193 results match your criteria: "H. Milton Stewart School of Industrial and Systems Engineering[Affiliation]"

Managing Forests for Biodiversity Conservation and Climate Change Mitigation.

Environ Sci Technol

May 2024

H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.

We include biodiversity impacts in forest management decision making by incorporating the countryside species area relationship model into the partial equilibrium model GLOBIOM-Forest. We tested three forest management intensities (low, medium, and high) and limited biodiversity loss via an additional constraint on regional species loss. We analyzed two scenarios for climate change mitigation.

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Background: Optimal pharmacologic thromboprophylaxis dosing is not well described in patients with subarachnoid hemorrhage (SAH) with an external ventricular drain (EVD). Our patients with SAH with an EVD who receive prophylactic enoxaparin are routinely monitored using timed anti-Xa levels. Our primary study goal was to determine the frequency of venous thromboembolism (VTE) and secondary intracranial hemorrhage (ICH) for this population of patients who received pharmacologic prophylaxis with enoxaparin or unfractionated heparin (UFH).

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Background: Despite the successes of the Global Polio Eradication Initiative, substantial challenges remain in eradicating the poliovirus. The Sabin-strain (live-attenuated) virus in oral poliovirus vaccine (OPV) can revert to circulating vaccine-derived poliovirus (cVDPV) in under-vaccinated communities, regain neurovirulence and transmissibility, and cause paralysis outbreaks. Since the cessation of type 2-containing OPV (OPV2) in 2016, there have been cVDPV type 2 (cVDPV2) outbreaks in four out of six geographical World Health Organization regions, making these outbreaks a significant public health threat.

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Opioids are vital to pain management and sedation after trauma-related hospitalization. However, there are many confounding clinical, social, and environmental factors that exacerbate pain, post-injury care needs, and receipt of opioid prescriptions following orthopaedic trauma. This retrospective study sought to characterize differences in opioid prescribing and dosing in a national Medicaid eligible sample from 2010-2018.

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Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient.

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Chad has seen a considerable reduction in cases of Guinea worm disease (or dracunculiasis) in domestic dogs in recent years. Tethering of dogs and application of Abate® larvicide to water sources appear to have contributed to this progress, but with 767 reported dog cases in 2021, accelerating elimination of the disease in Chad may require additional tools. We investigate the potential benefits of a hypothetical diagnostic test that could be capable of detecting prepatent infections in dogs.

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Article Synopsis
  • Glioblastoma (GBM) is a highly aggressive cancer characterized by genetic variability within tumors, making it difficult to treat effectively; this study aimed to develop a non-invasive MRI-based machine learning model to analyze this genetic heterogeneity.
  • The research introduced a Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) model, trained on data from 74 patients, to predict alterations in key GBM genes using MRI images, achieving higher accuracy than existing algorithms.
  • Results showed the WSO-SVM model to be effective, with accuracies of 80% for the EGFR gene and comparable results for others; the analysis also highlighted different contributions of MRI images, providing valuable insights into tumor genetics for better treatment planning
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Machine-Guided Discovery of Acrylate Photopolymer Compositions.

ACS Appl Mater Interfaces

April 2024

School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.

Additive manufacturing (AM) can be advanced by the diverse characteristics offered by thermoplastic and thermoset polymers and the further benefits of copolymerization. However, the availability of suitable polymeric materials for AM is limited and may not always be ideal for specific applications. Additionally, the extensive number of potential monomers and their combinations make experimental determination of resin compositions extremely time-consuming and costly.

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Traffic congestion results from the spatio-temporal imbalance of demand and supply. With the advances in connected technologies, incentive mechanisms for collaborative routing have the potential to provide behavior-consistent solutions to traffic congestion. However, such mechanisms raise privacy concerns due to their information-sharing and execution-validation procedures.

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Revealing the biology behind MRI signatures in high grade glioma.

medRxiv

December 2023

School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85287, USA.

Article Synopsis
  • MRI is commonly used in high-grade glioma treatments to map tumor boundaries and assist in surgery, revealing important tumor biology through its measurements.
  • The study found that specific MRI techniques (like T1+C) not only visualize the tumor's blood flow disruption but also indicate immune cell infiltration, enhancing our understanding of how these factors interact within the tumor environment.
  • The research offers a new, unbiased methodology for linking MRI results with tumor biology, laying the groundwork for future advancements in noninvasive diagnostics and treatment strategies for patients with high-grade gliomas.
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Tankyrases, a versatile protein group within the poly(ADP-ribose) polymerase family, are essential for post-translational poly(ADP-ribosyl)ation, influencing various cellular functions and contributing to diseases, particularly cancer. Consequently, tankyrases have become important targets for anti-cancer drug development. Emerging approaches in drug discovery aim to disrupt interactions between tankyrases and their binding partners, which hinge on tankyrase-binding motifs (TBMs) within partner proteins and ankyrin repeat cluster domains within tankyrases.

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Background: Setting prices for life-saving medical or pharmaceutical products needs to consider multiple factors, e.g., affordability and health outcomes across different populations.

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Objective: To determine the variation of outpatient opioid prescribing across the US in postoperative pediatric cardiac patients.

Study Design: Retrospective, cross-sectional study using a concatenated database of Medicaid claims between from 2016 through 2018 of children 0-17 years, discharged after cardiac surgery and receiving an opioid prescription within 30 days. Filled prescriptions were identified and converted to morphine milligram equivalents (MME).

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Nanopore long-read RNA sequencing reveals functional alternative splicing variants in human vascular smooth muscle cells.

Commun Biol

October 2023

Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Vascular smooth muscle cells (VSMCs) are the major contributor to vascular repair and remodeling, which showed high level of phenotypic plasticity. Abnormalities in VSMC plasticity can lead to multiple cardiovascular diseases, wherein alternative splicing plays important roles. However, alternative splicing variants in VSMC plasticity are not fully understood.

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Self-Supervised Contrastive Learning to Predict the Progression of Alzheimer's Disease with 3D Amyloid-PET.

Bioengineering (Basel)

September 2023

H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Early diagnosis of Alzheimer's disease (AD) is an important task that facilitates the development of treatment and prevention strategies, and may potentially improve patient outcomes. Neuroimaging has shown great promise, including the amyloid-PET, which measures the accumulation of amyloid plaques in the brain-a hallmark of AD. It is desirable to train end-to-end deep learning models to predict the progression of AD for individuals at early stages based on 3D amyloid-PET.

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Purpose: This study sought to examine grouped and right-censored (GRC) counts of adolescent marijuana use and estimate its temporal trajectories and sociodemographic disparities over almost half a century.

Methods: After compiling 46 waves of nationally representative data from the Monitoring the Future (MTF) study from 1976 to 2021 (sample size = 491,348), we utilized an innovative modified Poisson (mixture) approach to analyze past-year marijuana use quantified by GRC counts.

Results: The overall reduction in incidence rates of marijuana use was attributable to an almost 40% reduction in the risk of marijuana use (with the proportion of at-risk adolescents at 51.

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Objective: Senegal has demonstrated catalytic improvements in national coverage rates for early childhood vaccination, despite lower development assistance for childhood vaccines in Senegal compared with other low-income and lower-middle income countries. Understanding factors associated with historical changes in childhood vaccine coverage in Senegal, as well as heterogeneities across its 14 regions, can highlight effective practices that might be adapted to improve vaccine coverage elsewhere.

Design: Childhood vaccination coverage rates, demographic information and health system characteristics were identified from Senegal's Demographic and Health Surveys (DHS) and Senegal national reports for years 2005-2019.

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Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution.

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A simulation-based comparison of centralized and point-of-care supply chain strategies for autologous cell therapy.

Cytotherapy

December 2023

Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Background Aims: The selection between centralized and point-of-care (POC) manufacturing supply-chain network design is a crucial consideration in the autologous cell therapy (AuCT) industry, as each approach offers its advantages and disadvantages.

Methods: This study uses a simulation-based approach to compare and examine the two strategies using the supply chain for chimeric antigen receptor T-cell therapy manufacturing as an exemplar. When does it make sense to use one manufacturing strategy over another? Currently, major manufacturers in the AuCT industry use centralized supply-chain strategies predominantly in practice.

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Real-time semantic segmentation and anomaly detection of functional images for cell therapy manufacturing.

Cytotherapy

December 2023

H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA. Electronic address:

Background Aims: Cell therapy is a promising treatment method that uses living cells to address a variety of diseases and conditions, including cardiovascular diseases, neurologic disorders and certain cancers. As interest in cell therapy grows, there is a need to shift to a more efficient, scalable and automated manufacturing process that can produce high-quality products at a lower cost.

Methods: One way to achieve this is using non-invasive imaging and real-time image analysis techniques to monitor and control the manufacturing process.

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Article Synopsis
  • Early detection of Alzheimer's Disease is vital yet challenging due to incomplete patient imaging data, which is often caused by factors like cost and access to technology.
  • The proposed deep learning framework uses Mutual Knowledge Distillation (MKD) to effectively model different patient sub-groups based on available imaging modalities, allowing for better diagnosis.
  • The framework's effectiveness is demonstrated through simulations and a case study using Alzheimer's Disease Neuroimaging Initiative (ADNI) datasets, showcasing its potential to enhance early diagnosis despite data limitations.*
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Split or whole liver transplantation? Utilization and posttransplant survival.

Hepatol Commun

September 2023

H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.

Background: Split liver transplantation (SLT), where a single donor liver is divided for transplantation to 2 recipients, has the potential to increase the availability of size-matched livers for pediatric candidates and expand the supply of donor organs available for adult candidates. Although SLT is a well-established technique, the number of SLTs has remained flat during the past 2 decades, partly due to concerns about the posttransplant survival of SLT recipients compared with whole liver transplantation (WLT) recipients. Prior work on SLT versus WLT survival analysis had limitations because, for pediatric recipients, it did not consider the correlations between donor age/weight and the allograft type, and for adult recipients, it may have included records where the donor livers did not meet the split liver criteria (splittable).

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Asymptotic Optimality Theory for Active Quickest Detection with Unknown PostChange Parameters.

Seq Anal

May 2023

H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.

The active quickest detection problem with unknown post-change parameters is studied under the sampling control constraint, where there are local streams in a system but one is only able to take observations from one and only one of these local streams at each time instant. The objective is to raise a correct alarm as quickly as possible once the change occurs subject to both false alarm and sampling control constraints. Here we assume that exactly one of the local streams is affected, and the post-change distribution involves unknown parameters.

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Background: A key component of return-to-play (RTP) from sport-related concussion is the symptom-free waiting period (SFWP), i.e., the period during which athletes must remain symptom-free before permitting RTP.

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