GLSFormer: Gated - Long, Short Sequence Transformer for Step Recognition in Surgical Videos

Automated surgical step recognition is an important task that can significantly improve patient safety and decision-making during surgeries. Existing state-of-the-art methods for surgical step recognition either rely on separate, multi-stage modeling of spatial and temporal information or operate on short-range temporal resolution when learned jointly. However, the benefits of joint modeling of spatio-temporal features and long-range information are not taken in account. In this paper, we propose a vision transformer-based approach to jointly learn spatio-temporal features directly from sequence of frame-level patches. Our method incorporates a gated-temporal attention mechanism that intelligently combines short-term and long-term spatio-temporal feature representations. We extensively evaluate our approach on two cataract surgery video datasets, namely Cataract-101 and D99, and demonstrate superior performance compared to various state-of-the-art methods. These results validate the suitability of our proposed approach for automated surgical step recognition. Our code is released at: https://github.com/nisargshah1999/GLSFormerComment: Accepted to MICCAI 2023 (Early Accept

The metric distortion of multiwinner voting

We extend the recently introduced framework of metric distortion to multiwinner voting. In this framework, n agents and m alternatives are located in an underlying metric space. The exact distances between agents and alternatives are unknown. Instead, each agent provides a ranking of the alternatives, ordered from the closest to the farthest. Typically, the goal is to select a single alternative that approximately minimizes the total distance from the agents, and the worst-case approximation ratio is termed distortion. In the case of multiwinner voting, the goal is to select a committee of k alternatives that (approximately) minimizes the total cost to all agents. We consider the scenario where the cost of an agent for a committee is her distance from the q-th closest alternative in the committee. We reveal a surprising trichotomy on the distortion of multiwinner voting rules in terms of k and q: The distortion is unbounded when q≤k/3, asymptotically linear in the number of agents when k/3k/

Formulation and Process Optimization of Buccoadhesive Tablet of Rabeprazole

ABSTRACT The aim of the study was to prepare and evaluate bucco-adhesive tablets of rabeprazole sodium that avoid gastric degradation and first pass metabolism, thereby increasing the drug bioavailability and onset of action. The drug, rabeprazole sodium, belongs to a class of antisecretory compounds. In the present work, different ratios of Gantrez MS 955 along with HPMC K4M were studied to give bioadhesive strength. To stabilize the drug in human saliva different stabilizers were studied, of which sodium carbonate was found the best. A 3 2 full factorial design was applied to investigate the combined effect of Gantrez MS 955 concentration (X1) and HPMC K4M concentration (X2). Results of the multiple regression analysis revealed that the independent variables significantly affected the dependent variables (bioadhesive strength (Y1) and t50 (Y2)). On the basis of multiple linear regression analysis and contour plot evaluation, it was found that the effect of Gantrez is comparatively more pronounced than that of HPMC K4M on bioadhesion. The formulation F19 fulfilled all the criteria set from the desirability search. From the in vitro diffusion study flux was calculated for the optimized batch. Study of the effect of tablet diameter and the environmental factors on the bioadhesion of the tablet was done. To study the environmental factor on bioadhesion, prehydration time and contact time were considered. Result found that increase in prehydration time decrease in bioadhesive strength and increase in contact time increased bioadhesive strength. Thus a stable buccoadhesive formulation optimized for formulation ingredients and process parameters was prepared successfully

Combining therapeutic vaccines with chemo- and immunotherapies in the treatment of cancer

IntroductionBreakthroughs in cancer immunotherapy have spurred interest in the development of vaccines to mediate prophylactic protection and therapeutic efficacy against primary tumors or to prevent relapse. However, immunosuppressive mechanisms employed by cancer cells to generate effective resistance have hampered clinical translation of therapeutic cancer vaccines. To enhance vaccine efficacy, the immunomodulatory properties of cytoreductive therapies could amplify a cancer-specific immune response.Areas coveredHerein, the authors discuss therapeutic cancer vaccines that harness whole cells and antigen-targeted vaccines. First, recent advancements in both autologous and allogeneic whole-cell vaccines and combinations with checkpoint blockade and chemotherapy are reviewed. Next, tumor antigen-targeted vaccines using peptide-based vaccines and DNA-vaccines are discussed. Finally, combination therapies using antigen-targeted vaccines are reviewed.Expert opinionA deeper understanding of the immunostimulatory properties of cytoreductive therapies has supported their utility in combination therapies involving cancer vaccines as a potential strategy to induce a durable anti-tumor immune response for multiple types of cancers. Based on current evidence, combination therapies may have synergies that depend on the identity of the cytotoxic agent, vaccine target, dosing schedule, and cancer type. Together, these observations suggest that combining cancer vaccines with immunomodulatory cytoreductive therapy is a promising strategy for cancer therapy