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A refined bidirectional A $^{\ast }$ algorithm proposes to address the issue of imprecise path planning for unmanned mining vehicles navigating through complex open-pit mining terrains. To ensure the smooth traversal of these vehicles, a gradient factor incorporates into the cost function to circumvent obstacles along the pathway. Additionally, a weighted coefficient introduces into the heuristic function to fine-tune the combination of Euclidean and Manhattan distances, enhancing the accuracy of path distance measurement and ultimately leading to an optimal path. The enhanced algorithm adeptly simultaneously explores from both the starting and end points, significantly reducing search time and improving path planning efficiency. Utilizing the established map of the mining environment, an experiment for unmanned mining vehicle path planning devises, and a simulation test of the global path planning algorithm conducts using the MATLAB platform. The experimental results demonstrate that the refined bidirectional A $^{\ast }$ algorithm exhibits accelerated search speed and superior path planning effectiveness.

Mingxin Cao,1,* Enyu Shi,1,* Hanping Wang,1 Lujia Mao,1 Qiqi Wu,1 Xinming Li,2 Yanjie Liang,1 Xiaoying Yang,3 Yinsong Wang,1,3 Changyi Li1 1School and Hospital of Stomatology, Tianjin Medical University, Tianjin, 300070, People’s Republic of China; 2Tianjin Stomatological Hospital, School of Medicine, Nankai University, Tianjin Key Laboratory of Oral and Maxillofacial Function Reconstruction, Tianjin, 300041, People’s Republic of China; 3Tianjin Key Laboratory of Technologies Enabling Development of Clinical Therapeutics and Diagnostics, School of Pharmacy, Tianjin Medical University, Tianjin, 300070, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yinsong Wang; Changyi Li, Email wangyinsong@tmu.edu.cn; lichangyi@tmu.edu.cnAbstract: Oral squamous cell carcinoma (OSCC) is the most common type of malignant tumor in the head and neck, with a poor prognosis mainly due to recurrence and metastasis. Classical treatment modalities for OSCC like surgery and radiotherapy have difficulties in dealing with metastatic tumors, and together with chemotherapy, they have major problems related to non-specific cell death. Molecular targeted therapies offer solutions to these problems through not only potentially maximizing the anticancer efficacy but also minimizing the treatment-related toxicity. Among them, the receptor-mediated targeted delivery of anticancer therapeutics remains the most promising one. As OSCC exhibits a heterogeneous nature, selecting the appropriate receptors for targeting is the prerequisite. Hence, we reviewed the OSCC-associated receptors previously used in targeted therapy, focused on their biochemical characteristics and expression patterns, and discussed the application potential in personalized targeted therapy of OSCC. We hope that a better comprehension of this subject will help to provide the fundamental information for OSCC personalized therapeutic planning.Keywords: oral squamous cell carcinoma, receptors, targeted therapy, active targeting, drug delivery

Donghui Liu,1,2 Xuyao Wang,3 Long Li,4 Qingxin Jiang,5 Xiaoxue Li,2 Menglin Liu,2 Wenxin Wang,2 Enhong Shi,2 Chenyao Zhang,2 Yinghui Wang,2 Yan Zhang,1,* Liru Wang1,2,* 1School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang Province, People’s Republic of China; 2Department of Oncology, Heilongjiang Provincial Hospital, Harbin, Heilongjiang Province, People’s Republic of China; 3Department of Pharmacy, Harbin Second Hospital, Harbin, Heilongjiang Province, People’s Republic of China; 4Department of General Surgery, First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, People’s Republic of China; 5Department of General Surgery, Harbin 242 Hospital of Genertec Medical, Harbin, Heilongjiang Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yan ZhangSchool of Life Science and Technology, Harbin Institute of Technology, No. 92 Xidazhi Street, Nangang District, Harbin, Heilongjiang, People’s Republic of ChinaTel +86 13936253249Email ldhknight1@126.comLiru WangDepartment of Oncology, Heilongjiang Provincial Hospital, No. 82 Zhongshan Road, Xiangfang District, Harbin, Heilongjiang, People’s Republic of China, Tel +86 13633609001Email wangliru106@163.comBackground: The use of machine learning (ML) in predicting disease prognosis has increased, and scientists have adopted different methods for cancer classification to optimize the early screening of cancer to determine its prognosis in advance. In this study, we aimed at improving the prediction accuracy of gastric cancer in postoperation patients by constructing a highly effective prognostic model.Methods: The study used postoperative gastric cancer patient data from the SEER database. The LASSO regression method was used to construct a clinical prognostic model, and four machine learning methods (Boruta algorithm, neural network, support vector machine, and random forest) were used to screen and recombine the features to construct an ML prognostic model. Clinical information on 955 postoperative gastric cancer patients collected from the Affiliated Tumor Hospital of Harbin Medical University was used for external verification.Results: Experimental results showed that the AUC values of 1, 3 and 5 years in the training set, validation set and external validation set of clinical prognosis model and ML prognosis model directly established by LASSO regression are all around 0.8.Conclusion: Both models can accurately evaluate the prognosis of postoperative patients with gastric cancer, which may be helpful for accurate and personalized treatment of postoperative patients with gastric cancer.Keywords: machine learning, gastric cancer, prognosis, Boruta, ElasticNet, SVM, random forest

Bo Chen,1 Yapeng You,1 Aobo Ma,1 Yunjia Song,1 Jian Jiao,2 Liting Song,1 Enyu Shi,1 Xue Zhong,1 Ying Li,1 Changyi Li1 1School of Dentistry, Stomatological Hospital, Tianjin Medical University, Tianjin, People’s Republic of China; 2Department of Stomatology, Tianjin Medical University General Hospital, Tianjin, People’s Republic of ChinaCorrespondence: Ying Li; Changyi LiStomatological Hospital, Tianjin Medical University, No. 12 of Observatory Road, Heping District, Tianjin 300070, People’s Republic of ChinaTel +86-22-23332034; +86-22-23332003Fax +86-22-23332122Email yingli@tmu.edu.cn; lichangyi@tmu.edu.cnPurpose: Zinc (Zn), an essential trace element in the body, has stable chemical properties, excellent osteogenic ability and moderate immunomodulatory property. In the present study, a Zn-incorporated TiO2 nanotube (TNT) was fabricated on titanium (Ti) implant material. We aimed to evaluate the influence of nano-scale topography and Zn on behaviors of murine RAW 264.7 macrophages. Moreover, the effects of Zn-incorporated TNT surface-regulated macrophages on the behaviors and osteogenic differentiation of murine MC3T3-E1 osteoblasts were also investigated.Methods: TNT coatings were firstly fabricated on a pure Ti surface using anodic oxidation, and then nano-scale Zn particles were incorporated onto TNTs by the hydrothermal method. Surface topography, chemical composition, roughness, hydrophilicity, Zn release pattern and protein adsorption ability of the Zn-incorporated TiO2 nanotube surface were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), surface profiler, contact angle test, Zn release test and protein adsorption test. The cell behaviors and both pro-inflammatory (M1) and pro-regenerative (M2) marker gene and protein levels in macrophages cultured on Zn-incorporated TNTs surfaces with different TNT diameters were detected. The supernatants of macrophages were extracted and preserved as conditioned medium (CM). Furthermore, the behaviors and osteogenic properties of osteoblasts cultured in CM on various surfaces were evaluated.Results: The release profile of Zn on Zn-incorporated TNT surfaces revealed a controlled release pattern. Macrophages cultured on Zn-incorporated TNT surfaces displayed enhanced gene and protein expression of M2 markers, and M1 markers were moderately inhibited, compared with the LPS group (the inflammation model). When cultured in CM, osteoblasts cultured on Zn-incorporated TNTs showed strengthened cell proliferation, adhesion, osteogenesis-related gene expression, alkaline phosphatase activity and extracellular mineralization, compared with their TNT counterparts and the Ti group.Conclusion: This study suggests that the application of Zn-incorporated TNT surfaces may establish an osteogenic microenvironment and accelerate bone formation. It provided a promising strategy of Ti surface modification for a better applicable prospect.Keywords: titanium surface modification, TiO2 nanotube, zinc nanoparticles, immunomodulatory function, osseointegration

In this work, a finite size acoustic vector sensor (AVS) array is designed and its performance is theoretically and experimentally studied. The two-dimensional AVS array is comprised of five vector sensors and configured as a cross, and the array carrier is a cylindrically symmetric structure. Theoretical analysis and simulation indicate that the proposed method considering structure scattering can widen the working bandwidth. Furthermore, the utilization of vector sensor enables a significant white noise gain improvement at low frequencies, which makes the array more robust and easier to realize. Experiments have been done to study the array performance from several aspects including sensor noise characteristics, the beampattern, the direction-of-arrival (DOA) estimation ability and the array gain. From the change of the sensor directivity patterns or the amplitude distortion of the noise field, we can clearly observe the scattering field intensity. Moreover, it shows that the influence of the structure scattering on the tangential component of the vector field is symmetric, while that of the radial component is asymmetric. Experimental results also demonstrate that, with the proposed method, the 2nd and the 3rd order beamformers can be obtained which could be further used for the estimation of target DOA. In addition, an array gain of at least 6 dB is obtained capable of detection of weak signals. Our results indicate that the proposed array with a physical size less than one meter, although affected by nearby scatterers, can effectively break the Rayleigh limit and realize the remote detection in low-frequency regime.