For first-line non-small-cell lung cancer（NSCLC） therapy,detecting mutation status of the epidermal growth factor receptor（EGFR） gene constitutes a prudent test to identify patients who are most likely to benefit ...For first-line non-small-cell lung cancer（NSCLC） therapy,detecting mutation status of the epidermal growth factor receptor（EGFR） gene constitutes a prudent test to identify patients who are most likely to benefit from EGFR-tyrosine kinase inhibitor（TKI） therapy.Now,the material for detecting EGFR gene mutation status mainly comes from formalin-fixed and paraffin-embedded（FFPE） tissues.DNA extraction from FFPE and the amplification of EGFR gene by polymerase chain reaction（PCR） are two key steps for detecting EGFR gene mutation.We showed a simple method of DNA extraction from FFPE tissues for the effective amplification of EGFR gene.Extracting DNA from the FFPE tissues of NSCLC patients with 1% Triton X-100（pH=10.0） was performed by heating at 95 °C for 30 min.Meanwhile,a commercial kit was used to extract DNA from the same FFPE tissues of NSCLC patients for comparison.DNA extracted products were used as template for amplifying the exons 18,19,20 and 21 of EGFR by PCR for different amplified fragments.Results show that DNA fragment size extracted from FFPE tissues with 1% Triton X was about 250―500 base pairs（bp）.However,DNA fragment size extracted from FFPE tissues via commercial kit was about from several hundreds to several thousands bp.The DNA yield extracted from FFPE tissues with 1% Triton X was larger than that via commercial kit.For about 500 bp fragment,four exons of EGFR could not be amplified more efficiently from extracted DNA with 1% Triton X than with commercial kit.However,for about 200 bp fragment.This simple and non-laborious protocol could successfully be used to extract DNA from FFPE tissue for the amplification of EGFR gene by PCR,further screening of EGFR gene mutation and facilitating the molecular analysis of a large number of FFPE tissues from NSCLC patients.展开更多
5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent lat...5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and dynamic.Slicing enables service providers to develop various network slice architectures.As users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different expectations.This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks.Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies.Therefore,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover.The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being dropped.Hence,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity.Moreover,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces.The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.展开更多
BACKGROUND Mycobacterium mucogenicum(M.mucogenicum)belongs to the group of rapidly growing Nontuberculous mycobacteria.This microorganism is associated with a wide spectrum of infectious diseases.Due to a low detectio...BACKGROUND Mycobacterium mucogenicum(M.mucogenicum)belongs to the group of rapidly growing Nontuberculous mycobacteria.This microorganism is associated with a wide spectrum of infectious diseases.Due to a low detection rate or the time required for conventional culture methodology,a rapid and broad-spectrum method is necessary to identify rare pathogens.CASE SUMMARY A 12-year-old immunocompetent girl presented with painful masses for five months.The first mass was found in the right upper quadrant of the abdomen,and was about 1 cm×1.5 cm in size,tough but pliable in texture,with an irregular margin and tenderness.An abscess gradually formed and ulcerated with suppuration of the mass.Three new masses appeared on the back one by one.Chest computed tomography showed patchy and streaky cloudy opacities in both lungs.Needle aspiration of the abscess was performed,but the smear and conventional culture were negative,and the pathological examination showed no pathogens.We then performed next-generation sequencing using a formalinfixed,paraffin-embedded specimen to identify the pathogen.A significantly high abundance of M.mucogenicum was detected.The patient’s abscesses gradually decreased in size,while inflammation in both lungs improved following 12-wk of treatment.No recurrence was observed four months after the end of the one-year treatment period.CONCLUSION Next-generation sequencing is a promising tool for the rapid and accurate diagnosis of rare pathogens,even when using a formalin-fixed,paraffin-embedded specimen.展开更多
Background: Differential diagnosis of follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA) is often difficult since presence or absence of capsular/vascular invasion can not be determined by preope...Background: Differential diagnosis of follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA) is often difficult since presence or absence of capsular/vascular invasion can not be determined by preoperative fine needle aspiration cytology, and may not be judged unanimously on permanent sections even among experienced pathologists. Determination of molecular-genetic factors such as trefoil factor 3 (TFF3) mRNA in the follicular thyroid tumors may be useful aid to improve the accuracy of diagnosis, though it is considered to be unstable and relatively low concentrated genetic substance. Purpose of our study is to investigate expression level of TFF3 mRNA of thyroid follicular tumors using formalin-fixed, paraffin-embedded (FFPE) tissue. Methods: Study population included FFPE sections from 19 FTC cases, 20 FTA cases, 11 adenomatous goiter (G) cases and 12 samples of normal thyroid tissue (N) adjacent to thyroid tumors. RNeasy FFPE kit was used for extraction of total RNA. Purification and concentration values were determined by spectrophotometer. Extracted RNA was used for cDNA synthesis in reverse transcription. Synthesized cDNA subsequently proceeded for relative quantification of TFF3 mRNA by RT-qPCR using TFF3 primers. Glyceroldehyde-3-phosphate dehydrogenase (GAPDH) and hypoxanthin phosphorobosyltransferase1 (HPRT1) were used as control genes. The mean and standard deviation of TFF3 mRNA expression level were analyzed by software Multiplate RQ. Results: Extraction by the FFPE kit yielded high concentration of RNA in all cases. Purification values were 1.8 in average. Concentration values were significantly higher in FTC and FTA relative to G and N tissues, possibly due to high density of thyrocytes in the samples. Relative quantification of TFF3 mRNA expression level showed broad ranges both in FTC and FTA, while the analyses in G and N tissues indicated narrow ranges. Conclusion: FFPE tissues from thyroid follicular tumors can be used for measurement of unstable and low concentrated genetic substances such as TFF3 mRNA. Its diagnostic value yet remains to be determined.展开更多
Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value chain.Its highly heterogeneous network structu...Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value chain.Its highly heterogeneous network structure and diversified application requirements call for the applying of network slicing technology.Guaranteeing robust network slicing is essential for Industrial Internet,but it faces the challenge of complex slice topologies caused by the intricate interaction relationships among Network Functions(NFs)composing the slice.Existing works have not concerned the strengthening problem of industrial network slicing regarding its complex network properties.Towards this end,we aim to study this issue by intelligently selecting a subset of most valuable NFs with the minimum cost to satisfy the strengthening requirements.State-of-the-art AlphaGo series of algorithms and the advanced graph neural network technology are combined to build the solution.Simulation results demonstrate the superior performance of our scheme compared to the benchmark schemes.展开更多
In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Se...In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.展开更多
This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are c...This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are computed. Then, the forward and backward data slices for this attribute are generated by using the class as the slice scope and are combined to compute the corresponding class data slice. Finally, the class cohesion is computed based on all class data slices for the attributes. Compared to traditional cohesion metrics that use methods as the slice scope, the proposed metrics that use a single class as slice scope take into account the possible interactions between the methods. The experimental results show that class cohesion can be more accurately measured when using the class as the slice scope.展开更多
Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluatio...Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.展开更多
To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and intern...To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and internal node state, we find the deficiency of only using port information. Then, we define the gate level number computing method and the concept of slice, and propose using slice analysis to distill switching density as coefficients in a special circuit stage and participate in Bayesian inference with port information. Experiments show that this method can reduce the power-per-cycle estimation error by 21.9% and the root mean square error by 25.0% compared with the original model, and maintain a 700 ＋ speedup compared with the existing gate-level power analysis technique.展开更多
A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a pr...A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a procedure with the given labels, and then captures the callees＇ influence on callers when analyzing call statements. Phase 2 captures the callees＇ dependence on callers by replacing all given labels appearing in the corresponding sets of formal parameters. By the introduction of given labels, this slice method can obtain similar summary information in system-dependence-graph（SDG）-based algorithms for addressing the calling-context problem. With the use of the slice monad transformer, this monadic slicing approach achieves a high level of modularity and flexibility. It shows that the monadic interprocedural algorithm has less complexity and it is not less precise than SDG algorithms.展开更多
基金Supported by the Jilin Science & Technology Development Plan,China(No.201201060)the Scientific Research Foundation of Jilin Province,China(No.20100942)+1 种基金the Fund of Developing and Reforming Community of Jilin Province,China(No.2010-1928)the Health Scientific Research Foundation of Jilin Province,China(Nos.2009z081,2010Z083)
文摘For first-line non-small-cell lung cancer（NSCLC） therapy,detecting mutation status of the epidermal growth factor receptor（EGFR） gene constitutes a prudent test to identify patients who are most likely to benefit from EGFR-tyrosine kinase inhibitor（TKI） therapy.Now,the material for detecting EGFR gene mutation status mainly comes from formalin-fixed and paraffin-embedded（FFPE） tissues.DNA extraction from FFPE and the amplification of EGFR gene by polymerase chain reaction（PCR） are two key steps for detecting EGFR gene mutation.We showed a simple method of DNA extraction from FFPE tissues for the effective amplification of EGFR gene.Extracting DNA from the FFPE tissues of NSCLC patients with 1% Triton X-100（pH=10.0） was performed by heating at 95 °C for 30 min.Meanwhile,a commercial kit was used to extract DNA from the same FFPE tissues of NSCLC patients for comparison.DNA extracted products were used as template for amplifying the exons 18,19,20 and 21 of EGFR by PCR for different amplified fragments.Results show that DNA fragment size extracted from FFPE tissues with 1% Triton X was about 250―500 base pairs（bp）.However,DNA fragment size extracted from FFPE tissues via commercial kit was about from several hundreds to several thousands bp.The DNA yield extracted from FFPE tissues with 1% Triton X was larger than that via commercial kit.For about 500 bp fragment,four exons of EGFR could not be amplified more efficiently from extracted DNA with 1% Triton X than with commercial kit.However,for about 200 bp fragment.This simple and non-laborious protocol could successfully be used to extract DNA from FFPE tissue for the amplification of EGFR gene by PCR,further screening of EGFR gene mutation and facilitating the molecular analysis of a large number of FFPE tissues from NSCLC patients.
基金This work was supported partially by the BK21 FOUR program of the National Research Foundation of Korea funded by the Ministry of Education(NRF5199991514504)by theMSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2023-2018-0-01431)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and dynamic.Slicing enables service providers to develop various network slice architectures.As users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different expectations.This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks.Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies.Therefore,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover.The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being dropped.Hence,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity.Moreover,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces.The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.
基金Supported by the Clinical Research Foundation of the Third Affiliated Hospital of Sun Yat-Sen University,No.YHJH201904National Science and Technology Major Project,No.2018ZX10302204.
文摘BACKGROUND Mycobacterium mucogenicum(M.mucogenicum)belongs to the group of rapidly growing Nontuberculous mycobacteria.This microorganism is associated with a wide spectrum of infectious diseases.Due to a low detection rate or the time required for conventional culture methodology,a rapid and broad-spectrum method is necessary to identify rare pathogens.CASE SUMMARY A 12-year-old immunocompetent girl presented with painful masses for five months.The first mass was found in the right upper quadrant of the abdomen,and was about 1 cm×1.5 cm in size,tough but pliable in texture,with an irregular margin and tenderness.An abscess gradually formed and ulcerated with suppuration of the mass.Three new masses appeared on the back one by one.Chest computed tomography showed patchy and streaky cloudy opacities in both lungs.Needle aspiration of the abscess was performed,but the smear and conventional culture were negative,and the pathological examination showed no pathogens.We then performed next-generation sequencing using a formalinfixed,paraffin-embedded specimen to identify the pathogen.A significantly high abundance of M.mucogenicum was detected.The patient’s abscesses gradually decreased in size,while inflammation in both lungs improved following 12-wk of treatment.No recurrence was observed four months after the end of the one-year treatment period.CONCLUSION Next-generation sequencing is a promising tool for the rapid and accurate diagnosis of rare pathogens,even when using a formalin-fixed,paraffin-embedded specimen.
文摘Background: Differential diagnosis of follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA) is often difficult since presence or absence of capsular/vascular invasion can not be determined by preoperative fine needle aspiration cytology, and may not be judged unanimously on permanent sections even among experienced pathologists. Determination of molecular-genetic factors such as trefoil factor 3 (TFF3) mRNA in the follicular thyroid tumors may be useful aid to improve the accuracy of diagnosis, though it is considered to be unstable and relatively low concentrated genetic substance. Purpose of our study is to investigate expression level of TFF3 mRNA of thyroid follicular tumors using formalin-fixed, paraffin-embedded (FFPE) tissue. Methods: Study population included FFPE sections from 19 FTC cases, 20 FTA cases, 11 adenomatous goiter (G) cases and 12 samples of normal thyroid tissue (N) adjacent to thyroid tumors. RNeasy FFPE kit was used for extraction of total RNA. Purification and concentration values were determined by spectrophotometer. Extracted RNA was used for cDNA synthesis in reverse transcription. Synthesized cDNA subsequently proceeded for relative quantification of TFF3 mRNA by RT-qPCR using TFF3 primers. Glyceroldehyde-3-phosphate dehydrogenase (GAPDH) and hypoxanthin phosphorobosyltransferase1 (HPRT1) were used as control genes. The mean and standard deviation of TFF3 mRNA expression level were analyzed by software Multiplate RQ. Results: Extraction by the FFPE kit yielded high concentration of RNA in all cases. Purification values were 1.8 in average. Concentration values were significantly higher in FTC and FTA relative to G and N tissues, possibly due to high density of thyrocytes in the samples. Relative quantification of TFF3 mRNA expression level showed broad ranges both in FTC and FTA, while the analyses in G and N tissues indicated narrow ranges. Conclusion: FFPE tissues from thyroid follicular tumors can be used for measurement of unstable and low concentrated genetic substances such as TFF3 mRNA. Its diagnostic value yet remains to be determined.
基金supported by National Key R&D Program of China(2022YFB3104200)in part by National Natural Science Foundation of China(62202386)+2 种基金in part by Basic Research Programs of Taicang(TC2021JC31)in part by Fundamental Research Funds for the Central Universities(D5000210817)in part by Xi’an Unmanned System Security and Intelligent Communications ISTC Center,and in part by Special Funds for Central Universities Construction of World-Class Universities(Disciplines)and Special Development Guidance(0639022GH0202237 and 0639022SH0201237).
文摘Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value chain.Its highly heterogeneous network structure and diversified application requirements call for the applying of network slicing technology.Guaranteeing robust network slicing is essential for Industrial Internet,but it faces the challenge of complex slice topologies caused by the intricate interaction relationships among Network Functions(NFs)composing the slice.Existing works have not concerned the strengthening problem of industrial network slicing regarding its complex network properties.Towards this end,we aim to study this issue by intelligently selecting a subset of most valuable NFs with the minimum cost to satisfy the strengthening requirements.State-of-the-art AlphaGo series of algorithms and the advanced graph neural network technology are combined to build the solution.Simulation results demonstrate the superior performance of our scheme compared to the benchmark schemes.
基金supported by the National Natural Science Foundation of China(Grant No.61971057).
文摘In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.
基金The National Natural Science Foundation of China(No.60425206,60633010)the High Technology Research and Development Program of Jiangsu Province(No.BG2005032)
文摘This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are computed. Then, the forward and backward data slices for this attribute are generated by using the class as the slice scope and are combined to compute the corresponding class data slice. Finally, the class cohesion is computed based on all class data slices for the attributes. Compared to traditional cohesion metrics that use methods as the slice scope, the proposed metrics that use a single class as slice scope take into account the possible interactions between the methods. The experimental results show that class cohesion can be more accurately measured when using the class as the slice scope.
基金Supported by the Science and Technology Support Key Project of Jiangsu Province (DE2008365)~~
文摘Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.
文摘To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and internal node state, we find the deficiency of only using port information. Then, we define the gate level number computing method and the concept of slice, and propose using slice analysis to distill switching density as coefficients in a special circuit stage and participate in Bayesian inference with port information. Experiments show that this method can reduce the power-per-cycle estimation error by 21.9% and the root mean square error by 25.0% compared with the original model, and maintain a 700 ＋ speedup compared with the existing gate-level power analysis technique.
基金The National Outstanding Young Scientist Foundation by NSFC(No.60703086,60503020)
文摘A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a procedure with the given labels, and then captures the callees＇ influence on callers when analyzing call statements. Phase 2 captures the callees＇ dependence on callers by replacing all given labels appearing in the corresponding sets of formal parameters. By the introduction of given labels, this slice method can obtain similar summary information in system-dependence-graph（SDG）-based algorithms for addressing the calling-context problem. With the use of the slice monad transformer, this monadic slicing approach achieves a high level of modularity and flexibility. It shows that the monadic interprocedural algorithm has less complexity and it is not less precise than SDG algorithms.
