Land planarians (Platyhelminthes) also prey on web-building spiders

Although spiders and land planarians constitute diverse groups of terrestrial predators, interactions between them are still unknown. Here, we describe a predatory event of a land planarian (Choeradoplana cf. gladismariae) on a web-building spider (Helvibis longicauda) in the Brazilian Atlantic Forest. The prey was constricted and covered with sticky mucus while remaining on its web trying to protect its egg sac. The event was observed in the middle-end afternoon at ca. 1.80 m height. Our observation broadens the scope of possible natural enemies of web-building spiders and the prey items of land planarians. It also indicates that these organisms can capture and overpower dangerous predatory arthropods, suggesting that even complex three-dimensional sticky webs can be ineffective against the attack of land planarians. Finally, we also show that land planarians can exhibit a flexible foraging strategy, exploiting the environment during the day and at higher heights from the ground. Our observation opens new possibilities involving focal observations and experiments using spiders and land planarians as models in predator-prey research

QuantiDOPA: A Quantification Software for Dopaminergic Neurotransmission SPECT

Quantification of neurotransmission Single-Photon Emission Computed Tomography (SPECT) studies of the dopaminergic system can be used to track, stage and facilitate early diagnosis of the disease. The aim of this study was to implement QuantiDOPA, a semi-automatic quantification software of application in clinical routine to reconstruct and quantify neurotransmission SPECT studies using radioligands which bind the dopamine transporter (DAT). To this end, a workflow oriented framework for the biomedical imaging (GIMIAS) was employed. QuantiDOPA allows the user to perform a semiautomatic quantification of striatal uptake by following three stages: reconstruction, normalization and quantification. QuantiDOPA is a useful tool for semi-automatic quantification inDAT SPECT imaging and it has revealed simple and flexibl

Prone to supine surface-based registration for surgical planning in breast cancer treatment

Breast cancer is the most common invasive cancer in women worldwide. Many women with breast cancer have their malignant tumors detected before the lesions become clinically palpable. Occult lesions must be marked for the surgeon to ensure that they can be effectively resected. Image-guided wire localization (WGL) is the current standard of care for the excision of non-palpable carcinomas during breast conserving surgery. The integration of the information from multimodal imaging may be especially relevant in surgical planning as complement or an alternative to WGL. The combination of information from images in different positions is especially difficult due to large breast deformation. This work presents a system based on surface registration to localize the lesion in the operative position, starting from a prone MRI study and a surface of the patient in the supine positon. The pre-operative surface from the MRI is registered to the surface obtained in a supine position similar to the intraoperative setting. Triangular meshes have been used to model breast surface in both positions and surfaces are aligned using a Laplacian deformation with fiducials automatically obtained from 3 anatomical references. The evaluation of the methodology has been carried out in 13 cases in which a supine- CT was available achieving an average localization error of 6.7 m

A simple method for detecting oncofetal chondroitin sulfate glycosaminoglycans in bladder cancer urine

Proteoglycans in bladder tumors are modified with a distinct oncofetal chondroitin sulfate (ofCS) glycosaminoglycan that is normally restricted to placental trophoblast cells. This ofCS-modification can be detected in bladder tumors by the malarial VAR2CSA protein, which in malaria pathogenesis mediates adherence of parasite-infected erythrocytes within the placenta. In bladder cancer, proteoglycans are constantly shed into the urine, and therefore have the potential to be used for detection of disease. In this study we investigated whether recombinant VAR2CSA (rVAR2) protein could be used to detect ofCS-modified proteoglycans (ofCSPGs) in the urine of bladder cancer patients as an indication of disease presence. We show that ofCSPGs in bladder cancer urine can be immobilized on cationic nitrocellulose membranes and subsequently probed for ofCS content by rVAR2 protein in a custom-made dot-blot assay. Patients with high-grade bladder tumors displayed a marked increase in urinary ofCSPGs as compared to healthy individuals. Urine ofCSPGs decreased significantly after complete tumor resection compared to matched urine collected preoperatively from patients with bladder cancer. Moreover, ofCSPGs in urine correlated with tumor size of bladder cancer patients. These findings demonstrate that rVAR2 can be utilized in a simple biochemical assay to detect cancer-specific ofCS-modifications in the urine of bladder cancer patients, which may be further developed as a noninvasive approach to detect and monitor the disease

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Identification of Common Differentially Expressed Genes in Urinary Bladder Cancer

BACKGROUND: Current diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays. PURPOSE: Our goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays. METHODOLOGY/PRINCIPAL FINDINGS: BC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways. CONCLUSIONS/SIGNIFICANCE: The identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers