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.

Isobavachalcone Exhibits Potent Antifungal Efficacy by Inhibiting Enolase Activity and Glycolysis in .

Invasive fungal diseases (IFDs) are becoming increasingly acknowledged as a significant concern linked to heightened rates of morbidity and mortality. Regrettably, the available antifungal therapies for managing IFDs are constrained. Emerging evidence indicates that enolase holds promise as a potential target protein for combating IFDs; however, there is currently a deficiency in antifungal medications specifically targeting enolase.

Otilonium Bromide Exhibits Potent Antifungal Effects by Blocking Ergosterol Plasma Membrane Localization and Triggering Cytotoxic Autophagy in Candida Albicans.

Candidiasis, which presents a substantial risk to human well-being, is frequently treated with azoles. However, drug-drug interactions caused by azoles inhibiting the human CYP3A4 enzyme, together with increasing resistance of Candida species to azoles, represent serious issues with this class of drug, making it imperative to develop innovative antifungal drugs to tackle this growing clinical challenge. A drug repurposing approach is used to examine a library of Food and Drug Administration (FDA)-approved drugs, ultimately identifying otilonium bromide (OTB) as an exceptionally encouraging antifungal agent.

METTL3-mediated pre-miR-665/DLX3 mA methylation facilitates the committed differentiation of stem cells from apical papilla.

Methyltransferase-like 3 (METTL3) is a crucial element of N6-methyladenosine (mA) modifications and has been extensively studied for its involvement in diverse biological and pathological processes. In this study, we explored how METTL3 affects the differentiation of stem cells from the apical papilla (SCAPs) into odonto/osteoblastic lineages through gain- and loss-of-function experiments. The mA modification levels were assessed using mA dot blot and activity quantification experiments.

Geldanamycin confers fungicidal properties to azole by triggering the activation of succinate dehydrogenase.

Aims: Azoles have been widely employed for the treatment of invasive fungal diseases; however, their efficacy is diminished as pathogenic fungi tolerate them due to their fungistatic properties. Geldanamycin (GdA) can render azoles fungicidal by inhibiting the ATPase and molecular chaperone activities of heat shock protein 90 (Hsp90). Nonetheless, the clinical applicability of GdA is restricted due to its cytotoxic ansamycin scaffold structure, its induction of cytoprotective heat shock responses, and the conservative nature of Hsp90.

Expert consensus on irrigation and intracanal medication in root canal therapy.

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.

Expert consensus on difficulty assessment of endodontic therapy.

Endodontic diseases are a kind of chronic infectious oral disease. Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha. However, it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy (RCT).

Halofantrine Hydrochloride Acts as an Antioxidant Ability Inhibitor That Enhances Oxidative Stress Damage to .

, a prominent opportunistic pathogenic fungus in the human population, possesses the capacity to induce life-threatening invasive candidiasis in individuals with compromised immune systems despite the existence of antifungal medications. When faced with macrophages or neutrophils, demonstrates its capability to endure oxidative stress through the utilization of antioxidant enzymes. Therefore, the enhancement of oxidative stress in innate immune cells against presents a promising therapeutic approach for the treatment of invasive candidiasis.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images.

Background: Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC).

Methods: DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets.

Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model.

Objectives: Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy.

Methods: A total of 726 HER2 + cases who received no/single/dual anti-HER2 targeted therapies were split into three respective cohorts.