Biotechnology: Is There a Role for Medical Surveillance?

2009 ◽  
pp. 101-101-10
Author(s):  
DF Liberman ◽  
AM Ducatman ◽  
R Fink
Keyword(s):  
Medical Surveillance

scholarly journals Shotgun lipidomics of liver and brain tissue of Alzheimer’s disease model mice treated with acitretin

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anna A. Lauer ◽  
Daniel Janitschke ◽  
Malena dos Santos Guilherme ◽  
Vu Thu Thuy Nguyen ◽  
Cornel M. Bachmann ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Amyloid Β ◽  
Lipid Homeostasis ◽  
Medical Surveillance ◽  
Shotgun Lipidomics ◽  
App Processing ◽  
Cognitive Improvement ◽  
The Impact

AbstractAlzheimer’s disease (AD) is a very frequent neurodegenerative disorder characterized by an accumulation of amyloid-β (Aβ). Acitretin, a retinoid-derivative and approved treatment for Psoriasis vulgaris, increases non-amyloidogenic Amyloid-Precursor-Protein-(APP)-processing, prevents Aβ-production and elicits cognitive improvement in AD mouse models. As an unintended side effect, acitretin could result in hyperlipidemia. Here, we analyzed the impact of acitretin on the lipidome in brain and liver tissue in the 5xFAD mouse-model. In line with literature, triglycerides were increased in liver accompanied by increased PCaa, plasmalogens and acyl-carnitines, whereas SM-species were decreased. In brain, these effects were partially enhanced or similar but also inverted. While for SM and plasmalogens similar effects were found, PCaa, TAG and acyl-carnitines showed an inverse effect in both tissues. Our findings emphasize, that potential pharmaceuticals to treat AD should be carefully monitored with respect to lipid-homeostasis because APP-processing itself modulates lipid-metabolism and medication might result in further and unexpected changes. Moreover, deducing effects of brain lipid-homeostasis from results obtained for other tissues should be considered cautiously. With respect to acitretin, the increase in brain plasmalogens might display a further positive probability in AD-treatment, while other results, such as decreased SM, indicate the need of medical surveillance for treated patients.

A study on smart home for medical surveillance

2019 ◽  
Author(s):  
Eloutouate Lamiae ◽  
Elouaai Fatiha ◽  
Bouhorma Mohammed ◽  
Gibet Tani Hicham
Keyword(s):  
Smart Home ◽  
Medical Surveillance

scholarly journals Seasonal Trends for Environmental Illness Incidence in the U.S. Army

2021 ◽  
Author(s):  
David W DeGroot ◽  
Catherine A Rappole ◽  
Paige McHenry ◽  
Robyn M Englert
Keyword(s):  
Risk Mitigation ◽  
Cold Season ◽  
Incidence Rates ◽  
Cold Weather ◽  
Medical Surveillance ◽  
Piecewise Regression ◽  
Exertional Heat Illness ◽  
Policies And Procedures ◽  
Icd Codes ◽  
The U.S

ABSTRACT Introduction The incidence of and risk factors for exertional heat illness (EHI) and cold weather injury (CWI) in the U.S. Army have been well documented. The “heat season”, when the risk of EHI is highest and application of risk mitigation procedures is mandatory, has been arbitrarily defined as May 1 through September 30, while the “cold season” is understood to occur from October 1 to April 30 each year. The proportions of EHI and CWI that occur outside of the traditional heat and cold seasons are unknown. Additionally, it is unknown if either of the seasonal definitions are appropriate. The primary purpose of this study was to determine the proportion of EHI and of CWI that occur within the commonly accepted seasonal definitions. We also report the location-specific variability, seasonal definitions, and the demographic characteristics of the populations. Methods The U.S. Army installations with the highest frequency of EHI and of CWI from 2008 to 2013 were identified and used for analysis. In total there were 15 installations included in the study, with five installations used for analysis in both the EHI and CWI projects. In- and out-patient EHI and CWI data (ICD-9-CM codes 992.0 to 992.9 and ICD codes 991.0 to 991.9, respectively) were obtained from the Defense Medical Surveillance System. Installation-specific denominator data were obtained from the Defense Manpower Data Center, and incidence rates were calculated by week, for each installation. Segmental (piecewise) regression analysis was used to determine the start and end of the heat and cold seasons. Results Our analysis indicates that the heat season starts around April 22 and ends around September 9. The cold season starts on October 3 and ends on March 24. The majority (n = 6,445, 82.3%) of EHIs were diagnosed during the “heat season” of May 1 to September 30, while 10.3% occurred before the heat season started (January1 to April 30) and 7.3% occurred after the heat season ended (October 1 to December 31). Similar to EHI, 90.5% of all CWIs occurred within the traditionally defined cold season, while 5.7% occurred before and 3.8% occurred after the cold season. The locations with the greatest EHI frequency were Ft Bragg (n = 2,129), Ft Benning (n = 1,560), and Ft Jackson (n = 1,538). The bases with the largest proportion of CWI in this sample were Ft Bragg (17.8%), Ft Wainwright (17.2%), and Ft Jackson (12.7%). There were considerable inter-installation differences for the start and end dates of the respective seasons. Conclusions The present study indicates that the traditional heat season definition should be revised to begin  ∼3 weeks earlier than the current date of May 1; our data indicate that the current cold season definition is appropriate. Inter-installation variability in the start of the cold season was much larger than that for the heat season. Exertional heat illnesses are a year-round problem, with ∼17% of all cases occurring during non-summer months, when environmental heat strain and vigilance are lower. This suggests that EHI mitigation policies and procedures require greater year-round emphasis, particularly at certain locations.

??B-Readers?? and Asbestos Medical Surveillance

1988 ◽  
Vol 30 (8) ◽  
pp. 644-647 ◽  
Author(s):  
Alan M. Ducatman ◽  
CDR William N. Yang ◽  
Samuel A. Forman
Keyword(s):  
Medical Surveillance

Tuberculosis Screening in Silica-Exposed Workers

2021 ◽  
pp. 003335492110415
Author(s):  
Nicholas K. Reul ◽  
Zachary Gray ◽  
Barbara Burchell Braid ◽  
Margaret A. Leland
Keyword(s):  
Health Care Providers ◽  
Screening Tool ◽  
Washington State ◽  
Care Providers ◽  
Medical Surveillance ◽  
Tuberculosis Screening ◽  
Safety And Health ◽  
Health Practitioners ◽  
Exposed Workers ◽  
Public Health Practitioners

Both the Occupational Safety and Health Administration and Washington State require safety and health protections for workers exposed to respirable crystalline silica, including tuberculosis (TB) screening as part of occupational medical surveillance. We describe the creation of a TB screening tool for silica-exposed workers receiving regulated medical surveillance examinations in Washington State. The tool provides relevant clinical recommendations to assist health care providers and public health practitioners who choose to use the tool when performing such examinations. A cross-disciplinary team at the Washington State Department of Labor and Industries created the TB screening tool to help health care providers identify silica-exposed workers who should receive a comprehensive evaluation for active TB disease and workers who should or must receive testing for latent TB infection. The Washington State Adult Tuberculosis Screening Tool for Workers Exposed to Respirable Crystalline Silica benefits occupational and respiratory clinicians and public health practitioners by aiding both the individual- and population-level delivery of occupational health and TB screening services to silica-exposed workers receiving required medical surveillance examinations.

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