Search Results (61)

Background/Objectives: Red blood cell (RBC) alloimmunization is a significant challenge in transfusion medicine, particularly among transfusion-dependent patients, such as those with thalassemia. It arises from the production of antibodies against non-self RBC antigens and can lead to complications like hemolytic transfusion reactions. This study aimed to evaluate the prevalence, specificity, and clinical implications of RBC alloimmunization at the University Clinical Center of Serbia (UCCS), emphasizing transfusion-dependent populations. Methods: This retrospective study analyzed 27,530 transfusion records at UCCS between January 2023 and January 2024. Pre-transfusion testing included ABO and RhD typing, irregular antibody screening, and crossmatching. Data from 630 patients with positive antibody screening were reviewed. Alloantibody specificity was determined using indirect antiglobulin tests and advanced phenotyping methods. Results: Among 27,530 patients, 630 (2.29%) tested positive for irregular antibodies, predominantly males (57.14%) with a mean age of 49.6 years. Alloantibodies were detected in 70.47% of cases, most commonly targeting Rh (53.35%) and Kell (17.15%) systems. Anti-E (27.93%) and anti-D (18.02%) were the most frequent antibodies. Multiple alloantibodies were identified in 18.41% of patients, posing challenges for blood compatibility. In a total of 495 patients with thalassemia, antibodies were found in 9.69%. Alloimmunization was significantly associated with higher numbers of transfusions and pregnancies (p < 0.05). Conclusions: Our findings indicate that alloimmunization is predominantly associated with Rh and Kell antigens, suggesting that implementing targeted antigen matching may reduce the frequency of alloimmunization. While our study does not directly assess the impact of genotypic matching, the prior literature supports its role in enhancing transfusion safety, particularly for high-risk populations like thalassemia patients. Full article

The Human Leukocyte Antigen (HLA) system forms the central part of the immune system and is crucial in the recognition and elimination of “non-self” antigens. While this role of the HLA system is essential in the effective defense of the organism against pathogens, it is undesirable in organ and tissue transplantation because it enables the recognition of mismatched HLA molecules of the donor as being foreign and stimulates the graft rejection reaction. Organ transplantation involves the introduction of antigens that are more or less mismatched to the recipient; therefore, in order to achieve the best possible match in the HLA system between the recipient and the donor, a whole series of immunogenetic tests is performed, including crossmatching (XM). If performed before kidney transplantation, it represents the final in vitro test to rule out the presence of donor-specific antibodies, which may cause graft rejection and which may not have been detected by earlier serum screening. The beginning of XM was marked by the complement-dependent cytotoxicity (CDC) method developed by Terasaki and colleagues in 1964. Later, as a result of advances in technology and the need for methods that overcome the limitations of CDC, flow cytometry and Luminex XM assays were developed. The introduction of solid-phase technology brought a new dimension to the detection of low-level HLA antibodies and the determination of their specificities, which enabled the development and implementation of the virtual XM test (vXM). It is an in silico test that assesses the immunological match between the recipient and the organ donor based on the analysis of the specificity of the antibodies present in the recipient’s serum and the HLA typing of the organ donor. Each method has its own advantages and limitations, which are described below and need to be taken into account, considering their significant impact on clinical application in kidney transplantation. Full article

In this paper, we address the challenge of fingerprint liveness detection by proposing a dual pre-trained model approach that combines VGG16 and ResNet50 architectures. While existing methods often rely on a single feature extraction model, they may struggle with generalization across diverse spoofing materials and sensor types. To overcome this limitation, our approach leverages the high-resolution feature extraction of VGG16 and the deep layer architecture of ResNet50 to capture a more comprehensive range of features for improved spoof detection. The proposed approach integrates these two models by concatenating their extracted features, which are then used to classify the captured fingerprint as live or spoofed. Evaluated on the Livedet2013 and Livedet2015 datasets, our method achieves state-of-the-art performance, with an accuracy of 99.72% on Livedet2013, surpassing existing methods like the Gram model (98.95%) and Pre-trained CNN (98.45%). On Livedet2015, our method achieves an average accuracy of 96.32%, outperforming several state-of-the-art models, including CNN (95.27%) and LivDet 2015 (95.39%). Error rate analysis reveals consistently low Bonafide Presentation Classification Error Rate (BPCER) scores with 0.28% on LivDet 2013 and 1.45% on LivDet 2015. Similarly, the Attack Presentation Classification Error Rate (APCER) remains low at 0.35% on LivDet 2013 and 3.68% on LivDet 2015. However, higher APCER values are observed for unknown spoof materials, particularly in the Crossmatch subset of Livedet2015, where the APCER rises to 8.12%. These findings highlight the robustness and adaptability of our simple dual-model framework while identifying areas for further optimization in handling unseen spoof materials. Full article

Introduction: Renal transplantation ensures particular advantages for patients with end-stage kidney disease. However, in some cases, early complications may result in allograft dysfunction, which can ultimately lead to the loss of the graft. Creatinine is a poor biomarker for kidney injury due principally to its inability to help diagnose early acute renal failure and complete inability to help differentiate among its various causes. Different urinary and serum proteins have been intensively investigated as possible biomarkers in this setting. We focused on emerging serum biomarkers such as kidney injury molecule 1 (KIM-1) on a cohort of grafted patients. The motivation of this study was to analyze a predictive biological marker in comparison with standard markers for the evaluation of renal function, with the aim of observing if there are statistically significant differences regarding the performance and promptness of its increase compared to the current monitoring methods in order to improve graft survival, quality of life, and overall patient prognosis. Patients and Methods: We included 21 patients who had their first kidney transplantation (8 females, 13 males), with a follow-up period from transplantation of 3.14 years, without prior immunization, having complete HLA typing and a negative cross-match test before transplantation. We determined serum creatinine and KIM-1 in the whole cohort at the time of the enrollment in the study. Results: The mean creatinine value was 0.89 mg/dL ± 0.33. The mean value for KIM-1 was 13.56 +/− 21.52 in the Tx group vs. 5.91 +/− 3.26 in the control group with a p-value of 0.06. We defined patients at low risk (LR) of graft loss (serum creatinine < 0.9 mg/dL) and those at high risk (HR) (serum creatinine > 0.91 mg/dL). The mean values for KIM-1 were 6.09 +/− 1.67 in the LR vs. 21.77 +/− 29.71 in the HR group, with a p-value 0.01. Conclusions: There is a strong difference for KIM-1 at 24 h postTx between the two groups, showing a high correlation between KIM-1 and the predisposition of the graft dysfunction. Further studies are needed in order to clarify the utility of these novel biomarkers in the prediction of graft survival in renal transplantation patients. Full article

The physical origin of the Blazhko effect (BL), a phenomenon of a single or multiple periodic modulation(s) of the light curve, is under debate. Efficiently identifying and characterizing the BL is essential in understanding its origins and accounting for its effect on numerous applications of RRabs in the era of large time-domain surveys. In this study, we make use of Resnet 34, a well-known convolutional neural network (CNN) architecture, to identify RRab stars with BL from phased light curves collected from OGLE. Using reliably classified RRabs from frequency analysis to train, validate, and test our model, we show that our CNN method reaches accuracies up to 94%. We then applied our CNN method to some additional RRabs located in the Magellanic Cloud (MC) and the Galactic Bulge (GB), leading to the discovery of 113 and 2496 BL candidates, respectively. The identification accuracy for the MC Sample is estimated to be 91% after cross-matching the CNN classification results with those from frequency analysis. Similarly, the light-curve parameters of these classified BL/non-BL candidates by our CNN method from the GB region resemble those observed in the literature, confirming the reliability of our CNN classifications. Our CNN method is subject to issues related to light-curve quality and sampling, but its overall reliance on light-curve quality is comparable to that of frequency analysis. Furthermore, we find that BL modulation could be primarily characterized by variations in light-curve structure. Full article

Red blood cell (RBC) alloimmunization and antibodies formation against non-self antigens on red cells may occur after blood transfusion, pregnancies or other exposures. The RBC alloimmunization rate varies from 2% to 6% according to recent studies. The antibody screen is performed to identify or confirm the presence of antibodies in patient’s serum or plasma, as a preoperative or pretransfusion test. The antibody identification process and major crossmatch are critical steps of risk management in transfusion medicine. The aim of this article is to describe a flow chart of the antibody identification. I report three educational examples of case studies associated with the negative direct antiglobulin test and clinically significant single and multiple alloantibodies using the gel method, Anti-M, Anti-c and Anti-E, Anti-Jka and Anti-s. Furthermore, I provide a critical analysis of the current literature on the topic. The flow chart of the antibody identification may simplify the process and possibly reduce errors in routine workflow. Full article

Fairness in peer review is of vital importance in academic activities. Current peer review systems focus on matching suitable experts with proposals but often ignore the existence of outliers. Previous research has shown that outlier scores in reviews could decrease the fairness of these systems. Therefore, outlier detection in peer review systems is essential for maintaining fairness. In this paper, we introduce a novel method that employs data-crossing analysis to detect outlier scores, aiming to improve the reliability of peer review processes. We utilize a confidential dataset from a review organization. Due to the inability to access ground truth scores, we systematically devise data-driven deviations from an estimated ground truth through data-crossing analysis. These deviations reveal inconsistencies and abnormal scoring behaviors of different reviewers. Subsequently, the review process is strengthened by providing a structured mechanism to identify and mitigate biases. Extensive experiments demonstrate its effectiveness in improving the accuracy and fairness of academic assessments, contributing to the broader application of AI-driven methodologies to achieve more reliable and equitable outcomes. Full article

Non-HLA antibodies against heterogeneous targets on endothelial cells have been associated with allograft injuries. The endothelial cell crossmatch (ECXM) is used in the detection of non-HLA antibodies but remains non-discriminatory for specific antibody identification. The primary objective of this study was to delineate the specific non-HLA antibody signatures associated with ECXM positivity and to determine the correlation of ECXM status and non-HLA antibody signatures on allograft health. Serum specimens from 25 lung transplant recipients (LTRs) and 13 renal transplant recipients (RTRs) were collected as part of clinical evaluation, and testing for angiotensin II receptor type 1 (AT1R) and donor-specific MHC class I chain-related gene A (MICA) antibodies and ECXM was performed. Remnant sera were tested for non-HLA antibodies using the LABScreen™ Autoantibody (LSAUT) Group 1, 2, and 3 kits (One Lambda, Inc., Los Angeles, CA, USA). In both cohorts, the concordance of AT1R and MICA together or individually with ECXM+ status was poor (<0.7), suggesting the presence of other unaccounted antibodies. Autoantibody profiling revealed three distinct clusters targeting fibrotic products, cytoskeletal proteins, and cell signaling molecules. A comparative analysis of ECXM+ and ECXM− specimens identified nine and five differentially expressed antibodies in the LTR and RTR cohorts, respectively. Employing machine learning techniques (variable importance, feature selection, ROC-AUC), we derived a five-antibody panel (TNFα, collagen V, CXCL11, GDNF, GAPDH) and a two-antibody panel (TNFα, CXCL9) that effectively discriminated between ECXM+ and ECXM− status in the LTR and RTR cohorts, respectively. Distinct antibody signatures were identified in LTR and RTR cohorts that correlated with ECXM+ status and were associated with allograft dysfunction. Full article

(1) Background: We aimed to investigate the outcomes of human leukocyte antigen (HLA)-incompatible transplantation for patients who received desensitization with intravenous immunoglobulins (IVIg), plasmapheresis, and rituximab. (2) Methods: A comprehensive search of multiple electronic databases to identify studies that utilized desensitization was conducted. The random-effects model was used to calculate the pooled rates and the 95% confidence interval (CI). (3) Results: A total of 1517 studies were initially identified. From these, 16 studies met the inclusion criteria, encompassing 459 patients, with a mean age of 45 years, of whom 40.8% were male. CDC crossmatch was positive in 68.3% (95% CI: 43.5–85.8; I2 87%), and 89.4% (95% CI: 53.4–98.4%; I2 89.8%) underwent living-donor transplantation. The 1-year graft survival pooled rate was 88.9% (95% CI: 84.8–92; I2 0%) and the 5-year graft survival rate was 86.1% (95% CI: 81.2–89.9; I2 0%). The 1-year patient survival rate was 94.2% (95% CI: 91–96.3; I2 0%), and the 5-year patient survival rate was 88.9% (95% CI: 83.5–92.7%; I2 7.7%). The rate of antibody-mediated rejection was 37.7% (95% CI: 25–52.3; I2 80.3%), and the rate of acute cell-mediated rejection was 15.1% (95% CI: 9.1–24; I2 55%). (4) Conclusions: Graft and patient survival are favorable in highly sensitized patients who undergo desensitization using IVIg, plasmapheresis, and rituximab for HLA-incompatible transplantation. Full article

Background: The morbidity and mortality from AL amyloidosis has significantly improved with the development of novel treatments. Daratumumab is a highly effective treatment for AL amyloidosis, but end-stage kidney disease is a common complication of this condition. Kidney transplantation is the ideal form of renal replacement therapy but has historically been contraindicated in this group of patients. Methods: Given the improved survival and better treatments of both conditions, we argue that it is time to reconsider transplanting these patients. Results: We report our experience of transplanting four patients with AL amyloidosis who had achieved stable remission through treatment with daratumumab. Conclusions: We highlight the key challenges involved and discuss important clinical issues for patients receiving daratumumab, particularly the difficulties with interpreting the crossmatch in light of daratumumab and immunoglobulin therapy interference. We also discuss the complexities involved in balancing the risks of infection, relapse, rejection, and immunosuppression in such patients. Full article

A pre-transfusion crossmatch test is crucial for ensuring safe blood transfusions by identifying the compatibility between donor and recipient blood samples. Conventional tube methods for crossmatching have limitations, including subjectivity in result interpretation and the potential for human error. In this study, we evaluated the diagnostic performance of a new crossmatch test using Microscanner C3, which can overcome these shortcomings. The crossmatch test results using the method were obtained in 323 clinical samples. The sensitivity, specificity, positive predictive value, negative predictive value, and concordance rate of the crossmatch test using Microscanner C3 were 98.20%, 100.00%, 100.00%, 98.11%, and 99.07%, respectively. The diagnostic performance of the new system offers a promising alternative to conventional tube methods for pre-transfusion crossmatch testing. Microscanner C3 could also increase the automation, standardization, and accuracy of crossmatch tests. The crossmatch test using Microscanner C3 is thought to increase the efficiency and reliability in identifying blood samples suitable for transfusion, thereby improving patient safety and optimizing the use of blood products in clinical settings. Full article

Histocompatibility testing is pivotal in any renal transplantation workup, aimed at enhancing prospective donor recipient compatibility and improving transplant outcomes. The evolution and advancement of histocompatibility testing, particularly HLA typing, have significantly improved its precision. This study outlines the historical progression from serologic to DNA-based HLA typing, emphasizing the role of HLA proteins in immune response. Anti-HLA antibodies, targeting HLA proteins, pose challenges in renal transplantation. Monitoring and managing these antibodies are critical for renal transplant success. Complement-dependent cytotoxicity crossmatch and flow cytometry crossmatch are essential techniques for assessing donor–recipient compatibility. Panel-reactive antibody assesses antibodies against a panel of donor antigens, often HLA. Higher PRA levels (percentage) complicate donor matching, requiring specialized protocols. Virtual crossmatch evaluates recipient anti-HLA antibodies against potential donors through synthetic beads. This approach predicts crossmatch outcomes by comparing antibody profiles, offering a valuable tool for the risk assessment of renal transplantation. Despite advancements, a comprehensive understanding of alloreactive immune responses requires a combination of assays, emphasizing the importance of a multifaceted approach in histocompatibility testing. This is an attempt to compile the relevant information, providing a basis for comparison in a clear and foundational format for histocompatibility testing laboratories. Full article

Background: Laparoscopic cholecystectomy is associated with a high safety profile. This study seeks to quantify the incidence of blood transfusion in both the elective and emergency settings, examine related patient outcomes, and investigate selection criteria for pre-operative Group and Save (G&S) sampling. Methods: A prospective multi-centre observational study was conducted to investigate patients undergoing either elective or emergency laparoscopic cholecystectomy in the UK between January 2020 and May 2021. Multivariate logistical regression models were used to identify patient factors associated with the risk of transfusion and explore outcomes linked to pre-operative G&S sampling. Results: This study comprised 959 patients, with 631 (65.8%) undergoing elective cholecystectomy and 328 (34.2%) undergoing emergency surgery. The median age was 48 years (range: 35–59), with 724 (75.5%) of the patients being female. Only five patients (0.5%) required blood transfusions, receiving an average of three units, with the first unit administered approximately six hours post-operatively. Among these cases, three patients (60%) had underlying haematological conditions. In adjusted models, male gender was significantly associated with the need for a blood transfusion (OR 11.31, p = 0.013), while the presence of a pre-operative Group and Save sample did not demonstrate any positive impact on patient outcomes. Conclusions: The incidence of blood transfusion following laparoscopic cholecystectomy is very low. Male gender and haematological conditions may present as independent risk factors. Pre-operative G&S sampling did not yield any positive impact on patient outcomes and could be safely excluded in both elective and emergency cases, although certain population subsets will warrant further consideration. Full article

Efficient night-time vessel detection is of significant importance for maritime traffic management, fishery activity monitoring, and environmental protection. With the advancement in object-detection approaches, the method of night-time vessel detection has gradually shifted from traditional threshold segmentation to deep learning that balances efficiency and accuracy. However, the restricted spatial resolution of night-time light (NTL) remote sensing data (e.g., VIIRS/DNB images) results in fewer discernible features and insufficient training performance when detecting vessels that are considered small targets. To address this, we establish an Enhanced Dense Nested-Attention Network (DNA-net) to improve the detection of small vessel targets under low-light conditions. This approach effectively integrates the original VIIRS/DNB, spike median index (SMI), and spike height index (SHI) images to maintain deep-level features and enhance feature extraction. On this basis, we performed vessel detection based on the Enhanced DNA-net using VIIRS/DNB images of the Japan Sea, the South China Sea, and the Java Sea. It is noteworthy that the VIIRS Boat Detection (VBD) observations and the Automatic Identification System (AIS) data were cross-matched as the actual status of the vessels (VBD-AIS). The results show that the proposed Enhanced DNA-net achieves significant improvements in the evaluation metrics (e.g., IOU, P_d, F_a, and MPD) compared to the original DNA-net, achieving performance of 87.81%, 96.72%, 5.42%, and 0.36 Wpx, respectively. Meanwhile, we validated the detection performance of Enhanced DNA-net and strong VBD detection against VBD-AIS, showing that the Enhanced DNA-net achieves 1% better accuracy than strong VBD detection. Full article

The precise ascertainment of stellar ages is pivotal for astrophysical research into stellar characteristics and galactic dynamics. To address the prevalent challenges of suboptimal accuracy in stellar age determination and limited proficiency in apprehending nonlinear dynamics, this study introduces an enhanced model for stellar age determination, amalgamating the Feedforward Neural Network (FFNN) with TabNet (termed FFNN–TabNet). The methodology commences with the acquisition of a stellar dataset via meticulous cross-matching. Subsequent advancements encompass refinements to the activation functions within TabNet, coupled with augmentations to the Attentive transformer module by incorporating an FFNN module. These enhancements substantially boost training efficiency and precision in age estimation while amplifying the model’s capability to decode complex nonlinear interactions. Leveraging Bayesian Optimization Algorithm (BOA) for hyperparameter fine-tuning further elevates the model’s efficiency. Comprehensive ablation and comparative analyses validate the model’s superior performance in stellar age determination, demonstrating marked enhancements in accuracy. The experiment also demonstrates an enhanced ability of the model to capture nonlinear relationships between features. Full article