Investigating the impact of visual perspective in a motor imagery-based brain-robot interaction: A pilot study with healthy participants.

Introduction: Motor Imagery (MI)-based Brain Computer Interfaces (BCI) have raised gained attention for their use in rehabilitation therapies since they allow controlling an external device by using brain activity, in this way promoting brain plasticity mechanisms that could lead to motor recovery. Specifically, rehabilitation robotics can provide precision and consistency for movement exercises, while embodied robotics could provide sensory feedback that can help patients improve their motor skills and coordination. However, it is still not clear whether different types of visual feedback may affect the elicited brain response and hence the effectiveness of MI-BCI for rehabilitation. Methods: In this paper, we compare two visual feedback strategies based on controlling the movement of robotic arms through a MI-BCI system: 1) first-person perspective, with visual information that the user receives when they view the robot arms from their own perspective; and 2) third-person perspective, whereby the subjects observe the robot from an external perspective. We studied 10 healthy subjects over three consecutive sessions. The electroencephalographic (EEG) signals were recorded and evaluated in terms of the power of the sensorimotor rhythms, as well as their lateralization, and spatial distribution. Results: Our results show that both feedback perspectives can elicit motor-related brain responses, but without any significant differences between them. Moreover, the evoked responses remained consistent across all sessions, showing no significant differences between the first and the last session. Discussion: Overall, these results suggest that the type of perspective may not influence the brain responses during a MI- BCI task based on a robotic feedback, although, due to the limited sample size, more evidence is required. Finally, this study resulted into the production of 180 labeled MI EEG datasets, publicly available for research purposes.

A machine learning approach for single cell interphase cell cycle staging.

The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in nuclear morphology are also hallmarks of many diseases including cancer. Regrettably, automated reliable tools for cell cycle staging at single cell level using in situ images are still limited. It is therefore urgent to establish accurate strategies combining bioimaging with high-content image analysis for a bona fide classification. In this study we developed a supervised machine learning method for interphase cell cycle staging of individual adherent cells using in situ fluorescence images of nuclei stained with DAPI. A Support Vector Machine (SVM) classifier operated over normalized nuclear features using more than 3500 DAPI stained nuclei. Molecular ground truth labels were obtained by automatic image processing using fluorescent ubiquitination-based cell cycle indicator (Fucci) technology. An average F1-Score of 87.7% was achieved with this framework. Furthermore, the method was validated on distinct cell types reaching recall values higher than 89%. Our method is a robust approach to identify cells in G1 or S/G2 at the individual level, with implications in research and clinical applications.

Hereditary Gastric and Breast Cancer Syndromes Related to CDH1 Germline Mutation: A Multidisciplinary Clinical Review.

E-cadherin (CDH1 gene) germline mutations are associated with the development of diffuse gastric cancer in the context of the so-called hereditary diffuse gastric syndrome, and with an inherited predisposition of lobular breast carcinoma. In 2019, the international gastric cancer linkage consortium revised the clinical criteria and established guidelines for the genetic screening of CDH1 germline syndromes. Nevertheless, the introduction of multigene panel testing in clinical practice has led to an increased identification of E-cadherin mutations in individuals without a positive family history of gastric or breast cancers. This observation motivated us to review and present a novel multidisciplinary clinical approach (nutritional, surgical, and image screening) for single subjects who present germline CDH1 mutations but do not fulfil the classic clinical criteria, namely those identified as-(1) incidental finding and (2) individuals with lobular breast cancer without family history of gastric cancer (GC).

SRC inhibition prevents P-cadherin mediated signaling and function in basal-like breast cancer cells.

BACKGROUND: Basal-like breast cancer (BLBC) is a poor prognosis subgroup of triple-negative carcinomas that still lack specific target therapies and accurate biomarkers for treatment selection. P-cadherin is frequently overexpressed in these tumors, promoting cell invasion, stem cell activity and tumorigenesis by the activation of Src-Family kinase (SRC) signaling. Therefore, our aim was to evaluate if the treatment of BLBC cells with dasatinib, the FDA approved SRC inhibitor, would impact on P-cadherin induced tumor aggressive behavior. METHODS: P-cadherin and SRC expression was evaluated in a series of invasive Breast Cancer and contingency tables and chi-square tests were performed. Cell-cell adhesion measurements were performed by Atomic Force Microscopy, where frequency histograms and Gaussian curves were applied. 2D and 3D cell migration and invasion, proteases secretion and self-renew potential were evaluated in vitro. Student's t-tests were used to determine statistically significant differences. The cadherin/catenin complex interactions were evaluated by in situ proximity-ligation assay, and statistically significant results were determined by using Mann-Whitney test with a Bonferroni correction. In vivo xenograft mouse models were used to evaluate the impact of dasatinib on tumor growth and survival. ANOVA test was used to evaluate the differences in tumor size, considering a confidence interval of 95%. Survival curves were estimated by the Kaplan-Meier's method, using the log-rank test to assess significant differences for mice overall survival. RESULTS: Our data demonstrated that P-cadherin overexpression is significantly associated with SRC activation in breast cancer cells, which was also validated in a large series of primary tumor samples. SRC activity suppression with dasatinib significantly prevented the in vitro functional effects of P-cadherin overexpressing cells, as well as their in vivo tumorigenic and metastatic ability, by increasing mice overall survival. Mechanistically, SRC inhibition affects P-cadherin downstream signaling, rescues the E-cadherin/p120-catenin complex to the cell membrane, recovering cell-cell adhesion function. CONCLUSIONS: In conclusion our findings show that targeting P-cadherin/SRC signaling and functional activity may open novel therapeutic opportunities for highly aggressive and poor prognostic basal-like breast cancer.

Clinical and functional characterization of the CDH1 germline variant c.1679C>G in three unrelated families with hereditary diffuse gastric cancer.

Germline changes in the CDH1 tumor suppressor gene predispose to diffuse gastric cancer and lobular breast cancer. In carriers of deleterious germline CDH1 variants, prophylactic gastrectomy is recommended. In case of germline missense variants, it is mandatory to assess the functional impact on E-cadherin, the protein encoded by CDH1, and to predict their clinical significance. Herein, we have identified a recurrent germline missense variant, c.1679C>G, segregating with gastric cancer in three unrelated Spanish families. Through genetic, transcriptional, in silico and in vitro studies, we demonstrate the deleterious effect of the c.1679C>G variant and its association with hereditary diffuse gastric cancer, providing relevant data to relatives and allowing an accurate genetic counseling.

Targeting the PI3K Signalling as a Therapeutic Strategy in Colorectal Cancer.

Colorectal cancer (CRC) remains one of the leading causes of cancer mortality worldwide. Regarded as a heterogeneous disease, a number of biomarkers have been proposed to help in the stratification of CRC patients and to enable the selection of the best therapy for each patient towards personalized therapy. However, although the molecular mechanisms underlying the development of CRC have been elucidated, the therapeutic strategies available for these patients are still quite limited. Thus, over the last few years, a multitude of novel targets and therapeutic strategies have emerged focusing on deregulated molecules and pathways that are implicated in cell growth and survival. Particularly relevant in CRC are the activating mutations in the oncogene PIK3CA that frequently occur in concomitancy with KRAS and BRAF mutations and that lead to deregulation of the major signalling pathways PI3K and MAPK, downstream of EGFR. This review focus on the importance of the PI3K signalling in CRC development, on the current knowledge of PI3K inhibition as a therapeutic approach in CRC and on the implications PI3K signalling molecules may have as potential biomarkers and as new targets for directed therapies in CRC patients.

Predicting the Functional Impact of CDH1 Missense Mutations in Hereditary Diffuse Gastric Cancer.

The role of E-cadherin in Hereditary Diffuse Gastric Cancer (HDGC) is unequivocal. Germline alterations in its encoding gene (CDH1) are causative of HDGC and occur in about 40% of patients. Importantly, while in most cases CDH1 alterations result in the complete loss of E-cadherin associated with a well-established clinical impact, in about 20% of cases the mutations are of the missense type. The latter are of particular concern in terms of genetic counselling and clinical management, as the effect of the sequence variants in E-cadherin function is not predictable. If a deleterious variant is identified, prophylactic surgery could be recommended. Therefore, over the last few years, intensive research has focused on evaluating the functional consequences of CDH1 missense variants and in assessing E-cadherin pathogenicity. In that context, our group has contributed to better characterize CDH1 germline missense variants and is now considered a worldwide reference centre. In this review, we highlight the state of the art methodologies to categorize CDH1 variants, as neutral or deleterious. This information is subsequently integrated with clinical data for genetic counseling and management of CDH1 variant carriers.

Quantification of topological features in cell meshes to explore E-cadherin dysfunction.

In cancer, defective E-cadherin leads to cell detachment, migration and metastization. Further, alterations mediated by E-cadherin dysfunction affect cell topology and tissue organization. Herein, we propose a novel quantitative approach, based on microscopy images, to analyse abnormal cellular distribution patterns. We generated undirected graphs composed by sets of triangles which accurately reproduce cell positioning and structural organization within each image. Network analysis was developed by exploring triangle geometric features, namely area, edges length and formed angles, as well as their variance, when compared with the respective equilateral triangles. We generated synthetic networks, mimicking the diversity of cell-cell interaction patterns, and evaluated the applicability of the selected metrics to study topological features. Cells expressing wild-type E-cadherin and cancer-related mutants were used to validate our strategy. Specifically, A634V, R749W and P799R cancer-causing mutants present more disorganized spatial distribution when compared with wild-type cells. Moreover, P799R exhibited higher length and angle distortions and abnormal cytoskeletal organization, suggesting the formation of very dynamic and plastic cellular interactions. Hence, topological analysis of cell network diagrams is an effective tool to quantify changes in cell-cell interactions and, importantly, it can be applied to a myriad of processes, namely tissue morphogenesis and cancer.

Blind inpainting using l0 and total variation regularization.

In this paper, we address the problem of image reconstruction with missing pixels or corrupted with impulse noise, when the locations of the corrupted pixels are not known. A logarithmic transformation is applied to convert the multiplication between the image and binary mask into an additive problem. The image and mask terms are then estimated iteratively with total variation regularization applied on the image, and l0 regularization on the mask term which imposes sparseness on the support set of the missing pixels. The resulting alternating minimization scheme simultaneously estimates the image and mask, in the same iterative process. The logarithmic transformation also allows the method to be extended to the Rayleigh multiplicative and Poisson observation models. The method can also be extended to impulse noise removal by relaxing the regularizer from the l0 norm to the l1 norm. Experimental results show that the proposed method can deal with a larger fraction of missing pixels than two phase methods, which first estimate the mask and then reconstruct the image.

Quantification of mutant E-cadherin using bioimaging analysis of in situ fluorescence microscopy. A new approach to CDH1 missense variants.

Missense mutations result in full-length proteins containing an amino acid substitution that can be neutral or deleterious, interfering with the normal conformation, localization, and function of a protein. A striking example is the presence of CDH1 (E-cadherin gene) germline missense variants in hereditary diffuse gastric cancer (HDGC), which represent a clinical burden for genetic counseling and surveillance of mutation carriers and their families. CDH1 missense variants can compromise not only the function of E-cadherin but also its expression pattern. Here, we propose a novel method to characterize E-cadherin signature in order to identify cases with E-cadherin deregulation and functional impairment. The strategy includes a bioimaging pipeline to quantify the expression level and characterize the distribution of the protein from in situ immunofluorescence images. The algorithm computes 1D (dimension intensity) radial and internuclear fluorescence profiles to generate expression outlines and 2D virtual cells representing a typical cell within the populations analyzed. Using this new approach, we verify that cells expressing mutant forms of E-cadherin display fluorescence profiles distinct from those of the wild-type cells. Mutant proteins showed a significantly decrease of fluorescence intensity at the membrane and often abnormal expression peaks in the cytoplasm, reflecting the underlying molecular mechanism of trafficking deregulation. Our results suggest employing this methodology as a complementary approach to evaluate the pathogenicity of E-cadherin missense variants. Moreover, it can be applied to a wide range of proteins and, more importantly, to diseases characterized by aberrant protein expression or trafficking deregulation.

Convex total variation denoising of Poisson fluorescence confocal images with anisotropic filtering.

Fluorescence confocal microscopy (FCM) is now one of the most important tools in biomedicine research. In fact, it makes it possible to accurately study the dynamic processes occurring inside the cell and its nucleus by following the motion of fluorescent molecules over time. Due to the small amount of acquired radiation and the huge optical and electronics amplification, the FCM images are usually corrupted by a severe type of Poisson noise. This noise may be even more damaging when very low intensity incident radiation is used to avoid phototoxicity. In this paper, a Bayesian algorithm is proposed to remove the Poisson intensity dependent noise corrupting the FCM image sequences. The observations are organized in a 3-D tensor where each plane is one of the images acquired along the time of a cell nucleus using the fluorescence loss in photobleaching (FLIP) technique. The method removes simultaneously the noise by considering different spatial and temporal correlations. This is accomplished by using an anisotropic 3-D filter that may be separately tuned in space and in time dimensions. Tests using synthetic and real data are described and presented to illustrate the application of the algorithm. A comparison with several state-of-the-art algorithms is also presented.