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Catatrophic antiphospholipid syndrome (CAPS), a rare variant of antiphospholipid syndrome (APS), is associated with rapid multiorgan failure. While APS is associated with single medium-to-large blood vessel occlusions, CAPS is most often associated with several, concurrent vascular occlusions of small vessels, commonly of the kidneys, heart, skin and brain. We present a case of a 21-year-old female patient with a history of immune thrombocytopenia purpura and APS, who eventually developed concurrent cerebral venous sinus thrombosis, diffuse alveolar haemorrhage, renal thrombotic microangiopathy, and a necrotic, vasculitic wound on her forearm. Despite hospitalisation and treatment, her condition worsened and the patient eventually died after succumbing to suspected CAPS.
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Síndrome Antifosfolípido , Humanos , Síndrome Antifosfolípido/complicaciones , Femenino , Adulto Joven , Resultado Fatal , Enfermedad Catastrófica , Trombosis de los Senos Intracraneales/etiología , Trombosis de los Senos Intracraneales/tratamiento farmacológico , Trombosis de los Senos Intracraneales/terapia , Microangiopatías Trombóticas/etiología , Púrpura Trombocitopénica Idiopática/terapia , Púrpura Trombocitopénica Idiopática/complicaciones , Púrpura Trombocitopénica Idiopática/diagnósticoRESUMEN
OBJECTIVES: The aim of this study was to characterize the microbiome of multiple mucosal organs in cervical cancer (CC) patients. METHODS: We collected oral, gut, urinary tract, and vaginal samples from enrolled study participants, as well as tumor tissue from CC patients. The microbiota of different mucosal organs was identified by 16S rDNA sequencing and correlated with clinical-pathological characteristics of cervical cancer cases. RESULTS: Compared with controls, CC patients had reduced α-diversity of oral and gut microbiota (pOral_Sob < 0.001, pOral_Shannon = 0.049, pOral_Simpson = 0.013 pFecal_Sob = 0.030), although there was an opposite trend in the vaginal microbiota (pVaginal_Pielou = 0.028, pVaginal_Simpson = 0.006). There were also significant differences in the ß-diversity of the microbiota at each site between cases and controls (pOral = 0.002, pFecal = 0.037, pUrine = 0.001, pVaginal = 0.001). The uniformity of urine microbiota was lower in patients with cervical squamous cell carcinoma (pUrine = 0.036) and lymph node metastasis (pUrine_Sob = 0.027, pUrine_Pielou = 0.028, pUrine_Simpson = 0.021, pUrine_Shannon = 0.047). The composition of bacteria in urine also varied among patients with different ages (p = 0.002), tumor stages (p = 0.001) and lymph node metastasis (p = 0.002). In CC cases, Pseudomonas were significantly enriched in the oral, gut, and urinary tract samples. In addition, Gardnerella, Anaerococcus, and Prevotella were biomarkers of urinary tract microbiota; Abiotrophia and Lautropia were obviously enriched in the oral microbiota. The microbiota of tumor tissue correlated with other mucosal organs (except the gut), with a shift in the microflora between mucosal organs and tumors. CONCLUSIONS: Our study not only revealed differences in the composition and diversity of the vaginal and gut microflora between CC cases and controls, but also showed dysbiosis of the oral cavity and urethra in cervical cancer cases.
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Microbiota , Neoplasias del Cuello Uterino , Humanos , Femenino , Neoplasias del Cuello Uterino/microbiología , Neoplasias del Cuello Uterino/patología , Persona de Mediana Edad , Microbiota/genética , Adulto , Vagina/microbiología , Vagina/patología , Microbioma Gastrointestinal/genética , ARN Ribosómico 16S/genética , Membrana Mucosa/microbiología , Membrana Mucosa/patología , Estudios de Casos y Controles , Bacterias/clasificación , Bacterias/aislamiento & purificación , Bacterias/genética , Sistema Urinario/microbiología , Sistema Urinario/patología , Anciano , Biodiversidad , Boca/microbiologíaRESUMEN
OBJECTIVE: Cell division cycle 42 (CDC42) modulates inflammation and multiple organ dysfunction by regulating T-cell differentiation and macrophage polarization. This research intended to explore the association of blood CDC42 expression with septic risk, multi-organ dysfunctions, and mortality. METHODS: 145 sepsis patients and 50 health controls were recruited, then CDC42 expression in peripheral blood mononuclear cell (PBMC) from them was measured by RT-qPCR. RESULTS: CDC42 was decreased in sepsis patients versus health controls (P<0.001); meanwhile, the receiver operating characteristic (ROC) curve showed that CDC42 had a certain value to predict sepsis risk with an area under the curve (AUC) (95% confidence interval (CI): 0.797 (0.725-0.869). Furthermore, CDC42 was negatively correlated with C-reactive protein (P<0.001), tumor necrosis factor-alpha (P<0.001) and interleukin-17A (P<0.001) but less with interleukin-6 (P=0.056). Moreover, CDC42 was negatively related to the SOFA score (P<0.001) and its several subscales (respiratory system, liver, cardiovascular, and renal system) (P<0.05). Furthermore, CDC42 was lower in septic deaths versus survivors (P<0.001); meanwhile, the ROC curve exhibited a certain ability of CDC42 in estimating 28-day mortality with an AUC (95%CI) of 0.766 (0.676-0.855). CONCLUSION: Circulating CDC42 exhibits potency to be a prognostic biomarker reflecting multi-organ dysfunctions and higher mortality risk in sepsis.
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Inflamación , Insuficiencia Multiorgánica , Sepsis , Proteína de Unión al GTP cdc42 , Humanos , Sepsis/mortalidad , Sepsis/sangre , Femenino , Masculino , Persona de Mediana Edad , Insuficiencia Multiorgánica/mortalidad , Insuficiencia Multiorgánica/sangre , Inflamación/sangre , Proteína de Unión al GTP cdc42/metabolismo , Proteína de Unión al GTP cdc42/genética , Susceptibilidad a Enfermedades , Curva ROC , Biomarcadores/sangre , Estudios de Casos y Controles , Anciano , Pronóstico , Adulto , Factores de Riesgo , Leucocitos Mononucleares/metabolismoRESUMEN
Clinical manifestations of congenital syphilis (CS) include liver disease with/without impaired liver function, identified as syphilitic hepatitis. Hepatic involvement may be dramatic; therefore, early diagnosis is crucial to provide treatment and prevent fatal outcomes. A new resurgence of CS cases has been described in recent years worldwide. We reported our experience with a case series of infants hospitalized for liver disease with a final diagnosis of CS, highlighting the wide spectrum of liver involvement, the rapid progression in cases with late diagnosis, and the pitfalls of the management of this forgotten but reemerging disease. A retrospective analysis of CS patients with hepatic presentation in the period 2008-2023 was conducted. We collected five cases (three female) with a median age of 13.8 days (range 1-84 days). In three cases, mothers were not screened for syphilis during pregnancy, and in two cases, they were seronegative in the first trimester screening. None practiced specific therapy during pregnancy. Hepatic involvement was characterized by hepatosplenomegaly, in four cases associated with cholestatic jaundice and in three cases with liver failure. Rapid plasma reagin (RPR) and Treponema pallidum hemagglutination assay (TPHA) were positive in all cases in mothers and infants. CS presented with multiorgan involvement and was fatal in one case.Conclusions: It is important to consider CS in infants with cholestasis and acute liver failure, but also in sick infants with isolated hepatomegaly. Early recognition of infants with CS is critical to identify missed cases during pregnancy and to start early treatment.
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Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients, posing potential safety risks. We evaluated the performance of TotalSegmentator, a state-of-the-art adult-trained CT organ segmentation model, on a subset of organs in a pediatric CT dataset and explored optimization strategies to improve pediatric segmentation performance. TotalSegmentator was retrospectively evaluated on abdominal CT scans from an external adult dataset (n = 300) and an external pediatric data set (n = 359). Generalizability was quantified by comparing Dice scores between adult and pediatric external data sets using Mann-Whitney U tests. Two DL optimization approaches were then evaluated: (1) 3D nnU-Net model trained on only pediatric data, and (2) an adult nnU-Net model fine-tuned on the pediatric cases. Our results show TotalSegmentator had significantly lower overall mean Dice scores on pediatric vs. adult CT scans (0.73 vs. 0.81, P < .001) demonstrating limited generalizability to pediatric CT scans. Stratified by organ, there was lower mean pediatric Dice score for four organs (P < .001, all): right and left adrenal glands (right adrenal, 0.41 [0.39-0.43] vs. 0.69 [0.66-0.71]; left adrenal, 0.35 [0.32-0.37] vs. 0.68 [0.65-0.71]); duodenum (0.47 [0.45-0.49] vs. 0.67 [0.64-0.69]); and pancreas (0.73 [0.72-0.74] vs. 0.79 [0.77-0.81]). Performance on pediatric CT scans improved by developing pediatric-specific models and fine-tuning an adult-trained model on pediatric images where both methods significantly improved segmentation accuracy over TotalSegmentator for all organs, especially for smaller anatomical structures (e.g., > 0.2 higher mean Dice for adrenal glands; P < .001).
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Leptospirosis, an acute zoonotic infection caused by spirochetes of the genus Leptospira, poses significant health risks worldwide. Transmission occurs through contact with infected animals' urine, blood, or tissue. This case report examines a 44-year-old man with severe leptospirosis, presenting as Weil's disease, characterized by acute hypoxic respiratory failure and acute kidney injury (AKI) secondary to rhabdomyolysis, complicated by severe hyponatremia. The case underscores the diagnostic and management challenges associated with leptospirosis, highlighting the importance of interdisciplinary collaboration and comprehensive diagnostic evaluation.
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Immune checkpoint inhibitors (ICIs) activate T cells, causing immune-related adverse events (irAEs). Skin manifestations are common among irAEs, but ICI-associated bullous pemphigoid (BP) is rare. Inhibiting programmed death (PD)-1 signaling, in addition to causing epitope spreading, may disrupt B and T cell balance, causing excessive autoantibody production against the skin's basement membrane, leading to BP. A 70-year-old woman developed late-onset multi-organ irAEs, including diarrhea, thyroid dysfunction, and BP, while receiving pembrolizumab, a PD-1 inhibitor. This highlights the long-term risk of irAEs, which can occur 2-3 years after starting ICIs. In cases of multi-organ irAE, C-reactive protein levels and neutrophil/lymphocyte ratio are often low. These characteristics were observed in our case. Few papers address multiple organ involvement, highlighting the need to consider irAEs in a multi-organ context. While it is known that drug-induced skin reactions worsen as blood eosinophil counts increase, in our case, the eosinophil count remained normal, suggesting that ICI-associated BP might have been controlled without discontinuing the ICI and through tapering of low-dose oral prednisone treatment. Additionally, in this case, significant CD4-positive T cell infiltration was observed in the immunostaining examination of the blisters, indicating that severe CD4-positive T cell infiltration induced by the ICI might have led to multi-organ involvement, including severe diarrhea. Few reports focus on blood eosinophil counts in BP cases or discuss CD4 and CD8 immunostaining in BP cases. Therefore, future research should explore the relationship between blood eosinophil counts, immunostaining results, and the prognosis of irAEs, including BP, in treatment courses.
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Mitochondria, also called 'powerhouse of the cell', is meant for energy generation in eukaryotic cells. This action is performed by mitochondria through the oxidative phosphor-ylation (OXPHOS) of the respiratory chain (RC). Based on the functioning of the cell, the number of mitochondria varies up to thousands in number. Mutations in the mitochondrial DNA (mtDNA) and/or nuclear DNA (nDNA) genes may lead to the generation of primary mitochondrial disease (PMD) that affects the structure and function of mitochondria. The di-agnosis of such mitochondrial diseases occurs in early childhood and it can lead to serious, fetal and multi-organ diseases. Understanding epigenetic events and changes in the pathway can help improve the effectiveness of treatment. However, there are several reasons lack of the disease symptoms (age, sign, symptoms, morbidity and lethality), restricted availability of pre-clinical models along with extensive phenotypes that hamper the development of efficient drugs. Despite the introduction of new treatments and the encouraging results of treatments and therapies, there is no effective cure for PMD. This article contains information about the changes associated with cytopathic diseases that make possible the analysis of various diseases by genetic techniques. Increasing our under-standing of how mitochondrial DNA mutations affect mitochondrial metabolism and subse-quently result in neurodegenerative disease will prove vital to the development of targeted therapies and treatments.
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Partially-supervised multi-organ medical image segmentation aims to develop a unified semantic segmentation model by utilizing multiple partially-labeled datasets, with each dataset providing labels for a single class of organs. However, the limited availability of labeled foreground organs and the absence of supervision to distinguish unlabeled foreground organs from the background pose a significant challenge, which leads to a distribution mismatch between labeled and unlabeled pixels. Although existing pseudo-labeling methods can be employed to learn from both labeled and unlabeled pixels, they are prone to performance degradation in this task, as they rely on the assumption that labeled and unlabeled pixels have the same distribution. In this paper, to address the problem of distribution mismatch, we propose a labeled-to-unlabeled distribution alignment (LTUDA) framework that aligns feature distributions and enhances discriminative capability. Specifically, we introduce a cross-set data augmentation strategy, which performs region-level mixing between labeled and unlabeled organs to reduce distribution discrepancy and enrich the training set. Besides, we propose a prototype-based distribution alignment method that implicitly reduces intra-class variation and increases the separation between the unlabeled foreground and background. This can be achieved by encouraging consistency between the outputs of two prototype classifiers and a linear classifier. Extensive experimental results on the AbdomenCT-1K dataset and a union of four benchmark datasets (including LiTS, MSD-Spleen, KiTS, and NIH82) demonstrate that our method outperforms the state-of-the-art partially-supervised methods by a considerable margin, and even surpasses the fully-supervised methods. The source code is publicly available at LTUDA.
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BACKGROUND: Immunoglobulin A vasculitis (IgAV) is a kind of systemic vasculitis mediated by IgA immune complexes (IgA-ICs). Soluble CD89-IgA complex (sCD89-IgA) as a type of IgA-IC associated with renal involvement in IgAV, the ability of blood sCD89-IgA as a biomarker to predict renal or multi-organ involvement in children with IgAV is not evident, and this study mainly focused on this. METHODS: The clinical characteristics and blood samples of 57 pediatric patients with IgAV were collected. ELISA was used to detect plasma IgA-ICs and sCD89-IgA levels. Serum IgA levels were detected by Nephelometry method. Statistical analysis was conducted to analyze the relationship between sex, age, serum IgA levels, plasma IgA-ICs levels, plasma sCD89-IgA levels and the involvement of multiple organs (except skin) including kidneys in these patients. RESULTS: Compared to patients with simple skin involvement, patients with multi-organ involvement, especially kidneys, had higher levels of plasma IgA-ICs and sCD89-IgA, and the statistical difference was significant. In addition, a high level of plasma sCD89-IgA was a high-risk factor for patients to develop multi-organ or renal involvement in addition to the skin. ROC curve analysis showed that the AUC was 0.861 (Sensitivity: 83 %, Specificity: 88 %, p < 0.0001) when plasma sCD89-IgA predicted multi-organ involvement, and AUC 0.926 (Sensitivity: 94 %, Specificity: 88 %, p < 0.0001) for predicting renal involvement. CONCLUSIONS: The results suggested that plasma sCD89-IgA may be a potential biomarker for predicting multi-organ involvement (in addition to skin), especially renal involvement in IgAV pediatric patients.
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Cerebral vasculitis is a rare but severe complication of Systemic Lupus Erythematosus (SLE), presenting significant challenges in management due to its potential for devastating neurological consequences and poor prognosis. We present a case of an 18-year-old female with known SLE who presented with seizures, declining cognitive function, and unresponsiveness. Neurological examination, laboratory investigations, and radiological imaging supported the diagnosis of cerebral vasculitis secondary to SLE. Despite aggressive immunosuppressive therapy, the patient's neurological status continued to deteriorate, leading to respiratory failure and multiorgan dysfunction. Ultimately, the patient succumbed to multiorgan failure attributed to severe CNS vasculitis and its complications. This case underscores the importance of early recognition and aggressive management of cerebral vasculitis in SLE while highlighting the need for further research into more effective therapeutic strategies to improve patient outcomes.
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Lupus Eritematoso Sistémico , Vasculitis del Sistema Nervioso Central , Humanos , Femenino , Adolescente , Lupus Eritematoso Sistémico/complicaciones , Vasculitis del Sistema Nervioso Central/etiología , Vasculitis del Sistema Nervioso Central/complicaciones , Resultado FatalRESUMEN
OBJECTIVES: Treatment of hemorrhagic shock (HS) induced multi-organ injury remains a challenge. Bergapten (BeG) is a bioactive coumarin-derived compound, and previous articles have suggested that BeG may serve as a prospective therapeutic modality for HS. This study was designed to investigate the efficacy of BeG in the treatment of HS and its underlying mechanisms. METHODS: In this research, we established a rat model of HS, following which we assessed the protective effects of BeG on HS induced multi-organ injury. Subsequently, we scrutinized the activation of NLRP3 inflammasomes and pyroptosis in damaged organs. Additionally, we conducted examinations of AMPK and the downstream mitophagy pathway in damaged organs. Finally, we established a hypoxia/reoxygenation (H/R) model in HK-2 cells to simulate the in vitro HS process. Following AMPK inhibition with compound C, we evaluated the levels of mitophagy and cellular pyroptosis in BeG-treated HK-2 cells subjected to H/R. RESULTS: BeG treatment alleviated HS induced multi-organ injury. Subsequent analyses indicated that the therapeutic effects of BeG were related to the attenuation of NLRP3 inflammasome activation and pyroptosis. Additionally, we found BeG treatment stimulated the phosphorylation of AMPK, thereby enhancing mitophagy. Lastly, we found that the inhibition of AMPK in vitro attenuates BeG's enhancement of mitophagy and its suppression of pyroptosis. CONCLUSION: Our research indicates that BeG has the potential to alleviate multi-organ injury induced by HS. The protective effect of BeG is likely associated with its promotion of mitophagy through AMPK activation, thereby inhibiting NLRP3 inflammasome-mediated pyroptosis.
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Inflamasomas , Proteína con Dominio Pirina 3 de la Familia NLR , Piroptosis , Ratas Sprague-Dawley , Choque Hemorrágico , Choque Hemorrágico/tratamiento farmacológico , Choque Hemorrágico/complicaciones , Animales , Proteína con Dominio Pirina 3 de la Familia NLR/metabolismo , Piroptosis/efectos de los fármacos , Humanos , Masculino , Inflamasomas/metabolismo , Línea Celular , Ratas , Cumarinas/farmacología , Cumarinas/uso terapéutico , Mitofagia/efectos de los fármacos , Proteínas Quinasas Activadas por AMP/metabolismo , Modelos Animales de Enfermedad , Insuficiencia Multiorgánica/tratamiento farmacológico , Insuficiencia Multiorgánica/prevención & control , Insuficiencia Multiorgánica/etiologíaRESUMEN
Medical image segmentation has made remarkable progress with advances in deep learning technology, depending on the quality and quantity of labeled data. Although various deep learning model structures and training methods have been proposed and high performance has been published, limitations such as inter-class accuracy bias exist in actual clinical applications, especially due to the significant lack of small object performance in multi-organ segmentation tasks. In this paper, we propose an uncertainty-based contrastive learning technique, namely UncerNCE, with an optimal hybrid architecture for high classification and segmentation performance of small organs. Our backbone architecture adopts a hybrid network that employs both convolutional and transformer layers, which have demonstrated remarkable performance in recent years. The key proposal of this study addresses the multi-class accuracy bias and resolves a common tradeoff in existing studies between segmenting regions of small objects and reducing overall noise (i.e., false positives). Uncertainty based contrastive learning based on the proposed hybrid network performs spotlight learning on selected regions based on uncertainty and achieved accurate segmentation for all classes while suppressing noise. Comparison with state-of-the-art techniques demonstrates the superiority of our results on BTCV and 1K data.
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Aprendizaje Profundo , Procesamiento de Imagen Asistido por Computador , Redes Neurales de la Computación , Humanos , Incertidumbre , Procesamiento de Imagen Asistido por Computador/métodos , Algoritmos , Diagnóstico por Imagen , Aprendizaje AutomáticoRESUMEN
A wide variety of inflammatory mediators, mainly cytokines and chemokines, are induced during SARS CoV-2 infection. Among these proinflammatory mediators, chemokines tend to play a pivotal role in virus-mediated immunopathology. The C-C chemokine ligand 2 (CCL2), also known as monocyte chemoattractant protein-1 (MCP-1) is a potent proinflammatory cytokine and strong chemoattractant of monocytes, macrophages and CD4+ T cells bearing C-C chemokine receptor type-2 (CCR2). Besides controlling immune cell trafficking, CCL2 is also involved in multiple pathophysiological processes including systemic hyperinflammation associated cytokine release syndrome (CRS), organ fibrosis and blood coagulation. These pathological features are commonly manifested in severe and fatal cases of COVID-19. Given the crucial role of CCL2 in COVID-19 pathogenesis, the CCL2:CCR2 axis may constitute a potential therapeutic target to control virus-induced hyperinflammation and multi-organ dysfunction. Herein we describe recent advances on elucidating the role of CCL2 in COVID-19 pathogenesis, prognosis, and a potential target of anti-inflammatory interventions.
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COVID-19 , Quimiocina CCL2 , SARS-CoV-2 , Humanos , COVID-19/inmunología , COVID-19/virología , COVID-19/patología , Quimiocina CCL2/metabolismo , SARS-CoV-2/inmunología , SARS-CoV-2/patogenicidad , Pronóstico , Receptores CCR2/metabolismo , Biomarcadores , Antiinflamatorios/uso terapéutico , Síndrome de Liberación de Citoquinas/inmunología , Síndrome de Liberación de Citoquinas/virologíaRESUMEN
In the multi-organ segmentation task of medical images, there are some challenging issues such as the complex background, blurred boundaries between organs, and the larger scale difference in volume. Due to the local receptive fields of conventional convolution operations, it is difficult to obtain desirable results by directly using them for multi-organ segmentation. While Transformer-based models have global information, there is a significant dependency on hardware because of the high computational demands. Meanwhile, the depthwise convolution with large kernel can capture global information and have less computational requirements. Therefore, to leverage the large receptive field and reduce model complexity, we propose a novel CNN-based approach, namely adjacent-scale fusion U-Net with large kernel (ASF-LKUNet) for multi-organ segmentation. We utilize a u-shaped encoder-decoder as the base architecture of ASF-LKUNet. In the encoder path, we design the large kernel residual block, which combines the large and small kernels and can simultaneously capture the global and local features. Furthermore, for the first time, we propose an adjacent-scale fusion and large kernel GRN channel attention that incorporates the low-level details with the high-level semantics by the adjacent-scale feature and then adaptively focuses on the more global and meaningful channel information. Extensive experiments and interpretability analysis are made on the Synapse multi-organ dataset (Synapse) and the ACDC cardiac multi-structure dataset (ACDC). Our proposed ASF-LKUNet achieves 88.41% and 89.45% DSC scores on the Synapse and ACDC datasets, respectively, with 17.96M parameters and 29.14 GFLOPs. These results show that our method achieves superior performance with favorable lower complexity against ten competing approaches.ASF-LKUNet is superior to various competing methods and has less model complexity. Code and the trained models have been released on GitHub.
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Redes Neurales de la Computación , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Algoritmos , Corazón/diagnóstico por imagenRESUMEN
BACKGROUND: Multi-organ segmentation is a critical task in medical imaging, with wide-ranging applications in both clinical practice and research. Accurate delineation of organs from high-resolution 3D medical images, such as CT scans, is essential for radiation therapy planning, enhancing treatment outcomes, and minimizing radiation toxicity risks. Additionally, it plays a pivotal role in quantitative image analysis, supporting various medical research studies. Despite its significance, manual segmentation of multiple organs from 3D images is labor-intensive and prone to low reproducibility due to high interoperator variability. Recent advancements in deep learning have led to several automated segmentation methods, yet many rely heavily on labeled data and human anatomy expertise. PURPOSE: In this study, our primary objective is to address the limitations of existing semi-supervised learning (SSL) methods for abdominal multi-organ segmentation. We aim to introduce a novel SSL approach that leverages unlabeled data to enhance the performance of deep neural networks in segmenting abdominal organs. Specifically, we propose a method that incorporates a redrawing network into the segmentation process to correct errors and improve accuracy. METHODS: Our proposed method comprises three interconnected neural networks: a segmentation network for image segmentation, a teacher network for consistency regularization, and a redrawing network for object redrawing. During training, the segmentation network undergoes two rounds of optimization: basic training and readjustment. We adopt the Mean-Teacher model as our baseline SSL approach, utilizing labeled and unlabeled data. However, recognizing significant errors in abdominal multi-organ segmentation using this method alone, we introduce the redrawing network to generate redrawn images based on CT scans, preserving original anatomical information. Our approach is grounded in the generative process hypothesis, encompassing segmentation, drawing, and assembling stages. Correct segmentation is crucial for generating accurate images. In the basic training phase, the segmentation network is trained using both labeled and unlabeled data, incorporating consistency learning to ensure consistent predictions before and after perturbations. The readjustment phase focuses on reducing segmentation errors by optimizing the segmentation network parameters based on the differences between redrawn and original CT images. RESULTS: We evaluated our method using two publicly available datasets: the beyond the cranial vault (BTCV) segmentation dataset (training: 44, validation: 6) and the abdominal multi-organ segmentation (AMOS) challenge 2022 dataset (training:138, validation:16). Our results were compared with state-of-the-art SSL methods, including MT and dual-task consistency (DTC), using the Dice similarity coefficient (DSC) as an accuracy metric. On both datasets, our proposed SSL method consistently outperformed other methods, including supervised learning, achieving superior segmentation performance for various abdominal organs. These findings demonstrate the effectiveness of our approach, even with a limited number of labeled data. CONCLUSIONS: Our novel semi-supervised learning approach for abdominal multi-organ segmentation addresses the challenges associated with this task. By integrating a redrawing network and leveraging unlabeled data, we achieve remarkable improvements in accuracy. Our method demonstrates superior performance compared to existing SSL and supervised learning methods. This approach holds great promise in enhancing the precision and efficiency of multi-organ segmentation in medical imaging applications.
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INTRODUCTION: Donation after circulatory death (DCD) donors are becoming an important source of organs for heart-transplantation (HT), but there are limited data regarding their use in multiorgan-HT. METHODS: Between January 2020 and June 2023, we identified 87 adult multiorgan-HTs performed using DCD-donors [77 heart-kidney, 6 heart-lung, 4 heart-liver] and 1494 multiorgan-HTs using donation after brain death (DBD) donors (1141 heart-kidney, 165 heart-lung, 188 heart-liver) in UNOS. For heart-kidney transplantations (the most common multiorgan-HT combination from DCD-donors), we also compared donor/recipient characteristics, and early outcomes, including 6-month mortality using Kaplan-Meier (KM) and Cox hazards-ratio (Cox-HR). RESULTS: Use of DCD-donors for multiorgan-HTs in the United States increased from 1% in January to June 2020 to 12% in January-June 2023 (p < 0.001); but there was a wide variation across UNOS regions and center volumes. Compared to recipients of DBD heart-kidney transplantations, recipients of DCD heart-kidney transplantations were less likely to be of UNOS Status 1/2 at transplant (35.06% vs. 69.59%) and had lower inotrope use (22.08% vs. 43.30%), lower IABP use (2.60% vs. 26.29%), but higher durable CF-LVAD use (19.48% vs. 12.97%), all p < 0.01. Compared to DBD-donors, DCD-donors used for heart-kidney transplantations were younger [28(22-34) vs. 32(25-39) years, p = 0.004]. Recipients of heart-kidney transplantations from DCD-donors and DBD-donors had similar 6-month survival using both KM analysis, and unadjusted and adjusted Cox-HR models, including in propensity matched cohorts. Rates of PGF and in-hospital outcomes were also similar. CONCLUSIONS: Use of DCD-donors for multiorgan-HTs has increased rapidly in the United States and early outcomes of DCD heart-kidney transplantations are promising.
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Supervivencia de Injerto , Trasplante de Corazón , Donantes de Tejidos , Obtención de Tejidos y Órganos , Humanos , Femenino , Masculino , Obtención de Tejidos y Órganos/estadística & datos numéricos , Trasplante de Corazón/mortalidad , Persona de Mediana Edad , Donantes de Tejidos/provisión & distribución , Estados Unidos , Estudios de Seguimiento , Adulto , Pronóstico , Tasa de Supervivencia , Estudios Retrospectivos , Muerte EncefálicaRESUMEN
Cytokine Storm is a complex and heterogeneous state of life-threatening systemic inflammation and immunopathology. Autoinflammation is a mechanistic category of immune dysregulation wherein immunopathology originates due to poor regulation of innate immunity. The growing family of monogenic Systemic Autoinflammatory Diseases (SAIDs) has been a wellspring for pathogenic insights and proof-of-principle targeted therapeutic interventions. There is surprisingly little overlap between SAID and Cytokine Storm Syndromes, and there is a great deal to be inferred from those SAID that do, and do not, consistently lead to Cytokine Storm. This chapter will summarize how illustrations of the autoinflammatory paradigm have advanced the understanding of human inflammation, including the role of autoinflammation in familial HLH. Next, it will draw from monogenic SAID, both those with strong associations with cytokine storm and those without, to illustrate how the cytokine IL-18 links innate immune dysregulation and cytokine storm.
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Síndrome de Liberación de Citoquinas , Inmunidad Innata , Humanos , Síndrome de Liberación de Citoquinas/inmunología , Interleucina-18/inmunología , Interleucina-18/genética , Inflamación/inmunología , Enfermedades Autoinflamatorias Hereditarias/inmunología , Enfermedades Autoinflamatorias Hereditarias/genética , Animales , Citocinas/inmunología , Citocinas/metabolismoRESUMEN
Cystic echinococcosis (CE), the second most significant foodborne parasitic disease worldwide, poses a significant global health burden. Understanding its clinical and laboratory features is crucial for effective management. This study aimed to investigate the epidemiological, laboratory, and clinical characteristics of pediatric CE in an Iranian referral hospital. A cross-sectional study reviewed hospital records of patients with CE admitted to Children's Medical Center, Tehran, Iran, from 2011 to 2020. Data on demographics, diagnostics, clinical presentation, laboratory findings, and treatment were collected and analyzed. A total of 114 patients, with a mean age of 7.33 ± 2.9 years, were diagnosed with CE. The male-to-female ratio was 1.78, and 73.7% were urban residents. Abdominal pain (69%) and coughing (65%) were the most common symptoms. In confirming the cyst involvement across anatomical sites, pathology emerged as the most reliable method, with effectiveness ranging from 95% to 100%. Abdominal ultrasonography and computed tomography scan were frequently utilized imaging modalities, displaying effectiveness percentages of 71-85%. Liver and lung involvement predominated (66%), with 39% of cases showing multiorgan involvement. Spleen involvement was less common (6%), and neurological involvement was rare (1-2%). The majority of patients (n = 63, 67.7%) displayed cysts larger than 50 mm. All patients received albendazole treatment, and 104 patients (91.2%) underwent surgical procedures, with three postsurgical deaths. In conclusion, hospital records over 9 years indicate an increasing prevalence of CE, emphasizing the need for heightened awareness and effective public health interventions to control this parasitic infection.
RESUMEN
Diabetes mellitus is a typical metabolic disease that has become a major threat to human health worldwide. Ginseng polypeptide (GP), a small molecule active substance isolated from ginseng, has shown positive hypoglycemic effects in preliminary studies. However, its mechanism in ameliorating multiorgan damage in db/db mice is unclear. In this study, we utilized network pharmacology, molecular docking, and animal experiments to explore the targets and biological mechanisms of GP to ameliorate multiorgan damage in T2DM. The results showed that GP improves T2DM by inhibiting inflammation and oxidative damage, thereby alleviating hyperglycemia, insulin resistance, and multiorgan damage in db/db mice. These effects are potentially mediated through the PI3K-Akt signaling pathway and the MAPK signaling pathway. This study establishes GP's efficacy in alleviating T2DM and provides a robust theoretical basis for the development of new drugs or functional foods for treating this disease.