LncRNA RP11-301G19.1 is required for the maintenance of vascular smooth muscle cell contractile phenotype via sponging miR-17-5P/ATOH8 axis.

Long noncoding RNAs (LncRNAs) play essential roles in regulating gene expression in various biological processes. However, the function of lncRNAs in vascular smooth muscle cell (VSMC) transformation remains to be explained. In this work, we discover that a new bone marrow protein (BMP) signaling target, lncRNA RP11-301G19.1, is significantly induced in BMP7-treated VSMCs through lncRNA microarray analysis. Addition of BMP signaling inhibitor LDN-193189 attenuates the expression of ACTA2 and SM-22α, as well as the mRNA level of RP11-301G19.1. Furthermore, lncRNA RP11-301G19.1 is critical to the VSMC differentiation and is directly activated by SMAD1/9. Mechanistically, knocking down of RP11-301G19.1 leads to the decrease of ATOH8, another BMP target, while the forced expression of RP11-301G19.1 reactivates ATOH8. In addition, miR-17-5p, a miRNA negatively regulated by BMP-7, contains predicted binding sites for lncRNA RP11-301G19.1 and ATOH8 3'UTR. Accordingly, overexpression of miR-17-5p decreases the levels of them. Together, our results revealed the role of lncRNA RP11-301G19.1 as a miRNA sponge to upregulate ATOH8 in VSMC phenotype transformation.

STSN-Net: Simultaneous Tooth Segmentation and Numbering Method in Crowded Environments with Deep Learning.

Accurate tooth segmentation and numbering are the cornerstones of efficient automatic dental diagnosis and treatment. In this paper, a multitask learning architecture has been proposed for accurate tooth segmentation and numbering in panoramic X-ray images. A graph convolution network was applied for the automatic annotation of the target region, a modified convolutional neural network-based detection subnetwork (DSN) was used for tooth recognition and boundary regression, and an effective region segmentation subnetwork (RSSN) was used for region segmentation. The features extracted using RSSN and DSN were fused to optimize the quality of boundary regression, which provided impressive results for multiple evaluation metrics. Specifically, the proposed framework achieved a top F1 score of 0.9849, a top Dice metric score of 0.9629, and an mAP (IOU = 0.5) score of 0.9810. This framework holds great promise for enhancing the clinical efficiency of dentists in tooth segmentation and numbering tasks.

Convolutional neural network-assisted diagnosis of midpalatal suture maturation stage in cone-beam computed tomography.

OBJECTIVES: The selection of treatment for maxillary expansion is closely related to the calcification degree of the midpalatal suture. A classification method for individual assessment of the morphology of midpalatal suture in cone-beam computed tomography (CBCT) is useful for evaluating the calcification degree. Currently, convolutional neural networks (CNNs) have been introduced into the field of oral and maxillofacial imaging diagnosis. This study validated the ability of CNN models in assessing the maturation stage of the midpalatal suture. METHODS: The existing CNN model ResNet50 was trained to locate the CBCT transverse plane which contained a complete midpalatal suture. ResNet18, ResNet50, RessNet101, Inception-v3, and Efficientnetv2-s models were trained to evaluate the midpalatal suture maturation stage. Multi-class classification metrics, accuracy, recall, precision, F1-score, and area under the curve values from the receiver operating characteristic curve were used to evaluate the performance of the models, and gradient-weighted class activation map technology was utilised to visualise five midpalatal suture maturation stages for each model. RESULTS: Resnet50 demonstrated an accuracy of 99.74 % in identifying the transverse plane that contained the complete midpalatal suture. The highest accuracies achieved on the two-stage, three-stage, and five-stage maturation classification tests were 95.15, 88.06, and 75.37 %, all of which exceeded the average accuracy of three experienced orthodontists. CONCLUSIONS: The CNN model can locate the plane of the midpalatal suture in CBCT images and can assist clinicians in assessing the maturation stage of the midpalatal suture to select the means of maxillary expansion. CLINICAL SIGNIFICANCE: The application of artificial intelligence on CBCT midpalatal suture plane localisation and maturation stage evaluation enhances diagnostic and treatment efficiency and accuracy of individual assessment of midpalatal suture calcification degree. Additionally, it assists the clinical palatal expansion technique in achieving ideal results.

A TRIM66/DAX1/Dux axis suppresses the totipotent 2-cell-like state in murine embryonic stem cells.

2-cell-like cells (2CLCs)-which comprise only ∼1% of murine embryonic stem cells (mESCs)-resemble blastomeres of 2-cell-stage embryos and are used to investigate zygotic genome activation (ZGA). Here, we discovered that TRIM66 and DAX1 function together as negative regulators of the 2C-like state in mESCs. Chimeric assays confirmed that mESCs lacking TRIM66 or DAX1 function have bidirectional embryonic and extraembryonic differentiation potential. TRIM66 functions by recruiting the co-repressor DAX1 to the Dux promoter, and TRIM66's repressive effect on Dux is dependent on DAX1. A solved crystal structural shows that TRIM66's PHD finger recognizes H3K4-K9me3, and mutational evidence confirmed that TRIM66's PHD finger is essential for its repression of Dux. Thus, beyond expanding the scope of known 2CLC regulators, our study demonstrates that interventions disrupting TRIM66 or DAX1 function in mESCs yield 2CLCs with expanded bidirectional differentiation potential, opening doors for the practical application of these totipotent-like cells.

Use and performance of artificial intelligence applications in the diagnosis of chronic apical periodontitis based on cone beam computed tomography imaging.

OBJECTIVES: This study aims to investigate the diagnostic application of an artificial intelligence (AI) computer-aided diagnostic system based on a convolutional neural network algorithm in detecting chronic apical periodontitis in cone beam computed tomography (CBCT) images. METHODS: CBCT raw data of 55 single root chronic apical pe-riodontitis taken in 2nd Dental Center of Peking University School and Hospital from 49 patients from January 2017 to December 2021 were collected, and the chronic apical periodontitis areas were identified by experienced clinicians ma-nually and segmented layer by layer in Materialise Mimics Medical Software. Deep learning of lesion characterization was conducted via AI 3D U-Net, and the network segmentation results were compared manually with the test sets in terms of intersection over union (IOU), Dice coefficient, and pixel accuracy (PA). RESULTS: In our deep learning algorithm, the IOU for all actual true lesions in test set samples was 92.18%, and the Dice coefficient and the PA index were 95.93% and 99.27%, respectively. Lesion segmentation and volume measurements performed by humans and AI systems showed excellent agreement. CONCLUSIONS: AI systems based on deep learning methods can be applied for detecting chronic apical periodontitis on CBCT images in clinical applications.

Risk factors for postoperative cerebrospinal fluid leakage after transsphenoidal surgery for pituitary adenoma: a meta-analysis and systematic review.

OBJECTIVE: Postoperative cerebrospinal fluid (CSF) leakage represents a challenge even for experienced pituitary surgeons. We aimed to quantitatively synthesize data from studies regarding the risk factors for postoperative CSF leakage after transsphenoidal surgery (TSS) for pituitary adenoma (PA). METHODS: PubMed, Web of Science, The Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang database, and VIP database were searched for case-control and cohort studies, focusing on the risk factors associated with postoperative CSF leakage after TSS for PA. Pooled odds ratios (ORs) and 95% confidence intervals were calculated to determine the risk factors. RESULTS: A total of 34 case-control and cohort studies involving a total of 9,144 patients with PA were included in this systematic review. The overall rate of postoperative CSF leakage after TSS for PA was 5.6%. Tumor size, adenoma consistency, revision surgery, and intraoperative CSF leakage were independent risk factors for postoperative CSF leakage (ORs, 3.18-6.33). By contrast, the endoscopic approach showed a slight protective benefit compared with the microscopic approach in TSS (OR, 0.69). CONCLUSIONS: This review provides a comprehensive overview of the quality of the evidence base, informing clinical staff of the importance of screening risk factors for postoperative CSF leakage after TSS for PA. More attention should be paid to PA patients at high risk for CSF leakage after TSS to reduce complications and improve prognosis.

H3K18ac Primes Mesendodermal Differentiation upon Nodal Signaling.

Cellular responses to transforming growth factor ß (TGF-ß) depend on cell context. Here, we explored how TGF-ß/nodal signaling crosstalks with the epigenome to promote mesendodermal differentiation. We find that expression of a group of mesendodermal genes depends on both TRIM33 and nodal signaling in embryoid bodies (EBs) but not in embryonic stem cells (ESCs). Only in EBs, TRIM33 binds these genes in the presence of expanded H3K18ac marks. Furthermore, the H3K18ac landscape at mesendodermal genes promotes TRIM33 recruitment. We reveal that HDAC1 binds to active gene promoters and interferes with TRIM33 recruitment to mesendodermal gene promoters. However, the TRIM33-interacting protein p300 deposits H3K18ac and further enhances TRIM33 recruitment. ATAC-seq data demonstrate that TRIM33 primes mesendodermal genes for activation by maintaining chromatin accessibility at their regulatory regions. Altogether, our study suggests that HDAC1 and p300 are key factors linking the epigenome through TRIM33 to the cell context-dependent nodal response during mesendodermal differentiation.

Retraction Note to: Ultrasound Elastography supplement assessing nodal status of magnetic resonance imaging staged cervical N0 patients with nasopharyngeal carcinoma.

The Editors have retracted this article [1] because figure 2 has been substantially duplicated from a previously published article by Chen B et al., 2018 [2]. There is also significant and uncited overlap in the patient population between the two articles resulting in concerns relating to the scientific validity and novelty of the data.

Ultrasound Elastography supplement assessing nodal status of magnetic resonance imaging staged cervical N0 patients with nasopharyngeal carcinoma.

BACKGROUND: To determine whether ultrasound elastography can distinguish reactive or metastatic small lymph nodes (sLN) of magnetic resonance imaging (MRI) staged cervical N0 patients with nasopharyngeal carcinoma (NPC). METHODS: A pilot study was performed involving the diagnostic performances of conventional high-frequency ultrasound (CHFU) and/or shear wave elastography (SWE) for predicting metastases in sLN of MRI-staged N0 NPC patients with reference to the histologically-proven ultrasound guided core needle biopsy (US-CNB). The diagnosis of CHFU was based on the superficial lymph node ultrasonic criteria with the five-point-scale (FPS). The mean (Emean), minimum (Emin) and maximum (Emax) of the elasticity indices were measured by SWE at the stiffest part of the sLN in kilopascal. Diagnostic performances were analyzed using a receiver operating curve (ROC) on a per-node basis. The authenticity of this article has been validated by uploading the key raw data onto the Research Data Deposit public platform ( http://www.researchdata.org.cn ), with the approval RDD number as RDDA2017000447. RESULTS: All 113 cervical sLN of 49 MRI-staged cervical N0 NPC patients underwent evaluation of CHFU and SWE; 38 sLN (FPS < 2) were regarded as benign, which were excluded from subsequent analysis due to none biopsy-proven. And 75 indeterminate sLN (FPS ≥ 2) were referred to US-CNB and revealed 15 (20%) metastases. All SWE elastic indices were significantly higher in malignant sLNs than in benign sLNs (p < 0.05). Moreover, Emax exhibited the highest diagnostic value (AUC:0.733 ± 0.067, p = 0.005) with excellent measurement reproducibility (ICC: 0.786; 95%CI: 0.684, 0.864). CHFU plus SWE was superior to CHFU or SWE alone for predicting metastases in sLN of MRI-staged N0 patients with NPC (p < 0.001). CONCLUSIONS: CHFU plus SWE is an optional non-invasive modality to supplement MRI in assessing cervical nodal status of patients with NPC.

A Continuous Random Walk Model With Explicit Coherence Regularization for Image Segmentation.

Random walk is a popular and efficient algorithm for image segmentation, especially for extracting regions of interest (ROIs). One difficulty with the random walk algorithm is the requirement for solving a huge sparse linear system when applied to large images. Another limitation is its sensitivity to seeds distribution, i.e., the segmentation result depends on the number of seeds as well as their placement, which puts a burden on users. In this paper, we first propose a continuous random walk model with explicit coherence regularization (CRWCR) for the extracted ROI, which helps to reduce the seeds sensitivity, so as to reduce the user interactions. Then, a very efficient algorithm to solve the CRWCR model will be developed, which helps to remove the difficulty of solving huge linear systems. Our algorithm consists of two stages: initialization by performing one-dimensional random walk sweeping based on user-provided seeds, followed by the alternating direction scheme, i.e., Peaceman-Rachford scheme for further correction. The first stage aims to provide a good initial guess for the ROI, and it is very fast since we just solve a limited number of one-dimensional random walk problems. Then, this initial guess is evolved to the ideal solution by applying the second stage, which should also be very efficient since it fits well for GPU computing, and 10 iterations are usually sufficient for convergence. Numerical experiments are provided to validate the proposed model as well as the efficiency of the two-stage algorithm.

Role of TRIM33 in Wnt signaling during mesendoderm differentiation.

Tripartite motif 33 (TRIM33), a member of the transcription intermediate factor 1 (TIF1) family of transcription cofactors, mediates transforming growth factor-beta (TGF-ß) signaling through its PHD-Bromo cassette in mesendoderm differentiation during early mouse embryonic development. However, the role of the TRIM33 RING domain in embryonic differentiation is less clear. Here, we report that TRIM33 mediates Wnt signaling by directly regulating the expression of a specific subset of Wnt target genes, and this action is independent of its RING domain. We show that TRIM33 interacts with ß-catenin, a central player in Wnt signaling in mouse embryonic stem cells (mESCs). In contrast to previous reports in cancer cell lines, the RING domain does not appear to function as the E3 ligase for ß-catenin, since neither knockout nor overexpression of TRIM33 had an effect on ß-catenin protein levels in mESCs. Furthermore, we show that although TRIM33 seems to be dispensable for Wnt signaling through a reporter assay, loss of TRIM33 significantly impairs the expression of a subset of Wnt target genes, including Mixl1, in a Wnt signaling-dependent manner. Together, our results indicate that TRIM33 regulates Wnt signaling independent of the E3 ligase activity of its RING domain for ß-catenin in mESCs.

A novel VHLα isoform inhibits Warburg effect via modulation of PKM splicing.

Von Hippel-Lindau (VHL) is the most frequently mutated gene in clear cell renal carcinoma. Here, we identified a novel translational variant of VHL, termed VHLα, initiated from an alternative translational start site upstream and in frame with the ATG start codon. We showed that VHLα interacts with and regulates heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1), which consequently modulates pyruvate kinase transcript splicing and reprograms cellular glucose metabolism. Our study demonstrated that a novel VHL isoform may function as a tumor suppressor through inhibiting the Warburg effect.

Flavokawain A inhibits Cytochrome P450 in in vitro metabolic and inhibitory investigations.

ETHNOPHARMACOLOGICAL RELEVANCE: Flavokawain A, the major chalcone in kava extracts, was served as beverages for informal social occasions and traditional ceremonials in most South Pacific islands. It exhibited strong antiproliferative and apoptotic effects against human prostate and urinary bladder cancer cells. AIM OF THE STUDY: The current study was purposed to investigate the interaction between Flavokawain A and Cytochrome P450, including the inhibitory effects of Flavokawain A on predominant CYP450 isotypes and further clarified the inhibitory mechanism of FKA on CYP450 enzymes. Besides, study about identifying the key CYP450 isotypes responsible for the metabolism of FKA was also performed. MATERIALS AND METHODS: In this study, probe-based assays with rat liver microsome system were used to characterize the inhibitory effects of FKA. Molecular docking study was performed to further explore the binding site of FKA on CYP450 isoforms. In addition, chemical inhibition experiments using specific inhibitors (a-naphthoflavone, quinidine, sulfamethoxazde, ketoconazole, omeprazole) were performed to clarify the individual CYP450 isoform that are responsible for the metabolism of FKA. RESULTS: FKA showed significant inhibition on CYP1A2, CYP2D1, CYP2C6 and CYP3A2 activities with IC50 values of 102.23, 20.39, 69.95, 60.22µmol/L, respectively. The inhibition model was competitive, mixed-inhibition, uncompetitive, and noncompetitive for CYP1A2, CYP2D1, CYP2C6 and CYP3A2 enzymes. Molecular docking study indicated the ligand-binding conformation of FKA in the active site of CYP450 isoforms. The chemical inhibition experiments showed that the metabolic clearance rate of Flavokawain A decreased to 19.84%, 50.38%, and 67.02% of the control in the presence of ketoconazole, sulfamethoxazde and a-naphthoflavone. CONCLUSION: The study showed that Flavokawain A has varying inhibitory effect on CYP450 enzymes and CYP3A2 was the principal CYP isoform contributing to the metabolism of Flavokawain A. Besides, CYP2C6 and CYP1A2 isoforms also play important roles in the metabolism of FKA. Our results provided a basis for better understanding the biotransformation of FKA and prediction of drug-drug interaction of FKA.

The VHL short variant involves in protein quality control.

The von Hippel-Lindau (VHL) is the most important and frequently mutated gene in human clear cell renal cell carcinoma (ccRCC). In contrast to its long counterpart, the internal translational variant of VHL protein (VHLs) is evolutionarily conserved. Herein we present evidence that VHLs associates with ribosome complex via interaction with the large subunit 6 (RPL6). Manipulation of VHLs expression significantly alters protein synthesis, cell size and mitochondrial mass. VHLs deficiency leads to remarkable sensitivity to drug treatments eliciting nascent protein mis-folding and translational errors. The ubiquitination of nascent peptides are dramatically increased upon the ectopic over-expression of VHLs, which simultaneously co-localizes with proteasome and thus may facilitate the ubiquitin-proteasome mediated degradation. In summary, VHLs contributes to protein quality control in addition to its canonical function in maintaining homeostasis of hypoxia-induced factors alpha subunit (HIFα) in response to environmental oxygen supply.