bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Cr on the corrosion behavior of low carbon vanadium micro alloyed weathering steel in a simulated industrial atmosphere
Authors: Liu Yue , Zheng Xiao‐Ming , Cui Zi‐Xuan , Liu Peng‐Yu , Du Lin‐Xiu , Yang Zhi‐Nan 
Published: April 2024

AbstractThe study investigates the practical application of cyclic wet/dry corrosion tests in simulated industrial atmospheres to assess the impact of chromium (Cr) on the protective properties of vanadium micro‐alloyed weathering steels. Two types of steels were examined: a V‐N steel and a V‐N‐Cr micro‐alloyed weathering steel. These steels were subjected to corrosion tests with 0.01 mol/L NaHSO3 at a pH range of 4.4–4.8 for varying durations. The findings indicate that the inclusion of Cr in the composition of vanadium micro‐alloyed weathering steel enhances corrosion resistance and leads to the accumulation of Cr in the inner rust layer. Furthermore, the distribution of corrosion‐resistant elements (Cr, Ni, Cu, P, and Mo) in V‐N and V‐N‐Cr steels is analyzed. The rust layer was observed to exhibit stratification in the corrosive environment, with the outer layers being dense and uniform, while the inner layers were porous and exhibited poor adhesion to the matrix. The study also delves into the anticorrosion mechanism of vanadium weathering steel using techniques such as X‐ray diffractometer, electron probe microanalysis, and potential‐phase diagram.
Influence of initial pH and sulfate‐reducing bacteria concentration on the microbiologically influenced corrosion of buried pipeline steel
Authors: Liu Wenhui , Bi Wuxi , Hu Yabo , Lu Wenqi , Feng Wenhao , Wang Yipei , Li Yuheng , Liu Jianhua 
Published: April 2024

AbstractMicrobiologically influenced corrosion (MIC) caused by sulfate‐reducing bacteria (SRB) is a major threat to buried pipelines. The crevices beneath disbonded coatings provide the environment for the survival and growth of SRB, accelerating the attachment of SRB and significantly reducing the effectiveness of buried pipelines. In this work, the influence of initial pH values (6.4, 8.0) and SRB concentrations (2.0 × 101, 4.5 × 102, 2.5 × 103 cells/mL) were investigated on the behaviors of L415 carbon steel. The results indicated that the overall uniform corrosion rate of L415 carbon steel decreased while the maximum pitting corrosion rate exhibited an increasing trend with the increasing of initial concentration of SRB. In comparison to the pH 6.4 environment, the overall risk of pitting corrosion in pH 8.0 environment was reduced due to the biomineralization of SRB, enhancing the protection of metal materials.
Characterizing arginine, ornithine, and putrescine pathways in enteric pathobionts
Authors: Lillie Ian M. , Booth Charles E. , Horvath Adelaide E. , Mondragon Matthew , Engevik Melinda A. , Horvath Thomas D. 
Published: April 2024

AbstractArginine‐ornithine metabolism plays a crucial role in bacterial homeostasis, as evidenced by numerous studies. However, the utilization of arginine and the downstream products of its metabolism remain undefined in various gut bacteria. To bridge this knowledge gap, we employed genomic screening to pinpoint relevant metabolic targets. We also devised a targeted liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) metabolomics method to measure the levels of arginine, its upstream precursors, and downstream products in cell‐free conditioned media from enteric pathobionts, including Escherichia coli, Klebsiella aerogenes, K. pneumoniae, Pseudomonas fluorescens, Acinetobacter baumannii, Streptococcus agalactiae, Staphylococcus epidermidis, S. aureus, and Enterococcus faecalis. Our findings revealed that all selected bacterial strains consumed glutamine, glutamate, and arginine, and produced citrulline, ornithine, and GABA in our chemically defined medium. Additionally, E. coli, K. pneumoniae, K. aerogenes, and P. fluorescens were found to convert arginine to agmatine and produce putrescine. Interestingly, arginine supplementation promoted biofilm formation in K. pneumoniae, while ornithine supplementation enhanced biofilm formation in S. epidermidis. These findings offer a comprehensive insight into arginine‐ornithine metabolism in enteric pathobionts.
Impact of the gut microbiome on atherosclerosis
Authors: Mao Yuqin , Kong Chao , Zang Tongtong , You Lingsen , Wang Li‐Shun , Shen Li , Ge Jun‐Bo 
Published: April 2024

AbstractAtherosclerosis is a chronic inflammatory metabolic disease with a complex pathogenesis. However, the exact details of its pathogenesis are still unclear, which limits effective clinical treatment of atherosclerosis. Recently, multiple studies have demonstrated that the gut microbiota plays a pivotal role in the onset and progression of atherosclerosis. This review discusses possible treatments for atherosclerosis using the gut microbiome as an intervention target and summarizes the role of the gut microbiome and its metabolites in the development of atherosclerosis. New strategies for the treatment of atherosclerosis are needed. This review provides clues for further research on the mechanisms of the relationship between the gut microbiota and atherosclerosis.
Ppb‐level CO2 sensor based on a miniature multipass cell with eight‐petaled spot pattern
Authors: Wang Chenglong , Lin Leqing , Zeng Xiangyu , Xie Jiabao , Luo Huijian , Lin Haoyang , Wang Lihao , Tang Jieyuan , Cui Ruyue , Zhu Wenguo , Zhong Yongchun , Yu Jianhui , Dong Lei , Wu Hongpeng , Zheng Huadan 
Published: April 2024

AbstractThis paper presents an innovative carbon dioxide sensor leveraging a dense‐pattern multipass absorption cell. This novel design dramatically compacts an extensive optical path of approximately 11.4 m into a 70 mm inter‐mirror distance, effectively enhancing the system's sensitivity and reducing its size. Utilizing a 2004 nm diode laser, the sensor accurately targets a potent CO2 absorption line at 4989.9 cm−1. Experimental validation reveals remarkable linearity (R² = .999) and a detection limit of 59 ppb with 1 s integration time. The incorporation of Kalman filtering techniques further refines the sensor's performance, reducing the detection limit to 30 ppb—a substantial improvement of 49%. This advancement in sensor technology marks a significant step forward in efficient and precise CO2 monitoring.
Machine Learning Model Based on Radiomics for Preoperative Differentiation of Jaw Cystic Lesions
Authors: Fang Songling , Wang Yuepeng , He Yilin , Yu Taihui , Xie Yutong , Cai Yongkang , Li Wenhao , Wang Yan , Huang Zhiquan 
Published: April 2024

AbstractObjectiveThis study aims to use machine learning techniques together with radiomics methods to build a preoperative predictive diagnostic model from spiral computed tomography (CT) images. The model is intended for the differential diagnosis of common jaw cystic lesions.Study DesignRetrospective, case‐control study.SettingThis retrospective study was conducted at Sun Yat‐sen Memorial Hospital of Sun Yat‐sen University (Guangzhou, Guangdong, China). All the data used to build the predictive diagnostic model were collected from 160 patients, who were treated at the Department of Oral and Maxillofacial Surgery at Sun Yat‐sen Memorial Hospital of Sun Yat‐sen University between 2019 and 2023.MethodsWe included a total of 160 patients in this study. We extracted 107 radiomic features from each patient's CT scan images. After a feature selection process, we chose 15 of these radiomic features to construct the predictive diagnostic model.ResultsAmong the preoperative predictive diagnostic models built using 3 different machine learning methods (support vector machine, random forest [RF], and multivariate logistic regression), the RF model showed the best predictive performance. It demonstrated a sensitivity of 0.923, a specificity of 0.643, an accuracy of 0.825, and an area under the receiver operating characteristic curve of 0.810.ConclusionThe preoperative predictive model, based on spiral CT radiomics and machine learning algorithms, shows promising differential diagnostic capabilities. For common jaw cystic lesions, this predictive model has potential clinical application value, providing a scientific reference for treatment decisions.
International Society of Paediatric Oncology (SIOP) Global Mapping Programme: Latin American Society of Pediatric Oncology (SLAOP) country‐level report
Authors: Cappellano Andrea , Gorostegui Maite , Gonzalez‐Ramella Oscar , Filho Nevicolino Pereira Carvalho , Valencia Diana , Chantada Luisa , Sampor Claudia , Serrano María J. , Macedo Carla , Ramirez Oscar , Sardinas Susan , Lezcano Eva , Calderón Patricia , Gamboa Yessika , Fu Ligia , Gómez Wendy , Schelotto Magdalena , Ugaz Cecilia , Lobos Pablo , Aguiar Simone Dos Santos , Moreno Katiuska , Palma Julia , Sánchez Gissela , Moschella Filomena , Gassant Pascale Yola Heurtelou , Velasquez Thelma , Quintero Karina , Moreno Florencia , Villarroel Milena , Fuentes Alabi Soad , Vasquez Liliana , Challinor Julia , Chantada Guillermo L. 
Published: April 2024

AbstractBackgroundLatin American countries are improving childhood cancer care, showing strong commitment to implement the Global Initiative for Childhood Cancer, but there are scant publications of the situation at a continental level.MethodsAs part of the International Society of Paediatric Oncology Global Mapping project, delegates of each country participating in the Latin American Society of Pediatric Oncology (SLAOP) and chairs of national pediatric oncology societies and cooperative groups were invited to provide information regarding availability of national pediatric cancer control programs (NPCCP), pediatric oncology laws, pediatric oncology tumor registries, and training programs and support to diagnosis and treatment.ResultsNineteen of the 20 countries participating in SLAOP responded. National delegates reported nine countries with NPCCP and four of them were launched in the past 5 years. National pediatric tumor registries are available in eight countries, and three provided published survival results. Fellowship programs for training pediatric oncologists are available in 12 countries. National delegates reported that eight countries provide support to most essential diagnosis and treatments and 11 provide partial or minimal support that is supplemented by civil society organizations. Seven countries have a pediatric oncology law. There are three international cooperative groups and four national societies for pediatric oncology.ConclusionDespite many challenges, there were dramatic advances in survivorship, access to treatment, and availability of NPCCP in Latin America. Countries with highest social development scores in general provide more complete support and are more likely to have NPCCP, training programs, and reported survival results.
Simultaneous separation and determination of seven biphenyl cyclooctene lignans in Schisandra chinensis and its preparations by micellar electrokinetic chromatography with dual organic solvent system
Authors: Wang Meiyi , Ren Junzhao , Zhang Guangbin , Zhang Hongfen , Chang Ruimiao , Yu Haixia , Chen Anjia 
Published: April 2024

AbstractIntroductionGomisin is a natural dibenzo cyclooctene lignan, which is mainly derived from the family Magnoliaceae. It has anti‐inflammatory, antioxidant, anti‐tumor, anti‐aging, and hypoglycemic effects. Gomisins play important roles as medicines, nutraceuticals, food additives, and cosmetics.ObjectiveThe objective of this study is to establish a micellar electrokinetic chromatography (MEKC) method for simultaneous separation and determination of seven biphenyl cyclooctene lignans (Gomisin D, E, G, H, J, N, and O) in Schisandra chinensis and its preparations.MethodsThe method was optimized by studying the effects of the main parameters on the separation. The method has been validated and successfully applied to the determination of seven Gomisins in S. chinensis and its preparations.ResultsIn the separation system, the running buffer was composed of 20 mM Na2HPO4, 8.0 mM sodium dodecyl sulfate (SDS), 11% (v/v) methanol, and 6.0% (v/v) ethanol. A diode array detector was used with a detection wavelength of 230 nm, a separation voltage of 17 kV, and an operating temperature of 25°C. Under this condition, the seven analytes were separated at baseline within 20 min, and a good linear relationship was obtained with correlation coefficient ranging from 0.9919 to 0.9992. The limit of detection (LOD, S/N = 3) and the limit of quantification (LOQ, S/N = 10) ranged from 0.8 to 0.9 μg/mL and from 2.6 to 3.0 μg/mL, respectively. The recovery rate was between 99.1% and 102.5%.ConclusionThe experimental results indicated that this method is suitable for the separation and determination of seven Schisandra biphenyl cyclooctene lignan compounds in real samples. At the same time, it provides an effective reference for the quality control of S. chinensis and its preparations.
Deep‐learning computer vision can identify increased nuchal translucency in the first trimester of pregnancy
Authors: Kasera Bhavya , Shinar Shiri , Edke Parinita , Pruthi Vagisha , Goldenberg Anna , Erdman Lauren , Van Mieghem Tim 
Published: April 2024

AbstractObjectiveMany fetal anomalies can already be diagnosed by ultrasound in the first trimester of pregnancy. Unfortunately, in clinical practice, detection rates for anomalies in early pregnancy remain low. Our aim was to use an automated image segmentation algorithm to detect one of the most common fetal anomalies: a thickened nuchal translucency (NT), which is a marker for genetic and structural anomalies.MethodsStandardized mid‐sagittal ultrasound images of the fetal head and chest were collected for 560 fetuses between 11 and 13 weeks and 6 days of gestation, 88 (15.7%) of whom had an NT thicker than 3.5 mm. Image quality was graded as high or low by two fetal medicine experts. Images were divided into a training‐set (n = 451, 55 thick NT) and a test‐set (n = 109, 33 thick NT). We then trained a U‐Net convolutional neural network to segment the fetus and the NT region and computed the NT:fetus ratio of these regions. The ability of this ratio to separate thick (anomalous) NT regions from healthy, typical NT regions was first evaluated in ground‐truth segmentation to validate the metric and then with predicted segmentation to validate our algorithm, both using the area under the receiver operator curve (AUROC).ResultsThe ground‐truth NT:fetus ratio detected thick NTs with 0.97 AUROC in both the training and test sets. The fetus and NT regions were detected with a Dice score of 0.94 in the test set. The NT:fetus ratio based on model segmentation detected thick NTs with an AUROC of 0.96 relative to clinician labels. At a 91% specificity, 94% of thick NT cases were detected (sensitivity) in the test set. The detection rate was statistically higher (p = 0.003) in high versus low‐quality images (AUROC 0.98 vs. 0.90, respectively).ConclusionOur model provides an explainable deep‐learning method for detecting increased NT. This technique can be used to screen for other fetal anomalies in the first trimester of pregnancy.
Increase transparency and reproducibility of real‐world evidence in rare diseases through disease‐specific Federated Data Networks
Authors: van Baalen Valerie , Didden Eva‐Maria , Rosenberg Daniel , Bardenheuer Kristina , van Speybroeck Michel , Brand Monika 
Published: April 2024

AbstractPurposeIn rare diseases, real‐world evidence (RWE) generation is often restricted due to small patient numbers and global geographic distribution. A federated data network (FDN) approach brings together multiple data sources harmonized for collaboration to increase the power of observational research. In this paper, we review how to increase reproducibility and transparency of RWE studies in rare diseases through disease‐specific FDNs.MethodTo be successful, a multiple stakeholder scientific FDN collaboration requires a strong governance model in place. In such a model, each database owner remains in full control regarding the use of and access to patient‐level data and is responsible for data privacy, ethical, and legal compliance. Provided that all this is well documented and good database descriptions are in place, such a governance model results in increased transparency, while reproducibility is achieved through data curation and harmonization, and distributed analytical methods.ResultsLeveraging the OHDSI community set of methods and tools, two rare disease‐specific FDNs are discussed in more detail. For multiple myeloma, HONEUR—the Haematology Outcomes Network in Europe—has built a strong community among the data partners dedicated to scientific exchange and research. To advance scientific knowledge in pulmonary hypertension (PH) an FDN, called PHederation, was established to form a partnership of research institutions with PH databases coming from diverse origins.
Validity of ICD‐10‐based algorithms to identify patients with influenza in inpatient and outpatient settings
Authors: Benack Kirk , Nyandege Abner , Nonnenmacher Edward , Jan Saira , Setoguchi Soko , Gerhard Tobias , Strom Brian L. , Horton Daniel B. 
Published: April 2024

AbstractPurposeTo evaluate the validity of ICD‐10‐CM code‐based algorithms as proxies for influenza in inpatient and outpatient settings in the USA.MethodsAdministrative claims data (2015–2018) from the largest commercial insurer in New Jersey (NJ), USA, were probabilistically linked to outpatient and inpatient electronic health record (EHR) data containing influenza test results from a large NJ health system. The primary claims‐based algorithms defined influenza as presence of an ICD‐10‐CM code for influenza, stratified by setting (inpatient/outpatient) and code position for inpatient encounters. Test characteristics and 95% confidence intervals (CIs) were calculated using test‐positive influenza as a reference standard. Test characteristics of alternative outpatient algorithms incorporating CPT/HCPCS testing codes and anti‐influenza medication pharmacy claims were also calculated.ResultsThere were 430 documented influenza test results within the study period (295 inpatient, 135 outpatient). The claims‐based influenza definition had a sensitivity of 84.9% (95% CI 72.9%–92.1%), specificity of 96.3% (95% CI 93.1%–98.0%), and PPV of 83.3% (95% CI 71.3%–91.0%) in the inpatient setting, and a sensitivity of 76.7% (95% CI 59.1%–88.2%), specificity of 96.2% (95% CI 90.6%–98.5%), PPV of 85.2% (95% CI 67.5%–94.1%) in the outpatient setting. Primary inpatient discharge diagnoses had a sensitivity of 54.7% (95% CI 41.5%–67.3%), specificity of 99.6% (95% CI 97.7%–99.9%), and PPV of 96.7% (95% CI 83.3%–99.4%). CPT/HCPCS codes and anti‐influenza medication claims were present for few outpatient encounters (sensitivity 3%–10%).ConclusionsIn a large US healthcare system, inpatient ICD‐10‐CM codes for influenza, particularly primary inpatient diagnoses, had high predictive value for test‐positive influenza. Outpatient ICD‐10‐CM codes were moderately predictive of test‐positive influenza.
Open‐source large language models in action: A bioinformatics chatbot for PRIDE database
Authors: Bai Jingwen , Kamatchinathan Selvakumar , Kundu Deepti J. , Bandla Chakradhar , Vizcaíno Juan Antonio , Perez‐Riverol Yasset 
Published: April 2024

ABSTRACTWe here present a chatbot assistant infrastructure (https://www.ebi.ac.uk/pride/chatbot/) that simplifies user interactions with the PRIDE database's documentation and dataset search functionality. The framework utilizes multiple Large Language Models (LLM): llama2, chatglm, mixtral (mistral), and openhermes. It also includes a web service API (Application Programming Interface), web interface, and components for indexing and managing vector databases. An Elo‐ranking system‐based benchmark component is included in the framework as well, which allows for evaluating the performance of each LLM and for improving PRIDE documentation. The chatbot not only allows users to interact with PRIDE documentation but can also be used to search and find PRIDE datasets using an LLM‐based recommendation system, enabling dataset discoverability. Importantly, while our infrastructure is exemplified through its application in the PRIDE database context, the modular and adaptable nature of our approach positions it as a valuable tool for improving user experiences across a spectrum of bioinformatics and proteomics tools and resources, among other domains. The integration of advanced LLMs, innovative vector‐based construction, the benchmarking framework, and optimized documentation collectively form a robust and transferable chatbot assistant infrastructure. The framework is open‐source (https://github.com/PRIDE‐Archive/pride‐chatbot).
Development of a bronchopulmonary dysplasia nutrition focused physical examination tool: A modified Delphi study
Authors: Bathgate Jennifer R. , Pike Kimberli , Newkirk Melanie , Rigassio Radler Diane L. , Byham‐Gray Laura , Ziegler Jane 
Published: April 2024

AbstractObjectiveThe objectives of this study were to identify factors impacting nutrition needs in infants and children with bronchopulmonary dysplasia (BPD). A modified Delphi approach to obtain consensus among pediatric registered dietitian nutritionists (RDNs) was used to create a BPD‐specific nutrition focused physical examination (NFPE) tool.Study designRDNs, recruited through pediatric nutrition professional associations, completed a survey rating proposed NFPE components on a Likert scale of 1‐5 allowing open‐ended responses in a two‐round Delphi. Responses were analyzed, deidentified, and results were returned to panelists for in‐round feedback. Consensus was defined a priori as 75% agreement for usefulness or relevance ± 1 standard deviation.ResultsSix domains (anthropometrics, body composition, development, gastrointestinal, respiratory, and physical signs) and 38 components achieved consensus.ConclusionComponents for an evidence‐based tool to enhance nutrition assessment in infants and children with BPD were identified with consensus agreement by an expert panel of 19 pediatric RDNs.
Prevalence, stability, and clinical significance of an isolated low FEV1 spirometry pattern in children
Authors: Wyatt MacKenzie L. , Sokolow Andrew G. , Brown Rebekah F. , Kaslow Jacob A. , Tolle James J. , Weiner Daniel J. , Rosas‐Salazar Christian 
Published: April 2024

AbstractObjectivesIn adults, an isolated low FEV1 pattern (an FEV1 below the lower limit of normal with a preserved FVC and FEV1/FVC) has been associated with the risk of developing airway obstruction. Our objective was to examine the prevalence, stability, and clinical significance of an isolated low FEV1 pattern in the pediatric population.MethodsWe conducted a retrospective study of spirometries from children ages 6−21 years and categorized tests into spirometry patterns according to published guidelines and recent literature. In a subgroup of tests with an isolated low FEV1 pattern, we evaluated spirometry technique. We also examined the association of having a test with an isolated low FEV1 pattern with clinical markers of disease severity in a subgroup of children with cystic fibrosis (CF).ResultsThe isolated low FEV1 pattern was uncommon across the 29,979 tests included (n = 645 [2%]). In the 263 children with an isolated low FEV1 pattern who had a follow‐up test performed, the most frequent spirometry pattern at last test was normal (n = 123 [47%]). A primary diagnosis of CF was associated with increased odds of having at least one test with an isolated low FEV1 pattern (OR = 8.37, 95% CI = 4.70−15.96, p < .001). The spirometry quality in a subgroup of tests with an isolated low FEV1 pattern (n = 50) was satisfactory. In the subgroup of children with CF (n = 102), those who had a test with an isolated low FEV1 pattern had higher odds of using oral antibiotics in the last 12 months than those who had a normal pattern (OR = 3.50, 95% CI = 1.15−10.63, p = .03).ConclusionsThe isolated low FEV1 pattern can occur repeatedly over time, usually transitions to a normal pattern, is not due to a poor spirometry technique, and could be clinically relevant in children with chronic lung diseases.