Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been s...Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.展开更多
针对注水井分层注水量诊断技术难题,提出基于分布式光纤温度传感(Distributed Temperature Sensing,DTS)的注水井吸水剖面解释方法。建立考虑微量热效应的注水井温度剖面预测模型,模拟分析注水量、注水时间、储层导热系数等7个因素对温...针对注水井分层注水量诊断技术难题,提出基于分布式光纤温度传感(Distributed Temperature Sensing,DTS)的注水井吸水剖面解释方法。建立考虑微量热效应的注水井温度剖面预测模型,模拟分析注水量、注水时间、储层导热系数等7个因素对温度剖面的影响规律。通过正交试验模拟分析,确定不同因素对注水井温度剖面的影响程度从强到弱分别为注入水温度、注水时间、注水量、井筒半径、储层导热系数、井筒倾斜角度、注水层渗透率,明确影响注水井温度剖面的主控因素为注入水温度、注水时间和注入量。采用模拟退火(Simulated Annealing,SA)算法建立注水井DTS数据反演模型,对一口注水井现场实测DTS数据进行反演,获得较为准确的吸水剖面,单层最大吸水量误差百分比14.25%,平均误差11.09%,验证该反演方法的可靠性。通过DTS数据反演可以实现注水井吸水剖面定量解释,为注水效果评价提供直接依据。展开更多
Leukemia is one of the ten types of cancer that causes the biggest death in the world.Compared to other types of cancer,leukemia has a low life expectancy,so an early diagnosis of the cancer is necessary.A new strateg...Leukemia is one of the ten types of cancer that causes the biggest death in the world.Compared to other types of cancer,leukemia has a low life expectancy,so an early diagnosis of the cancer is necessary.A new strategy has been developed to identify various leukemia biomarkers by making blood cancer biosensors,especially by developing nanomaterial applications so that they can improve the performance of the biosensor.Although many biosensors have been developed,the detection of leukemia by using nanomaterials with electrochemical and optical methods is still less carried out compare to other types of cancer biosensors.Even the acoustic and calorimetric testing methods for the detection of leukemia by utilizing nanomaterials have not yet been carried out.Most of the reviewed works reported the use of gold nanoparticles and electrochemical characterization methods for leukemia detection with the object of study being conventional cancer cells.In order to be used clinically by the community,future research must be carried out with a lot of patient blood objects,develop non-invasive leukemia detection,and be able to detect all types of blood cancer specifically with one biosensor.This can lead to a fast and accurate diagnosis thus allowing for early treatment and easy periodic condition monitoring for various types of leukemia based on its biomarker and future design controlable via internet of things(IoT)so that why would be monitoring real times.展开更多
BACKGROUND Pulmonary tuberculosis(PTB)is prevalent in immunocompromised populations,including patients with hematologic malignancies,human immunodeficiency virus infections,and chronic diseases.Effective treatment for...BACKGROUND Pulmonary tuberculosis(PTB)is prevalent in immunocompromised populations,including patients with hematologic malignancies,human immunodeficiency virus infections,and chronic diseases.Effective treatment for acute promyelocytic leukemia(APL)combined with PTB is lacking.These patients show an extremely poor prognosis.Therefore,studies should establish efficient treatment options to improve patient survival and prognosis.CASE SUMMARY A 60-year-old male with pain in the right side of his chest and a fever for 4 d visited the outpatient department of our hospital.Peripheral blood smear revealed 54%blasts.Following bone marrow examinations,variant APL with TNRC18-RARA fusion gene was diagnosed.Chest computed tomography scan showed bilateral pneumonitis with bilateral pleural effusions,partial atelectasis in the lower lobes of both lungs,and the bronchoalveolar lavage fluid gene X-Pert test was positive,indicative of PTB.Carrimycin,ethambutol(EMB),and isoniazid(INH)were administered since he could not receive chemotherapy as the WBC count decreased continuously.After one week of treatment with carrimycin,the patient recovered from fever and received chemotherapy.Chemotherapy was very effective and his white blood cells counts got back to normal.After being given five months with rifampin,EMB and INH and chemotherapy,the patient showed complete remission from pneumonia and APL.CONCLUSION We report a case of PTB treated successfully with carrimycin with APL that requires chemotherapy.展开更多
Background:microRNA 34a(miR 34a)had been reported to have a diagnostic role in acute myeloid leukemia(AML).However,its value in the bone marrow(BM)of AML patients,in addition to its role in response to therapy is stil...Background:microRNA 34a(miR 34a)had been reported to have a diagnostic role in acute myeloid leukemia(AML).However,its value in the bone marrow(BM)of AML patients,in addition to its role in response to therapy is still unclear.The current study was designed to assess the diagnostic,prognostic,and predictive significance of miR 34a in the BM of AML patients.Methods:The miR.34a was assed in BM aspirate of 82 AML patients in relation to 12 normal control subjects using qRT-PCR.The data were assessed for correlation with the relevant dinical critenia,response to therapy,disease-free survival(DFS),and overall survival(OS)rates.Results:miR.34a was significantly downregulated in AML patients[0.005(3.3×10^(-6)-1.32)],compared to the control subjects[0.108(3.2× 10^(-4)-1.64),p=0.021].The.median relative quantification(RQ)of miR-34a was 0.106(range;0-32.12).The specifaity,sensitivity,and area under the curve(AUC)for the diagnosis of AML were(58.3%,69.5%,0.707,respectively,p=0.021).patients with upregulated miR-34a showed decreased platelets count<34.5 × 10^(9)/L,and achieved early complete remission(CR,p=0.031,p=0.044,respectively).Similarly,patients who were refractory to therapy showed decreased miR 34a levels in comparison to those who achieved CR[0.002(0-0.01)and 0.12(0-32.12),respectively,p=0.002].Therefore,miR 34a could significantly identify patients with CR with a specificity of 75%and sensitivity of 100%at a cut-off of 0.014(AUC=0.927,p=0.005).There was no considerable association between miR-34a expression and survival rates of the induded AML patients.Condusion:miR-34a could be a beneficial diagnostic biomarker for AML patients.In addition,it serves as a good indicator for response to therapy,which could possibly identify patients who are refractory to treatment with 100%sensitivity and 75%specificity.展开更多
Infection of leukemia in humans causes many complications in its later stages.It impairs bone marrow’s ability to produce blood.Morphological diagnosis of human blood cells is a well-known and well-proven technique f...Infection of leukemia in humans causes many complications in its later stages.It impairs bone marrow’s ability to produce blood.Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case.The binary classification is employed to distinguish between normal and leukemiainfected cells.In addition,various subtypes of leukemia require different treatments.These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia.This entails using multi-class classification to determine the leukemia subtype.This is usually done using a microscopic examination of these blood cells.Due to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for diagnosis.Researchers utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of classification.More advanced deep-learning methods are also utilized.Due to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding performances.This study introduces a deep learning-machine learning combined approach for leukemia diagnosis.It uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning classifiers.The transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature extractors.The extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia cells.For the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the system.This dataset achieves an impressive multi-class classification accuracy of 97.08%.The proposed approach is robust and generalized by a standardized dataset and the real image dataset with a limited sample size(520 images).Hence,this method can be explored further for leukemia diagnosis having a limited number of dataset samples.展开更多
Acute lymphoblastic leukemia (ALL) is characterized by immature and poorly differentiated B lymphocytes in large numbers in the blood. B cells are distinct from the cell types involved in their development (common lym...Acute lymphoblastic leukemia (ALL) is characterized by immature and poorly differentiated B lymphocytes in large numbers in the blood. B cells are distinct from the cell types involved in their development (common lymphoid progenitor cells, pro-B cells, pre-B cells, and mature cells). The process of B cell maturation depends on precise communication within the cell: signals activate specific genes that are essential for proper development. Errors in this intricate signaling network can lead to issues with B cell function and contribute to disease. B-lineage acute lymphoid leukemias, malignancies of precursor-stage B lymphoid cells inhibit lymphoid differentiation, leading to abnormal cell proliferation and survival. The process of developing leukemia (leukemogenesis) can be triggered by an overproduction of both hematopoietic stem cells (the cells that form all blood cells) and the immature versions of white blood cells called lymphoblasts. Acute lymphoblastic leukemia (ALL) with the presence of the Philadelphia chromosome (ALL Ph) is classified as a high-risk manifestation of the disease, this chromosome is the product of the reciprocal translocation, whose product is a BCR-ABL fusion protein. It is a highly active tyrosine kinase that can transform hematopoietic cells into cytokine-independent. Hyperphosphorylation cascades inhibit the differentiating function of IKZF1 as a tumor suppressor gene which leads to an abnormal proliferation of B cells due to the presence of the Philadelphia chromosome;it inhibits the differentiating process, leukemogenesis involving immature B cells in the bloodstream can result from the uncontrolled growth and division of hematopoietic stem cells and immature lymphoblasts (the precursors to B cells).展开更多
Hairy cell leukemia(HCL)is an uncommon mature B-cell malignancy characterized by a typical morphology,immunophenotype,and clinical profile.The vast majority of HCL patients harbor the canonical BRAF V600E mutation whi...Hairy cell leukemia(HCL)is an uncommon mature B-cell malignancy characterized by a typical morphology,immunophenotype,and clinical profile.The vast majority of HCL patients harbor the canonical BRAF V600E mutation which has become a rationalized target of the subsequently deregulated RAS-RAF-MEK-MAPK signaling pathway in HCL patients who have relapsed or who are refractory to front-line therapy.However,several HCL patients with a classical phenotype display non-canonical BRAF mutations or rearrangements.These include sequence variants within alternative exons and an oncogenic fusion with the IGH gene.Care must be taken in the molecular diagnostic work-up of patients with typical HCL but without the BRAF V600E to include investigation of these uncommon mechanisms.Identification,functional characterization,and reporting of further such patients is likely to provide insights into the pathogenesis of HCL and enable rational selection of targeted inhibitors in such patients if required.展开更多
In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects adults.Treatment depends on the type of leukemia...In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects adults.Treatment depends on the type of leukemia and the extent to which cancer has established throughout the body.Identifying leukemia in the initial stage is vital to providing timely patient care.Medical image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive processes.It can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human error.Many researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its subgroups.This study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical Images.The projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical images.The MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature extraction.Lastly,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia cancer.The hyperparameter tuning process using MPA helps enhance leukemia cancer classification performance.Simulation results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.展开更多
Objective: Improve the care of patients followed for acute leukemia in the Oncohematology department of the National Hospital of Niamey. Methods: This was a prospective study, over a period of 2 years from January 1, ...Objective: Improve the care of patients followed for acute leukemia in the Oncohematology department of the National Hospital of Niamey. Methods: This was a prospective study, over a period of 2 years from January 1, 2018 to December 31, 2019, in patients with acute leukemia in the Oncohematology department of the National Hospital of Niamey (HNN), whose diagnosis was made on a blood smear associated with a myelogram and immunophenotyping and who were consenting. Results: We collected 25 cases of acute leukemia confirmed by myelogram and immunophenotyping. The mean age of the patients was 31.32 years, with a predominance of women, a sex ratio of 0.92. Pupils and students were in the majority with 40% and most came from the Niamey region, i.e. 68%. Anemic syndrome was the most common clinical sign in 96%. ALL predominated in 64% of cases. On the blood count, the hyperleukocytosis was more marked in AML (mean white count: 197256.6 elts/mm3) than in ALL (137891.6 elts/mm3), it was the same for thrombocytopenia which is more marked in AML (75588.89/mm3) than in ALL (52156.25/mm3). Therapeutically, 52% of patients received chemotherapy. The mean overall survival was 16.223 ± 3.191 months, including a mean survival for AML of 6.853 ± 1200 months compared to 21.720 ± 5.920 months for ALL. Conclusion: Acute leukemia still remains a major problem in our context, due to the precariousness of limited financial, diagnostic and therapeutic resources. Thus reflecting in our results, the increasing number of cases, the diagnostic delay and the guarded prognosis. This is the reality in several other countries in the sub-region and even in certain developed countries.展开更多
The main goal of this research is to assess the impact of race, age at diagnosis, sex, and phenotype on the incidence and survivability of acute lymphocytic leukemia (ALL) among patients in the United States. By takin...The main goal of this research is to assess the impact of race, age at diagnosis, sex, and phenotype on the incidence and survivability of acute lymphocytic leukemia (ALL) among patients in the United States. By taking these factors into account, the study aims to explore how existing cancer registry data can aid in the early detection and effective treatment of ALL in patients. Our hypothesis was that statistically significant correlations exist between race, age at which patients were diagnosed, sex, and phenotype of the ALL patients, and their rate of incidence and survivability data were evaluated using SEER*Stat statistical software from National Cancer Institute. Analysis of the incidence data revealed that a higher prevalence of ALL was among the Caucasian population. The majority of ALL cases (59%) occurred in patients aged between 0 to 19 years at the time of diagnosis, and 56% of the affected individuals were male. The B-cell phenotype was predominantly associated with ALL cases (73%). When analyzing survivability data, it was observed that the 5-year survival rates slightly exceeded the 10-year survival rates for the respective demographics. Survivability rates of African Americans patients were the lowest compared to Caucasian, Asian, Pacific Islanders, Alaskan Native, Native Americans and others. Survivability rates progressively decreased for older patients. Moreover, this study investigated the typical treatment methods applied to ALL patients, mainly comprising chemotherapy, with occasional supplementation of radiation therapy as required. The study demonstrated the considerable efficacy of chemotherapy in enhancing patients’ chances of survival, while those who remained untreated faced a less favorable prognosis from the disease. Although a significant amount of data and information exists, this study can help doctors in the future by diagnosing patients with certain characteristics. It will further assist the health care professionals in screening potential patients and early detection of cases. This could also save the lives of elderly patients who have a higher mortality rate from this disease.展开更多
文摘针对Oligo(d T)亲和层析介质的吸附性能,以poly(A)为模型分子,考察了4种Oligo(d T)亲和层析介质的静态吸附平衡、吸附动力学和动态结合载量(DBC),探讨了载量影响相关机制。结果表明,4种介质的合适吸附条件均为0.6 mol·L-1Na Cl、p H=6~7;Monomix d T20静态吸附容量最大,且poly(A)能扩散至介质微球深层孔内,而Poros Oligo(d T)25、Praesto Jetted (d T)25和Nano Gel d T20等3种介质中poly(A)均主要为表层吸附、静态吸附容量稍低;对于DBC,Nano Gel d T20和Monomix d T20的10%穿透的DBC较高,而Poros Oligo (d T)25和Praesto Jetted (d T)25相对略低。经分析,影响载量的主要因素包含基质种类、微球孔径、配基密度、间隔臂和配基长度等。对于基质种类,聚苯乙烯基质可能孔道结构较为特别。对于微球孔径,应针对不同大小的m RNA分子定制不同孔径的微球,以平衡传质阻力与可及吸附表面积之间的矛盾,从而增大DBC。
基金supported by the National Natural Science Foundation of China(Grant Nos.32200590 to K.L.,81972358 to Q.W.,91959113 to Q.W.,and 82372897 to Q.W.)the Natural Science Foundation of Jiangsu Province(Grant No.BK20210530 to K.L.).
文摘Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.
文摘针对注水井分层注水量诊断技术难题,提出基于分布式光纤温度传感(Distributed Temperature Sensing,DTS)的注水井吸水剖面解释方法。建立考虑微量热效应的注水井温度剖面预测模型,模拟分析注水量、注水时间、储层导热系数等7个因素对温度剖面的影响规律。通过正交试验模拟分析,确定不同因素对注水井温度剖面的影响程度从强到弱分别为注入水温度、注水时间、注水量、井筒半径、储层导热系数、井筒倾斜角度、注水层渗透率,明确影响注水井温度剖面的主控因素为注入水温度、注水时间和注入量。采用模拟退火(Simulated Annealing,SA)算法建立注水井DTS数据反演模型,对一口注水井现场实测DTS数据进行反演,获得较为准确的吸水剖面,单层最大吸水量误差百分比14.25%,平均误差11.09%,验证该反演方法的可靠性。通过DTS数据反演可以实现注水井吸水剖面定量解释,为注水效果评价提供直接依据。
基金support from the Institut Teknologi Sepuluh Nopember under the project scheme of BRIN awards number:6/IV/KS/05/2023.
文摘Leukemia is one of the ten types of cancer that causes the biggest death in the world.Compared to other types of cancer,leukemia has a low life expectancy,so an early diagnosis of the cancer is necessary.A new strategy has been developed to identify various leukemia biomarkers by making blood cancer biosensors,especially by developing nanomaterial applications so that they can improve the performance of the biosensor.Although many biosensors have been developed,the detection of leukemia by using nanomaterials with electrochemical and optical methods is still less carried out compare to other types of cancer biosensors.Even the acoustic and calorimetric testing methods for the detection of leukemia by utilizing nanomaterials have not yet been carried out.Most of the reviewed works reported the use of gold nanoparticles and electrochemical characterization methods for leukemia detection with the object of study being conventional cancer cells.In order to be used clinically by the community,future research must be carried out with a lot of patient blood objects,develop non-invasive leukemia detection,and be able to detect all types of blood cancer specifically with one biosensor.This can lead to a fast and accurate diagnosis thus allowing for early treatment and easy periodic condition monitoring for various types of leukemia based on its biomarker and future design controlable via internet of things(IoT)so that why would be monitoring real times.
文摘BACKGROUND Pulmonary tuberculosis(PTB)is prevalent in immunocompromised populations,including patients with hematologic malignancies,human immunodeficiency virus infections,and chronic diseases.Effective treatment for acute promyelocytic leukemia(APL)combined with PTB is lacking.These patients show an extremely poor prognosis.Therefore,studies should establish efficient treatment options to improve patient survival and prognosis.CASE SUMMARY A 60-year-old male with pain in the right side of his chest and a fever for 4 d visited the outpatient department of our hospital.Peripheral blood smear revealed 54%blasts.Following bone marrow examinations,variant APL with TNRC18-RARA fusion gene was diagnosed.Chest computed tomography scan showed bilateral pneumonitis with bilateral pleural effusions,partial atelectasis in the lower lobes of both lungs,and the bronchoalveolar lavage fluid gene X-Pert test was positive,indicative of PTB.Carrimycin,ethambutol(EMB),and isoniazid(INH)were administered since he could not receive chemotherapy as the WBC count decreased continuously.After one week of treatment with carrimycin,the patient recovered from fever and received chemotherapy.Chemotherapy was very effective and his white blood cells counts got back to normal.After being given five months with rifampin,EMB and INH and chemotherapy,the patient showed complete remission from pneumonia and APL.CONCLUSION We report a case of PTB treated successfully with carrimycin with APL that requires chemotherapy.
文摘Background:microRNA 34a(miR 34a)had been reported to have a diagnostic role in acute myeloid leukemia(AML).However,its value in the bone marrow(BM)of AML patients,in addition to its role in response to therapy is still unclear.The current study was designed to assess the diagnostic,prognostic,and predictive significance of miR 34a in the BM of AML patients.Methods:The miR.34a was assed in BM aspirate of 82 AML patients in relation to 12 normal control subjects using qRT-PCR.The data were assessed for correlation with the relevant dinical critenia,response to therapy,disease-free survival(DFS),and overall survival(OS)rates.Results:miR.34a was significantly downregulated in AML patients[0.005(3.3×10^(-6)-1.32)],compared to the control subjects[0.108(3.2× 10^(-4)-1.64),p=0.021].The.median relative quantification(RQ)of miR-34a was 0.106(range;0-32.12).The specifaity,sensitivity,and area under the curve(AUC)for the diagnosis of AML were(58.3%,69.5%,0.707,respectively,p=0.021).patients with upregulated miR-34a showed decreased platelets count<34.5 × 10^(9)/L,and achieved early complete remission(CR,p=0.031,p=0.044,respectively).Similarly,patients who were refractory to therapy showed decreased miR 34a levels in comparison to those who achieved CR[0.002(0-0.01)and 0.12(0-32.12),respectively,p=0.002].Therefore,miR 34a could significantly identify patients with CR with a specificity of 75%and sensitivity of 100%at a cut-off of 0.014(AUC=0.927,p=0.005).There was no considerable association between miR-34a expression and survival rates of the induded AML patients.Condusion:miR-34a could be a beneficial diagnostic biomarker for AML patients.In addition,it serves as a good indicator for response to therapy,which could possibly identify patients who are refractory to treatment with 100%sensitivity and 75%specificity.
基金supported by the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS),the University of Technology Sydney,the Ministry of Education of the Republic of Korea,and the National Research Foundation of Korea (NRF-2023R1A2C1007742)in part by the Researchers Supporting Project Number RSP-2023/14,King Saud University。
文摘Infection of leukemia in humans causes many complications in its later stages.It impairs bone marrow’s ability to produce blood.Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case.The binary classification is employed to distinguish between normal and leukemiainfected cells.In addition,various subtypes of leukemia require different treatments.These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia.This entails using multi-class classification to determine the leukemia subtype.This is usually done using a microscopic examination of these blood cells.Due to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for diagnosis.Researchers utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of classification.More advanced deep-learning methods are also utilized.Due to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding performances.This study introduces a deep learning-machine learning combined approach for leukemia diagnosis.It uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning classifiers.The transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature extractors.The extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia cells.For the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the system.This dataset achieves an impressive multi-class classification accuracy of 97.08%.The proposed approach is robust and generalized by a standardized dataset and the real image dataset with a limited sample size(520 images).Hence,this method can be explored further for leukemia diagnosis having a limited number of dataset samples.
文摘Acute lymphoblastic leukemia (ALL) is characterized by immature and poorly differentiated B lymphocytes in large numbers in the blood. B cells are distinct from the cell types involved in their development (common lymphoid progenitor cells, pro-B cells, pre-B cells, and mature cells). The process of B cell maturation depends on precise communication within the cell: signals activate specific genes that are essential for proper development. Errors in this intricate signaling network can lead to issues with B cell function and contribute to disease. B-lineage acute lymphoid leukemias, malignancies of precursor-stage B lymphoid cells inhibit lymphoid differentiation, leading to abnormal cell proliferation and survival. The process of developing leukemia (leukemogenesis) can be triggered by an overproduction of both hematopoietic stem cells (the cells that form all blood cells) and the immature versions of white blood cells called lymphoblasts. Acute lymphoblastic leukemia (ALL) with the presence of the Philadelphia chromosome (ALL Ph) is classified as a high-risk manifestation of the disease, this chromosome is the product of the reciprocal translocation, whose product is a BCR-ABL fusion protein. It is a highly active tyrosine kinase that can transform hematopoietic cells into cytokine-independent. Hyperphosphorylation cascades inhibit the differentiating function of IKZF1 as a tumor suppressor gene which leads to an abnormal proliferation of B cells due to the presence of the Philadelphia chromosome;it inhibits the differentiating process, leukemogenesis involving immature B cells in the bloodstream can result from the uncontrolled growth and division of hematopoietic stem cells and immature lymphoblasts (the precursors to B cells).
文摘Hairy cell leukemia(HCL)is an uncommon mature B-cell malignancy characterized by a typical morphology,immunophenotype,and clinical profile.The vast majority of HCL patients harbor the canonical BRAF V600E mutation which has become a rationalized target of the subsequently deregulated RAS-RAF-MEK-MAPK signaling pathway in HCL patients who have relapsed or who are refractory to front-line therapy.However,several HCL patients with a classical phenotype display non-canonical BRAF mutations or rearrangements.These include sequence variants within alternative exons and an oncogenic fusion with the IGH gene.Care must be taken in the molecular diagnostic work-up of patients with typical HCL but without the BRAF V600E to include investigation of these uncommon mechanisms.Identification,functional characterization,and reporting of further such patients is likely to provide insights into the pathogenesis of HCL and enable rational selection of targeted inhibitors in such patients if required.
基金funded by Researchers Supporting Program at King Saud University,(RSPD2024R809).
文摘In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects adults.Treatment depends on the type of leukemia and the extent to which cancer has established throughout the body.Identifying leukemia in the initial stage is vital to providing timely patient care.Medical image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive processes.It can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human error.Many researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its subgroups.This study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical Images.The projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical images.The MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature extraction.Lastly,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia cancer.The hyperparameter tuning process using MPA helps enhance leukemia cancer classification performance.Simulation results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.
文摘Objective: Improve the care of patients followed for acute leukemia in the Oncohematology department of the National Hospital of Niamey. Methods: This was a prospective study, over a period of 2 years from January 1, 2018 to December 31, 2019, in patients with acute leukemia in the Oncohematology department of the National Hospital of Niamey (HNN), whose diagnosis was made on a blood smear associated with a myelogram and immunophenotyping and who were consenting. Results: We collected 25 cases of acute leukemia confirmed by myelogram and immunophenotyping. The mean age of the patients was 31.32 years, with a predominance of women, a sex ratio of 0.92. Pupils and students were in the majority with 40% and most came from the Niamey region, i.e. 68%. Anemic syndrome was the most common clinical sign in 96%. ALL predominated in 64% of cases. On the blood count, the hyperleukocytosis was more marked in AML (mean white count: 197256.6 elts/mm3) than in ALL (137891.6 elts/mm3), it was the same for thrombocytopenia which is more marked in AML (75588.89/mm3) than in ALL (52156.25/mm3). Therapeutically, 52% of patients received chemotherapy. The mean overall survival was 16.223 ± 3.191 months, including a mean survival for AML of 6.853 ± 1200 months compared to 21.720 ± 5.920 months for ALL. Conclusion: Acute leukemia still remains a major problem in our context, due to the precariousness of limited financial, diagnostic and therapeutic resources. Thus reflecting in our results, the increasing number of cases, the diagnostic delay and the guarded prognosis. This is the reality in several other countries in the sub-region and even in certain developed countries.
文摘The main goal of this research is to assess the impact of race, age at diagnosis, sex, and phenotype on the incidence and survivability of acute lymphocytic leukemia (ALL) among patients in the United States. By taking these factors into account, the study aims to explore how existing cancer registry data can aid in the early detection and effective treatment of ALL in patients. Our hypothesis was that statistically significant correlations exist between race, age at which patients were diagnosed, sex, and phenotype of the ALL patients, and their rate of incidence and survivability data were evaluated using SEER*Stat statistical software from National Cancer Institute. Analysis of the incidence data revealed that a higher prevalence of ALL was among the Caucasian population. The majority of ALL cases (59%) occurred in patients aged between 0 to 19 years at the time of diagnosis, and 56% of the affected individuals were male. The B-cell phenotype was predominantly associated with ALL cases (73%). When analyzing survivability data, it was observed that the 5-year survival rates slightly exceeded the 10-year survival rates for the respective demographics. Survivability rates of African Americans patients were the lowest compared to Caucasian, Asian, Pacific Islanders, Alaskan Native, Native Americans and others. Survivability rates progressively decreased for older patients. Moreover, this study investigated the typical treatment methods applied to ALL patients, mainly comprising chemotherapy, with occasional supplementation of radiation therapy as required. The study demonstrated the considerable efficacy of chemotherapy in enhancing patients’ chances of survival, while those who remained untreated faced a less favorable prognosis from the disease. Although a significant amount of data and information exists, this study can help doctors in the future by diagnosing patients with certain characteristics. It will further assist the health care professionals in screening potential patients and early detection of cases. This could also save the lives of elderly patients who have a higher mortality rate from this disease.
