PA-SAM: Prompt Adapter SAM for High-Quality Image Segmentation

The Segment Anything Model (SAM) has exhibited outstanding performance in various image segmentation tasks. Despite being trained with over a billion masks, SAM faces challenges in mask prediction quality in numerous scenarios, especially in real-world contexts. In this paper, we introduce a novel prompt-driven adapter into SAM, namely Prompt Adapter Segment Anything Model (PA-SAM), aiming to enhance the segmentation mask quality of the original SAM. By exclusively training the prompt adapter, PA-SAM extracts detailed information from images and optimizes the mask decoder feature at both sparse and dense prompt levels, improving the segmentation performance of SAM to produce high-quality masks. Experimental results demonstrate that our PA-SAM outperforms other SAM-based methods in high-quality, zero-shot, and open-set segmentation. We're making the source code and models available at https://github.com/xzz2/pa-sam.Comment: Code is available at https://github.com/xzz2/pa-sa

Establishment and verification of a nomogram that predicts the risk for coronary slow flow

BackgroundCoronary slow flow (CSF) has gained significance as a chronic coronary artery disease, but few studies have integrated both biological and anatomical factors for CSF assessment. This study aimed to develop and validate a simple-to-use nomogram for predicting CSF risk by combining biological and anatomical factors.MethodsIn this retrospective case-control study, 1042 patients (614 CSF cases and 428 controls) were randomly assigned to the development and validation cohorts at a 7:3 ratio. Potential predictive factors were identified using least absolute shrinkage and selection operator regression and subsequently utilized in multivariate logistic regression to construct the nomogram. Validation of the nomogram was assessed by discrimination and calibration.ResultsN-terminal pro brain natriuretic peptide, high density lipoprotein cholesterol, hemoglobin, left anterior descending artery diameter, left circumflex artery diameter, and right coronary artery diameter were independent predictors of CSF. The model displayed high discrimination in the development and validation cohorts (C-index 0.771, 95% CI: 0.737-0.805 and 0.805, 95% CI: 0.757-0.853, respectively). The calibration curves for both cohorts showed close alignment between predicted and actual risk estimates, demonstrating improved model calibration. Decision curve analysis suggested high clinical utility for the predictive nomogram.ConclusionThe constructed nomogram accurately and individually predicts the risk of CSF for patients with suspected CSF and may be considered for use in clinical care

The plant pathogen Gluconobacter cerinus strain CDF1 is beneficial to the fruit fly Bactrocera dorsalis

Abstract Plant pathogens can build relationships with insect hosts to complete their life cycles, and they often modify the behavior and development of hosts to improve their own fitness. In order to unravel whether some bacteria that can make fruit rot could have developed symbiotic interactions with Bactrocera dorsalis, we studied the symbiont bacteria profiles of the fly. We identified the bacterium Gluconobacter cerinus strain CDF1 from the ovaries and eggs of the oriental fruit fly B. dorsalis and the amount of Gluconobacter cerinus strain CDF1 increased significantly as the ovaries developed and in fruits on which non-sterile eggs were laid. Gluconobacter cerinus strain CDF1 addition to bananas fastens the rotting process and its addition to the eggs fastens their development/hatching rate. All in all, our data suggest that Gluconobacter cerinus strain CDF1 is beneficial to the fruit fly

Surface Structuring via Additive Manufacturing to Improve the Performance of Metal and Polymer Joints

In order to enhance the joint performance of Ti6Al4V titanium alloy (TC4) and ultra-high molecular weight polyethylene (UHMWPE) for biomedical applications, different structures were fabricated on TC4 surfaces via electron beam melting (EBM) method in this study. Macromorphologies and microinterfaces of TC4–UHMWPE joints produced via hot pressing technique were carefully characterized and analyzed. The effects of different surface structures on mechanical properties and fractured surfaces were investigated and compared. Strong direct bonding (1751 N) between UHMWPE and TC4 was achieved. The interfacial bonding behavior of TC4–UHMWPE joints was further discussed. This study demonstrates the importance of combining macro- and micromechanical interlocking, which is a promising strategy for improving metal–polymer joint performance. It also provides guidance for metal surface structuring from both theoretical and practical perspectives

Three-dimensional transistor arrays for intra- and inter-cellular recording

Electrical impulse generation and its conduction within cells or cellular networks are the cornerstone of electrophysiology. However, the advancement of the field is limited by sensing accuracy and the scalability of current recording technologies. Here we describe a scalable platform that enables accurate recording of transmembrane potentials in electrogenic cells. The platform employs a three-dimensional high-performance field-effect transistor array for minimally invasive cellular interfacing that produces faithful recordings, as validated by the gold standard patch clamp. Leveraging the high spatial and temporal resolutions of the field-effect transistors, we measured the intracellular signal conduction velocity of a cardiomyocyte to be 0.182 m s-1, which is about five times the intercellular velocity. We also demonstrate intracellular recordings in cardiac muscle tissue constructs and reveal the signal conduction paths. This platform could provide new capabilities in probing the electrical behaviours of single cells and cellular networks, which carries broad implications for understanding cellular physiology, pathology and cell-cell interactions