BACKGROUND:Measurement of cardiac troponin plays an important role in diagnosis of myocardial infarction.OBJECTIVE:To label the rabbit cardiac troponin C(cTnC) by a fluorescent probe 5-iodoaccetamidofluorescein(5-IAF),and to observe whether the 5-IAF can be used to study the interaction between cTnC and other contractile regulatory proteins.DESIGN,TIME AND SETTING:A randomized control experiment was performed at Department of Human Anatomy,Guangzhou Medical College,from January 2002 to December 2005.MATERIAL:Adult rabbits were provided by Experimental Animal Center of Guangzhou Medical College.METHODS:The rabbit cTnC DNA fragment was prepared with RT-PCR method.This gene fragment was cloned to pET expression vector by gene recombination technology.The site-directed mutagenesis were used to produce a mutant containing single cysteine at position 84 by replacing Cys35 with Ser,cTnC(C35S).The cTnC(C35S) was labeled by 5-IAF and 2-(4'-(iodoacetamido) anilino) naphthalene-6sulfonic acid(IAANS),Respectively.And then,the fluorescence emission(steady-state and time-resolved) was performed.MAIN OUTCOME MEASURE:The fluorescence properties of 5-IAF-labeled cTnC(C35S) and IAANS-labeled cTnC(C35S).RESULTS:The excitation of apo-cTnC(C35S)IAF was performed at 491 nm,and the emission peak was at 520 nm.Saturation of cTnC(C35S)IAF with Mg led to a 35% decrease in fluorescence intensity.Another 35% decrease with a 3 nm-blue shift was seen as the protein was saturated with Ca.The two-phase transitions of fluorescence emission from IAANS-labeled cTnC in response to Mg and Ca did not appear in fluorescence emission of 5-IAF-labeled cTnC.However,the Ca-induced conformational change in cTnC remained unchanged no matter which probe was used.Ca titration experiments showed that binding parameters derived from the fluorescence emission of the two probes were comparable.CONCLUSION:5-IAF is an appropriate probe that can be used to study the interaction between cardiac troponin C and other contractile regulatory proteins.

Objective To propose a classification method for ultrasound images of pedicle screw canals based on radiomics analysis,and to evaluate the integrity of the screw canal.Methods With thoracolumbar spine specimens from 4 fresh cadavers,50 pedicle screw canals were pre-established and ultrasound images of the canals were acquired.A total of 2 000 images(1 000 intact and 1 000 damaged canal samples)were selected.The dataset was randomly divided in a 4∶1 ratio using 5-fold cross-validation to form training and testing sets(consisting of 1 600 and 400 samples,respectively).Firstly,the optimal radius of the region of interest was identified using the Otsu's thresholding method,followed by feature extraction using pyradiomics.Principal component analysis and the least absolute shrinkage and selection operator algorithm were employed for dimensionality reduction and feature selection,respectively.Subsequently,3 machine learning models(support vector machine[SVM],logistic regression,and random forest)and 3 deep learning models(visual geometry group[VGG],ResNet,and Transformer)were used to classify the ultrasound images.The performance of each model was evaluated using accuracy.Results With a region of interest radius of 230 pixels,the SVM model achieved the highest classification accuracy of 96.25%.The accuracy of the VGG model was only 51.29%,while the accuracies of the logistic regression,random forest,ResNet,and Transformer models were 85.50%,80.75%,80.17%,and 75.18%,respectively.Conclusion For ultrasound images of pedicle screw canals,the machine learning model performs better than the deep learning model as a whole,and the SVM model has the best classification performance,which can be used to assist physicians in diagnosis.