Exploring research hotspots and future directions in neural tube defects field by bibliometric and bioinformatics analysis

BackgroundNeural tube defects (NTDs) is the most common birth defect of the central nervous system (CNS) which causes the death of almost 88,000 people every year around the world. Much efforts have been made to investigate the reasons that contribute to NTD and explore new ways to for prevention. We trawl the past decade (2013–2022) published records in order to get a worldwide view about NTDs research field.Methods7,437 records about NTDs were retrieved from the Web of Science (WOS) database. Tools such as shell scripts, VOSviewer, SCImago Graphica, CiteSpace and PubTator were used for data analysis and visualization.ResultsOver the past decade, the number of publications has maintained an upward trend, except for 2022. The United States is the country with the highest number of publications and also with the closest collaboration with other countries. Baylor College of Medicine has the closest collaboration with other institutions worldwide and also was the most prolific institution. In the field of NTDs, research focuses on molecular mechanisms such as genes and signaling pathways related to folate metabolism, neurogenic diseases caused by neural tube closure disorders such as myelomeningocele and spina bifida, and prevention and treatment such as folate supplementation and surgical procedures. Most NTDs related genes are related to development, cell projection parts, and molecular binding. These genes are mainly concentrated in cancer, Wnt, MAPK, PI3K-Akt and other signaling pathways. The distribution of NTDs related SNPs on chromosomes 1, 3, 5, 11, 14, and 17 are relatively concentrated, which may be associated with high-risk of NTDs.ConclusionBibliometric analysis of the literature on NTDs field provided the current status, hotspots and future directions to some extant. Further bioinformatics analysis expanded our understanding of NTDs-related genes function and revealed some important SNP clusters and loci. This study provided some guidance for further studies. More extensive cooperation and further research are needed to overcome the ongoing challenge in pathogenesis, prevention and treatment of NTDs

Histopathological Observation of Immunized Rhesus Macaques with Plague Vaccines after Subcutaneous Infection of Yersinia pestis

In our previous study, complete protection was observed in Chinese-origin rhesus macaques immunized with SV1 (20 µg F1 and 10 µg rV270) and SV2 (200 µg F1 and 100 µg rV270) subunit vaccines and with EV76 live attenuated vaccine against subcutaneous challenge with 6×106 CFU of Y. pestis. In the present study, we investigated whether the vaccines can effectively protect immunized animals from any pathologic changes using histological and immunohistochemical techniques. In addition, the glomerular basement membranes (GBMs) of the immunized animals and control animals were checked by electron microscopy. The results show no signs of histopathological lesions in the lungs, livers, kidneys, lymph nodes, spleens and hearts of the immunized animals at Day 14 after the challenge, whereas pathological alterations were seen in the corresponding tissues of the control animals. Giemsa staining, ultrastructural examination, and immunohistochemical staining revealed bacteria in some of the organs of the control animals, whereas no bacterium was observed among the immunized animals. Ultrastructural observation revealed that no glomerular immune deposits on the GBM. These observations suggest that the vaccines can effectively protect animals from any pathologic changes and eliminate Y. pestis from the immunized animals. The control animals died from multi-organ lesions specifically caused by the Y. pestis infection. We also found that subcutaneous infection of animals with Y. pestis results in bubonic plague, followed by pneumonic and septicemic plagues. The histopathologic features of plague in rhesus macaques closely resemble those of rodent and human plagues. Thus, Chinese-origin rhesus macaques serve as useful models in studying Y. pestis pathogenesis, host response and the efficacy of new medical countermeasures against plague

Analytical solution for thermal-diffusion induced stress model and numerical simulation of battery structure during charging-discharging process

During the course of thousands of charging and discharging cycles, batteries commonly undergo capacity fade and resistance growth, known as electrode aging. This phenomenon is attributed to local inhomogeneous deformation, as well as the possibility of fracture within electrode particles due to complex multi-physical couplings. To mitigate electrode aging and slow down the rate of fading, it is crucial to develop protective designs and tailored battery management strategies. However, accurately predicting potential fracturing and conducting precise battery simulations remain open challenges. This study presents a battery aging simulation model that incorporates multiphysical couplings of heat, concentration, stress, electric, and phase fields to assess battery performance at both the structural and electrode particle levels. Initially, an analytical solution is derived to determine stress distribution at the particle level within the thermal-concentration-mechanical deformation coupling, enabling quick calculation of stress distribution. Subsequently, a comprehensive battery structure is constructed to simulate discharge performance. Furthermore, the model computes the stress levels and fracture potential of the electrodes, thereby identifying locations prone to aging. Analytical and numerical findings indicate that tensile stress on the surface of an individual electrode acts as the driving force for fracture during lithium intercalation. Moreover, electrodes in close proximity to the electrolyte generate higher heat, while those near the electrode current collector are more susceptible to fracturing

Taxi Demand Prediction Based on a Combination Forecasting Model in Hotspots

Accurate taxi demand prediction can solve the congestion problem caused by the supply-demand imbalance. However, most taxi demand studies are based on historical taxi trajectory data. In this study, we detected hotspots and proposed three methods to predict the taxi demand in hotspots. Next, we compared the predictive effect of the random forest model (RFM), ridge regression model (RRM), and combination forecasting model (CFM). Thereafter, we considered environmental and meteorological factors to predict the taxi demand in hotspots. Finally, the importance of indicators was analyzed, and the essential elements were the time, temperature, and weather factors. The results indicate that the prediction effect of CFM is better than those of RFM and RRM. The experiment obtains the relationship between taxi demand and environment and is helpful for taxi dispatching by considering additional factors, such as temperature and weather

Trip Cost Estimation of Connected Autonomous Vehicle Mixed Traffic Flow in a Two-Route Traffic Network

With the advancement of connected autonomous vehicle (CAV) technology, research on future traffic conditions after the popularization of CAVs needs to be resolved urgently. Bounded rationality of human drivers is essential for simulating traffic flow precisely, but few studies focus on the traffic flow simulation considered bounded rationality in CAV mixed traffic flow. In this study, we introduce random bounded rationality into the hybrid feedback strategy (HFS) under CAV mixed traffic flow to explore the impacts of CAV penetration rate on the trip cost of vehicles. First, we investigated the bounded rationality of drivers, and we found that it follows normal contribution. Then, we proposed HFS considering random bounded rationality and the CAV penetration rate to simulate the traffic condition. The numerical results show that the enhancement of the CAV penetration rate could reduce total trip cost. The research could help us to simulate the CAVs mixed traffic flow more precisely and realistically

Simulation of Gas Fracturing in Reservoirs Based on a Coupled Thermo-Hydro-Mechanical-Damage Model

Gas fracturing technology for enhancing rock permeability is an area with considerable potential for development. However, the complexity and variability of underground conditions mean that a variety of rock physical parameters can affect the outcome of gas fracturing, with temperature being a critical factor that cannot be overlooked. The presence of a temperature field adds further complexity to the process of gas-induced rock fracturing. To explore the effects of temperature fields on gas fracturing technology, this paper employs numerical simulation software to model the extraction of shale gas under different temperature conditions using gas fracturing techniques. The computer simulations monitor variations in the mechanical characteristics of rocks during the process of gas fracturing. This analysis is performed both prior to and following the implementation of a temperature field. The results demonstrate that gas fracturing technology significantly improves rock permeability; temperature has an impact on the effectiveness of gas fracturing, with appropriately high temperatures capable of enhancing the fracturing effect. The temperature distribution plays a crucial role in influencing the results of gas fracturing. When the temperature is low, the fracturing effect is diminished, resulting in a lower efficiency of shale gas extraction. Conversely, when the temperature is high, the fracturing effect is more pronounced, leading to a higher shale gas production efficiency. Optimal temperatures can enhance the efficacy of gas fracturing and consequently boost the efficiency of shale gas extraction. Changes in the parameters of the rock have a substantial impact on the efficiency of gas extraction, and selecting suitable rock parameters can enhance the recovery rate of shale gas. This paper, through numerical simulation, investigates the influence of temperature on gas fracturing technology, with the aim of contributing to its improved application in engineering practices

Anisotropic emission of orientation-controlled mixed-dimensional perovskites for light-emitting devices

Perovskite light-emitting diodes (PeLEDs) are attracting increasing attention owing to their impressive efficiencies and high luminance across the full visible light range. Further improvement of the external quantum efficiency (EQE) of planar PeLEDs is limited by the light out-coupling efficiency. Introducing perovskite emitters with directional emission in PeLEDs is an effective way to improve light extraction. Here, we report that it is possible to achieve directional emission in mixed-dimensional perovskites by controlling the orientation of the emissive center in the film. Multiple characterization methods suggest that our mixed-dimensional perovskite film shows highly orientated transition dipole moments (TDMs) with the horizontal ratio of over 88%, substantially higher than that of the isotropic emitters. The horizontally dominated TDMs lead to PeLEDs with exceptional high light out-coupling efficiency of over 32%, enabling a high EQE of 18.2%

Characterization of Mu-Like Yersinia Phages Exhibiting Temperature Dependent Infection

ABSTRACT Yersinia pestis is the etiological agent of plague. Marmota himalayana of the Qinghai-Tibetan plateau is the primary host of flea-borne Y. pestis. This study is the report of isolation of Mu-like bacteriophages of Y. pestis from M. himalayana. The isolation and characterization of four Mu-like phages of Y. pestis were reported, which were named as vB_YpM_3, vB_YpM_5, vB_YpM_6, and vB_YpM_23 according to their morphology. Comparative genome analysis revealed that vB_YpM_3, vB_YpM_5, vB_YpM_6, and vB_YpM_23 are phylogenetically closest to Escherichia coli phages Mu, D108 and Shigella flexneri phage SfMu. The role of LPS core structure of Y. pestis in the phages’ receptor was pinpointed. All the phages exhibit “temperature dependent infection,” which is independent of the growth temperature of the host bacteria and dependent of the temperature of phage infection. The phages lyse the host bacteria at 37°C, but enter the lysogenic cycle and become prophages in the chromosome of the host bacteria at 26°C. IMPORTANCE Mu-like bacteriophages of Y. pestis were isolated from M. himalayana of the Qinghai-Tibetan plateau in China. These bacteriophages have a unique temperature dependent life cycle, follow a lytic cycle at the temperature of warm-blooded mammals (37°С), and enter the lysogenic cycle at the temperature of its flea-vector (26°С). A switch from the lysogenic to the lytic cycle occurred when lysogenic bacteria were incubated from lower temperature to higher temperature (initially incubating at 26°C and shifting to 37°C). It is speculated that the temperature dependent lifestyle of bacteriophages may affect the population dynamics and pathogenicity of Y. pestis