TMED11P expression associates with survival in triple negative breast cancer.

We mined published microarray data (1) to understand the most significant gene expression differences in the tumors of triple negative breast cancer patients based on survival following treatment: dead or alive. We observed significant transcriptome-wide differential expression of transmembrane emp24 protein transport domain containing 11, pseudogene, encoded by TMED11P when comparing the primary tumors of triple negative breast cancer patients dead or alive. TMED11P may be of relevance as a biomarker or as a molecule of interest in understanding the etiology or progression of triple negative breast cancer.

Rewiring phospholipid biosynthesis reveals robustness in membrane homeostasis and uncovers lipid regulatory players.

Intracellular transport of lipids by Lipid Transport Proteins (LTPs) is thought to work alongside vesicular transport to shuttle lipids from their place of synthesis to their destinations. Whereas many LTPs have been identified, it is largely unknown which routes and which LTPs a given lipid utilizes to navigate the multiple membranes of eukaryotic cells. The major and essential phospholipids, phosphatidylethanolamine (PE) and phosphatidylcholine (PC) can be produced by multiple pathways and, in the case of PE, also at multiple locations. Here, we present an approach in which we simplify and rewire yeast phospholipid synthesis by redirecting PE and PC synthesis reactions to distinct subcellular locations using chimeric enzymes fused to specific organelle targeting motifs. In rewired conditions, viability is expected to depend on homeostatic adaptation to the ensuing lipostatic perturbations and on efficient interorganelle lipid transport. We therefore performed genetic screens to identify factors involved in both of these processes. Among the candidates identified, we find genes linked to transcriptional regulation of lipid homeostasis, lipid metabolism and transport. In particular, we identify a requirement for Csf1 -an uncharacterized protein harboring a Chorein-N lipid transport domain- for survival under certain rewired conditions as well as lipidomic adaptation to cold, implicating Csf1 in interorganelle lipid transport and homeostatic adaptation.

Single Cell Transcriptomics Trajectory and Molecular Convergence of Clinically Relevant Mutations in Brugada Syndrome

Brugada syndrome (BrS) is a rare, inherited arrhythmia with high risk of sudden cardiac death. To evaluate the molecular convergence of clinically relevant mutations and to identify developmental cardiac cell types that are associated with BrS etiology, we collected 733 mutations represented by 16 sodium, calcium, potassium channels, regulatory and structural genes related to BrS. Among the clinically relevant mutations, 266 are unique singletons and 88 mutations are recurrent. We observed an over representation of clinically relevant mutations (~80%) in SCN5A gene, and also identified several candidate genes, including GPD1L, TRPM4 and SCN10A. Furthermore, protein domain enrichment analysis revealed that a large proportion of the mutations impacted ion-transport domains in multiple genes, including SCN5A, TRPM4 and SCN10A. A comparative protein domain analysis of SCN5A further established a significant (p=0.04) enrichment of clinically relevant mutations within ion-transport domain, including a significant (p=0.02) mutation hotspot within 1321-1380 residue. The enrichment of clinically relevant mutations within SCN5A ion transport domain is stronger (p=0.00003) among early onset of BrS. Our spatiotemporal cellular heart developmental (prenatal to adult) trajectory analysis applying single cell transcriptome identified the most frequently BrS mutated genes (SCN5A and GPD1L) are significantly upregulated in the prenatal cardiomyocytes. A more restrictive cellular expression trajectory is prominent in the adult heart ventricular cardiomyocytes compared to prenatal. Our study suggests that genomic and proteomic hotspots in BrS converge into ion transport pathway and cardiomyocyte as a major BrS associated cell type that provides insight into the complex genetic etiology of BrS.

Modelling of a Stochastic Spatiotemporal Variable in Transport Domain

In this article, building on our previous work, we engage in spatiotemporal modelling of transport demand in the Montreal metropolitan area over the period of six years. We employ classical machine learning and regression models, which predict bike-sharing demand in the form of daily cumulative sums of bike trips for each considered docking station. Hourly estimates of demand are then determined by considering the statistical distribution of demand across individual hours of an average day. In order to capture seasonal and other regular variation of demand, longer-term distribution characteristics of bike trips, such as their average number falling on each day of the week, month of the year, etc., were also used as input attributes. We initially conjectured that weather would be an important source of irregular variation in bike-sharing demand, and subsequently included several available meteorological variables in our models. We validated our models by Hold-Out and 10-Fold Cross-Validation, with encouraging results.

Applying Deep Learning Techniques for Sentiment Analysis to Assess Sustainable Transport

Users voluntarily generate large amounts of textual content by expressing their opinions, in social media and specialized portals, on every possible issue, including transport and sustainability. In this work we have leveraged such User Generated Content to obtain a high accuracy sentiment analysis model which automatically analyses the negative and positive opinions expressed in the transport domain. In order to develop such model, we have semiautomatically generated an annotated corpus of opinions about transport, which has then been used to fine-tune a large pretrained language model based on recent deep learning techniques. Our empirical results demonstrate the robustness of our approach, which can be applied to automatically process massive amounts of opinions about transport. We believe that our method can help to complement data from official statistics and traditional surveys about transport sustainability. Finally, apart from the model and annotated dataset, we also provide a transport classification score with respect to the sustainability of the transport types found in the use case dataset.

Let the Game Begin: Enhancing Sustainable Collaboration among Actors in Innovation Ecosystems in a Playful Way

Logistics and transport systems are complex systems for which sustainable innovations are urgently needed. Serious games are an acknowledged tool for training, learning, and decision making, as well as for helping to introduce innovative concepts for complex systems. Technological innovations for the transport domain that can improve sustainability are usually heavily dependent on the collaboration among actors. A simulation gaming approach can help these actors in understanding the challenges involved, and in finding solutions in a playful, interactive way. Our research approach includes a thorough literature review on games for innovation and collaboration in transport networks, and the development of two dedicated simulation games addressing sustainability innovations for the Port of Rotterdam, the largest seaport in Europe and one of the largest in the world. The two innovation cases are truck platooning and multi-sided digital platforms for barge transportation, both improving the sustainability of hinterland transportation. The games serve as instruments to reveal interactions and tensions among actors, contribute to the interpretation of their behavior, and eventually help all parties to reach a better understanding on how innovation adoption can be fostered, using an innovation ecosystem perspective. We are convinced that serious gaming, by providing a better understanding of the innovation process, will help the implementation of sustainability innovations in complex systems.

Structural basis for the reaction cycle of DASS dicarboxylate transporters

Citrate, α-ketoglutarate and succinate are TCA cycle intermediates that also play essential roles in metabolic signaling and cellular regulation. These di- and tricarboxylates are imported into the cell by the divalent anion sodium symporter (DASS) family of plasma membrane transporters, which contains both cotransporters and exchangers. While DASS proteins transport substrates via an elevator mechanism, to date structures are only available for a single DASS cotransporter protein in a substrate-bound, inward-facing state. We report multiple cryo-EM and X-ray structures in four different states, including three hitherto unseen states, along with molecular dynamics simulations, of both a cotransporter and an exchanger. Comparison of these outward- and inward-facing structures reveal how the transport domain translates and rotates within the framework of the scaffold domain through the transport cycle. Additionally, we propose that DASS transporters ensure substrate coupling by a charge-compensation mechanism, and by structural changes upon substrate release.