bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial Intelligence to Predict Mortality in Critically ill COVID-19 Patients Using Data from the First 24h: A Case Study from Lombardy Outbreak
Authors: Greco Massimiliano , Angelotti Giovanni , Caruso Pier Francesco , Zanella Alberto , Stomeo Niccolò , Costantini Elena , Protti Alessandro , Pesenti Antonio , Grasselli Giacomo , Cecconi Maurizio 
Published: May 2021

Abstract
Introduction: SARS-CoV-2 infection was first identified at the end of 2019 in China, and subsequently spread globally. COVID-19 disease frequently affects the lungs leading to bilateral viral pneumonia, progressing in some cases to severe respiratory failure requiring ICU admission and mechanical ventilation. Risk stratification at ICU admission is fundamental for resource allocation and decision making, considering that baseline comorbidities, age, and patient conditions at admission have been associated to poorer outcomes. Supervised machine learning techniques are increasingly diffuse in clinical medicine and can predict mortality and test associations reaching high predictive performance. We assessed performances of a machine learning approach to predict mortality in COVID-19 patients admitted to ICU using data from the Lombardy ICU Network.Methods: this is a secondary analysis of prospectively collected data from Lombardy ICU network. To predict survival at 7-,14- and 28 days we built two different models; model A included patient demographics, medications before admission and comorbidities, while model B also included the data of the first day since ICU admission. 10-fold cross validation was repeated 2500 times, to ensure optimal hyperparameter choice. The only constrain imposed to model optimization was the choice of logistic regression as final layer to increase clinical interpretability. Different imputation and over-sampling techniques were employed in model training.Results 1503 patients were included, with 766 deaths (51%). Exploratory analysis and Kaplan-Meier curves demonstrated mortality association with age and gender. Model A and B reached the greatest predictive performance at 28 days (AUC 0.77 and 0.79), with lower performance at 14 days (AUC 0.72 and 0.74) and 7 days (AUC 0.68 and 0.71). Male gender, age and number of comorbidities were strongly associated with mortality in both models. Among comorbidities, chronic kidney disease and chronic obstructive pulmonary disease demonstrated association. Mode of ventilatory assistance at ICU admission and Fraction of Inspired oxygen were associated with mortality in model B.Conclusions Supervised machine learning models demonstrated good performance in prediction of 28-day mortality. 7-days and 14-days predictions demonstrated lower performance. Machine learning techniques may be useful in emergency phases to reach higher predictive performance with reduced human supervision using complex data.
Clinical Outcomes of Atypical Lipomatous Tumor/Well-Differentiated Liposarcoma of the Extremities: Analysis of Recurrence Factors
Authors: Zeniya Toshiki , Emori Makoto , Tsuchie Hiroyuki , Nagasawa Hiroyuki , Iba Kousuke , Mizushima Emi , Keira Yoshiko , Shimizu Junya , Murahashi Yasutaka , Teramoto Atsushi , Miyakoshi Naohisa , Sugita Shintaro , Hasegawa Tadashi , Shimada Yoichi , Yamashita Toshihiko 
Published: May 2021

Abstract
Background: Atypical lipomatous tumors/well-differentiated liposarcomas (ALT/WDLPS) are low-grade, slow-growing, and locally aggressive tumors. We investigated clinical outcomes and recurrence factors for ALT/WDLPS of the extremities.Patients and Methods: The variables were evaluated as potential recurrence factor using Fisher’s exact test. The 5-year recurrence-free survival (RFS) rate was calculated using the Kaplan-Meier method, and differences in survival were assessed using a log-rank test in univariate analyses. Results: Sixty-two patients were identified, including 29 men and 33 women. The median age was 63.7 years (range, 34–82 years). The average maximum tumor diameter was 15.9 cm (range, 5–28 cm). The maximum tumor diameter (≥20 cm) was significantly associated with local recurrence (p=0.049). Ten patients (16.1%) developed local recurrence, and the mean time to recurrence was 48.4 months (range, 5–161 months).Conclusions: Tumor diameter ≥20 cm was identified as a risk factor for recurrence.
Effects of Systemic Diseases on Graft Preparation in Descemet Membrane Endothelial Keratoplasty
Authors: Özkan Burak , Koçluk Yusuf , Kasım Burcu 
Published: May 2021

Abstract
Purpose: To evaluate the effects of the systemic diseases and drugs of the donor on Descemet’s membrane (DM) graft preparation.Methods: 78 corneas of 58 donors, of whom the DM grafts were used in Descemet’s membrane endothelial keratoplasty (DMEK) surgery, between January 2018 – January 2020, were enrolled in this retrospective study. The hospital records of the donors were analyzed. Age, gender, blood type, systemic diseases, and drugs; complete blood count, biochemistry panel for liver and kidney functions in the last 48 hours, and the drugs used in the hospital, if any, in the last 24 hours were recorded. The grafts with tears that occurred while preparation, were included in group 1, and the successful grafts with no tears were included in group 2.Results: There were no statistically significant differences in the characteristics of the donors between groups. However, the breast cancer and the use of sevelamer were found to be significantly higher in group 1 (p=0.010, p=0.033, respectively)Conclusion: Although diabetic donors have been reported to be inappropriate candidates for the preparation of DM grafts for DMEK, most of the donors with several systemic diseases including diabetes can be used in DMEK surgery, with the right technique in DM graft preparation.
Numerical Investigation of Tunnel Face Sability using Forepoling or Fiberglass Nails
Authors: GEORGIOU DIMITRIOS , KAVVADAS MICHAEL , KALOS ALEXANDROS 
Published: May 2021

Abstract
Pre-support of tunnel excavation faces using fiberglass nails or forepoling umbrellas aims to improve face stability in cases where an unsupported excavation face will develop uncontrollably large face extrusion, leading to face instability. The paper presents the results of a large set of parametric 3D numerical analyses of tunnel face excavation by the Finite Element Code Simulia Abaqus, using various degrees of reinforcement by fiberglass nails or forepoling umbrellas. The analyses use the average face extrusion as a measure of face stability, considering that face instability is associated with large face extrusions while the safety factor against face instability can be correlated with lower face extrusions in case of pre-supported tunnel faces. The results of the analyses are normalized and a set of semi-empirical formulae and design graphs are produced to calculate the safety factor of supported tunnel faces against instability and other useful quantities in tunnel design (average face extrusion, volume loss and deconfinement coefficient) as a function of ground strength, overburden depth and amount of face reinforcement. The analyses show that tunnel face reinforcement with FG nails is much more effective and less costly in securing face stability than the use of forepoling umbrellas. It is shown that even a coarse grid of FG nails can achieve better results than very heavy forepoling, and the difference in effectiveness is more pronounced in weaker ground and or deeper tunnels.
Pitchfork and Hopf Bifurcations of Geared Systems in Permanent Contact Regime
Authors: Azimi Mohsen 
Published: May 2021

Abstract
Gears are known as important mechanical parts with various industrial applications. Many researchers investigated the complex nonlinear behavior of the geared systems by studying the effect of the clearance between the gears in mesh. This is while some studied the effect of both nonlinear suspension and clearance on nonlinear characteristics of such systems. Most of these studies are under assumption that the system operates under lightly loaded operational condition, where the separation of the teeth in mesh occurs. Alternatively, in this work, it is assumed that the transmitting load is big enough that gears in mesh do not separate and consequently the clearance between the teeth do not participates in the dynamic response of the system. Then analytical and numerical techniques are used to investigate the effect of nonlinear suspension on the dynamic behavior of the system. The results show that nonlinearity of the suspension has a great in uence on the creation of the nontrivial equilibria or limit cycle within the unstable regions, which for the right range of the parameters, can affect the rate of the amplitude detonation and stabilization of the system.
Statistical Feature–Based Steganalysis for Pixel-Value Differencing Steganography
Authors: Lin Wen-Bin , Lai Tai-Hung , Chang Ko-Chin 
Published: May 2021

Abstract
The security and embedding capacity of pixel-value differencing (PVD) steganography is superior to that of least significant bit replacement steganography. Several studies have proposed extended PVD steganography methods that use the original concept of PVD steganography. The majority of the studies have verified their security against regular-singular detection analysis or pixel difference histogram attacks. Weighted stego image steganalysis is the state-of-the-art technology for PVD steganography. This study proposed a suitable parameter for the estimator based on different relative embedding ratios and the size of normal embedding blocks. The experimental results revealed that the proposed technology does not require advance knowledge of the original image. In addition, the proposed method is accurate and precise at any embedding ratio. In the future, this method may be utilized to analyze the security of extended PVD steganography.
Microplastic Exposure Across Trophic Levels: Effects on the Host Microbiota of Freshwater Organisms
Authors: Varg Javier Edo , Outomuro David , Kunce Warren , Kuehrer Lukas , Svanbäck Richard , Johansson Frank 
Published: May 2021

Abstract
BackgroundMicroplastics are a pervasive pollutant widespread in sea- and freshwater from anthropogenic sources, and together with the presence of pesticides, they can have physical and chemical effects on aquatic organisms and on their microbiota. Few studies have explored the combined effects of microplastics and pesticides on the host microbiome, and more importantly, the effects across multiple trophic levels. In this work, we studied the effects of exposure to microplastics and the pesticide deltamethrin on the diversity and abundance of the host microbiome across a three-level food chain: daphnids-damselfly-dragonflies. Daphnids were the only organism exposed to 1µm microplastic beads, and they were fed to damselfly larvae. Those damselfly larvae were exposed to delthametrin, and then fed to the dragonfly larvae. The microbiotas of the daphnids, damselflies and dragonflies were analyzed. ResultsOur results suggest that the exposure to microplastics and deltamethrin had negative carry-over effects on the diversity and abundance of the microbiome across the three trophic levels. Moreover, the exposure to deltamethrin on the damselflies negatively affected their survival rate in the presence of the dragonfly predator, but no such effects were found on damselflies exposed to only microplastics. Conclusions﻿Our study highlights the importance of evaluating ecotoxicological effects at the community level. Importantly, the indirect exposure to microplastics and pesticides through diet can potentially have bottom-up effects in the trophic webs.
Clinical outcome of Laparoscopic and Robot-assisted Radical Cystectomy for Bladder Cancer in a Retrospective Study
Authors: Bai YuChen , Wang Shuai , Zheng Wei , Quan Jing , Wei Fei , Zhang Qi , Qi XiaoLong , Zhang DaHong 
Published: May 2021

Abstract
Background: With the rapid development of surgical technics and instruments, more and more bladder cancer patients are being treated by laparoscopic radical cystectomy (LRC) and robot-assisted radical cystectomy (RARC) .The aim of this retrospective study was to compare the perioperative and long-term outcomes of patients who underwent cystectomy by these two surgical approaches. Methods: We performed a retrospective review of the prospectively collected database of our hospital to identify patients with clinical stage Ta/T1/Tis to T3 who underwent RARC and LRC. Perioperative outcomes, recurrence, and overall survival (OS) were analyzed. Results: From March 2010 to December 2019, there were total of 218 patients, which including 82(38%) patients with LRC and 136(62%) patients with RARC. No perioperative death was observed in both groups. Tumor recurrence, death from any causes, and cancer-specific death occurred in 77, 55, and 39 patients respectively. The 5-year DFS, OS, and CSS rates for all included patients were 55.4%, 62.4%, and 66.4%, respectively. There were no significantly statistically differences between the RARC group and the LRC group for number of lymph nodes harvested, positive lymph node rate, positive margin rate and postoperative pathological stage (all P>0.05). Patients undergoing RARC had lower median estimated blood loss (180mL vs. 250 mL; P 0.015) and 90-days postoperative complications (30.8% vs. 46.3%; P 0.013) than LRC.Conclusions: For selected patients with RARC and LRC, both were safe and effective with a low complication rate and similar long-term outcome compared two groups. Moreover, the robotic approach resulted in lower median estimated blood loss and better outcome in postoperative complications.
A Phase II Study of Sequential Treatment With Anthracycline and Taxane Followed By Eribulin in Patients With HER2-Negative, Locally Advanced Breast Cancer (JBCRG-17)
Authors: Fukada Ippei , Ito Yoshinori , Kondo Naoto , Ohtani Shoichiro , Hattori Masaya , Tokunaga Eriko , Matusnami Nobuki , Mashino Kohjiro , Kosaka Taijiro , Tanabe Masahiko , Yotusmoto Daisuke , Yamanouchi Kosho , Sawaki Masataka , Kashiwaba Masahiro , Kawabata Hidetaka , Kuroi Katsumasa , Morita Satoshi , Ohno Shinji , Toi Masakazu , Masuda Norikazu 
Published: May 2021

Abstract
PurposeThe sequence of taxanes (T) followed by anthracyclines (A) as neoadjuvant chemotherapy (NAC) has been the standard of care for almost 20 years for locally advanced breast cancer (LABC). Sequential administration of eribulin (E) following A/T could provide a greater response rate for women with LABC.MethodsIn this single-arm, multicenter, Phase II prospective study, the patients received 4 cycles of the FEC regimen and 4 cycles of taxane. After the A/T-regimen, 4 cycles of E were administered followed by surgical resection. The primary endpoint was the clinical response rate. Eligible patients were women aged 20 years or older, with histologically confirmed invasive breast cancer, clinical Stage IIIA (T2-3 and N2 only), Stage IIIB, and Stage IIIC, HER2-negative.ResultsA preplanned interim analysis aimed to validate the trial assumptions was conducted after treatment of 20 patients and demonstrated that clinical progressive disease (cPD) rates in the E phase were significantly higher (30%) than assumed. Therefore, the Independent Data Monitoring Committee recommended stopping the study. Finally, 53 patients were enrolled, and 26 patients received the A/T/E-regimen. The overall observed clinical response rate (RR) was 73% (19/26); RRs were 77% (20/26) in the AT phase and 23% (6/26) in the E phase. Thirty percent (8/26) of patients had PD in the E phase, 6 of whom had achieved cCR/PR in the AT phase. Reported grade >3 AEs related to E were neutropenia (42%), white blood cell count decrease (27%), febrile neutropenia (7.6%), weight gain (3.8%), and weight loss (3.8%)ConclusionSequential administration of eribulin after the A/T-regimen provided no additional effect for LABC patients. Future research should continue to focus on identifying specific molecular biomarkers that can improve response rates.
Detection of SFTS Virus RNA and Total Antibodies in Wild Animals, Jiangsu, China, 2014-2019
Authors: Liang Shuyi , Li Zhifeng , Zhang Nan , Wang Xiaochen , Hu Jianli 
Published: May 2021

Abstract
Background Severe fever with thrombocytopenia syndrome (SFTS) is a novel infectious disease caused by severe fever with thrombocytopenia syndrome virus (SFTSV). Currently, SFTS is endemic to some areas in China, and wild animals are considered to play important roles in the circulation of SFTSV in the environment. Wild animals monitoring for SFTSV has been fulfilled since 2014 in Jiangsu Province. We studied the results of the detection to provide basic data for better diagnosis of wild animals. Methods This research was conducted in Jiangsu Province from 2014 to 2019. Sera of wild animals (Rodents, pheasants and hedgehogs) were collected to detect SFTSV both RNA and total antibodies by qRT-PCR and enzyme-linked immunosorbent assay. Statistical analysis was performed by using SPSS 25.0 (Chicago, IL, USA).Results A total of 95.8% (1298/1355) of the specimens had the same SFTSV RNA and total antibodies detection results. However, there was a significant difference between the detection rates of SFTSV RNA and total antibodies, and the detection consistency was very poor. The detection rate of SFTSV total antibodies was highest in hedgehogs(19.54%).Conclusions SFTSV total antibodies testing was preferred method during wild animals surveillance. Also, hedgehog could be a competent reservoir for SFTSV.
A Novel Signature Based on Pyroptosis-Related Genes for Predicting Breast Cancer
Authors: Shen Shuang , Chen Xin , Qu Rui , Guo Youming , Su Yingying , Jiang Hang , Luo Libo 
Published: May 2021

Abstract
Background: Breast cancer (BC) surpassed lung cancer as the most frequent malignant tumour in women. In recent years, pyroptosis has revealed itself as an inflammatory form of programmed cell death. However, it is unclear as to the expression of genes associated with pyroptosis in BC and its relationship to prognosis. Results: In this study, we identified 31 pyroptosis regulators that are differentially expressed between BC and normal breast. The differently expressed genes (DEG) allow BC patients to be divided into three subtypes. Through single-factor and multi-factor COX regression and the application of least absolute contraction and selection operator (LASSO) Cox regression method, the survival prognostic value of each gene related to pyroptosis in The Cancer Genome Atlas (TCGA) cohort was evaluated, and a 4-gene signature was constructed. BC patients of the TCGA cohort are divided into low-risk or high-risk groups by risk score. The survival of the low-risk group was significantly higher than the high-risk group (P <0.001). Using the median risk score from the TCGA cohort, BC patients from the Gene Expression Omnibus (GEO) cohort were divided into two risk sub-groups and similar conclusions were drawn. In combination with clinicopathological characteristics, the risk score is an independent predictive factor of OS in BC patients. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) indicated that the high-risk group's immune genes were enriched and immune status was reduced. Conclusions: In conclusion, pyroptosis-related genes are important for tumour immunity and can be used to predict the prognosis of BC.
Routing Algorithms as Tools for Integrating Social Distancing with Emergency Evacuation
Authors: Tsai Yi-Lin , Rastogi Chetanya , Kitanidis Peter K. , Field Christopher B. 
Published: May 2021

Abstract
We explore the implications of integrating social distancing with emergency evacuation, as would be expected when a hurricane approaches a city during the COVID-19 pandemic. Specifically, we compare DNN (Deep Neural Network)-based and non-DNN methods for generating evacuation strategies that minimize evacuation time while allowing for social distancing in emergency vehicles. A central question is whether a DNN-based method provides sufficient extra routing efficiency to accommodate increased social distancing in a time-constrained evacuation operation. We describe the problem as a Capacitated Vehicle Routing Problem and solve it using a non-DNN solution (Sweep Algorithm) and a DNN-based solution (Deep Reinforcement Learning). The DNN-based solution can provide decision-makers with more efficient routing than the typical non-DNN routing solution. However, it does not come close to compensating for the extra time required for social distancing, and its advantage disappears as the emergency vehicle capacity approaches the number of people per household.
Fat-Burning or Fat-Shaming? Theme and Community Overlap Between Online, Weight-Stigmatizing and Exercise-Promoting Networks.
Authors: Rojas-Sánchez Ahuitz , Harris Jenine K. , Sarrazin Philippe , Chalabaev Aïna 
Published: May 2021

Abstract
Purpose: This study aimed to determine if networks of users consistently posting about exercise and fat exist and overlap on social media sites.Method: We collected 3,772,507 posts from Twitter that included the words “fat” and “exercise”. Using network structure methods, we identified communities of interconnected users and overlaps between those tweeting “fat” and those tweeting “exercise”. Results: Common word pairings were identified using Natural Language Processing (NLP). Networks of users consistently talking about exercise (n=3,573) and fat (n=2,007) were found on Twitter. An increased mean total-degree and reduced average path length indicate that the fitness-talk network serves as a connecting bridge between highly scattered communities of the weight-talk network. Conclusion: We identified groups on Twitter dedicated to consistently producing weight stigmatizing content and promoting exercise with weight-loss messages. These groups partially overlap with pro-health groups which could lead to users looking for exercise advice in Twitter to find themselves immersed in a stigmatizing network.
Assessment of Bidirectional Relationships Between 98 Genera of the Human Gut Microbiota and Amyotrophic Lateral Sclerosis: A 2-Sample Mendelian Randomization Study
Authors: Zhang Linjing , Zhuang Zhenhuang , Zhang Gan , Huang Tao , Fan Dongsheng 
Published: May 2021

Abstract
BackgroundGrowing evidence suggests a mutual interaction between gut microbiome alterations and ALS pathogenesis. However, previous studies were susceptible to potential confounding factors and reverse causation bias, likely leading to inconsistent and biased results. Therefore, to decipher the potentially mutual relationship between gut microbiota and ALS, we used a bidirectional two-sample MR approach to examine the associations between the gut microbiome and ALS. Effects of potential metabolites on ALS were also estimated in MR design.ResultsUsing the inverse variance-weighted method, OTU10032 unclassified Enterobacteriaceae species-level OTU and unclassified Acidaminococcaceae were associated with a higher risk of ALS (per relative abundance: OR, 1.04; 95% CI, 1.01–1.07; P = 0.011 and OR, 1.02; 95% CI, 1.01–1.04; P = 0.009, respectively). Importantly, Gamma-Glu-Phe was showed potential deleterious effects on the risk of ALS (genetically predicted per a 1-standard deviation increase in the level of Gamma-Glu-Phe: OR, 1.96; 95% CI, 1.50–2.55; P = 0.012). Sensitivity analysis of the two candidate genera and metabolites using the MR-Egger and weighted-median methods produced similar estimates, and no horizontal pleiotropy or outliers were observed. Intriguingly, genetically predicted ALS was associated with an increase in the relative abundance of OTU4607_Sutterella (per 1-unit higher log odds: β, 2.23; 95% CI, 1.27–3.18; P = 0.020) and Lactobacillales_ORDER (per 1-unit higher log odds: β, 0.51; 95% CI, 0.09–0.94; P = 0.019).ConclusionsOur findings provide novel evidence supporting the bidirectional relationship between the gut microbiota and ALS and highlight that a transsynaptic, glutaminergic, excitotoxic mechanism could provide a pathogenic basis for ALS. These results may contribute to designing microbiome- and microbiome-dependent metabolite interventions in future ALS clinical trials.