APPLICATIONS ON TOP OF DNA CENTER: AUTOMATIC CONFIGURATION VALIDATION BASED ON TOPOLOGY FOR BASIC INTEROPERATION

A rule based service is provided for Configuration Simulation and Validation (CSV) for the devices managed on given network. With an understanding of the architecture of a network, the service can be employed to determine which devices need to be in the same Internet Protocol (IP) subnet. The service can be employed to suggest one or more configuration changes to the administrator such as, changes to address as a potential misconfiguration, improve operation, etc

APPLICATIONS ON TOP OF DNA CENTER: TOPOLOGY EVOLUTION BASED ON CUSTOMER NETWORK DYNAMICS

Techniques are provided for detecting and managing dynamically changing loads in a network, for example, during large scale events that may cause a bottleneck such as a stadium game event or a musical concert. These techniques allow network administrators to improve network efficiency by monitoring and tweaking the network capabilities in order to handle network load during periods of high demand without a detailed background knowledge of the network

WIRELESS NETWORK LOAD CORROBORATION USING MACHINE LEARNING (ML) BASED VIDEO ANALYTICS

Presented herein are techniques for correlating the output of a crowd counting machine learning (ML) algorithm, which operates on surveillance video, with observed network load to determine if a load spike is due to a valid network usage or an attacker trying to sabotage the network. The techniques presented herein include vision field classification based on access point (AP) coverage, linking of vision fields to AP coverage in DNAC UI, and consensus-based threat assessment and alerts

MACHINE-LEARNING OF LEADING INDICATORS FROM A PLURALITY OF SERVICES TO PERFORM MEMORY MANAGEMENT ON ANOTHER PLURALITY OF SERVICES WITH CORRELATING MEMORY USAGE PROFILE

Presented herein are techniques for machine-learning of leading indicators from a plurality of services and the use of these leading indicators to perform memory management operations on another plurality of services with correlating memory usage profiles. The techniques presented herein include collecting, as leading indicators, service event logs from a plurality of services. Machine-learning is then used to cross-correlate the leading indicators with memory use pattern snapshots at subsequent times for another plurality of services to predict the optimal when, how much, and how for execution of memory garbage collection on the latter set of services

OUTCOME OF MACHINE REASONING IN A NETWORK MANAGEMENT SYSTEM TOPOLOGY VIEW

A technique is described herein to provide a visualization overlaid on a network topology that illustrates the cascading impact of a network event before it happens. The technique may empower a network administrator to perform one or more steps to mitigate the issue and/or minimize its impact before the issue manifests itself into a critical network condition

Prediction of Coronary Risk by SYNTAX and Derived Scores Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery

The introduction of the SYNTAX (Synergy Between PCI With Taxus and Cardiac Surgery) score has prompted a renewed interest for angiographic risk stratification in patients undergoing percutaneous coronary intervention. Syntax score is based on qualitative and quantitative characterization of coronary artery disease by including 11 angiographic variables that take into consideration lesion location and characteristics. Thus far, this score has been shown to be an effective tool to risk-stratify patients with complex coronary artery disease undergoing percutaneous coronary intervention in the landmark SYNTAX trial, as well as in other clinical settings. This review provides an overview of its current applications, including its integration with other nonangiographic clinical scores, and explores future applications of the SYNTAX and derived scores. (C) 2013 by the American College of Cardiology FoundationAbbott VascularDoris Duke Charitable FoundationColumbia Univ, Med Ctr, New York, NY 10022 USACardiovasc Res Fdn, New York, NY USAUniv Bologna, Ist Cardiol, Bologna, ItalyUniversidade Federal de São Paulo, Hosp Israelita Albert Einstein, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, São Paulo, BrazilUniv Montreal, Hop Sacre Coeur Montreal, Montreal, PQ, CanadaUniversidade Federal de São Paulo, Hosp Israelita Albert Einstein, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, São Paulo, BrazilWeb of Scienc

Neuronal intermediate filament IgGs in CSF: Autoimmune Axonopathy Biomarkers

Objectives: To describe CSF-defined neuronal intermediate filament (NIF) autoimmunity. Methods: NIF-IgG CSF-positive patients (41, 0.03% of 118599 tested, 1996-2019) were included (serum was neither sensitive nor specific). Criteria-based patient NIF-IgG staining of brain and myenteric NIFs was detected by indirect immunofluorescence assay (IFA); NIF-specificity was confirmed by cell-based assays (CBAs, alpha internexin, neurofilament light [NF-L]), heavy-[NF-H] chain). Results: Sixty-one percent of 41 patients were men, median age, 61 years (range, 21-88). Syndromes were encephalopathy predominant (23), cerebellar ataxia predominant (11), or myeloradiculoneuropathies (7). MRI abnormalities (T2 hyperintensities of brain, spinal cord white matter tracts. and peripheral nerve axons) and neurophysiologic testing (EEG, EMG, evoked potentials) co-localized with clinical neurological phenotypes (multifocal in 29%). Thirty patients (73%) had 65 1 immunological perturbation: cancer (paraneoplastic), 22; systemic infection (parainfectious [including ehrlichosis, 3] or HIV), 7; checkpoint-inhibitor cancer immunotherapy, 4; other, 5. Cancers were as follows: neuroendocrine-lineage carcinomas, 12 (small cell, 6; Merkel cell, 5; pancreatic, 1 [11/12 had NF-L-IgG detected, versus 8/29 others, P = 0.0005]) and other, 11. Onset was predominantly subacute (92%) and accompanied by inflammatory CSF (75%), and immunotherapy response (77%). In contrast, CSF controls (15684 total) demonstrated NIF-IgG negativity (100% of test validation controls), and low frequencies of autoimmune diagnoses (20% of consecutively referred clinical specimens) and neuroendocrine-lineage carcinoma diagnosis (3.1% vs. 30% of NIF cases), P < 0.0001. Median NF-L protein concentration was higher in 8 NF-L-IgG-positive patients (median, 6718 ng/L) than 16 controls. Interpretation: Neurological autoimmunity, defined by CSF-detected NIF-IgGs, represents a continuum of treatable axonopathies, sometimes paraneoplastic or parainfectious

Effect of temperature and time delay in centrifugation on stability of select biomarkers of nutrition and non-communicable diseases in blood samples

Introduction: Preanalytical conditions are critical for blood sample integrity and poses challenge in surveys involving biochemical measurements. A cross sectional study was conducted to assess the stability of select biomarkers at conditions that mimic field situations in surveys. Material and methods: Blood from 420 volunteers was exposed to 2 – 8 °C, room temperature (RT), 22 – 30 °C and > 30 °C for 30 min, 6 hours, 12 hours and 24 hours prior to centrifugation. After different exposures, whole blood (N = 35) was used to assess stability of haemoglobin, HbA1c and erythrocyte folate; serum (N = 35) for assessing stability of ferritin, C-reactive protein (CRP), vitamins B12, A and D, zinc, soluble transferrin receptor (sTfR), total cholesterol, high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL), tryglicerides, albumin, total protein and creatinine; and plasma (N = 35) was used for glucose. The mean % deviation of the analytes was compared with the total change limit (TCL), computed from analytical and intra-individual imprecision. Values that were within the TCL were deemed to be stable. Result: Creatinine (mean % deviation 14.6, TCL 5.9), haemoglobin (16.4%, TCL 4.4) and folate (33.6%, TCL 22.6) were unstable after 12 hours at 22- 30°C, a temperature at which other analytes were stable. Creatinine was unstable even at RT for 12 hours (mean % deviation: 10.4). Albumin, CRP, glucose, cholesterol, LDL, triglycerides, vitamins B12 and A, sTfR and HbA1c were stable at all studied conditions. Conclusion: All analytes other than creatinine, folate and haemoglobin can be reliably estimated in blood samples exposed to 22-30°C for 12 hours in community-based studies

Gray Matter Changes in Parkinson's and Alzheimer's Disease and Relation to Cognition

Purpose of Review We summarize structural (s)MRI findings of gray matter (GM) atrophy related to cognitive impairment in Alzheimer's disease (AD) and Parkinson's disease (PD) in light of new analytical approaches and recent longitudinal studies results. Recent Findings The hippocampus-to-cortex ratio seems to be the best sMRI biomarker to discriminate between various AD subtypes, following the spatial distribution of tau pathology, and predict rate of cognitive decline. PD is clinically far more variable than AD, with heterogeneous underlying brain pathology. Novel multivariate approaches have been used to describe patterns of early subcortical and cortical changes that relate to more malignant courses of PD. New emerging analytical approaches that combine structural MRI data with clinical and other biomarker outcomes hold promise for detecting specific GM changes in the early stages of PD and preclinical AD that may predict mild cognitive impairment and dementia conversion

Impact of e-ASPECTS software on the performance of physicians compared to a consensus ground truth: a multi-reader, multi-case study

BackgroundThe Alberta Stroke Program Early CT Score (ASPECTS) is used to quantify the extent of injury to the brain following acute ischemic stroke (AIS) and to inform treatment decisions. The e-ASPECTS software uses artificial intelligence methods to automatically process non-contrast CT (NCCT) brain scans from patients with AIS affecting the middle cerebral artery (MCA) territory and generate an ASPECTS. This study aimed to evaluate the impact of e-ASPECTS (Brainomix, Oxford, UK) on the performance of US physicians compared to a consensus ground truth.MethodsThe study used a multi-reader, multi-case design. A total of 10 US board-certified physicians (neurologists and neuroradiologists) scored 54 NCCT brain scans of patients with AIS affecting the MCA territory. Each reader scored each scan on two occasions: once with and once without reference to the e-ASPECTS software, in random order. Agreement with a reference standard (expert consensus read with reference to follow-up imaging) was evaluated with and without software support.ResultsA comparison of the area under the curve (AUC) for each reader showed a significant improvement from 0.81 to 0.83 (p = 0.028) with the support of the e-ASPECTS tool. The agreement of reader ASPECTS scoring with the reference standard was improved with e-ASPECTS compared to unassisted reading of scans: Cohen's kappa improved from 0.60 to 0.65, and the case-based weighted Kappa improved from 0.70 to 0.81.ConclusionDecision support with the e-ASPECTS software significantly improves the accuracy of ASPECTS scoring, even by expert US neurologists and neuroradiologists