Supervised dimension reduction for optical vapor sensing

Detecting and identifying vapors at low concentrations is important for air quality assessment, food quality assurance, and homeland security. Optical vapor sensing using photonic crystals has shown promise for rapid vapor detection and identification. Despite the recent advances of optical sensing using photonic crystals, the data analysis method commonly used in this field has been limited to an unsupervised method called principal component analysis (PCA). In this study, we applied four different supervised dimension reduction methods on differential reflectance spectra data from optical vapor sensing experiments. We found that two of the supervised methods, linear discriminant analysis and least-squares regression PCA, yielded better interclass separation, vapor identification and improved classification accuracy compared to PCA.

Comparison between principal component analysis, linear discriminant analysis and least-squares regression principal component analysis for dimension reduction of spectral reactance data in optical vapor sensing.     

The stability of uric acid in ammonium hydroxide

We examined the stability of uric acid in dilute aqueous ammonium hydroxide solution by mass spectrometry. Uric acid decomposes in ammonium hydroxide even as dilute as 15 mmol/L when the mole ratio of ammonium hydroxide to uric acid is 50:1. There are at least four products of the decomposition, two of which have been identified as allantoin and urea. The slope of the decomposition curve indicates that uric acid is destroyed at an initial rate of 2-3% per hour. In ammonium hydroxide at a concentration of 1 mmol/L and a mole ratio of ammonium hydroxide to uric acid of less than or equal to 3.4, uric acid is not detectably decomposed. Evidently, any method for determination of uric acid that involves treating the analyte with ammonium hydroxide before analysis may destroy it. Therefore, a published method described as being "definitive" for uric acid (J Clin Chem Clin Biochem 1985; 23:129-35) could produce incorrect results because it involves storing the uric acid in 15 mmol/L ammonium hydroxide at a mole ratio of ammonium hydroxide to uric acid of greater than 120:1.     

Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements

Principal component analysis (PCA) is often used to reduce the dimension of data before applying more sophisticated data analysis methods such as non-linear classification algorithms or independent component analysis. This practice is based on selecting components corresponding to the largest eigenvalues. If the ultimate goal is separation of data in two groups, then these set of components need not have the most discriminatory power. We measured the distance between two such populations using Mahalanobis distance and chose the eigenvectors to maximize it, a modified PCA method, which we call the discriminant PCA (DPCA). DPCA was applied to diffusion tensor-based fractional anisotropy images to distinguish age-matched schizophrenia subjects from healthy controls. The performance of the proposed method was evaluated by the one-leave-out method. We show that for this fractional anisotropy data set, the classification error with 60 components was close to the minimum error and that the Mahalanobis distance was twice as large with DPCA, than with PCA. Finally, by masking the discriminant function with the white matter tracts of the Johns Hopkins University atlas, we identified left superior longitudinal fasciculus as the tract which gave the least classification error. In addition, with six optimally chosen tracts the classification error was zero.     

Critical comparison of diffuse reflectance spectroscopy and colorimetry as dermatological diagnostic tools for acanthosis nigricans: a chemometric approach

Quantification of skin changes due to acanthosis nigricans (AN), a disorder common among insulin-resistant diabetic and obese individuals, was investigated using two optical techniques: diffuse reflectance spectroscopy (DRS) and colorimetry. Measurements were obtained from AN lesions on the neck and two control sites of eight AN patients. A principal component/discriminant function analysis successfully differentiated between AN lesion and normal skin with 87.7% sensitivity and 94.8% specificity in DRS measurements and 97.2% sensitivity and 96.4% specificity in colorimetry measurements.     

Changes in frontal plane dynamics and the loading response phase of the gait cycle are characteristic of severe knee osteoarthritis application of a multidimensional analysis technique

BACKGROUND: Osteoarthritis of the knee is related to many correlated mechanical factors that can be measured with gait analysis. Gait analysis results in large data sets. The analysis of these data is difficult due to the correlated, multidimensional nature of the measures. METHODS: A multidimensional model that uses two multivariate statistical techniques, principal component analysis and discriminant analysis, was used to discriminate between the gait patterns of the normal subject group and the osteoarthritis subject group. Nine time varying gait measures and eight discrete measures were included in the analysis. All interrelationships between and within the measures were retained in the analysis. FINDINGS: The multidimensional analysis technique successfully separated the gait patterns of normal and knee osteoarthritis subjects with a misclassification error rate of <6%. The most discriminatory feature described a static and dynamic alignment factor. The second most discriminatory feature described a gait pattern change during the loading response phase of the gait cycle. INTERPRETATION: The interrelationships between gait measures and between the time instants of the gait cycle can provide insight into the mechanical mechanisms of pathologies such as knee osteoarthritis. These results suggest that changes in frontal plane loading and alignment and the loading response phase of the gait cycle are characteristic of severe knee osteoarthritis gait patterns. Subsequent investigations earlier in the disease process may suggest the importance of these factors to the progression of knee osteoarthritis.     

Optical spectral reflectance of human articular cartilage - relationships with tissue structure, composition and mechanical properties

The information from spectral reflectance of articular cartilage has been related to the integrity of the tissue. This study explores more in detail the interrelations between the cartilage composition, structure and mechanical properties, and optical spectral reflectance. Using human osteochondral samples the reflectance spectral images of articular cartilage were captured and analyzed by using CIELAB color space as well as principal component analysis. With both analysis methods statistically significant correlations were observed between the reflectance and histological integrity, as assessed by Mankin scoring, tissue proteoglycan content and dynamic modulus. In thick human cartilage, the reflectance was found to be independent of the cartilage thickness, suggesting negligible influence of the underlying subchondral bone. Based on the present results diagnostically relevant information on cartilage quality can be extracted using optical spectral reflectance measurements. These measurements could be feasible during arthroscopic surgery when more in-depth information of the properties of articular cartilage is needed.     

Are the classical markers sufficient to describe uremic solute accumulation in dialyzed patients? Hippurates reconsidered

Interdependencies of accumulated solutes, analyzed by liquid chromatography in dialyzed and non-dialyzed patients, were studied by multivariate statistical analysis. In principal component analysis, three principal components (PC1-PC3) were retained from the data on 22 accumulated compounds in dialyzed patients, whereas only one principal component was retained from analogous data of a non-dialyzed patient group. PC1 in the dialyzed patient group comprises concentrations of hippuric acid, p-hydroxyhippuric acid, tryptophan, and five unidentified fluorescent solutes in serum. Concentrations of the classical markers urea, uric acid, creatinine, and phosphate were closely related to PC2 in these patients. Indoleacetic acid and two unidentified fluorescent compounds constitute PC3. The compounds associated with the groups found by principal component analysis may be characterized by chemical structure and by the mechanism of their excretion via the remaining nephrons of dialyzed patients. In the non-dialyzed group, most of the solutes could be described by a single PC. This PC and PC1 from the dialyzed group correlated significantly with residual renal function, and with total ultraviolet absorbance and total fluorescence emission. The data suggest that it is of value to introduce a marker of uremic solute retention in addition to urea, to account for renal-function-related "organic-acid-like" compounds that are excreted by renal tubular secretion in dialyzed patients. The hippurates may serve this purpose.     

基于液相色谱-质谱技术的多发性骨髓瘤患者血清代谢组学分析

目的:应用代谢组学方法观察多发性骨髓瘤(MM)患者的血清代谢产物变化规律,探索MM诊断、预后判断及病情进展的潜在生物标志物.方法:收集MM患者26例和健康人50例的血清标本.将液相色谱-质谱检测所得的数据输入SIMCA-14.0软件,进行多变量统计分析.用主成分分析法、偏最小二乘法判别分析和正交偏最小二乘法判别分析模式...     

Multidimensional structures of comprehensive accessibility of community support for people with mental disorders in Japan: a nationwide investigation

The purpose of this study was to define the concept of comprehensive accessibility of community support for people with mental disorders and to clarify the multidimensional structures of comprehensive accessibility. We developed a self-administered questionnaire consisting of 47 items. A complete list of the municipalities in Japan was prepared, and the questionnaire was mailed to 3310 municipalities. Principal component analyses were applied to valid data in order to analyse the index and multidimensional structures of comprehensive accessibility. As a result, 14 principal components of community support for people with mental disorders were extracted. These principal components were interpreted as the scales for the evaluation of comprehensive accessibility. The two first principal component scores were interpreted as the index indicating the level of comprehensive accessibility. The other 12 principal components were interpreted as the scales constituting the multidimensional space of comprehensive accessibility.     

新疆地区不同民族人群心房颤动与血清尿酸水平的相关性研究

目的探讨新疆地区维吾尔族、汉族心房颤动(AF)患者心房颤动的发生与血清尿酸水平的关系。方法以维吾尔族、汉族心房颤动患者各100例作为病例组,以维吾尔族、汉族非心房颤动患者各100例作为对照组,记录各组患者的年龄、性别、尿酸水平,用药情况等。采用Logistic回归分析心房颤动发生的危险因素。结果维吾尔族、汉族病例组与对照组比较,年龄、低密度脂蛋白、总胆固醇、尿酸水平差异有统计学意义(P0.05),心房颤动组年龄、低密度脂蛋白、总胆固醇和尿酸均显著高于非心房颤动组。多因素Logistic回归分析结果发现,年龄(OR=1.114,95%CI=1.080~1.149,P0.01)、总胆固醇(OR=1.902,95%CI=1.434~2.522,P0.01)和尿酸(OR=1.023,95%CI=1.017~1.029,P0.01)是心房颤动的独立危险因素。结论在新疆地区维吾尔族和汉族人群中,血清尿酸可能是心房颤动的危险因素。     

Discriminant analysis of functional connectivity patterns on Grassmann manifold

The functional brain networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive function and brain disorders. Rather than analyzing each network encoded by a spatial independent component separately, we propose a novel algorithm for discriminant analysis of functional brain networks jointly at an individual level. The functional brain networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based Riemannian distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional brain networks that are informative for schizophrenia diagnosis.     

山东沿海女性居民血尿酸影响因素及与代谢综合征防治切点的研究

背景:沿海居民血尿酸的影响因素如何?血尿酸与代谢综合征防治切点如何?目前尚无中国人资料。目的:明确山东沿海20岁以上女性血尿酸与代谢综合征的关系。设计:随机、分层、整群抽样调查。单位:青岛大学医学院附属医院内分泌科。对象:于2004-05/10对山东沿海五市(青岛、日照、烟台、威海和东营)常住女性居民进行调查。年龄20～80岁,常住5年及5年以上,以家庭为单位的自然人群。方法:采用入户调查和现场调查相结合的方式,第1天填写调查问卷,第2天清晨采空腹血做血尿酸检测,对尿酸值高于正常的第3天复查并进行痛风和高尿酸血症的防治教育。主要观察指标:①一般情况调查:包括健康状况、饮食、体力活动、劳动强度和经济情况。②营养调查:分食物摄入频率调查和膳食调查两部分。③测量身高、体质量、腰围、臀围、血压、体质量指数。④测定空腹血糖、血尿酸、总胆固醇、三酰甘油、高密度脂蛋白胆固醇、尿素氮、肌酐含量。结果:①随着血尿酸浓度的升高,收缩压、舒张压、脉压、体质量指数、腰围、腰臀比、尿素氮、肌酐、三酰甘油、总胆固醇也逐渐升高,血尿酸280～319μmol/L、血尿酸320～349μmol/L、血尿酸>350μmol/L(高尿酸血症)三组上述指标均明显高于血尿酸<280μmol/L组(P<0.05～0.01),而高密度脂蛋白胆固醇随血尿酸浓度的升高而降低(P均<0.01)。②高血压、脂代谢紊乱、超重和肥胖、糖代谢紊乱及代谢综合征的患病率随着尿酸值的升高而升高;与血尿酸<280μmol/L组比较,血尿酸280～319μmol/L、血尿酸320～349μmol/L和高尿酸血症组发生代谢综合征的OR值分别为2.29(95%CI:1.81～2.89),4.15(95%CI:3.10～5.55),4.96(95%CI:3.85～6.39)。③非条件Logistic多元逐步回归分析显示年龄、高血压、食贝类量、尿素氮、肌酐、三酰甘油、腰臀比、轻体力活动为女性高尿酸血症独立的危险因子,高密度脂蛋白胆固醇为保护因素。结论:山东沿海女性代谢综合征患病率随血尿酸值的升高而升高,血尿酸超过280μmol/L应作为代谢综合征防治切点。控制代谢综合征,减少贝类等含高嘌呤海产品的摄入是预防高尿酸血症的发生的措施之一。临床医师应警惕高尿酸血症致病作用。     

男性2型糖尿病血尿酸与颈动脉粥样硬化的相关性研究

目的探讨男性2型糖尿病(T2DM)血尿酸(SUA)水平与颈动脉粥样硬化(CAS)的关系.方法选取男性2型糖尿病患者80例,分为有颈动脉粥样硬化组(G1组)49例、无颈动脉粥样硬化组(G2组)31例,另选35例健康者为正常对照组(G3组).检测入选者的空腹血糖(FPG)、餐后2h血糖(2hPG)、总胆固醇(TC)、血清甘油三酯(TG)、高密度脂蛋白胆固醇(HDL-C)、低密度脂蛋白胆固醇(LDL-C)、SUA、尿微量白蛋白(uA1b).结果 G1组、G2组间FPG、2hPG、TC、HDL-C差异无统计学意义.三组间TC差异无统计学意义(P>0.05).三组间FPG、2hPG、TG、HDL-C、LDL-C、uA1b、SUA,差异有统计学意义(P<0.01或P<0.05).G1组SUA水平明显高于G2组和G3组(P<0.01),G2组高于G3组(P<0.05).对CAS危险因素的Logistic回归分析,先后入选的变量是SUA、HDL-C和uA1b.其中SUA的影响因子最为突出.结论男性2型糖尿病患者伴发CAS时SUA水平升高,颈动脉粥样硬化危险因素Logistic回归分析显示,SUA与CAS相关,SUA可能是男性T2DM及CAS形成的危险因素.     

Clustering of cardiovascular risk factors associated with the insulin resistance syndrome: assessment by principal component analysis in young hyperandrogenic women

OBJECTIVE: Hyperinsulinemia is often associated with several metabolic abnormalities and increased blood pressure, which are risk factors for cardiovascular disease. It has been hypothesized that insulin resistance may underlie all these features. However, recent data suggest that some links between insulin resistance and these alterations may be indirect. The aim of our study was to further investigate this issue in a sample of young hyperandrogenic women, who often show insulin resistance and other metabolic abnormalities typical of the insulin resistance syndrome. RESEARCH DESIGN AND METHODS: We tested the hypothesis of a single factor underlying these features by principal component analysis, which should recognize one component if a single mechanism explains this association. The analysis was carried out in a sample of 255 young nondiabetic hyperandrogenic women. Variables selected for this analysis included the basic features of the insulin resistance syndrome and some endocrine parameters related to hyperandrogenism. RESULTS: Principal component analysis identified four separate factors, explaining 64.5% of the total variance in the data: the first included fasting and postchallenge insulin levels, BMI, triglycerides, HDL cholesterol, and uric acid; the second, BMI, blood pressure, and serum free testosterone; the third, fasting plasma glucose, postchallenge glucose and insulin levels, serum triglycerides, and free testosterone; and the fourth, postchallenge plasma insulin, serum free testosterone, and gonadotropin-releasing hormone agonist-stimulated 17-hydroxyprogesterone. CONCLUSIONS: These results support the hypothesis of multiple determinants in the clustering of abnormalities in the so-called insulin resistance syndrome.     

The effects of diphenylhydantoin on the relationship between high-density lipoprotein cholesterol and several biochemical assays

Correlations have been calculated between high-density lipoprotein cholesterol and total plasma cholesterol, albumin, gamma-glutamyl transpeptidase, aspartate aminotransferase, alkaline phosphatase, triglyceride, urea, creatinine and uric acid for diphenylhydantoin (DPH) users and for subjects attending a multiphasic health screening centre. For women DPH users, high-density lipoprotein levels correlated significantly with gamma glutamyl transpeptidase, cholesterol and alkaline phosphatase. These correlations were significantly different from those found for male DPH users and from subjects attending the health screening centre. In male DPH users, high-density lipoprotein cholesterol correlates negatively with urea and uric acid levels, a relationship which is found neither in women DPH users nor in the health screening centre population.     

Measurement of total serum protein by near-infrared reflectance spectroscopy

This study describes the measurement of total protein in serum by near-infrared reflectance spectroscopy. With an algorithm, generated by the calibration procedure, the protein content of serum samples was calculated from absorbance data at various wavelengths in the near-infrared. A good correlation (r = 0.993) was found between near-infrared reflectance spectroscopy measurement of serum protein and analysis by the biuret reaction.     

甲状腺功能正常的非糖尿病人群甲状腺激素水平与胰岛素抵抗的关系

目的 对甲状腺功能正常的非糖尿病人群中甲状腺激素水平与胰岛素抵抗关系进行横断面研究。方法 依托2011年由中华医学会发起的REACTION研究,选取大连地区符合标准的研究对象共5 428例。以促甲状腺激素（TSH）2.5 mU/L为分界,分为低TSH组及高TSH组,测量两组身高、体重、血压,进行口服葡萄糖耐量(OGTT),检验血脂、血肌酐（SCr）、血尿酸（UA）、血糖、糖化血红蛋白（HbA1c）、空腹胰岛素（FINS）、甲状腺功能,稳态模型评估胰岛素抵抗指数（HOMA IR）。研究甲状腺激素水平与胰岛素抵抗的相关性。结果 与低TSH组比较,高TSH组SCr、UA及游离甲状腺素（FT4）水平降低,低密度脂蛋白胆固醇（LDL C）、胆固醇（TC）、HbA1c、FINS及HOMA IR增高（P＜0.05）。TSH 、游离三碘甲状腺原氨酸（FT3）与HOMA IR呈正相关（r=0.145、0.040,P＜0.05）。而FT4水平与HOMA IR指数呈负相关（r=-0.071,P=0.000）。回归分析显示性别、舒张压（DBP）、BMI、高密度脂蛋白胆固醇（HDL C）、LDL C、TC、HbA1c、UA、TSH、FT4为影响HOMA IR的独立危险因素（P＜0.05）。其中HDL C及FT4为保护性因素（P＜0.05）。结论 在正常范围内的TSH水平与非糖尿病人群的胰岛素抵抗呈正相关,FT4与胰岛素抵抗呈负相关,且TSH、FT4为影响胰岛素抵抗的独立危险因素。     

Various metabolic effects in total parenteral feeding using a carbohydrate combination and amino-acid solution in the pre- and postoperative phase]

Ten metabolically healthy patients who had undergone gastric resection were fed intravenously from the preoperative to the 5th postoperative day. After the 24-hour preoperative infusion period the concentration of cholesterol, free fatty acids and alkaline phosphatase dropped significantly. So did the concentration of uric acid. During the postoperative period cholesterol and uric acid continued to fall. The concentration of free fatty acids remained low all the postoperative days. From the second postoperative day on the triglycerides rose continuously. Serum glutamic oxalacetic transaminase and serum lactic dehydrogenase reached their highest level on the first postoperative day. On the same day the alkaline phosphatase dropped to the lowest level. Five patients had a rise of total bilirubin up to 1.1 mg/100 at the end of the infusion period.     

User-defined serum aspartate and alanine aminotransferase, cholesterol, triglycerides, urea, and uric acid for the Beckman synchron CX 4/5 using Ames Sera-Pak reagents.

Beckman aspartate aminotransferase (AST), alanine aminotransferase (ALT), cholesterol, triglycerides, urea, and uric acid Liquid Reagents for Synchron CX 4/5 (48, 48, 25, 60, 26, and 30 cents US/test, respectively) are expensive. We have established our own methods for serum AST, ALT, cholesterol, triglycerides, urea, and uric acid (6, 6, 5, 12, 13, and 6 cents US/test, respectively) using Ames Sera-Pak reagents. Linearity of our AST, ALT, cholesterol, triglycerides, urea, and uric acid methods were either similar to or higher than the Beckman methods. The within run and day-to-day run precisions were acceptable. Recovery of our AST, ALT, cholesterol, triglycerides, urea, and uric acid were excellent. Our results for AST, ALT, cholesterol, triglycerides, urea, and uric acid correlated well with the Beckman results. Bilirubin (340.8 mumol/L) did not significantly interfere on our AST, ALT, cholesterol, triglycerides, and urea, while its concentrations of 165.8 mumol/L started giving negative interference on uric acid. Turbidity (2+) did not interfere significantly on our AST and ALT but started giving positive interference on cholesterol, triglycerides, urea, and uric acid. Hemolysis (2+) gave positive interference on our cholesterol, triglycerides, urea, and uric acid. Stability of Ames Sera-Pak working reagents was at least 30 days for AST, ALT, urea, and uric acid and 40 days for cholesterol and triglycerides.     

模式识别在昆布分类中的应用

目的应用光谱数学匹配方法对舟山昆布(又称海带)和海南昆布的一般成分差异做鉴别分析。方法用模式识别中主成分分析方法对可见紫外吸收光谱中0阶和1阶导数光谱数据完成分类识别。结果研究结果表明地域差异对昆布成分的含量有很大的影响。结论光谱数学匹配方法在区别不同产地药材所含组分差异上有较高灵敏度和一定的应用价值。