Cost-Benefit Analysis of Novel Access Modes: A Case Study in the San Francisco Bay Area

The first-mile, last-mile problem is a significant deterrent for potential transit riders, especially in suburban neighborhoods with low density. Transit agencies have typically sought to solve this problem by adding parking spaces near transit stations and adding stops to connect riders to fixed-route transit. However, these measures are often only short-term solutions. In the last few years, transit agencies have tested whether new mobility services, such as ridehailing, ridesharing, and microtransit, can offer fast, reliable connections to and from transit stations. However, there is limited research that evaluates the potential impacts of these projects. Concurrently, there is growing interest in the future of automated vehicles (AVs) and the potential of AVs to solve this first-mile problem by reducing the cost of providing these new mobility services to promote access to transit. This paper expands upon existing research to model the simulate the travel and revenue impacts of a fleet of automated vehicles that provide transit access services in the San Francisco Bay Area offered over a range of fares. The model simulates a fleet of AVs for first-mile transit access at different price points for three different service models (door-to-door ridehailing and ridesharing and meeting point ridesharing services). These service models include home-based drop-off and pick-up for single passenger service (e.g., Uber and Lyft), home-based drop-off and pick-up for multi-passenger service (e.g.,microtransit), and meeting point multi-passenger service (e.g., Via)

Sustainable freight: impacts of the London congestion charge and low emissions zone

This paper assesses whether two sustainability policies currently in effect in London, a congestion charge zone and a low emission zone, have affected freight operations and reduced vehicle kilometers travelled. It investigates responses by freight operators, including re-timing, re-routing, or reducing the number of trips, or replacing vehicles. Freight traffic trends from 1994 to 2012 were identified using road traffic estimates, cordon counts, and vehicle speed data and supplemented by interviews with freight industry experts and operators. Findings indicate that freight traffic increased throughout London during this timeframe, but declined in the central boroughs partly within the congestion charge zone. The congestion charge may have time-shifted some light goods trips, but most freight trips face a variety of constraints on operators’ delivery window. No evidence was found of re-routing of freight traffic or avoidance traffic around the charged zone. The low emission zone spurred higher levels of operational change than the congestion charge zone, and it was effective at spurring freight vehicle replacement. The paper also discusses freight operators’ perceptions of these policies and how they could be improved

HE4 (WFDC2) Promotes Tumor Growth in Endometrial Cancer Cell Lines

HE4, also known as WFDC2, is a useful biomarker for ovarian cancer when either used alone or in combination with CA125. HE4 is also overexpressed in endometrial cancer (EC), but its function in cancer cells is not clear. In this study, we investigate the role of HE4 in EC progression. An HE4-overexpression system was established by cloning the HE4 prototypic mRNA variant (HE4-V0) into a eukaryotic expression vector. Following transfection, stable clones in two EC cell lines were selected. The effects of HE4 overexpression on cell growth and function were measured with the use of cell proliferation assay, matrigel invasion, and soft agar gel colony formation assays. HE4-induced cancer cell proliferation in vivo was examined in a mouse xenograft model. HE4 overexpression significantly enhanced EC cell proliferation, matrigel invasion, and colony formation in soft agar. Moreover, HE4 overexpression promoted tumor growth in the mouse xenograft model. HE4 overexpression enhanced several malignant phenotypes in cell culture and in a mouse model. These results are consistent with our previous observation that high levels of serum HE4 closely correlate with the stage, myometrial invasion and tumor size in patients with EC. This study provides evidence that HE4 overexpression directly impacts tumor progression in endometrial cancer

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies