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Abstract Phototherapy is a promising antitumor modality, which consists of photothermal therapy (PTT) and photodynamic therapy (PDT). However, the efficacy of phototherapy is dramatically hampered by local hypoxia in tumors, overexpression of indoleamine 2,3-dioxygenase (IDO) and programmed cell death ligand-1 (PD-L1) on tumor cells. To address these issues, self-assembled multifunctional polymeric micelles (RIMNA) were developed to co-deliver photosensitizer indocyanine green (ICG), oxygenator MnO2, IDO inhibitor NLG919, and toll-like receptor 4 agonist monophosphoryl lipid A (MPLA). It is worth noting that RIMNA polymeric micelles had good stability, uniform morphology, superior biocompatibility, and intensified PTT/PDT effect. What’s more, RIMNA-mediated IDO inhibition combined with programmed death receptor-1 (PD-1)/PD-L1 blockade considerably improved immunosuppression and promoted immune activation. RIMNA-based photoimmunotherapy synergized with PD-1 antibody could remarkably inhibit primary tumor proliferation, as well as stimulate the immunity to greatly suppress lung metastasis and distant tumor growth. This study offers an efficient method to reinforce the efficacy of phototherapy and alleviate immunosuppression, thereby bringing clinical benefits to cancer treatment. Graphical Abstract

Abstract Background Salvia miltiorrhiza Bunge, a significant and widely used medicinal herb, is also recognized in the US Pharmacopoeia as a dietary supplement. However, the decline in yield and quality limits its further development as a traditional herbal medicine. Therefore, a deeper understanding of how synthetic communities (SynCom) affect the quality and yield of S. miltiorrhiza and the underlying mechanisms is necessary. Results In this study, we selected S. miltiorrhiza as the research subject and designed two synthetic communities (SynCom 1 and SynCom 2) using five endophytic fungi without significantly growth-promoting effect. We conducted both greenhouse and field experiments to investigate their impact on the yield and quality of the herbal plants. Greenhouse experiments confirmed that SynCom 1 significantly increased the biomass of S. miltiorrhiza, whereas SynCom 2 had the opposite effect. Field experiments further demonstrated that the application of SynCom 1 promoted photosynthesis and enhanced carbon and nitrogen metabolism, steady and markedly promoted plant growth, and thus increased S. miltiorrhiza yield compared to the uninoculated. In contrast, SynCom 2 inhibited yield but increased the content of the main active components. Un-targeted metabolomics analysis showed that SynCom 1 mainly promoted tricarboxylic acid cycle and nitrogen assimilation process to increase yield, and SynCom 2 mainly increase substrate content in the salvianolic acid and tanshinone synthesis pathways to improve quality. Conclusion These beneficial qualities exhibited by SynComs composed of fungi without apparent growth-promoting abilities represent an untapped resource that can be leveraged to enhance crop productivity. This opens up new research avenues for precision manipulation of plant microbiomes. Graphical abstract

Abstract This paper studies the problem of joint deployment, user association, channel, and resource allocation in unmanned aerial vehicle‐enabled access network. Since different user equipments performing different tasks and have different data rate requirements, the priority‐based traffic fairness problem is investigated. This problem, however, is a mixed integer nonlinear programming problem with NP‐hard complexity, making it challenging to be solved. To address this issue, a self‐organized and distributed framework “sense‐as‐you‐fly” based on the decomposition process, which divides the original problem into several subproblems, is proposed. Assuming without central controller, we derive the closed‐form resource allocation scheme and propose distributed many‐to‐one matching to optimize user association subproblem. Considering the coupled characteristics, the multi‐unmanned aerial vehicle deployment and channel allocation subproblems are modelled as a local altruistic game. The existence of Nash equilibrium is proved with the aid of exact potential game and efficient best response learning‐based algorithm is proposed. The original problem is finally addressed by solving the sub‐problems alternately and iteratively. Simulation results verify its effectiveness. By jointly optimizing multidimensional variables, the proposed algorithm unlocks network performance gains, especially in resource‐limited regimes.

Backgrounds: The functional recovery after peripheral nerve injury remains unsatisfactory. This study aims to perform a comprehensive evaluation of the efficacy of Fasudil Hydrochloride at treating the sciatic nerve transection injury in rats and the mechanism involved. Materials and methods: In animal experiments, 75 Sprague Dawley rats that underwent transection and repair of the right sciatic nerve were divided into a control, Fasudil, and Fas + LY group, receiving daily intraperitoneal injection of saline, Fasudil Hydrochloride (10 mg/kg), and Fasudil Hydrochloride plus LY294002 (5 mg/kg), respectively. At day 3 after surgery, the expression of ROCK2, p-PI3K, and p-AKT in L4-5 DRG and the lumbosacral enlargement was determined using Western blotting. At day 7 and 14, axon density in the distal stump was evaluated with immunostaining using the anti-Neurofilament-200 antibody. At day 30, retrograde tracing by injecting Fluoro-gold in the distal stump was performed. Three months after surgery, remyelination was analyzed with immostaining using the anti-MPZ antibody and the transmission electron microscope; Moreover, Motion-Evoked Potential, and recovery of sensorimotor functions was evaluated with a neuromonitor, Footprint, Hot Plate and Von Frey Filaments, respectively. Moveover, the Gastrocnemius muscles were weighed, and then underwent H＆E staining, and staining of the neuromuscular junction using α-Bungarotoxin to evaluate the extent of atrophy and degeneration of the endplates in the Gastrocnemius. In vitro, spinal motor neurons (SMNs) and dorsal root ganglia (DRG) were cultured to examine the impact of Fasudil Hydrochloride and LY294002 on the axon outgrowth. Results: Three days after injury, the expression of ROCK2 increased significantly (P＜0.01), and Fasudil application significantly increased the expression of p-PI3K and p-AKT in L4-6 DRG and the lumbosacral enlargement (P

Abstract Background Spermatogenesis is a highly regulated and complex process in which DNA methylation plays a crucial role. This study aimed to explore the differential methylation profiles in sperm DNA between patients with asthenospermia (AS) and healthy controls (HCs), those with oligoasthenospermia (OAS) and HCs, and patients with AS and those with OAS. Results Semen samples and clinical data were collected from five patients with AS, five patients with OAS, and six age-matched HCs. Reduced representation bisulfite sequencing (RRBS) was performed to identify differentially methylated regions (DMRs) in sperm cells among the different types of patients and HCs. A total of 6520, 28,019, and 16,432 DMRs were detected between AS and HC, OAS and HC, and AS and OAS groups, respectively. These DMRs were predominantly located within gene bodies and mapped to 2868, 9296, and 9090 genes in the respective groups. Of note, 12, 9, and 8 DMRs in each group were closely associated with spermatogenesis and male infertility. Furthermore, BDNF, SMARCB1, PIK3CA, and DDX27; RBMX and SPATA17; ASZ1, CDH1, and CHDH were identified as strong differentially methylated candidate genes in each group, respectively. Meanwhile, the GO analysis of DMR-associated genes in the AS vs. HC groups revealed that protein binding, cytoplasm, and transcription (DNA-templated) were the most enriched terms in the biological process (BP), cellular component (CC), and molecular function (MF), respectively. Likewise, in both the OAS vs. HC and AS vs. OAS groups, GO analysis revealed protein binding, nucleus, and transcription (DNA-templated) as the most enriched terms in BP, CC, and MF, respectively. Finally, the KEGG analysis of DMR-annotated genes and these genes at promoters suggested that metabolic pathways were the most significantly associated across all three groups. Conclusions The current study results revealed distinctive sperm DNA methylation patterns in the AS vs. HC and OAS vs. HC groups, particularly between patients with AS and those with OAS. The identification of key genes associated with spermatogenesis and male infertility in addition to the differentially enriched metabolic pathways may contribute to uncovering the potential pathogenesis in different types of abnormal sperm parameters.

Abstract Background Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management. Methods Integrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications. Results 457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p

The Asteraceae are widely distributed throughout the world, with diverse functions and large genomes. Many of these genes remain undiscovered and unstudied. In this study, we discovered a new gene ClNUM1 in Chrysanthemum lavandulifolium and studied its function. In this study, bioinformatics, RT-qPCR, paraffin sectioning, and tobacco transgenics were utilized to bioinformatically analyze and functionally study the three variable splice variants of the unknown gene ClNUM1 cloned from C. lavandulifolium. The results showed that ClNUM1.1 and ClNUM1.2 had selective 3′ splicing and selective 5′ splicing, and ClNUM1.3 had selective 5′ splicing. When the corresponding transgenic tobacco plants were subjected to abiotic stress treatment, in the tobacco seedlings, the ClNUM1.1 gene and the ClNUM1.2 gene enhanced salt and low-temperature tolerance and the ClNUM1.3 gene enhanced low-temperature tolerance; in mature tobacco plants, the ClNUM1.1 gene was able to enhance salt and low-temperature tolerance, and the ClNUM1.2 and ClNUM1.3 genes were able to enhance low-temperature tolerance. In summary, there are differences in the functions of the different splice variants and the different seedling stages of transgenic tobacco, but all of them enhanced the resistance of tobacco to a certain extent. The analysis and functional characterization of the ClNUM1 gene provided new potential genes and research directions for abiotic resistance breeding in Chrysanthemum.

Objective The talus is an important component in the ankle, and its treatment after injury is crucial. However, complications and adverse events due to incomplete traditional classifications may still occur, and these classifications fail to analyze the patterns and distribution of fractures from a three‐dimensional perspective. Therefore, in this study, we aimed to analyze the location and distribution of fracture lines in different types of talus fractures using three‐dimensional (3D) and heat mapping techniques. Additionally, we aimed to determine the surface area of the talus that can be utilized for different approaches of internal fixation, aiding in the planning of surgical procedures. Methods We retrospectively analyzed data from CT scans from 126 patients diagnosed with talus fractures at our two hospitals. We extracted the CT data of a healthy adult and created a standard talus model. We performed 3D reconstruction using patients' CT images and superimposed the fracture model onto the standard model for drawing fracture lines. Subsequently, we converted the fracture lines into a heat map for visualization. Additionally, we measured 20 specimens to determine the boundary for various ligaments attached to the talus. We determined the surface area of the talus available for different surgical approaches by integrating the boundary data with previously reported data on area of exposure. Results Without considering the displacement distance of the fracture, fracture types were classified as follows, by combining Hawkins and Sneppen classifications: talar neck, 41.3%; posterior talar tubercle, 22.2%; body for the talus and comminuted, 17.5%; lateral talar tubercle, 11.9%; and talar head, 7.1%. We established fracture line and heat maps using this classification. Additionally, we demonstrated the available area for anteromedial, anterolateral, posteromedial, posterolateral, and medial malleolus osteotomy and Chaput osteotomy approaches. Conclusion Fracture line and heat map analyses can aid surgeons in planning a single or combined surgical approach for the reduction and internal fixation of talus fractures. Demonstrating the different surgical approaches can help surgeons choose the most effective technique for individual cases.

Abstract Background Plant specialized (or secondary) metabolites (PSM), also known as phytochemicals, natural products, or plant constituents, play essential roles in interactions between plants and environment. Although many research efforts have focused on discovering novel metabolites and their biosynthetic genes, the resolution of metabolic pathways and identified biosynthetic genes was limited by rudimentary analysis approaches and enormous number of candidate genes. Results Here we integrated state-of-the-art automated machine learning (ML) frame AutoGluon-Tabular and multi-omics data from Arabidopsis to predict genes encoding enzymes involved in biosynthesis of plant specialized metabolite (PSM), focusing on the three main PSM categories: terpenoids, alkaloids, and phenolics. We found that the related features of genomics and proteomics were the top two crucial categories of features contributing to the model performance. Using only these key features, we built a new model in Arabidopsis, which performed better than models built with more features including those related with transcriptomics and epigenomics. Finally, the built models were validated in maize and tomato, and models tested for maize and trained with data from two other species exhibited either equivalent or superior performance to intraspecies predictions. Conclusions Our external validation results in grape and poppy on the one hand implied the applicability of our model to the other species, and on the other hand showed enormous potential to improve the prediction of enzymes synthesizing PSM with the inclusion of valid data from a wider range of species.

This study examines the nonlinear dynamic response of sandwich plates under low-velocity impacts (LVIs), which consist of a porous aluminum foam core with functionally graded (FG) graphene platelets (GPLs) reinforcement and two titanium alloy face sheets. The finite element method is employed to perform the numerical simulations and the Hertz contact theory is used to model the impact behavior. The generic Halpin-Tsai model, which incorporates the porosity effect, is adopted to estimate the mechanical properties of core made of the FG-GPLRC, based on the experimental data of the closed-cell aluminum alloy foam. The simulation results reveal that the FG-X configuration has the highest impact resistance, and that the addition of GPLs improves the impact performance. Moreover, a thicker core can reduce both the first contact time and the vibration period of plates, while a looser boundary condition can prolong the vibration time after the first impact. Additionally, a higher impactor velocity, mass and radius lead to a higher deflection and contact force. The oblique impact decreases the impact energy. This work provides a lighter and stiffer design for structure engineers when components suffer low-velocity impact.

Abstract Background The diagnosis of glioma has advanced since the release of the WHO 2021 classification with more molecular alterations involved in the integrated diagnostic pathways. Our study aimed to present our experience with the clinical features and management of astrocytoma, IDH mutant based on the latest WHO classification. Methods Patients diagnosed with astrocytoma, IDH‐mutant based on the WHO 5th edition classification of CNS tumors at our center from January 2009 to January 2022 were included. Patients were divided into WHO 2–3 grade group and WHO 4 grade group. Integrate diagnoses were retrospectively confirmed according to WHO 2016 and 2021 classification. Clinical and MRI characteristics were reviewed, and survival analysis was performed. Results A total of 60 patients were enrolled. 21.67% (13/60) of all patients changed tumor grade from WHO 4th edition classification to WHO 5th edition. Of these, 21.43% (6/28) of grade II astrocytoma and 58.33% (7/12) of grade III astrocytoma according to WHO 4th edition classification changed to grade 4 according to WHO 5th edition classification. Sex (p = 0.042), recurrent glioma (p = 0.006), and Ki‐67 index (p

Infrared and visible image fusion is an effective solution for image quality enhancement. However, conventional fusion models require the decomposition of source images into image blocks, which disrupts the original structure of the images, leading to the loss of detail in the fused images and making the fusion results highly sensitive to matching errors. This paper employs Convolutional Sparse Representation (CSR) to perform global feature transformation on the source images, overcoming the drawbacks of traditional fusion models that rely on image decomposition. Inspired by neural networks, a multi-layer CSR model is proposed, which involves five layers in a forward-feeding manner: two CSR layers acquiring sparse coefficient maps, one fusion layer combining sparse maps, and two reconstruction layers for image recovery. The dataset used in this paper comprises infrared and visible images selected from public dataset, as well as registered images collected by an actual Unmanned Aerial Vehicle (UAV). The source images contain ground targets, marine targets, and natural landscapes. To validate the effectiveness of the proposed image fusion model in this paper, comparative analysis is conducted with state-of-the-art (SOTA) algorithms. Experimental results demonstrate that the proposed fusion model outperforms other state-of-the-art methods by at least 10% in SF, EN, MI and QAB/F fusion metrics in most image fusion cases, thereby affirming its favorable performance.

Abstract Predictive markers and prognostic models are useful for the individualization of cancer treatment. In this study, we sought to identify clinical and molecular factors to predict overall survival in recurrent glioma patients receiving bevacizumab-containing regimens. A cohort of 102 patients was retrospectively collected from June 2011 to January 2022 at our institution. A nomogram was generated by Cox regression and feature selection algorithms based on 19 clinicopathological and 60 molecular variables. The model's performance was internally evaluated by bootstrapping in terms of discrimination and calibration. The median overall survival from the initiation of bevacizumab administration to death or last follow-up was 11.6 months (95% CI: 9.2–13.8 months) for all 102 patients, 10.2 months (95% CI: 6.4–13.3 months) for 66 patients with grade 4 tumors, and 13.8 months (lower limit of 95% CI: 11.5 months) for 36 patients with tumors of grade lower or not available. In the final model, a lower WHO 2021 grade (Grade lower or not available vs. Grade 4, HR: 0.398, 95% CI: 0.223–0.708, p = 0.00172), having received adjuvant radiochemotherapy (Yes vs. No, HR: 0.488, 95% CI: 0.268–0.888, p = 0.0189), and wildtype EGFR (Wildtype vs. Altered, HR: 0.193, 95% CI: 0.0506–0.733, p = 0.0157; Not available vs. Altered, HR: 0.386, 95% CI: 0.184–0.810, p = 0.0118) were significantly associated with longer overall survival in multivariate Cox regression. The overall concordance index was 0.652 (95% CI: 0.566–0.714), and the areas under the time-dependent curves for 6-, 12-, and 18-month overall survival were 0.677 (95% CI: 0.516–0.816), 0.654 (95% CI: 0.470–0.823), and 0.675 (95% CI: 0.491–0.860), respectively. A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-based therapy was established and internally validated. It could serve as a reference tool for clinicians to assess the extent the patients may benefit from bevacizumab and stratify their treatment response.

Abstract MALAT1, one of the few highly conserved nuclear long noncoding RNAs (lncRNAs), is abundantly expressed in normal tissues. Previously, targeted inactivation and genetic rescue experiments identified MALAT1 as a suppressor of breast cancer lung metastasis. On the other hand, Malat1-knockout mice are viable and develop normally. On a quest to discover the fundamental roles of MALAT1 in physiological and pathological processes, we find that this lncRNA is downregulated during osteoclastogenesis in humans and mice. Remarkably, Malat1 deficiency in mice promotes osteoporosis and bone metastasis of melanoma and mammary tumor cells, which can be rescued by genetic add-back of Malat1. Mechanistically, Malat1 binds to Tead3 protein, a macrophage-osteoclast–specific Tead family member, blocking Tead3 from binding and activating Nfatc1, a master regulator of osteoclastogenesis, which results in the inhibition of Nfatc1-mediated gene transcription and osteoclast differentiation. Notably, single-cell transcriptome analysis of clinical bone samples reveals that reduced MALAT1 expression in pre-osteoclasts and osteoclasts is associated with osteoporosis and metastatic bone lesions. Altogether, these findings identify Malat1 as a lncRNA that protects against osteoporosis and bone metastasis.

Glioblastoma (GBM) is the most common intrinsic and aggressive primary brain tumor in adults, with a median survival of approximately 15 months. GBM heterogeneity is considered responsible for the treatment resistance and unfavorable prognosis. Proneural-mesenchymal transition (PMT) represents GBM malignant progression and recurrence, which might be a breakthrough to understand GBM heterogeneity and overcome treatment resistance. PMT is a complicated process influenced by crosstalk between GBM and tumor microenvironment, depending on intricate ligand-receptor interactions. In this review, we summarize the autocrine and paracrine pathways in the GBM microenvironment and related ligand-receptor interactions inducing PMT. We also discuss the current therapies targeting the PMT-related autocrine and paracrine pathways. Together, this review offers a comprehensive understanding of the failure of GBM-targeted therapy and ideas for future tendencies of GBM treatment.

Abstract Background Sarcopenia is a senile syndrome of age-related muscle loss. It is thought to affect the development of chronic kidney disease and has a serious impact on the quality of life of the elder adults. Little is known about the association between sarcopenia and new-onset chronic kidney disease in middle-aged and elder adults. Using nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), we conducted a longitudinal analysis to investigate the association between sarcopenia status and new-onset chronic kidney disease in middle-aged and elder adults in China. Methods The study population consisted of 3676 participants aged 45 or older selected from 2011 CHARLS database who had no history of chronic kidney disease at the baseline and completed the follow-up in 2015. A multivariate cox regression model was employed to examine the association between sarcopenia and the incidence of new-onset chronic kidney disease. Results Followed up for 4 years, a total of 873 (22.5%) new cases of chronic kidney disease occurred. Among them, participants diagnosed with sarcopenia (HR1.45; 95% CI 1.15–1.83) were more likely to develop new-onset chronic kidney disease than those without sarcopenia. Similarly, patients with sarcopenia were more likely to develop new-onset chronic kidney disease than those with possible sarcopenia (HR 1.27; 95%CI 1.00-1.60). Subgroup analysis revealed that elder adults aged between 60 and 75 years old (HR 1.666; 95%CI 1.20-22.28), with hypertension (HR 1.57; 95%CI 1.02–2.40), people with sarcopenia had a significantly higher risk of developing new-onset chronic kidney disease than those without sarcopenia (all P

This paper tackles the exact consensus issue in nonlinearly parameterized multi-agent systems with unknown control directions, employing an adaptive learning control approach. The nonlinearly parameterized function is effectively compensated using neural networks and Fourier cardinal expansions. A cooperative consensus protocol is meticulously designed to achieve exact consensus through the application of iterative learning laws. The convergence of the consensus algorithm is rigorously analyzed using a composite energy function. Additionally, the robustness of the consensus algorithm is examined by introducing input disturbances to the controlled subsystem and bounded inputs to the leader. The scalability of the consensus protocol is explored through the context of formation control problems. Finally, the effectiveness of the constructed learning protocol is illustrated by simulations.

Abstract Observational evidence and climate model experiments suggest a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) since the mid-1990s. Increased greenhouse gases and the declined anthropogenic aerosols (AAs) over North America and Europe are believed to contribute to the AMOC slowdown. Asian AAs continue to increase but the associated impact has been unclear. Using ensembles of climate simulations, here we show that the radiative cooling resulting from increased Asian AAs drives an AMOC reduction. The increased AAs over Asia generate circumglobal stationary Rossby waves in the northern midlatitudes, which shift the westerly jet stream southward and weaken the subpolar North Atlantic westerlies. Consequently, reduced transport of cold air from North America hinders water mass transformation in the Labrador Sea and thus contributes to the AMOC slowdown. The link between increased Asian AAs and an AMOC slowdown is supported by different models with different configurations. Thus, reducing emissions of Asian AAs will not only lower local air pollution, but also help stabilize the AMOC.

Abstract Background Fibrous scars frequently form at the sites of bone nonunion when attempts to repair bone fractures have failed. However, the detailed mechanism by which fibroblasts, which are the main components of fibrous scars, impede osteogenesis remains largely unknown. Results In this study, we found that fibroblasts compete with osteogenesis in both human bone nonunion tissues and BMP2-induced ectopic osteogenesis in a mouse model. Fibroblasts could inhibit the osteoblastic differentiation of mesenchymal stem cells (MSCs) via direct and indirect cell competition. During this process, fibroblasts modulated the nuclear-cytoplasmic shuttling of YAP in MSCs. Knocking down YAP could inhibit osteoblast differentiation of MSCs, while overexpression of nuclear-localized YAP-5SA could reverse the inhibition of osteoblast differentiation of MSCs caused by fibroblasts. Furthermore, fibroblasts secreted DKK1, which further inhibited the formation of calcium nodules during the late stage of osteogenesis but did not affect the early stage of osteogenesis. Thus, fibroblasts could inhibit osteogenesis by regulating YAP localization in MSCs and secreting DKK1. Conclusions Our research revealed that fibroblasts could modulate the nuclear-cytoplasmic shuttling of YAP in MSCs, thereby inhibiting their osteoblast differentiation. Fibroblasts could also secrete DKK1, which inhibited calcium nodule formation at the late stage of osteogenesis.

Adipose tissue, an indispensable organ, fulfils the pivotal role of energy storage and metabolism and is instrumental in maintaining the dynamic equilibrium of energy and health of the organism. Adipocyte hypertrophy and adipocyte hyperplasia (adipogenesis) are the two primary mechanisms of fat deposition. Mature adipocytes are obtained by differentiating mesenchymal stem cells into preadipocytes and redifferentiation. However, the mechanisms orchestrating adipogenesis remain unclear. Autophagy, an alternative cell death pathway that sustains intracellular energy homeostasis through the degradation of cellular components, is implicated in regulating adipogenesis. Furthermore, adipose tissue functions as an endocrine organ, producing various cytokines, and certain inflammatory factors, in turn, modulate autophagy and adipogenesis. Additionally, autophagy influences intracellular redox homeostasis by regulating reactive oxygen species, which play pivotal roles in adipogenesis. There is a growing interest in exploring the involvement of autophagy, inflammation, and oxidative stress in adipogenesis. The present manuscript reviews the impact of autophagy, oxidative stress, and inflammation on the regulation of adipogenesis and, for the first time, discusses their interactions during adipogenesis. An integrated analysis of the role of autophagy, inflammation and oxidative stress will contribute to elucidating the mechanisms of adipogenesis and expediting the exploration of molecular targets for treating obesity-related metabolic disorders.

The inhibitory effect of hydrophilic volatile organic compounds (VOCs) on hydrophobic VOCs removal was found to be efficiently reduced by the fungal-bacterial biofilters (F&B-BFs) developed in the present study. Overall, the toluene and ethyl acetate mixture removal efficiencies (REs) and elimination capacities (ECs) of F&B-BFs were superior to those of bacterial biofilters (B-BFs). The REs for toluene and ethyl acetate were 32.5 ± 0.8 % and 74.6 ± 1.0 %, respectively, for F&B-BFs, in comparison to 8.0 ± 0.3 % and 60 ± 1.3 % for B-BFs. The ECs for toluene and ethyl acetate were 13.0 g m−3 h−1 and 149.2 g m−3 h−1, respectively, for the F&B–BF, compared to 3.2 g m−3 h−1 and 119.6 g m−3 h−1 for the B-BFs. This was achieved at a constant empty bed residence time (EBRT) of 45 s. F&B-BFs exhibited a superior mineralization efficiencies (MEs) compared to B-BFs for a VOC mixture of toluene and ethyl acetate (≈36.1 % vs ~ 29.6 %). This is attributed to the direct capture of VOCs by the presence of fungi, increased the contact time between VOCs and VOCs-degrading bacteria, and even distribution of VOCs-degrading bacteria in the F&B-BFs. Moreover, compared with B-BFs, the coupling effect of genus Pseudomonas degradation, and unclassified_f_Herpotrichiellaceae and unclassified_p_Ascomycota adsorption of F&B–BF resulted in a reduction in the impact of the presence of hydrophilic VOCs on the removal of hydrophobic VOCs, thereby enhancing the biofiltration performance of mixtures of hydrophilic and hydrophobic VOCs.

Background Conventional biofilters, which rely on bacterial activity, face challenges in eliminating hydrophobic compounds, such as aromatic compounds. This is due to the low solubility of these compounds in water, which makes them difficult to absorb by bacterial biofilms. Furthermore, biofilter operational stability is often hampered by acidification and drying out of the filter bed. Methods Two bioreactors, a bacterial biofilter (B-BF) and a fungal–bacterial coupled biofilter (F&B-BF) were inoculated with activated sludge from the secondary sedimentation tank of the Sinopec Yangzi Petrochemical Company wastewater treatment plant located in Nanjing, China. For approximately 6 months of operation, a F&B-BF was more effective than a B-BF in eliminating a gas-phase mixture containing benzene, toluene, ethylbenzene, and para-xylene (BTEp-X). Results After operating for four months, the F&B-BF showed higher removal efficiencies for toluene (T), ethylbenzene (E), benzene (B), and para-X (p-Xylene), at 96.9%, 92.6%, 83.9%, and 83.8%, respectively, compared to those of the B-BF (90.1%, 78.7%, 64.8%, and 59.3%). The degradation activity order for B-BF and F&B-BF was T > E > B > p-X. Similarly, the rates of mineralization for BTEp-X in the F&B-BF were 74.9%, 66.5%, 55.3%, and 45.1%, respectively, which were higher than those in the B-BF (56.5%, 50.8%, 43.8%, and 30.5%). Additionally, the F&B-BF (2 days) exhibited faster recovery rates than the B-BF (5 days). Conclusions It was found that a starvation protocol was beneficial for the stable operation of both the B-BF and F&B-BF. Community structure analysis showed that the bacterial genus Pseudomonas and the fungal genus Phialophora were both important in the degradation of BTEp-X. The fungal-bacterial consortia can enhance the biofiltration removal of BTEp-X vapors.

As an important intermediate for dual carbon targets, catalytic CO oxidation under mild conditions has received sufficient attention, as the reaction mechanism is directly related to the type of employed catalyst. High performance computing is performed with density functional theory to elucidate the mechanism of CO oxidation catalyzed by sulfur doped fullerene (C60-xSx (x = 1 ∼ 3)). The total activation energy for the first CO oxidation on C59S, C58S2, and C57S3 increases gradually, as implies that the CO oxidation on C59S should be easier than those on the other two dopants. Distinct electrons (0.852 e and 1.479 e) are transferred to oxygen atoms (O2) from C59S with the adsorption of O2 and CO. There is no synergistic effect for the doping S atoms. All elementary reactions on C59S are exothermic processes. This means that C59S is a potential material for addressing environmental protection issues and H2 purification for fuel cell applications.

Abstract Global surface temperature short‐term trends fluctuate between cooling and fast‐warming under the combined action of external forcing and internal variability, significantly influencing the detectability of near‐term climate change. A key driver of these variations is anthropogenic aerosols (AAs), which have undergone a non‐monotonic evolution with rapid reduction in recent decades. However, their reduction is projected to decelerate under a high carbon emission scenario, yet the impact on surface temperature trends remains unknown. Here, using initial‐perturbation large ensembles, we find that future slowdown in AA reduction over Europe and North America expedites the subpolar North Atlantic surface warming by intensifying the Atlantic meridional overturning circulation. Further, it accelerates the South Indian Ocean and Southern Ocean surface warming through positive low‐cloud feedback and oceanic dynamical adjustment, triggered by the poleward migration of westerlies under interhemispheric energy constraint. These AA‐driven warmings exacerbate greenhouse warming, significantly enhancing the detectability of local decadal warming trends.

Objective This study aims to assess the impact of surgical approaches and other factors on the incidence of Adjacent Segment Degeneration (ASD) following Spinal Fusion for Adolescent Idiopathic Scoliosis (AIS). Methods We conducted a comprehensive search of four electronic databases from their inception until March 30, 2023. Two independent reviewers screened titles, abstracts, and full texts and evaluated the methodological quality of the studies. A random-effects model was used to calculate the incidence of ASD. Results Our analysis included 14 studies involving 651 individuals. The overall incidence of ASD was 47% (95%CI: 0.37, 0.56). Subgroup analyses revealed that the prevalence of ASD increased with postoperative time (53% (95%CI: 0.31, 0.75) versus 48% (95%CI: 0.36, 0.60) versus 39% (95%CI: 0.22, 0.56)). For the number of fused segments, a group with more than 10 segments had a higher prevalence (49% (95%CI: 0.38, 0.60) versus 44% (95%CI: 0.21, 0.69)). In terms of regions, East Asia had the highest prevalence, followed by Occident and West Asia (52% (95%CI: 0.41, 0.62) versus 43% (95%CI: 0.20, 0.68) versus 37% (95%CI: 0.17, 0.59)). However, the surgical approach, male ratio, and the position of the lowest instrumented vertebra (LIV) did not show significant differences between groups. Funnel plots and Egger’s test did not reveal any significant publication bias (Egger’s test: t = 1.62, p -value = .1274). Conclusion This meta-analysis found that nearly half of AIS patients following spinal fusion surgery experienced ASD. Long-term follow-up, regular screening, and timely interventions are essential to reduce the prevalence of ASD.

Glioma is the leading cancer of the central nervous system (CNS). The efficacy of glioma treatment is significantly hindered by the presence of the blood-brain barrier (BBB) and blood-brain tumour barrier (BBTB), which prevent most drugs from entering the brain and tumours. Hence, we established a novel drug delivery nanosystem of brain tumour-targeting that could self-assemble the method using an amphiphilic Zein protein isolated from corn. Zein's amphiphilicity prompted it to self-assembled into NPs, efficiently containing TMZ. This allowed us to investigate temozolomide (TMZ) for glioblastoma (GBM) treatment. To construct TMZ-encapsulated NPs (TMZ@RVG-Zein NPs), the NPs' Zein was clocked to rabies virus glycoprotein 29 (RVG29). To verify that the NPs could penetrate the BBB and precisely target and kill the GBM cancer cell line, in vitro studies were performed. The process of NPs penetrating cancer cell membranes was investigated using enzyme-linked immunosorbent assays (ELISAs) to measure the expressions of nicotinic acetylcholine receptors (nAChRs) on the U87 cell line. Therefore, effective targeted brain cancer treatment is possible by forming NP clocks, a cell-penetrating natural Zein protein with an RVG29. These NPs can penetrate the blood-brain barrier (BBB) and enter the glioblastoma (U87) cell line to release TMZ. These NPs have a distinct cocktail of biocompatibility and brain-targeting abilities, making them ideal for involving brain diseases.

Abstract Controlling molecular spin quantum bits optically offers the potential to effectively reduce decoherence and raise the working temperature of quantum computers. Here, exchange interactions and spin dynamics, as mediated by an optically driven triplet state, are calculated for a molecule that consists of a pair of radicals and represents a potential quantum-circuit building block. Consistent with the previous experimental observation of spin coherence induced by the triplet state, our work demonstrates an optically driven quantum gate operation scheme in a molecule. A technological blueprint combining a two-dimensional molecular network and programmable nanophotonics, both of which are sufficiently developed, is proposed. We thus realize computational exploration of chemical databases to identify suitable candidates for molecular spin quantum bits and couplers to be hybridized with nanophotonic devices. The work presented here is proposed to realize a new approach for exploring molecular excited states and click chemistry, toward advancing molecular quantum technology.

Abstract Background Arbuscular mycorrhizal fungi (AMF) form symbiotic relationships with various terrestrial plants and have attracted considerable interest as biofertilizers for improving the quality and yield of medicinal plants. Despite the widespread distribution of AMFs in Salvia miltiorrhiza Bunge's roots, research on the impact of multiple AMFs on biomass and active ingredient accumulations has not been conducted. In this study, the effects of five native AMFs (Glomus formosanum, Septoglomus constrictum, Rhizophagus manihotis, Acaulospora laevis, and Ambispora gerdemannii) and twenty-six communities on the root biomass and active ingredient concentrations of S. miltiorrhiza were assessed using the total factor design method. Results Thirty-one treatment groups formed symbiotic relationships with S. miltiorrhiza based on the pot culture results, and the colonization rate ranged from 54.83% to 89.97%. AMF communities had higher colonization rates and total phenolic acid concentration than single AMF, and communities also appeared to have higher root fresh weight, dry weight, and total phenolic acid concentration than single inoculations. As AMF richness increased, there was a rising trend in root biomass and total tanshinone accumulations (ATTS), while total phenolic acid accumulations (ATP) showed a decreasing trend. This suggests that plant productivity was influenced by the AMF richness, with higher inoculation benefits observed when the communities contained three or four AMFs. Additionally, the affinities of AMF members were also connected to plant productivity. The inoculation effect of closely related AMFs within the same family, such as G. formosanum, S. constrictum, and R. manihotis, consistently yielded lower than that of mono-inoculation when any combinations were applied. The co-inoculation of S. miltiorrhiza with nearby or distant AMFs from two families, such as G. formosanum, R. manihotis, and Ac. laevis or Am. gerdemannii resulted in an increase of ATP and ATTS by more than 50%. AMF communities appear to be more beneficial to the yield of bioactive constituents than the single AMF, but overall community inoculation effects are related to the composition of AMFs and the relationship between members. Conclusion This study reveals that the AMF community has great potential to improve the productivity and the accumulation of bioactive constituents in S. miltiorrhiza, indicating that it is an effective way to achieve sustainable agricultural development through using the AMF community.

Abstract SiC MOSFET modules are widely used for bidirectional wireless charging of electric vehicles. However, prolonged use can result in bond wire faults, leading to reliability issues. To address this problem, a non‐contact bond wire monitoring method that can be carried out using the charging coil of the wireless charging device is proposed. Here, two monitoring loops are constructed based on the circuit topology, and their impedance magnitudes are measured on the charging coil to avoid the influence of battery voltage on monitoring results. To detect the bond wire condition, the impedance magnitude difference of the two monitoring loops is chosen as an indicator, which is very sensitive to the bond wire lift‐off. However, the monitoring results may be influenced by the aging of resonant capacitors and the offset of the charging coil. In particular, the influence of the coil offset is significant. To mitigate this effect, a prognostic parameter calibration method is proposed. Experimental results confirm the effectiveness of the proposed method, which provides a promising solution for the reliable and safe operation of SiC MOSFET modules in wireless charging devices.

Abstract Controlling an autonomous vehicle's unprotected left turn at an intersection is a challenging task. Traditional rule‐based autonomous driving decision and control algorithms struggle to construct accurate and trustworthy mathematical models for such circumstances, owing to their considerable uncertainty and unpredictability. To overcome this problem, a rule‐constrained reinforcement learning (RCRL) control method is proposed in this work for autonomous driving. To train a reinforcement learning controller with rule constraints, outcomes of the path planning module are used as a goal condition in the reinforcement learning framework. Since they include vehicle dynamics, the proposed approach is safer and more reliable compared to end‐to‐end learning, thereby ensuring that the generated trajectories are locally optimal while adjusting to unpredictable situations. In the experiments, a highly randomized two‐way four‐lane intersection is established based on the CARLA simulator to verify the effectiveness of the proposed RCRL control method. Accordingly, the results show that the proposed method can provide real‐time safe planning and ensure high passing efficiency for autonomous vehicles in the unprotected left turn task.

Abstract In this paper, the authors investigate the issue of constructing and incorporating an accurate vehicle dynamic model for model predictive control (MPC) with an application to autonomous vehicle path following. To achieve the desired performance, MPC employs a precise dynamic model. However, the uncertainty of complex systems and their operating environments presents a challenge to the development of an adequately accurate vehicle dynamic model. This paper proposes a Deep Gaussian Process Regression (DGPR) method to improve model precision. Meanwhile, the learning model is incorporated into a novel MPC framework to enhance closed‐loop performance. High‐fidelity simulations using CarSim‐MATLAB demonstrate the validity of the proposed approach in terms of enhancing the path following performance and lateral stability under the condition of large curvature at medium to high speeds on roads with different friction coefficients when compared to the nominal MPC approach.

Abstract Cooperative adaptive cruise control (CACC) realizes efficient, intelligent control of vehicle acceleration, deceleration, and steering, through inter‐vehicle communication and cooperative control. However, the close combination of the platoon makes it difficult for other vehicles to cut‐in, which can lead to severe traffic jams on certain sections of the road. The control effect of the CACC depends on the platoon penetration rate, which is the percentage of connected and autonomous vehicles (CAVs) in the total number of platoon members. There is no quantitative control method for different penetration rates, and it is difficult to quantify the impact of CACC vehicles on traffic. Therefore, this paper proposes an innovative CACC control method based on deep reinforcement learning (DRL). First, the altruism control and the quantitative control of the car‐following strategy are realized by the virtual car‐following distance method to reduce the exclusivity of the CACC platoon or improve the road utilization efficiency. Second, a more appropriate platoon reward function and collision avoidance method are proposed. Finally, the Car Learning to Act (CARLA) simulator is used. The obtained results confirm that the CACC control of CAVs based on DRL can absorb speed oscillation and improve fuel economy.

This paper presents a two-stage hybrid stochastic–robust coordination of energy management and self-healing in smart distribution networks with multiple microgrids. A multi-agent systems approach is first used for coupling energy management and self-healing strategies of microgrids, based on expert system rules. The second stage problem, a framework similar to that of the first stage, is then established for the smart distribution networks. Then, hybrid stochastic–robust optimization is used to model the uncertainties of demand, energy price, power generation of renewable energy sources, demand of electric vehicles, and accessibility of zone agents. Further, the grey wolf algorithm is used to solve the formulated optimization problem and achieve an optimal and reliable solution. The proposal is validated on a 69-bus distribution network consisting of three microgrids. The results validate that the proposal minimizes microgrids’ utilization indices, such as energy costs, energy losses, and network voltage drops, while simultaneously managing a flexible distribution network. It is also verified that the proposed multi-agent system design provides a high-speed and optimized self-healing solution for the network.

The aim of this research is to shed light on the complex interactions between player workload, traits, match-related factors, football performance, and injuries in the English Premier League. Using a range of statistical and machine learning techniques, this study analyzed a comprehensive dataset that included variables such as player workload, personal traits, and match statistics. The dataset comprises information on 532 players across 20 football clubs for the 2020–2021 English Premier League season. Key findings suggest that data, age, average minutes played per game, and club affiliations are significant indicators of both performance and injury incidence. The most effective model for predicting performance was Ridge Regression, whereas Extreme Gradient Boosting (XGBoost) was superior for predicting injuries. These insights are invaluable for data-driven decision-making in sports science and football teams, aiding in injury prevention and performance enhancement. The study’s methodology and results have broad applications, extending beyond football to impact other areas of sports analytics and contributing to a flexible framework designed to enhance individual performance and fitness.

The ocean tide loading (OTL) can result in displacements of centimeters or even decimeters at nearshore stations. Global ocean tide models exhibit errors in nearshore regions, which limit the accuracy of maintaining the coordinates of these stations. GNSS positioning can obtain tidal load displacements in nearshore areas, but it often requires long-term observation data and cannot provide timely correction models for newly established reference stations. This paper proposes a method for an empirical correction model of short-term OTL displacements using GNSS observations, where the kinematic coordinate sequences are first obtained by multi-GNSS precise point positioning with ambiguity resolution (PPP-AR), and then the OTL corrections are obtained by window-sliding forecast based on random forest modeling. Through experiments conducted in the Hong Kong region, the empirical model with a window of 15 days is established by the proposed method. After applying the empirical model, root mean square errors of the residuals are reduced by 1.5 (30.6%), 3.7 (53.6%), and 3.7 mm (37.8%) in the East, North, and Up (ENU) components, respectively. When using the global ocean tide model FES2014, the RMSE values are reduced by 1.2 (24.5%), 0.3 (4.3%), and 3.7 mm (37.8%) in the ENU components, respectively. The empirical model shows better effects for the OTL displacement compared to FES2014, especially in the N component, with an improvement ratio of about 49.3%.

Tissue damage often causes considerable suffering to patients due to slow recovery and poor prognosis. The use of electroactive materials to deliver biophysical signals plays a key role in regulating tissue regeneration processes. Among these materials, piezoelectric materials have unique electromechanical conversion capabilities, making them suitable for use as cell scaffolds. They can deform and emit electrical signals in response to external stimuli, thereby regulating cell proliferation and differentiation. In this review, recent advances are presented in piezoelectric materials as physical signaling mediators that regulate cell differentiation. The basic mechanisms, classification of these materials, and their different applications in tissue regeneration are described. Finally, a comprehensive discussion of current challenges and prospects in the field is provided. Together, existing experimental results basically show that piezoelectric materials can improve the process and effect of tissue repair, providing new technical options for the development of tissue engineering in the future.

BackgroundThe 2021 World Health Organization Classification of Central Nervous System Tumors updates glioma subtyping and grading system, and incorporates EGFR amplification (Amp) as one of diagnostic markers for glioblastoma (GBM).PurposeThis study aimed to describe the frequency, clinical value and molecular correlation of EGFR Amp in diffuse gliomas based on the latest classification.MethodsWe reviewed glioma patients between 2011 and 2022 at our hospital, and included 187 adult glioma patients with available tumor tissue for detection of EGFR Amp and other 59 molecular markers of interest. Clinical, radiological and pathological data was analyzed based on the status of EGFR Amp in different glioma subtypes.Results163 gliomas were classified as adult-type diffuse gliomas, and the number of astrocytoma, oligodendroglioma and GBM was 41, 46, and 76. EGFR Amp was more common in IDH-wildtype diffuse gliomas (66.0%) and GBM (85.5%) than IDH-mutant diffuse gliomas (32.2%) and its subtypes (astrocytoma, 29.3%; oligodendroglioma, 34.8%). EGFR Amp did not stratify overall survival (OS) in IDH-mutant diffuse gliomas and astrocytoma, while was significantly associated with poorer OS in IDH-wildtype diffuse gliomas, histologic grade 2 and 3 IDH-wildtype diffuse astrocytic gliomas and GBM.ConclusionOur study validated EGFR Amp as a diagnostic marker for GBM and still a useful predictor for shortened OS in this group.

Background Endophytic fungi can enhance the growth and synthesis of secondary metabolites in medicinal plants. Salvia miltiorrhiza Bunge is frequently employed for treating cardiovascular and cerebrovascular ailments, with the primary bioactive components being salvianolic acid and tanshinone. However, their levels in cultivated S. miltiorrhiza are inferior to that of the wild herbs, so the production of high-quality medicinal herbs is sharply declining. Consequently, the utilization of beneficial endophytic fungi to improve the yield and quality of S. miltiorrhiza holds great significance for the cultivation of medicinal plants. Methods In this study, nine non-pathogenic, endophytic fungal strains were introduced into sterile S. miltiorrhiza seedlings and cultivated both in vitro and in situ (the greenhouse). The effects of these strains on the growth indices, C and N metabolism, antioxidant activity, photosynthesis, and content of bioactive ingredients in S. miltiorrhiza were then evaluated. Results The results showed that the different genera, species, or strains of endophytic fungi regulated the growth and metabolism of S. miltiorrhiza in unique ways. These endophytic fungi primarily exerted their growth-promoting effects by increasing the net photosynthetic rate, intercellular CO2 concentration, and the activities of sucrose synthase, sucrose phosphate synthase, nitrate reductase, and glutamine synthetase. They also enhanced the adaptability and resistance to environmental stresses by improving the synthesis of osmoregulatory compounds and the activity of antioxidant enzymes. However, their regulatory effects on the growth and development of S. miltiorrhiza were affected by environmental changes. Moreover, the strains that significantly promoted the synthesis and accumulation of phenolic acids inhibited the accumulation of tanshinones components, and vice versa. The endophytic fungal strains Penicillium meloforme DS8, Berkeleyomyces basicola DS10, and Acremonium sclerotigenum DS12 enhanced the bioaccumulation of tanshinones. Fusarium solani DS16 elevated the rosmarinic acid content and yields in S. miltiorrhiza. The strain Penicillium javanicum DS5 improved the contents of dihydrotanshinone, salvianolic acid B, and rosmarinic acid. The strains P. meloforme DS8 and B. basicola DS10 improved resistance. Conclusion Various endophytic fungi affected the quality and yield of S. miltiorrhiza by regulating different physiological and metabolic pathways. This study also provides a novel and effective method to maximize the effects of beneficial endophytic fungi by selecting specific strains to design microbial communities based on the different ecological functions of endophytic fungi under varying environments and for specific production goals.

Cancer stem cells (CSCs) are highly related to initiate metastasis and drive tumor relapse/propagation, and the induced cancer stemness and plasticity render cancer intractable to various therapeutic approaches. To address them, a CSC membrane‐based fusion strategy is presented to target and attenuate cancer stemness and plasticity, and accordingly homogenous CSC‐inherited fusion membrane‐coated biomimetic nanoeffectors based on doxorubicin‐loaded hydroxyapatite nanoparticles are engineered. Such biomimetic nanoeffectors coated with fusion membrane consisting of CSCs and cancer cells can not only specifically target the solid breast tumor cells, but also target the latent CSCs. Systematic experiments validate that the constructed nanoeffectors disrupt energy metabolism, trigger lethal mitochondrial apoptosis, remarkably inhibit tumor proliferation, and downregulate the expressions of some target proteins associated with cancer stemness and metastasis to attenuate cancer stemness and the induced plasticity. Contributed by them, such nanoeffectors have been demonstrated to successfully hinder the progression of breast cancer, and decrease lung metastasis in two cancer metastasis mouse models. Such CSCs membrane‐based fusion membrane strategy provides a new candidate avenue rather than the currently dominant immune‐related pathway to repress cancer metastasis via targeting and attenuating cancer stemness.

Sample clustering techniques play a crucial role in the data-driven state evaluation of electromechanical equipment, and selecting an appropriate similarity measurement method for sample sets helps improve the clustering performance. The Jaccard coefficient is a commonly employed indicator of similarity for scalar set-type samples. In this paper, we propose an incremental clustering algorithm for matrix-type samples by defining an improved Jaccard coefficient. First, a new binary relation is formulated to derive a relationship matrix between samples. Second, an undirected graph is given by using the relationship matrix, and an improved pruning operation is provided to simplify the graph by eliminating redundant edges. Then, a new relationship matrix is generated according to the modified graph, which enables the calculation of the improved Jaccard coefficient. By using the improved Jaccard coefficient, the improved incremental clustering algorithm updates cluster centers by selecting a particular sample to maximize the sum of similarities between the selected sample and other samples within the same cluster. Finally, the effectiveness of the proposed incremental clustering algorithm is demonstrated in fault diagnosis and remaining useful life estimation application scenarios, respectively. The experimental results indicate that the improved algorithm outperforms traditional clustering methods.

Abstract Background The latest fifth edition of the World Health Organization (WHO) classification of the central nervous system (CNS) tumors (WHO CNS 5 classification) released in 2021 defined astrocytoma, IDH‐mutant, Grade 4. However, the understanding of this subtype is still limited. We conducted this study to describe the features of astrocytoma, IDH‐mutant, Grade 4 and explored the similarities and differences between histological and molecular subtypes. Methods Patients who underwent surgery from January 2011 to January 2022, classified as astrocytoma, IDH‐mutant, Grade 4 were included in this study. Clinical, radiological, histopathological, molecular pathological, and survival data were collected for analysis. Results Altogether 33 patients with astrocytoma, IDH‐mutant, Grade 4 were selected, including 20 with histological and 13 with molecular WHO Grade 4 astrocytoma. Tumor enhancement, intratumoral‐necrosis like presentation, larger peritumoral edema, and more explicit tumor margins were frequently observed in histological WHO Grade 4 astrocytoma. Additionally, molecular WHO Grade 4 astrocytoma showed a tendency for relatively longer overall survival, while a statistical significance was not reached (47 vs. 25 months, p = 0.22). TP53, CDK6, and PIK3CA alteration was commonly observed, while PIK3R1 (p = 0.033), Notch1 (p = 0.027), and Mycn (p = 0.027) alterations may affect the overall survival of molecular WHO Grade 4 astrocytomas. Conclusions Our study scrutinized IDH‐mutant, Grade 4 astrocytoma. Therefore, further classification should be considered as the prognosis varied between histological and molecular WHO Grade 4 astrocytomas. Notably, therapies aiming at PIK3R1, Notch 1, and Mycn may be beneficial.

Abstract Background Antibiotics are widely used for prophylactic therapy and for improving the growth performance of chicken. The problem of bacterial drug resistance caused by antibiotic abuse has previously attracted extensive attention; however, the influence of early-day use of prophylactic antibiotics on the gut microflora and on the disease resistance ability in chicks has not been explored. Here, we comprehensively evaluate the growth performance, gut microbial dynamics, level of antibiotic resistance genes (ARGs) in the gut microbial community, and resistance to H9N2 avian influenza virus (AIV) in chickens following long-term and short-term early-day prophylactic antibiotic treatment. Results Unexpectedly, long-term prophylactic enrofloxacin treatment slowed the growth rate of chickens, whereas short-term antibiotics treatments were found to increase the growth rate, but these changes were not statistically significant. Strikingly, expansions of Escherichia-Shigella populations were observed in early-life prophylactic antibiotics-treated groups of chickens, which is in contrast to the general perception that antibiotics should control their pathogenicity in chicks. The gut microbiota composition of chickens treated long term with antibiotics or received early-day antibiotics treatment tend to be more dramatically disturbed compared to the gut microbiome of chickens treated with antibiotics for a short term at a later date, especially after H9N2 AIV infection. Conclusions Our data provide evidence that early-day and long-term antibiotic treatments have a more adverse effect on the intestinal microbiome of chickens, compared to short-term late age antibiotic treatment. Furthermore, our metagenomic data reveal that both long-term and short-term antibiotic treatment increase the relative abundance of ARGs. Our findings highlight the adverse effects of prophylactic antibiotic treatment and provide a theoretical basis for the cautious administration of antibiotics in food-producing animal management. Video Abstract

Abstract Optical cavities, resonant with vibrational or electronic transitions of material within the cavity, enable control of light-matter interaction. Previous studies have reported cavity-induced modifications of chemical reactivity, fluorescence, phase behavior, and charge transport. Here, we explore the effect of resonant cavity-phonon coupling on the transient photoconductivity in a hybrid organic-inorganic perovskite. To this end, we measure the ultrafast photoconductivity response of perovskite in a tunable Fabry–Pérot terahertz cavity, designed to be transparent for optical excitation. The terahertz-cavity field-phonon interaction causes apparent Rabi splitting between the perovskite phonon mode and the cavity mode. We explore whether the cavity-phonon interaction affects the material’s electron-phonon interaction by determining the charge-carrier mobility through photoconductivity. Despite the apparent hybridization of cavity and phonon modes, we show that the perovskite properties in both ground (phonon response) and excited (photoconductive response) states remain unaffected by the tunable light-matter interaction. Yet the response of the integral perovskite-terahertz optical cavity system depends critically on the interaction strength of the cavity with the phonon: the transient terahertz response to optical excitation can be increased up to threefold by tuning the cavity-perovskite interaction strength. These results enable tunable switches and frequency-controlled induced transparency devices.

Abstract The vehicle detection algorithm based on visual perception has been applied in all types of automatic driving scenes. However, there are still flaws in the current detection algorithm model, especially for small objects. The detection effect of vehicle objects with small pixels in the image is often missed and wrongly detected. This research proposes an improved feature fusion module based on double‐channel residual pyramid (DRP) structure for autonomous detection algorithm which named binary residual feature pyramid network (BiResFPN) to solve the above problems. Firstly, a DRP structure, which can effectively supplement the shallow information of the network, is proposed. The residual structure is added to the output feature map for further supplement. Then, an average sampling method of positive and negative samples based on intersection‐over‐union (IOU) value is proposed on the basis of this structure, aimed at the unbalanced sampling of positive and negative samples in the training stage of faster regions with CNN features (RCNN). It leads to the reduction of the interference of a large number of simple negative samples, which makes the learned model better. The experimental results based on the KITTI and BDD100K dataset datasets show that the capability of the feature fusion module based on DRP structure is strong for small object detection. Compared with Faster‐RCNN (FPN), the detection algorithm of small object detection accuracy APsmall was increased by 2.6%, APmedium and APlarge was increased by 1.1% and 0.3%.