A Post-marketing Surveillance, Single-Centric Study to Evaluate the Safety and Tolerability of VELNEZ as a Space-Occupying Dressing Pack After Ear Surgery.

PURPOSE: The purpose of this study was to evaluate the safety and tolerability of VELNEZ (Datt Mediproducts Pvt. Ltd., New Delhi, India) as a space-occupying dressing for controlling hemorrhage after ear surgery. METHOD: A total of 21 patients were included in an open-label, interventional, single-arm post-marketing surveillance study to investigate the safety and efficacy of the VELNEZ ear pack. The patients were questioned for collecting data related to the subject's safety and comfort, adverse events, site assessment, and otoscopic examination from discharge day to last follow-up (eight follow-up visits) at regular intervals. The standardized questionnaires for VELNEZ tolerability (pain/pressure effect, infection, and general satisfaction) were used after ear surgery. RESULTS:  The average hemorrhage control time was 1.08 ± 0.16 minutes. None of the subjects reported moderate pain at any of the study visits following surgery. This biodegradable ear pack had an average disintegration time of 25.4 days in the ear cavity. No postoperative adverse events or serious adverse events were observed. CONCLUSION: VELNEZ is safe and effective as a space-occupying dressing pack after ear surgery and is well-tolerated by patients.

Pragmatic Coarse-Graining of Proteins: Models and Applications.

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.