Virginia Commonwealth University

About: Virginia Commonwealth University is a education organization based out in Richmond, Virginia, United States. It is known for research contribution in the topics: Population & Health care. The organization has 23822 authors who have published 49587 publications receiving 1787046 citations. The organization is also known as: VCU.

Guidelines for the management of rheumatoid arthritis: American College of Rheumatology Ad Hoc Committee on Clinical Guidelines

Abstract: RA is a chronic progressive polyarthritis (with varying systemic features) associated with substantial disability and economic losses. Successful treatment to limit joint damage and functional loss requires early diagnosis and timely initiation of disease-modifying agents. The goal of treatment is to arrest the disease and to achieve remission. Although remission rarely occurs, patients may still benefit from pharmacologic, nonpharmacologic, and if necessary, surgical interventions. Optimal longitudinal treatment requires comprehensive coordinated care and the expertise of a number of providers. Essential components of management include 1) establishment of the diagnosis of RA (versus other forms of polyarthritis), 2) systematic and regular evaluation of disease activity, 3) patient education/rehabilitation interventions, and initial treatment with NSAIDs, 4) use of DMARDs, 5) possible use of local or low-dose oral glucocorticoids, 6) minimization of the impact on the individual's function, 7) assessment of the adequacy of the treatment program, and 8) general health maintenance.

Rugged and breathable forms of stretchable electronics with adherent composite substrates for transcutaneous monitoring

Abstract: Research in stretchable electronics involves fundamental scientific topics relevant to applications with importance in human healthcare. Despite significant progress in active components, routes to mechanically robust construction are lacking. Here, we introduce materials and composite designs for thin, breathable, soft electronics that can adhere strongly to the skin, with the ability to be applied and removed hundreds of times without damaging the devices or the skin, even in regions with substantial topography and coverage of hair. The approach combines thin, ultralow modulus, cellular silicone materials with elastic, strain-limiting fabrics, to yield a compliant but rugged platform for stretchable electronics. Theoretical and experimental studies highlight the mechanics of adhesion and elastic deformation. Demonstrations include cutaneous optical, electrical and radio frequency sensors for measuring hydration state, electrophysiological activity, pulse and cerebral oximetry. Multipoint monitoring of a subject in an advanced driving simulator provides a practical example.

A common cold virus, rhinovirus 16, potentiates airway inflammation after segmental antigen bronchoprovocation in allergic subjects.

Abstract: Many patients with asthma have increased wheezing with colds We hypothesized that rhinovirus colds might increase asthma by augmenting airway allergic responses (histamine release and eosinophil influx) after antigen challenge Seven allergic rhinitis patients and five normal volunteers were infected with rhinovirus type 16 (RV16) and evaluated by segmental bronchoprovocation and bronchoalveolar lavage Segmental challenge with saline and antigen was performed 1 mo before infection, during the acute infection, and 1 mo after infection Lavage was performed immediately and 48 h after antigen challenge Data were analyzed by two-way analysis of variance, and a P value of < or = 005 was considered to be significant All volunteers inoculated with RV16 developed an acute respiratory infection BAL fluid obtained from allergic rhinitis subjects during the acute viral infection, and 1 mo after infection, showed the following significant RV16-associated changes after antigen challenge: (a) an enhanced release of histamine immediately after local antigen challenge; (b) persistent histamine leak 48 h afterwards; and (c) a greater recruitment of eosinophils to the airway 48 h after challenge These changes were not seen in non-allergic volunteers infected with RV16 and challenged with antigen, nor in allergic volunteers repetitively challenged with antigen but not infected with RV16, nor in RV16 infected allergic volunteers sham challenged with saline We conclude that rhinovirus upper respiratory infection significantly augments immediate and late allergic responses in the airways of allergic individuals after local antigen challenge These data suggest that one mechanism of increased asthma during a cold is an accentuation of allergic responses in the airway which may then contribute to bronchial inflammation

Effects of interleukin-1 blockade with anakinra on adverse cardiac remodeling and heart failure after acute myocardial infarction [from the Virginia Commonwealth University-Anakinra Remodeling Trial (2) (VCU-ART2) pilot study].

Abstract: A first pilot study of interleukin-1 blockade in ST-segment elevation acute myocardial infarction showed improved remodeling. In the present second pilot study, we enrolled 30 patients with clinically stable ST-segment elevation acute myocardial infarction randomized to anakinra, recombinant interleukin-1 receptor antagonist, 100 mg/day for 14 days or placebo in a double-blind fashion. The primary end point was the difference in the interval change in left ventricular (LV) end-systolic volume index between the 2 groups within 10 to 14 weeks. The secondary end points included changes in the LV end-diastolic volume index, LV ejection fraction, and C-reactive protein levels. No significant changes in end-systolic volume index, LV end-diastolic volume index, or LV ejection fraction were seen in the placebo group. Compared to placebo, treatment with anakinra led to no measurable differences in these parameters. Anakinra significantly blunted the increase in C-reactive protein between admission and 72 hours (+0.8 mg/dl, interquartile range −6.4 to +4.2, vs +21.1 mg/dl, interquartile range +8.7 to +36.6, p = 0.002), which correlated with the changes in LV end-diastolic volume index and LV end-systolic volume index at 10 to 14 weeks (R = +0.83, p = 0.002, and R = +0.55, p = 0.077, respectively). One patient in the placebo group (7%) died. One patient (7%) in the anakinra group developed recurrent acute myocardial infarction. More patients were diagnosed with new-onset heart failure in the placebo group (4, 27%) than in the anakinra group (1, 7%; p = 0.13). When the data were pooled with those from the first Virginia Commonwealth University-Anakinra Remodeling Trial (n = 40), this difference reached statistical significance (30% vs 5%, p = 0.035). In conclusion, interleukin-1 blockade with anakinra blunted the acute inflammatory response associated with ST-segment elevation acute myocardial infarction. Although it failed to show a statistically significant effect on LV end-systolic volume index, LV end-diastolic volume index, or LV ejection fraction in this cohort of clinically stable patients with near-normal LV dimensions and function, anakinra led to a numerically lower incidence of heart failure.

Channel State Information Prediction for 5G Wireless Communications: A Deep Learning Approach

Abstract: Channel state information (CSI) estimation is one of the most fundamental problems in wireless communication systems. Various methods, so far, have been developed to conduct CSI estimation. However, they usually require high computational complexity, which makes them unsuitable for 5G wireless communications due to employing many new techniques (e.g., massive MIMO, OFDM, and millimeter-Wave (mmWave)). In this paper, we propose an efficient online CSI prediction scheme, called OCEAN, for predicting CSI from historical data in 5G wireless communication systems. Specifically, we first identify several important features affecting the CSI of a radio link and a data sample consists of the information of the features and the CSI. We then design a learning framework that is an integration of a CNN (convolutional neural network) and a long short term with memory (LSTM) network. We also further develop an offline-online two-step training mechanism, enabling the prediction results to be more stable when applying it to practical 5G wireless communication systems. To validate OCEAN's efficacy, we consider four typical case studies, and conduct extensive experiments in the four scenarios, i.e., two outdoor and two indoor scenarios. The experiment results show that OCEAN not only obtains the predicted CSI values very quickly but also achieves highly accurate CSI prediction with up to 2.650-3.457 percent average difference ratio (ADR) between the predicted and measured CSI.