Agenesis of distal segment of right vertebral artery: a case report.

A case is being reported in which the basilar artery was formed only by the left vertebral artery. This was detected incidentally in a female on a non contrast magnetic resonance angiogram. The right vertebral artery arose as a direct branch of the right subclavian artery but terminated blindly at the level of second cervical vertebra. The left vertebral artery which contributed to the formation of basilar artery continued as left posterior cerebral artery while right posterior cerebral artery was seen as a continuation of right posterior communicating artery. The knowledge of variations of the vertebrobasilar arterial complex is important to Clinicians, Radiologists and Surgeons operating on the great vessels and its branches, particularly vascular surgeons dealing with vertebral artery in order to prevent a vascular catastrophe

Information-theoretic aspects of the generalized amplitude damping channel

The generalized amplitude damping channel (GADC) is one of the sources of noise in superconducting-circuit-based quantum computing. It can be viewed as the qubit analogue of the bosonic thermal channel, and it thus can be used to model lossy processes in the presence of background noise for low-temperature systems. In this work, we provide an information-theoretic study of the GADC. We first determine the parameter range for which the GADC is entanglement breaking and the range for which it is anti-degradable. We then establish several upper bounds on its classical, quantum, and private capacities. These bounds are based on data-processing inequalities and the uniform continuity of information-theoretic quantities, as well as other techniques. Our upper bounds on the quantum capacity of the GADC are tighter than the known upper bound reported recently in [Rosati et al., Nat. Commun. 9, 4339 (2018)] for the entire parameter range of the GADC, thus reducing the gap between the lower and upper bounds. We also establish upper bounds on the two-way assisted quantum and private capacities of the GADC. These bounds are based on the squashed entanglement, and they are established by constructing particular squashing channels. We compare these bounds with the max-Rains information bound, the mutual information bound, and another bound based on approximate covariance. For all capacities considered, we find that a large variety of techniques are useful in establishing bounds.Comment: 33 pages, 9 figures; close to the published versio

Biomarkers in solid organ transplantation: establishing personalized transplantation medicine.

Technological advances in molecular and in silico research have enabled significant progress towards personalized transplantation medicine. It is now possible to conduct comprehensive biomarker development studies of transplant organ pathologies, correlating genomic, transcriptomic and proteomic information from donor and recipient with clinical and histological phenotypes. Translation of these advances to the clinical setting will allow assessment of an individual patient's risk of allograft damage or accommodation. Transplantation biomarkers are needed for active monitoring of immunosuppression, to reduce patient morbidity, and to improve long-term allograft function and life expectancy. Here, we highlight recent pre- and post-transplantation biomarkers of acute and chronic allograft damage or adaptation, focusing on peripheral blood-based methodologies for non-invasive application. We then critically discuss current findings with respect to their future application in routine clinical transplantation medicine. Complement-system-associated SNPs present potential biomarkers that may be used to indicate the baseline risk for allograft damage prior to transplantation. The detection of antibodies against novel, non-HLA, MICA antigens, and the expression of cytokine genes and proteins and cytotoxicity-related genes have been correlated with allograft damage and are potential post-transplantation biomarkers indicating allograft damage at the molecular level, although these do not have clinical relevance yet. Several multi-gene expression-based biomarker panels have been identified that accurately predicted graft accommodation in liver transplant recipients and may be developed into a predictive biomarker assay

How many operating rooms are needed to manage non-elective surgical cases? A Monte Carlo simulation study.

BackgroundPatients often wait to have urgent or emergency surgery. The number of operating rooms (ORs) needed to minimize waiting time while optimizing resources can be determined using queuing theory and computer simulation. We developed a computer program using Monte Carlo simulation to determine the number of ORs needed to minimize patient wait times while optimizing resources.MethodsWe used patient arrival data and surgical procedure length from our institution, a tertiary-care academic medical center that serves a large diverse population. With ~4800 patients/year requiring non-elective surgery, and mean procedure length 185 min (median 150 min) we determined the number of ORs needed during the day and evening (0600-2200) and during the night (2200-0600) that resulted in acceptable wait times.ResultsSimulation of 4 ORs at day/evening and 3 ORs at night resulted in median wait time = 0 min (mean = 19 min) for emergency cases requiring surgery within 2 h, with wait time at the 95th percentile = 109 min. Median wait time for urgent cases needing surgery within 8-12 h was 34 min (mean = 136 min), with wait time at the 95th percentile = 474 min. The effect of changes in surgical length and volume on wait times was determined with sensitivity analysis.ConclusionsMonte Carlo simulation can guide decisions on how to balance resources for elective and non-elective surgical procedures

SkillBot: Towards Data Augmentation using Transformer language model and linguistic evaluation

Creating accurate, closed-domain, and machine learning-based chatbots that perform language understanding (intent prediction/detection) and language generation (response generation) requires significant datasets derived from specific knowledge domains. The common challenge in developing a closed-domain chatbot application is the lack of a comprehensive dataset. Such scarcity of the dataset can be complemented by augmenting the dataset with the use of state- of-the-art technologies existing in the field of Natural Language Processing, called ‘Transformer Models’. Our applied computing project experimented with a ‘Generative Pre-trained Transformer’ model, a unidirectional transformer decoder model for augmenting an original dataset limited in size and manually authored. This model uses unidirectional contextual representation i.e., text input is processed from left to right while computing embeddings corresponding to the input sentences. The primary goal of the project was to leverage the potential of a pre-trained transformer-based language model in augmenting an existing, but limited dataset. Additionally, the idea for using the model for text generation and appending the generated embedding to the input embedding supplied was to preserve the intent for the augmented utterances as well as to find a different form of expressions for the same intent which could be expressed by the potential users in the future. Our experiment showed improved performance for understanding language and generation for the chatbot model trained on the augmented dataset indicating that a pre-trained language model can be beneficial for the effective working of natural language-based applications such as a chatbot model trained on the augmented dataset indicating that a pre-trained language model can be beneficial for the effective working of natural language-based applications such as a chatbo

Multicentre observational cohort study of NSAIDs as risk factors for postoperative adverse events in gastrointestinal surgery

Introduction: Non-steroidal anti-inflammatory drugs (NSAIDs) are recommended as postoperative analgesia by the Enhanced Recovery After Surgery Society. Recent studies have raised concerns that NSAID administration following colorectal anastomosis may be associated with increased risk of anastomotic leak. This multicentre study aims to determine NSAIDs' safety profile following gastrointestinal resection. Methods and analysis: This prospective, multicentre cohort study will be performed over a 2-week period utilising a collaborative methodology. Consecutive adults undergoing open or laparoscopic, elective or emergency gastrointestinal resection will be included. The primary end point will be the 30-day morbidity, assessed using the Clavien-Dindo classification. This study will be disseminated through medical student networks, with an anticipated recruitment of at least 900 patients. The study will be powered to detect a 10% increase in complication rates with NSAID use. Ethics and dissemination: Following the Research Ethics Committee Chairperson's review, a formal waiver was received. This study will be registered as a clinical audit or service evaluation at each participating hospital. Dissemination will take place through previously described novel research collaborative networks

The use of reflectance measurements in the determination of diffusion of reactive dyes into cellulosic fiber

Reactive dye fixation and color yield of a dyed cellulosic fiber significantly depend on the dye diffusion into the fiber polymer system. In case of pad-dyeing processes, dye diffusion exerts a more significant influence on dye fixation and hence color yield. This article proposes a new method for determining the extent of diffusion of reactive dyes into the fiber in pad dyeings using Kubelka-Munk equation. The K/S values are used as in an equation, %D (extent of dye diffusion) = 100 - [(K/S diffusion index)/ (K/S reference) × 100]. The article introduces and explains how to determine the new K/S variables used in this equation. The new method is simple, nondestructive, relatively faster, and applicable to industrial dyehouses, and was validated by a microscopic analysis of dyed fiber cross-section carried out in this work and to the dye manufacturer's recommendations for dyebath-ingredient concentrations

Morphea (Localized Scleroderma) Presenting With Recurrent Skin and Soft Tissue Infections: A Diagnostic Dilemma.

Morphea or localized scleroderma is reported to be triggered through diverse stimuli. We present a case of morphea that presented as a non-healing wound with superimposed methicillin-sensitive Staphylococcus aureus (MSSA) infection. In our case, morphea was thought to have been potentially triggered by a post-surgical infection. We discuss the potential infectious triggers and common infections that may confound the diagnosis