Radiotherapy in the comprehensive treatment of rectal cancer

Introduction. A favorable outcome of the treatment of patients with rectal cancer in the early stages is not a difficult task, as it is easily solved thanks to only surgical intervention. The biggest problem is the treatment of patients with late-stage (III and IV) rectal cancer. The use of radiation therapy is an integral niche in the complex treatment of rectal cancer. Complete or partial clinical response of the tumor to neoadjuvant therapy is a favorable factor that correlates with an increase in overall and recurrence-free survival of patients with rectal cancer. Aim. To conduct an analysis of the effectiveness of radiotherapy and neoadjuvant chemoradiotherapy in the complex treatment of rectal cancer based on the results of the tumor's clinical response to the treatment. Research results. In both groups of  patients, the tumor was localized in the middle ampullary part of the rectum in 52.6% of the main group and 55.4% of the control group. In the lower ampullary section of the rectum in 22 patients of the main group (38.6%) and in 22 (39.3%) of the control group, respectively. The number of patients with tumor localization in the upper ampullary region was 5 (8.8%) and 35 (5.3%), respectively. Positive dynamics in the form of replacement of tumor tissue by fibrosis was observed in 89 (78.7%) patients in the compared groups. A complete clinical response was noted in 2 (3.5%) patients in the main group and in 1 (1.8%) in the control group. In 86 patients in the compared groups, II and III degrees of tumor regression according to TRG grading were recorded in 43 (75.4%) patients in the main group and 43 (76.8%) in the control group. Conclusions. In both groups, the tumor was most often localized in the middle ampullary part of the rectum, 52.6% in the main group and 55.4% of the control group. Positive dynamics in the form of replacement of tumor tissue by fibrosis was observed in 89 (78.7%) patients in the compared groups. A complete clinical response was noted in 2 (3.5%) patients in the main group and in 1 (1.8%) in the control group. Unsatisfactory dynamics in the form of IV and V degrees of tumor regression according to the TRG grading were noted in 12 (21.05%) patients of the main group and in 12 (21.4%) - in the control group

Judicial disagreement need not be political: dissent on the Estonian Supreme Court

I investigate the non-unanimous decisions of judges on the Estonian Supreme Court. I argue that since judges on the court enjoy high de jure independence, dissent frequently, and are integrated in the normal judicial hierarchy, the Estonian Supreme Court is a crucial case for the presumption that judicial disagreement reveals policy preferences. I analyse dissenting opinions using an ideal point response model. Examining the characteristics of cases which discriminated with respect to the recovered dimension, I show that this dimension cannot be interpreted as a meaningful policy dimension, but instead reflects disagreement about the proper scope of constitutional redress

Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy

Contains fulltext : 75361.pdf (publisher's version ) (Open Access)14 p

Mass spectrometry and multivariate analysis to classify cervical intraepithelial neoplasia from blood plasma: an untargeted lipidomic study

Cervical cancer is still an important issue of public health since it is the fourth most frequent type of cancer in women worldwide. Much effort has been dedicated to combating this cancer, in particular by the early detection of cervical pre-cancerous lesions. For this purpose, this paper reports the use of mass spectrometry coupled with multivariate analysis as an untargeted lipidomic approach to classifying 76 blood plasma samples into negative for intraepithelial lesion or malignancy (NILM, n = 42) and squamous intraepithelial lesion (SIL, n = 34). The crude lipid extract was directly analyzed with mass spectrometry for untargeted lipidomics, followed by multivariate analysis based on the principal component analysis (PCA) and genetic algorithm (GA) with support vector machines (SVM), linear (LDA) and quadratic (QDA) discriminant analysis. PCA-SVM models outperformed LDA and QDA results, achieving sensitivity and specificity values of 80.0% and 83.3%, respectively. Five types of lipids contributing to the distinction between NILM and SIL classes were identified, including prostaglandins, phospholipids, and sphingolipids for the former condition and Tetranor-PGFM and hydroperoxide lipid for the latter. These findings highlight the potentiality of using mass spectrometry associated with chemometrics to discriminate between healthy women and those suffering from cervical pre-cancerous lesions

Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening

Neuroendocrine–immune disequilibrium and endometriosis: an interdisciplinary approach

Endometriosis, a chronic disease characterized by endometrial tissue located outside the uterine cavity, affects one fourth of young women and is associated with chronic pelvic pain and infertility. However, an in-depth understanding of the pathophysiology and effective treatment strategies of endometriosis is still largely elusive. Inadequate immune and neuroendocrine responses are significantly involved in the pathophysiology of endometriosis, and key findings are summarized in the present review. We discuss here the role of different immune mechanisms particularly adhesion molecules, protein–glycan interactions, and pro-angiogenic mediators in the development and progression of the disease. Finally, we introduce the concept of endometrial dissemination as result of a neuroendocrine-immune disequilibrium in response to high levels of perceived stress caused by cardinal clinical symptoms of endometriosis

Genomic subtypes of breast cancer identified by array comparative genomic hybridization display distinct molecular and clinical characteristics

Abstract Introduction Breast cancer is a profoundly heterogeneous disease with respect to biologic and clinical behavior. Gene-expression profiling has been used to dissect this complexity and to stratify tumors into intrinsic gene-expression subtypes, associated with distinct biology, patient outcome, and genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. Methods We applied global DNA copy number and gene-expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene-expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy-number aberrations and genomic subgroups of breast cancer. Results We identified 31 genomic regions that were highly amplified in > 1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions revealed six genomic subtypes, termed 17q12, basal-complex, luminal-simple, luminal-complex, amplifier, and mixed subtypes. Four of them had striking similarity to intrinsic gene-expression subtypes and showed associations to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having a better prognosis, whereas the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene-expression subtypes, the former being enriched for 8p12-amplified cases, whereas the mixed subtype included many tumors with predominantly DNA copy-number losses and poor prognosis. Conclusions Global DNA copy-number analysis integrated with gene-expression data can be used to dissect the complexity of breast cancer. This revealed six genomic subtypes with different clinical behavior and a striking concordance to the intrinsic subtypes. These genomic subtypes may prove useful for understanding the mechanisms of tumor development and for prognostic and treatment prediction purposes