Wow, that portal vein is small: Preventing portal vein thrombosis in liver transplantation for small children

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107365/1/lt23865.pd

BCOR-Rearranged Sarcoma of the Tonsil.

A tonsillar mass in a young patient with no medical issues routinely presents as an infectious process. Practitioners must maintain a broad differential if diagnostic testing does not support an infection. Neoplasm must be excluded. Otolaryngologists must consider malignancies other than squamous cell carcinoma, the most common oropharyngeal malignancy, and lymphoma. Rare tumors, such as sarcomas, must also be considered. Otolaryngologists must be familiar with the proper management of rare oropharyngeal malignancies

A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum]

© 2005-2012 IEEE. Fuzzy Sets and Systems is an area of computational intelligence, pioneered by Lotfi Zadeh over 50 years ago in a seminal paper in Information and Control. Fuzzy Sets (FSs) deal with uncertainty in our knowledge of a particular situation. Research and applications in FSs have grown steadily over 50 years. More recently, we have seen a growth in Type-2 Fuzzy Set (T2 FS) related papers, where T2 FSs are utilized to handle uncertainty in realworld problems. In this paper, we have used bibliometric methods to obtain a broad overview of the area of T2 FSs. This method analyzes information on the bibliographic details of published journal papers, which includes title, authors, author address, journals and citations, extracted from the Science and Social Science Citation Indices in the Web of Science (WoS) database for the last 20 years (1997-2017). We have compared the growth of publications in the field of FSs, and its subset T2 FSs, identified highly cited papers in T2 FSs, highly cited authors, key institutions, and main countries with researchers involved in T2 FS related research

Defining the substrate for ventricular tachycardia ablation: The impact of rhythm at the time of mapping

BACKGROUND: Voltage mapping is critical to define substrate during ablation. In ventricular tachycardia, abnormal potentials may be targets. However, wavefront of activation could impact local signal characteristics. This may be particularly true when comparing sinus rhythm versus paced rhythms. We sought to determine how activation wavefront impacts electrogram characteristics. METHODS: Patients with ischemic cardiomyopathy, ventricular tachycardia, and without fascicular or bundle branch block were included. Point by point mapping was done and at each point, one was obtained during an atrial paced rhythm and one during a right ventricular paced rhythm. Signals were adjudicated after ablation to define late potentials, fractionated potentials, and quantify local voltage. Areas of abnormal voltage (defined as \u3c1.5 mV) were also determined. RESULTS: 9 patients were included (age 61.3 ± 9.2 years, 56% male, mean LVEF 34.9 ± 8.6%). LV endocardium was mapped with an average 375 ± 53 points/rhythm. Late potentials were more frequent during right ventricular pacing (51 ± 21 versus 32 ± 15, p \u3c 0.01) while overall scar area was higher during atrial pacing (22 ± 11% vs 13 ± 7%, p \u3c 0.05). In 1/9 patients, abnormal potentials were seen during a right ventricular paced rhythm that were not apparent in an atrial paced rhythm, ablation of which resulted in non-inducibility. CONCLUSION: Rhythm in which mapping is performed has an impact on electrogram characteristics. Whether one rhythm is preferable to map in remains to be determined. However, it is possible defining local signals during normal conduction as well as variable paced rhythms may impart a greater likelihood of elucidating arrhythmogenic substrate

Molecular Docking studies of Apigenin, Kaempferol, and Quercetin as potential target against spike receptor protein of SARS COV

COVID-19 has been categorized as a pandemic in early 2020 and is known to cause by Severe Acute Respiratory Syndrome Coronavirus (SARS–CoV2). Numerous investigators and people in the scientific community are trying to find a superlative way to avert and cure the ailment by using phytochemicals. Abundant studies have revealed that flavonoids can be very operative in averting virus-mediated infection. The purpose of this study was to accomplish molecular docking studies among plant-derived flavonoids (Apigenin, Kaempferol, and Quercetin) and spike receptor (PDB ID: 2AJF) protein of coronavirus. Pyrx virtual screening tool and biovia discovery studio visualizer were utilized in the current molecular docking investigations. Outcomes of docking studies exposed that selected phytochemicals have interacted with targeted spike receptor protein with binding energies in the range of -6.3 to -7.3 kcal. In conclusion among the various selected ligands, quercetin may be a better inhibitor for the deactivation of SARS-Coronavirus

Communication-Efficient Secure Logistic Regression

We present a new construction for secure logistic regression training, which enables two parties to train a model on private secret-shared data. Our goal is to minimize online communication and round complexity, while still allowing for an efficient offline phase. As part of our construction we develop many building blocks of independent interest. These include a new approximation technique for the sigmoid function, which results in a secure protocol with better communication; secure spline evaluation and secure powers computation protocols for fixed-point values; and a new comparison protocol that optimizes online communication. We also present a new two-party protocol for generating keys for distributed point functions (DPFs) over arithmetic sharing, where previous constructions do this only for Boolean outputs. We implement our protocol in an end-to-end system and benchmark its efficiency. We can securely evaluate a sigmoid in $18$ ms online time and $0.5$ KB of online communication. Our system can train a model over a database with $70,000$ samples and $15$ features with online communication of $208.09$ MB and online time of $2.24$ hours at the cost of $6.11$c over WAN. Our benchmarks demonstrate that we reduce online communication over state of the art by $\approx 10 \times$ for sigmoid and $\approx38\times$ for logistic regression training