Etiology and Diagnosis of Major Depression - A Novel Quantitative Approach

Copyright © 2013 Johnny T. Ottesen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Classical psychiatric opinions are relative uncertain and treatment results are not impressive when deal-ing with major depression. Depression is related to the endocrine system, but despite much effort a good quantitative measure for characterizing depression has not yet emerged. Methods: Based on ACTH and cortisol levels and using clustering analysis and mixture effect modeling we propose a novel and scientifically based quantitative index, denoted the O-index. The O-index combines a weighted and scaled deviation from normal values in both ACTH and cortisol. Results: Using ANOVA we compare the O-index with opinions reach by classical psychiatric diagnostic procedure (sensitivity 83%, specificity 59%, likelihood ratio positive 2.0, and likelihood ratio negative 0.29). The O-index nicely refines the etiology of depression: Combined with clinical data for 29 subjects earlier reported three categories emerge (p = 4.4 × 10−13): hypocortisolemic depressed, non-depressed, and hypercotisolemic depressed. The O-index also re-veals why it has been difficult to obtain good markers earlier. It explains that healthy subjects may have an elevated (suppressed) level of cortisol or ACTH, however, the healthy system is able to deal with such elevated (suppressed) lev-els by compensating through suppressing (stimulating) the other component. In contrast the O-index shows that de

Potential of immunotherapies in treating hematological cancer-infection comorbidities—a mathematical modelling approach

Background: The immune system attacks threats like an emerging cancer or infections like COVID-19 but it also plays a role in dealing with autoimmune disease, e.g., inflammatory bowel diseases, and aging. Malignant cells may tend to be eradicated, to appraoch a dormant state or escape the immune system resulting in uncontrolled growth leading to cancer progression. If the immune system is busy fighting a cancer, a severe infection on top of it may compromise the immunoediting and the comorbidity may be too taxing for the immune system to control. Method: A novel mechanism based computational model coupling a cancer-infection development to the adaptive immune system is presented and analyzed. The model maps the outcome to the underlying physiological mechanisms and agree with numerous evidence based medical observations. Results and Conclusions: Progression of a cancer and the effect of treatments depend on the cancer size, the level of infection, and on the efficiency of the adaptive immune system. The model exhibits bi-stability, i.e., virtual patient trajectories gravitate towards one of two stable steady states: a dormant state or a full-blown cancer-infection disease state. An infectious threshold curve exists and if infection exceed this separatrix for sufficiently long time the cancer escapes. Thus, early treatment is vital for remission and severe infections may instigate cancer progression. CAR T-cell Immunotherapy may sufficiently control cancer progression back into a dormant state but the therapy significantly gains efficiency in combination with antibiotics or immunomodulation

Increased Intracranial Pressure Attenuates the Pulsating Component of Cerebral Venous Outflow

Background: The underlying physiology of the intracranial pressure (ICP) curve morphology is still poorly understood. If this physiology is explained it could be possible to extract clinically relevant information from the ICP curve. The venous outflow from the cranial cavity is pulsatile, and in theory the pulsatile component of venous outflow from the cranial cavity should be attenuated with increasing ICP. In this study, we explored the relationship between ICP and the pulsatility of the venous outflow from the intracranial cavity. Methods: Thirty-seven neuro-intensive care patients that had been examined with phase-contrast magnetic resonance imaging regarding cerebral blood flow (CBF) through the internal carotid and vertebral arteries and venous flow in the internal jugular veins were retrospectively included. The pulsatility of the jugular flow was determined by calculating the venous pulsatile index. The results were correlated to clinical data registered in the patient data monitoring system, including ICP and cerebral perfusion pressure (CPP). Results: CBF was 996 ± 298 ml/min, and the flow in the internal jugular veins equaled 67 ± 17% of the CBF, with a range of 22–97%. The venous pulsatile index correlated negatively to ICP (R = − 0.47 p = 0.003). The lowest flow in the internal jugular veins over the cardiac cycle (Fmin) was not correlated to ICP. Temperature, end-tidal CO2, MAP, and CPP were not correlated to venous pulsatility. Conclusion: An increase in ICP correlates to a lower pulsatility of the venous outflow from the cranial cavity. A lower pulsatility could be due to increased pressure requirements to compress intracranial veins with increasing ICP