Cartilage adhesive and mechanical properties of enzymatically crosslinked polysaccharide tyramine conjugate hydrogels

Using a home-built tensile tester, adhesion and mechanical properties of injectable enzymatically crosslinkable hydrogels were determined by placing the hydrogels in between cartilage surfaces. Dextran–tyramine (Dex-TA) and hyaluronic acid–tyramine (HA-TA) conjugates as well as a 50/50 composite material of these polysaccharide conjugates were tested. To integrate the injectable hydrogels with the cartilage tissue, pretreatment of the tissue with a Dex-TA conjugate solution strongly improved the adhesion. Only failure of the crosslinked hydrogel was observed and not at the hydrogel–tissue interface. Moduli of a Dex-TA hydrogel are higher than those of a HA-TA hydrogel, whereas the ultimate strain of the HA-TA hydrogel was at least three times higher. The Dex-TA/HA-TA hydrogel has similar storage and elastic moduli as the Dex-TA gel and also an ultimate strain of ~30%, similarly as found for the HA-TA gel. The controlled biodegradability and gelation time of the Dex-TA/HA-TA hydrogel, the developed method for strong tissue adhesion of the gel particularly in comparison with fibrin glue, makes this material applicable as an injectable hydrogel for tissue regeneration application

Automated real-time collection of pathogen-specific diagnostic data: Syndromic infectious disease epidemiology

© Lindsay Meyers, Christine C Ginocchio, Aimie N Faucett, Frederick S Nolte, Per H Gesteland, Amy Leber, Diane Janowiak,. Background: Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. Objective: The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. Methods: We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. Results: The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. Conclusions: Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks

Salience-based selection: attentional capture by distractors less salient than the target

Current accounts of attentional capture predict the most salient stimulus to be invariably selected first. However, existing salience and visual search models assume noise in the map computation or selection process. Consequently, they predict the first selection to be stochastically dependent on salience, implying that attention could even be captured first by the second most salient (instead of the most salient) stimulus in the field. Yet, capture by less salient distractors has not been reported and salience-based selection accounts claim that the distractor has to be more salient in order to capture attention. We tested this prediction using an empirical and modeling approach of the visual search distractor paradigm. For the empirical part, we manipulated salience of target and distractor parametrically and measured reaction time interference when a distractor was present compared to absent. Reaction time interference was strongly correlated with distractor salience relative to the target. Moreover, even distractors less salient than the target captured attention, as measured by reaction time interference and oculomotor capture. In the modeling part, we simulated first selection in the distractor paradigm using behavioral measures of salience and considering the time course of selection including noise. We were able to replicate the result pattern we obtained in the empirical part. We conclude that each salience value follows a specific selection time distribution and attentional capture occurs when the selection time distributions of target and distractor overlap. Hence, selection is stochastic in nature and attentional capture occurs with a certain probability depending on relative salience

A phase 1 trial evaluating thioridazine in combination with cytarabine in patients with acute myeloid leukemia

We completed a phase 1 dose-escalation trial to evaluate the safety of a dopamine receptor D2 (DRD2) antagonist thioridazine (TDZ), in combination with cytarabine. Thirteen patients 55 years and older with relapsed or refractory acute myeloid leukemia (AML) were enrolled. Oral TDZ was administered at 3 dose levels: 25 mg (n = 6), 50 mg (n = 4), or 100 mg (n = 3) every 6 hours for 21 days. Intermediate-dose cytarabine was administered on days 6 to 10. Dose-limiting toxicities (DLTs) included grade 3 QTc interval prolongation in 1 patient at 25 mg TDZ and neurological events in 2 patients at 100 mg TDZ (gait disturbance, depressed consciousness, and dizziness). At the 50-mg TDZ dose, the sum of circulating DRD2 antagonist levels approached a concentration of 10 mM, a level noted to be selectively active against human AML in vitro. Eleven of 13 patients completed a 5-day lead-in with TDZ, of which 6 received TDZ with hydroxyurea and 5 received TDZ alone. During this period, 8 patients demonstrated a 19% to 55% reduction in blast levels, whereas 3 patients displayed progressive disease. The extent of blast reduction during this 5-day interval was associated with the expression of the putative TDZ target receptor DRD2 on leukemic cells. These preliminary results suggest that DRD2 represents a potential therapeutic target for AML disease. Future studies are required to corroborate these observations, including the use of modified DRD2 antagonists with improved tolerability in AML patients. This trial was registered at www.clinicaltrials.gov as #NCT02096289

Highly integrated multi-material fibers for soft robotics

Soft robots are envisioned as the next generation of safe biomedical devices in minimally invasive procedures. Yet, the difficulty of processing soft materials currently limits the size, aspect-ratio, manufacturing throughput, as well as, the design complexity and hence capabilities of soft robots. Multi-material thermal drawing is introduced as a material and processing platform to create soft robotic fibers imparted with multiple actuations and sensing modalities. Several thermoplastic and elastomeric material options for the fibers are presented, which all exhibit the rheological processing attributes for thermal drawing but varying mechanical properties, resulting in adaptable actuation performance. Moreover, numerous different fiber designs with intricate internal architectures, outer diameters of 700 µm, aspect ratios of 103, and a fabrication at a scale of 10s of meters of length are demonstrated. A modular tendon-driven mechanism enables 3-dimensional (3D) motion, and embedded optical guides, electrical wires, and microfluidic channels give rise to multifunctionality. The fibers can perceive and autonomously adapt to their environments, as well as, probe electrical properties, and deliver fluids and mechanical tools to spatially distributed targets

Low Adiponectin Levels Are an Independent Predictor of Mixed and Non-Calcified Coronary Atherosclerotic Plaques

Atherosclerosis is the primary cause of coronary artery disease (CAD). There is increasing recognition that lesion composition rather than size determines the acute complications of atherosclerotic disease. Low serum adiponectin levels were reported to be associated with coronary artery disease and future incidence of acute coronary syndrome (ACS). The impact of adiponectin on lesion composition still remains to be determined. We measured serum adiponectin levels in 303 patients with stable typical or atypical chest pain, who underwent dual-source multi-slice CT-angiography to exclude coronary artery stenosis. Atherosclerotic plaques were classified as calcified, mixed or non-calcified. In bivariate analysis adiponectin levels were inversely correlated with total coronary plaque burden (r = -0.21, p = 0.0004), mixed (r = -0.20, p = 0.0007) and non-calcified plaques (r = -0.18, p = 0.003). No correlation was seen with calcified plaques (r = -0.05, p = 0.39). In a fully adjusted multivariate model adiponectin levels remained predictive of total plaque burden (estimate: -0.036, 95%CI: -0.052 to -0.020, p<0.0001), mixed (estimate: -0.087, 95%CI: -0.132 to -0.042, p = 0.0001) and non-calcified plaques (estimate: -0.076, 95%CI: -0.115 to -0.038, p = 0.0001). Adiponectin levels were not associated with calcified plaques (estimate: -0.021, 95% CI: -0.043 to -0.001, p = 0.06). Since the majority of coronary plaques was calcified, adiponectin levels account for only 3% of the variability in total plaque number. In contrast, adiponectin accounts for approximately 20% of the variability in mixed and non-calcified plaque burden. Adiponectin levels predict mixed and non-calcified coronary atherosclerotic plaque burden. Low adiponectin levels may contribute to coronary plaque vulnerability and may thus play a role in the pathophysiology of ACS