A recent study by Qin et al emphasized the potential of zinc finger protein 71(ZNF71)as a promising biomarker for hepatocellular carcinoma(HCC).The authors offered valuable insights into the relationship between ZNF71...A recent study by Qin et al emphasized the potential of zinc finger protein 71(ZNF71)as a promising biomarker for hepatocellular carcinoma(HCC).The authors offered valuable insights into the relationship between ZNF71 and various clinical and pathological stages of HCC.However,several limitations are required to be addressed to improve the findings.These limitations include concerns regarding patient selection,the generalizability of the results,and the necessity for functional validation to establish ZNF71’s specific role in the progression of HCC.Furthermore,statistical issues related to multiple comparisons,confounding variables,and the inherent heterogeneity of high-throughput datasets warrant careful consideration.Future research should focus on multi-institutional cohorts,utilize in vivo models,and compare ZNF71 with established biomarkers to strengthen the clinical relevance of ZNF71.展开更多
A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional...A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional feature space through the nonlinear transformation. Among other fuzzy c-means and its variants, the number of clusters is first determined. A self-adaptive algorithm is proposed. The number of clusters, which is not given in advance, can be gotten automatically by a validity measure function. Finally, experiments are given to show better performance with the method of kernel based fuzzy c-means self-adaptive algorithm.展开更多
Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experien...Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.展开更多
Predominantly antibody deficiency(PAD)is the most prevalent form of primary immunodeficiency,and is characterized by broad clinical,immunological and genetic heterogeneity.Utilizing the current gold standard of whole ...Predominantly antibody deficiency(PAD)is the most prevalent form of primary immunodeficiency,and is characterized by broad clinical,immunological and genetic heterogeneity.Utilizing the current gold standard of whole exome sequencing for diagnosis,pathogenic gene variants are only identified in less than 20% of patients.While elucidation of the causal genes underlying PAD has provided many insights into the cellular and molecular mechanisms underpinning disease pathogenesis,many other genes may remain as yet undefined to enable definitive diagnosis,prognostic monitoring and targeted therapy of patients.Considering that many patients display a relatively late onset of disease presentation in their 2^(nd) or 3^(rd) decade of life,it is questionable whether a single genetic lesion underlies disease in all patients.Potentially,combined effects of other gene variants and/or non-genetic factors,including specific infections can drive disease presentation.In this review,we define(1)the clinical and immunological variability of PAD,(2)consider how genetic defects identified in PAD have given insight into B-cell immunobiology,(3)address recent technological advances in genomics and the challenges associated with identifying causal variants,and(4)discuss how functional validation of variants of unknown significance could potentially be translated into increased diagnostic rates,improved prognostic monitoring and personalized medicine for PAD patients.A multidisciplinary approach will be the key to curtailing the early mortality and high morbidity rates in this immune disorder.展开更多
文摘A recent study by Qin et al emphasized the potential of zinc finger protein 71(ZNF71)as a promising biomarker for hepatocellular carcinoma(HCC).The authors offered valuable insights into the relationship between ZNF71 and various clinical and pathological stages of HCC.However,several limitations are required to be addressed to improve the findings.These limitations include concerns regarding patient selection,the generalizability of the results,and the necessity for functional validation to establish ZNF71’s specific role in the progression of HCC.Furthermore,statistical issues related to multiple comparisons,confounding variables,and the inherent heterogeneity of high-throughput datasets warrant careful consideration.Future research should focus on multi-institutional cohorts,utilize in vivo models,and compare ZNF71 with established biomarkers to strengthen the clinical relevance of ZNF71.
文摘A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional feature space through the nonlinear transformation. Among other fuzzy c-means and its variants, the number of clusters is first determined. A self-adaptive algorithm is proposed. The number of clusters, which is not given in advance, can be gotten automatically by a validity measure function. Finally, experiments are given to show better performance with the method of kernel based fuzzy c-means self-adaptive algorithm.
文摘Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.
基金supported by The Jeffrey Modell Foundation and the Australian National Health and Medical Research Council(NHMRC,Senior Research Fellowship 1117687 to M.C.v2.).
文摘Predominantly antibody deficiency(PAD)is the most prevalent form of primary immunodeficiency,and is characterized by broad clinical,immunological and genetic heterogeneity.Utilizing the current gold standard of whole exome sequencing for diagnosis,pathogenic gene variants are only identified in less than 20% of patients.While elucidation of the causal genes underlying PAD has provided many insights into the cellular and molecular mechanisms underpinning disease pathogenesis,many other genes may remain as yet undefined to enable definitive diagnosis,prognostic monitoring and targeted therapy of patients.Considering that many patients display a relatively late onset of disease presentation in their 2^(nd) or 3^(rd) decade of life,it is questionable whether a single genetic lesion underlies disease in all patients.Potentially,combined effects of other gene variants and/or non-genetic factors,including specific infections can drive disease presentation.In this review,we define(1)the clinical and immunological variability of PAD,(2)consider how genetic defects identified in PAD have given insight into B-cell immunobiology,(3)address recent technological advances in genomics and the challenges associated with identifying causal variants,and(4)discuss how functional validation of variants of unknown significance could potentially be translated into increased diagnostic rates,improved prognostic monitoring and personalized medicine for PAD patients.A multidisciplinary approach will be the key to curtailing the early mortality and high morbidity rates in this immune disorder.
