Validation study of existing gene expression signatures for anti-TNF treatment in patients with rheumatoid arthritis

So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response.     

Inertial motion capture in conjunction with an artificial neural network can differentiate the gait patterns of hemiparetic stroke patients compared with able-bodied counterparts

Clinical gait analysis has proven to reduce uncertainties in selecting the appropriate quantity and type of treatment for patients with neuromuscular disorders. However, gait analysis as a clinical tool is under-utilised due to the limitations and cost of acquiring and managing data. To overcome these obstacles, inertial motion capture (IMC) recently emerged to counter the limitations attributed to other methods. This paper investigates the use of IMC for training and testing a back-propagation artificial neural network (ANN) for the purpose of distinguishing between hemiparetic stroke and able-bodied ambulation. Routine gait analysis was performed on 30 able-bodied control subjects and 28 hemiparetic stroke patients using an IMC system. An ANN was optimised to classify the two groups, achieving a repeatable network accuracy of 99.4%. It is concluded that an IMC system and appropriate computer methods may be useful for the planning and monitoring of gait rehabilitation therapy of stroke victims.     

Towards a novel monitor of intraoperative awareness: selecting paradigm settings for a movement-based brain-computer interface

During 0.1-0.2% of operations with general anesthesia, patients become aware during surgery. Unfortunately, pharmacologically paralyzed patients cannot seek attention by moving. Their attempted movements may however induce detectable EEG changes over the motor cortex. Here, methods from the area of movement-based brain-computer interfacing are proposed as a novel direction in anesthesia monitoring. Optimal settings for development of such a paradigm are studied to allow for a clinically feasible system. A classifier was trained on recorded EEG data of ten healthy non-anesthetized participants executing 3-second movement tasks. Extensive analysis was performed on this data to obtain an optimal EEG channel set and optimal features for use in a movement detection paradigm. EEG during movement could be distinguished from EEG during non-movement with very high accuracy. After a short calibration session, an average classification rate of 92% was obtained using nine EEG channels over the motor cortex, combined movement and post-movement signals, a frequency resolution of 4 Hz and a frequency range of 8-24 Hz. Using Monte Carlo simulation and a simple decision making paradigm, this translated into a probability of 99% of true positive movement detection within the first two and a half minutes after movement onset. A very low mean false positive rate of <0.01% was obtained. The current results corroborate the feasibility of detecting movement-related EEG signals, bearing in mind the clinical demands for use during surgery. Based on these results further clinical testing can be initiated.     

Selective activation of p120ctn-Kaiso signaling to unlock contact inhibition of ARPE-19 cells without epithelial-mesenchymal transition

Contact-inhibition ubiquitously exists in non-transformed cells and explains the poor regenerative capacity of in vivo human retinal pigment epithelial cells (RPE) during aging, injury and diseases. RPE injury or degeneration may unlock mitotic block mediated by contact inhibition but may also promote epithelial-mesenchymal transition (EMT) contributing to retinal blindness. Herein, we confirmed that EMT ensued in post-confluent ARPE-19 cells when contact inhibition was disrupted with EGTA followed by addition of EGF and FGF-2 because of activation of canonical Wnt and Smad/ZEB signaling. In contrast, knockdown of p120-catenin (p120) unlocked such mitotic block by activating p120/Kaiso, but not activating canonical Wnt and Smad/ZEB signaling, thus avoiding EMT. Nuclear BrdU labeling was correlated with nuclear release of Kaiso through p120 nuclear translocation, which was associated with activation of RhoA-ROCK signaling, destabilization of microtubules. Prolonged p120 siRNA knockdown followed by withdrawal further expanded RPE into more compact monolayers with a normal phenotype and a higher density. This new strategy based on selective activation of p120/Kaiso but not Wnt/β-catenin signaling obviates the need of using single cells and the risk of EMT, and may be deployed to engineer surgical grafts containing RPE and other tissues.     

Nitrogen stress induction on <Emphasis Type="Italic">Levisticum officinale</Emphasis> hairy roots grown in darkness and under photoperiod conditions: effect on growth and volatile components

Six-year-old Levisticum officinale (lovage) hairy root cultures were used to study the effect of eight different NH(4) (+):NO(3) (-) ratios on their growth and volatile components. All cultures were kept at 24 degrees C on orbital shakers at 80 rpm, in darkness or in a 16 h light/8 h dark photoperiod. Growth was evaluated by dry and fresh weight determination. The volatiles were isolated by distillation-extraction and analysed by GC and GC-MS. Greater growth was attained in darkness with 10:90 (control, SH medium), 50:50 and 25:75 NH(4) (+):NO(3) (-) ratios, and also with SH control medium under the photoperiod condition, with a 10, 14, 12.5 and 12.5 fold increase of biomass in terms of dry weight, respectively, at the end of 42 days of growth. UPGMA cluster analysis of the mixtures of volatiles isolated from the hairy roots grown with different NH(4) (+):NO(3) (-) ratios confirmed their chemical variability. Although no particular grouping was detected in relation to the NH(4) (+):NO(3) (-) ratios or light conditions studied, most of the mixtures of volatiles isolated from the hairy roots were either dominated by n-octanal, (Z)-falcarinol or both components in about the same relative amounts.     

Polymerase chain reaction-restriction fragment-length polymorphism method to distinguish Liriomyza huidobrensis from L. Langei (Diptera: Agromyzidae) applied to three recent leafminer invasions.

A molecular method is presented for differentiating the morphologically cryptic leafminers Liriomyza langei Frick and L. huidobrensis (Blanchard). This method requires polymerase chain reaction (PCR) amplification of a 1031-bp region of mitochondrial cytochrome oxidase DNA followed by restriction fragment analysis using the restriction enzymes SpeI and EcoRV. Spel cuts the mitochondrial fragment of L. langei into two fragments, but does not cut the L. huidobrensis fragment. EcoRV cuts the L. huidobrensis fragment into two fragments, but does not cut the L. langei fragment. This PCR-restriction fragment-length polymorphism (RFLP) method is faster and less costly than DNA sequencing,which is currently the only other way to differentiate these two species. We apply the method to samples from recently introduced leafminer populations in Sri Lanka, Canada, and South Africa and find that the invasive leafminer in all three locations is L. huidobrensis.     

Detection of the Mr 110,000 lung resistance-related protein LRP/MVP with monoclonal antibodies.

The Mr 110,000 lung resistance-related protein (LRP), also termed the major vault protein (MVP), constitutes >70% of subcellular ribonucleoprotein particles called vaults. Overexpression of LRP/MVP and vaults has been linked directly to MDR in cancer cells. Clinically, LRP/MVP expression can be of value to predict response to chemotherapy and prognosis. Monoclonal antibodies (MAbs) against LRP/MVP have played a critical role in determining the relevance of this protein in clinical drug resistance. We compared the applicability of the previously described MAbs LRP-56, LMR-5, LRP, 1027, 1032, and newly isolated MAbs MVP-9, MVP-16, MVP-18, and MVP-37 for the immunodetection of LRP/MVP by immunoblotting analysis and by immunocyto- and histochemistry. The availability of a broader panel of reagents for the specific and sensitive immunodetection of LRP/MVP should greatly facilitate biological and clinical studies of vault-related MDR.