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Abstract In 2022, two new classifications of myeloid neoplasms and acute leukemias were published: the 5th edition WHO Classification (WHO-HAEM5) and the International Consensus Classification (ICC). As with prior classifications, the WHO-HAEM5 and ICC made updates to the prior classification (revised 4th edition WHO Classification, WHO-HAEM4R) based on a consensus of groups of experts, who examined new evidence. Both WHO-HAEM5 and ICC introduced several new disease entities that are based predominantly on genetic features, superseding prior morphologic definitions. While it is encouraging that two groups independently came to similar conclusions in updating the classification of myeloid neoplasms and acute leukemias, there are several divergences in how WHO-HAEM5 and ICC define specific entities as well as differences in nomenclature of certain diseases. In this review, we highlight the similarities and differences between the WHO-HAEM5 and ICC handling of myeloid neoplasms and acute leukemias and present a practical approach to diagnosing and classifying these diseases in this current era of two divergent classification guidelines.

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Abstract Genomic profiling of hematologic malignancies has augmented our understanding of variants that contribute to disease pathogenesis and supported development of prognostic models that inform disease management in the clinic. Tumor only sequencing assays are limited in their ability to identify definitive somatic variants, which can lead to ambiguity in clinical reporting and patient management. Here, we describe the MSK-IMPACT Heme cohort, a comprehensive data set of somatic alterations from paired tumor and normal DNA using a hybridization capture-based next generation sequencing platform. We highlight patterns of mutations, copy number alterations, and mutation signatures in a broad set of myeloid and lymphoid neoplasms. We also demonstrate the power of appropriate matching to make definitive somatic calls, including in patients who have undergone allogeneic stem cell transplant. We expect that this resource will further spur research into the pathobiology and clinical utility of clinical sequencing for patients with hematologic neoplasms.

Comprehensive genomic sequencing is becoming a critical component in the assessment of hematologic malignancies, with broad implications for patient management. In this context, unequivocally discriminating somatic from germline events is challenging but greatly facilitated by matched analysis of tumor:normal pairs. In contrast to solid tumors, conventional sources of normal control (peripheral blood, buccal swabs, saliva) could be highly involved by the neoplastic process, rendering them unsuitable. In this work we describe our real-world experience using cell free DNA (cfDNA) isolated from nail clippings as an alternate source of normal control, through the dedicated review of 2,610 tumor:nail pairs comprehensively sequenced by MSK-IMPACT-heme. Overall, we find nail cfDNA is a robust source of germline control for paired genomic studies. In a subset of patients, nail DNA may have tumor DNA contamination, reflecting unique attributes of the hematologic disease and transplant history. Contamination is generally low level, but significantly more common among patients with myeloid neoplasms (20.5%; 304/1482) compared to lymphoid diseases (5.4%; 61/1128) and particularly enriched in myeloproliferative neoplasms with marked myelofibrosis. When identified in patients with lymphoid and plasma-cell neoplasms, mutations commonly reflected a myeloid profile and correlated with a concurrent/evolving clonal myeloid neoplasm. For nails collected after allogeneic stem-cell transplantation, donor DNA was identified in 22% (11/50). In this cohort, an association with recent history of graft-vs-host disease was identified. These findings should be considered as a potential limitation for the use of nail as normal control but could also provide important diagnostic information regarding the disease process.

IntroductionIn vivo studies of cancer biology and assessment of therapeutic efficacy are critical to advancing cancer research and ultimately improving patient outcomes. Murine cancer models have proven to be an invaluable tool in pre-clinical studies. In this context, multi-parameter flow cytometry is a powerful method for elucidating the profile of immune cells within the tumor microenvironment and/or play a role in hematological diseases. However, designing an appropriate multi-parameter panel to comprehensively profile the increasing diversity of immune cells across different murine tissues can be extremely challenging.MethodsTo address this issue, we designed a panel with 13 fixed markers that define the major immune populations –referred to as the backbone panel– that can be profiled in different tissues but with the option to incorporate up to seven additional fluorochromes, including any marker specific to the study in question.ResultsThis backbone panel maintains its resolution across different spectral flow cytometers and organs, both hematopoietic and non-hematopoietic, as well as tumors with complex immune microenvironments.DiscussionHaving a robust backbone that can be easily customized with pre-validated drop-in fluorochromes saves time and resources and brings consistency and standardization, making it a versatile solution for immuno-oncology researchers. In addition, the approach presented here can serve as a guide to develop similar types of customizable backbone panels for different research questions requiring high-parameter flow cytometry panels.

Radiation stress is defined as the excess momentum caused by ocean waves, which exerts an indispensable impact on the upper-layer ocean conditions as waves pass by. Previous research concentrated on sea surface cooling caused by typhoons. In this paper, we investigated the effect of wave-induced radiation stress on upper-layer ocean temperature (including sea surface temperature (SST) and mixed-layer temperature) under typhoon conditions, as well as the effect of radiation stress on the surface current field. The FVCOM-SWAVE model, which is based on the SWAN model, is used to simulate the response of upper-layer ocean temperature to radiation stress. The simulated results, when validated with Jason-3 satellite and ARGO data, could reproduce the observed phenomenon well in general. Compared to simulations without radiation stress, the bias in the SST results is reduced by about 1 °C if the radiation stress term is taken into account. The mixed-layer depth temperature is expected to be simulated more accurately, with a root mean square error (RMSE) of less than 1.63 °C and a correlation coefficient (COR) of about 0.94. Results show that wave-induced radiation stress enhances the surface current and causes certain deviations to the right so that the upper water diverges and upwelling increases, resulting in a decrease in SST. When the influence of double typhoons is considered, the airflow of LEKIMA(L) rotates from the northwest toward KROSA (R), limiting the development of significant wave height (SWH) and reducing the cooling range. As a result, the present study is of tremendous importance in precisely forecasting the ocean state of the western North Pacific (WNP).

Underwater acoustic target recognition is a hot research area in acoustic signal processing. With the development of deep learning, feature extraction and neural network computation have become two major steps of recognition. Due to the complexity of the marine environment, traditional feature extraction cannot express the characteristics of the targets well. In this paper, we propose an underwater acoustic target recognition approach named VFR. VFR adopts a novel feature extraction method by fusing three-dimensional FBank features, and inputs the extracted features into a residual network, instead of the classical CNN network, plus cross-domain pre-training to perform target recognition. The experimental results show that VFR achieves 98.5% recognition accuracy on the randomly divided ShipsEar dataset and 93.8% on the time-divided dataset, respectively, which are better than state-of-the-art results.

With the evolution of machine learning and deep learning, more and more researchers have utilized these methods in the field of underwater acoustic target recognition. In these studies, convolutional neural networks (CNNs) are the main components of recognition models. In recent years, a neural network model Transformer that uses a self-attention mechanism was proposed and achieved good performance in deep learning. In this paper, we propose a Transformer-based underwater acoustic target recognition model STM. To the best of our knowledge, this is the first work to introduce Transformer into the underwater acoustic field. We compared the performance of STM with CNN, ResNet18, and other multi-class algorithm models. Experimental results illustrate that under two commonly used dataset partitioning methods, STM achieves 97.7% and 89.9% recognition accuracy, respectively, which are 13.7% and 50% higher than the CNN Model. STM also outperforms the state-of-the-art model CRNN-9 by 3.1% and ResNet18 by 1.8%.

The sound speed profile data of seawater provide an important basis for carrying out underwater acoustic modeling and analysis, sonar performance evaluation, and underwater acoustic assistant decision-making. The data volume of the high-resolution sound speed profile is vast, and the demand for data storage space is high, which severely limits the analysis and application of the high-resolution sound speed profile data in the field of marine acoustics. This paper uses the dictionary learning method to achieve sparse coding of the high-resolution sound speed profile and uses a compressed sparse row method to compress and store the sparse characteristics of the data matrix. The influence of related parameters on the compression rate and recovery data error is analyzed and discussed, as are different scenarios and the difference in compression processing methods. Through comparative experiments, the average error of the sound speed profile data compressed is less than 0.5 m/s, the maximum error is less than 3 m/s, and the data volume is about 10% to 15% of the original data volume. This method significantly reduces the storage capacity of high-resolution sound speed profile data and ensures the accuracy of the data, providing technical support for efficient and convenient access to high-resolution sound speed profiles.

For signal control intersection, the Phase-Movement-Combination (PMC) styles could directly impact the control performance of the signal scheme. Automated vehicles use mechatronics technology to drive autonomously and safely according to the predetermined lane trajectory, which caused the phase movement combination and Phase Combination (PC) schemes become more and more complicated. Therefore, this paper proposed a method to consider the extensive PMC styles by fractionalizing movement compatibility relationships, and used discrete mathematics to calculate overall Feasible Phase Combination (FPC) schemes according to the requirements of the signal phase. A corresponding optimal timing model was also established for FPC schemes by minimizing the average vehicle delay and maximizing the intersection capacity. Results were compared against the conventional PC schemes for a variety of demand scenarios. It was concluded that the proposed signal control optimization method was effective to optimize the intersection control scheme, depending on different demand scenarios. First published online 19 August 2020

Acoustic particle velocities can provide additional energy flow information of the sound field; thus, the vector acoustic model is attracting increasing attention. In the current study, a vector wavenumber integration (VWI) model was established to provide benchmark solutions of ocean acoustic propagation. The depth-separated wave equation was solved using finite difference (FD) methods with second- and fourth-order accuracy, and the sound source singularity in this equation was treated using the matched interface and boundary method. Moreover, the particle velocity was calculated using the wavenumber integration method, consistent with the calculation of the sound pressure. Furthermore, the VWI model was verified using acoustic test cases of the free acoustic field, the ideal fluid waveguide, the Bucker waveguide, and the Munk waveguide by comparing the solutions of the VWI model, the analytical formula, and the image method. In the free acoustic field case, the errors of the second- and fourth-order FD schemes for solving the depth-separated equation were calculated, and the actual orders of accuracy of the FD schemes were tested. Moreover, the time-averaged sound intensity (TASI) was calculated using the pressure and particle velocity, and the TASI streamlines were traced to visualize the time-independent energy flow in the acoustic field and better understand the distribution of the acoustic transmission loss.

TAFRO syndrome is a rare clinicopathologic variant of idiopathic multicentric Castleman disease characterized by Thrombocytopenia, Ascites (anasarca), myeloFibrosis, Renal dysfunction, and Organomegaly. Here, we report a case of TAFRO syndrome in an HIV-negative young Caucasian male who presented with fever, normocytic anemia, thrombocytopenia, and acute renal insufficiency. The serum interleukin-6 (IL-6) level was elevated. Chest and abdominal CT revealed bilateral pleural effusion, ascites, splenomegaly, and multiple mildly enlarged lymph nodes. An excisional biopsy of inguinal lymph node showed a few atrophic follicles and expansion of interfollicular areas by marked vascular proliferation and polytypic plasmacytosis. HHV-8 was negative. Subsequent bone marrow biopsy was normocellular with moderately increased megakaryocytes and occasional megakaryocytic emperipolesis. His signs and symptoms improved after treatment with methylprednisolone and tocilizumab (anti-IL-6 receptor antibody). Our study confirms the distinctive nature of this syndrome, which should allow for better recognition and appropriate therapy. Keywords: Castleman-Kojima disease, TAFRO syndrome, Idiopathic multicentric Castleman disease, IL-6, HHV-8

The accuracy and efficiency of sound field calculations highly concern issues of hydroacoustics. Recently, one-dimensional spectral methods have shown high-precision characteristics when solving the sound field but can solve only simplified models of underwater acoustic propagation, thus their application range is small. Therefore, it is necessary to directly calculate the two-dimensional Helmholtz equation of ocean acoustic propagation. Here, we use the Chebyshev–Galerkin and Chebyshev collocation methods to solve the two-dimensional Helmholtz model equation. Then, the Chebyshev collocation method is used to model ocean acoustic propagation because, unlike the Galerkin method, the collocation method does not need stringent boundary conditions. Compared with the mature Kraken program, the Chebyshev collocation method exhibits a higher numerical accuracy. However, the shortcoming of the collocation method is that the computational efficiency cannot satisfy the requirements of real-time applications due to the large number of calculations. Then, we implemented the parallel code of the collocation method, which could effectively improve calculation effectiveness.

The accurate calculation of the sound field is one of the most concerning issues in hydroacoustics. The one-dimensional spectral method has been used to correctly solve simplified underwater acoustic propagation models, but it is difficult to solve actual ocean acoustic fields using this model due to its application conditions and approximation error. Therefore, it is necessary to develop a direct solution method for the two-dimensional Helmholtz equation of ocean acoustic propagation without using simplified models. Here, two commonly used spectral methods, Chebyshev–Galerkin and Chebyshev–collocation, are used to correctly solve the two-dimensional Helmholtz model equation. Since Chebyshev–collocation does not require harsh boundary conditions for the equation, it is then used to solve ocean acoustic propagation. The numerical calculation results are compared with analytical solutions to verify the correctness of the method. Compared with the mature Kraken program, the Chebyshev–collocation method exhibits higher numerical calculation accuracy. Therefore, the Chebyshev–collocation method can be used to directly solve the representative two-dimensional ocean acoustic propagation equation. Because there are no model constraints, the Chebyshev–collocation method has a wide range of applications and provides results with high accuracy, which is of great significance in the calculation of realistic ocean sound fields.

The normal mode model is important in computational atmospheric acoustics. It is often used to compute the atmospheric acoustic field under a time-independent single-frequency sound source. Its solution consists of a set of discrete modes radiating into the upper atmosphere, usually related to the continuous spectrum. In this article, we present two spectral methods, the Chebyshev-Tau and Chebyshev-Collocation methods, to solve for the atmospheric acoustic normal modes, and corresponding programs are developed. The two spectral methods successfully transform the problem of searching for the modal wavenumbers in the complex plane into a simple dense matrix eigenvalue problem by projecting the governing equation onto a set of orthogonal bases, which can be easily solved through linear algebra methods. After the eigenvalues and eigenvectors are obtained, the horizontal wavenumbers and their corresponding modes can be obtained with simple processing. Numerical experiments were examined for both downwind and upwind conditions to verify the effectiveness of the methods. The running time data indicated that both spectral methods proposed in this article are faster than the Legendre-Galerkin spectral method proposed previously.

Measurable residual disease is associated with inferior outcomes in patients with acute myeloid leukemia (AML). Measurable residual disease monitoring enhances risk stratification and may guide therapeutic intervention. The European LeukemiaNet working party recently came to a consensus recommendation incorporating leukemia associated immunophenotype-based different from normal approach by multi-color flow cytometry for measurable residual disease evaluation. However, the analytical approach is highly expertise-dependent and difficult to standardize. Here we demonstrate that loss of plasmacytoid dendritic cell differentiation after 7+3 induction in AML is highly specific for measurable residual disease positivity (specificity 97.4%) in a uniformly treated patient cohort. Moreover, loss of plasmacytoid dendritic cell differentiation as determined by a blast-to-plasmacytoid dendritic cell ratio >10 was strongly associated with inferior overall and relapse-free survival (RFS) [Hazard ratio 2.79, 95% confidence interval (95%CI): 0.98-7.97; P=0.077) and 3.83 (95%CI: 1.51-9.74; P=0.007), respectively), which is similar in magnitude to measurable residual disease positivity. Importantly, measurable residual disease positive patients who reconstituted plasmacytoid dendritic cell differentiation (blast/ plasmacytoid dendritic cell ratio

In order to retrieve similar trademarks from large-scale trademark databases, combining the characteristics of trademark images, this paper presents a trademark image retrieval method based on regional and border feature fusion. Based on the target image extraction, the proposed approach describes the target region and border features. The region feature description is mainly based on the concept of partition block statistics. The region is divided into equal-area unit using concentric circles, and feature extraction is performed in each small block unit. For the border feature description, this study first detect corners, and then construct a Delaunay graph and extract features by combining the corner detected and the Delaunay triangulation reconstruction. In the search process, the method also incorporates information such as the trademark's color characteristics, trademark classification, and trademark keywords. The present study carried out image retrieval experiment on CE-SHAPE-1 database containing 1400 MPEG-7 core experimental shape, a classification trademark database containing 2000 images, and a national trademark database containing approximately 4.89 million images. The experimental results show that the proposed approach combines the advantages of region and border feature description, and can choose the best among various local optimizations, which makes the retrieval result more effective, more in line with human visual perception, and improves the retrieval accuracy.

Atopic dermatitis (AD) is a chronic inflammatory skin disease. Here, we show that phospholipase C-β3 (PLC-β3)-deficient mice spontaneously develop AD-like skin lesions and more severe allergen-induced dermatitis than wild-type mice. Mast cells were required for both AD models and remarkably increased in the skin of Plcb3−/− mice because of the increased Stat5 and reduced SHP-1 activities. Mast cell-specific deletion of Stat5 gene ameliorated allergen-induced dermatitis, whereas that of Shp1 gene encoding Stat5-inactivating SHP-1 exacerbated it. PLC-β3 regulates the expression of periostin in fibroblasts and TSLP in keratinocytes, two proteins critically involved in AD pathogenesis. Furthermore, polymorphisms in PLCB3, SHP1, STAT5A, and STAT5B genes were associated with human AD. Mast cell expression of PLC-β3 was inversely correlated with that of phospho-STAT5, and increased mast cells with high levels of phospho-STAT5 were found in lesional skin of some AD patients. Therefore, STAT5 regulatory mechanisms in mast cells are important for AD pathogenesis.

The histological diagnosis of luetic lymphadenitis remains challenging for the pathologists particularly when the pertinent clinical information is lacking. Here we report a case of a 23-year-old male, an immigrant from South America, who had a history of epithelioid hemangioma, presented with a painless enlarged left inguinal lymph node. In addition to the characteristic follicular hyperplasia and capsular thickening, lymphohistiocytic nodules are also seen. Recognition of such rare nodular proliferation can be helpful in diagnosing luetic lymphadenitis.

Circulating immature platelet fraction (IPF) reflects real-time thrombopoiesis and correlates with platelet recovery from thrombocytopenic presentations. To understand the dynamics of IPF in platelet transfusions, we quantified the %-IPF in single-donor platelet components (SDP) during prolonged storage. %-IPF significantly increased from baseline by day 5 post-donation. Absolute IPF counts (A-IPC) had similar significant increments. However, gamma-irradiation suppressed the increments of %-IPF and A-IPC by >50%. Ultrastructural analysis of SDP units at day 10 showed well preserved morphology of immature platelets. Our findings suggest that IPF might actively expand ex-vivo and may have a longer shelf life than their mature counterparts. Closer study of IPF may be of critical clinical importance for transfusion practices.

CDX2, a master transcriptional regulator of intestinal cell differentiation and survival, has been used as a marker to indicate colorectal lineage in adenocarcinomas of unknown origin. Pancreatic ductal adenocarcinoma (PDAC) is one of the most common causes for adenocarcinomas of unknown origin, but CDX2 expression in pancreatic disease remains unclear. In this study, we systemically and extensively investigated the expression and role of CDX2 in PDAC. We reported that CDX2 expression is weak and heterogeneous is all normal pancreas and chronic pancreatitis. It is largely expressed in epithelial-lining cells of pancreatic ducts including main ducts, inter-lobular ducts, intra-lobular ducts, intercalated ducts and centroacinar cells, but not in acinar cells or islet cells. CDX2 expression is down regulated during the transformation process from PanIN to PDAC. Only one third of PDACs retain some degree of CDX2 expression, and this group of PDACs have reduced median survival time compared to that of CDX2 negative group (308 days vs. 586 days, p = 0.0065). Metastatic PDACs remain similar expression pattern to that of the primary sites. Our study clearly demonstrates CDX2 expression in pancreatic diseases including PDAC, which is practically important when CDX2 is used to establish the primary sites of adenocarcinomas of unknown origin. In addition, our study also provides CDX2 as a prognostic marker for PDAC and implicates an important role of CDX2 in the development of normal pancreas and PDAC.

Constitutive activation of the transcription factor Stat5 in hematopoietic stem/progenitor cells leads to various hematopoietic malignancies including myeloproliferative neoplasm (MPN). Our recent study found that phospholipase C (PLC)-β3 is a novel tumor suppressor involved in MPN, lymphoma and other tumors. Stat5 activity is negatively regulated by the SH2 domain-containing protein phosphatase SHP-1 in a PLC-β3-dependent manner. PLC-β3 can form the multimolecular SPS complex together with SHP-1 and Stat5. The close physical proximity of SHP-1 and Stat5 brought about by interacting with the C-terminal segment of PLC-β3 (PLC-β3-CT) accelerates SHP-1-mediated dephosphorylation of Stat5. Here we identify the minimal sequences within PLC-β3-CT required for its tumor suppressor function. Two of the three Stat5-binding noncontiguous regions, one of which also binds SHP-1, substantially inhibited in vitro proliferation of Ba/F3 cells. Surprisingly, an 11-residue Stat5-binding peptide (residues 988-998) suppressed Stat5 activity in Ba/F3 cells and in vivo proliferation and myeloid differentiation of hematopoietic stem/progenitor cells. Therefore, this study further defines PLC-β3-CT as the Stat5- and SHP-1-binding domain by identifying minimal functional sequences of PLC-β3 for its tumor suppressor function and implies their potential utility in the control of hematopoietic malignancies.

Introduction: In vivo studies of cancer biology and assessment of therapeutic efficacy are critical to advancing cancer research and ultimately improving patient outcomes. Murine cancer models have proven to be an invaluable tool in preclinical studies. In this context, multi-parameter flow cytometry is a powerful method for elucidating the profile of immune cells within the tumor microenvironment and/or play a role in hematological diseases. However, designing an appropriate multi-parameter panel to comprehensively profile the increasing diversity of immune cells across different murine tissues can be extremely challenging. Methods: To address this issue, we designed a panel with 13 fixed markers that define the major immune populations -referred to as the backbone panel-that can be profiled in different tissues but with the option to incorporate up to seven additional fluorochromes, including any marker specific to the study in question. Results: This backbone panel maintains its resolution across different spectral flow cytometers and organs, both hematopoietic and non-hematopoietic, as well as tumors with complex immune microenvironments. Discussion: Having a robust backbone that can be easily customized with prevalidated drop-in fluorochromes saves time and resources and brings consistency and standardization, making it a versatile solution for immunooncology researchers. In addition, the approach presented here can serve as a guide to develop similar types of customizable backbone panels for different research questions requiring high-parameter flow cytometry panels. [ABSTRACT FROM AUTHOR]