Impact of a staggered scaffold structure on the mechanical properties and cell response in bone tissue engineering

The primary goal of bone tissue engineering is to fabricate scaffolds that can provide a microenvironment similar to that of natural bone. Therefore, various scaffolds have been designed to replicate the bone structure. Although most tissues exhibit complicated structures, their basic structural unit includes stiff platelets arranged in a staggered micro-array. Therefore, many researchers have designed scaffolds with staggered patterns. However, relatively few studies have comprehensively analyzed this type of scaffold. In this review, we have analyzed scientific research pertaining to staggered scaffold designs and summarized their effects on the physical and biological properties of scaffolds. Compression tests or finite element analysis are typically used to evaluate the mechanical properties of scaffolds, and most studies have performed experiments in cell cultures. Staggered scaffolds improve mechanical strength and are beneficial for cell attachment, proliferation, and differentiation in comparison with conventional designs. However, very few have been studied in vivo experiments. Additionally, studies on the effect of staggered structures on angiogenesis or bone regeneration in vivo, particularly in large animals, are required. Currently, with the prevalence of artificial intelligence (AI)-based technologies, highly optimized models can be developed, resulting in better discoveries. In the future, AI can be used to deepen our understanding on the staggered structure, promoting its use in clinical applications.publishedVersio

Tetragonal Mexican-Hat Dispersion and Switchable Half-Metal State with Multiple Anisotropic Weyl Fermions in Penta-Graphene

In past decades, the ever-expanding library of 2D carbon allotropes has yielded a broad range of exotic properties for the future carbon-based electronics. However, the known allotropes are all intrinsic nonmagnetic due to the paired valence electrons configuration. Based on the reported 2D carbon structure database and first-principles calculations, herein we demonstrate that inherent ferromagnetism can be obtained in the prominent allotrope, penta-graphene, which has an unique Mexican-hat valence band edge, giving rise to van Hove singularities and electronic instability. Induced by modest hole-doping, being achievable in electrolyte gate, the semiconducting pentagraphene can transform into different ferromagnetic half-metals with room temperature stability and switchable spin directions. In particular, multiple anisotropic Weyl states, including type-I and type-II Weyl cones and hybrid quasi Weyl nodal loop, can be found in a sizable energy window of spin-down half-metal under proper strains. These findings not only identify a promising carbon allotrope to obtain the inherent magnetism for carbon-based spintronic devices, but highlight the possibility to realize different Weyl states by combining the electronic and mechanical means as well

Untargeted metabolomics of the cochleae from two laryngeally echolocating bats

High-frequency hearing is regarded as one of the most functionally important traits in laryngeally echolocating bats. Abundant candidate hearing-related genes have been identified to be the important genetic bases underlying high-frequency hearing for laryngeally echolocating bats, however, extensive metabolites presented in the cochleae have not been studied. In this study, we identified 4,717 annotated metabolites in the cochleae of two typical laryngeally echolocating bats using the liquid chromatography–mass spectroscopy technology, metabolites classified as amino acids, peptides, and fatty acid esters were identified as the most abundant in the cochleae of these two echolocating bat species, Rhinolophus sinicus and Vespertilio sinensis. Furthermore, 357 metabolites were identified as significant differentially accumulated (adjusted p-value <0.05) in the cochleae of these two bat species with distinct echolocating dominant frequencies. Downstream KEGG enrichment analyses indicated that multiple biological processes, including signaling pathways, nervous system, and metabolic process, were putatively different in the cochleae of R. sinicus and V. sinensis. For the first time, this study investigated the extensive metabolites and associated biological pathways in the cochleae of two laryngeal echolocating bats and expanded our knowledge of the metabolic molecular bases underlying high-frequency hearing in the cochleae of echolocating bats

Impact of Grain Subsidy Reform on the Land Use of Smallholder Farms: Evidence from Huang-Huai-Hai Plain in China

Smallholder farms have played an essential role in agricultural production and food security. In order to increase farm size, the Chinese government announced a reform of the grain subsidy program in 2015. Under the reform, 20% of the aggregate input subsidy, as well as the pilot subsidy to large-scale farmers and the incremental part of the agricultural support and protection subsidy budget, were used to support increasing farm size. This study evaluated the impact of China’s grain subsidy reform on the land use of smallholder farms to investigate whether the reform achieved its goal. Based on 2063 samples obtained from the 2013–2015 Survey for Agriculture and Village Economy data in Huang-Huai-Hai Plain, we conducted a difference-in-difference model to solve the problem of missing counterfactual states in policy evaluation. Farms from Henan and Shandong were assigned to the treatment group, and farms from Hebei were assigned to the control group. The results revealed that the average treatment effect on the treated of the impact of the grain subsidy reform on the wheat-sown area was −25% (0.10 ha). Furthermore, there was heterogeneity in regard to the subsidy reform effects in different sown-area groups. The reform had the most significant impact on the smallest farmers. We also found that China’s grain subsidy reform had a significant and positive effect on the amount of outflow land area, while the impact of subsidy reform on land tenure was insignificant. Our findings suggest that while encouraging large-scale farms, it is necessary to take into account farmers’ small-scale operations and gradually promote the transformation of small-scale operations to large-scale operations. The Chinese government should strengthen the supervision of land use to achieve the goal of ensuring food security

Co-delivery of doxorubicin and hydroxychloroquine via chitosan/alginate nanoparticles for blocking autophagy and enhancing chemotherapy in breast cancer therapy

Breast cancer (BC) is the most common malignancy in women worldwide, and the standard treatment is chemotherapy or radiotherapy after surgery. In order to reduce the side effects of chemotherapy, various nanoparticles (NPs) have been discovered and synthesized, which has become a promising treatment for BC. In this study, a co-delivery nanodelivery drug system (Co-NDDS) was designed and synthesized with 2,3-dimercaptosuccinic acid (DMSA) coated Fe3O4 NPs as core encapsulated into chitosan/alginate nanoparticles (CANPs) shell, doxorubicin (DOX) and hydroxychloroquine (HCQ) as loading drugs. Smaller NPs carrying DOX (FeAC-DOX NPs) were loaded into larger NPs containing HCQ (FeAC-DOX@PC-HCQ NPs) by ionic gelation and emulsifying solvent volatilization methods. The physicochemical properties of this Co-NDDS were characterised, followed by in vitro studies of the anticancer effects and mechanisms using two different BC cell lines, MCF-7 cells and MDA-MB-231 cells. The results indicated that the Co-NDDS showcases exemplary physicochemical qualities and encapsulation capacity, facilitating accurate intracellular release through pH-sensitive attributes. Importantly, NPs can significantly increase the in vitro cytotoxicity of co-administered drugs and effectively inhibit the autophagy level of tumour cells. The Co-NDDS constructed in this study provides a promising strategy for the treatment of BC

Received Signal Strength-Based Indoor Localization Using Hierarchical Classification

Commercial interests in indoor localization have been increasing in the past decade. The success of many applications relies at least partially on indoor localization that is expected to provide reliable indoor position information. Wi-Fi received signal strength (RSS)-based indoor localization techniques have attracted extensive attentions because Wi-Fi access points (APs) are widely deployed and we can obtain the Wi-Fi RSS measurements without extra hardware cost. In this paper, we propose a hierarchical classification-based method as a new solution to the indoor localization problem. Within the developed approach, we first adopt an improved K-Means clustering algorithm to divide the area of interest into several zones and they are allowed to overlap with one another to improve the generalization capability of the following indoor positioning process. To find the localization result, the K-Nearest Neighbor (KNN) algorithm and support vector machine (SVM) with the one-versus-one strategy are employed. The proposed method is implemented on a tablet, and its performance is evaluated in real-world environments. Experiment results reveal that the proposed method offers an improvement of 1.4% to 3.2% in terms of position classification accuracy and a reduction of 10% to 22% in terms of average positioning error compared with several benchmark methods

A Stochastic Trust Region Method for Unconstrained Optimization Problems

In this paper, a stochastic trust region method is proposed to solve unconstrained minimization problems with stochastic objectives. Particularly, this method can be used to deal with nonconvex problems. At each iteration, we construct a quadratic model of the objective function. In the model, stochastic gradient is used to take the place of deterministic gradient for both the determination of descent directions and the approximation of the Hessians of the objective function. The behavior and the convergence properties of the proposed method are discussed under some reasonable conditions. Some preliminary numerical results show that our method is potentially efficient

Routing Algorithm for DTN Based on Congestion Control

Different from Internet networks, DTN has its own unique characteristics, like intermittent connectivity, low data transfer rate, high latency and limited storage and node resources. Routing technology is always the key to DTN research. In this paper, a routing protocol that is PNCMOP was proposed. It makes some improvement of Epidemic routing protocol, and also to decrease the end-to-end average delay and improve delivery ratio, especially with congestion control. Simulation results show that PNCMOP achieved a good performance. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.334