Development of an advanced flow cytometry based high-resolution immunophenotyping method to benchmark early immune response in dairy cows

The determination of the somatic cell count of a milk sample is one of the most common methods to monitor udder health of a dairy cow. However, this procedure does not take into account the fact that cells in milk present a great variety of different cell types. The objective of our study was to establish a high-resolution differential cell count (HRDCC) by means of flow cytometry in blood and milk. We were able to detect ten subpopulations among the three main populations of immune cells and to determine their viability. Additionally, blood samples were analyzed for common laboratory biomarkers, i.e. differential blood counts, haptoglobin levels and several metabolic parameters. In this first feasibility study, we used three different vaccines to stimulate the immune system of five healthy cows each. Samples were collected shortly before, in between and after the vaccinations. Using multivariate statistical methods we saw a diagnostic benefit when HRDCCs were included compared to only the standard laboratory parameters. The impacts of all three vaccinations on the immune system were visible in blood HRDCCs as well as in milk HRDCCs. Cluster of Differentiation 8+ (CD8+) T cells, B cells and monocyte/macrophage subpopulations were among the most important and statistically relevant parameters for all treatments in both biofluids. Moreover, in one of the treatment groups intermediate monocytes showed a significant increase after both vaccinations. Although the use of HRDCC in blood or milk was shown to be highly relevant for early systemic diagnostic, to confirm these subpopulations further investigations in cows of different breed, lactation stage or health status are required.

Evaluating Digital Device Technology in Alzheimer's Disease via Artificial Intelligence

The use of digital technologies may help to diagnose Alzheimer's Disease (AD) at the pre-symptomatic stage. However, before implementation into clinical practice, digital measures (DMs) need to be evaluated for their diagnostic benefit compared to established questionnaire-based assessments, such as Mini-Mental State Examination (MMSE) and Functional Activity Questionnaire (FAQ). We analyzed data from smartphone based virtual reality game and Alzheimer's Disease Neuroimaging Initiative (ADNI). We employed an Artificial Intelligence (AI) based approach to elucidate the relationship of DMs to MMSE and FAQ. Furthermore, we used Machine Learning (ML) and statistical methods to assess the diagnostic benefit of DMs compared to questionnaire-based scores. We found non-trivial relationships between DMs, MMSE, and FAQ which can be visualized as a complex network. DM showed a better ability to discriminate between different stages of the disease than questionnaire-based methods. Our results indicate that DMs have the potential to act as a crucial measure in the early diagnosis and staging of AD.

SPECT/CT imaging of inflammation and calcification in human carotid atherosclerosis to identify the plaque at risk of rupture

Background Calcification and inflammation are atherosclerotic plaque compositional biomarkers that have both been linked to stroke risk. The aim of this study was to evaluate their co-existing prevalence in human carotid plaques with respect to plaque phenotype to determine the value of hybrid imaging for the detection of these biomarkers. Methods Human carotid plaque segments, obtained from endarterectomy, were incubated in [111In]In-DOTA-butylamino-NorBIRT ([111In]In-Danbirt), targeting Leukocyte Function-associated Antigen-1 (LFA-1) on leukocytes. By performing SPECT/CT, both inflammation from DANBIRT uptake and calcification from CT imaging were assessed. Plaque phenotype was classified using histology. Results On a total plaque level, comparable levels of calcification volume existed with different degrees of inflammation and vice versa. On a segment level, an inverse relationship between calcification volume and inflammation was evident in highly calcified segments, which classify as fibrocalcific, stable plaque segments. In contrast, segments with little or no calcification presented with a moderate to high degree of inflammation, often coinciding with the more dangerous fibrous cap atheroma phenotype. Conclusion Calcification imaging alone can only accurately identify highly calcified, stable, fibrocalcific plaques. To identify high-risk plaques, with little or no calcification, hybrid imaging of calcification and inflammation could provide diagnostic benefit.

The marginal diagnostic benefit of pancreatic cancer molecular profiling after germline testing.

10513 Background: Germline genetic testing is now universally recommended for patients (pts) with pancreatic ductal adenocarcinoma (PDAC) for purposes of both familial screening and therapeutic guidance. Treatment selection can be further informed by tumor molecular profiling (TMP) to identify targetable somatic alterations in pts with advanced disease, but this is inconsistently applied. Determination of the rate of actionable findings identified with TMP after germline testing, which we term marginal diagnostic benefit, may inform practice patterns and workflow in this patient population. Methods: This retrospective analysis included all pts with PDAC who underwent germline testing and TMP at UCSF over a 4-yr period. Medical records were reviewed for demographics, disease-specific data, and germline testing/TMP clinical reports. Alterations classified as ‘pathogenic’ or ‘likely pathogenic’ were included, and were deemed ‘actionable’ if there was clinical or preclinical evidence of benefit from targeted therapy in any cancer, as previously described. Results: From 1/2016-1/2020, 144/738 (20%) UCSF pts with PDAC completed both germline testing and TMP. Germline testing identified actionable pathogenic alterations in 10 (7%). TMP confirmed 8/10 of these alterations and identified 3 additional therapeutic targets. Among the 134 pts without actionable germline findings, TMP identified 45 new therapeutic targets in 41 (31%) pts, increasing the overall rate of actionable findings from 7% to 35%. Most (35/58, 60%) actionable alterations involved genes associated with the Homologous Recombination DNA Damage Repair (HR-DDR) pathway (Table). 80% of pts with HR-DDR pathway alterations (9/10 germline, 19/25 somatic) received platinum-based chemotherapy. Four pts were treated with targeted therapy based on test results: PARP-inhibitor (n = 2, germline BRCA1 and PALB2 mutations), PARP-inhibitor + ATR inhibitor (n = 1, somatic ARID1A mutation) and mTOR inhibitor (n = 1, somatic STK11 deletion). Conclusions: In this analysis, PDAC TMP after germline testing increased the detection of actionable alterations (the marginal diagnostic benefit) by five-fold. As more somatic tumor alterations become actionable with the development of targeted therapeutics, TMP is a necessary complement to germline testing to fully inform personalized treatment decisions for all pts with PDAC.[Table: see text]