Search

Nanocatalytic medicine, which aims to accurately target and effectively treat tumors through intratumoral in situ catalytic reactions triggered by tumor-specific environments or markers, is an emerging technology. However, the relative lack of catalytic activity of nanoenzymes in the tumor microenvironment (TME) has hampered their use in biomedical applications. Therefore, it is crucial to develop a highly sensitive probe that specifically responds to the TME or disease markers in the TME for precision diagnosis and treatment of diseases. In this work, a chiral photoacoustic (PA) nanoprobe (D/L-Ce@MoO3) based on the H2O2-catalyzed TME activation reaction was constructed in a one-step method using d-cysteine (D-Cys) or l-cysteine (L-Cys), polymolybdate, and cerium nitrate as raw materials. The designed and synthesized D/L-Ce@MoO3 chiral nanoprobe can perform in situ, non-invasive, and precise imaging of pharmacological acute liver injury. In vivo and in vitro experiments have shown that the D/L-Ce@MoO3 probe had chiral properties, the CD signal decreased upon reaction with H2O2, and the absorption and PA signals increased with increasing H2O2 concentration. This is because of the catalytic reaction between Ce ions doped in the nanoenzyme and the high expression of H2O2 caused by drug-induced liver injury to produce ·OH, which has a strong oxidizing property to kill tumor cells and destroy the Mo-S bond in the probe, thus converting the chiral probe into an achiral polyoxometalate (POM) with PA signal. [ABSTRACT FROM AUTHOR]

Dealing with high-dimensional data poses a significant challenge in machine learning. To address this issue, researchers have proposed feature selection as a viable solution. Due to the intricate search space involved in feature selection, swarm intelligence algorithms have gained popularity for their exceptional search capabilities. This study introduces a method called Clustering Probabilistic Particle Swarm Optimization (CPPSO) to revolutionize the traditional particle swarm optimization approach by incorporating probabilities to represent velocity and incorporating an elitism mechanism. Furthermore, CPPSO employs a clustering strategy based on the K-means algorithm, utilizing the Hamming distance to divide the population into two sub-populations to improve the performance. To assess CPPSO's performance, a comparative analysis is conducted against seven existing algorithms using twenty diverse datasets. These datasets are all based on real-world problems. Fifteen of these are frequently used in feature selection research, while the remaining five comprise imbalanced datasets as well as multi-label datasets. The experimental results demonstrate the superiority of CPPSO across a range of evaluation criteria, surpassing the performance of the comparative algorithms on the majority of the datasets. [ABSTRACT FROM AUTHOR]

DNA polymerase ζ (Pol ζ) plays an essential role in replicating damaged DNA templates but contributes to mutagenesis due to its low fidelity. Therefore, ensuring tight control of Pol ζ's activity is critical for continuous and accurate DNA replication, yet the specific mechanisms remain unclear. This study reveals a regulation mechanism of Pol ζ activity in human cells. Under normal conditions, an autoinhibition mechanism keeps the catalytic subunit, REV3L, inactive. Upon encountering replication stress, however, ATR-mediated phosphorylation of REV3L's S279 cluster activates REV3L and triggers its degradation via a caspase-mediated pathway. This regulation confines the activity of Pol ζ, balancing its essential role against its mutations causing potential during replication stress. Overall, our findings elucidate a control scheme that fine tunes the low-fidelity polymerase activity of Pol ζ under challenging replication scenarios. DNA polymerase ζ (Pol ζ) maintains continuity but impairs accuracy during DNA replication. Here, the authors report a mechanism by which human cells precisely control the essential, yet mutagenic, activity of Pol ζ to ensure both continuation and fidelity during DNA replication challenges. [ABSTRACT FROM AUTHOR]

Recent advances in computer vision and deep learning techniques have facilitated significant progress in video scene understanding, thus helping film and television practitioners achieve accurate video editing. However, so far, publicly available semantic segmentation datasets are mostly limited to indoor scenes, city streets, and natural images, often ignoring example objects in action movies, which is a research gap that needs to be urgently filled. In this paper, we introduce a large-scale, high-precision semantic segmentation dataset of props in Chinese martial arts movie clips, named ChineseMPD. Specifically, this dataset first establishes segmentation rules and general review criteria for audiovisual data, and then provides semantic segmentation annotations for six weapon props (Gun, Sword, Stick, Knife, Hook, and Arrow) with a summary of 32,992 objects.To the best of our knowledge, this dataset is the largest semantic segmentation dataset for movie props to date. ChineseMPD dataset not only significantly expands the application of traditional tasks of computer vision such as object detection and scene understanding, but also opens up new avenues for interdisciplinary research. [ABSTRACT FROM AUTHOR]

Endoscopic submucosal dissection (ESD) of fibrotic colorectal lesions is difficult and has a high complication rate. There are only a few reports on the utility of orthodontic rubber band (ORB) traction in reducing the difficulty of this procedure. This study aimed to investigate the risk factors for perforation when applying ORB traction during ESD of fibrotic colorectal lesions. We continuously collected the clinical data of 119 patients with fibrotic colorectal lesions who underwent ESD with ORB and clip traction between January 2019 and January 2024. Possible risk factors for perforation were analyzed. The median ORB-ESD operative time was 40 (IQR 28–62) min, and the en bloc and R0 resection rates were 94.1% and 84.0%, respectively. Perforation occurred in 16 of 119 patients (13.4%). The lesion size, lesion at the right half of the colon or across an intestinal plica, the degree of fibrosis, operation time, and the surgeon's experience were associated with perforation during ORB-ESD (P < 0.05). Multivariate logistic regression analysis showed that lesions in the right colon (OR 9.027; 95% CI 1.807–45.098; P = 0.007) and those across an intestinal plica (OR 7.771; 95% CI 1.298–46.536; P = 0.025) were independent risk factors for perforation during ORB-ESD. ORB-ESD is an effective and feasible approach to treat fibrotic colorectal lesions. Adequate preoperative evaluation is required for lesions in the right colon and across intestinal plicas to mitigate the risk of perforation. [ABSTRACT FROM AUTHOR]

The rapid development of China's economy has been accompanied by high levels of energy consumption and pollution. This development mode poses great challenges to the sustainable development of China's economy and environment, and it also creates contradictions in regional environmental governance. To realize healthy, harmonious and sustainable economic development, improving technology, enhancing energy efficiency and reducing energy consumption and carbon emissions have become choices that China has to make for intensive economic growth. In this study, we first estimate energy efficiency at the provincial level in China with the super-efficiency data envelopment analysis (SE-DEA) model; we then analyze the current status of carbon emissions and estimate the reverse technology spillover effect of outward foreign direct investment (OFDI). Second, Tobit regression and fixed effects models are used to test the impact of the reverse technology spillovers of OFDI and energy efficiency on carbon emissions, and the instrumental variable method is used to test for endogeneity. The regression results of various methods prove that our conclusion is robust. Finally, the mediating effect of energy efficiency is estimated, confirming that the reverse technology spillovers of OFDI not only directly affect carbon emissions but also indirectly affect carbon emissions through energy efficiency. Based on the research above, we propose policy recommendations for using the reverse technology spillovers of OFDI to improve energy efficiency and reduce carbon emissions. [ABSTRACT FROM AUTHOR]

Monitoring and controlling the carbon emissions need machine learning-based forecasting models at this modern era. Despite various of artificial neural networks (ANNs), we propose a novel FD3 framework to tackle carbon emissions prediction. In our approach, three "FD" procedures are executed: (1) frequency decomposition achieved by using complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN), an advanced version of the famous empirical mode decomposition (EMD); (2) forecasting dendritic neuron model (DNM) that has proved validity on numerous prediction tasks, showing advanced nonlinear fitting ability than traditional network-structured ANNs; and (3) fluctuation density measurement (FD function) that used to regulate the predicting strategy for each decomposed subseries. In experiments, the FD3 framework has shown better performance than seven baseline models in terms of three widely used time series prediction evaluation metrics. The success of our FD3 has confirmed the validity of "preprocessing-forecasting" workflow and provides better solutions for carbon emissions prediction. Furthermore, the design of FD function can give more insights for signal analysis that the selection of decomposed subseries can have huge impacts on the original data. [ABSTRACT FROM AUTHOR]

Spatial simulation and projection of ecosystem services value (ESV) changes caused by urban growth are important for sustainable development in arid regions. We developed a new model of cellular automata based grasshopper optimization algorithm (named GOA-CA) for simulating urban growth patterns and assessing the impacts of urban growth on ESV changes under climate change scenarios. The results show that GOA-CA yielded overall accuracy exceeding 98%, and FOM for 2010 and 2020 were 43.2% and 38.1%, respectively, indicating the effectiveness of the model. The prairie lost the highest economic ESVs (192 million USD) and the coniferous yielded the largest economic ESV increase (292 million USD) during 2000-2020. Using climate change scenarios as urban future land use demands, we projected three scenarios of the urban growth of Urumqi for 2050 and their impacts on ESV. Our model can be easily applied to simulating urban development, analyzing its impact on ESV and projecting future scenarios in global arid regions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University: Science B is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We present the gluon distribution functions of the pion and kaon in small-x and large-x regions, and compare them with the results obtained from lattice QCD and continuum Schwinger function methods. Whether in the small-x region or the large-x region, our gluon distribution of the pion is consistent with the results of lattice QCD and continuum Schwinger function methods. We also calculate the first four moments of gluon distributions of the pion and kaon at different Q 2 scales. In addition, we present the mass decomposition of the pion and kaon with the dynamical parton distribution functions calculated by the DGLAP equation with parton–parton recombination corrections. The mass structures of the pion and kaon are completely different from that of the proton. [ABSTRACT FROM AUTHOR]

Dipterocarpoideae species form the emergent layer of Asian rainforests. They are the indicator species for Asian rainforest distribution, but they are severely threatened. Here, to understand their adaptation and population decline, we assemble high-quality genomes of seven Dipterocarpoideae species including two autotetraploid species. We estimate the divergence time between Dipterocarpoideae and Malvaceae and within Dipterocarpoideae to be 108.2 (97.8‒118.2) and 88.4 (77.7‒102.9) million years ago, and we identify a whole genome duplication event preceding dipterocarp lineage diversification. We find several genes that showed a signature of selection, likely associated with the adaptation to Asian rainforests. By resequencing of two endangered species, we detect an expansion of effective population size after the last glacial period and a recent sharp decline coinciding with the history of local human activities. Our findings contribute to understanding the diversification and adaptation of dipterocarps and highlight anthropogenic disturbances as a major factor in their endangered status. Dipterocarp trees are iconic but severely threatened species in Asian rainforests. This study assembles high-quality genomes of seven dipterocarp species to reveal the molecular basis of key adaptations and identifies a recent sharp population decline coinciding with local human activity. [ABSTRACT FROM AUTHOR]

4D printing technology combines 3D printing and stimulus-responsive materials, enabling construction of complex 3D objects efficiently. However, unlike smart soft materials, 4D printing of ceramics is a great challenge due to the extremely weak deformability of ceramics. Here, we report a feasible and efficient manufacturing and design approach to realize direct 4D printing of ceramics. Photocurable ceramic elastomer slurry and hydrogel precursor are developed for the fabrication of hydrogel-ceramic laminates via multimaterial digital light processing 3D printing. Flat patterned laminates evolve into complex 3D structures driven by hydrogel dehydration, and then turn into pure ceramics after sintering. Considering the dehydration-induced deformation and sintering-induced shape retraction, we develop a theoretical model to calculate the curvatures of bent laminate and sintered ceramic part. Then, we build a design flow for direct 4D printing of various complex ceramic objects. This approach opens a new avenue for the development of ceramic 4D printing technology. Four-dimensional (4D) printing ceramics is a challenge due to their weak deformability. Here, the authors report a hydrogel-dehydration-driven direct 4D printing approach, enabling simple and efficient manufacturing of various complex ceramic objects [ABSTRACT FROM AUTHOR]

Internal carotid artery occlusion (ICAO) is a relatively uncommon but important cause of transient ischaemic attack and cerebral infarction. Hybrid surgery (HS) improves cerebral perfusion, but its impact on neurocognitive function has been controversial. Patients with symptomatic chronic ICAO treated by hybrid surgery or medical treatment from 2016 to 2019 were included. We recorded and analysed the clinical characteristics, angiographic data, outcomes and cognitive status. Functional assessments, including the National Institutes of Health Stroke Scale (NIHSS), the Barthel Index, and a battery of neuropsychological tests, including the Mini-Mental State Examination (MMSE), Alzheimer Disease Assessment Scale–Cognitive Subtest (ADAS-cog), verbal fluency, and Colour Trail test Parts 1 and 2, were administered. Significant improvements in the ADAS (before, 7.5 ± 6.2 versus after, 5.2 ± 5.7; P = 0.022), MMSE (before, 25.5 ± 2.8 versus after, 28.1 ± 2.3; P = 0.013), and Colour Trail test Part 1 (before, 118.3 ± 26.5 versus after, 96.2 ± 23.1; P = 0.016) were observed six months after HS. Moreover, the abovementioned postprocedure scales were ameliorated in the HS group. This study found that in patients with multiple symptomatic ICAO and objective ipsilateral ischaemia, successful HS leads to improvement in the scores of three cognitive tests. [ABSTRACT FROM AUTHOR]

High‐performance organic neuromorphic devices with miniaturized device size and computing capability are essential elements for developing brain‐inspired humanoid intelligence technique. However, due to the structural inhomogeneity of most organic materials, downscaling of such devices to nanoscale and their high‐density integration into compact matrices with reliable device performance remain challenging at the moment. Herein, based on the design of a semicrystalline polymer PBFCL10 with ordered structure to regulate dense and uniform formation of conductive nanofilaments, we realize an organic synapse with the smallest device dimension of 50 nm and highest integration size of 1 Kb reported thus far. The as‐fabricated PBFCL10 synapses can switch between 32 conductance states linearly with a high cycle‐to‐cycle uniformity of 98.89% and device‐to‐device uniformity of 99.71%, which are the best results of organic devices. A mixed-signal neuromorphic hardware system based on the organic neuromatrix and FPGA controller is implemented to execute spiking‐plasticity‐related algorithm for decision-making tasks. Designing high performance organic neuromorphic devices remains a challenge. Here, Liu et al. report the development of an organic synapse based on a semicrystalline polymer PBFCL10 with device dimension of 50 nm and integration size of 1 Kb and a mixed‐signal neuromorphic hardware system based on the organic neuromatrix and FPGA controller for decision‐making tasks. [ABSTRACT FROM AUTHOR]

Behavior is one of the important factors reflecting the health status of dairy cows, and when dairy cows encounter health problems, they exhibit different behavioral characteristics. Therefore, identifying dairy cow behavior not only helps in assessing their physiological health and disease treatment but also improves cow welfare, which is very important for the development of animal husbandry. The method of relying on human eyes to observe the behavior of dairy cows has problems such as high labor costs, high labor intensity, and high fatigue rates. Therefore, it is necessary to explore more effective technical means to identify cow behaviors more quickly and accurately and improve the intelligence level of dairy cow farming. Automatic recognition of dairy cow behavior has become a key technology for diagnosing dairy cow diseases, improving farm economic benefits and reducing animal elimination rates. Recently, deep learning for automated dairy cow behavior identification has become a research focus. However, in complex farming environments, dairy cow behaviors are characterized by multiscale features due to large scenes and long data collection distances. Traditional behavior recognition models cannot accurately recognize similar behavior features of dairy cows, such as those with similar visual characteristics, i.e., standing and walking. The behavior recognition method based on 3D convolution solves the problem of small visual feature differences in behavior recognition. However, due to the large number of model parameters, long inference time, and simple data background, it cannot meet the demand for real-time recognition of dairy cow behaviors in complex breeding environments. To address this, we developed an effective yet lightweight model for fast and accurate dairy cow behavior feature learning from video data. We focused on four common behaviors: standing, walking, lying, and mounting. We recorded videos of dairy cow behaviors at a dairy farm containing over one hundred cows using surveillance cameras. A robust model was built using a complex background dataset. We proposed a two-pathway X3DFast model based on spatiotemporal behavior features. The X3D and fast pathways were laterally connected to integrate spatial and temporal features. The X3D pathway extracted spatial features. The fast pathway with R(2 + 1)D convolution decomposed spatiotemporal features and transferred effective spatial features to the X3D pathway. An action model further enhanced X3D spatial modeling. Experiments showed that X3DFast achieved 98.49% top-1 accuracy, outperforming similar methods in identifying the four behaviors. The method we proposed can effectively identify similar dairy cow behaviors while improving inference speed, providing technical support for subsequent dairy cow behavior recognition and daily behavior statistics. [ABSTRACT FROM AUTHOR]

This study developed a new tool, differential staining fluorescence microscopy (DSFM), to measure the biovolume and track the location of enteric pathogens in mixed-species biofilms which can pose a risk to food safety in beef processing facilities. DSFM was employed to examine the impact of pathogenic bacteria, Escherichia coli O157:H7 and three different Salmonella enterica strains on mixed-species biofilms of beef processing facilities. Fourteen floor drain biofilm samples from three beef processing plants were incubated with overnight BacLight stained enteric pathogens at 7 °C for 5 days on stainless steel surface then counter-stained with FM-1-43 biofilm stain and analyzed using fluorescence microscopy. Notable variations in biovolume of biofilms were observed across the fourteen samples. The introduction of E. coli O157:H7 and S. enterica strains resulted in diverse alterations of biofilm biovolume, suggesting distinct impacts on mixed-species biofilms by different enteric pathogens which were revealed to be located in the upper layer of the mixed-species biofilms. Pathogen strain growth curve comparisons and verification of BacLight Red Stain staining effectiveness were validated. The findings of this study show that the DSFM method is a promising approach to studying the location of enteric pathogens within mixed-species biofilms recovered from processing facilities. Understanding how foodborne pathogens interact with biofilms will allow for improved targeted antimicrobial interventions. [ABSTRACT FROM AUTHOR]

To improve the detection speed of cow mounting behavior and the lightness of the model in dense scenes, this study proposes a lightweight rapid detection system for cow mounting behavior. Using the concept of EfficientNetV2, a lightweight backbone network is designed using an attention mechanism, inverted residual structure, and depth-wise separable convolution. Next, a feature enhancement module is designed using residual structure, efficient attention mechanism, and Ghost convolution. Finally, YOLOv5s, the lightweight backbone network, and the feature enhancement module are combined to construct a lightweight rapid recognition model for cow mounting behavior. Multiple cameras were installed in a barn with 200 cows to obtain 3343 images that formed the cow mounting behavior dataset. Based on the experimental results, the inference speed of the model put forward in this study is as high as 333.3 fps, the inference time per image is 4.1 ms, and the model mAP value is 87.7%. The mAP value of the proposed model is shown to be 2.1% higher than that of YOLOv5s, the inference speed is 0.47 times greater than that of YOLOv5s, and the model weight is 2.34 times less than that of YOLOv5s. According to the obtained results, the model proposed in the current work shows high accuracy and inference speed and acquires the automatic detection of cow mounting behavior in dense scenes, which would be beneficial for the all-weather real-time monitoring of multi-channel cameras in large cattle farms. [ABSTRACT FROM AUTHOR]

Background: Eucommia ulmoides (E. ulmoides) leaves are identified as a new resource of medicine and food homology. In this study, the structural characterization, physicochemical properties, and antioxidant activity of E. ulmoides polysaccharides (EUP) were studied. Results: Three components with different molecular weights of 1.51 × 105 Da (EUP1), 3.05 × 104 Da (EUP2) and 1.17 × 105 Da (EUP3) were purified from E. ulmoides leaves. They were composed of l-rhamnose (Rha), d-arabinose (Ara), d-mannose (Man), d-glucose (Glu) and d-galactose (Gal), while EUP2 also contained small amounts of d-xylose (Xyl). Three components all had typical polysaccharides absorption peaks, which may be polysaccharides with β configuration of pyranose structure, and amorphous structure of acid polysaccharides with good thermal stability below 270 ℃. However, the molecular weight, monosaccharide composition and apparent morphology of the three components were different, resulting in a stronger scavenging ability of EUP2 and EUP3 against DPPH and OH free radicals. Conclusion: The results will provide a theoretical reference for developing EUP-related foods and drugs. [ABSTRACT FROM AUTHOR]

Apiose is a natural pentose containing an unusual branched-chain structure. Apiosides are bioactive natural products widely present in the plant kingdom. However, little is known on the key apiosylation reaction in the biosynthetic pathways of apiosides. In this work, we discover an apiosyltransferase GuApiGT from Glycyrrhiza uralensis. GuApiGT could efficiently catalyze 2″-O-apiosylation of flavonoid glycosides, and exhibits strict selectivity towards UDP-apiose. We further solve the crystal structure of GuApiGT, determine a key sugar-binding motif (RLGSDH) through structural analysis and theoretical calculations, and obtain mutants with altered sugar selectivity through protein engineering. Moreover, we discover 121 candidate apiosyltransferase genes from Leguminosae plants, and identify the functions of 4 enzymes. Finally, we introduce GuApiGT and its upstream genes into Nicotiana benthamiana, and complete de novo biosynthesis of a series of flavonoid apiosides. This work reports an efficient phenolic apiosyltransferase, and reveals mechanisms for its sugar donor selectivity. Apiosides are plant bioactive natural products containing apiose, but the details of the key apiosylation reaction in their biosynthesis are missing. Here, the authors identify the apiosyltransferase GuApiGT that could efficiently catalyze 2″-O-apiosylation of flavonoid glycosides, solve its crystal structure and obtain mutants with altered sugar selectivity. [ABSTRACT FROM AUTHOR]

Ensuring safe human-robot interactions is a crucial concern in robotics research and development. However, controlling the social distance between quadruped robots and humans poses a significant challenge due to the large motion range of robots and the lack of specific social distance rules for human safety. This study proposes an innovative framework that integrates proxemic theory and ISO safety strategy to provide a new social distance control mechanism for human-quadruped robot interactions. The proposed framework uses a gated spike filter neural network (GSN) that fuses LiDAR and RGB-D data to estimate human-robot distance and ensures quantified human-robot social distance with continuous velocity limitations, which current approaches do not offer. The experimental results demonstrate that the GSN algorithm offers high accuracy and is well-suited for large-range human-robot distance control of quadruped robots. It has an average prediction error that is 31.4% lower than traditional Kalman filter methods and offers a more efficient and precise solution for real-time social distance control. Additionally, this study includes a detailed use case that demonstrates how to apply the proposed framework to human-quadruped robot interactions. Overall, this study's findings have implications for improving the safety and efficiency of human-robot interactions in various applications. [ABSTRACT FROM AUTHOR]

When copper ores containing pyrite are crushed and ground, many unavoidable Fe3+ ions will be produced and enter the flotation process. At present, the adsorption mechanism of Fe3+ on chalcopyrite and pyrite surfaces is not clear. Here, the adsorption behaviors of Fe3+ on the surfaces of chalcopyrite and pyrite were systematically investigated by micro-flotation tests, infrared spectra studies, X-ray photoelectron spectroscopy analysis (XPS), first-principles density functional theory calculations and theoretical analysis of the coordination field. The micro-flotation tests showed that the recovery rate of pyrite reduced with the growth of pH, but the recovery rate of chalcopyrite was basically unchanged. The infrared spectra analysis revealed that the intensities of the characteristic xanthate peaks of the C=S and C-O-C groups in the Fe3+-treated pyrite surface changed more noticeably than those of the xanthate peaks of the Fe3+-treated chalcopyrite. XPS showed that Fe (OH)3 was more easily and spontaneously adsorbed on pyrite than chalcopyrite surfaces. First-principles DFT calculations and electronic structure analysis further showed that pyrite had a stronger adsorption of Fe (OH)3 than chalcopyrite. This work sheds new light on the adsorption mechanism of Fe3+ on the surfaces of chalcopyrite and pyrite during flotation. [ABSTRACT FROM AUTHOR]

The PI3K/AKT pathway plays an essential role in tumour development. NOD-like receptors (NLRs) regulate innate immunity and are implicated in cancer, but whether they are involved in PI3K/AKT pathway regulation is poorly understood. Here, we report that NLRP6 potentiates the PI3K/AKT pathway by binding and destabilizing p85α, the regulatory subunit of PI3K. Mechanistically, NLRP6 recruits the E3 ligase RBX1 to p85α and ubiquitinates lysine 256 on p85α, which is recognized by the autophagy cargo receptor OPTN, causing selective autophagic degradation of p85α and subsequent activation of the PI3K/AKT pathway by reducing PTEN stability. We further show that loss of NLRP6 suppresses cell proliferation, colony formation, cell migration, and tumour growth in glioblastoma cells in vitro and in vivo. Disruption of the NLRP6/p85α interaction using the Pep9 peptide inhibits the PI3K/AKT pathway and generates potent antitumour effects. Collectively, our results suggest that NLRP6 promotes p85α degradation via selective autophagy to drive tumorigenesis, and the interaction between NLRP6 and p85α can be a promising therapeutic target for tumour treatment. The crosstalk between innate immunity and autophagy plays a critical role in cancer. Here, the authors report that an immune receptor NLRP6 potentiates the PI3K/AKT pathway by selective degradation of p85α. The NLRP6-p85α interaction offers a potential therapeutic target for tumor treatment. [ABSTRACT FROM AUTHOR]

Mode-pairing quantum key distribution (MP-QKD) is a potential protocol that is not only immune to all possible detector side channel attacks, but also breaks the repeaterless rate-transmittance bound without needing global phase locking. Here we analyze the finite-key effect for the MP-QKD protocol with rigorous security proof against general attacks. Moreover, we propose a six-state MP-QKD protocol and analyze its finite-key effect. The results show that the original protocol can break the repeaterless rate-transmittance bound with a typical finite number of pulses in practice. And our six-state protocol can improve the secret key rate significantly in long distance cases. Mode-pairing quantum key distribution (MP-QKD) is a potential protocol. Here the authors analyze the finite-key effect for the MPQKD protocol with rigorous security proof against general attacks. And they propose a six-state MP-QKD protocol and analyze its finite key effect. [ABSTRACT FROM AUTHOR]

In recent years, peer-to-peer (P2P) as a means of content distribution and sharing service are receiving extensive attention. In this paper, the hybrid P2P network structure model is combined with the knowledge of queueing theory. In order to address the problem generated by unnecessary online behavior of nodes, the working sleep mechanism for the serving nodes is introduced, and the synchronous multiple working vacation strategy is also adopted to decrease the system energy consumption. Then a queueing model with working vacation and repairable fault is built, which used to simulate the resource transmission process of P2P network and to study the performance of P2P sharing system. The steady-state probability vector is derived by employing quasi-birth-and-death process and matrix-geometric solution method. And the expressions for system performance indicators, such as the average delay, are obtained by employing Gauss–Seidel iteration method. Through numerical experiments, the performance indicators of the P2P resource sharing system are studied, which provides a theoretical basis to decrease online energy consumption of nodes in the hybrid P2P network. And through employing Nash equilibrium and social optimal strategy, the value of the social maximum benefit under the social optimization is obtained. [ABSTRACT FROM AUTHOR]

Moyamoya disease (MMD) is a chronic and progressive cerebrovascular stenosis or occlusive disease that occurs near Willis blood vessels. The aim of this study was to investigate the mutation of DIAPH1 in Asian population, and to compare the angiographic features of MMD patients with and without the mutation of the DIAPH1 gene. Blood samples of 50 patients with MMD were collected, and DIAPH1 gene mutation was detected. The angiographic involvement of the posterior cerebral artery was compared between the mutant group and the non-mutant group. The independent risk factors of posterior cerebral artery involvement were determined by multivariate logistic regression analysis. DIAPH1 gene mutation was detected in 9 (18%) of 50 patients, including 7 synonymous mutations and 2 missense mutations. However, the incidence of posterior cerebral artery involvement in mutation positive group was very higher than that in mutation negative group (77.8% versus 12%; p = 0.001). There is an association between DIAPH1 mutation and PCA involvement (odds ratio 29.483, 95% confidence interval 3.920–221.736; p = 0.001). DIAPH1 gene mutation is not a major genetic risk gene for Asian patients with moyamoya disease but may play an important role in the involvement of posterior cerebral artery. [ABSTRACT FROM AUTHOR]

Due to the high hardness and wear resistance of SiC particles, severe tool wear was prevalent when cutting SiC particles-reinforced aluminum matrix (SiCp/Al) composites with traditional machining methods. This paper aims to comprehensively investigate the feasibility of laser cutting SiCp/Al composites with high volume fraction of SiC particles under different processing parameters. Surface morphology and cross-section characteristics were analyzed for further understanding laser–SiCp/Al composite interaction/removal mechanisms. Results showed that high specific energy was the most significant factor affecting surface quality during laser cutting SiCp/Al composites, and the threshold value was ~ 90 J/mm for successfully cutting through 1.0-mm-thick samples and ~ 450 J/mm for 5.0-mm-thick ones. Stripes, re-solidified materials, dross and spatters were typical defects observed during high-power fiber laser cutting SiCp/Al composites with high volume fraction. The experimental results can most likely bring new knowledge to understand the characteristics of thermal defect and heat conduction following high-efficient fiber laser cutting SiCp/Al composites and also provide data for applying high-power fiber laser in advanced automotive/aerospace industry for future applications. [ABSTRACT FROM AUTHOR]

Ectoine has gained considerable attention as a high-value chemical with significant application potential and market demand. This study aimed to increase ectoine yields by blocking the metabolic shunt pathway of l-aspartate-4-semialdehyde, the precursor substrate in ectoine synthesis. The homoserine dehydrogenase encoded by hom in H. campaniensis strain XH26 is responsible for the metabolic shunt of l-aspartate-4-semialdehyde to glycine. CRISPR/Cas9 technology was used to seamlessly knockout hom, blocking the metabolic shunt pathway to increase ectoine yields. The ectoine yield of XH26/Δhom was 351.13 mg (g CDW)−1 after 48 h of incubation in 500 mL shake flasks using optimal medium with 1.5 mol L−1 NaCl, which was significantly higher than the 239.18 mg (g CDW)−1 of the wild-type strain. Additionally, the absence of the ectoine metabolic shunt pathway affects betaine synthesis, and thus the betaine yields of XH26/Δhom was 19.98 mg (g CDW)−1, considerably lower than the 69.58 mg (g CDW)−1 of the wild-type strain. Batch fermentation parameters were optimized, and the wild-type strain and XH26/Δhom were fermented in 3 L fermenters, resulting in a high ectoine yield of 587.09 mg (g CDW)−1 for the defective strain, which was significantly greater than the ectoine yield of 385.03 mg (g CDW)−1 of the wild-type strain. This study showed that blocking the metabolic shunt of synthetic substrates effectively increases ectoine production, and a reduction in the competitively compatible solute betaine appears to promote increased ectoine synthesis. [ABSTRACT FROM AUTHOR]

When plates with edge cracks in the rolling process is straightened by cyclic tensile and compressive stress, the tip of edge crack always accompanied by stress concentration, which leads to crack propagation. In this paper, damage parameters are imported into the plate straightening model based on determining the GTN damage parameters of magnesium alloy materials by inverse finite element calibration method, the influence of different straightening process schemes and prefabricated V-shaped crack geometry on crack growth is analyzed through the way of the combination of simulation and straightening experiment. The results show that the peak values of equivalent stress and equivalent strain under each straightening roll appear at the crack tip. The value of longitudinal stress and equivalent stain decrease with the distance to crack tip becomes larger. The peak value of longitudinal stress appears when the crack circumferential angle is about 100°, and the crack tip is easy to form crack propagation; when the plate passes roll 2 and roll 4, the equivalent stress and strain concentration at the crack tip are most obvious; when the reduction reaches a certain degree, the void volume fraction (VVF) reaches the VVF of the material breaking; with the increase of the entrance reduction, the number of VVF at the crack tip which reaches the material fracture increases, and the length of crack propagation increases; the stress concentration at the tip of V-shaped crack with large length–width ratio is obvious, and the VVF is more likely to reach the VVF at the time of material fracture, crack initiates and propagates easily. [ABSTRACT FROM AUTHOR]

Moso bamboo has been shown to accumulate high concentrations of iron and zinc in the seeds. However, the bioavailablity of iron and zinc in bamboo seeds is poorly understood. Here, we evaluated the bioaccessibility and bioavailability of iron and zinc in bamboo seeds by using an in vitro digestion protocol. Our evaluations revealed that values of bioaccessibility and bioavailability of iron were 25 and 21 mg kg−1 in bamboo seeds which were 1.6- and 1.7- fold higher than in rice, respectively. Also, values of bioaccessibility and bioavailability of zinc were 20 and 13 mg kg−1 in bamboo seeds which were 1.9- and 2.6- fold higher than in rice, respectively. Boiling process reduced both the bioaccessibility and bioavailability of iron and zinc. In addition, phytic acid concentration in bamboo seeds was only 0.42 times higher than in rice. By contrast, the tannins concentration in bamboo seeds was 2.2 times higher than in rice. Cellular localization results showed that iron and zinc were mainly concentrated in the embryo and the aleurone layer. These results clearly suggest that Moso bamboo seeds are rich in iron and zinc and have potential as a food for iron and zinc biofortification. [ABSTRACT FROM AUTHOR]

Schizophrenia is a severe psychotic disorder characterized by positive and negative symptoms, but their neural bases remain poorly understood. Here, we utilized a nested-spectral partition (NSP) approach to detect hierarchical modules in resting-state brain functional networks in schizophrenia patients and healthy controls, and we studied dynamic transitions of segregation and integration as well as their relationships with clinical symptoms. Schizophrenia brains showed a more stable integrating process and a more variable segregating process, thus maintaining higher segregation, especially in the limbic system. Hallucinations were associated with higher integration in attention systems, and avolition was related to a more variable segregating process in default-mode network (DMN) and control systems. In a machine-learning model, NSP-based features outperformed graph measures at predicting positive and negative symptoms. Multivariate analysis confirmed that positive and negative symptoms had opposite effects on dynamic segregation and integration of brain networks. Gene ontology analysis revealed that the effect of negative symptoms was related to autistic, aggressive and violent behavior; the effect of positive symptoms was associated with hyperammonemia and acidosis; and the interaction effect was correlated with abnormal motor function. Our findings could contribute to the development of more accurate diagnostic criteria for positive and negative symptoms in schizophrenia. Nested spectral partition (NSP) method, fMRI data, machine learning and gene otology analysis show that positive and negative symptoms of schizophrenia have opposite effects on the functional organization of resting-state brains. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced plastic (CFRP) composites exhibit great potential in repairing damaged metallic structures. This work aims to investigate the influences of working temperature on the mechanical performance of adhesively bonded CFRP repair of Ti6Al4V substrate with various central inclined cracks including strength recovery rate, failure displacement, energy absorption and failure modes. Differential scanning calorimeter (DSC) measurement was first performed under nitrogen environment to identify the glass transformation temperature (Tg) of adhesive and CFRP. Digital image correlation (DIC) technique was carried out to study the full-field strain distribution and damage evolution of repaired structures. Results showed that the repaired structures possessed the best repair effectiveness at the temperature of 80 °C, regardless of the types of original central inclined cracks. The failure mode was identified, and corresponding mechanisms were investigated. It was found that the working temperature presented limited influence on failure mode, and the dominant one was interfacial failure. The failure strength of repaired structures was mainly affected by the properties of adhesive rather than CFRP laminates. [ABSTRACT FROM AUTHOR]

Temporal control of delivery and release of drugs in tumors are important in improving therapeutic outcomes to patients. Here, we report a sequential stimuli-triggered in situ self-assembly and disassembly strategy to direct delivery and release of theranostic drugs in vivo. Using cisplatin as a model anticancer drug, we design a stimuli-responsive small-molecule cisplatin prodrug (P-CyPt), which undergoes extracellular alkaline phosphatase-triggered in situ self-assembly and succeeding intracellular glutathione-triggered disassembly process, allowing to enhance accumulation and elicit burst release of cisplatin in tumor cells. Compared with cisplatin, P-CyPt greatly improves antitumor efficacy while mitigates off-target toxicity in mice with subcutaneous HeLa tumors and orthotopic HepG2 liver tumors after systemic administration. Moreover, P-CyPt also produces activated near-infrared fluorescence (at 710 nm) and dual photoacoustic imaging signals (at 700 and 750 nm), permitting high sensitivity and spatial-resolution delineation of tumor foci and real-time monitoring of drug delivery and release in vivo. This strategy leverages the advantages offered by in situ self-assembly with those of intracellular disassembly, which may act as a general platform for the design of prodrugs capable of improving drug delivery for cancer theranostics. Manipulating molecular self-assembly and disassembly in vivo may permit temporal control of drug delivery and release. Here, the authors report a fluorogenic cisplatin prodrug for cancer theranostics by leveraging stimuli-triggered in situ self-assembly and intracellular disassembly processes. [ABSTRACT FROM AUTHOR]

Due to the interest in the potential pharmacological application of dandelion, the chemical constituents and activities of Taraxacum mongolicum Hand.-Mazz were studied. Box–Behnken response surface methodology was employed to optimize the protocol for extraction of flavonoid from dandelion. The molecular structures of different flavonoid compounds were acquired and analyzed by liquid chromatography-mass spectrometry (LC–MS) and nuclear magnetic resonance (NMR) spectroscopy. Several major flavonoid compounds were isolated and purified, namely, hesperetin-5′-O-β-rhamnoglucoside, hesperetin-7-glucuronide, kaempferol-3-glucoside, baicalein, hyperseroside, which were extracted for the first time from dandelion. Hesperetin-5′-O-β-rhamnoglucoside was identified as a new type of flavonoid that had never reported in the literature. This new flavonoid has outstanding antioxidant activity, as shown by its IC50 value (8.72 mg/L) for scavenging DPPH free radicals. The determination of the structure-related antioxidant activities could be interpreted based on DFT calculations. As such, we have not only illustrated the rich flavonoid contents in Taraxacum mongolicum Hand.-Mazz, but also revealed new types of flavonoid compounds in dandelion in terms of structure and antioxidant properties. [ABSTRACT FROM AUTHOR]

The results revealed varying levels of magnitude and breadth in neutralizing antibodies against live SARS-CoV-2 (wild-type, delta [B.1.617.2] and omicron [BA.1.1]) across four vaccines, with the mRNA vaccine RQ3013 demonstrating the highest levels of neutralizing antibodies[5]. Interestingly, the recombinant protein vaccine ZR202-CoV with CpG as adjuvant and the adenovirus-vectored vaccine ChAdTS-S showed much slower decline rates against omicron variants compared with the mRNA vaccine RQ3013 (2-4-fold vs 4-11-fold decrease, respectively). These authors contributed equally: Yuemiao Zhang, Meng-Ting Luo Dear Editor, As of July 2022, over 89% of Chinese population have finished COVID-19 vaccine primary immunization, mostly with two-dose inactivated vaccines. [Extracted from the article]

Acute lymphoblastic leukemia (ALL) is the most common type of cancer in children (age 0–14 years); however, the etiology remains incompletely understood. Several environmental exposures have been linked to risk of childhood ALL, including air pollution. Closely related to air pollution and human development is artificial light at night (ALAN), which is believed to disrupt circadian rhythm and impact health. We sought to evaluate outdoor ALAN and air pollution on risk of childhood ALL. The California Linkage Study of Early-Onset Cancers is a large population-based case–control in California that identifies and links cancer diagnoses from the California Cancer Registry to birth records. For each case, 50 controls with the same year of birth were obtained from birth records. A total of 2,782 ALL cases and 139,100 controls were identified during 2000–2015. ALAN was assessed with the New World Atlas of Artificial Night Sky Brightness and air pollution with an ensemble-based air pollution model of particulate matter smaller than 2.5 microns (PM2.5). After adjusting for known and suspected risk factors, the highest tertile of ALAN was associated with an increased risk of ALL in Hispanic children (odds ratio [OR] = 1.15, 95% confidence interval [CI] 1.01–1.32). There also appeared to be a borderline association between PM2.5 level and risk of ALL among non-Hispanic White children (OR per 10 µg/m3 = 1.24, 95% CI 0.98–1.56). We observed elevated risk of ALL in Hispanic children residing in areas of greater ALAN. Further work is needed to understand the role of ALAN and air pollution in the etiology of childhood ALL in different racial/ethnic groups. [ABSTRACT FROM AUTHOR]

There are growing demands for multimaterial three-dimensional (3D) printing to manufacture 3D object where voxels with different properties and functions are precisely arranged. Digital light processing (DLP) is a high-resolution fast-speed 3D printing technology suitable for various materials. However, multimaterial 3D printing is challenging for DLP as the current multimaterial switching methods require direct contact onto the printed part to remove residual resin. Here we report a DLP-based centrifugal multimaterial (CM) 3D printing method to generate large-volume heterogeneous 3D objects where composition, property and function are programmable at voxel scale. Centrifugal force enables non-contact, high-efficiency multimaterial switching, so that the CM 3D printer can print heterogenous 3D structures in large area (up to 180 mm × 130 mm) made of materials ranging from hydrogels to functional polymers, and even ceramics. Our CM 3D printing method exhibits excellent capability of fabricating digital materials, soft robots, and ceramic devices. Multimaterial 3D printing using digital light processing (DLP) is challenging because multimaterial switching methods require direct contact onto the printed part to remove residual resin. Here, the authors report a DLP-based centrifugal multimaterial 3D printing method to generate large-volume heterogeneous 3D objects where composition, property and function are programmable at voxel scale. [ABSTRACT FROM AUTHOR]

The development of transition metal-catalyzed β-C–H bond activation via highly-strained 4-membered metallacycles has been a formidable task. So far, only scarce examples have been reported to undergo β-C–H bond activation via 4-membered metallacycles, and all of them rely on precious metals. In contrast, earth-abundant and inexpensive 3d transition metal-catalyzed β-C–H bond activation via 4-membered metallacycles still remains an elusive challenge. Herein, we report a phosphine oxide-ligated Ni−Al bimetallic catalyst to activate secondary benzylic C(sp3)–H bonds of formamides via 4-membered nickelacycles, providing a series of α,β-unsaturated γ-lactams in up to 97% yield. The development of 3d-metal-catalyzed β-C–H bond activation via 4-membered metallacycles remains an elusive challenge. Here, the authors report a Ni-Al bimetal-catalyzed β-C(sp3)–H bond activation of formamides via 4-membered nickelacycles. [ABSTRACT FROM AUTHOR]

Programmed death ligand 1 (PD-L1) has been shown to be inducibly expressed on neutrophils to suppress host immunity during polymicrobial sepsis, virus and parasite infections. However, the role of PD-L1 on neutrophil-mediated antifungal immunity remains wholly unknown. Here, we show that the expression of PD-L1 on murine and human neutrophils was upregulated upon the engagement of C-type lectin receptor Dectin-1 with its ligand β-glucans, exposed on fungal pathogen Candida albicans yeast. Moreover, β-glucan stimulation induced PD-L1 translocation into nucleus to regulate the production of chemokines CXCL1 and CXCL2, which control neutrophil mobilization. Importantly, C. albicans infection-induced expression of PD-L1 leads to neutrophil accumulation in bone marrow, through mediating their autocrine secretion of CXCL1/2. Furthermore, neutrophil-specific deficiency of PD-L1 impaired CXCL1/2 secretion, which promoted neutrophil migration from bone marrow into the peripheral circulation, thereby conferring host resistance to C. albicans infection. Finally, either PD-L1 blockade or pharmacological inhibition of PD-L1 expression significantly increased neutrophil release from bone marrow to enhance host antifungal immunity. Our data together indicate that activation of Dectin-1/PD-L1 cascade by β-glucans inhibits neutrophil release from bone marrow reserve, contributing to the negative regulation of antifungal innate immunity, which functions as a potent immunotherapeutic target against life-threatening fungi infections. Programmed death ligand 1 (PD-L1) suppresses host immunity during infection and microbial sepsis. Here, the authors show that PD-L1 does this by regulating the secretion of CXCL1 and CXCL2 to control neutrophil mobilization during Candida albicans infection. [ABSTRACT FROM AUTHOR]

Hemorrhagic events are the main focus of attention during antithrombosis therapy in patients with coronary artery disease (CAD). This study aims to investigate the potential of using photoplethysmography (PPG) and machine learning techniques to assess hemorrhagic risk in patients with CAD. A total of 1638 patients with CAD were enrolled from January 2018 to October 2019, among which 114 patients were observed to have at least one positive event. Importantly, 102 patients with 9933 records were finally retained for analysis in this study. Participants were required to collect data using the portable PPG acquisition device and the specially designed Android APP. The data was collected and uploaded to a remote server. Based on collected PPG signals, we extracted features in a total of 30 dimensions from time-domain, frequency-domain, and wavelet packet decomposition. Logistic regression, support vector regression, random forest, and XGBoost regression models were established to achieve hemorrhagic risk evaluation, and then, their performances were compared. In total, 10 features extracted from PPG showed statistical significance (p < 0.01) between negative and positive groups. The newly established XGBoost model performed best in the hemorrhagic risk evaluation experiment, wherein the mean area under the curve (AUC) with tenfold cross-validation was 0.762 ± 0.024 and the sensitivity and specificity were 0.679 ± 0.051 and 0.714 ± 0.014, respectively. We established a data acquisition system for PPG signal collection, and demonstrated that a set of features extracted from PPG and the proposed machine learning model are promising in the evaluation of hemorrhagic risk among patients with CAD. In comparison with the traditional HAS-BLED score, the proposed method can obtain the quantitative risk prediction probability from a single PPG record, which has the advantages of dynamics and continuity, and can provide timely feedback for doctors' antithrombotic treatment, which is of great significance for doctors to quickly determine the effectiveness of the treatment and adjust the timely treatment plans accordingly. [ABSTRACT FROM AUTHOR]

Uveitis is a severe autoimmune disease, and a common cause of blindness; however, its individual cellular dynamics and pathogenic mechanism remain poorly understood. Herein, by performing single-cell RNA sequencing (scRNA-seq) on experimental autoimmune uveitis (EAU), we identify disease-associated alterations in cell composition and transcriptional regulation as the disease progressed, as well as a disease-related molecule, PIM1. Inhibiting PIM1 reduces the Th17 cell proportion and increases the Treg cell proportion, likely due to regulation of PIM1 to the protein kinase B (AKT)/Forkhead box O1 (FOXO1) pathway. Moreover, inhibiting PIM1 reduces Th17 cell pathogenicity and reduces plasma cell differentiation. Importantly, the upregulation of PIM1 in CD4+ T cells and plasma cells is conserved in a human uveitis, Vogt-Koyanagi-Harada disease (VKH), and inhibition of PIM1 reduces CD4+ T and B cell expansion. Collectively, a dynamic immune cellular atlas during uveitis is developed and implicate that PIM1 may be a potential therapeutic target for VKH. Uveitis is a complex autoimmune inflammatory disease of the eye and defining molecules involved is a priority. Here the authors use scRNA sequencing in mouse experimental autoimmune uveitis (EAU) and show PIM1 promotes the imbalance of Th17 and Treg cells, and find elevated PIM-1 in human uveitis disease. [ABSTRACT FROM AUTHOR]

Diabetic nephropathy (DN), an important complication of diabetic microvascular disease, is one of the leading causes of end-stage renal disease (ESRD), which brings heavy burdens to the whole society. Podocytes are terminally differentiated glomerular cells, which act as a pivotal component of glomerular filtration barrier. When podocytes are injured, glomerular filtration barrier is damaged, and proteinuria would occur. Dysfunction of podocytes contributes to DN. And degrees of podocyte injury influence prognosis of DN. Growing evidences have shown that epigenetics does a lot in the evolvement of podocyte injury. Epigenetics includes DNA methylation, histone modification, and non-coding RNA. Among them, histone modification plays an indelible role. Histone modification includes histone methylation, histone acetylation, and other modifications such as histone phosphorylation, histone ubiquitination, histone ADP-ribosylation, histone crotonylation, and histone β-hydroxybutyrylation. It can affect chromatin structure and regulate gene transcription to exert its function. This review is to summarize documents about pathogenesis of podocyte injury, most importantly, histone modification of podocyte injury in DN recently to provide new ideas for further molecular research, diagnosis, and treatment. [ABSTRACT FROM AUTHOR]