PREDICTING THE VULNERABILITY AND RESILIENCE TO CARDIOVASCULAR AND NEUROENDOCRINE EFFECTS OF STRESS IN ADULT RATS THROUGH A NOVEL MACHINE LEARNING APPROACH - Journal Article

Aug 5, 2026

Chronic stress elevates cardiovascular disease risk and neuroendocrine illness burden in humans and animals, yet individuals differ: some show vulnerability while others display resilience. The study predicts these stress-related outcomes in adult rats using a novel machine learning approach. Male rats received chronic stress or control treatment for six weeks, with cardiovascular and neuroendocrine responses measured at baseline and after exposure. Vulnerability and resilience were defined by heart rate and blood pressure reaction magnitude, and predictive patterns were learned using feature selection and classification.

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Journal of Advanced Zoology ISSN: 0253-7214 Volume 45 Special Issue 02 Year 2023 Page 1665:1675 PREDICTING THE VULNERABILITY AND RESILIENCE TO CARDIOVASCULAR AND NEUROENDOCRINE EFFECTS OF STRESS IN ADULT RATS THROUGH A NOVEL MACHINE LEARNING APPROACH Dr. Uttam Prasad Panigrahy1, Associate Professor, Department of Pharmaceutical Analysis, Faculty of Pharmaceutical sciences, Assam down town University, [uttampanigrahy@gmail.com](uttampanigrahy@gmail.com)[ ](uttampanigrahy@gmail.com)Dr.R.INDIRA2, Associate professor, Department of Zoology, CH. S.D. ST.THERESA'S (A) College for women,gavaravaram,eluru district Adhra pradesh, [rokkalaindira@gmail.com](rokkalaindira@gmail.com)[ ](rokkalaindira@gmail.com)Dr. Anand Konkala3, Associate professor of Zoology, Govt City College, Osmania University, Hyderabad, [konkala27@gmail.com](konkala27@gmail.com) Sanhita Purkayastha4,Assistant Professor, Barkhetri College, Assam, [sun_4U2Day@yahoo.com](sun_4U2Day@yahoo.com)[ ](sun_4U2Day@yahoo.com)[Dr. Jai Shanker Pillai HP](Dr. Jai Shanker Pillai HP5)[5](Dr. Jai Shanker Pillai HP5), Associate Professor, Department of Microbiology, Faculty of Science, Assam downtown University, Guwahati,[drjaishankerpillai@gmail.com](drjaishankerpillai@gmail.com)[ ](drjaishankerpillai@gmail.com)Dr. Ruchu Kuthiala6, Ph.D Scholar, Post Graduate Department (Home Science)of Sant Gadgebaba, Amaravati University, Amaravati MH, [clinicalnutruchu@gmail.com](clinicalnutruchu@gmail.com) | Article History
Received: 12 March 2023
Revised: 21 August 2023
Accepted:09 October 2023 | Abstract:
Chronic stress has been risk of cardiovascular disease and neuroendocrine illness in humans and animals. However, not all individuals are equally vulnerable to the negative effects of stress, and some may even exhibit resilience. Identifying biomarkers or other predictors of vulnerability and resilience could help to develop personalized prevention and treatment strategies. In this study, we aimed to predict vulnerability and resilience to stress-related health effects in adult rats using a novel machine learning approach. We exposed male rats to chronic stress or control conditions for six weeks and measured their cardiovascular and neuroendocrine responses at baseline and at the end of the stress exposure. Rats were considered vulnerable if they exhibited large growth in heart rate and reaction of blood pressure to stress, and resilient if they did not show significant changes in these parameters. We then applied a novel machine learning algorithm to identify patterns in the data that could predict vulnerability or resilience. In this case, we employed a combination methods for selecting features using Support Vector Machine and classification algorithm Principal component Analysis to identify the most important predictors of vulnerability and resilience. We also compared the performance of the machine learning approach with traditional | | --- | --- | 1665 Available online at: [https://jazindia.com](https://jazindia.com) PREDICTING THE VULNERABILITY AND RESILIENCE TO CARDIOVASCULAR AND NEUROENDOCRINE EFFECTS OF STRESS IN ADULT RATS THROUGH A NOVEL MACHINE LEARNING APPROACH | CC License
CC-BY-NC-SA 4.0 | statistical methods, such as logistic regression and discriminant analysis. Our results suggest that heart rate variability were among the most important predictor of vulnerability and resilience to stress-related health effects in rats. Specifically, rats with lower heart rate variability and higher cortisol levels at baseline were more likely to be vulnerable to stress. Conversely, rats with greater concentrations of antiinflammatory cytokines increased risk of becoming resilient to stress. The machine learning approach was more accurate in predicting vulnerability and resilience than traditional statistical methods, with an overall accuracy of 89%, respectively. Our study provides new insights into the complex interplay between stress and health, an

FAQs

What determines whether rats are classified as vulnerable or resilient in the study?

Vulnerable rats show large increases in heart rate and pronounced blood pressure responses to stress, while resilient rats do not show significant changes in these parameters.

Which machine learning methods are used to identify predictors?

The study uses feature selection with Support Vector Machine combined with Principal Component Analysis for classification, identifying important predictors of vulnerability and resilience.

What biomarkers or indicators are reported as key predictors?

Lower heart rate variability and higher baseline cortisol levels indicate greater vulnerability, while higher anti-inflammatory cytokine concentrations are associated with resilience.

Aug 5, 2026

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