Data analysis methods in optometry Part 3: the analysis of frequencies and proportions

In some studies, the data are not measurements but comprise counts or frequencies of particular events. In such cases, an investigator may be interested in whether one specific event happens more frequently than another or whether an event occurs with a frequency predicted by a scientific model.

Data analysis methods in optometry Part 4: an introduction to analysis of variance (ANOVA)

In any investigation in optometry involving more that two treatment or patient groups, an investigator should be using ANOVA to analyse the results assuming that the data conform reasonably well to the assumptions of the analysis. Ideally, specific null hypotheses should be built into the experiment from the start so that the treatments variation can be partitioned to test these effects directly. If 'post-hoc' tests are used, then an experimenter should examine the degree of protection offered by the test against the possibilities of making either a type 1 or a type 2 error. All experimenters should be aware of the complexity of ANOVA. The present article describes only one common form of the analysis, viz., that which applies to a single classification of the treatments in a randomised design. There are many different forms of the analysis each of which is appropriate to the analysis of a specific experimental design. The uses of some of the most common forms of ANOVA in optometry have been described in a further article. If in any doubt, an investigator should consult a statistician with experience of the analysis of experiments in optometry since once embarked upon an experiment with an unsuitable design, there may be little that a statistician can do to help.

Data analysis methods in optometry. Part 5: correlation

1. Pearson's correlation coefficient only tests whether the data fit a linear model. With large numbers of observations, quite small values of r become significant and the X variable may only account for a minute proportion of the variance in Y. Hence, the value of r squared should always be calculated and included in a discussion of the significance of r. 2. The use of r assumes that a bivariate normal distribution is present and this assumption should be examined prior to the study. If Pearson's r is not appropriate, then a non-parametric correlation coefficient such as Spearman's rs may be used. 3. A significant correlation should not be interpreted as indicating causation especially in observational studies in which there is a high probability that the two variables are correlated because of their mutual correlations with other variables. 4. In studies of measurement error, there are problems in using r as a test of reliability and the ‘intra-class correlation coefficient’ should be used as an alternative. A correlation test provides only limited information as to the relationship between two variables. Fitting a regression line to the data using the method known as ‘least square’ provides much more information and the methods of regression and their application in optometry will be discussed in the next article.

Data analysis methods in optometry Part 7: multiple linear regression

Multiple regression analysis is a complex statistical method with many potential uses. It has also become one of the most abused of all statistical procedures since anyone with a data base and suitable software can carry it out. An investigator should always have a clear hypothesis in mind before carrying out such a procedure and knowledge of the limitations of each aspect of the analysis. In addition, multiple regression is probably best used in an exploratory context, identifying variables that might profitably be examined by more detailed studies. Where there are many variables potentially influencing Y, they are likely to be intercorrelated and to account for relatively small amounts of the variance. Any analysis in which R squared is less than 50% should be suspect as probably not indicating the presence of significant variables. A further problem relates to sample size. It is often stated that the number of subjects or patients must be at least 5-10 times the number of variables included in the study.5 This advice should be taken only as a rough guide but it does indicate that the variables included should be selected with great care as inclusion of an obviously unimportant variable may have a significant impact on the sample size required.

Data analysis methods in optometry Part 8: Principal components analysis (PCA) and factor analysis (FA)

PCA/FA is a method of analyzing complex data sets in which there are no clearly defined X or Y variables. It has multiple uses including the study of the pattern of variation between individual entities such as patients with particular disorders and the detailed study of descriptive variables. In most applications, variables are related to a smaller number of ‘factors’ or PCs that account for the maximum variance in the data and hence, may explain important trends among the variables. An increasingly important application of the method is in the ‘validation’ of questionnaires that attempt to relate subjective aspects of a patients experience with more objective measures of vision.

Mathematical competence for information visualization by correspondence analysis methods

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

A tudásérték meghatározása minőségügyi szempontból, hálózatelemzési módszerekkel (The knowledge value in terms of quality with network analysis methods)

A minőségügy egyik kulcsfeladata, hogy azonosítsa az értékteremtés szempontjából kritikus tényezőket, meghatározza ezek értékét, valamint intézkedjen negatív hatásuk megelőzése és csökkentése érdekében. Az értékteremtés sok esetben folyamatokon keresztül történik, amelyek tevékenységekből, elvégzendő feladatokból állnak. Ezekhez megfelelő munkatársak kellenek, akiknek az egyik legfontosabb jellemzője az általuk birtokolt tudás. Mindezek alapján a feladat-tudás-erőforrás kapcsolatrendszer ismerete és kezelése minőségügyi feladat is. A komplex rendszerek elemzésével foglalkozó hálózatkutatás eszközt biztosíthat ehhez, ezért indokolt a minőségügyi területen történő alkalmazhatóságának vizsgálata. Az alkalmazási lehetőségek rendszerezése érdekében a szerzők kategorizálták a minőségügyi hálózatokat az élek (kapcsolatok) és a csúcsok (hálózati pontok) típusai alapján. Ezt követően definiálták a multimodális (több különböző csúcstípusból álló) tudáshálózatot, amely a feladatokból, az erőforrásokból, a tudáselemekből és a közöttük lévő kapcsolatokból épül fel. A hálózat segítségével kategóriákba sorolták a tudáselemeket, valamint a fokszámok alapján meghatározták értéküket. A multimodális hálózatból képzett tudáselem-hálózatban megadták az összefüggő csoportok jelentését, majd megfogalmaztak egy összefüggést a tudáselem-elvesztés kockázatának meghatározására. _______ The aims of quality management are to identify those factors that have significant influence on value production, qualify or quantify them, and make preventive and corrective actions in order to reduce their negative effects. The core elements of value production are processes and tasks, along with workforce having the necessary knowledge to work. For that reason the task-resource-knowledge structure is pertinent to quality management. Network science provides methods to analyze complex systems; therefore it seems reasonable to study the use of tools of network analysis in association with quality management issues. First of all the authors categorized quality networks according to the types of nodes (vertices) and links (edges or arcs). Focusing on knowledge management, they defined the multimodal knowledge network, consisting of tasks, resources, knowledge items and their interconnections. Based on their degree, network nodes can be categorized and their value can be quantified. Derived from the multimodal network knowledge-item network is to be created, where the meaning of cohesive subgroups is defined. Eventually they proposed a formula for determining the risk of knowledge loss.

Analysis methods for meso- and macroporous silicon etching baths

Analysis methods for electrochemical etching baths consisting of various concentrations of hydrofluoric acid (HF) and an additional organic surface wetting agent are presented. These electrolytes are used for the formation of meso- and macroporous silicon. Monitoring the etching bath composition requires at least one method each for the determination of the HF concentration and the organic content of the bath. However, it is a precondition that the analysis equipment withstands the aggressive HF. Titration and a fluoride ion-selective electrode are used for the determination of the HF and a cuvette test method for the analysis of the organic content, respectively. The most suitable analysis method is identified depending on the components in the electrolyte with the focus on capability of resistance against the aggressive HF.

Robustness of germination analysis methods for Copaifera langsdorffii Desf. (Fabaceae) seeds.

2016

Anti-neoplastic properties of hydralazine in prostate cancer

Prostate cancer (PCa) is a major cause of cancer-related morbidity and mortality worldwide. Although early disease is often efficiently managed therapeutically, available options for advanced disease are mostly ineffective. Aberrant DNA methylation associated with gene-silencing of cancer-related genes is a common feature of PCa. Therefore, DNA methylation inhibitors might constitute an attractive alternative therapy. Herein, we evaluated the anti-cancer properties of hydralazine, a non-nucleoside DNA methyltransferases (DNMT) inhibitor, in PCa cell lines. In vitro assays showed that hydralazine exposure led to a significant dose and time dependent growth inhibition, increased apoptotic rate and decreased invasiveness. Furthermore, it also induced cell cycle arrest and DNA damage. These phenotypic effects were particularly prominent in DU145 cells. Following hydralazine exposure, decreased levels of DNMT1, DNMT3a and DNMT3b mRNA and DNMT1 protein were depicted. Moreover, a significant decrease in GSTP1, BCL2 and CCND2 promoter methylation levels, with concomitant transcript re-expression, was also observed. Interestingly, hydralazine restored androgen receptor expression, with upregulation of its target p21 in DU145 cell line. Protein array analysis suggested that blockage of EGF receptor signaling pathway is likely to be the main mechanism of hydralazine action in DU145 cells. Our data demonstrate that hydralazine attenuated the malignant phenotype of PCa cells, and might constitute a useful therapeutic tool.

Infrequent promoter methylation of the MGMT gene in liver metastases from uveal melanoma.

Uveal melanoma is associated with a high mortality rate once metastases occur, with over >90% of metastatic patients dying within less than 1 year from metastases to the liver. The intraarterial hepatic (iah) administration of the alkylating agent fotemustine holds some promise with response rates of 36% and median survival of 15 months. Here, we investigated whether the DNA-repair-protein MGMT may be involved in the variability of response to fotemustine and temozolomide in uveal melanoma. Epigenetic inactivation of MGMT has been demonstrated to be a predictive marker for benefit from alkylating agent therapy in glioblastoma. We found a methylated MGMT promoter in 6% of liver metastases from 34 uveal melanoma patients. The mean MGMT activity measured in liver metastases with negligible liver tissue content was significantly lower than in liver tissue (146 versus 523 fmol/mg protein, p = 0.002). Expression of the MGMT protein was detectable in 50% of 88 metastases by immunohistochemistry on a tissue microarray. Expression was heterogeneous, and in accordance with MGMT activity data, usually lower than in the surrounding liver. Differential MGMT activity/expression between metastasis and liver tissue and more efficient depletion of MGMT with higher doses of alkylating agent therapy using iah delivery may provide the pharmacologic window for the higher response rate. However, these results do not support MGMT methylation status or protein expression as predictive markers for treatment outcome to iah chemotherapy with alkylating agents.

Sequence determinants of a microtubule tip localization signal (MtLS).

Microtubule plus-end-tracking proteins (+TIPs) specifically localize to the growing plus-ends of microtubules to regulate microtubule dynamics and functions. A large group of +TIPs contain a short linear motif, SXIP, which is essential for them to bind to end-binding proteins (EBs) and target microtubule ends. The SXIP sequence site thus acts as a widespread microtubule tip localization signal (MtLS). Here we have analyzed the sequence-function relationship of a canonical MtLS. Using synthetic peptide arrays on membrane supports, we identified the residue preferences at each amino acid position of the SXIP motif and its surrounding sequence with respect to EB binding. We further developed an assay based on fluorescence polarization to assess the mechanism of the EB-SXIP interaction and to correlate EB binding and microtubule tip tracking of MtLS sequences from different +TIPs. Finally, we investigated the role of phosphorylation in regulating the EB-SXIP interaction. Together, our results define the sequence determinants of a canonical MtLS and provide the experimental data for bioinformatics approaches to carry out genome-wide predictions of novel +TIPs in multiple organisms.

Tissue-based immune monitoring I: tumor core needle biopsies allow in-depth interrogation of the tumor microenvironment.

We sought to assess the feasibility and reproducibility of performing tissue-based immune characterization of the tumor microenvironment using CT-compatible needle biopsy material. Three independent biopsies were obtained intraoperatively from one metastatic epithelial ovarian cancer lesion of 7 consecutive patients undergoing surgical cytoreduction using a 16-gauge core biopsy needle. Core specimens were snap-frozen and subjected to immunohistochemistry (IHC) against human CD3, CD4, CD8, and FoxP3. A portion of the cores was used to isolate RNA for 1) real-time quantitative (q)PCR for CD3, CD4, CD8, FoxP3, IL-10 and TGF-beta, 2) multiplexed PCR-based T cell receptor (TCR) CDR3 Vβ region spectratyping, and 3) gene expression profiling. Pearson's correlations were examined for immunohistochemistry and PCR gene expression, as well as for gene expression array data obtained from different tumor biopsies. Needle biopsy yielded sufficient tissue for all assays in all patients. IHC was highly reproducible and informative. Significant correlations were seen between the frequency of CD3+, CD8+ and FoxP3+ T cells by IHC with CD3ε, CD8A, and FoxP3 gene expression, respectively, by qPCR (r=0.61, 0.86, and 0.89; all p< 0.05). CDR3 spectratyping was feasible and highly reproducible in each tumor, and indicated a restricted repertoire for specific TCR Vβ chains in tumor-infiltrating T cells. Microarray gene expression revealed strong correlation between different biopsies collected from the same tumor. Our results demonstrate a feasible and reproducible method of immune monitoring using CT-compatible needle biopsies from tumor tissue, thereby paving the way for sophisticated translational studies during tumor biological therapy.

Anchoring of both PKA and 14-3-3 inhibits the Rho-GEF activity of the AKAP-Lbc signaling complex.

A-kinase anchoring proteins (AKAPs) target the cAMP-regulated protein kinase (PKA) to its physiological substrates. We recently identified a novel anchoring protein, called AKAP-Lbc, which functions as a PKA-targeting protein as well as a guanine nucleotide exchange factor (GEF) for RhoA. We demonstrated that AKAP-Lbc Rho-GEF activity is stimulated by the alpha subunit of the heterotrimeric G protein G12. Here, we identified 14-3-3 as a novel regulatory protein interacting with AKAP-Lbc. Elevation of the cellular concentration of cAMP activates the PKA holoenzyme anchored to AKAP-Lbc, which phosphorylates the anchoring protein on the serine 1565. This phosphorylation event induces the recruitment of 14-3-3, which inhibits the Rho-GEF activity of AKAP-Lbc. AKAP-Lbc mutants that fail to interact with PKA or with 14-3-3 show a higher basal Rho-GEF activity as compared to the wild-type protein. This suggests that, under basal conditions, 14-3-3 maintains AKAP-Lbc in an inactive state. Therefore, while it is known that AKAP-Lbc activity can be stimulated by Galpha12, in this study we demonstrated that it is inhibited by the anchoring of both PKA and 14-3-3.

Antibody Signatures Reflect Different Disease Pathologies in Patients With Schistosomiasis Due to Schistosoma japonicum

Infection with Schistosoma japonicum causes high levels of pathology that is predominantly determined by the cellular and humoral response of the host. However, the specific antibody response that arises during the development of disease is largely undescribed in Asian schistosomiasis-endemic populations. A schistosome protein microarray was used to compare the antibody profiles of subjects with acute infection, with early or advanced disease associated with severe pathology, with chronic infection, and subjects exposed but stool negative for S. japonicum eggs to the antibody profiles of nonexposed controls. Twenty-five immunodominant antigens were identified, including vaccine candidates, tetraspanin-related proteins, transporter molecules, and unannotated proteins. Additionally, individuals with severe pathology had a limited specific antibody response, suggesting that individuals with mild disease may use a broad and strong antibody response, particularly against surface-exposed proteins, to control pathology and/or infection. Our study has identified specific antigens that can discriminate between S. japonicum-exposed groups with different pathologies and may also allow the host to control disease pathology and provide resistance to parasite infection.