Asiaticoside ameliorates uterine injury induced by zearalenone in mice by reversing endometrial barrier disruption, oxidative stress and apoptosis.

Zearalenone (ZEA) is a mycotoxin produced by Fusarium fungi that has been shown to have adverse effects on human and animal health, particularly on the fertility of females. As a saponin derived from the medicinal plant Centella asiatica, asiaticoside (AS) has multiple bioactivities. This study aimed to investigate the protective effects of AS on ZEA-induced uterine injury and the underlying mechanism.

ResNeXt-CC: a novel network based on cross-layer deep-feature fusion for white blood cell classification.

Accurate diagnosis of white blood cells from cytopathological images is a crucial step in evaluating leukaemia. In recent years, image classification methods based on fully convolutional networks have drawn extensive attention and achieved competitive performance in medical image classification. In this paper, we propose a white blood cell classification network called ResNeXt-CC for cytopathological images.

Identifying the genetic association between the cerebral cortex and fibromyalgia.

Fibromyalgia (FM) is a central sensitization syndrome that is strongly associated with the cerebral cortex. This study used bidirectional two-sample Mendelian randomization (MR) analysis to investigate the bidirectional causality between FM and the cortical surface area and cortical thickness of 34 brain regions. Inverse variance weighted (IVW) was used as the primary method for this study, and sensitivity analyses further supported the results.

SLIVER: Unveiling large scale gene regulatory networks of single-cell transcriptomic data through causal structure learning and modules aggregation.

Prevalent Gene Regulatory Network (GRN) construction methods rely on generalized correlation analysis. However, in biological systems, regulation is essentially a causal relationship that cannot be adequately captured solely through correlation. Therefore, it is more reasonable to infer GRNs from a causal perspective.

Cross-modal attention network for retinal disease classification based on multi-modal images.

Multi-modal eye disease screening improves diagnostic accuracy by providing lesion information from different sources. However, existing multi-modal automatic diagnosis methods tend to focus on the specificity of modalities and ignore the spatial correlation of images. This paper proposes a novel cross-modal retinal disease diagnosis network (CRD-Net) that digs out the relevant features from modal images aided for multiple retinal disease diagnosis.

UWAFA-GAN: Ultra-Wide-Angle Fluorescein Angiography Transformation via Multi-Scale Generation and Registration Enhancement.

Fundus photography, in combination with the ultra-wide-angle fundus (UWF) techniques, becomes an indispensable diagnostic tool in clinical settings by offering a more comprehensive view of the retina. Nonetheless, UWF fluorescein angiography (UWF-FA) necessitates the administration of a fluorescent dye via injection into the patient's hand or elbow unlike UWF scanning laser ophthalmoscopy (UWF-SLO). To mitigate potential adverse effects associated with injections, researchers have proposed the development of cross-modality medical image generation algorithms capable of converting UWF-SLO images into their UWF-FA counterparts.

Suppressing label noise in medical image classification using mixup attention and self-supervised learning.

Deep neural networks (DNNs) have been widely applied in medical image classification and achieve remarkable classification performance. These achievements heavily depend on large-scale accurately annotated training data. However, label noise is inevitably introduced in the medical image annotation, as the labeling process heavily relies on the expertise and experience of annotators.

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 microaneurysms (MAs), 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.

Establishment and validation of a nomogram to predict postoperative anemia after total hip arthroplasty.

Background: Anemia is a common complication of total hip arthroplasty (THA). In this study, we evaluated the preoperative risk factors for postoperative anemia after THA and developed a nomogram model based on related preoperative and intraoperative factors.

Methods: From January 2020 to May 2023, 927 THA patients at the same medical center were randomly assigned to either the training or validation cohort.

Altered whole brain functional activity in patients with fibromyalgia.

Objectives: Fibromyalgia (FM) is a chronic pain disorder that takes a severe physical and psychological toll on patients and severely reduces their quality of life. In recent years, an increasing number of studies have used functional magnetic resonance imaging (fMRI) to investigate its pathogenesis. However, a recent summary analysis of functional connectivity in patients with FM is lacking.

Microplastics as potential barriers to ultraviolet light emitting diode inactivation of MS2 bacteriophage: Influence of water-quality parameters.

Microplastics have emerged as a concerning contaminant in drinking water sources, potentially interacting with pathogenic microorganisms and affecting the disinfection processes. In this study, MS2 was selected as an alternative for the human enteric virus. The influence of microplastics polyvinylchloride (MPs-PVC) on ultraviolet light emitting diode (UV-LED) inactivation of MS2 was investigated under various water chemistry conditions, such as MPs-PVC concentration, pH, salinity, and humic acid concentration.

Global research trends of the application of artificial intelligence in bladder cancer since the 21st century: a bibliometric analysis.

Introduction: Since the significant breakthroughs in artificial intelligence (AI) algorithms, the application of AI in bladder cancer has rapidly expanded. AI can be used in all aspects of the bladder cancer field, including diagnosis, treatment and prognosis prediction. Nowadays, these technologies have an excellent medical auxiliary effect and are in explosive development, which has aroused the intense interest of researchers.

Research trends and hotspots in prostate cancer associated exosome: a bibliometric analysis.

Background: Prostate cancer is viewed as the second most common cancer in men worldwide. In our study, we used bibliometric analysis to construct a visual map of the relationship between prostate cancer and exosomes with the intent of uncovering research trends and current hotspots in this field.

Method: We searched the Web of Science Core Collection for all publications in the prostate cancer associated with exosome field came out since 2010.

Early clinical efficacy analysis of enhanced recovery following surgery combined with interscalene brachial plexus block for arthroscopic rotator cuff repair.

To explore the early clinical value of enhanced recovery after surgery (ERAS) with interscalene brachial plexus block (ISB) for arthroscopic rotator cuff repair (ARCR). We enrolled 240 patients who underwent arthroscopic rotator cuff repair, randomly divided into 3 groups (n = 80 each). Groups A, B, and C underwent only surgery, surgery + ERAS, and ISB + surgery + ERAS, respectively.

Retinal layers changes in patients with age-related macular degeneration treated with intravitreal anti-VEGF agents.

Background: The purpose of this study was to investigate retinal layers changes in patients with age-related macular degeneration (AMD) treated with anti-vascular endothelial growth factor (anti-VEGF) agents and to evaluate if these changes may affect treatment response.

Methods: This study included 496 patients with AMD or PCV who were treated with anti-VEGF agents and followed up for at least 6 months. A comprehensive analysis of retinal layers affecting visual acuity was conducted.

A lightweight network based on dual-stream feature fusion and dual-domain attention for white blood cells segmentation.

Introduction: Accurate white blood cells segmentation from cytopathological images is crucial for evaluating leukemia. However, segmentation is difficult in clinical practice. Given the very large numbers of cytopathological images to be processed, diagnosis becomes cumbersome and time consuming, and diagnostic accuracy is also closely related to experts' experience, fatigue and mood and so on.

Discriminative ensemble meta-learning with co-regularization for rare fundus diseases diagnosis.

Deep neural networks (DNNs) have been widely applied in the medical image community, contributing to automatic ophthalmic screening systems for some common diseases. However, the incidence of fundus diseases patterns exhibits a typical long-tailed distribution. In clinic, a small number of common fundus diseases have sufficient observed cases for large-scale analysis while most of the fundus diseases are infrequent.

Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review.

Optic never fibers in the visual pathway play significant roles in vision formation. Damages of optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and neurological diseases; also, there is a need to prevent the optic nerve fibers from getting damaged in neurosurgery and radiation therapy. Reconstruction of optic nerve fibers from medical images can facilitate all these clinical applications.

Arthroscopic vs. open Broström-Gould for repairing anterior talofibular ligament: mid-term outcomes comparison.

Introduction: There have been few mid-term follow-up studies comparing arthroscopic and open Broström-Gould repair of the anterior talofibular ligament (ATFL). The purpose of this study was to evaluate the mid-term therapeutic effectiveness of arthroscopic ATFL repair with open Broström-Gould repair for chronic lateral ankle instability.

Methods: We retrospectively reviewed the database of patients with chronic lateral ankle instability undergoing repair of the ATFL from June 2014 to June 2018.

Ga-cyc-DX600 PET/CT in ACE2-targeted tumor imaging.

Purpose: For the tumor-specific ACE2 expression, this research aimed to establish and verify ACE2-targeted PET imaging in differentiating tumors with distinct ACE2 expression.

Methods: Ga-cyc-DX600 was synthesized as tracer of ACE2 PET. NOD-SCID mice were used to prepare the subcutaneous tumor models with HEK-293 or HEK-293T/hACE2 cells to verify ACE2 specificity, with other kinds of tumor cells to evaluate the diagnostic efficiency for ACE2 expression, additionally, immunohistochemical analysis and western blot were used to certify the findings on ACE2 PET, which was then performed on four cancer patients and compared with FDG PET.

Multi-Learner Based Deep Meta-Learning for Few-Shot Medical Image Classification.

Few-shot learning (FSL) is promising in the field of medical image analysis due to high cost of establishing high-quality medical datasets. Many FSL approaches have been proposed in natural image scenes. However, present FSL methods are rarely evaluated on medical images and the FSL technology applicable to medical scenarios need to be further developed.

The role of autophagy in calcium oxalate kidney stone: A systematic review of the literature.

Calcium oxalate kidney stone is one of the common diseases in the urinary system and has a high recurrence rate. Currently, the pathogenesis of kidney stone and the methods to prevent recurrence are still being investigated. Autophagy, as an event of cellular self-repair, has received attention in the field of kidney stone in recent years.

LMO3 downregulation in PCa: A prospective biomarker associated with immune infiltration.

Prostate cancer is the third leading cause of new cancer cases and the second most common tumor type in men globally. LMO3 has been stated to play a vital role in some cancers; however, the prognostic value of LMO3 in PCa remains vague. Here, we utilized various web databases to elucidate in detail the prognostic value and molecular functions of LMO3 in PCa.