Search

Simple Summary: We present flow cytometry and clonality evaluation as a reliable and useful method for characterizing feline lymphomas. Neoplastic cell size is a crucial factor for prognosis. We have developed a novel system for cell sizing by flow cytometry that was 82–90% concordant with the gold standard of cytology. Moreover, from our retrospective analysis of survival for small versus large cells, we saw consistency between both methodologies. These results highlight the utility of our approach in providing prognostic insights. Feline lymphoma, a prevalent cancer in cats, exhibits varied prognoses influenced by anatomical site and cellular characteristics. In this study, we investigated the utility of flow cytometry and clonality analysis via PCR for antigen receptor rearrangement (PARR) with respect to characterizing the disease and predicting prognosis. For this purpose, we received fine needle aspirates and/or blood from 438 feline patients, which were subjected to flow cytometry analysis and PARR. We used a subset of the results from patients with confirmed B- or T-cell lymphomas for comparison to cytological or histological evaluation (n = 53). Using them as a training set, we identified the optimal set of flow cytometry parameters, namely forward scatter thresholds, for cell size categorization by correlating with cytology-defined sizes. Concordance with cytological sizing among this training set was 82%. Furthermore, 90% concordance was observed when the proposed cell sizing was tested on an independent test set (n = 24), underscoring the reliability of the proposed approach. Additionally, lymphoma subtypes defined by flow cytometry and PARR demonstrated significant survival differences, validating the prognostic utility of these methods. The proposed methodology achieves high concordance with cytological evaluations and provides an additional tool for the characterization and management of feline lymphoproliferative diseases. [ABSTRACT FROM AUTHOR]

First-line treatments of cancer do not always work, and even when they do, they cure the disease at unequal rates mostly owing to biological and clinical heterogeneity across patients. Accurate prediction of clinical outcome and survival following the treatment can support and expedite the process of comparing alternative treatments. We describe the methodology to dynamically determine remission probabilities for individual patients, as well as their prospects of progressionfree survival (PFS). The proposed methodology utilizes the ex vivo drug sensitivity of cancer cells, their immunophenotyping results, and patient information, such as age and breed, in training machine learning (ML) models, as well as the Cox hazards model to predict the probability of clinical remission (CR) or relapse across time for a given patient. We applied the methodology using the three types of data obtained from 242 canine lymphoma patients treated by (L)-CHOP chemotherapy. The results demonstrate substantial enhancement in the predictive accuracy of the ML models by utilizing features from all the three types of data. They also highlight superior performance and utility in predicting survival compared to the conventional stratification method. We believe that the proposed methodology can contribute to improving and personalizing the care of cancer patients. [ABSTRACT FROM AUTHOR]

Reports a study which determined whether rat outer medullary collecting duct secretes chlorine and whether transepithelial chlorine transport occurs through uptake across the basolateral membrane. How the study was conducted; Results; Discussion of the results.

E. coli O157:H7 is a foodborne pathogen that constitutes a global threat to human health. However, the quantification of this pathogen in food and environmental samples may be problematic at the low cell numbers commonly encountered in environmental samples. In this study, we used recombinase polymerase amplification (RPA) for the detection of E. coli O157:H7, real-time quantitative PCR (qPCR) for quantification, and droplet digital PCR (ddPCR) for absolute and accurate quantification of E. coli O157:H7 from spiked and environmental samples. Primer and probe sets were used for the detection of stx1 and stx2 using RPA. Genes encoding for stx1, stx2, eae, and rfbE were used to quantify E. coli O157:H7 in the water samples. Furthermore, duplex ddPCR assays were used to quantify the pathogens in these samples. Duplex assay set 1 used stx1 and rfbE genes, while assay set 2 used stx2 and eae genes. Droplet digital PCR was used for the absolute quantification of E. coli O15:H7 in comparison with qPCR for the spiked and environmental samples. The RPA results were compared to those from qPCR and ddPCR in order to assess the efficiency of the RPA compared with the PCR methods. The assays were further applied to the dairy lagoon effluent (DLE) and the high rate algae pond (HRAP) effluent, which were fed with diluted DLE. The RPA detected was <10 CFU/mL, while ddPCR showed quantification from 1 to 104 CFU/mL with a high reproducibility. In addition, quantification by qPCR was from 103 to 107 CFU/mL of the wastewater samples. Therefore, the RPA assay has potential as a point of care tool for the detection of E. coli O157:H7 from different environmental sources, followed by quantification of the target concentrations. [ABSTRACT FROM AUTHOR]

Background: To report the tumor, patient, and treatment characteristics of long-term metastatic uveal melanoma survivors., Methods: A non-comparative, retrospective case series of patients from a single institution surviving >24 months with metastatic uveal melanoma (UM)., Results: Nine patients met the study criteria and their charts were reviewed. The mean age at diagnosis of UM was 44.1 years (SD +/- 14.4 years). Initial treatment modalities included enucleation (67%), brachytherapy (22%), and proton beam radiation (11%). The average time from primary tumor diagnosis to detection of metastasis was 125.9 months (SD +/- 95 months). The most common location for initial metastasis was the liver. All patients underwent treatment for metastatic disease including systemic therapy, surgical resection, and isolated hepatic perfusion. The majority of patients received treatment with a tyrosine kinase inhibitor (sorafenib, sunitinib, and/or imatinib). The median survival with metastasis was 51 months (range 27-123 months). Patients had a long disease-free interval before presentation of metastatic disease., Conclusions: A small subset of patients with metastatic UM has prolonged survival. Identification of these patients may be helpful for future clinical trial design.