Serum Protein Concentration and Serum Protein Fractions in Bottlenose Dolphins (Tursiops truncatus) under Human Care Using Agarose Gel Electrophoresis

Serum protein electrophoresis (SPE) is the most used and reliable method to determine the percentage of serum protein subfractions. The interpretation of the kinetics of total proteins and albumin and globulin fractions is receiving increased attention in wild animals, as well as in domestic animals, due to the possibility of identifying typical pathologic patterns. However, the interpretation of these data had to be performed in light of an appropriate method—and species- specific reference intervals (RIs). In marine mammals, as well as other non-domestic species, specific attention should also be given to the different environment (free ranging vs. human managed) and the associated different exposure to environmental stimuli. The aim of this report was to establish RIs for the serum protein fractions evaluated using agarose gel electrophoresis (AGE) in bottlenose dolphins under human care. Peripheral blood samples were collected from 40 bottlenose dolphins during standard veterinary procedures to evaluate their health status. Total protein concentration was determined using the biuret method while AGE was performed using an automated system. A pooled dolphin’s serum sample was used to determine the intra-assay and inter-assay imprecision of AGE. The RIs were calculated using an Excel spreadsheet with the Reference Value Advisor set of macroinstructions. The intra and inter-assay imprecisions were 1.2% and 2.5%, respectively, for albumin; 2.9% and 5.7%, respectively, for α-globulins; 3.8% and 4.0%, respectively, for β-globulins; and 3.4% and 4.8%, respectively, for γ-globulins. The total protein, albumin, α-globulin, β-globulin, and γ-globulin concentrations were 65.5 ± 5.4 g/L, 45.5 ± 4.9 g/L, 8.0 ± 1.0 g/L, 5.0 ± 2.0 g/L, and 7.0 ± 2.0 g/L, respectively. We established the RIs for the total protein and serum protein fractions using AGE in bottlenose dolphins under human care

Biological Variation and Reference Change Value of Routine Hematology Measurands in a Population of Managed Bottlenose Dolphins (<i>Tursiops truncatus</i>)

Hematological analyses are particularly useful in assessing a dolphin’s health status. However, the creation of appropriate reference intervals for this species is difficult due to the low number of reference individuals. The implementation of individual reference intervals (iRIs) allows researchers to overcome this limitation and, moreover, also consider the within-individual variability. The aims of this study were (1) to evaluate the biological variations in some hematological measurands, including erythrocytes (RBC), hematocrit (Hct), mean cellular volume and hemoglobin content (MCV and MCHC, respectively), RBC distribution width (RDW), leukocytes (WBC), and platelets (PLT); and (2) to calculate the index of individuality (IoI) and reference change value (RCV), which enable the production of iRIs, in healthy managed bottlenose dolphins. Seven dolphins were included, and the results of six hematological exams were analyzed for each animal. Analytical imprecision (CVa), within-dolphin variation (CVi), and between-dolphins variations (CVg) were calculated, and the IoI and RCV were derived for each measurand. All the hematological measurands had intermediate IoI except WBC, for which Iol was low. The calculated RCV ranged from 10.33% (MCV) to 186.51% (WBC). The results reveal that the majority of hematological measurands have an intermediate level of individuality in dolphins, and thus the application of iRIs is appropriate. The calculated RCV can also be applied to other managed dolphins and could be useful in interpreting serial CBC exams

Using peripheral immune-inflammatory blood markers in tumors treated with immune checkpoint inhibitors: An INVIDIa-2 study sub-analysis

The neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammatory index (SII) have been reported as prognosticators in non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), and melanoma. This analysis of the INVIDIa-2 study on influenza vaccination in patients with cancer treated with immune checkpoint inhibitors (ICIs) assessed NLR and SII on overall survival (OS) by literature-reported (LR), receiver operating characteristic curve (ROC)-derived (ROC) cutoffs or as continuous variable (CV). NLR and SII with ROC cutoffs of &lt;3.4 (p &lt; 0.001) and &lt;831 (p &lt; 0.001) were independent factors for OS in multivariate analysis. SII with LR, ROC, or CV significantly predicted OS in NSCLC (p = 0.002, p = 0.003, p = 0.003), RCC (p = 0.034, p = 0.014, p = 0.014), and melanoma (p = 0.038, p = 0.022, p = 0.019). NLR with LR and ROC cutoffs predicted OS in first line (p &lt; 0.001 for both) and second line or beyond (p = 0.006 for both); likewise SII (p &lt; 0.001; p = 0.002 and p &lt; 0.001). NLR and SII are prognosticators in NSCLC, RCC, and melanoma treated with ICIs

Spatially resolved qualified sewage spot sampling to track SARS-CoV-2 dynamics in Munich - One year of experience

Rubio-Acero R, Beyerl J, Muenchhoff M, et al. Spatially resolved qualified sewage spot sampling to track SARS-CoV-2 dynamics in Munich - One year of experience. Science of The Total Environment. 2021;797: 149031

The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant

Le Gleut R, Plank M, Pütz P, et al. The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant. BMC Infectious Diseases. 2023;23(1): 466.**Background** Population-based serological studies allow to estimate prevalence of SARS-CoV-2 infections despite a substantial number of mild or asymptomatic disease courses. This became even more relevant for decision making after vaccination started. The KoCo19 cohort tracks the pandemic progress in the Munich general population for over two years, setting it apart in Europe. **Methods** Recruitment occurred during the initial pandemic wave, including 5313 participants above 13 years from private households in Munich. Four follow-ups were held at crucial times of the pandemic, with response rates of at least 70%. Participants filled questionnaires on socio-demographics and potential risk factors of infection. From Follow-up 2, information on SARS-CoV-2 vaccination was added. SARS-CoV-2 antibody status was measured using the Roche Elecsys® Anti-SARS-CoV-2 anti-N assay (indicating previous infection) and the Roche Elecsys® Anti-SARS-CoV-2 anti-S assay (indicating previous infection and/or vaccination). This allowed us to distinguish between sources of acquired antibodies. **Results** The SARS-CoV-2 estimated cumulative sero-prevalence increased from 1.6% (1.1-2.1%) in May 2020 to 14.5% (12.7-16.2%) in November 2021. Underreporting with respect to official numbers fluctuated with testing policies and capacities, becoming a factor of more than two during the second half of 2021. Simultaneously, the vaccination campaign against the SARS-CoV-2 virus increased the percentage of the Munich population having antibodies, with 86.8% (85.5-87.9%) having developed anti-S and/or anti-N in November 2021. Incidence rates for infections after (BTI) and without previous vaccination (INS) differed (ratio INS/BTI of 2.1, 0.7-3.6). However, the prevalence of infections was higher in the non-vaccinated population than in the vaccinated one. Considering the whole follow-up time, being born outside Germany, working in a high-risk job and living area per inhabitant were identified as risk factors for infection, while other socio-demographic and health-related variables were not. Although we obtained significant within-household clustering of SARS-CoV-2 cases, no further geospatial clustering was found. **Conclusions** Vaccination increased the coverage of the Munich population presenting SARS-CoV-2 antibodies, but breakthrough infections contribute to community spread. As underreporting stays relevant over time, infections can go undetected, so non-pharmaceutical measures are crucial, particularly for highly contagious strains like Omicron