bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phylogenetic variation in raw cow milk microbiota and the impact of forage combinations and use of silage inoculants
Authors: Ouamba Alexandre J. K. , Gagnon Mérilie , Varin Thibault , Chouinard P. Yvan , LaPointe Gisèle , Roy Denis 
Published: November 2023

IntroductionThe microbiota of bulk tank raw milk is known to be closely related to that of microbial niches of the on-farm environment. Preserved forage types are partof this ecosystem and previous studies have shown variations in their microbial ecology. However, little is known of the microbiota of forage ration combinations and the transfer rates of associated species to milk.MethodsWe identified raw milk bacteria that may originate from forage rations encompassing either hay (H) or grass/legume silage uninoculated (GL) as the only forage type, or a combination of GL and corn silage uninoculated (GLC), or grass/legume and corn silage both inoculated (GLICI). Forage and milk samples collected in the fall and spring from 24 dairy farms were analyzed using 16S rRNA gene high-throughput sequencing following a treatment with propidium monoazide to account for viable cells.Results and discussionThree community types separating H, GL, and GLICI forage were identified. While the H community was co-dominated byEnterobacteriaceae,Microbacteriaceae,Beijerinckiaceae, andSphingomonadaceae, the GL and GLICI communities showed high proportions ofLeuconostocaceaeandAcetobacteraceae, respectively. Most of the GLC and GLICI rations were similar, suggesting that in the mixed forage rations involving grass/legume and corn silage, the addition of inoculant in one or both types of feed does not considerably change the microbiota. Raw milk samples were not grouped in the same way, as the GLC milk was phylogenetically different from that of GLICI across sampling periods. Raw milk communities, including the GLICI group for which cows were fed inoculated forage, were differentiated byEnterobacteriaceaeand other Proteobacteria, instead of by lactic acid bacteria. Of the 113 amplicon sequence variants (ASVs) shared between forage rations and corresponding raw milk, bacterial transfer rates were estimated at 18 to 31%. Silage-based forage rations, particularly those including corn, share more ASVs with raw milk produced on corresponding farms compared to that observed in the milk from cows fed hay. These results show the relevance of cow forage rations as sources of bacteria that contaminate milk and serve to advance our knowledge of on-farm raw milk contamination.
Comparison of comprehensive quantitative EEG metrics between typically developing boys and girls in resting state eyes-open and eyes-closed conditions
Authors: Modarres Mo , Cochran David , Kennedy David N. , Frazier Jean A. 
Published: November 2023

IntroductionA majority of published studies comparing quantitative EEG (qEEG) in typically developing (TD) children and children with neurodevelopmental or psychiatric disorders have used a control group (e.g., TD children) that combines boys and girls. This suggests a widespread supposition that typically developing boys and girls have similar brain activity at all locations and frequencies, allowing the data from TD boys and girls to be aggregated in a single group.MethodsIn this study, we have rigorously challenged this assumption by performing a comprehensive qEEG analysis on EEG recoding of TD boys (n = 84) and girls (n = 62), during resting state eyes-open and eyes-closed conditions (EEG recordings from Child Mind Institute’s Healthy Brain Network (HBN) initiative). Our qEEG analysis was performed over narrow-band frequencies (e.g., separating low α from high α, etc.), included sex, age, and head size as covariates in the analysis, and encompassed computation of a wide range of qEEG metrics that included both absolute and relative spectral power levels, regional hemispheric asymmetry, and inter- and intra-hemispheric magnitude coherences as well as phase coherency among cortical regions. We have also introduced a novel compact yet comprehensive visual presentation of the results that allows comparison of the qEEG metrics of boys and girls for the entire EEG locations, pairs, and frequencies in a single graph.ResultsOur results show there are wide-spread EEG locations and frequencies where TD boys and girls exhibit differences in their absolute and relative spectral powers, hemispheric power asymmetry, and magnitude coherence and phase synchrony.DiscussionThese findings strongly support the necessity of including sex, age, and head size as covariates in the analysis of qEEG of children, and argue against combining data from boys and girls. Our analysis also supports the utility of narrow-band frequencies, e.g., dividing α, β, and γ band into finer sub-scales. The results of this study can serve as a comprehensive normative qEEG database for resting state studies in children containing both eyes open and eyes closed paradigms.
Use of comprehensive genomic profiling for biomarker discovery for the management of non-small cell lung cancer brain metastases
Authors: Abdulhaleem Mohammed , Hunting John C. , Wang Yuezhu , Smith Margaret R. , Agostino Ralph D’ jr. , Lycan Thomas , Farris Michael K. , Ververs James , Lo Hui-Wen , Watabe Kounosuke , Topaloglu Umit , Li Wencheng , Whitlow Christopher , Su Jing , Wang Ge , Chan Michael D. , Xing Fei , Ruiz Jimmy 
Published: November 2023

BackgroundClinical biomarkers for brain metastases remain elusive. Increased availability of genomic profiling has brought discovery of these biomarkers to the forefront of research interests.MethodIn this single institution retrospective series, 130 patients presenting with brain metastasis secondary to Non-Small Cell Lung Cancer (NSCLC) underwent comprehensive genomic profiling conducted using next generation circulating tumor deoxyribonucleic acid (DNA) (Guardant Health, Redwood City, CA). A total of 77 genetic mutation identified and correlated with nine clinical outcomes using appropriate statistical tests (general linear models, Mantel-Haenzel Chi Square test, and Cox proportional hazard regression models). For each outcome, a genetic signature composite score was created by summing the total genes wherein genes predictive of a clinically unfavorable outcome assigned a positive score, and genes with favorable clinical outcome assigned negative score.ResultsSeventy-two genes appeared in at least one gene signature including: 14 genes had only unfavorable associations, 36 genes had only favorable associations, and 22 genes had mixed effects. Statistically significant associated signatures were found for the clinical endpoints of brain metastasis velocity, time to distant brain failure, lowest radiosurgery dose, extent of extracranial metastatic disease, concurrent diagnosis of brain metastasis and NSCLC, number of brain metastases at diagnosis as well as distant brain failure. Some genes were solely associated with multiple favorable or unfavorable outcomes.ConclusionGenetic signatures were derived that showed strong associations with different clinical outcomes in NSCLC brain metastases patients. While these data remain to be validated, they may have prognostic and/or therapeutic impact in the future.Statement of translation relevanceUsing Liquid biopsy in NSCLC brain metastases patients, the genetic signatures identified in this series are associated with multiple clinical outcomes particularly these ones that lead to early or more numerous metastases. These findings can be reverse-translated in laboratory studies to determine if they are part of the genetic pathway leading to brain metastasis formation.
Prognostic value analysis of cholesterol and cholesterol homeostasis related genes in breast cancer by Mendelian randomization and multi-omics machine learning
Authors: Wu Haodong , Wu Zhixuan , Ye Daijiao , Li Hongfeng , Dai Yinwei , Wang Ziqiong , Bao Jingxia , Xu Yiying , He Xiaofei , Wang Xiaowu , Dai Xuanxuan 
Published: November 2023

IntroductionThe high incidence of breast cancer (BC) prompted us to explore more factors that might affect its occurrence, development, treatment, and also recurrence. Dysregulation of cholesterol metabolism has been widely observed in BC; however, the detailed role of how cholesterol metabolism affects chemo-sensitivity, and immune response, as well as the clinical outcome of BC is unknown. MethodsWith Mendelian randomization (MR) analysis, the potential causal relationship between genetic variants of cholesterol and BC risk was assessed first. Then we analyzed 73 cholesterol homeostasis-related genes (CHGs) in BC samples and their expression patterns in the TCGA cohort with consensus clustering analysis, aiming to figure out the relationship between cholesterol homeostasis and BC prognosis. Based on the CHG analysis, we established a CAG_score used for predicting therapeutic response and overall survival (OS) of BC patients. Furthermore, a machine learning method was adopted to accurately predict the prognosis of BC patients by comparing multi-omics differences of different risk groups. ResultsWe observed that the alterations in plasma cholesterol appear to be correlative with the venture of BC (MR Egger, OR: 0.54, 95% CI: 0.35-0.84, p&lt;0.006). The expression patterns of CHGs were classified into two distinct groups(C1 and C2). Notably, the C1 group exhibited a favorable prognosis characterized by a suppressed immune response and enhanced cholesterol metabolism in comparison to the C2 group. In addition, high CHG score were accompanied by high performance of tumor angiogenesis genes. Interestingly, the expression of vascular genes (CDH5, CLDN5, TIE1, JAM2, TEK) is lower in patients with high expression of CHGs, which means that these patients have poorer vascular stability. The CAG_score exhibits robust predictive capability for the immune microenvironment characteristics and prognosis of patients(AUC=0.79). It can also optimize the administration of various first-line drugs, including AKT inhibitors VIII Imatinib, Crizotinib, Saracatinib, Erlotinib, Dasatinib, Rapamycin, Roscovitine and Shikonin in BC patients. Finally, we employed machine learning techniques to construct a multi-omics prediction model(Risklight),with an area under the feature curve (AUC) of up to 0.89.ConclusionWith the help of CAG_score and Risklight, we reveal the signature of cholesterol homeostasis-related genes for angiogenesis, immune responses, and the therapeutic response in breast cancer, which contributes to precision medicine and improved prognosis of BC.
The impact of liver abscess formation on prognosis of patients with malignant liver tumors after transarterial chemoembolization
Authors: Wang Yunan , Chang Zhihui , Zheng Jiahe , Liu Zhaoyu , Zhang Jun 
Published: November 2023

PurposeLiver abscess is a rare and serious complication after transarterial chemoembolization (TACE) for liver cancer; however, its impact on the prognosis is unclear. This retrospective study examined the outcomes of patients with liver abscess formation following TACE for malignant liver tumors to elucidate the impact of liver abscess formation on the prognosis of these patients.MethodsFrom January 2017 to January 2022, 1,387 patients with malignant tumors underwent 3,341 sessions of TACE at our hospital. Clinical characteristics of patients at baseline and follow-up were examined, including treatment and outcome of liver abscess, tumor response to the TACE leading to liver abscess, and overall survival time.ResultsOf 1,387 patients, 15 (1.1%) patients with liver abscess complications after TACE resulted in a total of 16 (0.5%) cases of liver abscess after 3,341 TACE sessions (including one patient with two events). After antibiotic or percutaneous catheter drainage (PCD) treatment, all the infections associated with liver abscesses were controlled. In the PCD group, eight patients died before drainage tube removal, one retained the drainage tube until the end of follow-up, and five underwent drainage tube removal; the mean drainage tube removal time was 149.17 ± 134.19 days. The efficacy of TACE leading to liver abscess was evaluated as partial response (18.75%), stable disease (37.5%), and progressive disease (43.75%). Eleven patients died during the follow-up period owing to causes unrelated to infections caused by liver abscesses. The survival rates at 3 months, 6 months, 1 year, and 5 years were 86.7%, 50.9%, 25.5%, and 17%, respectively.ConclusionPatients with liver abscess formation following TACE for malignant liver tumors experienced prolonged drainage tube removal time after PCD; while this condition did not directly cause death, it indirectly contributed to a poor prognosis in these patients.
Efficacy and safety of high-dose ilaprazole-amoxicillin dual therapy for Helicobacter pylori eradication: a prospective, single-center, randomized trial
Authors: Cheng Jianping , Fan Chanjuan , Huang Kun , Zhai Lili , Wang Hui , Xie Dongling , Cai Yong , Li Zhen , Bai Qixuan , Wang Pan , Ding Haiou 
Published: November 2023

Background: Until now, there have been no randomized controlled trials directly evaluating the efficacy of high-dose ilaprazole-amoxicillin dual therapy (HT) in comparison to other standard treatments for H. pylori (Helicobacter pylori) infection. This study aimed to compare the effectiveness and safety of HT with bismuth quadruple therapy (BQT) as an initial treatment for H. pylori.Methods: This single-center, prospective, randomized clinical controlled trial recruited 225 consecutive patients. They were assigned to either HT group (ilaprazole, 10 mg, twice daily; amoxicillin 1,000 mg, three times daily) or BQT group (compound bismuth aluminate granules, 2.6 g, three times daily; ilaprazole, 5 mg, twice daily; amoxicillin, 1,000 mg, twice daily; clarithromycin, 500 mg, twice daily) for 14 days. The 13C-urea breath test assessed eradication success 4 weeks after treatment. The primary outcome focused on the eradication rate, with secondary outcomes including safety and compliance.Results: From February 2023 to March 2023, 228 subjects were screened, and 225 were randomized. The HT and BQT groups showed eradication rates of 76.3% and 61.3% (p = 0.015) both by intention-to-treat (ITT) analysis and per-protocol (PP) analysis. HT was associated with fewer adverse events than BQT (27.2% vs. 81.8%, p = 0.002). The most commonly reported adverse events was bitter taste of mouth (3.5% vs. 60.4%, p &lt; 0.001). There was no significant difference in compliance between the two groups (89.5% vs. 92.8%, p = 0.264).Conclusion: The 14-day HT treatment demonstrates better efficacy in H. pylori eradication treatment and improved safety and compliance compared to BQT. The results provide supporting evidence for 14-day HT can be potentially considered as a first-line regimen for empirical treatment.Clinical Trial Registration:https://www.chictr.org.cn/showproj.html?proj=186562, identifier ChiCTR2200066284
Evaluation of relative pollen productivities in temperate China for reliable pollen-based quantitative reconstructions of Holocene plant cover
Authors: Li Furong , Gaillard Marie-José , Xie Siqi , Huang Kangyou , Cui Qiaoyu , Fyfe Ralph , Marquer Laurent , Sugita Shinya 
Published: November 2023

The Landscape Reconstruction Algorithm (LRA) is regarded as the soundest approach for quantifying taxon-specific plant cover from pollen data. The reliability of relative pollen productivity (RPP) estimates is fundamental in the accuracy of quantitative vegetation reconstruction using the LRA approach. Inconsistent RPP estimates produced by different studies can cast doubt on the reliability and applicability of quantitative vegetation reconstruction. Therefore, it is crucial that the RPP estimates are evaluated before being applied for quantitative vegetation reconstruction. We have tested two alternative approaches, namely, a leave-one-out cross-validation (LOO) method and a splitting-by-subregion strategy, using surface pollen assemblages and the REVEALS model—the first step in the LRA—to evaluate the reliability of RPPs estimates of 10 target taxa obtained in the cultural landscape of Shandong. We compared the REVEALS estimates (RVs) with observations of regional vegetation abundance (OBVs) and pollen proportions (PPs). The RVs of all taxa are generally closer to OBVs than PPs, and the degree of similarity depends strongly on the abundance of individual taxa in plant and pollen; taxa dominant in the region show the highest similarity between RVs and OBVs, such as Artemisia, Poaceae, and Humulus. The RVs of all herb taxa except Humulus and Asteraceae SF Cichorioideae are slightly overrepresented, and the RVs of all tree taxa are underrepresented except for Castanea. The comparison of RVs with OBVs collected from different spatial extents shows that the RVs of all herb taxa are more similar to OBVs collected from shorter distances (100 km and 75 km for the entire region and the subregion, respectively), whereas the RVs of all tree taxa are more similar to OBVs collected from longer distances (150 km and 100 km for the entire region and the subregion, respectively). Furthermore, our findings highlight the importance to test different sizes of area for vegetation surveys for evaluation of the RVs given that the appropriate size of vegetation survey may vary between low pollen producers (mainly herbs) and high pollen producers (mainly trees). We consider that the LOO strategy is the best approach in this case study for evaluating the RPP estimates from surface moss polsters. The evaluation confirms the reliability of the obtained RPP estimates for their potential application in quantitative reconstruction of vegetation abundance in temperate China.
Harnessing the power of diffusion models for plant disease image augmentation
Authors: Muhammad Abdullah , Salman Zafar , Lee Kiseong , Han Dongil 
Published: November 2023

IntroductionThe challenges associated with data availability, class imbalance, and the need for data augmentation are well-recognized in the field of plant disease detection. The collection of large-scale datasets for plant diseases is particularly demanding due to seasonal and geographical constraints, leading to significant cost and time investments. Traditional data augmentation techniques, such as cropping, resizing, and rotation, have been largely supplanted by more advanced methods. In particular, the utilization of Generative Adversarial Networks (GANs) for the creation of realistic synthetic images has become a focal point of contemporary research, addressing issues related to data scarcity and class imbalance in the training of deep learning models. Recently, the emergence of diffusion models has captivated the scientific community, offering superior and realistic output compared to GANs. Despite these advancements, the application of diffusion models in the domain of plant science remains an unexplored frontier, presenting an opportunity for groundbreaking contributions.MethodsIn this study, we delve into the principles of diffusion technology, contrasting its methodology and performance with state-of-the-art GAN solutions, specifically examining the guided inference model of GANs, named InstaGAN, and a diffusion-based model, RePaint. Both models utilize segmentation masks to guide the generation process, albeit with distinct principles. For a fair comparison, a subset of the PlantVillage dataset is used, containing two disease classes of tomato leaves and three disease classes of grape leaf diseases, as results on these classes have been published in other publications.ResultsQuantitatively, RePaint demonstrated superior performance over InstaGAN, with average Fréchet Inception Distance (FID) score of 138.28 and Kernel Inception Distance (KID) score of 0.089 ± (0.002), compared to InstaGAN’s average FID and KID scores of 206.02 and 0.159 ± (0.004) respectively. Additionally, RePaint’s FID scores for grape leaf diseases were 69.05, outperforming other published methods such as DCGAN (309.376), LeafGAN (178.256), and InstaGAN (114.28). For tomato leaf diseases, RePaint achieved an FID score of 161.35, surpassing other methods like WGAN (226.08), SAGAN (229.7233), and InstaGAN (236.61).DiscussionThis study offers valuable insights into the potential of diffusion models for data augmentation in plant disease detection, paving the way for future research in this promising field.
Impact of quantitative safety targets on road fatality reduction: an empirical support toward governance plan
Authors: Cui Haizhou , Guo Yuliang , Li Yuchen , Zhang Jianwei , Wang Yida , Yang Lin , Hu Jiayi , Wong Hak Kei , Bai Yuxuan , Ma Yang , Chen Faan 
Published: November 2023

IntroductionThe role of quantitative target setting has become an important topic in debates on the improvement of road safety performance. Specifically, there are questions regarding the relationship between quantitative safety targets and their actual effects. Although previous studies have provided important insights into this subject, their empirical findings have largely been equivocal, and research on this topic remains inadequate.MethodsBased on panel data representing 20 years of observations from 34 OECD member states, we employed nonlinear and linear panel models to investigate whether and how the attributes of quantitative road safety targets (i.e., target ambition and duration) influence their success (i.e., target completion status and rate).ResultsThe results indicate that a quantitative target with a higher level of ambition is associated with a lower likelihood and rate of completion, whereas there is no support for a connection between target duration and final completion rate. This suggests that an excessively ambitious target does not necessarily result in better road safety performance and is detrimental to achieving expected fatality reductions.ConclusionFrom an empirical perspective, this study revealed a potential interaction effect between quantitative road safety targets and practical fatality reduction performance, providing government officials and policymakers with essential references for future practices on target setting and governance planning in regard to public health.