Subject(s)
Fasciitis , Lacrimal Duct Obstruction , Nasolacrimal Duct , Humans , Lacrimal Duct Obstruction/diagnosis , Lacrimal Duct Obstruction/etiology , Nasolacrimal Duct/diagnostic imaging , Nasolacrimal Duct/pathology , Fasciitis/diagnosis , Fasciitis/complications , Male , Female , Dacryocystorhinostomy/methodsABSTRACT
Within the next 1.5 decades, 1 in 7 U.S. adults is anticipated to suffer from age-related macular degeneration (AMD), a degenerative retinal disease which leads to blindness if untreated. Optical coherence tomography angiography (OCTA) has become a prime technique for AMD diagnosis, specifically for late-stage neovascular (NV) AMD. Such technologies generate massive amounts of data, challenging to parse by experts alone, transforming artificial intelligence into a valuable partner. We describe a deep learning (DL) approach which achieves multi-class detection of non-AMD vs. non-neovascular (NNV) AMD vs. NV AMD from a combination of OCTA, OCT structure, 2D b-scan flow images, and high definition (HD) 5-line b-scan cubes; DL also detects ocular biomarkers indicative of AMD risk. Multimodal data were used as input to 2D-3D Convolutional Neural Networks (CNNs). Both for CNNs and experts, choroidal neovascularization and geographic atrophy were found to be important biomarkers for AMD. CNNs predict biomarkers with accuracy up to 90.2% (positive-predictive-value up to 75.8%). Just as experts rely on multimodal data to diagnose AMD, CNNs also performed best when trained on multiple inputs combined. Detection of AMD and its biomarkers from OCTA data via CNNs has tremendous potential to expedite screening of early and late-stage AMD patients.
Subject(s)
Expert Testimony , Macular Degeneration/diagnostic imaging , Neural Networks, Computer , Tomography, Optical Coherence/methods , Biomarkers , Choroidal Neovascularization/diagnostic imaging , Deep Learning , Diagnosis, Differential , Humans , Predictive Value of Tests , ROC Curve , Risk , Severity of Illness IndexABSTRACT
In the version of this article originally published, the graph in Extended Data Fig. 2c was a duplication of Extended Data Fig. 2b. The correct version of Extended Data Fig. 2c is now available online.
ABSTRACT
Immunotherapy has drastically improved the prognosis of many patients with cancer, but it can also lead to severe immune-related adverse events. Biomarkers, which are molecular markers that indicate a patient's disease outcome or a patient's response to treatment, are therefore crucial to helping clinicians weigh the potential benefits of immunotherapy against its potential toxicities. Immunohistochemistry (IHC) has thus far been a powerful technique for discovery and use of biomarkers such as CD8+ tumor-infiltrating lymphocytes. However, IHC has limited reproducibility. Thus, if more IHC-based biomarkers are to reach the clinic, refinement of the technique using multiplexing or automation is key.
Subject(s)
Biomarkers, Tumor , CD8-Positive T-Lymphocytes/immunology , Immunotherapy , Lymphocytes, Tumor-Infiltrating/immunology , Neoplasms , Biomarkers, Tumor/immunology , Biomarkers, Tumor/metabolism , Humans , Immunohistochemistry , Neoplasms/diagnosis , Neoplasms/immunology , Neoplasms/metabolism , Neoplasms/therapy , PrognosisABSTRACT
Immune checkpoint inhibitors have been successful across several tumor types; however, their efficacy has been uncommon and unpredictable in glioblastomas (GBM), where <10% of patients show long-term responses. To understand the molecular determinants of immunotherapeutic response in GBM, we longitudinally profiled 66 patients, including 17 long-term responders, during standard therapy and after treatment with PD-1 inhibitors (nivolumab or pembrolizumab). Genomic and transcriptomic analysis revealed a significant enrichment of PTEN mutations associated with immunosuppressive expression signatures in non-responders, and an enrichment of MAPK pathway alterations (PTPN11, BRAF) in responders. Responsive tumors were also associated with branched patterns of evolution from the elimination of neoepitopes as well as with differences in T cell clonal diversity and tumor microenvironment profiles. Our study shows that clinical response to anti-PD-1 immunotherapy in GBM is associated with specific molecular alterations, immune expression signatures, and immune infiltration that reflect the tumor's clonal evolution during treatment.
Subject(s)
Antibodies, Monoclonal, Humanized/therapeutic use , Antineoplastic Agents, Immunological/therapeutic use , Brain Neoplasms/drug therapy , Glioblastoma/drug therapy , Nivolumab/therapeutic use , Programmed Cell Death 1 Receptor/antagonists & inhibitors , Adult , Aged , Brain Neoplasms/genetics , Brain Neoplasms/immunology , Female , Gene Expression Profiling , Genomics , Glioblastoma/genetics , Glioblastoma/immunology , Humans , Immune Tolerance/genetics , Immune Tolerance/immunology , Longitudinal Studies , Male , Middle Aged , Mutation , PTEN Phosphohydrolase/genetics , PTEN Phosphohydrolase/immunology , Protein Tyrosine Phosphatase, Non-Receptor Type 11/genetics , Protein Tyrosine Phosphatase, Non-Receptor Type 11/immunology , Proto-Oncogene Proteins B-raf/genetics , Proto-Oncogene Proteins B-raf/immunology , T-Lymphocytes/immunology , Treatment Outcome , Tumor Microenvironment/genetics , Tumor Microenvironment/immunology , Young AdultABSTRACT
This study reports the release of the complete nucleotide sequence of Komagataeibacter hansenii HUM-1, a new efficient producer of cellulose. Elucidation of the genome may provide more information to aid in understanding the genes necessary for cellulose biosynthesis.
ABSTRACT
This study reports the release of the complete nucleotide sequence of Komagataeibacter hansenii LMG 23726T This organism is a cellulose producer, and its genome may provide more information to aid in the understanding of the genes necessary for cellulose biosynthesis.
ABSTRACT
This study reports the release of the complete nucleotide sequence of Komagataeibacter hansenii SC-3B, a new efficient producer of cellulose. Elucidation of the genome may provide more information to aid in understanding the genes necessary for cellulose biosynthesis.