The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly re...The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.展开更多
A new method to detect multiple outliers in multivariate data is proposed. It is a combination of minimum subsets, resampling and self-organizing map (SOM) algorithm introduced by Kohonen,which provides a robust way w...A new method to detect multiple outliers in multivariate data is proposed. It is a combination of minimum subsets, resampling and self-organizing map (SOM) algorithm introduced by Kohonen,which provides a robust way with neural network. In this method, the number and organization of the neurons are selected by the characteristics of the spectra, e.g., the spectra data are often changed linearly with the concentration of the components and are often measured repeatedly, etc. So the spatial distribution of the neurons can be arranged by this characteristic. With this method, all the outliers in the spectra can be detected, which cannot be solved by the traditional method, and the speed of computation is higher than that of the traditional neural network method. The results of the simulation and the experiment show that this method is simple, effective, intuitionistic and all the outliers in the spectra can be detected in a short time. It is useful when associated with the regression model in the near infra-red research.展开更多
Alzheimers disease(AD)is a chronic neurodegenerative disease.The symptoms include memoryand spatial learning dificulties,language disorders,and loss of motivation,which get worse overtime,eventually ending in death.No...Alzheimers disease(AD)is a chronic neurodegenerative disease.The symptoms include memoryand spatial learning dificulties,language disorders,and loss of motivation,which get worse overtime,eventually ending in death.No ffective treatments are available for AD,currently.Currenttreatments only attenuate symptoms temporarily and are associated with severe side ffects.Nearinfra-red(NIR)light has been studied for a long time.We investigated the effect of NIR on ADusing a transgenic mouse model,which was obtained by co-injecting two vectors carrying ADmutations in amyloid precursor protein(APP)and presenilin-i(PSEN1)into C57BL/6J mice.The irradiation equipment consisted of an accommodating box and an LED array.The wave-length of NIR light emitted from LED was between 1040 nm and 1090 nm.The power densitydelivered at the level of the mice was approximately 15 mW/cm^(2),Firstly,we treated the micewith NIR for 40 days,Then,the irradiation was suspended for 28 days.Finally,another 15 daystreatment was brought to mice.We conducted Morris water maze and immunofluorescenceanalysis to evaluate the effects of treatment.Immunofuorescence analysis was based on mea-suring the quantity of plaques in mouse brain slices,Our results show that NIR light improvesmemory and spatial learning ability and reduces plaques moderately.NIR light represents apotential treatment for AD.展开更多
Introduction: Infra-red (IR) thermometry is a safe and valid method to determine internal and surface temperature in human subjects. Under conditions of brain damage (head injury or stroke) knowledge of changes in the...Introduction: Infra-red (IR) thermometry is a safe and valid method to determine internal and surface temperature in human subjects. Under conditions of brain damage (head injury or stroke) knowledge of changes in the temperature of intracranial tissue is justified because of the vulnerability of neurons to accelerated damage at temperatures at the upper end of the febrile range. Aim: To determine the temperature at the inner canthus (IC) of the eye as a potential surrogate for brain temperature. Methods: Invasive monitoring of deep brain structures, lateral ventricle and deep white matter. IR temperature readings obtained at right and left IC. Results: ?Strong correlations were evident between R and L IC and brain. Close, as well as poor, agreement between?? sites was shown in some patients and at some times. For right hemispheric lesions four had a better correlation between TbrV and TRIC when compared to TLIC.? When the correlation between TbrV and TLIC was better compared to TbrV and TRIC, four had a predominant right hemispheric lesion. Conclusions: Improved techniques for IR thermal imaging accuracy at the bedside has the potential to improve temperature measurement agreement. The predominant lesion side may have a bearing on maximum ipsilateral IC temperature Further studies are ongoing in this pilot study population.展开更多
Cases are presented to reveal how modern computerised infra-red thermal imaging has the potential to assist in early breast cancer detection. The history of thermography and some recent controversies surrounding mammo...Cases are presented to reveal how modern computerised infra-red thermal imaging has the potential to assist in early breast cancer detection. The history of thermography and some recent controversies surrounding mammography are discussed. Examples of thermal imaging combined with naturopathic interventions are described. Since 2002, more than 8000 women in New Zealand have chosen to include thermal imaging as a part of their breast health management. Breast thermal imaging combined with relevant health advice, resulted in a perceived worthwhile benefit to patients in managing overall health.展开更多
Mechanoluminescent(ML)materials,which have the ability to convert mechanical energy to optical energy,have found huge promising applications such as in stress imaging and anti-counterfeiting.However,the main reported ...Mechanoluminescent(ML)materials,which have the ability to convert mechanical energy to optical energy,have found huge promising applications such as in stress imaging and anti-counterfeiting.However,the main reported ML phosphors are based on trap-related ones,thus hindering the practical applications due to the requirement of complex light pre-irradiation process.Here,a self-recoverable near infrared(NIR)ML material of Lali-xO:xCr^(3+)(x=0.2%,0.4%,0.6%,0.8%,1.0%,and 1.2%)has been developed.Based on the preheating method and corresponding ML performance analysis,the influences of residual carriers are eliminated and the detailed dynamic luminescence process analysis is realized.Systematic experiments are conducted to reveal the origin of the ML emissions,demonstrating that ML is dictated more by the non-centrosymmetric piezoelectric crystal characteristic.In general,this work has provided significant references for exploring more efficient NIR ML materials,which may provide potential applications in anti-counterfeiting and bio-stress sensing.展开更多
Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models...Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R<sup>2</sup> 0.85) is better than the whole seed (0.33 R<sup>2</sup> 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R<sup>2</sup>_whole seed = 0.78, R<sup>2</sup>_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.展开更多
基金supported by the National Natural Science Foundation of China(32160782 and 32060737).
文摘The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.
文摘A new method to detect multiple outliers in multivariate data is proposed. It is a combination of minimum subsets, resampling and self-organizing map (SOM) algorithm introduced by Kohonen,which provides a robust way with neural network. In this method, the number and organization of the neurons are selected by the characteristics of the spectra, e.g., the spectra data are often changed linearly with the concentration of the components and are often measured repeatedly, etc. So the spatial distribution of the neurons can be arranged by this characteristic. With this method, all the outliers in the spectra can be detected, which cannot be solved by the traditional method, and the speed of computation is higher than that of the traditional neural network method. The results of the simulation and the experiment show that this method is simple, effective, intuitionistic and all the outliers in the spectra can be detected in a short time. It is useful when associated with the regression model in the near infra-red research.
基金supported by grants awarded by the National Major Scientic Research Program of China(Grant No.2011CB910404)the National Nature Science Foundation of China(Grant No.61227017)+1 种基金the State Key Basic Research Development Program of China(2012CB518103)National Outstanding Young Scientist Award of China(61425006).
文摘Alzheimers disease(AD)is a chronic neurodegenerative disease.The symptoms include memoryand spatial learning dificulties,language disorders,and loss of motivation,which get worse overtime,eventually ending in death.No ffective treatments are available for AD,currently.Currenttreatments only attenuate symptoms temporarily and are associated with severe side ffects.Nearinfra-red(NIR)light has been studied for a long time.We investigated the effect of NIR on ADusing a transgenic mouse model,which was obtained by co-injecting two vectors carrying ADmutations in amyloid precursor protein(APP)and presenilin-i(PSEN1)into C57BL/6J mice.The irradiation equipment consisted of an accommodating box and an LED array.The wave-length of NIR light emitted from LED was between 1040 nm and 1090 nm.The power densitydelivered at the level of the mice was approximately 15 mW/cm^(2),Firstly,we treated the micewith NIR for 40 days,Then,the irradiation was suspended for 28 days.Finally,another 15 daystreatment was brought to mice.We conducted Morris water maze and immunofluorescenceanalysis to evaluate the effects of treatment.Immunofuorescence analysis was based on mea-suring the quantity of plaques in mouse brain slices,Our results show that NIR light improvesmemory and spatial learning ability and reduces plaques moderately.NIR light represents apotential treatment for AD.
文摘Introduction: Infra-red (IR) thermometry is a safe and valid method to determine internal and surface temperature in human subjects. Under conditions of brain damage (head injury or stroke) knowledge of changes in the temperature of intracranial tissue is justified because of the vulnerability of neurons to accelerated damage at temperatures at the upper end of the febrile range. Aim: To determine the temperature at the inner canthus (IC) of the eye as a potential surrogate for brain temperature. Methods: Invasive monitoring of deep brain structures, lateral ventricle and deep white matter. IR temperature readings obtained at right and left IC. Results: ?Strong correlations were evident between R and L IC and brain. Close, as well as poor, agreement between?? sites was shown in some patients and at some times. For right hemispheric lesions four had a better correlation between TbrV and TRIC when compared to TLIC.? When the correlation between TbrV and TLIC was better compared to TbrV and TRIC, four had a predominant right hemispheric lesion. Conclusions: Improved techniques for IR thermal imaging accuracy at the bedside has the potential to improve temperature measurement agreement. The predominant lesion side may have a bearing on maximum ipsilateral IC temperature Further studies are ongoing in this pilot study population.
文摘Cases are presented to reveal how modern computerised infra-red thermal imaging has the potential to assist in early breast cancer detection. The history of thermography and some recent controversies surrounding mammography are discussed. Examples of thermal imaging combined with naturopathic interventions are described. Since 2002, more than 8000 women in New Zealand have chosen to include thermal imaging as a part of their breast health management. Breast thermal imaging combined with relevant health advice, resulted in a perceived worthwhile benefit to patients in managing overall health.
基金We gratefully acknowledge the financial support from the National Natural Science Foundation of China(No.52202003)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011893)+1 种基金State Key Laboratory of Powder Metallurgy,Central South University,Changsha,China(No.Sklpm-KF-27)Guangzhou Basic and Applied Basic Research Foundation(No.SL2022A04J00746)。
文摘Mechanoluminescent(ML)materials,which have the ability to convert mechanical energy to optical energy,have found huge promising applications such as in stress imaging and anti-counterfeiting.However,the main reported ML phosphors are based on trap-related ones,thus hindering the practical applications due to the requirement of complex light pre-irradiation process.Here,a self-recoverable near infrared(NIR)ML material of Lali-xO:xCr^(3+)(x=0.2%,0.4%,0.6%,0.8%,1.0%,and 1.2%)has been developed.Based on the preheating method and corresponding ML performance analysis,the influences of residual carriers are eliminated and the detailed dynamic luminescence process analysis is realized.Systematic experiments are conducted to reveal the origin of the ML emissions,demonstrating that ML is dictated more by the non-centrosymmetric piezoelectric crystal characteristic.In general,this work has provided significant references for exploring more efficient NIR ML materials,which may provide potential applications in anti-counterfeiting and bio-stress sensing.
文摘Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R<sup>2</sup> 0.85) is better than the whole seed (0.33 R<sup>2</sup> 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R<sup>2</sup>_whole seed = 0.78, R<sup>2</sup>_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.
