Live sobre Fevereiro Laranja - cuidados com a leucemia

Exploring the lived experience of mothers of children with leukemia: a qualitative study from Iran.

BACKGROUND: Leukemia, as one of the most common pediatric cancers, has negatively affected many children around the world. Parents often experience increased feeling of distress shortly after being informed about their child's diagnosis. The distress experienced by parents can adversely affect various aspects of their life. This study aimed to develop an understanding of the lived experience of the mothers whose children suffer from leukemia in Shiraz, Iran. METHODS: This phenomenological study was performed from April to August 2023, and 10 people were selected as participants by purposive sampling. In-depth and semi-structured interviews were performed for collecting the data. RESULTS: The participants' lived experiences during their children's leukemia were classified into five main categories, namely behavioral problems, spiritual issues, psychological problems, issues related to treatment, and economic matters. CONCLUSION: Knowing the experiences of parents, especially mothers, in managing and planning for the care of these children seems essential.

ResNeXt-CC: a novel network based on cross-layer deep-feature fusion for white blood cell classification.

Accurate diagnosis of white blood cells from cytopathological images is a crucial step in evaluating leukaemia. In recent years, image classification methods based on fully convolutional networks have drawn extensive attention and achieved competitive performance in medical image classification. In this paper, we propose a white blood cell classification network called ResNeXt-CC for cytopathological images. First, we transform cytopathological images from the RGB color space to the HSV color space so as to precisely extract the texture features, color changes and other details of white blood cells. Second, since cell classification primarily relies on distinguishing local characteristics, we design a cross-layer deep-feature fusion module to enhance our ability to extract discriminative information. Third, the efficient attention mechanism based on the ECANet module is used to promote the feature extraction capability of cell details. Finally, we combine the modified softmax loss function and the central loss function to train the network, thereby effectively addressing the problem of class imbalance and improving the network performance. The experimental results on the C-NMC 2019 dataset show that our proposed method manifests obvious advantages over the existing classification methods, including ResNet-50, Inception-V3, Densenet121, VGG16, Cross ViT, Token-to-Token ViT, Deep ViT, and simple ViT about 5.5-20.43% accuracy, 3.6-23.56% F1-score, 3.5-25.71% AUROC and 8.1-36.98% specificity, respectively.

HLA-DM and HLA-DO interplay for the peptide editing of HLA class II in healthy tissues and leukemia.

HLA class II antigen presentation is modulated by the activity of the peptide editor HLA-DM and its antagonist HLA-DO, with their interplay controlling the peptide repertoires presented by normal and malignant cells. The role of these molecules in allogeneic hematopoietic cell transplantation (alloHCT) is poorly investigated. Balanced expression of HLA-DM and HLA-DO can influence the presentation of leukemia-associated antigens and peptides targeted by alloreactive T cells, therefore affecting both anti-leukemia immunity and the potential onset of Graft versus Host Disease. We leveraged on a large collection of bulk and single cell RNA sequencing data, available at different repositories, to comprehensively review the level and distribution of HLA-DM and HLA-DO in different cell types and tissues of the human body. The resulting expression atlas will help future investigations aiming to dissect the dual role of HLA class II peptide editing in alloHCT, and their potential impact on its clinical outcome.

Application of image recognition technology in pathological diagnosis of blood smears.

Traditional manual blood smear diagnosis methods are time-consuming and prone to errors, often relying heavily on the experience of clinical laboratory analysts for accuracy. As breakthroughs in key technologies such as neural networks and deep learning continue to drive digital transformation in the medical field, image recognition technology is increasingly being leveraged to enhance existing medical processes. In recent years, advancements in computer technology have led to improved efficiency in the identification of blood cells in blood smears through the use of image recognition technology. This paper provides a comprehensive summary of the methods and steps involved in utilizing image recognition algorithms for diagnosing diseases in blood smears, with a focus on malaria and leukemia. Furthermore, it offers a forward-looking research direction for the development of a comprehensive blood cell pathological detection system.

[Causes and characteristics of pre-engraftment mortality after allogeneic hematopoietic stem cell transplantation].

Objective: To analyze the causes and demographic characteristics of pre-engraftment mortality in patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) and investigate the risk factors and measures for preventing pre-engraftment mortality. Methods: A retrospective case analysis, involving a total of 7 427 patients who underwent allo-HSCT at Peking University People's Hospital between January 2016 and July 2023, was conducted. Results: Among the 7 427 patients who underwent allo-HSCT, 56 cases (0.75% ) experienced pre-engraftment mortality. The median time to death for these 56 patients was +7 (-3 to +38) days after stem cell infusion. The median times to death for patients with acute leukemia (AL), severe aplastic anemia (SAA), and myelodysplastic syndrome (MDS) were +11 (-1 to +38), +3 (-1 to +34), and +16 (-1 to +38) days, respectively (P=0.013). The main causes of pre-engraftment mortality were infection (39.3% ), cardiac toxicity (28.6% ), and intracranial hemorrhage (26.8% ). Infection was the most common cause of pre-engraftment mortality in patients with AL and MDS (55.0% and 60.0% ), whereas cardiac toxicity was predominantly observed in patients with SAA (71.4% ), with no cases in patients with AL and only one case in patients with MDS. Among patients who died from intracranial hemorrhage, 53.3% had severe infections. The median times to death for infection, cardiac toxicity, and intracranial hemorrhage was +11 (-1 to +38), +2.5 (-1 to +17), and +8 (-3 to +37) days, respectively (P<0.001) . Conclusions: Infection is the primary cause of pre-engraftment mortality in allo-HSCT, and severe cardiac toxicity leading to pre-engraftment mortality should be closely monitored in patients with SAA.

Evaluating the combined and individual cytotoxic effect of beauvericin, enniatin B and ochratoxin a on breast cancer cells, leukemia cells, and fresh peripheral blood mononuclear cells.

Beauvericin (BEA), Enniatin B (ENN B), and Ochratoxin A (OTA) are mycotoxins produced by fungi species. Their main effect on several organs and systems is associated with chronic exposure going from immunotoxicity, estrogenic disorders, and renal failure to cancer (in animals and humans). OTA belongs to Group 1 according to the International Agency for Research in Cancer (IARC) and it has legislated limited values; not happening for BEA nor ENN B. Exposure to mixtures of mycotoxins occurs through food intake in daily consumption. The aim of this study was to evaluate the implication of BEA, ENN B, and OTA individually and combined in producing cytotoxicity in cells for immunological studies and cancer cell lines (human leukemia cells (HL-60), fresh human peripheral blood mononuclear cells (PBMCs), and human breast cancer (MDA-MB-231) cells). Cells were treated for 4 h and 24 h at different concentrations of BEA, ENN B, and OTA, respectively. Viability assays were carried out by flow cytometry using DAPI (4',6-diamindino-2-phenylindole, dihydrochloride) as a viability dye and the potential effects of synergism, addition, and antagonism were assessed through the Chou and Talalay method. Individual OTA treatment exerted the greatest cytotoxicity for PBMC cells (IC50 0.5 µM) while ENN B for HL-60 (IC50 0.25 µM) and MDA-MB-231 (IC50 0.15 µM). In binary combination [ENN B + OTA] resulted in exerting the greatest cytotoxicity for HL-60 and MDA-MB-231 cells; while [BEA + OTA] in PBMC cells. The triple combination resulted in being highly cytotoxic for PBMC cells compared to HL-60 and MDA-MB-231 cells. In summary, PBMC cells were the most sensible cells for all three mycotoxins and the presence of OTA in any of the combinations had the greatest toxicity causing synergism as the most common cytotoxic effect.

Identification of Risk Factors for Relapse in Childhood Leukemia Using Penalized Semi-parametric Mixture Cure Competing Risks Model.

BACKGROUND: Leukemia is the most common childhood malignancy. Identifying prognostic factors of patient survival and relapse using more reliable statistical models instead of traditional variable selection methods such as stepwise regression is of great importance. The present study aimed to apply a penalized semi-parametric mixture cure model to identify the prognostic factors affecting short-term and long-term survival of childhood leukemia in the presence of competing risks. The outcome of interest in this study was time to relapse. Study Design: A retrospective cohort study. METHODS: A total of 178 patients (0‒15 years old) with leukemia participated in this study (September 1997 to September 2016, followed up to June 2021) at Golestan University of Medical Sciences, Iran. Demographic, clinical, and laboratory data were collected, and then a penalized semi-parametric mixture cure competing risk model with smoothly clipped absolute deviation (SCAD) and least absolute shrinkage and selection operator (LASSO) regularizations was used to analyze the data. RESULTS: Important prognostic factors of relapse patients selected by the SCAD regularization method were platelets (150000‒400000 vs.>400000; odds ratio=0.31) in the cure part and type of leukemia (ALL vs. AML, hazard ratio (HR)=0.08), mediastinal tumor (yes vs. no, HR=16.28), splenomegaly (yes vs. no; HR=2.94), in the latency part. In addition, significant prognostic factors of death identified by the SCAD regularization method included white blood cells (<4000 vs.>11000, HR=0.25) and rheumatoid arthritis signs (yes vs. no, HR=5.75) in the latency part. CONCLUSION: Several laboratory factors and clinical side effects were associated with relapse and death, which can be beneficial in treating the disease and predicting relapse and death time.

The Italian Consensus Conference on the role of rehabilitation for children and adolescents with leukemia, central nervous system tumors, and bone cancer, part 2: general principles for the rehabilitation treatment of motor function impairments.

In Italy, 1400 children and 800 adolescents are diagnosed with cancer every year. About 80% of them can be cured but are at high risk of experiencing severe side effects, many of which respond to rehabilitation treatment. Due to the paucity of literature on this topic, the Italian Association of Pediatric Hematology and Oncology organized a Consensus Conference on the role of rehabilitation of motor impairments in children/adolescents affected by leukemia, central nervous system tumors, and bone cancer to state recommendations to improve clinical practice. This paper includes the consensus on the rehabilitation of children and adolescents with these cancers.

CoTCoNet: An optimized coupled transformer-convolutional network with an adaptive graph reconstruction for leukemia detection.

BACKGROUND: Swift and accurate blood smear analyses are crucial for diagnosing leukemia and other hematological malignancies. However, manual leukocyte count and morphological evaluation remain time-consuming and prone to errors. Additionally, conventional image processing methods struggle to differentiate cells due to visual similarities between malignant and benign cell morphology. METHOD: In response to above challenges, we propose Coupled Transformer Convolutional Network (CoTCoNet) framework for leukemia classification. CoTCoNet integrates dual-feature extraction to capture long-range global features and fine-grained spatial patterns, facilitating the identification of complex hematological characteristics. Additionally, the framework employs a graph-based module to uncover hidden, biologically relevant features of leukocyte cells, along with a Population-based Meta-Heuristic Algorithm for feature selection and optimization. Furthermore, we introduce a novel combination of leukocyte segmentation and synthesis, which isolates relevant regions while augmenting the training dataset with realistic leukocyte samples. This strategy isolates relevant regions while augmenting the training data with realistic leukocyte samples, enhancing feature extraction, and addressing data scarcity without compromising data integrity. RESULTS: We evaluated CoTCoNet on a dataset of 16,982 annotated cells, achieving an accuracy of 0.9894 and an F1-Score of 0.9893. We tested CoTCoNet on four diverse, publicly available datasets (including those above) to assess generalizability. Results demonstrate a significant performance improvement over existing state-of-the-art approaches. CONCLUSIONS: CoTCoNet represents a significant advancement in leukemia classification, offering enhanced accuracy and efficiency compared to traditional methods. By incorporating explainable visualizations that closely align with cell annotations, the framework provides deeper insights into its decision-making process, further solidifying its potential in clinical settings.

Changes in skeletal muscle function during chemotherapy and related factors in patients with acute leukemia.

INTRODUCTION: Skeletal muscle function is an important prognostically relevant indicator in patients with acute leukemia (AL), but skeletal dysfunction during chemotherapy is not well understood. This study aimed to investigate the factors that influence changes in skeletal muscle function from before the start of chemotherapy to before allogeneic hematopoietic stem cell transplantation (allo-HSCT). METHODS: This was a retrospective cohort study that included 90 patients with AL who underwent chemotherapy before transplantation to perform allo-HSCT (men, 67.3%; median age, 53 years). The outcome measure was defined as changes in skeletal muscle function from before chemotherapy to before allo-HSCT, and was assessed by measuring the psoas muscle index (PMI) as skeletal muscle quantity and computed tomography values (CTV) as skeletal muscle quality using a computed tomography scanner. We examined the differences in PMI and CTV before chemotherapy and allo-HSCT, and the factors associated with changes in PMI. RESULT: The mean PMI for before chemotherapy and allo-HSCT were 4.6 ± 1.4 cm2/m2 and 4.0 ± 1.3 cm2/m2 and significant differences were observed (p < 0.001). However, the mean CTV before chemotherapy and allo-HSCT were 47.3 ± 4.5 HU and 47.4 ± 5.0 HU, respectively, and no significant differences were found (p = 0.798). In stepwise multiple regression analysis, age and sex were identified as factors related to changes in PMI (age, p = 0.019; sex, p = 0.001). CONCLUSION: We found that skeletal muscle quantity decreased during chemotherapy in patients with AL and was influenced by male sex and older age. TRIAL REGISTRATION NUMBER:   TRIAL REGISTRATION NUMBER: 34-096(11,243). Date of registration: September 11, 2023.

How I treat: Coronavirus disease 2019 in leukemic patients and hematopoietic cell transplant recipients.

Among immunocompromised hosts, leukemia patients, and hematopoietic cell transplant recipients are particularly vulnerable, facing challenges in balancing coronavirus disease 2019 (COVID-19) management with their underlying conditions. In this How I Treat article, we discuss how we approach severe acute respiratory syndrome coronavirus 2 infections in daily clinical practice, considering the existing body of literature and for topics where the available data are not sufficient to provide adequate guidance, we provide our opinion based on our clinical expertise and experience. Diagnostic approaches include nasopharyngeal swabs for polymerase chain reaction testing and chest computed tomography scans for symptomatic patients at risk of disease progression. Preventive measures involve strict infection control protocols and prioritizing vaccination for both patients and their families. Decisions regarding chemotherapy or hematopoietic cell transplantation in leukemia patients with COVID-19 require careful consideration of factors such as COVID-19 severity and treatment urgency. Treatment protocols include early initiation of antiviral therapy, with nirmatrelvir/ritonavir or remdesivir. For cases of prolonged viral shedding, distinguishing between viable and non-viable viruses remains challenging but is crucial for determining contagiousness and guiding management decisions. Overall, individualized approaches considering immune status, clinical presentation, and viral kinetics are essential for effectively managing COVID-19 in leukemia patients.

Healthcare provider's perceptions of bleeding in patients with acute leukaemia undergoing induction chemotherapy: A qualitative study.

BACKGROUND: Bleeding is a primary outcome for many transfusion-related trials in acute leukaemia (AL) patients, typically graded using the World Health Organisation (WHO) bleeding scale (clinically significant bleed (CSB) is ≥grade 2). This composite outcome fails to differentiate minor bleeds that may not be significant, poorly represents the total burden of bleeding and lacks input from healthcare providers (HCPs) and patients. As part of a multi-step project to create a better bleeding tool for trials, our objective was to identify HCPs' perspectives on the components of CSB in AL patients. STUDY DESIGN AND METHODS: Using qualitative description, we interviewed 19 physicians and nurses who care for AL patients undergoing induction chemotherapy. Participants were recruited from professional organisations, networks and social media. An inductive approach to conventional content analysis was used. RESULTS: HCPs identified features of CSB as the anatomical site of bleeding, amount of bleeding, need for intervention and changes in vital signs. Using these characteristics, bleeding events were categorised into three groups: clinically significant, could evolve into a CSB and not clinically significant. HCPs considered the patient's condition, bleeding history and clinical intuitions when deciding whether a bleed could escalate into serious bleeding. DISCUSSION: Using data from HCPs, we categorised bleeds as clinically significant, could evolve into a CSB, and not significant. A study of patients' perspectives on the importance of different kinds of bleeding is the next step to creating a bleeding definition that is informed by evidence, clinicians and patients.

Prediction of leukemia peptides using convolutional neural network and protein compositions.

Leukemia is a type of blood cell cancer that is in the bone marrow's blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances fast and chronic growth gradually which are further classified into lymphocytic and myeloid leukemias. This work evaluates a unique deep convolutional neural network (CNN) classifier that improves identification precision by carefully examining concatenated peptide patterns. The study uses leukemia protein expression for experiments supporting two different techniques including independence and applied cross-validation. In addition to CNN, multilayer perceptron (MLP), gated recurrent unit (GRU), and recurrent neural network (RNN) are applied. The experimental results show that the CNN model surpasses competitors with its outstanding predictability in independent and cross-validation testing applied on different features extracted from protein expressions such as amino acid composition (AAC) with a group of AAC (GAAC), tripeptide composition (TPC) with a group of TPC (GTPC), and dipeptide composition (DPC) for calculating its accuracies with their receiver operating characteristic (ROC) curve. In independence testing, a feature expression of AAC and a group of GAAC are applied using MLP and CNN modules, and ROC curves are achieved with overall 100% accuracy for the detection of protein patterns. In cross-validation testing, a feature expression on a group of AAC and GAAC patterns achieved 98.33% accuracy which is the highest for the CNN module. Furthermore, ROC curves show a 0.965% extraordinary result for the GRU module. The findings show that the CNN model is excellent at figuring out leukemia illnesses from protein expressions with higher accuracy.

Kinetics characterization of a low immunogenic recombinant l-asparaginase from Phaseolus vulgaris with cytotoxic activity against leukemia cells.

l-asparaginases play a crucial role in the treatment of acute lymphoblastic leukemia (ALL), a type of cancer that mostly affects children and teenagers. However, it is common for these molecules to cause adverse reactions during treatment. These downsides ignite the search for novel asparaginases to mitigate these problems. Thus, this work aimed to produce and characterize a recombinant asparaginase from Phaseolus vulgaris (Asp-P). In this study, Asp-P was expressed in Escherichia coli with high yields and optimum activity at 40 °C, pH 9.0. The enzyme Km and Vmax values were 7.05 mM and 1027 U/mg, respectively. Asp-P is specific for l-asparagine, showing no activity against l-glutamine and other amino acids. The enzyme showed a higher cytotoxic effect against Raji than K562 cell lines, but only at high concentrations. In silico analysis indicated that Asp-P has lower immunogenicity than a commercial enzyme. Asp-P induced biofilm formation by Candida sp. due to sublethal dose, showing an underexplored potential of asparaginases. The absence of glutaminase activity, lower immunogenicity and optimal activity similar to physiological temperature conditions are characteristics that indicate Asp-P as a potential new commercial enzyme in the treatment of ALL and its underexplored application in the treatment of other diseases.

Electrochemical biosensors in early leukemia detection.

Leukemia, a type of blood cancer marked by an abnormal increase in white blood cells, poses a significant challenge to healthcare. The key to successful treatment lies in early detection. However, traditional methods often fall short. This review investigates the potential of electrochemical biosensors for a more accurate and earlier diagnosis of leukemia. Electrochemical biosensors are compact devices that transform biological interactions into electrical signals. Their small size, ease of use, and minimal sample requirements make them perfectly suited for point-of-care applications. Their remarkable sensitivity and specificity enable the detection of subtle biomolecular changes associated with leukemia, which is crucial for early disease detection. This review delves into studies that have utilized these biosensors to identify various types of leukemia. It examines the roles of electrodes, biorecognition elements, and signal transduction mechanisms. The discussion includes the integration of nanomaterials such as gold nanoparticles and nitrogen-doped graphene into biosensor design. These materials boost sensitivity, enhance signal amplification, and facilitate multi-analyte detection, thereby providing a more holistic view of the disease. Beyond technical advancements, the review underscores the practical benefits of these biosensors. Their portability makes them a promising tool for resource-constrained settings, enabling swift diagnosis in remote areas or at a patient's bedside. The potential for monitoring treatment effectiveness and detecting minimal residual disease to prevent relapse is also explored. This review emphasizes the transformative potential of electrochemical biosensors in combating leukemia. By facilitating earlier and more accurate diagnosis, these biosensors stand to revolutionize patient care and enhance treatment outcomes.

Early Onset Psychosis in a Pediatric Oncology Setting: A Case Report.

Schizophrenia (SCZ) and schizoaffective disorder (SHZ) are psychiatric disorders commonly identified in individuals in their late adolescence or early adulthood. Comorbidities are common, though a concurrent diagnosis of leukemia, one of the most frequently occurring cancers of adolescence, has not yet been described in such cases. This case study outlines the clinical presentation, course, and treatment response of two 17-year-old male adolescents whose psychotic disorders complicated their leukemia treatment. The first patient was diagnosed with leukemia and subsequently with SCZ while undergoing leukemia treatment. The second patient was diagnosed with SHZ prior to the onset of leukemia. The case study will follow the methodology of Robert E. Stake (Abma & Stake, 2014), as the two cases share a leukemia diagnosis and the reported mental health impact connected with cancer-directed treatment. Early identification and treatment are critical for both psychotic disorders and cancers, often impacting the long-term prognosis. However, when co-occurring, their interplay can present unique challenges to care.

Levofloxacin prophylaxis in pediatric oncology and hematopoietic stem cell transplantation: a literature review.

Bloodstream infections (BSI) are one of the leading causes of morbidity and mortality in children and young adults receiving chemotherapy for malignancy or undergoing hematopoietic stem cell transplantation (HSCT). Antibiotic prophylaxis is commonly used to decrease the risk of BSI; however, antibiotics carry an inherent risk of complications. The aim of this manuscript is to review levofloxacin prophylaxis in pediatric oncology patients and HSCT recipients. We reviewed published literature on levofloxacin prophylaxis to prevent BSI in pediatric oncology patients and HSCT recipients. Nine manuscripts were identified. The use of levofloxacin is indicated in neutropenic children and young adults receiving intensive chemotherapy for leukemia or undergoing HSCT. These results support the efficacy of levofloxacin in pediatric patients with leukemia receiving intensive chemotherapy and should be considered in pediatric patients undergoing HSCT prior to engraftment.

Therapeutic potential of inhibiting the PI3Kγ complex for leukemia.

In their recent paper published in Nature, Luo et al.1 investigate the cancer-cell-intrinsic roles of the PI3Kγ complex in leukemia. Their findings pinpoint PI3Kγ inhibition as a possible novel treatment avenue for a subset of acute leukemias.

Hematopoietic stem and progenitor cell membrane-coated vesicles for bone marrow-targeted leukaemia drug delivery.

Leukemia is a kind of hematological malignancy originating from bone marrow, which provides essential signals for initiation, progression, and recurrence of leukemia. However, how to specifically deliver drugs to the bone marrow remains elusive. Here, we develop biomimetic vesicles by infusing hematopoietic stem and progenitor cell (HSPC) membrane with liposomes (HSPC liposomes), which migrate to the bone marrow of leukemic mice via hyaluronic acid-CD44 axis. Moreover, the biomimetic vesicles exhibit superior binding affinity to leukemia cells through intercellular cell adhesion molecule-1 (ICAM-1)/integrin ß2 (ITGB2) interaction. Further experiments validate that the vesicles carrying chemotherapy drug cytarabine (Ara-C@HSPC-Lipo) markedly inhibit proliferation, induce apoptosis and differentiation of leukemia cells, and decrease number of leukemia stem cells. Mechanically, RNA-seq reveals that Ara-C@HSPC-Lipo treatment induces apoptosis and differentiation and inhibits the oncogenic pathways. Finally, we verify that HSPC liposomes are safe in mice. This study provides a method for targeting bone marrow and treating leukemia.