Urban Feature Extraction within a Complex Urban Area with an Improved 3D-CNN Using Airborne Hyperspectral Data

Article describes how airborne hyperspectral data has high spectral-spatial information, but mining and using this information effectively is still a great challenge. Therefore, a 3D-1D-CNN model was proposed for feature extraction in complex urban with hyperspectral images affected by cloud shadows

Bioinformatics analysis reveals TSPAN1 as a candidate biomarker of progression and prognosis in pancreatic cancer

Pancreatic cancer (PCC) is a common malignant tumor of the digestive system that is resistant to traditional treatments and has an overall 5-year survival rate of <7%. Transcriptomics research provides reliable biomarkers for diagnosis, prognosis, and clinical precision treatment, as well as the identification of molecular targets for the development of drugs to improve patient survival. We sought to identify new biomarkers for PCC by combining transcriptomics and clinical data with current knowledge regarding molecular mechanisms. Consequently, we employed weighted gene co-expression network analysis and differentially expressed gene analysis to evaluate genes co-expressed in tumor versus normal tissues using pancreatic adenocarcinoma data from The Cancer Genome Atlas and dataset GSE16515 from the Gene Expression Omnibus. Twenty-one overlapping genes were identified, with enrichment of key Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways, including epidermal growth factor receptor signaling, cadherin, cell adhesion, ubiquinone, and glycosphingolipid biosynthesis pathways, and retinol metabolism. Protein-protein interaction analysis highlighted 10 hub genes, according to Maximal Clique Centrality. Univariate and multivariate COX analyses indicated that TSPAN1 serves as an independent prognostic factor for PCC patients. Survival analysis distinguished TSPAN1 as an independent prognostic factor among hub genes in PCC. Finally, immunohistochemical staining results suggested that the TSPAN1 protein levels in the Human Protein Atlas were significantly higher in tumor tissue than in normal tissue. Therefore, TSPAN1 may be involved in PCC development and act as a critical biomarker for diagnosing and predicting PCC patient survival

The gut microbiome dysbiosis and regulation by fecal microbiota transplantation: umbrella review

BackgroundGut microbiome dysbiosis has been implicated in various gastrointestinal and extra-gastrointestinal diseases, but evidence on the efficacy and safety of fecal microbiota transplantation (FMT) for therapeutic indications remains unclear.MethodsThe gutMDisorder database was used to summarize the associations between gut microbiome dysbiosis and diseases. We performed an umbrella review of published meta-analyses to determine the evidence synthesis on the efficacy and safety of FMT in treating various diseases. Our study was registered in PROSPERO (CRD42022301226).ResultsGut microbiome dysbiosis was associated with 117 gastrointestinal and extra-gastrointestinal. Colorectal cancer was associated with 92 dysbiosis. Dysbiosis involving Firmicutes (phylum) was associated with 34 diseases. We identified 62 published meta-analyses of FMT. FMT was found to be effective for 13 diseases, with a 95.56% cure rate (95% CI: 93.88–97.05%) for recurrent Chloridoids difficile infection (rCDI). Evidence was high quality for rCDI and moderate to high quality for ulcerative colitis and Crohn’s disease but low to very low quality for other diseases.ConclusionGut microbiome dysbiosis may be implicated in numerous diseases. Substantial evidence suggests FMT improves clinical outcomes for certain indications, but evidence quality varies greatly depending on the specific indication, route of administration, frequency of instillation, fecal preparation, and donor type. This variability should inform clinical, policy, and implementation decisions regarding FMT

Measuring the Neutrino Cross Section Using 8 years of Upgoing Muon Neutrinos Observed with IceCube

The IceCube Neutrino Observatory detects neutrinos at energies orders of magnitude higher than those available to current accelerators. Above 40 TeV, neutrinos traveling through the Earth will be absorbed as they interact via charged current interactions with nuclei, creating a deficit of Earth-crossing neutrinos detected at IceCube. The previous published results showed the cross section to be consistent with Standard Model predictions for 1 year of IceCube data. We present a new analysis that uses 8 years of IceCube data to fit the ν$_{μ}$ absorption in the Earth, with statistics an order of magnitude better than previous analyses, and with an improved treatment of systematic uncertainties. It will measure the cross section in three energy bins that span the range 1 TeV to 100 PeV. We will present Monte Carlo studies that demonstrate its sensitivity

Non-standard neutrino interactions in IceCube

Non-standard neutrino interactions (NSI) may arise in various types of new physics. Their existence would change the potential that atmospheric neutrinos encounter when traversing Earth matter and hence alter their oscillation behavior. This imprint on coherent neutrino forward scattering can be probed using high-statistics neutrino experiments such as IceCube and its low-energy extension, DeepCore. Both provide extensive data samples that include all neutrino flavors, with oscillation baselines between tens of kilometers and the diameter of the Earth. DeepCore event energies reach from a few GeV up to the order of 100 GeV - which marks the lower threshold for higher energy IceCube atmospheric samples, ranging up to 10 TeV. In DeepCore data, the large sample size and energy range allow us to consider not only flavor-violating and flavor-nonuniversal NSI in the μ−τ sector, but also those involving electron flavor. The effective parameterization used in our analyses is independent of the underlying model and the new physics mass scale. In this way, competitive limits on several NSI parameters have been set in the past. The 8 years of data available now result in significantly improved sensitivities. This improvement stems not only from the increase in statistics but also from substantial improvement in the treatment of systematic uncertainties, background rejection and event reconstruction

IceCube Search for Earth-traversing ultra-high energy Neutrinos

The search for ultra-high energy neutrinos is more than half a century old. While the hunt for these neutrinos has led to major leaps in neutrino physics, including the detection of astrophysical neutrinos, neutrinos at the EeV energy scale remain undetected. Proposed strategies for the future have mostly been focused on direct detection of the first neutrino interaction, or the decay shower of the resulting charged particle. Here we present an analysis that uses, for the first time, an indirect detection strategy for EeV neutrinos. We focus on tau neutrinos that have traversed Earth, and show that they reach the IceCube detector, unabsorbed, at energies greater than 100 TeV for most trajectories. This opens up the search for ultra-high energy neutrinos to the entire sky. We use ten years of IceCube data to perform an analysis that looks for secondary neutrinos in the northern sky, and highlight the promise such a strategy can have in the next generation of experiments when combined with direct detection techniques