Mapping knowledge of the stem cell in traumatic brain injury: a bibliometric and visualized analysis

BackgroundTraumatic brain injury (TBI) is a brain function injury caused by external mechanical injury. Primary and secondary injuries cause neurological deficits that mature brain tissue cannot repair itself. Stem cells can self-renewal and differentiate, the research of stem cells in the pathogenesis and treatment of TBI has made significant progress in recent years. However, numerous articles must be summarized to analyze hot spots and predict trends. This study aims to provide a panorama of knowledge and research hotspots through bibliometrics.MethodWe searched in the Web of Science Core Collection (WoSCC) database to identify articles pertaining to TBI and stem cells published between 2000 and 2022. Visualization knowledge maps, including co-authorship, co-citation, and co-occurrence analysis were generated by VOSviewer, CiteSpace, and the R package “bibliometrix.”ResultsWe retrieved a total of 459 articles from 45 countries. The United States and China contributed the majority of publications. The number of publications related to TBI and stem cells is increasing yearly. Tianjin Medical University was the most prolific institution, and Professor Charles S. Cox, Jr. from the University of Texas Health Science Center at Houston was the most influential author. The Journal of Neurotrauma has published the most research articles on TBI and stem cells. Based on the burst references, “immunomodulation,” “TBI,” and “cellular therapy” have been regarded as research hotspots in the field. The keywords co-occurrence analysis revealed that “exosomes,” “neuroinflammation,” and “microglia” were essential research directions in the future.ConclusionResearch on TBI and stem cells has shown a rapid growth trend in recent years. Existing studies mainly focus on the activation mechanism of endogenous neural stem cells and how to make exogenous stem cell therapy more effective. The combination with bioengineering technology is the trend in this field. Topics related to exosomes and immune regulation may be the future focus of TBI and stem cell research

Uni-GBSA: An Automatic Workflow to Perform MM/GB(PB)SA Calculations for Virtual Screening

Evaluating the binding free energy of the protein-ligand complex is one of the most important tasks in drug design. Compared to methods like free energy perturbation (FEP) and thermodynamic integration (TI) which are accurate but resource expensive, and docking scoring functions which are less reliable but efficient, molecular mechanics/Generalized-Born (Poisson–Boltzmann) surface area (MM/GB(PB)SA), which balance accuracy and efficiency, is a good choice for evaluating binding free energy in virtual screening. There are several open-source tools for performing MM/GB(PB)SA calculations, but they are not easy to use, especially when processing a large number of molecules. Here we introduce Uni-GBSA, an automatic workflow to perform MM/GB(PB)SA calculations from force field building, structure optimization to free energy calculation. For evaluating several molecules against one protein target in virtual screening, Uni-GBSA offers a batch mode, eliminating many repeated calculations, to process the calculation for multi-molecules simultaneously and efficiently. Experiments show that Uni-GBSA with carefully designed default settings of parameters and workflow can obtain reliable binding free energy evaluation. Uni-GBSA software, including source code, is free and available at https://github.com/dptech-corp/Uni-GBSA

Novel affine‐invariant curve descriptor for curve matching and occluded object recognition

The authors present a new approach for affine distorted planar curve matching and exploit it for occluded object recognition. There are two main contributions in the study: First, a novel affine‐invariant curve descriptor (AICD) based on a new‐defined affine‐invariant signature and its unsigned sum is proposed to represent the local shape of a curve with high distinctiveness. Second, a part‐to‐part curve matching algorithm is developed by combining AICD with a curve segmentation strategy based on inflexion points, which can be applied to object recognition under affine distortions and partial occlusions. Experimental results demonstrate that the proposed method exhibits effectiveness in occluded object recognition better than the state‐of‐the‐art partial curve matching methods

Multiobjective Optimization of Tool Geometric Parameters Using Genetic Algorithm

Tool geometric parameters have a huge impact on tool wear. Up to now, there are only a few researches on tool geometric parameters and optimization, and the single objective function of parameter optimization used by researchers during high-speed machining (HSM) mainly is the minimum cutting force. However, the elevated cutting temperature also greatly affects tool wear due to the numerous cutting heat generation. Thus, to reduce tool wear, it is the most fundamental approach to taking into account the comprehensive control of the cutting force and cutting temperature because they are the two most important physical quantities in metal cutting processes. This work proposes a new optimization idea of the cutting-tool’s multi geometric parameters (three main parameters: rake angle, clearance angle, and cutting edge radius) with two objective functions (the cutting force and the temperature). Based on the response surface method (RSM), we have established the modified functional relation models of the influence of tool geometric parameters on the cutting force and temperature according to the finite element simulation results in high-speed cutting of Ti6Al4V. Then the models are solved by using a genetic algorithm, and the optimal tool geometric parameters values that can concurrently control the two objectives in their minimum values are obtained. The advantages lie in the strategy of the separate models of the cutting force and cutting temperature owing to their different dimensions and the solution of the models through giving the cutting force and cutting temperature different weight coefficients. The optimal results are verified by experiments, which shows that the optimal tool geometric parameters are very effective and vital for ensuring both the cutting force and the cutting temperature not too high. This work is of great significance to the cutting tool design theory and its manufacturing for reducing tool wear

Hierarchically distributed microstructure design of haptic sensors for personalized fingertip mechanosensational manipulation

Strategies to help reconstruct and restore haptic perception are essential for control of prosthetic limbs, clinical rehabilitation evaluation, and robotic manipulation. Here, we propose a hierarchically distributed microstructure based on electric contact theory to develop haptic sensors. The sensing range of the haptic sensor based on a hierarchically distributed microstructure is greatly enhanced by ten times relative to the one of the haptic sensor based on a common structure. Furthermore, variation in the response signal of the haptic sensor is up to five orders of magnitude and scales with the external pressure between 0.5 and 100 kPa, which is close to the range that a finger normally feels. Personalized manipulation of electrical appliances, a three-dimensional password matrix, and gesture control of a data glove demonstrate the fascinating potential of the haptic sensors for human–machine interactive systems, force-enhanced security systems, and wearable electrical systems.NRF (Natl Research Foundation, S’pore)Accepted versio

High Genetic Diversity and Structured Populations of the Oriental Fruit Moth in Its Range of Origin

The oriental fruit moth Grapholita ( = Cydia) molesta is a key fruit pest globally. Despite its economic importance, little is known about its population genetics in its putative native range that includes China. We used five polymorphic microsatellite loci and two mitochondrial gene sequences to characterize the population genetic diversity and genetic structure of G. molesta from nine sublocations in three regions of a major fruit growing area of China. Larval samples were collected throughout the season from peach, and in late season, after host switch by the moth to pome fruit, also from apple and pear. We found high numbers of microsatellite alleles and mitochondrial DNA haplotypes in all regions, together with a high number of private alleles and of haplotypes at all sublocations, providing strong evidence that the sampled area belongs to the origin of this species. Samples collected from peach at all sublocations were geographically structured, and a significant albeit weak pattern of isolation-by-distance was found among populations, likely reflecting the low flight capacity of this moth. Interestingly, populations sampled from apple and pear in the late season showed a structure differing from that of populations sampled from peach throughout the season, indicating a selective host switch of a certain part of the population only. The recently detected various olfactory genotypes in G. molesta may underly this selective host switch. These genetic data yield, for the first time, an understanding of population dynamics of G. molesta in its native range, and of a selective host switch from peach to pome fruit, which may have a broad applicability to other global fruit production areas for designing suitable pest management strategies.ISSN:1932-620

Solubility of H2S under Haloalkaliphilic Conditions: Experimental Measurement and Modeling with the Electrolyte NRTL Equation

Haloalkaliphilic biological desulfurization has been recognized as a promising technology due to its remarkable economy and good performance. The process removes H2S from gases using aqueous solutions of alkali carbonates. In this study, the solubility of H2S in an aqueous Na2CO3-NaHCO3 solution was first experimentally measured by a static analysis method at an operating pressure and temperature of biological desulfurization. An accurate and comprehensive thermodynamic model was developed based on the electrolyte nonrandom two-liquid model for the solubility of H2S in aqueous solutions of alkali carbonates. The solubility of H2S in pure water is predicted and compared favorably to previous literature, with the temperature varying from 298.16 to 377.45 K and pressure up to 39.6 bar. The average deviation of the model predictions compared to all experimental data is 0.95% for the solubility of H2S in an aqueous Na2CO3-NaHCO3 solution. This study will provide a valuable reference for the process design, simulation, and optimization of haloalkaliphilic biological desulfurization in the future

Sclerosing rhabdomyosarcoma presenting on the knee-joint

Sclerosing rhabdomyosarcoma is a rare pathological diagnosis that easily misdiagnosed. The majority of cases reported the tumor increased rapidly in size and the Ki-67 proliferation index ranged from 10% to 60%. Here, we report the first case of the tumor increased very slowly for 20 years and the Ki-67 proliferation index was lower than 2%, and discuss its histological features and immunohistochemical reactivity with Desmin and Ki-67 and so on

Nano-immobilization of PETase enzyme for enhanced polyethylene terephthalate biodegradation

PET hydmlase (PETase), discovered in Ideonella sakaiensis, is a promising agent for the biodegradation of polyethylene terephthalate (PET) capable of PET decomposition under mild reaction conditions with limited stability and productivity. Here, the immobilization of His-tagged PETase was achieved by synthesizing enzyme-inorganic nanoflowers, PETase@Co-3(PO4)(2), which was designed based on the principle of biomimetic mineralization. Immobilization of PETase onto nanostructured Co-3(PO4)(2) enjoys high enzyme loading and low mass transfer inhibition due to large specific surface area, high movement speed, and large surface curvature caused by small particle size. The nano-effect of inorganic carriers materialize the 10 degrees C optimum temperature swelling of the immobilized PETase with enhanced pH tolerance (6.0-10.0) than the free counterpart. The long-duration reaction showed that the productivity of terephthalic acid (TPA) was 3.5 times higher than that of the free enzyme. PETase@Co-3(PO4)(2) still retained 75% of the initial activity after 12 days compared with the free enzymes, which showed almost no activity. The excellent and stable catalytic performance of PETase@Co-3(PO4)( )2 with low cost demonstrates the synthetical usefulness of immobilization via biomimetic mineralization in the enzyme utilization in industrial PET depolymerization