BACKGROUND Cerebral infarction,previously referred to as cerebral infarction or ischemic stroke,refers to the localized brain tissue experiencing ischemic necrosis or softening due to disorders in brain blood supply,i...BACKGROUND Cerebral infarction,previously referred to as cerebral infarction or ischemic stroke,refers to the localized brain tissue experiencing ischemic necrosis or softening due to disorders in brain blood supply,ischemia,and hypoxia.The precision rehabilitation nursing model for chronic disease management is a continuous,fixed,orderly,and efficient nursing model aimed at standardizing the clinical nursing process,reducing the wastage of medical resources,and improving the quality of medical services.AIM To analyze the value of a precise rehabilitation nursing model for chronic disease management in patients with cerebral infarction.METHODS Patients(n=124)admitted to our hospital with cerebral infarction between November 2019 and November 2021 were enrolled as the study subjects.The random number table method was used to divide them into a conventional nursing intervention group(n=61)and a model nursing intervention group(n=63).Changes in the nursing index for the two groups were compared after conventional nursing intervention and precise rehabilitation intervention nursing for chronic disease management.RESULTS Compared with the conventional intervention group,the model intervention group had a shorter time to clinical symptom relief(P<0.05),lower Hamilton Anxiety Scale and Hamilton Depression Scale scores,a lower incidence of total complications(P<0.05),a higher disease knowledge mastery rate,higher safety and quality,and a higher overall nursing satisfaction rate(P<0.05).CONCLUSION The precision rehabilitation nursing model for chronic disease management improves the clinical symptoms of patients with cerebral infarction,reducing the incidence of total complications and improving the clinical outcome of patients,and is worthy of application in clinical practice.展开更多
BACKGROUND Receptor interacting protein kinase 1(RIPK1)-mediated cell death,including apoptosis and necroptosis,belongs to programmed cell death.It has been reported that RIPK1-mediated necroptosis exists in lesions o...BACKGROUND Receptor interacting protein kinase 1(RIPK1)-mediated cell death,including apoptosis and necroptosis,belongs to programmed cell death.It has been reported that RIPK1-mediated necroptosis exists in lesions of cerebral hemorrhage(CH).Electroacupuncture,a treatment derived from traditional Chinese medicine,could improve neurological impairment in patients with brain injury.AIM To investigate the protective role of cross electro-nape acupuncture(CENA)in CH,and clarify the potential mechanism.METHODS CH rat models were established,and CENA was applied to the experimental rats.Neurological functions and encephaledema were then measured.Necrotic cells in the brain of rats with CH were evaluated by propidium iodide staining.Necroptosis was assessed by immunofluorescence.Activation of the necroptosisrelated pathway was detected by western blot.Extraction of brain tissue,cerebrospinal fluid and serum samples was conducted to measure the expression and secretion of inflammatory cytokines by quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay.RESULTS The necroptotic marker p-MLKL was detectable in the brains of rats with CH.Next,we found that CENA could ameliorate neurological functions in rat models of CH.Moreover,the upregulation of RIPK1-mediated necroptosis-related molecules in the brains of rats with CH were inhibited by CENA.Further investigation revealed that CENA partially blocked the interaction between RIPK1 and RIPK3.Finally,in vivo assays showed that CENA decreased the expression of the inflammatory cytokines tumor necrosis factor-α,interleukin-6 and interleukin-8 in CH rat models.CONCLUSION These findings revealed that CENA exerts a protective role in CH models by inhibiting RIPK1-mediated necroptosis.展开更多
To further develop the methods to remotely sense the biochemical content of plant canopies,we report the results of an experiment to estimate the concentrations of three biochemical variables of corn,i.e.,nitrogen(N),...To further develop the methods to remotely sense the biochemical content of plant canopies,we report the results of an experiment to estimate the concentrations of three biochemical variables of corn,i.e.,nitrogen(N),crude fat(EE) and crude fiber(CF) concentrations,by spectral reflectance and the first derivative reflectance at fresh leaf scale. The correlations between spectral reflectance and the first derivative transformation and three biochemical variables were analyzed,and a set of estimation models were established using curve-fitting analyses. Coefficient of determination(R2),root mean square error(RMSE) and relative error of prediction(REP) of estimation models were calculated for the model quality evaluations,and the possible opti-mum estimation models of three biochemical variables were proposed,with R2 being 0.891,0.698 and 0.480 for the estimation models of N,EE and CF concentrations,respectively. The results also indicate that using the first derivative reflectance was better than using raw spectral reflectance for all three biochemical variables estimation,and that the first derivative reflectances at 759 nm,1954 nm and 2370 nm were most suitable to develop the estimation models of N,EE and CF concentrations,respectively. In addition,the high correlation coefficients of the theoretical and the measured biochemical parameters were obtained,especially for nitrogen(r=0.948).展开更多
The accumulation of thermal time usually represents the local heat resources to drive crop growth.Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data colle...The accumulation of thermal time usually represents the local heat resources to drive crop growth.Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity.To solve the critical problems of estimating air temperature(T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days(GDDs) calculation from remotely sensed data,a novel spatio-temporal algorithm for T a estimation from Terra and Aqua moderate resolution imaging spectroradiometer(MODIS) data was proposed.This is a preliminary study to calculate heat accumulation,expressed in accumulative growing degree days(AGDDs) above 10 ℃,from reconstructed T a based on MODIS land surface temperature(LST) data.The verification results of maximum T a,minimum T a,GDD,and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels.Overall,MODIS-derived AGDD was slightly underestimated with almost 10% relative error.However,the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper.Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring,agricultural climatic regionalization,and agro-meteorological disaster detection at the regional scale.展开更多
The present study aims to identify the narrow spectral bands that are most suitable for characterizing rice biophysical parameters. The data used for this study come from ground-level hyperspectral reflectance measure...The present study aims to identify the narrow spectral bands that are most suitable for characterizing rice biophysical parameters. The data used for this study come from ground-level hyperspectral reflectance measurements for five rice species at three levels of nitrogen fertilization during the growing period. Reflectance was measured in discrete narrow bands between 350 and 2500 nm. Observed rice biophysical parameters included leaf area index (LAI), wet biomass and dry biomass. The stepwise regression method was applied to identify the optimal bands for rice biophysical parameter estimation. This research indicated that combinations of four narrow bands in stepwise regression models explained 69% to 83% variability for LAI, 56% to 73% for aboveground wet biomass and 70% to 83% for leaf wet biomass. An overwhelming proportion of rice information was in a particular portion of near infrared (NIR) (1 100-1 150 nm), red-edge (700-750 nm), and a longer portion of green (550-600 nm). These were followed by the moisture-sensitive NIR (950-1 000 nm), the intermediate portion of shortwave infrared (SWIR) (1 650-1 700 nm), and another portion of NIR (1 000-1 050 nm).展开更多
文摘BACKGROUND Cerebral infarction,previously referred to as cerebral infarction or ischemic stroke,refers to the localized brain tissue experiencing ischemic necrosis or softening due to disorders in brain blood supply,ischemia,and hypoxia.The precision rehabilitation nursing model for chronic disease management is a continuous,fixed,orderly,and efficient nursing model aimed at standardizing the clinical nursing process,reducing the wastage of medical resources,and improving the quality of medical services.AIM To analyze the value of a precise rehabilitation nursing model for chronic disease management in patients with cerebral infarction.METHODS Patients(n=124)admitted to our hospital with cerebral infarction between November 2019 and November 2021 were enrolled as the study subjects.The random number table method was used to divide them into a conventional nursing intervention group(n=61)and a model nursing intervention group(n=63).Changes in the nursing index for the two groups were compared after conventional nursing intervention and precise rehabilitation intervention nursing for chronic disease management.RESULTS Compared with the conventional intervention group,the model intervention group had a shorter time to clinical symptom relief(P<0.05),lower Hamilton Anxiety Scale and Hamilton Depression Scale scores,a lower incidence of total complications(P<0.05),a higher disease knowledge mastery rate,higher safety and quality,and a higher overall nursing satisfaction rate(P<0.05).CONCLUSION The precision rehabilitation nursing model for chronic disease management improves the clinical symptoms of patients with cerebral infarction,reducing the incidence of total complications and improving the clinical outcome of patients,and is worthy of application in clinical practice.
基金supported by the National Natural Science Foundation of China (No. 40571115)the Hi-Tech Research and Development Program (863) of China (No. 2006AA120101)the National Basic Research Program (973) of China (No. 2006BAD10A09)
基金Supported by State Administration of Traditional Chinese Medicine of Heilongjiang Province,No.ZHY16-027Harbin Municipal Science and Technology BureauYouth Reserve Talent Project,No.2017RAQXJ170
文摘BACKGROUND Receptor interacting protein kinase 1(RIPK1)-mediated cell death,including apoptosis and necroptosis,belongs to programmed cell death.It has been reported that RIPK1-mediated necroptosis exists in lesions of cerebral hemorrhage(CH).Electroacupuncture,a treatment derived from traditional Chinese medicine,could improve neurological impairment in patients with brain injury.AIM To investigate the protective role of cross electro-nape acupuncture(CENA)in CH,and clarify the potential mechanism.METHODS CH rat models were established,and CENA was applied to the experimental rats.Neurological functions and encephaledema were then measured.Necrotic cells in the brain of rats with CH were evaluated by propidium iodide staining.Necroptosis was assessed by immunofluorescence.Activation of the necroptosisrelated pathway was detected by western blot.Extraction of brain tissue,cerebrospinal fluid and serum samples was conducted to measure the expression and secretion of inflammatory cytokines by quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay.RESULTS The necroptotic marker p-MLKL was detectable in the brains of rats with CH.Next,we found that CENA could ameliorate neurological functions in rat models of CH.Moreover,the upregulation of RIPK1-mediated necroptosis-related molecules in the brains of rats with CH were inhibited by CENA.Further investigation revealed that CENA partially blocked the interaction between RIPK1 and RIPK3.Finally,in vivo assays showed that CENA decreased the expression of the inflammatory cytokines tumor necrosis factor-α,interleukin-6 and interleukin-8 in CH rat models.CONCLUSION These findings revealed that CENA exerts a protective role in CH models by inhibiting RIPK1-mediated necroptosis.
基金Project supported by the National Natural Science Foundation of China (No. 40271078)the Basic Research Program of Science and Technology Department of China (No. 2003DEA2C010-13)
文摘To further develop the methods to remotely sense the biochemical content of plant canopies,we report the results of an experiment to estimate the concentrations of three biochemical variables of corn,i.e.,nitrogen(N),crude fat(EE) and crude fiber(CF) concentrations,by spectral reflectance and the first derivative reflectance at fresh leaf scale. The correlations between spectral reflectance and the first derivative transformation and three biochemical variables were analyzed,and a set of estimation models were established using curve-fitting analyses. Coefficient of determination(R2),root mean square error(RMSE) and relative error of prediction(REP) of estimation models were calculated for the model quality evaluations,and the possible opti-mum estimation models of three biochemical variables were proposed,with R2 being 0.891,0.698 and 0.480 for the estimation models of N,EE and CF concentrations,respectively. The results also indicate that using the first derivative reflectance was better than using raw spectral reflectance for all three biochemical variables estimation,and that the first derivative reflectances at 759 nm,1954 nm and 2370 nm were most suitable to develop the estimation models of N,EE and CF concentrations,respectively. In addition,the high correlation coefficients of the theoretical and the measured biochemical parameters were obtained,especially for nitrogen(r=0.948).
基金Project supported by the National Key Technology R&D Program of China (No. 2012BAH29B02)the PhD Programs Foundation of Ministry of Education of China (No. 200100101110035)
文摘The accumulation of thermal time usually represents the local heat resources to drive crop growth.Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity.To solve the critical problems of estimating air temperature(T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days(GDDs) calculation from remotely sensed data,a novel spatio-temporal algorithm for T a estimation from Terra and Aqua moderate resolution imaging spectroradiometer(MODIS) data was proposed.This is a preliminary study to calculate heat accumulation,expressed in accumulative growing degree days(AGDDs) above 10 ℃,from reconstructed T a based on MODIS land surface temperature(LST) data.The verification results of maximum T a,minimum T a,GDD,and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels.Overall,MODIS-derived AGDD was slightly underestimated with almost 10% relative error.However,the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper.Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring,agricultural climatic regionalization,and agro-meteorological disaster detection at the regional scale.
基金the National Natural Science Foundation of China (40571115)the Hi-Tech Research and Development Program (863) of China(2006AA10Z203).
文摘The present study aims to identify the narrow spectral bands that are most suitable for characterizing rice biophysical parameters. The data used for this study come from ground-level hyperspectral reflectance measurements for five rice species at three levels of nitrogen fertilization during the growing period. Reflectance was measured in discrete narrow bands between 350 and 2500 nm. Observed rice biophysical parameters included leaf area index (LAI), wet biomass and dry biomass. The stepwise regression method was applied to identify the optimal bands for rice biophysical parameter estimation. This research indicated that combinations of four narrow bands in stepwise regression models explained 69% to 83% variability for LAI, 56% to 73% for aboveground wet biomass and 70% to 83% for leaf wet biomass. An overwhelming proportion of rice information was in a particular portion of near infrared (NIR) (1 100-1 150 nm), red-edge (700-750 nm), and a longer portion of green (550-600 nm). These were followed by the moisture-sensitive NIR (950-1 000 nm), the intermediate portion of shortwave infrared (SWIR) (1 650-1 700 nm), and another portion of NIR (1 000-1 050 nm).
