ZnCe-LDO Nanozyme-Based Multifunctional Hydrogel Promotes Bone Regeneration by Inflammatory Macrophage Reprogramming and Piezo1 Activation.

Prolonged or excessive inflammation may lead to impaired vascularization and bone regeneration, hindering the normal repair process of bone tissue. Although the regulation of inflammation is crucial for promoting a conducive microenvironment for bone regeneration, individual anti-inflammatory interventions frequently are inadequate in facilitating effective bone repair. Here, a multifunctional hydrogel (GelMA-ZC-Yoda1) with multifaceted therapeutic strategy was designed by integrating Zinc/Cerium-layered double oxide nanozyme (ZnCe-LDO, with catalase-like activity) and Yoda1 (an activator of the mechanically sensitive Piezo1 ion channel) into photocurable GelMA hydrogel.

Impairing the interaction between Erg11 and cytochrome P450 reductase Ncp1 enhances azoles' antifungal activities.

Azole effectiveness against candidiasis can be compromised by Candida albicans resistance and tolerance, and unfortunately, few clinically useful compounds can enhance azole antifungal activities. We find that the amino acids V234, F235 and L238 of Erg11 are critical for its interaction with Ncp1, and the Ncp1-Erg11 association is important in azole response. Ellipticine and its analog phiKan 083 block this Erg11-Ncp1 interaction by targeting Ncp1, and boost antifungal effects of fluconazole in vitro and in vivo.

FAM83A Promotes the Progression and Metastasis of Head and Neck Squamous Cell Carcinoma via PKM2-Mediated Aerobic Glycolysis.

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive malignancy that frequently results in mortality due to postoperative recurrence. In our previous study, we identified for the first time that the family with sequence similarity 83, member A (FAM83A), is overexpressed in HNSCC and associated with poor patient prognosis. However, its role in HNSCC metabolism remains unclear.

An Ultrasound Signal-Guided Two-Stage Weakly Supervised Network for Intraoperative Glioma Localization and Infiltration Boundary Recognition Using a Nude Mouse Model.

Objective: Surgical resection is the standard treatment for glioma. While gross tumor regions can be identified, microscopic infiltration is often elusive without histopathology. Developing real-time techniques to approximate gold-standard boundaries intraoperatively is crucial for surgical accuracy and patient outcomes.

Structural state governs the mechanism of shear-band propagation in metallic glasses.

Shear bands (SBs) play a critical role in determining the mechanical behavior of metallic glasses (MGs). However, the rapid dynamics and highly localized nature of SB propagation present significant challenges for direct observation of their atomistic mechanisms using experimental techniques. In this study, we employ hybrid molecular dynamics/Monte Carlo simulations to investigate the atomic-scale mechanisms of SB propagation in MgCuY MGs, prepared using cooling rates as slow as 10 K s-comparable to experimental casting conditions and significantly slower than the 10 K s rates previously employed in atomistic simulations.

Expert consensus on management of instrument separation in root canal therapy.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes.

An AI-assisted fluorescence microscopic system for screening mitophagy inducers by simultaneous analysis of mitophagic intermediates.

Mitophagy, the selective autophagic elimination of mitochondria, is essential for maintaining mitochondrial quality and cell homeostasis. Impairment of mitophagy flux, a process involving multiple sequential intermediates, is implicated in the onset of numerous neurodegenerative diseases. Screening mitophagy inducers, particularly understanding their impact on mitophagic intermediates, is crucial for neurodegenerative disease treatment.

Deep learning model based on ultrasound images predicts BRAF V600E mutation in papillary thyroid carcinoma.

BRAF V600E mutation status detection facilitates prognosis prediction in papillary thyroid carcinoma (PTC). We developed a deep-learning model to determine the BRAF V600E status in PTC. PTC from three centers were collected as the training set (1341 patients), validation set (148 patients), and external test set (135 patients).

Case Report: A case study on the relationship between obesity and estrus in female captive panda.

This study investigated a case of abnormal estrus in a captive adult female giant panda () (X#, 130 kg) in 2024 to explore the possible relationship between overweight or obesity and estrus behavior in female giant pandas. Behavioral observations and urinary estrogen conjugate/creatinine (EC/CR) measurements revealed a significantly attenuated hormonal profile (peak EC/CR: 34.1 ng/mg vs.

Research on CT image segmentation and classification of liver tumors based on attention mechanism and improved U-Net model.

BackgroundLiver cancer is still one of the most common causes of death from cancer globally. The accurate segmentation of liver tumors from CT images is critical for diagnosis, treatment planning, and tracking. Conventional segmentation techniques frequently struggle to handle the intricacy of medical images, requiring the usage of sophisticated artificial intelligence (AI) methods to enhance accuracy and effectiveness.

Anatomy-inspired model for critical landmark localization in 3D spinal ultrasound volume data.

Three-dimensional (3D) spinal ultrasound imaging has demonstrated its promising potential in measuring spinal deformity through recent studies, and it is more suitable for massive early screening and longitudinal follow-up of adolescent idiopathic scoliosis (AIS) compared with X-ray imaging due to its radiation-free superiority. Moreover, some deformities with low observability, such as vertebral rotation, in X-ray images can also be reflected by critical landmarks in 3D ultrasound data. In this paper, we propose a localization network (LLNet) to extract lamina in 3D ultrasound data, which has been indicated as a meaningful anatomy for measuring vertebral rotation by clinical studies.

Artificial Intelligent-Enhanced Metabolite Profiling for Intraoperative IDH1 Genotyping in Glioma Using an Orthogonally Responsive SERS Probe.

Intraoperative identification of the isocitrate dehydrogenase type 1 (IDH1) genotype, a key molecular marker in glioma, is essential for optimizing surgical strategies and tailoring post-surgical treatments. However, current clinical practices lack effective methods for real-time IDH1 genotype detection during surgery. Here, a novel strategy is proposed for intraoperative IDH1 genotype identification by simultaneously measuring two redox-related metabolites.

Expert consensus on intentional tooth replantation.

Intentional tooth replantation (ITR) is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions. ITR is defined as the deliberate extraction of a tooth; evaluation of the root surface, endodontic manipulation, and repair; and placement of the tooth back into its original socket. Case reports, case series, cohort studies, and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery.

Dual-path neural network extracts tumor microenvironment information from whole slide images to predict molecular typing and prognosis of Glioma.

Background And Objective: Utilizing AI to mine tumor microenvironment information in whole slide images (WSIs) for glioma molecular subtype and prognosis prediction is significant for treatment. Existing weakly-supervised learning frameworks based on multi-instance learning have potential in WSIs analysis, but the large number of patches from WSIs challenges the effective extraction of key local patch and neighboring patch microenvironment info. Therefore, this paper aims to develop an automatic neural network that effectively extracts tumor microenvironment information from WSIs to predict molecular typing and prognosis of glioma.

ATF3 triggers M2 macrophage polarization to protect against pulp inflammation through WNT4 regulation.

Pulpitis is a common inflammatory oral disease that can lead to pulp necrosis. The aim of this study is to investigate the expression and regulatory mechanisms of ATF3, a potential therapeutic marker, in pulpitis. A mouse pulpitis model with different degrees of inflammation is established, and the expression of ATF3 in pulpitis is explored.

Expert consensus on pulpotomy in the management of mature permanent teeth with pulpitis.

Pulpotomy, which belongs to vital pulp therapy, has become a strategy for managing pulpitis in recent decades. This minimally invasive treatment reflects the recognition of preserving healthy dental pulp and optimizing long-term patient-centered outcomes. Pulpotomy is categorized into partial pulpotomy (PP), the removal of a partial segment of the coronal pulp tissue, and full pulpotomy (FP), the removal of whole coronal pulp, which is followed by applying the biomaterials onto the remaining pulp tissue and ultimately restoring the tooth.

Expert consensus on apical microsurgery.

Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus.

3D culture inhibits replicative senescence of SCAPs via UQCRC2-mediated mitochondrial oxidative phosphorylation.

Stem cells derived from the apical papilla (SCAPs) play a crucial role in tooth root development and dental pulp regeneration. They are important seed cells for bone/tooth tissue engineering. However, replicative senescence remains an unavoidable issue as in vitro amplification increases.

Intraoperative Real-Time IDH Diagnosis for Glioma Based on Automatic Analysis of Contrast-Enhanced Ultrasound Video.

Objective: Isocitrate dehydrogenase (IDH) is the most important molecular marker of glioma and is highly correlated to the diagnosis, treatment, and prognosis of patients. We proposed a real-time diagnosis method for IDH status differentiation based on automatic analysis of intraoperative contrast-enhanced ultrasound (CEUS) video.

Methods: Inspired by the Time Intensity Curve (TIC) analysis of CEUS utilized in clinical practice, this paper proposed an automatic CEUS video analysis method called ATAN (Automatic TIC Analysis Network).

Circ-SPATA13 regulates the osteogenic differentiation of human periodontal ligament stem cells through the miR-485-5p_R + 1/BMP7 axis.

Background: Human periodontal ligament stem cells (PDLSCs) are widely available and have strong osteogenic differentiation ability, which makes them promising tools for bone regeneration. Circular RNAs (circRNAs) play a variety of functions in the process of cell differentiation and are potential therapeutic targets. Here, we identified a new circRNA, circ-SPATA13, and found that it was highly positively correlated with the osteogenic differentiation of PDLSCs.

UDA-GS: A cross-center multimodal unsupervised domain adaptation framework for Glioma segmentation.

Gliomas are the most common and malignant form of primary brain tumors. Accurate segmentation and measurement from MRI are crucial for diagnosis and treatment. Due to the infiltrative growth pattern of gliomas, their labeling is very difficult.

A single-cell transcriptomic atlas of human stem cells from apical papilla during the committed differentiation.

Aim: Human stem cells derived from the apical papilla (SCAPs) are recognized for their multilineage differentiation potential and their capacity for functional tooth root regeneration. However, the molecular mechanisms underlying odonto/osteogenic differentiation remain largely unexplored. In this study, we utilized single-cell RNA sequencing (scRNA-seq) to conduct an in-depth analysis of the transcriptional changes associated with chemically induced osteogenesis in SCAPs.

Active learning based on multi-enhanced views for classification of multiple patterns in lung ultrasound images.

There are several main patterns in lung ultrasound (LUS) images, including A-lines, B-lines, consolidation and pleural effusion. LUS images of healthy lungs typically only exhibit A-lines, while other patterns may emerge or coexist in LUS images associated with different lung diseases. The accurate categorization of these primary patterns is pivotal for effective lung disease screening.

Classifying disorders of consciousness using a novel dual-level and dual-modal graph learning model.

Background: Disorders of consciousness (DoC) are a group of conditions that affect the level of awareness and communication in patients. While neuroimaging techniques can provide useful information about the brain structure and function in these patients, most existing methods rely on a single modality for analysis and rarely account for brain injury. To address these limitations, we propose a novel method that integrates two neuroimaging modalities, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), to enhance the classification of subjects into different states of consciousness.

Preoperative Ultrasound Radomics to Predict Posthepatectomy Liver Failure in Patients With Hepatocellular Carcinoma.

Purpose: Posthepatectomy liver failure (PHLF) is a major cause of postoperative mortality in hepatocellular carcinoma (HCC) patients. The study aimed to develop a method based on the two-dimensional shear wave elastography and clinical data to evaluate the risk of PHLF in HCC patients with chronic hepatitis B.

Methods: This multicenter study proposed a deep learning model (PHLF-Net) incorporating dual-modal ultrasound features and clinical indicators to predict the PHLF risk.