[Exploration and practice of novel models of cellular therapy and hematopoietic stem cell transplantation].

Hematopoietic stem cell transplantation provides an effective cure for various hematological diseases, especially malignant hematological diseases, its treatment system has been continuously optimized, the source of donors has been expanding, the indications have been expanding, and the therapeutic effect has also made breakthroughs to a certain extent. At present, the status of hematopoietic stem cell transplantation technology in most hematological diseases is still unshakable, but the recurrence of the primary disease and complications related to hematopoietic stem cell transplantation are still two major clinical challenges that affect the long-term survival and quality of life of patients. Cell therapy represented by chimeric antigen receptor T (CAR-T) has made breakthrough progress in the treatment of refractory/recurrent B-cell malignancies. Compared with traditional drugs, cell therapy has unique in vivo metabolic characteristics, relying on immune specific recognition and the repair ability of stem cells. It is currently emerging in the treatment of blood tumors and the management of transplant complications. Multiple clinical studies have preliminarily demonstrated a new diagnostic and therapeutic model combining cell therapy with hematopoietic stem cell transplantation.

Investigation of HLA susceptibility alleles and genotypes with hematological disease among Chinese Han population.

Several genes involved in the pathogenesis have been identified, with the human leukocyte antigen (HLA) system playing an essential role. However, the relationship between HLA and a cluster of hematological diseases has received little attention in China. Blood samples (n = 123913) from 43568 patients and 80345 individuals without known pathology were genotyped for HLA class I and II using sequencing-based typing. We discovered that HLA-A*11:01, B*40:01, C*01:02, DQB1*03:01, and DRB1*09:01 were prevalent in China. Furthermore, three high-frequency alleles (DQB1*03:01, DQB1*06:02, and DRB1*15:01) were found to be hazardous in malignant hematologic diseases when compared to controls. In addition, for benign hematologic disorders, 7 high-frequency risk alleles (A*01:01, B*46:01, C*01:02, DQB1*03:03, DQB1*05:02, DRB1*09:01, and DRB1*14:54) and 8 high-frequency susceptible genotypes (A*11:01-A*11:01, B*46:01-B*58:01, B*46:01-B*46:01, C*01:02-C*03:04, DQB1*03:01-DQB1*05:02, DQB1*03:03-DQB1*06:01, DRB1*09:01-DRB1*15:01, and DRB1*14:54-DRB1*15:01) were observed. To summarize, our findings indicate the association between HLA alleles/genotypes and a variety of hematological disorders, which is critical for disease surveillance.

Characterizing morphological alterations in blood related disorders through Atomic Force Microscopy.

Atomic Force Microscopy (AFM) is a very flexible method that can create topographical images from a range of materials and image surfaces. Significantly, AFM has emerged as an invaluable tool for dissecting the morphology and biochemical aspects of body cells and tissues. The high-resolution imaging capabilities of AFM enable researchers to discern alterations in cell morphology and understand the underlying mechanisms of diseases. It contributes to understanding disease etiology and progression. In the context of this review, our focus will be directed towards elucidating the pivotal role of AFM in analysis of blood related disorders. Through detailed comparisons with normal cells, we delve into the alterations in size, shape, and surface characteristics induced by conditions such as cancer, diabetes, anaemia, and infections caused by pathogens. In essence, various work described in this article highlights to bridge the gap between traditional microscopy and in-depth analysis of blood-related pathologies, which in turn offers valuable perspectives for both research and clinical applications in the field.

[Hematologic Diseases and Neurological Complications].

Many hematologic diseases can be complicated by neurological symptoms during the disease course. Hematologic diseases can contribute to strokes and neuropathies; thus, neurologists should be aware of them. Recent reports have increased of neurological side effects associated with new anticancer therapies such as immune checkpoint inhibitors and chimeric antigen receptor-T cell therapy. The relationship between hematologic diseases and neurological complications is expected to become more prevalent.

Recognition of Genetic Conditions After Learning With Images Created Using Generative Artificial Intelligence.

Importance: The lack of standardized genetics training in pediatrics residencies, along with a shortage of medical geneticists, necessitates innovative educational approaches. Objective: To compare pediatric resident recognition of Kabuki syndrome (KS) and Noonan syndrome (NS) after 1 of 4 educational interventions, including generative artificial intelligence (AI) methods. Design, Setting, and Participants: This comparative effectiveness study used generative AI to create images of children with KS and NS. From October 1, 2022, to February 28, 2023, US pediatric residents were provided images through a web-based survey to assess whether these images helped them recognize genetic conditions. Interventions: Participants categorized 20 images after exposure to 1 of 4 educational interventions (text-only descriptions, real images, and 2 types of images created by generative AI). Main Outcomes and Measures: Associations between educational interventions with accuracy and self-reported confidence. Results: Of 2515 contacted pediatric residents, 106 and 102 completed the KS and NS surveys, respectively. For KS, the sensitivity of text description was 48.5% (128 of 264), which was not significantly different from random guessing (odds ratio [OR], 0.94; 95% CI, 0.69-1.29; P = .71). Sensitivity was thus compared for real images vs random guessing (60.3% [188 of 312]; OR, 1.52; 95% CI, 1.15-2.00; P = .003) and 2 types of generative AI images vs random guessing (57.0% [212 of 372]; OR, 1.32; 95% CI, 1.04-1.69; P = .02 and 59.6% [193 of 324]; OR, 1.47; 95% CI, 1.12-1.94; P = .006) (denominators differ according to survey responses). The sensitivity of the NS text-only description was 65.3% (196 of 300). Compared with text-only, the sensitivity of the real images was 74.3% (205 of 276; OR, 1.53; 95% CI, 1.08-2.18; P = .02), and the sensitivity of the 2 types of images created by generative AI was 68.0% (204 of 300; OR, 1.13; 95% CI, 0.77-1.66; P = .54) and 71.0% (247 of 328; OR, 1.30; 95% CI, 0.92-1.83; P = .14). For specificity, no intervention was statistically different from text only. After the interventions, the number of participants who reported being unsure about important diagnostic facial features decreased from 56 (52.8%) to 5 (7.6%) for KS (P < .001) and 25 (24.5%) to 4 (4.7%) for NS (P < .001). There was a significant association between confidence level and sensitivity for real and generated images. Conclusions and Relevance: In this study, real and generated images helped participants recognize KS and NS; real images appeared most helpful. Generated images were noninferior to real images and could serve an adjunctive role, particularly for rare conditions.

[Analysis of a case of Kabuki syndrome due to a novel variant of KMT2D gene].

OBJECTIVE: To report on a case of Kabuki syndrome (KS) due to a novel variant of KMT2D gene. METHODS: A child diagnosed with KS at the Fujian Children's Hospital on July 25, 2022 was selected as the study subject. Whole exome sequencing was carried out for the child and her parents. Candidate variant was validated by Sanger sequencing and bioinformatic analysis. RESULTS: The child, a 4-month-old female, had presented with distinctive facial features, growth retardation, cardiac malformations, horseshoe kidney, hypothyroidism, and recurrent aspiration pneumonia. Whole exome sequencing revealed that she has harbored a heterozygous c.6285dup (p.Lys2096Ter) variant of the KMT2D gene. Sanger sequencing confirmed that neither of her parents had carried the same variant. The variant was previously unreported and may result in a truncated protein and loss of an enzymatic activity region. The corresponding site of the variant is highly conserved. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was classified as pathogenic (PVS1+PS2+PM2_Supporting). CONCLUSION: The c.6285dup variant of the KMT2D gene probably underlay the KS in this child.

Serum cytokine profiles during engraftment syndrome and acute graft-versus-host disease in adult patients after hematopoietic stem cell transplantation.

BACKGROUND: The underlying biology of engraftment syndrome (ES) following allogeneic hematopoietic stem cell transplantation (HSCT) is not fully elucidated, and the extent of its overlap with acute graft-versus-host disease (aGvHD) remains unclear. In order to establish potential indicator to distinguish ES more accurately, we conducted a retrospective analysis of cytokine levels during HSCT. METHODS: A total of 121 consecutive adult patients who underwent HSCT were enrolled in this study. Blood samples for interleukin (IL)-2, IL-2R, IL-4, IL-5, IL-6, IL-8, IL-10, IL-1ß, IL-12p70, interferon (IFN)-γ, IFN-α, tumor necrosis factor alpha (TNF-α) and C-reactive protein CRP were regularly assessed after transplantation and during transplantation related adverse events. Additionally, the balance of naïve, central memory and effector memory of CD4+ and CD8+ was analyzed around 30 and 60 days after stem cell infusion, respectively. RESULTS: Thirty (24.79 %) and 33 (27.27 %) patients were diagnosed with ES and aGvHD, respectively. ES was characterized by a significant increase in level of IL-5, IL-6, IL-8 and sIL-2R, while aGvHD was associated with a significant upregulation of IL-6, IL-5, IL-10 and sIL-2R in the patients from grade I to grade IV. Notably, patients got much higher levels of IL-6, IL-5 and sIL-2R when developed to ES than to aGvHD. Moreover, a pronounced shift from naïve to memory cells, both in CD4+ and CD8+ subsets, was found in ES patients. CONCLUSIONS: These findings suggest that cytokine profiles could serve as potential indicators for detecting and differentiating ES and aGvHD, enabling timely clinical intervention. Prospective clinical trials involving larger, independent patient cohorts are required to validate these observations.

Morphological analysis of patellofemoral joint in haemophilic arthropathy: A case-control study.

INTRODUCTION: Knees affected by haemophilic arthropathy exhibit distinct differences in both bone morphology and soft tissue behaviour. This study aims to analyse the morphological characteristics of the distal femur and patellofemoral joint in patients with haemophilia in comparison to normal healthy population. MATERIAL AND METHODS: Study was conducted as pair-matched case-control study with 43 individuals in both the haemophilia group and the control group. Patellar luxation, patellar tilt (PT), length of the patella in both axis (pAP, pML), depth and angle of trochlear sulcus (SD, SA), lateral trochlear inclination (LTI), medial and lateral femoral facet length (mFL, LFL), intercondylar depth (ID), transepicondylar axis (TEA) and lateral condyle length (LCL) were assessed on knee MRI. Correlation between Pettersson score and measured variables were also analysed. RESULTS: PT was medial sided in 10 (23.2%) cases in haemophilic group. Mean values of pAP, pML, PT were significantly lower in haemophilia group (p < .001, p: .007, p = .001 respectively). There were no significant changes in SA (p = .628), SD (p = .340), LTI (p = .685), LFL (p = .241) and MFC-LFC (p = .770) whilst mFL was significantly longer in haemophilia group (p = .009). ID (p < .001), TEA (p = .007) and LCL (p = .001) were all shorter in haemophilia group. Pettersson score was inversely correlated with pAP, pML, ID, TEA, LCL, pML/SA and ID/LCL. CONCLUSION: Morphological changes in haemophilic arthropathy involve a smaller and medially-tilted patella, narrowed lateral condyle and transepicondylar axis, combined with reduced intercondylar depth. These alterations must keep in mind especially in pre- and intraoperative assessments for arthroplasty procedures.

IKAROS gain of function disease: Allogeneic hematopoietic cell transplantation experience and expanded clinical phenotypes.

IKAROS, encoded by IKZF1, is a tumor suppressor and a key hematopoietic transcription factor responsible for lymphoid and myeloid differentiation. IKZF1 mutations result in inborn errors of immunity presenting with increased susceptibility to infections, immune dysregulation, and malignancies. In particular, patients carrying IKZF1 gain-of-function (GOF) mutations mostly exhibit symptoms of immune dysregulation and polyclonal plasma cell proliferation. Herein, we describe seven new IKAROS GOF cases from two unrelated families, presenting with novel infectious, immune dysregulation and hematologic diseases. Two of the patients underwent allogeneic hematopoietic cell transplantation (HCT) due to poorly responsive complications. HCT was well-tolerated achieving full engraftment in both patients receiving reduced intensity, matched unrelated donor grafts, with no severe acute or chronic graft-vs-host-disease, and in remission from their diseases 2.5 and 4 years post-HCT, respectively. These results suggest that HCT is a valid and curative option in patients with IKAROS GOF disease and severe clinical manifestations.

Targeting neutrophil extracellular traps: A novel strategy in hematologic malignancies.

Neutrophil extracellular traps (NETs) have emerged as a critical factor in malignant hematologic disease pathogenesis. These structures, comprising DNA, histones, and cytoplasmic proteins, were initially recognized for their role in immune defense against microbial threats. Growing evidence suggests that NETs contribute to malignant cell progression and dissemination, representing a double-edged sword. However, there is a paucity of reports on its involvement in hematological disorders. A comprehensive understanding of the intricate relationship between malignant cells and NETs is necessary to explore effective therapeutic strategies. This review highlights NET formation and mechanisms underlying disease pathogenesis. Moreover, we discuss recent advancements in targeted inhibitor development for selective NET disruption, empowering precise design and efficacious therapeutic interventions for malignant hematologic diseases.

Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases.

Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this work, we present a comprehensive digital microscopy system that enables BMA analysis for cell type counting and differentiation in an efficient and objective manner. This system not only provides an accessible and simple method to digitize, store, and analyze BMA samples remotely but is also supported by an Artificial Intelligence (AI) pipeline that accelerates the differential cell counting process and reduces interobserver variability. It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.

Sex-specific difference in phenotype of Kabuki syndrome type 2 patients: a matched case-control study.

BACKGROUND: Kabuki syndrome (KS) is a monogenic disorder leading to special facial features, mental retardation, and multiple system malformations. Lysine demethylase 6A, (KDM6A, MIM*300128) is the pathogenic gene of Kabuki syndrome type 2 (KS2, MIM#300867), which accounts for only 5%-8% of KS. Previous studies suggested that female patients with KS2 may have a milder phenotype. METHOD: We summarized the phenotype and genotype of KS2 patients who were diagnosed in Shanghai Children's Medical Center since July 2017 and conducted a 1:3 matched case-control study according to age and sex to investigate sex-specific differences between patients with and without KS2. RESULTS: There were 12 KS2 cases in this study, and 8 of them matched with 24 controls. The intelligence quotient (IQ) score of the case group was significantly lower than that of the control group (P < 0.001). In addition, both the incidence of intellectual disability (ID) (IQ < 70) and moderate-to-severe ID (IQ < 55) were significantly higher in the case group than those in the control group. No sex-specific difference was found in the incidence of ID or moderate-to-severe ID between the female cases and female controls, whereas there was a significant difference between male cases and male controls. Furthermore, the rate of moderate-to-severe ID and congenital heart disease (CHD) was significantly higher in the male group than that in the female group. CONCLUSIONS: Our results showed that a sex-specific difference was exhibited in the clinical phenotypes of KS2 patients. The incidence of CHD was higher in male patients, and mental retardation was significantly impaired. However, the female patients' phenotype was mild.

RNA therapeutics for the treatment of blood disorders.

Blood disorders are defined as diseases related to the structure, function, and formation of blood cells. These diseases lead to increased years of life loss, reduced quality of life, and increased financial burden for social security systems around the world. Common blood disorder treatments such as using chemical drugs, organ transplants, or stem cell therapy have not yet approached the best goals, and treatment costs are also very high. RNA with a research history dating back several decades has emerged as a potential method to treat hematological diseases. A number of clinical trials have been conducted to pave the way for the use of RNA molecules to cure blood disorders. This novel approach takes advantage of regulatory mechanisms and the versatility of RNA-based oligonucleotides to target genes and cellular pathways involved in the pathogenesis of specific diseases. Despite positive results, currently, there is no RNA drug to treat blood-related diseases approved or marketed. Before the clinical adoption of RNA-based therapies, challenges such as safe delivery of RNA molecules to the target site and off-target effects of injected RNA in the body need to be addressed. In brief, RNA-based therapies open novel avenues for the treatment of hematological diseases, and clinical trials for approval and practical use of RNA-targeted are crucial.

A machine learning approach to identify groups of patients with hematological malignant disorders.

BACKGROUND AND OBJECTIVE: Vaccination against SARS-CoV-2 in immunocompromised patients with hematologic malignancies (HM) is crucial to reduce the severity of COVID-19. Despite vaccination efforts, over a third of HM patients remain unresponsive, increasing their risk of severe breakthrough infections. This study aims to leverage machine learning's adaptability to COVID-19 dynamics, efficiently selecting patient-specific features to enhance predictions and improve healthcare strategies. Highlighting the complex COVID-hematology connection, the focus is on interpretable machine learning to provide valuable insights to clinicians and biologists. METHODS: The study evaluated a dataset with 1166 patients with hematological diseases. The output was the achievement or non-achievement of a serological response after full COVID-19 vaccination. Various machine learning methods were applied, with the best model selected based on metrics such as the Area Under the Curve (AUC), Sensitivity, Specificity, and Matthew Correlation Coefficient (MCC). Individual SHAP values were obtained for the best model, and Principal Component Analysis (PCA) was applied to these values. The patient profiles were then analyzed within identified clusters. RESULTS: Support vector machine (SVM) emerged as the best-performing model. PCA applied to SVM-derived SHAP values resulted in four perfectly separated clusters. These clusters are characterized by the proportion of patients that generate antibodies (PPGA). Cluster 1, with the second-highest PPGA (69.91%), included patients with aggressive diseases and factors contributing to increased immunodeficiency. Cluster 2 had the lowest PPGA (33.3%), but the small sample size limited conclusive findings. Cluster 3, representing the majority of the population, exhibited a high rate of antibody generation (84.39%) and a better prognosis compared to cluster 1. Cluster 4, with a PPGA of 66.33%, included patients with B-cell non-Hodgkin's lymphoma on corticosteroid therapy. CONCLUSIONS: The methodology successfully identified four separate patient clusters using Machine Learning and Explainable AI (XAI). We then analyzed each cluster based on the percentage of HM patients who generated antibodies after COVID-19 vaccination. The study suggests the methodology's potential applicability to other diseases, highlighting the importance of interpretable ML in healthcare research and decision-making.

Characteristics of unexpected antibodies in patients with blood disorders: Evidence in Vietnam.

BACKGROUND: In Vietnam, a lack of evidence about the unexpected antibodies hinders the capabilities to prepare the necessary resources and personnel for treating patients with blood disorders. This study aimed to measure the rates of different unexpected antibodies in patients having blood orders in Vietnam. STUDY DESIGN AND METHODS: A cross-sectional study was conducted at the National Institute of Hematology - Blood Transfusion, Vietnam on 5608 patients with blood disorders. Information was obtained from the medical records, blood transfusion forms, screening test forms. RESULTS: The prevalence rate of unexpected antibodies in patients with haematological disorders was 9.3%. The most prevalent occurrence was the presence of an atypical antibody type, accounting for 61% of patients. The co-occurrence of this atypical antibody type and other types of antibodies was also observed, with the respective occurrence rates of 23.9%, 10.1%, 3.8%, and 1.2% for the combination of two, three, four, and five unexpected antibody types. The presence of one type of unexpected antibody was predominant, namely anti-E, accounting for the highest proportion (32.9%), followed by anti-Mia (18.4%). Among the 125 patients, the most frequently observed combination of abnormal antibodies was anti-E with anti-c (14.3%) and anti-E with anti-Mia (3.4%). Among the cohort of 53 patients exhibiting three types of unexpected antibodies, the most prevalent combination observed was anti-c, anti-E, and anti-Mia (5.7%). CONCLUSION: This study revealed a prevalence rate of 9.3% in the presence of unexpected antibodies in patients with blood disorders. The occurrence of individual unexpected antibodies surpasses that of coordinated antibodies.