Trifolin attenuates hypertension-mediated cardiac injury by inhibiting cardiomyocyte apoptosis: Mechanistic insights and therapeutic potential.

Background: Hypertension-induced cardiac disease is a common complication and a significant contributor to mortality in hypertensive patients, largely due to cardiomyocyte apoptosis. Although Trifolin has been identified as a potential antihypertensive compound, its therapeutic role in hypertension-induced cardiac injury remains uncertain.

Purpose: This study aims to evaluate the protective effects of Trifolin and explore the underlying mechanisms of its action against hypertension-induced cardiac injury.

Multi-octave two-color soliton frequency comb in integrated chalcogenide microresonators.

Mid-infrared (MIR) Kerr microcombs are of significant interest for portable dual-comb spectroscopy and precision molecular sensing due to strong molecular vibrational absorption in the MIR band. However, achieving a compact, octave-spanning MIR Kerr microcomb remains a challenge due to the lack of suitable MIR photonic materials for the core and cladding of integrated devices and appropriate MIR continuous-wave (CW) pump lasers. Here, we propose a novel slot concentric dual-ring (SCDR) microresonator based on an integrated chalcogenide glass chip, which offers excellent transmission performance and flexible dispersion engineering in the MIR band.

Few-Shot Image Generation via Style Adaptation and Content Preservation.

Training a generative model with limited data (e.g., 10) is a very challenging task.

Baicalin ameliorates angiotensin II-induced cardiac hypertrophy and mitogen-activated protein kinase signaling pathway activation: A target-based network pharmacology approach.

Baicalin, a flavonoid glycoside from Scutellaria baicalensis Georgi., exerts anti-hypertensive effects. The present study aimed to assess the cardioprotective role of baicalin and explore its potential mechanisms.

Therapeutic potential of Pien Tze Huang in colitis-associated colorectal cancer: mechanistic insights from a mouse model.

Background: Pien Tze Huang (PZH), a traditional Chinese medicine formulation, is recognized for its therapeutic effect on colitis and colorectal cancer. However, its protective role and underlying mechanism in colitis-associated colorectal cancer (CAC) remain to be elucidated.

Methods: A CAC mouse model was established using AOM/DSS.

Instance Consistency Regularization for Semi-Supervised 3D Instance Segmentation.

Large-scale datasets with point-wise semantic and instance labels are crucial to 3D instance segmentation but also expensive. To leverage unlabeled data, previous semi-supervised 3D instance segmentation approaches have explored self-training frameworks, which rely on high-quality pseudo labels for consistency regularization. They intuitively utilize both instance and semantic pseudo labels in a joint learning manner.

Self-Supervised 3D Scene Flow Estimation and Motion Prediction Using Local Rigidity Prior.

In this article, we investigate self-supervised 3D scene flow estimation and class-agnostic motion prediction on point clouds. A realistic scene can be well modeled as a collection of rigidly moving parts, therefore its scene flow can be represented as a combination of rigid motion of these individual parts. Building upon this observation, we propose to generate pseudo scene flow labels for self-supervised learning through piecewise rigid motion estimation, in which the source point cloud is decomposed into local regions and each region is treated as rigid.

CMFAN: Cross-Modal Feature Alignment Network for Few-Shot Single-View 3D Reconstruction.

Few-shot single-view 3D reconstruction learns to reconstruct the novel category objects based on a query image and a few support shapes. However, since the query image and the support shapes are of different modalities, there is an inherent feature misalignment problem damaging the reconstruction. Previous works in the literature do not consider this problem.

Textbook oncological outcomes and prognosis after curative gastrectomy in advanced gastric cancer: A multicenter study.

Background: The impact of achieving textbook oncological outcome (TOO) as a multimodal therapy quality indicator on the prognosis of advanced gastric cancer (AGC) remains inadequately assessed.

Methods: Patients with AGC who underwent curative gastrectomy between January 2010 and December 2017 at two East Asian medical centers were included. TOO was defined as achieving the textbook outcome (TO) and receiving neoadjuvant and/or adjuvant chemotherapy (NCT or ACT).

OSATS scoring confirms ICG enhancement of performance in laparoscopic radical gastrectomy: a post-hoc analysis of a randomized controlled trial.

Background: Indocyanine green (ICG) fluorescence imaging is effective in increasing the number of lymph node dissections during laparoscopic radical gastrectomy; however, no studies have attempted to explain this phenomenon.

Methods: This study utilized the data from a previous randomized controlled trial (FUGES-012 study) investigating ICG-guided laparoscopic radical gastrectomy performed between November 2018 and July 2019. The Objective Structured Assessments of Technical Skills (OSATS) scoring system was used to grade videos from the ICG and non-ICG groups.

Evaluation of dynamic recurrence risk for locally advanced gastric cancer in the clinical setting of adjuvant chemotherapy: a real-world study with IPTW-based conditional recurrence analysis.

Background: The long-term dynamic recurrence hazard of locally advanced gastric cancer (LAGC) in the clinical setting of adjuvant chemotherapy (ACT) remains unclear.

Purpose: This study aimed to investigate the dynamic recurrence risk of LAGC in patients who received ACT or not.

Methods: The study assessed data from patients with LAGC who underwent radical gastrectomy between January, 2010 and October, 2015.

An international multi-institution real-world study of the optimal surveillance frequency for stage II/III gastric cancer: the more, the better?

Background: Due to lacking evidence on surveillance for gastric cancer (GC), this study aimed to determine the optimal postsurgical surveillance strategy for pathological stage (pStage) II/III GC patients and compare its cost-effectiveness with traditional surveillance strategies.

Methods: Prospectively collected data from stage II/III GC patients ( n =1661) who underwent upfront surgery at a large-volume tertiary cancer center in China (FJMUUH cohort) between January 2010 and October 2015. For external validation, two independent cohorts were included, which were composed of 380 stage II/III GC patients at an tertiary cancer center in U.

A scoring model for predicting early recurrence of gastric cancer with normal preoperative tumor markers: A multicenter study.

Introduction: Prognostic factors for postoperative early recurrence (ER) of gastric cancer (GC) in patients with normal or abnormal preoperative tumor markers (pre-TMs) remain unclear.

Materials And Methods: 2875 consecutive patients with GC who underwent radical gastrectomy (RG) between January 2010 and December 2016 were enrolled and randomly divided into training and internal validation groups. ER was defined as recurrence within two years of gastrectomy.

Semantic Consistent Embedding for Domain Adaptive Zero-Shot Learning.

Unsupervised domain adaptation has limitations when encountering label discrepancy between the source and target domains. While open-set domain adaptation approaches can address situations when the target domain has additional categories, these methods can only detect them but not further classify them. In this paper, we focus on a more challenging setting dubbed Domain Adaptive Zero-Shot Learning (DAZSL), which uses semantic embeddings of class tags as the bridge between seen and unseen classes to learn the classifier for recognizing all categories in the target domain when only the supervision of seen categories in the source domain is available.

Comparison of robotic versus laparoscopic versus open distal gastrectomy for locally advanced gastric cancer: a prospective trial-based economic evaluation.

Importance: It is largely unclear whether robotic distal gastrectomy (RDG) is cost-effective for locally advanced gastric cancer (LAGC).

Objective: To evaluate the cost-effectiveness of RDG, laparoscopic distal gastrectomy (LDG), and open distal gastrectomy (ODG) for patients with LAGC.

Design, Setting, And Participants: Inverse probability of treatment weighting (IPTW) was used to balance baseline characteristics.

Single-View 3D Mesh Reconstruction for Seen and Unseen Categories.

Single-view 3D object reconstruction is a fundamental and challenging computer vision task that aims at recovering 3D shapes from single-view RGB images. Most existing deep learning based reconstruction methods are trained and evaluated on the same categories, and they cannot work well when handling objects from novel categories that are not seen during training. Focusing on this issue, this paper tackles Single-view 3D Mesh Reconstruction, to study the model generalization on unseen categories and encourage models to reconstruct objects literally.

Unsupervised 3D Pose Transfer With Cross Consistency and Dual Reconstruction.

The goal of 3D pose transfer is to transfer the pose from the source mesh to the target mesh while preserving the identity information (e.g., face, body shape) of the target mesh.

Robust-EQA: Robust Learning for Embodied Question Answering With Noisy Labels.

Embodied question answering (EQA) is a recently emerged research field in which an agent is asked to answer the user's questions by exploring the environment and collecting visual information. Plenty of researchers turn their attention to the EQA field due to its broad potential application areas, such as in-home robots, self-driven mobile, and personal assistants. High-level visual tasks, such as EQA, are susceptible to noisy inputs, because they have complex reasoning processes.

The GLIM criteria as an effective tool for survival prediction in gastric cancer patients.

Background: The Global Leadership Initiative on Malnutrition released a new version of the malnutrition criteria (GLIM criteria). To investigate the influence of the GLIM criteria on the long-term efficacy of radical gastric cancer surgery and establish a nomogram to predict the long-term prognosis of patients with gastric cancer.

Methods: A retrospective analysis of 1121 patients with gastric cancer in our department from 2010 to 2013 was performed.

Assessment of Laparoscopic Spleen-Preserving Hilar Lymphadenectomy for Advanced Proximal Gastric Cancer Without Invasion Into the Greater Curvature: A Randomized Clinical Trial.

Importance: The survival benefit of laparoscopic total gastrectomy combined with spleen-preserving splenic hilar lymphadenectomy (LSTG) for locally advanced proximal gastric cancer (APGC) without invasion into the greater curvature remains uncertain.

Objective: To compare the long-term and short-term efficacy of LSTG (D2 + No. 10 group) and conventional laparoscopic total gastrectomy (D2 group) for patients with APGC that has not invaded the greater curvature.

DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning.

In this work, we develop methods for few-shot image classification from a new perspective of optimal matching between image regions. We employ the Earth Mover's Distance (EMD) as a metric to compute a structural distance between dense image representations to determine image relevance. The EMD generates the optimal matching flows between structural elements that have the minimum matching cost, which is used to calculate the image distance for classification.

Value of the Preoperative D-Dimer to Albumin Ratio for Survival and Recurrence Patterns in Gastric Cancer.

Background: D-dimer (DDI) and albumin are prognostic markers for numerous cancers; however, the predictive value of the preoperative DDI-to-albumin ratio (DAR) on the survival and recurrence patterns of gastric cancer (GC) remains unclear.

Objective: The aim of this study was to explore the prognostic value of the DAR in GC.

Methods: Our study included 1766 patients with GC, divided into training and testing cohorts at a ratio of 7:3.