Table_1_Markers of Inflammation and Monoamine Metabolism Indicate Accelerated Aging in Bipolar Disorder.DOCX

<p>Background: A mild pro-inflammatory status accompanies bipolar disorder (BD). Inflammation can cause a shift in monoamine metabolism, thereby activating more cytotoxic pathways. The extent to which low-grade inflammation in BD interacts with monoamine metabolism and how this accords to aging and clinical course is unknown.</p><p>Objectives: We evaluated the presence of alterations in inflammation and monoamine metabolism in BD throughout different mood states and the role of aging therein.</p><p>Methods: Sixty-seven patients with BD were included during an acute mood episode, either depressive (n = 29), (hypo)manic (n = 29), or mixed (n = 9). Plasma levels of inflammatory markers [tumor necrosis factor alpha (TNF-α), interferon gamma (IFN-y), interleukin-6 (IL-6), and C-reactive protein (CRP)] and markers of monoamine metabolism (neopterin, tryptophan, kynurenine, phenylalanine, and tyrosine) were measured repeatedly during a follow-up of 8 months. Levels in patients were compared to controls (n = 35) and correlated to HDRS-17 and YMRS scores. Spearman correlations and linear mixed model analysis were used for statistical analysis.</p><p>Results: Forty-nine patients and 30 controls (age range: 22–62 years) completed the study. No significant differences in inflammatory markers were found between patients and controls overall. Tryptophan, tyrosine, and phenylalanine levels were lower in patients. In both patients and controls, markers of inflammation correlated only weakly with markers of monoamine metabolism, but correlations representative for activity of cytotoxic pathways in monoamine metabolism were more pronounced in patients. In patients, but not in controls, older age was associated with increases in inflammatory markers (IL-6, CRP, neopterin) and the kynurenine/tryptophan ratio. None of the biological markers correlated significantly with mood symptom severity.</p><p>Conclusion: Our data suggest an increased susceptibility of patients with BD to develop a pro-inflammatory state and to shift monoamine metabolism toward more cytotoxic pathways. These findings are in support of the theory of neuroprogression and accelerated aging in BD. Since associations between biological markers and clinical characteristics are limited, it remains to be determined if alterations in biological markers are due to a disease effect or rather are a consequence of confounding factors.</p

Semi-automated digital measurement as the method of choice for beta cell mass analysis

<div><p>Pancreas injury by partial duct ligation (PDL) activates beta cell differentiation and proliferation in adult mouse pancreas but remains controversial regarding the anticipated increase in beta cell volume. Several reports unable to show beta cell volume augmentation in PDL pancreas used automated digital image analysis software. We hypothesized that fully automatic beta cell morphometry without manual micrograph artifact remediation introduces bias and therefore might be responsible for reported discrepancies and controversy. However, our present results prove that standard digital image processing with automatic thresholding is sufficiently robust albeit less sensitive and less adequate to demonstrate a significant increase in beta cell volume in PDL versus Sham-operated pancreas. We therefore conclude that other confounding factors such as quality of surgery, selection of samples based on relative abundance of the transcription factor Neurogenin 3 (Ngn3) and tissue processing give rise to inter-laboratory inconsistencies in beta cell volume quantification in PDL pancreas.</p></div

Fully automated analysis without manual data verification of insulin⁺ area results in both inclusion of noise and exclusion of weak positivity.

<p>(a) Inclusion of false positive signal (“noise”, white arrowheads). (b) Exclusion of weak positivity (white arrows). Left: raw image; middle: ROI (red) with automated threshold (green); right: ROI (red) on raw image.</p

Depiction of manual correction of false-positive and false-negative signal.

<p>(a) Manual correction of false-positive noise (white arrowheads). (b) Manual correction of false-negative weaker signal (compare red encircled areas on both panels). Left: automatic threshold ROI, right: manually corrected ROI. ROI Manager: the blue highlight indicates the depicted ROI: highest ROI value: automatic insulin area (ins auto), lowest ROI value: corrected insulin area (ins corr). The yellow boxes demonstrate the difference in plane area before (ins auto, 1) and after (ins, corr, 2) manual ROI correction: <b>a</b> ins auto: 0.056965 mm², ins corr: 0.065549 mm²; <b>b</b> ins auto: 0.037369 mm², ins corr: 0.106420 mm².</p