bluuebunny/crossref_metadata_2025_split huggingface dataset:
Profile‐likelihood Bayesian model averaging for two‐sample summary data Mendelian randomization in the presence of horizontal pleiotropy
Authors: Shapland Chin Yang , Zhao Qingyuan , Bowden Jack 
Published: January 2022

AbstractTwo‐sample summary data Mendelian randomization is a popular method for assessing causality in epidemiology, by using genetic variants as instrumental variables. If genes exert pleiotropic effects on the outcome not entirely through the exposure of interest, this can lead to heterogeneous and (potentially) biased estimates of causal effect. We investigate the use of Bayesian model averaging to preferentially search the space of models with the highest posterior likelihood. We develop a Metropolis‐Hasting algorithm to perform the search using the recently developed MR‐RAPS as the basis for defining a posterior distribution that efficiently accounts for pleiotropic and weak instrument bias. We demonstrate how our general modeling approach can be extended from a standard one‐component causal model to a two‐component model, which allows a large proportion of SNPs to violate the InSIDE assumption. We use Monte Carlo simulations to illustrate our methods and compare it to several related approaches. We finish by applying our approach to investigate the causal role of cholesterol on the development age‐related macular degeneration.
Albumin Nanoparticles Loaded with Hemin as Peroxidase Mimics for Immunoassay**
Authors: Khramtsov Pavel , Bochkova Maria , Timganova Valeria , Kiselkov Dmitriy , Zamorina Svetlana , Rayev Mikhail 
Published: January 2022

AbstractContemporary immunoassays commonly used in clinical diagnostics mostly utilize enzymes, such as horseradish peroxidase, for signal generation. Numerous research is dedicated to the development of artificial peroxidase‐mimicking catalysts with lower cost, high activity, better operational stability, and tunable properties. Herein we synthesized hemin‐loaded bovine serum albumin (BSA) nanoparticles and applied them as catalytic labels (nanozymes) in colorimetric immunoassay of anti‐tetanus antibodies. Hemin is a key part of the peroxidase catalytic center, possessing peroxidase like‐activity. Albumin nanoparticles were loaded with multiple hemin molecules and decorated with Streptococcal protein G. Resulting nanozymes possessed good colloidal stability and allowed for antibody detection in blood serum. The sensitivity of antibody detection was sufficient for the assessment of post‐vaccination immunity.
Depolymerization of Poly(1,2‐propylene carbonate) via Ring Closing Depolymerization and Methanolysis
Authors: Alberti Christoph , Rijono Desiree , Wehrmeister Moritz , Cheung Even , Enthaler Stephan 
Published: January 2022

AbstractThe conversion of end‐of‐life plastics to useful chemicals can contribute to a resource‐conserving and environmental‐benign society. In this regard, we studied the depolymerization via methanolysis of poly(1,2‐propylene carbonate) using straightforward metal salts as precatalysts. In more detail, in the presence of catalytic amounts of Zn(OAc)2or NaOAc and methanol 1,2‐propylene carbonate (generated by ring closing depolymerization), 1,2‐propanediol and dimethyl carbonate (generated by methanolysis) were obtained as beneficial products. Importantly, the selectivity for ring closing depolymerization vs. methanolysis of the polycarbonate depends on various parameters. Moreover, the reaction time is of significance, because in the initial stage of the process the ring closing depolymerization is dominant, while in the further course the amount of the methanolysis products are increasing and the amount of 1,2‐propylene carbonate is decreasing, due to conversion by methanolysis. Furthermore, the depolymerization of poly(1,2‐propylene carbonate) was connected with a consecutive depolymerization of poly(oxymethylene), that means the depolymerization product 1,2‐propanediol acts as depolymerization reagent for poly(oxymethylene) to generate 4‐methyl‐1,3‐dioxolane as suitable compound.
Bioinspired Carbon Dots as an Effective Fluorescent Sensing Platform for Tetracycline Detection and Bioimaging
Authors: Gao Xu , Qin Jing , Liu Jingyi , Yang Zhen , Zhang Guoliang , Hou Juan 
Published: January 2022

AbstractBioinspired carbon dots (CDs) with excellent biocompatibility were prepared from egg white as precursors through a simple hydrothermal method at 200 °C for 4 hours. The obtained CDs exhibited bright blue fluorescence, excellent optical stability, and sensitive response to tetracycline. Under the optimized synthetic conditions, the fluorescence quantum yield is 17.6 %. The fluorescence intensity of CDs at 440 nm could be quenched linearly with the addition of tetracycline in the range of 0.1–200 μmol L−1 due to the internal filtering effect. The proposed detection platform has been applied in the determination of tetracycline in milk samples with good results. The limit of detection is 32.3 nmol L−1, and the spiked recoveries are in the range of 93–103 %. Additionally, the CDs could also be applied to cell imaging, implying good biocompatibility and low toxicity. As a type of green and effective multi‐functional fluorescence materials, the CDs have potential applications in biochemical sensing and biomedical imaging.
Learning from our students: Being student‐centered in an unstable world
Authors: Weng John , Gleason Michael C. 
Published: January 2022

AbstractFrom the deaths of George Floyd and Breonna Taylor to the attack on Asian Americans in Georgia to the police shooting of Daunte Wright, the instances of traumatic events recently are too long to list, but the almost daily trauma is impacting our classrooms through the lived experiences of those who are a part of this living, dynamic system. Within this article we explore how we, as educators, have more responsibility than ever to acknowledge this trauma and work to support students bringing their whole selves to our classrooms.
Research Towards Key Issues of API Security
Authors: Sun Ronghua , Wang Qianxun , Guo Liang 
Published: January 2022

AbstractWith the mass application of virtualization, micro-services, and cloud-native technologies, the interaction between service entities through APIs has become a norm. Many platforms are still maintaining a large number of old APIs due to business needs. At the same time, many new APIs are gradually going online. Both of these statuses put forward higher requirements for API security. Focusing on old APIs’ security protection and other issues, this article starts from the process of asset discovery, vulnerability detection, and security auditing. Aiming at the problem of API asset discovery, this article summarizes the technical methods of automatically clustering unowned API assets using the characteristics of various commonly used APIs. Aiming at new API vulnerability detection, a security analysis method based on finite state machine is proposed. For the first time, the cross-network communication taint propagation based on dynamic taint analysis technology and system-level simulation technology is realized, enabling sensitive data flow tracing in API communication become feasible. We designed a flowbased API security audit system to improve automated API protection. Finally, We analyzed technical opportunities and challenges of API security in detail and prospected for API security research’s next direction and development trend.
A Multi-task Text Classification Model Based on Label Embedding Learning
Authors: Xu Yuemei , Fan Zuwei , Cao Han 
Published: January 2022

AbstractDifferent text classification tasks have specific task features and the performance of text classification algorithm is highly affected by these task-specific features. It is crucial for text classification algorithms to extract task-specific features and thus improve the performance of text classification in different text classification tasks. The existing text classification algorithms use the attention-based neural network models to capture contextualized semantic features while ignores the task-specific features. In this paper, a text classification algorithm based on label-improved attention mechanism is proposed by integrating both contextualized semantic and task-specific features. Through label embedding to learn both word vector and modified-TF-IDF matrix, the task-specific features can be extracted and then attention weights are assigned to different words according to the extracted features, so as to improve the effectiveness of the attention-based neural network models on text classification. Experiments are carried on three text classification task data sets to verify the performance of the proposed method, including a six-category question classification data set, a two-category user comment data set, and a five-category sentiment data set. Results show that the proposed method has an average increase of 3.02% and 5.85% in F1 value compared with the existing LSTMAtt and SelfAtt models.
A Privacy-Preserving Medical Data Traceability System Based on Attribute-Based Encryption on Blockchain
Authors: Zhao Yujuan , Cui Baojiang , Xu Jie 
Published: January 2022

AbstractWith the continuous development of distributed technology, blockchain has been widely applied to solve practical problems in various fields. Its advantages such as decentralization and non-tamperability perfectly meet the needs of permanent query of traceability scene information, and can solve the trust problem of multi-party participation in various links. At the same time, as data security has received more and more attention. The privacy protection and permission control of “on-chain” data need to be resolved. Medical data records are very valuable and sensitive data. Reliable storage and credible traceability are of great significance to the health of patients and the long-term development of medical undertakings. To issue the above problems, here, we propose a secure medical data traceability system that combines data desensitization and attribute-based encryption algorithms to achieve the traceability capabilities and ensure the reliable storage of medical data records on blockchain. Data desensitization provides a certain degree of security for sensitive data involving personal information in medical data. The introduction of attribute encryption has solved the problem of unauthorized access to data. Finally, we analyzed the security of the solution and Verify the efficiency of the program.
ExitSniffer: Towards Comprehensive Security Analysis of Anomalous Binding Relationship of Exit Routers
Authors: Zhang Qingfeng , Wang Xuebin , Shi Jinqiao , Wang Meiqi , Gao Yue , Zhao Can 
Published: January 2022

AbstractTor exit relays are operated by volunteers and the trustworthiness of Tor exit relays need to be revisited in a long-term manner. In this paper, we monitored the Tor network by developing a fast and distributed exit relay scanner (ExitSniffer) to probe all exit relays over a period of 16 months continuously, seeking to expose the anomalous binding relationship phenomena of exit routers simply by comparing the returnIP and consensusIP. We totally find 1983 malicious exit relays which average contribute 10.12% bandwidth of total Tor exit relays bandwidth monthly, resulting tremendous threaten for Tor user’s anonymity according to the current path-relay selecting algorithm. There exits two types of anomalous binding relationship consists 35 exit relay families, with different size ranging from 2 to 230, which are neither announced in the consensus document or detected by the Tor network.
Intelligent Evaluation of Global Spinal Alignment by a Decentralized Convolutional Neural Network
Authors: Nguyen Thong Phi , Jung Ji Won , Yoo Yong Jin , Choi Sung Hoon , Yoon Jonghun 
Published: January 2022

AbstractDegenerative changes of the spine can cause spinal misalignment, with part of the spine arching beyond normal limits or moving in an incorrect direction, potentially resulting in back pain and significantly limiting a person’s mobility. The most important parameters related to spinal misalignment include pelvic incidence, pelvic tilt, lumbar lordosis, thoracic kyphosis, and cervical lordosis. As a general rule, alignment of the spine for diagnosis and surgical treatment is estimated based on geometrical parameters measured manually by experienced doctors. However, these measurements consume the time and effort of experts to perform repetitive tasks that could be automated, especially with the powerful support of current artificial intelligence techniques. This paper focuses on creation of a decentralized convolutional neural network to precisely measure 12 spinal alignment parameters. Specifically, this method is based on detecting regions of interest with its dimensions that decrease by three orders of magnitude to focus on the necessary region to provide the output as key points. Using these key points, parameters representing spinal alignment are calculated. The quality of the method’s performance, which is the consistency of the measurement results with manual measurement, is validated by 30 test cases and shows 10 of 12 parameters with a correlation coefficient > 0.8, with pelvic tilt having the smallest absolute deviation of 1.156°.
Subcutaneous Low-Density Foreign Bodies Detection via Grating-Based Multimodal X-ray Imaging
Authors: Yin Meifang , Yuan Mingzhou , Deng Kai , Li Jing , Zhang Guangya , Zhu Jiayuan , Xie Weiping , Wu Jun 
Published: January 2022

AbstractDetecting low-density foreign bodies within soft tissues still stands for a serious challenge. Grating-based multimodal X-ray imaging typically has low hardware requirements while simultaneously providing three kinds of imaging information, i.e., absorption, phase-contrast, and dark-field. We aimed to explore the capacity of grating-based multimodal X-ray imaging technology for detecting common foreign bodies within subcutaneous tissues, and to assess the advantages as well as disadvantages of the three kinds of images obtained via grating-based X-ray multimodal technology in relation to diverse kinds of foreign bodies within different tissues. In this study, metal, glass, wood, plastic, graphite, and ceramic foreign bodies were injected into chunks of the pig adipose tissue and chicken thigh muscles. Next, a grating-based multimodal X-ray imaging device developed in our laboratory was used to detect the above foreign bodies within the adipose and muscle tissues. Our results show that grating-based multimodal X-ray imaging clearly revealed the subcutaneous foreign bodies within the adipose and muscle tissues by acquiring complementary absorption, phase-contrast, and dark-field imaging data in a single shot. Grating-based multimodal X-ray imaging has an exciting potential to detect foreign bodies underneath the epidermis.
Downregulated Calcium-Binding Protein S100A16 and HSP27 in Placenta-Derived Multipotent Cells Induce Functional Astrocyte Differentiation
Authors: Cheng Yu-Che , Huang Chi-Jung , Ku Wei-Chi , Guo Shu-Lin , Tien Lu-Tai , Lee Yih-Jing , Chien Chih-Cheng 
Published: January 2022

AbstractLittle is known about genes that induce stem cells differentiation into astrocytes. We previously described that heat shock protein 27 (HSP27) downregulation is directly related to neural differentiation under chemical induction in placenta-derived multipotent stem cells (PDMCs). Using this neural differentiation cell model, we cross-compared transcriptomic and proteomic data and selected 26 candidate genes with the same expression trends in both omics analyses. Those genes were further compared with a transcriptomic database derived from Alzheimer’s disease (AD). Eighteen out of 26 candidates showed opposite expression trends between our data and the AD database. The mRNA and protein expression levels of those candidates showed downregulation of HSP27, S100 calcium-binding protein A16 (S100A16) and two other genes in our neural differentiation cell model. Silencing these four genes with various combinations showed that co-silencing HSP27 and S100A16 has stronger effects than other combinations for astrocyte differentiation. The induced astrocyte showed typical astrocytic star-shape and developed with ramified, stringy and filamentous processes as well as differentiated endfoot structures. Also, some of them connected with each other and formed continuous network. Immunofluorescence quantification of various neural markers indicated that HSP27 and S100A16 downregulation mainly drive PDMCs differentiation into astrocytes. Immunofluorescence and confocal microscopic images showed the classical star-like shape morphology and co-expression of crucial astrocyte markers in induced astrocytes, while electrophysiology and Ca2+ influx examination further confirmed their functional characteristics. In conclusion, co-silencing of S100A16 and HSP27 without chemical induction leads to PDMCs differentiation into functional astrocytes.

Graphical abstract
Comparison of a computer vision system against three-dimensional motion capture for tracking football movements in a stadium environment
Authors: Aughey Robert J. , Ball Kevin , Robertson Sam J. , Duthie Grant M. , Serpiello Fabio R. , Evans Nicolas , Spencer Bartholomew , Ellens Susanne , Cust Emily , Haycraft Jade , Billingham Johsan 
Published: January 2022

AbstractThree-dimensional motion capture systems such as Vicon have been used to validate commercial electronic performance and tracking systems. However, three-dimensional motion capture cannot be used for large capture areas such as a full football pitch due to the need for many fragile cameras to be placed around the capture volume and a lack of suitable depth of field of those cameras. There is a need, therefore, for a hybrid testing solution for commercial electronic performance and tracking systems using highly precise three-dimensional motion capture in a small test area and a computer vision system in other areas to test for full-pitch coverage by the commercial systems. This study aimed to establish the validity of VisionKit computer vision system against three-dimensional motion capture in a stadium environment. Ten participants undertook a series of football-specific movement tasks, including a circuit, small-sided games and a 20 m sprint. There was strong agreement between VisionKit and three-dimensional motion capture across each activity undertaken. The root mean square difference for speed was 0.04 m·s−1 and for position was 0.18 m. VisionKit had strong agreement with the criterion three-dimensional motion capture system three-dimensional motion capture for football-related movements tested in stadium environments. VisionKit can thus be used to establish the concurrent validity of other electronic performance and tracking systems in circumstances where three-dimensional motion capture cannot be used.
Een rookvrije omgeving in het belang van het kind
Authors: Faber Timor , Breunis Leonieke J. , Been Jasper V. , Toebes Brigit 
Published: January 2022

SamenvattingKinderen die worden blootgesteld aan tabaksrook hebben vaker (levenslange) gezondheidsproblemen. Toch ademen nog veel kinderen in Nederland tabaksrook in. Rookvrije wetgeving is een krachtig middel om kinderen te beschermen tegen tabaksrook. Hierdoor worden minder baby’s te vroeg geboren en minder kinderen in het ziekenhuis opgenomen voor luchtweginfecties of ernstige astma-aanvallen. Onderzoek toont aan dat hoe meer plekken onder deze wetgeving vallen, hoe groter het gezondheidseffect is. Internationale juridische standaarden, waar Nederland aan gebonden is, nopen tot het invoeren van verder strekkende rookvrije wetgeving.
Ongewenste effecten van voorlichting over recreatief drugsgebruik
Authors: Spronk Desirée B. , Voorham Lotte , Goossens Ferry X. 
Published: January 2022

SamenvattingIn Nederland is drugspreventie een belangrijk onderdeel van het drugsbeleid. Harm reduction-interventies die zich richten op voorlichting over recreatief drugsgebruik vormen daarbinnen een belangrijke categorie. De nadruk ligt hierbij op het voorkómen van gezondheidsschade bij gebruik en niet zozeer op het voorkómen van het drugsgebruik op zich. Tegen de achtergrond van een stijging in het gebruik van verschillende soorten drugs is het van belang om kritisch te blijven en na te gaan of er bij voorlichting over recreatief drugsgebruik ook ongewenste effecten optreden. We presenteren hieronder een praktisch toetsingskader dat ondersteuning biedt bij het inschatten van eventuele ongewenste effecten bij dit type harm reduction-interventies.
Samenwerking tussen zorg- en hulpverleners in de achterstandswijk Overvecht
Authors: Leemrijse Chantal , Bitter Neis , Korevaar Joke 
Published: January 2022

SamenvattingUtrecht Overvecht is een achterstandswijk met ruim 34.000 inwoners. Veel inwoners (18%) hebben een bijstandsuitkering en de ervaren gezondheid is laag. Professionals uit de eerstelijnszorg en het sociale domein werken samen in de wijkaanpak Krachtige basiszorg. Gezamenlijk bieden zij geïntegreerde persoonsgerichte zorg dicht bij huis voor mensen met een stapeling van medische en sociaal-maatschappelijke problemen. Professionals zijn enthousiast omdat zij betere zorg kunnen bieden door samenwerking, maar zien ook ruimte voor verbetering.
Dertig jaar preventie van alcohol, roken en drugs op scholen
Authors: Lammers Jeroen , Onrust Simone , Maat Marianne 
Published: January 2022

SamenvattingHelder op School is het preventieprogramma voor scholen die aandacht willen schenken aan de preventie van alcohol, tabak, drugs en problematisch gamen. Het biedt handvatten voor basisscholen, middelbare scholen (inclusief het speciaal onderwijs), het mbo en het hbo/wo. Vanuit het programma worden interventies ontwikkeld, geïmplementeerd en onderzocht op effectiviteit. De brede opzet is de kracht van het programma, er wordt gewerkt vanuit de vier pijlers van Gezonde School: educatie, beleid, signaleren & zorg, en omgeving. Helder op School is de nieuwe naam voor De Gezonde School en Genotmiddelen, dat in 2019 zijn dertigjarig jubileum vierde. Dit artikel beschrijft de geschiedenis van het programma, de ontwikkeling die het heeft doorgemaakt, de wetenschappelijke fundering en de implementatiestructuur. Aan het eind volgt een aantal uitdagingen voor de toekomst.
Bevordering van mondgezondheid door jeugdartsen en jeugdverpleegkundigen op het consultatiebureau
Authors: van Spreuwel Peggy C. J. M. , Jerkovic-Cosic Katarina , Grift Brenda G. , van Loveren Cor , van der Heijden Geert J. M. G. 
Published: January 2022

Samenvatting
Inleiding
Het doel van dit vragenlijstonderzoek was om de attitude, kennis, informatiebehoefte en uitvoering van mondgezondheidsbevordering door jeugdartsen en jeugdverpleegkundigen op het consultatiebureau in kaart te brengen.

Methode
Tien jeugdgezondheidszorginstanties hebben een digitale vragenlijst over kennis, attitude en uitvoering van mondgezondheidsbevordering binnen hun organisatie verspreid. Jeugdartsen en jeugdverpleegkundigen werden gevraagd de vragenlijst in te vullen. Informatie werd verzameld over: 1) demografische kenmerken; 2) kennis over cariësrisicofactoren; 3) attitude ten opzichte van mondgezondheid; 4) uitvoering van mondgezondheidsbevordering tijdens consulten bij kinderen tot vier jaar; en 5) informatiebehoefte. De antwoorden van jeugdartsen en jeugdverpleegkundigen worden apart gepresenteerd.

Resultaten
Er zijn 146 vragenlijsten van 61 verschillende consultatiebureaus geanalyseerd. Respondenten hadden een positieve attitude en een meerderheid heeft voldoende basale kennis over cariësrisicofactoren. Tijdens een consult verwijst een minderheid (45%) actief naar een mondzorgprofessional voor preventie; 62% kijkt wel eens in de mond van een kind en 36% vindt dat er onvoldoende aandacht is voor mondgezondheidsbevordering op het consultatiebureau. Als reden daarvoor worden tijdsdruk, prioritering van te bespreken onderwerpen en gebrek aan kennis het meest genoemd.

Conclusie
Ondanks een positieve attitude en basale kennis over cariësrisicofactoren krijgt mondgezondheidsbevordering onvoldoende aandacht op het consultatiebureau. Mondgezondheidsbevordering op consultatiebureaus vraagt om een hogere prioriteit.