bluuebunny/crossref_metadata_2025_split huggingface dataset:
The MUC5B Promoter Polymorphism Associates With Severe COVID-19 in the European Population
Authors: van Moorsel Coline H. M. , van der Vis Joanne J. , Duckworth Anna , Scotton Chris J. , Benschop Claudia , Ellinghaus David , Ruven Henk J. T. , Quanjel Marian J. R. , Grutters Jan C. 
Published: November 2021

Background: Diversity in response on exposure to severe acute respiratory syndrome coronavirus 2 may be related to the innate immune response in the elderly. The mucin MUC5B is an important component of the innate immune response and expression levels are associated with the MUC5B promoter polymorphism, rs35705950. The high expressing T-allele is a risk allele for the non-infectious aging lung disease idiopathic pulmonary fibrosis (IPF). We investigated if MUC5B rs35705950 associates with severe COVID-19.Methods: In this retrospective candidate gene case-control study we recruited 108 Dutch patients (69% male, median age 66 years, 77% white) requiring hospitalization for COVID-19 (22% ICU stay, 24% died). For validation, genotypes were obtained from the UK-Biobank (n = 436, 57% male, median age 70 years, 27% died), for replication data from the severe COVID-19 GWAS group from Italy (n = 835) and Spain (n = 775) was used, each with a control cohort (n = 356,735, n = 1,255, n = 950, respectively). MUC5B association analysis was performed including adjustment for age and sex.Results: The rs35705950 T-allele frequency was significantly lower in Dutch white patients (n = 83) than in controls (0.04 vs. 0.10; p = 0.02). This was validated in the UK biobank cohort (0.08 vs. 0.11; p = 0.001). While age and sex differed significantly between cases and control, comparable results were obtained with age and sex as confounding variables in a multivariate analysis. The association was replicated in the Italian (p = 0.04), and Spanish (p = 0.03) case-control cohorts. Meta-analysis showed a negative association for the T-allele with COVID-19 (OR = 0.75 (CI: 0.67–0.85); p = 6.63 × 10−6).Conclusions: This study shows that carriage of the T-allele of MUC5B rs35705950 confers protection from development of severe COVID-19. Because the T-allele is a known risk allele for IPF, this study provides further evidence for the existence of trade-offs between optimal mucin expression levels in the aging lung.
Carotid Artery Perivascular Adipose Tissue Density Relates to Recanalization and Clinical Outcome After Mechanical Thrombectomy
Authors: Jin Jiaolei , Huang Rui , Chen Qiuyue , Ke Boxi , Tao Taotao , Zhao Rong , He Xinwei 
Published: November 2021

Background: Perivascular adipose tissue (PVAT) imaging can be used in clinical practice as a surrogate marker of vascular disease. We aimed to analyze the association between the density of carotid artery PVAT and clinical features and outcomes in stroke patients treated with mechanical thrombectomy.Methods: A total of 183 consecutive patients treated with mechanical thrombectomy due to anterior circulation large vessel occlusion were retrospectively included from January 2016 to May 2021. The density of carotid artery PVAT was evaluated by preoperative computed tomography angiography. Successful arterial recanalization was defined as a modified Thrombolysis in Cerebral Infarction score of 2b-3 on the final angiographic examination. Poor functional outcome was defined as a modified Rankin Scale (mRS) score &gt; 2 at 3 months after stroke. We assessed the independent effect of carotid artery PVAT density on revascularization, functional outcome, and mortality using logistic regression models adjusted for relevant confounders.Results: Patients with large artery atherosclerotic stroke have higher carotid artery PVAT density than patients with other stroke etiologies (–65.82 ± 12.96 vs. –75.77 ± 13.44, P &lt; 0.001). Higher carotid artery PVAT density was associated with unsuccessful recanalization [adjusted odds ratio (AOR) (95% CI), 2.968 (1.292, 6.819), P = 0.010], and poor outcome [AOR (95% CI), 2.704 (1.610, 4.541), P &lt; 0.001] and mortality [AOR (95% CI), 1.894 (1.040, 3.449), P = 0.037] at 3 months in stroke patients treated with thrombectomy.Conclusion: Higher carotid artery PVAT density before mechanical thrombectomy is an indicator of worse postprocedural arterial revascularization and a worse functional outcome in acute stroke patients.
Dabigatran Reversal With Idarucizumab and In-Hospital Mortality in Intracranial Hemorrhage: A Systematic Review of Real-Life Data From Case Reports and Case Series
Authors: Frol Senta , Sagris Dimitrios , Šabovič Mišo , Ntaios George , Oblak Janja Pretnar 
Published: November 2021

Background: Intracranial hemorrhage is a severe and possibly fatal consequence of anticoagulation therapy. Idarucizumab is used in dabigatran-treated patients suffering from intracranial hemorrhage (ICH) to reverse the anticoagulant effect of dabigatran. Systematic review of real-life mortality in these patients is missing.Objectives: A review of all published dabigatran-related ICH cases treated with idarucizumab was performed. We aimed to estimate in-hospital mortality rate in these patients.Method: We searched PubMed and Scopus for all published cases of ICH in idarucizumab/dabigatran-treated patients until May 15, 2021. The assessed outcome was in-hospital mortality.Results: We identified six eligible studies (case series) with 386 patients and 54 single case reports. In-hospital mortality rate was 11.4% in the case series and 9.7% in the case reports.Conclusions: Our analysis provides clinically relevant quantitative data regarding in-hospital mortality in idarucizumab/dabigatran-treated patients with ICH, which is estimated to be 9.7–11.4%.
The Effect of Sex and Wealth on Population Attributable Risk Factors for Dementia in South Africa
Authors: Bobrow Kirsten , Hoang Tina , Barnes Deborah E. , Gardner Raquel C. , Allen Isabel E. , Yaffe Kristine 
Published: November 2021

Background and Aims: South Africa is a middle-income country with high levels of income inequality and a rapidly aging population and increasing dementia prevalence. Little is known about which risk factors for dementia are important and how they differ by social determinants of health as well as key demographic characteristics such as sex and wealth. We sought to calculate the population attributable risks (PARs) for established potentially modifiable risk factors for dementia among these different groups.Methods: We obtained risk factor prevalence from population-based surveys for established dementia risk factors (diabetes, midlife hypertension, midlife obesity, physical inactivity, depression, smoking, low educational attainment, social isolation). We used relative risk estimates reported in previous meta-analyses and estimated PARs using Levin's formula and accounting for communality. We tested for one-way and two-way interactions by sex and wealth using Pearson's χ2. In stratified analyses, we performed tests for trend using logistic regression.Results: The prevalence of established risk factors for dementia ranged from 5% for depression to 64% for low education. After accounting for communality, the risk factors contributing the greatest PAR were low education (weighted PAR 12%, 95% CI 7% to 18%), physical inactivity (9, 5–14%), and midlife hypertension (6, 5–14%). Together, 45% of dementia cases may be attributable to modifiable risk factors (95% CI 25–59%). We found significant interactions (p &lt; 0.005) between sex, wealth, or both (sex * wealth) and each risk factor except social isolation and physical activity. Low education was inversely associated with wealth in both male and female. The PAR for midlife hypertension, obesity, and diabetes was associated with increasing wealth, and was higher in female. In contrast, the PAR for smoking was higher in male (8% vs. 2%) and was associated with increasing wealth among female only. We found that either a strategy of large reductions in selected risk factors with the highest PAR (midlife hypertension, smoking, physical inactivity) or small reductions across all risk factors could potentially reduce dementia cases by as many as 250,000 by 2050.Discussions: The potential impact on dementia risk by decreasing exposure to established dementia risk factors is large and differs by sex and social determinants of health like wealth. Risk factor PAR should inform national and local health policy dementia initiatives in South Africa including which risk factors to target in the whole population and which to target in high-risk groups for maximum public health benefit.
Functional Recovery and Serum Angiogenin Changes According to Intensity of Rehabilitation Therapy After Stroke
Authors: Garcia-Rodriguez Nicolás , Rodriguez Susana , Tejada Pedro Ignacio , Miranda-Artieda Zuberoa Maite , Ridao Natalia , Buxó Xavi , Pérez-Mesquida María Engracia , Beseler Maria Rosario , Salom Juan B. , Pérez Laura M. , Inzitari Marco , Otero-Villaverde Sergio , Martin-Mourelle Rosa , Molleda Mercedes , Quintana Manuel , Olivé-Gadea Marta , Penalba Anna , Rosell Anna 
Published: November 2021

Background: Rehabilitation is still the only treatment available to improve functional status after the acute phase of stroke. Most clinical guidelines highlight the need to design rehabilitation treatments considering starting time, intensity, and frequency, according to the tolerance of the patient. However, there are no homogeneous protocols and the biological effects are under investigation.Objective: To investigate the impact of rehabilitation intensity (hours) after stroke on functional improvement and serum angiogenin (ANG) in a 6-month follow-up study.Methods: A prospective, observational, longitudinal, and multicenter study with three cohorts: strokes in intensive rehabilitation therapy (IRT, minimum 15 h/week) vs. conventional therapy (NO-IRT, &lt;15 h/week), and controls subjects (without known neurological, malignant, or inflammatory diseases). A total of seven centers participated, with functional evaluations and blood sampling during follow-up. The final cohort includes 62 strokes and 43 controls with demographic, clinical, blood samples, and exhaustive functional monitoring.Results: The median (IQR) number of weekly hours of therapy was different: IRT 15 (15–16) vs. NO-IRT 7.5 (5–9), p &lt; 0.01, with progressive and significant improvements in both groups. However, IRT patients showed earlier improvements (within 1 month) on several scales (CAHAI, FMA, and FAC; p &lt; 0.001) and the earliest community ambulation achievements (0.89 m/s at 3 months). There was a significant difference in ANG temporal profile between the IRT and NO-IRT groups (p &lt; 0.01). Additionally, ANG was elevated at 1 month only in the IRT group (p &lt; 0.05) whereas it decreased in the NO-IRT group (p &lt; 0.05).Conclusions: Our results suggest an association of rehabilitation intensity with early functional improvements, and connect the rehabilitation process with blood biomarkers.
Stability of AI-Enabled Diagnosis of Parkinson’s Disease: A Study Targeting Substantia Nigra in Quantitative Susceptibility Mapping Imaging
Authors: Xiao Bin , He Naying , Wang Qian , Shi Feng , Cheng Zenghui , Haacke Ewart Mark , Yan Fuhua , Shen Dinggang 
Published: November 2021

Purpose: Parkinson’s disease (PD) diagnosis algorithms based on quantitative susceptibility mapping (QSM) and image algorithms rely on substantia nigra (SN) labeling. However, the difference between SN labels from different experts (or segmentation algorithms) will have a negative impact on downstream diagnostic tasks, such as the decrease of the accuracy of the algorithm or different diagnostic results for the same sample. In this article, we quantify the accuracy of the algorithm on different label sets and then improve the convolutional neural network (CNN) model to obtain a high-precision and highly robust diagnosis algorithm.Methods: The logistic regression model and CNN model were first compared for classification between PD patients and healthy controls (HC), given different sets of SN labeling. Then, based on the CNN model with better performance, we further proposed a novel “gated pooling” operation and integrated it with deep learning to attain a joint framework for image segmentation and classification.Results: The experimental results show that, with different sets of SN labeling that mimic different experts, the CNN model can maintain a stable classification accuracy at around 86.4%, while the conventional logistic regression model yields a large fluctuation ranging from 78.9 to 67.9%. Furthermore, the “gated pooling” operation, after being integrated for joint image segmentation and classification, can improve the diagnosis accuracy to 86.9% consistently, which is statistically better than the baseline.Conclusion: The CNN model, compared with the conventional logistic regression model using radiomics features, has better stability in PD diagnosis. Furthermore, the joint end-to-end CNN model is shown to be suitable for PD diagnosis from the perspectives of accuracy, stability, and convenience in actual use.
Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics
Authors: Gondal Mahnoor Naseer , Chaudhary Safee Ullah 
Published: November 2021

Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-drivenin silicoclinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalizedin silicomulti-scale models in clinical settings.
Predicting Pathological Complete Response After Neoadjuvant Chemotherapy in Advanced Breast Cancer by Ultrasound and Clinicopathological Features Using a Nomogram
Authors: Cui Hao , Zhao Dantong , Han Peng , Zhang Xudong , Fan Wei , Zuo Xiaoxuan , Wang Panting , Hu Nana , Kong Hanqing , Peng Fuhui , Wang Ying , Tian Jiawei , Zhang Lei 
Published: November 2021

Background and AimsPrediction of pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer is critical for surgical planning and evaluation of NAC efficacy. The purpose of this project was to assess the efficiency of a novel nomogram based on ultrasound and clinicopathological features for predicting pCR after NAC.MethodsThis retrospective study included 282 patients with advanced breast cancer treated with NAC from two centers. Patients received breast ultrasound before NAC and after two cycles of NAC; and the ultrasound, clinicopathological features and feature changes after two cycles of NAC were recorded. A multivariate logistic regression model was combined with bootstrapping screened for informative features associated with pCR. Then, we constructed two nomograms: an initial-baseline nomogram and a two-cycle response nomogram. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were analyzed. The C-index was used to evaluate predictive accuracy.ResultsSixty (60/282, 21.28%) patients achieved pCR. Triple-negative breast cancer (TNBC) and HER2-amplified types were more likely to obtain pCR. Size shrinkage, posterior acoustic pattern, and elasticity score were identified as independent factors by multivariate logistic regression. In the validation cohort, the two-cycle response nomogram showed better discrimination than the initial-baseline nomogram, with the C-index reaching 0.79. The sensitivity, specificity, and NPV of the two-cycle response nomogram were 0.77, 0.77, and 0.92, respectively.ConclusionThe two-cycle response nomogram exhibited satisfactory efficiency, which means that the nomogram was a reliable method to predict pCR after NAC. Size shrinkage after two cycles of NAC was an important in dependent factor in predicting pCR.
Repeat Breast-Conserving Surgery Versus Salvage Mastectomy for Ipsilateral Breast Tumour Recurrence After Breast-Conserving Surgery in Breast Cancer Patients: A Meta-Analysis
Authors: Mo Caiqin , Ruan Weihong , Lin Junyu , Chen Huaying , Chen Xiangjin 
Published: November 2021

BackgroundSalvage mastectomy (SM) is the standard surgery for ipsilateral breast tumour recurrence (IBTR). However, whether repeat breast-conserving surgery (RBCS) is an alternative method remains unclear. We performed a meta-analysis to compare the effects of RBCS and SM after IBTR for breast-conserving surgery (BCS).MethodsWe searched PubMed, Cochrane, Wiley Online and Embase for controlled studies comparing RBCS and SM after IBTR for BCS (published between 1993 and 2019, published in English). Our main endpoints were the secondary local recurrence rate (SLRR), distant metastasis rate (DMR) and overall survival (OS). We used a random-effects model or fixed-effects model for data pooling.ResultsFifteen of the 424 eligible studies were ultimately included, and all studies were retrospective cohort studies (n=2532 participants). 1) SLRR: The SLRR of RBCS was higher than SM (pooled relative rate (pRR) = 1.87, 95% CI 1.22 - 2.86, P=0.004). Stratified analysis was performed according to whether radiotherapy was performed after salvage surgery (radiotherapy group: 2ndRT, no radiotherapy group: no-2ndRT), and the following results were revealed: pRR=0.43 (95% CI 0.20-0.95, P=0.04) for group 2ndRT; and pRR=2.30 (95% CI 1.72-3.06, P&lt;0.00001) for group no-2ndRT. These results showed that the main cause of heterogeneity was salvage radiotherapy. 2) DMR: No significant difference in the DMR was observed between RBCS and SM (pRR = 0.61, 95% CI 0.37 - 1.01, P=0.05). 3) OS: No significant difference in OS was observed between RBCS and SM (pRR=0.65, 95% CI 0.39 - 1.08, P=0.10).ConclusionsThe SLRR of RBCS was higher than SM for ITBR after BCS, but survival was not affected. RBCS may be used as an alternative for IBTR patients after BCS with strict control for several indications, such as tumor size, recurrence interval and biological behavior, and attaching importance to subsequent salvage radiotherapy and systematic therapy.
Transition From Full Mu Opioid Agonists to Buprenorphine in Opioid Dependent Patients—A Critical Review
Authors: Soyka Michael 
Published: November 2021

Methadone, a full opioid agonist at the mu-, kappa-, and delta-receptor, and buprenorphine, a partial agonist at the mu receptor, are first-line medications in opioid maintenance treatment. Transition from methadone to buprenorphine may precipitate withdrawal, and no accepted algorithm for this procedure has been developed. Current treatment strategies recommend transfer from methadone to buprenorphine predominantly in patients at low doses of methadone (30–40 mg/day). There are some reports indicating that transition from higher doses of methadone may be possible. A number of dosing strategies have been proposed to soften withdrawal symptoms and facilitate transfer including use of other opioids or medications and especially microdosing techniques for buprenorphine. The case series and studies available thus far are reviewed.
Mental Health Problems Due to Social Isolation During the COVID-19 Pandemic in a Mexican Population
Authors: Genis-Mendoza Alma Delia , Martínez-Magaña José Jaime , López-Narváez María Lilia , González-Castro Thelma Beatriz , Juárez-Rojop Isela Esther , Nicolini Humberto , Tovilla-Zárate Carlos Alfonso , Castillo-Avila Rosa Giannina 
Published: November 2021

Introduction: Social isolation due to the COVID-19 pandemic has been identified as a risk factor of several mental disorders. Therefore, the present work aimed to evaluate the effect of social isolation experienced during the COVID-19 pandemic on the mental health of a Mexican population.Materials and Methods: A cross-sectional online survey was conducted in individuals of 18 years of age and over. The questioner was structured to identify onset or worsening of psychiatric symptoms due to social isolation by COVID-19. The survey included changes in eating habits, changes in personal hygiene habits, the starting the use or increased the use of psychoactive substances, symptoms of depression or post-traumatic stress.Results: A total of 1,011 individuals were included in the analysis. The majority were women (68.84%). Changes in eating habits were reported in 38.51% of the participants, 67.80% reported having their physical self-perception distorted or having started a low-calorie diet. Regarding symptoms of depression, 46.10% participants indicated to have at least one depressive symptom, and 4.46% reported suicidal ideation during social isolation. Interestingly, 6.09% of individuals reported that they used to have depressive symptoms prior the COVID-19 pandemic and those symptoms decreased due to social isolation. Additionally, 2.27% of individuals presented symptoms of post-traumatic stress due to the possibility of getting COVID-19.Conclusions: In this work we identified how social isolation has impacted the mental health of the Mexican population. We observed that practically all the symptoms evaluated were affected during isolation, such as personal hygiene and eating habits. Depression and suicidal ideation were the ones that increased the most in the general population, while in individuals who had symptoms of depression before isolation, these symptoms decreased during social isolation.