BACKGROUND: Near-infrared spectroscopy(NIRS) non-invasively monitors muscle tissue oxygen saturation(St O2). It may provide a continuous noninvasive measurement to identify occult hypoperfusion, guide resuscitation, a...BACKGROUND: Near-infrared spectroscopy(NIRS) non-invasively monitors muscle tissue oxygen saturation(St O2). It may provide a continuous noninvasive measurement to identify occult hypoperfusion, guide resuscitation, and predict the development of multiple organ dysfunction(MOD) after severe trauma. We evaluated the correlation between initial St O2 and the development of MOD in multi-trauma patients.METHODS: Patients presenting to our urban, academic, Level I Trauma Center/Emergency Department and meeting standardized trauma-team activation criteria were enrolled in this prospective trial. NIRS monitoring was initiated immediately on arrival with collection of St O2 at the thenar eminence and continued up to 24 hours for those admitted to the Trauma Intensive Care Unit(TICU). Standardized resuscitation laboratory measures and clinical evaluation tools were collected. The primary outcome was the association between initial St O2 and the development of MOD within the f irst 24 hours based on a MOD score of 6 or greater. Descriptive statistical analyses were performed; numeric means, multivariate regression and rank sum comparisons were utilized. Clinicians were blinded from the StO 2 values.RESULTS: Over a 14 month period, 78 patients were enrolled. Mean age was 40.9 years(SD 18.2), 84.4% were male, 76.9% had a blunt trauma mechanism and mean injury severity score(ISS) was 18.5(SD 12.9). Of the 78 patients, 26(33.3%) developed MOD within the first 24 hours. The MOD patients had mean initial St O2 values of 53.3(SD 10.3), signifi cantly lower than those of nonMOD patients 61.1(SD 10.0); P=0.002. The mean ISS among MOD patients was 29.9(SD 11.5), significantly higher than that of non-MODS patients, 12.1(SD 9.1)(P<0.0001). The mean shock index(SI) among MOD patients was 0.92(SD 0.28), also signifi cantly higher than that of non-MODS patients, 0.73(SD 0.19)(P=0.0007). Lactate values were not signifi cantly different between groups.CONCLUSION: Non-invasive, continuous St O2 near-infrared spectroscopy values during initial trauma resuscitation correlate with the later development of multiple organ dysfunction in this patient population.展开更多
A transfer learning system was designed to predict Xylosma racemosum compression strength.Near-infrared(NIR)spectral data for Acer mono and its compression strength values were used to resolve the weak generalization ...A transfer learning system was designed to predict Xylosma racemosum compression strength.Near-infrared(NIR)spectral data for Acer mono and its compression strength values were used to resolve the weak generalization problem caused by using a X.racemosum dataset alone.Transfer component analysis and principal component analysis are domain adaption and feature extraction processes to enable the use of A.mono NIR spectral data to design the transfer learning system.A five-layer neural network relevant to the X.racemosum dataset,was fine-tuned using the A.mono dataset.There were 109 A.mono samples used as the source dataset and 79 X.racemosum samples as the target dataset.When the ratio of the training set to the test set was 1:9,the correlation coeffi cient was 0.88,and mean square error was 8.84.The results show that NIR spectral data of hardwood species are related.Predicting the mechanical strength of hardwood species using multi-species NIR spectral datasets will improve the generalization ability of the model and increase accuracy.展开更多
Nitrogen(N)monitoring is essential in nurseries to ensure the production of high-quality seedlings.Nearinfrared spectroscopy(NIRS)is an instantaneous,nondestructive method to monitor N.Spectral data such as NIRS can a...Nitrogen(N)monitoring is essential in nurseries to ensure the production of high-quality seedlings.Nearinfrared spectroscopy(NIRS)is an instantaneous,nondestructive method to monitor N.Spectral data such as NIRS can also provide the basis for developing a new vegetation spectral index(VSI).Here,we evaluated whether NIRS combined with statistical modeling can accurately detect early variations in N concentration in leaves of young plants of Annona emargiaata and developed a new VSI for this task.Plants were grown in a hydroponics system with 0,2.75,5.5or 11 mM N for 45 days.Then we measured gas exchange,chlorophylla fluorescence,and pigments in leaves;analyzed complete leaf nutrients,and recorded spectral data for leaves at 966 to 1685 nm using NIRS.With a statistical learning approach,the dimensionality of the spectral data was reduced,then models were generated using two classes(N deficiency,N)or four classes(0,2.75,5.5,11 mM N).The best combination of techniques for dimensionality reduction and classification,respectively,was stepwise regression(PROC STEPDISC)and linear discriminant function.It was possible to detect N deficiency in seedlings leaves with 100%precision,and the four N concentrations with93.55%accuracy before photosynthetic damage to the plant occurred.Thereby,NIRS combined with statistical modeling of multidimensional data is effective for detecting N variations in seedlings leaves of A.emarginata.展开更多
文摘BACKGROUND: Near-infrared spectroscopy(NIRS) non-invasively monitors muscle tissue oxygen saturation(St O2). It may provide a continuous noninvasive measurement to identify occult hypoperfusion, guide resuscitation, and predict the development of multiple organ dysfunction(MOD) after severe trauma. We evaluated the correlation between initial St O2 and the development of MOD in multi-trauma patients.METHODS: Patients presenting to our urban, academic, Level I Trauma Center/Emergency Department and meeting standardized trauma-team activation criteria were enrolled in this prospective trial. NIRS monitoring was initiated immediately on arrival with collection of St O2 at the thenar eminence and continued up to 24 hours for those admitted to the Trauma Intensive Care Unit(TICU). Standardized resuscitation laboratory measures and clinical evaluation tools were collected. The primary outcome was the association between initial St O2 and the development of MOD within the f irst 24 hours based on a MOD score of 6 or greater. Descriptive statistical analyses were performed; numeric means, multivariate regression and rank sum comparisons were utilized. Clinicians were blinded from the StO 2 values.RESULTS: Over a 14 month period, 78 patients were enrolled. Mean age was 40.9 years(SD 18.2), 84.4% were male, 76.9% had a blunt trauma mechanism and mean injury severity score(ISS) was 18.5(SD 12.9). Of the 78 patients, 26(33.3%) developed MOD within the first 24 hours. The MOD patients had mean initial St O2 values of 53.3(SD 10.3), signifi cantly lower than those of nonMOD patients 61.1(SD 10.0); P=0.002. The mean ISS among MOD patients was 29.9(SD 11.5), significantly higher than that of non-MODS patients, 12.1(SD 9.1)(P<0.0001). The mean shock index(SI) among MOD patients was 0.92(SD 0.28), also signifi cantly higher than that of non-MODS patients, 0.73(SD 0.19)(P=0.0007). Lactate values were not signifi cantly different between groups.CONCLUSION: Non-invasive, continuous St O2 near-infrared spectroscopy values during initial trauma resuscitation correlate with the later development of multiple organ dysfunction in this patient population.
基金fully funded by the Program of National Natural Science Foundation of China(CN)(31700643)Fundamental Research Funds for the Central Universities(2572015AB24)。
文摘A transfer learning system was designed to predict Xylosma racemosum compression strength.Near-infrared(NIR)spectral data for Acer mono and its compression strength values were used to resolve the weak generalization problem caused by using a X.racemosum dataset alone.Transfer component analysis and principal component analysis are domain adaption and feature extraction processes to enable the use of A.mono NIR spectral data to design the transfer learning system.A five-layer neural network relevant to the X.racemosum dataset,was fine-tuned using the A.mono dataset.There were 109 A.mono samples used as the source dataset and 79 X.racemosum samples as the target dataset.When the ratio of the training set to the test set was 1:9,the correlation coeffi cient was 0.88,and mean square error was 8.84.The results show that NIR spectral data of hardwood species are related.Predicting the mechanical strength of hardwood species using multi-species NIR spectral datasets will improve the generalization ability of the model and increase accuracy.
基金a scholarship from Capes(Coordena??o de Aperfei?oamento de Pessoal de Nível Superior)-Brazil(Award number:001)for the first author。
文摘Nitrogen(N)monitoring is essential in nurseries to ensure the production of high-quality seedlings.Nearinfrared spectroscopy(NIRS)is an instantaneous,nondestructive method to monitor N.Spectral data such as NIRS can also provide the basis for developing a new vegetation spectral index(VSI).Here,we evaluated whether NIRS combined with statistical modeling can accurately detect early variations in N concentration in leaves of young plants of Annona emargiaata and developed a new VSI for this task.Plants were grown in a hydroponics system with 0,2.75,5.5or 11 mM N for 45 days.Then we measured gas exchange,chlorophylla fluorescence,and pigments in leaves;analyzed complete leaf nutrients,and recorded spectral data for leaves at 966 to 1685 nm using NIRS.With a statistical learning approach,the dimensionality of the spectral data was reduced,then models were generated using two classes(N deficiency,N)or four classes(0,2.75,5.5,11 mM N).The best combination of techniques for dimensionality reduction and classification,respectively,was stepwise regression(PROC STEPDISC)and linear discriminant function.It was possible to detect N deficiency in seedlings leaves with 100%precision,and the four N concentrations with93.55%accuracy before photosynthetic damage to the plant occurred.Thereby,NIRS combined with statistical modeling of multidimensional data is effective for detecting N variations in seedlings leaves of A.emarginata.
