bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new case of cutaneous melanocytoma harbouring the CRTC1‐TRIM11 fusion: case report
Authors: Miry Achraf , Aissaoui Asmae , Malki Samia , Bouhahyaoui Youssef , Bennani Amal , Souaf Ihssane , Fouchardière Arnaud De La 
Published: November 2020

Abstract
Background: The diagnosis of dermal primary and metastatic melanocytic tumors is often problematic. Recently, a new entity has been proposed, cutaneous melanocytoma with CRTC1‐TRIM11 fusion (CMCT). Case presentation: We report the 11th case of cutaneous melanocytoma harbouring the CRTC1-TRIM11 fusion. The patient is a 35‐year‐old female patient, with no particular history, who presented in the dermatology department for a 1.5cm nodular lesion on the dorsal aspect of the left foot. The lesion evolved for more than one year. She underwent tumour resection for clinical suspicion of malignant melanoma. Pathological examination of the resected specimen after H&E stain revealed a dermal symmetrical proliferation made of spindle cells showing a melanocytic differentiation proved by expression of Melan A, S100 protein and SOX10. FISH study helped exclude a clear cell sarcoma. RNA sequencing showed the CRTC1-TRIM11 fusion.Conclusions: Since only 11 cases have been documented, and because of the overlap with the clear cell sarcoma, the characterization of CMCT is still not fully satisfactory.
Assessment of Personality, Psychomotor Abilities, Spirituality and Team Work in Surgeons Depending on Experience: a Prospective Pilot Study
Authors: Vukojević Mladenka , Dodaj Arta , Zovko Ana , Brekalo Zdrinko , Galic Kristina , Kvesic Ante , Splavski Bruno 
Published: November 2020

Abstract
Background: A few studies described surgical personality, inquiring all its dimensions, as well as surgeons’ psychomotor abilities and propensity for teamwork. Even fewer papers examined their spirituality and its impact on the effectiveness of daily surgical labor. The aim of this paper is to evaluate personality traits, psychomotor abilities and spirituality in surgeons and surgical residents, as well as propensity for teamwork in relation to their work experience.Methods: The study involved 15 male surgeons aged 40-49 and 15 male surgical residents aged 30-39, who were divided into the case and control group according to their age. The Eysenck Personality Questionnaire, visual stimulus response rate, oculomotor, and manual ability assessments, movement stability testing, intrinsic/extrinsic religious orientation, and teamwork efficiency questionnaires were used. Results: No statistically significant differences in personality traits, psychomotor abilities, religious orientation, and propensity for teamwork were recorded between surgeons and residents. These may support the specialty choice, and selection of surgical teams helping them to make important professional decisions, which well-affect the patients’ outcome.
Impact of Colloid Infusion on Outcomes in Patients with Septic Shock
Authors: Ge Chenglong , Peng Qianyi , Jiang Yuan , Liu Zhiyong , Li Wenchao , Zhang Lina , Ai Yuhang 
Published: November 2020

Abstract
Background: Although colloid solution has been widely used in practice, its impact on mortality in patients with septic shock remains unknown. We evaluated the association of colloid infusion with outcomes in septic shock patients.Methods: Medical Information Mart for Intensive Care (MIMIC)-III was used to identify patients with septic shock. Propensity score matching (PSM) was employed to balance the baseline differences. Cox proportional hazards model, Wilcoxon rank-sum test, and logistic regression were utilized to determine the associations of colloid infusion with mortality, length of stay, and recovery of kidney function, respectively.Results: A total of 4,553 septic shock patients were studied, including 1,158 with colloid infusion, and 3,395 without colloid infusion. After PSM, 1,012 pairs of patients were matched. Significant benefits in the mortality rate were observed in the colloid group compared with the non-colloid group, with the 28-day mortality [hazard ratio (HR) 0.62; 95% confidence interval [CI], 0.52-0.73; P < 0.001], and the 90-day mortality [HR 0.76; 95% CI 0.65-0.88; P < 0.001]. Colloid infusion was not associated with the renal function recovery [HR 1.06; 95% CI 0.87–1.29; P = 0.547] in either population. Nevertheless, subgroup analysis revealed that colloid infusion did not affect the 28-day mortality in people with sepsis of AKI stage 1. In addition, the use of dextran did not decrease the 28-day mortality (HR 1.41; 95% CI 0.19-10.59; P = 0.736). Conclusion: In septic shock patients, colloid infusion (albumin or hydroxyethyl starch) improved short-term survival, but had no clear effect on the recovery of renal function.
A PET/CT Phantom for Evaluating The PET Image Quality of Micro-Lesion and CT Performance Parameters
Authors: Lu Shujie , Zhang Peng , Li Chengwei , Sun Jie , Liu Wenli , Zhang Pu 
Published: November 2020

Abstract
Background: Recent years, PET/CT equipment has played an increasingly important role in the medical field, and its quality control and evaluation requirements have become more stringent. Correspondingly, the performance testing phantom used for PET/CT quality control needs to be upgraded and optimized to meet the requirement of equipment imaging quality testing. The commonly used NEMA IEC Body performance testing phantom has the defects that it cannot detect micro-lesion and cannot measure CT performance parameters. This article proposes a NIM PET/CT phantom capable of simultaneously testing the performance of PET and CT equipment, and evaluates its imaging quality.Methods: Compared with the NEMA IEC Body phantom, the PET performance testing module in the phantom has new balls with inner diameters of 4mm and 7mm. Combined with the CT performance testing module, it can be used for both PET and CT performance testing. The 28mm and 37mm balls are filled with pure water as a cold stove, and the remaining balls are filled with F-FDG solution as a hot stove. The activity concentration ratio of the hot ball to the background is 4:1. This study compares the imaging results of the NIM PET/CT phantom and the NEMA IEC Body phantom to verify its effectiveness; compares the imaging results of 3 different brands of PET/CT on the NIM phantom to verify that it is on different equipment The generalization ability of the system; apply PSF and TOF technology to the reconstruction algorithm and compare the improvement of the image quality; finally, the accuracy of the CT low-contrast module and the uniformity of the background are verified.Results: The imaging quality of the NIM PET/CT phantom and the NEMA IEC Body phantom is relatively consistent. The NIM phantom under different types of PET/CT scans can detect 7mm balls without affecting the imaging quality of other areas, which is better The device can detect 4mm small balls, which can clearly classify the ability of different devices to present images of small lesions; the integration of PSF technology into the reconstruction algorithm significantly improves the image resolution and hot bulb contrast, but the edges of the lesions are still blurred , TOF technology improves the detection limit of the equipment and improves the overall quality of the image. PSF&TOF technology combines the advantages of the two, significantly reducing image noise and strengthening image details, so that the image quality has been comprehensively improved; the measurement in the CT module The result is consistent with the true value, and the relative error is within ±5%. The CT value transition between the background and pure water area is smooth, and the background uniformity is good.Conclusion: NIM PET/CT Phantom and NEMA IEC Body phantom are comparability, and the former includes all the functions of the latter. In addition, the phantom can meet the testing requirement of different grades of PET/CT.
Obstructive Sleep Apnea Related to Abdominal Adipose Tissue Distribution Assessed by Bioelectrical Impedance Analysis in Obese Patients
Authors: Ma Bingwei , Wang Xingchun , Du Lei , Wang Shilin , Ma Huihui , Zhong Donglei , Chen Yao , Lu Liesheng , Qu Shen 
Published: November 2020

Abstract
Background: The aim of this study was to identify the association between obstructive sleep apnea syndrome (OSAS) and abdominal fat distribution in obese individuals.Methods: A total of 94 obese patients were enrolled in the study from January 2018 to July 2020. Demographic data were collected. OSAS was diagnosed based on the results of overnight polysomnography, and the abdominal fat distribution was measured by bioelectrical impedance analysis (BIA). Univariate and multivariate logistic regression analyses were used to investigate the association between OSAS and the distribution of abdominal fat. Results: 1) The mean age (SD) of the patients included in this study was 32.44 (11.81) years and the majority were women (62.77%). The overall incidence rate of OSAS was 51.06%, and 24 (25.53%) patients had mild OSAS, 10 (10.64%) had moderate OSAS, and 14 (14.89%) had severe OSAS. 2) The incidence of OSAS among men was higher than in women (62.86% vs. 44.07%). The apnea hypopnea index (AHI) of men was significantly higher than that of women (5.50, interquartile range [IQR] 3.80-30.6 vs. 4.2, IQR 1.4-12 events/hour, P=0.014). Additionally, men had a significantly higher visceral fat area (180.29±51.64 vs. 143.88±53.42 cm2, P=0.002). 3) Patients with OSAS had a significantly higher visceral fat area than patients without OSAS (178.28±59.89 vs. 135.68±40.58 cm2, P=0.013). Multivariate analysis demonstrated that abdominal fat area and fasting plasma glucose were independent risk factors for OSAS (odds ratio, 1.016; 95% confidence interval, 1.005-1,026, P=0.005; odds ratio, 1.618; 95% confidence interval, 1.149-2.278, P=0.006). Conclusions: In obese patients, the abdominal visceral adipose deposit was an independent risk factor for OSAS. Therefore, improving the distribution of abdominal fat may contribute to alleviating the severity of OSAS.
Health Related Quality of Life of Patients with Chronic Non-Communicable Diseases During the Coronavirus Pandemic in Ethiopia: A Multi-Facility Study
Authors: Shimels Tariku , Kassu Rodas Asrat , Bogale Gelila , Bekele Mahteme , Getnet Melsew , Getachew Abrham , Shewamene Zewdneh , Abraha Mebratu 
Published: November 2020

Abstract
BackgroundThe Coronavirus pandemic is presenting several challenges in Ethiopia on an unprecedented scale. It is affecting the country in different ways ranging from a significant impact on the economy to a disrupted public health delivery of both curative and preventive services. The aim of this study was to assess health related quality of life of patients with chronic non-communicable diseases during the Coronavirus pandemic in Addis Ababa, Ethiopia.MethodsA multi-facility based cross sectional study design was conducted in August 2020 among public health institutions in Addis Ababa. Health facilities were chosen purposively based on high number of patient flow. Participants from each health facility were drawn after proportional to size allocation. A translated EQ-5D-3L VAS instrument was used to collect data. Analysis was done using SPSS v.26.0. Descriptive statistics, Mann Whitney U test, Kruskal Wallis test, Spearman’s rank correlation test and Binary logistic regression were applied. ResultsOf the 409 participants included in the study, majority were in the age group of 46-60 (36%), females (56%), from hospitals (54.8%), jobless (25.4%), married (63.3%) and orthodox Christian (71.4%). Above two third of the patients reported no problems for self-care, usual activity and depression/anxiety. All dimensions showed an increasing proportion of moderate to severe problems in the age group beyond 45. Facility type (U=16651, P=0.001), comorbid condition (U=13248.00, P=0.000) and age (rs=-0.27, p=0.000) were found to show statistically significant score difference for GQoL. An overall prevalence of any problem was 59%. Education level, visit to a health center and marriage were associated with less odds of an affected HRQoL unlike lower monthly income and presence of comorbidities which were opposite.Conclusions﻿HRQoL of patients in the study settings was found to be suboptimal and below the general population. Education and arrangement of safe and quality health services to such group of patients is warranted especially during the COVID-19 pandemic.
Personalized Prognostication of Kidney Transplant Candidates on the Waiting List: A Machine Learning Approach
Authors: Kawakita Satoru , Ranasinghe Omesh , Wood Emily , Beaumont Jennifer 
Published: November 2020

Abstract
BackgroundKidney transplantation (KT) remains the best available treatment for end-stage kidney disease. Currently, there is an unmet need for personalized clinical decision aids that help clinicians and KT candidates on the waitlist (WL) make informed decisions. To this end, we took a machine learning (ML)-based approach by using random survival forest with competing risks (RSF-CR) to develop a personalized prognostication system to predict the patient outcomes.MethodsWe obtained data from the Scientific Registry of Transplant Recipients (n=65,583) and developed RSF-CR models to predict the cumulative incidence functions (CIFs) of receipt of KT (CIFKT) and WL removal due to death or deteriorating condition (CIFdeath) at one year post-listing. Hyperparameter tuning was performed with the integrated Brier score of out-of-bag predicted CIFs as the performance metrics. Feature selection was performed based on variable importance computed by the optimized model. Final model performance was evaluated on a hold-out validation set via receiver operating characteristics (ROC) analysis, decision curve analysis, and additional performance measures (e.g. recall, precision, and F1).ResultsThe selected model revealed 16 and 18 prognostic factors for the prediction of CIFKT and CIFdeath respectively. The model also demonstrated good prognostic ability with an area under the ROC curve and an integrated Brier score of 73.4 [72.7, 74.0] and 16.1 [0.0, 40.5] for CIFKT and 75.0 [73.7, 76.4] and 4.6 [0.0, 11.4] for CIFdeath on a validation dataset. Dichotomization at selected threshold probabilities yielded a precision, recall, and F1 of 0.927, 0.824, and 0.873 for CIFKT and 0.975, 0.785, and 0.869 for CIFdeath.ConclusionsRSF-CR revealed new predictors of the potential outcomes at one year post-listing for KT candidates. While the class imbalance problem was observed, adjustment of the threshold probability allowed the model to become a binary classifier with outstanding performance. This work demonstrated the value of using RSF-CR in the identification of prognostic factors and personalized prediction of the outcomes for KT candidates on WL. More research is warranted to fully unlock the potential of ML in providing personalized medicine.
Novel and Recurrent BRCA1/BRCA2 Germline Mutations in Patients with Breast /Ovarian Cancer: A Series from the South of Tunisia
Authors: Ayed-Guerfali Dorra Ben , Kridis-Rejab Wala Ben , Ammous-Boukhris Nihel , Ayadi Wajdi , Charfi Slim , Khanfir Afef , Sellami-Boudawara Tahia , Frikha Mounir , Daoud Jamel , Mokdad-Gargouri Raja 
Published: November 2020

Abstract
Background: The incidence of breast/ovarian cancer is increasing in Tunisia especially in young women and mostly those with family history. However, the spectrum of BRCA mutations remains little explored in Tunisian patients in particular in the southern region. Methods: We sequenced the entire coding regions of BRCA1and BRCA2 genes using Next Generation Sequencing (NGS) in 134 selected patients with breast/ovarian cancer. Results: Among the 134 patients, 19 (14.17%) carried pathogenic mutations (10 are BRCA1 mutation carriers and 9 are BRCA2 mutation carriers) that are mainly frameshisft indel (76.9%). Interestingly, 5 out of the 13 variants (38.46%) were found at least twice in unrelated patients, as the c.1310-1313 delAAGA in BRCA2 and the c.5030_5033 delCTAA that has been identified in 4/98 BC patients and in 3/15 OC patients from unrelated families with strong history of cancer. Besides recurrent mutations, 6 variant (4 in BRCA1 and 2 in BRCA2) were not reported previously. Furthermore, 3 unrelated patients carried the VUS c.9976A>T, (K3326*) in BRCA2 exon 27. BRCA carriers correlated significantly with tumor site (p=0.029) and TNBC cases (p=0.008). In the groups of patients (31-40 y and 41-50 y), BRCA1 mutations occurred more frequently in patients with OC than those with BC, and conversely BRCA2 carriers are mostly affected with BC (p=0.001 and p=0.044 respectively).Conclusions: The overall frequency of the BRCA germline mutations was 14.17% in patients with high risk of breast /ovarian cancer. We identified recurrent mutations as the c.1310_1313 delAAGA in BRCA2 gene and the c.5030_5033 delCTAA in BRCA1 gene that were found in 4% and 20% of familial BC and OC respectively. Our data will contribute in the implementation of genetic counseling and testing for families with high-risk of breast/ovarian cancer.
Population-specific Interaction of the TRIM46&nbsp;/ MUC1&nbsp;Locus With Cigarette Smoking May Influence the Risk of Gout
Authors: Fanning Niamh Catherine , Topless Ruth K , Phipps-Green Amanda , Pearson John F , Cadzow Murray , Major Tanya J , White Douglas H , Dalbeth Nicola , Merriman Tony R , Stamp Lisa K 
Published: November 2020

Abstract
Background: Epidemiological and prospective studies suggest that current-smoking may be protective against developing gout and that smoking cessation may increase risk. The aim of this study was to identify interactions between smoking, genetic risk variants and the risk of gout. Methods: A cohort of 520 New Zealand (NZ) East and West Polynesian participants with and 629 without gout were included in our discovery analysis. A cohort of European participants (7576 with and 364,445 without) and South Asian participants (156 with and 7504 without gout) of the UK Biobank were used for replication. Five loci with previous evidence of smoking-influenced associations with serum urate levels were tested for their interaction with smoking status (current-smoker or ex-smoker vs. never-smoker as the reference group) in determining gout risk. The 5 loci were in genes, SLC2A9, ABCG2, GCKR, TRIM46, and HNF4G.Results: A non-additive interaction between genotype and smoking on gout risk was observed between ex-smoker status and TRIM46 (rs11264341) in NZ East and West Polynesian people [interaction ORmeta = 0.58 (0.37-0.92), p = 0.021], but not in European (OR = 0.94 (0.88-1.01), p = 0.10) or South Asian (0.96 (0.55-1.66), p = 0.88) participants of the UK Biobank. TRIM46 (rs11264341) interacted with current-smoker status in the Asian UK Biobank cohort [interaction OR = 2.68 (1.26-5.68), p = 0.010]. In smoking status subgroups the C-allele of rs11264341 increased risk of gout specifically in never-smokers (OR= 1.41 (1.04-1.92), p = 0.029) of the NZ Polynesian sample set and in current-smokers (2.39 (1.13-5.05), p=0.022) of the South Asian sample set. There was no evidence of interaction between smoking-status and the 4 remaining loci in 2 or more of the ancestral populations analysed in this study.Conclusion: We provide evidence for a non-additive interaction between TRIM46 (rs11264341) and smoking behaviour associated with gout risk in a NZ Polynesian sample set and a South Asian sample set, but not in a European sample set. MUC1, that encodes a transmembrane mucin in the lungs whose expression and function is affected by cigarette smoke, is a possible candidate gene at the TRIM46 locus.
Deep Learning Based Image Recognition for 5G Smart IoT Applications
Authors: Li Jing , li Xinfang , Ning Yuwen 
Published: November 2020

Abstract
With the advent of the 5G era，the development of massive data learning algorithms and in-depth research on neural networks, deep learning methods are widely used in image recognition tasks. However, there is currently a lack of methods for identifying and classifying efficiently Internet of Things (IoT) images. This paper develops an IoT image recognition system based on deep learning, i.e., uses convolutional neural networks (CNN) to construct image recognition algorithms, and uses principal component analysis (PCA) and linear discriminant analysis (LDA) to extract image features, respectively. The effectiveness of the two PCA and LDA image recognition methods is verified through experiments. And when the image feature dimension is 25, the best image recognition effect can be obtained. The main classifier used for image recognition in the IoT is the support vector machine (SVM), and the SVM and CNN are trained by using the database of this paper. At the same time, the effectiveness of the two for image recognition is checked, and then the trained classifier is used for image recognition. It is found that a CNN and SVM-based secondary classification IoT image recognition method improves the accuracy of image recognition. The secondary classification method combines the characteristics of the SVM and CNN image recognition methods, and the accuracy of the image recognition method is verified to provide an effective improvement through experimental verification.
Development and Validation of a Discrimination Model Between Primary PLA2R-Negative Membranous Nephropathy and Minimal Change Disease Confirmed by Renal Biopsy
Authors: Wu Feng , Zhang Yiding , Cui Wen , Dong Yijun , Geng Yingyang , Liu Changhao , Li Zemeng , Xie Yandong , Cai Xiaojing , Shang Jin , Xiao Jing , Zhao Zhanzheng 
Published: November 2020

Abstract
BackgroundMembranous nephropathy (MN) and minimal change disease (MCD) are two common causes leading to nephrotic syndrome (NS). They have similar clinical feature but different treatment strategy and prognosis. M-type phospholipase A2 receptor (PLA2R) is considered as a specific marker of membranous nephropathy. However, its sensitivity is only about 70%. Therefore, there is a lack of effective and noninvasive tools to distinguish PLA2R-negative MN and MCD patients without renal biopsy. We aim to develop a discrimination model using noninvasive parameters for distinguishing the two diseases and support immediate treatment before result of renal biopsy.MethodsA total 949 patients who were pathologically diagnosed as idiopathic MN or primary MCD in the First Affiliated Hospital of Zhengzhou University from January 2017 to August 2019 were enrolled in this study, including 805 idiopathic MN (605 PLAR2-positive MN and 200 PLA2R-negative MN) and 144 primary MCD. Based on the basic information and laboratory examination of 200 PLA2R-negative MN and 144 MCD, we used univariate and multivariate logistic regression analysis to select the relevant variables and develop the discrimination model. ROC curves and calibration curves were used to evaluate the diagnostic ability and calibration ability of the model. The decision curve was used to show the net benefit. We also tested the effectiveness of our model in all 949 patients.ResultsA novel model that included age, albumin, urea, high density lipoprotein, urea and red blood cell count was established for PLA2R-negative MN and MCD. The discrimination model has good differential capability (an AUC of 0.889 in training group and an AUC of 0.920 in test group) and calibration capability. When testing in all 949 patients, our model also showed good discrimination ability for all idiopathic MN and MCD.Conclusion﻿We constructed a discrimination model with high diagnostic effectiveness for PLA2R-negative MN and MCD. The model could also be used for all idiopathic MN and MCD patients.