Domain Adaptation on Graphs by Learning Aligned Graph Bases

A common assumption in semi-supervised learning with graph models is that the class label function varies smoothly on the data graph, resulting in the rather strict prior that the label function has low-frequency content. Meanwhile, in many classification problems, the label function may vary abruptly in certain graph regions, resulting in high-frequency components. Although the semi-supervised estimation of class labels is an ill-posed problem in general, in several applications it is possible to find a source graph on which the label function has similar frequency content to that on the target graph where the actual classification problem is defined. In this paper, we propose a method for domain adaptation on graphs motivated by these observations. Our algorithm is based on learning the spectrum of the label function in a source graph with many labeled nodes, and transferring the information of the spectrum to the target graph with fewer labeled nodes. While the frequency content of the class label function can be identified through the graph Fourier transform, it is not easy to transfer the Fourier coefficients directly between the two graphs, since no one-to-one match exists between the Fourier basis vectors of independently constructed graphs in the domain adaptation setting. We solve this problem by learning a transformation between the Fourier bases of the two graphs that flexibly ``aligns'' them. The unknown class label function on the target graph is then reconstructed such that its spectrum matches that on the source graph while also ensuring the consistency with the available labels. The proposed method is tested in the classification of image, online product review, and social network data sets. Comparative experiments suggest that the proposed algorithm performs better than recent domain adaptation methods in the literature in most settings

DOMAIN ADAPTATION VIA TRANSFERRING SPECTRAL PROPERTIES OF LABEL FUNCTIONS ON GRAPHS

We propose a domain adaptation algorithm that relies on a graph representation of data samples in the source and target domains. The algorithm combines the information of the known class labels in the source and target domains through the Fourier coefficients of the class label function in the two graphs. The proposed method does not require an ordering or a one-to-one mapping between the samples of the source and target domains; instead, it uses only a small set of matched pairs that serve the purpose of "aligning" the source and target Fourier bases. The estimation of the coefficients of the label function in the source and target Fourier bases is then formulated as a simple convex optimization problem. The proposed domain adaptation algorithm is tested in face recognition under varying pose and illumination and is observed to provide significant improvement over reference classification approaches especially when the data distributions in the source and target domains differ significantly

Evaluation of the Retro-Orbital Fatty Tissue Volume in Delayed Orbital Blow-Out Fractures

Purpose: In patients where diplopia and enophthalmia are manifest, surgical intervention is usually necessary. The pathogenesis of these symptoms usually includes the prolapse of orbital tissues into the sinus or compression by the surrounding bone structures. Although the retro-orbital fatty tissue, orbital fascia, and the muscle tissue can be reduced to the original place after being incarcerated into the maxillary space, it is obvious that the procedure can lead to significant fibrosis in these structures. The authors have aimed to carry out a quantitative evaluation of the fatty tissue volumes in patients with repair delayed for more than two weeks

A Rare Case of Sunitinib-Induced Hyperammonemic Encephalopathy and Hypothyroidism in Metastatic Renal Cell Carcinoma

WOS: 000372176400034PubMed ID: 24901901Sunitinib has become a standard treatment agent for metastatic renal cell carcinoma (RCC) for several years. However, various adverse events have been reported. We present a rare adverse effect of hyperammonemic encephalopathy induced by sunitinib. A 66-year-old woman with metastatic RCC referred to the emergency department with confusion that developed 14 days after the initiation of 50 mg/d of sunitinib. Her serum ammonia and thyroid-stimulating hormone levels were markedly elevated (146 mu g/dL and 27.27 mu IU/mL, respectively). Sunitinib was discontinued, and an enema with lactulose and l-thyroxine were administered. Her mental status and neurologic symptoms were normalized 7 days after the treatment. Serum ammonia level decreased to 61 mu g/dL and thyroid stimulating hormone level decreased 22.34 mu IU/mL. The incidence of sunitinib-induced hyperammonemia is rarely reported. The relationship between sunitinib and the development of hyperammonemia is not well understood, and the mechanism is unclear. Sunitinib-induced hyperammonemia is very rare, and to the best of our knowledge, this is fourth case hyperammonemia and first case hyperammonemic encephalopathy with hypothyroidism as an adverse effect. Therefore, it is important for clinicians to be aware of hyperammonemia that can occur in several days after the initiation of sunitinib treatment in metastatic RCC

Efficacy and Safety of Trastuzumab Emtansine in Her2 Positive Metastatic Breast Cancer: Real-World Experience

Aim The aim of this study is to evaluate the efficacy and toxicity of trastuzumab emtansine (T-DM1) in cases with metastatic breast cancer (mBC) in different lines of treatment. Method Retrospective analysis of T-DM1 results of human epidermal growth factor receptor 2 (Her2) positive 414 cases with mBC from 31 centers in Turkey. Findings Except 2, all of the cases were female with a median age of 47. T-DM1 had been used as second-line therapy in 37.7% of the cases and the median number of T-DM1 cycles was 9. Progression-free survival (PFS) and overall survival (OS) times were different according to the line of treatment. The median OS was found as 43, 41, 46, 23 and 17 months for 1st, 2nd, 3rd, 4th and 5th line, respectively (p = 0.032) while the median PFS was found as 37, 12, 8, 8 and 8 months, respectively (p = 0.0001). Treatment was well tolerated by the patients. The most common grade 3-4 adverse effects were thrombocytopenia (2.7%) and increased serum gamma-glutamyl transferase (2%). Discussion The best of our knowledge this is the largest real-life experience about the safety and efficacy of T-DM1 use in cases with mBC after progression of Her2 targeted treatment. This study suggests and supports that T-DM1 is more effective in earlier lines of treatment and is a reliable option for mBC