LDA-VGHB: identifying potential lncRNA-disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine.

Long noncoding RNAs (lncRNAs) participate in various biological processes and have close linkages with diseases. In vivo and in vitro experiments have validated many associations between lncRNAs and diseases. However, biological experiments are time-consuming and expensive. Here, we introduce LDA-VGHB, an lncRNA-disease association (LDA) identification framework, by incorporating feature extraction based on singular value decomposition and variational graph autoencoder and LDA classification based on heterogeneous Newton boosting machine. LDA-VGHB was compared with four classical LDA prediction methods (i.e. SDLDA, LDNFSGB, IPCARF and LDASR) and four popular boosting models (XGBoost, AdaBoost, CatBoost and LightGBM) under 5-fold cross-validations on lncRNAs, diseases, lncRNA-disease pairs and independent lncRNAs and independent diseases, respectively. It greatly outperformed the other methods with its prominent performance under four different cross-validations on the lncRNADisease and MNDR databases. We further investigated potential lncRNAs for lung cancer, breast cancer, colorectal cancer and kidney neoplasms and inferred the top 20 lncRNAs associated with them among all their unobserved lncRNAs. The results showed that most of the predicted top 20 lncRNAs have been verified by biomedical experiments provided by the Lnc2Cancer 3.0, lncRNADisease v2.0 and RNADisease databases as well as publications. We found that HAR1A, KCNQ1DN, ZFAT-AS1 and HAR1B could associate with lung cancer, breast cancer, colorectal cancer and kidney neoplasms, respectively. The results need further biological experimental validation. We foresee that LDA-VGHB was capable of identifying possible lncRNAs for complex diseases. LDA-VGHB is publicly available at https://github.com/plhhnu/LDA-VGHB.

SEnSCA: Identifying possible ligand-receptor interactions and its application in cell-cell communication inference.

Multicellular organisms have dense affinity with the coordination of cellular activities, which severely depend on communication across diverse cell types. Cell-cell communication (CCC) is often mediated via ligand-receptor interactions (LRIs). Existing CCC inference methods are limited to known LRIs. To address this problem, we developed a comprehensive CCC analysis tool SEnSCA by integrating single cell RNA sequencing and proteome data. SEnSCA mainly contains potential LRI acquisition and CCC strength evaluation. For acquiring potential LRIs, it first extracts LRI features and reduces the feature dimension, subsequently constructs negative LRI samples through K-means clustering, finally acquires potential LRIs based on Stacking ensemble comprising support vector machine, 1D-convolutional neural networks and multi-head attention mechanism. During CCC strength evaluation, SEnSCA conducts LRI filtering and then infers CCC by combining the three-point estimation approach and single cell RNA sequencing data. SEnSCA computed better precision, recall, accuracy, F1 score, AUC and AUPR under most of conditions when predicting possible LRIs. To better illustrate the inferred CCC network, SEnSCA provided three visualization options: heatmap, bubble diagram and network diagram. Its application on human melanoma tissue demonstrated its reliability in CCC detection. In summary, SEnSCA offers a useful CCC inference tool and is freely available at https://github.com/plhhnu/SEnSCA.

Cell-cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies.

Carcinomas are complex ecosystems composed of cancer, stromal and immune cells. Communication between these cells and their microenvironments induces cancer progression and causes therapy resistance. In order to improve the treatment of cancers, it is essential to quantify crosstalk between and within various cell types in a tumour microenvironment. Focusing on the coordinated expression patterns of ligands and cognate receptors, cell-cell communication can be inferred through ligand-receptor interactions (LRIs). In this manuscript, we carry out the following work: (i) introduce pipeline for ligand-receptor-mediated intercellular communication estimation from single-cell transcriptomics and list a few available LRI-related databases and visualization tools; (ii) demonstrate seven classical intercellular communication scoring strategies, highlight four types of representative intercellular communication inference methods, including network-based approaches, machine learning-based approaches, spatial information-based approaches and other approaches; (iii) summarize the evaluation and validation avenues for intercellular communication inference and analyze the advantages and limitations for the above four types of cell-cell communication methods; (iv) comment several major challenges while provide further research directions for intercellular communication analysis in the tumour microenvironments. We anticipate that this work helps to better understand intercellular crosstalk and to further develop powerful cell-cell communication estimation tools for tumor-targeted therapy.

Circ_0026579 knockdown ameliorates lipopolysaccharide-induced human lung fibroblast cell injury by regulating CXCR1 via miR-370-3p.

Pneumonia is an inflammatory disease in lower respiratory tracts and its development involves the regulation of RNAs. Circular RNAs are a class of RNA subgroups that can mediate the progression of pneumonia. However, the molecular mechanism of circ_0026579 in regulating pneumonia occurrence remains unclear. The study is designed to reveal the role of circ_0026579 in lipopolysaccharide (LPS)-induced human lung fibroblast cell injury and the underlying mechanism. The expression levels of circ_0026579, miR-370-3p and C-X-C motif chemokine receptor 1 (CXCR1) were detected by quantitative real-time polymerase chain reaction or by western blotting. The production of tumour necrosis factor-α, interleukin (IL)-1ß and IL-6 was assessed by enzyme-linked immunosorbent assays. Malondialdehyde and superoxide dismutase levels were analysed using commercial kits. Cell viability, proliferation and apoptosis were analysed by cell counting kit-8 assay, 5-Ethynyl-2'-deoxyuridine assay and flow cytometry analysis, respectively. The binding relationship between miR-370-3p and circ_0026579 or CXCR1 was identified by dual-luciferase reporter assay, RNA immunoprecipitation assay and RNA pull-down assay. Circ_0026579 and CXCR1 expression were significantly upregulated, whereas miR-370-3p was downregulated in the serum of pneumonia patients. LPS treatment induced inflammatory response, oxidative stress and cell apoptosis and inhibited cell proliferation in MRC-5 cells; however, these effects were reversed after circ_0026579 depletion. In terms of the mechanism, circ_0026579 acted as a miR-370-3p sponge, and miR-370-3p combined with CXCR1. Additionally, circ_0026579 depletion ameliorated LPS-induced MRC-5 cell disorder by increasing miR-370-3p expression. CXCR1 overexpression also relieved the miR-370-3p-mediated effects in LPS-treated MRC-5 cells. Further, circ_0026579 induced CXCR1 expression by interacting with miR-370-3p. Circ_0026579 absence ameliorated MRC-5 cell dysfunction induced by LPS through the regulation of the miR-370-3p/CXCR1 axis.

Sustainable development of urban agglomeration based on material metabolism: a case study on Fujian Delta, China.

As highly concentrated urbanized areas, urban agglomerations bear increasing resource depletion and environmental pressures, which threaten the regional sustainable development. Resource and environmental problems arising from the process of urbanization can be attributed to the dislocation or maladjustment of material metabolism in time or space. Conducting research on material metabolism at the level of urban agglomerations is helpful in finding the root causes of environmental problems to provide support for the reduction of regional resource consumption and pollution emissions. The material metabolism characteristics of the urban agglomeration and internal cities of the Fujian Delta Urban Agglomeration (FDUA) in China are evaluated using the material flow analysis. The following results are observed. (1) The economic development of the FDUA is still at risk of resource consumption, and a large proportion of hidden flow (HF > 80%) drags down the overall metabolic efficiency and sustainable development. (2) The discharge of various pollutants in the FDUA generally shows a downward trend. Improving metabolic efficiency, delayed MCI growth, and improved overall regional environmental quality are observed. (3) Cities that have relatively scarce land resources but are economically developed, such as Xiamen, still bear a relatively heavy ecological burden (ECdmc > 1). (4) Regional collaboration is conducive to the sustainable development of multiple regions. On the one hand, the results of this study provide decision-making basis for the sustainable development of the national ecological civilization demonstration area. On the other hand, this work guides the establishment of a comprehensive industrial linkage and cooperation mechanism for the same type of small- and medium-sized urban agglomerations.

Computational drug repositioning using similarity constrained weight regularization matrix factorization: A case of COVID-19.

Amid the COVID-19 crisis, we put sizeable efforts to collect a high number of experimentally validated drug-virus association entries from literature by text mining and built a human drug-virus association database. To the best of our knowledge, it is the largest publicly available drug-virus database so far. Next, we develop a novel weight regularization matrix factorization approach, termed WRMF, for in silico drug repurposing by integrating three networks: the known drug-virus association network, the drug-drug chemical structure similarity network, and the virus-virus genomic sequencing similarity network. Specifically, WRMF adds a weight to each training sample for reducing the influence of negative samples (i.e. the drug-virus association is unassociated). A comparison on the curated drug-virus database shows that WRMF performs better than a few state-of-the-art methods. In addition, we selected the other two different public datasets (i.e. Cdataset and HMDD V2.0) to assess WRMF's performance. The case study also demonstrated the accuracy and reliability of WRMF to infer potential drugs for the novel virus. In summary, we offer a useful tool including a novel drug-virus association database and a powerful method WRMF to repurpose potential drugs for new viruses.

Identification of exosomal circRNA CD226 as a potent driver of nonsmall cell lung cancer through miR-1224-3p/high mobility group AT-hook 2 axis.

Circular RNAs (circRNAs) are crucial for the pathogenesis of nonsmall lung cancer (NSCLC). Here, we set out to unravel the precise function of circRNA CD226 (circCD226) in NSCLC pathogenesis. The exosomes from serum specimens were observed by transmission electron microscopy. CircCD226, miR-1224-3p and high mobility group AT-hook 2 (HMGA2) were quantified by qRT-PCR, western blot and immunohistochemistry. Actinomycin D and Ribonuclease (RNase) R treatments and subcellular localization assay were used for circCD226 characterization. Cell viability, proliferation, migration, invasion and sphere formation abilities were gauged by CCK-8, EDU, wound-healing, transwell and sphere formation assays, respectively. Directed relationships among circCD226, miR-1224-3p and HMGA2 were examined by RNA pull-down, dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. The abundance of circCD226 was elevated in serum exosomes, tissues and cells of NSCLC. NSCLC serum exosomes enhanced NSCLC cell proliferation, migration, invasion and stemness. Loss of circCD226 impeded cell proliferation, migration, invasion and stemness in vitro , as well as tumor growth in vivo . Mechanistically, circCD226 sponged miR-1224-3p, and miR-1224-3p targeted HMGA2. CircCD226 involved the posttranscriptional regulation of HMGA2 through miR-1224-3p. Moreover, the miR-1224-3p/HMGA2 axis was identified as a functionally downstream effector of circCD226 in regulating NSCLC cell behaviors. Our study identifies circCD226 as a potential driver in NSCLC development depending on the regulation of miR-1224-3p/HMGA2 axis.

LPI-deepGBDT: a multiple-layer deep framework based on gradient boosting decision trees for lncRNA-protein interaction identification.

BACKGROUND: Long noncoding RNAs (lncRNAs) play important roles in various biological and pathological processes. Discovery of lncRNA-protein interactions (LPIs) contributes to understand the biological functions and mechanisms of lncRNAs. Although wet experiments find a few interactions between lncRNAs and proteins, experimental techniques are costly and time-consuming. Therefore, computational methods are increasingly exploited to uncover the possible associations. However, existing computational methods have several limitations. First, majority of them were measured based on one simple dataset, which may result in the prediction bias. Second, few of them are applied to identify relevant data for new lncRNAs (or proteins). Finally, they failed to utilize diverse biological information of lncRNAs and proteins. RESULTS: Under the feed-forward deep architecture based on gradient boosting decision trees (LPI-deepGBDT), this work focuses on classify unobserved LPIs. First, three human LPI datasets and two plant LPI datasets are arranged. Second, the biological features of lncRNAs and proteins are extracted by Pyfeat and BioProt, respectively. Thirdly, the features are dimensionally reduced and concatenated as a vector to represent an lncRNA-protein pair. Finally, a deep architecture composed of forward mappings and inverse mappings is developed to predict underlying linkages between lncRNAs and proteins. LPI-deepGBDT is compared with five classical LPI prediction models (LPI-BLS, LPI-CatBoost, PLIPCOM, LPI-SKF, and LPI-HNM) under three cross validations on lncRNAs, proteins, lncRNA-protein pairs, respectively. It obtains the best average AUC and AUPR values under the majority of situations, significantly outperforming other five LPI identification methods. That is, AUCs computed by LPI-deepGBDT are 0.8321, 0.6815, and 0.9073, respectively and AUPRs are 0.8095, 0.6771, and 0.8849, respectively. The results demonstrate the powerful classification ability of LPI-deepGBDT. Case study analyses show that there may be interactions between GAS5 and Q15717, RAB30-AS1 and O00425, and LINC-01572 and P35637. CONCLUSIONS: Integrating ensemble learning and hierarchical distributed representations and building a multiple-layered deep architecture, this work improves LPI prediction performance as well as effectively probes interaction data for new lncRNAs/proteins.

LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification.

BACKGROUND: Long noncoding RNAs (lncRNAs) have dense linkages with a plethora of important cellular activities. lncRNAs exert functions by linking with corresponding RNA-binding proteins. Since experimental techniques to detect lncRNA-protein interactions (LPIs) are laborious and time-consuming, a few computational methods have been reported for LPI prediction. However, computation-based LPI identification methods have the following limitations: (1) Most methods were evaluated on a single dataset, and researchers may thus fail to measure their generalization ability. (2) The majority of methods were validated under cross validation on lncRNA-protein pairs, did not investigate the performance under other cross validations, especially for cross validation on independent lncRNAs and independent proteins. (3) lncRNAs and proteins have abundant biological information, how to select informative features need to further investigate. RESULTS: Under a hybrid framework (LPI-HyADBS) integrating feature selection based on AdaBoost, and classification models including deep neural network (DNN), extreme gradient Boost (XGBoost), and SVM with a penalty Coefficient of misclassification (C-SVM), this work focuses on finding new LPIs. First, five datasets are arranged. Each dataset contains lncRNA sequences, protein sequences, and an LPI network. Second, biological features of lncRNAs and proteins are acquired based on Pyfeat. Third, the obtained features of lncRNAs and proteins are selected based on AdaBoost and concatenated to depict each LPI sample. Fourth, DNN, XGBoost, and C-SVM are used to classify lncRNA-protein pairs based on the concatenated features. Finally, a hybrid framework is developed to integrate the classification results from the above three classifiers. LPI-HyADBS is compared to six classical LPI prediction approaches (LPI-SKF, LPI-NRLMF, Capsule-LPI, LPI-CNNCP, LPLNP, and LPBNI) on five datasets under 5-fold cross validations on lncRNAs, proteins, lncRNA-protein pairs, and independent lncRNAs and independent proteins. The results show LPI-HyADBS has the best LPI prediction performance under four different cross validations. In particular, LPI-HyADBS obtains better classification ability than other six approaches under the constructed independent dataset. Case analyses suggest that there is relevance between ZNF667-AS1 and Q15717. CONCLUSIONS: Integrating feature selection approach based on AdaBoost, three classification techniques including DNN, XGBoost, and C-SVM, this work develops a hybrid framework to identify new linkages between lncRNAs and proteins.

Effects of Abdominal Binders on Postoperative Pain and Functional Recovery: A Systematic Review and Meta-Analysis.

OBJECTIVE: This study aimed to assess the effectiveness of abdominal binders (ABs) on postoperative pain and functional recovery in patients receiving abdominal surgery. METHODS: The Pubmed, Embase, Cochrane Library, and PEDro databases were searched for clinical trials published up to November 30, 2019. Randomized controlled trials that compared the effects of wearing an AB to not wearing an AB in participants after abdominal surgery were included. The primary outcomes were pain, pulmonary function, and physical function, as assessed by the visual analog scale score, a spirometry device, and the 6-minute walk test, respectively. The registration number of this review in PROSPERO is CRD42020165303. RESULTS: Fourteen trials involving 1,317 participants were included. Pooled estimates for the visual analog scale score and the 6-minute walk test showed significant differences between the AB group and the control group, especially on the fourth day following surgery (mean difference [MD] = -2.82, 95% confidence interval [CI] = -3.41 to -2.22; P < 0.00001; MD = 50.97 meters, 95% CI = 39.99-61.95 m; P < 0.00001). However, no significant differences were found in pulmonary function (forced vital capacity [FVC]: MD = 0.01, 95% CI = -0.29 to -0.32; P = 0.94; forced expiratory volume during the first second [FEV1]: MD = -0.05, 95% CI = -0.24 to 0.14; P = 0.63; FEV1/FVC: MD = 3.14, 95% CI = -2.78 to 9.06; P = 0.30). CONCLUSION: ABs probably improve postoperative pain and physical function, especially on the fourth day or more following abdominal surgery, but they have no effects on pulmonary function.

Effect of Therapeutic Ultrasound for Neck Pain: A Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the effects and safety of therapeutic ultrasound in patients with neck pain. DATA SOURCES: The PubMed, EMBASE, CENTRAL, and Physiotherapy Evidence databases were searched for articles published before December 1, 2020. STUDY SELECTION: Randomized controlled trials that compared the effects of therapeutic ultrasound on neck pain were included in this review. The included studies compared therapeutic ultrasound plus other treatments with the other treatments alone or compared therapeutic ultrasound with sham or no treatment. Outcome measures involved the effects on pain, disability, and quality of life. Other treatments included all nonultrasonic therapies (eg, various exercises, massage, electrotherapy). DATA EXTRACTION: Data on the study population, therapeutic ultrasound intervention, combined intervention, outcome measures, and follow-up were extracted. DATA SYNTHESIS: Twelve randomized controlled trials (705 patients) fulfilled the inclusion criteria. Seven studies compared therapeutic ultrasound plus other treatments vs the other treatments alone (449 patients). Therapeutic ultrasound yielded additional benefits for pain, but there was high heterogeneity and we could not draw a clear conclusion. Ultrasound did not have a better effect on disability or quality of life when it was combined with other treatments. Five studies compared therapeutic ultrasound with sham or no treatment (256 patients), and the pooled data showed that therapeutic ultrasound significantly reduced pain intensity. No adverse events of therapeutic ultrasound were reported in the included studies. CONCLUSIONS: Therapeutic ultrasound may reduce the intensity of pain more than sham or no treatment, and it is a safe treatment. Whether therapeutic ultrasound in combination with other conventional treatments produced additional benefits on pain intensity, disability, or quality of life is not clear. The randomized trials included in this review had different levels of quality and high heterogeneity. A large trial using a valid methodology is warranted.

The Effect of Pulsed Electromagnetic Fields on Angiogenesis.

A pulsed electromagnetic field (PEMF) has been used to treat inflammation-based diseases such as osteoporosis, neurological injury, and osteoarthritis. Numerous animal experiments and in vitro studies have shown that PEMF may affect angiogenesis. For ischemic diseases, in theory, blood flow may be richer by increasing the number of blood vessels which supply blood to ischemic tissue. PEMF plays a role in enhancing angiogenesis, and their clinical application may go far beyond the current scope. In this review, we analyzed and summarized the effects and possible mechanisms of PEMF on angiogenesis. Most studies have shown that PEMF with specific parameters can promote angiogenesis, which is manifested by an increased vascular growth rate and increased capillary density. The potential mechanisms consist of promoting vascular endothelial cell proliferation, migration, and tube formation, and increasing the expression level of vascular endothelial growth factor (VEGF), fibroblast growth factor 2 (FGF2), angiopoietin-2 (Ang-2), and other angiogenic growth factors. Additionally, PEMF has an impact on the activation of voltage-gated calcium channels (VGCC). Bioelectromagnetics. © 2021 Bioelectromagnetics Society.

Probing antiviral drugs against SARS-CoV-2 through virus-drug association prediction based on the KATZ method.

It is urgent to find an effective antiviral drug against SARS-CoV-2. In this study, 96 virus-drug associations (VDAs) from 12 viruses including SARS-CoV-2 and similar viruses and 78 small molecules are selected. Complete genomic sequence similarity of viruses and chemical structure similarity of drugs are then computed. A KATZ-based VDA prediction method (VDA-KATZ) is developed to infer possible drugs associated with SARS-CoV-2. VDA-KATZ obtained the best AUCs of 0.8803 when the walking length is 2. The predicted top 3 antiviral drugs against SARS-CoV-2 are remdesivir, oseltamivir, and zanamivir. Molecular docking is conducted between the predicted top 10 drugs and the virus spike protein/human ACE2. The results showed that the above 3 chemical agents have higher molecular binding energies with ACE2. For the first time, we found that zidovudine may be effective clues of treatment of COVID-19. We hope that our predicted drugs could help to prevent the spreading of COVID.

Critical Review of Synthesis, Toxicology and Detection of Acyclovir.

Acyclovir (ACV) is an effective and selective antiviral drug, and the study of its toxicology and the use of appropriate detection techniques to control its toxicity at safe levels are extremely important for medicine efforts and human health. This review discusses the mechanism driving ACV's ability to inhibit viral coding, starting from its development and pharmacology. A comprehensive summary of the existing preparation methods and synthetic materials, such as 5-aminoimidazole-4-carboxamide, guanine and its derivatives, and other purine derivatives, is presented to elucidate the preparation of ACV in detail. In addition, it presents valuable analytical procedures for the toxicological studies of ACV, which are essential for human use and dosing. Analytical methods, including spectrophotometry, high performance liquid chromatography (HPLC), liquid chromatography/tandem mass spectrometry (LC-MS/MS), electrochemical sensors, molecularly imprinted polymers (MIPs), and flow injection-chemiluminescence (FI-CL) are also highlighted. A brief description of the characteristics of each of these methods is also presented. Finally, insight is provided for the development of ACV to drive further innovation of ACV in pharmaceutical applications. This review provides a comprehensive summary of the past life and future challenges of ACV.

Peripheral blood markers predictive of outcome and immune-related adverse events in advanced non-small cell lung cancer treated with PD-1 inhibitors.

BACKGROUND: Selected patients with advanced non-small cell lung cancer (NSCLC) benefit from immunotherapy, especially immune checkpoint inhibitors such as PD-1 (programmed cell death protein 1) inhibitor. Peripheral blood biomarkers would be most convenient to predict treatment outcome and immune-related adverse events (irAEs) in candidate patients. This study explored associations between inflammation-related peripheral blood markers and onset of irAEs and outcome in patients with advanced NSCLC receiving PD-1 inhibitors. METHODS: A retrospective analysis was conducted of 102 patients with advanced NSCLC receiving PD-1 inhibitors from January 2017 to May 2019. Cox regression models were employed to assess the prognostic effect of low/high neutrophil/lymphocyte ratio (NLR), lactate dehydrogenase (LDH), and prognostic nutrition index (PNI) on overall survival (OS) and progression-free survival (PFS). Logistic regression models were used to analyze the correlation between peripheral blood markers and the onset of irAEs. RESULT: NLR < 5, LDH < 240 U/L, or PNI ≥ 45 was favorably associated with significantly better outcomes compared with higher, higher, or lower values, respectively. The multivariate analysis determined that these parameters were independently associated with both better PFS (p = 0.049, 0.046, 0.014, respectively) and longer OS (p = 0.007, 0.031, < 0.001, respectively). Patients with three favorable factors among NLR, LDH, and PNI had better PFS and OS than did those with two, one, or none. PNI and NLR were associated with the onset of irAEs. CONCLUSION: In patients with advanced NSCLC treated with PD-1 inhibitors, pretreatment NLR, LDH, and PNI may be useful predictive markers of clinical outcome and irAEs.

Single-cell RNA-seq clustering: datasets, models, and algorithms.

Single-cell RNA sequencing (scRNA-seq) technologies allow numerous opportunities for revealing novel and potentially unexpected biological discoveries. scRNA-seq clustering helps elucidate cell-to-cell heterogeneity and uncover cell subgroups and cell dynamics at the group level. Two important aspects of scRNA-seq data analysis were introduced and discussed in the present review: relevant datasets and analytical tools. In particular, we reviewed popular scRNA-seq datasets and discussed scRNA-seq clustering models including K-means clustering, hierarchical clustering, consensus clustering, and so on. Seven state-of-the-art scRNA clustering methods were compared on five public available datasets. Two primary evaluation metrics, the Adjusted Rand Index (ARI) and the Normalized Mutual Information (NMI), were used to evaluate these methods. Although unsupervised models can effectively cluster scRNA-seq data, these methods also have challenges. Some suggestions were provided for future research directions.

Pulsed Electromagnetic Fields Increase Angiogenesis and Improve Cardiac Function After Myocardial Ischemia in Mice.

BACKGROUND: Previous studies have shown that pulsed electromagnetic fields (PEMF) stimulate angiogenesis and may be a potential treatment strategy to improve cardiac function after myocardial infarction (MI). This study explored the effects and its related mechanisms of PEMF in MI mice.Methods and Results:MI mice were used in PEMF treatment (15 Hz 1.5 mT PEMF or 30 Hz 3.0 mT PEMF) for 45 min per day for 2 weeks. Furthermore, an in vivo Matrigel plug assay was used to observe the effect of PEMF in promoting angiogenesis. Compared with the sham PEMF group, PEMF treatment with 30 Hz 3.0 mT significantly improved heart function. PEMF treatment with 15 Hz 1.5 mT and 30 Hz 3.0 mT both increased capillary density, decreased infarction area size, increased the protein expression of vascular endothelial growth factor (VEGF), vascular endothelial growth factor receptor 2 (VEGFR2), Ser473-phosphorylated Akt (pSer473-Akt) and S1177-phosphorylated endothelial nitric oxide synthase (pS1177-eNOS), and increased the mRNA level of VEGF and hypoxia inducible factor 1-alpha (HIF-1α) in the infarct border zone. Additionally, treatment with 30 Hz 3.0 mT also increased protein and mRNA level of fibroblast growth factor 2 (FGF2), and protein level of ß1 integrin, and shows a stronger therapeutic effect. CONCLUSIONS: PEMF treatment could promote angiogenesis of the infarct border zone and improve cardiac function in MI mice. A treatment parameter of 30 Hz 3.0 mT is remarkably effective in MI mice. The effect is associated with the proangiogenic signaling pathways of HIF-1α/VEGF/Akt/eNOS or HIF-1α/FGF2/Akt/eNOS.

Efficacy of Extracorporeal Shockwave Therapy on Pain and Function in Myofascial Pain Syndrome of the Trapezius: A Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the effect of extracorporeal shockwave therapy (ESWT) on pain and function in myofascial pain syndrome (MPS) of the trapezius. DATA SOURCES: PubMed, EMBASE, Web of Science, Physiotherapy Evidence Database, and The Cochrane Central Register of Controlled Trials were systematically searched from the time of their inception to September 2019. STUDY SELECTION: Randomized controlled trials comparing the effects of ESWT on MPS of the trapezius were included in this review. DATA EXTRACTION: Data related to study participants, intervention, follow-up period, measure time, and outcomes were extracted. The Physiotherapy Evidence Database scale and the Cochrane Collaboration Tool for Assessing Risk of Bias were used to assess study quality and risk of bias. DATA SYNTHESIS: In total, 10 articles (n=477 patients) met our criteria and were included in this study. The overall effectiveness was calculated using a meta-analysis method. The meta-analysis revealed that ESWT exhibited significant improvement in pain reduction compared with sham ESWT or ultrasound treatment, but no significant effect when compared with conventional treatments (dry needling, trigger point injection, laser therapy) as for pain intensity and neck disability index. CONCLUSIONS: ESWT appears to benefit patients with MPS of the trapezius by alleviating pain. ESWT may not be an ideal therapeutic method to replace conventional therapies but could serve as an adjunct therapeutic method to those treatments.

Effectiveness of Pulsed Electromagnetic Fields on Bone Healing: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

The effect of pulsed electromagnetic field (PEMF) on bone healing is still uncertain and it has not been established as a standardized treatment. The aim of this systematic review and meta-analysis is to evaluate the effect of PEMF on bone healing in patients with fracture. We searched CNKI, Wan Fang, VIP, EMbase, PubMed, CENTRAL, Web of Science, Physiotherapy Evidence Database, and Open Grey websites for randomized controlled trials (published before July 2019 in English or Chinese) comparing any form of PEMF to sham. Reference lists were also searched. Related data were extracted by two investigators independently. The bias risk of the articles and the evidence strength of the outcomes were evaluated. Twenty-two studies were eligible and included in our analysis (n = 1,468 participants). The pooled results of 14 studies (n = 1,131 participants) demonstrated that healing rate in PEMF group was 79.7% (443/556), and that in the control group was 64.3% (370/575). PEMF increased healing rate (RR = 1.22; 95% confidence interval [CI] = 1.10-1.35; I2 = 48%) by the Mantel-Haenszel analysis, relieved pain (standardized mean difference (SMD) = -0.49; 95% CI = -0.88 to -0.10; I2 = 60%) by the inverse variance analysis, and accelerated healing time (SMD = -1.01; 95% CI = -2.01 to -0.00; I2 = 90%) by the inverse variance analysis. Moderate quality evidence suggested that PEMF increased healing rate and relieved pain of fracture, and very low-quality evidence showed that PEMF accelerated healing time. Larger and higher quality randomized controlled trials and pre-clinical studies of optimal frequency, amplitude, and duration parameters are needed. © 2020 Bioelectromagnetics Society.

The pathways by which the marine diatom Thalassiosira sp. OUC2 biodegrades p-xylene, combined with a mechanistic analysis at the proteomic level.

A marine diatom, Thalassiosira sp. OUC2, was isolated from natural seawater collected from Daya Bay, China. This diatom degraded 1.25-40 mg L-1p-xylene within five days, at a removal efficiency exceeding 98%. Gas chromatography-mass spectrometer (GC-MS) analysis indicated that p-xylene was converted into 4-methylbenzyl alcohol, p-toluic acid, and p-cresol in the presence of strain OUC2. Meanwhile, proteomic analysis showed that, after exposure to p-xylene, several algal enzymes were significantly upregulated: including monooxygenase, alcohol dehydrogenase, benzaldehyde dehydrogenase, benzoate 1,2-dioxygenase, and catechol 2,3-dioxygenase. Moreover, ecotoxicological tests suggested that the intermediate metabolites were less toxic than the parent compound (p-xylene). Thalassiosira sp. OUC2 may thus be suitable for the remediation of p-xylene-contaminated marine environments.