Hasil untuk "Diseases of the blood and blood-forming organs"

LU Fang, MO Huihui, SU Wujin et al.

[Objective] To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. [Methods] HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. [Results] Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. [Conclusion] The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.

Daniel Aguilar-Hidalgo, Joel Ostblom, M Mona Siu et al.

The emergence of spatial patterns and organized growth is a hallmark of developing tissues. While symmetry-breaking and scaling laws govern these processes, how cells coordinate spatial patterning with size regulation remains unclear. Here, we combine quantitative imaging, a Turing activator-repressor model with self-organized reactive boundaries, and in vitro models of early mouse development to study mesodermal pattern formation in two-dimensional (2D) gastruloids. We show that colony size dictates symmetry: small colonies (radius approximately 100 micrometers) spontaneously break symmetry, while larger ones remain centro-symmetric, consistent with size-dependent positional information and model predictions. The mesodermal domain area scales robustly with colony size following a power law, independent of cell density, indicating that cells sense and respond to gastruloid size. Time-lapse imaging reveals a biphasic growth law: an early power-law expansion followed by exponential arrest, marking a dynamical phase transition. These dynamics, conserved across sizes, reflect features of criticality seen in physical systems, where self-organization, scaling, and boundary feedback converge. Our findings uncover a minimal mechanism for size-dependent pattern formation and growth control. This framework enables quantitative investigation of symmetry-breaking and scaling in self-organizing tissues, offering insights into the physical principles underlying multicellular organization.

André Baruchel, Karsten Nysom, Hyoung Jin Kang et al.

Abstract Children with relapsed acute leukemia have a poor prognosis; current relapse treatments are toxic, and novel treatments are needed. The anti‐CD38 antibody isatuximab is approved for relapsed‐refractory multiple myeloma in adults. We present results of the ISAKIDS study (NCT03860844) investigating isatuximab in children with relapsed‐refractory acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML). This Phase 2, single‐arm, multicenter, open‐label study enrolled children aged 28 days to <18 years. Patients received isatuximab 20 mg/kg induction on Day 1, then weekly for 5 weeks (ALL) or 3 weeks (AML). Standard salvage chemotherapy was added on Day 8. Participants showing possible response could receive consolidation with every‐other‐week isatuximab (two doses) plus chemotherapy (T‐ALL, B‐ALL) or optional second induction (AML). The primary endpoint was the complete response (CR) rate (proportion with CR or CR with incomplete peripheral recovery [CRi]). CR/CRi was observed for 32/59 (54%) evaluable patients (B‐ALL, 13/25 [52%]; T‐ALL, 5/11 [45%]; and AML, 14/23 [61%]). Secondary endpoints included minimal residual disease (MRD) status and safety. Based on local and central analysis, 56% (18/32) of CR/CRi patients reached MRD negativity using 10−4 sensitivity threshold for ALL and 10−3 sensitivity threshold for AML. One event of fatal cytokine release syndrome was reported in a patient with a high baseline white blood cell count, leading to trial adaptation. The toxicity of isatuximab with chemotherapy was otherwise manageable. Despite initial evidence of efficacy of isatuximab combined with intensive chemotherapy, CR/CRi rates did not meet stringent prespecified criteria to proceed to ISAKIDS Stage 2 (≥60% [T‐ALL] and ≥70% [B‐ALL and AML]).

Sofía Estrada-Nieves, David G. García-Gutiérrez, Rosalía Reynoso-Camacho et al.

<b>Background/Objectives</b>: Obesity-related insulin resistance leads to the development of type 2 diabetes mellitus (T2DM); however, the pathophysiology of these metabolic alterations remains incompletely understood. This study aimed to characterize the lipidomic alterations during obesity–insulin resistance–T2DM progression in a high-sugar diet (HSD) model. <b>Methods</b>: Fruit flies were fed either a standard diet (SD) or an HSD and monitored across a 14-day period. Metabolic phenotyping and lipidomic profiling were conducted during the experiment. <b>Results</b>: After two days of HSD, fruit flies exhibited an obesity phenotype (50% increase in triglyceride content) and insulin resistance (hyperglycemia and insulin overexpression), progressing to an early T2DM-like state (increased triglycerides, hyperglycemia, and normal insulin expression) from days 4 to 6, and finally to a late T2DM-like phenotype (increased triglycerides, hyperglycemia, and insulin down-regulation) from days 8 to 14. Multivariate analyses indicated an altered lipidome profile in HSD-fed fruit flies from day 2 until the end of the experiment. Fatty acids and phosphatidylethanolamines (PEs) containing 16:0, 16:1, and 18:1 acyl chains were significantly altered during the development of obesity-related insulin resistance and early T2DM-like state (days 2 to 6); whereas palmitic acid and oleic acid-LysoPE alterations were associated with the onset and progression of obesity-related T2DM-like state (days 4 to 14). <b>Conclusions</b>: The progression from obesity-related insulin resistance to a T2DM-like state in an HSD-fed D. melanogaster model is accompanied by distinct lipidomic signatures involving 16- and 18-carbon fatty acid derivatives. These findings provide insight into potential biomarkers and mechanistic pathways in the early pathogenesis of T2DM.

Stacey A. Fedewa, Leonard A. Valentino, Andee Koo et al.

Background: Drug trials are vital to establish safe and effective treatments for congenital hemophilia, a bleeding disorder that affects about 800,000 males worldwide. The global distribution of hemophilia drug trials (HDTs) and their alignment with hemophilia care is unknown. Objectives: This study aimed to evaluate the global distribution of HDTs and its association with hemophilia care. Methods: In this cross-sectional study, HDTs conducted between 2007 and 2022 were selected from the clinicaltrials.gov database. The density of trials per 1000 expected males with hemophilia (eMwH) was assessed according to hemophilia care measures (factor VIII and IX utilization per 1000 eMwH) derived from World Federation of Hemophilia data. Results: Among 124 trials, 55 countries were represented, with an average of 7.9 countries per trial. Most HDT sites were in high-income (74.4%) or upper middle (20.1%)–income countries. The number of sites in lower-middle–income countries doubled, from 12 in 2007-2011 to 30 in 2017-2022—a nonsignificant increase from 5.8% to 7.0% (P = .53). Factor utilization was substantially reduced in lower-middle (0.4 international units [IUs] per 1000 eMwH) and upper middle (2.8 IUs per 1000 eMwH) compared with high (6.8 IUs per 1000 eMwH) income countries. HDT density was moderately correlated with factor usage (r = 0.436; P ≤ .001). Conclusion: Most HDT sites were located in high-income countries, although a substantial proportion were in upper middle–income countries. A small but increasing number of trials were conducted in lower-middle–income countries, where factor usage is relatively low. This study provides evidence on the global distribution of HDT and raises questions regarding the generalizability, barriers, opportunities, and ethics of trials for a rare bleeding disorder.

Maksuda Akter, Rabea Khatun, Md Manowarul Islam

Acute lymphoblastic leukemia (ALL) is the most malignant form of leukemia and the most common cancer in adults and children. Traditionally, leukemia is diagnosed by analyzing blood and bone marrow smears under a microscope, with additional cytochemical tests for confirmation. However, these methods are expensive, time consuming, and highly dependent on expert knowledge. In recent years, deep learning, particularly Convolutional Neural Networks (CNNs), has provided advanced methods for classifying microscopic smear images, aiding in the detection of leukemic cells. These approaches are quick, cost effective, and not subject to human bias. However, most methods lack the ability to quantify uncertainty, which could lead to critical misdiagnoses. In this research, hybrid deep learning models (InceptionV3-GRU, EfficientNetB3-GRU, MobileNetV2-GRU) were implemented to classify ALL. Bayesian optimization was used to fine tune the model's hyperparameters and improve its performance. Additionally, Deep Ensemble uncertainty quantification was applied to address uncertainty during leukemia image classification. The proposed models were trained on the publicly available datasets ALL-IDB1 and ALL-IDB2. Their results were then aggregated at the score level using the sum rule. The parallel architecture used in these models offers a high level of confidence in differentiating between ALL and non-ALL cases. The proposed method achieved a remarkable detection accuracy rate of 100% on the ALL-IDB1 dataset, 98.07% on the ALL-IDB2 dataset, and 98.64% on the combined dataset, demonstrating its potential for accurate and reliable leukemia diagnosis.

Xuanzhong Chen, Ye Jin, Xiaohao Mao et al.

Rare diseases, despite their low individual incidence, collectively impact around 300 million people worldwide due to the vast number of diseases. The involvement of multiple organs and systems, and the shortage of specialized doctors with relevant experience, make diagnosing and treating rare diseases more challenging than common diseases. Recently, agents powered by large language models (LLMs) have demonstrated notable applications across various domains. In the medical field, some agent methods have outperformed direct prompts in question-answering tasks from medical examinations. However, current agent frameworks are not well-adapted to real-world clinical scenarios, especially those involving the complex demands of rare diseases. To bridge this gap, we introduce RareAgents, the first LLM-driven multi-disciplinary team decision-support tool designed specifically for the complex clinical context of rare diseases. RareAgents integrates advanced Multidisciplinary Team (MDT) coordination, memory mechanisms, and medical tools utilization, leveraging Llama-3.1-8B/70B as the base model. Experimental results show that RareAgents outperforms state-of-the-art domain-specific models, GPT-4o, and current agent frameworks in diagnosis and treatment for rare diseases. Furthermore, we contribute a novel rare disease dataset, MIMIC-IV-Ext-Rare, to facilitate further research in this field.

Volodimyr A. Ushenko, Anton Sdobnov, Liliya Trifonyuk et al.

We introduce a 3D Mueller Matrix (MM) image reconstruction technique using digital holographic approach for the layer-by-layer profiling thin films with polycrystalline structures, like dehydrated blood smears. The proposed method effectively extracts optical anisotropy parameters for a detailed quantitative analysis. The investigation revealed the method sensitivity to subtle changes in optical anisotropy properties resulting from alterations in the quaternary and tertiary structures of blood proteins, leading to disturbances in crystallization structures at the macro level at the very early stage of a disease. Spatial distributions of linear and circular birefringence and dichroism are analyzed in partially depolarizing polycrystalline blood films obtained from healthy tissues and cancerous prostate tissues at various stages of adenocarcinoma. Changes in the values of the 1st to 4th order statistical moments, characterizing the distributions of optical anisotropy in different phase sections of the smear volumes, are observed and quantified. Comparative analysis of optical anisotropy distributions from healthy patients highlighted the 3rd and 4th order statistical moments for linear and circular birefringence and dichroism as the most promising for diagnostic purposes. We achieved an excellent accuracy (>90%) for early cancer diagnosis and differentiation of its stages, demonstrating the techniques significant potential for rapid and accurate definitive cancer diagnosis compared to existing screening approaches.

Yunan LI, Jianxin ZHEN, Shuang LIANG et al.

Objective To establish a method for qualitative detection of the presence or absence of all KIR genes by quantitative polymerase chain reaction(Q-PCR). Methods Based on the polymorphism of high-resolution level KIR alleles in Chinese population and the IPD-KIR database, KIR gene-specific primers were designed to amplify all the 16 KIR genes and 2DS4-Normal and 2DS4-Deleted subtypes by Q-PCR. Meanwhile, one negative control and one positive control specific amplifying human growth hormone (HGH) gene fragment were set to monitor the false positive and false negative results in PCR amplification, respectively. A total of 302 samples with known KIR genotype previously identified by KIR PCR-SSP commercial kit were randomly selected for blind inspection to verify the reliability of KIR Q-PCR method established by authors. Results The results of 300 samples detected by our KIR Q-PCR method were consistent with the known results, but two samples showed inconsistent results. One sample was negative for 2DS5 by Q-PCR but positive by PCR-SSP, another sample was positive for 2DS1 by Q-PCR but negative by PCR-SSP. The two doubtful samples were genotyped by sequencing-based typing (PCR-SBT) for 2DS5 and 2DS1, respectively. PCR-SBT results confirmed that the results of Q-PCR test was correct. Conclusion The KIR Q-PCR method established in this paper can provide accurate and reliable results for testing the presence or absence of KIR genes.

Koushik Sivarama Krishnan, P. J. Joe Nikesh, Swathi Gnanasekar et al.

An innovative two-stage methodology for categorizing blood clot origins is presented in this paper, which is important for the diagnosis and treatment of ischemic stroke. First, a background classifier based on MobileNetV3 segments big whole-slide digital pathology images into numerous tiles to detect the presence of cellular material. After that, different pre-trained image classification algorithms are fine-tuned to determine the origin of blood clots. Due to complex blood flow dynamics and limitations in conventional imaging methods such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound, identifying the sources of blood clots is a challenging task. Although these techniques are useful for identifying blood clots, they are not very good at determining how they originated. To address these challenges, our method makes use of robust computer vision models that have been refined using information from whole-slide digital pathology images. Out of all the models tested, the PoolFormer \cite{yu2022metaformer} performs better than the others, with 93.4\% accuracy, 93.4\% precision, 93.4\% recall, and 93.4\% F1-score. Moreover, it achieves the good weighted multi-class logarithmic loss (WMCLL) of 0.4361, which emphasizes how effective it is in this particular application. These encouraging findings suggest that our approach can successfully identify the origin of blood clots in a variety of vascular locations, potentially advancing ischemic stroke diagnosis and treatment approaches.

Mesfin Taye

Centrifugation is a commonly performed laboratory procedure that helps to separate blood cells such as $RBCs$, $WBCs$, and platelets from plasma or serum. Although centrifugation is a routine procedure in most medical laboratories, the factors that affect the efficacy of the centrifugation process have never been studied analytically. In this paper, we examine the effect of the centrifugation time on the efficacy of the centrifugation process by studying the dynamics of the blood cells via the well-known Langevin equation or equivalently, by solving the Fokker-Plank equation. Our result depicts that the speed of the centrifuge is one of the determinant factors concerning the efficacy of the centrifugation process. As the angular speed increases, the centrifugal force steps up and as result, the particles are forced to separate from the plasma or serum. The room temperature also considerably affects the dynamics of analyse during centrifugation. Most importantly, the generation of heat during centrifugation steps up the temperature within a centrifuge and as a result, not only the stability of the sample but also mobility of analyse is affected. We show that as the centrifuge temperature steps up, the velocity of the cells as well as the displacement of the cell in the fluid decreases. We then study the dynamics of the whole blood during capillary action where in this case the blood flows upward in a narrow space without the assistance of external forces. Previous investigations show that the height that the fluid rises increases as the surface tension steps up.

Yuchao He, Yongli Song, Yonghui Xia

This paper investigates the existence of periodic solutions in blood flow propagating through vessels with free boundary conditions via the bifurcation theory. It is rigorously proved that a local $C^1$-curve of small-amplitude periodic solutions is bifurcated. In contrast to previous studies on periodic flows that primarily focus on constant vorticity, our work emphasizes the bifurcation analysis of periodic solutions in blood flow with harmonic vorticity and external body forces. To utilize Crandall-Rabinowitz bifurcation theorem, the fundamental challenge lies in reducing a multiple variable-PDE subject to free boundary conditions to a system of one variable-ODE with fixed boundary conditions.

Xinyu Ye, Xin Huang, Xing Fu et al.

Abstract Background Bone metastasis is the leading cause of death in patients with prostate cancer (PCa) and currently has no effective treatment. Disseminated tumor cells in bone marrow often obtain new characteristics to cause therapy resistance and tumor recurrence. Thus, understanding the status of disseminated prostate cancer cells in bone marrow is crucial for developing a new treatment. Methods We analyzed the transcriptome of disseminated tumor cells from a single cell RNA-sequencing data of PCa bone metastases. We built a bone metastasis model through caudal artery injection of tumor cells, and sorted the tumor hybrid cells by flow cytometry. We performed multi-omics analysis, including transcriptomic, proteomic and phosphoproteomic analysis, to compare the difference between the tumor hybrid cells and parental cells. In vivo experiments were performed to analyze the tumor growth rate, metastatic and tumorigenic potential, drug and radiation sensitivity in hybrid cells. Single cell RNA-sequencing and CyTOF were performed to analyze the impact of hybrid cells on tumor microenvironment. Results Here, we identified a unique cluster of cancer cells in PCa bone metastases, which expressed myeloid cell markers and showed a significant change in pathways related to immune regulation and tumor progression. We found that cell fusion between disseminated tumor cells and bone marrow cells can be source of these myeloid-like tumor cells. Multi-omics showed the pathways related to cell adhesion and proliferation, such as focal adhesion, tight junction, DNA replication, and cell cycle, were most significantly changed in these hybrid cells. In vivo experiment showed hybrid cells had a significantly increased proliferative rate, and metastatic potential. Single cell RNA-sequencing and CyTOF showed tumor-associated neutrophils/monocytes/macrophages were highly enriched in hybrid cells-induced tumor microenvironment with a higher immunosuppressive capacity. Otherwise, the hybrid cells showed an enhanced EMT phenotype with higher tumorigenicity, and were resistant to docetaxel and ferroptosis, but sensitive to radiotherapy. Conclusion Taken together, our data demonstrate that spontaneous cell fusion in bone marrow can generate myeloid-like tumor hybrid cells that promote the progression of bone metastasis, and these unique population of disseminated tumor cells can provide a potential therapeutic target for PCa bone metastasis.

Daiki Mukai, Naonori Harada, Ikumi Shibano et al.

Zhenyu Liu, Peipei Xu, Ying Du et al.

Maxx Richard Rahman, Jacob Bejder, Thomas Christian Bonne et al.

Sports officials around the world are facing incredible challenges due to the unfair means of practices performed by the athletes to improve their performance in the game. It includes the intake of hormonal based drugs or transfusion of blood to increase their strength and the result of their training. However, the current direct test of detection of these cases includes the laboratory-based method, which is limited because of the cost factors, availability of medical experts, etc. This leads us to seek for indirect tests. With the growing interest of Artificial Intelligence in healthcare, it is important to propose an algorithm based on blood parameters to improve decision making. In this paper, we proposed a statistical and machine learning-based approach to identify the presence of doping substance rhEPO in blood samples.

A. Coclite, G. Pascazio, M. D. de Tullio et al.

In vascular targeted therapies, blood-borne carriers should realize sustained drug release from the luminal side towards the diseased tissue. In this context, such carriers are required to firmly adhere to the vessel walls for a sufficient period of time while resisting force perturbations induced by the blood flow and circulating cells. Here, a hybrid computational model, combining a Lattice Boltzmann (LBM) and Immersed Boundary Methods (IBM), is proposed for predicting the strength of adhesion of particles in narrow capillaries (7.5 $μ\mathrm{m})$ traversed by blood cells. While flowing down the capillary, globular and biconcave deformable cells ( $7 μ\mathrm{m}$ ) encounter $2 μ\mathrm{m}$ discoidal particles, adhering to the vessel walls. Particles present aspect ratios ranging from $0.25$ to $1.0$ and a mechanical stiffness varying from rigid $(\mathrm{Ca}=0)$ to soft $\left(\mathrm{Ca}=10^{-3}\right)$. Cell-particle interactions are quantitatively predicted over time via three independent parameters: the cell membrane stretching $δp$; the cell-to-particle distance $r$, and the number of engaged ligand-receptor bonds $N_{\mathrm{L}}$.

Andrea Duminuco, Calogero Vetro, Cinzia Maugeri et al.

Infections occurring in immunocompromised patients after intensive chemotherapy are often difficult to eradicate and are capable of even being fatal. New emergent and dangerous drug-resistant micro-organisms are likely to appear in these specific scenarios. Clinical features mainly include progressive pneumonia, bacteriemia/fungemia, or extrapulmonary dissemination among infections. The treatment of these microorganisms is still an open challenge since there is a lack of clear treatment guidelines. Indeed, infections from these microorganisms can lead to a rapidly fatal clinical course in immunocompromised patients, especially those who have acute leukemia. We describe the case of a young patient with acute myeloid leukemia who contracted an infection from <i>Saprochaete capitata</i> during post-chemotherapy aplasia.

Wenji Sun, Jiafeng Zhang, Aakash Shah et al.

AbstractObjectiveLeukocytes play an important role in the body's immune system. The aim of this study was to assess alterations in neutrophil phenotype and function in pump‐assisted circulation in vitro.MethodsHuman blood was circulated for four hours in three circulatory flow loops with a CentriMag blood pump operated at a flow of 4.5 L/min at three rotational speeds (2100, 2800, and 4000 rpm), against three pressure heads (75, 150, and 350 mm Hg), respectively. Blood samples were collected hourly for analyses of neutrophil activation state (Mac‐1, CD62L, CD162), neutrophil reactive oxygen species (ROS) production, apoptosis, and neutrophil phagocytosis.ResultsActivated neutrophils indicated by both Mac‐1 expression and decreased surface expression of CD62L and CD162 receptors increased with time in three loops. The highest level of neutrophil activation was observed in the loop with the highest rotational speed. Platelet‐neutrophil aggregates (PNAs) progressively increased in two loops with lower rotational speeds. PNAs peaked at one hour after circulation and decreased subsequently in the loop with the highest rotational speed. Neutrophil ROS production dramatically increased at one hour after circulation and decreased subsequently in all three loops with similar levels and trends. Apoptotic neutrophils increased with time in all three loops. Neutrophil phagocytosis capacity in three loops initially elevated at one hour after circulation and decreased subsequently. Apoptosis and altered phagocytosis were dependent on rotational speed.ConclusionsOur study revealed that the pump‐assisted circulation induced neutrophil activation, apoptosis, and functional impairment. The alterations were strongly associated with pump operating condition and duration.