Myeloid sarcoma (MS) is a rare hematological neoplasm with poor prognosis, posing a significant clinical challenge due to the absence of effective and standardized treatments. We conducted a retrospective analysis of 162 MS patients treated at 12 centers to compare outcomes between intensive chemotherapy and allogeneic hematopoietic stem cell transplantation (allo-HSCT). Our analysis revealed that allo-HSCT demonstrated superior overall survival (OS) within the initial 36 months compared to intensive chemotherapy alone (p = 0.
View Article and Find Full Text PDFBone Marrow Transplant
November 2024
There are two main categories of networks studied in the complexity physics community: Monopartite and bipartite networks. In this paper, we present a general framework that provides insights into the connection between these two classes. When a random bipartite network is projected into a monopartite network, under quite general conditions, the result is a nonrandom monopartite network, the features of which can be studied analytically.
View Article and Find Full Text PDFHaematologica
June 2024
Adhesion molecules play essential roles in the homeostatic regulation and malignant transformation of hematopoietic cells. The dysregulated expression of adhesion molecules in leukemic cells accelerates disease progression and the development of drug resistance. Thus, targeting adhesion molecules represents an attractive anti-leukemic therapeutic strategy.
View Article and Find Full Text PDFChronic myelomonocytic leukemia (CMML) is a clonal hematopoietic stem cell malignancy, and allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the only curable treatment. The outcomes after transplant are influenced by both disease characteristics and patient comorbidities. To develop a novel prognostic model to predict the post-transplant survival of CMML patients, we identified risk factors by applying univariable and multivariable Cox proportional hazards regression to a derivation cohort.
View Article and Find Full Text PDFFront Psychol
November 2022
With the popularity of Internet technology, reading has developed in the direction of digitalization and mobileization. And entering the metaverse era, both the subject and object of reading may be redefined, presenting a new developmental pattern. This process brings a crisis to reading, such as the fragmentation of reading, the obstruction of reading needs, and the replacement of classical reading.
View Article and Find Full Text PDFBetween 2020 and 2021, 31,525 hematopoietic stem cell transplantations (HSCTs) were reported to the Chinese Blood and Marrow Transplantation Registry Group throughout mainland China. In this report, we describe the activity and current trends for HSCT in China during the SARS-CoV-2 pandemic. In 2020, a total of 13,415 cases of HSCT were reported from 166 transplantation teams, and 75% (10,042 cases) were allogeneic HSCTs.
View Article and Find Full Text PDFBackground: Oral cavity squamous cell carcinoma (OSCC) is an aggressive malignant tumor with high recurrence and poor prognosis in the advanced stage. Patient-derived xenografts (PDXs) serve as powerful preclinical platforms for drug testing and precision medicine for cancer therapy. We assess which molecular signatures affect tumor engraftment ability and tumor growth rate in OSCC PDXs.
View Article and Find Full Text PDFWith the popularization of higher education and the promotion of college enrollment expansion, the number of college graduates increases sharply. At the same time, the continuous transformation and upgrading of the industrial structure put forward higher requirements on the employability of college students, which leads to the imbalance between supply and demand in the labor market. The key to dealing with employment difficulties lie in the improvement of college students' employability.
View Article and Find Full Text PDFZhongguo Shi Yan Xue Ye Xue Za Zhi
October 2021
Objective: To analyze the clinical efficacy and safety of allogeneic hematopoietic stem cell transplantation (allo-HSCT) for paroxysmal nocturnal hemoglobinuria (PNH), and preliminarily explore the role of an improved post-transplantation cyclophosphamide (PTCy) based conditioning regimen in PNH patients receiving transplantation.
Methods: Clinical related data of PNH sufferers receiving allo-HSCT in Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology were collected, and hematopoietic reconstitution, chimerism, PNH cloning, graft-versus-host disease (GVHD), infection, and survival were analyzed.
Results: Totally five PNH patients receiving allo-HSCT were enrolled, including 1 case with classic PNH, 3 cases with aplastic anemia-PNH syndrome, 1 case with myelodysplastic syndrome, three of them (case 1-3) received the improved PTCy based conditioning regimen before HSCT.
GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country's GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is finding the right direction to upgrade the industry so that the country can enhance its competitiveness.
View Article and Find Full Text PDFZhongguo Shi Yan Xue Ye Xue Za Zhi
October 2018
Objective: To analyze the effect of autologous hematopoietic stem cell transplantation in the treatment of patients with recurrent refractory B cell non-Hodgkin's lymphoma (NHL) and the related factors affecting the prognosis.
Methods: The clinical data of 47 cases of recurrent refractory B cell NHL treated in our hospital were retrospectively analyzed. Survival curves were drawn by Kaplan-Meier, and survival analyses were performed.
The Belt and Road initiative (BRI) was announced in 2013 by the Chinese government. Its goal is to promote the cooperation between European and Asian countries, as well as enhancing the trust between members and unifying the market. Since its creation, more and more developing countries are joining the initiative.
View Article and Find Full Text PDFComplex networks are often used to represent systems that are not static but grow with time: People make new friendships, new papers are published and refer to the existing ones, and so forth. To assess the statistical significance of measurements made on such networks, we propose a randomization methodology-a time-respecting null model-that preserves both the network's degree sequence and the time evolution of individual nodes' degree values. By preserving the temporal linking patterns of the analyzed system, the proposed model is able to factor out the effect of the system's temporal patterns on its structure.
View Article and Find Full Text PDFUnderstanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by being repeatedly and persistently among the first to collect the items that later become hugely popular.
View Article and Find Full Text PDFAccurate identification of effective epidemic threshold is essential for understanding epidemic dynamics on complex networks. In this paper, we systematically study how the recovery rate affects the susceptible-infected-removed spreading dynamics on complex networks, where synchronous and asynchronous updating processes are taken into account. We derive the theoretical effective epidemic threshold and final outbreak size based on the edge-based compartmental theory.
View Article and Find Full Text PDFPageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters.
View Article and Find Full Text PDFIndividuals are always limited by some inelastic resources, such as time and energy, which restrict them to dedicate to social interaction and limit their contact capacities. Contact capacity plays an important role in dynamics of social contagions, which so far has eluded theoretical analysis. In this paper, we first propose a non-Markovian model to understand the effects of contact capacity on social contagions, in which each adopted individual can only contact and transmit the information to a finite number of neighbors.
View Article and Find Full Text PDFThe organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability.
View Article and Find Full Text PDFRecommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs.
View Article and Find Full Text PDFHow to design an accurate and robust ranking algorithm is a fundamental problem with wide applications in many real systems. It is especially significant in online rating systems due to the existence of some spammers. In the literature, many well-performed iterative ranking methods have been proposed.
View Article and Find Full Text PDFOnline users nowadays are facing serious information overload problem. In recent years, recommender systems have been widely studied to help people find relevant information. Adaptive social recommendation is one of these systems in which the connections in the online social networks are optimized for the information propagation so that users can receive interesting news or stories from their leaders.
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