bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of Seasonal Ambient Air Pollution With a Risk of Adverse Perinatal Outcomes in Full-term Pregnancies: A Retrospective Cohort Study in Wenzhou, China
Authors: Huang Huijun , Yu Qiu-Yan , Zheng Tian , Wang Shan-shan , Yang Xin-Jun 
Published: January 2022

Abstract
Prenatal exposures to ambient air pollution have been proved to be associated with adverse perinatal outcomes in previous studies. However, few studies have examined the interaction between air pollution and season of conception on term low birth weight (TLBW) or macrosomia. Birth registry data of singleton live births in Wenzhou, China between January 2015 to December 2016 were accessed from the Wenzhou maternal and child health information management platform, and the ambient air pollutants in Wenzhou were obtained on the Chinese Air Quality Online Monitoring and Analysis Platform. Single/two-pollutant binary logistic regression models were used to assess the associations between ambient air pollutants (PM2.5, PM10, NO2, SO2, and O3) and TLBW/macrosomia, further exploring if the season of conception interacts with air pollution to impact birth weight. Finally, 213,959 term newborns were selected, including 2452 (1.1 %) TLBW infants and 13173 (6.1 %) macrosomia. In single/two-pollutant models, we observed an increased risk of TLBW associated with maternal exposure to PM2.5, PM10, SO2, and NO2 during the entire pregnancy, especially in the the 2nd trimester. Maternal exposure to O3 during the 1st trimester was associated with increased macrosomia risk, and O3 exposure during the 3rd trimester was associated with increased TLBW risk contrarily. Pregnant women conceived in the warm season may undergo more adverse ambient air environment that is related to the risks of TLBW.
Racial and Ethnic Disparities in the Refusal of Surgical Treatment in Women 40 Years and Older With Breast Cancer in the United States Between 2010 and 2017
Authors: Fwelo Pierre , Yusuf Zenab , Adjei Abigail , Huynh Gabriel , Du Xianglin 
Published: January 2022

Abstract
Purpose Although surgical resection is the main modality of treatment for breast cancer, some patients elect to refuse the recommended surgery. We assessed racial and ethnic differences in women 40 years and older who received or refused to receive surgical treatment for breast cancer in the United States and whether racial disparities in mortality were affected by their differences in the prevalence of refusal for surgical treatmentMethods We studied 277,127 women with breast cancer using the Surveillance, Epidemiology, and End Results (SEER) data and performed multivariable logistic regressions to investigate the association between surgery status of breast cancer and race/ethnicity. Additionally, we performed Cox logistic regression analyses to determine the predictors of mortality outcomes. Results Of 277,127 patients with breast cancer, 1,468 (0.53%) refused to receive the recommended surgical treatment in our cohort. Non-Hispanic Black women were 112% more likely to refuse recommended surgical treatment for breast cancer compared to their non-Hispanic White counterparts [adjusted odds ratio: 2.12, 95% confidence interval (CI)=1.82-2.47]. Women who underwent breast conserving surgery [hazards ratio (HR): 0.15, 95% CI: 0.13-0.16] and mastectomy (HR:0.21, 95% CI: 0.18-0.23) had lower hazard ratios of mortality as compared to women who refused the recommended treatment after adjusting for covariates. Conclusion Race/ethnicity was associated with refusal for recommended surgery, especially among non-Hispanic Black women. Also, surgery refusal was associated with a higher risk of all-cause and breast cancer-related mortality. These disparities stress the need to tailor interventions aimed at raising awareness of the importance of following physician recommendations among minorities.
The Valuable Role of Armc1 in Invasive Breast Cancer as a Novel Biomarker
Authors: Gan Yunhao , Zhong Fuxin , Li Lingyu , Wang Hao 
Published: January 2022

Abstract
Background: Invasive breast carcinoma (BRCA) is a common type of breast cancer with high incidence in clinics, so it is significant to find an effective biomarker for BRCA diagnosis and treatment. Although some Armadillo (Arm)-repeat proteins families are confirmed to be biomarkers in cancers, the role of Armadillo repeat-containing 1 (ARMC1) in BRCA remains unknown.Methods: We analyzed the ARMC1 expression in normal breast tissues and BRCA samples, and its association with overall survival by the public database. χ² test evaluated the risks associated with ARMC1 expression in TCGA-BRCA patient samples. The ARMC1 mutations in BRCA were explored in the cBioportal database. Besides, the GO and KEGG analysis was used to explore the potential signaling pathways of ARMC1 in BRCA. Lastly, Immunohistochemistry and immunohistochemistry were performed to validate the ARMC1 expression in BRCA.Results: ARMC1 level in tumor sample was significantly higher than that in normal tissue, and it was also related to lower survival. The factors in clinical patients such as tumor stage and grade and histology were associated with ARMC1 expression. There were 32% of ARMC1 genetic mutations in BRCA, and the amplification and high expression made up the majority of them. Also, ARMC1 might regulate BRCA by involving in the cell cycle. Increased ARMC1 expression was found in clinical breast carcinoma tissues by our confirmatory experiments.Conclusions: All the results revealed that ARMC1 may play a significant role in BRCA as a biomarker, it provides valuable clues for the treatment and diagnosis of invasive breast cancer.
Genome-Wide Association Analysis To Delineate High-Quality Snps For Seed Micronutrient Density In Chickpea (Cicer Arietinum L.)
Authors: Fayaz Humara , Tyagi Sandhya , Wani Aijaz A. , Pandey Renu , Akhtar Sabina , Bhat Mohd Ashraf , Chitikineni Annapurna , Varshney Rajeev Kumar , Thudi Mahendar , Kumar Upendra , Mir Reyazul Rouf 
Published: January 2022

Abstract
Chickpea is the most important nutrient rich grain legume crop in the world. A diverse core set of 147 chickpea genotypes was genotyped with 50K Cicer SNP array and trait phenotyped in two different environments for four seed micro-nutrients (Cu, Fe, Mn, and Zn). The trait data and high-throughput 50K SNP genotypic data was used for genome-wide association study (GWAS) that led the discovery of gene/QTLs for seed Cu, Fe, Mn, and Zn concentrations in chickpea. The analysis of seed micronutrient data revealed significant differences for all the four micronutrient concentrations (P ≤ 0.05). The mean concentration of seed Fe, Zn, Cu, and Mn pooled over two-year data was 146.1 ppm, 45.9 ppm, 63.8 ppm and 27.0 ppm respectively. The analysis of results led to the identification of 35 SNPs significantly associated with seed Zn, Cu, Fe and Mn concentrations. Among these 35 MTAs, 5 were stable (consistently identified in different environments), 6 were major (explain more than 15% phenotypic variation for an individual trait) and 3 were both major and stable MTAs. The stable and major MTAs identified during the present study shall prove useful in molecular breeding programs aimed at enhancing seed nutrient density of chickpea.
A Framework to Support the Progressive Implementation of Integrated Team-based Care for the Management of Copd: a Collective Case Study
Authors: Sibbald Shannon L. , Misra Vaidehi , daSilva Madelyn , Licskai Christopher 
Published: January 2022

Abstract
Background: In Canada, there is widespread agreement about the need for integrated models of team-based care. However, there is less agreement on how to support the scale-up and spread of successful models; there is limited empirical evidence to support this process in chronic disease management. We studied the supporting, and mitigating factors required to successfully implement and scale-up an integrated model of team-based care in primary care.Methods: We conducted a collective case study using multiple methods of data collection including interviews, document analysis, living documents, and a focus group. Our study explored a team-based model of care for chronic obstructive pulmonary disease (COPD) known as Best Care COPD (BCC) that has been implemented in primary care settings across Southwestern Ontario. BCC is a quality improvement initiative that was developed to enhance the quality of care for patients with COPD. Participants included healthcare providers involved in the delivery of the BCC program. Results: We identified several mechanisms influencing the scale-up and spread of BCC and categorized them as Foundational (e.g., evidence-based program, readiness to implement, peer-led implementation team), Transformative (adaptive process, empowerment and collaboration, embedded evaluation), and Enabling Mechanisms (provider training, administrative support, role clarity, patient outcomes). Based on these results, we developed a framework to inform the progressive implementation of integrated, team-based care for chronic disease management. Our framework builds off our empirical work and is framed by local contextual factors. Conclusions: This study explores the implementation and spread of integrated team-based care in a primary care setting. Despite the study’s focus on COPD, we believe the findings can be applied in other chronic disease contexts. We provide a framework to support the progressive implementation of integrated team-based care for chronic disease management.
High-Entropy-Stabilized Polyanionic Cathodes with Multiple Redox Reactions for Sodium-Ion Battery Applications
Authors: Li Huangxu , Xu Ming , Long Huiwu , Zheng Jingqiang , Yuan Kuo , Zhang Liuyun , Xie YangYang , Li Shihao , Gao Jun , Lai Yanqing , Zhang Zhian 
Published: January 2022

Abstract
High-entropy (HE) materials containing multiple elements have created a growing interest in exploring the property limits of electrodes in energy storage and understanding the underlying chemical/physical mechanisms. Here, we show a substantial improvement in performance of HE-based cathodes in sodium-ion batteries (SIBs). Polyanionic structure has a large compositional flexibility and can incorporate many active transition-metal (TM) species, which is an ideal platform to design HE cathode materials. As a proof of concept, we show that HE sodium superionic conductor (HE-NASICON) materials can be synthesized via a facile sol-gel method. By comparing a group of HE-NASICON cathodes containing different contents of TM species, we demonstrate that the multi-Na-ions intercalation/deintercalation process is highly reversible, whereas capacity and cycling stability are improved. The HE-NASICON cathode with equal molarity of five TM species achieves a high capacity of 161 mA h g−1 and capacity retention of 85% when cycling at a high rate of 5 C over 1000 cycles. In-situ XRD and spherical-aberration-corrected transmission electron microscope (ACTEM) also demonstrate a robust trigonal phase with a volume change of merely 4.07% during the multi-Na-ions storage. These results reveal the effectiveness of HE concept in expediting high-performance polyanionic cathodes for real SIBs applications.
An Evaluation Framework Combining Real-Time Transmission Electron Microscopy and Integrated Machine Learning-Particle Filter Estimation Enables Detection and Quantitative Tracking of Nanoscale Defects During Plastic Deformation Processes
Authors: Sasaki Kai , Muramatsu Mayu , Hirayama Kenta , Endo Katsuhiro , Murayama Mitsuhiro 
Published: January 2022

Abstract
Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.
Alternative Liquid Assisted-Sintering of AL/CU Composites Using Selective Powders of AS-Cast Al-ZN Alloy
Authors: Ortiz Eder Lopes , Osório Wislei Riuper , Bortolozo Ausdinir Danilo , Padilha Giovana da Silva 
Published: January 2022

Abstract
Al and its alloys constitute one of the most versatile, economical and attractive materials for a wide range of applications. The 7xxx and 2xxx series alloys are those of achieving the highest mechanical strength among aluminum alloys. In this investigation, using powder metallurgy provides the microstructural and mechanical properties characterizations of non-commercial Al6Cu5Zn alloy by using powder metallurgy. Initial powder sizes are determined and the best condition is obtained for the distribution comprised between 75-106 μm. The samples are sintered at 585 oC, 600 oC and 615 oC during 0.5, 1.5 h and 3 h. It is found that mechanical behavior similar to as-cast Al-Cu based alloys is attained (~ 125 MPa) when the samples at 615 oC during 3 h are sintered. Considering the reduction of energy consumption and metal fumes commonly produced in foundry, Al-Zn powder can be used with Al and Cu elemental powders to constitute an Al6Cu5Zn alloy.
3-oxo-C12:2-HSL, Quorum Sensing Molecule from Human Intestinal Microbiota, Inhibits Pro-inflammatory Pathways in Immune Cells via Bitter Taste Receptors
Authors: Coquant Garance , Aguanno Doriane , Brot Loic , Belloir Christine , Delugeard Julie , Roger Nathalie , Pham Hang-Phuong , Briand Loic , Moreau Marielle , De Sordi Luisa , Carrière Véronique , Grill Jean-Pierre , Thenet Sophie , Seksik Philippe 
Published: January 2022

Abstract
In the gut ecosystem, microorganisms regulate group behaviour and interplay with the host via a molecular system called quorum sensing (QS). The QS molecule 3-oxo-C12:2-HSL, first identified in human gut microbiota, exerts anti-inflammatory effects and could play a role in inflammatory bowel diseases where dysbiosis has been described. Our aim was to identify which signalling pathways are involved in this effect. We observed that 3-oxo-C12:2-HSL decreases expression of pro-inflammatory cytokines such as, Interleukine-1β (-3 %) and Tumor Necrosis Factor-α (TNFα) (40 %) by stimulated immune RAW264.7 cells and decreased TNF secretion by stimulated PBMC in a dose-dependent manner, between 25 µM to 100 µM. Transcriptomic analysis of RAW264.7 cells exposed to 3-oxo-C12:2-HSL, in a pro-inflammatory context, highlighted JAK-STAT, NF-κB and TFN signalling pathways and we confirmed that 3-oxo-C12:2-HSL inhibited JAK1 and STAT1 phosphorylation. We also showed through a screening assay that 3-oxo-C12:2-HSL interacted with several human bitter taste receptors. Its anti-inflammatory effect involved TAS2R38 as shown by pharmacologic inhibition and led to an increase in intracellular calcium levels. We thus unravelled the involvement of several cellular pathways in the anti-inflammatory effects exerted by the QS molecule 3-oxo-C12:2-HSL.
Building Reliable Radiomic Models Using Image Perturbation
Authors: Teng Xinzhi , Zhang Jiang , Zwanenburg Alex , Sun Jiachen , Huang Yu-hua , Lam Saikit , Zhang Yuanpeng , Li Bing , Zhou Ta , Xiao Haonan , Liu Chenyang , Li Wen , Han Xinyang , Ma Zongrui , Cai Jing , Li Tian 
Published: January 2022

Abstract
Radiomic model reliability is a central premise for its clinical translation. Presently, it is assessed using test-retest or external data, which, unfortunately, is often scarce in reality. Therefore, we aimed to develop a novel image perturbation-based method (IPBM) for the first of its kind toward building a reliable radiomic model. We first developed a radiomic prognostic model for head-and-neck cancer patients on a training (70%) and evaluated on a testing (30%) cohort using C-index. Subsequently, we applied the IPBM to CT images of both cohorts (Perturbed-Train and Perturbed-Test cohort) to generate 60 additional samples for both cohorts. Model reliability was assessed using intra-class correlation coefficient (ICC) to quantify consistency of the C-index among the 60 samples in the Perturbed-Train and Perturbed-Test cohorts. Besides, we re-trained the radiomic model using reliable RFs exclusively (ICC>0.75) to validate the IPBM. Results showed moderate model reliability in Perturbed-Train (ICC:0.565, 95%CI:0.518-0.615) and Perturbed-Test (ICC:0.596, 95%CI:0.527-0.670) cohorts. An enhanced reliability of the re-trained model was observed in Perturbed-Train (ICC:0.782, 95%CI:0.759-0.815) and Perturbed-Test (ICC:0.825, 95%CI:0.782-0.867) cohorts, indicating validity of the IPBM. To conclude, we demonstated capability of the IPBM toward building reliable radiomic models, providing community with a novel model reliability assessment strategy prior to prospective evaluation.
Adherence to Mediterranean-DASH Intervention for Neurodegenerative Delay Diet Can Decreased Risk of Age Associated Poor Muscle Strength; A Cross- Sectional from Kurdish Cohort Study
Authors: Pasdar Yahya , Moradi Shima , Saedi Saman , Hamzeh Behrooz , Najafi Farid 
Published: January 2022

Abstract
The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet aims to reduce dementia and the decline in brain health that often occurs as people get older. Loss of muscle strength (sarcopenia) is a geriatric syndrome that has associated with the loss of skeletal muscle mass and strength. The current study aimed to investigate the association between adherence to MIND diet and decrease the risk of age-associated poor muscle strength. This cross-sectional study was performed using data from Ravansar's non-communicable diseases (RaNCD) cohort study on 3181 adults (48.5% men) aged 35–65 years. The dietary intake of the studied participants was assessed by the use of a 114-item food frequency questionnaire (FFQ) developed by RaNCD cohort study. The MIND diet and the major dietary patterns were computed based on their dietary intake and three dietary patterns were identified including plant-based diet, high protein diet, and unhealthy diet. Hand grip strength (HGS) was measured using a hand-held hydraulic handgrip dynamometer and poor HGS was defined as HGS less than 32.8 and 20.5 kg in men and women, respectively. We found that greater adherence to MIND diet was associated with lower risk of poor HGS (OR: 0.65; CI 95%: 0.51-0.83). Furthermore, participants who were in third tertiles of plant- based and high protein diet were more likely 37% and 33% lower risk of poor HGS (OR: 0.63; CI 95%: 0.5-0.79), (OR: 0.67; CI 95%: 0.54-0.84), respectively. On the other hand, greater following to unhealthy diet was related to higher risk of poor HGS (OR: 1.39; CI 95%: 1.11-1.74). Overall, our findings provide that adhere to plant- based and high protein diet, as well as MIND diet had protective effects on age related poor HGS, while adherence to unhealthy diet can developed age related poor HGS.
Resolving Missing Protein Problems Using Functional Class Scoring
Authors: Wong Bertrand Jernhan , Kong Weijia , Wong Limsoon , Goh Wilson Wen Bin 
Published: January 2022

Abstract
Despite technological advances in proteomics, incomplete coverage and inconsistency issues persist, resulting in “data holes”. These data holes cause the missing protein problem (MPP), where relevant proteins are persistently unobserved, or sporadically observed across samples. This hinders biomarker and drug discovery from proteomics data. Network-based approaches are powerful: The Functional Class Scoring (FCS) method using protein complexes was able to easily recover missed proteins with weak or partial support. However, there are limitations: The verification approach (in determining missing protein recovery) is potentially biased as the test data was based on relatively outdated Data-Dependent Acquisition (DDA) proteomics and FCS does not provide a scoring scheme for individual protein components (in significant complexes). To address these issues: First, we devised a more rigorous evaluation of FCS based on same-sample technical replicates. And second, we evaluate using data from more recent Data-Independent Acquisition (DIA) technologies (viz. SWATH).Although cross-replicate examination reveals some inconsistencies amongst same-class samples, tissue-differentiating signal is nonetheless strongly conserved. This confirms FCS as a viable method that selects biologically meaningful networks. We also report that predicted missing proteins are statistically significant based on FCS p-values. Although cross-replicate verification rates are not spectacular, the predicted missing proteins as a whole, have higher peptide support than non-predicted proteins. FCS also has the capacity to predict missing proteins that are often lost due to weak specific peptide support. As a yet unresolved limitation, we find that FCS cannot assign meaningful probabilities to individual protein components (no relationship between actual probability of verification and FCS-assigned probability) as it only provides a p-value at the level of complexes.
Dispersal and Oviposition Patterns of Lycorma Delicatula (Hemiptera: Fulgoridae) During Oviposition Period in Ailanthus Altissima (Simaroubaceae)
Authors: Jung Minhyung , Kho Jung-Wook , Gook Do-Hun , Lee Young Su , Lee Doo-Hyung 
Published: January 2022

Abstract
The spotted lanternfly (SLF), Lycorma delicatula (Hemiptera: Fulgoridae), has the potential to become a global pest and is currently expanding its range in the United States. In this study, we investigated the dispersal patterns of SLF in Ailanthus altissima during its oviposition period in South Korea using fluorescent marking system. Oviposition patterns of SLF were then analyzed by surveying egg masses in A. altissima patches. The recapture rate of fluorescent-marked SLF rapidly decreased < 30% within the first two weeks. During the oviposition period, seven cases of among-patch dispersal of SLF adults were observed with a minimum estimated dispersal distance mainly ranging between 10 - 60 m and a maximum of 1,740 m. Also, the number of A. altissima trees detected with fluorescent-marked SLF increased until late September. Based on the egg mass survey, a total of 159 egg masses were detected from 38 out of 247 A. altissima trees. Furthermore, ca. 80% of egg masses were located < 2.5 m above the ground. Finally, the number of egg masses showed significant positive correlations with the height and diameter at root collar of A. altissima trees; both tree height and DRC were significantly larger from the trees with egg masses.