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

Rehan Ishaque, Abdul Subhan Talpur, Hafiza Sidra et al.

ABSTRACT Introduction Paroxysmal nocturnal haemoglobinuria (PNH) is an uncommon, life‐threatening disease, caused by intravascular haemolysis by the complement system. In this review, we aim to compare the efficacy of the available agents across patient‐centred outcomes in complement inhibitor‐naive patients. Methods Following PRISMA guidelines, a comprehensive literature search was conducted on PubMed, Cochrane CENTRAL and ClinicalTrials.gov for studies published up to 30th May 2025. A frequentist model network meta‐analyses were conducted in RStudio (v5.4.1) using a common‐effects model. Results A total of four randomized controlled trials evaluating four complement inhibitor agents (ravulizumab, crovalimab, eculizumab and pegcetacoplan) were included in this systematic review and network meta‐analysis, involving 589 complement inhibitor–naïve adults with PNH. Across outcomes, all active treatments demonstrated benefit compared with placebo or supportive care. In the exploratory network meta‐analysis of transfusion avoidance, no consistent statistically significant differences were observed between active treatments, although ravulizumab showed higher odds compared with crovalimab (OR = 2.69, 95% CI: 1.13–6.41; p = 0.0256). For change in FACIT‐Fatigue score, all active treatments improved fatigue versus placebo, with some statistically significant differences observed between agents; however, these comparisons were based on indirect evidence from a sparse network. Conclusion This study suggests that available complement inhibitors improve key outcomes versus placebo/supportive care in complement inhibitors naive PNH. However, the evidence network is sparse (four trials) and the cross‐trial differences limit reliable inference regarding relative efficacy between active agents. Comparative findings should be interpreted as hypothesis‐generating.

Guantong Qi, Jiasheng Wang, Mei Ling Chong et al.

Millions of children worldwide are affected by severe rare Mendelian disorders, yet exome and genome sequencing still fail to provide a definitive molecular diagnosis for a large fraction of patients, prolonging the diagnostic odyssey. Bridging this gap increasingly requires transitioning from DNA-only interpretation to multi-modal diagnostic reasoning that combines genomic data, transcriptomic sequencing (RNA-seq), and phenotype information; however, computational frameworks that coherently integrate these signals remain limited. Here we present RareCollab, an agentic diagnostic framework that pairs a stable quantitative Diagnostic Engine with Large Language Model (LLM)-based specialist modules that produce high-resolution, interpretable assessments from transcriptomic signals, phenotypes, variant databases, and the literature to prioritize potential diagnostic variants. In a rigorously curated benchmark of Undiagnosed Diseases Network (UDN) patients with paired genomic and transcriptomic data, RareCollab achieved 77% top-5 diagnostic accuracy and improved top-1 to top-5 accuracy by ~20% over widely used variant-prioritization approaches. RareCollab illustrates how modular artificial intelligence (AI) can operationalize multi-modal evidence for accurate, scalable rare disease diagnosis, offering a promising path toward reducing the diagnostic odyssey for affected families.

Wilkie Delgado-Font, Miriela Escobedo-Nicot, Manuel González-Hidalgo et al.

Red blood cell (RBC) deformation is the consequence of several diseases, including sickle cell anemia, which causes recurring episodes of pain and severe pronounced anemia. Monitoring patients with these diseases involves the observation of peripheral blood samples under a microscope, a time-consuming procedure. Moreover, a specialist is required to perform this technique, and owing to the subjective nature of the observation of isolated RBCs, the error rate is high. In this paper, we propose an automated method for differentially enumerating RBCs that uses peripheral blood smear image analysis. In this method, the objects of interest in the image are segmented using a Chan-Vese active contour model. An analysis is then performed to classify the RBCs, also called erythrocytes, as normal or elongated or having other deformations, using the basic shape analysis descriptors: circular shape factor (CSF) and elliptical shape factor (ESF). To analyze cells that become partially occluded in a cluster during sample preparation, an elliptical adjustment is performed to allow the analysis of erythrocytes with discoidal and elongated shapes. The images of patient blood samples used in the study were acquired by a clinical laboratory specialist in the Special Hematology Department of the ``Dr. Juan Bruno Zayas'' General Hospital in Santiago de Cuba. A comparison of the results obtained by the proposed method in our experiments with those obtained by some state-of-the-art methods showed that the proposed method is superior for the diagnosis of sickle cell anemia. This superiority is achieved for evidenced by the obtained F-measure value (0.97 for normal cells and 0.95 for elongated ones) and several overall multiclass performance measures. The results achieved by the proposed method are suitable for the purpose of clinical treatment and diagnostic support of sickle cell anemia.

Zhen-Yi Jin, Chun-Min Li, Hong Qu et al.

Abstract Objective To compare the predictive efficacy of the PADUA and Caprini models for pulmonary embolism (PE) in gynecological inpatients, analyze the risk factors for PE, and validate whether both models can effectively predict mortality rates. Methods A total of 355 gynecological inpatients who underwent computed tomography pulmonary angiography (CTPA) were included in the retrospective analysis. The comparative assessment of the predictive capabilities for PE between the PADUA and Caprini was carried out using receiver operating characteristic (ROC) curves. Logistic regression analysis was used to identify risk factors associated with PE. Additionally, Kaplan–Meier survival analysis plots were generated to validate the predictive efficacy for mortality rates. Results Among 355 patients, the PADUA and Caprini demonstrated the area under the curve (AUC) values of 0.757 and 0.756, respectively. There was no statistically significant difference in the AUC between the two models (P = 0.9542). Multivariate logistic analysis revealed immobility (P < 0.001), history of venous thromboembolism (VTE) (P = 0.002), thrombophilia (P < 0.001), hormonal treatment (P = 0.022), and obesity (P = 0.019) as independent risk factors for PE. Kaplan–Meier survival analysis demonstrated the reliable predictive efficacy of both the Caprini (P = 0.00051) and PADUA (P = 0.00031) for mortality. ROC for the three- and six-month follow-ups suggested that the Caprini model exhibited superior predictive efficacy for mortality. Conclusions The PADUA model can serve as a simple and effective tool for stratifying high-risk gynecological inpatients before undergoing CTPA. The Caprini model demonstrated superior predictive efficacy for mortality rates.

Daniel J. Tan, Qianyi Xu, Kay Choong See et al.

In healthcare, multi-organ system diseases pose unique and significant challenges as they impact multiple physiological systems concurrently, demanding complex and coordinated treatment strategies. Despite recent advancements in the AI based clinical decision support systems, these solutions only focus on individual organ systems, failing to account for complex interdependencies between them. This narrow focus greatly hinders their effectiveness in recommending holistic and clinically actionable treatments in the real world setting. To address this critical gap, we propose a novel Hierarchical Multi-Agent Reinforcement Learning (HMARL) framework. Our architecture deploys specialized and dedicated agents for each organ system and facilitates inter-agent communication to enable synergistic decision-making across organ systems. Furthermore, we introduce a dual-layer state representation technique that contextualizes patient conditions at both global and organ-specific levels, improving the accuracy and relevance of treatment decisions. We evaluate our HMARL solution on the task of sepsis management, a common and critical multi-organ disease, using both qualitative and quantitative metrics. Our method learns effective, clinically aligned treatment policies that considerably improve patient survival. We believe this framework represents a significant advancement in clinical decision support systems, introducing the first RL solution explicitly designed for multi-organ treatment recommendations. Our solution moves beyond prevailing simplified, single-organ models that fall short in addressing the complexity of multi-organ diseases.

LG Figorelle, K Carneiro, RC Samico et al.

Introdução: “Atrittion rate” é um termo de difícil tradução, utilizado para determinar a taxa de pacientes que não recebem tratamento com linhas subsequentes apesar de terem linfoma ativo. Esta taxa é de extrema utilidade em doenças incuráveis e com alta taxa de mortalidade como o linfoma da célula do manto (LCM). Em pesquisa recente, foi demonstrado que 24% dos pacientes nunca recebem uma segunda linha de tratamento (Husain e cols. Value in Health 2022; 25, supplement: S588) e os autores sugerem a necessidade de tratamentos mais efetivos nas linhas mais precoces para mitigar a perda de pacientes para linhas subsequentes.5882022 Objetivo: Analisar a taxa de pacientes com LCM com doença ativa que não receberam linhas subsequentes de tratamento (Attrition Rate). Material e métodos: Análise do banco de dados do Estudo Brasileiro de Linfoma da Célula do Manto (REDCap, J Biomed Inform. 2009;42:377-81) onde estão incluídos 203 pacientes com diagnóstico de LCM entre 2010 e 2022. Para este trabalho, a análise foi fechada em 26/07/2023. Os pacientes foram incluídos de 13 centros de 7 cidades brasileiras sendo 7 públicos, 5 privados e 1 público-privado. Foram selecionados 201 pacientes que iniciaram algum tipo de tratamento. Em cada linha de tratamento, os pacientes com linfoma ativo foram selecionados e os desfechos “tratamento vs não-tratamento” e “vivo vs morto” foram analisados. Resultados: 201 pacientes iniciaram um tratamento de primeira linha. 140 pacientes permaneceram com linfoma ativo mas apenas 97 iniciaram um tratamento de segunda linha (Attrition rate 31%). 64 pacientes permaneceram com registro de LCM ativo em segunda linha e 37 foram submetidos a uma terceira linha (attrition rate 42%). Na última data de seguimento, 89 pacientes tinham LCM ativo documentado e 49 foram a óbito (55%). Apenas 4 pacientes foram a óbito em remissão completa do LCM. Em outros 11 pacientes que foram a óbito, LCM ativo não pôde ser comprovado. O Status de doença na última visita ou óbito só pode ser conclusivo em 146 pacientes. Conclusão: Um considerável número de pacientes com LCM não recebe tratamentos subsequentes a despeito de permanecerem com doença ativa. A maioria destes pacientes faleceram. As causas para este problema não estão claras. Duas possibilidades podem ser um curto tempo de seguimento dos pacientes ou, ainda, o excesso de pacientes cuja presença de linfomas não foi determinada. Para a apresentação no Congresso, analisaremos estes fatores bem como a variação da “attrition rate” entre pacientes da rede pública e privada bem como de acordo com o tratamento na primeira linha.

Lihua Qiu, Tingyu Wang, Xiuhua Sun et al.

Xiangyi Kong, Peng Gao, Jing Wang et al.

Abstract Early detection and diagnosis of many cancers is very challenging. Late stage detection of a cancer always leads to high mortality rates. It is imperative to develop novel and more sensitive and effective diagnosis and therapeutic methods for cancer treatments. The development of new cancer treatments has become a crucial aspect of medical advancements. Nanobots, as one of the most promising applications of nanomedicines, are at the forefront of multidisciplinary research. With the progress of nanotechnology, nanobots enable the assembly and deployment of functional molecular/nanosized machines and are increasingly being utilized in cancer diagnosis and therapeutic treatment. In recent years, various practical applications of nanobots for cancer treatments have transitioned from theory to practice, from in vitro experiments to in vivo applications. In this paper, we review and analyze the recent advancements of nanobots in cancer treatments, with a particular emphasis on their key fundamental features and their applications in drug delivery, tumor sensing and diagnosis, targeted therapy, minimally invasive surgery, and other comprehensive treatments. At the same time, we discuss the challenges and the potential research opportunities for nanobots in revolutionizing cancer treatments. In the future, medical nanobots are expected to become more sophisticated and capable of performing multiple medical functions and tasks, ultimately becoming true nanosubmarines in the bloodstream. Graphical abstract

Benson Gary, Bhandari Trupti, Gomez Keith et al.

The necessity of a multidisciplinary team (MDT) approach in haemophilia care is well recognised globally, with international guidelines advocating this. Prior to the coronavirus disease 2019 pandemic, virtual MDT haemophilia care was gaining support worldwide. However, the pandemic necessitated the rapid implementation of innovative virtual solutions to ensure continued access to multidisciplinary care. A multidisciplinary panel of healthcare professionals who specialise in haemophilia care in the United Kingdom gathered to discuss the following: the current landscape of haemophilia MDT care and best practices, the benefits, challenges, and opportunities for virtual MDT care, managing bleeds remotely, virtual paediatric care, and the future of virtual MDT care. The consensus was that virtual MDT care is widely used, however formats vary depending on the healthcare setting, available resources, MDT preferences, and local policy. Advisors agreed that virtual MDT care has several benefits, such as improved convenience/choice for their patients and wider patient reach. However, many patient-specific and logistical challenges exist. Hybrid care models may provide an opportunity to overcome these challenges. The decision on how bleeds are managed (virtually versus face-to-face) depends on provider preference, the patient-provider relationship, and the patient’s disease severity, history, and ability to self-manage. As such, this should be assessed on a case-by-case basis. Virtual tracking tools cannot be solely relied upon for MDT decisionmaking as patient accuracy cannot be ascertained. The MDT composition for paediatric care should be tailored to the patients’ and their parents’/caregivers’ needs. Lastly, hybridised care will likely be adopted for future haemophilia management and will facilitate the advancement of MDT care.

Lucas Amoudruz, Athena Economides, Petros Koumoutsakos

Red blood cells (RBCs) are vital for transporting oxygen from the lungs to the body's tissues through the intricate circulatory system. They achieve this by binding and releasing oxygen molecules to the abundant hemoglobin within their cytosol. The volume of RBCs affects the amount of oxygen they can carry, yet whether this volume is optimal for transporting oxygen through the circulatory system remains an open question. This study explores, through high-fidelity numerical simulations, the impact of RBC volume on advectve oxygen transport efficiency through arterioles which form the area of greatest flow resistance in the circulatory system. The results show that, strikingly, RBCs with volumes similar to those found in vivo are most efficient to transport oxygen through arterioles. The flow resistance is related to the cell-free layer thickness, which is influenced by the shape and the motion of the RBCs: at low volumes RBCs deform and fold while at high volumes RBCs collide and follow more diffuse trajectories. In contrast, RBCs with a healthy volume maximize the cell-free layer thickness, resulting in a more efficient advectve transport of oxygen.

Yu-Hsiang Chang, Yang-Hsien Lin, Kung-Bin Sung

Integrating optical diffraction tomography with imaging flow cytometry enables label-free quantifications of the three-dimensional (3D) morphology and hemoglobin content of red blood cells (RBCs) in their natural form. Self-rotation of RBCs flowing in a microfluidic channel has been utilized to achieve various projection directions for 3D reconstruction. However, the practicality of this technique has not been sufficiently studied. We improved the accuracy of estimating the rotation angle of RBCs and demonstrated 3D reconstructions of both healthy and glutaraldehyde-treated RBCs. Results showed the capability to quantify changes in RBC morphology, hemoglobin content, and membrane fluctuations generated by glutaraldehyde treatments, demonstrating the potential to detect changes frequently present in various RBC membrane disorders.

Erdenebayar Namjil, Munkhsoyol Gan-Ochir, Yanjindulam Natsagdorj

In 1963, Mongolian blood transfusion service was established officially with the independent creation of Blood Transfusion Central Station in Ulaanbaatar. In the following year of 1964, rural blood centers were organized under the provincial central hospitals in all provinces, thus blood transfusion care and service has started nationwide. As part of the continuous improvement of the legal framework for the blood transfusion sector, the Donor Law of Mongolia was adopted in 2000, amended in 2012, and revised in 2018. In 1994, Mongolian blood transfusion service has shifted from paid blood donation practice to the nonremunerated and has achieved a 100% voluntary nonremunerated blood donor, in 2016. The World Health Organization recommends that in low- and middle-income countries, the share of blood donors in the total population to be 1.5. As of 2020, this figure has reached at 1.8% in Ulaanbaatar. The National Center for Transfusion Medicine (NCTM) has introduced drastic technological innovations in blood and blood products (BBP) production periodically. Since 2007, the NCTM has been implementing three international standards in its activity including requirements for quality and competence for medical laboratories MNS ISO 15189:2015, quality management system MNS ISO 9001:2016, and occupational health and safety management system OHSAS 18001:2007/MNS OHSAS 18001/2012. In 2020, the Mongolian blood transfusion service provided safe and quality assured BBP to health care organizations with 100% of fulfillment nationwide.

Stefania Momi, Jessica Canino, Mauro Vismara et al.

Deep vein thrombosis results from the cooperative action of leukocytes, platelets, and endothelial cells. The proline-rich tyrosine kinase Pyk2 regulates platelet activation and supports arterial thrombosis. In this study, we combined pharmacological and genetic approaches to unravel the role of Pyk2 in venous thrombosis. We found that mice lacking Pyk2 almost completely failed to develop deep venous thrombi upon partial ligation of the inferior vena cava. Pyk2-deficient platelets displayed impaired exposure of phosphatidylserine and tissue factor expression by endothelial cells and monocytes was completely prevented by inhibition of Pyk2. In human umbilical vein endothelial cells (HUVEC), inhibition of Pyk2 hampered IL-1b-induced expression of VCAM and P-selectin, and von Willebrand factor release. Pyk2-deficient platelets showed defective adhesion on von Willebrand factor and reduced ability to bind activated HUVEC under flow. Moreover, inhibition of Pyk2 in HUVEC strongly reduced platelet adhesion. Similarly, Pyk2-deficient neutrophils were unable to efficiently roll and adhere to immobilized endothelial cells under venous flow conditions. Moreover, platelets and neutrophils from Pyk2- knockout mice showed defective ability to form heterogeneous aggregates upon stimulation, while platelet monocyte interaction occurred normally. Consequently, platelet neutrophil aggregates, abundant in blood of wild-type mice upon inferior vena cava ligation, were virtually undetectable in Pyk2-knockout mice. Finally, we found that expression of Pyk2 was required for NETosis induced by activated platelets. Altogether our results demonstrate a critical role of Pyk2 in the regulation of the coordinated thromboinflammatory responses of endothelial cells, leukocytes and platelets leading to venous thrombosis. Pyk2 may represent a novel promising target in the treatment of deep vein thrombosis.

Stefan Röhrl, Alice Hein, Lucie Huang et al.

The quality of datasets plays a crucial role in the successful training and deployment of deep learning models. Especially in the medical field, where system performance may impact the health of patients, clean datasets are a safety requirement for reliable predictions. Therefore, outlier detection is an essential process when building autonomous clinical decision systems. In this work, we assess the suitability of Self-Organizing Maps for outlier detection specifically on a medical dataset containing quantitative phase images of white blood cells. We detect and evaluate outliers based on quantization errors and distance maps. Our findings confirm the suitability of Self-Organizing Maps for unsupervised Out-Of-Distribution detection on the dataset at hand. Self-Organizing Maps perform on par with a manually specified filter based on expert domain knowledge. Additionally, they show promise as a tool in the exploration and cleaning of medical datasets. As a direction for future research, we suggest a combination of Self-Organizing Maps and feature extraction based on deep learning.

I. Zacharoudiou, J. W. S. McCullough, P. V. Coveney

In recent years, it has become increasingly common for high performance computers (HPC) to possess some level of heterogeneous architecture - typically in the form of GPU accelerators. In some machines these are isolated within a dedicated partition, whilst in others they are integral to all compute nodes - often with multiple GPUs per node - and provide the majority of a machine's compute performance. In light of this trend, it is becoming essential that codes deployed on HPC are updated to execute on accelerator hardware. In this paper we introduce a GPU implementation of the 3D blood flow simulation code HemeLB that has been developed using CUDA C++. We demonstrate how taking advantage of NVIDIA GPU hardware can achieve significant performance improvements compared to the equivalent CPU only code on which it has been built whilst retaining the excellent strong scaling characteristics that have been repeatedly demonstrated by the CPU version. With HPC positioned on the brink of the exascale era, we use HemeLB as a motivation to provide a discussion on some of the challenges that many users will face when deploying their own applications on upcoming exascale machines.

Mehmet Tahir Huyut, Andrei Velichko

Since February 2020, the world has been engaged in an intense struggle with the COVID-19 dis-ease, and health systems have come under tragic pressure as the disease turned into a pandemic. The aim of this study is to obtain the most effective routine blood values (RBV) in the diagnosis and prognosis of COVID-19 using a backward feature elimination algorithm for the LogNNet reservoir neural network. The first dataset in the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 tests. The LogNNet-model achieved the accuracy rate of 99.5% in the diagnosis of the disease with 46 features and the accuracy of 99.17% with only mean corpuscular hemoglobin concentration, mean corpuscular hemoglobin, and activated partial prothrombin time. The second dataset consists of a total of 3899 patients with a diagnosis of COVID-19 who were treated in hospital, of which 203 were severe patients and 3696 were mild patients. The model reached the accuracy rate of 94.4% in determining the prognosis of the disease with 48 features and the accuracy of 82.7% with only erythrocyte sedimentation rate, neutrophil count, and C reactive protein features. Our method will reduce the negative pressures on the health sector and help doctors to understand the pathogenesis of COVID-19 using the key features. The method is promising to create mobile health monitoring systems in the Internet of Things.

LF Pelle, ME Cas, SB Azeredo et al.

Introdução: A pandemia SARS-CoV-2, conhecido como COVID-19, trouxe dificuldades importantes para as diversas áreas da saúde, especialmente no que se refere a doação de sangue, que foi reduzida a números preocupantes. Com isso, fez-se necessário instituir meios para amenizar os baixos estoques de sangue neste período. Assim, o Serviço de Hemoterapia do Hospital São Vicente de Paulo (SHHSVP) e o Programa de Extensão ComSaúde da Universidade de Passo Fundo, encontraram na Sétima Região Tradicionalista, que concentra em torno de 140 entidades (Centros Tradicionalistas Gaúcho e Piquetes de Laço), e na Academia Passo-Fundense de Letras (APL) apoiadores para realização de ações sobre doação de sangue com a temática: “Gaúcho doador: doe sangue, mostre seu valor”. As atividades da campanha incluíram lives educativas sobre o processo de doação sangue, bem como oficinas online de confecção de poesias, concurso de poesias gaudérias e grupos de doação de sangue. Desenvolvimento: O projeto gaúcho doador iniciou-se em setembro, mês de comemorações tradicionalistas, em especial do dia do gaúcho. A ideia surgiu da necessidade de doações de sangue devido aos baixos estoques nos bancos de sangue, e iniciou com a sensibilização de possíveis doadores na comunidade da Sétima Região Tradicionalista, que envolve 42 municípios e 140 entidades, através da educação e da cultura regional, neste período da pandemia. Além disso, desenvolver atividades de cidadania na comunidade de Passo Fundo e na região por meio de ações educativas em um ambiente virtual com disseminação das informações via redes sociais, a exemplo da live sobre doação de sangue, em que se explicou o funcionamento de todo processo de doação bem como respondeu dúvidas dos participantes, e oficina de produção de poesias com a ajuda das instituições responsáveis. A partir disso, foi lançado um desafio por meio de um concurso de poesias sobre o tema doação na linguagem gauchesca: “Gaúcho Doador. Doe sangue, Mostre Seu Valor”, em diferentes categorias, categorizadas por idade desde crianças a idosos, coordenada pela APL, que além da oficina sobre as regras do concurso elegeu os vencedores, que foram premiados em uma solenidade no dia 25 de novembro de 2020, também comemorado dia do doador, no SHHSVP, conduzido pela APL com a participação dos vencedores do concurso, autoridades, parceiros do projeto e o Hemozito pilchado, o qual foi confeccionado especialmente para o evento. Essa ação foi extremamente importante, visto que, por estarmos em um período de pandemia, as doações de sangue sofreram grande impacto negativo. Além de aumentar o número de doações espontâneas no SHHSVP esse projeto foi de suma importância para a interação da comunidade, uma vez que uniu cultura e educação em prol da saúde. Ademais, a campanha Gaúcho Doador trouxe visibilidade nas mídias sociais e nas entidades tradicionalistas para a importância da doação de sangue e inclusão de novos doadores, os quais são potenciais futuros doadores e disseminadores da importância dessa ação. Conclusão: A doação de sangue é um ato que salva vidas, por isso sua carência gera preocupação. A campanha Gaúcho Doador atuou como uma alternativa para captar novos doadores e valorizar a cultura tradicionalista. Esta campanha proporcionou que os valores gaúchos impulsionassem a doação de sangue e assim, juntos, eles criaram uma nova tradição no coração dos gaúchos.

LS Oliveira, PCC Bariani, PL Filgueiras et al.

Introdução: A Leucemia Aguda Indiferenciada não possui a expressão de nenhum marcador definidor de linhagem. Para categoriza-lá, é necessário realizar imunofenotipagem com um painel de anticorpos monoclonais abrangente para excluir leucemias de linhagens incomuns, como as derivadas de precursores de células dendríticas, de células NK, basófilos e tumores não hematopoiéticos. Essa entidade é rara, com incidência desconhecida. Os blastos não apresentam características de diferenciação mielóide, são negativos para as colorações mieloperoxidade e esterase. Geralmente expressam HLA-DR, CD34 e/ou CD38 e podem ser positivos para TdT. O CD7, embora frequentemente considerado um antígeno de células T, é expresso fracamente em alguns progenitores hematopoiéticos CD34+ e pode ser expresso de forma semelhante nessas leucemias. Relato de caso: Mulher, 25 anos, previamente hígida, encaminhada para Hematologia em julho de 2021 devido a anemia, plaquetopenia e leucocitose. Na admissão, apresentava abscesso amigdaliano, além de petéquias em membros e na região do tronco. A análise de sangue periférico e de medula óssea evidenciou presença de 97% de blastos de tamanho grande, com relação núcleo-citoplasmática intermediária, citoplasma basofílico e agranular, alguns apresentando vacúolos, núcleo com cromatina frouxa, contorno irregular, apresentando 1 a 3 nucléolos evidentes. Imunofenotipagem mostrou os seguintes marcadores: CD45dim, CD34-, CD117+, CD33-, HLA-DR+, CD38+, CD123+(fraco), CD14-, CD7+, CD11b-, CD56-, CD13-, CD19-, CD11c-, CD64-, CD15-, CD133-, CD41a-, CD61-, TdT+, cCD79a-, CD3-, cCD3-, MPO-. A citogenética convencional apresentou deleção do 13q. Realizado também RT-PCR para BCR-ABL1 qualitativo que resultou negativo. Solicitado também Biologia Molecular com pesquisa dos rearranjos RUNX1-RUX1T1, CBFBetaMYH11 e das mutações FLT3 e NPM1, ainda com resultados pendentes. O tratamento proposto foi esquema de indução de remissão com daunorrubicina 60 mg/m2/dia nos dias 1-3, e citarabina, 100 mg/m2 infusão intravenosa contínua de 24 horas nos dias 1-7. Programado reavaliação da medula óssea após recuperação hematológica da primeira indução de remissão. Discussão: Nos últimos anos ocorreram avanços no diagnóstico e estratificação de risco das Leucemias Agudas, o que nos permite reconhecer a situação descrita neste relato de caso. A paciente do caso apresenta um fenótipo indiferenciado associado a uma alteração citogenética que, no contexto de uma LMA, classificaria como relacionada a alterações mielodisplásicas. Porém, pacientes com fenótipo indiferenciado também podem apresentar alterações citogenéticas. O tratamento indicado é semelhante ao da LMA de alto risco, sendo indicado Transplante de Medula Óssea Alogênico. Conclusão: Os dados para avaliação de estratificação de risco e prognóstico nessa situação são limitados, sendo necessário mais estudos científicos.

Alice Briole, Thomas Podgorski, Bérengère Abou

The deformability of red blood cells is an essential parameter that controls the rheology of blood as well as its circulation in the body. Characterizing the rigidity of the cells and their heterogeneity in a blood sample is thus a key point in the understanding of occlusive phenomena, particularly in the case of erythrocytic diseases in which healthy cells coexist with pathological cells. However, measuring intracellular rheology in small biological compartments requires the development of specific techniques. We propose a technique based on molecular rotors-viscosity-sensitive fluorescent probes-to evaluate the above key point. DASPI molecular rotor has been identified with spectral fluorescence properties decoupled from those of hemoglobin, the main component of the cytosol. After validation of the rotor as a viscosity probe in model fluids, we showed by confocal microscopy that, in addition to binding to the membrane, the rotor penetrates spontaneously and uniformly into red blood cells. Experiments conducted on temperature-stiffened red blood cells show that molecular rotors can probe their overall rigidity. A simple model allowed us to separate the contribution of the cytosol from that of the membrane, providing a quantification of cytosol rigidification with temperature, consistent with independent measurements of the viscosity of hemoglobin solutions. Our experiments demonstrate that the rotor can be used to quantify the intracellular rheology of red blood cells at the cellular level, as well as the heterogeneity of this stiffness in a blood sample. This technique opens up new possibilities for biomedical applications, diagnosis and disease monitoring.

Joshua Mathew, Xin Tian, Min Wu et al.

Blood oxygen saturation (SpO$_2$) is an essential indicator of respiratory functionality and is receiving increasing attention during the COVID-19 pandemic. Clinical findings show that it is possible for COVID-19 patients to have significantly low SpO$_2$ before any obvious symptoms. The prevalence of cameras has motivated researchers to investigate methods for monitoring SpO$_2$ using videos. Most prior schemes involving smartphones are contact-based: They require a fingertip to cover the phone's camera and the nearby light source to capture re-emitted light from the illuminated tissue. In this paper, we propose the first convolutional neural network based noncontact SpO$_2$ estimation scheme using smartphone cameras. The scheme analyzes the videos of a participant's hand for physiological sensing, which is convenient and comfortable, and can protect their privacy and allow for keeping face masks on. We design our neural network architectures inspired by the optophysiological models for SpO$_2$ measurement and demonstrate the explainability by visualizing the weights for channel combination. Our proposed models outperform the state-of-the-art model that is designed for contact-based SpO$_2$ measurement, showing the potential of our proposed method to contribute to public health. We also analyze the impact of skin type and the side of a hand on SpO$_2$ estimation performance.