Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods / 法医学杂志

OBJECTIVES@#To estimate postmortem interval (PMI) by analyzing the protein changes in skeletal muscle tissues with the protein chip technology combined with multivariate analysis methods.@*METHODS@#Rats were sacrificed for cervical dislocation and placed at 16 ℃. Water-soluble proteins in skeletal muscles were extracted at 10 time points (0 d, 1 d, 2 d, 3 d, 4 d, 5 d, 6 d, 7 d, 8 d and 9 d) after death. Protein expression profile data with relative molecular mass of 14 000-230 000 were obtained. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) were used for data analysis. Fisher discriminant model and back propagation (BP) neural network model were constructed to classify and preliminarily estimate the PMI. In addition, the protein expression profiles data of human skeletal muscles at different time points after death were collected, and the relationship between them and PMI was analyzed by heat map and cluster analysis.@*RESULTS@#The protein peak of rat skeletal muscle changed with PMI. The result of PCA combined with OPLS discriminant analysis showed statistical significance in groups with different time points (P<0.05) except 6 d, 7 d and 8 d after death. By Fisher discriminant analysis, the accuracy of internal cross-validation was 71.4% and the accuracy of external validation was 66.7%. The BP neural network model classification and preliminary estimation results showed the accuracy of internal cross-validation was 98.2%, and the accuracy of external validation was 95.8%. There was a significant difference in protein expression between 4 d and 25 h after death by the cluster analysis of the human skeletal muscle samples.@*CONCLUSIONS@#The protein chip technology can quickly, accurately and repeatedly obtain water-soluble protein expression profiles in rats' and human skeletal muscles with the relative molecular mass of 14 000-230 000 at different time points postmortem. The establishment of multiple PMI estimation models based on multivariate analysis can provide a new idea and method for PMI estimation.

Heart sound classification based on improved mel frequency cepstrum coefficient and integrated decision network method / 生物医学工程学杂志

Heart sound analysis is significant for early diagnosis of congenital heart disease. A novel method of heart sound classification was proposed in this paper, in which the traditional mel frequency cepstral coefficient (MFCC) method was improved by using the Fisher discriminant half raised-sine function (F-HRSF) and an integrated decision network was used as classifier. It does not rely on segmentation of the cardiac cycle. Firstly, the heart sound signals were framed and windowed. Then, the features of heart sounds were extracted by using improved MFCC, in which the F-HRSF was used to weight sub-band components of MFCC according to the Fisher discriminant ratio of each sub-band component and the raised half sine function. Three classification networks, convolutional neural network (CNN), long and short-term memory network (LSTM), and gated recurrent unit (GRU) were combined as integrated decision network. Finally, the two-category classification results were obtained through the majority voting algorithm. An accuracy of 92.15%, sensitivity of 91.43%, specificity of 92.83%, corrected accuracy of 92.01%, and F score of 92.13% were achieved using the novel signal processing techniques. It shows that the algorithm has great potential in early diagnosis of congenital heart disease.

Value of discriminant analysis for screening of clonorchiasis sinensis / 中国血吸虫病防治杂志

Objective To build a discriminant function of clonorchiasis sinensis using stepwise discriminant analysis, so as to investigate the feasibility of discriminant analysis for clonorchiasis sinensis screening. Methods Ten villages in Mulan County of Harbin City were sampled as the study sites using a cluster random sampling method. The fecal samples were collected from the permanent residents in the study sites and detected for Clonorchis sinensis eggs using the modified Kato-Katz smear technique. A questionnaire of clonorchiasis sinensis was designed. All data were entered into Epidata 3.1, and a discriminant analysis was performed using the software SPSS version 15.0. Variable were screened using the stepwise discriminant analysis, and the discriminant function was built using the Fisher’s discriminant analysis method. The effectiveness of the discriminant function for clonorchiasis sinensis screening was evaluated by comparison with the modified Kato-Katz smear method. Results Eight variables with statistical significance were included to build the discriminant function, including chronic cholecystitis, cholangitis, gender, eating raw fish, abdominal distension, ethnicity, abdominal pain and age, and the correction rate of the discriminant function was 88.75% to identify clonorchiasis sinensis. Conclusions The discriminant function of clonorchiasis sinensis can be rapidly and simply built based on the strong data processing and analysis capability of the SPSS software, which is rapid to screen clonorchiasis sinensis in Harbin City. Such a function has a high discriminant analysis capability, and provides insights into the establishment of rapid screening of clonorchiasis sinensis in other endemic areas.

Prediction of pathological grading of Henoch-Schönlein purpura nephritis in children based on Fisher stepwise discriminant analysis / 中华实用儿科临床杂志

Objective@#To establish the pathological grades of Henoch-Schönlein purpura nephritis(HSPN) in children with diagnostic prediction models by stepwise Fisher discriminant in children.@*Methods@#Based on the investigation of 28 clinical indicators from 144 cases with HSPN came from Children′s Hospital of Chongqing Medical University, the sensitive indicators were found and stepwise Fisher discriminant model was established and its accuracy in predicting the pathological classification of HSPN was tested.@*Results@#There were 5 laboratory indicators and clinical manifestations with different pathological grades of HSPN.In children with pathological grade Ⅱ, Ⅲ and Ⅳ, 5 indicators were screened (P<0.05) and stepwise Fisher discriminant models were established.And the correct rate of comprehensive diagnosis was (61.371±8.740)% in 100 random sampling diagnostic simulations; in children with pathological grade Ⅲa and Ⅲb, 5 indicators were also screened (P<0.05) and stepwise Fisher discriminant models were established.And the correct rate of comprehensive diagnosis was (68.015±5.736)% in 100 random sampling diagnostic simulations.@*Conclusions@#The stepwise Fisher discriminant models established in this research have a better diagnostic accuracy in forecasting for pathological grade of HSPN, and have a certain guiding value on early treatment and prognosis evaluation of children with newly diagnosed HSPN.

Prediction of pathological grading of Henoch＿Sch?nlein purpura nephritis in children based on Fisher step-Wise discriminant analysis / 中华实用儿科临床杂志

Objective To establish the pathological grades of Henoch-Sch?nlein purpura nephriti(s HSPN) in children with diagnostic prediction models by stepwise Fisher discriminant in children. Methods Based on the in-vestigation of 28 clinical indicators from 144 cases with HSPN came from Children′s Hospital of Chongqing Medical University,the sensitive indicators were found and stepwise Fisher discriminant model was established and its accuracy in predicting the pathological classification of HSPN was tested. Results There were 5 laboratory indicators and clini-cal manifestations with different pathological grades of HSPN. In children with pathological gradeⅡ,ⅢandⅣ,5 indi-cators were screened(P<0. 05)and stepwise Fisher discriminant models were established. And the correct rate of comprehensive diagnosis was(61. 371 ± 8. 740)% in 100 random sampling diagnostic simulations;in children with pathological gradeⅢa and Ⅲb,5 indicators were also screened(P<0. 05)and stepwise Fisher discriminant models were established. And the correct rate of comprehensive diagnosis was(68. 015 ± 5. 736)% in 100 random sampling diagnostic simulations. Conclusions The stepwise Fisher discriminant models established in this research have a better diagnostic accuracy in forecasting for pathological grade of HSPN,and have a certain guiding value on early treatment and prognosis evaluation of children with newly diagnosed HSPN.

Single trial classification of motor imagery electroencephalogram based on Fisher criterion / 生物医学工程学杂志

In order to realize brain-computer interface (BCI), optimal features of single trail motor imagery electroencephalogram (EEG) were extracted and classified. Mu rhythm of EEG was obtained by preprocessing, and the features were optimized by spatial filtering, which are estimated from a set of data by method of common spatial pattern. Classification decision can be made by Fisher criterion, and classification performance can be evaluated by cross validation and receiver operating characteristic (ROC) curve. Optimal feature dimension determination projected by spatial filter was discussed deeply in cross-validation way. The experimental results show that the high discriminate accuracy can be guaranteed, meanwhile the program running speed is improved. Motor imagery intention classification based on optimized EEG feature provides difference of states and simplifies the recognition processing, which offers a new method for the research of intention recognition.

The diagnostic value of four serum tumor markers for gastric cancer based on pattern recognition techniques* / 重庆医学

Objective To evaluate the diagnostic value of serum tumors CA72-4,CA242,CA19-9 and carcino-embryonic antigen(CEA)in patients with gastric cancer based on pattern recognition techniques.Methods Data of serum concentrations of CA72-4,CA242,CA19-9 and CEA of 212 patients with gastric cancer,116 patients with benign gastric disease and 117 healthy subjects were retrospectively analyzed;and the diagnostic performance of each tumor marker,four tumor markers based principle component analysis(PCA),decision tree,PCA-decision tree and the fisher discriminant analysis models were established.Results CA242 had the best diagnostic effect on gastric cancer,and the area under the ROC curve(AUC)was 0.841(95％CI:0.804-0.877).PCA model showed that the serum levels of four tumor markers in patients with gastric cancer were significantly different from those in benign and healthy patients,and obvious metabolic disorders of serum with four tumor markers were found among the patients with gastric cancer.The diagnosis accuracy of the decision tree,PCA-decision tree and the Fisher discriminant analysis models for gastric cancer patients was 58.6％,65.5％and 58.6％respectively,and for non-gastric cancer patients(benign gastric diseases and healthy controls)was 94.7％,99.4％and 97.6％.And the prediction accuracy of the decision tree,PCA-decision tree and the fisher discriminant analysis models for gastric cancer patients was 65.7％,77.6％and 73.1％,and for non-gastric cancer patients was 87.5％,96.9％and 96.9％,respectively.Conclusion The PCA-decision tree model of serum CA72-4,CA242,CA19-9 and CEA might be helpful for the diagnosis and prediction of patients with gastric cancer.

Soil changes in a subtropical seasonal forest chronosequences in the south of Brazil / Mudanças no solo em cronossequências da floresta estacional subtropical no sul do Brasil

ABSTRACT:The abandonment of field crops and the vegetation recovery in exhausted soils have been a recently studied subject as a way to assess the forest role on the soil recovering. The aim of this study was assess changes in the chemical(14 variables) and grain size (sand, silt, and clay) soil features in four forests chronosequences grew over abandoned field crops in the edge of the Brazilian Southern plateau, Rio Grande do Sul State. There were selected 25 forests aging from 5 to >100 years old in areas of slopes and highlands where samples of Leptosols and Regosols were collected at 15cm in depth. The Fisher's Discriminant Analysis showed that some variable groups of soils can distinguish significantly the soils under different forest ages. Six chemical features of soil fertility were the best monitoring indicators of areas impacted by agriculture. Changes in soil did not occur in a linear way towards time.

RESUMO:O abandono de terras agrícolas e a recuperação da vegetação e dos solos exauridos têm sido um tema recentemente investigado como forma de avaliar o papel da floresta na recuperação do solo. O objetivo deste estudo foi verificar as mudanças nas propriedades químicas (14 variáveis) e granulométricos (areia, silte e argila) em quatro cronossequências florestais originadas após o cultivo agrícola no rebordo do Planalto Meridional, sul do Brasil. Foram selecionadas 25 florestas com idades variando de 5 a >100 anos, localizadas em áreas de encostas e patamares onde amostras de Neossolos Litólicos e Regolíticos Eutróficos foram coletados a 15cm de profundidade. A análise discriminante de Fisher demonstrou que alguns grupos de variáveis dos solos podem distinguir significativamente os solos sob as diferentes idades florestais. Seis atributos químicos relacionados com a fertilidade do solo poderiam ser considerados os melhores indicadores de monitoramento das áreas impactadas pela agricultura. As mudanças no solo não ocorreram de forma linear ao longo do tempo.

EVALUACIÓN ASISTIDA POR COMPUTADOR DE LA VIABILIDAD ESPERMÁTICA EN HUMANOS / COMPUTER-ASSISTED EVALUATION OF SPERM VITALITY IN HUMANS

En la actualidad una de cada seis parejas presenta problemas de fertilidad y en el 50% de los casos se debe al factor masculino. A la fecha, el análisis seminal es la única prueba que permite determinar el potencial fértil de un hombre. Entre otros parámetros, la viabilidad espermática es evaluada manualmente presentando una variabilidad debido a la subjetividad producida por la fatiga ocular del experto. El propósito de este trabajo fue desarrollar y validar experimentalmente una herramienta computacional flexible, programable y modular basada en el procesamiento digital de imágenes, para la identificación y clasificación de espermatozoides humanos en una muestra seminal. Las regiones fueron extraídas mediante la técnica de análisis discriminante de Fisher y su clasificación se realizó a través del análisis de agrupamiento y particularmente la técnica de K-medias. Los resultados obtenidos muestran 87,9% de exactitud en la identificación de los espermatozoides vivos y los espermatozoides muertos, 93,4% de efectividad para detectar espermatozoides vivos y 76% de efectividad para detectar los espermatozoides muertos, a partir de un conjunto de 110 imágenes obtenidas de 14 individuos, en comparación con el análisis manual acorde a los procedimientos establecidos por la Organización Mundial de la Salud. La herramienta computacional mostrada aquí contribuye al análisis objetivo de espermatozoides humanos, convirtiéndose en una alternativa a los costosos sistemas comerciales de análisis seminal asistido por computador.

Currently one out of six couples present fertility problems, with 50% of the cases being due to the male. Until now, seminal fluid analysis is the only test that evaluates a male's fertility potential. Among other parameters, sperm viability is manually assessed, which contributes to high data variability as a result of expert subjectivity and eye-fatigue. The purpose of the present study was to develop and experimentally validate a flexible, programmable and modular-based computational tool for digital image processing, identification and classification of human sperm in a semen sample. The regions were extracted using Fisher discriminant analysis and classification methods by cluster analysis and particularly the K-means technique. The results show 87.9% accuracy in identifying living and dead sperm, 93.4% effectiveness in detecting live sperm and 76% effectiveness in detecting dead sperm, from a set of 110 images obtained from 14 individuals, compared with manual analysis according to the procedures established by the World Health Organization. This computational tool contributes to the objective analysis of human sperm, becoming an alternative to expensive commercial systems for computer-assisted semen analysis.

Fisher discriminant analysis of ultrasonography index in diagnosing characters of ovarian neoplasms / 中国医学影像技术

Objective To construct Fisher discrminant functions with index of ultrasonography. Methods A total of 48 non-neoplastic ovarian cysts, 137 benign and 120 malignant ovarian tumors were enrolled in this study. Taking ultrasonographic parameters and Doppler blood flow signals as differential diagnosis variable, a diagnosis model was developed using stepwise discriminant analysis. Then a projection and territorial map were drew and the diagnostic ability of the model was verified with substitution method and jackknife. Results ①Univariate analysis indicated that ovarian cysts volume, end-diastolic blood flow velocity (V_(ED)), mean blood flow velocity (V_m), resistance index (RI), pulse index (PI), physical property, echo, shape, boundary, ascites and blood flow signal have statistical difference among the three kinds of ovarian cysts. ②Stepwise discriminant analysis showed that volume, resistance index, physical property, shape and boundary are the independent prognostic variables. The two Fisher discriminant functions were as following: Function 1=0.002volume-4.793 RI+0.468physical property+0.862shape+0.901boundary-4.076, Function 2=0.005volume-1.480 RI+0.851physical property-0.291shape+0.443boundary+0.524. ③The projective positions of three kinds of ovarian cysts at 2D coordinates were clear. ④The sensibility and specificity of mode for diagnosis non-neoplastic ovarian cysts, benign and malignant ovarian tumors was 91.67%, 88.32% and 93.33% with substitution method, and was 91.67%, 86.13% and 93.33% with jackknife method. Conclusion Cysts volume, RI, physical property, shape and boundary are the significant differential prognostic variables. Fisher discriminant analysis can provide a reliable prognostic model for ovarian cysts.

The value of Fisher discriminant analysis in the diagnosis of ectopic pregnancy / 中国综合临床

Objective To discuss the value of Fisher discriminant analysis of serum progesterone and the growing rate of β-human chorionic gonadotropin in the prediction of early ectopic pregnancy. Methods 66 patients with ectopic pregnancy (11 cases were successfully treated expectantly and 55 cases were treated surgically including 40 cases of rupture of fallopian tube and 15 cases of tubal abortion) and 55 patients with intrauterine pregnancy and 50 patients with threatened abortion were chosen. Serum progesterone,β-HCG,48 hβ-HCG and the 48 h growing rate of β-HCG in each group were measured and a Fisher discriminant analysis was used. Results The serum progester-one was (30.27± 18.20) nmol/L in ectopic pregnancy group,( 108.44±23.27 ) nmol/L in intrauterine pregnancy group and (91.68±34.90) nmol/L in threatened abortion group. The first β-HCG was ( 3767.63 ± 3530.38 ) U/L in ectopie pregnancy group,(29 028.65 ± 10 874.01 )U/L in intrauterine pregnancy group and (13 457.47±16 367.65)U/L in threatened abortion group. The second β-HCG was (4349.24±3536.22)U/L in ectopic pregnancygroup,(56 139.46 ± 23 296.87 ) U/L in intrauterine pregnancy group and (23 270.63 ± 23 811.68 ) U/L in threat-ened abortion group. The growing rate of β-HCG ( β-HCG/the first serum β-HCG) was 1.29 ± 0.28 in ectopic preg-nancy group,1.93 ± 0.36 in intrauterine pregnancy group and 1.97±0.28 in threatened abortion group. There was significant difference in serum progesterone,the first β-HCG and the second β-HCG as well as the growing rate of β-HCG among the groups(P<0.05 or <0.01). Fisher discriminant analysis of combing progesterone and the growing rate of β-HCG were connected with diagnosis of ectopic pregnancy,however,the only one serum β-HCG was not con-nected with diagnosis of ectopic pregnancy. 98.5% of ectopic pregnancy,65.6% of intrauterine pregnancy and 64.0% of threatened abortion were correctly classified in the Fisher discfiminant analysis,with overall correct rate of 77.8%. Conclusion Fisher discriminant analysis of combing progesterone and the growing rate of β-HCG can bet-ter predict the early ectopic pregnancy.

HPLC Fingerprint of Rhizoma Belamcandae / 中国药房

OBJECTIVE: To establish the HPLC fingerprint of Rhizoma Belamcandae. METHODS: The fingerprint of Rhizoma Belamcandae was established by HPLC on Lichrospher C18(250 mm?4.6mm,5um).The mobile phase consisted of 1% acetic acid acetonitrile -1% acetic acid solution at a flow rate of 1.0 mL?min-1. The column temperature was 30 ℃.Cluster analysis was conducted with peak area as quantitative characteristic value. Canonical discriminant function and Fisher's discriminant function of the HPLC finger print of Rhizoma Belamcanda were established using stepwise classification scheme. RESULTS: The fingerprint of Rhizoma Belamcandae has been established. The discrimination and classification results by the two kinds of functions were totally consistent with each other, with corresponding rate of 100%. CONCLUSION: The two discriminant functions are of theoretical and practical value for they provide an accurate and rapid tool for the identification of the unknown samples as well as a new model for the quality control of Chinese medicines.