bluuebunny/crossref_metadata_2025_split huggingface dataset:
PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~200,000 patients
Authors: Giardiello Daniele , Hooning Maartje J , Hauptmann Michael , Keeman Renske , Heemskerk-Gerritsen Bernadette A. M , Becker Heiko , Blomqvist Carl , Bojesen Stig E , Bolla Manjeet K , Camp Nicola J , Czene Kamila , Devilee Peter , Eccles Diana M , Fasching Peter A , Figueroa Jonine D , Flyger Henrik , García-Closas Montserrat , Haiman Christopher A , Hamann Ute , Hopper John L , Jakubowska Anna , Leeuwen Floor E , Lindblom Annika , Lubiński Jan , Margolin Sara , Martinez Maria Elena , Nevanlinna Heli , Nevelsteen Ines , Pelders Saskia , Pharoah Paul D.P , Siesling Sabine , Southey Melissa C , Hout Annemieke H van der , Hest Liselotte P van , Chang-Claude Jenny , Hall Per , Easton Douglas F , Steyerberg Ewout W , Schmidt Marjanka K 
Published: June 2022

Abstract
Background:
Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.
Methods:
We included data from 207,510 invasive breast cancer patients participating in 23 studies. 8,225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent Area Under the Curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.
Results:
The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI):0.56–0.74) versus 0.63 (95%PI:0.54–0.71). PredictCBC-2.0 was well-calibrated with an observed/expected (O/E) ratio at 10 years of 0.92 (95%PI:0.34–2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed potential clinical utility of PredictCBC-2.0 between thresholds of 4–12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.
Conclusions:
Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision making towards CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.
Evaluation of plasma levels of iron, copper, zinc, selenium and some transporter proteins in patients with IBD compared to IBS
Authors: shokri Behnosh , Kopi Tayebeh Azramezani , Alhooei Saman , parsian hadi , Kashifard Mehrdad , Mosapour Abbas , gholinia hemmat , Halalkhor Sohrab 
Published: June 2022

Abstract
Background and purpose: Inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are both chronic gastrointestinal diseases with different pathophysiology but similar symptoms. In this study, we intend to investigate the pattern of changes in plasma levels of Fe, Zn, Se, Cu and ferritin, transferrin and ceruloplasmin, as well as oxidative and antioxidant capacity in IBD patients compared to IBS and the healthy group.Methods: This case-control study was performed on three groups of 30 patients with IBD and IBS and healthy individuals. ELISA method was used to measure the levels of ferritin and total oxidant, atomic absorption method for selenium and copper, and spectrophotometry for iron, zinc, transferrin and ceruloplasmin.Results: According to the results of this study, we showed that the levels of oxidative stress and transferrin, selenium, and zinc in men with IBD compared to IBS and control, showed a significant difference while in women no significant changes were observed in other factors except transferrin and Zn. There was also a significant increase in MDA, a decrease in TAC and a decrease in zinc and transferrin in the entire population with IBD. Also, lower levels of Fe and Se were observed in IBD patients compared to IBS and the healthy group. However, this difference was not statistically significant.Conclusion: The results of this study showed that the study of some trace elements may help us to find a more effective and easier method in diagnosing and differentiating people with IBD and IBS.
Prognostic Utility of SOX2, STAT3, and CD44high/CD24low Expression in Penile Cancer
Authors: Barros Felipe Dubourcq , Torres Leuridan Cavalcante , Araujo Carolline , Dubourcq Beatriz Cavalcanti , Dubourcq Luis Cavalcanti , Marinho Felipe da Silva , Guimaraes Gustavo 
Published: June 2022

Abstract
Purpose
Penile cancer has a high incidence in developing countries. The standard treatment is removal of the primary tumor and, when necessary, inguinal lymphadenectomy. Currently the most important prognostic factor is lymph node disease, however the available staging methods are inaccurate, and the high morbidity rate of lymphadenectomy has stimulated the study of predictive biomarkers of lymph node metastasis for selecting the patients who need lymphadenectomy. SOX2, STAT3 and CD44high/CD24low were chosen because they have provided good predictive results in other squamous cell carcinoma (SCC), although there are no studies for penile cancer. Thus, the expression of SOX2, STAT3, CD24+, and CD44 + in the penile cancer tumor microenvironment was investigated for correlation with tumor behavior in SCC.
Methods
This observational, prospective, translational study included 34 men and investigated the expression of SOX2, STAT3, CD24+, and CD44 + in tumor tissue by flow cytometry.
Results
The median age of the 38 evaluated patients with penile cancer was 61 (37–80) years. Most patients presented a tumor located on the glans penis (82.3%), with the usual histological type (79.4%) and 61.7% of patients presented stage pT2. No metastasis was found in 85.3% of patients. The expression of SOX2, STAT3 and CD44high/CD24low in the microenvironment of penile SCC treated with lymphadenectomy was significantly associated with aggressive tumor behavior (p < 0.05). STAT3 expression shows discrepant points when evaluated in context of angiolymphatic vascular invasion.
Conclusion
SOX2, STAT3 and CD44high/CD24low in penile SCC can be indicators of prognosis, allowing for selection of more aggressive treatment when necessary.
Divergent Directed Evolution of a TetR-type Repressor Towards Aromatic Molecules
Authors: Nasr Mohamed , Martin Vincent , Kwan David 
Published: June 2022

Abstract
Reprogramming cellular behaviour is one of the hallmarks of synthetic biology. To this end, prokaryotic allosteric transcription factors (aTF) have been repurposed as versatile tools for processing small molecule signals into cellular responses. Expanding the toolbox of aTFs that recognize new inducer molecules is of considerable interest in many applications. Here, we first establish a resorcinol responsive aTF-based biosensor in Escherichia coli using the TetR-family repressor RolR from Corynebacterium glutamicum. We then perform an iterative walk along the fitness landscape of RolR to identify new inducer specificities, namely catechol, methyl catechol, caffeic acid, protocatechuate, L-DOPA, and the tumour biomarker homovanillic acid. Finally, we demonstrate the versatility of these engineered aTFs by transplanting them into the model eukaryote Saccharomyces cerevisiae. This work provides a framework for efficient aTF engineering to expand ligand specificity towards novel molecules on laboratory timescales, which, more broadly, is invaluable across a wide range of applications such as protein and metabolic engineering, as well as point-of-care diagnostics.
Analyzing and Predicting Success in Music
Authors: Kang Inwon , Manduluk Michael , Szymanski Boleslaw K. 
Published: June 2022

Abstract
The emergence of streaming services, e.g., Spotify, has changed the way people listen to music and the way musicians achieve fame and success. Classical music has been the backbone of Western media for a long time, but Spotify has introduced the public to a much wider variety of music, also opening a new venue for musicians to gain exposure. In this paper, we use open-source data from Spotify and Musicbrainz databases to construct collaboration-based and genre-based networks. Our goal is to find the correlation between various features of each artist, their current stage of a career, and the level of their success in the music field. We build regression models using XGBoost to first analyze correlation between features provided by Spotify. We then analyze the correlation between the digital music world of Spotify and the more traditional world of Billboard charts. We find that within certain bounds, machine learning techniques such as decision tree classifiers and Q-based models perform quite well on predicting success of musicians from the data on their early careers. We also find features that are highly predictive of the artist’s success. The most prominent among them are artists’ collaboration counts and the span of their career. Our findings also show that classical musicians are still very centrally placed in the general, genre agnostic network of musicians. Using these models and success metrics, we make suggestions that aspiring musicians can rely on considering which aspects of their career should be improved to increase their success measures in both Spotify and Billboard charts.
Optimization of simultaneous removal of phosphate and nitrate in synthetic wastewater by enhanced electrocoagulation process
Authors: Torabinejad-yazdi Shima , Delnavaz Mohammad 
Published: June 2022

Abstract
The presence of pollutants such as nitrate and phosphate compounds affects the quality of water resources. This study aims to investigate the simultaneous removal of nitrate and phosphate in a batch reactor using an enhanced electrocoagulation process. Initial concentration, current density, pH, and time were the chosen effective parameters considered in 5 levels. Their effect on the removal efficiency of phosphate and nitrate was evaluated. Experiments were designed by the response surface method (RSM) to save time and costs. For this purpose, first, 30 experiments were modeled by design expert software, and then optimal conditions were determined for variables. The optimal conditions were obtained by the following items: current density 36.5 A/m2, initial concentration 140 mg/L, pH 6, and time 65min. These conditions led to removing 77% of nitrate and 98% of phosphate. Finally, the effect of electrode coating with ZnO nanoparticles performed by the sol-gel method under optimal conditions was considered. Cyclic voltammetry (CV) was used to evaluate the impact of the coating layer. The modified electrode by nanoparticles provides a larger surface area which consumes less energy than a simple electrode.
Dynamical Model of Mild Atherosclerosis: Applied Mathematical Aspects
Authors: Mukherjee Debasmita , Muni Sishu Shankar , Fatoyinbo Hammed Olawale 
Published: June 2022

Abstract
Atherosclerosis is a chronic inflammatory disease occurs due to plaque accumulation in the inner artery wall. In atherosclerotic plaque formation monocytes and macrophages play a significant role in controlling the disease dynamics. In the present article, the entire biochemical process of atherosclerotic plaque formation is presented in terms of an autonomous system of nonlinear ordinary differential equations involving concentrations of oxidized low-density lipoprotein (LDL), monocytes, macrophages, and foam cells as the key dependent variables. To observe the capacity of monocytes and macrophages the model has been reduced to a two-dimensional temporal model using quasi steady state approximation theory. Linear stability analysis of the two-dimensional ordinary differential equations (ODEs) model has revealed the stability of the equilibrium points in the system. We have considered both one- and two- parameter bifurcation analysis with respect to parameters associated to the rate at which macrophages phagocytose oxidised LDL and the rate at which LDL enters into the intima. The bifurcation diagrams reveal the oscillating nature of the curves representing concentration of monocytes and macrophages with respect to significant model parameters. We are able to find the threshold values at which the plaque accumulation accelerates in an uncontrollable way. Further to observe the impact of diffusion, a spatiotemporal model has been developed. Numerical investigation of the partial differential equations (PDEs) model reveals the existence of travelling wave in the system which ensures the fact that the development of atherosclerotic plaque formation follows reaction-diffusion wave.
Role of nano selenium in alleviating the effects of salt stress in date palm trees (Phoenix dactylifera L.). A Fourier Transform Infrared (FTIR) Spectroscopy Study.
Authors: Mahdi Ali S. , Abd Abdulkareem M , Awad khairullah 
Published: June 2022

Abstract
The current study used the Fourier Transform Infrared (FTIR) spectroscopy to determine the corresponding changes caused by salt-induced biochemical changes at different NaCl concentrations (2.5 as control level, 5, 10, and 20 ds.m− 1). FTIR also determines the potential role of selenium nanoparticles (Se NPs) at two concentrations (80 and 160 ppm) in alleviating salinity stress on date palm (Phoenix dactylifera L.) trees. Notably, the study found the appearance of a new peak at 2850 cm− 1 in the lipid region (2800–3000 cm− 1) when date palm trees were exposed to salinity and tested at all levels. This peak was not seen in the control treatment or when salinity was combined with foliar spraying of Se NPs at the two tested concentrations (80 and 160 ppm). Furthermore, a clear and distinct peak at 1735 cm− 1 was only seen in plants exposed to salinity at 10 or 20 ds.m− 1. This peak was attributed to membrane lipid compounds that contain carbonyl-ester groups. In addition, the findings demonstrate that the treatments from various studies affected the secondary structure of proteins (1500–1800 cm− 1) and carbohydrates (1200–1500 cm− 1), and this was evident by the appearance and disappearance of some characteristic peaks in these regions.
Chronic ER stress promotes cGAS/mtDNA-induced autoimmunity via ATF6 in myotonic dystrophy type 2
Authors: Günther Claudia , Rösing Sarah , Ullrich Fabian , Meisterfeld Susann , Schmidt Franziska , Eberl Nadia , Wegner Julia , Schlee Martin , Wieland Anja , Hilbig Daniel , Reuner Ulrike , Mirtschink Peter , Drukewitz Stephan , Rapp Alexander , Zillinger Thomas , Beissert Stefan , Paeschke Katrin , Hartmann Gunther , Bartok Eva 
Published: June 2022

Abstract
Nucleic acid accumulation in repeat expansion disease poses multiple challenges to cellular integrity. Myotonic dystrophy type 2 (DM2) results from large CCTG repeats in the CNBP gene leading to myopathy and an increased prevalence of autoimmunity. Here, we observed that DM2 patients exhibited a type-I interferon signature in blood and cultured fibroblasts. RNA repeat accumulation was prevalent in the cytosol of DM2 patient fibroblasts, facilitating repeat-associated non-AUG translation. The ensuing chronic endoplasmic reticulum (ER) stress response led to an ATF6-controlled induction of type-I IFN dependent on the cGAS/STING pathway. Recapitulating chronic ER stress in the monocytic THP-1 cell line revealed its dependence on mitochondrial DNA (mtDNA). Correspondingly, mitochondrial stress and cytosolic leakage of mtDNA was observed in DM2 patient fibroblasts. Altogether, our study demonstrates a novel mechanism by which large repeat expansions cause chronic ER and mitochondrial stress and induce a type-I interferon response that predisposes to autoimmunity.
Keywords: ER stress, ATF6, Autoimmunity, type I IFN, repeat expansions
Nutritional profile and effects on fungal growth of yeast symbionts associated with North American spruce beetle (Dendroctonus rufipennis)
Authors: Davis Thomas Seth , Stewart Jane E. , Clark Caitlin , Buiten Charlene Van 
Published: June 2022

Abstract
We characterized yeasts isolated from the integument of North America spruce beetle (Dendroctous rufipennis Kirby) across four populations, using molecular methods to identify 59 representative isolates. Seven yeast species were detected; Wickerhamomyces canadensis (Wickerham) Kurtzman et al. (Sachharomycetales: Saccharomycetaceae) was the most common (74% of isolates) and found in all populations. Isolates of W. canadensis were subsequently tested for in vitro competitive interactions with symbiotic (Leptographium abietinum) and pathogenic (Beauvaria bassiana) fungi, and isolates were nutritionally profiled (N and P content). Three key findings emerged: (1) exposure to yeast headspace emissions had isolate-dependent effects on colony growth of symbiotic and pathogenic fungi; most isolates of W. canadensis slightly inhibited growth rates of symbiotic (L. abietinum) and entomopathogenic (B. bassiana) fungi. (2) A single volatile (2-phenylethanol) was produced by W. canadensis on growth media and was emitted at an average rate of 1.47 µg− 1·mg− 1 yeast·min− 1. Exposure to vapors of synthetic 2-phenylethanol reduced growth rates of both L. abietinum and B. bassiana by 36% on average. (3) W. canadensis cultures were high in both protein (0.8%) and phosphorous (7.2%) in comparison to spruce phloem, but isolates varied in nutritional content with the most nutrient-rich strains isolated from populations in outbreak or post-outbreak population phases. We conclude that W. canadensis is a primary yeast symbiont of D. rufipennis in the southern Rocky Mountains and may serve as a source of volatile emissions that can affect growth of associated microbes. Although W. canadensis has higher nutritional content than spruce tree phloem, the concentration of limiting nutrients (protein and phosphorous) is less than reported for the symbiotic fungus L. abietinum, and variation in nutritional content may be associated with beetle population density.
Prediction of Heart Disease using Data Mining Classifiers
Authors: K UMA 
Published: June 2022

Abstract
Fist size muscle acquires the name of an important part of the human body by pumping blood to all the parts of the body. Cardiovascular disease is the major cause of death in the nation. Though the data available in the health field is vast, still there is a need to develop decision supporting system to maintain, analyze, and knowledge evaluation. One such technique that can be used to address such a problem is data mining. Data mining techniques can help to classify the whether a patient having heart disease or not. This paper explores the different classification techniques for heart disease prediction. Logistic Regression, Support Vector Machine, Naïve Bayes, Nearest Neighbor, and Decision Tree methods are applied. To assess performance of the classifiers various measures are taken includes accuracy, recall, precision and F1-score. Methods: An abundant data generated by the healthcare industry leads to exploring the required information to make a decision-making system using data mining techniques. Classification methods such as SVM, Naive Bayes, KNN, Logistic Regression, and Decision Tree are applied to predict heart disease with a different dataset. Results: Five classification techniques are applied to predict the two different heart disease datasets. By inference, the different classifiers work differently on selected attributes of datasets in terms of accuracy, precision, recall, and F1-score measurements. Conclusion: Our research focuses on comparing the results of classification techniques applied to two different heart disease datasets. Various performance metrics were used to compare and contrast the two datasets of heart disease.
WITHDRAWN: Computational modeling of the combustion process in small-scale chemical reactors
Authors: Chen Junjie 
Published: June 2022

Abstract
A two-dimensional computational fluid dynamics model of a small-scale chemical reactor is solved to study the effects of different operating conditions on combustion characteristics and the steady-state, self-sustained flame stability of fuel-air mixtures. Computational fluid dynamics simulations are conducted to gain insights into small-scale chemical reactor performance such as temperatures, reaction rates, and flames. The factors affecting combustion characteristics are determined for small-scale chemical reactors. Particular focus is placed on determining essential factors that affect the performance of small-scale chemical reactors. The results indicate that flames can be stabilized in narrow channels but very careful design is necessary. Large transverse and axial gradients are observed even at these small scales under certain conditions. The cavity structure can induce recirculation of hot products, thereby improving flame stability. An optimum flow velocity for greatest flame stability exists. The flow rate has a strong effect on flame stability. Fast flows decrease the rate of heat transfer upstream and can cause blowout. Slow flows can also cause loss of flame stability by making conductive heat transfer so dominant that the reaction region is spread, and the external heat losses become too large compared to heat generation to sustain combustion. Small-scale combustion can offer advantages. Aside from the larger radial heat transfers, faster ignition can happen, and low temperatures could be envisioned. However, loss of flame stability due to blowout or extinction and high wall temperatures are main issues that require careful thermal management.
WITHDRAWN: Process characteristics of highly exothermic reactions in micro-structured systems
Authors: Chen Junjie 
Published: June 2022

Abstract
Micro-combustion is the sequence of exothermic chemical reaction between a fuel and an oxidant accompanied by the production of heat and conversion of chemical species at the micro level. The release of heat can result in the production of light in the form of a flame. This study relates to the process characteristics of highly exothermic reactions in micro-structured systems. Numerical simulations are conducted to gain insights into micro-structured system performance such as species concentrations, temperatures, and flames. The transport effects such as diffusion of heat and mass are investigated, including the exchange of mass, energy, and momentum within the micro-structured systems. The factors affecting the process characteristics of highly exothermic reactions are determined for the micro-structured systems. Transport phenomena are studied in reactor design. Particular focus is placed on determining essential factors that affect the performance of the micro-structured systems. The results indicate that highly exothermic reaction systems with large dimensions lead to a delay in flame ignition and may cause blowout. As the surface-to-volume ratio increases, heat loss to walls of the highly exothermic reaction system increases which leads to flame quenching. The cavity structure can induce recirculation of hot products, thereby improving flame stability. Fast flows can cause blowout and slow flows can cause extinction. There exists an optimum inlet velocity for greatest flame stability. A critical issue of fuel-rich cases is the loss of combustion efficiency. Combustion at the microscale can offer many advantages. Faster ignition and more efficient heat transfer can be achieved, but the design is challenging due to the loss of flame stability. Significant amount of heat is transferred through the walls which leads to flame quenching, but the increased rate of heat transfer through solid walls is advantageous in the case of steam reformers used for hydrogen production.