BACKGROUND Colorectal cancer(CRC)remains one of the leading causes of cancer-related morbidity and mortality worldwide.Growing evidence suggests that gut microbial dysbiosis plays a crucial role in tumorigenesis and c...BACKGROUND Colorectal cancer(CRC)remains one of the leading causes of cancer-related morbidity and mortality worldwide.Growing evidence suggests that gut microbial dysbiosis plays a crucial role in tumorigenesis and can influence therapeutic responses.AIM To explore the associations between serum S100A12 and soluble CD14(sCD14)levels and gut microbiota alterations in patients with CRC,and to assess the predictive utility of these biomarkers in forecasting chemotherapy response.METHODS A retrospective analysis was conducted on 104 patients diagnosed with advanced CRC(CRC group)and 104 age-matched and sex-matched healthy controls.Serum concentrations of S100A12 and sCD14 were measured using enzyme-linked immunosorbent assay.Fecal samples collected before chemotherapy were subjected to 16S rRNA sequencing to profile gut microbial composition.Pearson correlation analysis was used to evaluate the relationship between biomarker levels and microbial abundance.Receiver operating characteristic(ROC)curves were used to assess the predictive performance of S100A12 and sCD14 for chemotherapy response.RESULTS CRC patients exhibited significantly higher serum levels of S100A12 and sCD14 compared to healthy individuals(P<0.05).Patients with moderate to severe gut dysbiosis showed the highest elevations of these biomarkers(P<0.05).Elevated levels of S100A12 and sCD14 were positively correlated with Fusobacterium nucleatum and Prevotella abundance,and negatively correlated with Faecalibacterium prausnitzii and Akkermansia muciniphila(P<0.05).Both biomarkers significantly decreased following chemotherapy(P<0.05).Non-responders to chemotherapy had higher pre-treatment levels of S100A12 and sCD14 compared to responders(P<0.05).Combined ROC analysis showed improved diagnostic accuracy compared to either marker alone.CONCLUSION Serum S100A12 and sCD14 levels are closely associated with gut microbiota imbalance and chemotherapy response in CRC patients.These markers may serve as promising predictive indicators for treatment efficacy and offer potential value in individualized treatment strategies.展开更多
Stroke is a common cardiovascular and cerebrovascular disease with high morbidity,high mortality and high disability rate.In this paper,a stroke risk prediction and evaluation model based on support vector machine,ran...Stroke is a common cardiovascular and cerebrovascular disease with high morbidity,high mortality and high disability rate.In this paper,a stroke risk prediction and evaluation model based on support vector machine,random forest,BP neural network and genetic algorithm optimization neural network algorithm was established by using a raw dataset including 10 characteristic variables such as gender,age,hypertension,heart disease,and 1 stroke target variable.The experimental results show that the average blood glucose level,body mass index,hypertension and other variables have a great impact on the risk of stroke,and the neural network algorithm optimized by the genetic algorithm performs slightly better than the other three models.展开更多
The scientific idea of earthquake prediction in China is introduced in this paper. The various problems on evaluation of earthquake prediction ability are analyzed. The practical effect of prediction on annual seismic...The scientific idea of earthquake prediction in China is introduced in this paper. The various problems on evaluation of earthquake prediction ability are analyzed. The practical effect of prediction on annual seismic risk areas in 1990~2000 in China is discussed based on R-value evaluation method, and the ability of present earthquake prediction in China is reviewed.展开更多
The evaluation of the implementation effect of the power substation project can find out the problems of the project more comprehensively,which has important practical significance for the further development of the p...The evaluation of the implementation effect of the power substation project can find out the problems of the project more comprehensively,which has important practical significance for the further development of the power substation project.To ensure accuracy and real-time evaluation,this paper proposes a novel hybrid intelligent evaluation and prediction model based on improved TOPSIS and Long Short-Term Memory(LSTM)optimized by a Sperm Whale Algorithm(SWA).Firstly,under the background of considering the development of new energy,the influencing factors of power substation project implementation effect are analyzed from three aspects of technology,economy and society.Moreover,an evaluation model based on improved TOPSIS is constructed.Then,an intelligent prediction model based on SWA optimized LSTM is designed.Finally,the scientificity and accuracy of the proposed model are verified by empirical analysis,and the important factors affecting the implementation effect of power substation projects are pointed out.展开更多
Using RS and GIS means, this article analyzes the general geological characteristics and the structural belt distribution features in Wenchuan County, Sichuan province, P.R. China as well as the characteristics of the...Using RS and GIS means, this article analyzes the general geological characteristics and the structural belt distribution features in Wenchuan County, Sichuan province, P.R. China as well as the characteristics of the large-scale landslides, mud-rock flows, earthquake lakes, etc., after the earthquake on May 12, 2008. Based on the above work, comprehensive indoor and outdoor research is launched on disaster distribution characteristics and their relationship with earthquakes, terrains, strata, lithology, and structures. Weights of evidence method is utilized to quantitatively analyze and evaluate the spatial distribution of secondary geological disasters after the earthquake occurred. 3 remedying grades for secondary geological disasters are derived from the results of the weights of Evidence, followed by suggestions given to remedy earthquake secondary disasters.展开更多
In silico prediction of potential synthetic targets is the prerequisite for function-led discovery of new zeolites. Millions of hypothetical zeolitic structures have been predicted via various computational methods, b...In silico prediction of potential synthetic targets is the prerequisite for function-led discovery of new zeolites. Millions of hypothetical zeolitic structures have been predicted via various computational methods, but most of them are experimentally inaccessible under conventional synthetic conditions.Screening out unfeasible structures is crucial for the selection of synthetic targets with desired functions.The local interatomic distance（LID） criteria are a set of structure rules strictly obeyed by all existing zeolite framework types. Using these criteria, many unfeasible hypothetical structures have been detected. However, to calculate their LIDs, all hypothetical structures need to be fully optimized without symmetry constraints. When evaluating a large number of hypothetical structures, such calculations may become too computationally expensive due to the forbiddingly high degree of freedom. Here, we propose calculating LIDs among structures optimized with symmetry constraints and using them as new structure evaluation criteria, i.e., the LIDsymcriteria, to screen out unfeasible hypothetical structures. We find that the LIDsymcriteria can detect unfeasible structures as many as the original non-symmetric LID criteria do, yet require at least one order of magnitude less computation at the initial geometry optimization stage.展开更多
On the basis of the assumption that ω^2 model accords with source displacement spectra of moderate-small shocks, we calculate the apparent stress values of 1 020 moderate-small shocks recorded by the Digital Seismic ...On the basis of the assumption that ω^2 model accords with source displacement spectra of moderate-small shocks, we calculate the apparent stress values of 1 020 moderate-small shocks recorded by the Digital Seismic Network of Yunnan Province by using the low-frequency fiat level and corner frequencies. The results show that the apparent stress is of good significance in earthquake prediction. The moderate-small shock with apparent stress larger than 0.9 MPa can be used as a referential index to predict moderate-strong earthquakes in Yunnan area. And its relevant predictability evaluation （R value） has a high confidence level.展开更多
A large number of residential buildings are still distributed above the elevation of the backwater line in a reservoir area of Baoshan City. The stability of the reservoir bank is a problem after the reservoir is impo...A large number of residential buildings are still distributed above the elevation of the backwater line in a reservoir area of Baoshan City. The stability of the reservoir bank is a problem after the reservoir is impounded. Through comprehensive engineering geological surveying and mapping, drilling and GIS results, the stability of bank collapse is analyzed and predicted, the engineering geological evaluation is carried out, and the treatment measures and suggestions are put forward.展开更多
In the light of the study of domestic and foreign ur-ban ecosystem,this article puts forward a set of ideological systemsfor the forecast,evaluation and tactic,and conducts initial primaryexploration of its forecast a...In the light of the study of domestic and foreign ur-ban ecosystem,this article puts forward a set of ideological systemsfor the forecast,evaluation and tactic,and conducts initial primaryexploration of its forecast and evaluation methods.展开更多
Bridge maintenance is a long-term process that is prone to accidents.Identifying and reducing hidden dangers is crucial in decreasing the occurrence of such accidents.This study proposes a two-stage risk evaluation mo...Bridge maintenance is a long-term process that is prone to accidents.Identifying and reducing hidden dangers is crucial in decreasing the occurrence of such accidents.This study proposes a two-stage risk evaluation model based on the likelihood exposure conse-quence(LEC)method,which includes an occurrence stage and a development stage.The model utilizes hidden danger data accumulated over a long period to reflect the current maintenance stage’s risk level.Additionally,a risk prediction model based on the Bayesian network is established to better identify hidden dangers that have a significant impact on construction risk levels(CRLs).The models are validated using 50 weeks of hid-den danger data obtained from a real-world bridge maintenance project.The results show that certain hidden dangers have high risk levels when the CRL is high,and small changes in the risk level of certain hidden dangers can have a significant impact on the CRL.This study’s models can aid in the development of more targeted HD prevention measures.展开更多
文摘BACKGROUND Colorectal cancer(CRC)remains one of the leading causes of cancer-related morbidity and mortality worldwide.Growing evidence suggests that gut microbial dysbiosis plays a crucial role in tumorigenesis and can influence therapeutic responses.AIM To explore the associations between serum S100A12 and soluble CD14(sCD14)levels and gut microbiota alterations in patients with CRC,and to assess the predictive utility of these biomarkers in forecasting chemotherapy response.METHODS A retrospective analysis was conducted on 104 patients diagnosed with advanced CRC(CRC group)and 104 age-matched and sex-matched healthy controls.Serum concentrations of S100A12 and sCD14 were measured using enzyme-linked immunosorbent assay.Fecal samples collected before chemotherapy were subjected to 16S rRNA sequencing to profile gut microbial composition.Pearson correlation analysis was used to evaluate the relationship between biomarker levels and microbial abundance.Receiver operating characteristic(ROC)curves were used to assess the predictive performance of S100A12 and sCD14 for chemotherapy response.RESULTS CRC patients exhibited significantly higher serum levels of S100A12 and sCD14 compared to healthy individuals(P<0.05).Patients with moderate to severe gut dysbiosis showed the highest elevations of these biomarkers(P<0.05).Elevated levels of S100A12 and sCD14 were positively correlated with Fusobacterium nucleatum and Prevotella abundance,and negatively correlated with Faecalibacterium prausnitzii and Akkermansia muciniphila(P<0.05).Both biomarkers significantly decreased following chemotherapy(P<0.05).Non-responders to chemotherapy had higher pre-treatment levels of S100A12 and sCD14 compared to responders(P<0.05).Combined ROC analysis showed improved diagnostic accuracy compared to either marker alone.CONCLUSION Serum S100A12 and sCD14 levels are closely associated with gut microbiota imbalance and chemotherapy response in CRC patients.These markers may serve as promising predictive indicators for treatment efficacy and offer potential value in individualized treatment strategies.
基金2024 University-level Training Program for College Students'Innovation Entrepreneurship(No.202410060069)。
文摘Stroke is a common cardiovascular and cerebrovascular disease with high morbidity,high mortality and high disability rate.In this paper,a stroke risk prediction and evaluation model based on support vector machine,random forest,BP neural network and genetic algorithm optimization neural network algorithm was established by using a raw dataset including 10 characteristic variables such as gender,age,hypertension,heart disease,and 1 stroke target variable.The experimental results show that the average blood glucose level,body mass index,hypertension and other variables have a great impact on the risk of stroke,and the neural network algorithm optimized by the genetic algorithm performs slightly better than the other three models.
基金The Development and Planning Project of National Important Base Research (G19980407).
文摘The scientific idea of earthquake prediction in China is introduced in this paper. The various problems on evaluation of earthquake prediction ability are analyzed. The practical effect of prediction on annual seismic risk areas in 1990~2000 in China is discussed based on R-value evaluation method, and the ability of present earthquake prediction in China is reviewed.
文摘The evaluation of the implementation effect of the power substation project can find out the problems of the project more comprehensively,which has important practical significance for the further development of the power substation project.To ensure accuracy and real-time evaluation,this paper proposes a novel hybrid intelligent evaluation and prediction model based on improved TOPSIS and Long Short-Term Memory(LSTM)optimized by a Sperm Whale Algorithm(SWA).Firstly,under the background of considering the development of new energy,the influencing factors of power substation project implementation effect are analyzed from three aspects of technology,economy and society.Moreover,an evaluation model based on improved TOPSIS is constructed.Then,an intelligent prediction model based on SWA optimized LSTM is designed.Finally,the scientificity and accuracy of the proposed model are verified by empirical analysis,and the important factors affecting the implementation effect of power substation projects are pointed out.
基金funded by the National Key Technology R and D Program in the 11th Five year Plan of China(No.2006BAB01A08)
文摘Using RS and GIS means, this article analyzes the general geological characteristics and the structural belt distribution features in Wenchuan County, Sichuan province, P.R. China as well as the characteristics of the large-scale landslides, mud-rock flows, earthquake lakes, etc., after the earthquake on May 12, 2008. Based on the above work, comprehensive indoor and outdoor research is launched on disaster distribution characteristics and their relationship with earthquakes, terrains, strata, lithology, and structures. Weights of evidence method is utilized to quantitatively analyze and evaluate the spatial distribution of secondary geological disasters after the earthquake occurred. 3 remedying grades for secondary geological disasters are derived from the results of the weights of Evidence, followed by suggestions given to remedy earthquake secondary disasters.
基金supported by the National Natural Science Foundation of China(Nos.21622102,21621001 and 21320102001)the National Key Research and Development Program of China(No.2016YFB0701100)
文摘In silico prediction of potential synthetic targets is the prerequisite for function-led discovery of new zeolites. Millions of hypothetical zeolitic structures have been predicted via various computational methods, but most of them are experimentally inaccessible under conventional synthetic conditions.Screening out unfeasible structures is crucial for the selection of synthetic targets with desired functions.The local interatomic distance（LID） criteria are a set of structure rules strictly obeyed by all existing zeolite framework types. Using these criteria, many unfeasible hypothetical structures have been detected. However, to calculate their LIDs, all hypothetical structures need to be fully optimized without symmetry constraints. When evaluating a large number of hypothetical structures, such calculations may become too computationally expensive due to the forbiddingly high degree of freedom. Here, we propose calculating LIDs among structures optimized with symmetry constraints and using them as new structure evaluation criteria, i.e., the LIDsymcriteria, to screen out unfeasible hypothetical structures. We find that the LIDsymcriteria can detect unfeasible structures as many as the original non-symmetric LID criteria do, yet require at least one order of magnitude less computation at the initial geometry optimization stage.
基金Project of National Natural Science Foundation (40574016)Joint Seismological Science Foundation of China (104047)Science and Technological Planning Item of Social Development of Jiangsu Province (BS2005069)
文摘On the basis of the assumption that ω^2 model accords with source displacement spectra of moderate-small shocks, we calculate the apparent stress values of 1 020 moderate-small shocks recorded by the Digital Seismic Network of Yunnan Province by using the low-frequency fiat level and corner frequencies. The results show that the apparent stress is of good significance in earthquake prediction. The moderate-small shock with apparent stress larger than 0.9 MPa can be used as a referential index to predict moderate-strong earthquakes in Yunnan area. And its relevant predictability evaluation （R value） has a high confidence level.
文摘A large number of residential buildings are still distributed above the elevation of the backwater line in a reservoir area of Baoshan City. The stability of the reservoir bank is a problem after the reservoir is impounded. Through comprehensive engineering geological surveying and mapping, drilling and GIS results, the stability of bank collapse is analyzed and predicted, the engineering geological evaluation is carried out, and the treatment measures and suggestions are put forward.
文摘In the light of the study of domestic and foreign ur-ban ecosystem,this article puts forward a set of ideological systemsfor the forecast,evaluation and tactic,and conducts initial primaryexploration of its forecast and evaluation methods.
基金supported by the Shanghai Municipal Science and Technology Major Project of China(No.2021SHZDZX0100)the Shanghai Municipal Commission of Science and Technology Project of China(No.19511132101)the Fundamental Research Funds for the Central Universities of China.
文摘Bridge maintenance is a long-term process that is prone to accidents.Identifying and reducing hidden dangers is crucial in decreasing the occurrence of such accidents.This study proposes a two-stage risk evaluation model based on the likelihood exposure conse-quence(LEC)method,which includes an occurrence stage and a development stage.The model utilizes hidden danger data accumulated over a long period to reflect the current maintenance stage’s risk level.Additionally,a risk prediction model based on the Bayesian network is established to better identify hidden dangers that have a significant impact on construction risk levels(CRLs).The models are validated using 50 weeks of hid-den danger data obtained from a real-world bridge maintenance project.The results show that certain hidden dangers have high risk levels when the CRL is high,and small changes in the risk level of certain hidden dangers can have a significant impact on the CRL.This study’s models can aid in the development of more targeted HD prevention measures.
