The Survey, Taxonomy, and Future Directions of Trustworthy AI: A Meta Decision of Strategic Decisions

When making strategic decisions, we are often confronted with overwhelming information to process. The situation can be further complicated when some pieces of evidence are contradicted each other or paradoxical. The challenge then becomes how to determine which information is useful and which ones should be eliminated. This process is known as meta-decision. Likewise, when it comes to using Artificial Intelligence (AI) systems for strategic decision-making, placing trust in the AI itself becomes a meta-decision, given that many AI systems are viewed as opaque "black boxes" that process large amounts of data. Trusting an opaque system involves deciding on the level of Trustworthy AI (TAI). We propose a new approach to address this issue by introducing a novel taxonomy or framework of TAI, which encompasses three crucial domains: articulate, authentic, and basic for different levels of trust. To underpin these domains, we create ten dimensions to measure trust: explainability/transparency, fairness/diversity, generalizability, privacy, data governance, safety/robustness, accountability, reproducibility, reliability, and sustainability. We aim to use this taxonomy to conduct a comprehensive survey and explore different TAI approaches from a strategic decision-making perspective

Survey of Trustworthy AI: A Meta Decision of AI

When making strategic decisions, we are often confronted with overwhelming information to process. The situation can be further complicated when some pieces of evidence are contradicted each other or paradoxical. The challenge then becomes how to determine which information is useful and which ones should be eliminated. This process is known as meta-decision. Likewise, when it comes to using Artificial Intelligence (AI) systems for strategic decision-making, placing trust in the AI itself becomes a meta-decision, given that many AI systems are viewed as opaque "black boxes" that process large amounts of data. Trusting an opaque system involves deciding on the level of Trustworthy AI (TAI). We propose a new approach to address this issue by introducing a novel taxonomy or framework of TAI, which encompasses three crucial domains: articulate, authentic, and basic for different levels of trust. To underpin these domains, we create ten dimensions to measure trust: explainability/transparency, fairness/diversity, generalizability, privacy, data governance, safety/robustness, accountability, reproducibility, reliability, and sustainability. We aim to use this taxonomy to conduct a comprehensive survey and explore different TAI approaches from a strategic decision-making perspective.Cloud-based Computational Decision, Artificial Intelligence, Machine Learning9. Industry, innovation and infrastructur

Pre-operative self-efficacy education vs. usual care for patients undergoing joint replacement surgery: a pilot randomised controlled trial

Background Hip and knee replacement is a major surgical procedure performed worldwide. Despite 20 or so years of clinical research and care guidelines, the management of acute postoperative pain continues to be a concern. A growing number of self-efficacy strategies are being included in education programs for patients to enable then to have a central role in managing their illness and symptoms. Aims and Objectives The purpose of this pilot study was to evaluate the feasibility of testing an education intervention to improve self-efficacy in patients undergoing hip or knee replacement. Methods A single-blinded, parallel, pilot randomised control trial design was used. Ninety-one patients undergoing hip or knee replacement surgery were randomly assigned to an intervention or control group. Intervention group participants were given a DVD demonstrating self-efficacy activities to undertake four times before admission. Feasibility criteria related to recruitment, protocol adherence and missing data were assessed. Participants were assessed for pain, anxiety, self-efficacy and healthcare utilisation. Results In relation to recruitment, 55% of screened patients were eligible and of these 81% enrolled (n = 91). Exclusion following randomisation was 10% with missing data ranging from 0 to 20.7%. Nineteen per cent of participants were lost to follow up in the control group and 20% lost to follow up in DVD group. Protocol adherence to components of the intervention varied. Both groups were generally satisfied with pain management during hospitalisation, and there were no differences in groups on clinical outcome measures. Conclusions Preliminary evidence for the benefits of self-efficacy-based education for patients undergoing hip or knee replacement was identified. Additional findings included a need to strengthen the intervention and reducing the number of data collection points to improve the protocol, missing data and numbers lost to follow up before a larger trial is undertaken

Crystal structure of a tripartite complex between C3dg, C-terminal domains of factor H and OspE of Borrelia burgdorferi

Complement is an important part of innate immunity. The alternative pathway of complement is activated when the main opsonin, C3b coats non-protected surfaces leading to opsonisation, phagocytosis and cell lysis. The alternative pathway is tightly controlled to prevent autoactivation towards host cells. The main regulator of the alternative pathway is factor H (FH), a soluble glycoprotein that terminates complement activation in multiple ways. FH recognizes host cell surfaces via domains 19–20 (FH19-20). All microbes including Borrelia burgdorferi, the causative agent of Lyme borreliosis, must evade complement activation to allow the infectious agent to survive in its host. One major mechanism that Borrelia uses is to recruit FH from host. Several outer surface proteins (Osp) have been described to bind FH via the C-terminus, and OspE is one of them. Here we report the structure of the tripartite complex formed by OspE, FH19-20 and C3dg at 3.18 Å, showing that OspE and C3dg can bind simultaneously to FH19-20. This verifies that FH19-20 interacts via the “common microbial binding site” on domain 20 with OspE and simultaneously and independently via domain 19 with C3dg. The spatial organization of the tripartite complex explains how OspE on the bacterial surface binds FH19-20, leaving FH fully available to protect the bacteria against complement. Additionally, formation of tripartite complex between FH, microbial protein and C3dg might enable enhanced protection, particularly on those regions on the bacteria where previous complement activation led to deposition of C3d. This might be especially important for slow-growing bacteria that cause chronic disease like Borrelia burgdorferi.Peer reviewe

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

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

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

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