Adoptive immunotherapy is a new potential method of tumour therapy, among which anti‐CD19 chimeric antigen receptor T‐cell therapy (CAR‐T cell), is a typical treatment agent for haematological ...malignancies. Previous clinical trials showed that the quality and phenotype of CAR‐T cells expanded ex vivo would seriously affect the tumour treatment efficacy. Although magnetic beads are currently widely used to expand CAR‐T cells, the optimal expansion steps and methods have not been completely established. In this study, the differences between CAR‐T cells expanded with anti‐CD3/CD28 mAb‐coated beads and those expanded with cell‐based aAPCs expressing CD19/CD64/CD86/CD137L/mIL‐15 counter‐receptors were compared. The results showed that the number of CD19‐specific CAR‐T cells with a 4‐1BB and CD28 co‐stimulatory domain was much greater with stimulation by aAPCs than that with beads. In addition, the expression of memory marker CD45RO was higher, whereas expression of exhausted molecules was lower in CAR‐T cells expanded with aAPCs comparing with the beads. Both CAR‐T cells showed significant targeted tumoricidal effects. The CAR‐T cells stimulated with aAPCs secreted apoptosis‐related cytokines. Moreover, they also possessed marked anti‐tumour effect on NAMALWA xenograft mouse model. The present findings provided evidence on the safety and advantage of two expansion methods for CAR‐T cells genetically modified by piggyBac transposon system.
Nitrogen is an essential element for sugarcane growth and development and is generally applied in the form of urea often much more than at recommended rates, causing serious soil degradation, ...particularly soil acidification, as well as groundwater and air pollution. In spite of the importance of nitrogen for plant growth, fewer reports are available to understand the application and biological role of N
fixing bacteria to improve N
nutrition in the sugarcane plant.
In this study, a total of 350 different bacterial strains were isolated from rhizospheric soil samples of the sugarcane plants. Out of these, 22 isolates were selected based on plant growth promotion traits, biocontrol, and nitrogenase activity. The presence and activity of the nifH gene and the ability of nitrogen-fixation proved that all 22 selected strains have the ability to fix nitrogen. These strains were used to perform 16S rRNA and rpoB genes for their identification. The resulted amplicons were sequenced and phylogenetic analysis was constructed. Among the screened strains for nitrogen fixation, CY5 (Bacillus megaterium) and CA1 (Bacillus mycoides) were the most prominent. These two strains were examined for functional diversity using Biolog phenotyping, which confirmed the consumption of diverse carbon and nitrogen sources and tolerance to low pH and osmotic stress. The inoculated bacterial strains colonized the sugarcane rhizosphere successfully and were mostly located in root and leaf. The expression of the nifH gene in both sugarcane varieties (GT11 and GXB9) inoculated with CY5 and CA1 was confirmed. The gene expression studies showed enhanced expression of genes of various enzymes such as catalase, phenylalanine-ammonia-lyase, superoxide dismutase, chitinase and glucanase in bacterial-inoculated sugarcane plants.
The results showed that a substantial number of Bacillus isolates have N-fixation and biocontrol property against two sugarcane pathogens Sporisorium scitamineum and Ceratocystis paradoxa. The increased activity of genes controlling free radical metabolism may at least in part accounts for the increased tolerance to pathogens. Nitrogen-fixation was confirmed in sugarcane inoculated with B. megaterium and B. mycoides strains using N-balance and
N
isotope dilution in different plant parts of sugarcane. This is the first report of Bacillus mycoides as a nitrogen-fixing rhizobacterium in sugarcane.
The exploitation of cheap and efficient electrocatalysts is the key to make energy‐related electrocatalytic techniques commercially viable. In recent years, transition metal phosphides (TMPs) ...electrocatalysts have gained a great deal of attention owing to their multifunctional active sites, tunable structure, and composition, as well as unique physicochemical properties. This review summarizes the up‐to‐date progress on TMPs in energy‐related electrocatalysis from diversified synthetic methods, ingenious‐modulated strategies, and novel applications. In order to set forth theory–structure–performance relationships upon TMPs, the corresponding reaction mechanisms, electrocatalytsts' structure/composition designs and desired electrochemical performance are jointly discussed, along with demonstrating their practical electrocatalytic applications in overall water splitting, metal–air batteries, lithium–sulfur batteries, etc. In the end, some underpinning issues and research orientations of TMPs toward efficient energy‐related electrocatalysis are briefly proposed.
This review summarizes the recent modulated strategies of transition metal phosphides upon elemental doping, interfacial regulation, phase modification, structural engineering, and nanocarbon incorporation. Benefitted from the optimized structure and composition, transition metal phosphides (TMPs) display excellent performance in electrocatalytic hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, CO2 reduction reaction, etc., along with their practical applications in water electrolyzer, metal–air batteries, and lithium–sulfur batteries, etc.
Machine learning algorithms have been used widely in various applications and areas. To fit a machine learning model into different problems, its hyper-parameters must be tuned. Selecting the best ...hyper-parameter configuration for machine learning models has a direct impact on the model’s performance. It often requires deep knowledge of machine learning algorithms and appropriate hyper-parameter optimization techniques. Although several automatic optimization techniques exist, they have different strengths and drawbacks when applied to different types of problems. In this paper, optimizing the hyper-parameters of common machine learning models is studied. We introduce several state-of-the-art optimization techniques and discuss how to apply them to machine learning algorithms. Many available libraries and frameworks developed for hyper-parameter optimization problems are provided, and some open challenges of hyper-parameter optimization research are also discussed in this paper. Moreover, experiments are conducted on benchmark datasets to compare the performance of different optimization methods and provide practical examples of hyper-parameter optimization. This survey paper will help industrial users, data analysts, and researchers to better develop machine learning models by identifying the proper hyper-parameter configurations effectively.
A community integrated energy system (CIES) with an electric vehicle charging station (EVCS) provides a new way for tackling growing concerns of energy efficiency and environmental pollution, it is a ...critical task to coordinate flexible demand response and multiple renewable uncertainties. To this end, a novel bi-level optimal dispatching model for the CIES with an EVCS in multi-stakeholder scenarios is established in this paper. In this model, an integrated demand response program is designed to promote a balance between energy supply and demand while maintaining a user comprehensive satisfaction within an acceptable range. To further tap the potential of demand response through flexibly guiding users energy consumption and electric vehicles behaviors (charging, discharging and providing spinning reserves), a dynamic pricing mechanism combining time-of-use and real-time pricing is put forward. In the solution phase, by using sequence operation theory (SOT), the original chance-constrained programming (CCP) model is converted into a readily solvable mixed-integer linear programming (MILP) formulation and finally solved by CPLEX solver. The simulation results on a practical CIES located in North China demonstrate that the presented method manages to balance the interests between CIES and EVCS via the coordination of flexible demand response and uncertain renewables.
Prader-Willi syndrome (PWS) is a rare and multisystemic genetic disorder that is characterized by severe hypotonia, hyperphagia, short stature, and global developmental delay. Although early ...recombinant human growth hormone (rhGH) treatment has been proven to rescue some symptoms and bring additional benefits to PWS patients, studies in patients under 2 years old are scarce. Thus, this study aims to investigate the effectiveness and safety of rhGH treatment for young children.
A total of 96 genetically confirmed Chinese PWS infants or toddlers (47 males) followed between 2013 and 2022 were retrospectively analyzed. Sixty-five infants (early treatment group) started rhGH treatment during their first year, and 31 toddlers (later treatment group) started at the age of 1-2 years. Auxological parameters, carbohydrate metabolism parameters, thyroid function, liver function, insulin-like growth factor-1 (IGF-1), and radiographs were acquired before the initiation of the treatment and every 3-6 months thereafter. Height/length, weight, and weight for height were expressed as standard deviation scores (SDSs) according to WHO child growth standards.
The mean SDS of length/height in the early treatment group was significantly higher than that in the later treatment group throughout the observation period (all P < 0.001). The change in the length SDS between the two groups at 1 year old and 4 years old was 1.50 (95% CI, 0.88-2.13) and 0.63 (95% CI, 0.16-1.10), respectively. Compared to the later treatment group, the weight SDS in the early treatment group increased by 0.94 (95% CI, 0.37-1.52) at 1 year old and 0.84 (95% CI, 0.28-1.39) at 2 years old. No statistical significance was found after 2.5 years of age. No significant differences were observed in IGF-1, incidence of liver dysfunction, hypothyroidism or spinal deformity between the two groups.
rhGH treatment improved growth and body composition in infants and toddlers. Furthermore, an early start of rhGH treatment is expected to have more efficacy than the later treatment group without an increase in adverse effects.
Electroreduction of carbon dioxide (CO2) into high‐value and readily collectable liquid products is vital but remains a substantial challenge due to the lack of highly efficient and robust ...electrocatalysts. Herein, Bi‐based metal‐organic framework (CAU‐17) derived leafy bismuth nanosheets with a hybrid Bi/BiO interface (Bi NSs) is developed, which enables CO2 reduction to formic acid (HCOOH) with high activity, selectivity, and stability. Specially, the flow cell configuration is employed to eliminate the diffusion effect of CO2 molecules and simultaneously achieve considerable current density (200 mA cm−2) for industrial application. The faradaic efficiency for transforming CO2 to HCOOH can achieve over 85 or 90% in 1 m KHCO3 or KOH for at least 10 h despite a current density that exceeds 200 mA cm−2, outperforming most of the reported CO2 electroreduction catalysts. The hybrid Bi/BiO surface of leafy bismuth nanosheets boosts the adsorption of CO2 and protects the surface structure of the as‐prepared leafy bismuth nanosheets, which benefits its activity and stability for CO2 electroreduction. This work shows that modifying electrocatalysts by surface oxygen groups is a promising pathway to regulate the activity and stability for selective CO2 reduction to HCOOH.
Herein, leafy bismuth nanosheets are shown to achieve CO2 electroreduction to HCOOH with high activity (>200 mA cm−2), selectivity (>90%) and stability (>10 h) by employing in gas diffusion cell configuration. According to the in‐depth characterizations, the large electrochemically accessible surface area and the superficial BiO species for Bi nanosheets are the key factors that enable the high catalytic activity.
By modeling the uncertainty of spinning reserves provided by energy storage with probabilistic constraints, a new optimal scheduling mode is proposed in this paper for minimizing the operating costs ...of an isolated microgrid (MG) by using chance-constrained programming. The model is transformed into a readily solvable mixed integer linear programming formulation in general algebraic modeling system (GAMS) via a proposed discretized step transformation approach and finally solved by applying the CPLEX solver. By properly setting the confidence levels of the spinning reserve probability constraints, the MG operation can achieve a tradeoff between reliability and economy. The test results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab MG test system reveal that the proposal significantly exceeds the commonly used hybrid intelligent algorithm with much better and more stable optimization results and significantly reduced calculation times.
Lithium niobate (LiNbO
) on insulator (LNOI) is a promising material platform for integrated photonics due to single crystal LiNbO
film’s wide transparent window, high refractive index, and high ...second-order nonlinearity. Based on LNOI, the fast-developing ridge-waveguide fabrication techniques enabled various structures, devices, systems, and applications. We review the basic structures including waveguides, cavities, periodically poled LiNbO
, and couplers, along with their fabrication methods and optical properties. Treating those basic structures as building blocks, we review several integrated devices including electro-optic modulators, nonlinear optical devices, and optical frequency combs with each device’s operating mechanism, design principle and methodology, and performance metrics. Starting from these integrated devices, we review how integrated LNOI devices boost the performance of LiNbO
’s traditional applications in optical communications and data center, integrated microwave photonics, and quantum optics. Beyond those traditional applications, we also review integrated LNOI devices’ novel applications in metrology including ranging system and frequency comb spectroscopy. Finally, we envision integrated LNOI photonics’ potential in revolutionizing nonlinear and quantum optics, optical computing and signal processing, and devices in ultraviolet, visible, and mid-infrared regimes. Beyond this outlook, we discuss the challenges in integrated LNOI photonics and the potential solutions.
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