bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Pilot Study on Plasma Iipidomic Profile of Giant Pulmonary Bulla
Authors: Guo Zhifeng , Yan Furong , Xu Yuan , Zeng Yiming 
Published: August 2020

Abstract
Background: The symptom of chronic obstructive pulmonary disease (COPD) and giant pulmonary bulla (GPB) also called giant emphysematous bulla (GEB) is too similar to distinguish, and the treatment of the two diseases are completely different because of the different pathology. We investigated the plasma lipid profiles from patients of COPD and GPB to find targeted lipid changes responsible for differentiation between two diseases.Methods: Plasma was collected from 9 patients with COPD, and 10 patients with COPD and GPB. Extracted lipids were analyzed using high performance liquid chromatography-triple quadrupole mass spectrometry (HPLC-QqQ-MS) to characterize lipid profiles. Principal components analysis (PCA), orthogonal projection to latent structures-discriminant analysis (OPLS-DA) and variable importance in projection (VIP) scores were used to estimate the importance of each lipid variable.Results: The HPLC-QqQ-MS method identified 582 kinds of lipids at negative mode, and 577 kinds of lipids at positive mode. Lipid profiles were significantly different between COPD and GPB. Principal discriminant phospholipids between COPD and GPB were LPC(16:1)+AcO, LPC(16:0)+AcO, LPC(18:2)+AcO, LPC(18:1)+AcO, PC(16:0/22:5)+AcO, PC(18:2/18:2)+AcO, LPE(18:0)-H, LPE(16:0)-H, LPE(18:2)-H, PE(18:1/18:2)-H and FFA(24:0)(GPB group were significantly decreased compared to COPD group, VIP>1 and P<0.05).Conclusions: Our study provides insights into the alteration of the plasma lipid profile of GPB patients, commonly resulting from COPD, that may lead to improved GPB treatment and differentiation of this disease from COPD. Furthermore, LPC (16:0) +AcO was found to have a high potential to be a possible biomarker to distinguish the two diseases.
Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer
Authors: Han Yiqun , Wang Jiayu , Xu Binghe 
Published: August 2020

Abstract
Background: To develop and validate a prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NCT) of triple-negative breast cancer (TNBC).Methods: We systematically searched Gene Expression Omnibus, ArrayExpress, and PubMed for the gene expression profiles of operable TNBC accessible to NCT. The molecular heterogeneity was detected with hierarchical clustering method, and the biological profiles of differentially expressed genes were investigated by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analyses, and Gene Set Enrichment Analysis (GSEA). Next, the machine-learning algorithms including random-forest analysis and least absolute shrinkage and selection operator (LASSO) analysis were synchronously performed and, then, the intersected proportion of genes were undergone binary logistic regression to fulfill variables selection. The predictive response score (pRS) system was built as the product of the gene expression and coefficient obtained from logistic analysis. Last, the cohorts were randomly divided in a 7:3 ratio into training cohort and validation cohort for the introduction of robust model, and a nomogram was constructed with the independent predictors for pCR rate.Results: A total of 217 individuals from four cohort datasets (GSE32646, GSE25065, GSE25055, GSE21974) with complete clinicopathological information were included. Based on the microarray data, a six-gene panel (ATP4B, FBXO22, FCN2, RRP8, SMERK2, TET3) was identified. A robust nomogram, adopting pRS and clinical tumor size stage, was established and the performance was successively validated by calibration curves and receiver operating characteristic curves with the area under curve 0.704 and 0.756, respectively. Results of GSEA revealed that the biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response.Conclusions: This study provided a robust prediction model for pCR rate and revealed potential mechanisms of distinct response to NCT in TNBC, which were promising and warranted to further validate in the perspective.
ACE2 Protein-protein Interaction Networks Reveal Potential Druggable Targets for SARS-CoV-2
Authors: Xia Qiaoxi , Chen Mantong , Zhou Xiao , Lin Ling , Zhao Yan , Zheng Xiaoqi , Huang Meihui , Wang Shaohong , Du Zepeng 
Published: August 2020

Abstract
Background The novel coronavirus SARS-CoV-2 pandemic has infected more than 10 million people, killed over 500,000 so far. Currently, no effective drugs are available to treat this infectious disease, due to limited knowledge of the molecular mechanisms of SARS-CoV-2 infection. ACE2 (angiotensin I converting enzyme 2) has long been identified as the major receptor for coronavirus entry the host cells. Methods In this study, we constructed the protein-protein interaction networks (PPIN) based on ACE2 and its interacting proteins, combined with the expression change and co-expression relationship. The potential drugs targeting the proteins in the PPIN were explored.Results ACE2 and its interacting proteins AAMP and HRAS are obviously increased, and their PPIN show distinguishing expression patterns during the COVID-19 progression. At least six pathways are activated for the host cell in the response to the virus. Moreover, drug-target networks were built to provide important clues to block ACE2 and its interacting proteins. Except the reported four drugs for ACE2, its interacting protein CALM1 and HRAS are great potentially druggable. We also considered the path initiated from ACE2 to nucleus by cascades of interaction, especially for the transcription factors in the PPIN which are also druggable. Conclusion In summary, this study provides new insight into the disruption of the biological response to virus mediated by ACE2, but also its cascade interacting proteins when considering of PPIN.
Effects of Whole Body Vibration exercise on Lumbar-Abdominal Muscles Activation for patients with chronic low back pain
Authors: dong yulin , wang huifang , Zhu Yan , Chen Binlin , Zheng Yili , liu xiaochen , qiao jun , wang xueqiang 
Published: August 2020

Abstract
BackgroundWhole body vibration (WBV) training as an intervention method can cure chronic low back pain (CLBP). Different WBV parameters exert different effects on lumbar-abdominal muscle performance. Currently, there is a lack of study researched the influence of WBV training on patients with CLBP by lumbar–abdominal muscle activity. Therefore, this study aimed to investigate how WBV and exercise and their interactions influence lumbar-abdominal muscle activity in patients with CLBP.Methodsa group of ambulatory patients with chronic low back pain. Muscle activities of the multifidus, erector spinae, abdominal oblique externus muscle and the rectus abdominis muscle were measured by surface electromyography, whereas participants performed 4 different exercises during three whole body vibration conditions and a no-vibration condition in a single experimental session.ResultsCompared with the same exercises without whole body vibration, muscle activity increased when whole body vibration was added to the exercises. The frequency and exercise presented significant effects on the root mean square of multifidus, whereas exercise and frequency also resulted in significant interaction effects.ConclusionAdding whole body vibration to exercise could increase muscle activation of lumbar–abdominal muscle in patients with CLBP. The optimum frequency for lumbar–abdominal muscles is 15 Hz. The best exercises include plank for multifidus and erector spinae, V crunch for rectus abdominis and single bridge for abdominal oblique externus.Trial registration:ChiCTR-TRC-13003708. Registered 19 October 2013, http://www.chictr.org.cn/showproj.aspx?proj=5852
The salivary metatranscriptome as an accurate diagnostic indicator of oral cancer
Authors: Banavar Guruduth , Ogundijo Oyetunji , Toma Ryan , Rajagopal Sathyapriya , Lim Yenkai , Tang Kai Dun , Camacho Francine , Torres Pedro , Gline Stephanie , Parks Matthew , Kenny Liz , Dimitrova Nevenka , Perlina Ally , Tily Hal , Amar Salomon , Vuyisich Momchilo , Punyadeera Chamindie 
Published: August 2020

Abstract
Despite advances in cancer treatment, the five-year mortality rate for oral cancers (OC) is 40%, mainly due to the lack of early diagnostics. To advance early diagnostics for high-risk and average-risk populations, we developed and evaluated machine-learning (ML) classifiers using metatranscriptomic data from saliva samples (n=433) collected from oral premalignant disorders (OPMD), OC patients (n=71) and normal controls (n=171). Our diagnostic classifiers yielded a receiver operating characteristics (ROC) area under the curve (AUC) up to 0.9, sensitivity up to 83% (92.3% for stage 1 cancer) and specificity up to 97.9%. Our metatranscriptomic signature incorporates both taxonomic and functional microbiome features, and reveals a number of previously known and novel taxa and functional pathways associated with OC. For the first time, we demonstrate the potential clinical utility of an AI/ML model for diagnosing OC early, opening a new era of non-invasive diagnostics, enabling early intervention and improved patient outcomes.
The impact of procalcitonin to C-reactive protein ratio (PCR) kinetics as a predictor of mortality in nosocomial bloodstream infections
Authors: Hakyemez Ismail Necati , Aslan Turan , Durdu Bulent 
Published: August 2020

Abstract
Background: This study was performed to investigate the combination of serum C-reactive protein (CRP) and procalcitonin (PCT) kinetics as a best marker in predicting mortality in patients with nosocomial blood stream infection (BSI).Methods: We retrospectively reviewed the medical records of patients ≥ 18 years of age with nosocomial BSIs hospitalized in intensive care units during the period from January 2016 to June 2018. Eighty-four patients who met the inclusion criteria were included in the study. Clinical, microbiological and biochemical data were compared in patients who survivors and deaths. Binary logistic regression analyses (backward LR) were used to identify independent risk factors. A receiver operating characteristic (ROC) curve analysis was performed to compare the predictive accuracy. The kinetic changes were expressed as Δ (delta) and defined the as difference between level on day 5 and level at day 1 of BSI.Results: Of the 84 included patients, 46 (58.4%) had survivors and 35 (41.6%) had deaths. In univariate analysis, renal disease (p = 0.007), cardiac disease (p = 0.042), septic shock (p = <0.001), maximum SOFA (p = <0.001) and APACHE-II (p <0.001), ΔCRP (p = 0.004), ΔPCT (p = <0.001), and ΔPCR (p = 0.025) were significantly higher in non-survivors than in survivors. In the logistic regression analysis, APACHE-II score (odds ratio (OR) = 1.46, 95% confidence interval (CI) = 1.20-1.78, p <0.001), ΔCRP (OR = 1.18, %95 CI =1.04-1.34, p = 0.009), ΔPCT (OR = 0.87, 95% CI = 0.79-0.95, p = 0.001), and ∆PCR (OR = 36.78, 95% CI = 4.52-299.01, p = 0.001) were independent predictors of 28-day mortality. After a ROC analysis, the AUC of ∆PCR was higher than that of ∆PCT for mortality in ICU patients (0.745 vs. 0.712, p <0.001).Conclusions: The PCR kinetic was a strong independent predictor of mortality in patients with nosocomial BSIs in intensive care units. Especially in patients with CRP and PCT tested together, it is expected to be a fast and rational tool for clinical practice.
Geological Environmental and Socioeconomic Factors of Disease Spectrum in Chinese Population
Authors: GONG Jin 
Published: August 2020

Abstract
Through the correlation analysis of statistical data of provinces and autonomous regions, this paper has comprehensively, systematically and quantitativelystudied the natural geography, geological environment, socioeconomic, geochemical and hydrogeological constraints of endemic diseases, cancer and common diseases in mainland China. In order to prevent the rational design of medical experimental plan, provide a scientific basis. The results show that, the occurrence of different human diseases is subject to different environmental conditions. Keshan disease, Kashin-Beck disease, endemic goiter and fluorosis, in addition to soil selenium, groundwater iodine and fluoride, but also by a variety of environmental factors; Total nitrogen in soil has an promote effect to gastric cancer and liver cancer. The amount of nitrogen fertilizer has an effect to rectal cancer, pancreatic cancer and lymphatic cancer, and soil arsenic has significant inhibitory effect to lung cancer, pancreatic cancer and lymphatic cancer. River water hardness, salinity and soil calcium, magnesium and other elements for a variety of cancers may also have inhibitory effect. Cerebrovascular disease and myocardial infarction have shown the features of urban population in cold and droughts in the north; Chronic obstructive pulmonary disease and respiratory tract infections show the features of the population in the mountain mining and smelting industries; Chronic nephropathy reflects the characteristics of arsenic and sulfur poisoning in plateau areas; Alzheimer disease shows the characteristics of people in farming areas. The average content of elements in sediments of water system, the county territory of 26 longevity counties in China are relatively high compared with the national average, and the human beneficial elements are relatively high; while the harmful elements in human bodies are relatively low. If we make full use of soil (stream sediment) geochemical measurement data, combined with the results of this study, it is possible to greatly refine the spatial distribution prediction maps of population diseases in mainland China. The author believes that by improving the climatic and geographical conditions of residence and increasing the intake of certain chemical elements in an appropriate form(Especially the food chain diet structure), it will certainly play an important role in reducing the occurrence and development of diseases and improving human health.
Evaluation of immune cellular enzymes, oxidative and nitrosative Stress in Saudi Patients with Cutaneous Leishmaniasis in Al-AHssa, before and after treatment
Authors: Saif Mossad Ahmad , Al-Mohammad Hamdan Ibrahim 
Published: August 2020

Abstract
Background Macrophages, within which Leishmania sp. replicate, generate large amounts of reactive oxygen species (ROS) and reactive nitrogen species (RNS) to kill these parasites. Methods The aim of the present study was to assess oxidative, nitrosative stresses, and some immune enzymes in blood of cutaneous leishmaniasis (CL) patients before and after treatment as well as in control individuals. Serum activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidas (GSH-Px) and the levels of reduced glutathione, malondialdehyde (MAD) and nitric oxide (NO) as well as L-arginase, myeloperoxidase (MPO), adenosine deaminase (ADA) have been studied. Results The activities of the L-arginase, MPO and ADA, the levels of MDA and NO are significantly elevated (P < 0.001), while that of SOD, CAT, and GSH-Px, and GSH level were significantly (P < 0.001) reduced in untreated patients compared with the corresponding activities of the treated and control individuals. The treatment ameliorated these agents in comparison to the untreated group but there was still variations between the values of treated and control groups. Conclusion These results suggested that oxidative and nitrusative stress may play an important role in the pathogenesis of untreated cutaneous leishmaniasis
Effects of grade B liver dysfunction on the level of free hexafluoroisopropanol of sevoflurane metabolites in patients with abdominal surgery
Authors: Yang Xiao-lin , Li Ming , Feng Yan , Zhang Guo-Yuan 
Published: August 2020

Abstract
Background: Study shows the metabolite, hexafluoroisopropanol (HFIP) from sevoflurane, has a strong inhibition on the central nervous system. This study aims to compare the level of free HFIP in the blood after inhaled a same concentration of sevoflurane in patients with normal liver function versus grade B liver dysfunction and observe its effect on patients’ recovery quality.Methods: Twenty four patients with normal liver function and twenty four patients with grade B liver dysfunction undergoing elective abdominal surgery were selected and assigned to group A and group B, respectively. All patients were inhaled sevoflurane (1.5MAC) for anesthesia about 3 h. The free HFIP concentration was determined at the time points of 0.5 h, 1 h, 2 h, 3 h after inhaled sevoflurane and 0.5 h, 1 h, 2 h, 4 h after discontinuation of sevoflurane, respectively. Patients’ eyes opening time, orientation recovery time, command response time and extubation time were observed after operation. The visual analogue scale (VAS) and Ramsay sedation score (RSS) were also evaluated at different time points after extubation. Results: Although the peak time of free HFIP in group B was 1 h later than that in group A, no significant differences were found in the peak concentration and other corresponding time points’ free HFIP concentrations between the two groups (P<0.05). All the eyes opening time, orientation recovery time, command response time and extubation time in group B were longer than those in group A (P<0.05). Compared to group A, a lower VAS score and a higher RSS score were found in group B at 0 min, 15 min, 30 min,1 h, 2 h and 3 h after extubation, respectively (P<0.05). Conclusion: The status of patients with grade B liver dysfunction does not affect the degree of sevoflurane metabolism. However, it can significantly prolong the peak time of free HFIP when compared with normal liver function.Trial registry number: Identified as ChiCTR 2000028901at http://www.chictr.org.cn/
Identification of key genes related to macrophage infiltration in gastric cancer based on WGCNA
Authors: Chen Haiyan , Zhang Cangang , Cao Shuai , Cao Meng , Zhang Nana , Adiila Ayarick Vivian , Zhong Jinjin , Liu Haibo , Wang Yili 
Published: August 2020

Abstract
Background: Gastric cancer (GC) is rampant around the world. Most of the GC cases are detected in advanced stages with poor prognosis. The identification of marker genes for early diagnosis is of great significance. Studying the tumor environment is helpful to acknowledge the process of tumorigenesis, development, and metastasis.Methods: In GEO, 22 kinds of immune cell infiltration were calculated by CIBERSORT. Macrophages were discovered remarkably infiltrated higher in GC compared with normal tissues. WGCNA was utilized to construct the network and then identify key modules and genes related to macrophages in TCGA.Results: Finally, 18 hub genes were verified. In the PPI bar chart, the top 3 genes were chosen as hub genes involved in most pathways. On the TIMER and THPA websites, it is verified that the expression levels of CYBB, CD86 and C3AR1 genes in tumor tissues were higher than those in normal tissues.Conclusion: These genes may work as biomarkers or targets for accurate diagnosis and treatment of GC in the future. Our findings may be a new strategy for the treatment of GC.
Intraventricular neuroepithelial tumors: Surgical outcome, technical considerations and review of literature
Authors: Aftahy Amir Kaywan , Barz Melanie , Krauss Philipp , Liesche Friederike , Wiestler Benedikt , Combs Stephanie E. , Straube Christoph , Meyer Bernhard , Gempt Jens 
Published: August 2020

Abstract
Background
Intraventricular neuroepithelial tumors (IVT) are rare lesions and comprise different pathological entities such as ependymomas, subependymomas and central neurocytomas. The treatment of choice is neurosurgical resection, which can be challenging due to their intraventricular location. Different surgical approaches to the ventricles are described. Here we describe a large series of IVTs, its postoperative outcome at a single tertiary center and discuss suitable surgical approaches.
Methods
We performed a retrospective chart review at a single tertiary neurosurgical center between 03/2009-05/2019. We included patients that underwent resection of an IVT emphasizing on surgical approach, extent of resection, clinical outcome and postoperative complications.
Results
45 IVTs were resected from 03/2009 to 05/2019, 13 ependymomas, 21 subependymomas, 10 central neurocytomas and one glioependymal cyst. Median age was 52,5 years with 55.6% (22) male and 44.4% (20) female patients. Gross total resection was achieved in 93.3% (42/45). 84.6% (11/13) of ependymomas, 100% (12/21) of subependymomas, 90% (9/10) of central neurocytomas and one glioependymal cyst were completely removed. Postoperative rate of new neurological deficits was 26.6% (12/45). Postoperative new permanent cranial nerve deficits occurred in one case with 4th ventricle subependymoma and one in 4th ventricle ependymoma. Postoperative KPSS was 90% (IR 80–100). 31.1% of the patients improved in KPSS, 48.9% remained unchanged and 20% declined. Postoperative adverse events rate was 20.0%. Surgery-related mortality was 2.2%. The rate of shunt/cisternostomy-dependent hydrocephalus was 13.3% (6/45). 15.4% of resected ependymomas underwent adjuvant radiotherapy. Mean follow-up was 26,9 (± 30.1) months.
Conclusion
Our surgical findings emphasize satisfactory complete resection throughout all entities. Surgical treatment can remain feasible, if institutional experience is given. Satisfying long-term survival and cure is possible by complete removal. Gross total resection should always be performed under function-remaining aspects due to mostly benign or slow growing nature of IVTs. Further data is needed to evaluate standard of care and alternative therapy options in rare cases of tumor recurrence or in case of patient collective not suitable for operative resection.
Machine Learning in Otolaryngology-Head and Neck surgery: A Systematic Review Protocol
Authors: Lee Chang Woo , Mantelakis Angelos , Tailor Bhavesh Vijay , Khajuria Ankur 
Published: August 2020

Abstract
Background: Machine learning describes a subfield of artificial intelligence which utilises statistical algorithms to identify patterns in large datasets. Based on previous learning, inferences or predictions can be made given novel data. Alongside its promising potential to revolutionise consumer technology, there has been growing interest in the application of machine learning algorithms to medical practice. The aim of this study is to evaluate the applications of machine learning in Otolaryngology-Head and Neck surgery.Methods: A systematic search of EMBASE, MEDLINE and CENTRAL will be conducted from January 1990 to June 2020. Studies utilising machine learning as a tool for diagnosis, or to predict disease prognosis or post-operative outcomes in the field of Otolaryngology-Head and Neck surgery will be included. The primary outcome of interest is the accuracy of machine learning models for clinical diagnosis, disease prognostication, and in predicting post-operative outcomes. This protocol adheres to the Preferred Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines.Discussion: To our knowledge, this will be the first systematic review to assimilate and critically appraise original research on the applications of machine learning across the field of Otolaryngology-Head and Neck surgery. This review has the potential to inform the current state of this technology and guide future study of machine learning approaches within the specialty.Systematic review registration: PROSPERO CRD42020192493