Optical time-lapse microscopy for rapid assessment of microbial quality in hygroscopic food samples.

In the food industry, time-to-result is crucial for faster release of products, minimising recalls, mitigation of microbial contamination problems and, ultimately, food safety. Carrageenan is isolated from red seaweed (Rhodophyta) and applied in various foods and beverages as a gelling, thickening, texturing, or stabilizing agent due to its hygroscopic properties. Currently, the standard industry plate count method entails a one-hundred-fold dilution of the sample before mixing with molten agar for assessment of the level of microbial contamination in carrageenan samples prior to business-to-business shipment.

Obtaining the patient's perspective on frailty: a mini-review of qualitative studies.

There is a small, but growing, evidence base on obtaining the patient's perspective on frailty, which can help guide future research and clinical management strategies. This mini-review provides a brief summary of some qualitative studies on the patient's perspective on frailty with a focus on the study design and emerging findings to date. We reviewed seven studies in total, examining how they approached the research question and their main findings.

High-dose glucocorticoids in the treatment of postoperative pain after video-assisted thoracoscopic surgery-protocol for systematic review and meta-analysis.

Background: Video-assisted thoracoscopic surgery (VATS) is widely used in lung cancer surgery, as this technique causes less pain and faster recovery than open thoracotomy. However, significant postoperative pain persists in a number of patients, often leading to increased opioid use and opioid-related adverse events in addition to prolonged admission times. Perioperatively administered glucocorticoids have been demonstrated effective in reducing pain after other types of surgeries, but the effect in VATS remains unclear.

DenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation.

Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for segmentation, it falls short in landmark detection, a strength of shape-based approaches.

Methods: In this work, we propose a dense image-to-shape representation that enables the joint learning of landmarks and semantic segmentation by employing a fully convolutional architecture.

Large-scale screening identifies enzyme combinations that remove grown oral biofilm.

Bacteria in the oral cavity are responsible for the development of dental diseases such as caries and periodontitis, but it is becoming increasingly clear that the oral microbiome also benefits human health. Many oral care products on the market are antimicrobial, killing a large part of the oral microbiome but without removing the disease-causing biofilm. Instead, non-biocidal matrix-degrading enzymes may be used to selectively remove biofilm without harming the overall microbiome.