Analysis of Kernel Matrices via the von Neumann Entropy and Its Relation to RVM Performances.

Kernel methods have played a major role in the last two decades in the modeling and visualization of complex problems in data science. The choice of kernel function remains an open research area and the reasons why some kernels perform better than others are not yet understood. Moreover, the high computational costs of kernel-based methods make it extremely inefficient to use standard model selection methods, such as cross-validation, creating a need for careful kernel design and parameter choice. These reasons justify the prior analyses of kernel matrices, i.e., mathematical objects generated by the kernel functions. This paper explores these topics from an entropic standpoint for the case of kernelized relevance vector machines (RVMs), pinpointing desirable properties of kernel matrices that increase the likelihood of obtaining good model performances in terms of generalization power, as well as relate these properties to the model's fitting ability. We also derive a heuristic for achieving close-to-optimal modeling results while keeping the computational costs low, thus providing a recipe for efficient analysis when processing resources are limited.

A switch in regulatory T cells through farm exposure during immune maturation in childhood.

BACKGROUND: Farm exposure protects against development of allergies early in life. At 4.5 years, protection against asthma by farm-milk exposure was partially mediated by regulatory T cells (Tregs). The aim of this study was to investigate the critical time window of the 'asthma-protective' farm effect via Tregs during childhood immune maturation. METHODS: Tregs were assessed longitudinally at 4.5 and 6 years in 111 children (56 farm and 55 reference children) from the PASTURE/EFRAIM birth cohort (flow cytometry). Peripheral blood mononuclear cells were cultured unstimulated (U), with phorbol 12-myristate 13-acetate/ionomycin (PI) or lipopolysaccharide (LPS), and stained for Tregs (CD4+ CD25high FOXP3upper20% ). mRNA expression of Treg/Th1/Th2/Th17-associated cell markers was measured ex vivo. Suppressive capacity of Tregs on effector cells and cytokines was assessed. Detailed questionnaires assessing farm exposures and clinical phenotypes from birth until age 6 years were answered by the parents. RESULTS: Treg percentage before and after stimulation and FOXP3mRNA expression ex vivo decreased from age 4.5 to 6 years (P(U,LPS) < 0.001; P(PI) = 0.051; P(FOXP3) < 0.001). High vs low farm-milk and animal-stable exposure was associated with decreased LPS-stimulated Treg percentage at age 6 years (P(LPS) = 0.045). Elevated LPS-stimulated-Treg percentage at age 6 was associated with increased risk of asthma (aOR = 11.29, CI: 0.96-132.28, P = 0.053). Tregs from asthmatics vs nonasthmatics suppressed IFN-γ (P = 0.015) and IL-9 (P = 0.023) less efficiently. mRNA expression of Th1/Th2/Th17-associated cell markers decreased between 4.5 and 6 years (P < 0.001). CONCLUSIONS: Tregs at the age of 6 years were decreased with farm exposure and increased within asthmatics, opposite to age 4.5 years. This immunological switch defines a critical 'time window' for Treg-mediated asthma protection via environmental exposure before age 6 years.

Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods.

Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB) modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization.

Gene discovery for facioscapulohumeral muscular dystrophy by machine learning techniques.

Facioscapulohumeral muscular dystrophy (FSHD) is a neuromuscular disorder that shows a preference for the facial, shoulder and upper arm muscles. FSHD affects about one in 20-400,000 people, and no effective therapeutic strategies are known to halt disease progression or reverse muscle weakness or atrophy. Many genes may be incorrectly regulated in affected muscle tissue, but the mechanisms responsible for the progressive muscle weakness remain largely unknown. Although machine learning (ML) has made significant inroads in biomedical disciplines such as cancer research, no reports have yet addressed FSHD analysis using ML techniques. This study explores a specific FSHD data set from a ML perspective. We report results showing a very promising small group of genes that clearly separates FSHD samples from healthy samples. In addition to numerical prediction figures, we show data visualizations and biological evidence illustrating the potential usefulness of these results.

Predicting fecal sources in waters with diverse pollution loads using general and molecular host-specific indicators and applying machine learning methods.

In this study we use a machine learning software (Ichnaea) to generate predictive models for water samples with different concentrations of fecal contamination (point source, moderate and low). We applied several MST methods (host-specific Bacteroides phages, mitochondrial DNA genetic markers, Bifidobacterium adolescentis and Bifidobacterium dentium markers, and bifidobacterial host-specific qPCR), and general indicators (Escherichia coli, enterococci and somatic coliphages) to evaluate the source of contamination in the samples. The results provided data to the Ichnaea software, that evaluated the performance of each method in the different scenarios and determined the source of the contamination. Almost all MST methods in this study determined correctly the origin of fecal contamination at point source and in moderate concentration samples. When the dilution of the fecal pollution increased (below 3 log10 CFU E. coli/100 ml) some of these indicators (bifidobacterial host-specific qPCR, some mitochondrial markers or B. dentium marker) were not suitable because their concentrations decreased below the detection limit. Using the data from source point samples, the software Ichnaea produced models for waters with low levels of fecal pollution. These models included some MST methods, on the basis of their best performance, that were used to determine the source of pollution in this area. Regardless the methods selected, that could vary depending on the scenario, inductive machine learning methods are a promising tool in MST studies and may represent a leap forward in solving MST cases.

Effective classification and gene expression profiling for the Facioscapulohumeral Muscular Dystrophy.

The Facioscapulohumeral Muscular Dystrophy (FSHD) is an autosomal dominant neuromuscular disorder whose incidence is estimated in about one in 400,000 to one in 20,000. No effective therapeutic strategies are known to halt progression or reverse muscle weakness and atrophy. It is known that the FSHD is caused by modifications located within a D4ZA repeat array in the chromosome 4q, while recent advances have linked these modifications to the DUX4 gene. Unfortunately, the complete mechanisms responsible for the molecular pathogenesis and progressive muscle weakness still remain unknown. Although there are many studies addressing cancer databases from a machine learning perspective, there is no such precedent in the analysis of the FSHD. This study aims to fill this gap by analyzing two specific FSHD databases. A feature selection algorithm is used as the main engine to select genes promoting the highest possible classification capacity. The combination of feature selection and classification aims at obtaining simple models (in terms of very low numbers of genes) capable of good generalization, that may be associated with the disease. We show that the reported method is highly efficient in finding genes to discern between healthy cases (not affected by the FSHD) and FSHD cases, allowing the discovery of very parsimonious models that yield negligible repeated cross-validation error. These models in turn give rise to very simple decision procedures in the form of a decision tree. Current biological evidence regarding these genes shows that they are linked to skeletal muscle processes concerning specific human conditions.

Differential sensitivity to detergents of actin cytoskeleton from nerve endings.

Detergent-resistant membranes (DRM), an experimental model used to study lipid rafts, are typically extracted from cells by means of detergent treatment and subsequent ultracentrifugation in density gradients, Triton X-100 being the detergent of choice in most of the works. Since lipid rafts are membrane microdomains rich in cholesterol, depletion of this component causes solubilization of DRM with detergent. In previous works from our group, the lack of effect of cholesterol depletion on DRM solubilization with Triton X-100 was detected in isolated rat brain synaptosomes. In consequence, the aim of the present work is to explore reasons for this observation, analyzing the possible role of the actin cytoskeleton, as well as the use of an alternative detergent, Brij 98, to overcome the insensitivity to Triton X-100 of cholesterol-depleted DRM. Brij 98 yields Brij-DRM that are highly dependent on cholesterol, since marker proteins (Flotillin-1 and Thy-1), as well as actin, appear solubilized after MCD treatment. Pretreatment with Latrunculin A results in a significant increase in Flotillin-1, Thy-1 and actin solubilization by Triton X-100 after cholesterol depletion. Studies with transmission electron microscopy show that combined treatment with MCD and Latrunculin A leads to a significant increase in solubilization of DRM with Triton X-100. Thus, Triton-DRM resistance to cholesterol depletion can be explained, at least partially, thanks to the scaffolding action of the actin cytoskeleton, without discarding differential effects of Brij 98 and Triton X-100 on specific membrane components. In conclusion, the detergent of choice is important when events that depend on the actin cytoskeleton are going to be studied.

Parsimonious selection of useful genes in microarray gene expression data.

Machine learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number of features and a few observations, making the modeling a nontrivial undertaking. In this study, we apply entropic filter methods for gene selection, in combination with several off-the-shelf classifiers. The introduction of bootstrap resampling techniques permits the achievement of more stable performance estimates. Our findings show that the proposed methodology permits a drastic reduction in dimension, offering attractive solutions in terms of both prediction accuracy and number of explanatory genes; a dimensionality reduction technique preserving discrimination capabilities is used for visualization of the selected genes.

Application of recombinant and non-recombinant peptides in the determination of tumor response to cancer therapy.

An early and reliable assessment of therapeutic efficacy during the treatment of cancer is essential to achieve an optimal treatment regimen and patient outcome. The use of labeled peptides to monitor tumor response is associated with several advantages. For example, peptides are very stable, non-immunogenic, are easy to label for imaging, they undergo rapid clearance from the circulation, can penetrate tumor tissue, and are inexpensive to synthesize. In this review, studies using recombinant and non-recombinant peptides to monitor the response of glioblastoma multiforme, lung, breast, pancreas, colon, prostate, and skin carcinomas to radiation and/or chemotherapeutics such as camptothecin, doxorubicin, etoposide, 5-fluorouracil, paclitaxel, AG3340, sunitinib, and dasatinib, are presented. A consideration of the imaging techniques available to monitor peptide localization, including near-infrared (NIR) fluorescence, magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasonography, is also included. Peptides that have been successfully used to monitor various tumor types and therapies have been shown to target proteins that undergo changes in expression in response to treatment, endothelial cells that respond to radiation, or mediators of apoptosis. Peptides that are able to selectively bind responsive versus unresponsive tumors have also been identified. Therefore, the advantages associated with the use of peptides, combined with the capacity for selected peptides to assess tumor response as demonstrated in various studies, support the use of labeled peptides to evaluate the effectiveness of a given cancer therapy.

Pegylated arginase I: a potential therapeutic approach in T-ALL.

Adult patients with acute lymphoblastic T cell leukemia (T-ALL) have a very poor prognosis and few effective therapeutic options. Therefore, novel therapies that increase the efficacy of the treatments and that prolong T-ALL patient survival are needed. Malignant T cells require high concentrations of nutrients to sustain their increased rate of proliferation. In this study, we determined whether L-Arginine depletion by the pegylated form of the L-Arginine-metabolizing enzyme arginase I (peg-Arg I) impairs the proliferation of malignant T cells. Our results show that peg-Arg I depleted L-Arginine levels in vitro and in vivo. In addition, treatment of malignant T-cell lines with peg-Arg I significantly impaired their proliferation, which correlated with a decreased progression into the cell cycle, followed by the induction of apoptosis. Furthermore, peg-Arg I impaired the expression of cyclin D3, a fundamental protein in T-ALL proliferation, through a global arrest in protein synthesis. Injection of peg-Arg I plus chemotherapy agent Cytarabine prolonged survival in mice bearing T-ALL tumors. This antitumoral effect correlated with an inhibition of T-ALL proliferation in vivo, a decreased expression of cyclin D3, and T-ALL apoptosis. The results suggest the potential benefit of L-Arginine depletion by peg-Arg I in the treatment of T-cell malignancies.

Human prostate cancer heterotransplants: a review on this experimental model.

A common model used for preclinical research was in vitro human tumor cell culture. An alternative model was the direct implantation of a unique patient's tumor biopsy specimens into immunodeficient host mice. Published data from PubMed (http://www.ncbi.nlm.nih.gov) and Current Contents Connect databases (http://thomsonreuters.com/products_services/science/science_products/a-z/current_contents_connect) were reviewed. Prostate cancer (PCa) heterotransplantation was evaluated using histopathology, morphology, cell differentiation, DNA content, tumor marker expression, metastases, tumor kinetics, tumor take rate and tumor vasculature in the first tumor heterotransplant. The heterotransplanted tumor retained the biological properties of the original tumor, such as morphology, degree of differentiation, pathology, secretory activity, expression of tumor markers and human vasculature. Human PCa heterotransplants have considerable experimental advantages over cell culture following xenotransplantation.

Molecular indicators used in the development of predictive models for microbial source tracking.

A number of chemical, microbial, and eukaryotic indicators have been proposed as indicators of fecal pollution sources in water bodies. No single one of the indicators tested to date has been able to determine the source of fecal pollution in water. However, the combined use of different indicators has been demonstrated to be the best way of defining predictive models suitable for determining fecal pollution sources. Molecular methods are promising tools that could complement standard microbiological water analysis. In this study, the feasibility of some proposed molecular indicators for microbial source tracking (MST) was compared (names of markers are in parentheses): host-specific Bacteroidetes (HF134, HF183, CF128, and CF193), Bifidobacterium adolescentis (ADO), Bifidobacterium dentium (DEN), the gene esp of Enterococcus faecium, and host-specific mitochondrial DNA associated with humans, cattle, and pigs (Humito, Bomito, and Pomito, respectively). None of the individual molecular markers tested enabled 100% source identification. They should be combined with other markers to raise sensitivity and specificity and increase the number of sources that are identified. MST predictive models using only these molecular markers were developed. The models were evaluated by considering the lowest number of molecular indicators needed to obtain the highest rate of identification of fecal sources. The combined use of three molecular markers (ADO, Bomito, and Pomito) enabled correct identification of 75.7% of the samples, with differentiation between human, swine, bovine, and poultry sources. Discrimination between human and nonhuman fecal pollution was possible using two markers: ADO and Pomito (84.6% correct identification). The percentage of correct identification increased with the number of markers analyzed. The best predictive model for distinguishing human from nonhuman fecal sources was based on 5 molecular markers (HF134, ADO, DEN, Bomito, and Pomito) and provided 90.1% correct classification.

Human benign prostatic hyperplasia heterotransplants as an experimental model.

Benign prostatic hyperplasia is a nonmalignant adenomatous enlargement of the periurethral prostate gland. It is a common disease in older men. In addition to man, spontaneous benign prostatic hyperplasia occurs in chimpanzee and the dog. Alternatives to these spontaneous models are induced benign prostatic hyperplasia, xenografts and in vitro models. Xenografts may be induced by cells cultured in vitro or by the heterotransplantation of primary surgical specimens into immunosuppressed mice. The purpose of this review is to integrate data from more than 30 years of heterotransplantation research in the study of benign hyperplasia of the prostate. Heterotransplantation has provided data regarding the histopathology, morphology, tissue markers, androgen receptor expression, tissue kinetics, take rate and tissue vasculature for this prostate disease. There are advantages, as well as limitations, that have been identified for human prostate disease heterotransplants versus xenotransplantation of cultured cells. Overall, heterotransplanted tissue is better at retaining tissue morphology, pathology, secretory activity, expression of tissue markers and human vasculature of the patient's original specimen. Furthermore, heterotransplanted tissue preserves the three-dimensional tissular architecture of the prostate to maintain critical stromal-epithelial cell interactions.

Serially heterotransplanted human prostate tumours as an experimental model.

* Introduction * Serially heterotransplanted human tumours in immunosuppressed mice: similarity to the tumour of origin - Cytological and histological analysis - Karyotype - Marker expression - Other PC markers - Tumour cell proliferation and frequency of mitosis - Vasculature - Stromal compartment - Heterotransplant hormone dependency - Androgen dependent - Partially androgen dependent - Androgen independent - Metastases * Conclusions Preclinical research on prostate cancer (PC) therapies uses several models to represent the human disease accurately. A common model uses patient prostate tumour biopsies to develop a cell line by serially passaging and subsequent implantation, in immunodeficient mice. An alternative model is direct implantation of patient prostate tumour biopsies into immunodeficient mice, followed by serial passage in vivo. The purpose of this review is to compile data from the more than 30 years of human PC serial heterotransplantation research. Serially heterotransplanted tumours are characterized by evaluating the histopathology of the resulting heterotransplants, including cellular differentiation, karyotype, marker expression, hormone sensitivity, cellular proliferation, metastatic potential and stromal and vascular components. These data are compared with the initial patient tumour specimen and, depending on available information, the patient's clinical outcome was compared with the heterotransplanted tumour. The heterotansplant model is a more accurate preclinical model than older generation serially passaged or genetic models to investigate current and newly developed androgen-deprivation agents, antitumour compounds, anti-angiogenic drugs and positron emission tomography radiotracers, as well as new therapeutic regimens for the treatment of PC.

Small-cell neuroendocrine carcinoma of the prostate: are heterotransplants a better experimental model?

Small-cell neuroendocrine carcinoma of the prostate (SCNCP) is an uncommon type of prostate cancer. However, it is of clinical importance because it is one of the most aggressive tumors of the prostate with a very poor prognosis. There exist few artificially cultured tumor cell lines to study SCNCP. Then, another approach to that study consists in the use of fresh tumor tissue obtained from patients and its heterotransplantation into host mice. The purpose of this review is to integrate data from more than 20 years of heterotransplantation research in the study of small-cell neuroendocrine carcinoma of the prostate (SCNCP). Heterotransplantation has provided data regarding the histopathology, karyotype, DNA content, cell cycle frequency, tumor markers, androgen receptor expression, metastasis and take rate of this prostate disease. When possible, comparisons between original in situ specimens removed from patients and heterotransplanted tissue from host mice have been made. There are advantages, as well as limitations, that have been identified for SCNCP heterotransplants versus xenotransplantation of cultured cells. Overall, heterotransplanted tumors are better than conventional tumor xenografts at retaining tumor morphology, pathology, secretory activity and expression of tumor markers of the patient's original specimen. Furthermore, heterotransplanted tissue preserves the three-dimensional tumor architecture of the prostate to maintain critical stromal-epithelial cell interactions.

New multiplatform computer program for numerical identification of microorganisms.

The classification of bacteria by using genomic methods or expensive biochemical-based commercial kits is sometimes beyond the reach of many laboratories that need to perform numerous classifications of unknown bacterial strains in a fast, cheap, and reliable way. A new computer program, Identax, for the computer-assisted identification of microorganisms by using only results obtained from conventional biochemical tests is presented. Identax improves current microbial identification software and provides a multiplatform and user-friendly program. It can be executed from any operating system and can be downloaded without any cost from the Identax website (www.identax.org).

Targeted adriamycin delivery to MXT-B2 metastatic mammary carcinoma cells by transferrin liposomes: effect of adriamycin ADR-to-lipid ratio.

In the protein-targeted therapy for cancer, transferrin (Tf) is used to reach a selective and specific target in cancer cells. Tf is used conjugated to chemotherapeutic drugs, insulin, toxins, antibodies, polymers, nanoparticles, lipoplexes and liposomes. Using this latter approach, hydrophobically derivatized Tf was incorporated to liposomal bilayers. The biological activity of Tf-liposome was tested using MXT-B2 cells, a metastatic mammary carcinoma cell line. In Tf binding assays, the Scatchard analysis indicated 4.5x10(5) Tf receptors/cell. In cell growth assays, Tf-liposomes stimulated cell growth in a dose-dependent manner, up to a maximum of 32% of the total free Tf stimulation. Following this, we prepared Tf-liposomes encapsulating adriamycin (ADR) at two different ADR-to-lipid ratios. In vitro cytotoxicity assays against MXT-B2 cells gave IC(50) values 2.1-times lower for Tf-liposomal ADR in comparison to control liposomal ADR. However, similar IC(50) values were found for low ADR-to-lipid ratio Tf-liposomal ADR, as well as for control liposomal ADR. The free Tf added in excess increased the IC(50) value of Tf-liposomal ADR by 51%, while the IC(50) value of control liposomal ADR was unaffected, supporting a receptor-mediated mechanism of targeting by Tf. In addition, the lower IC(50) value is correlated with a higher total of ADR accumulation in the cells.

The novel highly lipophilic topoisomerase I inhibitor DB67 is effective in the treatment of liver metastases of murine CT-26 colon carcinoma.

Colorectal carcinoma occurs in 1 of 20 individuals in most developed countries. The relapse after resection with metastatic liver disease is a major cause of death. 7-t-Butyldimethylsilyl-10-hydroxycamptothecin (DB67) has been incorporated into liposomes allowing for intravenous (i.v.) administration. A preclinical efficacy study of liposomal DB67 was performed using the colon carcinoma CT-26 cell line. The therapeutic dose for DB67 and liposomal DB67 was found to be 7 mg/kg per day using the qdx5/1 schedule. The results are compared with those obtained with irinotecan. The treatment with liposomal DB67 administered intravenously was more effective in reducing the weight and volume of primary spleen tumors and the weight and extent of liver metastases than free DB67 or liposomal DB67 administered intraperitoneally, but less effective than irinotecan. When the primary tumor was resected, treatment with liposomal DB67 administered intravenously was more effective in reducing the weight and extent of liver metastases than DB67 or liposomal DB67 administered intraperitoneally, and irinotecan. DB67 showed a higher accumulation in spleen and liver after its i.v. administration in liposomal form compared with its free or liposomal form administered intraperitoneally. DB67 and liposomal DB67 are more effective than irinotecan in the treatment of liver metastases after resection of the primary tumor.

[Cystic multilocular nephroma. Report of a case]. / Nefroma multilocular quístico. Presentación de un caso.

We present a new case of multilocular cystic nephroma, and a review of literature. If C.T. diagnoses a cystic disease we apply the Bosniak classification. Multilocular cystic nephroma appears as a cystic disease, separately fibrous thin walls, with or without calcifications. We have to make a distinctive diagnosis between RCC and multilocular. Definitive diagnosis is always histological.