Feature extraction and pattern recognition of gas pipeline flow noise signals in a strong noisy background.

The purpose of this study is to put forward a feature extraction and pattern recognition method for the flow noise signal of natural gas pipelines in view of the complex situation brought by the rapid development and expansion of urban natural gas infrastructure in China, especially in the case that there are active and abandoned pipelines, metal and nonmetal pipelines, and natural gas, water and power pipelines coexist in the underground of the city. Because the underground situation is unknown, gas leakage incidents caused by natural gas pipeline rupture occur from time to time, posing a threat to personal safety. Therefore, the motivation of this study is to provide a feasible method to accelerate the aging, renewal and transformation of urban natural gas pipelines to ensure the safe operation of urban natural gas pipeline network and promote the high-quality development of urban economy. Through the combination of experimental test and numerical simulation, this study establishes a database of urban natural gas pipeline flow noise signals, and uses principal component analysis (PCA) to extract the characteristics of flow noise signals, and develops a mathematical model for feature extraction. Then, a classification and recognition model based on backpropagation neural network (BPNN) is constructed, which realizes the detection and recognition of convective noise signals. The research results show that the theoretical method based on acoustic feature analysis provides guidance for the orderly and safe construction of urban natural gas pipeline network and ensures its safe operation. The research conclusion shows that through the simulation analysis of 75 groups of gas pipeline flow noise under different working conditions. Combined with the experimental verification of ground flow noise signals, the feature extraction and pattern recognition method proposed in this study has a recognition accuracy of up to 97% under strong noise background, which confirms the accuracy of numerical simulation and provides theoretical basis and technical support for the detection and recognition of urban gas pipeline flow noise.

WNT inhibitory factor 1 (WIF1) is a novel fusion partner of RUNX family transcription factor 1 (RUNX1) in acute myeloid leukemia with t(12;21)(q14;q22).

As a member of the core transcription factor family, RUNX1 plays an important role in stem cell differentiation. RUNX1 rearrangements are common in myeloid and lymphoid tumors [1]. (Blood 129(15):2070-2082, 2017). One of the most commonly detected abnormalities in acute myeloid leukemia (AML) is the translocation t(8;21)(q22;q22) (Blood Adv 4(1):229-238, 2020), resulting in a RUNX1::RUNX1T1 fusion. Occasionally, RUNX1 is translocated with other genes. This article describes an AML patient with a specific chromosomal translocation involving the RUNX1 gene and the identification of the RUNX1::WIF1 fusion. Chromosomal abnormalities were detected through karyotype analysis, break gene involved was identified via fluorescence in situ hybridization (FISH), and the novel fusion was identified through transcriptome sequencing and subsequently confirmed through reverse transcription-polymerase chain reaction (RT-PCR) and Sanger sequencing. A 79-year-old female patient diagnosed with AML was found to have a t(12;21)(q14;q12) translocation. FISH analysis provided evidence of RUNX1 gene rearrangement. Additionally, transcriptomic sequencing revealed a novel fusion known as RUNX1::WIF1, which consists of RUNX1 exon 2 and WIF1 exon 3. The novel fusion was further confirmed through RT-PCR and Sanger sequencing. We identified WIF1 as a novel fusion partner of RUNX1 in AML. Additionally, this is the first report of a RUNX1 fusion gene with the break point in intron 2, resulting in an out-of-frame fusion. Further research is needed to investigate the impact of this novel fusion on the establishment and progression of the disease.

Clinical laboratory characteristics and gene mutation spectrum of Ph-negative MPN patients with atypical variants of JAK2, MPL, or CALR.

OBJECTIVE: To evaluate the incidence, clinical laboratory characteristics, and gene mutation spectrum of Ph-negative MPN patients with atypical variants of JAK2, MPL, or CALR. METHODS: We collected a total of 359 Ph-negative MPN patients with classical mutations in driver genes JAK2, MPL, or CALR, and divided them into two groups based on whether they had additional atypical variants of driver genes JAK2, MPL, or CALR: 304 patients without atypical variants of driver genes and 55 patients with atypical variants of driver genes. We analyzed the relevant characteristics of these patients. RESULTS: This study included 359 patients with Ph-negative MPNs with JAK2, MPL, or CALR classical mutations and found that 55 (15%) patients had atypical variants of JAK2, MPL, or CALR. Among them, 28 cases (51%) were male, and 27 (49%) were female, with a median age of 64 years (range, 21-83). The age of ET patients with atypical variants was higher than that of ET patients without atypical variants [70 (28-80) vs. 61 (19-82), p = 0.03]. The incidence of classical MPL mutations in ET patients with atypical variants was higher than in ET patients without atypical variants [13.3% (2/15) vs. 0% (0/95), p = 0.02]. The number of gene mutations in patients with atypical variants of driver genes PV, ET, and Overt-PMF is more than in patients without atypical variants of PV, ET, and Overt-PMF [PV: 3 (2-6) vs. 2 (1-7), p < 0.001; ET: 4 (2-8) vs. 2 (1-7), p < 0.05; Overt-PMF: 5 (2-9) vs. 3 (1-8), p < 0.001]. The incidence of SH2B3 and ASXL1 mutations were higher in MPN patients with atypical variants than in those without atypical variants (SH2B3: 16% vs. 6%, p < 0.01; ASXL1: 24% vs. 13%, p < 0.05). CONCLUSION: These data indicate that classical mutations of JAK2, MPL, and CALR may not be completely mutually exclusive with atypical variants of JAK2, MPL, and CALR. In this study, 30 different atypical variants of JAK2, MPL, and CALR were identified, JAK2 G127D being the most common (42%, 23/55). Interestingly, JAK2 G127D only co-occurred with JAK2V617F mutation. The incidence of atypical variants of JAK2 in Ph-negative MPNs was much higher than that of the atypical variants of MPL and CALR. The significance of these atypical variants will be further studied in the future.

The Diagnosis of Chronic Myeloid Leukemia with Deep Adversarial Learning.

Chronic myeloid leukemia (CML) is a clonal proliferative disorder of granulocytic lineage, with morphologic evaluation as the first step for a definite diagnosis. This study developed a conditional generative adversarial network (cGAN)-based model, CMLcGAN, to segment megakaryocytes from myeloid cells in bone marrow biopsies. After segmentation, the statistical characteristics of two types of cells were extracted and compared between patients and controls. At the segmentation phase, the CMLcGAN was evaluated on 517 images (512 × 512) which achieved a mean pixel accuracy of 95.1%, a mean intersection over union of 71.2%, and a mean Dice coefficient of 81.8%. In addition, the CMLcGAN was compared with seven other available deep learning-based segmentation models and achieved a better segmentation performance. At the clinical validation phase, a series of seven-dimensional statistical features from various cells were extracted. Using the t-test, five-dimensional features were selected as the clinical prediction feature set. Finally, the model iterated 100 times using threefold cross-validation on whole slide images (58 CML cases and 31 healthy cases), and the final best AUC was 84.93%. In conclusion, a CMLcGAN model was established for multiclass segmentation of bone marrow cells that performed better than other deep learning-based segmentation models.

Using artificial intelligence technology to fight COVID-19: a review.

In late December 2019, a new type of coronavirus was discovered, which was later named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Since its discovery, the virus has spread globally, with 2,975,875 deaths as of 15 April 2021, and has had a huge impact on our health systems and economy. How to suppress the continued spread of new coronary pneumonia is the main task of many scientists and researchers. The introduction of artificial intelligence technology has provided a huge contribution to the suppression of the new coronavirus. This article discusses the main application of artificial intelligence technology in the suppression of coronavirus from three major aspects of identification, prediction, and development through a large amount of literature research, and puts forward the current main challenges and possible development directions. The results show that it is an effective measure to combine artificial intelligence technology with a variety of new technologies to predict and identify COVID-19 patients.

The role of computational fluid dynamics tools on investigation of pathogen transmission: Prevention and control.

Transmission mechanics of infectious pathogen in various environments are of great complexity and has always been attracting many researchers' attention. As a cost-effective and powerful method, Computational Fluid Dynamics (CFD) plays an important role in numerically solving environmental fluid mechanics. Besides, with the development of computer science, an increasing number of researchers start to analyze pathogen transmission by using CFD methods. Inspired by the impact of COVID-19, this review summarizes research works of pathogen transmission based on CFD methods with different models and algorithms. Defining the pathogen as the particle or gaseous in CFD simulation is a common method and epidemic models are used in some investigations to rise the authenticity of calculation. Although it is not so difficult to describe the physical characteristics of pathogens, how to describe the biological characteristics of it is still a big challenge in the CFD simulation. A series of investigations which analyzed pathogen transmission in different environments (hospital, teaching building, etc) demonstrated the effect of airflow on pathogen transmission and emphasized the importance of reasonable ventilation. Finally, this review presented three advanced methods: LBM method, Porous Media method, and Web-based forecasting method. Although CFD methods mentioned in this review may not alleviate the current pandemic situation, it helps researchers realize the transmission mechanisms of pathogens like viruses and bacteria and provides guidelines for reducing infection risk in epidemic or pandemic situations.

Identification of acquired PIGA mutations and additional variants by next-generation sequencing in paroxysmal nocturnal hemoglobinuria.

INTRODUCTION: Paroxysmal Nocturnal Hemoglobinuria (PNH) is an acquired clonal disease of hematopoietic stem cells. It is caused by somatic mutation of the X-linked PIGA gene, resulting in a deficient expression of glycosylphosphatidylinositol-anchored proteins (GPI-APs). In this study, we aimed to explore the diagnostic value of next-generation sequencing (NGS) and potential molecular basis in PNH patients. METHODS: Genomic DNA of 85 PNH patients was analyzed by a 114-gene NGS panel. RESULTS: Mutational analysis of PIGA identified 124 mutations in 92% PNH patients, including 101 distinct mutations and 23 recurrent mutations. Among them, 102 mutations were newly reported. Most mutations were located in exon 2 of PIGA gene, and truncated mutation was the most common one. Other mutations were detected in 26 out of 85 cases, including five cases of DNMT3A variants, four cases of ASXL1 variants, and four cases of U2AF1 variants. Clonal analysis was performed in one case and outlined a linear evolution pattern in classic PNH. There was a positive correlation between number of PIGA mutations and fraction of GPI-APs deficient granulocytes. CONCLUSION: The detection of PIGA mutations and additional variants by targeted NGS not only shed light on the genetic characteristics of PNH, but also provided an important reference value in the diagnosis of PNH at molecular level.

[Co-occurrence of t(8;21)(q22;q22) and t(9;22)(q34;q11) in a case with chronic myelogenous leukemia].

OBJECTIVE: To delineate laboratory and clinical characteristics of a case with chronic myelogenous leukemia (CML) and co-occurrence of t(9;22)(q34;q11) and t(8;21)(q22;q22). METHODS: The patient was subjected to cytogenetic, molecular, morphological and immunophenotypic analyses. RESULTS: Cytogenetic analysis revealed presence of t(8;21)(q22;q22) in addition to t(9;22)(q34;q11) in the patient. Chimeric BCR/ABL and AML1/ETO genes were detected by fluorescence in situ hybridization (FISH). Transcripts of BCR/ABL210 and AML1/ETO fusion genes were detected by relative quantity PCR. Morphological study suggested that the patient was at the chronic phase of CML. No significant immunophenotypic abnormality was detected by flow cytometry. CONCLUSION: Co-occurrence of t(8;21)(q22;q22) and t(9;22)(q34;q11) is rare in CML. Only 5 similar cases have been described previously. This case suggested that chromosomal alterations may precede morphological, flow cytometric and clinical changes and accelerate progression of the disease.

Distinct clinical characteristics draw a new prognostic model for splenic marginal zone lymphoma in HBV high prevalent region.

Splenic marginal zone lymphoma (SMZL) is a rare indolent B-cell neoplasm with hepatitis virus supposed to involve in the pathogenesis. The characteristics of SMZL derived from Caucasia population and high hepatitis C virus (HCV) infection region have been widely investigated, but few was reported in the Eastern population with HBV prevalent region. We analyzed the clinical characteristics, cytogenetic aberrations and prognostic factors in 160 SMZL patients from China. 25 patients (16%) were HBsAg-positive and 54 (34%) patients with resolved HBV infection. IGH gene usage was analyzed in 39 patients. The preferential usages of IGHV genes were IGHV1-2 (26%), followed by IGHV4-34 (18%) and IGHV2-70 (10%). The patients with HBV infection presented biased IGHV-D-J rearrangements and mutational status. Using three independent factors hemoglobin level, HBsAg positivity and complex karyotype, we developed a new hierarchical prognostic model, which showed a better c-index than the previously reported IIL and HPLL scoring systems in SMZL. In conclusion, SMZL in HBV prevalent region have unique clinical and biological characteristics and new prognostic scoring model should be adopted in this population.

High incidence of MYC and BCL2 abnormalities in mantle cell lymphoma, although only MYC abnormality predicts poor survival.

The incidence and prognostic role of MYC and BCL2 rearrangements in mature B-cell lymphomas have been extensively studied, except the infrequent mantle cell lymphoma (MCL). Here, we analyzed the MYC and BCL2 abnormalities and other cytogenetic aberrations by fluorescence in situ hybridization (FISH) in 50 MCL patients with bone marrow involvement. Eighteen patients (36.0%) had MYC gains and/or amplifications, and twelve patients (24.0%) had BCL2 gains and/or amplifications. Among the 18 patients with MYC abnormality, four had simultaneous MYC translocations, but no BCL2 translocation was detected among patients with BCL2 abnormality. Only two patients (4.0%) had both MYC and BCL2 abnormalities. The patients with a MYC abnormality had a significantly higher tumor burden, a higher percentage of medium/high risk MIPI group and genomic instability compared to those without this abnormality. However, no significant difference was observed between patients with or without a BCL2 abnormality in terms of clinical and cytogenetic factors. Patients with a MYC abnormality had poorer progress-free survival (PFS) (9.0 vs. 48.0 months, p = .000) and overall survival (OS) (12.0 vs. 94.5 months, p = .000), but the presence of a BCL2 abnormality did not significantly influence either PFS or OS. In multivariate analysis, the MYC abnormality was the independent adverse factor for both PFS and OS, and intensive chemotherapy did not improve the outcome of these patients. Thus, the presence of a MYC but not BCL2 abnormality predicted the poor survival of MCL patients, and a new treatment strategy should be developed for these patients.

[The clinic and pathologic significance of plasma cell myeloma with CCND1].

OBJECTIVE: To study the clinical and pathologic features of multiple myeloma(MM) with CCND1. METHODS: Retrospectively analyzed the clinical and pathologic profiles of 158 patients with MM from 2010 to 2013. The clinical and morphologic features of bone marrow aspiration, biopsy and immunophenotypic analysis which was carried out by flow cytometry and immunohistochemistry were analyzed in all patients with MM respectively. CCND1 translocation was studied by FISH method in all cases. Classical cytogenetic studies of bone marrow were performed in 24 cases whose CCND1 was positive. RESULTS: In the 158 patients with MM, CCND1 was detected in 31 patients (19.6%）. In 31 patients, type IgA, IgD, IgG, IgM, light-chain only and nonsecretory MM were 4 cases,4 cases,11 cases,1 case, 6 cases and 5 cases respectively. A high incidence of CCND1 was observed in IgD and nonsecretory MM comparied with IgA and IgG respectively (P<0.05). but no statistical significance was reached between κ and λ type patients (P=0.627). The morphology of plasma cell in bone marrow biopsies were small Lymphocyte- Like 24 cases,mature plasma cell 6 cases and immature plasma cell 1 case. Immunophenotype of all 31 cases was CD38⁺CD138⁺CD19⁻CD45⁻, (CD56⁺ in 11 cases, CD20⁺ in 9 cases, CD117⁺ in 3 cases. MM with CCND1 showed a strong association with CD20 expression, the lack of CD56 expression. Immunohistochemistry showed positive for cyclinD1 in 22 cases. CONCLUSION: A high incidence of CCND1 was detected in the IgD and nonsecretory MM, and correlated with Small Lymphocyte- Like, higher positive rate of CD20, cyclinD1 and the lack of CD56 expression. MM with CCND1 must be distinguished from LPL and other mature B cell lymphomas which have plasmacytoid differentiation.

Research on the optimal energy consumption of oil pipeline.

Most of the Chinese crude oil is easy to curdle and has high viscosity, so heating transportation is usually selected. Energy consumption by this method mainly comes from furnaces and pumps. Currently, operating parameters of these pipelines were determined according to experience of dispatch. It cause high energy consumption and high cost of pipeline running, so it could not adapt to energy conservation policy. The present study focused on consuming lowest energy to operate oil transportation line. To begin with, several optimization variables were set which included pump combinations, suction pressure, discharge pressure, and station temperature. Then constraint conditions were set to establish an optimal mathematical model of running transportation line. Furthermore, genetic algorithm was used to solve the model, in meantime, selection operation, cross operation and mutation operation in the genetic algorithm were improved. Finally, a crude oil pipeline running optimization software was developed. Through optimal analyzing, S-L transportation line and contrasting with the actual working conditions, it was found that optimal operation scheme could reduce energy consumption by 5% - 9%. In addition, optimal operation scheme also considered the effect of seasons and flow on energy consumption of S-L transportation line.

Dynamic simulation of an underground gas storage injection-production network .

Underground gas storage is a well-known strategic practice to seasonal peak shaving and emergency facility. The changing operation conditions of injection-production network directly affects the reliability of downstream gas supply of the city. In the present study, a model of injection-production network on the basis of field data analysis and research was established. By comparing the actual node pressure and simulation results, the reliability of model was verified. Based on the volume of underground gas storage and downstream gas consumption, the best seasonal peak-shaving schedule of the whole year was set. According to dynamic analysis of network, 20% increase in downstream demand could be fulfilled. Besides, the study also analyzed the well pressure and flow rate changes after shutdown of gas well, which is most likely to fail, and concludes that the best rescue time should be within 4 hr after gas supply interruption. The results would help in making decisions about the operation of injection-production network, which have important significance in the environmental protection.

The Prevalence of JAK2, MPL, and CALR Mutations in Chinese Patients With BCR-ABL1-Negative Myeloproliferative Neoplasms.

OBJECTIVES: To evaluate the mutation frequency of JAK2 V617F, JAK2 exon 12, MPL exon 10, and CALR exon 9 and the value of the combined tests in the diagnosis of BCR-ABL1-negative myeloproliferative neoplasms (MPNs). METHODS: In the current study, mutations of JAK2 V617F, JAK2 exon 12, MPL exon 10, and CALR exon 9 were analyzed in 929 Chinese patients with BCR-ABL1-negative MPN, including 234 cases of polycythemia vera (PV), 428 ETs, 187 PMFs, and 80 unclassifiable MPNs (MPN-Us). RESULTS: Our result showed that the positive rate of any of four mutations in patients with PV, ET, PMF, and MPN-U was 89.3%, 83.4%, 87.2%, and 77.5%, respectively, which significantly improved the diagnostic rate, especially in ET and PMF. Meanwhile, we also found that the patients without any of four mutations were younger than those with one or more mutations. Unexpectedly, the coexistence of JAK2 V617F and CALR exon 9 was identified in six (0.6%) patients, and JAK2 V617F and MPL exon 10 were present simultaneously in two (0.2%) patients. In addition, we also identified several novel mutation types in CALR exon 9. CONCLUSIONS: The combined genetic tests of JAK2 V617F, JAK2 exon 12, MPL exon 10, and CALR exon 9 help improve the diagnostic rate for BCR-ABL1-negative MPN.

[Pathological diagnosis of pediatric Burkitt lymphoma involving bone marrow].

OBJECTIVE: To investigate pathologic and differential diagnostic features of pediatric Burkitt lymphoma (BL). METHODS: A total of 20 cases of pediatric BL were retrospectively reviewed for their clinical and pathologic profiles. Bone marrow aspiration specimens were available in all cases and bone marrow biopsies were available for immunohistochemical study in 18 cases. Flow cytometry study was available in 16 cases. MYC translocation by FISH method was performed in 11 cases. RESULTS: Atypical lymphocytes with cytoplasmic vacuoles were found in bone marrow smears in all 20 cases and peripheral blood films in all 19 available cases. The bone marrow biopsies showed infiltration by uniform medium-sized atypical lymphocytes with multiple small nucleoli but without the starry-sky pattern in all 18 cases. Immunohistochemistry showed the following results in all 18 cases: positive for CD20, PAX-5, CD10, CD34 and TdT, but negative for bcl-2 and CD3 with Ki-67 > 95%.Flow cytometry showed CD19+CD20+CD10+FMC7+CD22+TdT-CD3- in 16 cases, including κ+ in 8 cases, λ+ in 7 cases, and κ-λ- in 1 case. MYC gene rearrangement by FISH was observed in 10 of the 11 cases. CONCLUSIONS: The histopathology of BL is distinct, including atypical lymphocytes with cytoplasmic vacuoles in bone marrow aspirate, lack of starry-sky patternin bone marrow biopsy. Generally, the diagnosis should be made with a combined immunophenotype and FISH approach. Pediatric BL must be distinguished from DLBCL and B-cell lymphoma, unclassifiable, which has intermediate features between DLBCL and Burkitt lymphoma.

[Primary bone marrow diffuse large B cell lymphoma: three case reports and literature review].

OBJECTIVE: To report the diagnosis, differential diagnosis and treatment of three rare cases of primary bone marrow diffuse large B cell lymphoma (DLBCL), and to improve the recognition of this disease. METHODS: The clinical characteristics, therapeutic course and the outcome of these patients were reviewed. Meanwhile, a series of examinations including morphology, flow cytometry, immunohistochemistry and molecular biology of bone marrow samples were also performed. RESULTS: These three patients who were old at the onset age (56, 60 and 70 years old), primarily revealed as abnormal blood count and experienced an aggressive course of disease. Physical and imaging examination showed no enlargement of lymph node, liver and spleen, the patients were finally diagnosed as primary bone marrow DLBCL by bone marrow morphology, flow cytometry and immunohistochemistry analyses. They were treated with rituximab combined chemotherapy, which achieved a complete response, but still need longer follow-up to further evaluate their survival. CONCLUSION: Primary bone marrow DLBCL was encountered rarely in clinical practice, and this is the first report in China. Further investigation of pathogenesis and therapeutic strategies of this rare disease was warranted.

Optimal energy consumption analysis of natural gas pipeline.

There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the operating parameters of many pipelines are determined empirically by dispatchers, resulting in high energy consumption. This practice does not abide by energy reduction policies. Therefore, based on a full understanding of the actual needs of pipeline companies, we introduce production unit consumption indicators to establish an objective function for achieving the goal of lowering energy consumption. By using a dynamic programming method for solving the model and preparing calculation software, we can ensure that the solution process is quick and efficient. Using established optimization methods, we analyzed the energy savings for the XQ gas pipeline. By optimizing the boot program, the import station pressure, and the temperature parameters, we achieved the optimal energy consumption. By comparison with the measured energy consumption, the pipeline now has the potential to reduce energy consumption by 11 to 16 percent.