NETME: on-the-fly knowledge network construction from biomedical literature

Background The rapidly increasing biological literature is a key resource to automatically extract and gain knowledge concerning biological elements and their relations. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Results We introduce a novel system called NETME, which, starting from a set of full-texts obtained from PubMed, through an easy-to-use web interface, interactively extracts biological elements from ontological databases and then synthesizes a network inferring relations among such elements. The results clearly show that our tool is capable of inferring comprehensive and reliable biological networks.

Biomedical relation extraction via knowledge-enhanced reading comprehension

Background In biomedical research, chemical and disease relation extraction from unstructured biomedical literature is an essential task. Effective context understanding and knowledge integration are two main research problems in this task. Most work of relation extraction focuses on classification for entity mention pairs. Inspired by the effectiveness of machine reading comprehension (RC) in the respect of context understanding, solving biomedical relation extraction with the RC framework at both intra-sentential and inter-sentential levels is a new topic worthy to be explored. Except for the unstructured biomedical text, many structured knowledge bases (KBs) provide valuable guidance for biomedical relation extraction. Utilizing knowledge in the RC framework is also worthy to be investigated. We propose a knowledge-enhanced reading comprehension (KRC) framework to leverage reading comprehension and prior knowledge for biomedical relation extraction. First, we generate questions for each relation, which reformulates the relation extraction task to a question answering task. Second, based on the RC framework, we integrate knowledge representation through an efficient knowledge-enhanced attention interaction mechanism to guide the biomedical relation extraction. Results The proposed model was evaluated on the BioCreative V CDR dataset and CHR dataset. Experiments show that our model achieved a competitive document-level F1 of 71.18% and 93.3%, respectively, compared with other methods. Conclusion Result analysis reveals that open-domain reading comprehension data and knowledge representation can help improve biomedical relation extraction in our proposed KRC framework. Our work can encourage more research on bridging reading comprehension and biomedical relation extraction and promote the biomedical relation extraction.

A Systematic Review and Meta-Analysis of the Effectiveness of Neuroprotectants for Paclitaxel-Induced Peripheral Neuropathy

BackgroundPaclitaxel-induced peripheral neuropathy (PIPN) is a disabling side effect of paclitaxel with few effective preventive strategies. We aim to determine the efficacy of pharmacological and non-pharmacological neuroprotective interventions in preventing PIPN incidence.MethodsBiomedical literature databases were searched from years 2000 to 2021 for trials comparing neuroprotective interventions and control. Meta-analysis was performed using the random-effects model. The primary outcome was the incidence of PIPN.ResultsOf 24 relevant controlled trials, 14 were eligible for meta-analysis. Pooled results from seven non-pharmacological trials were associated with a statistically significant 48% relative reduction of PIPN risk with low heterogeneity. Conversely, pooled results from six pharmacological trials were associated with a significant 20% relative reduction of PIPN risk with moderate heterogeneity. Both pharmacological and non-pharmacological approaches appear effective in reducing PIPN incidence in the treatment arm compared to control (pooled RR < 1).ConclusionCurrent evidence suggests that both interventions may reduce PIPN risk. Non-pharmacological interventions appear more effective than pharmacological interventions.

M2PP: a novel computational model for predicting drug-targeted pathogenic proteins

Background Detecting pathogenic proteins is the origin way to understand the mechanism and resist the invasion of diseases, making pathogenic protein prediction develop into an urgent problem to be solved. Prediction for genome-wide proteins may be not necessarily conducive to rapidly cure diseases as developing new drugs specifically for the predicted pathogenic protein always need major expenditures on time and cost. In order to facilitate disease treatment, computational method to predict pathogenic proteins which are targeted by existing drugs should be exploited. Results In this study, we proposed a novel computational model to predict drug-targeted pathogenic proteins, named as M2PP. Three types of features were presented on our constructed heterogeneous network (including target proteins, diseases and drugs), which were based on the neighborhood similarity information, drug-inferred information and path information. Then, a random forest regression model was trained to score unconfirmed target-disease pairs. Five-fold cross-validation experiment was implemented to evaluate model’s prediction performance, where M2PP achieved advantageous results compared with other state-of-the-art methods. In addition, M2PP accurately predicted high ranked pathogenic proteins for common diseases with public biomedical literature as supporting evidence, indicating its excellent ability. Conclusions M2PP is an effective and accurate model to predict drug-targeted pathogenic proteins, which could provide convenience for the future biological researches.

Efficacy and Safety of Proton Therapy for Medulloblastoma Patients: A Mata-Analysis

Background: Currently, photon therapy is mainly used for radiotherapy, however, the long-term side effects of photon therapy are sometimes reported, especially in children, including cognitive decline, mental decline, growth retardation, endocrine dysfunction and secondary tumor.Compared with photon radiotherapy, proton therapy is a novel method of radiation therapy, which reduces acute and late radiation damage and improves patients’ quality of life. Therefore, we evaluated proton therapy on medulloblastoma patients by meta-analysis in this study. Materials and Methods: A clinical randomized controlled trial was conducted by retrieving the main databases PubMed (Medline), EMbase, Cochrane Library, Chinese Biomedical Literature Database (CBM), Chinese Zhi-wang (CNKI), Wanfang Database, and VIP Database. We analyzed the literature which matched the quality criteria for the prognostic impact of proton and photon therapy on medulloblastoma patients. Results: Ten articles were included in this study. The overall survival (OS) rate and side effects were comprehensively analyzed. The results showed that proton radiotherapy significantly reduced the side effects and recurrence rate of tumor. Conclusion: Proton therapy could significantly reduce the side effects and recurrence rate of medulloblastoma in patients.

Natural Language Processing–Assisted Literature Retrieval and Analysis for Combination Therapy in Cancer

PURPOSE Despite advances in molecular therapeutics, few anticancer agents achieve durable responses. Rational combinations using two or more anticancer drugs have the potential to achieve a synergistic effect and overcome drug resistance, enhancing antitumor efficacy. A publicly accessible biomedical literature search engine dedicated to this domain will facilitate knowledge discovery and reduce manual search and review. METHODS We developed RetriLite, an information retrieval and extraction framework that leverages natural language processing and domain-specific knowledgebase to computationally identify highly relevant papers and extract key information. The modular architecture enables RetriLite to benefit from synergizing information retrieval and natural language processing techniques while remaining flexible to customization. We customized the application and created an informatics pipeline that strategically identifies papers that describe efficacy of using combination therapies in clinical or preclinical studies. RESULTS In a small pilot study, RetriLite achieved an F 1 score of 0.93. A more extensive validation experiment was conducted to determine agents that have enhanced antitumor efficacy in vitro or in vivo with poly (ADP-ribose) polymerase inhibitors: 95.9% of the papers determined to be relevant by our application were true positive and the application's feature of distinguishing a clinical paper from a preclinical paper achieved an accuracy of 97.6%. Interobserver assessment was conducted, which resulted in a 100% concordance. The data derived from the informatics pipeline have also been made accessible to the public via a dedicated online search engine with an intuitive user interface. CONCLUSION RetriLite is a framework that can be applied to establish domain-specific information retrieval and extraction systems. The extensive and high-quality metadata tags along with keyword highlighting facilitate information seekers to more effectively and efficiently discover knowledge in the combination therapy domain.

Is acupuncture effective for knee osteoarthritis? A protocol for a systematic review and meta-analysis

IntroductionKnee osteoarthritis (KOA) is one of the leading causes of disability. The effectiveness of acupuncture for treating KOA remains controversial. This protocol describes the method of a systematic review and meta-analysis evaluating the effectiveness and safety of acupuncture for treating KOA.Methods and analysisFour English databases (PubMed, Embase, Cochrane Library databases and Web of Science) and four Chinese databases (China National Knowledge Infrastructure, Chinese Biomedical Literature Database, VIP Database for Chinese Technical Periodicals, and Wanfang) will be searched from the database inception to 1 September 2021. All randomised controlled trials related to acupuncture for KOA will be included. Extracted data will include publication details, basic information, demographic data, intervention details and patient outcomes. The primary outcome will be pain intensity. Risk of bias will be assessed using the Cochrane Collaboration’s tool for assessing risk of bias. Article selection, data extraction and risk of bias assessment will be performed in duplicate by two independent reviewers. If the meta-analysis is precluded, we will conduct a descriptive synthesis using a best-evidence synthesis approach. The strength of recommendations and quality of evidence will be assessed using the Grading of Recommendations Assessment Development and Evaluation working group methodology.Ethics and disseminationEthics approval is not required because individual patient data are not included. This protocol was registered in the international Prospective Register of Systematic Reviews on 25 February 2021. The systematic review and meta-analysis will be submitted for publication in a peer-reviewed journal. The findings will also be disseminated through conference presentations.Trial registration numberCRD42021232177.

Music therapy for sleep quality in cancer patients with insomnia：A protocol for systematic review and meta-analysis

Review question / Objective: The aim of this systematic review is to compare music therapy in terms of efficacy in cancer patients with insomnia disorders to better inform clinical practice. Condition being studied: The effectiveness of music therapy for cancer- associate insomnia is the main interest of this systematic review. Information sources: MEDLINE (PubMed, Ovid) The Cochrane Library, Web of Science, Embase and Electronic retrieval of Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CHKD-CNKI), VIP database, Wanfang Database will be searched from inception time to date. In addition, the included literature will be reviewed and relevant literature will be supplemented.

Kuntai Capsule Combined With Letrozole on Gonadal Hormone Levels and Ovarian Function in Patients With PCOS: A Systematic Review and Meta-Analysis

BackgroundThe efficacy of Kuntai capsule combined with letrozole (LE) in improving ovarian function of polycystic ovary syndrome (PCOS) has been evaluated before, but there is still a lack of evidence-based support for the regulation of sex hormone levels. In recent years, new randomized clinical trials (RCTs) have been reported on the effect of combined therapy on regulating sex hormone levels.ObjectiveWe aimed to systematically evaluate the efficacy of Kuntai capsule combined with LE in the treatment of PCOS.MethodsA search across the China Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), Wanfang database, PubMed, Web of Science, The Cochrane Library, and Embase was conducted on Kuntai capsule combined with LE in the treatment of PCOS. The time of the self-built database was up to April 30, 2021. RCTs of LE in the control group and LE combined with Kuntai capsule in the experimental group were selected. RevMan5.3 software was used for data analysis.ResultsA total of 17 studies were gathered, which included 1,684 patients. The meta-analysis results showed that the total effective rate of the combined group was 93.36% and that of the LE group was 78.15%. The improvement in the ovulation rate, pregnancy rate, number of mature follicles, endometrial thickness, cervical mucus score, and serum follicle stimulating hormone (FSH), luteinizing hormone (LH), and prolactin (PRL) in the combined group was consistent with the results of a previous meta-analysis and was better than that in the LE group (p < 0.05). In addition, the combination group was better than the LE group in regulating the levels of estradiol (E2) and testosterone (T) (p < 0.05). There were no adverse drug reactions in the two groups during treatment.ConclusionAs a type of pure traditional Chinese medicine preparation, Kuntai capsule combined with LE had a better effect than LE alone in the treatment of PCOS, with advantages mainly reflected in enhancing ovarian function and regulating the levels of sex hormones in vivo, among others, but the value of combined therapy still needs to be verified by more high-quality RCTs.