bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract P5-08-12: Efficacy of futibatinib, an irreversible fibroblast growth factor receptor (FGFR) inhibitor, in breast cancer models with FGFR alterations
Authors: Saridogan Turcin , Akcakanat Argun , Zhao Ming , Evans Kurt W. , Yuca Erkan , Scott Stephen , Kirby Bryce P. , Zheng Xiaofeng , Damodaran Senthil , Meric-Bernstam Funda 
Published: March 2022

Abstract
Purpose: Several FGFR alterations have been found in breast cancer, however, their role as a therapeutic target in breast has been controversial. Futibatinib (TAS-120; Taiho) is a novel, selective pan-FGFR inhibitor which irreversibly binds to and inhibits FGFR1-4 at nanomolar concentrations. We sought to determine the efficacy of futibatinib in breast cancer models with differing FGFR alterations. Experimental Design: In vivo, antitumor efficacy was evaluated by tumor growth curves and event-free survival in a panel of patient-derived xenografts (PDXs) from breast cancer patients with different FGFR1-4 alterations. Genomic alterations in the PDXs were characterized by next generation sequencing. Correlation of FGFR gene expression in matched patient tumors and PDXs was analyzed by RNA sequencing. In vitro, FGFR2 Y375C mutant and FGFR2-BICC1 fusion expressing MCF10A cell lines were generated, and effect on cell proliferation, colony formation assay, and cell signaling was assessed with and without futibatinib. Frequency of FGFR mutations and FGFR2 amplification was compiled from internal and public databases. Results: Breast cancer PDXs varied in their expression of FGFR1-4. FGFR gene expression significantly correlated between matched patient tumors and PDXs derived from them, however, PDXs had higher levels of FGFR3 and FGFR4 expression compared to patient samples. Futibatinib inhibited tumor growth in three of 10 PDX models, with tumor stabilization in a FGFR2 amplified model and prolonged tumor regression (more than 110 days) in a PDX bearing a FGFR2 Y375C mutation. In vitro, expression of FGFR2 Y375C, as well as FGFR2-BICC fusion in normal-like MCF10A cells enhanced growth, colony formation ability and FGFR signaling. Cells expressing FGFR2 Y375C as well as FGFR2-BICC fusions were more sensitive to futibatinib. In the five breast cancer genomic series we analyzed, FGFR2 mutations and amplifications were found in 1.1%-2.6% and 1.4%-2.5%, respectively. Conclusions: Futibatinib had single agent activity of selected breast cancer PDX models. FGFR2 activating mutations and amplification may represent rare but promising therapeutic targets to FGFR inhibition.
Citation Format: Turcin Saridogan, Argun Akcakanat, Ming Zhao, Kurt W. Evans, Erkan Yuca, Stephen Scott, Bryce P. Kirby, Xiaofeng Zheng, Senthil Damodaran, Funda Meric-Bernstam. Efficacy of futibatinib, an irreversible fibroblast growth factor receptor (FGFR) inhibitor, in breast cancer models with FGFR alterations [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-08-12.
Abstract P5-10-07: A preclinical evaluation of the isoform-specific PI3K inhibitor in HER2+ breast cancer models with resistance to trastuzumab
Authors: De Pradip , Aske Jennifer Carlson , Dey Nandini 
Published: March 2022

Abstract
Background: The PI3K pathway mediates trastuzumab resistance. However, early attempts to indirectly target this signaling pathway with everolimus had limited success. We hypothesize that isoform-specific PI3K inhibitors may enhance the efficacy of anti-HER2 therapy. Methods: We conducted a preclinical proof-of-concept in vitro study of the selective PI3K alpha/delta inhibitor copanlisib or PI3K alpha inhibitor alpelisib alone and in combination with either trastuzumab (hmAB) or tucatinib (HER2-specific kinase inhibitor) in HER2 amplified breast cancer cell lines including trastuzumab-resistant (BT474HR), PIK3CA mutated/HER2 amplified (HCC1954 & MDA-MB453) and PIK3CA wild type/HER2 amplified (SKBR3). Results: When used alone or in combination with the HER2 targeted therapies trastuzumab or tucatinib, copanlisib and alpelisib have anti-proliferative effects in real-time cell proliferation or 3D-ON-TOP assays. Both isoform-specific inhibitors dose-dependently inhibited PI3K signaling and were effective regardless of trastuzumab-resistant and PIK3CA status. Compared to alpelisib, copanlisib was more effective in inducing apoptosis by Annexin V staining. Tucantinib dose-dependently blocked HER2 phosphorylation and p-HER2-SHC-GRB2-mediated MAPK signaling. Significantly, the combination of HER2-targeted therapy (trastuzumab or tucatinib) and copanlisib/alpelisib more effectively inhibited both 3D-ON-TOP colony formation and the HER2 downstream signaling cascade than either drug alone. Conclusion: Our study shows that blocking the PI3K pathway is an essential determinant of response to anti-HER2 regimens in trastuzumab-resistant breast cancers.
Citation Format: Pradip De, Jennifer Carlson Aske, Nandini Dey. A preclinical evaluation of the isoform-specific PI3K inhibitor in HER2+ breast cancer models with resistance to trastuzumab [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-10-07.
Abstract P5-15-09: A LINE Bot mobile app module to augment long-term and real-time follow-up of patients with breast cancer
Authors: Lien Pei-Ju , Huang Chi-Cheng , Tseng Ling-Ming 
Published: March 2022

Abstract
Purpose: Female breast cancer is one of the most frequent cancer types in Taiwan, and several novel therapeutic options have been introduced in recent years. Patients usually received a combination of treatment modalities based on the pathological type, cancer staging and personal preferences. Due to the complexity of treatment involved, specifically associated adverse reactions and variable treatment duration, assessment of quality of life (QoL), long-term and real-time surveillance are difficult to achieve. To overcome the above limitations, we developed a LINE Bot module to augment the follow-up of patients with breast cancer. Materials and Methods: The LINE Bot is comprised of personal information including disease characteristics, therapeutic timeframe, a quality-of-life measuring instrument, the EORTC QLQ-C30 and QLQ-BR23, knowledge and guidance concerning breast cancer. The mobile app also serves as a platform for the patients to interact with their conducting physicians. Results: During the nine-month enrollment period, 108 patients who had received breast cancer therapies at our institute were identified on hospitalization or outpatient basis. Invitation was made in person, and an access to the mobile app or a direct link to online quality-of-life questionnaire was provided. Patients with ECOG=0 reported better global health/Global quality of life status (62 versus 14, P&lt;0.01), physical function (90 versus 73, P&lt;0.05), cognitive function (81 versus 28, P&lt;0.01), less pain (24 versus 67, P&lt;0.01) and dyspnea (10 versus 67, P&lt;0.01) compared to those with ECOG&gt;1. Patients in the status of follow-up had better role function than those undergoing active treatment (92 versus 78, P&lt;0.05). Conclusion: The establishment of the LINE Bot module could improve outcomes assessment for patients themselves and physicians in charge. It provided an opportunity to reflect quality-of-life influenced by each treatment modality and disease status as these patients could repeat the questionnaire at any timing. The platform for interaction could also contribute to enhancing the quality of care.
Citation Format: Pei-Ju Lien, Chi-Cheng Huang, Ling-Ming Tseng. A LINE Bot mobile app module to augment long-term and real-time follow-up of patients with breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-15-09.
Abstract PD3-04: Multi-omics characterization of triple-negative breast cancer identifies therapeutic vulnerabilities and epigenetic immune suppression in the mesenchymal subtype
Authors: Lehmann Brian D , Colaprico Antonio , Silva Tiago C , Chen Jianjiao , An Hanbing , Ban Yuguang , Wang Lily , James Jamaal L , Balko Justin , Gonzalez-Ericsson Paula I , Sanders Melinda E , Zhang Bing , Pietenpol Jennifer A , Chen Xi S 
Published: March 2022

Abstract
Triple-negative breast cancer (TNBC) is a collection of biologically diverse cancers characterized by distinct transcriptional patterns, biology and immune composition. TNBCs display transcriptional diversity with at least four tumor-intrinsic subtypes that include two basal-like (BL1, BL2), a mesenchymal (M) and a luminal androgen receptor (LAR) subtype. Using integrative analyses of transcriptomic, epigenetic, proteomic and phospho-proteomic patterns we have identified subtype-specific vulnerabilities, which advanced our understanding of the cellular origins of TNBC subtypes. In mesenchymal subtype tumors we observed high mutation load and genomic instability, absence of immune cells, low PD-L1 expression, loss of global DNA methylation and transcriptional repression of antigen presentation genes through the polycomb repressor complex 2 (PRC2). Using cell line models, we demonstrate that MHC-I expression is epigenetically silenced by the PRC2 in mesenchymal TNBC cell lines and inhibition of EZH2 restores expression. Pharmacological inhibition of EZH2 enhances chemotherapy efficacy in syngeneic murine tumor models providing a rationale for using PRC2 inhibitors in PD-L1 negative mesenchymal tumors.
Citation Format: Brian D Lehmann, Antonio Colaprico, Tiago C Silva, Jianjiao Chen, Hanbing An, Yuguang Ban, Lily Wang, Jamaal L James, Justin Balko, Paula I Gonzalez-Ericsson, Melinda E Sanders, Bing Zhang, Jennifer A Pietenpol, Xi S Chen. Multi-omics characterization of triple-negative breast cancer identifies therapeutic vulnerabilities and epigenetic immune suppression in the mesenchymal subtype [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD3-04.
Abstract TF2-1: A journey through the life of HER2: How did we get here and where are we going?
Authors: Blenman K 
Published: March 2022

Abstract
After the discovery in the early 1980s that human epidermal growth factor receptor 2 (HER2; ERBB2) could trigger exaggerated cell growth and division, it eventually became clear that blocking this protein could slow or stop some types of breast cancer. Since then, several HER2 inhibitors have been USA FDA approved. However, despite this breakthrough success, many HER2-positive breast cancer patients do not benefit from these therapies, or they initially benefit but become resistant over time. Here we discuss the details of the heterogeneity in response, resistance mechanisms/signaling, alternative HER2q activation mechanisms (mutation), and heterogeneity in amplicon structure and does it matter.
Citation Format: K Blenman. A journey through the life of HER2: How did we get here and where are we going? [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr TF2-1.
Carotid Intima-Media Thickness Percentiles in Adolescence and Young Adulthood and Their Association With Obesity and Hypertensive Blood Pressure in a Population Cohort
Authors: Neuhauser Hannelore K. , Büschges Julia , Schaffrath Rosario Angelika , Schienkiewitz Anja , Sarganas Giselle , Königstein Karsten , Schweizer Dieter , Schmidt-Trucksäss Arno 
Published: March 2022

Background:
This study aimed to derive carotid intima media thickness (CIMT) percentiles from a population-based sample of adolescents and young adults using improved technology, standardization and quality control, and to investigate the association of CIMT with hypertensive blood pressure (BP) and obesity.

Methods:
Four thousand seven hundred nine 14- to 28-year-old participants of the German KiGGS cohort 11-year follow-up, which was based on a nationwide population sample, had B-mode ultrasound CIMT measurement with semi-automated edge-detection and automatic ECG-gated real-time quality control. CIMT percentiles were estimated from far wall CIMT during 2 to 6 heart cycles using the GAMLSS statistical model. Hypertensive BP, overweight, obesity, and a risk score from added Z scores of triglycerides, total/HDL (high-density lipoprotein)-cholesterol ratio, and glycated hemoglobin were based on standardized measurements at baseline and follow-up.

Results:
CIMT differed by sex at all ages, furthermore by age and height in a nonlinear fashion. Percentiles were estimated simultaneously by age and height. Hypertensive BP and obesity were associated cross-sectionally and longitudinally with a higher risk of CIMT ≥75th percentile in log-binomial regression models adjusted for age, sex, height, current smoking, and cardiovascular risk score. For CIMT ≥90th percentile, the relative risk effect estimates were consistently >1 but often had large confidence intervals including 1, largest adjusted relative risk 3.37 (95% CI, 1.41–8.04) for the combination of hypertensive BP and obesity at follow-up.

Conclusions:
Based on state-of-the-art measurements and statistical techniques, these population-based CIMT percentiles by sex, age and height add unbiased evidence for the association of subclinical atherosclerosis with hypertensive BP and obesity in the young.
Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis
Authors: Mohammad Saif M. 
Published: March 2022

AbstractThe importance and pervasiveness of emotions in our lives makes affective computing a tremendously important and vibrant line of work. Systems for automatic emotion recognition (AER) and sentiment analysis can be facilitators of enormous progress (e.g., in improving public health and commerce) but also enablers of great harm (e.g., for suppressing dissidents and manipulating voters). Thus, it is imperative that the affective computing community actively engage with the ethical ramifications of their creations. In this article, I have synthesized and organized information from AI Ethics and Emotion Recognition literature to present fifty ethical considerations relevant to AER. Notably, this ethics sheet fleshes out assumptions hidden in how AER is commonly framed, and in the choices often made regarding the data, method, and evaluation. Special attention is paid to the implications of AER on privacy and social groups. Along the way, key recommendations are made for responsible AER. The objective of the ethics sheet is to facilitate and encourage more thoughtfulness on why to automate, how to automate, and how to judge success well before the building of AER systems. Additionally, the ethics sheet acts as a useful introductory document on emotion recognition (complementing survey articles).
Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization
Authors: Laskar Md Tahmid Rahman , Hoque Enamul , Huang Jimmy Xiangji 
Published: March 2022

AbstractThe Query-Focused Text Summarization (QFTS) task aims at building systems that generate the summary of the text document(s) based on the given query. A key challenge in addressing this task is the lack of large labeled data for training the summarization model. In this article, we address this challenge by exploring a series of domain adaptation techniques. Given the recent success of pre-trained transformer models in a wide range of natural language processing tasks, we utilize such models to generate abstractive summaries for the QFTS task for both single-document and multi-document scenarios. For domain adaptation, we apply a variety of techniques using pre-trained transformer-based summarization models including transfer learning, weakly supervised learning, and distant supervision. Extensive experiments on six datasets show that our proposed approach is very effective in generating abstractive summaries for the QFTS task while setting a new state-of-the-art result in several datasets across a set of automatic and human evaluation metrics.
Dual Attention Model for Citation Recommendation with Analyses on Explainability of Attention Mechanisms and Qualitative Experiments
Authors: Zhang Yang , Ma Qiang 
Published: March 2022

Abstract
Based on an exponentially increasing number of academic articles, discovering and citing comprehensive and appropriate resources have become non-trivial tasks. Conventional citation recommendation methods suffer from severe information losses. For example, they do not consider the section header of the paper that the author is writing and for which they need to find a citation, the relatedness between the words in the local context (the text span that describes a citation), or the importance of each word from the local context. These shortcomings make such methods insufficient for recommending adequate citations to academic manuscripts. In this study, we propose a novel embedding-based neural network called dual attention model for citation recommendation (DACR) to recommend citations during manuscript preparation. Our method adapts the embedding of three semantic pieces of information: words in the local context, structural contexts,1 and the section on which the author is working. A neural network model is designed to maximize the similarity between the embedding of the three inputs (local context words, section headers, and structural contexts) and the target citation appearing in the context. The core of the neural network model comprises self-attention and additive attention; the former aims to capture the relatedness between the contextual words and structural context, and the latter aims to learn their importance. Recommendation experiments on real-world datasets demonstrate the effectiveness of the proposed approach. To seek explainability on DACR, particularly the two attention mechanisms, the learned weights from them are investigated to determine how the attention mechanisms interpret “relatedness” and “importance” through the learned weights. In addition, qualitative analyses were conducted to testify that DACR could find necessary citations that were not noticed by the authors in the past due to the limitations of the keyword-based searching.
Boring Problems Are Sometimes the Most Interesting
Authors: Sproat Richard 
Published: March 2022

Abstract
In a recent position paper, Turing Award Winners Yoshua Bengio, Geoffrey Hinton, and Yann LeCun make the case that symbolic methods are not needed in AI and that, while there are still many issues to be resolved, AI will be solved using purely neural methods. In this piece I issue a challenge: Demonstrate that a purely neural approach to the problem of text normalization is possible. Various groups have tried, but so far nobody has eliminated the problem of unrecoverable errors, errors where, due to insufficient training data or faulty generalization, the system substitutes some other reading for the correct one. Solutions have been proposed that involve a marriage of traditional finite-state methods with neural models, but thus far nobody has shown that the problem can be solved using neural methods alone. Though text normalization is hardly an “exciting” problem, I argue that until one can solve “boring” problems like that using purely AI methods, one cannot claim that AI is a success.
Response of different crops and weeds to three biotypes of Meloidogyne graminicola: crop rotation and succession strategies for irrigated rice fields
Authors: Soares Mayra R.C. , Carneiro Regina M.D.G. , Dias-Arieira Claudia R. 
Published: March 2022

Summary
Rice, one of the most consumed cereal crops worldwide, is commonly grown under flooded conditions, which directly influences the nematode community. Meloidogyne graminicola is the predominant species in rice fields, causing significant damage and requiring integrated management practices. This study aimed to investigate the response of different Poaceae crops, soybean, and common weeds of rice to three biotypes of M. graminicola (G1, G2 and G3) recently detected in Brazil. The highest reproduction factor (RF) for the three nematode populations was detected in the weeds Echinochloa colonum and E. crus-galli, followed by rice and Italian ryegrass. Wheat ‘TBio Sonic’ and millet ‘ADR 500’ served as poor hosts to the nematodes, whereas black oat, white oat, signalgrass, millet ‘ADR 905’, maize, wheat ‘TBio Toruk’, and soybean acted as non-hosts (RF < 1) in both experiments. Of the three M. graminicola biotypes, G1 was the most aggressive, followed by G3 and G2 (lowest RF values). The findings of the current study can support the selection of crop rotation or succession approaches for the management of different biotypes of M. graminicola in irrigated rice fields.
Shame, Sin and the Seminary
Authors: Folland Paul 
Published: March 2022

Abstract
The intention of this paper, through a literature based reflective methodology, is to consider the role and implications of shame within the Christian community of a theological college, and suggest mitigating factors that could support the development of a mutually accountable community that would facilitate discipleship growth. Within Regents Theological College in the UK, the aim is to educate students – the majority of whom are 18–30 years old – to go on to serve Jesus in a variety of roles both inside and outside the Church. Our aspiration then, is not just to teach theological and practical skills, but also to raise up disciples of Jesus, willing to serve Him with their heads, hands and hearts. The outcomes suggested by this paper have implications not only for seminary environments, but also for churches and youth groups.
The Hollow Men of Liyanage Amarakeerthi: The Nexus Between Nationalism and Capitalism in the Sri Lankan Media
Authors: Ratnayake Madhubhashini Disanayaka 
Published: March 2022

Liyanage Amarakeerthi, Kurulu Hadawatha [The Heart of a Bird], Fast Publishing Pvt Ltd., Colombo, Sri Lanka, 2013, pp. 366, SL ₹500, ISBN-978-9556772548 (Paperback) Liyanage Amarakeerthi, Rathu Iri Adina Atha [The Hand that Underlines in Red], Vidarshana Publishers, Dehiwala, Sri Lanka, 2019, pp. 211, SL ₹500, ISBN 9786245087099 (Paperback)