Does native Trypanosoma cruzi calreticulin mediate growth inhibition of a mammary tumor during infection?

Indexación: Web of Science.Background: For several decades now an antagonism between Trypanosoma cruzi infection and tumor development has been detected. The molecular basis of this phenomenon remained basically unknown until our proposal that T. cruzi Calreticulin (TcCRT), an endoplasmic reticulum-resident chaperone, translocated-externalized by the parasite, may mediate at least an important part of this effect. Thus, recombinant TcCRT (rTcCRT) has important in vivo antiangiogenic and antitumor activities. However, the relevant question whether the in vivo antitumor effect of T. cruzi infection is indeed mediated by the native chaperone (nTcCRT), remains open. Herein, by using specific modified anti-rTcCRT antibodies (Abs), we have neutralized the antitumor activity of T. cruzi infection and extracts thereof, thus identifying nTcCRT as a valid mediator of this effect. Methods: Polyclonal anti-rTcCRT F(ab')(2) Ab fragments were used to reverse the capacity of rTcCRT to inhibit EAhy926 endothelial cell (EC) proliferation, as detected by BrdU uptake. Using these F(ab')(2) fragments, we also challenged the capacity of nTcCRT, during T. cruzi infection, to inhibit the growth of an aggressive mammary adenocarcinoma cell line (TA3-MTXR) in mice. Moreover, we determined the capacity of anti-rTcCRT Abs to reverse the antitumor effect of an epimastigote extract (EE). Finally, the effects of these treatments on tumor histology were evaluated. Results: The rTcCRT capacity to inhibit ECs proliferation was reversed by anti-rTcCRT F(ab')(2) Ab fragments, thus defining them as valid probes to interfere in vivo with this important TcCRT function. Consequently, during infection, these Ab fragments also reversed the in vivo experimental mammary tumor growth. Moreover, anti-rTcCRT Abs also neutralized the antitumor effect of an EE, again identifying the chaperone protein as an important mediator of this anti mammary tumor effect. Finally, as determined by conventional histological parameters, in infected animals and in those treated with EE, less invasive tumors were observed while, as expected, treatment with F(ab')(2) Ab fragments increased malignancy. Conclusion: We have identified translocated/externalized nTcCRT as responsible for at least an important part of the anti mammary tumor effect of the chaperone observed during experimental infections with T. cruzi.http://bmccancer.biomedcentral.com/articles/10.1186/s12885-016-2764-

Improved vision based pose estimation for industrial robots via sparse regression

In this work amonocular machine vision based pose estimation system is developed for industrial robots and the accuracy of the estimated pose is im-proved via sparse regression. The proposed sparse regressionbased methodis usedimprove the accuracy obtained from the Levenberg-Marquardt (LM) based pose estimation algorithmduring the trajectory tracking of an industrial robot’s end effector. The proposed method utilizes a set of basis functions to sparsely identify the nonlinear relationship between the estimated pose and the true pose provided by a laser tracker.Moreover,a camera target was designed and fitted with fiducial markers,andto prevent ambiguities in pose estimation, the markers are placed in such a way to guarantee the detection of at least two distinct nonparallel markers from a single camera within ± 90° in all directions of the cam-era’s view. The effectiveness of the proposed method is validated by an experi-mental study performed using a KUKA KR240 R2900 ultra robot while follow-ing sixteen distinct trajectories based on ISO 9238. The obtained results show that the proposed method provides parsimonious models which improve the pose estimation accuracy and precision of the vision based system during trajectory tracking of industrial robots' end effector

Leaf Morphology, Taxonomy and Geometric Morphometrics: A Simplified Protocol for Beginners

Taxonomy relies greatly on morphology to discriminate groups. Computerized geometric morphometric methods for quantitative shape analysis measure, test and visualize differences in form in a highly effective, reproducible, accurate and statistically powerful way. Plant leaves are commonly used in taxonomic analyses and are particularly suitable to landmark based geometric morphometrics. However, botanists do not yet seem to have taken advantage of this set of methods in their studies as much as zoologists have done. Using free software and an example dataset from two geographical populations of sessile oak leaves, we describe in detailed but simple terms how to: a) compute size and shape variables using Procrustes methods; b) test measurement error and the main levels of variation (population and trees) using a hierachical design; c) estimate the accuracy of group discrimination; d) repeat this estimate after controlling for the effect of size differences on shape (i.e., allometry). Measurement error was completely negligible; individual variation in leaf morphology was large and differences between trees were generally bigger than within trees; differences between the two geographic populations were small in both size and shape; despite a weak allometric trend, controlling for the effect of size on shape slighly increased discrimination accuracy. Procrustes based methods for the analysis of landmarks were highly efficient in measuring the hierarchical structure of differences in leaves and in revealing very small-scale variation. In taxonomy and many other fields of botany and biology, the application of geometric morphometrics contributes to increase scientific rigour in the description of important aspects of the phenotypic dimension of biodiversity. Easy to follow but detailed step by step example studies can promote a more extensive use of these numerical methods, as they provide an introduction to the discipline which, for many biologists, is less intimidating than the often inaccessible specialistic literature

Superconductivity in Cu_xTiSe_2

Charge density waves (CDWs) are periodic modulations of the conduction electron density in solids. They are collective states that arise from intrinsic instabilities often present in low dimensional electronic systems. The layered dichalcogenides are the most well-studied examples, with TiSe_2 one of the first CDW-bearing materials known. The competition between CDW and superconducting collective electronic states at low temperatures has long been held and explored, and yet no chemical system has been previously reported where finely controlled chemical tuning allows this competition to be studied in detail. Here we report how, upon controlled intercalation of TiSe_2 with Cu to yield Cu_xTiSe_2, the CDW transition is continuously suppressed, and a new superconducting state emerges near x = 0.04, with a maximum T_c of 4.15 K found at x = 0.08. Cu_xTiSe_2 thus provides the first opportunity to study the CDW to Superconductivity transition in detail through an easily-controllable chemical parameter, and will provide new insights into the behavior of correlated electron systems.Comment: Accepted to Nature Physic

A population-based controlled experiment assessing the epidemiological impact of digital contact tracing

While Digital contact tracing (DCT) has been argued to be a valuable complement to manual tracing in the containment of COVID-19, no empirical evidence of its effectiveness is available to date. Here, we report the results of a 4-week population-based controlled experiment that took place in La Gomera (Canary Islands, Spain) between June and July 2020, where we assessed the epidemiological impact of the Spanish DCT app Radar Covid. After a substantial communication campaign, we estimate that at least 33% of the population adopted the technology and further showed relatively high adherence and compliance as well as a quick turnaround time. The app detects about 6.3 close-contacts per primary simulated infection, a significant percentage being contacts with strangers, although the spontaneous follow-up rate of these notified cases is low. Overall, these results provide experimental evidence of the potential usefulness of DCT during an epidemic outbreak in a real population

The "Ram Effect": A "Non-Classical" Mechanism for Inducing LH Surges in Sheep

During spring sheep do not normally ovulate but exposure to a ram can induce ovulation. In some ewes an LH surge is induced immediately after exposure to a ram thus raising questions about the control of this precocious LH surge. Our first aim was to determine the plasma concentrations of oestradiol (E2) E2 in anoestrous ewes before and after the "ram effect" in ewes that had a "precocious" LH surge (starting within 6 hours), a "normal" surge (between 6 and 28h) and "late» surge (not detected by 56h). In another experiment we tested if a small increase in circulating E2 could induce an LH surge in anoestrus ewes. The concentration of E2 significantly was not different at the time of ram introduction among ewes with the three types of LH surge. "Precocious" LH surges were not preceded by a large increase in E2 unlike "normal" surges and small elevations of circulating E2 alone were unable to induce LH surges. These results show that the "precocious" LH surge was not the result of E2 positive feedback. Our second aim was to test if noradrenaline (NA) is involved in the LH response to the "ram effect". Using double labelling for Fos and tyrosine hydroxylase (TH) we showed that exposure of anoestrous ewes to a ram induced a higher density of cells positive for both in the A1 nucleus and the Locus Coeruleus complex compared to unstimulated controls. Finally, the administration by retrodialysis into the preoptic area, of NA increased the proportion of ewes with an LH response to ram odor whereas treatment with the α1 antagonist Prazosin decreased the LH pulse frequency and amplitude induced by a sexually active ram. Collectively these results suggest that in anoestrous ewes NA is involved in ram-induced LH secretion as observed in other induced ovulators

Case-Based Statistical Learning: A Non-Parametric Implementation with a Conditional-Error Rate SVM

© 2013 IEEE. Machine learning has been successfully applied to many areas of science and engineering. Some examples include time series prediction, optical character recognition, signal and image classification in biomedical applications for diagnosis and prognosis and so on. In the theory of semi-supervised learning, we have a training set and an unlabeled data, that are employed to fit a prediction model or learner, with the help of an iterative algorithm, such as the expectation-maximization algorithm. In this paper, a novel non-parametric approach of the so-called case-based statistical learning is proposed in a low-dimensional classification problem. This supervised feature selection scheme analyzes the discrete set of outcomes in the classification problem by hypothesis-testing and makes assumptions on these outcome values to obtain the most likely prediction model at the training stage. A novel prediction model is described in terms of the output scores of a confidence-based support vector machine classifier under class-hypothesis testing. To have a more accurate prediction by considering the unlabeled points, the distribution of unlabeled examples must be relevant for the classification problem. The estimation of the error rates from a well-trained support vector machines allows us to propose a non-parametric approach avoiding the use of Gaussian density function-based models in the likelihood ratio test

Response-adapted treatment with rituximab, bendamustine, mitoxantrone, and dexamethasone followed by rituximab maintenance in patients with relapsed or refractory follicular lymphoma after first-line immunochemotherapy: Results of the RBMDGELTAMO08 phase II trial

Background Consensus is lacking regarding the optimal salvage therapy for patients with follicular lymphoma who relapse after or are refractory to immunochemotherapy. Methods This phase II trial evaluated the efficacy and safety of response-adapted therapy with rituximab, bendamustine, mitoxantrone, and dexamethasone (RBMD) in follicular lymphoma patients who relapsed after or were refractory to first-line immunochemotherapy. Sixty patients received three treatment cycles, and depending on their response received an additional one (complete/unconfirmed complete response) or three (partial response) cycles. Patients who responded to induction received rituximab maintenance therapy for 2 years. Results Thirty-three (55%) and 42 (70%) patients achieved complete/unconfirmed complete response after three cycles and on completing induction therapy (4-6 cycles), respectively (final overall response rate, 88.3%). Median progression-free survival was 56.4 months (median follow-up, 28.3 months; 95% CI, 15.6-51.2). Overall survival was not reached. Progression-free survival did not differ between patients who received four vs six cycles (P = .6665), nor between patients who did/did not receive rituximab maintenance after first-line therapy (P = .5790). Median progression-free survival in the 10 refractory patients was 25.5 months (95% CI, 0.6-N/A) and was longer in patients who had shown progression of disease after 24 months of first-line therapy (median, 56.4 months; 95% CI, 19.8-56.4) than in those who showed early progression (median, 42.31 months; 95% CI, 24.41-NA) (P = .4258). Thirty-six (60%) patients had grade 3/4 neutropenia. Grade 3/4 febrile neutropenia and infection were recorded during induction (4/60 [6.7%] and 5/60 [8.3%] patients, respectively) and maintenance (2/43 [4.5%] and 4/43 [9.1%] patients, respectively). Conclusions This response-adapted treatment with RBMD followed by rituximab maintenance is an effective and well-tolerated salvage treatment for relapsed/refractory follicular lymphoma following first-line immunochemotherapy