A Specific Network Link and Path Likelihood Prediction Tool

Communications have always been a crucial part of any military operation. As the pace of warfare and the technological complexity of weaponry have increased, so has the need for rapid information to assess battlefield conditions. Message passing across a network of communication nodes allowed commanders to communicate with their forces. It is clear that an accurate prediction of communication usage through a network will provide commanders with useful intelligence of friendly and unfriendly activities. Providing a specific network link and path likelihood prediction tool gives strategic military commanders additional intelligence information and enables them to manage their limited resources more efficiently. In this study, Dijkstra\u27s algorithm has been modified to allow the Queueing Network Analyzer\u27s (QNA) analysis output to act as a node\u27s goodness metric. QNA\u27s calculation of the expected Total Sojourn Time for the completion of queueing and service in a node provides accurate measurement of expected congestion. The modified Dijkstra\u27s algorithm in the Generalized Network Analyzer (GNA) is verified and empirically validated to properly deliver traffic. It appropriately generates the fastest traffic path from a start node to a destination node. This implementation includes notification if input parameters exceed the network\u27s processing capability. GNA\u27s Congestion Control displays notification and informs the user certain network input parameters must be lowered (PTR or BSTR) or where certain nodes must be improved to maintain node stability. With this unstable node identification, users can determine which node needs attention and improvements. Once this instability is removed, a good QoS is achieved and analysis proceeds

A functional genomic and proteomic perspective of sea urchin calcium signaling and egg activation

AbstractThe sea urchin egg has a rich history of contributions to our understanding of fundamental questions of egg activation at fertilization. Within seconds of sperm–egg interaction, calcium is released from the egg endoplasmic reticulum, launching the zygote into the mitotic cell cycle and the developmental program. The sequence of the Strongylocentrotus purpuratus genome offers unique opportunities to apply functional genomic and proteomic approaches to investigate the repertoire and regulation of Ca2+ signaling and homeostasis modules present in the egg and zygote. The sea urchin “calcium toolkit” as predicted by the genome is described. Emphasis is on the Ca2+ signaling modules operating during egg activation, but the Ca2+ signaling repertoire has ramifications for later developmental events and adult physiology as well. Presented here are the mechanisms that control the initial release of Ca2+ at fertilization and additional signaling components predicted by the genome and found to be expressed and operating in eggs at fertilization. The initial release of Ca2+ serves to coordinate egg activation, which is largely a phenomenon of post-translational modifications, especially dynamic protein phosphorylation. Functional proteomics can now be used to identify the phosphoproteome in general and specific kinase targets in particular. This approach is described along with findings to date. Key outstanding questions regarding the activation of the developmental program are framed in the context of what has been learned from the genome and how this knowledge can be applied to functional studies

AR2, a novel automatic muscle artifact reduction software method for ictal EEG interpretation: Validation and comparison of performance with commercially available software.

Objective: To develop a novel software method (AR2) for reducing muscle contamination of ictal scalp electroencephalogram (EEG), and validate this method on the basis of its performance in comparison to a commercially available software method (AR1) to accurately depict seizure-onset location. Methods: A blinded investigation used 23 EEG recordings of seizures from 8 patients. Each recording was uninterpretable with digital filtering because of muscle artifact and processed using AR1 and AR2 and reviewed by 26 EEG specialists. EEG readers assessed seizure-onset time, lateralization, and region, and specified confidence for each determination. The two methods were validated on the basis of the number of readers able to render assignments, confidence, the intra-class correlation (ICC), and agreement with other clinical findings. Results: Among the 23 seizures, two-thirds of the readers were able to delineate seizure-onset time in 10 of 23 using AR1, and 15 of 23 using AR2 (

Hospital characteristics and patient populations served by physician owned and non physician owned orthopedic specialty hospitals

<p>Abstract</p> <p>Background</p> <p>The emergence of physician owned specialty hospitals focusing on high margin procedures has generated significant controversy. Yet, it is unclear whether physician owned specialty hospitals differ significantly from non physician owned specialty hospitals and thus merit the additional scrutiny that has been proposed. Our objective was to assess whether physician owned specialty orthopedic hospitals and non physician owned specialty orthopedic hospitals differ with respect to hospital characteristics and patient populations served.</p> <p>Methods</p> <p>We conducted a descriptive study using Medicare data of beneficiaries who underwent total hip replacement (THR) (N = 10,478) and total knee replacement (TKR) (N = 15,312) in 29 physician owned and 8 non physician owned specialty orthopedic hospitals during 1999–2003. We compared hospital characteristics of physician owned and non physician owned specialty hospitals including procedural volumes of major joint replacements (THR and TKR), hospital teaching status, and for profit status. We then compared demographics and prevalence of common comorbid conditions for patients treated in physician owned and non physician owned specialty hospitals. Finally, we examined whether the socio-demographic characteristics of the neighborhoods where physician owned and non physician owned specialty hospitals differed, as measured by zip code level data.</p> <p>Results</p> <p>Physician owned specialty hospitals performed fewer major joint replacements on Medicare beneficiaries in 2003 than non physician owed specialty hospitals (64 vs. 678, P < .001), were less likely to be affiliated with a medical school (6% vs. 43%, P = .05), and were more likely to be for profit (94% vs. 28%, P = .001). Patients who underwent major joint replacement in physician owned specialty hospitals were less likely to be black than patients in non physician owned specialty hospitals (2.5% vs. 3.1% for THR, P = .15; 1.8% vs. 6.3% for TKR, P < .001), yet physician owned specialty hospitals were located in neighborhoods with a higher proportion of black residents (8.2% vs. 6.7%, P = .76). Patients in physician owned hospitals had lower rates of most common comorbid conditions including heart failure and obesity (P < .05 for both).</p> <p>Conclusion</p> <p>Physician owned specialty orthopedic hospitals differ significantly from non physician owned specialty orthopedic hospitals and may warrant the additional scrutiny policy makers have proposed.</p

Automated High-Content Live Animal Drug Screening Using C. elegans Expressing the Aggregation Prone Serpin α1-antitrypsin Z

The development of preclinical models amenable to live animal bioactive compound screening is an attractive approach to discovering effective pharmacological therapies for disorders caused by misfolded and aggregation-prone proteins. In general, however, live animal drug screening is labor and resource intensive, and has been hampered by the lack of robust assay designs and high throughput work-flows. Based on their small size, tissue transparency and ease of cultivation, the use of C. elegans should obviate many of the technical impediments associated with live animal drug screening. Moreover, their genetic tractability and accomplished record for providing insights into the molecular and cellular basis of human disease, should make C. elegans an ideal model system for in vivo drug discovery campaigns. The goal of this study was to determine whether C. elegans could be adapted to high-throughput and high-content drug screening strategies analogous to those developed for cell-based systems. Using transgenic animals expressing fluorescently-tagged proteins, we first developed a high-quality, high-throughput work-flow utilizing an automated fluorescence microscopy platform with integrated image acquisition and data analysis modules to qualitatively assess different biological processes including, growth, tissue development, cell viability and autophagy. We next adapted this technology to conduct a small molecule screen and identified compounds that altered the intracellular accumulation of the human aggregation prone mutant that causes liver disease in α1-antitrypsin deficiency. This study provides powerful validation for advancement in preclinical drug discovery campaigns by screening live C. elegans modeling α1-antitrypsin deficiency and other complex disease phenotypes on high-content imaging platforms

Early immune factors associated with the development of post-acute sequelae of SARS-CoV-2 infection in hospitalized and non-hospitalized individuals

BackgroundInfection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to post-acute sequelae of SARS-CoV-2 (PASC) that can persist for weeks to years following initial viral infection. Clinical manifestations of PASC are heterogeneous and often involve multiple organs. While many hypotheses have been made on the mechanisms of PASC and its associated symptoms, the acute biological drivers of PASC are still unknown.MethodsWe enrolled 494 patients with COVID-19 at their initial presentation to a hospital or clinic and followed them longitudinally to determine their development of PASC. From 341 patients, we conducted multi-omic profiling on peripheral blood samples collected shortly after study enrollment to investigate early immune signatures associated with the development of PASC.ResultsDuring the first week of COVID-19, we observed a large number of differences in the immune profile of individuals who were hospitalized for COVID-19 compared to those individuals with COVID-19 who were not hospitalized. Differences between individuals who did or did not later develop PASC were, in comparison, more limited, but included significant differences in autoantibodies and in epigenetic and transcriptional signatures in double-negative 1 B cells, in particular.ConclusionsWe found that early immune indicators of incident PASC were nuanced, with significant molecular signals manifesting predominantly in double-negative B cells, compared with the robust differences associated with hospitalization during acute COVID-19. The emerging acute differences in B cell phenotypes, especially in double-negative 1 B cells, in PASC patients highlight a potentially important role of these cells in the development of PASC