GST-π was purified from human placenta and its antiserum was raised in rabbits. The antibody IgC was purified and degraded into Fab' fragment which was conjugated with horseradish peroxidase (HRP) using N-succini...GST-π was purified from human placenta and its antiserum was raised in rabbits. The antibody IgC was purified and degraded into Fab' fragment which was conjugated with horseradish peroxidase (HRP) using N-succinimidyl-4-(N-maleimido-methyl) cyclo-hexane-1-carboxylate (SMCC) as crosslinking reagent to produce Fab'-HRP conjugate. A sandwich ELISA was established for the microquantitative determination of GST-π. The sensitivity was 11 pg/tube, which was far more sensitive than the radioimmunoassay so far reported. Using this method, the serum GST-π of 41 cases normal adult was found to be 1.06±0.94 ng/ml. The upper limit of the normal value was 2.6 ng/ml. In 30 cases of primary hepatocarcinoma, the level of serum GST-π was 24.4± 17.4 ng/ml, which was 23 times higher than the normal average value (P<0.01). The positive rate was 90%. In contrast, serum GST-π in 25 cases of chronic hepatitis was determined to be 1.74±1.16 ng/ml, which was not significantly different from the normal value (P>0.05). The pseudo-positive rate was 12.0%.展开更多
In our report, the values of whole blood serotonin (5-HT) in 87 apudoma patients (diagnosed by operation and pathology) were summarized. Among them, the levels of urinary 5-hydroxyindole-3-acetic acid (5-HIAA) of 44 p...In our report, the values of whole blood serotonin (5-HT) in 87 apudoma patients (diagnosed by operation and pathology) were summarized. Among them, the levels of urinary 5-hydroxyindole-3-acetic acid (5-HIAA) of 44 patients were also tested. The results showed that both parametres of apudoma patients were higher than those of non-apudoma, post-operative patients of apudoma as well as the normal. The increasing extent of the levels of whole blood 5-HT and urinary 5-HIAA in small intestinal carcihoid was the most obvious one but that of rectum was not. The referable diagnostic values suggested were: 5-HT>130 ng ml, 5-HIAA>30 mg/ 24 hours.展开更多
Corona Virus Disease-2019(COVID-19)continues to spread rapidly in the world.It has dramatically affected daily lives,public health,and the world economy.This paper presents a segmentation and classification framework ...Corona Virus Disease-2019(COVID-19)continues to spread rapidly in the world.It has dramatically affected daily lives,public health,and the world economy.This paper presents a segmentation and classification framework of COVID-19 images based on deep learning.Firstly,the classification process is employed to discriminate between COVID-19,non-COVID,and pneumonia by Convolutional Neural Network(CNN).Then,the segmentation process is applied for COVID-19 and pneumonia CT images.Finally,the resulting segmented images are used to identify the infected region,whether COVID-19 or pneumonia.The proposed CNN consists of four Convolutional(Conv)layers,four batch normalization layers,and four Rectified Linear Units(ReLUs).The sizes of Conv layer used filters are 8,16,32,and 64.Four maxpooling layers are employed with a stride of 2 and a 2×2 window.The classification layer comprises a Fully-Connected(FC)layer and a soft-max activation function used to take the classification decision.A novel saliencybased region detection algorithm and an active contour segmentation strategy are applied to segment COVID-19 and pneumonia CT images.The acquired findings substantiate the efficacy of the proposed framework for helping the specialists in automated diagnosis applications.展开更多
The unavailability of sufficient information for proper diagnosis,incomplete or miscommunication between patient and the clinician,or among the healthcare professionals,delay or incorrect diagnosis,the fatigue of clin...The unavailability of sufficient information for proper diagnosis,incomplete or miscommunication between patient and the clinician,or among the healthcare professionals,delay or incorrect diagnosis,the fatigue of clinician,or even the high diagnostic complexity in limited time can lead to diagnostic errors.Diagnostic errors have adverse effects on the treatment of a patient.Unnecessary treatments increase the medical bills and deteriorate the health of a patient.Such diagnostic errors that harm the patient in various ways could be minimized using machine learning.Machine learning algorithms could be used to diagnose various diseases with high accuracy.The use of machine learning could assist the doctors in making decisions on time,and could also be used as a second opinion or supporting tool.This study aims to provide a comprehensive review of research articles published from the year 2015 to mid of the year 2020 that have used machine learning for diagnosis of various diseases.We present the various machine learning algorithms used over the years to diagnose various diseases.The results of this study show the distribution of machine learning methods by medical disciplines.Based on our review,we present future research directions that could be used to conduct further research.展开更多
Coronaviruses are a well-known family of viruses that can infect humans or animals.Recently,the new coronavirus(COVID-19)has spread worldwide.All countries in the world are working hard to control the coronavirus dise...Coronaviruses are a well-known family of viruses that can infect humans or animals.Recently,the new coronavirus(COVID-19)has spread worldwide.All countries in the world are working hard to control the coronavirus disease.However,many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system,which leads to the mass spread of diseases.As a powerful tool,artificial intelligence(AI)has been successfully applied to solve various complex problems ranging from big data analysis to computer vision.In the process of epidemic control,many algorithms are proposed to solve problems in various fields of medical treatment,which is able to reduce the workload of the medical system.Due to excellent learning ability,AI has played an important role in drug development,epidemic forecast,and clinical diagnosis.This research provides a comprehensive overview of relevant research on AI during the outbreak and helps to develop new and more powerful methods to deal with the current pandemic.展开更多
In this study, we have observed the conditions of clinical application of Model CLRHA Auricular Point Detector from the aspects of accessory diagnosis and effective comparison of acupuncture at positive point and non-...In this study, we have observed the conditions of clinical application of Model CLRHA Auricular Point Detector from the aspects of accessory diagnosis and effective comparison of acupuncture at positive point and non-positive point. The preliminary results show that using this device to seek reaction point is quick and reliable, the coincidence rate of diagnosis is higher (76. 77 % ); the indix is objective. It can effectively direct doctors to select acupoints correctly for treatment, resulting in improving the therapeutic effect. The results of contrastive observation show that the therapeutic effect of positive point group is much better than that of non-positive point group (P < 0. 001 ). This instrument has following characteristics, i. e. it is simple, safe, small and exquisite to be portable, and economic. It is more suitable to the clinical needs, possessing a higher practical value.展开更多
This article reviews the basic theories, methods, and clinical applications of eye diagnosis in traditional Chinese medicine(TCM). It introduces cutting-edge methods and applications and explains that the modernizatio...This article reviews the basic theories, methods, and clinical applications of eye diagnosis in traditional Chinese medicine(TCM). It introduces cutting-edge methods and applications and explains that the modernization of TCM eye diagnosis includes “equipment-assisted diagnosis” and “artificial intelligencebased diagnosis”. The article also notes that while there are many recent studies of the static attributes of eyes in modern TCM eye diagnosis, modern application research on the dynamic attributes of eyes in TCM diagnosis theory is relatively rare. We propose, therefore, that introducing advanced eye-movement detection technology into TCM clinical diagnosis could help to further modernize TCM eye diagnosis.展开更多
Recently,the diagnoses of dental caries and other dental issues are in a queue as only X-ray-based techniques are available in most hospitals around the world.Terahertz(THz)parametric imaging(TPI)is the latest technol...Recently,the diagnoses of dental caries and other dental issues are in a queue as only X-ray-based techniques are available in most hospitals around the world.Terahertz(THz)parametric imaging(TPI)is the latest technology that can be applied for medical applications,especially dental caries.This technology is harmless and thus suitable for biological samples owing to the low energy of THz emission.In this paper,a developed TPI system is used to investigate the two-dimensional(2 D)and three-dimensional(3D)images of different samples from human teeth.After analyzing the measured images of human teeth,the results suggest that the THz parametric technology is capable of investigating the inner side structure of the teeth.This technique can be useful in detecting the defects in all types of human and animal teeth.The measurement and analytical calculations have been performed by using the TPI system and MATLAB,respectively,and both are in good agreement.The characteristics of THz waves and their interactions with the tooth samples are summarized.And the available THz-based technologies,such as TPI,and their potential applications of diagnoses are also presented.展开更多
Helicobacter pylori(H.pylori)neutrophil-activating protein(HP-NAP)was originally identified as a virulence factor of H.pylori for its ability to activate neutrophils to generate respiratory burst by releasing reactive...Helicobacter pylori(H.pylori)neutrophil-activating protein(HP-NAP)was originally identified as a virulence factor of H.pylori for its ability to activate neutrophils to generate respiratory burst by releasing reactive oxygen species.Later on,HP-NAP was also found to be involved in the protection of H.pylori from DNA damage,supporting the survival of H.pylori under oxidative stress.This protein is highly conserved and expressed by virtually all clinical isolates of H.pylori.The majority of patients infected with H.pylori produced antibodies specific for HP-NAP,suggesting its important role in immunity.In addition to acting as a pathogenic factor by activating the innate immunity through a wide range of human leukocytes,including neutrophils,monocytes,and mast cells,HP-NAP also mediates adaptive immunity through the induction of T helper cell typeⅠresponses.The pro-inflammatory and immunomodulatory properties of HP-NAP not only make it play an important role in disease pathogenesis but also make it a potential candidate for clinical use.Even though there is no convincing evidence to link HP-NAP to a disease outcome,recent findings supporting the pathogenic role of HP-NAP will be reviewed.In addition,the potential clinical applications of HP-NAP in vaccine development,clinical diagnosis,and drug development will be discussed.展开更多
Clustered regularly interspaced short palindromic repeat(CRISPR)has been gaining much attention in the modern medical field and has been widely used for the diagnosis and treatment of diseases in recent years.In this ...Clustered regularly interspaced short palindromic repeat(CRISPR)has been gaining much attention in the modern medical field and has been widely used for the diagnosis and treatment of diseases in recent years.In this review,we will introduce the application of CRISPR in disease diagnosis and treatment,including its use in detecting pathogens,gene mutations,and genetic diseases,as well as its application in gene therapy for single-gene diseases,cancer,viral infectious diseases,and cardiovascular diseases.Additionally,we will discuss the potential future directions and challenges of CRISPR in the diagnosis and treatment of diseases,and provide a thorough overview of the ways in which CRISPR is used for diagnosing and treating diseases.展开更多
Android applications are becoming increasingly powerful in recent years. While their functionality is still of paramount importance to users, the energy efficiency of these applications is also gaining more and more a...Android applications are becoming increasingly powerful in recent years. While their functionality is still of paramount importance to users, the energy efficiency of these applications is also gaining more and more attention. Researchers have discovered various types of energy defects in Android applications, which could quickly drain the battery power of mobile devices. Such defects not only cause inconvenience to users, but also frustrate Android developers as diagnosing the energy inefficiency of a software product is a non-trivial task. In this work, we perform a literature review to understand the state of the art of energy inefficiency diagnosis for Android applications. We identified 55 research papers published in recent years and classified existing studies from four different perspectives, including power estimation method, hardware component, types of energy defects, and program analysis approach. We also did a cross-perspective analysis to summarize and compare our studied techniques. We hope that our review can help structure and unify the literature and shed light on future research, as well as drawing developers' attention to build energy-efficient Android applications.展开更多
Multi-sensor measurement iswidely employed in rotatingmachinery to ensure the safety ofmachines.The information provided by the single sensor is not comprehensive.Multi-sensor signals can provide complementary informa...Multi-sensor measurement iswidely employed in rotatingmachinery to ensure the safety ofmachines.The information provided by the single sensor is not comprehensive.Multi-sensor signals can provide complementary information in characterizing the health condition of machines.This paper proposed a multi-sensor fusion convolution neural network(MF-CNN)model.The proposed model adds a 2-D convolution layer before the classical 1-D CNN to automatically extract complementary features of multi-sensor signals and minimize the loss of information.A series of experiments are carried out on a rolling bearing test rig to verify the model.Vibration and sound signals are fused to achieve higher classification accuracy than typical machine learning model.In addition,the model is further applied to gas turbine abnormal detection,and shows great robustness and generalization.展开更多
文摘GST-π was purified from human placenta and its antiserum was raised in rabbits. The antibody IgC was purified and degraded into Fab' fragment which was conjugated with horseradish peroxidase (HRP) using N-succinimidyl-4-(N-maleimido-methyl) cyclo-hexane-1-carboxylate (SMCC) as crosslinking reagent to produce Fab'-HRP conjugate. A sandwich ELISA was established for the microquantitative determination of GST-π. The sensitivity was 11 pg/tube, which was far more sensitive than the radioimmunoassay so far reported. Using this method, the serum GST-π of 41 cases normal adult was found to be 1.06±0.94 ng/ml. The upper limit of the normal value was 2.6 ng/ml. In 30 cases of primary hepatocarcinoma, the level of serum GST-π was 24.4± 17.4 ng/ml, which was 23 times higher than the normal average value (P<0.01). The positive rate was 90%. In contrast, serum GST-π in 25 cases of chronic hepatitis was determined to be 1.74±1.16 ng/ml, which was not significantly different from the normal value (P>0.05). The pseudo-positive rate was 12.0%.
文摘In our report, the values of whole blood serotonin (5-HT) in 87 apudoma patients (diagnosed by operation and pathology) were summarized. Among them, the levels of urinary 5-hydroxyindole-3-acetic acid (5-HIAA) of 44 patients were also tested. The results showed that both parametres of apudoma patients were higher than those of non-apudoma, post-operative patients of apudoma as well as the normal. The increasing extent of the levels of whole blood 5-HT and urinary 5-HIAA in small intestinal carcihoid was the most obvious one but that of rectum was not. The referable diagnostic values suggested were: 5-HT>130 ng ml, 5-HIAA>30 mg/ 24 hours.
基金This research was funded by the Deanship of Scientific Research at Princess Nourah Bint Abdulrahman University through the Fast-track Research Funding Program.
文摘Corona Virus Disease-2019(COVID-19)continues to spread rapidly in the world.It has dramatically affected daily lives,public health,and the world economy.This paper presents a segmentation and classification framework of COVID-19 images based on deep learning.Firstly,the classification process is employed to discriminate between COVID-19,non-COVID,and pneumonia by Convolutional Neural Network(CNN).Then,the segmentation process is applied for COVID-19 and pneumonia CT images.Finally,the resulting segmented images are used to identify the infected region,whether COVID-19 or pneumonia.The proposed CNN consists of four Convolutional(Conv)layers,four batch normalization layers,and four Rectified Linear Units(ReLUs).The sizes of Conv layer used filters are 8,16,32,and 64.Four maxpooling layers are employed with a stride of 2 and a 2×2 window.The classification layer comprises a Fully-Connected(FC)layer and a soft-max activation function used to take the classification decision.A novel saliencybased region detection algorithm and an active contour segmentation strategy are applied to segment COVID-19 and pneumonia CT images.The acquired findings substantiate the efficacy of the proposed framework for helping the specialists in automated diagnosis applications.
基金supported in part by Zayed University,office of research under Grant No.R17089.
文摘The unavailability of sufficient information for proper diagnosis,incomplete or miscommunication between patient and the clinician,or among the healthcare professionals,delay or incorrect diagnosis,the fatigue of clinician,or even the high diagnostic complexity in limited time can lead to diagnostic errors.Diagnostic errors have adverse effects on the treatment of a patient.Unnecessary treatments increase the medical bills and deteriorate the health of a patient.Such diagnostic errors that harm the patient in various ways could be minimized using machine learning.Machine learning algorithms could be used to diagnose various diseases with high accuracy.The use of machine learning could assist the doctors in making decisions on time,and could also be used as a second opinion or supporting tool.This study aims to provide a comprehensive review of research articles published from the year 2015 to mid of the year 2020 that have used machine learning for diagnosis of various diseases.We present the various machine learning algorithms used over the years to diagnose various diseases.The results of this study show the distribution of machine learning methods by medical disciplines.Based on our review,we present future research directions that could be used to conduct further research.
基金This work is supported in part by the Jiangsu Basic Research Programs-Natural Science Foundation under Grant Numbers BK20181407in part by the National Natural Science Foundation of China under Grant Numbers U1936118,61672294+3 种基金in part by Six peak talent project of Jiangsu Province(R2016L13)Qinglan Project of Jiangsu Province,and“333”project of Jiangsu Province,in part by the National Natural Science Foundation of China under Grant Numbers U1836208,61702276,61772283,61602253,and 61601236in part by National Key R&D Program of China under Grant 2018YFB1003205in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund,in part by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China.Zhihua Xia is supported by BK21+program from the Ministry of Education of Korea.
文摘Coronaviruses are a well-known family of viruses that can infect humans or animals.Recently,the new coronavirus(COVID-19)has spread worldwide.All countries in the world are working hard to control the coronavirus disease.However,many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system,which leads to the mass spread of diseases.As a powerful tool,artificial intelligence(AI)has been successfully applied to solve various complex problems ranging from big data analysis to computer vision.In the process of epidemic control,many algorithms are proposed to solve problems in various fields of medical treatment,which is able to reduce the workload of the medical system.Due to excellent learning ability,AI has played an important role in drug development,epidemic forecast,and clinical diagnosis.This research provides a comprehensive overview of relevant research on AI during the outbreak and helps to develop new and more powerful methods to deal with the current pandemic.
文摘In this study, we have observed the conditions of clinical application of Model CLRHA Auricular Point Detector from the aspects of accessory diagnosis and effective comparison of acupuncture at positive point and non-positive point. The preliminary results show that using this device to seek reaction point is quick and reliable, the coincidence rate of diagnosis is higher (76. 77 % ); the indix is objective. It can effectively direct doctors to select acupoints correctly for treatment, resulting in improving the therapeutic effect. The results of contrastive observation show that the therapeutic effect of positive point group is much better than that of non-positive point group (P < 0. 001 ). This instrument has following characteristics, i. e. it is simple, safe, small and exquisite to be portable, and economic. It is more suitable to the clinical needs, possessing a higher practical value.
文摘This article reviews the basic theories, methods, and clinical applications of eye diagnosis in traditional Chinese medicine(TCM). It introduces cutting-edge methods and applications and explains that the modernization of TCM eye diagnosis includes “equipment-assisted diagnosis” and “artificial intelligencebased diagnosis”. The article also notes that while there are many recent studies of the static attributes of eyes in modern TCM eye diagnosis, modern application research on the dynamic attributes of eyes in TCM diagnosis theory is relatively rare. We propose, therefore, that introducing advanced eye-movement detection technology into TCM clinical diagnosis could help to further modernize TCM eye diagnosis.
基金the Research Fund for International Young Scientist Fund under Grant No.61750110520the Special Project for Guiding Local Science and Technology Development under Grant No.2018ZYYD006the Hubei Polytechnic University Laboratory Fund under Grant No.19XJK24R。
文摘Recently,the diagnoses of dental caries and other dental issues are in a queue as only X-ray-based techniques are available in most hospitals around the world.Terahertz(THz)parametric imaging(TPI)is the latest technology that can be applied for medical applications,especially dental caries.This technology is harmless and thus suitable for biological samples owing to the low energy of THz emission.In this paper,a developed TPI system is used to investigate the two-dimensional(2 D)and three-dimensional(3D)images of different samples from human teeth.After analyzing the measured images of human teeth,the results suggest that the THz parametric technology is capable of investigating the inner side structure of the teeth.This technique can be useful in detecting the defects in all types of human and animal teeth.The measurement and analytical calculations have been performed by using the TPI system and MATLAB,respectively,and both are in good agreement.The characteristics of THz waves and their interactions with the tooth samples are summarized.And the available THz-based technologies,such as TPI,and their potential applications of diagnoses are also presented.
基金Supported by National Science Council of Taiwan,No.NSC101-2311-B-007-007
文摘Helicobacter pylori(H.pylori)neutrophil-activating protein(HP-NAP)was originally identified as a virulence factor of H.pylori for its ability to activate neutrophils to generate respiratory burst by releasing reactive oxygen species.Later on,HP-NAP was also found to be involved in the protection of H.pylori from DNA damage,supporting the survival of H.pylori under oxidative stress.This protein is highly conserved and expressed by virtually all clinical isolates of H.pylori.The majority of patients infected with H.pylori produced antibodies specific for HP-NAP,suggesting its important role in immunity.In addition to acting as a pathogenic factor by activating the innate immunity through a wide range of human leukocytes,including neutrophils,monocytes,and mast cells,HP-NAP also mediates adaptive immunity through the induction of T helper cell typeⅠresponses.The pro-inflammatory and immunomodulatory properties of HP-NAP not only make it play an important role in disease pathogenesis but also make it a potential candidate for clinical use.Even though there is no convincing evidence to link HP-NAP to a disease outcome,recent findings supporting the pathogenic role of HP-NAP will be reviewed.In addition,the potential clinical applications of HP-NAP in vaccine development,clinical diagnosis,and drug development will be discussed.
基金supported by the National Natural Science Foundation of China(21907077,92153303,21721005,91940000)Fundamental Research Funds for the Central Universities(2042023kf0118)。
文摘Clustered regularly interspaced short palindromic repeat(CRISPR)has been gaining much attention in the modern medical field and has been widely used for the diagnosis and treatment of diseases in recent years.In this review,we will introduce the application of CRISPR in disease diagnosis and treatment,including its use in detecting pathogens,gene mutations,and genetic diseases,as well as its application in gene therapy for single-gene diseases,cancer,viral infectious diseases,and cardiovascular diseases.Additionally,we will discuss the potential future directions and challenges of CRISPR in the diagnosis and treatment of diseases,and provide a thorough overview of the ways in which CRISPR is used for diagnosing and treating diseases.
基金supported by the Guangdong Basic and Applied Basic Research Foundation(2021A1515012297)the Shenzhen Science and Technology Innovation Commission(R2020A045)the Open Project of Guangdong Provincial Key Laboratory of High-Performance Computing(2021).
文摘Android applications are becoming increasingly powerful in recent years. While their functionality is still of paramount importance to users, the energy efficiency of these applications is also gaining more and more attention. Researchers have discovered various types of energy defects in Android applications, which could quickly drain the battery power of mobile devices. Such defects not only cause inconvenience to users, but also frustrate Android developers as diagnosing the energy inefficiency of a software product is a non-trivial task. In this work, we perform a literature review to understand the state of the art of energy inefficiency diagnosis for Android applications. We identified 55 research papers published in recent years and classified existing studies from four different perspectives, including power estimation method, hardware component, types of energy defects, and program analysis approach. We also did a cross-perspective analysis to summarize and compare our studied techniques. We hope that our review can help structure and unify the literature and shed light on future research, as well as drawing developers' attention to build energy-efficient Android applications.
基金support from the National Natural Science Foundation of China (Grant No.U1809219)the Key Research and Development Project of Zhejiang Province (Grant No.2020C01088).
文摘Multi-sensor measurement iswidely employed in rotatingmachinery to ensure the safety ofmachines.The information provided by the single sensor is not comprehensive.Multi-sensor signals can provide complementary information in characterizing the health condition of machines.This paper proposed a multi-sensor fusion convolution neural network(MF-CNN)model.The proposed model adds a 2-D convolution layer before the classical 1-D CNN to automatically extract complementary features of multi-sensor signals and minimize the loss of information.A series of experiments are carried out on a rolling bearing test rig to verify the model.Vibration and sound signals are fused to achieve higher classification accuracy than typical machine learning model.In addition,the model is further applied to gas turbine abnormal detection,and shows great robustness and generalization.
