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Background Few large-sample studies in China have focused on the early survival of dental implants. The present study aimed to report the early survival rates of implants and determine the related influencing factors. Methods All patients receiving dental implants at our institution between 2006 and 2017 were included. The endpoint of the study was early survival rates of implants, according to gender, age, maxilla/mandible, dental position, bone augmentation, bone augmentation category, immediate implant, submerged implant category, implant diameter, implant length, implant torque, and other related factors. Initially, SPSS22.0 was used for statistical analysis. The Chi-square test was used to screen all factors, and those with p  < 0.05 were further introduced into a multiple logistic regression model to illustrate the risk factors for early survival rates of implants. Results In this study, we included 1078 cases (601 males and 477 females) with 2053 implants. After implantation, 1974 implants were retained, and the early survival rate was 96.15%. Patients aged 30–60 years (OR  2.392), with Class I bone quality (OR  3.689), bone augmentation (OR  1.742), immediate implantation (OR  3.509), and implant length < 10 mm (OR  2.972), were said to possess risk factors conducive to early survival rates. Conclusions The early survival rate of implants in our cohort exceeded 96%, with risk factors including age, tooth position, bone quality, implant length, bone augmentation surgery, and immediate implantation. When the above factors coexist, implant placement should be treated carefully.

Purpose Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles. Methods Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1. Results QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71–100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds. Conclusions The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles.

Anagrelide (ANA) is a phosphodiesterase 3A (PDE3A) inhibitor, commonly prescribed for essential thrombocythemia. It also functions as a molecular glue, inducing complex formation between PDE3A and Schlafen 12. This association either triggers apoptosis or inhibits proliferation in tumor cells, supporting its use in cancer therapy. Conventionally administered orally, ANA undergoes rapid metabolism and elimination, resulting in a short drug exposure time at the site of action. Here, we explored the pharmacokinetic profile of a subcutaneously (SC) injected ANA formulation in Sprague-Dawley rats by quantifying plasma ANA and metabolite concentrations using liquid-chromatography-tandem mass spectrometry. We further evaluated the tumor regression efficacy of orally and SC administered ANA in a patient-derived gastrointestinal stromal xenograft mouse model - UZLX-GIST2B - characterized by a exon 9 driver mutation. The SC ANA exhibited extended-release plasma concentration-time profiles compared to intravenous and oral administrations. After a single administration in rats, plasma concentrations of ANA were detected up to 56 days later, and ANA metabolites up to 30 days later. The SC formulation also significantly reduced tumor volumes and demonstrated dose-dependent histological responses, nearly eradicating tumor tissue in 11 days with the highest dose. These findings suggest that the SC slow-release formulation maintains stable drug concentrations during treatment, potentially improving therapeutic efficacy at the target site.

Lane change operation is widely used in numerous traffic scenarios; to minimize lane change time and avoid collisions with other vehicles required by intelligent vehicles, an optimal lane change motion is proposed for the shortest time free lane change and emergency obstacle avoidance lane change. First, two optimal lane change motion models are constructed based on a 3-degree-of-freedom dynamical vehicle model. Because of uncertain parameters in the vehicle model, the optimal lane change motion problem is an uncertain optimal control problem. Subsequently, targeted at nonlinearity and uncertain parameters, an extended adaptive pseudo-spectral method is also presented on the basis of approximate and numerical integration of parameter space. Finally, solving the optimal lane change motion problem, optimization results, control results based on the nonlinear model predictive control algorithm, and experimental results are shown under circumstances of certain vehicle mass and uncertain vehicle mass. As for uncertain parameters, optimization results are featured with robustness. Thus, uncertain parameters need not be measured, and optimization calculation need not be carried out in real time. The algorithm put forward here could be adopted to solve an uncertain optimal control problem. The optimal lane change motion can be extended to apply in more complex operations like merging, double-lane change, entering/exiting highways, or overtaking another vehicle.

Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

Chinese herbs Desmodium styracifolium (Ds) and Pyrrosiae petiolosa (Pp) have been widely used to treat urolithiasis with few side effects in traditional Chinese medicine (TCM). In vitro crystallization study has confirmed their prophylaxis of Calcium oxalate (CaO x ) stones formation. However, little is known on their possible mechanisms in vivo. In the present study, we proposed to systematically evaluate their antilithic effects and clarify the underlying mechanism of Ds and Pp using a rat nephrolithiasis model and administering the aqueous extracts. Adult male Wistar rats were fed with 5% ammonium oxalate (AmO x ) forage to induce nephrolithiasis. After 1 week, the rats were randomly divided into eight groups, and given low, medium, and high dose of each herb treatments (275, 550 and 1,100 mg/kg for Ds and 150, 300 and 600 mg/kg for Pp) by gavage for 3 weeks. In contrast to urolithic rats, urinary oxalate significantly reduced, and urinary calcium increased in medium and high dose Ds groups. Few depositions were observed in kidney with slight dilation of tubules and inflammatory infiltration. Osteopontin (OPN), nitric oxide (NO), and malondialdehyde (MDA) levels significantly decreased, but Superoxide dismutase (SOD) activities were enhanced in kidneys. In high dose Pp group, crystals were found in the dilation of tubules with slight inflammatory infiltration. Partial serum and urinary variables returned to the normal range. In conclusion, medium and high dose Ds has beneficial effect in preventing CaO x stone formation by rising urinary Citrate excretion, decreasing urinary calcium, diuresis, and antioxidative effects. Although high dose Pp has relatively weak prophylaxis, it indicates significant anti-inflammatory and antioxidant effects.

Multipotent mesenchymal stem cell (MSC) therapies are being tested clinically for a variety of disorders. However, despite the remarkable clinical advancements in this field, most applications still use traditional culture media containing fetal bovine serum. Platelet-rich plasma (PRP) appears as a novel application for tissue engineering and its effect on bone healing is thought to be mainly dependent on the proliferation promoting function, with the molecular mechanisms largely unknown. In this study, mouse osteogenic progenitor mesenchymal stem cells (MSCs) were cultured in PRP or washed platelet (WPLT)-treated wells or in untreated wells, and analyzed on cycloxygenase 2 (COX2) expression (qRT-PCR), cell growth (MTT assay) and cell differentiation (alkaline phosphatase activity). The results showed that PRP and WPLT stimulated cell growth similarly in the first 6 days, together with the steady induction of COX2 and PGE2. 10 μmol/l celecoxib (an inhibitor of COX2) significantly inhibited the pro-proliferation effects. Interestingly, WPLT had stronger effects than PRP in proliferation at the later time points (6-9 days). ALP activity assay and collagen 1a expression revealed PRP had a mild but statistically significant pro-differentiation effect, while no obvious effects observed in WLPT group. In summary, PRP stimulates initial growth of MSCs in a COX2 partially dependent manner and the less obvious osteogenic differentiation promoting effects of WPLT strongly indicates WPLT rather than the PRP should be the optional choice for expanding MSCs in vitro for clinical use.

In this paper, the mean square asymptotic stability of stochastic Markovian jump neural networks with different time scales and randomly occurred nonlinearities is investigated. In terms of linear matrix inequality (LMI) approach and delay-partitioning projection technique, delay-dependent stability criteria are derived for the considered neural networks for cases with or without the information of the delay rates via new Lyapunov-Krasovskii functionals. We also obtain that the thinner the delay is partitioned, the more obviously the conservatism can be reduced. An example with simulation results is given to show the effectiveness of the proposed approach.

To shorten design period and reduce development costs, computer modeling & simulation is important for HEV design and development. In this paper, real-time simulation for a Series Hybrid Electric Vehicle (SHEV) is made to test its fuzzy logic control strategy based on dSPACE-DS1103 development kits. The whole real-time simulation schematic is designed and the vehicle forward-facing simulation model is set up. Driver behavior is simulated by two potentiometers and introduced into the system to realize close-loop control. A real-time monitoring interface is also developed to observe the experiment results. Experiment results show that the real-time simulation platform works well and the SHEV fuzzy logic control strategy is effective.