Search

The NUP214-ABL1 fusion gene is a constitutively active tyrosine kinase that can be detected in 6% of T-cell acute lymphoblastic leukemia (T-ALL) patients, and it can also be found in B-cell acute lymphoblastic leukaemia (B-ALL). However the NUP214-ABL1 fusion in acute myeloid leukemia (AML) has not yet been reported. Up to now, the sensitivity of NUP214-ABL1-positive patients to tyrosine kinase inhibitor (TKI) is still controversial. Here we report the first case of an AML patient carrying NUP214-ABL1 fusion gene. The conventional AML chemotherapy regimen for the patient was successful. Identification of additional AML patients with NUP214-ABL1 fusion gene will provide treatment experience and prognostic evaluation.

Background: Adult T-cell acute lymphoblastic leukemia (T-ALL) is a rare hematological malignancy and significantly linked to poor outcomes. Early T-cell precursor (ETP) leukemia is a unique subtype of T-ALL. The aim of this study is to compare the differences between ETP and non-ETP ALLs in China.Methods: We retrospectively analyzed the records of 122 adult T-ALL patients diagnosed and treated at our center between January 2014 and June 2019. All the patients enrolled were categorized into ETP and non-ETP ALL by immunophenotype, and further statistical analyses about clinical data and prognostic factors were performed.Results: Among the 122 cases, the male-to-female ratio was 2.8:1, and the median age is 29 (range, 16–82) years. Except for 10 patients with insufficient immunophenotyping results, 47.3% (53/112) are ETP and 52.7% (59/112) are non-ETP. Compared with non-ETP patients, ETP-ALL patients had lower white blood cell counts and lactate dehydrogenase levels, while they were older and had higher platelet counts and fibrinogen levels (all p < 0.05). Complete remission (CR) was achieved in 68.0% (83/122) of patients, 64.2 and 76.3% in ETP and non-ETP, respectively (p = 0.160). In total, 44.6% (37/83) of patients relapsed. Allogeneic stem cell transplantation (allo-SCT) was successfully performed in 36.1% (44/122) of patients, of which 79.5% (35/44) were in CR1. With a median follow-up of 9.1 (range, 0.5–70.3) months, the estimated 2-year overall survival (OS) and relapse-free survival (RFS) rates for the cohort were 38.0 ± 5.1 and 39.1 ± 6.3%, respectively. In the ETP group, the 2-year OS rate was 40.7 ± 8.2% and the RFS rate was 47.2 ± 10.7%, while in the non-ETP group, the 2-year OS rate was 37.9 ± 7.0% and the RFS rate was 39.2 ± 8.3% (both p > 0.05). In the landmark analysis of CR1 patients who had a survival of more than 6 months, the allo-SCT group had significantly better survival outcomes than the chemotherapy group, and the 2-year OS rates and RFS rates were 80.1 ± 7.3 vs. 28.4 ± 8.4% and 68.9 ± 8.8 vs. 12.8 ± 7.2%, respectively (both p < 0.0001). A multivariate analysis suggests that allo-SCT acts as an independent prognostic factor for both OS and RFS.Conclusions: Our results revealed that ETP accounted for a high proportion of T-ALL in Chinese. There are no CR rates and prognosis differences between ETP and non-ETP. Allo-SCT in CR1 can significantly improve patients' survival.

The effect of time from diagnosis to treatment (TDT) on overall survival of patients with acute myeloid leukemia (AML) remains obscure. Furthermore, whether chemotherapy delay impacts overall survival (OS) of patients with a special molecular subtype has not been investigated. Here, we enrolled 364 cases of AML to assess the effect of TDT on OS by fractional polynomial regression in the context of clinical parameters and genes of FLT3ITD, NPM1, CEBPA, DNMT3a, and IDH1/2 mutations. Results of the current study show IDH1/2 mutations are associated with older age, M0 morphology, an intermediate cytogenetic risk group, and NPM1 mutations. TDT associates with OS for AML patients in a nonlinear pattern with a J shape. Moreover, adverse effect of delayed treatment on OS was observed in patients with IDH1/2 mutations, but not in those with IDH1/2 wildtype. Therefore, initiating chemotherapy as soon as possible after diagnosis might be a potential strategy to improve OS in AML patients with IDH1/2 mutations.

In this study, the cavitation effect induced by two charges in underwater explosions near free surfaces is numerical researched by two dimensional compressible multiphase fluids based on a four-equation system with a phase transition model. The occurrence of the generation, development, and collapse of cavitation in two-charge underwater explosions near free surfaces can be captured directly. The detailed density, pressure, and vapor volume fraction contours during the interaction process are obtained and can better reveal the characteristic underlying the cavitation, free surface, and explosion bubbles. Numerical results reveal that the cavitation domain has expanded to an area much deeper than the explosion bubble location in two-charge underwater explosions, which should be paid enough attention due to its influence on the input load of underwater structures. The detailed density and pressure contours during the interaction process can also be captured and can better reveal the mechanism underlying the explosion bubble, cavitation, and surface wave dynamics. The present results can expand the currently limited database of multiphase fluid in underwater explosions and also provide new insights into the strong nonlinear interaction between underwater explosion and cavitation, which provides a deep understanding of multi-point explosions.

Underwater explosion cavitation is generally simulated using a one-fluid model based on compressible multicomponent flows. Owing to the lack of mass and heat transfer between liquid and vapor phases, this model is incapable of extensively analyzing the cavitation mechanism in underwater explosion. In this study, we extend the phase transition model provided by Chiapolino et al. to the field of underwater explosion cavitation. The model presents a more accurate description of the thermodynamics of cavitation processes involving liquid–vapor phase transition. The numerical results show that the phase transition exhibits significant potential in the study of underwater explosion cavitation, and the likely occurrence of creation, development, and collapse of the cavitation can be captured. A vortex band composed of a large number of tiny cavitation bubbles can be observed in the numerical results, which is consistent with the experiment in underwater explosion near a free surface. The variation range of the cavitation domain calculated by the phase transition model is basically consistent with the experiment, which proves the reliability and accuracy of the calculation model. Meanwhile, the distribution characteristics of quantities such as density, pressure, and vapor phase volume fraction in the cavitation domain can be effectively obtained in simulation, which are usually difficult to capture in experiments. The creation mechanism of cavitation near a free surface and rigid wall is different. However, the collapse mechanism is similar. The results of this study could provide an in-depth understanding of the dynamic behavior of cavitation in underwater explosion.

Objective. Posttransplantation diabetes mellitus (PTDM) is a known complication of transplantation that affects the prognosis. Tacrolimus (Tac or FK506) is a widely used immunosuppressant that has been reported to be a risk factor for PTDM and to further induce complications in heart and skeletal muscles, but the mechanism is still largely unknown. In our preliminary experiments, we found that after Tac treatment, blood glucose increased, and the weight of skeletal muscle declined. Here, we hypothesize that tacrolimus can induce PTDM and influence the atrophy of skeletal muscle. Methods. We designed preliminary experiments to establish a tacrolimus-induced PTDM model. Gene expression profiles in quadriceps muscle from this rat model were characterized by oligonucleotide microarrays. Then, differences in gene expression profiles in muscle from PTDM rats that received tacrolimus and control subjects were analyzed by using GeneSpring GX 11.0 software (Agilent). Functional annotation and enrichment analysis of differentially expressed genes (DEGs) helped us identify clues for the side effects of tacrolimus. Results. Our experiments found that the quadriceps in tacrolimus-induced PTDM group were smaller than those in the control group. The study identified 275 DEGs that may be responsible for insulin resistance and the progression of PTDM, including 86 upregulated genes and 199 downregulated genes. GO and KEGG functional analysis of the DEGs showed a significant correlation between PTDM and muscle development. PPI network analysis screened eight hub genes and found that they were related to troponin and tropomyosin. Conclusions. This study explored the molecular mechanism of muscle atrophy in a tacrolimus-induced PTDM model by bioinformatics analyses. We identified 275 DEGs and identified significant biomarkers for predicting the development and progression of tacrolimus-induced PTDM.