Lesson Learnt and Future of AI Applied to Manufacturing

This chapter touches on several aspects related to the role of Artificial Intelligence (AI) and Machine Learning (ML) in the manufacturing sector, and is split in different sub-chapters, focusing on specific new technology enablers that have the potential of solving or minimizing known issues in the manufacturing and, more in general, in the Industrial Internet of Things (IIoT) domain. After introducing AI/ML as a technology enabler for the IoT in general and for manufacturing in particular, the next four sections detail two key technology enablers (EdgeML and federated learning scenarios, challenges and tools), one most important area of the IoT system that needs to decrease energy consumption and increase reliability (reduce receiver Processing complexity and enhancing reliability through multi-connectivity uplink connections), and finally a glimpse at the future describing a promising new technology (Embodied AI), its link with millimetre waves connectivity and potential business impact

Effects of common haplotypes of the ileal sodium dependent bile acid transporter gene on the development of sporadic and familial colorectal cancer: A case control study

<p>Abstract</p> <p>Background</p> <p>The genetics of sporadic and non-syndromic familial colorectal cancer (CRC) is not well defined. However, genetic factors that promote the development of precursor lesions, i.e. adenomas, might also predispose to CRC. Recently, an association of colorectal adenoma with two variants (c.507C>T;p.L169L and c.511G>T;p.A171S) of the ileal sodium dependent bile acid transporter gene (<it>SLC10A2</it>) has been reported. Here, we reconstructed haplotypes of the <it>SLC10A2 </it>gene locus and tested for association with non-syndromic familial and sporadic CRC compared to 'hyper-normal' controls who displayed no colorectal polyps on screening colonoscopy.</p> <p>Methods</p> <p>We included 150 patients with sporadic CRC, 93 patients with familial CRC but exclusion of familial adenomatous polyposis and Lynch's syndrome, and 204 'hyper-normal' controls. Haplotype-tagging <it>SLC10A2 </it>gene variants were identified in the Hapmap database and genotyped using PCR-based 5' exonuclease assays with fluorescent dye-labelled probes. Haplotypes were reconstructed using the PHASE algorithm. Association testing was performed with both SNPs and reconstructed haplotypes.</p> <p>Results</p> <p>Minor allele frequencies of all <it>SLC10A2 </it>polymorphisms are within previously reported ranges, and no deviations from Hardy-Weinberg equilibrium are observed. However, we found no association with any of the <it>SLC10A2 </it>haplotypes with sporadic or familial CRC in our samples (all P values > 0.05).</p> <p>Conclusion</p> <p>Common variants of the <it>SLC10A2 </it>gene are not associated with sporadic or familial CRC. Hence, albeit this gene might be associated with early stages of colorectal neoplasia, it appears not to represent a major risk factor for progression to CRC.</p

Within-patient genetic diversity of SARS-CoV-2

SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, is evolving into different genetic variants by accumulating mutations as it spreads globally. In addition to this diversity of consensus genomes across patients, RNA viruses can also display genetic diversity within individual hosts, and co-existing viral variants may affect disease progression and the success of medical interventions. To systematically examine the intra-patient genetic diversity of SARS-CoV-2, we processed a large cohort of 3939 publicly-available deeply sequenced genomes with specialised bioinformatics software, along with 749 recently sequenced samples from Switzerland. We found that the distribution of diversity across patients and across genomic loci is very unbalanced with a minority of hosts and positions accounting for much of the diversity. For example, the D614G variant in the Spike gene, which is present in the consensus sequences of 67.4% of patients, is also highly diverse within hosts, with 29.7% of the public cohort being affected by this coexistence and exhibiting different variants. We also investigated the impact of several technical and epidemiological parameters on genetic heterogeneity and found that age, which is known to be correlated with poor disease outcomes, is a significant predictor of viral genetic diversity

Functional and spatial proteomics profiling reveals intra- and intercellular signaling crosstalk in colorectal cancer

Precision oncology approaches for patients with colorectal cancer (CRC) continue to lag behind other solid cancers. Functional precision oncology—a strategy that is based on perturbing primary tumor cells from cancer patients—could provide a road forward to personalize treatment. We extend this paradigm to measuring proteome activity landscapes by acquiring quantitative phosphoproteomic data from patient-derived organoids (PDOs). We show that kinase inhibitors induce inhibitor- and patient-specific off-target effects and pathway crosstalk. Reconstruction of the kinase networks revealed that the signaling rewiring is modestly affected by mutations. We show non-genetic heterogeneity of the PDOs and upregulation of stemness and differentiation genes by kinase inhibitors. Using imaging mass-cytometry-based profiling of the primary tumors, we characterize the tumor microenvironment (TME) and determine spatial heterocellular crosstalk and tumor-immune cell interactions. Collectively, we provide a framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno-) oncology in CRC.ISSN:2589-004