Overcoming brain-derived therapeutic resistance in HER2+ breast cancer brain metastasis.

Brain metastasis of HER2+ breast cancer occurs in about 50% of all women with metastatic HER2+ breast cancer and confers poor prognosis for patients. Despite effective HER2-targeted treatments of peripheral HER2+ breast cancer with Trastuzumab +/-HER2 inhibitors, limited brain permeability renders these treatments inefficient for HER2+ breast cancer brain metastasis (BCBM). The scarcity of suitable patient-derived in-vivo models for HER2+ BCBM has compromised the study of molecular mechanisms that promote growth and therapeutic resistance in brain metastasis. We have generated and characterized new HER2+ BCBM cells (BCBM94) isolated from a patient HER2+ brain metastasis. Repeated hematogenic xenografting of BCBM94 consistently generated BCBM in mice. The clinically used receptor tyrosine kinase inhibitor (RTKi) Lapatinib blocked phosphorylation of all ErbB1-4 receptors and induced the intrinsic apoptosis pathway in BCBM94. Neuregulin-1 (NRG1), a ligand for ErbB3 and ErbB4 that is abundantly expressed in the brain, was able to rescue Lapatinib-induced apoptosis and clonogenic ability in BCBM94 and in HER2+ BT474. ErbB3 was essential to mediate the NRG1-induced survival pathway that involved PI3K-AKT signalling and the phosphorylation of BAD at serine 136 to prevent apoptosis. High throughput RTKi screening identified the brain penetrable Poziotinib as highly potent compound to reduce cell viability in HER2+ BCBM in the presence of NRG1. Successful in-vivo ablation of BCBM94- and BT474-derived HER2+ brain tumors was achieved upon two weeks of treatment with Poziotinib. MRI revealed BCBM remission upon poziotinib, but not with Lapatinib treatment. In conclusion, we have established a new patient-derived HER2+ BCBM in-vivo model and identified Poziotinib as highly efficacious RTKi with excellent brain penetrability that abrogated HER2+ BCBM brain tumors in our mouse models.

Activation of mitochondrial TRAP1 stimulates mitochondria-lysosome crosstalk and correction of lysosomal dysfunction.

Numerous studies have established the involvement of lysosomal and mitochondrial dysfunction in the pathogenesis of neurodegenerative disorders such as Alzheimer's and Parkinson diseases. Building on our previous studies of the neurodegenerative lysosomal lipidosis Niemann-Pick C1 (NPC1), we have unexpectedly discovered that activation of the mitochondrial chaperone tumor necrosis factor receptor-associated protein 1 (TRAP1) leads to the correction of the lysosomal storage phenotype in patient cells from multiple lysosomal storage disorders including NPC1. Using small compound activators specific for TRAP1, we find that activation of this chaperone leads to a generalized restoration of lysosomal and mitochondrial health. Mechanistically, we show that this process includes inhibition of oxidative phosphorylation and reduction of oxidative stress, which results in activation of AMPK and ultimately stimulates lysosome recycling. Thus, TRAP1 participates in lysosomal-mitochondrial crosstalk to maintain cellular homeostasis and could represent a potential therapeutic target for multiple disorders.

Evaluation of an Artificial Intelligence web-based software to detect and classify dental structures and treatments in panoramic radiographs.

OBJECTIVES: To evaluate the diagnostic reliability of a web-based Artificial Intelligence program on the detection and classification of dental structures and treatments present on panoramic radiographs. METHODS: A total of 300 orthopantomographies (OPG) were randomly selected for this study. First, the images were visually evaluated by two calibrated operators with radiodiagnosis experience that, after consensus, established the "ground truth". Operators' findings on the radiographs were collected and classified as follows: metal restorations (MR), resin-based restorations (RR), endodontic treatment (ET), Crowns (C) and Implants (I). The orthopantomographies were then anonymously uploaded and automatically analyzed by the web-based software (Denti.Ai). Results were then stored, and a statistical analysis was performed by comparing them with the ground truth in terms of Sensitivity (S), Specificity (E), Positive Predictive Value (PPV) Negative Predictive Value (NPV) and its later representation in the area under (AUC) the Receiver Operating Characteristic (ROC) Curve. RESULTS: Diagnostic metrics obtained for each study variable were as follows: (MR) S=85.48%, E=87.50%, PPV=82.8%, NPV=42.51%, AUC=0.869; (PR) S=41.11%, E=93.30%, PPV=90.24%, NPV=87.50%, AUC=0.672; (ET) S=91.9%, E=100%, PPV=100%, NPV=94.62%, AUC=0.960; (C) S=89.53%, E=95.79%, PPV=89.53%, NPV=95.79%, AUC=0.927; (I) S, E, PPV, NPV=100%, AUC=1.000. CONCLUSIONS: Findings suggest that the web-based Artificial intelligence software provides a good performance on the detection of implants, crowns, metal fillings and endodontic treatments, not being so accurate on the classification of dental structures or resin-based restorations. CLINICAL SIGNIFICANCE: General diagnostic and treatment decisions using orthopantomographies can be improved by using web-based artificial intelligence tools, avoiding subjectivity and lapses from the clinician.

Suitability of Sustainable Agricultural Drainage Systems for adapting agriculture to climate change.

This paper presents a comprehensive and practical method for Sustainable Agricultural Drainage Systems (SADS) design. It is aimed at studying the suitability of using surface runoff as irrigation source. The method determines the optimum amount of surface runoff to be used for irrigation considering both environmental constraints (aquifers recharge, discharge to natural water courses) and investment and operation costs. The developed method has been applied to the Spanish irrigation district "Villalar de los Comuneros Sector 1" located in Valladolid. The estimation of the optimum SADS provision was calculated for most of the major crops at the irrigation district highlighting that SADS facilities can reduce the amount of external provision of water for irrigation while maintaining the aquifer's recharge and the natural discharge to water courses. The simulations run for climate change forecasting scenarios (Representative Concentration Pathways, RCP, RCP45, RCP60, RCP85) showed that optimum SADS would reduce irrigation requirements and would increase natural fluxes (both aquifers and natural water courses) therefore improving the general water cycle in rural environments with productive agriculture.

A deep learning approach using synthetic images for segmenting and estimating 3D orientation of nanoparticles in EM images.

BACKGROUND AND OBJECTIVE: Nanoparticles present properties that can be applied to a wide range of fields such as biomedicine, electronics or optics. The type of properties depends on several characteristics, being some of them related with the particle structure. A proper characterization of nanoparticles is crucial since it could affect their applications. To characterize a particle shape and size, the nanotechnologists employ Electron Microscopy (EM) to obtain images of nanoparticles and perform measures over them. This task could be tedious, repetitive and slow, we present a Deep Learning method based on Convolutional Neural Networks (CNNs) to detect, segment, infer orientations and reconstruct microscope images of nanoparticles. Since machine learning algorithms depend on annotated data and there is a lack of annotated datasets of nanoparticles, our work makes use of artificial datasets of images resembling real nanoparticles photographs. METHODS: Our work is divided into three tasks. Firstly, a method to create annotated datasets of artificial images resembling Scanning Electron Microscope (SEM). Secondly, two models of convolutional neural networks are trained using the artificial datasets previously generated, the first one is in charge of the detection and segmentation of the nanoparticles while the second one will infer the nanoparticle orientation. Finally, the 3D reconstruction module will recreate in a 3D scene the set of detected particles. RESULTS: We have tested our method with five different shapes of basic nanoparticles: spheres, cubes, ellipsoids, hexagonal discs and octahedrons. An analysis of the reconstructions was conducted by manually comparing each of them with the real images. The results obtained have been promising, the particles are segmented and reconstructed accordingly to their shapes and orientations. CONCLUSIONS: We have developed a method for nanoparticle detection and segmentation in microscope images. Moreover, we can also infer an approximation of the 3D orientation of the particles and, in conjunction with the detections, create a 3D reconstruction of the photographs. The novelty of our approximation lies in the dataset used. Instead of using annotated images, we have created the datasets simulating the microscope images by using basic geometrical objects that imitate real nanoparticles.

Enhancing vessel visibility in fundus images to aid the diagnosis of retinopathy of prematurity.

Retinopathy of prematurity is a disease that can affect premature or in similar conditions babies. For diagnosing of retinopathy of prematurity, the infant is examined as soon as possible. Due to the nature of the examination, the images obtained are poor in quality. This article presents an automated method for processing fundus images to improve the visibility of the vascular network. The method includes several processing tasks whose parameters are predicted using an artificial neural network. A set of 88 clinical images were used in this work. The performance of our proposal is efficient, and the average processing time was 42 ms. The method was assessed using both the contrast improvement index and expert opinions. The contrast improvement index average was 2; this means the processed image successfully improved its contrast. Three pediatric ophthalmologists validated the proposed method and agreed that the visual enhancement can help observe clearly the retinal vessels.

Small-molecule activation of lysosomal TRP channels ameliorates Duchenne muscular dystrophy in mouse models.

Duchenne muscular dystrophy (DMD) is a devastating disease caused by mutations in dystrophin that compromise sarcolemma integrity. Currently, there is no treatment for DMD. Mutations in transient receptor potential mucolipin 1 (ML1), a lysosomal Ca2+ channel required for lysosomal exocytosis, produce a DMD-like phenotype. Here, we show that transgenic overexpression or pharmacological activation of ML1 in vivo facilitates sarcolemma repair and alleviates the dystrophic phenotypes in both skeletal and cardiac muscles of mdx mice (a mouse model of DMD). Hallmark dystrophic features of DMD, including myofiber necrosis, central nucleation, fibrosis, elevated serum creatine kinase levels, reduced muscle force, impaired motor ability, and dilated cardiomyopathies, were all ameliorated by increasing ML1 activity. ML1-dependent activation of transcription factor EB (TFEB) corrects lysosomal insufficiency to diminish muscle damage. Hence, targeting lysosomal Ca2+ channels may represent a promising approach to treat DMD and related muscle diseases.

Mannose receptor (CD206) activation in tumor-associated macrophages enhances adaptive and innate antitumor immune responses.

Solid tumors elicit a detectable immune response including the infiltration of tumor-associated macrophages (TAMs). Unfortunately, this immune response is co-opted into contributing toward tumor growth instead of preventing its progression. We seek to reestablish an antitumor immune response by selectively targeting surface receptors and endogenous signaling processes of the macrophage subtypes driving cancer progression. RP-182 is a synthetic 10-mer amphipathic analog of host defense peptides that selectively induces a conformational switch of the mannose receptor CD206 expressed on TAMs displaying an M2-like phenotype. RP-182-mediated activation of this receptor in human and murine M2-like macrophages elicits a program of endocytosis, phagosome-lysosome formation, and autophagy and reprograms M2-like TAMs to an antitumor M1-like phenotype. In syngeneic and autochthonous murine cancer models, RP-182 suppressed tumor growth, extended survival, and was an effective combination partner with chemo- or immune checkpoint therapy. Antitumor activity of RP-182 was also observed in CD206high patient-derived xenotransplantation models. Mechanistically, via selective reduction of immunosuppressive M2-like TAMs, RP-182 improved adaptive and innate antitumor immune responses, including increased cancer cell phagocytosis by reprogrammed TAMs.

Agonist-specific voltage-dependent gating of lysosomal two-pore Na+ channels.

Mammalian two-pore-channels (TPC1, 2; TPCN1, TPCN2) are ubiquitously- expressed, PI(3,5)P2-activated, Na+-selective channels in the endosomes and lysosomes that regulate luminal pH homeostasis, membrane trafficking, and Ebola viral infection. Whereas the channel activity of TPC1 is strongly dependent on membrane voltage, TPC2 lacks such voltage dependence despite the presence of the presumed 'S4 voltage-sensing' domains. By performing high-throughput screening followed by lysosomal electrophysiology, here we identified a class of tricyclic anti-depressants (TCAs) as small-molecule agonists of TPC channels. TCAs activate both TPC1 and TPC2 in a voltage-dependent manner, referred to as Lysosomal Na+ channel Voltage-dependent Activators (LyNa-VAs). We also identified another compound which, like PI(3,5)P2, activates TPC2 independent of voltage, suggesting the existence of agonist-specific gating mechanisms. Our identification of small-molecule TPC agonists should facilitate the studies of the cell biological roles of TPCs and can also readily explain the reported effects of TCAs in the modulation of autophagy and lysosomal functions.

genoDraw: A Web Tool for Developing Pedigree Diagrams Using the Standardized Human Pedigree Nomenclature Integrated with Biomedical Vocabularies.

The integration of genetic information in current clinical routine has raised a need for tools to exploit family genetic knowledge. On the clinical side, an application for managing and visualizing pedigree diagrams could provide genetics specialists with an integrated environment with potential positive impact on their current practice. This article presents a web tool (genoDraw) that provides clinical practitioners with the ability to create, maintain and visualize patients' and their families' information in the form of pedigree diagrams. genoDraw implements a graph-based three-step process for generating diagrams according to a de facto standard in the area and clinical terminologies. It also complies with five characteristics identified as indispensable for the next-generation of pedigree drawing software: comprehensiveness, data-drivenness, automation, interactivity and compatibility with biomedical vocabularies. The platform was implemented and tested, confirming its potential interest to clinical routine.

Measuring Relevant Information in Health Social Network Conversations and Clinical Diagnosis Cases.

The Internet and social media is an enormous source of information. Health social networks and online collaborative environments enable users to create shared content that afterwards can be discussed. The aim of this paper is to present a novel methodology designed for quantifying relevant information provided by different participants in clinical online discussions. The main goal of the methodology is to facilitate the comparison of participant interactions in clinical conversations. A set of key indicators for different aspects of clinical conversations and specific clinical contributions within a discussion have been defined. Particularly, three new indicators have been proposed to make use of biomedical knowledge extraction based on standard terminologies and ontologies. These indicators allow measuring the relevance of information of each participant of the clinical conversation. Proposed indicators have been applied to one discussion extracted from PatientsLikeMe, as well as to two real clinical cases from the Sanar collaborative discussion system. Results obtained from indicators in the tested cases have been compared with clinical expert opinions to check indicators validity. The methodology has been successfully used for describing participant interactions in real clinical cases belonging to a collaborative clinical case discussion tool and from a conversation from a health social network. This work can be applied to assess collaborative diagnoses, discussions among patients, and the participation of students in clinical case discussions. It permits moderators and educators to obtain a quantitatively measure of the contribution of each participant.

Graphics Processing Unit-Enhanced Genetic Algorithms for Solving the Temporal Dynamics of Gene Regulatory Networks.

Understanding the regulation of gene expression is one of the key problems in current biology. A promising method for that purpose is the determination of the temporal dynamics between known initial and ending network states, by using simple acting rules. The huge amount of rule combinations and the nonlinear inherent nature of the problem make genetic algorithms an excellent candidate for finding optimal solutions. As this is a computationally intensive problem that needs long runtimes in conventional architectures for realistic network sizes, it is fundamental to accelerate this task. In this article, we study how to develop efficient parallel implementations of this method for the fine-grained parallel architecture of graphics processing units (GPUs) using the compute unified device architecture (CUDA) platform. An exhaustive and methodical study of various parallel genetic algorithm schemes-master-slave, island, cellular, and hybrid models, and various individual selection methods (roulette, elitist)-is carried out for this problem. Several procedures that optimize the use of the GPU's resources are presented. We conclude that the implementation that produces better results (both from the performance and the genetic algorithm fitness perspectives) is simulating a few thousands of individuals grouped in a few islands using elitist selection. This model comprises 2 mighty factors for discovering the best solutions: finding good individuals in a short number of generations, and introducing genetic diversity via a relatively frequent and numerous migration. As a result, we have even found the optimal solution for the analyzed gene regulatory network (GRN). In addition, a comparative study of the performance obtained by the different parallel implementations on GPU versus a sequential application on CPU is carried out. In our tests, a multifold speedup was obtained for our optimized parallel implementation of the method on medium class GPU over an equivalent sequential single-core implementation running on a recent Intel i7 CPU. This work can provide useful guidance to researchers in biology, medicine, or bioinformatics in how to take advantage of the parallelization on massively parallel devices and GPUs to apply novel metaheuristic algorithms powered by nature for real-world applications (like the method to solve the temporal dynamics of GRNs).

The Place of Transanal Endoscopic Surgery in the Treatment of Rectourethral Fistula.

OBJECTIVE: To assess the role of transanal endoscopic operation (TEO) or transanal endoscopic microsurgery (TEM) in rectourethral fistulas (RUF). RUF may appear after radical prostatectomy. Their treatment represents a challenge; many therapies have been proposed, from conservative to aggressive surgical approaches. Transanal endoscopic surgery (TEO or TEM) is a minimally invasive technique to access the site of the RUF to perform repair. MATERIALS AND METHODS: This is an observational study with prospective data collection, conducted between September 2006 and December 2015. All patients were diagnosed with RUF following management of prostate cancer. Conservative treatment was administered in the form of urinary and fecal diversion with cystotomy and terminal colostomy, to achieve total urinary and fecal exclusion. If the fistula persisted, it was treated by TEO or TEM, with or without biological mesh interposition. If this failed, gracilis muscle was applied as salvage therapy. RESULTS: Ten patients were diagnosed with RUF. In 1 patient (1 of 10), the fistula healed with bladder catheterization alone. In another patient (1 of 9), it resolved after total urinary and fecal exclusion. Eight patients underwent repair by TEO or TEM, 4 with biological mesh interposition; all 4 presented recurrence. In the other 4 patients treated via TEO or TEM, 2 had early recurrence, whereas the others had healed at follow-up visits after 4-6 months (2 of 8)-a success rate of 25%. The 6 patients who recurred were treated with gracilis muscle interposition via a transperineal approach. CONCLUSION: The low rate of positive results obtained by TEO or TEM argues against its use as technique of choice in RUF, and against the use of biological meshes.

Querying clinical data in HL7 RIM based relational model with morph-RDB.

BACKGROUND: Semantic interoperability is essential when carrying out post-genomic clinical trials where several institutions collaborate, since researchers and developers need to have an integrated view and access to heterogeneous data sources. One possible approach to accommodate this need is to use RDB2RDF systems that provide RDF datasets as the unified view. These RDF datasets may be materialized and stored in a triple store, or transformed into RDF in real time, as virtual RDF data sources. Our previous efforts involved materialized RDF datasets, hence losing data freshness. RESULTS: In this paper we present a solution that uses an ontology based on the HL7 v3 Reference Information Model and a set of R2RML mappings that relate this ontology to an underlying relational database implementation, and where morph-RDB is used to expose a virtual, non-materialized SPARQL endpoint over the data. CONCLUSIONS: By applying a set of optimization techniques on the SPARQL-to-SQL query translation algorithm, we can now issue SPARQL queries to the underlying relational data with generally acceptable performance.

A semantic interoperability approach to support integration of gene expression and clinical data in breast cancer.

INTRODUCTION: The introduction of omics data and advances in technologies involved in clinical treatment has led to a broad range of approaches to represent clinical information. Within this context, patient stratification across health institutions due to omic profiling presents a complex scenario to carry out multi-center clinical trials. METHODS: This paper presents a standards-based approach to ensure semantic integration required to facilitate the analysis of clinico-genomic clinical trials. To ensure interoperability across different institutions, we have developed a Semantic Interoperability Layer (SIL) to facilitate homogeneous access to clinical and genetic information, based on different well-established biomedical standards and following International Health (IHE) recommendations. RESULTS: The SIL has shown suitability for integrating biomedical knowledge and technologies to match the latest clinical advances in healthcare and the use of genomic information. This genomic data integration in the SIL has been tested with a diagnostic classifier tool that takes advantage of harmonized multi-center clinico-genomic data for training statistical predictive models. CONCLUSIONS: The SIL has been adopted in national and international research initiatives, such as the EURECA-EU research project and the CIMED collaborative Spanish project, where the proposed solution has been applied and evaluated by clinical experts focused on clinico-genomic studies.

Gastric Acid Secretion from Parietal Cells Is Mediated by a Ca2+ Efflux Channel in the Tubulovesicle.

Gastric acid secretion by parietal cells requires trafficking and exocytosis of H/K-ATPase-rich tubulovesicles (TVs) toward apical membranes in response to histamine stimulation via cyclic AMP elevation. Here, we found that TRPML1 (ML1), a protein that is mutated in type IV mucolipidosis (ML-IV), is a tubulovesicular channel essential for TV exocytosis and acid secretion. Whereas ML-IV patients are reportedly achlorhydric, transgenic overexpression of ML1 in mouse parietal cells induced constitutive acid secretion. Gastric acid secretion was blocked and stimulated by ML1 inhibitors and agonists, respectively. Organelle-targeted Ca2+ imaging and direct patch-clamping of apical vacuolar membranes revealed that ML1 mediates a PKA-activated conductance on TV membranes that is required for histamine-induced Ca2+ release from TV stores. Hence, we demonstrated that ML1, acting as a Ca2+ channel in TVs, links transmitter-initiated cyclic nucleotide signaling with Ca2+-dependent TV exocytosis in parietal cells, providing a regulatory mechanism that could be targeted to manage acid-related gastric diseases.

Enhancing Collaborative Case Diagnoses Through Unified Medical Language System-Based Disambiguation: A Case Study of the Zika Virus.

BACKGROUND: During clinical case diagnoses, especially in low-resourced areas, the use of vocabularies within Unified Medical Language System (UMLS) can strengthen discussions between health professionals and, in certain cases, eliminate the need, enabling faster treatment. INTRODUCTION: This article presents the benefits of using UMLS as a collaborative discussion tool and verifies its impact. MATERIALS AND METHODS: The Sanar system has been improved by UMLS when using text retrieval to extract relevant medical concepts from cases investigated by the user and to provide contextualized searches of related articles. An experiment was conducted, focused on team engagement and discussion of a Zika virus case using Sanar, both with and without UMLS contextualization. RESULTS: The use of the tool was measured, and it was determined that the discussion in the group with UMLS support was more complete based on better information and inclusion of more variables. Clinicians involved responded to a questionnaire evaluating the relevance of functions. DISCUSSION: From the questionnaire showed that most of the group supported UMLS as important in complex diagnostics; the use of knowledge extraction before discussion is relevant to align knowledge of participants with more variables, such as the Zika virus, and to minimize the need for interaction in widely discussed cases. CONCLUSIONS: Based on the results obtained with the questionnaire, the use of UMLS provides acceleration in the diagnostic process that precedes interaction with other health professionals through clinical discussion tools. For future work, a mobile version will support offline navigation for locations with limited Internet access.

Cohort Selection and Management Application Leveraging Standards-based Semantic Interoperability and a Groovy DSL.

This paper describes a new Cohort Selection application implemented to support streamlining the definition phase of multi-centric clinical research in oncology. Our approach aims at both ease of use and precision in defining the selection filters expressing the characteristics of the desired population. The application leverages our standards-based Semantic Interoperability Solution and a Groovy DSL to provide high expressiveness in the definition of filters and flexibility in their composition into complex selection graphs including splits and merges. Widely-adopted ontologies such as SNOMED-CT are used to represent the semantics of the data and to express concepts in the application filters, facilitating data sharing and collaboration on joint research questions in large communities of clinical users. The application supports patient data exploration and efficient collaboration in multi-site, heterogeneous and distributed data environments.

MCOLN1 is a ROS sensor in lysosomes that regulates autophagy.

Cellular stresses trigger autophagy to remove damaged macromolecules and organelles. Lysosomes 'host' multiple stress-sensing mechanisms that trigger the coordinated biogenesis of autophagosomes and lysosomes. For example, transcription factor (TF)EB, which regulates autophagy and lysosome biogenesis, is activated following the inhibition of mTOR, a lysosome-localized nutrient sensor. Here we show that reactive oxygen species (ROS) activate TFEB via a lysosomal Ca(2+)-dependent mechanism independent of mTOR. Exogenous oxidants or increasing mitochondrial ROS levels directly and specifically activate lysosomal TRPML1 channels, inducing lysosomal Ca(2+) release. This activation triggers calcineurin-dependent TFEB-nuclear translocation, autophagy induction and lysosome biogenesis. When TRPML1 is genetically inactivated or pharmacologically inhibited, clearance of damaged mitochondria and removal of excess ROS are blocked. Furthermore, TRPML1's ROS sensitivity is specifically required for lysosome adaptation to mitochondrial damage. Hence, TRPML1 is a ROS sensor localized on the lysosomal membrane that orchestrates an autophagy-dependent negative-feedback programme to mitigate oxidative stress in the cell.