Molecular Regulation of Porcine Skeletal Muscle Development: Insights from Research on CDC23 Expression and Function.

Cell division cycle 23 (CDC23) is a component of the tetratricopeptide repeat (TPR) subunit in the anaphase-promoting complex or cyclosome (APC/C) complex, which participates in the regulation of mitosis in eukaryotes. However, the regulatory model and mechanism by which the CDC23 gene regulates muscle production in pigs are largely unknown. In this study, we investigated the expression of CDC23 in pigs, and the results indicated that CDC23 is widely expressed in various tissues and organs. In vitro cell experiments have demonstrated that CDC23 promotes the proliferation of myoblasts, as well as significantly positively regulating the differentiation of skeletal muscle satellite cells. In addition, Gene Set Enrichment Analysis (GSEA) revealed a significant downregulation of the cell cycle pathway during the differentiation process of skeletal muscle satellite cells. The protein-protein interaction (PPI) network showed a high degree of interaction between genes related to the cell cycle pathway and CDC23. Subsequently, in differentiated myocytes induced after overexpression of CDC23, the level of CDC23 exhibited a significant negative correlation with the expression of key factors in the cell cycle pathway, suggesting that CDC23 may be involved in the inhibition of the cell cycle signaling pathway in order to promote the differentiation process. In summary, we preliminarily determined the function of CDC23 with the aim of providing new insights into molecular regulation during porcine skeletal muscle development.

Application of deep learning in isolated tooth identification.

BACKGROUND: Teeth identification has a pivotal role in the dental curriculum and provides one of the important foundations of clinical practice. Accurately identifying teeth is a vital aspect of dental education and clinical practice, but can be challenging due to the anatomical similarities between categories. In this study, we aim to explore the possibility of using a deep learning model to classify isolated tooth by a set of photographs. METHODS: A collection of 5,100 photographs from 850 isolated human tooth specimens were assembled to serve as the dataset for this study. Each tooth was carefully labeled during the data collection phase through direct observation. We developed a deep learning model that incorporates the state-of-the-art feature extractor and attention mechanism to classify each tooth based on a set of 6 photographs captured from multiple angles. To increase the validity of model evaluation, a voting-based strategy was applied to refine the test set to generate a more reliable label, and the model was evaluated under different types of classification granularities. RESULTS: This deep learning model achieved top-3 accuracies of over 90% in all classification types, with an average AUC of 0.95. The Cohen's Kappa demonstrated good agreement between model prediction and the test set. CONCLUSIONS: This deep learning model can achieve performance comparable to that of human experts and has the potential to become a valuable tool for dental education and various applications in accurately identifying isolated tooth.

LncRNA TCONS_00323213 Promotes Myogenic Differentiation by Interacting with PKNOX2 to Upregulate MyoG in Porcine Satellite Cells.

Myogenic differentiation is a complex biological process that is regulated by multiple factors, among which long noncoding RNAs (lncRNAs) play an essential role. However, in-depth studies on the regulatory mechanisms of long noncoding RNAs (lncRNAs) in myogenic differentiation are limited. In this study, we characterized the role of the novel lncRNA TCONS_00323213, which is upregulated during porcine skeletal muscle satellite cell (PSC) differentiation in myogenesis. We found that TCONS_00323213 affected the proliferation and differentiation of PSC in vitro. We performed quantitative polymerase chain reaction (qPCR), 5-ethynyl-20-deoxyuridine (EdU), western blotting, immunofluorescence staining, pull-down assays, and cleavage under targets and tagmentation (CUT and Tag) assays to clarify the effects and action mechanisms of TCONS_00323213. LncRNA TCONS_00323213 inhibited myoblast proliferation based on analyses of cell survival rates during PSC proliferation. Functional analyses revealed that TCONS_00323213 promotes cell differentiation and enhances myogenin (MyoG), myosin heavy chain (MyHC), and myocyte enhancer factor 2 (MEF2C) during myoblast differentiation. As determined by pull-down and RNA immunoprecipitation (RIP) assays, the lncRNA TCONS_00323213 interacted with PBX/Knotted Homeobox 2 (PKNOX2). CUT and Tag assays showed that PKNOX2 was significantly enriched on the MyoG promoter after lncRNA TCONS_00323213 knockdown. Our findings demonstrate that the interaction between lncRNA TCONS_00323213 and PKNOX2 relieves the inhibitory effect of PKNOX2 on the MyoG promoter, increases its expression, and promotes PSC differentiation. This novel role of lncRNA TCONS_00323213 sheds light on the molecular mechanisms by which lncRNAs regulate porcine myogenesis.

Instrumental and visual evaluation of the color adjustment potential of a recently introduced single­shade composite resin versus multishade composite resins.

STATEMENT OF PROBLEM: Single-shade composite resins simplify the process of shade selection by providing a narrow range of color but the ability to simulate all shades. However, evidence is limited for the color shifting ability of a newly developed single­shade composite resin. PURPOSE: The purpose of this in vitro study was to evaluate the instrumental color adjustment potential (CAP-I) and visual color adjustment potential (CAP-V) of a recently introduced single-shade composite resin compared with conventional multishade composite resins against different background colors. MATERIAL AND METHODS: Four multishade composite resins (Spectrum TPH3, Beautifil II, Clearfil AP-X, and Gradia Direct) and a single-shade composite resin (Charisma Diamond One) were tested. Four base shades (A1, A2, A3, and A3.5) of the same composite resin (Filtek Z350XT) were selected as different background colors. Dual specimens (an outer base material with an inner hole filled with inner test material) and single specimens of all test and base materials were prepared (n=6 per group). Spectral reflectance values were obtained by using a spectroradiometer. The color difference (ΔE00) and relative translucency parameter (RTP) were calculated by using the CIEDE2000 and RTPCIEDE2000 formula. Visual scoring of color matching was performed by independent observers. The CAP-I and CAP-V values were calculated according to ΔE00 and visual scoring. Analysis of variance (ANOVA) was used for statistical analysis (α=.05). RESULTS: CAP-I and CAP-V were significantly affected by composite resin type, background color, and their interaction (P<.001). Positive CAP-I and CAP-V values were found for the majority of test materials. Charisma Diamond One exhibited the highest CAP-I value under all background colors, the highest CAP-V value under most background colors, and the significantly highest RTP value (P<.001). CONCLUSIONS: The color adjustment potential was dependent on the material type and background color. Charisma Diamond One exhibited the highest color adjustment potential and the most pronounced color shifting ability.

Design of integrated searching and tracking optical systems based on freeform mirrors.

Target searching and tracking photoelectric systems are widely used in civil and military fields. Achieving both efficient search and fine-observation imaging while minimizing the volume and weight of the system is the most concerning problem. In this paper, a dual-mode integrated optical system is proposed, which shares large size components between large field of view (FOV) search module and high-resolution tracking module by using the Biconic Zernike freeform mirrors. Compared with the traditional searching and tracking system utilizing multi-camera matching, this scheme significantly reduces the volume and weight of the remote sensing payload. At the orbit altitude of 500 km, this proposed system has a swath of 87.5 km with a ground resolution of 10 m in search mode. In tracking mode, it can observe an area of 19 km2 with a ground resolution of 1 m. It can meet the requirements of wide-area search and focus tracking simultaneously, providing a feasible scheme for the lightweight design of space optical cameras.

Identification of differentially expressed miRNAs in serum extracellular vesicles (EVs) of Kazakh sheep at early pregnancy.

MiRNAs-containing extracellular vesicles (EVs) possess the unique function of mediating intercellular communication and participating in many biological processes such as post-transcriptional gene regulation of embryo implantation and placental development. In the present study, Illumina small-RNA sequencing was used to identify differentially expressed (DE) miRNAs in serum EVs of pregnant (P) and non-pregnant (NP) Kazakh sheep at Day 17 from mating. The specifically and differentially expressed miRNAs at early pregnancy in sheep were verified by using RT-PCR. The target genes of DE miRNAs were predicted by bioinformatics software, and the functional and pathway enrichment analysis was performed on Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. A total of 562 miRNAs (210 novel miRNAs) were identified by sequencing, of which 57 miRNAs were differentially expressed, 49 were up-regulated, 8 were down-regulated and 22 novel miRNAs were specifically expressed in the pregnant sheep. Eight highly expressed known miRNA (miR-378-3p, miR-320-3p, miR-22-3p, let-7b, miR-423-3p, miR-221, miR-296-3p, miR-147-3p) in pregnant group were down-regulated in the control group. miRNAs-containing pregnancy-related terms and regulatory pathways regulation were enriched using both GO and KEGG analyses. Moreover, we also envisioned a miRNA-mRNA interaction network to understand the function of miRNAs involved in the early pregnancy serum regulatory network. The results of RT-PCR verification confirmed the reliability of small-RNA sequencing. Among them, miR-22-3p and miR-378-3p were significantly differentially expressed (DE) between pregnant sheep and non-pregnant group (p <  0.01). The site at which oar-miR-22-3p binds MAPK3 was determined with a dual-luciferase system. This is the first integrated analysis of the expression profiles of EV-miRNAs and their targets during early pregnancy in ewes. These data identify key miRNAs that influence the implantation of sheep in the early stage of pregnancy, and provide theoretical basis for further molecular regulatory mechanisms research.

Transcriptome Analysis Reveals Long Intergenic Non-Coding RNAs Contributed to Intramuscular Fat Content Differences between Yorkshire and Wei Pigs.

Intramuscular fat (IMF) content is closely related to various meat traits, such as tenderness, juiciness, and flavor. The IMF content varies considerably among pig breeds with different genetic backgrounds. Long intergenic non-coding RNAs (lincRNAs) have been widely identified in many species and found to be an important class of regulators that can participate in multiple biological processes. However, the mechanism behind lincRNAs regulation of pig IMF content remains unknown and requires further study. In our study, we identified a total of 156 lincRNAs in the longissimus dorsi muscle of Wei (fat-type) and Yorkshire (lean-type) pigs using previously published data. These identified lincRNAs have shorter transcript length, longer exon length, lower exon number, and lower expression level as compared with protein-coding transcripts. We predicted potential target genes (PTGs) that are potentially regulated by lincRNAs in cis or trans regulation. Gene ontology and pathway analyses indicated that many potential lincRNAs target genes are involved in IMF-related processes or pathways, such as fatty acid catabolic process and adipocytokine signaling pathway. In addition, we analyzed quantitative trait locus (QTL) sites that differentially expressed lincRNAs (DE lincRNAs) between Wei and Yorkshire pigs co-localized. The QTL sites where DE lincRNAs co-localize are mostly related to IMF content. Furthermore, we constructed a co-expressed network between DE lincRNAs and their differentially expressed PTGs (DEPTGs). On the basis of their expression levels, we suggest that many DE lincRNAs can affect IMF development by positively or negatively regulating their PTGs. This study identified and analyzed some lincRNAs- and PTGs-related IMF development of the two pig breeds and provided new insight into research on the roles of lincRNAs in the two types of breeds.

Systematic Analysis of Long Non-Coding RNAs and mRNAs in the Ovaries of Duroc Pigs During Different Follicular Stages Using RNA Sequencing.

The dynamic process involving the selection and maturation of follicles is regulated and controlled by a highly synchronized and exquisitely timed cascade of gene expression. Studies have shown that long non-coding RNA (lncRNA) is essential for the normal maintenance of animal reproductive function and has an important regulatory function in ovarian development and hormone secretion. In this study, a total of 2076 lncRNAs (1362 known lncRNAs and 714 new lncRNAs) and 25,491 mRNAs were identified in libraries constructed from Duroc ovaries on days 0, 2 and 4 of follicle development. lncRNAs were shorter, had fewer exons, exhibited a shorter ORF (Open Reading Frame) length and lower expression levels, and were less conserved than mRNAs. Furthermore, 1694 transcripts (140 lncRNAs and 1554 mRNAs) were found to be differentially expressed in pairwise comparisons. A total of 6945 co-localized mRNAs were detected in cis in 2076 lncRNAs. The most enriched GO (Gene Ontology) terms were related to developmental processes. KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis revealed that the differentially expressed lncRNAs targeted mRNAs, and the differentially expressed mRNAs were related to the TGF-ß signaling pathway, the PI3K-Akt signaling pathway, the Retinol metabolic pathway and the Wnt signaling pathway. This study deepened our understanding of the genetic basis and molecular mechanisms of follicular development in pigs.

Characterizing structural variants based on graph-genotyping provides insights into pig domestication and local adaption.

Structural variants (SVs), such as deletions (DELs) and insertions (INSs), contribute substantially to pig genetic diversity and phenotypic variation. Using a library of SVs discovered from long-read primary assemblies and short-read sequenced genomes, we map pig genomic SVs with a graph-based method for re-genotyping SVs in 402 genomes. Our results demonstrate that those SVs harboring specific trait-associated genes may greatly shape pig domestication and local adaptation. Further characterization of SVs reveals that some population-stratified SVs may alter the transcription of genes by affecting regulatory elements. We identify that the genotypes of two DELs (296-bp DEL, chr7: 52,172,101-52,172,397; 278-bp DEL, chr18: 23,840,143-23,840,421) located in muscle-specific enhancers are associated with the expression of target genes related to meat quality (FSD2) and muscle fiber hypertrophy (LMOD2 and WASL) in pigs. Our results highlight the role of SVs in domestic porcine evolution, and the identified candidate functional genes and SVs are valuable resources for future genomic research and breeding programs in pigs.

MYOD induced lnc-MEG3 promotes porcine satellite cell differentiation via interacting with DLST.

Long non-coding RNAs (lncRNAs) are involved in the process of muscle cell differentiation and play an important role. Previous studies have shown that lncRNA-MEG3 promotes the differentiation of porcine skeletal muscle satellite cells (PSCs), but the regulatory mechanism of MEG3 interaction with target protein has not been well studied. We demonstrated that MEG3 can bind dihydrolipoamide succinyltransferase (DLST) by RNA pull down and RIP-qPCR. Subsequently, knockdown and overexpression experiments showed that DLST promotes PSCs differentiation. Rescue experiments showed that the expression of DLST protein was significantly increased with MEG3 overexpression and decreased with MEG3 knockdown, while its mRNA expression was not changed. Furthermore, we have successfully predicted and validated that the transcription factor myogenic differentiation (MYOD) binds to the MEG3 core promoter though utilizing chromatin immunoprecipitation (CHIP) and luciferase reporter assays. The results indicated that MYOD acts as a transcription factor of MEG3 to promote MEG3 transcription. Knockdown of MEG3 in vivo indicated that MEG3 is involved in skeletal muscle regeneration. It is concluded that MYOD acts as a transcription factor to induce MEG3 expression. MEG3 acts as a molecular scaffold to bind and promote DLST protein expression. This paper provides a new molecular mechanism for MEG3 to promote the differentiation of PSCs.

Temporomandibular joint segmentation in MRI images using deep learning.

OBJECTIVES: Temporomandibular joint (TMJ) internal derangements (ID) represent the most prevalent temporomandibular joint disorder (TMD) in the population and its diagnosis typically relies on magnetic resonance imaging (MRI). TMJ articular discs in MRIs usually suffer from low resolution and contrast, and it is difficult to identify them. In this study, we applied two convolutional neural networks (CNN) to delineate mandibular condyle, articular eminence, and TMJ disc in MRI images. METHODS: The models were trained on MRI images from 100 patients and validated on images from 40 patients using 2D slices and 3D volume as input, respectively. Data augmentation and five-fold cross-validation scheme were applied to further regularize the models. The accuracy of the models was then compared with four raters having different expertise in reading TMJ-MRI images to evaluate the performance of the models. RESULTS: Both models performed well in segmenting the three anatomical structures. A Dice coefficient of about 0.7 for the articular disc, more than 0.9 for the mandibular condyle, and Hausdorff distance of about 2mm for the articular eminence were achieved in both models. The models reached near-expert performance for the segmentation of TMJ articular disc and performed close to the expert in the segmentation of mandibular condyle and articular eminence. They also surpassed non-experts in segmenting the three anatomical structures. CONCLUSION: This study demonstrated that CNN-based segmentation models can be a reliable tool to assist clinicians identifying key anatomy on TMJ-MRIs. The approach also paves the way for automatic diagnosis of TMD. CLINICAL SIGNIFICANCE: Accurately locating the articular disc is the hardest and most crucial step in the interpretation of TMJ-MRIs and consequently in the diagnosis of TMJ-ID. Automated software that assists in locating the articular disc and its surrounding structures would improve the reliability of TMJ-MRI interpretation, save time and assist in reader training. It will also serve as a foundation for additional automated analysis of pathology in TMJ structures to aid in TMD diagnosis.

Transcriptome analysis reveals the long intergenic noncoding RNAs contributed to skeletal muscle differences between Yorkshire and Tibetan pig.

The difference between the skeletal muscle growth rates of Western and domestic breeds is remarkable, but the potential regulatory mechanism involved is still unclear. Numerous studies have pointed out that long intergenic noncoding RNA (lincRNA) plays a key role in skeletal muscle development. This study used published Yorkshire (LW) and Tibetan pig (TP) transcriptome data to explore the possible role of lincRNA in the difference in skeletal muscle development between the two breeds. 138 differentially expressed lincRNAs (DELs) were obtained between the two breeds, and their potential target genes (PTGs) were predicted. The results of GO and KEGG analysis revealed that PTGs are involved in multiple biological processes and pathways related to muscle development. The quantitative trait loci (QTLs) of DELs were predicted, and the results showed that most QTLs are related to muscle development. Finally, we constructed a co-expression network between muscle development related PTGs (MDRPTGs) and their corresponding DELs on the basis of their expression levels. The expression of DELs was significantly correlated with the corresponding MDRPTGs. Also, multiple MDRPTGs are involved in the key regulatory pathway of muscle fiber hypertrophy, which is the IGF-1-AKT-mTOR pathway. In summary, multiple lincRNAs that may cause differences in skeletal muscle development between the two breeds were identified, and their possible regulatory roles were explored. The findings of this study may provide a valuable reference for further research on the role of lincRNA in skeletal muscle development.

Transcriptome Analysis of In Vitro Fertilization and Parthenogenesis Activation during Early Embryonic Development in Pigs.

Parthenogenesis activation (PA), as an important artificial breeding method, can stably preserve the dominant genotype of a species. However, the delayed development of PA embryos is still overly severe and largely leads to pre-implantation failure in pigs. The mechanisms underlying the deficiencies of PA embryos have not been completely understood. For further understanding of the molecular mechanism behind PA embryo failure, we performed transcriptome analysis among pig oocytes (meiosis II, MII) and early embryos at three developmental stages (zygote, morula, and blastocyst) in vitro fertilization (IVF) and PA group. Totally, 11,110 differentially expressed genes (DEGs), 4694 differentially expressed lincRNAs (DELs) were identified, and most DEGs enriched the regulation of apoptotic processes. Through cis- and trans-manner functional prediction, we found that hub lincRNAs were mostly involved in abnormal parthenogenesis embryonic development. In addition, twenty DE imprinted genes showed that some paternally imprinted genes in IVF displayed higher expression than that in PA. Notably, we identified that three DELs of imprinted genes (MEST, PLAGL1, and DIRAS3) were up regulated in IVF, and there was no significant change in PA group. Disordered expression of key genes for embryonic development might play key roles in abnormal parthenogenesis embryonic development. Our study indicates that embryos derived from different production techniques have varied in vitro development to the blastocyst stage, and they also affect the transcription level of corresponding genes, such as imprinted genes. This work will help future research on these genes and molecular-assisted breeding for pig parthenotes.

Analysis of long intergenic non-coding RNAs transcriptomic profiling in skeletal muscle growth during porcine embryonic development.

Skeletal muscle growth plays a critical role during porcine muscle development stages. Genome-wide transcriptome analysis reveals that long intergenic non-coding RNAs (lincRNAs) are implicated as crucial regulator involving in epigenetic regulation. However, comprehensive analysis of lincRNAs in embryonic muscle development stages remain still elusive. Here, we investigated the transcriptome profiles of Duroc embryonic muscle tissues from days 33, 65, and 90 of gestation using RNA-seq, and 228 putative lincRNAs were identified. Moreover, these lincRNAs exhibit the characteristics of shorter transcripts length, longer exons, less exon numbers and lower expression level compared with protein-coding transcripts. Expression profile analysis showed that a total of 120 lincRNAs and 2638 mRNAs were differentially expressed. In addition, we also performed quantitative trait locus (QTL) mapping analysis for differentially expressed lincRNAs (DE lincRNAs), 113 of 120 DE lincRNAs were localized on 2200 QTLs, we observed many QTLs involved in growth and meat quality traits. Furthermore, we predicted potential target genes of DE lincRNAs in cis or trans regulation. Gene ontology and pathway analysis reveals that potential targets of DE lincRNAs mostly were enriched in the processes and pathways related to tissue development, MAPK signaling pathway, Wnt signaling pathway, TGF-beta signaling pathway and insulin signaling pathway, which involved in skeletal muscle physiological functions. Based on cluster analysis, co-expression network analysis of DE lincRNAs and their potential target genes indicated that DE lincRNAs highly regulated protein-coding genes associated with skeletal muscle development. In this study, many of the DE lincRNAs may play essential roles in pig muscle growth and muscle mass. Our study provides crucial information for further exploring the molecular mechanisms of lincRNAs during skeletal muscle development.

Transcriptome analysis reveals that long noncoding RNAs contribute to developmental differences between medium-sized ovarian follicles of Meishan and Duroc sows.

Ovulation rate is an extremely important factor affecting litter size in sows. It differs greatly among pig breeds with different genetic backgrounds. Long non-coding RNAs (lncRNAs) can regulate follicle development, granulosa cell growth, and hormone secretion, which in turn can affect sow litter size. In this study, we identified 3554 lncRNAs and 25,491 mRNAs in M2 follicles of Meishan and Duroc sows. The lncRNA sequence and open reading frame lengths were shorter than mRNAs, and lncRNAs had fewer exons, were less abundant, and more conserved than protein-coding RNAs. Furthermore, 201 lncRNAs were differentially expressed (DE) between breeds, and quantitative trait loci analysis of DE lncRNAs were performed. A total of 127 DE lncRNAs were identified in 119 reproduction trait-related loci. In addition, the potential target genes of lncRNAs in cis or trans configurations were predicted. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that some potential target genes were involved in follicular development and hormone secretion-related biological processes or pathways, such as progesterone biosynthetic process, estrogen metabolic process, ovarian steroidogenesis, and PI3K-Akt signaling pathway. Furthermore, we also screened 19 differentially expressed lncRNAs in the PI3K-Akt signaling pathway as candidates. This study provides new insights into the roles of lncRNAs in follicular growth and development in pigs.

Localization of cementoenamel junction in intraoral ultrasonographs with machine learning.

OBJECTIVE: Our goal was to automatically identify the cementoenamel junction (CEJ) location in ultrasound images using deep convolution neural networks (CNNs). METHODS: Three CNNs were evaluated using 1400 images and data augmentation. The training and validation were performed by an experienced nonclinical rater with 1000 and 200 images, respectively. Four clinical raters with different levels of experience with ultrasound tested the networks using the other 200 images. In addition to the comparison of the best approach with each rater, we also employed the simultaneous truth and performance level estimation (STAPLE) algorithm to estimate a ground truth based on all labelings by four clinical raters. The final CEJ location estimate was obtained by taking the first moment of the posterior probability computed using the STAPLE algorithm. The study also computed the machine learning-measured CEJ-alveolar bone crest distance. RESULTS: Quantitative evaluations of the 200 images showed that the comparison of the best approach with the STAPLE-estimate yielded a mean difference (MD) of 0.26 mm, which is close to the comparison with the most experienced nonclinical rater (MD=0.25 mm) but far better than the comparison with clinical raters (MD=0.27-0.33 mm). The machine learning-measured CEJ-alveolar bone crest distances correlated strongly (R = 0.933, p < 0.001) with the manual clinical labeling and the measurements were in good agreement with the 95% Bland-Altman's lines of agreement between -0.68 and 0.57 mm. CONCLUSIONS: The study demonstrated the feasible use of machine learning methodology to localize CEJ in ultrasound images with clinically acceptable accuracy and reliability. Likelihood-weighted ground truth by combining multiple labels by the clinical experts compared favorably with the predictions by the best deep CNN approach. CLINICAL SIGNIFICANCE: Identification of CEJ and its distance from the alveolar bone crest play an important role in the evaluation of periodontal status. Machine learning algorithms can learn from complex features in ultrasound images and have potential to provide a reliable and accurate identification in subsecond. This will greatly assist dental practitioners to provide better point-of-care to patients and enhance the throughput of dental care.

Three-dimensional periodontal investigations using a prototype handheld ultrasound scanner with spatial positioning reading sensor.

AIM: To demonstrate the feasibility of the 3D ultrasound periodontal tissue reconstruction of the lateral area of a porcine mandible using standard 2D ultrasound equipment and spatial positioning reading sensors. MATERIAL AND METHOD: Periodontal 3D reconstructions were performed using a free-hand prototype based on a 2D US scanner and a spatial positioning reading sensor. For automated data processing, deep learning algorithms were implemented and trained using semi-automatically seg-mented images by highly specialized imaging professionals. RESULTS: US probe movement analysis showed that non-parallel 2D frames were acquired during the scanning procedure. Comparing 3 different 3D periodontal reconstructions of the same porcine mandible, the accuracy ranged between 0.179 mm and 0.235 mm. CONCLUSION: The present study demonstrated the diagnostic potential of 3D reconstruction using a free-hand 2D US scanner with spatial positioning readings. The use of auto-mated data processing with deep learning algorithms makes the process practical in the clinical environment for assessment of periodontal soft tissues.

Automated integration of facial and intra-oral images of anterior teeth.

BACKGROUND AND OBJECTIVE: Digital smile design is the technique that dentists use to analyze, design, and visualize therapeutic results on a computing workstation prior to actual treatment. Despite it being a crucial step in digital smile design, the process of labeling and integrating the information in facial and intra-oral images is laborious. Therefore, this study aims to develop an automated photo integrating system to facilitate this process. METHODS: The teeth in intra-oral images were distinguished by their curvature and finely segmented using an active contour model. The facial keypoints were detected by a sophisticated facial landmark detector algorithm; these keypoints were then overlaid on the corresponding intra-oral image by extracting the contour of the teeth in the facial and intra-oral photographs. With this system, the tooth width-to-height ratios, smile line, and facial midline were automatically marked in the intra-oral image. The accuracy of the proposed segmentation algorithm was evaluated by applying it to 50 images with 274 maxillary anterior teeth. RESULTS: The proposed algorithm recognized 96.0% (263/274) of teeth in our selected image set. The results were then compared to those obtained by applying manual segmentation to the remaining 263 recognized teeth. With a 95% confidence interval, a Jaccard index of 0.928 ± 0.081, average distance of 0.128 ± 0.109 mm, and Hausdorff distance between the results and ground truth of 0.461 ± 0.495 mm were achieved. CONCLUSIONS: The results of this study show that the proposed automated system can eliminate the need for dentists to employ a laborious image integration process. It also has the potential for broad applicability in the field of dentistry.

MEG3 Promotes Differentiation of Porcine Satellite Cells by Sponging miR-423-5p to Relieve Inhibiting Effect on SRF.

Although thousands of long noncoding RNAs (lncRNAs) have been identified in porcine growth and development, the regulation mechanisms of functional lncRNAs have not been well explored. In this study, using 5'- and 3'-rapid amplification of cDNA ends (RACE) assays, we obtained two different variants of lncRNA maternally expressed gene 3 (MEG3), namely, MEG3 v1 and MEG3 v2, that were both highly expressed in porcine skeletal muscle and in the early stage of the differentiation of porcine satellite cells. Moreover, we identified the core transcript MEG3 v2. Functional analyses showed that MEG3 overexpression could effectively arrest myoblasts in the G1 phase, inhibit DNA replication, and promote myoblast differentiation, whereas MEG3 knockdown resulted in the opposite effects. Interestingly, the expression of serum response factor (SRF), a crucial transcription factor for myogenesis process, remarkably increased and decreased in mRNA and protein levels with the respective overexpression and knockdown of MEG3. Dual luciferase reporter assay showed that MEG3 could attenuate the decrease of luciferase activity of SRF induced by miR-423-5p in a dose-dependent manner. MEG3 overexpression could relieve the inhibitory effect on SRF and myoblast differentiation induced by miR-423-5p. In addition, results of RNA immunoprecipitation analysis suggested that MEG3 could act as a ceRNA for miR-423-5p. Our findings initially established a novel connection among MEG3, miR-423-5p, and SRF in porcine satellite cell differentiation. This novel role of MEG3 may shed new light on understanding of molecular regulation of lncRNA in porcine myogenesis.

Identification of circular RNAs in the ovarian follicles of Meishan and Duroc sows during the follicular phase.

Circular RNAs (circRNAs) are a newly discovered class of endogenous non-coding RNAs that play an important role in growth and development by regulating gene expression and participating in a variety of biological processes. However, the role of circRNAs in porcine follicles remains unclear. Therefore, this study examined middle-sized ovarian follicles obtained from Meishan and Duroc sows at day 4 of the follicular phase. High-throughput RNA sequencing (RNA-seq) was utilized to construct circRNAs, and differential expression was identified. The findings were validated using reverse transcription PCR (RT-PCR) and DNA sequencing, GO and KEGG analyses were performed, and potential miRNA targets were identified. The RNA-seq identified a total of 15,866 circRNAs, with 244 differentially expressed in the Meishan relative to the Duroc (111 up-regulated and 133 down-regulated). The RT-PCR finding confirmed the RNA-seq results, and quantitative real-time PCR (qPCR) analysis examining a subset of the circRNAs showed that they are resistant to RNase R digestion. Bioinformatics analysis (GO and KEGG) showed that the host genes associated with the differentially expressed circRNAs are involved in reproduction and follicular development signaling pathways. Furthermore, many of the circRNAs were found to interact with miRNAs that are associated with follicular development. This study presents a new perspective for studying circRNAs and provides a valuable resource for further examination into the potential roles of circRNAs in porcine follicular development.