Search

Biomarkers are a range of biological signals that measure the presence and severity of the disease. This literature review assesses circulating DNA (ctDNA) and microRNA (miRNA) biomarkers detected in liquid and tissue biopsies and their importance in the prognosis, outcomes, and treatments for non-small cell lung cancer (NSCLC). These biomarkers have the potential for clinical use; however, further studies with requisite data and sufficiently large trials are required to refine our understanding of their applicability. The prognostic significance of ctDNA and miRNA biomarkers in NSCLC care has demonstrated that liquid biopsy and molecular diagnostic testing may provide a feasible and noninvasive method for tailoring treatment plans to the specific mutational landscape of diverse NSCLC patients. However, further testing must be conducted to analyze the significance and benefit of ctDNA and miRNA biomarkers in larger cohorts and substantiate the standardization of liquid biopsy in clinical practice.

Neutrophils are a type of white blood cell essential for the function of the innate immune system. To elucidate mechanisms of neutrophil biology, many studies are performed in vertebrate animal model systems. In Danio rerio (zebrafish), in vivo imaging of neutrophils is possible due to transgenic strains that possess fluorescently labeled leukocytes. However, due to the relative abundance of neutrophils, the counting process is laborious and subjective. In this article, we propose the use of a custom trained “you only look once” (YOLO) machine learning algorithm to automate the identification and counting of fluorescently labeled neutrophils in zebrafish. Using this model, we found the correlation coefficient between human counting and the model equals r = 0.8207 with an 8.65% percent error, while variation among human counters was 5% to 12%. Importantly, the model was able to correctly validate results of a previously published article that quantitated neutrophils manually. While the accuracy can be further improved, this model notably achieves these results in mere minutes compared with hours via standard manual counting protocols and can be performed by anyone with basic programming knowledge. It further supports the use of deep learning models for high throughput analysis of fluorescently labeled blood cells in the zebrafish model system.

Background: In India, blood units reactive by the initial screening assays are discarded. A significant number of these are falsely positive, leading to wastage of precious blood. Also of importance is the dilemma created when it comes to donor disclosure. Hence, it is important to evaluate the positive predictive value (PPV) of the initial screening assay to identify false-positive screening results and implement a more balanced algorithm for donor disclosure and counseling. The study was undertaken with an objective of comparing signal-to-cutoff ratio (S/Co) of positive results in HBV, HCV, and HIV screening of electrochemiluminescent (ECI) assay with the results of ID-NAT so as to predict a S/Co ratio of indicative of true positives. Methods: The retrospective study was conducted in the transfusion-transmissible infection Laboratory in a Regional Blood Transfusion Centre in South India. Consecutive blood donors from January 2015 to December 2019 were evaluated simultaneously for HBV, HCV, and HIV by ECI (Vitros 3600, Ortho Clinical Diagnostics) and ID-NAT (Procleix Panther System by Grifols), and the positive results either by one or both were analyzed. Results: A total of 163,596 voluntary donor samples were evaluated. In case of HBV, a S/Co ratio of 1000 predicts a true positive more than 94% of the time. In case of HCV, a S/Co ratio of 8 predicts a true positive more than 95% of the time. Finally, a S/Co ratio of 30 predicts a true positive as well as true negative 100% of the time in case of HIV. Conclusions: It is challenging to propose a standard S/Co ratio because the performance of each assay varies across laboratories. However, the study throws light on the role of the S/Co ratio in reducing the perplexity during donor notification.

Background and Objective: It is important to strengthen deceased donor organ transplant program to help the patients who do not have living kidney donor available. However, there are lots of challenges in deceased donor program. There are challenges to convince families of brain dead patients for organ donation, but transportation of organ as well as allocation is also difficult. One of the main challenges for transplant immunology laboratory is correct crossmatch technique which is sensitive as well as quick and easy to perform. The aim of this study is to evaluate the results of Luminex lysate donor-specific antibody (DSA) crossmatch (LumCross-match) testing for deceased donor renal transplant cases and correlate with graft dysfunction. Methods: We use Luminex lysate DSA crossmatch for human leukocyte antigen testing for deceased donor renal transplants. In 2 years, we had 177 deceased donations and 1184 crossmatches were done. Results: Total 342 patients received kidneys in 2 years. No hyperacute rejection was reported though 28 cases had signs of antibody-mediated rejection posttransplant. Conclusion: We found Luminex lysate crossmatch useful in deceased donor transplant program because of easy procedure, high throughput, more sensitive, and less laborious as well as for posttransplant monitoring.

Introduction: Although CDC has been the gold standard for many years, this assay is certainly not perfect and its use is associated with several problems. The Luminex anti-HLA antibody detection assay is reportedly more sensitive and specific. One of the test is Luminex DSA cross match which is more sensitive than CDC cross match. It is also considered cost effective tool to evaluate pre and post renal transplant cases. Material and Methods: We started Luminex based Donor specific antibody Cross Match tests (DSA Xm) with lysate by the end of 2009 along with CDC after standardization. This study is planned to evaluate the results of DSA Xm of last three years & also to observe antibody medicated rejections after renal transplant. Results: Total 3137 Luminex DSA Cross Match tests were done & 515 tests were positive cross match with negative CDC xm result. Out of 515 positive results 164 were positive for class I, 223 were positive for class II and 128 were positive for both class I & II. In the three years total 1129 renal transplants were done at various centers and total 42 cases of Antibody medicated rejections were reported. Out of 42 patients, 36 patients had pre transplant history of CDC negative & Luminex DSA xm positive. Conclusion: We evaluated our three year results of DSA Xm test and found a cost effective, sensitive and useful supplementary test to evaluate pre and post renal transplant cases.

Alloimmunization is an adverse consequence of exposition to red blood cell antigens through transfusion, pregnancy, or transplantation. Alloimmunization to red cell antigens creates problem not only in immunohematological testing but also causes difficulty in finding compatible blood for those patients who develop multiple alloantibodies. Moreover, the development of multiple alloantibodies can significantly complicate transfusion therapy and/or provokes hemolytic transfusion reactions, the severity of which can vary from mild to extremely severe. We are presenting an interesting case with multiple alloantibodies. Patient's samples were investigated for antibody screening using commercially available three cell panels, and the antibody was identified using different lots of identification panel. Red cell phenotyping was done with minor blood group antisera. After workup, antigen-negative compatible blood was provided for transfusion.

Neutrophils are a type of white blood cell essential for the function of the innate immune system. To elucidate mechanisms of neutrophil biology, many studies are performed in vertebrate animal model systems. In Danio rerio (zebrafish), in vivo imaging of neutrophils is possible due to transgenic strains that possess fluorescently labeled leukocytes. However, due to the relative abundance of neutrophils, the counting process is laborious and subjective. In this article, we propose the use of a custom trained “you only look once” (YOLO) machine learning algorithm to automate the identification and counting of fluorescently labeled neutrophils in zebrafish. Using this model, we found the correlation coefficient between human counting and the model equals r = 0.8207 with an 8.65% percent error, while variation among human counters was 5% to 12%. Importantly, the model was able to correctly validate results of a previously published article that quantitated neutrophils manually. While the accuracy can be further improved, this model notably achieves these results in mere minutes compared with hours via standard manual counting protocols and can be performed by anyone with basic programming knowledge. It further supports the use of deep learning models for high throughput analysis of fluorescently labeled blood cells in the zebrafish model system.

Background: Platelet additive solutions (PAS) are crystalloid nutrient media used in place of plasma for platelet storage. They replace 60%–70% of plasma in platelet components, so the amount of storage plasma can be decreased. Platelets in PAS have lower risk for allergic transfusion reactions with equivalent clinical efficacy for controlling bleeding. Aim: The aim of this study is to evaluate the clinical and laboratory efficacy of PAS-platelets. Materials and Methods: A total of 1674 single donor platelet (SDP) were collected in PAS in the month of June to September 2016 by different apheresis systems. The quality control tests were done on 356 units in 4 months. Total number of SDP were processed with Amicus device (n = 232), Trima Accel (n = 84), and MCS+ (n = 40). The parameters analyzed were antibody titer of anti-A and anti-B, volume, platelet count, pH, bacterial contamination, and reporting of adverse transfusion reaction. Antibody titers were checked by tube technique, and platelet counts were checked by hematology analyzer Sysmex poch 100i. The swirling was checked manually, and pH was checked with pH strips. Results: Out of 356, 164 units were O group, 113 units were B group, 68 units were of A group, and the remaining 11 units were of AB Group. Anti-A and anti-B titer was significantly reduced in PAS-SDP and found 1:32 or less for all the units. All the units found negative for bacterial contamination. No transfusion reaction was reported of the units transfused. All other quality parameters for platelets also found satisfactory after implementing the additive solution. Conclusion: The ABO antibody titers were significantly reduced after addition of PAS. This facilitates the ABO incompatible SDP transfusion and helps in inventory management. The risk of allergic transfusion reaction decreases after reducing the amount of plasma from SDP units. Using PAS-SDP certainly improve the inventory management for platelets with no compromise on clinical and laboratory efficacy.

Routinely, Immunohematology Reference Testing Center receives samples with blood group discrepancy, presence of allo/autoantibodies, positive direct antiglobulin test (DAT), etc. We are presenting a case in which we not only resolved blood group discrepancy but also identified multiple alloantibodies reacting at different phases. A tricenarian female patient was diagnosed with chronic anemia with hemoglobin level below 7 g/dl. The patient had a history of blood transfusion and pregnancy as well. On blood grouping, the patient's forward grouping was “AB” and reverse was “O.” Indirect antiglobulin test was found to be positive while DAT and autocontrol were negative. After complete investigation, patient blood group was confirmed to be subgroup of AB along with anti-A1 antibody. Furthermore, a cold-reacting alloantibody with high thermal amplitude was detected along with one warm-reacting alloantibody.