Covalent Organic Framework-Structured Raman Probes for Ultrasensitive In Vivo Bioimaging.

Organic Raman probes, including polymers and small molecules, have attracted great attention in biomedical imaging owing to their excellent biocompatibility. However, the development of organic Raman probes is usually hindered by a mismatch between their absorption spectra and wavelength-fixed excitation, which makes it difficult to achieve resonance excitation necessary to obtain strong Raman signals. Herein, we introduce a covalent organic framework (COF) into the fine absorption spectrum regulation of organic Raman probes, resulting in their significant Raman signal enhancement. In representative examples, a polymer poly(diketopyrrolopyrrole-p-phenylenediamine) (DPP-PD) and a small molecule azobenzene are transformed into the corresponding COF-structured Raman probes. Their absorption peaks show an accurate match of less than 5 nm with the NIR excitation. As such, the COF-structured Raman probes acquire highly sensitive bioimaging capabilities compared to their precursors with negligible signals. By further mechanism studies, we discover that the crystallinity and size of COFs directly affect the π-conjugation degree of Raman probes, thus changing their bandgaps and absorption spectra. Our study offers a universal and flexible method for improving the signal performance of organic Raman probes without changing their structural units, making it more convenient to obtain the highly sensitive organic Raman probes for in vivo bioimaging.

Highly Stretchable, Fast Self-Healing, Self-Adhesive, and Strain-Sensitive Wearable Sensor Based on Ionic Conductive Hydrogels.

Conductive hydrogels integrate the conductive performance and soft nature, which is like that of human skin. Thus, they are more suitable for the preparation of wearable human-motion sensors. Nevertheless, the integration of outstanding multiple functionalities, such as stretchability, toughness, biocompatibility, self-healing, adhesion, strain sensitivity, and durability, by a simple way is still a huge challenge. Herein, we have developed a multifunctional chitosan/oxidized hyaluronic acid/hydroxypropyl methylcellulose/poly(acrylic acid)/tannic acid/Al3+ hydrogel (CS/OHA/HPMC/PAA/TA/Al3+) by using a two-step method with hydroxypropyl methylcellulose (HPMC), acrylic acid (AA), tannic acid (TA), chitosan (CS), oxidized hyaluronic acid (OHA), and aluminum chloride hexahydrate (AlCl3·6H2O). Due to the synergistic effect of dynamic imine bonds between CS and OHA, dynamic metal coordination bonds between Al3+ and -COOH and/or TA as well as reversible hydrogen, the hydrogel showed excellent tensile property (elongation at break of 3168%) and desirable toughness (0.79 MJ/m3). The mechanical self-healing efficiency can reach 95.5% at 30 min, and the conductivity can recover in 5.2 s at room temperature without stimulation. The favorable attribute of high transparency (98.5% transmittance) facilitates the transmission of the optical signal and enables visualization of the sensor. It also shows good adhesiveness to various materials and is easy to peel off without residue. The resistance of the hydrogel-based sensors shows good electrical conductivity (2.33 S m-1), good durability, high sensing sensitivity (GF value of 4.12 under 1600% strain), low detection limit (less than 1%), and short response/recovery time (0.54/0.31 s). It adhered to human skin and monitored human movements such as the bending movements of joints, swallowing, and speaking successfully. Therefore, the obtained multifunctional conductive hydrogel has great potential applications in wearable strain sensors.

Insight into the Feasibility of Fatty Acyl Chlorides with 10-18 Carbons for the Ball-Milling Synthesis of Thermoplastic Cellulose Esters.

Fatty acid cellulose esters (FACE) are common cellulose-based thermoplastics, and their thermoplasticity is determined by both the contents and the lengths of the side chains. Herein, various FACE were synthesized by the ball-milling esterification of cellulose and fatty acyl chlorides containing 10-18 carbons, and their structures and thermoplasticity were thoroughly studied. The results showed that FACE with high degrees of substitution (DS) and low melting flow temperatures (Tf) were achieved as the chain lengths of the fatty acyl chlorides were reduced. In particular, a cellulose decanoate with a DS of 1.85 and a Tf of 186 °C was achieved by feeding 3 mol of decanoyl chloride per mole anhydroglucose units of cellulose. However, cellulose stearate (DS = 1.53) synthesized by the same protocols cannot melt even at 250 °C. More interestingly, the fatty acyl chlorides with 10 and 12 carbons resulted in FACE with superior toughness (elongation at break up to 94.4%). In contrast, due to their potential crystallization of the fatty acyl groups with 14-18 carbons, the corresponding FACE showed higher tensile strength and Young's modulus than the others. This study provides some theoretical basis for the mechanochemical synthesis of thermoplastic FACE with designated properties.

NK-92 cells labeled with Fe3O4-PEG-CD56/Avastin@Ce6 nanoprobes for the targeted treatment and noninvasive therapeutic evaluation of breast cancer.

Adoptive cellular immunotherapy as a promising and alternative cancer therapy platform is critical for future clinical applications. Natural killer (NK) cells have attracted attention as an important type of innate immune regulatory cells that can rapidly kill multiple adjacent cancer cells. However, these cells are significantly less effective in treating solid tumors than in treating hematological tumors. Herein, we report the synthesis of a Fe3O4-PEG-CD56/Avastin@Ce6 nanoprobe labeled with NK-92 cells that can be used for adoptive cellular immunotherapy, photodynamic therapy and dual-modality imaging-based in vivo fate tracking. The labeled NK-92 cells specifically target the tumor cells, which increases the amount of cancer cell apoptosis in vitro. Furthermore, the in vivo results indicate that the labeled NK-92 cells can be used for tumor magnetic resonance imaging and fluorescence imaging, adoptive cellular immunotherapy, and photodynamic therapy after tail vein injection. These data show that the developed multifunctional nanostructure is a promising platform for efficient innate immunotherapy, photodynamic treatment and noninvasive therapeutic evaluation of breast cancer.

New insights into nanotherapeutics for periodontitis: a triple concerto of antimicrobial activity, immunomodulation and periodontium regeneration.

Periodontitis is a chronic inflammatory disease caused by the local microbiome and the host immune response, resulting in periodontal structure damage and even tooth loss. Scaling and root planning combined with antibiotics are the conventional means of nonsurgical treatment of periodontitis, but they are insufficient to fully heal periodontitis due to intractable bacterial attachment and drug resistance. Novel and effective therapeutic options in clinical drug therapy remain scarce. Nanotherapeutics achieve stable cell targeting, oral retention and smart release by great flexibility in changing the chemical composition or physical characteristics of nanoparticles. Meanwhile, the protectiveness and high surface area to volume ratio of nanoparticles enable high drug loading, ensuring a remarkable therapeutic efficacy. Currently, the combination of advanced nanoparticles and novel therapeutic strategies is the most active research area in periodontitis treatment. In this review, we first introduce the pathogenesis of periodontitis, and then summarize the state-of-the-art nanotherapeutic strategies based on the triple concerto of antibacterial activity, immunomodulation and periodontium regeneration, particularly focusing on the therapeutic mechanism and ingenious design of nanomedicines. Finally, the challenges and prospects of nano therapy for periodontitis are discussed from the perspective of current treatment problems and future development trends.

Activatable Semiconducting Polymer Nanoinducers Amplify Oxidative Damage via Sono-Ferroptosis for Synergistic Therapy of Bone Metastasis.

Bone metastases are secondary malignant tumors that commonly occur after the spread of advanced cancer cells. We herein report the activatable semiconducting polymer nanoinducers (ASPNFP) that can amplify oxidative damage via sono-ferroptosis for bone metastasis treatment. ASPNFP are constructed by encapsulating plasma amine oxidase-based semiconducting polymer nanoparticles (SPNP) and Fe3O4 nanoparticles into singlet oxygen (1O2)-responsive nanocarriers. ASPNFP generate 1O2 under ultrasound (US) irradiation via a sonodynamic effect to destroy the stability of 1O2-responsive nanocarriers, allowing US-triggered releases of SPNP and Fe3O4 nanoparticles. SPNP decompose polyamines in tumor cells to produce acrolein and hydrogen peroxide (H2O2), in which H2O2 promotes Fenton reaction mediated by Fe3O4 nanoparticles for inducing enhanced ferroptosis and generation of hydroxyl radicals (•OH). The generated acrolein, 1O2, and •OH can simultaneously amplify the oxidative damage. ASPNFP thus mediate an amplified sono-ferroptosis effect to inhibit the growth of bone metastasis and restrict tumor metastasis.

3D Bioprinting-Based Dopamine-Coupled Flexible Material for Nasal Cartilage Repair.

INTRODUCTION: Since 3D printing can be used to design implants according to the specific conditions of patients, it has become an emerging technology in tissue engineering and regenerative medicine. How to improve the mechanical, elastic and adhesion properties of 3D-printed photocrosslinked hydrogels is the focus of cartilage tissue repair and reconstruction research. MATERIALS AND METHODS: We established a strategy for toughening hydrogels by mixing GelMA-DOPA (GD), which is prepared by coupling dopamine (DA) with GelMA, with HAMA, bacterial cellulose (BC) to produce composite hydrogels (HB-GD). HB-GD hydrogel scaffolds were characterized in vitro by scanning electron microscopy (SEM), Young's modulus, swelling property and rheological property tests. And biocompatibility and chondrogenic ability were tested by live/dead staining, DNA quantitative analysis and immunofluorescence staining. Combined with 3D bioprinting technology, mouse chondrocytes (ADTC5) were added to form a biological chain to construct an in vitro model, and the feasibility of the model for nasal cartilage regeneration was verified by cytology evaluation. RESULTS: With the increase of GD concentration, the toughness of the composite hydrogel increased (47.0 ± 2.7 kPa (HB-5GD)-158 ± 3.2 kPa (HB-20GD)), and it had excellent swelling properties, rheological properties and printing properties. The HB-GD composite hydrogel promoted the proliferation and differentiation of ATDC5. Cells in 3D printed scaffolds had higher survival rates (> 95%) and better protein expression than the encapsulated cultures. CONCLUSION: The HB-10GD hydrogel can be made into a porous scaffold with precise shape, good internal pore structure, high mechanical strength and good swelling rate through extrusion 3D printing. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.

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.

Sono-Triggered Cascade Lactate Depletion by Semiconducting Polymer Nanoreactors for Cuproptosis-Immunotherapy of Pancreatic Cancer.

The high level of lactate in tumor microenvironment not only promotes tumor development and metastasis, but also induces immune escape, which often leads to failures of various tumor therapy strategies. We here report a sono-triggered cascade lactate depletion strategy by using semiconducting polymer nanoreactors (SPNLCu) for cancer cuproptosis-immunotherapy. The SPNLCu mainly contain a semiconducting polymer as sonosensitizer, lactate oxidase (LOx) conjugated via a reactive oxygen species (ROS)-cleavable linker and chelated Cu2+. Upon ultrasound (US) irradiation, the semiconducting polymer generates singlet oxygen (1O2) to cut ROS-cleavable linker to allow the release of LOx that catalyzes lactate depletion to produce hydrogen peroxide (H2O2). The Cu2+ will be reduced to Cu+ in tumor microenvironment, which reacts with the produced H2O2 to obtain hydroxyl radical (⋅OH) that further improves LOx release via destroying ROS-cleavable linkers. As such, sono-triggered cascade release of LOx achieves effective lactate depletion, thus relieving immunosuppressive roles of lactate. Moreover, the toxic Cu+ induces cuproptosis to cause immunogenic cell death (ICD) for activating antitumor immunological effect. SPNLCu are used to treat both subcutaneous and deep-tissue orthotopic pancreatic cancer with observably enhanced efficacy in restricting the tumor growths. This study thus provides a precise and effective lactate depletion tactic for cancer therapy.

Pyridinium-Yne Click Polymerization: A Facile Strategy toward Functional Poly(Vinylpyridinium Salt)s with Multidrug-Resistant Bacteria Killing Ability.

Polymeric materials with antibacterial properties hold great promise for combating multidrug-resistant bacteria, which pose a significant threat to public health. However, the synthesis of most antibacterial polymers typically involves complicated and time-consuming procedures. In this study, we demonstrate a simple and efficient strategy for synthesizing functional poly(vinylpyridinium salt)s via pyridinium-yne click polymerization. This click polymerization could proceed with high atom economy under mild conditions without any external catalyst, yielding soluble and thermally stable poly(vinylpyridinium salt)s with satisfactory molecular weights and well-defined structures in excellent yields. Additionally, the incorporation of luminescent units such as fluorene, tetraphenylethylene, and triphenylamine into the polymer backbone confers excellent aggregation-enhanced emission properties upon the resulting polymers, rendering them suitable for bacterial staining. Moreover, the existence of pyridinium salt imparts intrinsic antibacterial activity against multidrug-resistant bacteria to the polymers, enabling them to effectively inhibit wound bacterial infection and significantly expedite the healing process. This work not only provides an efficient method to prepare antibacterial polymers, but also opens up the possibility of various applications of polymers in healthcare and other antibacterial fields.

Quinoid Conjugated Polymer Nanoparticles with NIR-II Absorption Peak Toward Efficient Photothermal Therapy.

Recently, extensive efforts have been devoted to the development of the second near-infrared bio-window (NIR-II, 1000-1700 nm) theranostic agents owing to the excellent tissue-penetration capability of NIR-II light. The exploration of organic NIR-II photothermal therapy materials, especially those with absorption peak over 1000 nm, is an appealing yet significantly challenging task. Herein, we have designed conjugated polymer nanoparticles (PIS NPs) with NIR-II absorption peak at 1026 nm through a combined strategy of introducing quinoid donor-acceptor (D-A) structures, constructing intramolecular "conformational locks" and extending the conjugation area to narrow the band gap. Irradiated at 1064 nm, PIS NPs showed remarkable photothermal conversion performance for efficient photothermal ablation of tumor cells in vitro and in vivo. This study provides useful insights into the rational design of organic NIR-II photothermal agents based on multiple strategies.

Porphyromonas gingivalis predicts local recurrence after endoscopic submucosal dissection of early esophageal squamous cell carcinoma or precancerous lesion.

BACKGROUND: Porphyromonas gingivalis plays an oncogenic role in development and progression of esophageal squamous cell carcinoma (ESCC). However, the impact of P. gingivalis on local recurrence of early ESCC or precancerous lesion after ESD treatment remains unknown. The present study aimed to evaluate the impact of P. gingivalis on local recurrence after ESD treatment of early ESCC or high-grade dysplasia (HGD). METHODS: The amount of P. gingivalis was assessed by immunohistochemistry in 205 patients with early ESCC or HGD. Univariate and multivariate Cox regression analyses were performed to determine the effect of P. gingivalis on local recurrence. Propensity score matching analysis was performed to reduce the imbalance of baseline characteristics. A nomogram integrating significant prognostic factors was built for local recurrence prediction. RESULTS: The amount of P. gingivalis increased significantly in neoplasms that invaded up to muscularis mucosa and submucosa compared with lesions confined to epithelium or lamina propria. Overabundance of P. gingivalis was positively associated with invasion depth, post-ESD stricture and local recurrence. Univariate and multivariate Cox regression analyses revealed that P. gingivalis, longitudinal length of lesion and lymphovascular invasion were independent predictors for post-ESD recurrence. A nomogram comprising P. gingivalis, lymphovascular involvement, and lesion length performed well for prediction of post-ESD local recurrence with the concordance indices of 0.72 (95%CI, 0.62 to 0.80), 0.72 (95%CI, 0.63 to 0.80), and 0.74 (95%CI, 0.65 to 0.83) in the validation cohort, the entire cohort, and the subcohort after PSM, respectively. CONCLUSION: P. gingivalis overabundance is a risk factor and a potential predictor for local recurrence of early ESCC or HGD after ESD treatment. Thus, clearance of P. gingivalis represents an attractive strategy for prognosis improvement and for prevention of ESCC.

Hierarchically Structured Nanoparticle-Free Omniphobic Membrane for High-Performance Membrane Distillation.

The functional loss of membranes caused by pore wetting, mineral scaling, or structural instability is a critical challenge in membrane distillation (MD), which primarily hinders its practical applications. Herein, we propose a novel and facile strategy to fabricate omniphobic membranes with exceptionally robust MD performance. Specifically, a substrate with a hierarchical re-entrant architecture was constructed via spray-water-assisted non-solvent-induced phase separation (SWNIPS), followed by a direct fluorinated surface decoration via "thiol-ene" click chemistry. Deionized (DI) water contact angle measurements revealed an ultrahigh surface water contact angle (166.8 ± 1.8°) and an ultralow sliding angle (3.6 ± 1.1°) of the resultant membrane. Destructive abrasion cycle and ultrasonication tests confirmed its structural robustness. Moreover, the membrane possessed excellent wetting resistance, as evidenced by the prevention of membrane pore penetration by all low-surface-tension testing liquids, allowing stable long-term MD operation to treat brine wastewater with a surfactant content of 0.6 mM. In a desalination experiment using shale gas wastewater, the omniphobic membrane exhibited robust MD performance, achieving a high water recovery ratio of ∼60% without apparent changes in water flux and permeate conductivity over the entire membrane process. Overall, our study paves the way for a nanoparticle-free methodology for the scalable fabrication of high-performance MD membranes with surface omniphobicity and structural robustness in hypersaline wastewater treatment.

Stimuli-responsive composite biopolymer actuators with selective spatial deformation behavior.

Bioinspired actuators with stimuli-responsive and deformable properties are being pursued in fields such as artificial tissues, medical devices and diagnostics, and intelligent biosensors. These applications require that actuator systems have biocompatibility, controlled deformability, biodegradability, mechanical durability, and stable reversibility. Herein, we report a bionic actuator system consisting of stimuli-responsive genetically engineered silk-elastin-like protein (SELP) hydrogels and wood-derived cellulose nanofibers (CNFs), which respond to temperature and ionic strength underwater by ecofriendly methods. Programmed site-selective actuation can be predicted and folded into three-dimensional (3D) origami-like shapes. The reversible deformation performance of the SELP/CNF actuators was quantified, and complex spatial transformations of multilayer actuators were demonstrated, including a biomimetic flower design with selective petal movements. Such actuators consisting entirely of biocompatible and biodegradable materials will offer an option toward constructing stimuli-responsive systems for in vivo biomedicine soft robotics and bionic research.

Study on the Preparation and Properties of Jute Microcrystalline Cellulose Membrane.

The preparation and performance control of the cellulose membrane are one of the hot topics in the environmentally friendly separation membrane field. In this study, microcrystalline cellulose (MCC) was prepared by microwave-assisted acidic hydrolysis of cellulose obtained from jute, followed by the use of a mixture of N-methylmorpholine-N-oxide and water as a solvent to obtain the homogeneous casting liquid, which was scraped and subsequently immersed in the coagulation bath to form a smooth and dense cellulose membrane. During membrane formation, the crystal structure of MCC changed from type I to type II, but the chemical structure remained unchanged. The mechanical strength and separation performance of the membrane were related to the content of MCC in the casting liquid. When the content of MCC was about 7%, the tensile strength of the membrane reached a maximum value of 13.49 MPa, and the corresponding elongation at break was 68.12%. The water flux (J) and rejection rate (R) for the bovine serum albumin were 19.51 L/(m2·h) and 95.37%, respectively, under an optimized pressure of 0.2 MPa. In addition, the coagulation bath had a significant effect on the membrane separation performance, and J and R were positively and negatively correlated with the polarity of the coagulation bath. Among them, it was note-worthy that J and R of membrane formed in ethanol were 33.95 L/(m2·h) and 91.43%, separately. Compared with water as a coagulation bath, J was increased by 74% at the situation and R was roughly equivalent, showing better separation performance. More importantly, the relationship between the structure and separation performances has also been studied preliminarily. This work provides certain guidance for the preparation of high-performance MCC membranes.

The application of a fully digital approach in the treatment of skeletal class III malocclusion: a preliminary study.

BACKGROUND: Skeletal malocclusion patients have facial malformations and occlusal dysfunctions that require orthodontic-orthognathic joint treatment, while the combination treatment takes time and requires close communication between surgeons and orthodontists. Thus, improving the efficiency and effectiveness of the combination treatment is necessary, and it is still a challenge. Now, digital technology provides us with an excellent alternative. Despite the widespread use of digital technology in orthognathic surgery simulation and clear aligner orthodontic therapy, it has not been fully integrated into the combined orthognathic and orthodontic treatment process, and the components remain independent. METHODS: A fully digital approach to seamlessly integrating various parts of the combined treatment through digital technology was investigated in this study in order to achieve an efficient transition. Five patients with skeletal Class III malocclusion were enrolled, and all made fully digital treatment plans at the beginning of actual implementation, which included the design of pre-surgical orthodontic, orthognathic surgery, and post-surgical orthodontic. Then, every aspect of the clinical operation was carried out in accordance with the fully digital routine. After the entire treatment process was completed, the skeleton and dentition discrepancy between virtual planning and the actual result was evaluated. RESULTS: All participants completed the fully digital treatment process, and no complication was observed. The linear deviation of the skeletal anatomy was less than 1 mm, and the angular deviation was less than 1 degree. Except in one case in the lower dentition, the deviation of the virtual dental design from the real alignment was less than 2 mm. Furthermore, with one exception of maxillary anterior-posterior dimension, the linear deviations of the skeleton were not statistically significant. Therefore, the simulation accuracy of the fully digital approach was clinically acceptable. CONCLUSIONS: The digital treatment approach is clinically feasible and has achieved satisfactory results. The discrepancy between virtual design of the entire digital process and actual post-treatment situation was acceptable in clinic. A fully digital approach was proved effective in the treatment of skeletal Class III malocclusion, with which the efficient transition of treatment procedures was realized.

Three-dimensional printed titanium mesh combined with iliac cancellous bone in the reconstruction of mandibular defects secondary to ameloblastoma resection.

BACKGROUND: The reconstruction of large mandibular defects is a challenge, and free vascularized bone flaps are most commonly used. However, the precision and symmetry of this repair are deficient, and patients have a risk of vascular embolism, flap necrosis, and donor site complications. Therefore, to explore an ideal alternative in mandibular reconstruction with high surgical accuracy and low complications is indispensable. METHODS: Seven patients with recurrent or large-scope ameloblastoma were enrolled in this study. All patients were provided with a fully digital treatment plan, including the design of osteotomy lines, surgical guides, and three-dimensional printed titanium mesh for implantation. With the assistance of surgical guide, ameloblastomas were resected, and custom 3D printed titanium mesh combined with posterior iliac bone harvest was used in mandibular reconstruction. A comparison was made between the discrepant surgical outcomes and the intended surgical plan, as well as the average three-dimensional deviation of the mandible before and after the surgery. At the same time, the resorption rate of the implanted bone was evaluated. RESULTS: All patients completed the fully digital treatment process successfully without severe complications. Image fusion showed that the postoperative contour of the mandible was basically consistent with surgical planning, except for a slight increase in the inferior border of the affected side. The mean three-dimensional deviation of the mandible between the preoperative and postoperative periods was 0.78 ± 0.41 mm. The mean error between the intraoperative bone volume and the digital planning bone volume was 2.44%±2.10%. Furthermore, the bone resorption rates of the harvested graft 6 months later were 32.15%±6.95%. CONCLUSIONS: The use of digital surgical planning and 3D-printed templates can assist surgeons in performing surgery precisely, and the 3D-printed titanium mesh implant can improve the patient's facial symmetry. 3D printed titanium mesh combined with posterior iliac cancellous bone graft can be regarded as an ideal alternative in extensive mandibular reconstruction.

Prediction of orthognathic surgery plan from 3D cephalometric analysis via deep learning.

BACKGROUND: Preoperative planning of orthognathic surgery is indispensable for achieving ideal surgical outcome regarding the occlusion and jaws' position. However, orthognathic surgery planning is sophisticated and highly experience-dependent, which requires comprehensive consideration of facial morphology and occlusal function. This study aimed to investigate a robust and automatic method based on deep learning to predict reposition vectors of jawbones in orthognathic surgery plan. METHODS: A regression neural network named VSP transformer was developed based on Transformer architecture. Firstly, 3D cephalometric analysis was employed to quantify skeletal-facial morphology as input features. Next, input features were weighted using pretrained results to minimize bias resulted from multicollinearity. Through encoder-decoder blocks, ten landmark-based reposition vectors of jawbones were predicted. Permutation importance (PI) method was used to calculate contributions of each feature to final prediction to reveal interpretability of the proposed model. RESULTS: VSP transformer model was developed with 383 samples and clinically tested with 49 prospectively collected samples. Our proposed model outperformed other four classic regression models in prediction accuracy. Mean absolute errors (MAE) of prediction were 1.41 mm in validation set and 1.34 mm in clinical test set. The interpretability results of the model were highly consistent with clinical knowledge and experience. CONCLUSIONS: The developed model can predict reposition vectors of orthognathic surgery plan with high accuracy and good clinically practical-effectiveness. Moreover, the model was proved reliable because of its good interpretability.

Automatic craniomaxillofacial landmarks detection in CT images of individuals with dentomaxillofacial deformities by a two-stage deep learning model.

BACKGROUND: Accurate cephalometric analysis plays a vital role in the diagnosis and subsequent surgical planning in orthognathic and orthodontics treatment. However, manual digitization of anatomical landmarks in computed tomography (CT) is subject to limitations such as low accuracy, poor repeatability and excessive time consumption. Furthermore, the detection of landmarks has more difficulties on individuals with dentomaxillofacial deformities than normal individuals. Therefore, this study aims to develop a deep learning model to automatically detect landmarks in CT images of patients with dentomaxillofacial deformities. METHODS: Craniomaxillofacial (CMF) CT data of 80 patients with dentomaxillofacial deformities were collected for model development. 77 anatomical landmarks digitized by experienced CMF surgeons in each CT image were set as the ground truth. 3D UX-Net, the cutting-edge medical image segmentation network, was adopted as the backbone of model architecture. Moreover, a new region division pattern for CMF structures was designed as a training strategy to optimize the utilization of computational resources and image resolution. To evaluate the performance of this model, several experiments were conducted to make comparison between the model and manual digitization approach. RESULTS: The training set and the validation set included 58 and 22 samples respectively. The developed model can accurately detect 77 landmarks on bone, soft tissue and teeth with a mean error of 1.81 ± 0.89 mm. Removal of region division before training significantly increased the error of prediction (2.34 ± 1.01 mm). In terms of manual digitization, the inter-observer and intra-observer variations were 1.27 ± 0.70 mm and 1.01 ± 0.74 mm respectively. In all divided regions except Teeth Region (TR), our model demonstrated equivalent performance to experienced CMF surgeons in landmarks detection (p > 0.05). CONCLUSIONS: The developed model demonstrated excellent performance in detecting craniomaxillofacial landmarks when considering manual digitization work of expertise as benchmark. It is also verified that the region division pattern designed in this study remarkably improved the detection accuracy.

High-Strength, Large-Deformation, Dual Cross-Linking Network Liquid Crystal Elastomers Based on Quadruple Hydrogen Bonds.

Liquid crystal elastomers (LCEs) with large deformation under external stimuli have attracted extensive attention in various applications such as soft robotics, 4D printing, and biomedical devices. However, it is still a great challenge to reduce the damage to collimation and enhance the mechanical and actuation properties of LCEs simultaneously. Here, we construct a new method of a double cross-linking network structure to improve the mechanical properties of LCEs. The ureidopyrimidinone (UPy) group with quadruple hydrogen bonds was used as the physical cross-linking unit, and pentaerythritol tetra(3-mercaptopropionate) was used as the chemical cross-link. The LCEs showed a strong mechanical tensile strength of 8.5 MPa and excellent thermally induced deformation (50%). In addition, the introduction of quadruple hydrogen bonds endows self-healing ability to extend the service life of LCEs. This provides a generic strategy for the fabrication of high-strength LCEs, inspiring the development of actuators and artificial muscles.