Introduction We evaluated the value of hematopoietic progenitor cells (HPCs) counted in Sysmex XN analyzers to predict the mobilization and collection of CD34+ cells in apheresis for stem cell transplantation. Methods Eighty patients who underwent stem cell transplantation were enrolled (50 autologous and 30 allogeneic). In the autologous group, patients were considered poor mobilizers when the CD34+ count was <10 × 106/L or <20 × 106/L in patients with multiple myeloma who were going to undergo two transplants. ROC curves were generated, and HPC cutoffs were calculated. Results The correlation between the HPC and CD34+ cell counts was good. Two algorithms were proposed. In the first algorithm, samples collected the day before apheresis, negative and positive HPC cutoffs were selected to detect poor and good mobilization and, therefore, the need or not to administer plerixafor. In the second algorithm, samples collected pre‐apheresis, the negative HPC cutoff was an indication to delay apheresis; an HPC higher than the optimal cutoff was an indication to start apheresis. When the HPC values were between these cutoffs, there was an indication to count CD34+ cells for a better decision‐making. Finally, in samples collected pre‐apheresis, HPC counts could be used to predict patients who would have poor CD34+ cell collections. In the allogeneic group, all the donors mobilized well, and very few needed two apheresis procedures. Conclusions The HPC count is useful for decision‐making in the management of patients subjected to apheresis procedures to collect peripheral blood stem cells.

Malignant pleural effusion and peritoneal carcinomatosis are frequent causes of effusion. Cytological evaluation (PAP-stained slides followed by immunocytochemistry, IHC, if applicable) is currently the gold standard for the diagnosis of malignant effusions, but its sensitivity varies between 40 and 80%, being a time-consuming technique. Although flow cytometry (FC) is not routinely used in the diagnosis or follow-up of nonhematopoietic neoplasms, it has the advantage of being rapidly applicable to fresh samples, potentially decreasing the time for the diagnosis. The main objective of this study was to assess the utility of FC as a confirmatory tool in the diagnosis of neoplastic effusions, based on the expression of EpCAM antibody in tumor cells versus the cytological evaluation. In this work 1,535 serous fluids were collected, of which 101 (68 pleural, 33 ascites) were selected through a screening algorithm and sent to the FC and cytological evaluation. Seventy-three of these samples (46 pleural, 27 ascites) were considered malignant as determined by clinical, cytological and radiological criteria. According to our data, 75% (55/73) of these samples were positive by Cytology/IHC and 74% (54/73) by FC. We noticed that, although the sensitivity, specificity, and area under the curve were similar, the turnaround time was shorter when using FC. Moreover, these results clearly improved by combining both techniques. We conclude that FC provides information about malignant effusions faster than immunohistochemical staining, and we believe that performing both techniques in parallel would improve diagnostic performance.

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Aging population is at higher risk of developing severe COVID-19, including hospitalization and death. In this work, to further understand the relationship between host age-related factors, immunosenescence/exhaustion of the immune system and the response to the virus, we characterized immune cell and cytokine responses in 58 COVID-19 patients admitted to the hospital and 40 healthy controls of different age ranges. Lymphocyte populations and inflammatory profiles were studied in blood samples, using different panels of multicolor flow cytometry. As expected, our analysis reveals differences at both the cellular and cytokine level in COVID-19 patients. Interestingly, when the age range analysis was carried out, the immunological response to the infection was found to differ with age, being especially affected in the group of 30–39 years. In this age range, an increased exhausted T cell response and a decrease of naïve T helper lymphocytes was found in patients, as well as a reduced concentration of the proinflammatory TNF, IL-1β and IL-8 cytokines. Besides, the correlation between age and the study variables was evaluated, and multiple cell types and interleukins were found to correlate with donor age. Notably, the correlations of T helper naïve and effector memory cells, T helper 1–17 cells, TNF, IL-10, IL-1β, IL-8, among others, showed differences between healthy controls and COVID-19 patients. Our findings, in the context of other previous studies, suggest that aging affects the behavior of the immune system in COVID-19 patients. They suggest that young individuals are able to mount an initial response to SARS-CoV-2, but some of them present an accelerated exhaustion of the cell response and an insufficient inflammatory response, resulting in a moderate to severe COVID-19. On the other hand, in older patients there is a smaller immune cell response to the virus, reflected in fewer differences in immune populations between COVID-19 patients and controls. Nevertheless, old patients show more evidence of an inflammatory phenotype, suggesting that the underlying inflammation associated with their age is exacerbated by the SARS-CoV-2 infection.