Effect of total flavonoids of Cuscuta chinensis Lam. (Convolvulaceae) on oxidative stress injury in mouse testis and epididymis, and on serum levels of reproductive hormones in oligoasthenospermia mice model

Purpose: To investigate the effect of total flavonoids of Cuscuta chinensis (TFCC) on oxidative stress injury in testis and epididymis, and serum levels of reproductive hormones in an oligoasthenospermia (OAS) mice model. Methods: Thirty male Wistar mice were randomly assigned to three groups of 10 mice each: control group, OAS group and TFCC group. With the exception of control group, OAS was orally induced in the mice with ornidazole. The TFCC group received TFCC. Reactive oxygen species (ROS), malondialdehyde (MDA) and superoxide dismutase (SOD) were determined. Serum levels of follicle stimulating hormone (FSH), luteinizing hormone (LH) and testosterone were also measured. Results: The levels of ROS and MDA in the testis and epididymis significantly increased in OAS group, when compared to control mice (p < 0.05). However, TFCC administration significantly reduced their levels in these tissues (p < 0.05). In contrast, SOD activity significantly decreased in the testis and epididymis of mice in OAS group, relative to control group, but increased significantly after TFCC exposure (p < 0.05). Serum FSH and LH were markedly elevated in OAS group, but treatment with TFCC significantly reduced the levels of these hormones (p < 0.05). Conclusion: These results suggest that TFCC effectively improves sperm quality and reduces oxidative damage in testis and epididymis of mice with oligoasthenospermia via a mechanism involving the regulation of serum levels of reproductive hormones. Thus, TFCC may be useful in the treatment of oligoasthenospermia

Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery

Purpose: Depth estimation in robotic surgery is vital in 3D reconstruction, surgical navigation and augmented reality visualization. Although the foundation model exhibits outstanding performance in many vision tasks, including depth estimation (e.g., DINOv2), recent works observed its limitations in medical and surgical domain-specific applications. This work presents a low-ranked adaptation (LoRA) of the foundation model for surgical depth estimation. Methods: We design a foundation model-based depth estimation method, referred to as Surgical-DINO, a low-rank adaptation of the DINOv2 for depth estimation in endoscopic surgery. We build LoRA layers and integrate them into DINO to adapt with surgery-specific domain knowledge instead of conventional fine-tuning. During training, we freeze the DINO image encoder, which shows excellent visual representation capacity, and only optimize the LoRA layers and depth decoder to integrate features from the surgical scene. Results: Our model is extensively validated on a MICCAI challenge dataset of SCARED, which is collected from da Vinci Xi endoscope surgery. We empirically show that Surgical-DINO significantly outperforms all the state-of-the-art models in endoscopic depth estimation tasks. The analysis with ablation studies has shown evidence of the remarkable effect of our LoRA layers and adaptation. Conclusion: Surgical-DINO shed some light on the successful adaptation of the foundation models into the surgical domain for depth estimation. There is clear evidence in the results that zero-shot prediction on pre-trained weights in computer vision datasets or naive fine-tuning is not sufficient to use the foundation model in the surgical domain directly. Code is available at https://github.com/BeileiCui/SurgicalDINO.Comment: Accepted by IPCAI 2024 (IJCAR Special Issue

Performance of bone tracer for diagnosis and differentiation of transthyretin cardiac amyloidosis: a systematic review and meta-analysis

PURPOSE :Bone tracers have been validated for many years in detecting transthyretin cardiac amyloidosis (TTR-CA). However, several new studies suggest conflicting results. Our study aimed to systematically evaluate the accuracy of bone radiotracers for diagnosis and differentiation of TTR-CA via a systematic review and meta-analysis.METHODS:We retrieved articles assessing the performance of bone tracer in diagnosing and differentiating TTR-CA from PubMed, the Cochrane Library, ScienceDirect, and DOAJ databases, dating up to 10 July 2020. The meta-analysis was conducted through Stata 16 software, and the risk of bias for the included studies was assessed by the QUADAS-2 tool. Moreover, we made a comprehensive review.RESULTS:Fourteen articles were included in the systematic review, and 9 in the meta-analysis. The pooled sensitivity was 0.97 (95% confidence interval [95% CI] 0.85–0.99) with heterogeneity (I2=73.5, 95% CI 55.6–91.2), and the specificity was 0.92 (95% CI 0.82–0.96) with heterogeneity (I2=42.0, 95% CI 0.0–86.9). The pooled positive and negative likelihood ratios were 11.49 (95% CI 5.07–26.0) and 0.03 (95% CI 0.01–0.18), respectively. The diagnostic odds ratio was 341 (95% CI 53–2194), and the area under the receiver operating characteristic curve was 0.96 (95% CI 0.94–0.97).CONCLUSION:The findings evidence that the bone radiotracer is a valuable noninvasive approach that provides high accuracy for diagnosing TTR-CA and plays a modest role in differentiating TTR-CA from immunoglobulin amyloid light-chain cardiac amyloidosis. 99mTc-HMDP may be more accurate than 99mTc-PYP, 99mTc-DPD, and 18F-NaF in the TTR-CA detecting process, and 18F-NaF is a promising bone tracer to diagnose and differentiate TTR-CA

Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian Splatting

In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fields (NeRF)-based methods have recently risen to prominence for their exceptional ability to reconstruct scenes but are hampered by slow inference speed, prolonged training, and inconsistent depth estimation. Some previous work utilizes ground truth depth for optimization but is hard to acquire in the surgical domain. To overcome these obstacles, we present Endo-4DGS, a real-time endoscopic dynamic reconstruction approach that utilizes 3D Gaussian Splatting (GS) for 3D representation. Specifically, we propose lightweight MLPs to capture temporal dynamics with Gaussian deformation fields. To obtain a satisfactory Gaussian Initialization, we exploit a powerful depth estimation foundation model, Depth-Anything, to generate pseudo-depth maps as a geometry prior. We additionally propose confidence-guided learning to tackle the ill-pose problems in monocular depth estimation and enhance the depth-guided reconstruction with surface normal constraints and depth regularization. Our approach has been validated on two surgical datasets, where it can effectively render in real-time, compute efficiently, and reconstruct with remarkable accuracy

Mitigation of Multiple Environmental Footprints for China’s Pig Production Using Different Land Use Strategies

Pig production contributes considerably to land use and greenhouse gas (GHG) and reactive nitrogen (Nr) emissions. Land use strategies were widely proposed, but the spillover effects on biological flow are rarely explored. Here, we simultaneously assessed the carbon (C), nitrogen (N), and cropland footprints of China's pig production at the provincial scale in 2017. The environmental impacts of land use strategies were further evaluated. Results show that one kg live-weight pig production generated an average of 1.9 kg CO2-equiv and 59 g Nr emissions, occupying 3.5 m2 cropland, with large regional variations. A large reduction in GHG (58-64%) and Nr (12-14%) losses and occupied cropland (10-11%) could be achieved simultaneously if combined strategies of intensive crop production, improved feed-protein utilization efficiency, and feeding co-products were implemented. However, adopting a single strategy may have environmental side-effects. Reallocating cropland that pigs used for feed to plant food alternatives would enhance human-edible energy (3-20 times) and protein delivery (1-5 times) and reduce C and N footprints, except for rice and vegetables. Reallocating cropland to beef and milk production would decrease energy and protein supply. Therefore, a proper combination of land use strategies is essential to alleviate land use changes and nutrient emissions without sacrificing food supply

A Kind of New Surface Modeling Method Based on DEM Data

Surface elevation changes greatly in the river erosion area. Due to the limitation of the acquisition equipment and cost, the traditional seismic acquisition data has sparse physical points both horizontally and longitudinally, the density of surface measurement data is not enough to survey the surface structure in detail. With the development of science and technology, and the application of satellite technology, the DEM elevation data obtained from the geographic information system (GIS) are becoming more and more accurate. In this paper, a precise modeling is performed on the surface based on the geographic information from the river erosion area and combined with the results of the surface survey control points, a good effect is achieved.Key words: River erosion area; Geographic information; Similarity coefficient; Kriging interpolation; Surface modeling; High and low frequency static