It has been shown that a widely quoted formula for estimating medical linac photon skyshine equivalent doses is erroneous. Monte Carlo calculations have been performed to develop an easy method for quickly and accurately estimating skyshine radiation levels and to gain improved physical insight into the skyshine phenomenon. Calculations of linac photon skyshine have been performed for 4, 6, 10, 15, and 18 MV beams for 10 × 10 cm2 and 40 × 40 cm2 fields and for a range of room dimensions and roof thicknesses. The effect of flattening filter free beams has been considered. Air kerma rates (AKRs) can be accurately fitted to a simple algebraic formula that is a function of the horizontal distance from the isocenter with a single energy dependent fitting parameter. The AKR, at a height of 1.3 m above level ground, reaches a local maximum at a distance dmax = 1.5dw + 1.1h, where dw is the horizontal distance from the isocenter to the outside of the side wall, and h is the vertical distance from the isocenter to the top of the roof. For thin roofs, low energy beams lead to significantly more skyshine than high energy beams because low energy photons are more easily scattered through large angles. In the absence of a roof, the maximum skyshine dose rate is on the order of 8 × 10-7 times the dose rate at isocenter. The average energy of the skyshine photons is about 0.15 MeV, and it is remarkably independent of almost all parameters. A simple methodology is outlined for the evaluation of photon skyshine.Structure-based virtual screening of the Enamine database of 1.7 million compounds followed by WaterMap calculations (a molecular-dynamics-simulation-based method) was applied to identify novel acetylcholinesterase (AChE) inhibitors. The inhibitory potency of 29 selected compounds against electric eel (ee) AChE was determined using Ellman’s method. Three compounds were found to be active (success rate 10 %). For the most potent compound (∼40 % inhibition at 10 μM), 20 derivatives were discovered based on the Enamine similarity search. Finally, five compounds were found to be promising (IC50 ranged from 6.3 μM to 17.5 μM) inhibitors of AChE. The performed similarity and fragment analysis confirmed significant structural novelty for these AChE inhibitors. Toxicity/safety of selected compounds was determined in zebrafish model.

To accelerate the use of outcome measures in rheumatology, we developed and evaluated a natural language processing (NLP) pipeline for extracting these measures from free-text outpatient rheumatology notes within the ACR’s Rheumatology Informatics System for Effectiveness (RISE) registry.

We included all patients in RISE (2015 to 2018). The NLP pipeline extracted scores corresponding to eight measures of RA disease activity (DA) and functional status (FS) documented in outpatient rheumatology notes. Score extraction performance was evaluated by chart review, and we assessed agreement with scores documented in structured data. We conducted an external validation of our NLP pipeline using data from rheumatology notes from an academic medical center that is not included in the RISE registry.

We processed over 34 million notes from 854,628 patients, 158 practices, and 24 EHR systems from RISE. Manual chart review revealed a sensitivity, positive predictive value (PPV), and F1 score of 95%, 87%, and 91%, respectively. Substantial agreement was observed between scores extracted from RISE notes and scores derived from structured data (kappa 0.43 – 0.68 among DA and 0.86-0.98 among FS measures). In the external validation, we found a sensitivity, PPV, and F1 score of 92%, 69%, and 79%, respectively.

We developed an NLP pipeline to extract RA outcome measures from a national registry of notes from multiple EHR systems and found it to have good internal and external validity. This pipeline can facilitate measurement of clinical and patient reported outcomes for use in research and quality measurement.

We developed an NLP pipeline to extract RA outcome measures from a national registry of notes from multiple EHR systems and found it to have good internal and external validity. This pipeline can facilitate measurement of clinical and patient reported outcomes for use in research and quality measurement.

Patient communities use social media for peer support and information seeking. This study assessed the feasibility of using public patient-generated health data (PGHD) from the social network Twitter to identify diverse lupus patients and gather their perspectives about disease symptoms and medications.

We extracted public lupus-related Twitter messages (N=47,715 tweets) in English posted by users (N=8,446) in the United States between September 1, 2017, and October 31, 2018. We analyzed the data to describe lupus patients and the expressed themes (symptoms and medications). Two independent coders analyzed the data; Cohen’s Kappa coefficient was used to ensure interrater reliability. Differences in symptom and medication expressions were analyzed using two-tailed Z tests and a combination of one-way ANOVA tests and unpaired t-tests.

We found that lupus patients on Twitter are diverse in gender and race about one-third (34.64%, 62/179) were persons of color (POC), and 85.47% were female. The expressed disease symptoms and medications varied significantly by gender and race. Much of our findings correlated with documented clinical observations, e.g., expressions of general pain (8.39%, 709/8,446), flares (6.05%, 511/8,446), and fatigue (4.18%, 353/8,446). However, our data also revealed less well-known patient observations, e.g., possible racial disparities within ocular manifestations of lupus.

Our results indicate that social media surveillance can provide valuable lupus patient perspective data of clinical relevance. The medical community has the opportunity to harness this information to inform the patient-centered care within underrepresented patient groups such as POC.

Our results indicate that social media surveillance can provide valuable lupus patient perspective data of clinical relevance. The medical community has the opportunity to harness this information to inform the patient-centered care within underrepresented patient groups such as POC.Bone marrow-derived mesenchymal stem cells (BMSCs) and their exosomes are of great significance for the recovery of cardiac function in patients with myocardial infarction (MI). However, the underlying mechanisms of BMSCs applied to MI treatment remain unclear. Fluorescence-activated cell sorting (FACs) are performed to assess the apoptosis, reactive oxygen species levels and glucose uptake capacity of BMSCs. Reverse transcription polymerase chain reaction is conducted to detect the levels of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), hepatocyte growth factor (HGF), insulin-like growth factor (IGF), transforming growth factor-beta 1, connective tissue growth factor, and platelet-derived growth factor. The levels of apoptosis-related proteins were detected by Western blot. The levels of VEGF, bFGF, HGF, and IGF were assessed by enzyme-linked immunosorbent assay. The biochemical kits are applied to detect the levels of malondialdehyde, superoxide dismutase, and adenosine triphosphate/adenosine diphosphate. 2,3,5-triphenyltetrazolium and Masson staining and immunofluorescence are performed to assess myocardial function of rats. Angiopoietin-like protein 4 (ANGPTL4) alleviates apoptosis and oxidative stress of BMSCs induced by serum deprivation and hypoxia; ANGPTL4 activates paracrine and accelerate metabolic energy of BMSCs; and ANGPTL4 treated-BMSCs alleviate myocardial injury of rats with MI. ANGPTL4 treated-BMSCs alleviate myocardial injury in rats with MI, indicating the combination therapy of ANGPTL4 and BMSCs may alleviate myocardial injury in rats with MI.

Frameless treatment with the Gamma Knife Icon is still relatively new as a treatment option. As a result, additional confidence/knowledge about the uncertainty that exists within each portion of the treatment workflow could be gained especially regarding steps that have not been previously studied in the literature.

The Icon base delivery device (Perfexion) uncertainty is quantified and validated. The novel portions of the Icon such as mask immobilization, cone-beam computed tomography image guidance, and the intrafraction motion management methods are studied specifically and to a greater extent to determine a total workflow uncertainty of frameless treatment with the Icon.

The uncertainty of each treatment workflow step has been identified with the total workflow uncertainty being identified in this work as 1.3mm with a standard deviation of 0.51mm.

The total uncertainty of frameless treatment with the Icon has been evaluated and this data may indicate the need for setup margin in this setting with data that could be used by other institutions to calculate needed setup margin per their preferred recipe after validation of this data in their context.

The total uncertainty of frameless treatment with the Icon has been evaluated and this data may indicate the need for setup margin in this setting with data that could be used by other institutions to calculate needed setup margin per their preferred recipe after validation of this data in their context.In virology, the term seasonality describes variations in virus prevalence at more or less regular intervals throughout the year. Specifically, it has long been recognized that outbreaks of human influenza viruses, respiratory syncytial virus (RSV), and human coronaviruses occur in temperate climates during the winter season, whereas low activity is detected during the summer months. Other human respiratory viruses, such as parainfluenza viruses, human metapneumoviruses, and rhinoviruses, show highest activity during the spring or fall season in temperate regions, depending on the virus and subtype. In tropical climates, influenza viruses circulate throughout the year and no distinct seasonal patterns are observed, although virus outbreaks tend to spike during the rainy season. Overall, seasonality is more pronounced with greater distance from the equator, and tends to be less pronounced in regions closer to the equator (Li et al, 2019).Carbon nanodots are currently one of the hot topics in the nanomaterials world, due to their accessible synthesis and promising features. However, the purification of these materials is still a critical aspect, especially for syntheses involving molecular precursors. Indeed, the presence of unreacted species or small organic molecules formed during solvothermal treatments can affect the properties of the synthesized nanomaterials. To illustrate the extreme importance of this issue, we present two case studies in which insufficient purification results in misleading conclusions regarding the chiral and fluorescent properties of the investigated materials. Key to identify molecular species is the use of nuclear magnetic resonance, which proves to be an effective tool. Our work highlights the need to include nuclear magnetic resonance as a standard characterization technique for carbon-based nanomaterials, to minimize the risk of observing properties that arise from molecular species, rather than the target carbon nanodots.