bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patientensicherheit in der Dermatologie: Definitionen und Fehlermonitoring
Authors: Elsner P. 
Published: April 2021

ZusammenfassungMedizinethisch ist der Arzt nach dem „Nil nocere“-Prinzip verpflichtet, einem Patienten durch eine Behandlung zu nutzen und nicht zu schaden, auch wenn die Behandlung erfolglos sein mag. Das ärztliche Haftungs- und Berufsrecht fordert, dass eine Behandlung nach dem Standard eines sorgfältigen Facharztes zu erfolgen hat. Gleichwohl kommt es in Kliniken und Praxen immer wieder zu „vermeidbaren unerwünschten medizinischen Ereignissen“, die definiert sind als „Patienten schadende Vorkommnisse, die eher auf der Behandlung als auf der Erkrankung selbst beruhen und die durch einen Fehler verursacht sind“. Patientensicherheit als in der Medizin erstrebenswertes Handlungsziel bedeutet die Minimierung derartiger unerwünschter Ereignisse. Dies setzt voraus, dass unerwünschte Ereignisse und die zu ihnen führenden Risikosituationen erfasst und analysiert werden; dafür eignen sich Register wie „Critical Incidence Reporting Systems“ (CIRS) und die Fälle der Gutachterkommissionen bei den Landesärztekammern. Die Analyse von Gutachten zu Behandlungsfehlervorwürfen gegen Dermatologen ergab, dass nicht operative Therapiefehler an der Spitze der bestätigten Fehler stehen, gefolgt von Diagnostikfehlern und operativen Therapiefehlern. Aus diesen Erkenntnissen können konkrete Empfehlungen für Initiativen zur Verbesserung der Patientensicherheit in der Dermatologie abgeleitet werden.
Vitamin D und Omega-3-Fettsäuren – gemeinsam gegen Entzündungen
Authors: Schmiedel Volker 
Published: April 2021

ZusammenfassungDie Datenlage zu Vitamin D und Omega-3-Fettsäuren ist enorm. Während Vitamin D direkt im zellulären und humoralen Immunsystem wirkt, sind die Derivate aus Omega-3-Fettsäuren antiinflammatorisch. Beides führte dazu, dass stille Entzündungen erst gar nicht entstehen oder entstandene chronische Entzündungskrankheiten gelindert oder sogar geheilt werden können.
Update Breast Cancer 2020 Part 5 – Moving Therapies From Advanced to Early Breast Cancer Patients
Authors: Lux Michael P. , Schneeweiss Andreas , Hartkopf Andreas D. , Müller Volkmar , Janni Wolfgang , Belleville Erik , Stickeler Elmar , Thill Marc , Fasching Peter A. , Kolberg Hans-Christian , Untch Michael , Harbeck Nadia , Wöckel Achim , Thomssen Christoph , Schulmeyer Carla E. , Welslau Manfred , Overkamp Friedrich , Schütz Florian , Lüftner Diana , Ditsch Nina 
Published: April 2021

AbstractIn recent years, significant progress has been made in new therapeutic approaches to breast cancer, particularly in patients with HER2-positive and HER2-negative/hormone receptor-positive (HR+) breast cancer. In the case of HER2-positive tumours, these approaches have included, in particular, treatment with pertuzumab, T-DM1, neratinib and, soon, also tucatinib and trastuzumab deruxtecan (neither of which has yet been authorised in Europe). In patients with HER2−/HR+ breast cancer, CDK4/6 inhibitors and the PIK3CA inhibitor alpelisib are of particular importance. Further novel therapies, such as Akt kinase inhibitors and oral SERDs (selective estrogen receptor down regulators), are already being investigated in ongoing clinical trials. These therapeutic agents are not only being introduced into curative, (neo-)adjuvant therapeutic settings for HER2-positive tumours; a first favourable study on abemaciclib as an adjuvant therapy has now also been published. In patients with triple-negative breast cancer, after many years of negative study results with the Trop-2 antibody drug conjugate (ADC) sacituzumab govitecan, a randomised study has been published that may represent a significant therapeutic advance. This review describes the latest developments in breast cancer subsequent to the ESMO Congress 2020.
Edoxaban Dosing Time Affects Blood Coagulation Inhibition in Rats
Authors: Nagata Naoto , Kawasumi Muneo , Fujimura Akio , Ando Hitoshi 
Published: April 2021

AbstractCoagulation–fibrinolytic system activity shows daily rhythmicity, with hypercoagulability in the morning and hypocoagulability in the evening. Consequently, the efficacy of anticoagulants may be influenced by their dosing time. Edoxaban, a selective inhibitor of the active form of coagulation factor X (FXa), is taken orally once daily, but the optimal dosing time is unknown. This study evaluated the dosing time-dependent effects of edoxaban on coagulation activity and thrombus formation in rats. Edoxaban (10 mg/kg) or vehicle was administered to Wistar rats at zeitgeber time (ZT)-2 (beginning of the light phase) or ZT14 (beginning of the dark phase), followed by blood collection at ZT4, ZT10, ZT16, or ZT22, to measure the activity of coagulation factors and edoxaban concentrations, or followed by inferior vena cava ligations at ZT4 or ZT16, to assess the efficacy of edoxaban against thrombus formation. Coagulation FX activity was high during the light phase, and a single dose of edoxaban administered at ZT2 inhibited FX activity and thrombus formation more potently compared with the same dose administered at ZT14. The inhibitory effects during the light phase could be attributed, at least in part, to the high blood concentration of edoxaban achieved by dosing at ZT2. Morning dosing of edoxaban leads to a high blood concentration of the drug during the morning hours and thus may better counteract the hypercoagulability and hypofibrinolytic activity characteristic of the morning hours. Optimizing the dosing time may contribute to improving the efficacy of edoxaban.
Exome Sequencing Reveals De Novo Variants in Congenital Scoliosis
Authors: Murakami Kohei , Kikugawa Shingo , Seki Shoji , Terai Hidetomi , Suzuki Takako , Nakano Masaki , Takahashi Jun , Nakamura Yukio 
Published: April 2021

AbstractCongenital scoliosis (CS) is a lateral curvature of the spine characterized by the presence of vertebral anomalies. Pathogenic genetic variants in the TBX6 gene are one of the causes of CS. However, since many clinically diagnosed cases of CS are without known TBX6 gene variations, this study aims to uncover new genes related to disease susceptibility of CS by exome sequencing (ES). This study employed ES in a cohort of 5 Japanese patients with CS and their healthy parents or a sister for a total of 16 samples among 5 families. Variant interpretation was performed using SIFT, PolyPhen-2, Mutation Taster, and CADD. Four de novo variants were identified by ES and confirmed by Sanger sequencing: 1 frameshift variant (SHISA3) and 3 missense variants (AGBL5, HDAC4, and PDE2A). ES also uncovered 1 homozygous variant in the MOCOS gene. All of these variants were predicted to be deleterious by SIFT, PolyPhen-2, Mutation Taster, and/or CADD. The number of de novo variants identified in this study was exactly what would be expected by chance. Additional functional studies or gathering matched patients using Gene Matcher are needed.
Transient Neonatal Diabetes Mellitus and Seizure with an Unknown Etiology
Authors: Gunes Sevinc Odabasi , Calisici Erhan , Arslan Mutluay , Akin Onur , Karagol Belma Saygili 
Published: April 2021

AbstractNeonatal diabetes mellitus (NDM) is a monogenic form of diabetes, usually occurring in the first 6 months of life. Here, we present a newborn, which was admitted with epileptic seizure on the postnatal second day of life. Sepsis and meningitis were ruled out. Cranial imaging and electroencephalography revealed normal. She developed transient NDM on the follow-up and was diagnosed to carry an ABCC8 mutation. Although the neurological features are more common in patients with KCJN11 mutations, patients with ABCC8 mutations could also represent with subtle neurodevelopmental changes or even with epileptic seizures. The genetic testing and appropriate therapy is important in this patient group for predicting clinical course and possible additional features.
Syntaxin Binding Protein 1 Related Epilepsies
Authors: Fontana Alessandra , Consentino Maria Chiara , Motta Milena , Costanza Giuseppe , Lo Bianco Manuela , Marino Simona , Falsaperla Raffaele , Praticò Andrea D. 
Published: April 2021

AbstractSyntaxin binding protein 1 (STXBP1), commonly known as MUNC18–1, is a member of SEC1 family membrane trafficking proteins; their function consists in controlling the soluble N-ethylmaleimide-sensitive factor attachment protein receptors complex assembly, making them essentials regulators of vesicle fusion. The precise function and molecular mechanism through which Munc18–1 contributes to neurotransmitter releasing is not entirely understood, but several evidences suggest its probable role in exocytosis. In 2008, heterozygous de novo mutations in neuronal protein Munc18–1 were first referred as a cause of Ohtahara syndrome development. Currently, a wide examination of the published data proved that 3.1% of patients with severe epilepsy carry a pathogenic de novo mutation including STXBP1 and approximately 10.2% of early onset epileptic encephalopathy is due to an aberrant STXBP1 form codified by the mutated gene. STXBP1 mutations can be associated to a wide clinical heterogeneity. All affected individuals show developmental delay and approximately the 95% of cases have seizures and early onset epileptic encephalopathy, characterized by infantile spasms as the main consistent feature. Burst suppression pattern and hypsarrhythmia are the most frequent EEG anomalies. Other neuronal disorders include Rett syndrome and behavioral and movement disorders. Mild dysmorphic features have been detected in a small number of cases. No genotype–phenotype correlation has been reported. Management of STXBP1 encephalopathy requires a multidisciplinary approach, including epilepsy control and neurological rehabilitation. About 25% of patients are refractory to standard therapy. A single or combined antiepileptic drugs may be required. Several studies described vigabatrin, valproic acid, levetiracetam, topiramate, clobazam, and oxcarbazepine as effective in seizure control. Lamotrigine, zonisamide, and phenobarbital are also commonly used. To date, it remains unclear which therapy is the most effective. Severe morbidity and high mortality are inevitable consequences in some of these patients.
Rare Clinical Presentation in a Case of Pediatric Guillain-Barré Syndrome and Rehabilitation Outcome
Authors: Sharma G. Sonachand , Gupta Anupam , K. Raghavendra , Navin B.P. , Khanna Meeka , Asranna Ajay , Patil Ramesh 
Published: April 2021

Abstract
Nearly half of patients with Guillain-Barré syndrome (GBS) have cranial nerve involvement. Ocular muscle weakness or ophthalmoplegia occurs in ~10% of these patients. Patients presenting with bilateral ptosis, with or without ophthalmoplegia, is a rare finding. Anti-GQ1b antibody has been found in Miller Fisher syndrome and GBS with ophthalmoplegia variants. We report a case of GBS in a young boy presenting with rare presentation of tetraplegia, bilateral ptosis, and facial palsy, no ataxia but ophthalmoplegia with seronegative anti-GQ1b antibody. Patient showed recovery in cranial nerves involvement as well as with motor and functional recovery after 3 weeks of inpatient rehabilitation (Barthel Index score improved to 60/100 at the time of discharge from 20/100 at the time of admission). He was independent for most of the activity of daily livings including ambulation at the time of discharge from rehabilitation unit (p < 0.001).
Self-consistent tomography of temporally correlated errors
Authors: Huo Mingxia , Li Ying 
Published: April 2021

Abstract
The error model of a quantum computer is essential for optimizing quantum algorithms to minimize the impact of errors using quantum error correction or error mitigation. Noise with temporal correlations, e.g. low-frequency noise and context-dependent noise, is common in quantum computation devices and sometimes even significant. However, conventional tomography methods have not been developed for obtaining an error model describing temporal correlations. In this paper, we propose self-consistent tomography protocols to obtain a model of temporally correlated errors, and we demonstrate that our protocols are efficient for low-frequency noise and context-dependent noise.
Covid19 Drug Efficacy Statistical Analysis
Authors: Zhang Xuerong , Zhu Qinyu , Qiang Jiaying , Shen Jiaming 
Published: April 2021

Abstract
Recently, a new SARS-CoV-2 coronavirus named COVID 19 sparked panic worldwide. More than 1000 ongoing therapeutics were dealing with it. However, the efficacy of these treatments was still fuzzy. In this paper, we analyzed 4 main types of treatments individually and mutually based on clinical trials data. T-test, models like COX and GEE logistic regression are adopted to evaluate the efficacy.
Predictive Analysis of Class Attention Based on CNN Model
Authors: Liu Xiang , Li Guoyi , Xu Luo , Wu Yuning 
Published: April 2021

Abstract
As the current classroom teaching reform has been integrated into every class of higher vocational colleges, modern artificial intelligence, deep learning, big data and other high-end technologies are integrated into the classroom, and classroom teaching has become more and more diverse. But the attention of modern vocational and technical students to the classroom has also received widespread attention from the society. This article uses artificial intelligence and big data technology to analyze class attention, and then uses the CNN model to predict the overall class attention. This article discusses the core literacy strategies for cultivating the efficiency of vocational and technical students in the classroom, and proposes methods such as setting suspense to guide independent inquiry, organizing learning to discover learning rules, and in-depth exploration of students’ independent learning ability, so as to increase the attention of the classroom. Based on the current popular CNN target detection algorithms can be divided into two categories. The first category is a two-stage detection algorithm, which divides the detection problem into two stages. First, generate candidate regions, and then classify the candidate regions. The typical representative of these algorithms is the R-CNN series algorithm based on region proposal. The other type is the 1-stage detection algorithm, which makes predictions for every part of the image, that is, it does not need to generate candidate regions. On this basis, a target prediction system based on the CNN model is designed and implemented, which predicts and analyzes the class attention of higher vocational colleges, uses a deep learning framework, and uses PyQt5 as an interface development framework combined with python. Experimental research results show that the designed CNN-based classroom attention model in higher vocational colleges can effectively predict and analyze students, and the effect of the practical experiment is good.
Evaluation System of College Physical Education Practice Teaching Based on Big Data
Authors: Zhang Yinan 
Published: April 2021

Abstract
With the development of the era of big data as the background, the physical education methods of universities have greatly improved. For other educational software like MOOC, some universities use the Internet to innovate the educational methods of sports theory courses, innovating educational software to improve the educational level of physical education theory course in Colleges and Universities Effectively enable students in the era of big data. After years of reform and practice, college physical education has achieved certain results, but in recent years, the physical health of college students has shown a downward trend. The physical health of college students depends on the students’ awareness of physical fitness, the process of participating in physical exercise, and the lifestyle habits they develop. The cultivation of these factors is closely related to college physical education activities, and is also the task of college physical education activities. And goals. Students’ behaviors in all aspects of life can be recorded in the form of big data. This article explores how to use big data to better reform physical education. Improve the scientificity and rationality of physical education. Use detailed data to objectively reflect the existing problems of college physical education, and explore the direction and path of college physical education reform.
Teaching Mode of Chinese and Western Art History Course Based on Big Data
Authors: Qi Bin 
Published: April 2021

Abstract
At present, with the rapid development of network technology and social economy, the reform of teaching concept is deepening. The traditional teaching mode can no longer meet people’s growing learning needs. The application of network technology in teaching is more and more common. The corresponding network teaching platform is also in continuous development, at the same time, its hybrid teaching mode combined with traditional teaching is also constantly deepening into the classroom of colleges and universities. Based on the subject of “Chinese and Western art history” course in a school, this paper first summarizes the teaching characteristics and defects of Chinese and Western art history course, and describes the application method of big data technology in it. Through practical statistics, students’ views on the new mode of education are counted. Through data analysis, the help of new education mode on students’ learning results is obtained Compared with the traditional education mode, the new education mode can enhance students’ interest in learning and improve their academic performance.
Practice Teaching Method of Electronic Commerce Major Based on Data Mining Algorithm
Authors: Deng Jianghua , Qing Haohua 
Published: April 2021

Abstract
With the rapid development of network, communication, and information technology, e-commerce has received widespread attention as a new business model. E-commerce has become a popular term, and e-commerce has become a popular mainstream in universities. However, as a comprehensive and free subject of art and science penetration, e-commerce puts forward more comprehensive requirements for teaching content, process and methods. Based on the above background, the purpose of this article is to study the professional practice teaching methods of e-commerce based on data mining algorithms. This article first analyzes the privacy issues caused by decentralized data mining under the condition of rapid development of e-commerce. How to build a more accurate model to complete data mining tasks without revealing personal privacy, mainly discussing data mining privacy protection algorithms. Next, through literary research method, questionnaire survey method, case research method, and interview method, explore the practical teaching method of e-commerce professional based on data mining algorithm. The role is to study the problems and solutions that blended learning needs to solve in specific applications. The experimental results show that, compared with the previous guidance method, the new teaching method can improve students’ initiative, enthusiasm and creativity by about 10% in the learning process.
Design of Electric Power Data Acquisition System Based on Internet of Things
Authors: Du Haodong , Huang Fu , Liu Libin 
Published: April 2021

Abstract
In today’s era of rapid economic development, China’s Internet is also developing rapidly, and intelligence is becoming more and more common in people’s daily life, which also promotes the intelligence of my country’s electricity data collection. This paper designs a power data acquisition system based on the power Internet of Things. Through the analysis of the power Internet of Things and its relationship with the smart grid, a data acquisition system is constructed with three parts: smart meters, concentrators and data management systems. And use GPRS and VPN to analyze, explain how to analyze the collected data.
RETRACTED: Judgment and Coping Strategies of IAPE Based on Big Data Analysis
Authors: Zeng Fanglian , Gao Qiuli 
Published: April 2021

Abstract
With the rapid development of Internet technology, we ushered in a new era of data. The advantages of Internet technology have made it widely and deeply applied in all fields of society. IAPE (IAPE) is a key issue in today’s education field, and it is urgent to solve the current IAPE problem in schools. This article combines the advantages of current Internet technology and data technology, and takes two universities as examples to explore the differences between IAPE and traditional IAPE in the era of big data, and analyze the advantages of the former. The experiment shows that the former can improve the quality of IAPE’s teaching work, and when compared with the two teaching modes, 31% of the participants in the experimental group are satisfied, and 36% of them are very satisfied, while only 25% of the control group were satisfied. Therefore, in addition to expounding the problems of IAPE in the era of big data, this article also conducts some research and discussion on the methods and strategies to deal with this problem on this basis.
Trend Analysis of Journal of Finance Based on Web of Science Database
Authors: Liang Shidi 
Published: April 2021

Abstract
Web of Science is a website which provides subscription-based access to multiple databases that provide comprehensive citation data for many different academic disciplines. Based on the Web of Science database, this paper used Citespace and Bibliometric to analyze the research articles published by Journal of Finance in recent ten years. Through the co-occurrence analysis, keyword analysis and trend analysis of the papers published by Journal of Finance, we can be more familiar with the use function of such measurement tools, which can help us explore the research status, research hotspots and future research directions in different fields to understand the research changes and improve the system construction..
RETRACTED: Discussion on the Innovation Based Goal in Entrepreneurship and Path Optimization of Contemporary College Students in Big Data Era
Authors: Yang Xiran , Ji Xiaofei 
Published: April 2021

Abstract
In the context of building an innovative country, the cultivation of university students in innovation and entrepreneurship has become a significant educational content in colleges and universities. Through the analysis of the status quo of students in universities in innovation and entrepreneurship, some countermeasures are proposed in this paper for solution to the issues of college students in innovation and entrepreneurship. According to the demands of college students and development in the society, cultivation of students in colleges and universities in innovation and entrepreneurship can not only help them grow into talents in practice and innovation, but also provide certain reference significance for training talents with innovative thinking to start up businesses in current colleges and universities.