TY  - BOOK
AU  - Fahim, Maria 
AU  - Supervisor : Dr. Muhammad Asim Waris
TI  - Assessment of Stress Biomarkers in the Saliva of Smokers and Nonsmokers via UV Photospectrometry and POMS
U1  - 610 
PY  - 2022///
CY  - Islamabad : 
PB  - SMME- NUST; 
KW  - MS Biomedical Sciences (BMS)
N1  - Smoking is one of the major health catastrophes. Smoking is believed to be
the major cause of chronic diseases like Cardiovascular complications, stroke,
pregnancy issues, respiratory failure, etc. There are three important transdiagnostic
emotional factors that make the population vulnerable to initiation of smoking i.e.
anhedonia anxiety sensitivity, distress tolerance. Research studies for the past five
decades have proven the adverse effect of stress on brain physiology and
functioning. The human body responds to trauma (physical or non-physical stress) in
a definite manner. This response of the body can be qualitatively and quantitatively
monitored through several chemicals in the bloodstream, saliva, or urine; responding
to the stress, called stress biomarkers i.e. Brain-derived neurotrophic factor, cortisol,
cytokines etc. Saliva delivers an efficient specimen for various diagnostic procedures
due to the presence of different biological products and secondary metabolites of
xenobiotics and helps in determining the disease progressions as well as therapy
outcomes depending on the variations in the markers/triggers. The nature of mindset
and mood states are evaluated by a scales designed to rate the behavior of an
individual towards the environmental stimuli that may be physical or psychological
in nature. This psychological rating scale is known as the profile of mood state
(POMS). This scale was initially originated by McNair, Droppleman, and Lorr in
1971. This scale is presented in the form a questionnaire including different
questions regarding the mode and feelings of a subject.This research work aims to
further elucidate the utilization of UV Photospectrometry for quantitatively assessing
POMS and its relation to the stress biomarker.
The samples were collected form the vicinity of the university campus H-12
Islamabad. The samples were processed and stored at the biomedical laboratory of
School of Mechanical and Manufacturing Engineering (SMME), NUST. A total of
twenty-four (24) male subjects were analyzed. A total of two groups were
considered. Group 1 included the non-smoking participants, while group 2 included
smoking participants. Simple spitting technique was used for the collection of
unstimulated saliva. About 4 ml unstimulated saliva was collected in the sterile
falcon tube. Saliva was temporarily stored in cool boxes at 4°C and immediately
II
shifted to the facility. Centrifugation of the salivary sample was done at 4°C for 5
minutes and 10,000 rpm. Saliva sample was frozen at -80°C until sample collection
span was completed.
The mood state of the participants was also evaluated using the profile of
mood state technique used initially by McNair, Lorr, and Droppleman in 1971. The
total mood disturbance (TMD) score was calculated that ranges from -32 to 200. The
questionnaire was accessed from ―Mackenzie, B. (2001) Profile of Mood States
(POMS) [WWW] Available from: https://www.brianmac.co.uk/poms.htm [Accessed
26/6/2022]‖. Simulated neural networking (SNN) was applied to the collected data
from smokers and non-smokers for accuracy scoring. The required statistical
analysis was performed and the data was statistically analyzed through a software
―GraphPad Prism 8.0‖ and the respective graphs were plotted.
UV spectrophotometry studies provided peak plasma concentration peaks at
the lower UV range of 190 to 210 nm, but with no significant difference,
representing the presence of biological stress markers. The profile of mood state
evaluation studies concluded that the smoking participants were presented with a
significantly higher level of individual mood profile scores i.e. anger (****,
P<0.0001), confusion (**, P<0.0014), fatigue (*, P<0.0354), tension (*, P<0.0422)
and stress as compared to nonsmoking participants. The vigorous score was
significantly high in the nonsmoking individuals (****, P<0.0001). Similarly, total
mood disturbance score was also significantly high in the smoking participants. The
application of artificial neural networking through artificial machine learning scored
the accuracy of the results 84% which is a reliable outcome.
The current research work concludes that different stress stimuli including
physiological stress and psychological stress tends to initiate/increase the smoking
behavior among the community. Likewise, it is also concluded that smoking
initiation may not be always triggered in response to stress. Numerous factors i.e.
lack of education, negative inspiration, or behavior to impress are also involved.
Furthermore, the adaptation of smoking behavior as a result of stressful stimuli is not
a valid approach to reduce the noxious/stressful stimuli. The stress may further be
exaggerated by smoking
UR  - http://10.250.8.41:8080/xmlui/handle/123456789/30872
ER  -