A study of ovarian cancer biomarker amplification using ultrasound for early stage detection

The application of serum biomarker to ovarian tumors for early stage detection and clinical diagnosis is a rapidly expanding research area. The problem with conventional markers is that they are often released too late or at too low a level to be detected in time to trigger effective treatment. Ultrasound has been used to influence bio-effects in living cells, but there is only one reported case of the use of ultrasound to enhance the release of a biomarker (Carcinoembryonic antigen CEA). In this study we report the use of ultrasound to enhance the release of a combination of ovarian cancer biomarkers (CA125 and CA19-9) to help in the diagnosis of ovarian cancer at an early stage. The results indicated that after 5 min sonication at a frequency of 1 MHz and intensity of 0.3 W cm⁻², the CA125 and CA19-9 levels were increased by 2.02 and 4.21-fold respectively. These findings suggest that ultrasonic treatment can be used to enhance the release of serum biomarkers from ovarian tumors.     

拉曼光谱在癌症诊断中的应用

在各种疾病中癌症的死亡率居第二位。另一方面只要能早期发现和诊断,几乎所有癌症都能治疗。本文介绍拉曼光谱在癌症诊断和抗癌药物筛选中的应用,结果表明拉曼光谱可能识别恶性变化的标记物,在癌症的早期诊断中是一项有用的技术。     

A Novel Method for Colorectal Cancer Screening Based on Circulating Tumor Cells and Machine Learning

Colorectal cancer is one of the most common types of cancer, and it can have a high mortality rate if left untreated or undiagnosed. The fact that CRC becomes symptomatic at advanced stages highlights the importance of early screening. The reference screening method for CRC is colonoscopy, an invasive, time-consuming procedure that requires sedation or anesthesia and is recommended from a certain age and above. The aim of this study was to build a machine learning classifier that can distinguish cancer from non-cancer samples. For this, circulating tumor cells were enumerated using flow cytometry. Their numbers were used as a training set for building an optimized SVM classifier that was subsequently used on a blind set. The SVM classifier’s accuracy on the blind samples was found to be 90.0%, sensitivity was 80.0%, specificity was 100.0%, precision was 100.0% and AUC was 0.98. Finally, in order to test the generalizability of our method, we also compared the performances of different classifiers developed by various machine learning models, using over-sampling datasets generated by the SMOTE algorithm. The results showed that SVM achieved the best performances according to the validation accuracy metric. Overall, our results demonstrate that CTCs enumerated by flow cytometry can provide significant information, which can be used in machine learning algorithms to successfully discriminate between healthy and colorectal cancer patients. The clinical significance of this method could be the development of a simple, fast, non-invasive cancer screening tool based on blood CTC enumeration by flow cytometry and machine learning algorithms.     

基于舌近红外反射光谱的人体血清多种蛋白含量无创测量

探讨一种基于近红外反射光谱的人体血清白蛋白、球蛋白和总蛋白三种生化指标的无创检测方法。采集58例志愿者舌尖处近红外反射光谱,考虑这些光谱数据与血清蛋白浓度间因个体差异等存在非线性映射关系,在计算归一化光谱反射率及分析样本蛋白含量统计分布上,采用支持向量机分别建立三种蛋白成分近红外光谱定量回归模型,并与传统的偏最小二乘法进行比较。实验结果表明,支持向量机校正模型的预测效果较好且明显优于偏最小二乘法校正模型,对白蛋白、球蛋白和总蛋白的预测相关系数分别达到0.894,0.931和0.863,预测的均方误差为2.19,1.93和4.38。因此,支持向量机可有效抵抗活体检测定量分析中存在的非线性因素,提高模型的鲁棒性。同时也表明舌的近红外光谱信息能够较客观的反映人体理化指标的变化,用于血清蛋白含量的快速无创检测具有较高的可行性。     

Intrinsic Fluorescence of Protoporphyrin IX from Blood Samples Can Yield Information on the Growth of Prostate Tumours

Prostate cancer is one of the most common types of cancer in men, and unfortunately many prostate tumours remain asymptomatic until they reach advanced stages. Diagnosis is typically performed through Prostate-Specific Antigen (PSA) quantification, Digital Rectal Examination (DRE) and Transrectal Ultrasonography (TU). The antigen (PSA) is secreted by all prostatic epithelial cells and not exclusively by cancerous ones, so its concentration also increases in the presence of other prostatic diseases. DRE and TU are not reliable for early detection, when histological analysis of prostate tissue obtained from a biopsy is necessary. In this context, fluorescence techniques are very important for the diagnosis of cancer. In this paper we explore the potential of using endogenous phorphyrin blood fluorescence as tumour marker for prostate cancer. Substances such as porphyrin derivatives accumulate substantially more in tumours than in normal tissues; thus, measuring blood porphyrin concentration by autofluorescence intensity may provide a good parameter for determining tumour stage. In this study, the autofluorescence of blood porphyrin was analyzed using fluorescence and excitation spectroscopy on healthy male NUDE mice and in those with prostate cancer induced by inoculation of DU145 cells. A significant contrast between the blood of normal and cancer subjects could be established. Blood porphyrin fluorophore showed an enhancement on the fluorescence band around 632 nm following tumour growth. Fluorescence detection has advantages over other light-based investigation methods: high sensitivity, high speed and safety. However it does carry the drawback of low specificity of detection. The extraction of blood porphyrin using acetone can solve this problem, since optical excitation of further molecular species can be excluded, and light scattering from blood samples is negligible.     

基于IABC-SVR算法的拉曼光谱定量分析山羊血清蛋白含量

提出了一种基于拉曼光谱和改进人工蜂群算法优化支持向量机回归（IABC-SVR）算法快速定量检测山羊血清蛋白含量的方法。传统人工蜂群算法在数据区域规模较大时,收敛速度逐渐减慢, 出现效率低、精准度下降、局部最优解概率高等问题。所提出的算法解决了这些问题,使算法在进化前期避免陷入局部最优解,在进化中后期能够保持解的全局搜索能力。常规测定血清蛋白总量的方法通常采用凯氏定氮法、双缩脲法等,但存在时效慢、污染样本等缺点。采用拉曼光谱法进行检测,具有快速、无损的优点。以山羊血清为分析对象,按一定体积比配置35组待测样本,用拉曼光谱仪采集拉曼光谱,光谱采集范围为300~1 300 cm-1,采用基线矫正去除荧光背景,使用Savitzky-Golay光谱平滑法对原始光谱进行平滑处理,归一化处理光谱数据,并对拉曼光谱特征峰进行归属。实验结果表明,拉曼光谱能够表征血清中主要化学集团的信息,且由于官能团浓度差异,光谱特征峰强度随浓度变化明显,因此基于特征峰信息可以测定血清蛋白总量。实验中,以购买的山羊血清蛋白含量为基准,通过配置样本的体积比得到各组待测血清样本的蛋白含量,配置的单个液体样本体积为3 mL,随机选取8组实验样本作为模型测试集,剩余27组作为模型训练集。以经过处理的光谱特征峰强度和对应的血清蛋白含量分别作为模型的输入值及输出值,建立IABC-SVR,ABC-SVR和BP三种算法的定量模型,对测试集血清蛋白总量进行预测。最后通过均方差(MSE),相关系数（r）与建模时间分别进行对比,结果表明通过IABC-SVR建立的山羊血清蛋白定量矫正模型效果最佳,模型的相关系数为0.990 27,均方误差为0.244 3,建模时间为1.9 s,预测值方差均小于0.001 g·mL-1,预测准确率为99.8%。实验结果表明,应用激光拉曼光谱技术结合IABC-SVR算法,对快速定量检测山羊血清蛋白含量,具有较高的准确率和稳定性。     

肿瘤患者血清中钴元素含量测定方法研究

本文建立了一种用石墨炉原子吸收光谱法测定肿瘤患者血清中微量钴的方法，血清以（１＋）硝酸沉淀消除蛋白后，加Ｔｒｉｔｏｎ Ｘ－１００和偏钒酸铵基体改进剂直接测定。     

肿瘤发展过程中类胡萝卜素、卟啉代谢的模拟及其荧光分析

通过肿瘤发展过程中类胡萝卜素、卟啉代谢的模拟及其荧光分析,研究了类胡萝卜素对血清荧光法癌诊断的影响。采取肘静脉血制取血清,采用光致发光的方法研究了血清中的发光中心,模拟癌发展过程中类胡萝卜素和卟啉的代谢水平对血清荧光癌诊断方法的影响。血清中主要的发光是来自具有共轭基团的血清蛋白、类胡萝卜素和卟啉的电子跃迁。随着血清中类胡萝卜素含量的增加,520nm荧光峰强度提高,614nm附近的波谷亦升高,诊断I值(荧光强度的比值,见引言中公式(1))会下降即降低了癌诊断的阳性率。     

Exploring the Relationship among Predictability,Prediction Accuracy and Data Frequency of Financial Time Series

In this paper, we aim to reveal the connection between the predictability and prediction accuracy of stock closing price changes with different data frequencies. To find out whether data frequency will affect its predictability, a new information-theoretic estimator Plz, which is derived from the Lempel–Ziv entropy, is proposed here to quantify the predictability of five-minute and daily price changes of the SSE 50 index from the Chinese stock market. Furthermore, the prediction method EEMD-FFH we proposed previously was applied to evaluate whether financial data with higher sampling frequency leads to higher prediction accuracy. It turns out that intraday five-minute data are more predictable and also have higher prediction accuracy than daily data, suggesting that the data frequency of stock returns affects its predictability and prediction accuracy, and that higher frequency data have higher predictability and higher prediction accuracy. We also perform linear regression for the two frequency data sets; the results show that predictability and prediction accuracy are positive related.     

Different classification algorithms and serum surface enhanced Raman spectroscopy for noninvasive discrimination of gastric diseases

In this study, surface enhanced Raman spectroscopy (SERS) was used to investigate the spectral characteristics of blood serum for the purpose of diagnosing stomach diseases. SERS spectral data was collected from patients with atrophic gastritis, both pre‐operation and post‐operation gastric cancer, and from healthy individuals. Visual differences in the SERS spectra were observed between the four groups which indicate corresponding biomolecule concentration changes in blood. To further investigate the diagnostic ability of human serum, the spectral data was analyzed with three chemometric processes. These three methods extracted features and classified from the spectral data. Principal component analysis (PCA) was first performed to reduce the dimensionality of the original spectral data. Then, the classification methods support vector machine (SVM), linear discriminant analysis (LDA) and classification and regression tree (CART) were used for the evaluation of diagnostic ability. Accuracies of 96.5%, 88.8% and 87.1% were obtained for PCA‐SVM, PCA‐LDA and PCA‐CART, respectively. Copyright © 2016 John Wiley & Sons, Ltd.     

Gd-DTPA-induced dynamic metabonomic changes in rat biofluids

ObjectivesThe purposes of this study were (1) to detect the dynamic metabonomic changes induced by gadopentetate dimeglumine (Gd-DTPA) and (2) to investigate the potential metabolic disturbances associated with the pathogenesis of nephrogenic systemic fibrosis (NSF) at the early stage.MethodsA nuclear magnetic resonance (NMR)-based metabolomics approach was used to investigate the urinary and serum metabolic changes induced by a single tail vein injection of Gd-DTPA (dosed at 2 and 5 mmol/kg body weight) in rats. Urine and serum samples were collected on days 1, 2 and 7 after dosing.ResultsMetabolic responses of rats to Gd-DTPA administration were systematic involving changes in lipid metabolism, glucose metabolism, TCA cycle, amino acid metabolism and gut microbiota functions. Urinary and serum metabonomic recovery could be observed in both the 2 and 5 mmol/kg body weight group, but the metabolic effects of high-dosed (5 mmol/kg body weight) Gd-DTPA lasted longer. It is worth noting that hyperlipidemia was observed after Gd-DTPA injection, and nicotinate might play a role in the subsequent self-recovery of lipid metabolism. The disturbance of tyrosine, glutamate and gut microbiota metabolism might associate with the progression of NSF.ConclusionThese findings offered essential information about the metabolic changes induced by Gd-DTPA, and could be potentially important for investigating the pathogenesis of NSF at the early stage. Moreover, the recovery of rats administrated with Gd-DTPA may have implications in the treatment of early stage NSF.     

Application of Two Novel Acoustic Emission Parameters on Identifying the Instability of Granite

The issue of monitoring and early warning of rock instability has received increasing critical attention in the study of rock engineering. To investigate the damage evolution process of granite under triaxial compression tests, acoustic emission (AE) tests were performed simultaneously. This study firstly introduced two novel parameters, i.e., the coefficient of variation (CoV) of the information entropy and correlation dimension of the amplitude data from the AE tests, to identify the precursor of the failure of granite. Then the relationship between the changes in these parameters and the stress-time curve was compared and analyzed. The results of this study show that: (1) There is a strong correlation between the CoV of the information entropy and the failure process of granite. The granite failed when the CoV curve raised to a plateau, which could be used as an indicator of rock instability. (2) The fluctuation of the correlation dimension indicates the different stages during the loading process, i.e., the initial compaction stage, the linear elastic stage, the yield stage, and the failure stage. Each stage contains a descending and a rising process in the correlation dimension curve, and the exhibited starting point or the bottom point at the correlation dimension curve could be selected as the indicator point for the rock instability. (3) The combined analysis of the Information entropy and Correlation dimension can improve the accuracy of rock instability prediction. This study provides new insights into the prediction of rock instability, which has theoretical implications for the stability of subsurface engineering rock masses.     

Detection of breast cancer based on novel porous silicon Bragg reflector surface-enhanced Raman spectroscopy-active structure

In this Letter, the surface-enhanced Raman scattering(SERS) signal of early breast cancer(BRC) patient serum is obtained by a composite silver nanoparticles(Ag NPs) PSi Bragg reflector SERS substrate. Based on these advantages, the serum SERS signals of 30 normal people and 30 early BRC patients were detected by this substrate. After a baseline correction of the experimental data, principal component analysis and linear discriminant analysis were used to complete the data processing. The results showed that the diagnostic accuracy, specificity,and sensitivity of the composite Ag NPs PSi Bragg reflector SERS substrate were 95%, 96.7%, and 93.3%, respectively. The results of this exploratory study prove that the detection of early BRC serum based on a composite Ag NPs PSi Bragg reflector SERS substrate is with a stable strong SERS signal, and an unmarked and noninvasive BRC diagnosis technology. In the future, this technology can serve as a noninvasive clinical tool to detect cancer diseases and have a considerable impact on clinical medical detection.     

Research on Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition Improved by the Niche Genetic Algorithm

Due to the influence of signal-to-noise ratio in the early failure stage of rolling bearings in rotating machinery, it is difficult to effectively extract feature information. Variational Mode Decomposition (VMD) has been widely used to decompose vibration signals which can reflect more fault omens. In order to improve the efficiency and accuracy, a method to optimize VMD by using the Niche Genetic Algorithm (NGA) is proposed in this paper. In this method, the optimal Shannon entropy of modal components in a VMD algorithm is taken as the optimization objective, by using the NGA to constantly update and optimize the combination of influencing parameters composed of α and K so as to minimize the local minimum entropy. According to the obtained optimization results, the optimal input parameters of the VMD algorithm were set. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a rolling bearing. The decomposition process of the rolling-bearing fault signal was transferred to the variational frame by the NGA-VMD algorithm, and several eigenmode function components were obtained. The energy feature extracted from the modal component containing the main fault information was used as the input vector of a particle swarm optimized support vector machine (PSO-SVM) and used to identify the fault type of the rolling bearing. The analysis results of the simulation signal and measured signal show that: the NGA-VMD algorithm can decompose the vibration signal of a rolling bearing accurately and has a better robust performance and correct recognition rate than the VMD algorithm. It can highlight the local characteristics of the original sample data and reduce the interference of the parameters selected artificially in the VMD algorithm on the processing results, improving the fault-diagnosis efficiency of rolling bearings.     

Analyzing normal proliferating,hypoxic and necrotic regions of T-47D human breast cancer spheroids using Raman spectroscopy

Raman spectroscopy is an advanced chemical analytical technique that has gained significant interest in cancer research, in particular early detection and monitoring of cancer, with added advantages of non-invasive and real-time diagnosis. Recently, studies have shown its sensitivity to monitor chemical changes during cancer progression. This information will lead to identification of chemical markers (molecular fingerprints of chemical composition) that can be used as biological markers. In this study, we used a tumor spheroid model that mimics the characteristics of a non-vascular in vitro tumor model, we used a combination of Raman and multivariate approach to identify chemical changes associated with normal proliferating, hypoxic and necrotic regions of T-47D human breast cancer spheroid model. The results provide evidence that lipids, amide I, III and nucleic acid contents differ significantly in normal, hypoxic and necrotic regions. Principal component analysis loading plots has suggested that normal proliferating region separated with low amide I and high-tryptophan content compared to hypoxic and necrotic regions. These differences observed in three regions might be useful in identification of new spectral markers associated stress faced by each region progressing toward necrosis.     

胃癌患者血红蛋白的表面增强拉曼光谱分析

胃癌患者能够得到早期诊断对其治疗具有十分重要的意义,疾病状态下的血红蛋白拉曼光谱检测在血液代用品的高铁血红蛋白含量检测中以及血氧饱和定量测定中占很大优势。本实验采用微波加热法制备银胶体粒子,依次对20例胃癌患者和11例健康人的血红蛋白进行表面增强拉曼光谱分析。采用SERS谱峰归属分析结果显示胃癌患者血红蛋白中的酪氨酸、苯丙氨酸和吡咯环的含量均低于正常人。本文还讨论了血红素的分子结构,在血红蛋白和氧气结合的前后,Fe2+分别处于高低自旋态,离子半径也随着与氧结合缩小了0.075 nm从而滑落入卟啉环平面中央的孔隙之中。这种空间的拉伸变化会牵动与铁相连的F8His,使得珠蛋白中两股螺旋之间空隙缩小,导致将HC2酪氨酸排挤出空隙。利用这一机理,对血红蛋白1 560 cm-1的吸收峰进行研究,证实了胃癌患者酪氨酸含量确实低于正常人。为了能得到更加明显的诊断区分,利用降维的思想,采用主成分分析(PCA)的方法对所有的拉曼光谱进行多元统计分析,得出三维的诊断散点图。为了更加精确的得出诊断准确率,用判别分析得出诊断的灵敏度和特异性分别为90.0%和90.9%,总判别正确率为90.3%。此项研究表明：对氧合血红蛋白的表面增强拉曼光谱诊断分析有希望成为一项新型的胃癌诊断技术应用于医学领域。     

Surface-enhanced Raman scattering study of carcinoembryonic antigen in serum from patients with colorectal cancers

In this work, we developed a SERS platform for quantitative detection of carcinoembryonic antigen (CEA) in serum of patients with colorectal cancers. Anti-CEA-functionalized 4-mercaptobenzoic acid–labeled Au/Ag core-shell bimetallic nanoparticles were prepared first and then used to analyze CEA antigen solutions of different concentrations. A calibration curve was established in the range from 5 × 10^?3 to 5 × 10⁵ ng/mL. Finally, this new SERS probe was applied for quantitative detection of CEA in serum obtained from 26 colorectal cancer patients according to the calibration curve. The results were in good agreement with that obtained by electrochemical luminescence method, suggesting that SERS immunoassay has high sensitivity and specificity for CEA detection in serum. A detection limit of 5 pg/ml was achieved. This study demonstrated the feasibility and great potential for developing this new technology into a clinical tool for analysis of tumor markers in the blood.     

基于脉冲耦合神经网络和图像熵的各向异性扩散模型研究

在图像去噪过程中, 大部分基于偏微分方程的各向异性扩散模型均使用梯度信息检测边缘, 当边缘部分被噪声严重污染时, 这些方法不能有效检测出这些边缘, 因而无法保留边缘特征. 为了较完整的保留图像的区域信息, 用脉冲耦合神经网络(PCNN)能使具有相似输入的神经元同时产生脉冲的性质对噪声图像做处理, 得到图像熵序列, 并将图像熵序列作为边缘检测算子引入到扩散方程中, 不仅能克服仅用梯度作为边缘检测算子易受噪声影响的弊端, 而且能较完整地保留图像的区域信息. 然后, 用最小交叉熵准则搜索使去噪前后图像信息量差异最小的阈值, 设计最佳阈值控制扩散强度, 建立基于脉冲耦合神经网络与图像熵改进的各向异性扩散模型(PCNN-IEAD). 分析与仿真结果表明, 该模型与经典模型相比, 保留了更多的图像信息, 能够兼顾去除图像的噪声和保护图像的边缘纹理等细节信息, 较完整的保留了图像的区域信息, 性能指标同样也证实了新模型的优越性. 另外, 该模型的运行时间较经典模型的短, 因此, 该模型是一个理想的模型.     

Magnetic resonance in the era of molecular imaging of cancer

Magnetic resonance imaging (MRI) has played an important role in the diagnosis and management of cancer since it was first developed, but other modalities also continue to advance and provide complementary information on the status of tumors. In the future, there will be a major continuing role for noninvasive imaging in order to obtain information on the location and extent of cancer, as well as assessments of tissue characteristics that can monitor and predict treatment response and guide patient management. Developments are currently being undertaken that aim to provide improved imaging methods for the detection and evaluation of tumors, for identifying important characteristics of tumors such as the expression levels of cell surface receptors that may dictate what types of therapy will be effective and for evaluating their response to treatments. Molecular imaging techniques based mainly on radionuclide imaging can depict numerous, specific, cellular and molecular markers of disease and have unique potential to address important clinical and research challenges. In this review, we consider what continuing and evolving roles will be played by MRI in this era of molecular imaging. We discuss some of the challenges for MRI of detecting imaging agents that report on molecular events, but highlight also the ability of MRI to assess other features such as cell density, blood flow and metabolism which are not specific hallmarks of cancer but which reflect molecular changes. We discuss the future role of MRI in cancer and describe the use of selected quantitative imaging techniques for characterizing tumors that can be translated to clinical applications, particularly in the context of evaluating novel treatments.     

Bacterial pyomyositis: MRI and clinical correlation

OBJECTIVE: To characterize the findings of magnetic resonance imaging (MRI) of bacterial pyomyositis (PM) and correlate these data with the clinical information. MATERIALS AND METHODS: Eighty-one patients were diagnosed with PM in our institute between 1997 and 2003. Of these, 40 patients (21 male, 19 female; mean age, 53 years) also underwent MRI examination. The clinical manifestation underlying medical problems and the characteristics of MRI were analyzed. Thirty of the patients received surgical intervention or image-guided drainage/aspiration of the abscess along with administration of antibiotics, while the remaining 10 patients were promptly treated solely with antibiotics. RESULTS: Thirty-one of 40 patients had underlying medical problems. These involved diabetes mellitus (DM, n = 16), malignancies including cervical cancer, prostate cancer, non-Hodgkin's lymphoma and acute lymphocytic leukemia (n = 10, one case also had DM), autoimmune disease or asthma with long-term steroid usage (n = 4, one case also had DM), liver cirrhosis (n = 2) and chronic renal insufficiency (n = 1). Four patients had no abscess formation at presentation (invasive or early purulent stage), while the remaining 36 cases presented with at least one abscess (purulent stage). Patients older than 40 years or DM patients tended to have larger abscess(s) (P < .05). Gadolinium-enhanced images demonstrated either thick (n = 12) or thin rim enhancement (n = 24) of the abscess wall. For those 10 patients promptly treated solely with antibiotics, nine demonstrated thin rim enhancement of the abscess (P < .05). CONCLUSION: Magnetic resonance imaging plays an important role in the early recognition of bacterial PM. By precisely demarcating the extent of the disease, MRI can allow planning prompt antibiotic treatment combined with or without interventional procedures.