Automatic extraction of facial median sagittal plane for patients with asymmetry based on the EDMA alignment algorithm.

BACKGROUND: We aimed to establish a novel method for automatically constructing three-dimensional (3D) median sagittal plane (MSP) for mandibular deviation patients, which can increase the efficiency of aesthetic evaluating treatment progress. We developed a Euclidean weighted Procrustes analysis (EWPA) algorithm for extracting 3D facial MSP based on the Euclidean distance matrix analysis, automatically assigning weight to facial anatomical landmarks. METHODS: Forty patients with mandibular deviation were recruited, and the Procrustes analysis (PA) algorithm based on the original mirror alignment and EWPA algorithm developed in this study were used to construct the MSP of each facial model of the patient as experimental groups 1 and 2, respectively. The expert-defined regional iterative closest point algorithm was used to construct the MSP as the reference group. The angle errors of the two experimental groups were compared to those of the reference group to evaluate their clinical suitability. RESULTS: The angle errors of the MSP constructed by the two EWPA and PA algorithms for the 40 patients were 1.39 ± 0.85°, 1.39 ± 0.78°, and 1.91 ± 0.80°, respectively. The two EWPA algorithms performed best in patients with moderate facial asymmetry, and in patients with severe facial asymmetry, the angle error was below 2°, which was a significant improvement over the PA algorithm. CONCLUSIONS: The clinical application of the EWPA algorithm based on 3D facial morphological analysis for constructing a 3D facial MSP for patients with mandibular deviated facial asymmetry deformity showed a significant improvement over the conventional PA algorithm and achieved the effect of a dental clinical expert-level diagnostic strategy.

Automatic three-dimensional facial symmetry reference plane construction based on facial planar reflective symmetry net.

OBJECTIVES: Three-dimensional (3D) facial symmetry analysis is based on the 3D symmetry reference plane (SRP). Artificial intelligence (AI) is widely used in the dental and oral sciences. This study developed a novel deep learning model called the facial planar reflective symmetry net (FPRS-Net) to automatically construct an SRP and established a method for defining a 3D point-cloud region of interest (ROI) and high-dimensional feature computations suitable for this network model. METHODS: Overall, 240 patients were enroled. The deep learning model was trained and predicted using 200 samples, and its clinical suitability was evaluated with 40 samples. Four FPRS-Net models were prepared, each using supervised and unsupervised learning approaches based on full facial and ROI data (FPRS-NetS, FPRS-NetSR, FPRS-NetU, and FPRS-NetUR). These models were trained on 160 3D facial datasets, validated on 20 cases, and tested on another 20 cases. The model predictions were evaluated using an additional 40 clinical 3D facial datasets by comparing the mean square error of the SRP between the parameters predicted by the four FPRS-Net models and the truth plane. The clinical suitability of FPRS-Net models was evaluated by measuring the angle error between the predicted and ground-truth planes; experts evaluated the predicted SRP of the four FPRS-Net models using the visual analogue scales (VAS) method. RESULTS: The FPRS-NetSR and FPRS-NetU models achieved an average angle error of 0.84° and 0.99° in predicting 3D facial SRP, respectively, with a VAS value of >8. Using the four FPRS-Net models to create an SRP in 40 cases of 3D facial data required <4 s. CONCLUSIONS: Our study demonstrated a new solution for automatically constructing oral clinical 3D facial SRPs. CLINICAL SIGNIFICANCE: This study proposes a novel deep learning algorithm (FPRS-Net) to construct a symmetry reference plane that can reduce workload, shorten the time required for digital design, reduce dependence on expert experience, and improve therapeutic efficiency and effectiveness in dental clinics.

Cannabidiol Inhibits Epithelial Ovarian Cancer: Role of Gut Microbiome.

Epithelial ovarian cancer is among the deadliest gynecological tumors worldwide. Clinical treatment usually consists of surgery and adjuvant chemo- and radiotherapies. Due to the high rate of recurrence and rapid development of drug resistance, the current focus of research is on finding effective natural products with minimal toxic side effects for treating epithelial ovarian tumors. Cannabidiol is among the most abundant cannabinoids and has a non-psychoactive effect compared to tetrahydrocannabinol, which is a key advantage for clinical application. Studies have shown that cannabidiol has antiproliferative, pro-apoptotic, cytotoxic, antiangiogenic, anti-inflammatory, and immunomodulatory properties. However, its therapeutic value for epithelial ovarian tumors remains unclear. This study aims to investigate the effects of cannabidiol on epithelial ovarian tumors and to elucidate the underlying mechanisms. The results showed that cannabidiol has a significant inhibitory effect on epithelial ovarian tumors. In vivo experiments demonstrated that cannabidiol could inhibit tumor growth by modulating the intestinal microbiome and increasing the abundance of beneficial bacteria. Western blot assays showed that cannabidiol bound to EGFR/AKT/MMPs proteins and suppressed EGFR/AKT/MMPs expression in a dose-dependent manner. Network pharmacology and molecular docking results suggested that cannabidiol could affect the EGFR/AKT/MMPs signaling pathway.

Construction and efficacy testing of DNA vaccines containing HLA-A*02:01-restricted SARS-CoV-2 T-cell epitopes predicted by immunoinformatics.

Vaccines play essential roles in the fight against the COVID-19 pandemic. The development and assessment of COVID-19 vaccines have generally focused on the induction and boosting of neutralizing antibodies targeting the SARS-CoV-2 spike (S) protein. Due to rapid and continuous variation in the S protein, such vaccines need to be regularly updated to match newly emerged dominant variants. T-cell vaccines that target MHC I- or II-restricted epitopes in both structural and non-structural viral proteins have the potential to induce broadly cross-protective and long-lasting responses. In this work, the entire proteome encoded by SARS-CoV-2 (Wuhan-hu-1) is subjected to immunoinformatics-based prediction of HLA-A*02:01-restricted epitopes. The immunogenicity of the predicted epitopes is evaluated using peripheral blood mononuclear cells from convalescent Wuhan-hu-1-infected patients. Furthermore, predicted epitopes that are conserved across major SARS-CoV-2 lineages and variants are used to construct DNA vaccines expressing multi-epitope polypeptides. Most importantly, two DNA vaccine constructs induce epitope-specific CD8 + T-cell responses in a mouse model of HLA-A*02:01 restriction and protect immunized mice from challenge with Wuhan-hu-1 virus after hACE2 transduction. These data provide candidate T-cell epitopes useful for the development of T-cell vaccines against SARS-CoV-2 and demonstrate a strategy for quick T-cell vaccine candidate development applicable to other emerging pathogens.

Spatial Trueness Evaluation of 3D-Printed Dental Model Made of Photopolymer Resin: Use of Special Structurized Dental Model.

(1) Background: Various 3D printers are available for dental practice; however, a comprehensive accuracy evaluation method to effectively guide practitioners is lacking. This in vitro study aimed to propose an optimized method to evaluate the spatial trueness of a 3D-printed dental model made of photopolymer resin based on a special structurized dental model, and provide the preliminary evaluation results of six 3D printers. (2) Methods: A structurized dental model comprising several geometrical configurations was designed based on dental crown and arch measurement data reported in previous studies. Ninety-six feature sizes can be directly measured on this original model with minimized manual measurement errors. Six types of photo-curing 3D printers, including Objet30 Pro using the Polyjet technique, Projet 3510 HD Plus using the Multijet technique, Perfactory DDP and DLP 800d using the DLP technique, Form2 and Form3 using the SLA technique, and each printer's respective 3D-printable dental model materials, were used to fabricate one set of physical models each. Regarding the feature sizes of the simulated dental crowns and dental arches, linear measurements were recorded. The scanned digital models were compared with the design data, and 3D form errors (including overall 3D deviation; flatness, parallelism, and perpendicularity errors) were measured. (3) Results: The lowest overall 3D deviation, flatness, parallelism, and perpendicularity errors were noted for the models printed using the Objet30 Pro (overall value: 45 µm), Form3 (0.061 ± 0.019 mm), Objet30 Pro (0.138 ± 0.068°), and Projet 3510 HD Plus (0.095 ± 0.070°), respectively. In color difference maps, different deformation patterns were observed in the printed models. The feature size proved most accurate for the Objet30 Pro fabricated models (occlusal plane error: 0.02 ± 0.36%, occlusogingival direction error: -0.06 ± 0.09%). (4) Conclusions: The authors investigated a novel evaluation approach for the spatial trueness of a 3D-printed dental model made of photopolymer resin based on a structurized dental model. This method can objectively and comprehensively evaluate the spatial trueness of 3D-printed dental models and has a good repeatability and generalizability.

Rethinking running biomechanics: a critical review of ground reaction forces, tibial bone loading, and the role of wearable sensors.

This study presents a comprehensive review of the correlation between tibial acceleration (TA), ground reaction forces (GRF), and tibial bone loading, emphasizing the critical role of wearable sensor technology in accurately measuring these biomechanical forces in the context of running. This systematic review and meta-analysis searched various electronic databases (PubMed, SPORTDiscus, Scopus, IEEE Xplore, and ScienceDirect) to identify relevant studies. It critically evaluates existing research on GRF and tibial acceleration (TA) as indicators of running-related injuries, revealing mixed findings. Intriguingly, recent empirical data indicate only a marginal link between GRF, TA, and tibial bone stress, thus challenging the conventional understanding in this field. The study also highlights the limitations of current biomechanical models and methodologies, proposing a paradigm shift towards more holistic and integrated approaches. The study underscores wearable sensors' potential, enhanced by machine learning, in transforming the monitoring, prevention, and rehabilitation of running-related injuries.

Chairside digital design and manufacturing method for children's band and loop space maintainers.

OBJECTIVES: This study proposes a chairside digital design and manufacturing method for band and loop space maintainers and preliminarily validates its clinical feasibility. METHODS: Clinical cases of 10 children requiring space maintenance caused by premature loss of primary teeth were collected. Intraoral scan data of the affected children were also collected to establish digital models of the missing teeth. Using a pediatric band and loop space maintainer design software developed by our research team, a rapid personalized design of band and loop structures was achieved, and a digital model of an integrated band and loop space maintainer was ultimately generated. A chairside space maintainer was manufactured through metal computer numerical control machining for the experimental group, whereas metal 3D printing in the dental laboratory was used for the control group. A model fitting assessment was conducted for the space maintainers of both groups, and senior pediatric dental experts were invited to evaluate the clinical feasibility of the space maintainers with regard to fit and stability using the visual analogue scale scoring system. Statistical analysis was also performed. RESULTS: The time spent in designing and manufacturing the 10 space maintainers of the experimental group was all less than 1 h. Statistical analysis of expert ratings showed that the experimental group outperformed the control group with regard to fit and stability. Both types of space maintainers met clinical requirements. CONCLUSIONS: The chairside digital design and manufacturing method for pediatric band and loop space maintainers proposed in this study can achieve same-day fitting of space maintainers at the first appointment, demonstrating good clinical feasibility and significant potential for clinical application.

Three-Dimensional Virtual Reconstruction of External Nasal Defects Based on Facial Mesh Generation Network.

(1) Background: In digital-technology-assisted nasal defect reconstruction methods, a crucial step involves utilizing computer-aided design to virtually reconstruct the nasal defect's complete morphology. However, current digital methods for virtual nasal defect reconstruction have yet to achieve efficient, precise, and personalized outcomes. In this research paper, we propose a novel approach for reconstructing external nasal defects based on the Facial Mesh Generation Network (FMGen-Net), aiming to enhance the levels of automation and personalization in virtual reconstruction. (2) Methods: We collected data from 400 3D scans of faces with normal morphology and combined the structured 3D face template and the Meshmonk non-rigid registration algorithm to construct a structured 3D facial dataset for training FMGen-Net. Guided by defective facial data, the trained FMGen-Net automatically generated an intact 3D face that was similar to the defective face, and maintained a consistent spatial position. This intact 3D face served as the 3D target reference face (3D-TRF) for nasal defect reconstruction. The reconstructed nasal data were extracted from the 3D-TRF based on the defective area using reverse engineering software. The '3D surface deviation' between the reconstructed nose and the original nose was calculated to evaluate the effect of 3D morphological restoration of the nasal defects. (3) Results: In the simulation experiment of 20 cases involving full nasal defect reconstruction, the '3D surface deviation' between the reconstructed nasal data and the original nasal data was 1.45 ± 0.24 mm. The reconstructed nasal data, constructed from the personalized 3D-TRF, accurately reconstructed the anatomical morphology of nasal defects. (4) Conclusions: This paper proposes a novel method for the virtual reconstruction of external nasal defects based on the FMGen-Net model, achieving the automated and personalized construction of the 3D-TRF and preliminarily demonstrating promising clinical application potential.

Integrating an LSTM framework for predicting ankle joint biomechanics during gait using inertial sensors.

The ankle joint plays a crucial role in gait, facilitating the articulation of the lower limb, maintaining foot-ground contact, balancing the body, and transmitting the center of gravity. This study aimed to implement long short-term memory (LSTM) networks for predicting ankle joint angles, torques, and contact forces using inertial measurement unit (IMU) sensors. Twenty-five healthy participants were recruited. Two IMU sensors were attached to the foot dorsum and the vertical axis of the distal anteromedial tibia in the right lower limb to record acceleration and angular velocity during running. We proposed a LSTM-MLP (multilayer perceptron) model for training time-series data from IMU sensors and predicting ankle joint biomechanics. The model underwent validation and testing using a custom nested k-fold cross-validation process. The average values of the coefficient of determination (R2), mean absolute error (MAE), and mean squared error (MSE) for ankle dorsiflexion joint and moment, subtalar inversion joint and moment, and ankle joint contact forces were 0.89 ± 0.04, 0.75 ± 1.04, and 2.96 ± 4.96 for walking, and 0.87 ± 0.07, 0.88 ± 1.26, and 4.1 ± 7.17 for running, respectively. This study demonstrates that IMU sensors, combined with LSTM neural networks, are invaluable tools for evaluating ankle joint biomechanics in lower limb pathological diagnosis and rehabilitation, offering a cost-effective and versatile alternative to traditional experimental settings.

Intrahepatic homeobox protein MSX-1 is a novel host restriction factor of hepatitis B virus.

Chronic hepatitis B virus (HBV) infection (CHB) is a risk factor for the development of liver fibrosis, cirrhosis, and hepatocellular carcinoma. Covalently closed circular DNA serves as the sole transcription template for all viral RNAs and viral transcription is driven and enhanced by viral promoter and enhancer elements, respectively. Interactions between transcription factors and these cis-elements regulate their activities and change the production levels of viral RNAs. Here, we report the identification of homeobox protein MSX-1 (MSX1) as a novel host restriction factor of HBV in liver. In both HBV-transfected and HBV-infected cells, MSX1 suppresses viral gene expression and genome replication. Mechanistically, MSX1 downregulates enhancer II/core promoter (EnII/Cp) activity via direct binding to an MSX1 responsive element within EnII/Cp, and such binding competes with hepatocyte nuclear factor 4α binding to EnII/Cp due to partial overlap between their respective binding sites. Furthermore, CHB patients in immune active phase express higher levels of intrahepatic MSX1 but relatively lower levels of serum and intrahepatic HBV markers compared to those in immune tolerant phase. Finally, MSX1 was demonstrated to induce viral clearance in two mouse models of HBV persistence, suggesting possible therapeutic potential for CHB.IMPORTANCECovalently closed circular DNA plays a key role for the persistence of hepatitis B virus (HBV) since it serves as the template for viral transcription. Identification of transcription factors that regulate HBV transcription not only provides insights into molecular mechanisms of viral life cycle regulation but may also provide potential antiviral targets. In this work, we identified host MSX1 as a novel restriction factor of HBV transcription. Meanwhile, we observed higher intrahepatic MSX1 expression in chronic hepatitis B virus (CHB) patients in immune active phase compared to those in immune tolerant phase, suggesting possible involvement of MSX1 in the regulation of HBV activity by the host. Lastly, intrahepatic overexpression of MSX1 delivered by recombinant adenoviruses into two mouse models of HBV persistence demonstrated MSX1-mediated repression of HBV in vivo, and MSX1-induced clearance of intrahepatic HBV DNA in treated mice suggested its potential as a therapeutic target for the treatment of CHB.

A Data-Driven Approach for Fatigue Detection during Running Using Pedobarographic Measurements.

Background: Detecting fatigue at the early stages of a run could aid training programs in making adjustments, thereby reducing the heightened risk of injuries from overuse. The study aimed to investigate the effects of running fatigue on plantar force distribution in the dominant and nondominant feet of amateur runners. Methods: Thirty amateur runners were recruited for this study. Bilateral time-series plantar forces were employed to facilitate automatic fatigue gait recognition using convolutional neural network (CNN) and CNN-based long short-term memory network (ConvLSTM) models. Plantar force data collection was conducted both before and after a running-induced fatigue protocol using a FootScan force plate. The Keras library in Python 3.8.8 was used to train and tune deep learning models. Results: The results demonstrated that more mid-forefoot and heel force occurs during bilateral plantar and less midfoot fore force occurs in the dominant limb after fatigue (p < 0.001). The time of peak forces was significantly shortened at the midfoot and sum region of the nondominant foot, while it was delayed at the hallux region of the dominant foot (p < 0.001). In addition, the ConvLSTM model showed higher performance (Accuracy = 0.867, Sensitivity = 0.874, and Specificity = 0.859) in detecting fatigue gait than CNN (Accuracy = 0.800, Sensitivity = 0.874, and Specificity = 0.718). Conclusions: The findings of this study could offer empirical data for evaluating risk factors linked to overuse injuries in a single limb, as well as facilitate early detection of fatigued gait.

Lipid nanoparticle-mediated delivery of IL-21-encoding mRNA induces viral clearance in mouse models of hepatitis B virus persistence.

Hepatitis B virus (HBV) covalently closed circular DNA (cccDNA), the transcription template for all viral mRNAs, is highly stable and current treatment options cannot effectively induce its clearance. Previously, we established an HBV persistence mouse model based on a clinical isolate (termed BPS) and identified interleukin-21 (IL-21) as a potent inducer of HBV clearance. Lipid nanoparticle (LNP) mediated delivery of mRNA has proven to be a highly safe and effective delivery platform. This work explored the applicability and effectiveness of the mRNA-LNP platform in IL-21-based HBV therapies. First, LNP-encapsulated murine IL-21 mRNA (LNP-IL-21) was prepared, characterized, and demonstrated to engender IL-21 expression in vitro and in vivo. Next, LNP-IL-21 was shown to induce clearance of both serum and intrahepatic HBV antigen and DNA in two HBV persistence mouse models based on BPS and recombinant cccDNA (rcccDNA), respectively, which was associated with HBV-specific humoral and cellular immune responses. Furthermore, peripheral blood mononuclear cells from BPS persistence mice treated ex vivo with LNP-IL-21 and HBV surface antigen (HBsAg) could induce similar HBV clearance upon infusion into recipient mice. These findings indicated that IL-21 combined with mRNA-LNP platform represents a valid and promising strategy for developing novel therapeutics against chronic HBV infection.

Foot Pronation Prediction with Inertial Sensors during Running: A Preliminary Application of Data-Driven Approaches.

Abnormal foot postures may affect foot movement and joint loading during locomotion. Investigating foot posture alternation during running could contribute to injury prevention and foot mechanism study. This study aimed to develop feature-based and deep learning algorithms to predict foot pronation during prolonged running. Thirty-two recreational runners have been recruited for this study. Nine-axial inertial sensors were attached to the right dorsum of the foot and the vertical axis of the distal anteromedial tibia. This study employed feature-based machine learning algorithms, including support vector machine (SVM), extreme gradient boosting (XGBoost), random forest, and deep learning, i.e., one-dimensional convolutional neural networks (CNN1D), to predict foot pronation. A custom nested k-fold cross-validation was designed for hyper-parameter tuning and validating the model's performance. The XGBoot classifier achieved the best accuracy using acceleration and angular velocity data from the foot dorsum as input. Accuracy and the area under curve (AUC) were 74.7 ± 5.2% and 0.82 ± 0.07 for the subject-independent model and 98 ± 0.4% and 0.99 ± 0 for the record-wise method. The test accuracy of the CNN1D model with sensor data at the foot dorsum was 74 ± 3.8% for the subject-wise approach with an AUC of 0.8 ± 0.05. This study found that these algorithms, specifically for the CNN1D and XGBoost model with inertial sensor data collected from the foot dorsum, could be implemented into wearable devices, such as a smartwatch, for monitoring a runner's foot pronation during long-distance running. It has the potential for running shoe matching and reducing or preventing foot posture-induced injuries.

Combined Use of Immune Checkpoint Inhibitors and Phytochemicals as a Novel Therapeutic Strategy against Cancer.

Immune checkpoint inhibitor (ICI) therapy has dramatically changed cancer treatment, opening novel opportunities to cure malignant diseases. To date, most prevalently targeted immune checkpoints are programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), with many others being under extensive investigations. However, according to available data, only a fraction of patients may respond to ICI therapy. Additionally, this therapy may cause severe adverse immune-related side effects, such as diarrhea, headache, muscle weakness, rash, hepatitis and leucopenia, although most of them are not fatal, they can affect the patient's treatment outcome and quality of life. On the other hand, growing evidence has shown that phytochemicals with anticancer effects may combine ICI therapy to augment the safety and effectiveness of the treatment against cancer while reducing the adverse side effects. In this review, we summarize the state of art in the various experiments and clinical application of ICIs plus phytochemicals, with a focus on their combined use as a novel therapeutic strategy to cure cancer.

Establishment and characterization of a novel reverse genetic system of BK polyomavirus.

BK polyomavirus (BKV) is a small non-enveloped DNA virus. BKV infection or reactivation may cause BKV-associated nephropathy and hemorrhagic cystitis in immunosuppressed transplant recipients. No effective antivirals or prevention strategies are available against BKV infections. The current BKV reverse system employs the transfection of purified full-length linear viral genomes released by enzyme digestion from BKV genomic plasmids. The method is laborious and often results in variable DNA yield and quality, which can affect the efficiency of transfection and subsequent formation of circular viral genomes in cells. In this study, we report the generation of circular viral genomes by Cre-mediated DNA recombination in cells directly transfected with BKV precursor genomic plasmids. The novel system supported efficient viral expression and replication, and produced a higher level of infectious virions compared with the transfection with linear BKV genomes. Furthermore, we successfully constructed recombinant BKV capable of reporter gene expression. In conclusion, the novel BKV reverse genetic system allows for simpler manipulation of BKV genome with better virus yield, providing a tool for the study of BKV life cycle and antiviral screening.

Understanding the Role of Children's Footwear on Children's Feet and Gait Development: A Systematic Scoping Review.

Children's footwear plays an important role in the healthy growth of foot and gait development during the growing stage. This review aims to synthesize findings of previous investigations and to explore the biomechanical influences of different types of children's footwear on foot health and gait development, thus guiding the healthy and safe growth of children's feet and gait. Online databases were searched for potential eligible articles, including Web of Science, Google Scholar, and PubMed. In total, nineteen articles were identified after searching based on the inclusion requirements. The following five aspects of biomechanical parameters were identified in the literature, including spatiotemporal, kinematics, kinetics, electromyography (EMG), and plantar pressure distribution. Children's footwear can affect their foot health and gait performance. In addition, children's shoes with different flexibility and sole hardness have different effects on children's feet and gait development. Compared to barefoot, the stride length, step length, stride time, and step time were increased, but cadence was decreased with wearing shoes. Furthermore, the support base and toe-off time increased. Double support time and stance time increased, but single support time decreased. The hip, knee, and ankle joints showed increased range of motion in children with the rear-foot strike with larger ground reaction force as well. Future studies may need to evaluate the influence of footwear types on gait performance of children in different age groups. Findings in this study may provide recommendations for suitable footwear types for different ages, achieving the aim of growth and development in a healthy and safe manner.

Comparison Study of Extraction Accuracy of 3D Facial Anatomical Landmarks Based on Non-Rigid Registration of Face Template.

(1) Background: Three-dimensional (3D) facial anatomical landmarks are the premise and foundation of facial morphology analysis. At present, there is no ideal automatic determination method for 3D facial anatomical landmarks. This research aims to realize the automatic determination of 3D facial anatomical landmarks based on the non-rigid registration algorithm developed by our research team and to evaluate its landmark localization accuracy. (2) Methods: A 3D facial scanner, Face Scan, was used to collect 3D facial data of 20 adult males without significant facial deformities. Using the radial basis function optimized non-rigid registration algorithm, TH-OCR, developed by our research team (experimental group: TH group) and the non-rigid registration algorithm, MeshMonk (control group: MM group), a 3D face template constructed in our previous research was deformed and registered to each participant's data. The automatic determination of 3D facial anatomical landmarks was realized according to the index of 32 facial anatomical landmarks determined on the 3D face template. Considering these 32 facial anatomical landmarks manually selected by experts on the 3D facial data as the gold standard, the distance between the automatically determined and the corresponding manually selected facial anatomical landmarks was calculated as the "landmark localization error" to evaluate the effect and feasibility of the automatic determination method (template method). (3) Results: The mean landmark localization error of all facial anatomical landmarks in the TH and MM groups was 2.34 ± 1.76 mm and 2.16 ± 1.97 mm, respectively. The automatic determination of the anatomical landmarks in the middle face was better than that in the upper and lower face in both groups. Further, the automatic determination of anatomical landmarks in the center of the face was better than in the marginal part. (4) Conclusions: In this study, the automatic determination of 3D facial anatomical landmarks was realized based on non-rigid registration algorithms. There is no significant difference in the automatic landmark localization accuracy between the TH-OCR algorithm and the MeshMonk algorithm, and both can meet the needs of oral clinical applications to a certain extent.

Automated recognition of asymmetric gait and fatigue gait using ground reaction force data.

Introduction: The purpose of this study was to evaluate the effect of running-induced fatigue on the characteristic asymmetry of running gait and to identify non-linear differences in bilateral lower limbs and fatigued gait by building a machine learning model. Methods: Data on bilateral lower limb three-dimensional ground reaction forces were collected from 14 male amateur runners before and after a running-induced fatigue experiment. The symmetry function (SF) was used to assess the degree of symmetry of running gait. Statistical parameter mapping (Paired sample T-test) algorithm was used to examine bilateral lower limb differences and asymmetry changes pre- and post-fatigue of time series data. The support vector ma-chine (SVM) algorithm was used to recognize the gait characteristics of both lower limbs before and after fatigue and to build the optimal algorithm model by setting different kernel functions. Results: The results showed that the ground reaction forces were asymmetrical (SF > 0.5) both pre-and post-fatigue and mainly concentrated in the medial-lateral direction. The asymmetry of the medial-lateral direction increased significantly after fatigue (p < 0.05). In addition, we concluded that the polynomial kernel function could make the SVM model the most accurate in classifying left and right gait features (accuracy of 85.3%, 82.4%, and 82.4% in medial-lateral, anterior-posterior and vertical directions, respectively). Gaussian radial basis kernel function was the optimal kernel function of the SVM algorithm model for fatigue gait recognition in the medial-lateral and vertical directions (accuracy of 54.2% and 62.5%, respectively). Moreover, polynomial was the optimal kernel function of the anterior-posterior di-rection (accuracy = 54.2%). Discussion: We proved in this study that the SVM algorithm model depicted good performance in identifying asymmetric and fatigue gaits. These findings can provide implications for running injury prevention, movement monitoring, and gait assessment.

Dataset of lower extremity joint angles, moments and forces in distance running.

This study presents a database of joint angles, moments, and forces of the lower extremity from distance running at a submaximal speed in recreational runners. Twenty recreational runners participated in two experimental sessions, specifically pre and post a 5k treadmill run, with a synchronous collection of markers trajectories and ground reaction forces for both limbs in walking and running trials. The raw data in C3D files could be used for musculoskeletal modelling. Extra datasets of joint angles, moments, and forces are presented ready-for-use in MAT files, which could be as reference for study of biomechanical alterations from distance running. Applying advanced data processing techniques (Machine Learning algorithms) to these datasets ( C3D & MAT ), such as Principal Component Analysis, could extract key features of variation, thus potentially being applied for correlation with accelerometric and gyroscope parameters from wearable sensors during field running. Dataset of multi-segmental foot could be another contribution for the investigation of foot complex biomechanics from distance running. The dataset from Asian males may also be used for population-based studies of running biomechanics.

Interleukin-33 mediates both immune-related and non-immune-related inhibitory effects against hepatitis B virus.

Chronic infection by hepatitis B virus (HBV) is associated with high risks of liver fibrosis, cirrhosis and hepatocellular carcinoma. HBV covalently closed circular DNA (cccDNA) in the nucleus of infected hepatocyte serves as transcription template. Neither natural resolution of acute infection nor current treatment options for chronic infection are believed to cause cccDNA clearance. We previously showed that injection of IL-33-expressing plasmid facilitated clearance of intrahepatic HBV DNA in a mouse model of HBV persistence. In this work, HBV-targeting therapeutic effects of IL-33 were further explored. Murine IL-33 delivered by recombinant adeno-associated virus (AAV-mIL-33) induced clearance of both serum HBV markers and intrahepatic HBV DNA in two mouse models of HBV persistence based on replicon plasmid and recombinant cccDNA (rcccDNA) respectively. Clearance was associated with serum ALT elevations and liver infiltrations by CD4+ and CD8+ T cells, indicating IL-33-induced cellular immune responses against HBV-harboring cells. Adoptive transfer of splenocytes from AAV-mIL-33-cured mice was indeed sufficient to engender similar clearance in recipient mice. In vitro, intracellular, instead of extracellular, IL-33 was mainly responsible for repressing viral transcription, protein production and genome replication in Huh7 cells transfected with HBV replicon or rcccDNA. IL-33 was shown to be recruited onto rcccDNA minichromosome accompanied by loss of transcriptional activation epigenetic marks. Finally, transfection of IL-33 into HBV-infected HepG2/NTCP cells resulted in reduced transcription, antigen expression and genome replication, suggesting repression of canonical cccDNA. These data demonstrated diverse inhibitory effects on HBV and HBV-infected cells mediated by IL-33, and suggest IL-33 as an interesting therapeutic candidate.