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Scientific understanding of the changes in the Water-Energy-Food (WEF) nexus is crucial for regional development. As the spatial foundation of human activities, land use plays a pivotal role in shaping WEF nexus relations. However, little research has fully explored the impacts of land use changes within the WEF nexus from the human activities perspective. In this study, a novel theoretical framework was developed according to the logic flow “human activities-land use–WEF nexus”. Based on the LUI, the WEF score, and the ICCD between land use changes and WEF, the WEF score of various scenarios was forecasted using the ARIMA model. The findings revealed the various land use structures and LUI among nine provinces, with more intensive land use in lower reaches. During two decades, a discernible increase in both WEF system scores and ICCD was found in YRB. The WEF scores of all provinces had surpassed the threshold of 0.3 for two decades, and Inner Mongolia grew the fastest from 0.223 to 0.524. The ICCD of nine provinces evolved with fluctuations, from an imminent unbalanced or near coordination level in 2000 to primary coordination or moderate coordination level in 2020. The optimal land use scenarios varied across provinces, attributed to factors such as resource and environmental constraints (Qinghai and Sichuan), specialized agriculture or industry (Gansu, Ningxia, and Inner Mongolia), differentiated zonal characteristics (Shaanxi and Shanxi), and rapid industrialization and urbanization (Henan and Shandong). To attain sustainable development within the YRB, it is imperative to formulate differentiated land use strategies in each province, and universal strategies should also be established for each land use type.

IntroductionHepatocellular carcinoma (HCC) is a pressing global issue, with Hepatitis B virus (HBV) infection remaining the primary. Emodin, an anthraquinone compound extracted from the natural plant’s. This study investigates the molecular targets and possible mechanisms of emodin in treating HBV-related HCC based on network pharmacology and molecular docking and validates the screened molecular targets through in vitro experiments.MethodsPotential targets related to emodin were obtained through PubChem, CTD, PharmMapper, SuperPred, and TargetNet databases. Potential disease targets for HBV and HCC were identified using the DisGeNET, GeneCards, OMIM, and TTD databases. A Venn diagram was used to determine overlapping genes between the drug and the diseases. Enrichment analysis of these genes was performed using GO and KEGG via bioinformatics websites. The overlapping genes were imported into STRING to construct a protein-protein interaction network. Cytoscape 3.9.1 software was used for visualizing and analyzing the core targets. Molecular docking analysis of the drug and core targets was performed using Schrodinger. The regulatory effects of emodin on these core targets were validate through in vitro experiments.ResultsA total of 43 overlapping genes were identified. GO analysis recognized 926 entries, and KEGG analysis identified 135 entries. The main pathways involved in the KEGG analysis included cancer, human cytomegalovirus infection and prostate cancer. The binding energies of emodin with HSP90AA1, PTGS2, GSTP1, SOD2, MAPK3, and PCNA were all less than -5 kcal/mol. Compared to normal liver tissue, the mRNA levels of XRCC1, MAPK3, and PCNA were significantly elevated in liver cancer tissue. The expression levels of XRCC1, HIF1A, MAPK3, and PCNA genes were closely related to HCC progression. High expressions of HSP90AA1, TGFB1, HIF1A, MAPK3, and PCNA were all closely associated with poor prognosis in HCC. In vitro experiments demonstrated that emodin significantly downregulated the expression of HSP90AA1, MAPK3, XRCC1, PCNA, and SOD2, while significantly upregulating the expression of PTGS2 and GSTP1.ConclusionThis study, based on network pharmacology and molecular docking validation, suggests that emodin may exert therapeutic effects on HBV-related HCC by downregulating the expression of XRCC1, MAPK3, PCNA, HSP90AA1, and SOD2, and upregulating the expression of PTGS2 and GSTP1.

Application of deep learning (DL) and machine learning (ML) is rapidly increasing in the medical field. DL is gaining significance for medical image analysis, particularly, in oral and maxillofacial surgeries. Owing to the ability to accurately identify and categorize both diseased and normal soft- and hard-tissue structures, DL has high application potential in the diagnosis and treatment of tumors and in orthognathic surgeries. Moreover, DL and ML can be used to develop prediction models that can aid surgeons to assess prognosis by analyzing the patient's medical history, imaging data, and surgical records, develop more effective treatment strategies, select appropriate surgical modalities, and evaluate the risk of postoperative complications. Such prediction models can play a crucial role in the selection of treatment strategies for oral and maxillofacial surgeries. Their practical application can improve the utilization of medical staff, increase the treatment accuracy and efficiency, reduce surgical risks, and provide an enhanced treatment experience to patients. However, DL and ML face limitations, such as data drift, unstable model results, and vulnerable social trust. With the advancement of social concepts and technologies, the use of these models in oral and maxillofacial surgery is anticipated to become more comprehensive and extensive.

Abstract Exercise-induced mechanical loading can increase bone strength whilst mechanical unloading enhances bone-loss. Here, we investigated the role of lncRNA NONMMUT004552.2 in unloading-induced bone-loss. Knockout of lncRNA NONMMUT004552.2 in hindlimb-unloaded mice caused an increase in the bone formation and osteoblast activity. The silencing of lncRNA NONMMUT004552.2 also decreased the osteoblast apoptosis and expression of Bax and cleaved caspase-3, increased Bcl-2 protein expression in MC3T3-E1 cells. Mechanistic investigations demonstrated that NONMMUT004552.2 functions as a competing endogenous RNA (ceRNA) to facilitate the protein expression of spectrin repeat containing, nuclear envelope 1 (Syne1) by competitively binding miR-15b-5p and subsequently inhibits the osteoblast differentiation and bone formation in the microgravity unloading environment. These data highlight the importance of the lncRNA NONMMUT004552.2/miR-15b-5p/Syne1 axis for the treatment of osteoporosis.

Rice is one of the most important staple crops worldwide. However, the bacterial blight of rice caused by Xanthomonas oryzae pv. oryzae (Xoo) poses a major threat to the production of rice. In this study, we isolated and identified the strain Pseudomonas aeruginosa SF416, which exhibited significant antagonistic activity against Xoo, from a soil sample collected in a winter wheat field in Shannanzhalang County, Tibet, China. The bacterial solution (BS) and cell-free supernatant (CFS) of SF416 had significant prevention effects for the bacterial blight of rice, with an efficacy of 45.1% and 34.18%, respectively, while they exhibited a slightly lower therapeutic efficiency of 31.64% and 25.09%. The genomic analysis showed that P. aeruginosa SF416 contains genes involved in cell motility, colonization, cold and hot shock proteins, antibiotic resistance, and plant growth promotion. SF416 also harbors two sets of phenazine-1-carboxylic acid (PCA) synthesis gene clusters, phz1 (phzA1-G1) and phz2 (phzA2-G2), and other phenozine product-synthesis--related genes phzS, phzM, and phzH, as well as genes in the SF416 genome that share high similarity with the ones in the genomes of P. aeruginosa M18, suggesting that the two sets of PCA synthesis gene clusters are responsible for the antagonistic effect of SF416 against Xoo. A comparative antiSMASH analysis revealed that P. aeruginosa SF416 contains 17 gene clusters related to secondary metabolite synthesis, 7 of which, encoding for pyochelin, azetidomonamide A/B, L-2-amino-4-methoxy-trans-3-butenoic acid, hydrogen cyanide, pyocyanine, pseudopaline, and bicyclomycin, are conserved in strains of P. aeruginosa. Moreover, SF416 can produce protease and siderophores and display a broad-spectrum antagonistic activity against various major plant pathogenic bacteria and fungi. The results suggest that P. aeruginosa SF416 could be a potential candidate agent for the bacterial blight of rice.

BackgroundThe psychological status of Chinese postgraduate students majoring in stomatology after the COVID-19 restrictions still remains unclear. The objective of this study is to evaluate the mental status through a cross-sectional survey and gather related theoretical evidence for psychological intervention on postgraduate students majoring in stomatology.MethodsAn online survey was administered, and subjective well-being, anxiety, stress and depression symptoms were assessed using the 5-item World Health Organization Well-Being Index (WHO-5), item Generalized Anxiety Disorder Scale (GAD-7), 10-item Perceived Stress Scale (PSS-10), and Patient Health Questionnaire-9 (PHQ-9), respectively, wherein suicidal ideation and sleep-related problems were measured with PHQ-9 and Insomnia Severity Index (ISI).ResultsA total of 208 participants who completed one questionnaire were considered as valid. It was found that female respondents generally exhibited significantly higher levels of PSS-10, PHQ-9, and GAD-7 scores and shorter physical activity hours than male students. Students from rural areas demonstrated significantly higher levels of PHQ-9, suicidal ideation, and less portion of good or fair family economic support. Additionally, individuals from only-child families reported increased levels of activity hours (1.78 ± 2.07, p = 0.045) and a higher portion (55.10%, p = 0.007) of having clear future plan as compared with multiple-child families. The risk factors for anxiety symptoms (GAD-7 score) were higher scores of PSS-10 (OR = 1.15, 95% CI = 1.09–1.22), PHQ-9 (OR = 1.35, 95% CI = 1.22–1.49), and ISI-7 (OR = 1.14, 95% CI = 1.06–1.23), while owning a clear graduation plan was the protective factor (OR = 0.55, 95% CI = 0.31–0.98). Moreover, the risk factors for depressive symptoms (PHQ-9) included PSS-10 (OR = 1.10, 95% CI = 1.04–1.16), GAD-7 (OR = 1.38, 95% CI = 1.25–1.52), suicidal ideation (OR = 5.66, 95% CI = 3.37–9.51), and ISI-7 (OR = 1.17, 95% CI = 1.09–1.25). Approximately 98.08% of Chinese postgraduates studying stomatology reported experiencing at least moderate stress after the COVID-19 restrictions.ConclusionWithin the limitations of this study, senior students were more inclined to stress, while anxiety symptoms were related to severer levels of stress, depression, and insomnia. Depressive symptoms were associated with higher levels of stress, anxiety, insomnia, suicidal ideation, and lower levels of self-reported well-being. Thus, psychological interventions for postgraduates should be timely and appropriately implemented by strengthening well-being, reasonably planning for the future, and good physique, thereby mitigating the psychological issues after COVID-19 restrictions.

The water–energy–food (WEF) nexus constitutes a pivotal aspect of regional ecological protection and high-quality development. The exertion of multiple WEF-related policies would engender both synergies and trade-offs within the WEF nexus. However, a quantified framework that integrates the impact of multiple WEF-related policies with conventional WEF nexus assessments and simulations is currently lacking. This study quantified the WEF nexus in the Yellow River basin (YRB) of China under the influence of multiple policies, calculated the current and future WEF scores under different policy combination scenarios using the improved entropy weight method, the auto-regressive integrated moving average (ARIMA) model, and the linear optimization method. The results revealed the following: (1) From 2000 to 2020, WEF overall scores and subsystem scores were substantially increased with spatial heterogeneity. (2) Scenario analysis indicated that policy implementation would generally accelerate WEF score improvements in each city, yet embracing all policies simultaneously was not optimal for each city. (3) The spatial heterogeneity in policy impacts was also found in the YRB, with higher trade-offs in the upper reaches of cities, and higher synergies in the middle and lower reaches of cities. To attain high-quality development within the YRB, the related policies’ implementation should consider the regional disparities and enhance the optimization of resource allocation across the regions.

Abstract Background Immunosuppression induced by programmed cell death protein 1 (PD1) presents a significant constraint on the effectiveness of chimeric antigen receptor (CAR)-T therapy. The potential of combining PD1/PDL1 (Programmed cell death 1 ligand 1) axis blockade with CAR-T cell therapy is promising. However, developing a highly efficient and minimally toxic approach requires further exploration. Our attempt to devise a novel CAR structure capable of recognizing both tumor antigens and PDL1 encountered challenges since direct targeting of PDL1 resulted in systemic adverse effects. Methods In this research, we innovatively engineered novel CARs by grafting the PD1 domain into a conventional second-generation (2G) CAR specifically targeting CD19. These CARs exist in two distinct forms: one with PD1 extramembrane domain (EMD) directly linked to a transmembrane domain (TMD), referred to as PE CAR, and the other with PD1 EMD connected to a TMD via a CD8 hinge domain (HD), known as PE8HT CAR. To evaluate their efficacy, we conducted comprehensive assessments of their cytotoxicity, cytokine release, and potential off-target effects both in vitro and in vivo using tumor models that overexpress CD19/PDL1. Results The findings of our study indicate that PE CAR demonstrates enhanced cytotoxicity and reduced cytokine release specifically towards CD19 + PDL1 + tumor cells, without off-target effects to CD19-PDL1 + tumor cells, in contrast to 2G CAR-T cells. Additionally, PE CAR showed ameliorative differentiation, exhaustion, and apoptosis phenotypes as assessed by flow cytometry, RNA-sequencing, and metabolic parameter analysis, after encountering CD19 + PDL1 + tumor cells. Conclusion Our results revealed that CAR grafted with PD1 exhibits enhanced antitumor activity with lower cytokine release and no PD1-related off-target toxicity in tumor models that overexpress CD19 and PDL1. These findings suggest that our CAR design holds the potential for effectively addressing the PD1 signal.

Urinothorax is a rare cause of pleural effusion. Infected urinothorax is even rarer. Here we present a case of infected urinothorax from renal mass causing obstructive uropathy. Patient improved with pleural drainage and a multidisciplinary approach of treatment between team involving urologist and pulmonologist. This case highlights the complexity in the diagnosis and management of infected urinothorax.

Natural rubber is an important national strategic and industrial raw material. The leaf anthracnose of rubber trees caused by the Colletotrichum species is one of the important factors restricting the yields of natural rubber. In this study, we isolated and identified strain Bacillus velezensis SF334, which exhibited significant antagonistic activity against both C. australisinense and C. siamense, the dominant species of Colletotrichum causing rubber tree leaf anthracnose in the Hainan province of China, from a pool of 223 bacterial strains. The cell suspensions of SF334 had a significant prevention effect for the leaf anthracnose of rubber trees, with an efficacy of 79.67% against C. siamense and 71.8% against C. australisinense. We demonstrated that SF334 can lead to the lysis of C. australisinense and C. siamense mycelia by causing mycelial expansion, resulting in mycelial rupture and subsequent death. B. velezensis SF334 also harbors some plant probiotic traits, such as secreting siderophore, protease, cellulase, pectinase, and the auxin of indole-3-acetic acid (IAA), and it has broad-spectrum antifungal activity against some important plant pathogenic fungi. The genome combined with comparative genomic analyses indicated that SF334 possesses most genes of the central metabolic and gene clusters of secondary metabolites in B. velezensis strains. To our knowledge, this is the first time a Bacillus velezensis strain has been reported as a promising biocontrol agent against the leaf anthracnose of rubber trees caused by C. siamense and C. australisinense. The results suggest that B. velezensis could be a potential candidate agent for the leaf anthracnose of rubber trees.

Bacterial leaf streak (BLS) of rice is a severe disease caused by the bacterial pathogen Xanthomonas oryzae pv. oryzicola (Xoc) that has gradually become the fourth major disease on rice in some rice-growing regions in southern China. Previously, we isolated a Bacillus velezensis strain 504 that exhibited apparent antagonistic activity against the Xoc wild-type strain RS105, and found that B. velezensis 504 was a potential biocontrol agent for BLS. However, the underlying mechanisms of antagonism and biocontrol are not completely understood. Here we mine the genomic data of B. velezensis 504, and the comparative transcriptomic data of Xoc RS105 treated by the cell-free supernatants (CFSs) of B. velezensis 504 to define differentially expressed genes (DEGs). We show that B. velezensis 504 shares over 89% conserved genes with FZB42 and SQR9, two representative model strains of B. velezensis, but 504 is more closely related to FZB42 than SQR9, as well as B. velezensis 504 possesses the secondary metabolite gene clusters encoding the essential anti-Xoc agents difficidin and bacilysin. We conclude that approximately 77% of Xoc RS105 coding sequences are differentially expressed by the CFSs of B. velezensis 504, which significantly downregulates genes involved in signal transduction, oxidative phosphorylation, transmembrane transport, cell motility, cell division, DNA translation, and five physiological metabolisms, as well as depresses an additional set of virulence-associated genes encoding the type III secretion, type II secretion system, type VI secretion system, type IV pilus, lipopolysaccharides and exopolysaccharides. We also show that B. velezensis 504 is a potential biocontrol agent for bacterial blight of rice exhibiting relative control efficiencies over 70% on two susceptible cultivars, and can efficiently antagonize against some important plant pathogenic fungi including Colletotrichum siamense and C. australisinense that are thought to be the two dominant pathogenic species causing leaf anthracnose of rubber tree in Hainan province of China. B. velezensis 504 also harbors some characteristics of plant growth-promoting rhizobacterium such as secreting protease and siderophore, and stimulating plant growth. This study reveals the potential biocontrol mechanisms of B. velezensis against BLS, and also suggests that B. velezensis 504 is a versatile plant probiotic bacterium.

In the present study, the structure, magnetic phase transition, and magnetocaloric performance of Al20Mn20Fe20Co14.5+xCr25.5-x (x = 0, 1, and 2), a series of typical rare-earth-free high-entropy (HE) alloys, were experimentally determined and theoretically analyzed based on first-principle calculation. Ferromagnetic behavior was established and their Curie temperature could be tuned in a wide temperature range, which correlated with Co content; specifically, it increased from 282.8 K for Co14.5Cr25.5 to 345.8 K for Co16.5Cr23.5. In addition, the electronic density of states and magnetic moments associated with each consistent element were analyzed in the HE alloys. Maximum magnetic entropy changes of 1.135, 1.150, and 1.096 J/kgK were obtained for an x of 0, 1, and 2 under a magnetic field change of 5 T. These values are comparable or superior to those of reported 3d metal-based HE alloys. Furthermore, the experimental characterizations and theoretical predications agreed well, which provided an in-depth understanding of the rare-earth-free HE Al-Mn-Co-Fe-Cr alloy system, which is expected to be expanded to other systems in the future.

Abstract This paper develops a distributed cooperative control strategy (DCCS) to plan and optimize the collision‐free trajectory for the connected automated vehicle (CAV) at an isolated roundabout. The representation of the trajectories of CAVs is defined within a roundabout. The central angle and lane radius are used to indicate the location of vehicles, and the corresponding angular velocity is used to describe the vehicle's speed through the roundabout. This trajectory definition method simplifies the proposed problem into two parts: the trajectory optimization of each vehicle in a specific lane and the lane change coordination of CAVs in the roundabout. To solve the trajectory optimization problem, a mixed‐integer linear programming (MILP) model is formulated at the vehicle level to minimize the travel time and make the trajectory as smooth as possible. A model predictive control (MPC) framework is designed to coordinate lane‐change conflicts and push CAVs’ trajectories toward global optimization. The proposed framework integrates the vehicles’ trajectory optimization results so that all CAVs reach a consensus. Numerical experiments test the effect of the strategy in terms of traffic efficiency and mobility performance under different demand pattern scenarios. The results show that the proposed RA‐DCCS (Roundabout‐DCCS) can make all CAVs smooth and conflict‐free trajectories and enable vehicles to execute reasonable lane change decisions.

As production and life require more and more high-end and precise power equipment, high-quality electrical energy becomes the basis for the operation of these equipment. The impact of voltage sags on these devices has also increased. The quantification of the impact of voltage sags on various sensitive equipment through tests is an important basis for equipment manufacturers to improve the equipment’s ability to withstand voltage sag and users to take governance measures. The existing test schemes are to manually change the voltage sag conditions, repeatedly test, manually analyze the test data and draw the voltage sag tolerance curve. The actual process operation is trivial and has low degree automation, which consumes a lot of human resources. This paper put forward an auto test system, it comprehensively considers the characteristics of voltage sag, sensitive equipment types, attributes, and load status, automatically generates voltage characteristic vectors, automatically tests and resets the equipment, automatically analyzes the experimental results and draws the voltage sag tolerance curve, which greatly reduces the test time and labor costs.

Advancements in smart grid technology and the extensive applications of electric power big data have made in-depth exploration of the behavioral characteristics of power consumers highly necessary for further development of the electricity market. This paper proposes an effective and interpretable load curve classification method that based on sequential trajectory feature learning and a random forest algorithm. Firstly, the unsupervised K-medoid clustering algorithm is used to obtain and filter precise category labels. Next, the fused lasso generalized eigenvector (FLAG) technique is used to search for interpretable sub-sequences from the labeled data in order to properly account for the sequential trajectory feature of load curves and increase the speed of the computation process. Following that, shapelet transformation is used to extract the sequential trajectory features from original data. Finally, in order to inherit the interpretability of shapelet, the random forest is trained on the sequential trajectory features. The simulated examples based on the real load curves of the specific city in China were investigated in order to assess the performance of the proposed load curve categorization approach. The results of the simulation demonstrate that the proposed approach has considerable advantages in terms of effectiveness, accuracy, and interpretability of load classification.

For the low concentration and intractable VOCs and CO2, plasma-coupled catalysis has superior advantages and development potential to deal with them. However, there are critical issues such as efficiency to be further improved and unclear coupling mechanism to reveal. In this review, various types of catalysts are categorized and evaluated by exploring their enhancement effect in plasma-catalytic system to indicate their synergistic excellence and application limitation. Besides, the detailed research of synergistic mechanism between plasma and catalysis is given more attention, which is rapidly progressing due to the development of in-situ experimental techniques and kinetic analysis approach. In our view, the future direction of plasma catalysis is to reveal the synergistic mechanism more deeply for efficiency improvement with efficient catalysts, and pave the way for practical application.

Driven by emerging technologies such as the Internet of Things, 4K/8K video applications, virtual reality, and the metaverse, global internet protocol traffic has experienced an explosive growth in recent years. The surge in traffic imposes higher requirements for the data rate, spectral efficiency, cost, and power consumption of optical transceivers in short-reach optical networks, including data-center interconnects, passive optical networks, and 5G front-haul networks. Recently, a number of self-coherent detection (SCD) systems have been proposed and gained considerable attention due to their spectral efficiency and low cost. Compared with coherent detection, the narrow-linewidth and high-stable local oscillator can be saved at the receiver, significantly reducing the hardware complexity and cost of optical modules. At the same time, machine learning (ML) algorithms have demonstrated a remarkable performance in various types of optical communication applications, including channel equalization, constellation optimization, and optical performance monitoring. ML can also find its place in SCD systems in these scenarios. In this paper, we provide a comprehensive review of the recent progress in SCD systems designed for high-speed optical short- to medium-reach transmission links. We discuss the diverse applications and the future perspectives of ML for these SCD systems.

Abstract Background Robinia pseudoacacia is a widely planted pioneer tree species in reforestations on barren mountains in northern China. Because of its nitrogen-fixing ability, it can play a positive role in soil and forest restoration. After clear-cutting of planted stands, R. pseudoacacia stands become coppice plantations. The impacts of shifting from seedling to coppice stands on soil bacterial community and soil properties have not been well described. This study aims to quantify how soil properties and bacterial community composition vary between planted seedling versus coppice stands. Methods Nine 20 m × 20 m plots were randomly selected in seedling and coppice stands. The bulk soil and rhizosphere soil were sampled in summer 2017. Bulk soil was sampled at 10 cm from the soil surface using a soil auger. Rhizosphere soil samples were collected using a brush. The soil samples were transported to the laboratory for chemical analysis, and bacterial community composition and diversity was obtained through DNA extraction, 16S rRNA gene amplification and high-throughput sequencing. Results The results showed that, compared to seedling plantations, soil quality decreased significantly in coppice stands, but without affecting soil exchangeable Mg2+ and K+. Total carbon (C) and nitrogen (N) were lower in the rhizosphere than in bulk soil, whereas nutrient availability showed an opposite trend. The conversion from seedling to coppice plantations was also related to significant differences in soil bacterial community structure and to the reduction of soil bacterial α-diversity. Principal component analysis (PCA) showed that bacterial community composition was similar in both bulk and rhizosphere soils in second-generation coppice plantations. Specially, the conversion from seedling to coppice stands increased the relative abundance of Proteobacteria and Rhizobium, but reduced that of Actinobacteria, which may result in a decline of soil nutrient availability. Mantel tests revealed that C, N, soil organic matter (SOM), nitrate nitrogen (NO3 −-N) and available phosphorus positively correlated with bacterial community composition, while a variation partition analysis (VPA) showed that NO3 −-N explained a relatively greater proportion of bacterial distribution (15.12%), compared with C and SOM. Surprisingly, N showed no relationship with bacterial community composition, which may be related to nitrogen transportation. Conclusions The conversion from seedling to coppice stands reduced soil quality and led to spatial-temporal homogenization of the soil bacterial community structure in both the rhizosphere and bulk soils. Such imbalance in microbial structure can accelerate the decline of R. pseudoacacia. This may affect the role of R. pseudoacacia coppice stands in soil and forest restoration of barren lands in mountain areas.

Chimeric antigen receptor (CAR)-modified T cells targeting CD19 demonstrate unparalleled responses in B cell malignancies. However, high tumor burden limits clinical efficacy and increases the risk of cytokine release syndrome and neurotoxicity, which is associated with over-activation of the CAR-T cells. The hinge domain plays an important role in the function of CAR-T cells. We hypothesized that deletion of glycine, an amino acid with good flexibility, may reduce the flexibility of the hinge region, thereby mitigating CAR-T cell over-activation. This study involved generating a novel CAR by deletion of two consecutive glycine residues in the CD8 hinge domain of second-generation (2nd) CAR, thereafter named 2nd-GG CAR. The 2nd-GG CAR-T cells showed similar efficacy of CAR expression but lower hinge flexibility, and its protein affinity to CD19 protein was lower than that of 2nd CAR-T cells. Compared to the 2nd CAR-T cells, 2nd-GG CAR-T cells reduced proinflammatory cytokine secretion without diminishing the specific cytotoxicity toward tumor cells in vitro. Furthermore, 2nd-GG CAR-T cells prolonged overall survival in an immunodeficient mouse model bearing NALM-6 when tumor burden was high. This study demonstrated that a lower-flexibility of CD8α hinge improved survival under high tumor burden and reduced proinflammatory cytokines in preclinical studies. While there is potential for improved safety and efficacy, yet this needs validation with clinical trials.

Hydrogels that possess adequate toughness in bulk and at soft interface are highly desirable. We report a fully physically crosslinked dual Amylopectin (Amy, the first network)/poly(N-hydroxyethyl acrylamide) (PHEAA, the second network) hydrogel, where both networks were hydrogen bonding (H-bonding) crosslinked, with super toughness in bulk and tunable adhesion at hydrogel-soft tissue interface. Through adjustment of hydrogen bond density, strong and tough hydrogels were prepared that exhibited different levels of adhesion strength and three adhesive failure mechanisms. We replaced Amy with oxidized starch (OSA) to synthesize dual and hybrid chemically/physically crosslinked OSA/PHEAA double network (DN) hydrogels that were capable of forming Schiff's bases at hydrogel-hydrogel or hydrogel-tissue interfaces, aside from interfacial H-bonding, incurring sustained, high interfacial toughness (1850 J m−2 hydrogel-hydrogel and 610 J m−2 hydrogel-tissue) in wet environments. Such tough and adhesive DN hydrogels have great potential in various applications such as engineering of artificial soft tissues or implantable devices that are intended to adhere to internal organs or tissues.

Abstract A simple, multiple‐hydrogen‐bond approach to fabricating physically crosslinked, Amylopectin reinforced polyacrylamide/poly(vinyl alcohol) (Amy/PAAm/PVA) double‐network (DN) hydrogels with super toughness in bulk and at solid interfaces is reported. The Amy/PAAm/PVA DN hydrogels exhibit high tensile strength (854.1 kPa), high extensibility (≈eight times), high bulk toughness (4094.8 kJ m−3), good self‐recovery property (≈92% of self‐recovery at room temperature), and strong adhesion to nonporous glass surfaces (≈158 kPa). Such tough and adhesive DN hydrogels have great potential for various applications in engineering artificial soft tissues, flexible electronics, and wearable devices.

Abstract To study the fractal dimensions of the soil particle size distributions (PSDs) within different plantations (of Pinus densiflora, Quercus acutissima, Robinia pseudoacacia, and Larix kaempferi) and evaluate PSDs as an indicator of the likelihood of Robinia pseudoacacia invasion, the soil porosity of 0–20 cm soil layers was measured at different plantations in the Yaoxiang Forest Farm, Shandong Province, China. The results showed that the fractal dimension (D m) values varied from 2.59 to 2.70 among the different plantations and were significantly negatively correlated to sand content and positively correlated to silt content and clay content. Significant negative correlations were observed between D m and both soil organic matter (SOM) (P

Through analyzing the transient components and transient characteristics in transient zero-sequence current (TZSC), a novel fault feeder detection method based on the transient correlation of non-power frequency components (NPFCs) for the resonant grounded system is proposed. Firstly, using variational mode decomposition combined with fast Fourier transformation (VMD–FFT) to decompose the TZSC, by removing the power frequency components and noise signals, the transient NPFCs can be obtained. Secondly, to reflect the overall changing trend between faulty and healthy currents, the moving average filter is introduced to smooth the NPFCs; in this way, the fault transient features can be accurately revealed. Finally, the faulty feeder can be detected by comparing the threshold with the maximum difference value of comprehensive correlation coefficient of NPFCs. The detection results show that the proposed fault detection method can accurately select the faulty feeder; it is unaffected by fault resistances, fault phase angles, etc. Moreover, the detection method can resist noise interference.

Clustering electric load curves is an important part of the load data mining process. In this paper, we propose a clustering algorithm by combining singular value decomposition and KICIC clustering algorithm (SVD-KICIC) for analyzing the characteristics of daily load curves to mitigate some of the traditional clustering algorithm problems, such as only considering intra-class distance and low computational efficiency when dealing with massive load data. Our method identifies effective daily load curve characteristics using the singular value decomposition technique to improve dimensionality reduction, which improves low computational efficiency by reducing the number of dimensions inherent in big data. Additionally, the method performs SVD on the load data to obtain singular values for determination of weight of the KICIC algorithm, which leverages intra-class and inter-class distances of the load data and further improves the computational efficiency of the algorithm. Finally, we perform a series of simulations of actual load curves from a certain city to validate that the algorithm proposed in this paper has a short operation time, high clustering quality, and solid robustness that improves the clustering performance of the load curves.

The location problem of logistics park is the basis of logistics network planning. The establishment of conventional logistics park location planning model requires consideration of multiple factors, including position relationships between site selection points and demand points, economic cost, service efficiency, and consumer satisfaction. “Green development concept” gradually leads the trend of social and economic development in the contemporary world. The green logistics park emerges as the requirement of era. There are obvious differences between the site selection rules and the location demand of the green logistics park with the conventional logistics park. On the basis of analyzing the evaluation indexes of green logistics park and the factors affecting the site selection, this article builds a single-objective decision model based on the comprehensive cost. The model sets transportation cost and environment cost as the objective function. In addition, according to the constraints of location and quantity of the proposed logistics park, the model is divided into four parts to refine, and the solving process based on hybrid particle algorithm and alternate location allocation heuristic algorithm is given. The model and algorithm are feasible by analyzing the numerical example. Finally, the green logistics park site selection scheme is designed. The location model that considers the single comprehensive cost target provides a simple and feasible decision method for the green logistics park location.

Persistent hyperkinetic circulation after liver transplantation has been described in humans, but similar changes have not been well characterized in the rat model. This study aimed to investigate the hemodynamics of the systemic and splanchnic circulations in both arterialized and nonarterialized hepatic allografts. Orthotopic liver transplantation was performed in four groups of Sprague-Dawley rats. Group A comprised sham-operated rats with hepatic artery ligation that did not receive transplants; group B comprised rats that received transplants without arterialization; group C comprised sham-operated rats with intact hepatic artery that did not receive transplants; and group D comprised rats that received transplants with arterialization. Blood flow measurements were performed three weeks after the surgical procedure, using the radioactive microsphere method. The results showed that rats that received transplants exhibited a significantly higher cardiac index and lower systemic vascular resistance than the control rats. Splanchnic hyperemia was also present with increased mesenteric blood flow. However, there was no difference in hemodynamics between rats that received arterialized transplants and those that received nonarterialized transplants. Arterial collateral vessels from adjacent tissues were observed in the nonarterialized grafts; this was confirmed histologically. It is concluded that rats that undergo orthotopic liver transplantation exhibit hyperdynamic circulation, regardless of the arterial reconstruction procedure, possibly due to extensive collateral formation in the hepatosplanchnic circulation.