12 research outputs found
Mixed convection boundary-layer flow along a vertical surface embedded in a porous medium with a convective boundary condition.
An analysis of the mixed convection boundary-layer flow on one face of a semi-infinite vertical surface embedded in a fluid-saturated porous medium is presented. It is assumed
that the other face of the surface is in contact with a hot or cooled fluid maintaining the surface at a constant "temperature Tf
Observation of the screening signature in the lateral photovoltage of electrons in the Quantum Hall regime
The lateral photovoltage generated in the plane of a two-dimensional electron
system (2DES) by a focused light spot, exhibits a fine-structure in the quantum
oscillations in a magnetic field near the Quantum Hall conductivity minima. A
double peak structure occurs near the minima of the longitudinal conductivity
oscillations. This is the characteristic signature of the interplay between
screening and Landau quantization.Comment: 4 pages, 4 figures, to be published in Phys. Rev.
Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes
Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues
Comparison of Post-Creation Procedures and Costs between Surgical and an Endovascular Approach to Arteriovenous Fistula Creation
Protein composition of microparticles shed from human placenta during placental perfusion: Potential role in angiogenesis and fibrinolysis in preeclampsia
Rotary oscillation of a composite sphere in a concentric spherical cavity using slip and stress jump conditions
Management of Thrombocytopenia in Cancer Patients
Chemotherapy-induced thrombocytopenia (CIT) is a frequent complication of cancer therapy, leading to increased risk of bleeding, when the thrombocytopenia is severe (<10,000/mcL). However, the major clinical relevance of CIT is the subsequent delay or dose reduction in chemotherapy. CIT, therefore, leads to reduced relative dose intensity (RDI) of cancer therapy. Reduced RDI has been shown in several studies to impact progression-free survival and other cancer outcomes. While there are a number of factors leading to reduced RDI, CIT is a common cause. We review the causes and clinical manifestations of CIT, the current recommendations for management, and the status of research to develop targeted therapies to treat CIT
Two-dimensional oblique stagnation-point flow towards a stretching surface in a viscoelastic fluid
A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis
Objective: Diabetic macular edema (DME) is the primary cause of vision loss among individuals with diabetes mellitus (DM). We developed, validated, and tested a deep learning (DL) system for classifying DME using images from three common commercially available optical coherence tomography (OCT) devices.
Research design and methods: We trained and validated two versions of a multitask convolution neural network (CNN) to classify DME (center-involved DME [CI-DME], non-CI-DME, or absence of DME) using three-dimensional (3D) volume scans and 2D B-scans, respectively. For both 3D and 2D CNNs, we used the residual network (ResNet) as the backbone. For the 3D CNN, we used a 3D version of ResNet-34 with the last fully connected layer removed as the feature extraction module. A total of 73,746 OCT images were used for training and primary validation. External testing was performed using 26,981 images across seven independent data sets from Singapore, Hong Kong, the U.S., China, and Australia.
Results: In classifying the presence or absence of DME, the DL system achieved area under the receiver operating characteristic curves (AUROCs) of 0.937 (95% CI 0.920-0.954), 0.958 (0.930-0.977), and 0.965 (0.948-0.977) for the primary data set obtained from CIRRUS, SPECTRALIS, and Triton OCTs, respectively, in addition to AUROCs >0.906 for the external data sets. For further classification of the CI-DME and non-CI-DME subgroups, the AUROCs were 0.968 (0.940-0.995), 0.951 (0.898-0.982), and 0.975 (0.947-0.991) for the primary data set and >0.894 for the external data sets.
Conclusions: We demonstrated excellent performance with a DL system for the automated classification of DME, highlighting its potential as a promising second-line screening tool for patients with DM, which may potentially create a more effective triaging mechanism to eye clinics