bluuebunny/crossref_metadata_2025_split huggingface dataset:
Failure of Stereotactic Core Needle Biopsy in Women Recalled for Suspicious Calcifications at Screening Mammography: Frequency, Causes and Final Outcome in a Multi-institutional, Observational Follow-up Study
Authors: Duijm Lucien EM , Strobbe Luc J , Smallenburg Vivian van Breest , Vreuls Willem , Boerman Thom , Beek Hermen C van , de Coul-Froger Clemence L op , Setz-Pels Wikke , Voogd Adri C 
Published: October 2021

Abstract
PurposeWe determined the failure rate of stereotactic core needle biopsy (SCNB) and its causes and final outcome in women recalled for calcifications at screening mammography.MethodsWe included a consecutive series of 624,039 screens obtained in a Dutch screening region between January 2009 and July 2019. Radiology reports and pathology results were obtained of all recalled women during two-year follow-up. ResultsA total of 3,495 women (19.6% of 17,809 recalls) were recalled for suspicious calcifications. SCNB was indicated in 2,818 women, of whom 12 had incomplete follow-up and another 12 women refused biopsy. DCIS or invasive cancer was diagnosed in 880 of the remaining 2,794 women (31.5%). SCNB failed in 62 women (2.2%, 36/2,794). These failures were mainly due to a too posterior (n=30) or too superficial location (n=17) of the calcifications or calcifications too faint for biopsy (n=13). Of these 62 women, 10 underwent surgical biopsy, yielding one DCIS (intermediate grade) and two invasive cancers (one intermediate grade and one high grade) and another two women were diagnosed with DCIS (both high grade) at follow-up. Thus, the malignancy rate after SCNB failure was 8.1% (5/62). Calcifications were neither depicted at SCNB specimen radiography nor at pathology in 16 women after (repeated) SCNB (0.6%, 31/2,732). None of them proved to have breast cancer at 2 year follow-up. ConclusionThe failure rate of SCNB for suspicious calcifications is low but close surveillance is warranted, as breast cancer may be present in up to 8% of these women.
Tissue-wide Metabolomics Reveals Wide Impact of Gut Microbiota on Mice Metabolite Composition
Authors: Zarei Iman , Koistinen Ville M. , Kokla Marietta , Klåvus Anton , Babu Ambrin Farizah , Lehtonen Marko , Auriola Seppo , Hanhineva Kati 
Published: October 2021

Abstract
BackgroundThe essential role of gut microbiota in health and disease is well recognized, but the biochemical details that underlie the beneficial impact remain largely undefined. To maintain its stability, microbiota participates in an interactive host-microbiota metabolic signaling, impacting the metabolic phenotypes of the host. Dysbiosis of gut bacteria results in the alteration of certain microbial and host metabolites, and identifying these markers could enhance the early detection of certain diseases. Herein, we report LC-MS based non-targeted metabolic profiling that demonstrates a large effect of gut microbiota on mammalian tissue metabolites. It was hypothesized that gut microbiota influences the overall biochemistry of the host metabolome and this effect is tissue-specific. ResultsThirteen different tissues from germ-free (GF) and conventional (MPF) C57BL/6NTac mice were selected and their metabolic differences were analyzed. Our study demonstrated a large effect of the microbiome on mammalian biochemistry at different tissue levels and resulted in statistically significant modulation of metabolites from multiple metabolic pathway and subpathway classifications (p ≤ 0.05). Hundreds of molecular features were detected exclusively in one mouse group, with the majority of these being unique to specific tissue. A significantly large number of chemical classes were found in the gastrointestinal tissues and arose because of the presence of the microbiome, wherein at least 59% of all detectable features vary in abundance between the two mouse lines. ConclusionsA vast metabolic response of host to metabolites generated by the microbiota was observed, suggesting that the gut microbiota has a direct impact on host metabolism.
Machine Learning based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and its Components
Authors: Yoosefzadeh-Najafabadi Mohsen , Torabi Sepideh , Torkamaneh Davoud , Tulpan Dan , Rajcan Istvan , Eskandari Milad M 
Published: October 2021

Abstract

Genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering quantitative trait loci (QTL) associated with complex traits in plant species. Insufficient statistical power is a limiting factor that current conventional GWAS methods are suffering from, especially in narrow genetic bases plants such as soybean. In this study, we evaluated the potential use of two machine learning (ML) algorithms, support vector machine (SVR) and random forest (RF), in GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying QTL associated with soybean yield and its components. In this study, important soybean yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and date to maturity were assessed using a panel of 227 soybean genotypes evaluated across four environments. Using the SVR-mediated GWAS method, we were able to discover a greater number and most relevant QTL associated with the target traits, supported by the functional annotation of candidate gene analyses. This study for the first time demonstrated the potential benefit of using sophisticated mathematical approaches, such as ML algorithms, in GWAS for identifying QTL that can improve the efficiency of genomic-based breeding programs.
Mesenchymal Stem Cells Derived from Adipose Accelerate the Progression of Colon Cancer by Inducing a MT-CAFs Phenotype via TRPC3/NF-KB Axis
Authors: Xue Chunling , Gao Yang , Li Xuechun , Zhang Mingjia , Yang Ying , Han Qin , Sun Zhao , Bai Chunmei , Zhao Robert Chunhua 
Published: October 2021

Abstract
Background: There is increasing evidence that mesenchymal stem cells (MSCs) help shape the tumor microenvironment and promote tumor progression, and ion channels might play a critical role in this process. Methods: Gene chip was used for a general analysis of gene expression changes in MSC-transformed CAF cells (MT-CAFs). We screened out the ion channel protein TRPC3 with WB detecion and lentivirus knockdown. Calcium influx was detected by two-photon microscope. MTS and Transwell detected growth, migration, and invasion of MT-CAFs and HCT116 cells. Bioinformatic tools and clinical specimens were to assess the relationship between TRPC3 and surrvival.Results: We screened out the ion channel protein TRPC3 with significantly increased expression, which caused calcium influx, and further activated the NF-KB signaling pathway. Knockdown or inhibition of TRPC3 in MSCs significantly reduced the activation of NF-KB, and decreased the growth, migration, and invasion of MT-CAFs. After TRPC3 knockdown, the ability of MT- CAFs to promote tumor migration and invasion was impaired. Conversely, the upregulation of TRPC3 expression in MT-CAFs had the opposite effect. In vivo, TRPC3 expressed on MSCs also contributed to the tumorigenesis and progression of cancer cells. In addition, the Oncomine and GEPIA databases showed that TRPC3 expression is higher in colon cancer tissue compared with normal colon tissues, and is positively correlated with the expression of the CAF genes alpha-smooth muscle (α-SMA/ACTA2) and fibroblast activation protein Alpha (FAP). The disease-free survival of patients with positive TRPC3 expression in mesenchymal cells was significantly shorter than in those with negative expression. Conclusions: These results indicate that TRPC3 expressed on MT-CAFs plays a critical role in tumor progression via the NF-KB signaling pathway, and is correlated with poor prognosis in colon cancer patients. Therefore, TRPC3 may be a novel therapeutic target for the treatment of colon cancer.
EventSKG: a Framework for Public Safety Event Knowledge Graph Construction using Social Network Data
Authors: Yang Xing , Xu Chenhui , Zhu Dongtao , Gui Yuanmiao , Sun Shaomin , Li Wenbo , Tang Yuyang 
Published: October 2021

Abstract
The social network data contain a great deal of unstructured knowledge which is useful to understand public safety incidents. The structure of social network data, such as news, statistical statements, social network messages, government reports and so on, is complicated. So, it is difficult to obtain knowledge from social network data because social network data are multi-source heterogeneous. Knowledge graph is one of the effective tools for processing such multi-source heterogeneous data. However, the previous works didn’t notice the particularity of entities in public safety incidents and the linguistic characteristics of Chinese. Moreover, previous works on event knowledge graph mainly focus on single data source which make it is difficult to process multi-source social network data. Thus, the construction of a public safety incident knowledge graph using complex social network data in the Chinese environment is still a difficult problem. In this paper, a framework for public safety event knowledge graph construction towards Chinese social network data, namely EventSKG, is proposed. EventSKG contains a direct mapping module for knowledge extraction from structured data, an Event-Specific FLAT model for entity extraction from unstructured data, a manual template for relation extraction from unstructured data, and an integration surgery to connect the triples obtained from different data source. An event knowledge graph related to the flood disaster in 2020 in China is constructed via EventSKG framework, which contains 14397 entities and 43168 relations. The event knowledge graph will form associations around network data from various sources for the same event, not only enabling humans to better understand the event, but also providing basic knowledge base for future intelligent understanding of events.
Assessment of Neuroendocrine Changes and the Hypothalamo-Pituitary Autoimmunity in Patients With COVID-19
Authors: Gonen Mustafa Sait , De Bellis Annamaria , Durcan Emre , Bellastella Giuseppe , Cirillo Paolo , Scappaticcio Lorenzo , Longo Miriam , Bircan Basak Ecem , Sahin Serdar , Sulu Cem , Ozkaya Hande Mefkure , Konukoglu Dildar , Kartufan Fatma Ferda , Kelestimur Fahrettin 
Published: October 2021

Abstract
Purpose: The SARS-CoV-2 may affect the hypothalamic-pituitary axis and pituitary dysfunction may occur. Therefore, we investigated neuroendocrine changes, particularly, secondary adrenal insufficiency using a dynamic test and the role of autoimmunity in pituitary dysfunction in the patients with COVID-19.Methods: The single-center, prospective, case-control study included PCR-confirmed COVID-19 patients and healthy controls. Basal hormone levels were measured and ACTH stimulation test was performed. Anti-pituitary (APA) and anti-hypothalamic antibodies (AHA) were also determined. Results: We examined a total of 49 patients with COVID-19 and 28 healthy controls. The frequency of adrenal insufficiency in patients with COVID-19 was found as 8.2%. The patients with COVID-19 had lower free T3, IGF-1, total testosterone levels, and higher cortisol and prolactin levels when compared with controls. We also, demonstrated the presence of APA in three and AHA in one of four patients with adrenal insufficiency. Conclusions: The COVID-19 may result in adrenal insufficiency, so the routine screening of adrenal functions is these patients is needed. Endocrine disturbances in COVID-19 are similar to those seen in acute stressful conditions or infections. Also, pituitary or hypothalamic autoimmunity may play a role in neuroendocrine abnormality in COVID-19.
Agrobacterium Rhizogenes Influences Bioactive Metabolites in Hairy Root Culture of Aerva Javanica (Burm.f.) Juss. ex Schult and in Silico Assessment of Human Breast Cancer Activity
Authors: Sriniva Ramasamy , Boobalan Selvakumar , Saranyaa Venkatachalam , Mouliganesh Sekar , Seenivasagan Renganathan , Kamalanathan D. 
Published: October 2021

Abstract
The authors have requested that this preprint be removed from Research Square.
DFB Suppresses Obesity-Driven CRC Via Restricting Progenitor to Terminally Exhausted T Cell Differentiation
Authors: Xu Yihua , Wang Hao , Wang Tao , Chen Chunhui , Yao Wanyu , Sun Ruibo , Ma Ye , Zhang Qingyuan , Wu Liyi , Zeng Shanmei , Sun Xuegang 
Published: October 2021

Abstract
Background: Obesity contributes to about 30% incidence of colorectal cancer (CRC). Obese tumor microenvironment compromises anti-tumor immunity by eliciting exhausted T cells (Tex). Hypothesizing that Dahuang Fuzi Baijiang Decoction (DFB), a combined classical prescription from “Synopsis of Golden Chamber”, modulates the differentiation of tumor-infiltrating CD8+ T cellsMethods: Our present study was to use transgenic ob/ob mice to examine the effects of DFB and to explore its novel mechanism on modulating the differentiation of tumor-infiltrating CD8+ T cells.Results: DFB regresses tumor growth in high-fat diet induced obese mice via expanding PD-1intTIM3- and restricting PD-1hiTIM3+ subset. TCF1 is highly expressed in PD-1intTIM3- subset but is absent in PD-1hiTIM3+ cells. We next confirm that progenitor PD-1intTCF+ cells robustly produce TNFɑ and IFNγ while terminally differentiated PD-1intTCF+ cells have defects in generating TNFɑ. With transgenic ob/ob mice, we find that DFB produces cooperative efficacy with anti-PD-1 (ɑPD-1) by limiting PD-1hiTim3+ subset and amplifying PD-1intTCF+ population. Finally, we identify that the differentiation from progenitor to terminal Tex is driven, at least in part, by CCL2. CCR2 inhibitor enhances the response to ɑPD-1 by promoting the counts of progenitor Tex. Conclusion: Altogether, DFB dampens CCL2 and preserves progenitor Tex in obese microenvironment to restrain CRC progression. These finds provide unambiguous evidence that traditional Chinese formula DFB can prevent tumor progression by modulating adaptive immunity and give rise to strong rationale for further clinical verification.
Stochastic Variational Variable Selection for High-Dimensional Microbiome Data
Authors: Dang Tung , Kumaishi Kie , Usui Erika , Kobori Shungo , Sato Takumi , Toda Yusuke , Yamasaki Yuji , Tsujimoto Hisashi , Ichihashi Yasunori , Iwata Hiroyoshi 
Published: October 2021

Abstract
Background: The rapid and accurate identification of a minimal-size core set of representative microbial species plays an important role in the clustering of microbial community data and interpretation of the clustering results. However, the huge dimensionality of microbial metagenomics data sets is a major challenge for the existing methods such as Dirichlet multinomial mixture (DMM) models. In the framework of the existing methods, computational burdens for identifying a small number of representative species from a huge number of observed species remain a challenge. Results: We proposed a novel framework to improve the performance of the widely used DMM approach by combining three ideas: (i) We extended the finite DMM model to the infinite case, via the consideration of Dirichlet process mixtures and estimate the number of clusters as a random variables. (ii) We proposed an indicator variable to identify representative operational taxonomic units that substantially contribute to the differentiation among clusters. (iii) To address the computational burdens of the high-dimensional microbiome data, we proposed are a stochastic variational inference, which approximates the posterior distribution using a controllable distribution called variational distribution, and stochastic optimization algorithms for fast computation. With the proposed method named stochastic variational variable selection (SVVS), we analyzed the root microbiome data collected in our soybean field experiment and the human gut microbiome data from three published data sets of large-scale case-control studies. Conclusions: SVVS demonstrated a better performance and significantly faster computation than existing methods in all cases of testing data sets. In particular, SVVS is the only method that can analyze the massive high-dimensional microbial data with above 50,000 microbial species and 1,000 samples. Furthermore, it was suggested that microbial species selected as a core set played important roles in the recent microbiome studies.
Comparison of quadriceps and hamstring muscle strength after exercises with and without blood flow restriction in the postoperative period of the anterior cruciate ligament: a randomized controlled trial.
Authors: Melo Rafael Francisco Vieira , Cohen Moises , Komatsu William Ricardo , Melo Maria Eduarda Vieira , Freitas Mellissa Sales 
Published: October 2021

Abstract
BACKGROUND
The anterior cruciate ligament (ACL) reconstruction surgery takes the patient through a period where muscle mass loss occurs. The blood flow restriction combined with strengthening exercises can be an alternative to improve the muscle strength of the quadriceps and hamstrings in the postoperative period of ACL reconstruction.
Objective
Compare the gain in muscle strength between exercises with and without occlusion in the quadriceps and hamstring muscles in the postoperative period of reconstruction of the anterior cruciate ligament.
Methods
This is a randomized, prospective, longitudinal clinical trial, parallel, analytical, experimental type, with random allocation.The study included the participation of postoperative patients, with reconstruction of the anterior cruciate ligament. The isometric muscle strength of knee extension and flexion was evaluated using a digital hand dynamometer and the physical function of the knee, using the Lysholm, KOOS and IKDC questionnaires in the pre -operative and after 4, 8 and 12 weeks. All patients signed a written informed consent form prior to the start of the study
Results
After comparing the rehabilitation of the groups, a statistical difference was observed in quadriceps muscle strength (p <0.01) after 12 weeks and hamstrings (p <0.01) after 8 and 12 weeks in the injured legs. In the analysis of the participants' physical function, there was a significant difference in the Lysholm questionnaire (p <0.01) after 8 and 12 weeks, in the KOOS pain questionnaire (p <0.01) after 4 weeks, symptoms and daily activities (p <0, 01) after 8 and 12 weeks, quality of life (p <0.01) after 12 weeks, and in the IKDC questionnaire (p <0.01) after 8 and 12 weeks.
Conclusion
The blood flow restriction has proved to be efficient for improving muscle strength of the quadriceps, hamstrings and physical function of the knee after reconstruction of the anterior cruciate ligament in early rehabilitation.
A Noninvasive Quantification Approach for Monitoring Brain Metabolic Alterations After Surgical Intervention in Ischemic Cerebrovascular Disease
Authors: Wang Min , Cui Bixiao , Shan Yi , Yang Hongwei , Yan Zhuangzhi , Sundar Lalith Kumar Shiyam , Alberts Ian , Rominger Axel , Shi Kuangyu , Ma Yan , Jiang Jiehui , Lu Jie 
Published: October 2021

Abstract
Purpose: Non-invasive quantification of cerebral metabolic rate for glucose (CMRGlc) and characterizing cerebral metabolism of cerebrovascular territories are useful for the understanding of ischemic cerebrovascular disease (ICVD). Here, we proposed a non-invasive quantification approach based on image-derived input function (IDIF) suitable for ICVD patients and monitored the pathophysiological changes after surgical intervention.Methods: Sixteen healthy controls and 26 ischemic cerebrovascular disease patients with baseline and after surgical visits underwent 18F-FDG PET/MR imaging. The voxel-wise CMRGlc maps were derived via our proposed IDIF method. The CMRGlc and standardized uptake value ratio (SUVR) maps were subsequently used to extract quantitative values within 7 volumes of interest (gray matter, white matter, anterior, middle, and posterior cerebral artery, basilar artery, and cerebellar artery territory). Intraclass correlation coefficient (ICC) and absolute percentage error were employed to measure consistency in healthy controls. The quantitative differences of healthy controls and patients at baseline and after surgical visits were statistically analyzed. Results: For healthy controls, there were no significant differences for region CMRGlc values across bilateral and unilateral IDIF measurements (ICC: 0.91-0.98). Significant differences in CMRGlc were observed across the cohorts in all territories (P< 0.001). The CMRGlc values in the ipsilateral side were significantly increased after surgery intervention (P < 0.05) for all territories (percentage changes: 7.4%~22.5%). Only the posterior cerebral artery and basilar artery territories (-2.8% and 1.9%) were significant differences for SUVR (P < 0.05). The diagnostic ability of CMRGlc in various territories (area under curve: 0.923-0.966) was significantly higher than of SUVR. There was a significant association between CMRGlc with the national institutes of health stroke scores (r: -0.54, P = 0.0041).Conclusion: These observations suggested the non-invasive quantification approach based on IDIF allowed the individual metabolism measurement of cerebrovascular territories after surgery and identified the glucose pathology changes underlying territories.
Lack of An Association Between Dietary Patterns and Adiposity Among Primary School Children in Kilimanjaro Tanzania
Authors: Mosha Mary Vincent , Paulo Heavenlight A , Msuya Sia E. , Grosskurth Heiner , Filteau Suzanne 
Published: October 2021

Abstract
Introduction: Good dietary habits for children should be shaped while children are still growing so these behaviours benefit children in their later life. We examined dietary patterns and their association with adiposity among primary school children from northern Tanzania. Methods: We collected dietary data by 24-hour recall and food frequency questionnaire (FFQ) for 1170 primary school children aged 9 – 11 years from 20 primary schools in the Kilimanjaro region. We used factor analysis and FFQ data to identify dietary patterns. Children were categorised into terciles of their adherence to each dietary pattern. We used multilevel logistic regression to evaluate the association of dietary pattern terciles with adiposity indicators: body mass index z–scores (BMI z scores), body fat percentage by bioelectrical impedance, triceps and subscapular skinfold thicknesses, and waist circumference. Results: Fifteen percent of children had BMI Z> 1.0, indicating overweight or obesity. We identified two dietary patterns by factor analysis: a healthy pattern characterised by frequent consumption of fruits and vegetables and a mixed dietary pattern characterised by intake of fatty snacks, sweets and sugar snacks, sugary beverages, meat and alternatives, milk, and milk products. After adjusting for potential confounders, for both models: model 1 (age and sex) and model 2 (age, sex, school type, time spent walking to school, district (urban/ rural), availability of television and electronic gadgets at home and neighbourhood playground), we found no evidence of associations of adherence to either dietary pattern with adiposity measures. Conclusion: Dietary patterns were not associated with adiposity in Tanzanian primary school children, possibly because of limitations of the FFQ, which did not record information on portion sizes. Future research should focus on understanding the key foods / snacks consumed by school children, portion sizes and their long-term effects on adiposity in children.