bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geomorphometric descriptions of archipelagic aprons off the southern flanks of French Frigate Shoals and Necker Island edifices, Northwest Hawaiian Ridge
Authors: Gardner James V. , Calder Brian R. , Armstrong Andrew A. 
Published: March 2021

AbstractThis study describes the geomorphometries of archipelagic aprons on the southern flanks of the French Frigate Shoals and Necker Island edifices on the central Northwest Hawaiian Ridge that are hotspot volcanoes that have been dormant for 10–11 m.y. The archipelagic aprons are related to erosional headwall scarps and gullies on landslide surfaces but also include downslope gravitational features that include slides, debris avalanches, bedform fields, and outrunners. Some outrunners are located 85 km out onto the deep seafloor in water depths of 4900 m. The bedforms are interpreted to be the result of slow downslope sediment creep rather than products of turbidity currents. The archipelagic aprons appear to differ in origin from those off the Hawaiian Islands. The landslides off the Hawaiian Islands occurred because of oversteepening and loading during the constructive phase of the islands whereas the landslides off the French Frigate Shoals and Necker Island edifices may have resulted from vertical tectonics due to the uplift and relaxation of a peripheral bulge or isolated earthquakes long after the edifices passed beyond the hotspot. The lack of pelagic drape in water depths above the 4600 m depth of the local carbonate compensation depth suggests that the archipelagic apron off the French Frigate Shoals edifice is much younger, perhaps Quaternary in age, than that off the Necker Island edifice, which has a 50 m pelagic drape. The pelagic drape off the Necker Island edifice suggests that the landslides may be as old as 9 Ma. The lack of pelagic drape off the French Frigate Shoals edifice suggests that the most recent landslides are more recent, perhaps even Quaternary in age. The presence of a chute-like feature on the mid-flank of the French Frigate Shoals edifice appears to be the result of rejuvenated volcanism that occurred long after the initial volcanism ceased to build the edifice.
Senolytic elimination of Cox2-expressing senescent cells inhibits the growth of premalignant pancreatic lesions
Authors: Kolodkin-Gal Dror , Roitman Lior , Ovadya Yossi , Azazmeh Narmen , Assouline Benjamin , Schlesinger Yehuda , Kalifa Rachel , Horwitz Shaul , Khalatnik Yonatan , Hochner-Ger Anna , Imam Ashraf , Demma Jonathan Abraham , Winter Eitan , Benyamini Hadar , Elgavish Sharona , Khatib Areej AS , Meir Karen , Atlan Karine , Pikarsky Eli , Parnas Oren , Dor Yuval , Zamir Gideon , Ben-Porath Ittai , Krizhanovsky Valery 
Published: March 2021

ObjectiveCellular senescence limits tumourigenesis by blocking the proliferation of premalignant cells. Additionally, however, senescent cells can exert paracrine effects influencing tumour growth. Senescent cells are present in premalignant pancreatic intraepithelial neoplasia (PanIN) lesions, yet their effects on the disease are poorly characterised. It is currently unknown whether senolytic drugs, aimed at eliminating senescent cells from lesions, could be beneficial in blocking tumour development.DesignTo uncover the functions of senescent cells and their potential contribution to early pancreatic tumourigenesis, we isolated and characterised senescent cells from PanINs formed in a Kras-driven mouse model, and tested the consequences of their targeted elimination through senolytic treatment.ResultsWe found that senescent PanIN cells exert a tumour-promoting effect through expression of a proinflammatory signature that includes high Cox2 levels. Senolytic treatment with the Bcl2-family inhibitor ABT-737 eliminated Cox2-expressing senescent cells, and an intermittent short-duration treatment course dramatically reduced PanIN development and progression to pancreatic ductal adenocarcinoma.ConclusionsThese findings reveal that senescent PanIN cells support tumour growth and progression, and provide a first indication that elimination of senescent cells may be effective as preventive therapy for the progression of precancerous lesions.
Core needle biopsy wash as a tool for acquiring additional diagnostic material for laboratory testing
Authors: Mojica Wilfrido , Cwiklinski Katherine , Jin Xiaobing , Liu Weiguo , Yergeau Donald 
Published: March 2021

AimsTo determine if a simple prewash step added to the processing workflow of tissue procurement by a core needle biopsy device will recover enough cells to expand the laboratory testing armamentarium.MethodsTissue was obtained from unfixed resection specimens using a core needle device and washed in a buffered solution before fixation. This creates a liquid aliquot from which dislodged cells can be kept and separated from the tissue specimen, the latter of which can then undergo traditional formalin-fixed, paraffin-embedded processing.ResultsCells dislodged from the tissue during the biopsy procedure are recoverable, are representative of the tissue section and of sufficient quantities for additional laboratory testing.ConclusionsThe core needle biopsy wash is an under-recognised and underutilised approach to extending the diagnostic capabilities of the limited amount of targeted material obtained during this common procedure. The ability to recover supplemental amounts of diagnostic material yields great potential as a substrate for a multitude of current and developing laboratory assays.
Automated text messaging follow-up for patients who receive peripheral nerve blocks
Authors: Gessner Daniel , Hunter Oluwatobi O , Kou Alex , Mariano Edward R 
Published: March 2021

BackgroundRoutine follow-up of patients who receive a nerve block for ambulatory surgery typically consists of a phone call from a regional anesthesia clinician. This process can be burdensome for both patients and clinicians but is necessary to assess the efficacy and complication rate of nerve blocks.MethodsWe present our experience developing an automated system for completing follow-up via short message service text messaging and our preliminary results using it at three clinical sites. The system is built on REDCap, a secure online research data capture platform developed by Vanderbilt University and currently available worldwide.ResultsOur automated system queried patients who received a variety of nerve block techniques, assessed patient-reported nerve block duration, and surveyed patients for potential complications. Patient response rate to text messaging averaged 91% (higher than our rates of daily phone contact reported previously) for patients aged 18 to 90 years.ConclusionsGiven the wide availability of REDCap, we believe this automated text messaging system can be implemented in a variety of health systems at low cost with minimal technical expertise and will improve both the consistency of patient follow-up and the service efficiency of regional anesthesia practices.
A dual regulatory effect of naringenin on bone homeostasis in two diabetic mice models
Authors: Liu Shufen , Dong Jingcheng , Bian Qin 
Published: March 2021

Objective: Naringenin (NAR), a flavanone in citrus fruits, has been reported to have both anti-diabetic and anti-osteoporotic effects. This study aimed to explore the effect of NAR on bone homeostasis under diabetic condition. Methods: High fat diet and streptozotocin (STZ) induced type 1 diabetic (T1DM) and leptin receptor knockout (db/db) type 2 diabetic (T2DM) mice were used to evaluate NAR effects. Melbine (DMBG) was administrated as positive control. Body weight and fasting blood glucose were monitored weekly and monthly. After 8 weeks and 74 days treatment, bone mass was evaluated by microcomputed tomography ([Formula: see text]CT) including BV/TV, Tb.N, and Tb.Th, as well as histological and histomorphometric detection. Bone resorption rate indicated by C-terminal telopeptide of type I collagen (CTIX) and N-terminal propeptide of type I procollagen (PINP) was examined by ELISA assays. Results: NAR treatment reduced body weight and blood glucose in both diabetic models, and had better hypoglycemic effect than DMBG at early stage. High fat diet and STZ-treated mice lost while db/db mice gained bone mass. NAR improved bone microarchitecture by regulating the related parameters to the similar levels as the control. Osteoblast activity was little affected, but osteoclast function was decreased in NAR-treated STZ mice. Consistently, NAR reduced bone resorption rate which was increased in both diabetic models. Conclusion: NAR exerts an anti-diabetic effect by lowering elevated level of blood glucose, regulating impaired bone mass, and reducing overactivated bone resorption rate in T1DM and T2DM conditions. Naringenin has a potential to prevent diabetes induced impairment in bone.
Systematic Analysis of Intronic miRNAs Reveals Cooperativity within the Multicomponent FTX Locus to Promote Colon Cancer Development
Authors: Kwok Zhi Hao , Zhang Bin , Chew Xiao Hong , Chan Jia Jia , Teh Velda , Yang Henry , Kappei Dennis , Tay Yvonne 
Published: March 2021

Abstract

Approximately half of all miRNA reside within intronic regions and are often cotranscribed with their host genes. However, most studies of intronic miRNA focus on individual miRNA, while conversely most studies of protein-coding and noncoding genes frequently ignore any intron-derived miRNA. We hypothesize that the individual components of such multigenic loci may play cooperative or competing roles in driving disease progression and that examining the combinatorial effect of these components would uncover deeper insights into their functional importance. To address this, we performed systematic analyses of intronic miRNA:host loci in colon cancer. The FTX locus, comprising of a long noncoding RNA FTX and multiple intronic miRNA, was highly upregulated in cancer, and cooperativity within this multicomponent locus promoted cancer growth. FTX interacted with DHX9 and DICER and regulated A-to-I RNA editing and miRNA expression. These results show for the first time that a long noncoding RNA can regulate A-to-I RNA editing, further expanding the functional repertoire of long noncoding RNA. Intronic miR-374b and miR-545 inhibited tumor suppressors PTEN and RIG-I to enhance proto-oncogenic PI3K-AKT signaling. Furthermore, intronic miR-421 may exert an autoregulatory effect on miR-374b and miR-545. Taken together, our data unveil the intricate interplay between intronic miRNA and their host transcripts in the modulation of key signaling pathways and disease progression, adding new perspectives to the functional landscape of multigenic loci.

Significance:
This study illustrates the functional relationships between individual components of multigenic loci in regulating cancer progression.
See related commentary by Calin, p. 1212
Vascular Normalization to Improve Treatment of COVID-19: Lessons from Treatment of Cancer
Authors: Munn Lance L. , Stylianopoulos Triantafyllos , Jain Natalie K. , Hardin C. Corey , Khandekar Melin J. , Jain Rakesh K. 
Published: March 2021

Abstract
The dramatic impact of the COVID-19 pandemic has resulted in an “all hands on deck” approach to find new therapies to improve outcomes in this disease. In addition to causing significant respiratory pathology, infection with SARS-CoV-2 (like infection with other respiratory viruses) directly or indirectly results in abnormal vasculature, which may contribute to hypoxemia. These vascular effects cause significant morbidity and may contribute to mortality from the disease. Given that abnormal vasculature and poor oxygenation are also hallmarks of solid tumors, lessons from the treatment of cancer may help identify drugs that can be repurposed to treat COVID-19. Although the mechanisms that result in vascular abnormalities in COVID-19 are not fully understood, it is possible that there is dysregulation of many of the same angiogenic and thrombotic pathways as seen in patients with cancer. Many anticancer therapeutics, including androgen deprivation therapy (ADT) and immune checkpoint blockers (ICB), result in vascular normalization in addition to their direct effects on tumor cells. Therefore, these therapies, which have been extensively explored in clinical trials of patients with cancer, may have beneficial effects on the vasculature of patients with COVID-19. Furthermore, these drugs may have additional effects on the disease course, as some ADTs may impact viral entry, and ICBs may accelerate T-cell–mediated viral clearance. These insights from the treatment of cancer may be leveraged to abrogate the vascular pathologies found in COVID-19 and other forms of hypoxemic respiratory failure.
Phenotypic Models of CAR T-Cell Activation Elucidate the Pivotal Regulatory Role of CAR Downmodulation
Authors: Greenman Raanan , Pizem Yoav , Haus-Cohen Maya , Horev Guy , Denkberg Galit , Shen-Orr Shai , Rubinstein Jacob , Reiter Yoram 
Published: March 2021

Abstract
Adoptive cell immunotherapy with chimeric antigen receptor (CAR) showed limited potency in solid tumors, despite durable remissions for hematopoietic malignancies. Therefore, an investigation of ways to enhance the efficacy of CARs' antitumor response has been engaged upon. We previously examined the interplay between the biophysical parameters of CAR binding (i.e., affinity, avidity, and antigen density), as regulators of CAR T-cell activity and detected nonmonotonic behaviors of affinity and antigen density and an interrelation between avidity and antigen density. Here, we built an evolving phenotypic model of CAR T-cell regulation, which suggested that receptor downmodulation is a key determinant of CAR T-cell function. We verified this assumption by measuring and manipulating receptor downmodulation and intracellular signaling processes. CAR downmodulation inhibition, via actin polymerization inhibition, but not inhibition of regulatory inhibitory phosphatases, was able to increase CAR T-cell responses. In addition, we documented trogocytosis in CAR T cells that depends on actin polymerization. In summary, our study modeled the parameters that govern CAR T-cell engagement and revealed an underappreciated mechanism of T-cell regulation. These results have a potential to predict and therefore advance the rational design of CAR T cells for adoptive cell treatments.
See related article on p. 872
Abstract PO023: Single-cell transcriptomics identifies gene expression networks driving differentiation and tumorigenesis in the human fallopian tube
Authors: Dinh Huy Q. , Lin Xianzhi , Abbasi Forough , Nameki Robbin , Haro Marcela , Olingy Claire , Chang Heidi , Hernandez Lourdes , Gayther Simon , Wright Kelly N. , Aspuria Paul-Joseph , Karlan Beth , Corona Rosario I. , Li Andrew , Rimel B.J. , Siedhoff Matthew , Medeiros Fabiola , Lawrenson Kate 
Published: March 2021

Abstract
The human fallopian tube harbors the cell-of-origin for the majority of high-grade serous ‘ovarian’ cancers (HGSCs), but its cellular composition, particularly the epithelial component, is poorly characterized. We performed single-cell transcriptomic profiling in 12 primary fallopian specimens from 8 patients, analyzing around 53,000 individual cells to map the major immune, fibroblastic and epithelial cell types present in this organ. We identified 10 epithelial sub-populations, characterized by diverse transcriptional programs including SOX17 (enriched in secretory epithelial cells), TTF3 and RFX3 (enriched in ciliated cells) and NR2F2 (enriched in early, partially differentiated secretory cells). Based on transcriptional signatures, we reconstructed a trajectory whereby secretory cells differentiate into ciliated cells via a RUNX3high intermediate. Computational deconvolution of the cellular composition of advanced HGSCs based on epithelial subset signatures identified the ‘early secretory’ population as a likely precursor state for the majority of HGSCs. The signature of this rare population of cells comprised both epithelial (EPCAM, KRT) and mesenchymal (THY1, ACTA2) features, and was enriched in mesenchymal-type HGSCs, a group known to have particularly poor prognoses. This cellular and molecular compendium of the human fallopian tube in cancer-free women is expected to advance our understanding of the earliest stages of fallopian epithelial neoplasia. Further computational analyses on fibroblast and immune cells together with tumor single-cell data reveals extended contribution of non-epithelial microenvironment and cell-cell interactions and communications in fallopian tube that potentially drive HGSC progression.
Citation Format: Huy Q. Dinh, Xianzhi Lin, Forough Abbasi, Robbin Nameki, Marcela Haro, Claire Olingy, Heidi Chang, Lourdes Hernandez, Simon Gayther, Kelly N. Wright, Paul-Joseph Aspuria, Beth Karlan, Rosario I. Corona, Andrew Li, B.J. Rimel, Matthew Siedhoff, Fabiola Medeiros, Kate Lawrenson. Single-cell transcriptomics identifies gene expression networks driving differentiation and tumorigenesis in the human fallopian tube [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO023.
Abstract IA-05: Deep learning radiomics in cancer imaging
Authors: Hosny Ahmed 
Published: March 2021

Abstract
Radiographic medical images contain a vast wealth of information allowing for accurate non-invasive tumor characterization and ultimately improving cancer care. Radiomics enables the extraction of mineable high-dimensional features from images, quantification of tumor phenotypes for survival, recurrence, and treatment response prediction, and ultimately better patient stratification. Recent advances in AI, deep learning in particular, has allowed for the automated extraction of imaging features without the need for pre-definition. In this talk, we will be exploring deep learning radiomics applications in cancer patients from both single time point and longitudinal imaging data. We will also be identifying challenges regarding the stability, reproducibility, and transparency of such approaches.
Citation Format: Ahmed Hosny. Deep learning radiomics in cancer imaging [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-05.
Abstract IA-07: Radiomics: Transforming standard imaging into mineable data for diagnostic and theragnostic applications
Authors: Lambin Philippe 
Published: March 2021

Abstract
The rise of radiomics, the high-throughput mining of quantitative image features from (standard-of-care) medical imaging for knowledge extraction and application within clinical decision support systems (animation: https://youtu.be/Tq980GEVP0Y) to improve diagnostic, prognostic, and predictive accuracy, has significant and substantial implications for the medical community (1, 2, 5). Radiomic analysis exploits sophisticated image analysis tools and the exponential growth of medical imaging data to develop and validate powerful image-based signatures/models. We will describe the process of radiomics, its pitfalls, challenges, opportunities, and its capacity to improve clinical decision making (presently primarily in the care of patients with cancer, however, all imaged patients may benefit from quantitative radiology) (5,8). Finally, the field of radiomics is emerging rapidly; however, the field lacks standardized evaluation of both the scientific integrity and the clinical significance of the numerous published radiomics investigations resulting from this growth. There is a clear and present need for rigorous evaluation criteria and reporting guidelines in order for radiomics to mature as a discipline (see www.radiomics.world). Certain author’s proposed that radiomics could be used as a “virtual biopsy”. It could be the case in the sense that several reports demonstrated that biological features of tumours such as EGFR mutations, HPV status and even hypoxia could be quantified by radiomics (6). There are however two main differences: a) Radiomics is based on the whole tumour in contrast to a biopsy taken most often randomly in an heterogeneous tumour and b) the radiomics values is a continuous variable in contrast to molecular biology assays which are often dichotomized (e.g. mt vs wt). Interestingly, certain radiomics signatures e.g. a proliferation radiomics signature, works as well with cone beam CT which opens the field of “4D-Radiomics” (4, 7). The next step is however a “totalomisc” approach in which radiomics signatures will be used in a multifactorial Decision Support System for both diagnostic or theragnostic questions (3, 9, 10).
Citation Format: Philippe Lambin. Radiomics: Transforming standard imaging into mineable data for diagnostic and theragnostic applications [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-07.
Abstract IA-19: Machine learning and AI in molecular pathology diagnostics and clinical management of cancer
Authors: Snuderl Matija 
Published: March 2021

Abstract
Molecular diagnostics of cancer has undergone a revolution driven by development of high throughput molecular techniques. It is increasingly recognized that malignant tumors previously considered a single entity are in fact composed of multiple different entities that vary in their molecular genetics, underlying biology and most importantly clinical outcome. Integration of omic- and clinical data into practical classification schemes requires novel machine learning approaches to manage big data in a clinically reasonable turnaround time. Accurate molecular classification will make future clinical trials more informative and lead to development of novel therapeutic strategies. While highly informative, advanced molecular testing is expensive and not widely available. We have developed novel methods to predict mutations directly from histopathological slides using artificial intelligence (AI) and image analysis. Mutations in various genes including EGFR, STK11, and BRAF can be predicted with high accuracy by the analysis of the H&E slide image, which is a standard stain in pathology laboratories across the world. Mutational prediction by AI provides a rapid low-cost method to screen patients for potentially targetable mutations in cancer. Cloud based AI mutational predictors could also bring molecular diagnostics to remote or medically underserved areas.
Citation Format: Matija Snuderl. Machine learning and AI in molecular pathology diagnostics and clinical management of cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-19.