bluuebunny/crossref_metadata_2025_split huggingface dataset:
Knee and hip osteoarthritis and risk of nine cancers in a large real-world matched cohort study
Authors: Turkiewicz Aleksandra , Díaz Yesika , Duarte-Salles Talita , Prieto-Alhambra Daniel 
Published: September 2021

Abstract

Objectives
Joint replacement due to end-stage OA has been linked to incidence of several cancers. We aimed to estimate the association between newly diagnosed knee and hip OA and incidence of nine common cancer types.

Methods
We identified persons with incident knee or hip OA, aged ≥40 years, between 2009 and 2015 in the SIDIAP database in Catalonia, Spain. We matched up to three OA-free controls on age, sex and general practitioner. We followed participants from 1 year after OA diagnosis until migration, death, end of study at 31 December 2017 or incident cancer of: stomach, colorectal, liver, pancreas, lung, skin, breast, prostate and bladder. We used flexible parametric survival models, adjusted for confounders. Estimates were corrected for misclassification using probabilistic bias analysis.

Results
We included 117 750 persons with knee OA and matched 309 913 persons without, with mean (s.d.) age of 67.5 (11.1) years and 63% women. The hip cohort consisted of 39 133 persons with hip OA and 116 713 controls. For most of the included cancers, the hazard ratios (HRs) were close to 1. The HR of lung cancer for knee OA exposure was 0.80 (95% CI: 0.71, 0.89) and attenuated to 0.98 (0.76, 1.27) in non-smokers. The hazard of colorectal cancer was lower in persons with both knee and hip OA by 10–20%.

Conclusions
Knee and hip OA are not associated with studied incident cancers, apart from lower risk of colorectal cancer. The often-reported protective association of knee OA with lung cancer is explained by residual confounding.
Time in remission as an alternative outcome measure for rheumatoid arthritis: a 10-year prospective study of 2618 new users of anti-TNF
Authors: Tužil Jan , Mlčoch Tomáš , Závada Jakub , Svoboda Michal , Pavelka Karel , Doležal Tomáš 
Published: September 2021

Abstract

Objective
Achieving targeted disease activity (DA) is the primary therapeutic strategy in RA. Point measurements of DA are done at out-patient visits, however true DA between visits remains unobserved. This study sought to describe and validate a new outcome measure, i.e. time in remission (TIR).

Methods
Patients were enrolled in the Czech ATTRA-RA registry. TIR was calculated using linear interpolation of the DAS28-ESR determined at outpatient visits. Correlation coefficients were computed between TIR and DAS28-CRP, HAQ, Simple Disease Activity Index (SDAI), patient global assessment (PGA) and physician global assessment (PhGA). Using logistic regression, TIR was used as a predictor of remission (SDAI ≤3.3) and non-disability (HAQ &lt;0.5). The predictive value of TIR was compared with point and sustained remission using the cross-validated area under receiver-operating curves.

Results
Since 2010, 2618 RA patients started anti-TNF therapy and were followed until 2020 or until treatment discontinuation. During the first 6 months of therapy, 56% of patients had no remission (TIR = 0), and 22% of patients reached sustained remission (TIR = 1), while 22% of patients had point remissions with 0 &lt; TIR &lt; 1. EULAR good responders and moderate/non-responders spent 64 ± 42% and 6 ± 18% of time in remission, respectively. The mean TIR grew during the follow-up and was correlated with DAS28-CRP, SDAI, HAQ, PGA, and PhGA (P &lt; 0.0001). TIR at 3 and 6 months predicted remission (SDAI ≤3.3) and non-disability (HAQ &lt;0.5) at 13 and 19 months better than point or sustained remission.

Conclusions
TIR is an intuitive way of estimating unobserved DA between scheduled visits; its calculation only requires two consecutive DA values (https://www.medevio.cz/tir-calculator/). TIR is a valid predictor of RA outcomes.
Tumour necrosis factor inhibitor dose adaptation in psoriatic arthritis and axial spondyloarthritis (TAPAS): a retrospective cohort study
Authors: Michielsens Celia A J , den Broeder Nathan , Mulder Michelle L M , van den Hoogen Frank H J , Verhoef Lise M , den Broeder Alfons A 
Published: September 2021

Abstract

Objectives
We investigated the effect of disease activity-guided dose optimization (DAGDO) of TNF inhibitor (TNFi) on disease activity and TNFi dose in PsA and axial spondyloarthritis (axSpA) patients with low disease activity (LDA).

Methods
A retrospective cohort study was conducted in PsA and axSpA patients doing well on TNFi and eligible for TNFi DAGDO. Three different treatment periods were defined: (i) full dose continuation period, (ii) TNFi DAGDO period, and (iii) period with stable TNFi dose after DAGDO. A mixed-model analysis was used to estimate mean Disease Activity Score 28-joint count CRP (DAS28-CRP) and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) during these periods, and a mean percentage of the daily defined dose (%DDD) was calculated as secondary outcome.

Results
Three hundred and twenty-four patients (153 PsA and 171 axSpA) were included, with a mean of 6.5 DAS28-CRP and 6.4 BASDAI measurements and a median follow-up duration of 46 and 44 months, respectively. A corrected difference of 0.06 (95% CI: −0.09, 0.21) in mean DAS28-CRP was found for the TNFi DAGDO period and 0.03 (95% CI: −0.14, 0.20) for the period with stable TNFi dose, compared with full dose continuation period. Differences for BASDAI were 0.03 (95% CI: −0.21, 0.27) and 0.05 (95% CI: −0.24, 0.34), respectively. The mean %DDD for the three treatment periods was for PsA 108%, 62% and 78%, and for axSpA 108%, 62% and 72%, respectively.

Conclusion
DAGDO of TNFi reduces drug exposure and has no negative effects on disease activity in PsA and axSpA patients compared with full dose continuation.
Serum lipidomics reveals distinct metabolic profiles for asymptomatic hyperuricemic and gout patients
Authors: Liu Shijia , Wang Yingzhuo , Liu Huanhuan , Xu Tingting , Wang Ma-Jie , Lu Jiawei , Guo Yunke , Chen Wenjun , Ke Mengying , Zhou Guisheng , Lu Yan , Chen Peidong , Zhou Wei 
Published: September 2021

Abstract

Objectives
This study aimed to characterize the systemic lipid profile of patients with asymptomatic hyperuricemia (HUA) and gout using lipidomics, and to find potential underlying pathological mechanisms therefrom.

Methods
Sera were collected from Affiliated Hospital of Nanjing University of Chinese Medicine as centre 1 (discovery and internal validation sets) and Suzhou Hospital of Traditional Chinese Medicine as centre 2 (external validation set), including 88 normal subjects, 157 HUA and 183 gout patients. Lipidomics was performed by ultra high performance liquid chromatography plus Q-Exactive mass spectrometry (UHPLC-Q Exactive MS). Differential metabolites were identifed by both variable importance in the projection ≥1 in orthogonal partial least-squares discriminant analysis mode and false discovery rate adjusted P ≤ 0.05. Biomarkers were found by logistic regression and receiver operating characteristic (ROC) analysis.

Results
In the discovery set, a total of 245 and 150 metabolites, respectively, were found for normal subjects vs HUA and normal subjects vs gout. The disturbed metabolites included diacylglycerol, triacylglycerol (TAG), phosphatidylcholine, phosphatidylethanolamine, phosphatidylinositol, etc. We also found 116 differential metabolites for HUA vs gout. Among them, the biomarker panel of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 could differentiate well between HUA and gout. The area under the receiver operating characteristic ROC curve was 0.8288, the sensitivity was 82% and the specificity was 78%, at a 95% CI 0.747, 0.9106. In the internal validation set, the predictive accuracy of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 panel for differentiation of HUA and gout reached 74.38%, while it was 84.03% in external validation set.

Conclusion
We identified serum biomarkers panel that have the potential to predict and diagnose HUA and gout patients.
America’s Most Divided Sport: Polarization and Inequality in Attitudes about Youth Football
Authors: Lindner Andrew M , Hawkins Daniel N 
Published: September 2021

AbstractFootball may be America’s most popular sport, but with growing evidence of the risk of sport-associated concussions, some adults are reconsidering which sports to encourage children to play. Using data from a nationally representative sample of 958 respondents, we examine how political party, belief in patriotic displays in sport, attention to concussion news, social class, and race are associated with support for children playing each of the five major U.S. sports: baseball, basketball, hockey, soccer, and football. Our findings suggest that unlike other sports, attitudes about youth participation in football are divided by views on patriotism in sport, age, race, education, and attention to concussion news. For many Americans, football is connected to participation in a civil religion, which celebrates national pride and respect for the military. We argue that child safety advocates who aim to steer children away from football must grapple with the deeper cultural and identity-based framework associated with the sport.
A Comparative Analysis of the Fiduciary Duties of Loyalty of Trustees in English Common Law and Chinese Law
Authors: Tian Shulun 
Published: September 2021

Abstract
England is the cradle of trusts and China introduced this flexible institution for its own needs and promulgated its trust law in 2001. Different to England, China does not have unified fiduciary doctrines and the Chinese trust has a strong contractarian nature. This article compares Chinese law and English law in terms of the rules about trustees’ duties of loyalty. The apparent differences reflected on micro rules may find their explanation in the macro trust structures and legislative backgrounds.
Gestational Exposure to Ultrafine Particles Reveals Sex- and Dose-Specific Changes in Offspring Birth Outcomes, Placental Morphology, and Gene Networks
Authors: Behlen Jonathan C , Lau Carmen H , Li Yixin , Dhagat Prit , Stanley Jone A , Rodrigues Hoffman Aline , Golding Michael C , Zhang Renyi , Johnson Natalie M 
Published: September 2021

AbstractParticulate matter (PM) causes adverse developmental outcomes following prenatal exposure, but the underlying biological mechanisms remain uncertain. Here we elucidate the effects of diesel exhaust ultrafine particle (UFP) exposure during pregnancy on placental and fetal development. Time-mated C57Bl/6n mice were gestationally exposed to UFPs at a low dose (LD, 100 µg/m3) or high dose (HD, 500 µg/m3) for 6 h daily. Phenotypic effects on fetuses and placental morphology at gestational day (GD) of 18.5 were evaluated, and RNA sequencing was characterized for transcriptomic changes in placental tissue from male and female offspring. A significant decrease in average placental weights and crown to rump lengths was observed in female offspring in the LD exposure group. Gestational UFP exposure altered placental morphology in a dose- and sex-specific manner. Average female decidua areas were significantly greater in the LD and HD groups. Maternal lacunae mean areas were increased in the female LD group, whereas fetal blood vessel mean areas were significantly greater in the male LD and HD groups. RNA sequencing indicated several disturbed cellular functions related to lipid metabolism, which were most pronounced in the LD group and especially in female placental tissue. Our findings demonstrate the vulnerability of offspring exposed to UFPs during pregnancy, highlighting sex-specific effects and emphasizing the importance of mitigating PM exposure to prevent adverse health outcomes.
Characterization of the early gene expression profile inPopulus ussuriensisunder cold stress using PacBio SMRT sequencing integrated with RNA-seq reads
Authors: Li Wenlong , Fu Yanrui , Lv Wanqiu , Zhao Shicheng , Feng He , Shao Liying , Li Chenghao , Yang Jingli 
Published: September 2021

AbstractPopulus ussuriensis is an important and fast-growing afforestation plant species in north-eastern China. The whole-genome sequencing of P. ussuriensis has not been completed. Also, the transcriptional network of P. ussuriensis response to cold stress remains unknown. To unravel the early response of P. ussuriensis to chilling (3 °C) stress and freezing (−3 °C) stresses at the transcriptional level, we performed single-molecule real-time (SMRT) and Illumina RNA sequencing for P. ussuriensis. The SMRT long-read isoform sequencing led to the identification of 29,243,277 subreads and 575,481 circular consensus sequencing reads. Approximately 50,910 high-quality isoforms were generated, and 2272 simple sequence repeats and 8086 long non-coding RNAs were identified. The Ca2+ content and abscisic acid (ABA) content in P. ussuriensis were significantly increased under cold stresses, while the value in the freezing stress treatment group was significantly higher than the chilling stress treatment group. A total of 49 genes that are involved in the signal transduction pathways related to perception and transmission of cold stress signals, such as the Ca2+ signaling pathway, ABA signaling pathway and MAPK signaling cascade, were found to be differentially expressed. In addition, 158 transcription factors from 21 different families, such as MYB, WRKY and AP2/ERF, were differentially expressed during chilling and freezing treatments. Moreover, the measurement of physiological indicators and bioinformatics observations demonstrated the altered expression pattern of genes involved in reactive oxygen species balance and the sugar metabolism pathway during chilling and freezing stresses. This is the first report of the early responses of P. ussuriensis to cold stress, which lays the foundation for future studies on the regulatory mechanisms in cold-stress response. In addition the full-length reference transcriptome of P. ussuriensis deciphered could be used in future studies on P. ussuriensis.
Predictors of rheumatic fever in sore throat patients: a systematic review and meta-analysis
Authors: Kulik Ellen , Stuart Beth , Willcox Merlin 
Published: September 2021

Abstract

Background
Concerns about rheumatic fever (RF) drive antibiotic prescriptions for sore throat (ST) in endemic areas. Better guidance is needed on which patients are likely to develop RF in order to avoid misuse and overuse of antibiotics. Our aim was to identify predictive factors for RF in ST patients.

Methods
Multiple databases were searched to identify cohort, case–control, cross-sectional or randomised controlled trials that measured RF incidence in ST patients. An inverse variance random effects model was used to pool the data and calculate odds ratios (ORs).

Results
Seven studies with a total of 6890 participants were included: three RCTs and four observational studies. Factors significantly associated with RF development following ST were positive group A streptococcal (GAS) swab (OR 1.74 [95% confidence interval {CI} 1.13 to 2.69]), previous RF history (OR 13.22 [95% CI 4.86 to 35.93]) and a cardiac murmur (OR 3.55 [95% CI 1.81 to 6.94]). Many potential risk factors were not reported in any of the included studies, highlighting important evidence gaps.

Conclusions
ST patients in endemic areas with a positive GAS swab, previous RF history and a cardiac murmur are at increased risk of developing RF. This review identifies vital gaps in our knowledge of factors predicting RF development in ST patients. Further research is needed to develop better clinical prediction tools and rationalise antibiotic use for ST.
Analysis of Differentially Expressed Rice Genes Reveals the ATP-Binding Cassette Transporters as Candidate Genes Against the Sheath Blight Pathogen, Rhizoctonia solani
Authors: Oh Youngjae , Lee Seonghee , Rioux Renee , Singh Pratibha , Jia Melissa H. , Jia Yulin , Mysore Kirankumar S. 
Published: September 2021

Sheath blight is a serious rice disease worldwide, and genes involved in resistance remain unclear. In the present study, a virulent field isolate of Rhizoctonia solani was used to inoculate detached leaves of a sheath blight-resistant rice cultivar, Jasmine 85; a suppression subtractive cDNA library was constructed using RNA isolated 16 h postinoculation (hpi); and differentially expressed genes were identified from the cDNA library. A total of 159 uniquely expressed sequence tags were identified, including 105 from rice with enrichment in categories related to cellular response, molecular signaling, and host defense. Coupled with gene expression studies by DNA microarray, 27 highly induced genes involved in signal transduction and defense responses were identified within 16 hpi. Three members of the ATP-binding cassette (ABC) transporter gene family ( OsABC1, OsABC9, and OsABC12) encoding pleiotropic drug resistance-like ABC transporters were mapped to different sheath blight resistance quantitative trait loci (QTLs), and their differential expressions were validated. Three high-resolution melting (HRM) markers were developed from these ABC gene family members to distinguish alleles between sheath blight-susceptible cultivar Lemont and resistant cultivar Jasmine 85. Association of sheath blight resistance to these HRM markers was examined in 77 recombinant inbred lines derived from the cross between Jasmine 85 and Lemont. The OsABC9 gene located in a major sheath blight resistance QTL qShB9-2 showed a major contribution to sheath blight resistance. These results are useful for marker-assisted selection and functional validation of the ABC genes in sheath blight disease resistance. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022.
Effects of Diet on the Microbiome and Serum Metabolome of South Asian Infants at 1 Year
Authors: Bruce Colin Y. , Shanmuganathan Meera , Azab Sandi M. , Britz-McKibbin Philip , Anand Sonia S. , de Souza Russell J. , Stearns Jennifer C. 
Published: September 2021

AbstractDiet is known to affect the gut microbiome and metabolome composition in adults, but this has not been fully explored in infants. Dietary patterns from 1 year-old infants (n=182) from the South Asian Birth Cohort (START) study were compared to gut microbiome alpha and beta diversity and to taxa abundance differences. Diet – serum metabolite associations were identified using multivariate analysis (partial least squares-discriminant analysis, PLS-DA) and univariate analysis (T-Test). Dietary biomarkers identified from START were also examined in a separate cohort of white Caucasian infants (CHILD Cohort Study, n=82). Lastly, the association of diet with gut microbiome and serum biomarkers, considering maternal, perinatal and infant characteristics was investigated using multivariate forward stepwise regression. A dietary pattern characterized by breastfeeding, supplemented by formula and dairy was the strongest predictor of the gut microbiome that also differentiated the serum metabolome of infants. The formula and dairy dietary pattern was associated with a panel of circulating metabolites in both cohorts, including: S-methylcysteine, branched-chain/aromatic amino acids, lysine, dimethylglycine, and methionine. Breastfeeding status, the prominent feature of the dietary pattern, was also associated with a sub-set of serum metabolites in both cohorts. In START, this diet pattern was associated with the metabolites tryptophan betaine, 2-hydroxybutyric acid, tyrosine, phenylalanine, and trimethyl-N-oxide. In the CHILD Cohort Study(CHILD), breastfeeding status was associated with the metabolites aminooctanoic acid, 3-hydroxybutyric acid, and methyl-proline. The results of our study suggest that breastfeeding has the largest effect on the composition of the gut microbiome and the serum metabolome at 1 year, even when solid food diet and other covariates are considered.
An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
Authors: Pham Hieu H. , Nguyen Ha Q. , Lam Khanh , Le Linh T. , Nguyen Dung B. , Nguyen Hieu T. , Le Tung T. , Nguyen Thang V. , Dao Minh , Vu Van 
Published: September 2021

ABSTRACTInterpretation of chest radiographs (CXR) is a difficult but essential task for detecting thoracic abnormalities. Recent artificial intelligence (AI) algorithms have achieved radiologist-level performance on various medical classification tasks. However, only a few studies addressed the localization of abnormal findings from CXR scans, which is essential in explaining the image-level classification to radiologists. Additionally, the actual impact of AI algorithms on the diagnostic performance of radiologists in clinical practice remains relatively unclear. To bridge these gaps, we developed an explainable deep learning system called VinDr-CXR that can classify a CXR scan into multiple thoracic diseases and, at the same time, localize most types of critical findings on the image. VinDr-CXR was trained on 51,485 CXR scans with radiologist-provided bounding box annotations. It demonstrated a comparable performance to experienced radiologists in classifying 6 common thoracic diseases on a retrospective validation set of 3,000 CXR scans, with a mean area under the receiver operating characteristic curve (AUROC) of 0.967 (95% confidence interval [CI]: 0.958–0.975). The sensitivity, specificity,F1-score, false-positive rate (FPR), and false-negative rate (FNR) of the system at the optimal cutoff value were 0.933 (0.898–0.964), 0.900 (0.887–0.911), 0.631 (0.589–0.672), 0.101 (0.089– 0.114) and 0.067 (0.057–0.102), respectively. For the localization task with 14 types of lesions, our free-response receiver operating characteristic (FROC) analysis showed that the VinDr-CXR achieved a sensitivity of 80.2% at the rate of 1.0 false-positive lesion identified per scan. A prospective study was also conducted to measure the clinical impact of the VinDr-CXR in assisting six experienced radiologists. The results indicated that the proposed system, when used as a diagnosis supporting tool, significantly improved the agreement between radiologists themselves with an increase of 1.5% in mean Fleiss’ Kappa. We also observed that, after the radiologists consulted VinDr-CXR’s suggestions, the agreement between each of them and the system was remarkably increased by 3.3% in mean Co-hen’s Kappa. Altogether, our results highlight the potentials of the proposed deep learning system as an effective assistant to radiologists in clinical practice. Part of the dataset used for developing the VinDr-CXR system has been made publicly available athttps://physionet.org/content/vindr-cxr/1.0.0/.