Showing papers by "University of Utah published in 2022"

Why and how does early adversity influence development? Toward an integrated model of dimensions of environmental experience

Abstract: Abstract Two extant frameworks – the harshness-unpredictability model and the threat-deprivation model – attempt to explain which dimensions of adversity have distinct influences on development. These models address, respectively, why, based on a history of natural selection, development operates the way it does across a range of environmental contexts, and how the neural mechanisms that underlie plasticity and learning in response to environmental experiences influence brain development. Building on these frameworks, we advance an integrated model of dimensions of environmental experience, focusing on threat-based forms of harshness, deprivation-based forms of harshness, and environmental unpredictability. This integrated model makes clear that the why and the how of development are inextricable and, together, essential to understanding which dimensions of the environment matter. Core integrative concepts include the directedness of learning, multiple levels of developmental adaptation to the environment, and tradeoffs between adaptive and maladaptive developmental responses to adversity. The integrated model proposes that proximal and distal cues to threat-based and deprivation-based forms of harshness, as well as unpredictability in those cues, calibrate development to both immediate rearing environments and broader ecological contexts, current and future. We highlight actionable directions for research needed to investigate the integrated model and advance understanding of dimensions of environmental experience.

Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System

Abstract: Taskflow aims to streamline the building of parallel and heterogeneous applications using a lightweight task graph-based approach. Taskflow introduces an expressive task graph programming model to assist developers in the implementation of parallel and heterogeneous decomposition strategies on a heterogeneous computing platform. Our programming model distinguishes itself as a very general class of task graph parallelism with in-graph control flow to enable end-to-end parallel optimization. To support our model with high performance, we design an efficient system runtime that solves many of the new scheduling challenges arising out of our models and optimizes the performance across latency, energy efficiency, and throughput. We have demonstrated the promising performance of Taskflow in real-world applications. As an example, Taskflow solves a large-scale machine learning workload up to 29% faster, 1.5× less memory, and 1.9× higher throughput than the industrial system, oneTBB, on a machine of 40 CPUs and 4 GPUs. We have opened the source of Taskflow and deployed it to large numbers of users in the open-source community.

Revisiting the HIF switch in the tumor and its immune microenvironment

Abstract: Hypoxia-inducible factor (HIF)-1α and HIF-2α play nonoverlapping, complementary roles in solid tumors by promoting changes in metabolism, enhancing angiogenesis, and inducing a more aggressive phenotype. The HIFs also modulate gene expression profiles of the non-malignant immune cell types within the tumor microenvironment (TME), sculpting a tumor-permissive niche that facilitates tumor progression and drives resistance to therapy. HIF inhibition may impact tumor progression by directly blocking its tumor-promoting function in tumor cells and by modulating the tumor-enabling function of the immune TME, with potential for improving responses to immune checkpoint blockade (ICB). Selective HIF-2α inhibition provides clinical benefit for the treatment of clear cell renal cell carcinoma (ccRCC) and is currently being evaluated in other solid tumor types. Due to their complementarity, the direct targeting of both HIF-1α and HIF-2α may provide additional benefit over that of targeting each isoform alone. Hypoxia is a hallmark of all solid tumors and their metastases. This leads to activation of the hypoxia-inducible factor (HIF) family of transcription factors, which modulate gene expression within both tumor cells and immune cells within the tumor microenvironment, influencing tumor progression and treatment response. The best characterized HIF isoforms, HIF-1α and HIF-2α, show nonoverlapping and often antagonistic roles. With the recent availability of inhibitors that target one or both HIFs, including the first-in-class selective HIF-2α inhibitor belzutifan, the prospect of HIF-α isoform-selective targeting is now a reality. Here, we summarize current knowledge on the unique contributions of the two HIF-α isoforms to tumor progression in the context of the complex tumor immune microenvironment, highlighting important considerations for therapy. Hypoxia is a hallmark of all solid tumors and their metastases. This leads to activation of the hypoxia-inducible factor (HIF) family of transcription factors, which modulate gene expression within both tumor cells and immune cells within the tumor microenvironment, influencing tumor progression and treatment response. The best characterized HIF isoforms, HIF-1α and HIF-2α, show nonoverlapping and often antagonistic roles. With the recent availability of inhibitors that target one or both HIFs, including the first-in-class selective HIF-2α inhibitor belzutifan, the prospect of HIF-α isoform-selective targeting is now a reality. Here, we summarize current knowledge on the unique contributions of the two HIF-α isoforms to tumor progression in the context of the complex tumor immune microenvironment, highlighting important considerations for therapy. (a disintegrin and metalloproteinase domain–containing protein 10 ) a cell surface protein that cleaves membrane proteins. cancer-associated fibroblasts are a fibroblast-related cell type found in the tumor microenvironment. clear cell renal cell carcinoma is the most common type of kidney cancer. binds to HIF to enhance transcription activation. a protein that downregulates immune responses. an enzyme that hydrolyzes 5′-triphosphates. cells that make up blood vessels. an asparaginyl hydroxylase that regulates HIF. primary liver cancer. enzymes that remove acetyl groups from histone proteins. transcription factors activated by hypoxia. a core sequence of 5′-RCGTG-3′ bound by HIF. half-maximal inhibitory concentration is the amount of a drug needed to inhibit a biological process by half. a type of immunotherapy that blocks immune checkpoints in cytotoxic T cells, resulting in reactivation of T cells. a protein that acts as a ‘kill me’ signal. a sensor of cell stress expressed on NK cells. the percentage of people within a study who are still alive after a specified time. a cancer model where tissue or cancer cells are taken from a patient and implanted into a mouse. a protein found on the surface of immune cells that modulates T cell activity. the cell surface ligand that binds PD-1. the length of time that a person lives with a disease that does not get worse. enzymes that hydroxylate HIF. a transcriptomic methodology that examines gene expression in single cells. macrophages that are found within the tumor microenvironment. the environment around a tumor including non-neoplastic cells. a drug that inhibits tyrosine kinases. a protein that ubiquitinates hydroxylated HIF-α.

Do sex and gender modify the association between green space and physical health? A systematic review

Abstract: A growing literature shows that green space can have protective effects on human health. As a marginalized group, women often have worse life outcomes than men, including disparities in some health outcomes. Given their marginalization, women might have "more to gain" than men from living near green spaces. Yet, limited research has deliberately studied whether green space-health associations are stronger for women or men. We conducted a systematic review to synthesize empirical evidence on whether sex or gender modifies the protective associations between green space and seven physical health outcomes (cardiovascular disease, cancer, diabetes, general physical health, non-malignant respiratory disease, mortality, and obesity-related health outcomes). After searching five databases, we identified 62 articles (including 81 relevant analyses) examining whether such effect modification existed. We classified analyses based on whether green space-health were stronger for women, no sex/gender differences were detected, or such associations were stronger for men. Most analyses found that green space-physical health associations were stronger for women than for men when considering study results across all selected health outcomes. Also, women showed stronger protective associations with green space than men for obesity-related outcomes and mortality. Additionally, the protective green space-health associations were slightly stronger among women for green land cover (greenness, NDVI) than for public green space (parks), and women were also favored over men when green space was measured very close to one's home (0-500 m). Further, the green space-health associations were stronger for women than for men in Europe and North America, but not in other continents. As many government agencies and nongovernmental organizations worldwide work to advance gender equity, our review shows that green space could help reduce some gender-based health disparities. More robust empirical studies (e.g., experimental) are needed to contribute to this body of evidence.

Hybrid gene selection approach using XGBoost and multi-objective genetic algorithm for cancer classification

Abstract: Microarray gene expression data are often accompanied by a large number of genes and a small number of samples. However, only a few of these genes are relevant to cancer, resulting in significant gene selection challenges. Hence, we propose a two-stage gene selection approach by combining extreme gradient boosting (XGBoost) and a multi-objective optimization genetic algorithm (XGBoost-MOGA) for cancer classification in microarray datasets. In the first stage, the genes are ranked using an ensemble-based feature selection using XGBoost. This stage can effectively remove irrelevant genes and yield a group comprising the most relevant genes related to the class. In the second stage, XGBoost-MOGA searches for an optimal gene subset based on the most relevant genes' group using a multi-objective optimization genetic algorithm. We performed comprehensive experiments to compare XGBoost-MOGA with other state-of-the-art feature selection methods using two well-known learning classifiers on 14 publicly available microarray expression datasets. The experimental results show that XGBoost-MOGA yields significantly better results than previous state-of-the-art algorithms in terms of various evaluation criteria, such as accuracy, F-score, precision, and recall.

Multipartite Genome of Lyme Disease Borrelia: Structure, Variation and Prophages

Abstract: All members of the Borrelia genus that have been examined harbour a linear chromosome that is about 900 kbp in length, as well as a plethora of both linear and circular plasmids in the 5-220 kbp size range. Genome sequences for 27 Lyme disease Borrelia isolates have been determined since the elucidation of the B. burgdorferi B31 genome sequence in 1997. The chromosomes, which carry the vast majority of the housekeeping genes, appear to be very constant in gene content and organization across all Lyme disease Borrelia species. The content of the plasmids, which carry most of the genes that encode the differentially expressed surface proteins that interact with the spirochete's arthropod and vertebrate hosts, is much more variable. Lyme disease Borrelia isolates carry between 7-21 different plasmids, ranging in size from 5-84 kbp. All strains analyzed to date harbor three plasmids, cp26, lp54 and lp17. The plasmids are unusual, as compared to most bacterial plasmids, in that they contain many paralogous sequences, a large number of pseudogenes, and, in some cases, essential genes. In addition, a number of the plasmids have features indicating that they are prophages. Numerous methods have been developed for Lyme disease Borrelia strain typing. These have proven valuable for clinical and epidemiological studies, as well as phylogenomic and population genetic analyses. Increasingly, these approaches have been displaced by whole genome sequencing techniques. Some correlations between genome content and pathogenicity have been deduced, and comparative whole genome analyses promise future progress in this arena.

NexRAN: Closed-loop RAN slicing in POWDER -A top-to-bottom open-source open-RAN use case

Abstract: Much like earlier "network softwarization" efforts, the Open RAN concept is poised to have a transformative impact on the manner in which radio access networks (RANs) are realized and operated. The inherent complexity of the RAN ecosystem and the fact that it is rapidly evolving makes Open RAN a rich area of research into use cases, system realization, security, and more. This same complexity, however, hampers research efforts. Specifically, there is a lack of end-to-end open source software and fully-developed use cases associated with the Open RAN ecosystem. Further, to truly advance the state of the art will require use cases to be explored in realistic wireless environments. This paper describes our efforts to address these shortcomings by realizing NexRAN, a top-to-bottom, open-source Open RAN use case in the POWDER mobile and wireless research platform. Specifically, NexRAN allows closed-loop control of a RAN slicing realization in an O-RAN ecosystem. RAN slicing is implemented in the srsRAN open source mobility stack and is exposed through a custom service model to the NexRAN xApp, which executes on a RAN intelligent controller (RIC) from the O-RAN Alliance. The NexRAN xApp realizes policy driven closed-loop control of RAN slices by reading the current state of RAN elements (using the O-RAN key performance measurements (KPM) service model) and controlling slice behavior via the custom slicing service model. We demonstrate and evaluate NexRAN in the POWDER platform and have open sourced all aspects of our realization to enable research into this domain.

Status Report on the Third Round of the NIST Post-Quantum Cryptography Standardization Process

Abstract: The National Institute of Standards and Technology is in the process of selecting public-key cryptographic algorithms through a public, competition-like process. The new public-key cryptography standards will specify additional digital signature, public-key encryption, and key-establishment algorithms to augment Federal Information Processing Standard (FIPS) 186-4, Digital Signature Standard (DSS), as well as NIST Special Publication (SP) 800-56A Revision 3, Recommendation for Pair-Wise Key-Establishment Schemes Using Discrete Logarithm Cryptography, and SP 800-56B Revision 2, Recommendation for Pair-Wise Key Establishment Using Integer Factorization Cryptography. It is intended that these algorithms will be capable of protecting sensitive information well into the foreseeable future, including after the advent of quantum computers. The first round of the NIST Post-Quantum Cryptography Standardization Process began in December 2017 with 69 candidate algorithms that met both the minimum acceptance criteria and submission requirements. The first round lasted until January 2019, during which candidate algorithms were evaluated based on their security, performance, and other characteristics. NIST selected 26 algorithms to advance to the second round for more analysis. The second round continued until July 2020, after which seven 'finalist' and eight 'alternate' candidate algorithms were selected to move into the third round. This report describes the evaluation and selection process, based on public feedback and internal review, of the third-round candidates. The report summarizes each of the 15 third-round candidate algorithms and identifies those selected for standardization, as well as those that will continue to be evaluated in a fourth round of analysis. The public-key encryption and key-establishment algorithm that will be standardized is CRYSTALS-Kyber. The digital signatures that will be standardized are CRYSTALS-Dilithium, Falcon, and SPHINCS+. While there are multiple signature algorithms selected, NIST recommends CRYSTALS-Dilithium as the primary algorithm to be implemented. In addition, four of the alternate key-establishment candidate algorithms will advance to a fourth round of evaluation: BIKE, Classic McEliece, HQC, and SIKE. These candidates are still being considered for future standardization. NIST will also issue a new Call for Proposals for public-key digital signature algorithms to augment and diversify its signature portfolio.

BridgeDPI: a novel Graph Neural Network for predicting drug–protein interactions

Abstract: Exploring drug-protein interactions (DPIs) provides a rapid and precise approach to assist in laboratory experiments for discovering new drugs. Network-based methods usually utilize a drug-protein association network and predict DPIs by the information of its associated proteins or drugs, called 'guilt-by-association' principle. However, the 'guilt-by-association' principle is not always true because sometimes similar proteins cannot interact with similar drugs. Recently, learning-based methods learn molecule properties underlying DPIs by utilizing existing databases of characterized interactions but neglect the network-level information.We propose a novel method, namely BridgeDPI. We devise a class of virtual nodes to bridge the gap between drugs and proteins and construct a learnable drug-protein association network. The network is optimized based on the supervised signals from the downstream task-the DPI prediction. Through information passing on this drug-protein association network, a Graph Neural Network can capture the network-level information among diverse drugs and proteins. By combining the network-level information and the learning-based method, BridgeDPI achieves significant improvement in three real-world DPI datasets. Moreover, the case study further verifies the effectiveness and reliability of BridgeDPI.The source code of BridgeDPI can be accessed at https://github.com/SenseTime-Knowledge-Mining/BridgeDPI. The source data used in this study is available on the https://github.com/IBM/InterpretableDTIP (for the BindingDB dataset), https://github.com/masashitsubaki/CPI_prediction (for the C.ELEGANS and HUMAN) datasets, http://dude.docking.org/ (for the DUD-E dataset), repectively.

Stellar solutions with zero complexity obtained through a temporal metric deformation

Abstract: Abstract Two new static and spherically symmetric interior solutions in the regime isotropic and anisotropic fluid pressure with vanishing complexity are constructed. For the construction of these interior solutions the framework of Gravitational Decoupling considering an unusual way through the choose a temporal metric deformation is used. We use the Einstein’s universe solution and an ansatz as seed solutions. The solutions fulfill the fundamental physical acceptability conditions for a restricted set of compactness parameters.

Optimal Management of Asymptomatic Carotid Stenosis in 2021: The Jury is Still Out. An International, Multispecialty, Expert Review and Position Statement

Abstract: Objectives The recommendations of international guidelines for the management of asymptomatic carotid stenosis (ACS) often vary considerably and extend from a conservative approach with risk factor modification and best medical treatment (BMT) alone, to a more aggressive approach with a carotid intervention plus BMT. The aim of the current multispecialty position statement is to reconcile the conflicting views on the topic. Materials and methods A literature review was performed with a focus on data from recent studies. Results Several clinical and imaging high-risk features have been identified that are associated with an increased long-term ipsilateral ischemic stroke risk in patients with ACS. Such high-risk clinical/imaging features include intraplaque hemorrhage, impaired cerebrovascular reserve, carotid plaque echolucency/ulceration/ neovascularization, a lipid-rich necrotic core, a thin or ruptured fibrous cap, silent brain infarction, a contralateral transient ischemic attack/stroke episode, male patients Conclusions Although aggressive risk factor control and BMT should be implemented in all ACS patients, several high-risk features that may increase the risk of a future cerebrovascular event are now documented. Consequently, some guidelines recommend a prophylactic carotid intervention in high-risk patients to prevent future cerebrovascular events. Until the results of the much-anticipated randomized controlled trials emerge, the jury is still out regarding the optimal management of ACS patients.