Deep Learning Guided Autonomous Retinal Surgery using a Robotic Arm, Microscopy, and iOCT Imaging

Recent technological advancements in retinal surgery has led to the modern operating room consisting of a surgical robot, microscope, and intraoperative optical coherence tomography (iOCT). The integration of these tools raises the fundamental question of how to effectively combine them to enable surgical autonomy. In this work, we address this question by developing a unified framework that enables real-time autonomous surgical workflows utilizing the aforementioned devices. To achieve this, we make the following contributions: (1) we develop a novel imaging system that integrates microscopy and iOCT in real-time, accomplished by dynamically tracking the surgical instrument via a small iOCT scanning region (e.g. B-scan), which was not previously possible; (2) implementing various convolutional neural networks (CNN) that automatically segment and detect task-relevant information for surgical autonomy; (3) enabling surgeons to intuitively select goal waypoints within both the microscope and iOCT views through simple mouse-click interactions; (4) integrating model predictive control (MPC) for real-time trajectory generation that respects kinematic constraints to ensure patient safety. We show the utility of our system by tackling subretinal injection (SI), a challenging procedure that involves inserting a microneedle below the retinal tissue for targeted drug delivery, a task surgeons find challenging due to requiring tens-of-micrometers of accuracy and precise depth perception. We validate our system by conducting 30 successful SI trials on pig eyes, achieving needle insertion accuracy of $26 \pm 12 \mu m$ to various subretinal goals and duration of $55 \pm 10.8$ seconds. Preliminary comparisons to a human operator performing SI in robot-assisted mode highlight the enhanced safety of our system.Comment: pending submission to a journa

Effects of advanced glycation end-products (AGEs) on skin keratinocytes by nuclear factor-kappa B (NF-κB) activation

Advance glycation end-products (AGEs) are produced in patients with long-term hyperglycemia metabolic disorder and responsible for multiple symptoms including impaired wound healing. This study was designed to reveal the roles and possible mechanism of AGE in diabetic wound healing. Sixteen Sprague-Dawley (SD) rats were divided into two groups randomly; the streptozotocin (STZ) induced diabetic group and the normal group. Eight weeks later, epidermal growth factor (EGF) and AGE levels, nuclear factor-kappa B (NF-κB) localization and cell viability were measured in vivo. Keratinocytes from normal skin were cultured in AGE-enriched conditional media, and the cell viability, apoptosis, adhesion and migration were detected in order to find the directed evidence between AGE and keratinocytes. AGE content was higher and NF-κB expression was more localized in the nuclear of keratinocytes in diabetic skins. AGE could inhibit normal cell growth by inducing apoptosis and arresting cell division cycle, inhibiting cell adhesion and promoting migration which might be mediated by NF-κB in vitro. Blocking NF-κB activity could reverse effects of AGE on cell proliferation and migration, but not adhesion. Therefore, AGE could damage the skin keratinocytes function in vivo and in vitro, and the activation of NF-κB is involved in this process.Key words: AGE, NF-kappaB, keratinocytes, diabetes, wound healing

DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding

Visually-situated languages such as charts and plots are omnipresent in real-world documents. These graphical depictions are human-readable and are often analyzed in visually-rich documents to address a variety of questions that necessitate complex reasoning and common-sense responses. Despite the growing number of datasets that aim to answer questions over charts, most only address this task in isolation, without considering the broader context of document-level question answering. Moreover, such datasets lack adequate common-sense reasoning information in their questions. In this work, we introduce a novel task named document-level chart question answering (DCQA). The goal of this task is to conduct document-level question answering, extracting charts or plots in the document via document layout analysis (DLA) first and subsequently performing chart question answering (CQA). The newly developed benchmark dataset comprises 50,010 synthetic documents integrating charts in a wide range of styles (6 styles in contrast to 3 for PlotQA and ChartQA) and includes 699,051 questions that demand a high degree of reasoning ability and common-sense understanding. Besides, we present the development of a potent question-answer generation engine that employs table data, a rich color set, and basic question templates to produce a vast array of reasoning question-answer pairs automatically. Based on DCQA, we devise an OCR-free transformer for document-level chart-oriented understanding, capable of DLA and answering complex reasoning and common-sense questions over charts in an OCR-free manner. Our DCQA dataset is expected to foster research on understanding visualizations in documents, especially for scenarios that require complex reasoning for charts in the visually-rich document. We implement and evaluate a set of baselines, and our proposed method achieves comparable results

Unveiling early-life microbial colonization profile through characterizing low-biomass maternal-infant microbiomes by 2bRAD-M

IntroductionThe microbial composition of human breast milk and infant meconium offers critical insights into the early microbial colonization profile, and it greatly contributes to the infant’s immune system and long-term health outcomes. However, analyzing these samples often faces technical challenges and limitations of low-resolution using conventional approaches due to their low microbial biomass.MethodsHere, we employed the type IIB restriction enzymes site-associated DNA sequencing for microbiome (2bRAD-M) as a reduced metagenomics method to address these issues and profile species-level microbial composition. We collected breast milk samples, maternal feces, and infant meconium, comparing the results from 2bRAD-M with those from both commonly used 16S rRNA amplicon sequencing and the gold-standard whole metagenomics sequencing (WMS).ResultsThe accuracy and robustness of 2bRAD-M were demonstrated through its consistently high correlation of microbial individual abundance and low whole-community-level distance with the paired WMS samples. Moreover, 2bRAD-M enabled us to identify clinical variables associated with infant microbiota variations and significant changes in microbial diversity across different lactation stages of breast milk.DiscussionThis study underscores the importance of employing 2bRAD-M in future large-scale and longitudinal studies on maternal and infant microbiomes, thereby enhancing our understanding of microbial colonization in early life stages and demonstrating further translational potential

Optimization of Total Flavonoid Compound Extraction from Gynura medica Leaf Using Response Surface Methodology and Chemical Composition Analysis

Optimization of total flavonoid compound (TFC) extraction from Gynura medica leaf was investigated using response surface methodology (RSM) in this paper. The conditions investigated were 30–60% (v/v) ethanol concentration (X1), 85–95 °C extraction temperature (X2) and 30–50 (v/w) liquid-to-solid ratio (X3). Statistical analysis of the experiments indicated that temperature and liquid-to-solid ratio significantly affected TFC extraction (p < 0.01). The Box-Behnken experiment design showed that polynomial regression models were in good agreement with the experimental results, with the coefficients of determination of 0.9325 for TFC yield. The optimal conditions for maximum TFC yield were 55% ethanol, 92 °C and 50 (v/w) liquid-to-solid ratio with a 30 min extraction time. Extracts from these conditions showed a moderate antioxidant value of 54.78 μmol quercetin/g dry material (DM), 137.3 μmol trolox/g DM for 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 108.21 μmol quercetin/g DM, 242.31 μmol trolox/g DM for 2,2-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS+), respectively. HPLC-DAD-MS analysis showed that kaempferol-3-O-glucoside was the principal flavonoid compound in Gynura medica leaf

HIMO: A New Benchmark for Full-Body Human Interacting with Multiple Objects

Generating human-object interactions (HOIs) is critical with the tremendous advances of digital avatars. Existing datasets are typically limited to humans interacting with a single object while neglecting the ubiquitous manipulation of multiple objects. Thus, we propose HIMO, a large-scale MoCap dataset of full-body human interacting with multiple objects, containing 3.3K 4D HOI sequences and 4.08M 3D HOI frames. We also annotate HIMO with detailed textual descriptions and temporal segments, benchmarking two novel tasks of HOI synthesis conditioned on either the whole text prompt or the segmented text prompts as fine-grained timeline control. To address these novel tasks, we propose a dual-branch conditional diffusion model with a mutual interaction module for HOI synthesis. Besides, an auto-regressive generation pipeline is also designed to obtain smooth transitions between HOI segments. Experimental results demonstrate the generalization ability to unseen object geometries and temporal compositions.Project page: https://lvxintao.github.io/himo, accepted by ECCV 202

A Rare Genetic Defect of MBL2 Increased the Risk for Progression of IgA Nephropathy

The aim of this study was to investigate the association between lectin pathway-related genetic variations and progression in IgA nephropathy. Biopsy-proven IgAN patients with eGFR ≥15 ml/min/1.73 m2 at baseline and a minimum follow-up of 12-months were enrolled. A total of 1,007 patients and 121 healthy controls were enrolled from two Chinese renal centers. The discovery cohort consisted of 606 patients, and the validation cohort consisted of 401 patients. First, promoters, all exons and their boundary regions of MBL2 and FCN2 were sequenced in 50 patients, and then 37 variations were identified. Of these variations, 7 expression-associated variations were selected and genotyped in the whole discovery cohort. We found that rs1800450 in MBL2 and rs7851696 in FCN2 were associated with an increased risk for ESRD as well as serum MBL or L-ficolin levels. However, only rs1800450 was successively validated for its association with ESRD (HR, 15.91; 3.27–77.34; P = 0.001) in the fully adjusted model in the validation cohort. In addition, 2.7% of patients, and 2.5% of healthy controls carried rs1800450-AA. IgAN patients with rs1800450-AA lacked expression of MBL in both serum and renal tissue and had more severe tubulointerstitial damage. Furthermore, a combined effect of rs1800450-AA with a previously reported clinical risk score was observed in which patients with both a high clinical risk score (≥1%) and rs1800450-AA had a strikingly increased 10-years ESRD risk by 37.1-fold (7.17 to 192.13-fold). In summary, IgAN patients carrying MBL2 rs1800450-AA have a high risk for renal function deterioration, probably due to inactivation of the complement MBL pathway