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  1. Article: Biodefense: Expanding Nursing Strategies After the SARS-CoV-2 Threat.

    Wangi, Karolus / Smith, Colin

    Journal of radiology nursing

    2023  

    Abstract: The COVID-19 pandemic has impacted the nursing profession and its existence in terms of preventing infection from spreading at the levels of patient care and management. Vigilance is essential in combating potential re-emerging diseases in the future. ... ...

    Abstract The COVID-19 pandemic has impacted the nursing profession and its existence in terms of preventing infection from spreading at the levels of patient care and management. Vigilance is essential in combating potential re-emerging diseases in the future. Hence, exploring a new framework, biodefense, is the best way to reframe nursing preparedness for new biological threats or new pandemics at any level of nursing care.
    Language English
    Publishing date 2023-04-04
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2198723-3
    ISSN 1555-9912 ; 1546-0843
    ISSN (online) 1555-9912
    ISSN 1546-0843
    DOI 10.1016/j.jradnu.2023.03.008
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Perspective: A resident's role in promoting safe machine-learning tools in sleep medicine.

    Smith, Colin M / Vendrame, Martina

    Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine

    2023  Volume 19, Issue 11, Page(s) 1985–1987

    Abstract: Residents and fellows can play a helpful role in promoting safe and effective machine-learning tools in sleep medicine. Here we highlight the importance of establishing ground truths, considering key variables, and prioritizing transparency and ... ...

    Abstract Residents and fellows can play a helpful role in promoting safe and effective machine-learning tools in sleep medicine. Here we highlight the importance of establishing ground truths, considering key variables, and prioritizing transparency and accountability in the development of machine-learning tools within the field of artificial intelligence. Through understanding, communication, and collaboration, in-training physicians have a meaningful opportunity to help progress the field toward safe machine-learning tools in sleep medicine.
    Citation: Smith CM, Vendrame M. Perspective: a resident's role in promoting safe machine-learning tools in sleep medicine.
    MeSH term(s) Humans ; Artificial Intelligence ; Machine Learning ; Physicians ; Internship and Residency ; Sleep
    Language English
    Publishing date 2023-07-24
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2397213-0
    ISSN 1550-9397 ; 1550-9389
    ISSN (online) 1550-9397
    ISSN 1550-9389
    DOI 10.5664/jcsm.10724
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6590: Show issues Location:
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  3. Article: Transit communication via Twitter during the COVID-19 pandemic.

    Zhang, Wenwen / Barchers, Camille / Smith-Colin, Janille

    Environment and planning. B, urban analytics and city science

    2022  Volume 50, Issue 5, Page(s) 1244–1261

    Abstract: Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especially during times of disruption and disaster. This work examines how transit agencies used Twitter during ... ...

    Abstract Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especially during times of disruption and disaster. This work examines how transit agencies used Twitter during the COVID-19 pandemic to communicate with riders and how the content and general activity influence rider interaction and Twitter handle popularity. We analyzed 654,345 tweets generated by the top 40 transit agencies in the US, based on Vehicles Operated in Annual Maximum Service (VOM), from January 2020 to August 2021. We developed an analysis framework, using advanced machine learning and natural language processing models, to understand how agencies' tweeting patterns are associated with rider interaction outcomes during the pandemic. From the transit agency perspective, we find smaller agencies tend to generate a higher percentage of COVID-related tweets and some agencies are more repetitive than their peers. Six topics (i.e., face covering, essential service appreciation, free resources, social distancing, cleaning, and service updates) were identified in the COVID-related tweets. From the followers' interaction perspective, most agencies gained followers after the start of the pandemic (i.e., March 2020). The percentage of follower gains is positively correlated with the percentage of COVID-related tweets, tweets replying to followers, and tweets using outlinks. The average like counts per COVID-related tweet is positively correlated with the percentage of COVID-related tweets and negatively correlated with the percentage of tweets discussing social distancing and agency repetitiveness. This work can inform transportation planners and transit agencies on how to use Twitter to effectively communicate with riders to improve public perception of health and safety as it relates to transit ridership during delays and long-term disruptions such as those created by the COVID-19 public health crisis.
    Language English
    Publishing date 2022-11-10
    Publishing country United States
    Document type Journal Article
    ISSN 2399-8083
    ISSN 2399-8083
    DOI 10.1177/23998083221135609
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  4. Article: Clinical Predictors of Postmortem Amyloid and Nonamyloid Cerebral Small Vessel Disease in Middle-Aged to Older Adults.

    Dallaire-Théroux, Caroline / Smith, Colin / Duchesne, Simon

    Neurology. Clinical practice

    2024  Volume 14, Issue 3, Page(s) e200271

    Abstract: Background and objectives: Sporadic cerebral small vessel disease (CSVD) is a class of important pathologic processes known to affect the aging brain and to contribute to cognitive impairment. We aimed to identify clinical risk factors associated with ... ...

    Abstract Background and objectives: Sporadic cerebral small vessel disease (CSVD) is a class of important pathologic processes known to affect the aging brain and to contribute to cognitive impairment. We aimed to identify clinical risk factors associated with postmortem CSVD in middle-aged to older adults.
    Methods: We developed and tested risk models for their predictive accuracy of a pathologic diagnosis of nonamyloid CSVD and cerebral amyloid angiopathy (CAA) in a retrospective sample of 160 autopsied cases from the Edinburgh Brain Bank. Individuals aged 40 years and older covering the spectrum of healthy aging and common forms of dementia (i.e., highly-prevalent etiologies such as Alzheimer disease (AD), vascular cognitive impairment (VCI), and mixed dementia) were included. We performed binomial logistic regression models using sample splitting and cross-validation methods. Demographics, lifestyle habits, traditional vascular risk factors, chronic medical conditions,
    Results: Forty percent of our sample had a clinical diagnosis of dementia (AD = 33, VCI = 26 and mixed = 5) while others were cognitively healthy (n = 96). The mean age at death was 73.8 (SD 14.1) years, and 40% were female. The presence of none-to-mild vs moderate-to-severe nonamyloid CSVD was predicted by our model with good accuracy (area under the curve [AUC] = 0.84, sensitivity [SEN] = 72%, specificity [SPE] = 95%), with the most significant clinical predictors being age, history of cerebrovascular events, and cognitive impairment. The presence of CAA pathology was also predicted with high accuracy (AUC = 0.86, SEN = 93%, SPE = 79%). Significant predictors included alcohol intake, history of cerebrovascular events, and cognitive impairment. In a subset of atypical dementias (n = 24), our models provided poor predictive performance for both nonamyloid CSVD (AUC = 0.50) and CAA (AUC = 0.43).
    Discussion: CSVD pathology can be predicted with high accuracy based on clinical factors in patients within the spectrum of AD, VCI, and normal aging. Whether this prediction can be enhanced by the addition of fluid and neuroimaging biomarkers warrants additional study. Improving our understanding of clinical determinants of vascular brain health may lead to novel strategies in the prevention and treatment of vascular etiologies contributing to cognitive decline.
    Classification of evidence: This study provides Class II evidence that selected clinical factors accurately distinguish between middle-aged to older adults with and without cerebrovascular small vessel disease (amyloid and nonamyloid) pathology.
    Language English
    Publishing date 2024-03-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2645818-4
    ISSN 2163-0933 ; 2163-0402
    ISSN (online) 2163-0933
    ISSN 2163-0402
    DOI 10.1212/CPJ.0000000000200271
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  5. Article: Mental Health Support of Frontline Medical Personnel in the Javits New York Medical Station Federal COVID-19 Treatment Center.

    Kaplan, Alexander / Smith, Colin M

    Federal practitioner : for the health care professionals of the VA, DoD, and PHS

    2022  Volume 39, Issue 5, Page(s) 202–206

    Abstract: Background: The federal government responded to the early epicenter of the COVID-19 pandemic in the United States by mobilizing uniformed services and other federal medical personnel to treat patients at the Javits New York Medical Station. Deployment ... ...

    Abstract Background: The federal government responded to the early epicenter of the COVID-19 pandemic in the United States by mobilizing uniformed services and other federal medical personnel to treat patients at the Javits New York Medical Station. Deployment of large numbers of personnel required flexible psychiatric and psychological support.
    Observations: This report details the establishment of mental health support services for frontline personnel in a large convention center and explores lessons learned to encourage future mental health professionals to apply creative and assertive mental health interventions in disaster settings.
    Conclusions: Timely and effective interventions included securing safe therapeutic space in high-traffic areas, developing relationships with leadership and frontline workers in their own work environments, and disseminating services throughout the civilian medical system. We suggest mental health supplementation during the medical response mission strengthened morale in frontline workers in a disaster scenario.
    Language English
    Publishing date 2022-05-13
    Publishing country United States
    Document type Journal Article
    ISSN 1078-4497
    ISSN 1078-4497
    DOI 10.12788/fp.0261
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  6. Article ; Online: Psychosocial burden in transfusion dependent

    Wangi, Karolus / Birriel, Barbara / Smith, Colin

    Journal of Taibah University Medical Sciences

    2023  Volume 18, Issue 6, Page(s) 1217–1219

    Abstract: Beta-thalassemia ... ...

    Abstract Beta-thalassemia major
    Language English
    Publishing date 2023-05-10
    Publishing country Saudi Arabia
    Document type Journal Article
    ZDB-ID 2817396-X
    ISSN 1658-3612 ; 1658-3612
    ISSN (online) 1658-3612
    ISSN 1658-3612
    DOI 10.1016/j.jtumed.2023.05.002
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  7. Article ; Online: An overview of clinical machine learning applications in neurology.

    Smith, Colin M / Weathers, Allison L / Lewis, Steven L

    Journal of the neurological sciences

    2023  Volume 455, Page(s) 122799

    Abstract: Machine learning techniques for clinical applications are evolving, and the potential impact this will have on clinical neurology is important to recognize. By providing a broad overview on this growing paradigm of clinical tools, this article aims to ... ...

    Abstract Machine learning techniques for clinical applications are evolving, and the potential impact this will have on clinical neurology is important to recognize. By providing a broad overview on this growing paradigm of clinical tools, this article aims to help healthcare professionals in neurology prepare to navigate both the opportunities and challenges brought on through continued advancements in machine learning. This narrative review first elaborates on how machine learning models are organized and implemented. Machine learning tools are then classified by clinical application, with examples of uses within neurology described in more detail. Finally, this article addresses limitations and considerations regarding clinical machine learning applications in neurology.
    MeSH term(s) Humans ; Health Personnel ; Machine Learning ; Neurology
    Language English
    Publishing date 2023-11-14
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 80160-4
    ISSN 1878-5883 ; 0022-510X ; 0374-8642
    ISSN (online) 1878-5883
    ISSN 0022-510X ; 0374-8642
    DOI 10.1016/j.jns.2023.122799
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 308: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article: Part II: Missouri's Fentanyl Poisonings Rise to Record Levels.

    Stoecker, William V / Smith, Colin L / Connors, Elizabeth

    Missouri medicine

    2023  Volume 120, Issue 1, Page(s) 10–14

    Abstract: Missouri's dramatic rise in fentanyl-related overdoses was reported in Part I of this two-part series. In Part II, we report that previous efforts to combat the surge in illicit fentanyl supply from China failed, as Chinese factories shifted production ... ...

    Abstract Missouri's dramatic rise in fentanyl-related overdoses was reported in Part I of this two-part series. In Part II, we report that previous efforts to combat the surge in illicit fentanyl supply from China failed, as Chinese factories shifted production to basic fentanyl precursor chemicals, known as dual-use pre-precursors. Mexican drug cartels now synthesize fentanyl from these basic chemicals and have overpowered the Mexican government. All efforts to reduce the fentanyl supply appear to be failing. Missouri has implemented harm reduction methods: training first responders and educating people who use drugs in safer practices. Harm reduction agencies are distributing naloxone at unprecedented levels. The "One Pill Can Kill" campaign begun by the Drug Enforcement Agency (DEA) in 2021 and foundations created by bereaved parents aim to educate young people on the extraordinary danger of counterfeit pills. In 2022, Missouri is at a crossroads, with record numbers of fatalities from illicit fentanyl and new levels of effort by harm reduction agencies to combat the soaring rate of deaths from this powerful narcotic.
    MeSH term(s) Humans ; Adolescent ; Missouri/epidemiology ; China ; Emergency Responders ; Fentanyl ; Government
    Chemical Substances Fentanyl (UF599785JZ)
    Language English
    Publishing date 2023-02-13
    Publishing country United States
    Document type Journal Article
    ZDB-ID 427362-x
    ISSN 0026-6620
    ISSN 0026-6620
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.B 182: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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  9. Article: Neurotrauma.

    Smith, Colin

    Handbook of clinical neurology

    2017  Volume 145, Page(s) 115–132

    Abstract: Traumatic brain injury remains a major cause of morbidity and mortality throughout the world, affecting young and old alike. Pathologic data have been developed through observations of human autopsies and developing animal models to investigate ... ...

    Abstract Traumatic brain injury remains a major cause of morbidity and mortality throughout the world, affecting young and old alike. Pathologic data have been developed through observations of human autopsies and developing animal models to investigate mechanisms, although animal models do not represent the polypathology of human brain injury and there are likely to be significant differences in the anatomic basis of injury and cellular responses between species. Traumatic brain injury can be defined pathologically as either focal or diffuse, and can be considered to be either primary, directly related to the force associated with the neurotrauma, or secondary, developing as a downstream consequence of the neurotrauma. While neuropathology has traditionally focused on severe head injury, there is increasing recognition of the long-term consequences of traumatic brain injury, particularly repetitive mild traumatic brain injury, and a possible long-term association with chronic traumatic encephalopathy.
    Language English
    Publishing date 2017
    Publishing country Netherlands
    Document type Journal Article
    ISSN 0072-9752
    ISSN 0072-9752
    DOI 10.1016/B978-0-12-802395-2.00008-0
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  10. Article ; Online: Predicting binding affinity changes from long-distance mutations using molecular dynamics simulations and Rosetta.

    Wells, Nicholas G M / Smith, Colin A

    Proteins

    2023  Volume 91, Issue 7, Page(s) 920–932

    Abstract: Computationally modeling how mutations affect protein-protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high-throughput methods for estimating ... ...

    Abstract Computationally modeling how mutations affect protein-protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high-throughput methods for estimating binding free energy changes are currently limited to mutations directly at the interface due to difficulties in accurately modeling how long-distance mutations propagate their effects through the protein structure. However, the modeling and design of such mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high-throughput Rosetta-based side-chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict long-distance mutational perturbations to protein binding. Our approach uses an analytical framework grounded in alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict internal long-distance mutational perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of mutations at the protein-protein interface. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions.
    MeSH term(s) Molecular Dynamics Simulation ; Proteins/chemistry ; Entropy ; Mutation ; Protein Binding
    Chemical Substances Proteins
    Language English
    Publishing date 2023-03-02
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 806683-8
    ISSN 1097-0134 ; 0887-3585
    ISSN (online) 1097-0134
    ISSN 0887-3585
    DOI 10.1002/prot.26477
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