GlanceSeg: Real-time microaneurysm lesion segmentation with gaze-map-guided foundation model for early detection of diabetic retinopathy

Early-stage diabetic retinopathy (DR) presents challenges in clinical diagnosis due to inconspicuous and minute microangioma lesions, resulting in limited research in this area. Additionally, the potential of emerging foundation models, such as the segment anything model (SAM), in medical scenarios remains rarely explored. In this work, we propose a human-in-the-loop, label-free early DR diagnosis framework called GlanceSeg, based on SAM. GlanceSeg enables real-time segmentation of microangioma lesions as ophthalmologists review fundus images. Our human-in-the-loop framework integrates the ophthalmologist's gaze map, allowing for rough localization of minute lesions in fundus images. Subsequently, a saliency map is generated based on the located region of interest, which provides prompt points to assist the foundation model in efficiently segmenting microangioma lesions. Finally, a domain knowledge filter refines the segmentation of minute lesions. We conducted experiments on two newly-built public datasets, i.e., IDRiD and Retinal-Lesions, and validated the feasibility and superiority of GlanceSeg through visualized illustrations and quantitative measures. Additionally, we demonstrated that GlanceSeg improves annotation efficiency for clinicians and enhances segmentation performance through fine-tuning using annotations. This study highlights the potential of GlanceSeg-based annotations for self-model optimization, leading to enduring performance advancements through continual learning.Comment: 12 pages, 10 figure

Effects of Probiotics on Gut Microbiota in Type 2 Diabetes Patients

Objective: To study the effect of probiotics on gut microbiota in Type 2 diabetes patients and its clinical application value. Methods: Select Type 2 diabetes patients to take orally probiotics for 24 weeks, collect stool samples of subjects at the baseline and end of the trial, identify and analyze gut microbiota of each sample by 16srRNA high-throughput sequencing, and compare the changes of blood glucose, blood lipid and insulin resistance before and after the intervention. Results: A total of 75 patients completed clinical observations. 16srRNA high-throughput sequencing showed that the proportion of the subjects with increased Actinobacteria and Tenericutes at the end of the trial has increased (37.8% and 75.7% respectively). The genus level analysis showed that the number of subjects with increased intestinal probiotics and with decreased conditioned pathogens all increased. Cluster analysis before and after intervention showed that the gut microbiota of samples in the same group had a higher similarity. Compared with the subjects at the baseline status, at the end of the trial after the intervention, fasting blood glucose (FBG) of the subjects significantly decreased (P<0.05), the proportion of the subjects with triglyceride (TG) and cholesterol up to standard increased, and HOMA-IR was significantly improved (P<0.05). Conclusions: Probiotics can regulate the gut microbiota of Type 2 diabetes patients, promote fasting blood glucose (FBG) to reach the standard and improve insulin resistance, and help improve lipid metabolism

Carbon Sequestration in Relation to Shrub Size in the Desert Ecosystem

Desert ecosystems have been reported as the location of the long-sought ‘missing sink’ for atmospheric carbon dioxide and as a potentially important area for carbon sequestering from fossil fuel combustion in the future (Stone 2008). Researchers have found that net uptake of carbon in the Mojave Desert ranged from 102 to 127 g C m2/yr during a 3-year period, which is equivalent to the net ecosystem production of many forest ecosystems with a much higher biomass (Luyssaert et al. 2007; Wohlfahrt et al. 2008). Shrub is the dominant plant of desert ecosystems (Gratani et al. 2011); hence, it is important to understand the dynamics of carbon sequestration by shrubs as well as their role in desert ecosystem carbon balance. Information on the carbon sequestration associated with shrub size is limited. Our objective was, therefore, to find out the relationship between carbon sequestration potential and size of shrubs

The Characters of Soil Microbial Biomass and Metabolic Quotient Associated with Shrub Development in the Arid Region

Soil microbial biomass (MBC), as the most active of soil organic constituents, controls many important ecological processes in the ecosystem including nutrient cycling and litter decomposition (Jia et al. 2010), and is considered to be the most sensitive biological indicator of soil quality (Sinha et al. 2009). Moreover, soil microbial metabolic quotient (qCO2) reflects the quantity and quality of soil organic matter, soil nutrient availability, microbial substrate utilization efficiency and ecosystem stability (Mao et al. 2010). Shrub is the dominant vegetation of desert ecosystems, contributing to soil nutrient conservation and carbon sequestration. Considerable research related to shrubs in desert ecosystems has been reported, however changes of soil microbial properties throughout the process of shrub development remains poorly documented. The main objective of this study was to explore how soil microbial biomass and qCO2 change with shrub development

LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving

A map, as crucial information for downstream applications of an autonomous driving system, is usually represented in lanelines or centerlines. However, existing literature on map learning primarily focuses on either detecting geometry-based lanelines or perceiving topology relationships of centerlines. Both of these methods ignore the intrinsic relationship of lanelines and centerlines, that lanelines bind centerlines. While simply predicting both types of lane in one model is mutually excluded in learning objective, we advocate lane segment as a new representation that seamlessly incorporates both geometry and topology information. Thus, we introduce LaneSegNet, the first end-to-end mapping network generating lane segments to obtain a complete representation of the road structure. Our algorithm features two key modifications. One is a lane attention module to capture pivotal region details within the long-range feature space. Another is an identical initialization strategy for reference points, which enhances the learning of positional priors for lane attention. On the OpenLane-V2 dataset, LaneSegNet outperforms previous counterparts by a substantial gain across three tasks, \textit{i.e.}, map element detection (+4.8 mAP), centerline perception (+6.9 DET$_l$), and the newly defined one, lane segment perception (+5.6 mAP). Furthermore, it obtains a real-time inference speed of 14.7 FPS. Code is accessible at https://github.com/OpenDriveLab/LaneSegNet.Comment: Accepted in ICLR 202

Few-Layer Graphene Integrated Tilted Fiber Grating For All-Optical Switching

Recently, the integration of two-dimensional materials with optical fibers has opened up a great opportunity to develop all-fiber signal-processing devices. Graphene is an ideal material for all-optical signal processing via thermal-optic effect because of its high electrical and thermal conductivity, as well as broadband light-matter interactions with fast responses. Herein, we report the achievement of all-optical switching with fast response by integrating few-layer graphene onto a tilted fiber Bragg grating (TFBG) inscribed in a reduced-diameter fiber. Relying on graphene's decent photothermal effect, the transmission spectrum of the TFBG could be all-optically modulated by tuning the incident pump power. The all-optical switch can consequently operate at a series of wavelengths owing to the TFBG's comb-like resonances. The reduced diameter of the graphene-integrated TFBG and the pump at its resonant wavelength promise the all-optical switch to have a fast-dynamic response of around 1 μs and an extinction ratio exceeding 13 dB. This compact device with graphene integration has the potentials to be integrated into all-fiber system to extend the functions of all-optical signal processing

Visual In-Context Prompting

In-context prompting in large language models (LLMs) has become a prevalent approach to improve zero-shot capabilities, but this idea is less explored in the vision domain. Existing visual prompting methods focus on referring segmentation to segment the most relevant object, falling short of addressing many generic vision tasks like open-set segmentation and detection. In this paper, we introduce a universal visual in-context prompting framework for both tasks. In particular, we build on top of an encoder-decoder architecture, and develop a versatile prompt encoder to support a variety of prompts like strokes, boxes, and points. We further enhance it to take an arbitrary number of reference image segments as the context. Our extensive explorations show that the proposed visual in-context prompting elicits extraordinary referring and generic segmentation capabilities to refer and detect, yielding competitive performance to close-set in-domain datasets and showing promising results on many open-set segmentation datasets. By joint training on COCO and SA-1B, our model achieves $57.7$ PQ on COCO and $23.2$ PQ on ADE20K. Code will be available at https://github.com/UX-Decoder/DINOv.Comment: technical repor

p97/VCP is highly expressed in the stem-like cells of breast cancer and controls cancer stemness partly through the unfolded protein response

p97/VCP, an evolutionarily concerned ATPase, partakes in multiple cellular proteostatic processes, including the endoplasmic reticulum (ER)-associated protein degradation (ERAD). Elevated expression of p97 is common in many cancers and is often associated with poor survival. Here we report that the levels of p97 positively correlated with the histological grade, tumor size, and lymph node metastasis in breast cancers. We further examined p97 expression in the stem-like cancer cells or cancer stem cells (CSCs), a cell population that purportedly underscores cancer initiation, therapeutic resistance, and recurrence. We found that p97 was consistently at a higher level in the CD4