Freeze-dried nanocomposite gel beads for oral drug delivery. In vitro simulation of gastro-intestinal drug release

We investigated entrapment efficiency, swelling and drug release from freeze-dried gel beads prepared with Gellan gum and a synthetic clay, Laponite. Polymeric beads loaded with two model molecules having different molecular weights were prepared and subjected to in vitro release studies in simulated gastric and intestinal fluids. The experimental observations confirm that laponite may be an effective additive for fabricating sustained drug delivery systems from gellan gum by means of ionotropic gelation and freeze-drying

Low-Level Light Therapy in Orthodontic Treatment: A Systematic Review

This current review aims to provide an overview of the most recent research from the last 10 years on the potential of low-level light therapy (LLLT) in the orthodontic field, particularly focusing on studies about tooth movement, root resorption, pain perception during treatment, and the stability of orthodontic miniscrews. “Low-level laser,” “orthodontic,” and “LLLT” were the search terms utilized on the databases Scopus, Web of Science, and PubMed, and the Boolean operator “AND” was utilized. Of the 974 studies found, 41 publications related to our topic were included in this review. Many authors agree that LLLT could trigger an enhanced biological reaction next to the tooth in the periodontium, promoting osteoblast proliferation and differentiation, while it could also have a positive impact on bone regeneration and on increasing the rate of tooth movement, enhancing the stability of miniscrews and minimizing the occurrence of root resorption. Regarding pain management during treatment studies, the results have been controversial. Conclusions: even though further studies are still needed, the use of LLLT can improve both clinical results and patient comfort during treatment by reducing treatment duration, improving clinical aspects, such as miniscrew stability, and minimizing root resorption. Further investigations are needed to assess whether LLLT offers any real benefits regarding pain relief

Chemical investigation and screening of anti-proliferative activity on human cell lines of pure and nano-formulated lavandin essential oil

Lavandin essential oil (LEO), a natural sterile hybrid obtained by crossbreeding L. angustifolia × L. latifolia, is mainly composed by active components belonging to the family of terpenes endowed with relevant anti-proliferative activity, which can be enhanced by proper application of nanotechnology. In particular, this study reports the chemical characterization and the screening of the anti-proliferative activity on different human cell lines of pure and nano-formulated lavandin essential oil (EO). LEO and its formulation (NanoLEO) were analyzed by HS/GC-MS (Headspace/Gas Chromatography-Mass Spectrometry) to describe and compare their chemical volatile composition. The most abundant compounds were linalool and 1,8-cineole (LEO: 28.6%; 27.4%) (NanoLEO: 60.4%; 12.6%) followed by α-pinene (LEO: 9.6%; NanoLEO: 4.5%), camphor (LEO: 6.5%; NanoLEO: 7.0%) and linalyl acetate (LEO: 6.5%; NanoLEO: 3.6%). The cytotoxic effects of LEO and NanoLEO were investigated on human neuroblastoma cells (SHSY5Y), human breast adenocarcinoma cells (MCF-7), human lymphoblastic leukemia cells (CCRF CEM), human colorectal adenocarcinoma cells (Caco-2) and one normal breast epithelial cell (MCF10A) by the MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide)-assay. Caco-2, MCF7 and MCF10A normal cells resulted more resistant to the treatment with LEO, while CCRF-CEM and SHSY5Y cells were more sensitive. The antiproliferative effect of LEO resulted amplified when the essential oil was supplied as nanoformulation, mainly in Caco-2 cells. Scanning and transmission electron microscopy investigations were carried out on Caco-2 cells to outline at ultrastructural level possible affections induced by LEO and NanoLEO treatments

Intravenous angiotensin II for the treatment of high-output shock (ATHOS trial): a pilot study

INTRODUCTION: Patients with distributive shock who require high dose vasopressors have a high mortality. Angiotensin II (ATII) may prove useful in patients who remain hypotensive despite catecholamine and vasopressin therapy. The appropriate dose of parenteral angiotensin II for shock is unknown. METHODS: In total, 20 patients with distributive shock and a cardiovascular Sequential Organ Failure Assessment score of 4 were randomized to either ATII infusion (N =10) or placebo (N =10) plus standard of care. ATII was started at a dose of 20 ng/kg/min, and titrated for a goal of maintaining a mean arterial pressure (MAP) of 65 mmHg. The infusion (either ATII or placebo) was continued for 6 hours then titrated off. The primary endpoint was the effect of ATII on the standing dose of norepinephrine required to maintain a MAP of 65 mmHg. RESULTS: ATII resulted in marked reduction in norepinephrine dosing in all patients. The mean hour 1 norepinephrine dose for the placebo cohort was 27.6 ± 29.3 mcg/min versus 7.4 ± 12.4 mcg/min for the ATII cohort (P =0.06). The most common adverse event attributable to ATII was hypertension, which occurred in 20% of patients receiving ATII. 30-day mortality for the ATII cohort and the placebo cohort was similar (50% versus 60%, P =1.00). CONCLUSION: Angiotensin II is an effective rescue vasopressor agent in patients with distributive shock requiring multiple vasopressors. The initial dose range of ATII that appears to be appropriate for patients with distributive shock is 2 to 10 ng/kg/min. TRIAL REGISTRATION: Clinicaltrials.gov NCT01393782. Registered 12 July 2011

Rapid prediction of wall shear stress in stenosed coronary arteries based on deep learning

There is increasing evidence that coronary artery wall shear stress (WSS) measurement provides useful prognostic information that allows prediction of adverse cardiovascular events. Computational Fluid Dynamics (CFD) has been extensively used in research to measure vessel physiology and examine the role of the local haemodynamic forces on the evolution of atherosclerosis. Nonetheless, CFD modelling remains computationally expensive and time-consuming, making its direct use in clinical practice inconvenient. A number of studies have investigated the use of deep learning (DL) approaches for fast WSS prediction. However, in these reports, patient data were limited and most of them used synthetic data generation methods for developing the training set. In this paper, we implement 2 approaches for synthetic data generation and combine their output with real patient data in order to train a DL model with a U-net architecture for prediction of WSS in the coronary arteries. The model achieved 6.03% Normalised Mean Absolute Error (NMAE) with inference taking only 0.35 s; making this solution time-efficient and clinically relevant