Association between the neutrophil-to-lymphocyte ratio and cognitive impairment: a meta-analysis of observational studies

BackgroundSystemic inflammation is one of the underlying mechanisms of cognitive impairment. The neutrophil-to-lymphocyte ratio (NLR) has emerged as a systemic inflammation indicator. This meta-analysis aimed to evaluate the association between high NLR and cognitive impairment (CI) risk.MethodA comprehensive systematic search was conducted to identify eligible studies published until May 30, 2023. The reference group comprised patients with the lowest NLR level, whereas the exposure group comprised those with the highest NLR level. The main outcome was to examine the relationship between NLR and CI risk. The secondary outcome included the association between patient characteristics or comorbidities and CI risk.ResultsThis meta-analysis included 11 studies published between 2018 and 2023, involving 10,357 patients. Patients with CI had a higher NLR than those without (mean difference=0.35, 95% confidence interval [CI]: 0.26–0.44, p < 00001, I2 = 86%). Consistently, pooled results revealed an association between high NLR and CI risk (odds ratio [OR]=2.53, 95% CI:1.67–3.82, p<0.0001, I2 = 84%). Furthermore, aging (mean difference =4.31 years, 95% CI:2.83–5.8, p < 0.00001, I2 = 92%), diabetes (OR=1.59, 95% CI:1.35–1.88, p < 0.00001, I2 = 66%), and hypertension (OR=1.36, 95% CI:1.19–1.57, p < 0.00001, I2 = 0%) were significant risk factors for CI. However, no significant associations were observed between CI and male gender (OR = 0.84, 95% CI:0.64–1.11, p = 0.22, I2 = 81%), body mass index (mean = −0.32 kg/m2, 95% CI: −0.82, 0.18, p = 0.2, I2 = 82%), alcohol consumption (OR = 1.11, 95% CI:0.95−1.3, p = 1.35, I2 = 0%), and smoking (OR = 0.99, 95% CI:0.87–1.13, p = 0.86, I2 = 0%). Meta-regression found that diabetes and hypertension, but not age, significantly moderated the association between NLR and CI.ConclusionThis meta-analysis showed a significant association between high NLR and increased CI risk. Moreover, meta-regression identified diabetes and hypertension, but not age, as significant moderating factors in the relationship between NLR and CI. To validate and strengthen these findings, further large-scale studies are required.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023430384, identifier CRD42023430384

Exploiting likely-positive and unlabeled data to improve the identification of protein-protein interaction articles

<p>Abstract</p> <p>Background</p> <p>Experimentally verified protein-protein interactions (PPI) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be made faster by ranking newly-published articles' relevance to PPI, a task which we approach here by designing a machine-learning-based PPI classifier. All classifiers require labeled data, and the more labeled data available, the more reliable they become. Although many PPI databases with large numbers of labeled articles are available, incorporating these databases into the base training data may actually reduce classification performance since the supplementary databases may not annotate exactly the same PPI types as the base training data. Our first goal in this paper is to find a method of selecting likely positive data from such supplementary databases. Only extracting likely positive data, however, will bias the classification model unless sufficient negative data is also added. Unfortunately, negative data is very hard to obtain because there are no resources that compile such information. Therefore, our second aim is to select such negative data from unlabeled PubMed data. Thirdly, we explore how to exploit these likely positive and negative data. And lastly, we look at the somewhat unrelated question of which term-weighting scheme is most effective for identifying PPI-related articles.</p> <p>Results</p> <p>To evaluate the performance of our PPI text classifier, we conducted experiments based on the BioCreAtIvE-II IAS dataset. Our results show that adding likely-labeled data generally increases AUC by 3~6%, indicating better ranking ability. Our experiments also show that our newly-proposed term-weighting scheme has the highest AUC among all common weighting schemes. Our final model achieves an F-measure and AUC 2.9% and 5.0% higher than those of the top-ranking system in the IAS challenge.</p> <p>Conclusion</p> <p>Our experiments demonstrate the effectiveness of integrating unlabeled and likely labeled data to augment a PPI text classification system. Our mixed model is suitable for ranking purposes whereas our hierarchical model is better for filtering. In addition, our results indicate that supervised weighting schemes outperform unsupervised ones. Our newly-proposed weighting scheme, TFBRF, which considers documents that do not contain the target word, avoids some of the biases found in traditional weighting schemes. Our experiment results show TFBRF to be the most effective among several other top weighting schemes.</p

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

The Development of Contract Research Organizations in Taiwan：Case Study on Clinical Trials Management

昂貴的藥物研發成本，促使製藥生技產業的委外營運模式，以合約方式提供在藥物研發過程中專業化服務的產業，而近年來由於委外研發服務的高效率，已明顯縮短了新藥開發的時程；同時，在全球醫藥研發服務產業的市場中，約有超過七成的收益來自於臨床試驗服務；由此顯見醫藥研發服務產業中的臨床試驗部分的重要性。 醫藥研發服務是個高度國際性競爭的產業，如何找到發展的核心利基以突破重圍，是許多後進企業或國家所必需面對的嚴峻考驗。因此，本研究主要描述台灣目前的醫藥研發服務產業以及臨床試驗產業發展概況，並探討台灣是否具備發展臨床試驗產業的實力。透過本研究，希望對於台灣發展臨床試驗產業，或是推動台灣成為亞太臨床試驗中心，都能提供作為規劃與執行時的參考資訊。 本研究重要結論與建議如下： 1. 以新藥研發價值鏈而言，台灣目前在每一個階段的工作均已佈局，其中又以臨床試驗階段最有潛力加入國際的競爭市場；長期而言，為追求醫藥產業最大的經濟效益，應強化國內的基礎研發工作，進而刺激與培養國內醫藥研發服務產業的能量。 2. 產業政策的落實不能只談邏輯架構或觀念，應該設定明確的推動方案、目標與達成時間表，要推動產業必須貫徹以管理的觀念；同時也應加速業者與官方之間的溝通協調，其中包括藥政主管單位對於產業發展應由被動轉為積極主動的角色，另外，政府部門跨部會的整合也是相當重要的。 3. 國內的全民健保制度涵蓋了所有醫療資源的運用，而健保制度的設計缺乏鼓勵預防與醫藥研發的投入的機制。因此建議應深入分析與探討健保對於產業的影響，進而能以更積極正面的態度促進製藥生技或醫藥研發服務產業的發展。 4. 建議國內可以由政府與製藥產業界共同出資，成立具有公信力且目標明確的教育訓練組織，提供以實務為導向且有系統的在職教育，用以規劃與培植國家未來所需要的專業臨床試驗人才。 5. 建議國內應就醫療院所執行臨床試驗相關作業訂定管理原則，包括臨床試驗贊助款的管理與運用規範、相關執行人員的權利義務等，藉由透明化的標準與明確的獎勵制度，提高醫師與醫院參與臨床試驗的動機；同時也應鼓勵醫院設立專責的臨床試驗辦公室，執行各項協調、整合與管理的工作，並促進與產業界間的互動。The cost of drug research and development has soared during the past years. And this compels pharmaceutical and biotechnology companies to look for new, smarter ways of running their businesses. One of their strategies is trying to accelerate drug development by outsourcing. The size of the outsourcing market for Contract Research Organizations (CROs) is rising. Clinical-trial operations hold over 70% of the revenue in the CRO industry. Competition in the CRO industry is extremely international in scope. The key issues for the catching-up company or country is to find their own niche. This study goes on to identify and profile the development of clinical trials and the CRO industry in Taiwan. It also seeks to identify ways of showcasing Taiwan as an Asia-Pacific Clinical Trail Service Center. There are several conclusions from this study: 1. In the value chain of new drug discovery and development, the current status in Taiwan has the potential to join the international market by conducting the clinical trials. In the long term, we should consolidate our basic medical research to pursue the maximum benefit of biotechnology and pharmaceutical industry, and then to enhance the capability of CRO in Taiwan. 2. The policy for improving industry must be set up after the explicit acting plans, goals and time schedule. It should go through with management, not just a structure or concept. We have to hasten the communication between industry and government. The medical legal authorities need to be more active. Ultimate integration of the functions of the related government departments is exceedingly important. 3. The National Health Insurance (NHI) system covers all of the medical resources in Taiwan, but it lack for the incentive to encourage the medical research. It is recommended that NHI Program should probe into the impact of the biotechnology and pharmaceutical industry, and then try to revise it with more positive thinking. 4. It is very important for Taiwan to improve the professional in clinical trials. Setting up a training center funded by both government and industries is strongly recommended. The organization will have the definite goals and accountability, and provide practical training and systematic continuing education. 5. We need more regulating operations of clinical trials of hospitals in Taiwan. These operations should include the usage of the fees from sponsors, and the rights and responsibilities of all staff. We should set up a transparent standard and obviously encourage a mechanism to enhance the motivation of physicians and hospitals to participate in clinical trials. Hospitals should be encouraged to establish an independent office for clinical trials to perform all the details. This office will promote the interaction within the industries

[[alternative]]Correlational Study of Labor Support, Lotus of Control and Birth Satisfaction for Parturient Women

[[abstract]]本研究在探討產婦獲得的生產支持與其生產控制感、生產滿意度之間的相關性。採描述型相關性研究，資料收集採回溯性方式收案。於五家醫療院所的產後單位收案，第一胎的產後婦女符合下列條件者將予以收案：（1）沒有懷孕及生產合併症；及（2）以陰道生產方式生產且有足月正常新生兒。收案人數為184人。研究工具為結構式問卷表，項目包含：產婦個人基本屬性/產科學資料、疼痛視覺類比量表、布氏生產支持適應量表、生產控制量表中文版本及生產滿意度量表，皆於產後48小時內以問卷量表內容測量。資料以SPSS17.0 SOBEL軟體分析，統計結果在單變異分析方面，人口學之「孕期的自我照顧方法」產前教育與生產滿意度（p<.05）、產科學之「會陰部剃薙」與生產滿意度（p<.05）、生產支持與生產滿意度（p<.001）、生產控制感與生產滿意度（p<.001）之間達統計顯著相關，將其分別進入階層複回歸後發現，生產支持與生產控制感皆可降低「孕期的自我照顧方法」產前教育與「會陰部剃薙」對婦女生產滿意度的影響，因而再以生產支持及生產控制感分別進行SOBEL test，以探討其對「孕期的自我照顧方法」產前教育及「會陰部剃薙」與生產滿意度之間的中介效應，結果發現中介變項為生產支持時未達統計顯著相關；中介變項為生產控制感時達統計顯著相關（p<.05），中介效應分別為51.89%及45.62%，顯示生產控制感可以增加51.89%婦女在接受「孕期的自我照顧方法」產前教育及45.62%婦女在接受「會陰部剃薙」時的生產滿意度。期望藉由本研究結果提供醫護人員合宜的分娩照護之建議，在提供會陰部剃薙等醫療介入措施時，宜先考量婦女有無接受的必要性，經由事前詳盡的解說後由婦女自主選擇，並宜規劃設計對婦女有幫助的產前教育課程，促進婦女獲得生產控制感，以提升其生產滿意度及親子關係的建立。[[abstract]]This research investigated the degree of labor support perceived by new mothers and the correlation between a new mother’s lotus of control during labor and her overall satisfaction with the labor experience. The author employed a descriptive correlational approach and collected data using a retrospective method. Postpartum primapara women registered at the maternity wards of five hospitals were targeted by this research and were considered eligible for participation if 1) pregnancy and birth were free of comorbidities, and 2) delivery had been vaginal with the healthy newborn surviving to the first month. A total of 184 women met eligibility criteria and were recruited in this study. The questionnaires consisted of the Visual Analogue Scale for Pain (VASP), Bryanton Adaptation of the Nursing Supporting Labor Questionnaire (BANSILQ), Labour Agentry Scale (LAS), Mackey Childbirth Satisfaction Rating Scale, and selected demographic and obstetrical questions. Data were analyzed using SPSS 17.0 SOBEL software. In terms of one way analysis of variance (ANOVA), results showed significant correlations between “satisfaction with labor” and the following variables: “prenatal maternity self-care education” (p<.05), “perineal shaving” (p<.05), “labor support” (p<.001) and “lotus of control during labor” (p<.001). When identified correlations were then subjected to hierarchical multiple regression analysis, the two variables of “labor support” and “lotus of control during labor” were identified as able to diminish the influence of “prenatal maternity self-care education” and “perineal shaving” on “satisfaction with labor”. Next, a SOBEL test was conducted on each of these two variables to assess their mediating effect on the respective relationships of “prenatal maternity self-care education” and “perineal shaving” with “satisfaction with labor”. When “labor support” was introduced as the mediating variable, correlations failed to reach statistical significance. However, a significant correlation was found when “lotus of control” was introduced (p<.05), with mediating effects registering 51.89% and 45.62%, respectively. Such indicates that the variable “lotus of control” is able to increase labor satisfaction in expectant mothers by 51.89% and 45.62% when, respectively, receiving prenatal maternity self-care education and perineal shaving.It is hoped that the results of this research will provide valuable information for physicians and nurses responsible for delivering effective maternity care. In providing interventions such as perineal shaving, it is important to first determine whether the expectant mother accepts such and then, after discussing intervention particulars, allowing her to decide whether or not to proceed. Results also highlight the important role of effective prenatal education courses in helping enhance the lotus of control of expectant mothers, which can enhance labor satisfaction and lay the foundations for a healthy mother-child relationship

A CLOUD-BASED FRAMEWORK FOR ONLINE MANAGEMENT OF MASSIVE BIMS USING HADOOP AND WEBGL A CLOUD-BASED FRAMEWORK FOR ONLINE MANAGEMENT OF MASSIVE BIMS USING HADOOP AND WEBGL

ABSTRACT This paper presents a Cloud-based system framework for providing a web-based building information model (BIM) service. Cloud computing technologies were used to develop a BIM data center, which can handle the big data of massive BIMs using multiple servers in a distributed manner. In addition, the system allows multiple users to access the BIM data center online to submit and review BIMs concurrently. In this study, the advanced technologies/tools of web development and Cloud computing were applied and incorporated to develop a prototype system, named CloudBIM. On the client side, this study applied WebGL and HTML5 in the web-based interface development to achieve the 3D display of BIMs and the dynamic interaction with viewers through browsers. Users can access the services of CloudBIM by using PCs, laptops and tablets anytime anywhere to view the 3D model via browsers, which support WebGL. On the server side, this study used Apache Hadoop, an open-sourced distributed file system based on Google&apos;s technologies, to establish a BIM data center. The Hadoop Distributed File System (HDFS) can utilize multiple servers to provide mass storage spaces in a distributed manner. Based on the use of Apache HBase, which provides Bigtable-like structured storage for HDFS, this study proposes database schema for storing the information from massive BIMs in two bigtables, named Object table and Property table respectively. In addition, Hadoop MapReduce, a Hadoop component for the parallel processing of large data sets, is utilized for model data acquisition by parsing the IFC files of uploaded models in parallel