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Pseudomyxoma peritonei (PMP) is a rare, progressive, slowly growing neoplastic condition which is poorly understood, with a 5-year progression-free survival rate as low as 48%. PMP is most commonly caused by appendiceal mucinous neoplasms (AMN), and understanding their genetic biology and pathogenicity may allow for the development of better novel systemic treatments to target key deleterious mutations and the implicated pathways. The primary aim of this systematic review was to identify the genetic profile of histologically confirmed human PMP or AMN samples. The secondary aim was to identify whether genetic marks could be used to predict patient survival. Ovid EMBASE, Ovid MEDLINE, PubMed, and Web of Science were searched to identify studies investigating the genetic profile of histologically-confirmed human PMP or AMN samples. We review findings of 46 studies totalling 2181 tumour samples. The most frequently identified somatic gene mutations in patients with PMP included KRAS (38–100%), GNAS (17–100%), and TP53 (5–23%); however, there were conflicting results of their effect on survival. Three studies identified molecular subtypes based on gene expression profiles classifying patients into oncogene-enriched, immune-enriched, and mixed molecular subtypes with prognostic value. This review summarises the current literature surrounding genetic aberrations in PMP and AMNs and their potential utility for targeted therapy. Given the recent advances in clinical trials to directly target KRAS and GNAS mutations in other cancers, we propose a rationale to explore these mutations in future pre-clinical studies in PMP with a view for a future clinical trial. Graphical Abstract

Background Business intelligence can give businesses the ability to understand their strengths, weaknesses, and opportunities for improvement and can help reduce uncertainty in the decision-making process. With the increasing use of electronic dental records creating more and more dental data each day, it is an opportune time to determine if the data can be coupled with business intelligence systems to improve the management decision-making process in dental organizations to result in service improvement. Methods A scoping review was performed to map the research on the use of business intelligence in dental organizations and to identify any gaps in the existing literature. This scoping review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-Scr) framework. The following databases were searched: Medline, Embase, Emcare, Cinahl, Informit, Web of Science, and Scopus. Data extracted from the articles included the organization type, purpose/aims, the software utilized, data sources utilized, outcomes measured, decision-makers involved, service benefit type, and service improvements. Results In all, 945 articles were found during the search strategy, with 25 articles selected for full-text review. Of these 25 articles, only 3 met the final inclusion in this review. All three included articles were centered around dental school organizations and all situated in the United States. All three articles demonstrated a benefit from management decision-makers utilizing business intelligence systems for improving service efficiency. Conclusion There is limited evidence to show that managers utilizing business intelligence systems in dental school organizations can lead to improvements in the organization's services. There was no evidence to support the use of a business intelligence system in other types of dental organizations. More research is required in this area.

The field of circadian research on Restless Legs Syndrome (RLS) and periodic limb movements (PLMs) is reviewed in general. RLS has five obligatory criteria for diagnosis: (1) an urge to move the legs often accompanied by uncomfortable leg sensations; (2) symptoms are worse at rest, i.e., lying or sitting; (3) there is a least partial and temporary relief of symptoms by activity, e.g., walking or stretching or bending the legs; (4) symptoms are worse later in the day or at night; and (5) mimics of RLS such as leg cramps and positional discomfort should be excluded by history and physical. In addition, RLS is frequently accompanied by PLMs, either periodic limb movements of sleep (PLMS) as determined by polysomnography or periodic limb movements while awake (PLMW) as determined by the suggested immobilization test (SIT). Since the criteria for RLS were based upon clinical experience only, an early question after the development of the criteria was whether criteria 2 and 4 were the same or different phenomena. In other words, were RLS patients worse at night only because they were lying down, and were RLS patients worse lying down only because it was night? Early circadian studies performed during recumbency at different times of the day suggest that the uncomfortable sensations, PLMS, and PLMW as well as voluntary movement in response to leg discomfort follow a similar circadian pattern with worsening at night independent of body position and independent of sleep timing or duration. Other studies demonstrated that RLS patients get worse when sitting or lying down independent of the time of day. These studies as a whole suggest that the worsening at rest and the worsening at night criteria for RLS are related but separate phenomena and that criteria 2 and 4 for RLS should be kept separate based upon the circadian studies, as had been the case previously based upon clinical grounds alone. To more fully prove the circadian rhythmicity of RLS, studies should be conducted to see if bright light shifts the signs and symptoms of RLS to a different circadian time in concert with circadian markers.

Purpose: Rhabdomyosarcomas are a major cause of cancer death in children, described with MYCN amplification and, in the alveolar subtype, transcription driven by the PAX3-FOXO1 fusion protein. Our aim was to determine the prevalence of N-Myc protein expression and the potential therapeutic effects of reducing expression in rhabdomyosarcomas, including use of an antigene strategy that inhibits transcription.Experimental Design: Protein expression was assessed by immunohistochemistry. MYCN expression was reduced in representative cell lines by RNA interference and an antigene peptide nucleic acid (PNA) oligonucleotide conjugated to a nuclear localization signal peptide. Associated gene expression changes, cell viability, and apoptosis were analyzed in vitro. As a paradigm for antigene therapy, the effects of systemic treatment of mice with rhabdomyosarcoma cell line xenografts were determined.Results: High N-Myc levels were significantly associated with genomic amplification, presence of the PAX3/7-FOXO1 fusion genes, and proliferative capacity. Sustained reduction of N-Myc levels in all rhabdomyosarcoma cell lines that express the protein decreased cell proliferation and increased apoptosis. Positive feedback was shown to regulate PAX3-FOXO1 and N-Myc levels in the alveolar subtype that critically decrease PAX3-FOXO1 levels on reducing N-Myc. Pharmacologic systemic administration of the antigene PNA can eliminate alveolar rhabdomyosarcoma xenografts in mice, without relapse or toxicity.Conclusion: N-Myc, with its restricted expression in non-fetal tissues, is a therapeutic target to treat rhabdomyosarcomas, and blocking gene transcription using antigene oligonucleotide strategies has therapeutic potential in the treatment of cancer and other diseases that has not been previously realized in vivo. Clin Cancer Res; 18(3); 796–807. ©2011 AACR.

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CCR Translation for This Article from Antitumor Activity of Sustained N-Myc Reduction in Rhabdomyosarcomas and Transcriptional Block by Antigene Therapy

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The Community Multiscale Air Quality Model (CMAQ) has been a vital tool for air quality research and management at the United States Environmental Protection Agency (U.S. EPA), and at government environmental agencies and academic institutions worldwide. CMAQ requires a significant amount of disk space to store and archive input and output. For example, an annual simulation over the contiguous United States with horizontal grid cell spacing of 12 km requires 2–3 TB of input data and can produce anywhere from 7–45 TB of output data, depending upon modelling configuration, and desired post-processing output (e.g., for evaluations or graphics). After a simulation is complete, model data are archived for several years, or even decades, to ensure the replicability of conducted research. As a result, careful disk space management is essential to optimize resources and ensure the uninterrupted progress of ongoing research and applications requiring large scale, air quality modelling. Proper disk space management may include applying optimal data compression techniques that are executed on input and output files for all CMAQ simulations. There are several (not limited to) such utilities that compress files using losslessness compression, such as GNU Gzip and Basic Leucine Zipper Domain (bzip2). A new approach is proposed in this study that reduces the precision of the air quality model emissions input to reduce storage requirements (after a losslessness compression utility is applied) and accelerate runtime. The new approach is tested using CMAQ simulations and post-processed CMAQ output to examine the impact on the air quality model performance. In total, four simulations were conducted, and nine cases were post-processed from direct simulation output to determine disk space efficiency, runtime efficiency, and model (predictive) accuracy. Three simulations were run with emissions input containing only five, four, or three significant digits. To enhance the analysis of disk space efficiency, altered emissions CMAQ simulations were additionally post-processed to contain five, four, or three significant digits. The fourth, and final, simulation was run using the full precision emissions files with no alteration. Thus, in total, 13 gridded products (four simulations and nine cases) were analysed in this study. Results demonstrate that the altered emission files reduced the disk space footprint by 6 %, 25 %, and 48 % compared to the unaltered emission files when using the bzip2 compression utility for files containing five, four, or three significant digits, respectively. Similarly, the altered output files reduced the required disk space by 19 %, 47 %, and 69 % compared to the unaltered CMAQ output files when using the bzip2 compression utility for files containing five, four, or three significant digits, respectively. For both compressed datasets, bzip2 performed better than gzip, in terms of compression size, by 5–27 % for emission data and 15–28 % for CMAQ output for files containing five, four, or three significant digits. Additionally, CMAQ runtime was reduced by 2–7 % for simulations using emission files with reduced precision data on a non-dedicated environment. Finally, the model estimated pollutant concentrations from the four simulations were compared to observed data from the U.S. EPA Air Quality System (AQS) and the Ammonia Monitoring Network (AMON). Model performance statistics were negligibly impacted (e.g., normalized mean bias differed by less than 0.01 % for all altered simulations and cases). In summary, by reducing the precision of CMAQ emissions data to five, four, or three significant digits, the simulation runtime on a non-dedicated environment was slightly reduced, disk space usage was substantially reduced, and model accuracy remained relatively unchanged compared to the base CMAQ simulation, which suggests that the precision of the emissions data could be reduced to more efficiently use computing resources while minimizing the impact on CMAQ simulations.

Background: Esophageal adenocarcinoma (EAC) is usually resistant to cytotoxic therapies and immunotherapies have gained little traction. Cancer-associated fibroblasts (CAF) are a major stromal cell population in the EAC tumor microenvironment associated with prognosis and treatment outcomes. Recent evidence suggests that cancer cell phenotypes related to EMT may determine CAF heterogeneity, but the molecular and cellular biology that underlies myofibroblast fate in EAC is not well understood. Methods: To obtain the most comprehensive profile of CAF heterogeneity in EAC, we performed histopathologic, single-cell RNA sequencing and transcriptomic analyses on 28 samples from 26 patients and prognostic validation using two EAC cohorts from genomic consortia. Results: Combining histologic and molecular profiles revealed five CAF phenotypes, including three myofibroblast phenotypes, associated with EMT-related signatures in EAC cells and cellular interactions that promote tumor progression and metastasis. We identified a specific myofibroblast subtype (CAF5) in close proximity to cancer cells and tumor vasculature with exclusive expression of TRPA1, offering a potential therapeutic vulnerability. We reconstructed CAF differentiation trajectories from esophagus-resident universal fibroblasts to identify candidate genes central to the CAF phenotype, and used this knowledge to construct a combined EMT-myofibroblast four gene signature (GSN, ATF1, ZEB2 and POSTN) that was highly prognostic in EAC and several other solid tumors. Conclusions: This study stratifies EAC patients into two prognostic groups and reports important data supporting a cancer – CAF signalling axis, promoting myofibroblastic differentiation, that may inform more effective treatment strategies.

Restless Legs Syndrome (RLS) is characterized by bothersome leg discomfort accompanied by an urge to move to obtain relief and symptoms are worse at night and on lying down. There is at least partial and temporary relief with activity. It is also an opioid responsive disorder, often accompanied by iron deficiency with or without anemia, and inflammation may be a precipitating factor in some cases. We created two in-vivo opiate receptor knock out mouse models of RLS - a triple opiate receptor knock-out mouse and a mu opiate receptor knock-out mouse. Both sets of animals were restless during the sleep period as is also true of RLS. Both of our knockout models showed statistically significantly decreased Hemoglobin and Hematocrit indicating anemia and both models showed statistically significant decreases in serum iron suggestive of either iron deficiency anemia or inflammatory anemia. The rest of the hematologic studies were not consistent enough to determine which of these two types of anemia was present in either model. An additional experiment in normal wild type mice showed a statistically significant decrease in serum iron when an opiate receptor blocker was used. To our knowledge this is the first demonstration that deficiency of endogenous opioids might play a role in the production of anemia. Our hypothesis is that an intact endogenous opiate system is necessary for red cell homeostasis. The presence of opioid receptors both on red blood cells and on various immunologically based white blood cells suggest mechanisms by which deficiency in the endogenous opiate system could cause anemia of either the iron deficiency or inflammatory types. The administration of opioid agonists or antagonists to iron deficient cultures of red blood cell precursors is a next step in determining the role of the endogenous opiate system in the maintenance of red cell homeostasis and in the possible prevention of iron deficiency or inflammatory anemia where iron dysregulation is key.

The mammalian respiratory system or lung is a tree-like branching structure, and the main site of gas exchange with the external environment. Structurally, the lung is broadly classified into the proximal (or conducting) airways and the distal alveolar region, where the gas exchange occurs. In parallel with the respiratory tree, the pulmonary vasculature starts with large pulmonary arteries that subdivide rapidly ending in capillaries adjacent to alveolar structures to enable gas exchange. The NOTCH signalling pathway plays an important role in lung development, differentiation and regeneration post-injury. Signalling via the NOTCH pathway is mediated through activation of four NOTCH receptors (NOTCH1-4), with each receptor capable of regulating unique biological processes. Dysregulation of the NOTCH pathway has been associated with development and pathophysiology of multiple adult acute and chronic lung diseases. This includes accumulating evidence that alteration of NOTCH3 signalling plays an important role in the development and pathogenesis of chronic obstructive pulmonary disease, lung cancer, asthma, idiopathic pulmonary fibrosis and pulmonary arterial hypertension. Herein, we provide a comprehensive summary of the role of NOTCH3 signalling in regulating repair/regeneration of the adult lung, its association with development of lung disease and potential therapeutic strategies to target its signalling activity.

This work performs a direct comparison between generalized polynomial chaos (GPC) expansion techniques applied to structural acoustic problems. Broadly, the GPC techniques are grouped in two categories: , where the stochastic sampling is predetermined according to a quadrature rule; and , where an arbitrary selection of points is used as long as they are a representative sample of the random input. As a baseline comparison, Monte Carlo type simulations are also performed although they take many more sampling points. The test problems considered include both canonical and more applied cases that exemplify the features and types of calculations commonly arising in vibrations and acoustics. A range of different numbers of random input variables are considered. The primary point of comparison between the methods is the number of sampling points they require to generate an accurate GPC expansion. This is due to the general consideration that the most expensive part of a GPC analysis is evaluating the deterministic problem of interest; thus the method with the fewest sampling points will often be the fastest. Accuracy of each GPC expansion is judged using several metrics including basic statistical moments as well as features of the actual reconstructed probability density function.

Objective/background Adults with multiple sclerosis (MS) often present with conditions that mimic restless legs syndrome (RLS), thereby adding complexity into the assessment of RLS severity. The current gold-standard measures of RLS severity rely on a fixed seven-day time frame, which limits the ability of these measures for studying acute changes in RLS severity. The present study examined if subjective and objective scores from the suggested immobilization test (SIT) provide a valid and reliable acute measure of RLS severity in persons with MS. Patients/methods Participants with MS and RLS (n = 20) and MS without RLS (n = 20) were matched by age, gender, and disability. All participants completed validated questionnaires for RLS severity followed by the SIT, conducted at 18:00 (±15 min) on the same day of the week for two consecutive weeks. Participants wore accelerometer devices for seven nights to capture periodic limb movements (PLMs) during the night. Results Self-reported RLS severity during the SIT had excellent construct validity and convergent validity, but moderate test-retest reliability. Device-measured PLMs, while not themselves a direct measure of RLS severity, were significantly associated with PLMs during the night and had excellent test-retest reliability during the SIT in adults with MS. Conclusions Our results suggest that the SIT represents a valid acute measure for capturing self-reported sensory aspects of RLS severity and should be considered in future research and clinical practice as a standardized acute measure of subjective RLS severity in adults with MS who present with RLS.

Only survey studies have linked specific individual psychiatric disorders such as anxiety, depression and schizophrenia to Restless Legs Syndrome (RLS), Periodic Limb Movements in Sleep (PLMS) or both. We therefore aim to polysomnographically characterize sleep in a sample of physician-based, newly diagnosed cases of RLS with various ICD-10 psychiatric diagnoses. Retrospective analysis of data from a convenience sample of psychiatric patients (n = 43) per standard clinical sleep disorder cut-offs was conducted. Next, a cluster analysis was performed on the sleep data, taking into account the psychiatric diagnosis, comorbid non-psychiatric somatic problems and medication. We found that 37.2% of our sample showed clinically significant PLMS ≥ 15 and 76.5% exhibited an apnea hypopnea index (AHI) ≥ 5. Sleep structure was unaltered apart from the PLMS-related parameters. Two clusters were statistically identified: Cluster 1 primarily representing recurrent major depressive issues and Cluster 2 representing present but not predominant mood symptomatology as well as mixed disorders with personality problems. The known confounders were controlled. A PLMS index ≥ 15 was differentially distributed among the two clusters with Cluster 1: 10 out of 17 with PLMS index ≥ 15, Cluster 2: 1 out of 16 with PLMS index ≥15, whilst AHI was not different. Patients in Cluster 1 have a higher rate of periodic leg movements than patients in Cluster 2. This suggests that the high association with PLMS is primarily driven by affective disorders. Our findings warrant questioning of RLS symptomatology in patients with psychiatric conditions.

SARS-CoV-2, the virus that causes COVID-19, is constantly mutating, leading to new variants (1). Variants have the potential to affect transmission, disease severity, diagnostics, therapeutics, and natural and vaccine-induced immunity. In November 2020, CDC established national surveillance for SARS-CoV-2 variants using genomic sequencing. As of May 6, 2021, sequences from 177,044 SARS-CoV-2-positive specimens collected during December 20, 2020-May 6, 2021, from 55 U.S. jurisdictions had been generated by or reported to CDC. These included 3,275 sequences for the 2-week period ending January 2, 2021, compared with 25,000 sequences for the 2-week period ending April 24, 2021 (0.1% and 3.1% of reported positive SARS-CoV-2 tests, respectively). Because sequences might be generated by multiple laboratories and sequence availability varies both geographically and over time, CDC developed statistical weighting and variance estimation methods to generate population-based estimates of the proportions of identified variants among SARS-CoV-2 infections circulating nationwide and in each of the 10 U.S. Department of Health and Human Services (HHS) geographic regions.* During the 2-week period ending April 24, 2021, the B.1.1.7 and P.1 variants represented an estimated 66.0% and 5.0% of U.S. SARS-CoV-2 infections, respectively, demonstrating the rise to predominance of the B.1.1.7 variant of concern† (VOC) and emergence of the P.1 VOC in the United States. Using SARS-CoV-2 genomic surveillance methods to analyze surveillance data produces timely population-based estimates of the proportions of variants circulating nationally and regionally. Surveillance findings demonstrate the potential for new variants to emerge and become predominant, and the importance of robust genomic surveillance. Along with efforts to characterize the clinical and public health impact of SARS-CoV-2 variants, surveillance can help guide interventions to control the COVID-19 pandemic in the United States.

The 21st Century Cures Act (Cures Act), signed into law in 2016, was designed to advance new therapies by modernizing clinical trials, funding research initiatives, and accelerating the development and use of health information technology. To analyze the current issues in cancer care related to the implementation and impact of the Cures Act, NCCN convened a multistakeholder working group. Participants discussed the legislation’s impact on the oncology community since enactment and identified the remaining gaps and challenges as experienced by stakeholders. In June 2020, the policy recommendations of the working group were presented at the virtual NCCN Policy Summit: Accelerating Advances in Cancer Care Research: A Lookback at the 21st Century Cures Act in 2020. The summit consisted of informative discussions and a multistakeholder panel to explore the recommendations and the future of the Cures Act. This article explores identified policy recommendations from the NCCN Working Group and the NCCN Policy Summit, and analyzes opportunities to advance innovative cancer care and patient access to data.

Marine fish movement plays a critical role in ecosystem functioning and is increasingly studied with acoustic telemetry. Traditionally, this research has focused on single species and small spatial scales. However, integrated tracking networks, such as the Integrated Tracking of Aquatic Animals in the Gulf of Mexico (iTAG) network, are building the capacity to monitor multiple species over larger spatial scales. We conducted a synthesis of passive acoustic monitoring data for 29 species (889 transmitters), ranging from large top predators to small consumers, monitored along the west coast of Florida, USA, over 3 yr (2016-2018). Space use was highly variable, with some groups using all monitored areas and others using only the area where they were tagged. The most extensive space use was found for Atlantic tarpon Megalops atlanticus and bull sharks Carcharhinus leucas. Individual detection patterns clustered into 4 groups, ranging from occasionally detected long-distance movers to frequently detected juvenile or adult residents. Synchronized, alongshore, long-distance movements were found for Atlantic tarpon, cobia Rachycentron canadum, and several elasmobranch species. These movements were predominantly northbound in spring and southbound in fall. Detections of top predators were highest in summer, except for nearshore Tampa Bay where the most detections occurred in fall, coinciding with large red drum Sciaenops ocellatus spawning aggregations. We discuss the future of collaborative telemetry research, including current limitations and potential solutions to maximize its impact for understanding movement ecology, conducting ecosystem monitoring, and supporting fisheries management.