bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract IA-11: Combining multiplexed assays of variant effect and modeling to drive variant interpretation
Authors: Fowler Douglas
Published: March 2021

Germline genetic variation can strongly influence lifetime cancer risk and somatic variation can influence prognosis and treatment. However, variants are difficult to interpret, even when they occur in cancer-associated genes. Multiplexed assays of variant effect leverage deep sequencing to enable the experimental assessment of thousands of genetic variants simultaneously. The resulting large-scale variant functional data can be used to drive variant interpretation, empowering the use of genetic information in cancer prevention and treatment. We are developing multiplexed assays of variant effect that can be deployed widely, with the ultimate goal of measuring the effect of most variants at most disease-related genes in the human genome.

Citation Format: Douglas Fowler. Combining multiplexed assays of variant effect and modeling to drive variant interpretation [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-11.
Abstract IA-22: Automated treatment planning and quality assurance in radiation oncology
Authors: Purdie Thomas G.
Published: March 2021

The delivery of radiation for the treatment of cancer is a complicated process that requires both clinical and technical expertise to ensure radiation treatments are safe and effective. Sub-optimal radiation treatments have the potential to result in significant detriment to the patient and several studies have shown radiation treatments, which deviate from established clinical guidelines, result in worse patient outcomes. Therefore, the current radiation treatment process requires substantial multi-disciplinary resources to both generate and verify radiation treatments are of high-quality. In this talk, a previously validated machine learning platform customized for radiation oncology will be presented. The method automatically learns based on data from thousands of previously treated patients which relationships and patterns in radiation oncology image and treatment data and has been applied for automated data mining activities, automated quality assurance to support expedited radiation treatment review, and for radiation dose prediction to develop new radiation treatments by best deciding where dose should be placed and how dose should be delivered without requiring any manual intervention. Therefore, the method can be used to both generate personalized radiation treatments and to quantitatively score radiation treatments for quality and classify radiation treatments that have errors. The automated platform can readily be integrated into current clinical process to improve efficiency in the radiation treatment planning and plan review processes and to better utilize the vast data we have to ensure we are providing patients with highly personalized radiation treatments.

Citation Format: Thomas G. Purdie. Automated treatment planning and quality assurance in radiation oncology [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-22.
Abstract PO-052: Exploring patient derived xenografts based pharmacogenomic data for precision oncology
Authors: Mer Arvind Singh , Haibe-Kains Benjamin
Published: March 2021

Preclinical cancer models play a vital role in oncology research and precision medicine. Patient-derived tumor xenografts (PDXs) are used as reliable preclinical models for studying tumor biology and for testing anti-cancer therapies that are tailored according to genomic characteristics of tumors. Several academic groups, research institutes, and commercial organizations are generating and distributing PDX models. However the distributed nature of PDX model generation and lack of central repository make it challenging to find PDX models with specific characteristics. Furthermore this also hinders meta-analysis (across datasets) of PDX pharmacogenomic data. International consortia and catalogs of PDX models such as PDXNet, EurOPDX and PDXFinder are being developed to standardize PDX associated metadata and facilitate material sharing. Recently we have developed Xenograft Visualization & Analysis (Xeva), an open-source software package in R programming language. Xeva allows PDX growth curve visualization, different response metrics computation and biomarker discovery. Extending to this we have developed XevaDB, a database of PDX drug response and genomic profiles. XevaDB is the first resource to allow concurrent visualization of drug response and associated molecular data such as mutation and copy number alterations. Furthermore XevaDB enables exploration of the tumor growth curve of a PDX model, along with corresponding control. XevaDB contains PDXs from >600 individual patients, spanning across nine different tissue types and >70 drugs. Using XevaDB, we have performed meta-analysis of PDX pharmacogenomic data and have identified 90 pathways significantly associated with response to 53 drugs (FDR < 5%). Our results show that activity of the EGFR signaling pathway is significantly associated with erlotinib response in lung cancer PDXs. We have also found that in PDXs, response to binimetinib is associated with the MAP kinase activation pathway. XevaDB provides a comprehensive resource to search and explore PDX pharmacogenomic data. By combining drug response with genomic data of PDXs, XevaDB allows researchers to quickly find the model of interest and access the data to answer their biological questions. As PDXs based pharmacogenomic datasets continue to expand, XevaDB will facilitate easy access and analysis of this valuable data by the scientific community.

Citation Format: Arvind Singh Mer, Benjamin Haibe-Kains. Exploring patient derived xenografts based pharmacogenomic data for precision oncology [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 PO-052.
Abstract PO-066: Data standardization, integration and meta-analysis of preclinical pharmacogenomics studies for gene expression biomarker discovery
Authors: Smirnov Petr , Haibe-Kains Benjamin
Published: March 2021

The sparsity of predictive biomarkers for drug response remains a major impediment to the clinical success of precision oncology. Over the past decade, massive studies combining in-vitro drug screening with high-throughput molecular profiling of cancer cell lines have been published, with the goal of discovering novel predictive biomarkers for drug response. Unfortunately, inconsistencies in the data, as well as a lack of standards in the field, has effectively siloed the findings of these studies away from the clinical researchers working in precision medicine. In our previous work developing the PharmacoGx/PharmacoDB platform, we have reprocessed and curated the 7 largest pharmacogenomic studies released to date. Together, these studies profiled 760 compounds across ~1600 cell lines, in over 650,000 drug dose response experiments. Here, we present an update of this database, and describe our preliminary findings from a statistical meta-analysis of these data for the discovery of gene expression biomarkers. Our meta-analysis looked for markers consistently associated with drug response across 11 tissue types and 70 compounds found in at least 3 studies in the examined dataset. From these data, we find approximately 4338 consistent associations across studies surviving multiple hypothesis correction, in 1946 genes, across 8 tissues and 34 different drugs. The results show evidence of both drug-mechanism specific markers of response, as well as markers of multi-drug resistance phenotypes. Within lung cancer cell lines, we observe an enrichment of TGF-β signalling related genesets among markers of multi-drug sensitivity and resistance. We discuss our approach to validate these markers using organoid, in vivo and clinical datasets. Finally, we detail tools we are building for researchers to explore our database of putative biomarkers and the data supporting them; focusing on exposing our findings to the clinical precision medicine research community. Ultimately, our goal is to extract a database of high confidence preclinical associations from the consensus of published pharmacogenomic studies. This database would be the first step in translating findings from these massive preclinical studies towards novel clinically actionable biomarkers for use in the pursuit of precision cancer care.

Citation Format: Petr Smirnov, Benjamin Haibe-Kains. Data standardization, integration and meta-analysis of preclinical pharmacogenomics studies for gene expression biomarker discovery [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 PO-066.
Abstract PO-075: Kinotype to phenotype: Perturbed phosphoproteomic state predicts cancer cell growth rates in vitro
Authors: Robson Isaac S. , Berginski Matthew E. , Gomez Shawn M.
Published: March 2021

Numerous aspects of cellular signaling are regulated by the kinome - the network of over 500 protein kinases that guides and modulates information transfer throughout the cell. The key role played by both individual kinases and assemblies of kinases organized into functional subnetworks leads to kinome dysregulation being a key driver of many diseases, particularly cancer. Linked with their role in disease, the druggability of kinases has led to increased interest in the development of kinase inhibitors, with over fifty now having achieved FDA approval. These and other yet to be approved compounds have been used in a variety of contexts, including in screens to test their efficacy as potential therapeutics. Recent proteomics techniques including Kinobeads and multiplexed inhibitor beads linked with mass spectroscopy (MIB/MS) are a relatively new mechanism which affords the ability to assess the state of the protein kinome en masse. When combined with perturbation with targeted kinase inhibitors, the quantification of the dynamic response of the kinome provides a novel platform for the study of cell signaling and potential design of drug therapies. Here, we describe an approach that links the state of the kinome, or kinotype, with a downstream cancer cell phenotype, in this case, cellular growth. Integrating independent perturbation and growth response data sets, we find that the kinotype of a cell has a significant and predictive relationship with cell growth. More specifically, we characterize kinome response to perturbation via Kinobeads within models aimed at predicting cellular growth inhibition rates. Integrating 82 drugs, 237 kinases, and 380 cell lines (both malignant and nonmalignant) into a sparse GLM predicts growth rate inhibition at multiple doses of an unseen small molecule with an r^2 value of 0.624 (Bonferroni corrected p-value of 5.7 × 10^−69), even with an unmatched dataset. We further explore the use of higher-level kinase relationships, i.e., kinome subnetworks, along with manifold learning approaches as a component of these models to better ascertain the potential impact of kinome architecture in cellular response. Together, this systems view of the kinome presents potential opportunities for improved cancer disease classification, the identification of new drug targets, as well as impacting on the broader design of combination therapies for cancer treatment.

Citation Format: Isaac S. Robson, Matthew E. Berginski, Shawn M. Gomez. Kinotype to phenotype: Perturbed phosphoproteomic state predicts cancer cell growth rates in vitro [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 PO-075.
Abstract PR-09: Genetic risk scores for breast cancer based on machine learning analysis of chromosomal-scale length variation
Authors: Ko Charmeine , Toh Christopher , Brody James P.
Published: March 2021

Inherited factors are thought to be responsible for a substantial fraction of breast cancers, but only a small fraction of breast cancers are caused by mutations to known genes, like BRCA1. Most current genetic risk scores for breast cancer focus on the additive effects of single nucleotide polymorphisms (SNPs) found in germ-line DNA. This process ignores epistatic interactions between different genes. We sought to use modern machine learning algorithms to identify complex patterns in germ line DNA that are correlated with the incidence of breast cancer, a strategy which should include epistatic interactions. We looked for these patterns in measurements of chromosomal-scale length variation of germ line DNA. These measurements represents the sum of many insertions, deletions, and copy number variations across the chromosome. We evaluated several different machine learning models, including: a generalized linear model, a distributed random forest, a gradient boosting machine, and a deep learning model. We evaluated these models on two independent large datasets, the Cancer Genome Atlas (TCGA) and the UK Biobank. We found that chromosomal-scale length variation of germline DNA, in combination with machine learning models, can be used to predict whether a woman will develop breast cancer. In the Cancer Genome Atlas (TCGA) dataset, we used a dataset with 968 (cases) women who had been diagnosed with breast cancer and 3715 (controls) women who had not been diagnosed with breast cancer. We found that a gradient boosting algorithm could differentiate between those two classes of women with an AUC=0.73. In the UK Biobank dataset, we identified 1534 (cases) women who had been diagnosed with breast cancer and compared them with a set of 4391 (controls) women who had no report of any type of cancer. In this UK Biobank dataset, we could distinguish between the two classes of women with an AUC =0.83. In conclusion, we found that artificial intelligence algorithms could be used to develop effective genetic risk scores for breast cancer.

Citation Format: Charmeine Ko, Christopher Toh, James P. Brody. Genetic risk scores for breast cancer based on machine learning analysis of chromosomal-scale length variation [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 PR-09.
Interception Targets ofAngelica GigasNakai Root Extract versus Pyranocoumarins in Prostate Early Lesions and Neuroendocrine Carcinomas in TRAMP Mice
Authors: Tang Su-Ni , Jiang Peixin , Kim Sangyub , Zhang Jinhui , Jiang Cheng , Lü Junxuan
Published: March 2021

We reported efficacy of Angelica gigas Nakai (AGN) root ethanol extract and equimolar decursin (D)/decursinol angelate (DA) through daily gavage starting at 8 weeks of age (WOA) to male transgenic adenocarcinoma of mouse prostate (TRAMP) mice such that these modalities suppressed precancerous epithelial lesions in their dorsolateral prostate (DLP) to similar extent, but AGN extract was better than the D/DA mixture at promoting the survival of mice bearing prostate neuroendocrine carcinomas to 28 WOA. Here, we compared by microarray hybridization the mRNA levels in pooled DLP tissues and individual neuroendocrine carcinomas to characterize potential molecular targets of AGN extract and D/DA. Clustering and principal component analyses supported distinct gene expression profiles of TRAMP DLP versus neuroendocrine carcinomas. Pathway Enrichment, Gene Ontology, and Ingenuity Pathway Analyses of differential genes indicated that AGN and D/DA affected chiefly processes of lipid and mitochondrial energy metabolism and oxidation-reduction in TRAMP DLP, while AGN affected neuronal signaling, immune systems and cell cycling in neuroendocrine carcinomas. Protein–Protein Interaction Network analysis predicted and reverse transcription-PCR verified multiple hub genes common in the DLP of AGN- and D/DA-treated TRAMP mice at 28 WOA and select hub genes attributable to the non-D/DA AGN components. The vast majority of hub genes in the AGN-treated neuroendocrine carcinomas differed from those in TRAMP DLP. In summary, the transcriptomic approach illuminated vastly different signaling pathways and networks, cellular processes, and hub genes of two TRAMP prostate malignancy lineages and their associations with the interception efficacy of AGN and D/DA.

Prevention Relevance:

This study explores potential molecular targets associated with in vivo activity of AGN root alcoholic extract and its major pyranocoumarins to intercept precancerous epithelial lesions and early malignancies of the prostate. Without an ethically-acceptable, clearly defined cancer initiation risk reduction strategy available for the prostate, using natural products like AGN to delay formation of malignant tumors could be a plausible approach for prostate cancer prevention.
Prevention of Skin Carcinogenesis by the Non-β-blocking R-carvedilol Enantiomer
Authors: Liang Sherry , Shamim Md Abdullah , Shahid Ayaz , Chen Mengbing , Cleveland Kristan H. , Parsa Cyrus , Orlando Robert , Andresen Bradley T. , Huang Ying
Published: March 2021

Skin cancer is the most common malignancy worldwide and is rapidly rising in incidence, representing a significant public health challenge. The β-blocker, carvedilol, has shown promising effects in preventing skin cancer. However, as a potent β-blocker, repurposing carvedilol to an anticancer agent is limited by cardiovascular effects. Carvedilol is a racemic mixture consisting of equimolar S- and R-carvedilol, whereas the R-carvedilol enantiomer does not possess β-blocking activity. Because previous studies suggest that carvedilol's cancer preventive activity is independent of β-blockade, we examined the skin cancer preventive activity of R-carvedilol compared with S-carvedilol and the racemic carvedilol. R- and S-carvedilol were equally effective in preventing EGF-induced neoplastic transformation of the mouse epidermal JB6 Cl 41-5a (JB6 P+) cells and displayed similar attenuation of EGF-induced ELK-1 activity. R-carvedilol appeared slightly better than S-carvedilol against UV-induced intracellular oxidative stress and release of prostaglandin E2 from the JB6 P+ cells. In an acute UV-induced skin damage and inflammation mouse model using a single irradiation of 300 mJ/cm2 UV, topical treatment with R-carvedilol dose dependently attenuated skin edema and reduced epidermal thickening, Ki-67 staining, COX-2 protein, and IL6 and IL1β mRNA levels similar to carvedilol. In a chronic UV (50–150 mJ/cm2) induced skin carcinogenesis model in mice with pretreatment of test agents, topical treatment with R-carvedilol, but not racemic carvedilol, significantly delayed and reduced skin squamous cell carcinoma development. Therefore, as an enantiomer present in an FDA-approved agent, R-carvedilol may be a better option for developing a safer and more effective preventive agent for skin carcinogenesis.

Prevention Relevance:

In this study, we demonstrated the skin cancer preventive activity of R-carvedilol, the non-β-blocking enantiomer present in the racemic β-blocker, carvedilol. As R-carvedilol does not have β-blocking activity, such a preventive treatment would not lead to common cardiovascular side effects of β-blockers.
How to Reprogram Myeloma-Associated Macrophages: Target IKZF1
Authors: De Sanctis Francesco , Bronte Vincenzo
Published: March 2021

Cancer cells hijack tumor-associated macrophages to sustain their outgrowth. In this issue, Mougiakakos and colleagues identify the IKZF1–IRF4/IRF5 axis as a key molecular pathway regulating macrophage polarization in multiple myeloma. These results suggest targeting IKZF1 could provide a new strategy to reprogram myeloma-associated macrophages toward a tumoricidal and immune-activating phenotype.

See article by Mougiakakos et al., p. 265
TRPV1 (Transient Receptor Potential Vanilloid 1) Sensitization of Skeletal Muscle Afferents in Type 2 Diabetic Rats With Hyperglycemia
Authors: Ishizawa Rie , Kim Han-Kyul , Hotta Norio , Iwamoto Gary A. , Mitchell Jere H. , Smith Scott A. , Vongpatanasin Wanpen , Mizuno Masaki
Published: March 2021

The blood pressure response to exercise is exaggerated in type 2 diabetes (T2D). However, the underlying mechanisms remain unclear. It is hypothesized that one mechanism mediating the potentiated cardiovascular response in T2D is the sensitization of chemically sensitive afferent neurons by activation of metaboreceptors. To test this hypothesis, we examined TRPV1 (transient receptor potential vanilloid 1)-induced cardiovascular responses in vivo and muscle afferent discharge ex vivo in T2D rats. Additionally, TRPV1 and PKC (protein kinase C) protein levels in dorsal root ganglia subserving skeletal muscle were assessed. For 14 to 16 weeks, Sprague-Dawley rats were given either a normal diet (control) or a high-fat diet in combination with a low dose (35 and 25 mg/kg) of streptozotocin (T2D). Administration of capsaicin, TRPV1 agonist, in hindlimb evoked significantly greater increases in mean arterial pressure and renal sympathetic nerve activity in decerebrated T2D than control. In a muscle-nerve preparation, the discharge to capsaicin exposure in group IV afferents isolated from T2D was likewise significantly augmented at a magnitude that was proportional to glucose concentration. Moreover, the discharge to capsaicin was potentiated by acute exposure of group IV afferents to a high-glucose environment. T2D showed significantly increased phospholyrated-TRPV1 and -PKCα levels in dorsal root ganglia neurons as compared with control. These findings suggest that group IV muscle afferents are sensitized by PKC-induced TRPV1 overactivity in early stage T2D with hyperglycemia and, thereby, may contribute to the potentiated circulatory response to TRPV1 activation in the disease.
FPR-1 (Formyl Peptide Receptor-1) Activation Promotes Spontaneous, Premature Hypertension in Dahl Salt-Sensitive Rats
Authors: Edwards Jonnelle M. , Roy Shaunak , Galla Sarah L. , Tomcho Jeremy C. , Bearss Nicole R. , Waigi Emily W. , Mell Blair , Cheng Xi , Saha Piu , Vijay-Kumar Matam , McCarthy Cameron G. , Joe Bina , Wenceslau Camilla F.
Published: March 2021

Cell death has long been a characteristic phenotype of organ damage in hypertension, and recently, leaky gut has been revealed as a novel hypertensive phenotype. However, despite the increase in bacterial and damaged mitochondrial products in the circulation of hypertensive patients and animals, the mechanistic contribution of these two phenomena to hypertension pathophysiology is unknown. Mitochondria and bacteria both start protein translation with an N-formyl methionine residue and thus are the only sources of NFPs (N-formyl peptides), which activate the FPR-1 (formyl peptide receptor-1). We hypothesized that the synergistic action of bacterial and mitochondrial NFPs would cause the spontaneous elevation of blood pressure and vascular remodeling in male Dahl salt-sensitive rats via FPR-1. We observed that mitochondria-derived peptides originating from cell death in the kidneys are responsible for FPR-1–induced vascular hypercontractility and remodeling and premature elevation of BP in Dahl salt-sensitive rats fed a low-salt diet. However, a high-salt diet leads to gut barrier disruption and, subsequently, a synergistic action of mitochondria, and bacteria-derived leaky gut NFPs lead to a severe and established hypertension. Administration of an FPR-1 antagonist lowered blood pressure in Dahl salt-sensitive rats on a low-salt diet but amoxicillin administration did not. These results reveal for the first time that cell death can be a cause of hypertensive pathophysiology, whereas leaky gut is a consequence.
Obstructive Sleep Apnea–Induced Neurogenic Nocturnal Hypertension
Authors: Kario Kazuomi , Hettrick Douglas A. , Prejbisz Aleksander , Januszewicz Andrzej
Published: March 2021

There is a bidirectional, causal relationship between obstructive sleep apnea (OSA) and hypertension. OSA-related hypertension is characterized by high rates of masked hypertension, elevated nighttime blood pressure, a nondipper pattern of nocturnal hypertension, and abnormal blood pressure variability. Hypoxia/hypercapnia-related sympathetic activation is a key pathophysiological mechanism linking the 2 conditions. Intermittent hypoxia also stimulates the renin-angiotensin-aldosterone system to promote hypertension development. The negative and additive cardiovascular effects of OSA and hypertension highlight the importance of effectively managing these conditions, especially when they coexist in the same patient. Continuous positive airway pressure is the gold standard therapy for OSA but its effects on blood pressure are relatively modest. Furthermore, this treatment did not reduce the cardiovascular event rate in nonsleepy patients with OSA in randomized controlled trials. Antihypertensive agents targeting sympathetic pathways or the renin-angiotensin-aldosterone system have theoretical potential in comorbid hypertension and OSA, but current evidence is limited and combination strategies are often required in drug resistant or refractory patients. The key role of sympathetic nervous system activation in the development of hypertension in OSA suggests potential for catheter-based renal sympathetic denervation. Although long-term, randomized controlled trials are needed, available data indicate sustained and relevant reductions in blood pressure in patients with hypertension and OSA after renal denervation, with the potential to also improve respiratory parameters. The combination of lifestyle interventions, optimal pharmacological therapy, continuous positive airway pressure therapy, and perhaps also renal denervation might improve cardiovascular risk in patients with OSA.
Increase in Bioavailability of Nitric Oxide After Renal Denervation Improves Kidney Function in Sheep With Hypertensive Kidney Disease
Authors: Singh Reetu R. , McArdle Zoe M. , Booth Lindsea C. , May Clive N. , Head Geoff A. , Moritz Karen M. , Schlaich Markus P. , Denton Kate M.
Published: March 2021

Overactivity of renal sympathetic nerves and nitric oxide (NO) deficiency occur in hypertensive chronic kidney disease (CKD). In sheep with hypertensive CKD and NO deficiency, renal denervation (RDN) reduces blood pressure and improves kidney function (glomerular filtration rate). We hypothesized that this improvement in glomerular filtration rate after RDN is associated with increased NO bioavailability. In this study, glomerular filtration rate response to systemic inhibition of NOS (NO synthase) was examined in healthy and CKD sheep at 2 and 30 months after a sham (intact nerves) or RDN procedure. Basal urinary total nitrate (nitrate+nitrite) excretion was examined at 2 and 30 months, and kidney protein expression of endothelial and neuronal NOS was assessed at 30 months. Urinary nitrate+nitrite in CKD-RDN and healthy sheep was ≈50% to 70% greater than in CKD-intact. During NOS inhibition, the fall in glomerular filtration rate in CKD-RDN sheep was ≈20% greater than in CKD-intact. These effects in CKD-RDN sheep were similar to those in healthy sheep. Endothelial NOS protein expression was lower in CKD-intact sheep compared with healthy sheep and compared with CKD-RDN. In summary, RDN normalizes NO bioavailability and restores contribution of NO to renal hemodynamics in CKD. These changes may promote improvements in kidney function and sustained blood pressure lowering after RDN in hypertensive CKD.
Spontaneous Cervical Artery Dissection in Vascular Ehlers-Danlos Syndrome
Authors: Adham Salma , Billon Clarisse , Legrand Anne , Domigo Valérie , Denarié Nicolas , Charpentier Etienne , Jeunemaitre Xavier , Frank Michael
Published: March 2021

Background and Purpose:

Vascular Ehlers-Danlos syndrome is a rare inherited connective tissue disorder because of pathogenic variants in the
COL3A1
gene. Arterial complications can affect all anatomic areas and about 25% involve supra-aortic trunks (SATs) but no systematic assessment of cervical artery lesions has been made. The primary objective was to determine an accurate prevalence of spontaneous SAT lesions in a large series of patients with vascular Ehlers-Danlos syndrome at diagnosis and during follow-up. Secondary objectives were to study their neurological consequences (transient ischemic attack or stroke) and the possible relationships with sex, genotype, ascertainment status.

Methods:

A retrospective review of a monocentric cohort of patients with molecularly proven vascular Ehlers-Danlos syndrome followed in a tertiary referral center from 2000 to 2017.

Results:

One hundred forty-four patients were analyzed, 56.9% (n=82) had SAT lesions: 64.6% females, 74.4% index-case patients. Most lesions were identified in early arterial assessment (48% at first work-up, mean age of 35.7±13.0 years). Cumulative incidence of a first identification of a SAT lesion was 41.7% at 40 years old. On the complete period of survey, 183 SAT lesions (with 132 dissections and 33 aneurysms) were identified, mainly in internal carotid arteries (56.3%) and vertebral arteries (28.9%), more rarely in patients with
COL3A1
null mutations (
P
=0.008). Transient ischemic attack or stroke were reported in n=16 (19.5%) of the 82 patients with SAT lesions without relation with age, sex, treatment, or hypertension.

Conclusions:

Cervical artery lesions are frequent and mostly asymptomatic in patients with vascular Ehlers-Danlos syndrome. Local dissections and aneurysms are the most frequent type of lesions, but transient ischemic attack or stroke seem rare.
Reforecasting Two Heavy-Precipitation Events with Three Convection-Permitting Ensembles
Authors: Capecchi Valerio
Published: March 2021

We investigate the potential added value of running three limited-area ensemble systems (with the WRF, Meso-NH, and MOLOCH models and a grid spacing of approximately 2.5 km) for two heavy-precipitation events in Italy. Such high-resolution ensembles include an explicit treatment of convective processes and dynamically downscale the ECMWF global ensemble predictions, which have a grid spacing of approximately 18 km. The predictions are verified against rain gauge data, and their accuracy is evaluated over that of the driving coarser-resolution ensemble system. Furthermore, we compare the simulation speed (defined as the ratio of simulation length to wall-clock time) of the three limited-area models to estimate the computational effort for operational convection-permitting ensemble forecasting. We also study how the simulation wall-clock time scales with increasing numbers of computing elements (from 36 to 1152 cores). Objective verification methods generally show that convection-permitting forecasts outperform global forecasts for both events, although precipitation peaks remain largely underestimated for one of the two events. Comparing simulation speeds, the MOLOCH model is the fastest and the Meso-NH is the slowest one. The WRF Model attains efficient scalability, whereas it is limited for the Meso-NH and MOLOCH models when using more than 288 cores. We finally demonstrate how the model simulation speed has the largest impact on a joint evaluation with the model performance because the accuracy of the three limited-area ensembles, amplifying the forecasting capability of the global predictions, does not differ substantially.
Preaching by the Rivers of Babylon: How an Exile from Pulpit and Pew Can Change White Preaching On the Other Side of Pandemic
Authors: Sigmon Casey T.
Published: March 2021

Preaching platforms have always influenced the message preachers prepare and the message people receive, for good and for ill. The shift from the pulpit platform to social media platforms during stay-at-home orders due to the COVID-19 pandemic reveals a legacy of White supremacy haunting the sanctuary. This essay explores this legacy, its relationship with technoculture, and its impact on the practice of White preaching.
From the Margins of the Spice Garden Economy: Agroforestry and Gendered Practices in the Western Ghats, Karnataka
Authors: Rao Manisha
Published: March 2021

The present coronavirus pandemic has created havoc in lives and livelihoods of people across the world. In just a few months, the world as we knew it has irretrievably changed. If one were to trace the roots of the crisis, it would lead one to the shift from sustainable farming systems to market-based systems that have increased agricultural productivity but have led to the breakdown of humanity’s relationship with nature.

In the Malnad (up-ghat) region of the Uttara Kannada district of Karnataka, known for its diversified spice garden agroforestry practices, a similar change can be observed. Over the last decade, there has been an increasing conversion of paddy land and forest encroachments for cultivation of areca, leading to a change in the biodiversity of the region. The changes in the land use patterns and the destruction of the environment caused by infrastructure projects are among some of the important reasons that have resulted in increasing drought-like situations in an area known to be the wettest region of the Western Ghats and resulting in epidemics endemic to the region.

However, in the shadow of the areca-spice garden economy of this region, there is a lesser known but growing economy—the home garden agroforestry. The gendered practices of the home gardens, run mainly by the women of the community, provide the vital everyday inputs for the household. Though high in terms of use value, the home gardens are low in terms of exchange value. It is in the context of mapping the cultural and developmental contours of this region that one tries to understand the gendered practices of the local communities that are a beacon of hope in times of a pandemic. In this article, one attempts to examine the marginal though crucial initiatives of women of this district to preserve the biodiversity of the region and provide for food in the kitchens. Finally, it attempts to connect the dots between gender, environment and development and argues for the adoption of a critical feminist political ecology perspective to analyse the gendered agroforestry practices.
Dalits and Choice of School: A Sociological Study of Private Schools in Telangana State
Authors: Harinath Silveru , Gundemeda Nagaraju
Published: March 2021

Why parents prefer private schools when the government schools provide education free of cost is the major question confronting the social scientists in contemporary India. What constitutes school choice and what is the nature of the relationship between the socio-economic background of the children studying in government and private schools are some of the key research questions addressed in this article. What is the response of the Dalits towards government and private schools, as most of the previous empirical studies are based on government schools? The current article, based on an empirical study conducted in private schools in Telangana, argues that caste, class and gender play a significant role in shaping school choice among the Dalits. Though a Dalit middle-class parent provides equal opportunity for his/her daughter on par with a son, working-class Dalit parents prefer a private school for sons and a government school for daughters. As English as medium of instruction provided in private schools is perceived as a standard of quality, and, therefore, the aspired option tends to attract Dalits to private schools, they experience the paradoxical situation. On the one hand, they are not happy with the functioning of government schools; on the other, they find it extremely difficult to cope up with the multiple demands of private schools such as higher fees and hidden forms of discrimination on the lines of caste and class.
The Overlap Between Teen Dating Violent Offending and Violent Victimization
Authors: Pusch Natasha , Reisig Michael D.
Published: March 2021

Teen dating violence (TDV) affects both males and females, and the negative consequences associated with such violence last into adulthood. This study had three objectives: (a) determine the extent of overlap in TDV offending and TDV victimization, (b) test whether social ties explain the TDV overlap, and (c) assess whether the effects of social ties on teen dating violence are invariant between sexes. This study used data from the 2018 Arizona Youth Study ( N = 5,189). The findings confirmed that TDV overlap exists. In addition, social ties appeared to partially explain this overlap. Finally, some social ties appeared more general, predicting TDV for both sexes, whereas others were not. For instance, Paternal Attachment was found to reduce the probability of dating violence among female participants only. The findings lend support to prevention programs that aim to strengthen ties between parents and teens.
Motion planning approach for car-like robots in unstructured scenario
Authors: Sun Xuehao , Deng Shuchao , Zhao Tingting , Tong Baohong
Published: March 2021

When a car-like robot travels in an unstructured scenario, real-time motion planning encounters the problem of unstable motion state in obstacle avoidance planning. This paper presents a hybrid motion planning approach based on the timed-elastic-band (TEB) approach and artificial potential field. Different potential fields in an unstructured scenario are established, and the real-time velocity of the car-like robot is planned by using the conversion function of the virtual potential energy of the superimposed potential field and the virtual kinetic energy of the robot. The optimized TEB approach plans the local optimal path and solves the problems related to the local minimum region and non-reachable targets. The safety area of the dynamic obstacle is constructed to realize turning or emergency stop obstacle avoidance, thereby effectively ensuring the safety of the car-like robot in emergency situations. The simulation experiments show that the proposed approach has superior kinematic characteristics and satisfactory obstacle avoidance planning effects and can improve the motion comfort and safety of the car-like robot. In the practical test, the car-like robot moves stably in a dynamic scenario, and the proposed approach satisfies the actual application requirements.
Quantifying the Influence of Individual, Community, and Health System Factors on Quality of Life Among Inner-City African Americans With Type 2 Diabetes
Authors: Campbell Jennifer A. , Yan Alice , Walker Renee E. , Weinhardt Lance , Wang Yang , Walker Rebekah J. , Egede Leonard E.
Published: March 2021

Purpose

The purpose of this study is to examine the association of individual, community, and health system factors on quality of life among inner-city African Americans with type 2 diabetes.

Methods

Primary data from a cross-sectional study with a community sample of 241 inner-city African Americans with type 2 diabetes were analyzed. Paper-based surveys were administered in which the SF-12 was used to capture the physical component (PCS) and mental component (MCS) of quality of life. Four regression approaches (sequential, stepwise with backward and forward selection, and all possible subsets regression) were used to examine the influence of individual, community, and health system factors on PCS and MCS after adjusting for relevant covariates using a conceptual framework.

Results

In fully adjusted models, having less than a high school education and having major depression were associated with lower quality-of-life scores for MCS across all 4 regression approaches. Being employed was positively associated with better quality-of-life scores for PCS across all 4 regression approaches. PCS was higher across all 4 regression approaches for those reporting a history of trauma. At the health systems level, usual source of care was associated with better PCS across 3 regression approaches.

Conclusions

These results highlight key factors that influence quality of life among inner-city African Americans with type 2 diabetes that could be targets for interventions in this population. However, additional research is needed to understand existing pathways that may be driving many of these relationships.
Religion and Attitudes toward Childlessness in the United States
Authors: Uecker Jeremy E. , Bonhag Rebecca , Burtt J. J. , Evans Hannah R. , Hernandez Amanda D.
Published: March 2021

Attitudes toward childlessness have received little attention from social scientists even as childlessness as a family form has become more popular. One key predictor of childlessness attitudes is religious commitment, though few studies have examined this association in-depth. Using data from two recent, national datasets—the National Survey of Family Growth and the Survey of U.S. Catholics and Family Life—we assess the relationships between individuals’ religious characteristics and various attitudes about their own and others’ childlessness, as well as how these factors may vary across gender. We find strong associations between religious affiliation, religious attendance, and religious salience, and each of the outcomes such that religious commitment tends to be associated with more negative attitudes toward childlessness. Interactions across gender were rare and the direction of the interactions was mixed. Religion is a pivotal factor in perpetuating pronatalist attitudes in the United States among both men and women.
Journal of Marketing Education: A Retrospective Overview Between 1979 and 2019
Authors: Donthu Naveen , Kumar Satish , Mills Adam , Pattnaik Debidutta
Published: March 2021

Journal of Marketing Education ( JMED) is an important academic source for the progression of innovative research and experiential wisdom, both of which enhance the knowledge of marketing educators. The primary objective of this study is to provide a retrospection on the emergence and growth of JMED using scientometrics—in simple terms, is the quantification of science. Applying bibliometric methods, the top articles, authors, and topics in JMED titles are identified. A thematic analysis groups JMED articles into 10 semantic clusters: team environment, innovative teaching techniques, students’ evaluation of teaching, qualitative assessment of marketing outlets, technological diffusion in marketing education, experiential learning, marketing values and ethics, self-regulated learning, objective exams, and multiple experiential techniques and student learning. Among these, technological diffusion in marketing education, marketing values and ethics, and multiple experiential techniques and student learning are the most popular and evolving. Apart from informing JMED readers about possible future avenues of the journal, this study may provide valuable information to its editorial board.
Vital aspirations for geography in an era of negativity: Valuing life differently with Deleuze
Authors: Roberts Tom , Dewsbury JD
Published: March 2021

Human geography has seen a vitalist renaissance over the past decade; however, geography’s concerns are mounting in relation to vitalism’s critical efficacy and political relevance. This article pushes back against these concerns. Drawing on the philosophy of Gilles Deleuze, we engage with vitalism as a critical pause and consequently as a vital aspiration in an intellectual climate that is growing increasingly enamoured of negativity as the barometer of serious thinking. In sum, we show how Deleuze’s ‘non-organic vitalism’ promotes a wilder sense of thinking and a more affirmative politics, without acquiescing to the problems of the present.
Advantages of Geophysics to Improve Site Characterization and Reliability for Transportation Projects
Authors: Rahimi Salman , Wood Clinton M. , Kokkali Panagiota (Yota) , Rivers Benjamin
Published: March 2021

Under the Federal Highway Administration’s innovation development program “Every Day Counts” (EDC-5), the initiative on Advanced Geotechnical Methods in Exploration (A-GaME) aims to improve the knowledge in U.S. practice on existing but underutilized subsurface exploration methods. The A-GaME suite of technologies is a group of proven and effective exploration technologies and practices that, in conjunction with limited conventional exploration methods, mitigate the risks of geotechnical uncertainties and optimize subsurface exploration programs for improved site characterization and reliability over a wider coverage area and maximum return-on-investment. Transportation agencies are becoming more eager to employ alternative exploration methods to supplement their investigations and limit uncertainty emanating from geotechnical subsurface conditions. In this context, Arkansas Department of Transportation, in collaboration with the University of Arkansas, has implemented geophysical methods in subsurface investigation to acquire adequate information in relation to bedrock depth and rippability for new construction and to address slope stability issues along roadways. Different geophysical methods have been employed, including multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and microtremor horizontal to vertical spectral ratio (MHVSR). Two case studies are presented here, one for a proposed and one for an existing transportation project. According to the results of these case histories, the joint application of MASW and MHVSR was determined to be valuable for rock rippability estimates for roadway projects, whereas the combined use of MASW, MHVSR, and ERT produced significant additional subsurface information for landslide assessments and remediation efforts.
Effect of Taper on Shear Stiffness of Steel-Reinforced Neoprene Bearing Pads
Authors: Patil Satyajeet R. , Consolazio Gary R. , Hamilton H. R.
Published: March 2021

Steel-reinforced elastomeric bearing pads are widely used in bridge construction to vertically support girders on piers while also accommodating translational and rotational girder deformations caused by live loads and temperature changes. To support sloped girders, flat bearing pads of uniform thicknesses are typically used with either tapered steel shim plates or an inclined concrete bearing seat. The use of tapered pads has the potential to reduce both construction time and cost by eliminating the need for tapered plates or seats to match the girder slope. However, limited research has been performed to investigate the effect of introducing taper on relevant design properties of bearing pads. In this paper, results are presented from experimental testing that was performed to quantify the effect of taper on shear stiffnesses of pads having varied geometric characteristics (plan view dimensions, elastomer thicknesses, and slope angles). An experimental bearing pad test device was designed and utilized to impose shear loads in accordance with ASTM standards, while simultaneously maintaining a constant axial load. Bearing pads chosen for testing were tapered variations of standard flat bridge bearing pads used in the state of Florida, U.S. Results obtained from the study revealed that shear stiffness was not significantly influenced by the introduction of taper angle, the direction of shear along the length of pads, or axial load level. The shear stiffness of tapered pads remained within approximately 10% of the shear stiffness of corresponding flat pads.