Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
Objective To detect the specific mutations in rpoB gene of Mycobacterium tuberculosis by oligonucleotide microarray. Methods Four wild-type and 8 mutant probes were used to detect rifampin resistant strains. Target DN...Objective To detect the specific mutations in rpoB gene of Mycobacterium tuberculosis by oligonucleotide microarray. Methods Four wild-type and 8 mutant probes were used to detect rifampin resistant strains. Target DNA of M. tuberculosis was amplified by PCR, hybridized and scanned. Direct sequencing was performed to verify the results of oligonucleotide microarray Results Of the 102 rifampin-resistant strains 98 （96.1%） had mutations in the rpoB genes. Conclusion Oligonucleotide microarray with mutation-specific probes is a reliable and useful tool for the rapid and accurate diagnosis of rifampin resistance in M. tuberculosis isolates.展开更多
Objective The study is to identify the carrier rate of common deafness mutation in Chinese pregnant women via detecting deafness gene mutations with gene chip. Methods The pregnant women in obstetric clinic without he...Objective The study is to identify the carrier rate of common deafness mutation in Chinese pregnant women via detecting deafness gene mutations with gene chip. Methods The pregnant women in obstetric clinic without hearing impairment and hearing disorders family history were selected. The informed consent was signed. Peripheral blood was taken to extract genom- ic DNA. Application of genetic deafness gene chip for detecting 9 mutational hot spot of the most common 4 Chinese deafness genes, namely GJB2 （35delG, 176del16bp, 235delC, 299delAT）, GJB3 （C538T） ,SLC26A4 （ IVS72A〉G, A2168G） and mito- chondrial DNA 12S rRNA （A1555G, C1494T） . Further genetic testing were provided to the spouses and newborns of the screened carriers. Results Peripheral blood of 430 pregnant women were detected, detection of deafness gene mutation carri- ers in 24 cases（4.2%）, including 13 cases of the GJB2 heterozygous mutation, 3 cases of SLC26A4 heterozygous mutation, 1 cases of GJB3 heterozygous mutation, and 1 case of mitochondrial 12S rRNA mutation. 18 spouses and 17 newborns took further genetic tests, and 6 newborns inherited the mutation from their mother. Conclusion The common deafness genes muta- tion has a high carrier rate in pregnant women group, 235delC and IVS7-2A〉G heterozygous mutations are common.展开更多
A highly sensitive electrochemiluminescence-polymerase chain reaction (ECL-PCR) method for K-ras point mutation detection is developed. Briefly, K-ras oncogene was amplified by a Ru(bpy)3(2+) (TBR)-labeled forward and...A highly sensitive electrochemiluminescence-polymerase chain reaction (ECL-PCR) method for K-ras point mutation detection is developed. Briefly, K-ras oncogene was amplified by a Ru(bpy)3(2+) (TBR)-labeled forward and a biotin-labeled reverse primer, and followed by digestion with MvaI restriction enzyme, which only cut the wild-type amplicon containing its cutting site. The digested product was then adsorbed to the streptavidin-coated microbead through the biotin label and detected by ECL assay. The experiment results showed that the different genotypes can be clearly discriminated by ECL-PCR method. It is useful in point mutation detection, due to its sensitivity, safety, and simplicity.展开更多
Objective: To determine the feasibility of detecting p53 gene mutations for early diagnosis of lung cancer using the samples from bronchoscopic examination. Methods: Point mutations of the exon 5-8 of p53 gene were de...Objective: To determine the feasibility of detecting p53 gene mutations for early diagnosis of lung cancer using the samples from bronchoscopic examination. Methods: Point mutations of the exon 5-8 of p53 gene were detected in 85 bronchoscopic samples of 35 patients suspected to be lung cancer using silver staining PCR-SSCP. Results: p53 gene mutations were founded in 10 of 35 patients(28.6%). The incidence of p53 gene mutations (14.9%) was obviously higher than the cytological positive incidence(2.9%) in samples of sputum, bronchoalveolar lavage and brush, especially for the sputum(27.7%). In the bronchoscopic biopsy specimens, the incidence of p53 gene mutations (12.5%) was lower than that of pathologic positive result (50.0%). However, in view of all the bronchoscopic samples, there was no statistically difference between cytopathologic positive results (11.8%) and the incidence of p53 gene mutations (14.1%). Although the p53 mutations were most common in the samples from the patients bronchoscopically manifested as neoplasm compared with other manifestations, there was no statistical difference. It is valuable to notice that 3 patients with p53 gene mutation merely presented as bronchial inflammation in bronchoscope. Conclusion: Results indicated that the value of detecting p53 gene mutation for the diagnosis of lung cancer using the bronchoscopic samples was more superior to cytological examination and detection of p53 gene mutations in post-bronchoscopic sputum was easy and effective, may be used as a valuable method for early diagnosis of lung cancer.展开更多
To study the rpoB and katG gene mutation rate and its markers.MethodsCross-sectional study methods were used to study Tuberculosis. A total of 45 sputum samples were collected from Annapurna Neurological Institute and...To study the rpoB and katG gene mutation rate and its markers.MethodsCross-sectional study methods were used to study Tuberculosis. A total of 45 sputum samples were collected from Annapurna Neurological Institute and Allied sciences. Then, acid fast bacilli staining were performed. Positive and negative samples were carried for conventional polymerase chain reaction identification and electrophoresis.ResultsOut of 45 samples, 3 were acid fast bacilli positive and the rest were negative. Male participants were more as compare to female participants and the mutation in rpoB and katG gene was found similar i.e. 6.66% among the total samples.ConclusionsWe can conclude that genetic mutation in Mycobacterium tuberculosis can be identified directly from the clinical samples. However, we have carried this study in less sample size and to validate research on large number of sample is recommended.展开更多
Detection of point mutations in driver genes is of great significance for the early diagnosis,treatment,and prognostic evaluation of cancer.However,current detection methods do not offer versatility,specificity,and ra...Detection of point mutations in driver genes is of great significance for the early diagnosis,treatment,and prognostic evaluation of cancer.However,current detection methods do not offer versatility,specificity,and rapid performance simultaneously.Thus,multiple mutation detection processes are necessary,which results in long processing times and high costs.In this study,we developed a thermodynamics-guided two-way interlocking DNA cascade system for universal multiplexed mutation detection(TTI-CS).This strategy is based on the DNA probe,which changes the thermodynamic balance of the DNA cascade by the designed bubble structure,thereby achieving a good distinction between mutant and wild-type DNA.The designed method greatly shortens the detection time through two-way intrusion.In addition,this method only changes two inexpensive trigger and bridge sequences,which replace the specific and expensive nucleic acid probes used in analyses based on traditional DNA probe methods,thereby enabling multiple detections.We performed the detection of synthetic single-stranded DNA for the five mutation points and successfully detected in endometrial cancer specimens.The detection limit of this method is0.1%,which better meets the needs of clinical low-abundance multiple mutation detection.Overall,TTI-CS is currently one of the best methods for detecting multiple mutation detections.展开更多
In the engineering field,switching systems have been extensively studied,where sudden changes of parameter value and structural form have a significant impact on the operational performance of the system.Therefore,it ...In the engineering field,switching systems have been extensively studied,where sudden changes of parameter value and structural form have a significant impact on the operational performance of the system.Therefore,it is important to predict the behavior of the switching system,which includes the accurate detection of mutation points and rapid reidentification of the model.However,few efforts have been contributed to accurately locating the mutation points.In this paper,we propose a new measure of mutation detection—the threshold-based switching index by analogy with the Lyapunov exponent.We give the algorithm for selecting the optimal threshold,which greatly reduces the additional data collection and the relative error of mutation detection.In the system identification part,considering the small data amount available and noise in the data,the abrupt sparse Bayesian regression(abrupt-SBR)method is proposed.This method captures the model changes by updating the previously identified model,which requires less data and is more robust to noise than identifying the new model from scratch.With two representative dynamical systems,we illustrate the application and effectiveness of the proposed methods.Our research contributes to the accurate prediction and possible control of switching system behavior.展开更多
Enzyme assisted DNA probes are powerful tools in molecular diagnostics for their simplicity,rapidity,and low detection limit.However,cost of probes,difficulty in optimization and disturbance of secondary structure hin...Enzyme assisted DNA probes are powerful tools in molecular diagnostics for their simplicity,rapidity,and low detection limit.However,cost of probes,difficulty in optimization and disturbance of secondary structure hindered the wider application of enzyme assisted DNA probes.To solve the problems,we designed a new system named shared-probe system.By introducing two unlabeled single stranded DNA named Sh1 and Sh2 as the bridge between probe and the substrate,the same sequence of dually labeled probe with stable performance was shared for different mutations,thus sparing the expense and time cost on designing,synthesizing and optimizing corresponding probes.Besides,the hybridization between Sh1 and the substrate could overcome secondary structures,which guaranteed the detection of different substrates.The performance and generality of the design were tested by low abundance detection in synthetic single DNA samples and the limit of detection was 0.05%for PTENR130 Q,EGFR-L858 R and 0.02%for BRCA1-NM007294.3.In genomic DNA samples,the limit of detection of 0.1%can be achieved for EGFR-L858 R,demonstrating the potential of clinical application in our design.展开更多
With the growth of the discipline of digital communication,the topic has acquiredmore attention in the cybersecuritymedium.The Intrusion Detection(ID)system monitors network traffic to detect malicious activities.The ...With the growth of the discipline of digital communication,the topic has acquiredmore attention in the cybersecuritymedium.The Intrusion Detection(ID)system monitors network traffic to detect malicious activities.The paper introduces a novel Feature Selection(FS)approach for ID.Reptile Search Algorithm(RSA)—is a new optimization algorithm;in this method,each agent searches a new region according to the position of the host,which makes the algorithm suffers from getting stuck in local optima and a slow convergence rate.To overcome these problems,this study introduces an improved RSA approach by integrating Cauchy Mutation(CM)into the RSA’s structure.Thus,the CM can effectively expand search space and enhance the performance of the RSA.The developed RSA-CM is assessed on five publicly available ID datasets:KDD-CUP99,NSL-KDD,UNSW-NB15,CIC-IDS2017,and CIC-IDS2018 and two engineering problems.The RSA-CM is compared with the original RSA,and three other state-of-the-art FS methods,namely particle swarm optimization,grey wolf optimization,and multi-verse optimizer,and quantitatively is evaluated using fitness value,the number of selected optimum features,accuracy,precision,recall,and F1-score evaluationmeasures.The results reveal that the developed RSA-CMgot better results than the other competitive methods applied for FS on the ID datasets and the examined engineering problems.Moreover,the Friedman test results confirm that RSA-CMhas a significant superiority compared to other methods as an FS method for ID.展开更多
BACKGROUND The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis(HS)in children.We also hope to ...BACKGROUND The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis(HS)in children.We also hope to promote the application of gene detection technology in children with HS,with the goals of identifying more related gene mutations,supporting the acquisition of improved molecular genetic information to further reveal the pathogenesis of HS in children,and providing important guidance for the diagnosis,treatment,and prevention of HS in children.CASE SUMMARY A 1-year and 5-month-old patient presented jaundice during the neonatal period,mild anemia 8 months later,splenic enlargement at 1 year and 5 months,and brittle red blood cell permeability.Genetic testing was performed on the patient,their parents,and sister.Swiss Model software was used to predict the protein structure of complex heterozygous mutations in ANK1 and SPTA1.Genetic testing revealed that the patient harbored a new mutation in the ANK1 gene from the father and a mutation in the SPTA1 gene from the mother.Combined with the clinical symptoms of the children,it is suggested that the newly discovered complex heterozygous mutations of ANK1 and SPTA1 may be the cause,providing important guidance for revealing the pathogenesis,diagnosis,treatment,and promotion of gene detection technology in children with HS.CONCLUSION This case involves an unreported complex heterozygous mutation of ANK1 and SPTA1,which provides a reference for exploring HS.展开更多
This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the g...This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the grey value of targets is enhanced by calculating the local energy. Image segmentation based on the adaptive threshold is used to solve the problems that the grey value of noise is enhanced with the grey value improvement of targets. Experimental results show that compared with the adaptive Butterworth high-pass filter method, the proposed algorithm is more effective and faster for the infrared small target detection.展开更多
BACKGROUND Patients diagnosed with non-small-cell lung cancer with activated epidermal growth factor receptor mutations are more likely to develop leptomeningeal(LM)metastasis than other types of lung cancers and have...BACKGROUND Patients diagnosed with non-small-cell lung cancer with activated epidermal growth factor receptor mutations are more likely to develop leptomeningeal(LM)metastasis than other types of lung cancers and have a poor prognosis.Early diagnosis and effective treatment of leptomeningeal carcinoma can improve the prognosis.CASE SUMMARY A 55-year-old female with a progressive headache and vomiting for one month was admitted to Peking University First Hospital.She was diagnosed with lung adenocarcinoma with osseous metastasis 10 months prior to admittance.epidermal growth factor receptor(EGFR)mutation was detected by genomic examination,so she was first treated with gefitinib for 10 months before acquiring resistance.Cell-free cerebrospinal fluid(CSF)circulating tumor DNA detection by next-generation sequencing was conducted and indicated the EGFR-Thr790Met mutation,while biopsy and cytology from the patient’s CSF and the first enhanced cranial magnetic resonance imaging(MRI)showed no positive findings.A month later,the enhanced MRI showed linear leptomeningeal enhancement,and the cytology and biochemical examination in CSF remained negative.Therefore,osimertinib(80 mg/d)was initiated as a second-line treatment,resulting in a good response within a month.CONCLUSION This report suggests clinical benefit of osimertinib in LM patients with positive detection of the EGFR-Thr790Met mutation in CSF and proposes that the positive findings of CSF circulating tumor DNA as a liquid biopsy technology based on the detection of cancer-associated gene mutations may appear earlier than the imaging and CSF findings and may thus be helpful for therapy.Moreover,the routine screening of chest CT with the novel coronavirus may provide unexpected benefits。展开更多
Kirsten rat sarcoma viral oncogene homolog(namely KRAS)is a key biomarker for prognostic analysis and targeted therapy of colorectal cancer.Recently,the advancement of machine learning,especially deep learning,has gre...Kirsten rat sarcoma viral oncogene homolog(namely KRAS)is a key biomarker for prognostic analysis and targeted therapy of colorectal cancer.Recently,the advancement of machine learning,especially deep learning,has greatly promoted the development of KRAS mutation detection from tumor phenotype data,such as pathology slides or radiology images.However,there are still two major problems in existing studies:inadequate single-modal feature learning and lack of multimodal phenotypic feature fusion.In this paper,we propose a Disentangled Representation-based Multimodal Fusion framework integrating Pathomics and Radiomics(DRMF-PaRa)for KRAS mutation detection.Specifically,the DRMF-PaRa model consists of three parts:(1)the pathomics learning module,which introduces a tissue-guided Transformer model to extract more comprehensive and targeted pathological features;(2)the radiomics learning module,which captures the generic hand-crafted radiomics features and the task-specific deep radiomics features;(3)the disentangled representation-based multimodal fusion module,which learns factorized subspaces for each modality and provides a holistic view of the two heterogeneous phenotypic features.The proposed model is developed and evaluated on a multi modality dataset of 111 colorectal cancer patients with whole slide images and contrast-enhanced CT.The experimental results demonstrate the superiority of the proposed DRMF-PaRa model with an accuracy of 0.876 and an AUC of 0.865 for KRAS mutation detection.展开更多
A measure of the“goodness”or efficiency of the test suite is used to determine the proficiency of a test suite.The appropriateness of the test suite is determined through mutation analysis.Several Finite State Machi...A measure of the“goodness”or efficiency of the test suite is used to determine the proficiency of a test suite.The appropriateness of the test suite is determined through mutation analysis.Several Finite State Machine(FSM)mutants are produced in mutation analysis by injecting errors against hypotheses.These mutants serve as test subjects for the test suite(TS).The effectiveness of the test suite is proportional to the number of eliminated mutants.The most effective test suite is the one that removes the most significant number of mutants at the optimal time.It is difficult to determine the fault detection ratio of the system.Because it is difficult to identify the system’s potential flaws precisely.In mutation testing,the Fault Detection Ratio(FDR)metric is currently used to express the adequacy of a test suite.However,there are some issues with this metric.If both test suites have the same defect detection rate,the smaller of the two tests is preferred.The test case(TC)is affected by the same issue.The smaller two test cases with identical performance are assumed to have superior performance.Another difficulty involves time.The performance of numerous vehicles claiming to have a perfect mutant capture time is problematic.Our study developed three metrics to address these issues:FDR/|TS|,FDR/|TC|,and FDR/|Time|;In this context,most used test generation tools were examined and tested using the developed metrics.Thanks to the metrics we have developed,the research contributes to eliminating the problems related to performance measurement by integrating the missing parameters into the system.展开更多
On grounds of the advent of real-time applications,like autonomous driving,visual surveillance,and sports analysis,there is an augmenting focus of attention towards Multiple-Object Tracking(MOT).The tracking-by-detect...On grounds of the advent of real-time applications,like autonomous driving,visual surveillance,and sports analysis,there is an augmenting focus of attention towards Multiple-Object Tracking(MOT).The tracking-by-detection paradigm,a commonly utilized approach,connects the existing recognition hypotheses to the formerly assessed object trajectories by comparing the simila-rities of the appearance or the motion between them.For an efficient detection and tracking of the numerous objects in a complex environment,a Pearson Simi-larity-centred Kuhn-Munkres(PS-KM)algorithm was proposed in the present study.In this light,the input videos were,initially,gathered from the MOT dataset and converted into frames.The background subtraction occurred whichfiltered the inappropriate data concerning the frames after the frame conversion stage.Then,the extraction of features from the frames was executed.Afterwards,the higher dimensional features were transformed into lower-dimensional features,and feature reduction process was performed with the aid of Information Gain-centred Singular Value Decomposition(IG-SVD).Next,using the Modified Recurrent Neural Network(MRNN)method,classification was executed which identified the categories of the objects additionally.The PS-KM algorithm identi-fied that the recognized objects were tracked.Finally,the experimental outcomes exhibited that numerous targets were precisely tracked by the proposed system with 97%accuracy with a low false positive rate(FPR)of 2.3%.It was also proved that the present techniques viz.RNN,CNN,and KNN,were effective with regard to the existing models.展开更多
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金supported by the grant from the National Natural Science Foundation of China (No. 30400018)
文摘Objective To detect the specific mutations in rpoB gene of Mycobacterium tuberculosis by oligonucleotide microarray. Methods Four wild-type and 8 mutant probes were used to detect rifampin resistant strains. Target DNA of M. tuberculosis was amplified by PCR, hybridized and scanned. Direct sequencing was performed to verify the results of oligonucleotide microarray Results Of the 102 rifampin-resistant strains 98 （96.1%） had mutations in the rpoB genes. Conclusion Oligonucleotide microarray with mutation-specific probes is a reliable and useful tool for the rapid and accurate diagnosis of rifampin resistance in M. tuberculosis isolates.
文摘Objective The study is to identify the carrier rate of common deafness mutation in Chinese pregnant women via detecting deafness gene mutations with gene chip. Methods The pregnant women in obstetric clinic without hearing impairment and hearing disorders family history were selected. The informed consent was signed. Peripheral blood was taken to extract genom- ic DNA. Application of genetic deafness gene chip for detecting 9 mutational hot spot of the most common 4 Chinese deafness genes, namely GJB2 （35delG, 176del16bp, 235delC, 299delAT）, GJB3 （C538T） ,SLC26A4 （ IVS72A〉G, A2168G） and mito- chondrial DNA 12S rRNA （A1555G, C1494T） . Further genetic testing were provided to the spouses and newborns of the screened carriers. Results Peripheral blood of 430 pregnant women were detected, detection of deafness gene mutation carri- ers in 24 cases（4.2%）, including 13 cases of the GJB2 heterozygous mutation, 3 cases of SLC26A4 heterozygous mutation, 1 cases of GJB3 heterozygous mutation, and 1 case of mitochondrial 12S rRNA mutation. 18 spouses and 17 newborns took further genetic tests, and 6 newborns inherited the mutation from their mother. Conclusion The common deafness genes muta- tion has a high carrier rate in pregnant women group, 235delC and IVS7-2A〉G heterozygous mutations are common.
文摘A highly sensitive electrochemiluminescence-polymerase chain reaction (ECL-PCR) method for K-ras point mutation detection is developed. Briefly, K-ras oncogene was amplified by a Ru(bpy)3(2+) (TBR)-labeled forward and a biotin-labeled reverse primer, and followed by digestion with MvaI restriction enzyme, which only cut the wild-type amplicon containing its cutting site. The digested product was then adsorbed to the streptavidin-coated microbead through the biotin label and detected by ECL assay. The experiment results showed that the different genotypes can be clearly discriminated by ECL-PCR method. It is useful in point mutation detection, due to its sensitivity, safety, and simplicity.
基金the Research Foundation of the Ministry of Public Health of PR China !(No. 94-1-316).
文摘Objective: To determine the feasibility of detecting p53 gene mutations for early diagnosis of lung cancer using the samples from bronchoscopic examination. Methods: Point mutations of the exon 5-8 of p53 gene were detected in 85 bronchoscopic samples of 35 patients suspected to be lung cancer using silver staining PCR-SSCP. Results: p53 gene mutations were founded in 10 of 35 patients(28.6%). The incidence of p53 gene mutations (14.9%) was obviously higher than the cytological positive incidence(2.9%) in samples of sputum, bronchoalveolar lavage and brush, especially for the sputum(27.7%). In the bronchoscopic biopsy specimens, the incidence of p53 gene mutations (12.5%) was lower than that of pathologic positive result (50.0%). However, in view of all the bronchoscopic samples, there was no statistically difference between cytopathologic positive results (11.8%) and the incidence of p53 gene mutations (14.1%). Although the p53 mutations were most common in the samples from the patients bronchoscopically manifested as neoplasm compared with other manifestations, there was no statistical difference. It is valuable to notice that 3 patients with p53 gene mutation merely presented as bronchial inflammation in bronchoscope. Conclusion: Results indicated that the value of detecting p53 gene mutation for the diagnosis of lung cancer using the bronchoscopic samples was more superior to cytological examination and detection of p53 gene mutations in post-bronchoscopic sputum was easy and effective, may be used as a valuable method for early diagnosis of lung cancer.
基金supported and funded by Department of Medical Microbiology,Nobel College,Pokhara University,Kathmandu Nepal with grant number MM-124
文摘To study the rpoB and katG gene mutation rate and its markers.MethodsCross-sectional study methods were used to study Tuberculosis. A total of 45 sputum samples were collected from Annapurna Neurological Institute and Allied sciences. Then, acid fast bacilli staining were performed. Positive and negative samples were carried for conventional polymerase chain reaction identification and electrophoresis.ResultsOut of 45 samples, 3 were acid fast bacilli positive and the rest were negative. Male participants were more as compare to female participants and the mutation in rpoB and katG gene was found similar i.e. 6.66% among the total samples.ConclusionsWe can conclude that genetic mutation in Mycobacterium tuberculosis can be identified directly from the clinical samples. However, we have carried this study in less sample size and to validate research on large number of sample is recommended.
基金supported by the Science and Technology Innovation Project of Hubei Province(No.2019ACA138)the National Natural Science Foundation of China(Nos.81871732 and 81974409)。
文摘Detection of point mutations in driver genes is of great significance for the early diagnosis,treatment,and prognostic evaluation of cancer.However,current detection methods do not offer versatility,specificity,and rapid performance simultaneously.Thus,multiple mutation detection processes are necessary,which results in long processing times and high costs.In this study,we developed a thermodynamics-guided two-way interlocking DNA cascade system for universal multiplexed mutation detection(TTI-CS).This strategy is based on the DNA probe,which changes the thermodynamic balance of the DNA cascade by the designed bubble structure,thereby achieving a good distinction between mutant and wild-type DNA.The designed method greatly shortens the detection time through two-way intrusion.In addition,this method only changes two inexpensive trigger and bridge sequences,which replace the specific and expensive nucleic acid probes used in analyses based on traditional DNA probe methods,thereby enabling multiple detections.We performed the detection of synthetic single-stranded DNA for the five mutation points and successfully detected in endometrial cancer specimens.The detection limit of this method is0.1%,which better meets the needs of clinical low-abundance multiple mutation detection.Overall,TTI-CS is currently one of the best methods for detecting multiple mutation detections.
基金the National Natural Science Foundation of China(Grant No.12072261)。
文摘In the engineering field,switching systems have been extensively studied,where sudden changes of parameter value and structural form have a significant impact on the operational performance of the system.Therefore,it is important to predict the behavior of the switching system,which includes the accurate detection of mutation points and rapid reidentification of the model.However,few efforts have been contributed to accurately locating the mutation points.In this paper,we propose a new measure of mutation detection—the threshold-based switching index by analogy with the Lyapunov exponent.We give the algorithm for selecting the optimal threshold,which greatly reduces the additional data collection and the relative error of mutation detection.In the system identification part,considering the small data amount available and noise in the data,the abrupt sparse Bayesian regression(abrupt-SBR)method is proposed.This method captures the model changes by updating the previously identified model,which requires less data and is more robust to noise than identifying the new model from scratch.With two representative dynamical systems,we illustrate the application and effectiveness of the proposed methods.Our research contributes to the accurate prediction and possible control of switching system behavior.
基金the National Natural Science Foundation of China(Nos.21705053 and 81871732)the Natural Science Foundation of Hubei Province(No.2017CFB117)+1 种基金Hubei Province Health and Family Planning Scientific Research Project(No.J2017Q017)Wuhan Youth Science and Technology Plan(No.2017050304010293)。
文摘Enzyme assisted DNA probes are powerful tools in molecular diagnostics for their simplicity,rapidity,and low detection limit.However,cost of probes,difficulty in optimization and disturbance of secondary structure hindered the wider application of enzyme assisted DNA probes.To solve the problems,we designed a new system named shared-probe system.By introducing two unlabeled single stranded DNA named Sh1 and Sh2 as the bridge between probe and the substrate,the same sequence of dually labeled probe with stable performance was shared for different mutations,thus sparing the expense and time cost on designing,synthesizing and optimizing corresponding probes.Besides,the hybridization between Sh1 and the substrate could overcome secondary structures,which guaranteed the detection of different substrates.The performance and generality of the design were tested by low abundance detection in synthetic single DNA samples and the limit of detection was 0.05%for PTENR130 Q,EGFR-L858 R and 0.02%for BRCA1-NM007294.3.In genomic DNA samples,the limit of detection of 0.1%can be achieved for EGFR-L858 R,demonstrating the potential of clinical application in our design.
文摘With the growth of the discipline of digital communication,the topic has acquiredmore attention in the cybersecuritymedium.The Intrusion Detection(ID)system monitors network traffic to detect malicious activities.The paper introduces a novel Feature Selection(FS)approach for ID.Reptile Search Algorithm(RSA)—is a new optimization algorithm;in this method,each agent searches a new region according to the position of the host,which makes the algorithm suffers from getting stuck in local optima and a slow convergence rate.To overcome these problems,this study introduces an improved RSA approach by integrating Cauchy Mutation(CM)into the RSA’s structure.Thus,the CM can effectively expand search space and enhance the performance of the RSA.The developed RSA-CM is assessed on five publicly available ID datasets:KDD-CUP99,NSL-KDD,UNSW-NB15,CIC-IDS2017,and CIC-IDS2018 and two engineering problems.The RSA-CM is compared with the original RSA,and three other state-of-the-art FS methods,namely particle swarm optimization,grey wolf optimization,and multi-verse optimizer,and quantitatively is evaluated using fitness value,the number of selected optimum features,accuracy,precision,recall,and F1-score evaluationmeasures.The results reveal that the developed RSA-CMgot better results than the other competitive methods applied for FS on the ID datasets and the examined engineering problems.Moreover,the Friedman test results confirm that RSA-CMhas a significant superiority compared to other methods as an FS method for ID.
基金Supported by The Science and Technology Department of Sichuan Province,No.2021JDKP0015.
文摘BACKGROUND The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis(HS)in children.We also hope to promote the application of gene detection technology in children with HS,with the goals of identifying more related gene mutations,supporting the acquisition of improved molecular genetic information to further reveal the pathogenesis of HS in children,and providing important guidance for the diagnosis,treatment,and prevention of HS in children.CASE SUMMARY A 1-year and 5-month-old patient presented jaundice during the neonatal period,mild anemia 8 months later,splenic enlargement at 1 year and 5 months,and brittle red blood cell permeability.Genetic testing was performed on the patient,their parents,and sister.Swiss Model software was used to predict the protein structure of complex heterozygous mutations in ANK1 and SPTA1.Genetic testing revealed that the patient harbored a new mutation in the ANK1 gene from the father and a mutation in the SPTA1 gene from the mother.Combined with the clinical symptoms of the children,it is suggested that the newly discovered complex heterozygous mutations of ANK1 and SPTA1 may be the cause,providing important guidance for revealing the pathogenesis,diagnosis,treatment,and promotion of gene detection technology in children with HS.CONCLUSION This case involves an unreported complex heterozygous mutation of ANK1 and SPTA1,which provides a reference for exploring HS.
基金supported by the National Natural Science Foundation of China (61171194)
文摘This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the grey value of targets is enhanced by calculating the local energy. Image segmentation based on the adaptive threshold is used to solve the problems that the grey value of noise is enhanced with the grey value improvement of targets. Experimental results show that compared with the adaptive Butterworth high-pass filter method, the proposed algorithm is more effective and faster for the infrared small target detection.
文摘BACKGROUND Patients diagnosed with non-small-cell lung cancer with activated epidermal growth factor receptor mutations are more likely to develop leptomeningeal(LM)metastasis than other types of lung cancers and have a poor prognosis.Early diagnosis and effective treatment of leptomeningeal carcinoma can improve the prognosis.CASE SUMMARY A 55-year-old female with a progressive headache and vomiting for one month was admitted to Peking University First Hospital.She was diagnosed with lung adenocarcinoma with osseous metastasis 10 months prior to admittance.epidermal growth factor receptor(EGFR)mutation was detected by genomic examination,so she was first treated with gefitinib for 10 months before acquiring resistance.Cell-free cerebrospinal fluid(CSF)circulating tumor DNA detection by next-generation sequencing was conducted and indicated the EGFR-Thr790Met mutation,while biopsy and cytology from the patient’s CSF and the first enhanced cranial magnetic resonance imaging(MRI)showed no positive findings.A month later,the enhanced MRI showed linear leptomeningeal enhancement,and the cytology and biochemical examination in CSF remained negative.Therefore,osimertinib(80 mg/d)was initiated as a second-line treatment,resulting in a good response within a month.CONCLUSION This report suggests clinical benefit of osimertinib in LM patients with positive detection of the EGFR-Thr790Met mutation in CSF and proposes that the positive findings of CSF circulating tumor DNA as a liquid biopsy technology based on the detection of cancer-associated gene mutations may appear earlier than the imaging and CSF findings and may thus be helpful for therapy.Moreover,the routine screening of chest CT with the novel coronavirus may provide unexpected benefits。
基金supported by the National Natural Science Foundation of China(Nos.61932018,32241027,62072441,62272326,62132015,and U22A2037)the Beijing Municipal Administration of Hospitals Incubating Program(No.PX2021013).
文摘Kirsten rat sarcoma viral oncogene homolog(namely KRAS)is a key biomarker for prognostic analysis and targeted therapy of colorectal cancer.Recently,the advancement of machine learning,especially deep learning,has greatly promoted the development of KRAS mutation detection from tumor phenotype data,such as pathology slides or radiology images.However,there are still two major problems in existing studies:inadequate single-modal feature learning and lack of multimodal phenotypic feature fusion.In this paper,we propose a Disentangled Representation-based Multimodal Fusion framework integrating Pathomics and Radiomics(DRMF-PaRa)for KRAS mutation detection.Specifically,the DRMF-PaRa model consists of three parts:(1)the pathomics learning module,which introduces a tissue-guided Transformer model to extract more comprehensive and targeted pathological features;(2)the radiomics learning module,which captures the generic hand-crafted radiomics features and the task-specific deep radiomics features;(3)the disentangled representation-based multimodal fusion module,which learns factorized subspaces for each modality and provides a holistic view of the two heterogeneous phenotypic features.The proposed model is developed and evaluated on a multi modality dataset of 111 colorectal cancer patients with whole slide images and contrast-enhanced CT.The experimental results demonstrate the superiority of the proposed DRMF-PaRa model with an accuracy of 0.876 and an AUC of 0.865 for KRAS mutation detection.
文摘A measure of the“goodness”or efficiency of the test suite is used to determine the proficiency of a test suite.The appropriateness of the test suite is determined through mutation analysis.Several Finite State Machine(FSM)mutants are produced in mutation analysis by injecting errors against hypotheses.These mutants serve as test subjects for the test suite(TS).The effectiveness of the test suite is proportional to the number of eliminated mutants.The most effective test suite is the one that removes the most significant number of mutants at the optimal time.It is difficult to determine the fault detection ratio of the system.Because it is difficult to identify the system’s potential flaws precisely.In mutation testing,the Fault Detection Ratio(FDR)metric is currently used to express the adequacy of a test suite.However,there are some issues with this metric.If both test suites have the same defect detection rate,the smaller of the two tests is preferred.The test case(TC)is affected by the same issue.The smaller two test cases with identical performance are assumed to have superior performance.Another difficulty involves time.The performance of numerous vehicles claiming to have a perfect mutant capture time is problematic.Our study developed three metrics to address these issues:FDR/|TS|,FDR/|TC|,and FDR/|Time|;In this context,most used test generation tools were examined and tested using the developed metrics.Thanks to the metrics we have developed,the research contributes to eliminating the problems related to performance measurement by integrating the missing parameters into the system.
文摘On grounds of the advent of real-time applications,like autonomous driving,visual surveillance,and sports analysis,there is an augmenting focus of attention towards Multiple-Object Tracking(MOT).The tracking-by-detection paradigm,a commonly utilized approach,connects the existing recognition hypotheses to the formerly assessed object trajectories by comparing the simila-rities of the appearance or the motion between them.For an efficient detection and tracking of the numerous objects in a complex environment,a Pearson Simi-larity-centred Kuhn-Munkres(PS-KM)algorithm was proposed in the present study.In this light,the input videos were,initially,gathered from the MOT dataset and converted into frames.The background subtraction occurred whichfiltered the inappropriate data concerning the frames after the frame conversion stage.Then,the extraction of features from the frames was executed.Afterwards,the higher dimensional features were transformed into lower-dimensional features,and feature reduction process was performed with the aid of Information Gain-centred Singular Value Decomposition(IG-SVD).Next,using the Modified Recurrent Neural Network(MRNN)method,classification was executed which identified the categories of the objects additionally.The PS-KM algorithm identi-fied that the recognized objects were tracked.Finally,the experimental outcomes exhibited that numerous targets were precisely tracked by the proposed system with 97%accuracy with a low false positive rate(FPR)of 2.3%.It was also proved that the present techniques viz.RNN,CNN,and KNN,were effective with regard to the existing models.
