Effect of orthodontics combined with fibre-reinforced composite resin-bonded fixed partial denture on anterior dentition defects with minimal vertical intermaxillary space.

BACKGROUND: Prosthodontics are often performed to treat patients with malocclusion and dentition defects. However, single prosthodontics cannot properly correct the disharmony of teeth, dental arch and other parts affected by malocclusion, and some patients may have difficulty in recovering the occlusal function due to poor prosthodontics. OBJECTIVE: This study aims to investigate the effect of orthodontics combined with fibre-reinforced composite resin-bonded fixed partial denture (FRC-RBFPD) on anterior dentition defects with minimal vertical intermaxillary space. METHODS: Sixty-two patients with anterior dentition defects with minimal vertical mandibular space admitted to our hospital between March 2021 and May 2023 were enrolled in this study. The participants were divided into the observation group (31 cases) and the control group (31 cases), according to the treatment plan. The control group was treated with traditional therapy, and the observation group was treated with orthodontic combined FRC-RBFPD therapy. Periodontal conditions (periodontal pocket depth [PD], the plaque index [PLI], the sulcus bleeding index [SBI]), levels of inflammatory factors in gingival crevicular fluid (high mobility group box 1 [HMGB1]), myeloid cell triggering receptor-1 (TREM-1), monocyte chemoattractant protein-1 (MCP-1), pain (visual analogue scale [VAS]), the clinical response rate and the incidence of adverse reactions were collected and compared. RESULTS: After 1, 3, 5 and 9 months following treatment, the scores of the PD, PLI, SBI, HMGB1, VAS, TREM-1 and MCP-1 in the observation group were found to be lower than those in the control group (FPD treatment= 352.532, FPLI score treatment= 112.341, FSBI score treatment= 79.479, FVAS score treatment= 96.132, FHMGB1 treatment= 52.532, FTREM-1 score treatment= 64.593, FMCP-1 score treatment= 53.582, and they were all statistically significant P< 0.05). There was a statistically significant difference in the response rate between the two groups (97.77% vs. 80.65%, χ2= 4.026, P= 0.045). No statistically significant difference was observed in the incidence of adverse reactions between the two groups (6.45% vs. 16.13%, χ2= 1.449, P= 0.229). CONCLUSION: Orthodontics combined with FRC-RBFPD shows an ideal restorative effect on patients with anterior dentition defects and minimal vertical intermaxillary space.

All Resistive Pressure-Temperature Bimodal Sensing E-Skin for Object Classification.

Electronic skin (E-skin) with multimodal sensing ability demonstrates huge prospects in object classification by intelligent robots. However, realizing the object classification capability of E-skin faces severe challenges in multiple types of output signals. Herein, a hierarchical pressure-temperature bimodal sensing E-skin based on all resistive output signals is developed for accurate object classification, which consists of laser-induced graphene/silicone rubber (LIG/SR) pressure sensing layer and NiO temperature sensing layer. The highly conductive LIG is employed as pressure-sensitive material as well as the interdigital electrode. Benefiting from high conductivity of LIG, pressure perception exhibits an excellent sensitivity of -34.15 kPa-1 . Meanwhile, a high temperature coefficient of resistance of -3.84%°C-1 is obtained in the range of 24-40 °C. More importantly, based on only electrical resistance as the output signal, the bimodal sensing E-skin with negligible crosstalk can simultaneously achieve pressure and temperature perception. Furthermore, a smart glove based on this E-skin enables classifying various objects with different shapes, sizes, and surface temperatures, which achieves over 92% accuracy under assistance of deep learning. Consequently, the hierarchical pressure-temperature bimodal sensing E-skin demonstrates potential application in human-machine interfaces, intelligent robots, and smart prosthetics.

Thermal Deformation Behavior and Dynamic Softening Mechanisms of Zn-2.0Cu-0.15Ti Alloy: An Investigation of Hot Processing Conditions and Flow Stress Behavior.

Through isothermal hot compression experiments at various strain rates and temperatures, the thermal deformation behavior of Zn-2.0Cu-0.15Ti alloy is investigated. The Arrhenius-type model is utilized to forecast flow stress behavior. Results show that the Arrhenius-type model accurately reflects the flow behavior in the entire processing region. The dynamic material model (DMM) reveals that the optimal processing region for the hot processing of Zn-2.0Cu-0.15Ti alloy has a maximum efficiency of about 35%, in the temperatures range (493-543 K) and a strain rate range (0.01-0.1 s-1). Microstructure analysis demonstrates that the primary dynamic softening mechanism of Zn-2.0Cu-0.15Ti alloy after hot compression is significantly influenced by temperature and strain rate. At low temperature (423 K) and low strain rate (0.1 s-1), the interaction of dislocations is the primary mechanism for the softening Zn-2.0Cu-0.15Ti alloys. At a strain rate of 1 s-1, the primary mechanism changes to continuous dynamic recrystallization (CDRX). Discontinuous dynamic recrystallization (DDRX) occurs when Zn-2.0Cu-0.15Ti alloy is deformed under the conditions of 523 K/0.1 s-1, while twinning dynamic recrystallization (TDRX) and CDRX are observed when the strain rate is 10 s-1.

Ultrastretchable High-Conductivity MXene-Based Organohydrogels for Human Health Monitoring and Machine-Learning-Assisted Recognition.

Conductive hydrogels as promising candidates of wearable electronics have attracted considerable interest in health monitoring, multifunctional electronic skins, and human-machine interfaces. However, to simultaneously achieve excellent electrical properties, superior stretchability, and a low detection threshold of conductive hydrogels remains an extreme challenge. Herein, an ultrastretchable high-conductivity MXene-based organohydrogel (M-OH) is developed for human health monitoring and machine-learning-assisted object recognition, which is fabricated based on a Ti3C2Tx MXene/lithium salt (LS)/poly(acrylamide) (PAM)/poly(vinyl alcohol) (PVA) hydrogel through a facile immersion strategy in a glycerol/water binary solvent. The fabricated M-OH demonstrates remarkable stretchability (2000%) and high conductivity (4.5 S/m) due to the strong interaction between MXene and the dual-network PVA/PAM hydrogel matrix and the incorporation between MXene and LS, respectively. Meanwhile, M-OH as a wearable sensor enables human health monitoring with high sensitivity and a low detection limit (12 Pa). Furthermore, based on pressure mapping image recognition technology, an 8 × 8 pixelated M-OH-based sensing array can accurately identify different objects with a high accuracy of 97.54% under the assistance of a deep learning neural network (DNN). This work demonstrates excellent comprehensive performances of the ultrastretchable high-conductive M-OH in health monitoring and object recognition, which would further explore extensive potential application prospects in personal healthcare, human-machine interfaces, and artificial intelligence.

"Perfect" designer chromosome V and behavior of a ring derivative.

Perfect matching of an assembled physical sequence to a specified designed sequence is crucial to verify design principles in genome synthesis. We designed and de novo synthesized 536,024-base pair chromosome synV in the "Build-A-Genome China" course. We corrected an initial isolate of synV to perfectly match the designed sequence using integrative cotransformation and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated editing in 22 steps; synV strains exhibit high fitness under a variety of culture conditions, compared with that of wild-type V strains. A ring synV derivative was constructed, which is fully functional in Saccharomyces cerevisiae under all conditions tested and exhibits lower spore viability during meiosis. Ring synV chromosome can extends Sc2.0 design principles and provides a model with which to study genomic rearrangement, ring chromosome evolution, and human ring chromosome disorders.