bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pre-hospital Transdermal Glyceryl Trinitrate in Patients With Stroke Mimics: Data From the Right-2 Randomised-controlled Ambulance Trial
Authors: Tunnage Bronwyn , Woodhouse Lisa J , Dixon Mark , Anderson Craig S , Ankolekar Sandeep , Appleton Jason P , Cala Lesley , England Timothy J , Krishnan Kailash , Havard Diane , Mair Grant , Muir Keith , Phillips Steve J , Potter John , Price Christopher I , Randall Marc , Robinson Thompson G , Roffe Christine , Sandset Else C , Siriwardena Niro , Scutt Polly , Wardlaw Joanna M , Sprigg Nikola , Bath Philip M 
Published: January 2021

Abstract
Background: Prehospital stroke trials will inevitably recruit patients with non-stroke conditions, so called stroke mimics. We undertook a pre-specified analysis to determine outcomes in patients with mimics in the second Rapid Intervention with Glyceryl trinitrate in Hypertensive stroke Trial (RIGHT-2). Methods: RIGHT-2 was a prospective, multicentre, paramedic-delivered, ambulance-based, sham-controlled, participant-and outcome-blinded, randomised-controlled trial of transdermal glyceryl trinitrate (GTN) in adults with ultra-acute presumed stroke in the UK. Final diagnosis (intracerebral haemorrhage, ischaemic stroke, transient ischaemic attack, mimic) was determined by the hospital investigator. This pre-specified subgroup analysis assessed the safety and efficacy of transdermal GTN (5 mg daily for 4 days) versus sham patch among stroke mimic patients. The primary outcome was the 7-level modified Rankin Scale (mRS) at 90 days. Results Among 1149 participants in RIGHT-2, 297 (26%) had a final diagnosis of mimic (GTN 134, sham 163). The mimic group were younger, mean age 67 (SD: 18) vs 75 (SD: 13) years, had a longer interval from symptom onset to randomisation, median 75 [95% CI: 47,126] vs 70 [95% CI:45,108] minutes, less atrial fibrillation and a lower systolic blood pressure and Face-Arm-Speech-Time tool score than the stroke group. The three most common mimic diagnoses were seizure (17%), migraine or primary headache disorder (17%) and functional disorders (14%). At 90 days, the GTN group had a better mRS score as compared to the sham group (adjusted common odds ratio 0.54; 95% confidence intervals 0.34, 0.85; p = 0.008), a difference that persisted at 365 days. There was no difference in the proportion of patients who died in hospital, were discharged to a residential care facility, or suffered a serious adverse event. Conclusions One-quarter of patients suspected by paramedics to have an ultra-acute stroke were subsequently diagnosed with a non-stroke condition. GTN was associated with unexplained improved functional outcome observed at 90 days and one year, a finding that may represent an undetected baseline imbalance, chance, or real efficacy. GTN was not associated with harm. Trial registration: This trial is registered with International Standard Randomised Controlled Trials Number ISRCTN 26986053. Funding: The RIGHT-2 trial was supported by the British Heart Foundation
Morbidity After Elective Surgery in Patients on Chronic Dialysis: a Systematic Review and Meta-analysis
Authors: Palamuthusingam Dharmenaan , Nadarajah Arun , Johnson David , Pascoe Elaine , Hawley Carmel , Fahim Magid 
Published: January 2021

Abstract
Background: Patients on chronic dialysis are at increased risk of postoperative mortality following elective surgery compared to patients with normal kidney function, but morbidity outcomes are less often reported. This study ascertains the excess odds of postoperative cardiovascular and infection related morbidity outcomes for patients on chronic dialysis. Methods: Systematic searches were performed using MEDLINE, Embase and the Cochrane Library to identify relevant studies published from inception to January 2020. Eligible studies reported postoperative morbidity outcomes in chronic dialysis and non-dialysis patients undergoing major non-transplant surgery. Risk of bias was assessed using the Newcastle-Ottawa Scale and the certainty of evidence was summarised using GRADE. Random effects meta-analyses were performed to derive summary odds estimates. Meta-regression and sensitivity analyses were performed to explore heterogeneity. Results: Forty-nine studies involving 10 513 934 patients with normal kidney function and 43 092 patients receiving chronic dialysis were included. Patients on chronic dialysis had increased unadjusted odds of postoperative cardiovascular and infectious complications within each surgical discipline. However, the excess odds of cardiovascular complications was attenuated when odds ratios were adjusted for age and comorbidities; myocardial infarction (general surgery, OR 1.83 95% 1.29 – 2.36) and stroke (general surgery, OR 0.95, 95%CI 0.84-1.06). The excess odds of infectious complications remained substantially higher for patients on chronic dialysis, particularly sepsis (general surgery, OR 2.42, 95%CI 2.12-2.72). Conclusion: Patients on chronic dialysis are at increased odds of both cardiovascular and infectious complications following elective surgery, with the excess odds of cardiovascular complications attributable to being on dialysis being highest among younger patients without comorbidities. However, further research is needed to better inform perioperative risk assessment.
Sputum Colour as a Marker for Bacteria in Acute Exacerbations of COPD: Protocol for a Systematic Review and Meta-Analysis.
Authors: Spies Ruan , Potter Matthew Wade , Hollamby Ruan , Walt Stefan van der , Hohlfeld Ameer , Ochodo Eleanor , Zyl-Smit Richard Nellis van 
Published: January 2021

Abstract
BackgroundChronic obstructive pulmonary disease (COPD) is a major cause of years of life lost globally. Acute exacerbations of COPD (AECOPD) drive disease progression, reduce quality of life and are a source of mortality in COPD. Approximately 50% of AECOPD are due to bacterial infections. Diagnosing bacterial infection as the aetiology of AECOPD however remains challenging as investigations are limited by practicality, accuracy and expense. Clinicians have traditionally used sputum colour as a marker of bacterial infection in AECOPD, despite the lack of high-quality evidence for this practice. The aim of this systematic review and meta-analysis is to determine the diagnostic accuracy of sputum colour in the diagnosis of bacterial causes of AECOPD. MethodsArticles will be searched for in electronic databases (PubMed, Scopus, Web of Science, Africa-Wide, CINAHL and Health Source Nursing Academy) and we will conduct a review of citation indexes and the grey literature. Two reviewers will independently conduct study selection, against pre-defined eligibility criteria, data extraction and quality assessment of included articles using the QUADAS-2 tool. We will perform a meta‐analysis using a bivariate logistic regression model with random effects. We will explore heterogeneity through the visual examination of the forest plots of sensitivities and specificities and through the inclusion of possible sources of heterogeneity as covariates in a meta-regression model if sufficient studies are included in the analysis. We also perform a sensitivity analysis to explore the effect of study quality on our findings. The results of this review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis statement and will be submitted for peer-review and publication.DiscussionThe findings of this review will assist clinicians in diagnosing the aetiology of AECOPD and may have important implications for decision making in resource-limited settings, as well as for antimicrobial stewardship.Systematic review registration: PROSPERO CRD42019141498
WITHDRAWN: Analysis of Fracture Distribution in the Surgical Neck Region of the Proximal Humerus: a 3D Bone Cortical Thickness Mapping Study
Authors: Guo Jialiang , Dong Weichong , Zhou Yali , Jin Lin , Tian Siyu , Wang Zhongzheng , Hou Zhiyong , Zhang Yingze 
Published: January 2021

Abstract
Objection: Among the many studies on the proximal humerus, few have focused on cortical bone distribution around the surgical neck region and its relationship with the epiphysis. Materials and methods: Ninety-five surgical neck fracture patients with available plain X-rays and CT scans were enrolled. In addition, 38 normal subjects were also included to illustrate the cortical thickness of the diaphysis, cortical change region and greater tuberosity.Results: The fracture lines were mainly distributed in the cortical change region. Significant differences were found in cortical thickness between the diaphysis, surgical region and greater tuberosity in men and women. The thickest cortex was noted in the diaphysis, and the thinnest cortex was noted in the greater tuberosity. No significant differences were observed in the width of the cortical change region in man and women.Conclusion: The surgical neck region had decreased cortical thickness. It was concluded that the epiphysis connection region had an effect and acted on the proximal humeral fracture pattern in adults; therefore, the surgical neck fracture was identified as an epiphyseal relative fracture.
TNF-α suppresses drug resistance via NF-κB/PXR pathway in non-small cell lung cancer
Authors: Huang Weiqing , Wang Ping , Qi Shiyu , Zhang Yuanyuan , Han Wei , Kong Qingnuan 
Published: January 2021

Abstract
Background

Reduced sensitivity to chemotherapeutic agents caused by multidrug resistance is the main obstacle in the treatment of non-small cell lung cancer (NSCLC). Activated NF-κB/PXR pathway stimulated by procytokine TNF-α is implicated in the formation of multidrug resistance phenotype. However, the underlying mechanisms are obscure, and results concluded in various tumors are conflicted. Herein, we explored the effects of TNF-α on NF-κB/PXR pathway activation and multidrug resistance development in NSCLC.
Methods

Cancerous tissues were used to evaluate the expression of TNF-α on inflammatory stroma cells and tumor cells separately and analyze their correlations with the NF-κB/PXR pathway as well as clinical chemoresistance. Alterations of the NF-κB/PXR pathway and multidrug resistance gene ABCB1 transcripts in response to TNF-α application were observed on the A549 cell line.
Results

Our results demonstrated that TNF-α produced by inflammatory stromal cells was associated with clinical chemoresistance and negatively correlated to PXR expression. Moreover, TNF-α induced activated NF-κB and repressed PXR at mRNA and protein expression levels in A549 cancer cells. Furthermore, ABCB1 transcripts changes were consistent with PXR expression.
Conclusions

Our findings suggested potentially inhibitory effects of TNF-α produced by inflammatory stroma cells on multidrug resistance in solid NSCLC through mediating NF-κB/PXR pathway activation. These results further the understanding of the roles of inflammatory cells infiltrating tumors and suggest more subtle regulation mechanisms of TNF-α that should be further explored to discover distinct targeted molecules overcoming drug resistance.
Learning Sequential Patterns Using Spatio-Temporal Attention Networks for Video Classification
Authors: Deshmukh Shubhada , Patwardhan Manasi , Mahajan Anjali , Deshpande Sadanand 
Published: January 2021

Abstract
Extensive research effort has been focused on extracting temporal patterns from videos, to improve the accuracy of video classification using a deep neural network based approaches. In this paper, we show that long term dependency patterns may not be enough to achieve sufficient improved results. We propose the Attention-based Spatio-Temporal model (AST) for video classification, which is a self-attention model that learns to attend to spatial features using Convolutional Neural Network (CNN) and temporal features using attention mechanisms. We evaluate our model on motion dependent Action recognition (UCF-101) dataset, facial expression recognition (MMI) dataset, and micro-expression recognition (CASME2) dataset and generated real-life Facial Expression Recognition (FER) dataset and improved by 10%, 4.7% and 5.6% accuracy respectively as compared to state-of-art on the three standard datasets and a synthetic dataset as well.In our research, we performed several experiments for detecting expressions and actions, the AST model plays a vital role in selecting the frames and carry the sequential context in the real-time application as well. We also experimented by extracting the features using the Active shape model (ASM) for FER and found the AST model surpasses other approaches.
SY-707, an ALK/FAK/IGF1R Inhibitor, Suppresses Growth and Metastasis of Breast Cancer Cells
Authors: Liu Ping , Sun Yinghui , Liu Shuang , Niu Jing , Liu Xijie , Li Binghui , Chu Qiaoyun 
Published: January 2021

Abstract
Background Focal adhesion kinase (FAK), a multi-functional cytoplasmic tyrosine kinase, plays a critical role in cancer migration, proliferation and metastasis via regulating multiple signaling pathways. SY-707 is an ALK/FAK/IGF1R multi-kinase inhibitor and now evaluated in Phase II clinical trial for ALK positive non-small cell lung cancer (NSCLC).MethodsHTRF (Homogeneous Time-Resolved Fluorescence) assay was used to analyze kinase enzyme activity to determine inhibitory activities of SY-707 on other kinases. ATP content, PE-Annexin V and would healing assays were used to examine cell proliferation, cell cycle and migration when cells were treated with SY707. Then, SD rat and beagle dog models were used to evaluate the pharmacokinetics profile, and mouse xenograft model was used to evaluate the in vivo anti-cancer activities of SY707. ResultsIn this study, we assessed preclinical anti-growth and anti-metastasis potency of SY-707 in breast cancer cells. SY-707 was able to inhibit the growth of breast cancer cell lines and induced cell apoptosis by suppressing the FAK signaling pathways. Moreover, SY-707 exerted inhibition on cell migration and adhesion in a dose-dependent manner. In T47D xenograft mice, SY-707 had significant anti-tumor activities lonely or synergistically with Paclitaxel. Meanwhile, SY-707 also displayed significant suppression on spontaneous metastasis of tumor to the lung in 4T1 murine breast cancer xenograft model. ConclusionsSY-707 illustrated potent anti-proliferation and anti-migration potential in breast cancer in vitro and in vivo, implying its therapeutic application for the treatment of breast cancer in future clinical trials.
Robo2 Predicts a Better Prognosis and Inhibits Malignant Behavior in Vivo in Pancreatic Ductal Adenocarcinoma
Authors: Ding Cheng , Li Yatong , Wang Shunda , Xing Cheng , Chen Lixin , Zhang Hanyu , Wang Yizhi , Dai MengHua 
Published: January 2021

Abstract
BackgroundPancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with an extremely poor prognosis and a high mortality rate. Genome-wide studies have shown that the SLIT/ROBO signaling pathway plays an important role in pancreatic tumor development and progression. However, the effect and mechanism of ROBO2 in the progression of pancreatic cancer remains largely unknown.MethodsIn this study, real-time polymerase chain reaction (RT-PCR) and western blot analyses were adopted to evaluate the expression level of ROBO2 and proteins in pancreatic cell lines. Cell migration and invasion and cell proliferation were conducted in AsPC-1 and MIA PaCa-2 cell lines. RNA sequencing and western blot were undertaken to explore the mechanisms and potential targeted molecules. ROBO2 expression in tumor tissues was evaluated by immunohistochemistry in 95 patients.ResultsROBO2 expression was downregulated in PDAC cell lines and tissue samples. A high level of ROBO2 was associated with good overall survival. Upregulation of ROBO2 inhibited PDAC cell proliferation, migration, and invasion, whereas the opposite results were found in the ROBO2 downregulation group. In addition, xenograft animal models further confirmed the effect of ROBO2 on proliferation. Finally, the RNA sequencing results indicated that ROBO2 facilitates anti-tumorigenicity partly via inhibiting ECM1 in PDAC. ConclusionsOur work suggests that ROBO2 inhibits tumor progression in PDAC and may serve as a predictive biomarker and therapeutic target in PDAC.
Dissemination of Circulating Tumor Cell Clusters Occurs Early in Non‑metastatic Breast Cancer Patients
Authors: Reduzzi Carolina , Cosimo Serena Di , Gerratana Lorenzo , Motta Rosita , Martinetti Antonia , Vingiani Andrea , D'Amico Paolo , Zhang Youbin , Vismara Marta , Depretto Catherine , Scaperrotta Gianfranco , Folli Secondo , Pruneri Giancarlo , Cristofanilli Massimo , Daidone Maria Grazia , Cappelletti Vera 
Published: January 2021

Abstract
Background: Metastatic spreading is promoted by cancer cell seeding from the primary tumor into the bloodstream. In patients with metastatic breast cancer (MBC), the clinical relevance of circulating tumor cell clusters (CTC-clusters) has been extensively reported, while their study in earlier stages is limited. Several methods, besides the FDA-cleared CellSearch®, limited to the detection of epithelial-enriched clusters, can be used for the detection of CTC-clusters. We hypothesize that resorting to marker-independent approaches can improve CTC-cluster detection. Methods: Blood samples collected from healthy donors and spiked-in with tumor mammospheres, or from BC patients, were processed for CTC-cluster detection with 3 technologies: CellSearch®, CellSieve™ filters, ScreenCell® filters. The number of CTC-clusters was compared among the technologies and analyzed in relation to patient characteristics and outcome. Results: In spiked-in samples, the 3 technologies showed similar capability of recover epithelial mammospheres, whereas, in a series of 19 clinical samples processed in parallel with the CellSearch® and CellSieve™ filters (that allow the detection of both epithelial and non-epithelial clusters), CTC-clusters were detected in 53% of samples with the CellSearch®, versus 79% and 84% with the CellSieve™, when considering only epithelial or both epithelial and non-epithelial clusters, respectively. Next, blood samples from 37 non-metastatic breast cancer (NMBC) and 23 MBC patients were processed using ScreenCell® filters for attaining both unbiased enrichment and marker-independent identification of clusters based on cytomorphological criteria. At baseline, CTC-clusters were detected in 70% of NMBC cases and in 20% of MBC patients (median number= 2, range 0–20, versus 0, range 0‑15, P =0.0015). Among NMBC patients, clusters were slightly higher in women with node-positive than node‑negative status (0 versus 3, P =0.1110 ) and were more frequently observed in women with luminal‑like and triple-negative tumors than in patients with HER2-positive disease (median CTC-cluster number =4, 5, and 0 for luminal‑like, triple-negative, and HER2-positive BC, respectively, P =0.0467). Conclusions: We demonstrated that CTC-cluster detection can be improved by a marker-independent enrichment and identification, and we reported that CTC-clusters are more frequently detected in NMBC than in MBC patients, suggesting that dissemination of CTC-clusters is an early event in BC natural history.
Weld Defect Detection and Image Defect Recognition Using Deep Learning Technology
Authors: Cheng Yu , Deng HongGui , Feng YuXin , Xiang JunJiang 
Published: January 2021

Abstract
Welding defects not only bring several economic losses to enterprises and individuals but also threatens peoples lives. We propose a deep learning model, where the data-trained deep learning algorithm is employed to detect the weld defects, and the Convolutional Neural Networks (CNNs) are utilized to recognize the image features. The Transfer Learning (TL) is adopted to reduce the training time via simple adjustments and hyperparameter regulations. The designed deep learning-based model is compared with other classic models to prove its effectiveness in weld defect detection and image recognition further. The results show this model can accurately identify weld defects and eliminates the complexity of manually extracting features, reaching a recognition accuracy of 92.54%. Hence, the reliability and automation of detection and recognition is improved signifificantly. Actual application also verififies the effectiveness of TL in weld defect detection and image defect recognition. Therefore, our research results can provide theoretical and practical references for effificient automatic detection of steel plates, cost reduction, and the high-quality development of iron and steel enterprises.Index Terms - convolutional neural network, deep learning, image detect recognition, transfer learning, weld defect detection
Improving Early Diagnosis of Rare Diseases Using Natural Language Processing in Unstructured Medical Records: An Illustration From Dravet Syndrome&nbsp;
Authors: Barco Tommaso Lo , Kuchenbuch Mathieu , Garcelon Nicolas , Neuraz Antoine , Nabbout Rima 
Published: January 2021

Abstract
BackgroundThe growing use of Electronic Health Records (EHRs) is promoting the application of data mining in health-care. A promising use of big data in this field is to develop models to support early diagnosis and to establish natural history. Dravet Syndrome (DS) is a rare Developmental and Epileptic Encephalopathy that commonly initiates in the first year of life with febrile seizures (FS). Age at diagnosis is often delayed after two years, as it is difficult to differentiate DS at onset from FS.We aimed to explore if some clinical terms (concepts) are significantly more used in the electronic narrative medical reports of individuals with DS before the age of two years compared to those of individuals with FS. These concepts would allow an earlier detection of patients with DS resulting in an earlier orientation toward expert centers that can provide early diagnosis and care.MethodsData were collected from the Necker Enfants Malades Hospital using a document-based data warehouse, Dr Warehouse, which employs Natural Language Processing, a computer technology consisting in processing written information. Using Unified Medical Language System Meta-thesaurus, phenotype concepts can be recognized in medical reports. We selected individuals with DS (DS Cohort) and individuals with FS (FS Cohort) with confirmed diagnosis after the age of four years. A phenome-wide analysis was performed evaluating the statistical associations between the phenotypes of DS and FS, based on concepts found in the reports produced before two years and using a series of logistic regressions. ResultsWe found significative higher representation of concepts related to seizures’ phenotype distinguishing DS from FS in the first phases, namely the major recurrence of complex febrile convulsions (long-lasting and/or with focal signs) and other seizure-types. Some typical early onset non-seizure concepts also emerged, in relation to neurodevelopment and gait disorders. ConclusionsNarrative medical reports of individuals younger than two years with FS contain specific concepts linked to DS diagnosis, which can be automatically detected by software exploiting NLP. This approach could represent an innovative and sustainable methodology to decrease time of diagnosis of DS and could be transposed to other rare diseases.