bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrating Transcriptome-Wide Association Study and mRNA Expression Profiling Identifies Novel Genes Associated With Osteonecrosis of the Femoral Head
Authors: Ma Mei , Li Peilin , Liu Li , Cheng Shiqiang , Cheng Bolun , Liang Chu Jun , Tan Sijia , Li Wenyu , Wen Yan , Guo Xiong , Wu Cuiyan 
Published: June 2021

ObjectiveThis study aims to identify novel candidate genes associated with osteonecrosis of the femoral head (ONFH).MethodsA transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study dataset of osteonecrosis (ON) in the UK Biobank with pre-computed mRNA expression reference weights of muscle skeleton (MS) and blood. The ON-associated genes identified by TWAS were further subjected to gene ontology (GO) analysis by the DAVID tool. Finally, a trans-omics comparative analysis of TWAS and genome-wide mRNA expression profiling was conducted to identify the common genes and the GO terms shared by both DNA-level TWAS and mRNA-level expression profile for ONFH.ResultsTWAS totally identified 564 genes that were with PTWAS value &lt;0.05 for MS and blood, such as CBX1 (PTWAS = 0.0001 for MS), SRPK2 (PTWAS = 0.0002 for blood), and MYO5A (PTWAS = 0.0005 for blood). After comparing the genes detected by TWAS with the differentially expressed genes identified by mRNA expression profiling, we detected 59 overlapped genes, such as STEAP4 [PTWAS = 0.0270, FC (fold change)mRNA = 7.03], RABEP1 (PTWAS = 0.010, FCmRNA = 2.22), and MORC3 (PTWAS = 0.0053, FCmRNA = 2.92). The GO analysis of TWAS-identified genes discovered 53 GO terms for ON. Further comparing the GO results of TWAS and mRNA expression profiling identified four overlapped GO terms, including cysteine-type endopeptidase activity (PTWAS = 0.0006, PmRNA = 0.0227), extracellular space (PTWAS = 0.0342, PmRNA = 0.0012), protein binding (PTWAS = 0.0112, PmRNA = 0.0106), and ATP binding (PTWAS = 0.0464, PmRNA = 0.0033).ConclusionSeveral ONFH-associated genes and GO terms were identified by integrating TWAS and mRNA expression profiling. It provides novel clues to reveal the pathogenesis of ONFH.
The Ependymal Region Prevents Glioblastoma From Penetrating Into the Ventricle via a Nonmechanical Force
Authors: Li Kaishu , Song Haimin , Wang Chaohu , Lin Zhiying , Yi Guozhong , Yang Runwei , Ni Bowen , Wang Ziyu , Zhu Taichen , Zhang Wanghao , Wang Xiran , Liu Zhifeng , Huang Guanglong , Liu Yawei 
Published: June 2021

BackgroundIntraventricular penetration is rare in glioblastoma (GBM). Whether the ependymal region including the ependyma and subventricular zone (SVZ) can prevent GBM invasion remains unclear.MethodsMagnetic resonance imaging (MRI) and haematoxylin–eosin (HE) staining were performed to evaluate the size and anatomical locations of GBM. Binary logistic regression analysis was used to assess the correlation between tumor-ependyma contact, ventricle penetration and clinical characteristics. Cell migration and invasion were assessed via Transwell assays and an orthotopic transplantation model.ResultsAmong 357 patients with GBM, the majority (66%) showed ependymal region contact, and 34 patients (10%) showed ventricle penetration of GBM. GBM cells were spread along the ependyma in the orthotopic transplantation model. The longest tumor diameter was an independent risk factor for GBM-ependymal region contact, as demonstrated by univariate (OR = 1.706, p &lt; 0.0001) and multivariate logistic regression analyses (OR = 1.767, p &lt; 0.0001), but was not associated with ventricle penetration. Cerebrospinal fluid (CSF) could significantly induce tumor cell migration (p &lt; 0.0001), and GBM could grow in CSF. Compared with those from the cortex, cells from the ependymal region attenuated the invasion of C6 whether cocultured with C6 or mixed with Matrigel (p = 0.0054 and p = 0.0488). Immunofluorescence analysis shows a thin gap with GFAP expression delimiting the tumor and ependymal region.ConclusionThe ependymal region might restrict GBM cells from entering the ventricle via a non-mechanical force. Further studies in this area may reveal mechanisms that occur in GBM patients and may enable the design of new therapeutic strategies.
Clinical Subtypes and vHIT Parameters in a Population With Bilateral Vestibulopathy
Authors: Mancino-Moreira Fiorella , Rueda Almudena , Esteban-Sanchez Jonathan , Martin-Sanz Eduardo 
Published: June 2021

Objective:To evaluate the different peripheral, neurological, genetic, and systemic etiologies of bilateral vestibulopathy (BVP) and the value of vHIT in the diagnostic process.Materials and methods:A retrospective case review was performed on 176 patients diagnosed with BVP in a tertiary referral center, between 2010 and 2020. Inclusion criteria comprised imbalance and/or oscillopsia during locomotion and horizontal angular VOR gain on both sides &lt;0.8. We classified patients into different groups according to (1) their fulfillment of the Barany guideline for bilateral vestibulopathy (2) the definite etiology of BVP and (3) the four clinical subtypes distributed in our population (recurrent vertigo with BVP, rapidly progressive BVP, slowly progressive BVP, and slowly progressive BVP with ataxia). Medical history of vertigo, hypoacusis or migraine, and family background of imbalance and/or oscillopsia were assessed. Horizontal, posterior, and superior semicircular canal angular VOR gain was registered along with saccadic parameters such as velocity, and dispersion of the saccades' latency values.Results:Barany's Society diagnostic criteria for BVP was accomplished in 89 patients. Among our patients, 13.6% had migraines in their medical history and the idiopathic group accounted for 50% of the population. All four clinical subtypes were found in our population, slowly progressive bilateral vestibulopathy without vertigo was the most frequent one. A percentage of our population could not be categorized into any of the former subtypes, many of these patients were diagnosed with BVP after suffering a single vertigo episode. Lower vHIT gains were found in those patients with Barany's criteria for BVP and oscillopsia was significantly more prevalent in this group.Conclusions:Bilateral vestibulopathy manifests with very different patterns representing a very heterogeneous condition. The distribution of the clinical subtypes and Barany's criteria are a useful clinical tool to differentiate groups of patients. The vHIT can serve as an initial tool for identifying patients with BVP. The finding of bilateral vestibular involvement in a clinically suspected unilateral vestibulopathy should be considered in some patients.
Clinical Outcome in Patients With Intracerebral Hemorrhage Stratified by Type of Antithrombotic Therapy
Authors: Baharoglu Merih Irem , Coutinho Jonathan M. , Marquering Henk A. , Majoie Charles B. , Roos Yvo B. 
Published: June 2021

Background: Antithrombotic therapy influences clinical outcome after spontaneous intracerebral hemorrhage (ICH). However, evidence on the effect of different antithrombotic therapies on outcome and a comparison between different therapies is scarce, while this is important for medical decision making. Therefore, we investigated clinical outcome after ICH stratified by type of antithrombotic therapy.Patients/Methods: We performed a cohort study selecting consecutive ICH patients from our database, excluding patients without data on medication or therapeutic heparin use. Primary outcome was poor outcome (modified Rankin Scale ≥ 4) after 90 days. Secondary outcome was mortality at 90 days. We analyzed outcome and survival in patients with ICH using vitamin K antagonists (VKA), antiplatelet therapy (AP), and direct oral anticoagulant (DOAC) compared to no antithrombotic therapy adjusted for age, National Institutes of Health Stroke Scale (NIHSS), infratentorial localization, intraventricular extension, history of hypertension, diabetes, or stroke, and interaction between age and NIHSS.Results: We included 916 patients (223 AP, 161 VKA, and 40 DOAC). VKA (adjusted odds ratio [aOR] 3.2, 95% confidence interval [CI], 1.6–6.3) and AP (aOR = 2.0, 95%CI: 1.1–3.7) were associated with poor outcome. DOAC use did not reach statistical significance (aOR = 2.4, 95%CI: 0.8–7.7). Patients who used any antithrombotic therapy had poorer survival compared to patients without antithrombotic treatment and patients using AP and DOAC had better survival compared to VKA after adjustment.Conclusions: Patients with antithrombotic therapy have worse clinical outcome after ICH. Patients using VKA have higher risk of poor outcome and mortality compared to patients using AP. These findings highlight the deleterious effect of antithrombotic therapy in patients with ICH and stress the need for effective therapies for ICH patients.
Gray Matter Abnormalities in Type 1 and Type 2 Diabetes: A Dual Disorder ALE Quantification
Authors: Yu Kevin K. K. , Cheing Gladys L. Y. , Cheung Charlton , Kranz Georg S. , Cheung Alex Kwok-Kuen 
Published: June 2021

Aims/hypothesis: Diabetes mellitus (DM) is associated with comorbid brain disorders. Neuroimaging studies in DM revealed neuronal degeneration in several cortical and subcortical brain regions. Previous studies indicate more pronounced brain alterations in type 2 diabetes mellitus (T2DM) than in type 1 diabetes mellitus (T1DM). However, a comparison of both types of DM in a single analysis has not been done so far. The aim of this meta-analysis was to conduct an unbiased objective investigation of neuroanatomical differences in DM by combining voxel-based morphometry (VBM) studies of T1DM and T2DM using dual disorder anatomical likelihood estimation (ALE) quantification.Methods: PubMed, Web of Science and Medline were systematically searched for publications until June 15, 2020. VBM studies comparing gray matter volume (GMV) differences between DM patients and controls at the whole-brain level were included. Study coordinates were entered into the ALE meta-analysis to investigate the extent to which T1DM, T2DM, or both conditions contribute to gray matter volume differences compared to controls.Results: Twenty studies (comprising of 1,175 patients matched with 1,013 controls) were included, with seven studies on GMV alterations in T1DM and 13 studies on GMV alterations in T2DM. ALE analysis revealed seven clusters of significantly lower GMV in T1DM and T2DM patients relative to controls across studies. Both DM subtypes showed GMV reductions in the left caudate, right superior temporal lobe, and left cuneus. Conversely, GMV reductions associated exclusively with T2DM (&gt;99% contribution) were found in the left cingulate, right posterior lobe, right caudate and left occipital lobe. Meta-regression revealed no significant influence of study size, disease duration, and HbA1c values.Conclusions/interpretation: Our findings suggest a more pronounced gray matter atrophy in T2DM compared to T1DM. The increased risk of microvascular or macrovascular complications, as well as the disease-specific pathology of T2DM may contribute to observed GMV reductions.Systematic Review Registration: [PROSPERO], identifier [CRD42020142525].
Radiomics Nomogram for Identifying Sub-1 cm Benign and Malignant Thyroid Lesions
Authors: Wu Xinxin , Li Jingjing , Mou Yakui , Yao Yao , Cui Jingjing , Mao Ning , Song Xicheng 
Published: June 2021

PurposeTo develop and validate a radiomics nomogram for identifying sub-1 cm benign and malignant thyroid lesions.MethodA total of 171 eligible patients with sub-1 cm thyroid lesions (56 benign and 115 malignant) who were treated in Yantai Yuhuangding Hospital between January and September 2019 were retrospectively collected and randomly divided into training (n = 136) and validation sets (n = 35). The radiomics features were extracted from unenhanced and arterial contrast-enhanced computed tomography images of each patient. In the training set, one-way analysis of variance and least absolute shrinkage and selection operator (LASSO) logistic regression were used to select the features related to benign and malignant lesions, and the LASSO algorithm was used to construct the radiomics signature. Combined with clinical independent predictive factors, a radiomics nomogram was constructed with a multivariate logistic regression model. The performance of the radiomics nomogram was evaluated by using the receiver operating characteristic (ROC) and calibration curves in the training and validation sets. The clinical usefulness was evaluated by using decision curve analysis (DCA).ResultsThe radiomics signature consisting of 13 selected features achieved favorable prediction efficiency. The radiomics nomogram, which incorporated radiomics signature and clinical independent predictive factors including age and Thyroid Imaging Reporting and Data System category, showed good calibration and discrimination in the training (area under the ROC [AUC]: 0.853; 95% confidence interval [CI]: 0.797, 0.899) and validation sets (AUC: 0.851; 95% CI: 0.735, 0.931). DCA demonstrated that the nomogram was clinically useful.ConclusionAs a noninvasive preoperative prediction tool, the radiomics nomogram incorporating radiomics signature and clinical predictive factors shows favorable predictive efficiency for identifying sub-1 cm benign and malignant thyroid lesions.
Training and Validation of Deep Learning-Based Auto-Segmentation Models for Lung Stereotactic Ablative Radiotherapy Using Retrospective Radiotherapy Planning Contours
Authors: Wong Jordan , Huang Vicky , Giambattista Joshua A. , Teke Tony , Kolbeck Carter , Giambattista Jonathan , Atrchian Siavash 
Published: June 2021

PurposeDeep learning-based auto-segmented contour (DC) models require high quality data for their development, and previous studies have typically used prospectively produced contours, which can be resource intensive and time consuming to obtain. The aim of this study was to investigate the feasibility of using retrospective peer-reviewed radiotherapy planning contours in the training and evaluation of DC models for lung stereotactic ablative radiotherapy (SABR).MethodsUsing commercial deep learning-based auto-segmentation software, DC models for lung SABR organs at risk (OAR) and gross tumor volume (GTV) were trained using a deep convolutional neural network and a median of 105 contours per structure model obtained from 160 publicly available CT scans and 50 peer-reviewed SABR planning 4D-CT scans from center A. DCs were generated for 50 additional planning CT scans from center A and 50 from center B, and compared with the clinical contours (CC) using the Dice Similarity Coefficient (DSC) and 95% Hausdorff distance (HD).ResultsComparing DCs to CCs, the mean DSC and 95% HD were 0.93 and 2.85mm for aorta, 0.81 and 3.32mm for esophagus, 0.95 and 5.09mm for heart, 0.98 and 2.99mm for bilateral lung, 0.52 and 7.08mm for bilateral brachial plexus, 0.82 and 4.23mm for proximal bronchial tree, 0.90 and 1.62mm for spinal cord, 0.91 and 2.27mm for trachea, and 0.71 and 5.23mm for GTV. DC to CC comparisons of center A and center B were similar for all OAR structures.ConclusionsThe DCs developed with retrospective peer-reviewed treatment contours approximated CCs for the majority of OARs, including on an external dataset. DCs for structures with more variability tended to be less accurate and likely require using a larger number of training cases or novel training approaches to improve performance. Developing DC models from existing radiotherapy planning contours appears feasible and warrants further clinical workflow testing.
Case Report: Eighteen Month Relapse- Free Survival Following Radical Multidisciplinary Oncological Treatment in a 68-Year-Old Male Patient With Histiocytic Sarcoma
Authors: Wehrmann Stefan , Rudolph Hagen , Ernst Dominikus , Siepmann Timo , Kaltofen Dorothea , Hänel Mathias , Mirow Lutz 
Published: June 2021

IntroductionHistiocytic Sarcoma (HS) is a rare and aggressive malignancy, and patients can present with rapid tumor growth and invasion. The optimal diagnostic and therapeutic management is unknown since only a few cases have been published. Here we report a patient with histiocytic sarcoma of the right groin.CaseA 68 year-old male patient presented to our hospital with suspicion of a superinfected atheroma of the right groin. Computed tomography showed an abdominal tumor of unknown entity. Detailed assessment including immunohistochemically evaluation of biopsy material confirmed HS. The patient underwent radical tumor resection including compartment-resection of the right thigh. During five additional cycles of chemotherapy over a period of 1.5 years he remained relapse-free.SummaryDiagnostic work up and treatment of HS is challenging, as there is a paucity of clinical reports and lack of standard guidelines for care. In the present case report, aggressive multidisciplinary treatment resulted in good clinical outcome, however, further studies evaluating this approach in similar patients are needed.
Determining Clinical Patient Selection Guidelines for Head and Neck Adaptive Radiation Therapy Using Random Forest Modelling and a Novel Simplification Heuristic
Authors: Weppler Sarah , Quon Harvey , Schinkel Colleen , Ddamba James , Harjai Nabhya , Vigal Clarisse , Beers Craig A. , Van Dyke Lukas , Smith Wendy 
Published: June 2021

PurposeTo determine which head and neck adaptive radiotherapy (ART) correction objectives are feasible and to derive efficient ART patient selection guidelines.MethodsWe considered various head and neck ART objectives including independent consideration of dose-sparing of the brainstem/spinal cord, parotid glands, and pharyngeal constrictor, as well as prediction of patient weight loss. Two-hundred head and neck cancer patients were used for model development and an additional 50 for model validation. Patient chart data, pre-treatment images, treatment plans, on-unit patient measurements, and combinations thereof were assessed as potential predictors of each objective. A stepwise approach identified combinations of predictors maximizing the Youden index of random forest (RF) models. A heuristic translated RF results into simple patient selection guidelines which were further refined to balance predictive capability and practical resource costs. Generalizability of the RF models and simplified guidelines to new data was tested using the validation set.ResultsTop performing RF models used various categories of predictors, however, final simplified patient selection guidelines only required pre-treatment information for ART predictions, indicating the potential for significant ART process streamlining. The simplified guidelines for each objective predicted which patients would experience increases in dose to: brainstem/spinal cord with sensitivity = 1.0, specificity = 0.66; parotid glands with sensitivity = 0.82, specificity = 0.70; and pharyngeal constrictor with sensitivity = 0.84, specificity = 0.68. Weight loss could be predicted with sensitivity = 0.60 and specificity = 0.55. Furthermore, depending on the ART objective, 28%-58% of patients required replan assessment, less than for previous studies, indicating a step towards more effective patient selection.ConclusionsThe above ART objectives appear to be practically achievable, with patients selected for ART according to simple clinical patient selection guidelines. Explicit ART guidelines are rare in the literature, and our guidelines may aid in balancing the potential clinical gains of ART with high associated resource costs, formalizing ART trials, and ensuring the reproducibility of clinical successes.
Effects of Exercise on Sleep Quality and Insomnia in Adults: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Xie Yi , Liu Shuai , Chen Xue-Jiao , Yu Hai-Han , Yang Yuan , Wang Wei 
Published: June 2021

Study Objectives: We conducted a meta-analysis to assess the effects of different regular exercise (lasting at least 2 months on a regular basis) on self-reported and physiological sleep quality in adults. Varied exercise interventions contained traditional physical exercise (e.g., walking, cycling) and mind–body exercise characterized by gentle exercise with coordination of the body (e.g., yoga).Methods: Procedures followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Systematical searches were conducted in three electronic databases (PubMed, Embase, and Web of Science) for relevant research that involved adult participants without pathological diseases receiving exercise intervention. The search strategy was based on the population, intervention, comparison, and outcome study design (PICOS) framework. The self-reported outcomes included varied rating scales of Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Epworth Sleepiness Scale (ESS). Subgroup meta-analyses of PSQI scores were conducted based on type of exercise, duration of intervention, and participants' age and gender. The physiological outcomes were measured by Actigraph. All meta-analyses were performed in a fixed or random statistic model using Revman software.Results: Twenty-two randomized controlled trials were included in the analysis. The overall analysis on subjective outcomes suggests that exercise interventions significantly improved sleep quality in adults compared with control interventions with lower PSQI (MD −2.19; 95% CI −2.96 to −1.41), ISI (MD −1.52; 95% CI −2.63 to −0.41), and ESS (MD −2.55; 95% CI −3.32 to −1.78) scores. Subgroup analyses of PSQI scores showed both physical and mind–body exercise interventions resulted in improvements of subjective sleep to the same extent. Interestingly, short-term interventions (≤3 months) had a significantly greater reduction in sleep disturbance vs. long-term interventions (&gt;3 months). Regarding physiological sleep, few significant effects were found in various sleep parameters except the increased sleep efficiency in the exercise group vs. control group.Conclusions: Results of this systematic review suggest that regular physical as well as mind–body exercise primarily improved subjective sleep quality rather than physiological sleep quality in adults. Specifically, self-reported sleep quality, insomnia severity, and daytime sleepiness could be improved or ameliorated with treatment of exercise, respectively, evaluated by PSQI, ISI, and ESS sleep rating scales.