS_006 was upregulated in synovium samples from patients with RA and promoted the tumor-like proliferation, migration, and invasion of RASFs. Mechanistically, circCDKN2B-AS_006 was shown to regulate the expression of runt-related transcription factor 1 (RUNX1) by sponging miR-1258, influencing the Wnt/ß-catenin signaling pathway, and promoting the epithelial-to-mesenchymal transition (EMT) in RASFs. Moreover, in the collagen-induced arthritis (CIA) mouse model, intra-articular injection of lentivirus-shcircCDKN2B-AS_006 was capable of alleviating the severity of arthritis and inhibiting the aggressive behaviors of SFs. Furthermore, the correlation analysis results revealed that the circCDKN2B-AS_006/miR-1258/RUNX1 axis in the synovium was correlated with the clinical indicators of RA patients. CircCDKN2B-AS_006 promoted the proliferation, migration, and invasion of RASFs by modulating the miR-1258/RUNX1 axis.

The role of E2A in ATPR-induced cell differentiation and cycle arrest in acute myeloid leukaemia cells.

Acute myeloid leukaemia (AML) is a biologically heterogeneous disease with an overall poor prognosis; thus, novel therapeutic approaches are needed. Our previous studies showed that 4-amino-2-trifluoromethyl-phenyl retinate (ATPR), a new derivative of all-trans retinoic acid (ATRA), could induce AML cell differentiation and cycle arrest. The current study aimed to determine the potential pharmacological mechanisms of ATPR therapies against AML. Our findings showed that E2A was overexpressed in AML specimens and cell lines, and mediate AML development by inactivating the P53 pathway. The findings indicated that E2A expression and activity decreased with ATPR treatment. Furthermore, we determined that E2A inhibition could enhance the effect of ATPR-induced AML cell differentiation and cycle arrest, whereas E2A overexpression could reverse this effect, suggesting that the E2A gene plays a crucial role in AML. We identified P53 and c-Myc were downstream pathways and targets for silencing E2A cells using RNA sequencing, which are involved in the progression of AML. Taken together, these results confirmed that ATPR inhibited the expression of E2A/c-Myc, which led to the activation of the P53 pathway, and induced cell differentiation and cycle arrest in AML.

Nesfatin-1 exerts protective effects on acidosis-stimulated chondrocytes and rats with adjuvant-induced arthritis by inhibiting ASIC1a expression.

Nesfatin-1, a newly identified energy-regulating peptide, has been reported to possess antioxidant, anti-inflammatory, and antiapoptotic properties; however, to date, its effect on rheumatoid arthritis (RA) has not been previously explored in detail. We previously showed that activation of acid-sensing ion channel 1a (ASIC1a) by acidosis plays an important role in RA pathogenesis. Therefore, in this study, we evaluated the effects of nesfatin-1 on acidosis-stimulated chondrocyte injury in vitro and in vivo and examined the involvement of ASIC1a and the mechanism underlying the effects of nesfatin-1 on RA. Acid-stimulated articular chondrocytes were used to examine one of the several possible mechanisms underlying RA pathogenesis in vitro. The mRNA expression profile of acid-induced chondrocytes treated or not treated with nesfatin-1 was investigated by RNA sequencing. The effects of nesfatin-1 on oxidative stress, inflammation, and apoptosis in acid-induced chondrocytes were measured. The mechanistic effect of nesfatin-1 on ASIC1a expression and intracellular Ca2+ in acid-stimulated chondrocytes was studied. Rats with adjuvant-induced arthritis (AA) were used for in vivo analysis of RA pathophysiology. Cartilage degradation and ASIC1a expression in chondrocytes were detected in rats with AA after intraarticular nesfatin-1 injection. The in vitro experiments showed that nesfatin-1 decreased acidosis-induced cytotoxicity and elevation of intracellular Ca2+ levels in chondrocytes. Moreover, it attenuated acid-induced oxidative stress, inflammation, and apoptosis in chondrocytes. Nesfatin-1 decreased ASIC1a protein levels in acid-stimulated chondrocytes via the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) and nuclear factor kappa-B (NF-κB) signaling pathways. In vivo analysis showed that nesfatin-1 ameliorated cartilage degradation and decreased ASIC1a expression in the chondrocytes of rats with AA. Collectively, nesfatin-1 suppressed acidosis-induced oxidative stress, inflammation, and apoptosis in acid-stimulated chondrocytes and alleviated arthritis symptoms in rats with AA, and its mechanism may be related to its ability to decrease ASIC1a protein levels via the MAPK/ERK and NF-κB pathways.

Estrogen antagonizes ASIC1a-induced chondrocyte mitochondrial stress in rheumatoid arthritis.

BACKGROUND: Destruction of articular cartilage and bone is the main cause of joint dysfunction in rheumatoid arthritis (RA). Acid-sensing ion channel 1a (ASIC1a) is a key molecule that mediates the destruction of RA articular cartilage. Estrogen has been proven to have a protective effect against articular cartilage damage, however, the underlying mechanisms remain unclear. METHODS: We treated rat articular chondrocytes with an acidic environment, analyzed the expression levels of mitochondrial stress protein HSP10, ClpP, LONP1 by q-PCR and immunofluorescence staining. Transmission electron microscopy was used to analyze the mitochondrial morphological changes. Laser confocal microscopy was used to analyze the Ca2+, mitochondrial membrane potential (Δψm) and reactive oxygen species (ROS) level. Moreover, ASIC1a specific inhibitor Psalmotoxin 1 (Pctx-1) and Ethylene Glycol Tetraacetic Acid (EGTA) were used to observe whether acid stimulation damage mitochondrial function through Ca2+ influx mediated by ASIC1a and whether pretreatment with estrogen could counteract these phenomena. Furthermore, the ovariectomized (OVX) adjuvant arthritis (AA) rat model was treated with estrogen to explore the effect of estrogen on disease progression. RESULTS: Our results indicated that HSP10, ClpP, LONP1 protein and mRNA expression and mitochondrial ROS level were elevated in acid-stimulated chondrocytes. Moreover, acid stimulation decreased mitochondrial membrane potential and damaged mitochondrial structure of chondrocytes. Furthermore, ASIC1a specific inhibitor PcTx-1 and EGTA inhibited acid-induced mitochondrial abnormalities. In addition, estrogen could protect acid-stimulated induced mitochondrial stress by regulating the activity of ASIC1a in rat chondrocytes and protects cartilage damage in OVX AA rat. CONCLUSIONS: Extracellular acidification induces mitochondrial stress by activating ASIC1a, leading to the damage of rat articular chondrocytes. Estrogen antagonizes acidosis-induced joint damage by inhibiting ASIC1a activity. Our study provides new insights into the protective effect and mechanism of action of estrogen in RA.

Frozen embryo transfer in the menstrual cycle after moderate-severe ovarian hyperstimulation syndrome: a retrospective analysis.

BACKGROUND: Ovarian hyperstimulation syndrome (OHSS) is a rare but serious complication of controlled ovarian stimulation. Frozen-embryo transfer (ET) is prompted to be performed in the next menstrual cycles after cancellation of fresh-ET after occurrence of OHSS. However, effects of frozen-ET in the second menstrual cycle have never been investigated. Therefore, this study aimed to assess this in the menstrual cycle after OHSS. METHODS: The OHSS group included 342 women with moderate-severe OHSS who underwent the first frozen-ET in the second menstrual cycle in the First Affiliated Hospital of Anhui Medical University from June 2018 to September 2019. A total of 342 women without OHSS who received frozen-ET in the second menstrual cycle were selected as control group matched by age, body mass index, fertility history, ovulation induction scheme. Uni- and multi-variable conditional logistic regression was used to estimate the association between moderate-severe OHSS and pregnancy outcomes. RESULTS: There were no significant differences in maternal outcomes (miscarriage, preterm birth and pregnancy complications including gestational diabetes mellitus, pregnancy-induced hypertension, placenta previa, premature rupture of membranes and postpartum hemorrhage) and in neonatal outcome (birth-weight and body length, neonatal congenital diseases and other complications) between the two groups in either uni- or multi-variable models. CONCLUSIONS: Frozen-ET in the menstrual cycle after OHSS has similar maternal and neonatal outcomes as in women without OHSS. This study indicates that frozen-ET could be performed in the second menstrual cycle in women who recovered from moderate-severe OHSS.

ZEB1 serves as an oncogene in acute myeloid leukaemia via regulating the PTEN/PI3K/AKT signalling pathway by combining with P53.

Acute myeloid leukaemia is a complex, highly aggressive hematopoietic disorder. Currently, in spite of great advances in radiotherapy and chemotherapy, the prognosis for AML patients with initial treatment failure is still poor. Therefore, the need for novel and efficient therapies to improve AML treatment outcome has become desperately urgent. In this study, we identified the expression of ZEB1 (a transcription factor) and focused on its possible role and mechanisms in the progression of AML. According to the data provided by the Gene Expression Profiling Interactive Analysis (GEPIA), high expression of ZEB1 closely correlates with poor prognosis in AML patients. Additionally, the overexpression of ZEB1 was observed in both AML patients and cell lines. Further functional experiments showed that ZEB1 depletion can induce AML differentiation and inhibit AML proliferation in vitro and in vivo. Moreover, ZEB1 expression was negatively correlated with tumour suppressor P53 expression and ZEB1 can directly bind to P53. Our results also revealed that ZEB1 can regulate PTEN/PI3K/AKT signalling pathway. The inhibitory effect of ZEB1 silencing on PTEN/PI3K/AKT signalling pathway could be significantly reversed by P53 small interfering RNA treatment. Overall, the present data indicated that ZEB1 may be a promising therapeutic target for AML treatment or a potential biomarker for diagnosis and prognosis.

Acidosis induces synovial fibroblasts to release vascular endothelial growth factor via acid-sensitive ion channel 1a.

Acid-sensitive ion channel 1a (ASIC1a) is a member of the extracellular H+ activated cation channel family. Studies have shown that tissue acidification contributes to the formation of microvessels in rheumatoid arthritis (RA) synovial tissue, but its underlying mechanisms remain unclear. The purpose of this study was to investigate the role of tissue acidification in microvascular formation of arthritic synovial tissue and the effect of ASIC1a on vascular endothelial growth factor (VEGF) release from arthritic synovial tissue. Our results indicate that ASIC1a expression, VEGF expression, and microvessel density (MVD) are elevated in RA synovial tissue and adjuvant arthritis (AA) rat synovial tissue. When AA rats were treated with ASIC1a-specific blocker psalmotoxin-1 (PcTx-1), the expression of ASIC1a, VEGF expression, and MVD were all reduced. Acidification of RA synovial fibroblasts (RASF) can promote the release of VEGF. PcTx-1 and ASIC1a-short hairpin RNA can inhibit acid-induced release of VEGF. In addition, the ASIC1a overexpression vector can promote acid-induced VEGF release. This indicates that extracellular acidification induces the release of VEGF by RASF via ASIC1a. These findings suggest that blocking ASIC1a mediates the release of VEGF from synoviocytes may provide a potential therapeutic strategy for RA therapy.

ASIC1a promotes the proliferation of synovial fibroblasts via the ERK/MAPK pathway.

Synovial hyperplasia, a profound alteration in the structure of synovial tissue, is the basis for cumulative joint destruction in rheumatoid arthritis (RA). It is generally accepted that controlling synovial hyperplasia can delay the progression of RA. As one of the most intensively studied isoforms of acid-sensing ion channels (ASICs), ASIC1a contributes to various physiopathologic conditions, including RA, due to its unique property of being permeable to Ca2+. However, the role and the regulatory mechanisms of ASIC1a in synovial hyperplasia are poorly understood. Here, rats induced with adjuvant arthritis (AA) and human primary synovial fibroblasts were used in vivo and in vitro to investigate the role of ASIC1a in the proliferation of RA synovial fibroblasts (RASFs). The results show that the expression of ASIC1a was significantly increased in synovial tissues and RASFs obtained from patients with RA as well as in the synovium of rats with AA. Moreover, extracellular acidification improved the ability of RASFs colony formation and increased the expression of proliferation cell nuclear antigen (PCNA) and Ki67, which was abrogated by the specific ASIC1a inhibitor psalmotoxin-1 (PcTX-1) or ASIC1a-short hairpin RNA (ASIC1a-shRNA), suggesting that extracellular acidification promotes the proliferation of RASFs by activating ASIC1a. In addition, the activation of c-Raf and extracellular signal-regulated protein kinases (ERKs) signaling was blocked with PcTX-1 or ASIC1a-shRNA and the proliferation of RASFs was further inhibited by the ERK inhibitor (U0126), indicating that ERK/MAPK signaling contributes to the proliferation process of RASFs promoted by the activation of ASIC1a. These findings gave us an insight into the role of ASIC1a in the proliferation of RASFs, which may provide solid foundation for ASIC1a as a potential target in the treatment of RA.

Evolutionary Overview of Consumer Health Informatics: Bibliometric Study on the Web of Science from 1999 to 2019.

BACKGROUND: Consumer health informatics (CHI) originated in the 1990s. With the rapid development of computer and information technology for health decision making, an increasing number of consumers have obtained health-related information through the internet, and CHI has also attracted the attention of an increasing number of scholars. OBJECTIVE: The aim of this study was to analyze the research themes and evolution characteristics of different study periods and to discuss the dynamic evolution path and research theme rules in a time-series framework from the perspective of a strategy map and a data flow in CHI. METHODS: The Web of Science core collection database of the Institute for Scientific Information was used as the data source to retrieve relevant articles in the field of CHI. SciMAT was used to preprocess the literature data and construct the overlapping map, evolution map, strategic diagram, and cluster network characterized by keywords. Besides, a bibliometric analysis of the general characteristics, the evolutionary characteristics of the theme, and the evolutionary path of the theme was conducted. RESULTS: A total of 986 articles were obtained after the retrieval, and 931 articles met the document-type requirement. In the past 21 years, the number of articles increased every year, with a remarkable growth after 2015. The research content in 4 different study periods formed the following 38 themes: patient education, medicine, needs, and bibliographic database in the 1999-2003 study period; world wide web, patient education, eHealth, patients, medication, terminology, behavior, technology, and disease in the 2004-2008 study period; websites, information seeking, physicians, attitudes, technology, risk, food labeling, patient, strategies, patient education, and eHealth in the 2009-2014 study period; and electronic medical records, health information seeking, attitudes, health communication, breast cancer, health literacy, technology, natural language processing, user-centered design, pharmacy, academic libraries, costs, internet utilization, and online health information in the 2015-2019 study period. Besides, these themes formed 10 evolution paths in 3 research directions: patient education and intervention, consumer demand attitude and behavior, and internet information technology application. CONCLUSIONS: Averaging 93 publications every year since 2015, CHI research is in a rapid growth period. The research themes mainly focus on patient education, health information needs, health information search behavior, health behavior intervention, health literacy, health information technology, eHealth, and other aspects. Patient education and intervention research, consumer demand, attitude, and behavior research comprise the main theme evolution path, whose evolution process has been relatively stable. This evolution path will continue to become the research hotspot in this field. Research on the internet and information technology application is a secondary theme evolution path with development potential.

E2F4 functions as a tumour suppressor in acute myeloid leukaemia via inhibition of the MAPK signalling pathway by binding to EZH2.

Acute myeloid leukaemia (AML) is an aggressive and mostly incurable haematological malignancy with frequent relapse after an initial response to standard chemotherapy. Therefore, novel therapies are urgently required to improve AML clinical outcome. Here, we aim to study the dysregulation of a particular transcription factor, E2F4, and its role in the progression of AML. In this study, human clinical data from the Gene Expression Profiling Interactive Analysis (GEPIA) revealed that increased E2F4 expression was associated with poor prognosis in AML patients. Moreover, the experimental results showed that E2F4 was aberrantly overexpressed in human AML patients and cell lines. Depletion of E2F4 inhibited the proliferation, induced the differentiation and suppressed the growth of AML cells in a nude mouse model. By contrast, overexpression of E2F4 promoted the proliferation and inhibited the differentiation of AML cells in vitro. Additionally, E2F4 expression not only is positively correlated with EZH2 but also can bind to EZH2. RNA microarray results also showed that E2F4 can regulate MAPK signalling pathway. EZH2 can reverse the inhibitory effect of E2F4 silencing on MAPK signaling pathway. In summary, our data suggest that E2F4 may be a potential therapeutic target for AML therapy.

ATPR induces acute promyelocytic leukemia cells differentiation and growth arrest by blockade of SHP2/Rho/ROCK1 pathway.

Acute promyelocytic leukemia (APL) is a form of acute myeloid leukemia with a unique chromosome translocation t (15;17), commonly complicated by a complex coagulopathy. 4-Amino-2-trifuoromethyl-phenyl retinate (ATPR), a novel all-trans retinoic acid (ATRA) derivative, was synthesized by our group and known to possess obvious biological anti-tumor activities. It has previously been shown that ATPR could induce differentiation and inhibit proliferation of APL cells, although the mechanism responsible for this effect was not well understood. In this study, we demonstrated that ATPR remarkably inhibited the expression and activity of SHP2. Further experiments showed silencing SHP2 or using SHP2 inhibition (SHP099) enhanced the effect of ATPR on cell proliferation and maturation. In addition, we also demonstrated that Rho/ROCK1 might be regulated by SHP2. Using Y-27632, a ROCK inhibitor, further proved that ROCK1 played an important role in ATPR-induced differentiation and proliferation suppression. In conclusion, the results from this study revealed that ATPR induced APL cells terminal differentiation and growth arrest by blockade of SHP2/Rho/ ROCK1 pathway.