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Abstract The Ediacaran Period marks a pivotal time in geodynamo evolution when the geomagnetic field is thought to approach the weak state where kinetic energy exceeds magnetic energy, as manifested by an extremely high frequency of polarity reversals, high secular variation, and an ultralow dipole field strength. However, how the geodynamo transitioned from this state into one with more stable field behavior is unknown. Here, we address this issue through a high-resolution magnetostratigraphic investigation of the ~494.5 million-year-old Jiangshanian Global Standard Stratotype and Point (GSSP) section in South China. Our paleomagnetic results document zones with rapid reversals, stable polarity and a ~80 thousand-year-long interval without a geocentric axial dipole field. From these changes, we suggest that for most of the Cambrian, the solid inner core had not yet grown to a size sufficiently large to stabilize the geodynamo. This unusual field behavior can explain paleomagnetic data used to define paradoxical true polar wander, supporting instead the rotational stability of the solid Earth during the great radiation of life in the Cambrian.

Abstract Sterol carrier protein 2 (SCP2) is highly expressed in human osteoarthritis (OA) cartilage, accompanied by ferroptosis hallmarks, especially the accumulation of lipid hydroperoxides (LPO). However, the role of SCP2 in chondrocyte ferroptosis remains unexplored. Here, we identify that SCP2 transports cytoplasmic LPO to mitochondria in RSL3-induced chondrocyte ferroptosis, resulting in mitochondrial membrane damage and release of reactive oxygen species (ROS). The localization of SCP2 on mitochondria is associated with mitochondrial membrane potential, but independent of microtubules transport or voltage-dependent anion channel. Moreover, SCP2 promotes lysosomal LPO increase and lysosomal membrane damage through elevating ROS. However, SCP2 is not directly involved in the cell membrane rupture caused by RSL3. Inhibition of SCP2 markedly protects mitochondria and reduces LPO levels, attenuating chondrocyte ferroptosis in vitro and alleviating the progression of OA in rats. Our study demonstrates that SCP2 mediates the transport of cytoplasmic LPO to mitochondria and the spread of intracellular LPO, accelerating chondrocyte ferroptosis.

Conclusions: T-tube is safe and effective in the treatment of SBAS. The severity of secretion retention increased in patients with long-term placement of the T-tube. For patients with mild stenosis and anatomical stenosis, the T-tube removal can be attempted at about 1 year of follow-up.

IntroductionWheat is a food crop with a large global cultivation area, and the content and quality of wheat glutenin accumulation are important indicators of the quality of wheat flour.MethodsTo elucidate the gene expression regulation and metabolic characteristics related to the gluten content during wheat grain formation, transcriptomic and metabolomic analyses were performed for the high gluten content of the Xinchun 26 cultivar and the low proteins content of the Xinchun 34 cultivar at three periods (7 d, 14 d and 21 d) after flowering.ResultsTranscriptomic analysis revealed that 5573 unique differentially expressed genes (DEGs) were divided into two categories according to their expression patterns during the three periods. The metabolites detected were mainly divided into 12 classes. Lipid and lipid-like molecule levels and phenylpropanoid and polyketide levels were the highest, and the difference analysis revealed a total of 10 differentially regulated metabolites (DRMs) over the three periods. Joint analysis revealed that the DEGs and DRMs were significantly enriched in starch and sucrose metabolism; the citrate cycle; carbon fixation in photosynthetic organisms; and alanine, aspartate and glutamate metabolism pathways. The genes and contents of the sucrose and gluten synthesis pathways were analysed, and the correlation between gluten content and its related genes was calculated. Based on weighted correlation network analysis (WGCNA), by constructing a coexpression network, a total of 5 specific modules and 8 candidate genes that were strongly correlated with the three developmental stages of wheat grain were identified.DiscussionThis study provides new insights into the role of glutenin content in wheat grain formation and reveals potential regulatory pathways and candidate genes involved in this developmental process.

BackgroundsUAVs for crop protection hold significant potential for application in mountainous orchard areas in China. However, certain issues pertaining to UAV spraying need to be addressed for further technological advancement, aimed at enhancing crop protection efficiency and reducing pesticide usage. These challenges include the potential for droplet drift, limited capacity for pesticide solution. Consequently, efforts are required to overcome these limitations and optimize UAV spraying technology.MethodsIn order to balance high deposition and low drift in plant protection UAV spraying, this study proposes a plant protection UAV spraying method. In order to study the operational effects of this spraying method, this study conducted a UAV spray and grid impact test to investigate the effects of different operational parameters on droplet deposition and drift. Meanwhile, a spray model was constructed using machine learning techniques to predict the spraying effect of this method.Results and discussionThis study investigated the droplet deposition rate and downwind drift rate on three types of citrus trees: traditional densely planted trees, dwarf trees, and hedged trees, considering different particle sizes and UAV flight altitudes. Analyzing the effect of increasing the grid on droplet coverage and deposition density for different tree forms. The findings demonstrated a significantly improved droplet deposition rate on dwarf and hedged citrus trees compared to traditional densely planted trees and adopting a fixed-height grid increased droplet coverage and deposition density for both the densely planted and trellised citrus trees, but had the opposite effect on dwarfed citrus trees. When using the grid system. Among the factors examined, the height of the sampling point exhibited the greatest influence on the droplet deposition rate, whereas UAV flight height and droplet particle size had no significant impact. The distance in relation to wind direction had the most substantial effect on droplet drift rate. In terms of predicting droplet drift rate, the BP neural network performed inadequately with a coefficient of determination of 0.88. Conversely, REGRESS, ELM, and RBFNN yielded similar and notably superior results with a coefficient of determination greater than 0.95. Notably, ELM demonstrated the smallest root mean square error.

Urbanization causes immense eutrophication pressure on small urban wetlands, which play a vital role in urban ecosystems. However, our comprehension of the prolonged impacts of eutrophication on these types of wetlands continues to be significantly limited. To address this knowledge gap, we analyzed monthly physical–chemical variables and seasonal phytoplankton and zooplankton communities at the Taipa-Coloane wetland in Macau, China, from 2013 to 2019. Through the generalized additive model (GAM) and principal component analysis (PCA), we found that the aquatic system mainly exhibited interannual variations instead of seasonal variations, with nutrient loads and river discharge (turbidity and salinity) being the most prominent features affected by anthropogenic activities and climate change. Over the years, the increasing turbidity and phytoplankton showed that bottom-up effects predominated the aquatic systems. Under the bottom-up effects of eutrophication and turbidity, the phytoplankton communities showed high adaptation that MP and S1 occupied more dominance after 2016, with higher abundance but lower diversity. Moreover, the bottom-up effects further affected the structure of zooplankton communities. The dominance of rotifers filter feeders (RF) decreased over the years while middle copepods and cladocerans filter feeders (MCF) increased, implying a trend of zooplankton toward large size over time. Overall, our result reveals the bottom-up control pattern in the aquatic systems of small urban wetlands. This research provides valuable insights into the dynamics and responses of plankton communities to environmental changes in small urban wetlands, providing valuable information for future conservation efforts.

In order to effectively control and predict the settlement deformation of the surrounding ground surface caused by deep foundation excavation, the deep foundation pit project of Baoding City Automobile Technology Industrial Park is explored as an example. The initial population approach of the whale algorithm (WOA) is optimized using Cubic mapping, while the weights of the shrinkage envelope mechanism are adjusted to avoid the algorithm falling into local minima, the improved whale algorithm (IWOA) is proposed. Meanwhile, 10 benchmark test functions are selected to simulate the performance of IWOA, and the advantages of IWOA in learning efficiency and convergence speed are verified. The IWOA-LSTM deep foundation excavation deformation prediction model is established by optimizing the input weights and hidden layer thresholds in the deep long short-term memory (LSTM) neural network using the improved whale algorithm. The IWOA-LSTM prediction model is compared with LSTM, WOA-optimized LSTM (WOA-LSTM) and traditional machine learning, the results show that the final prediction score of the IWOA-LSTM prediction model is higher than the score of other models, and the prediction accuracy is better than that of traditional machine learning.

Abstract Background In a significant proportion of cancers, point mutations of TP53 gene occur within the DNA-binding domain, resulting in an abundance of mutant p53 proteins (mutp53) within cells, which possess tumor-promoting properties. A potential and straightforward strategy for addressing p53-mutated cancer involves the induction of autophagy or proteasomal degradation. Based on the previously reported findings, elevating oxidative state in the mutp53 cells represented a feasible approach for targeting mutp53. However, the nanoparticles previous reported lacked sufficient specificity of regulating ROS in tumor cells, consequently resulted in unfavorable toxicity in healthy cells. Results We here in showed that cerium oxide CeO2 nanoparticles (CeO2 NPs) exhibited an remarkable elevated level of ROS production in tumor cells, as compared to healthy cells, demonstrating that the unique property of CeO2 NPs in cancer cells provided a feasible solution to mutp53 degradation. CeO2 NPs elicited K48 ubiquitination-dependent degradation of wide-spectrum mutp53 proteins in a manner that was dependent on both the dissociation of mutp53 from the heat shock proteins Hsp90/70 and the increasing production of ROS. As expected, degradation of mutp53 by CeO2 NPs abrogated mutp53-manifested gain-of-function (GOF), leading to a reduction in cell proliferation and migration, and dramatically improved the therapeutic efficacy in a BxPC-3 mutp53 tumor model. Conclusions Overall, CeO2 NPs increasing ROS specifically in the mutp53 cancer cells displayed a specific therapeutic efficacy in mutp53 cancer and offered an effective solution to address the challenges posed by mutp53 degradation, as demonstrated in our present study.

Abstract Background HER2-low could be found in some patients with triple-negative breast cancer (TNBC). However, its potential impacts on clinical features and tumor biological characteristics in TNBC remain unclear. Methods We enrolled 251 consecutive TNBC patients retrospectively, including 157 HER2-low (HER2low) and 94 HER2-negtive (HER2neg) patients to investigate the clinical and prognostic features. Then, we performed single-cell RNA sequencing (scRNA-seq) with another seven TNBC samples (HER2neg vs. HER2low, 4 vs. 3) prospectively to further explore the differences of tumor biological properties between the two TNBC phenotypes. The underlying molecular distinctions were also explored and then verified in the additional TNBC samples. Results Compared with HER2neg TNBC, HER2low TNBC patients exhibited malignant clinical features with larger tumor size (P = 0.04), more lymph nodes involvement (P = 0.02), higher histological grade of lesions (P

Despite the natural abundance and promising properties of Si, there are few examples of crystalline Si-based catalysts. Here, the authors report an epitaxial growth method to construct Co single atoms on Si for light driven CO2 reduction to syngas.

The current challenges for diabetic cardiomyopathy (DCM) are unclear mechanisms and no effective therapy in clinics. Here, the authors found that the decrease of cardiac retinol dehydrogenase 10 in type 2 diabetes leads to retinol metabolism disorder, cardiac lipid toxicity and cardiomyopathy development, suggesting that correcting the imbalance of cardiac retinol metabolism may be an effective strategy for the treatment of DCM.

Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction is one of the most challenging problems in computational biology and chemistry, and has puzzled scientists for 50 years. The advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much attention. Subsequent release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community, especially in the fields of biology and medicine. AF2 is thought to have a significant impact on structural biology and research areas that need protein structure information, such as drug discovery, protein design, prediction of protein function, et al. Though the time is not long since AF2 was developed, there are already quite a few application studies of AF2 in the fields of biology and medicine, with many of them having preliminarily proved the potential of AF2. To better understand AF2 and promote its applications, we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success, and particularly focus on reviewing its applications in the fields of biology and medicine. Limitations of current AF2 prediction will also be discussed.

For the complex structure of fibrous network materials, it is a challenge to analyze the network strength and deformation mechanism. Here, we identify a failure mode transition within the network material comprising brittle fibers and bonds, which is related to the strength ratio of the bond to the fiber. A failure criterion for this type of fibrous network is proposed to quantitatively characterize this transition between bond damage and fiber damage. Additionally, tensile experiments on carbon and ceramic fibrous network materials were conducted, and the experimental results show that the failure modes of these network materials satisfy the theoretical prediction. The relationship between the failure mode, the relative density of network and strength of the components is established based on finite element analysis of the 3D network model. The failure mode transforms from bond damage to fiber damage as increasing of bond strength. According to the transition of the failure modes in the brittle fibrous network, it is possible to tailor the mechanical properties of fibrous network material by balancing the competition between bond and fiber properties, which is significant for optimizing material design and engineering applications.

When addressing the technical challenges of achieving precise force tracking during the local polishing process of polishing robots, controlling the contact state between the robot and the workpiece surface is essential. To this end, a contact motion-planning strategy based on dynamic systems is designed to generate trajectory routes during local polishing. The trajectory simulation of the local modulation dynamic system is achieved through the employment of the support vector regression (SVR) algorithm with a Gaussian kernel, facilitating the learning process. The feasibility and stability of planning local paths are validated using the local modulation dynamic system. To maintain a constant contact force between the end-effector polishing robot and the workpiece, an integral adaptive impedance control strategy is utilized, enabling the robot’s compliant control. Subsequently, an experimental system for the polishing robot is constructed in order to verify the effectiveness of the motion-planning system. The experimental results demonstrate that the proposed motion-planning approach is applicable in practical polishing processes, ensuring smooth contact and maintaining the desired contact force when scanning nonlinear surfaces, and thus showcasing stability and practicality.

The application of deoiling hydrocyclone systems as the downstream of three-phase gravity separator (TPGS) systems is one of the most commonly deployed produced water treatment processes in offshore oil and gas production. Due to the compact system’s complexity and tailor-made features, it is always challenging to develop some optimally coordinated control solution for the coupled hydrocyclone and TPGS systems. It is obvious that coordinated control can better fulfill legislative discharge regulation by robustly maintaining high separation efficiencies. This paper presents a new control solution for a set of integrated hydrocyclone and TPGS systems by applying an improved multi-variable model reference adaptive control (MV-MRAC) approach with the aim of achieving both asymptotic output tracking and unknown disturbance rejection. A robust MV-MRAC controller design is proposed based on a control parameterization derived from a factorization of a high-frequency gain matrix Kp=LDS as a product of three matrices, where L represents unity lower triangular, D=sign(D) represents diagonal, and S represents positive definite, and a teaching–learning-based optimization (TLBO) algorithm for optimizing the adaption rates. The developed solution is analyzed and compared with a commonly deployed PI control solution on a model that is derived from a lab-scale produced water treatment process. This simulation study demonstrates the promising potential of the proposed control solution compared with the currently deployed PI control solution.

Abstract Growth strata are important for understanding regional tectonic evolution. However, it is difficult to identify growth strata in the field, because of subsequent intensive modification and erosion. To address this problem, we studied two paleomagnetic sections at the stable deposition setting and the growth end of the Miocene growth strata of the Gengma Basin. Average inclinations of the two sections show a systematic deviation of 4.7° ± 5.2°. The anisotropy of magnetic susceptibility results for the growth end of the section A demonstrate a sedimentary fabric. However, the tilt‐corrected K3 axis deviates to the southwest from the normal direction of the bedding by 5.4° ± 3.8°, the magnetic foliation deviates to the equatorial plane by 5.3° ± 4.7°. The K3 axis is perpendicular to the bedding at the stable deposition setting. The deviation of the K3 axis from the normal direction of bedding is interpreted as the growth angle, which can be used to correct the paleomagnetic inclination data.

ObjectiveTo develop a Multi-Feature-Combined (MFC) model for proof-of-concept in predicting local failure (LR) in NSCLC patients after surgery or SBRT using pre-treatment CT images. This MFC model combines handcrafted radiomic features, deep radiomic features, and patient demographic information in an integrated machine learning workflow.MethodsThe MFC model comprised three key steps. (1) Extraction of 92 handcrafted radiomic features from the GTV segmented on pre-treatment CT images. (2) Extraction of 512 deep radiomic features from pre-trained U-Net encoder. (3) The extracted handcrafted radiomic features, deep radiomic features, along with 4 patient demographic information (i.e., gender, age, tumor volume, and Charlson comorbidity index), were concatenated as a multi-dimensional input to the classifiers for LR prediction. Two NSCLC patient cohorts from our institution were investigated: (1) the surgery cohort includes 83 patients with segmentectomy or wedge resection (7 LR), and (2) the SBRT cohort includes 84 patients with lung SBRT (9 LR). The MFC model was developed and evaluated independently for both cohorts, and was subsequently compared against the prediction models based on only handcrafted radiomic features (R models), patient demographic information (PI models), and deep learning modeling (DL models). ROC with AUC was adopted to evaluate model performance with leave-one-out cross-validation (LOOCV) and 100-fold Monte Carlo random validation (MCRV). The t-test was performed to identify the statistically significant differences.ResultsIn LOOCV, the AUC range (surgery/SBRT) of the MFC model was 0.858-0.895/0.868-0.913, which was higher than the three other models: 0.356-0.480/0.322-0.650 for PI models, 0.559-0.618/0.639-0.682 for R models, and 0.809/0.843 for DL models. In 100-fold MCRV, the MFC model again showed the highest AUC results (surgery/SBRT): 0.742-0.825/0.888-0.920, which were significantly higher than PI models: 0.464-0.564/0.538-0.628, R models: 0.557-0.652/0.551-0.732, and DL models: 0.702/0.791.ConclusionWe successfully developed an MFC model that combines feature information from multiple sources for proof-of-concept prediction of LR in patients with surgical and SBRT early-stage NSCLC. Initial results suggested that incorporating pre-treatment patient information from multiple sources improves the ability to predict the risk of local failure.

Visual Question Answering (VQA) with external knowledge requires external knowledge and visual content to answer questions about images. The defect of existing VQA solutions is that they need to identify task-related information in the obtained pictures, questions, and knowledge graphs. It is necessary to properly fuse and embed the information between different modes identified, to reduce the noise and difficulty in cross-modality reasoning of VQA models. However, this process of rationally integrating information between different modes and joint reasoning to find relevant evidence to correctly predict the answer to the question still deserves further study. This paper proposes a bimodal Graph Neural Network model combining pre-trained Language Models and Knowledge Graphs (BIGNN-LM-KG). Researchers built the concepts graph by the images and questions concepts separately. In constructing the concept graph, we used the combined reasoning advantages of LM+KG. Specifically, use KG to jointly infer the images and question entity concepts to build a concept graph. Use LM to calculate the correlation score to screen the nodes and paths of the concept graph. Then, we form a visual graph from the visual and spatial features of the filtered image entities. We use the improved GNN to learn the representation of the two graphs and to predict the most likely answer by fusing the information of two different modality graphs using a modality fusion GNN. On the common dataset of VQA, the model we proposed obtains good experiment results. It also verifies the validity of each component in the model and the interpretability of the model.

Abstract Background Video‐assisted thoracoscopic surgery (VATS) is the preferred treatment for resectable non‐small cell lung cancer. The increased survival of patients after a first operation has caused increases in the incidence of locoregional recurrence or second primary lung cancer and a concomitant increase in the number of patients who require secondary surgery. Ipsilateral secondary operation is also commonly practiced, albeit with enhanced difficulty. Therefore, it is necessary to evaluate the feasibility and safety of VATS for ipsilateral lung cancer after pulmonary resection. Methods Patients who underwent ipsilateral secondary VATS in the West China Hospital, Sichuan University from 2012 to 2021 were assessed retrospectively. All included patients had a pulmonary resection. Clinical characteristics, perioperative outcomes, and survival data were collected, with an emphasis on conversion to thoracotomy, postoperative complications, 30‐day mortality, and survival. Logistic regression analysis was used to identify predictors of postoperative complications. Results Seventy patients were enrolled, of which 10 (14.3%) had converted thoracotomy, 17 (24.3%) had postoperative complications, and two (2.9%) had grade III complications. No patient died within 30 days after surgery. High Charlson comorbidity index (CCI) and severe pleural adhesion were independent predictors for complications. The median follow‐up was 50 months (range: 3–120), and the 5‐year overall survival was 78.2%. Conclusion Secondary VATS for ipsilateral lung cancer for patients who had pulmonary resection was feasible and safe. Strict preoperative evaluation and careful management of pleural adhesion are crucial for the success of the surgery.

Palaeomagnetic data from South China and compiled reliable palaeopoles from 4 other continents reveals a ~50˚ true polar wander (TPW) event occurring 450–440 million years ago. Sweeping Gondwana across the South Pole, this TPW event induced the Ordovician glaciation and mass extinction.

In order to explore the key components affecting the emulsification characteristics in hydrolyzed rice protein. rice protein was hydrolyzed by acidprotease, papain and trypsin, respectively. The relationships between the structural and functional properties of different hydrolyzed rice proteins were studied by surface hydrophobicity, Fourier transform infrared spectroscopy (FTIR), emulsifying activity index and emulsifying stability index. 10 kDa were separated from the rice protein with degree of 2% treated with trypsin (trypsin 2%) by ultrafiltration. The interfacial tension, quartz crystal microbalance with dissipation (QCM-D), mean diameter particle, confocal laser scanning microscope (CLSM) and storage stability were measured to explore the influence of molecular weight on the interfacial characterization and emulsion stability. The results demonstrated that hydrolysates treated with trypsin exhibited the highest yield. Compared with the rice protein, the surface hydrophobicity of the enzymatic hydrolysis products declined significantly except for the rice protein with degree of 6% treated with trypsin (trypsin 6%). The secondary structure content revealed that the β-sheet contents of hydrolyzed rice protein significantly decreased, showing that the structure of hydrolyzed rice protein was more unfolded. The trypsin 2% exhibited the better emulsifying capacity. The mean diameter particle of 10 kDa had lower interfacial tension and thicker interfacial film than the others. The emulsion prepared by >10 kDa exhibited better emulsion stability. The results indicated that the emulsion stabilized by high molecular peptides was more stable than the smaller ones.

Abstract With the in‐depth understanding of programmed cell death 1 ligand 1 (PD‐L1) in non‐small cell lung cancer (NSCLC), PD‐L1 has become a vital immunotherapy target and a significant biomarker. The clinical utility of detecting PD‐L1 by immunohistochemistry or next‐generation sequencing has been written into guidelines. However, the application of these methods is limited in some circumstances where the biopsy size is small or not accessible, or a dynamic monitor is needed. Radiomics can noninvasively, in real‐time, and quantitatively analyze medical images to reflect deeper information about diseases. Since radiomics was proposed in 2012, it has been widely used in disease diagnosis and differential diagnosis, tumor staging and grading, gene and protein phenotype prediction, treatment plan decision‐making, efficacy evaluation, and prognosis prediction. To explore the feasibility of the clinical application of radiomics in predicting PD‐L1 expression, immunotherapy response, and long‐term prognosis, we comprehensively reviewed and summarized recently published works in NSCLC. In conclusion, radiomics is expected to be a companion to the whole immunotherapy process.

Background: Venous malformations (VMs) are the most common low-flow vascular malformations. Although various sclerosants are effective, their relative effects have not yet been well established. Methods: We searched the PubMed, Embase, Cochrane Library, Scopus, and Web of Science databases for randomized clinical trials up to April 1, 2021. We estimated odds ratios using pairwise analysis and network meta-analysis (NMA) with random-effects. We calculated the surface under the cumulative ranking curve for each treatment and performed a cluster analysis. Results: A total of 22 randomized clinical trials (1 805 patients) comparing 11 different therapeutic regimens were identified. Polidocanol foam and ethanol showed significant improvement in VMs compared with bleomycin and sodium morrhuate, while polidocanol foam and polidocanol combined with bleomycin were significantly superior to ethanol and sodium morrhuate in terms of safety. Bleomycin foam was ranked as the most effective treatment; however, the evidence stems from one small study, and most comparative effect estimates were not statistically significant. Ethanol ranked second only to bleomycin foam in terms of its efficacy. The surface under cumulative ranking curve (SUCRA) cluster analysis demonstrated that bleomycin, polidocanol, polidocanol foam, bleomycin combined with dexamethasone, and polidocanol combined with bleomycin were the five treatments with higher SUCRA values for both outcomes compared with those of the second group of sodium morrhuate and sodium tetradecyl sulfate. The last cluster included only ethanol, which was characterized by relatively good efficacy and obvious side effects. Conclusion: Polidocanol foam and ethanol are more effective than bleomycin and sodium morrhuate in treating VMs, whereas ethanol and sodium morrhuate are associated with obvious adverse effects.

Abstract Background Poor air quality can result in a variety of respiratory disorders. However, the air quality index (AQI) and the level of fine particulate matter (PM2.5) on the progression and prognosis of nonsmall‐cell lung cancer (NSCLC) are unclear. Methods We launched a cohort study focused on the relationship between air quality and overall survival as well as progression, incorporating data from 590 patients with NSCLC in our medical center between November 1, 2013 and March 1, 2016. Forty‐nine patients from Sichuan Cancer Hospital were used for validation. Results Cases with poorer AQI 6 months before NSCLC diagnosis were more likely to progress to stage III to IV NSCLC than controls (OR = 2.61, 95% CI 1.35–5.24, p = 0.005). Similarly, if exposed to high levels of PM2.5 during these 6 months, overall survival was poor (HR [95% CI] = 1.53 [1.13, 2.07], p = 0.006). According to multivariate analysis, age, gender, KPS, PM2.5, hyperlipemia, and NSCLC stage were independent risk factors of overall survival. A predictive model developed by these factors above yielded a favorable agreement (C‐index = 0.758) on the calibration curve. External validation was conducted by 46 patients from Sichuan Cancer Hospital displaying an AUC of 0.724 (0.684–0.763). Conclusions PM2.5 and AQI levels affect disease progression and long‐term survival in NSCLC patients. An overall survival prediction model based on the PM2.5 level can help clinicians predict the risk of death in NSCLC.

The helicon plasma source is of great significance for the magnetoplasma rocket engine (MPRE) to be used as an effective propulsion device. In this paper, a multi-fluid, two-dimensional, axisymmetric model coupled with the electromagnetic field was developed to simulate the helicon plasma source in the MPRE. The simulation results demonstrate that the operation mode of the helicon plasma source in the MPRE gradually converts to a high-order wave mode and the resonance between the electromagnetic field and electrons is observed; due to the resonance, the deposit power density inside the plasma increases significantly, and the plasma density is two orders of magnitude higher than that in the inductively coupled plasma source. As the magnetic field intensity increases, the helicon plasma source enters into a high-order wave mode, which suggests that the MPRE can improve the utilization rate of the working medium by a stronger magnetic field.

BackgroundOsteoarthritis (OA) is a degenerative disease closely related to aging. Nevertheless, the role and mechanisms of aging in osteoarthritis remain unclear. This study aims to identify potential aging-related biomarkers in OA and to explore the role and mechanisms of aging-related genes and the immune microenvironment in OA synovial tissue.MethodsNormal and OA synovial gene expression profile microarrays were obtained from the Gene Expression Omnibus (GEO) database and aging-related genes (ARGs) from the Human Aging Genomic Resources database (HAGR). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO), and Gene set variation analysis (GSVA) enrichment analysis were used to uncover the underlying mechanisms. To identify Hub ARDEGs with highly correlated OA features (Hub OA-ARDEGs), Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning methods were used. Furthermore, we created diagnostic nomograms and receiver operating characteristic curves (ROC) to assess Hub OA-ARDEGs’ ability to diagnose OA and predict which miRNAs and TFs they might act on. The Single sample gene set enrichment analysis (ssGSEA) algorithm was applied to look at the immune infiltration characteristics of OA and their relationship with Hub OA-ARDEGs.ResultsWe discovered 87 ARDEGs in normal and OA synovium samples. According to functional enrichment, ARDEGs are primarily associated with inflammatory regulation, cellular stress response, cell cycle regulation, and transcriptional regulation. Hub OA-ARDEGs with excellent OA diagnostic ability were identified as MCL1, SIK1, JUND, NFKBIA, and JUN. Wilcox test showed that Hub OA-ARDEGs were all significantly downregulated in OA and were validated in the validation set and by qRT-PCR. Using the ssGSEA algorithm, we discovered that 15 types of immune cell infiltration and six types of immune cell activation were significantly increased in OA synovial samples and well correlated with Hub OA-ARDEGs.ConclusionSynovial aging may promote the progression of OA by inducing immune inflammation. MCL1, SIK1, JUND, NFKBIA, and JUN can be used as novel diagnostic biomolecular markers and potential therapeutic targets for OA.

Purebred Bamei piglets present problems, including slow growth, respiratory disease, and post-weaning stress. This study investigated the effects of Lactobacillus plantarum QP28-1- and Bacillus subtilis QB8-fermented feed supplementation on the growth performance, immunity, and intestinal microflora of Bamei piglets from Qinghai, China. A total of 48 purebred Bamei piglets (25 days; 6.8 ± 0.97 kg) were divided into the following four groups for a 28-day diet experiment: basal feed (CK); diet containing 10% Lactobacillus plantarum-fermented feed (L); diet containing 10% Bacillus subtilis-fermented feed (B); and diet containing a mixture of 5% Lactobacillus plantarum + 5% Bacillus subtilis-fermented feed (H). The daily weight gain and daily food intake of group H increased (p < 0.05), and the feed/weight gain ratios of the groups fed with fermented feed decreased more than that of the CK group. The levels of three immune factors, namely immunoglobulin (Ig)M, IgG, and interferon-γ, were higher (p < 0.05), whereas those of tumor necrosis factor-α, interleukin (IL)-1β, and IL-6 were lower (p < 0.05) in the fermented feed groups than in the CK group. Total protein was higher (p < 0.05), while urea nitrogen, total cholesterol and triglycerides were lower (p < 0.05) in the mixed-fermented feed group than in the CK group. Analysis of the gut microbiota showed that the addition of fermented feed increased the α-diversity of the gut microbiota, increasing the abundances of probiotics including Lactobacillus, Muribaculaceae, Ruminococcaceae, Prevotellaceae, and Rikenellaceae. Additionally, correlation analysis demonstrated that several of these probiotic bacteria were closely related to serum immunity. In conclusion, fermented feed supplementation rebuilt the intestinal microbiota of Bamei piglets, thereby reducing the feed/weight ratio, improving feed intake, and enhancing immunity.

Curcumin exhibits antioxidant and antitumor properties, but its poor chemical stability limits its application. Insoluble peptide precipitates formed by proteolysis of rice glutelin are usually discarded, resulting in resource waste. The coupled treatment of heat-assisted pH shifting and compounded chitosan (CS) was used to fabricate rice peptide aggregate–chitosan complexes (RPA–CS). The structure, interfacial behavior, emulsion properties, and digestibility of curcumin-loaded RPA–CS Pickering emulsions were investigated. Increasing the CS concentration led to lower interfacial tension but larger particle size, and the three-phase contact angle of the RPA–CS complexes approached 90°. Quartz crystal microbalance with dissipation (QCM–D) indicated that RPA–CS complexes with 6 g·kg−1 of CS (RPA–CS6) had the highest K1 (0.592 × 106 Hz−1) and K4 (0.487 × 106 Hz−1), suggesting that the softest interfacial layers were formed. The solid–liquid balance of RPA–RPA–CS emulsions was lower than 0.5, declaring that they had more elastic behavior than that of RPA emulsions. RPA–RPA–CS4-and RPA–CS6 emulsions had better storage stability, lower FFA release (79.8% and 76.3%, respectively), and higher curcumin bioaccessibility (65.2% and 68.2%, respectively) than RPA emulsions. This study showed that a low-value insoluble rice peptide precipitate could be used as a valuable emulsifier in foods, which may increase the economics and sustainability of the food supply.

The sesquiterpene alkaloid dendrobine, widely recognized as the main active compound and a quality control standard of medicinal orchids in the Chinese Pharmacopoeia, demonstrates diverse biological functions. In this study, we engineered Dendrobium catenatum as a chassis plant for the production of dendrobine through the screening and pyramiding of key biosynthesis genes. Initially, previously predicted upstream key genes in the methyl-D-erythritol 4-phosphate (MEP) pathway for dendrobine synthesis, including 4-(Cytidine 5′-Diphospho)-2-C-Methyl-d-Erythritol Kinase (CMK), 1-Deoxy-d-Xylulose 5-Phosphate Reductoisomerase (DXR), 2-C-Methyl-d-Erythritol 4-Phosphate Cytidylyltransferase (MCT), and Strictosidine Synthase 1 (STR1), and a few downstream post-modification genes, including Cytochrome P450 94C1 (CYP94C1), Branched-Chain-Amino-Acid Aminotransferase 2 (BCAT2), and Methyltransferase-like Protein 23 (METTL23), were chosen due to their deduced roles in enhancing dendrobine production. The seven genes (SG) were then stacked and transiently expressed in the leaves of D. catenatum, resulting in a dendrobine yield that was two-fold higher compared to that of the empty vector control (EV). Further, RNA-seq analysis identified Copper Methylamine Oxidase (CMEAO) as a strong candidate with predicted functions in the post-modification processes of alkaloid biosynthesis. Overexpression of CMEAO increased dendrobine content by two-fold. Additionally, co-expression analysis of the differentially expressed genes (DEGs) by weighted gene co-expression network analysis (WGCNA) retrieved one regulatory transcription factor gene MYB61. Overexpression of MYB61 increased dendrobine levels by more than two-fold in D. catenatum. In short, this work provides an efficient strategy and prospective candidates for the genetic engineering of D. catenatum to produce dendrobine, thereby improving its medicinal value.

Abstract Large-scale trapped-ion quantum computers hold great promise to outperform classical computers and are crucially desirable for finance, pharmaceutical industry, fundamental chemistry and other fields. Currently, a big challenge for trapped-ion quantum computers is the poor scalability mainly brought by the optical elements that are used for optical addressing. Metasurfaces provide a promising solution due to their excellent flexibility and integration ability. Here, we propose and numerically demonstrate a scalable off-axis metalens array for optical addressing working at the wavelength of 350 nm. Metalens arrays designed for x linearly polarized and left circularly polarized light respectively can focus the collimated addressing beam array into a compact focused spot array with spot spacing of 5 μm, featuring crosstalk below 0.82%. Graphical Abstract

Advanced security applications require materials responsive to different stimuli with remarkable stability. Here, Sargent et al. introduce Ge homogenously into a silica scaffold and obtain a colourtuned germanium silicon oxide with ultra-long phosphorescence and delayed fluorescence across a broad temperature range.

Introduction: The principal voltage-gated Na+ channel, NaV1.5 governs heart excitability and conduction. NaV1.5 dysregulation is responsible for ventricular arrhythmias and subsequent sudden cardiac death (SCD) in post-infarct hearts. The transcription factor Meis1 performs a significant role in determining differentiation fate and regenerative capability of cardiomyocytes. However, the functions of Meis1 in ischemic arrhythmias following myocardial infarction (MI) are still largely undefined. Objectives: Here we aimed to study whether Meis1 could act as a key regulator to mediate cardiac Na+ channel and its underlying mechanisms. Methods: Heart-specific Meis1 overexpression was established by AAV9 virus injection in C57BL/6 mice. The QRS duration, the incidence of ventricular arrhythmias and cardiac conduction velocity were evaluated by ECG, programmed electrical stimulation and optical mapping techniques respectively. The conventional patch clamp technique was performed to explore the INa characteristics of isolated mouse ventricular myocytes. In vitro, Meis1 was also overexpressed in hypoxic-treated neonatal cardiomyocytes. The analysis of immunoblotting and immunofluorescence were used to detect the changes in the expression of NaV1.5 in each group. Results: We found that forced expression of Meis1 rescued the prolongation of QRS complex, produced anti-arrhythmic activity and improved epicardial conduction velocity in infarcted mouse hearts. In terms of mechanisms, cardiac electrophysiological changes of MI mice can be ameliorated by the recovery of Meis1, which is characterized by the restoration of INa current density and NaV1.5 expression level of cardiomyocytes in the marginal zone of MI mouse hearts. Furthermore, in vitro studies showed that Meis1 was also able to rescue hypoxia-induced decreased expression and dysfunction of NaV1.5 in ventricular myocytes. We further revealed that E3 ubiquitin ligase CDC20 led to the ubiquitination and degradation of Meis1, which blocked the transcriptional regulation of SCN5A by Meis1 and ultimately led to the electrophysiological remodeling in ischemic-hypoxic cardiomyocytes. Conclusion: CDC20 mediates ubiquitination of Meis1 to govern the transcription of SCN5A and cardiac electrical conduction in mouse cardiomyocytes. This finding uncovers a new mechanism of NaV1.5 dysregulation in infarcted heart, and provides new therapeutic strategies for malignant arrhythmias and sudden cardiac death following MI.

Abstract Overcoming drug resistance is an inevitable challenge to the success of cancer treatment. Recently, in ovarian cancer, a highly chemoresistant tumor, we demonstrated an important role of shear stress in stem-like phenotype and chemoresistance using a three-dimensional microfluidic device, which most closely mimics tumor behavior. Here, we examined a new mechanosensitive microRNA—miR-199a-3p. Unlike most key microRNA biogenesis in static conditions, we found that Dicer, Drosha, and Exportin 5 were not involved in regulating miR-199a-3p under ascitic fluid shear stress (0.02 dynes/cm2). We further showed that hepatocyte growth factor (HGF), but not other ascitic cytokines/growth factors such as epidermal growth factor and tumor necrosis factor α or hypoxia, could transcriptionally downregulate miR-199a-3p through its primary transcript miR-199a-1 and not miR-199a-2. Shear stress in the presence of HGF resulted in a concerted effect via a specific c-Met/PI3K/Akt signaling axis through a positive feedback loop, thereby driving cancer stemness and drug resistance. We also showed that miR-199a-3p expression was inversely correlated with enhanced drug resistance properties in chemoresistant ovarian cancer lines. Patients with low miR-199a-3p expression were more resistant to platinum with a significantly poor prognosis. miR-199a-3p mimic significantly suppressed ovarian tumor metastasis and its co-targeting in combination with cisplatin or paclitaxel further decreased the peritoneal dissemination of ovarian cancer in mice. These findings unravel how biophysical and biochemical cues regulate miR-199a-3p and is important in chemoresistance. miR-199a-3p mimics may serve as a novel targeted therapy for effective chemosensitization.

Lotus-seedpod structured Li2ZnTi3O8/C (P-LZTO) microspheres obtained by the molten salt method are reported for the first time. The received phase-pure Li2ZnTi3O8 nanoparticles are inserted into the carbon matrix homogeneously to form a Lotus-seedpod structure, as confirmed by the morphological and structural measurements. As the anode for lithium-ion batteries, the P-LZTO material demonstrates excellent electrochemical performance with a high rate capacity of 193.2 mAh g-1 at 5 A g-1 and long-term cyclic stability up to 300 cycles at 1 A g-1. After even 300 cyclings, the P-LZTO particles can maintain their morphological and structural integrity. The superior electrochemical performances have arisen from the unique structure where the polycrystalline structure is beneficial for shorting the lithium-ion diffusion path, while the well-encapsulated carbon matrix can not only enhance the electronic conductivity of the composite but also alleviate the stress anisotropy during lithiation/delithiation process, leading to well-preserved particles.

Objective This study aims to evaluate the diagnostic value of human serum cysteine protease inhibitors (cystatin 4 [CST4]) in colorectal cancer (CRC) patients. Methods A total of 291 patients who were admitted to Zhuzhou Central Hospital for colonoscopy from January 2020 to December 2021 and met the inclusion criteria were selected. Serum samples of the patients were collected, and CST4 was detected by double-antibody sandwich enzyme-linked immunosorbent assay. Simultaneously, CEA and CA19-9 were detected, and the patients were divided into the CRC group, benign lesion group, and healthy control group. An attempt was made to construct a CRC prediction model including CST4 and draw a subject working characteristic curve as a diagnostic threshold for CRC prediction, and evaluate the diagnostic efficacy of the above indicators. At the same time, the expression analysis of CST4, CEA, and CA19-9 was verified by combining the data of CRC in the Tumor Genome Atlas (TCGA). Results In this study, the levels of serum CST4, CEA, and CA19-9 in the CRC group were higher than those in the colorectal benign lesion group and healthy control group, with statistical significance ( P

Abstract Stimuli‐responsive structural coloration allows the color change of soft substrates in response to environmental stimuli such as heat, humidity, and solvents. Such color‐changing systems enable smart soft devices, such as the camouflageable skin of soft robots or chromatic sensors in wearable devices. However, individually and independently programmable stimuli‐responsive color pixels remain significant challenges among the existing color‐changing soft materials and devices, which are crucial for dynamic display. Inspired by the dual‐color concavities on butterfly wings, a morphable concavity array to pixelate the structural color of two‐dimensional photonic crystal elastomer and achieve individually and independently addressable stimuli‐responsive color pixels is designed. The morphable concavity can convert its surface between concave and flat upon changes in the solvent and temperature, accompanied by angle‐dependent color‐shifting. Through multichannel microfluidics, the color of each concavity can be controllably switched. Based on the system, the dynamic display by forming reversibly editable letters and patterns for anti‐counterfeiting and encryption are demonstrated. It is believed that the strategy of pixelating optical properties through locally altering surface topography can inspire the design of new transformable optical devices, such as artificial compound eyes or crystalline lenses for biomimetic and robotic applications.

Abstract Vital organ injury is one of the leading causes of global deaths. Accumulating studies have demonstrated that dexmedetomidine (DEX) has an outstanding protective effect on multiple organs for its antiinflammatory and antiapoptotic properties, while the underlying molecular mechanism is not clearly understood. Autophagy, an adaptive catabolic process, has been found to play a crucial role in the organ-protective effects of DEX. Herein, we present a first attempt to summarize all the evidence on the proposed roles of autophagy in the action of DEX protecting against vital organ injuries via a comprehensive review. We found that most of the relevant studies (17/24, 71%) demonstrated that the modulation of autophagy was inhibited under the treatment of DEX on vital organ injuries (e.g. brain, heart, kidney, and lung), but several studies suggested that the level of autophagy was dramatically increased after administration of DEX. Albeit not fully elucidated, the underlying mechanisms governing the roles of autophagy involve the antiapoptotic properties, inhibiting inflammatory response, removing damaged mitochondria, and reducing oxidative stress, which might be facilitated by the interaction with multiple associated genes (i.e., hypoxia inducible factor-1α, p62, caspase-3, heat shock 70 kDa protein, and microRNAs) and signaling cascades (i.e., mammalian target of rapamycin, nuclear factor-kappa B, and c-Jun N-terminal kinases pathway). The authors conclude that DEX hints at a promising strategy in the management of vital organ injuries, while autophagy is crucially involved in the protective effect of DEX.

Drought stress is one of the major abiotic stresses to wheat worldwide, with negative effects on wheat growth and yield. Assessing genetic variation and drought stress tolerance of key agronomic and physiological traits of spring wheat and screening germplasm resources for higher drought tolerance and yield stability are a prerequisite for developing new, better-adapted spring wheat varieties. This study evaluated nine important agronomic and physiological traits in 152 spring wheat cultivars under non-stress (NS) and drought-stress (DS) conditions. Under DS conditions, grain yield per plot (GYP) and grain weight per spike (GWE) were significantly reduced by 33.8% and 31.7%, and their drought-tolerance indexes (DIs) were only 0.66 and 0.69, respectively, indicating that GYP and GWE are the most susceptible traits to drought stress. The SPAD value of flag leave at flowering stage decreased by 13.9% under DS conditions, and the DI of SPAD was 0.86. In addition, DI-SPAD was significantly positively correlated with DIs of plant height (PH), grain number per spikelet (GPS), grain number per spike (GNS), GWE and GYP, indicating that the drought tolerance and yield of wheat are closely related to chlorophyll retention. Six wheat germplasm accessions were identified for their ability to sustain grain yield and improve drought tolerance simultaneously. These results provide insights into the genetic co-variation between grain yield and drought stress tolerance and provide a theoretical basis for the development of new wheat cultivars with excellent drought tolerance and high yields in the presence and absence of drought.

Recently, deep learning-based object detection techniques have arisen alongside time-consuming training and data collection challenges. Although few-shot learning techniques can boost models with few samples to lighten the training load, these approaches still need to be improved when applied to remote-sensing images. Objects in remote-sensing images are often small with an uncertain scale. An insufficient amount of samples would further aggravate this issue, leading to poor detection performance. This paper proposes a Gaussian-scale enhancement (GSE) strategy and a multi-branch patch-embedding attention aggregation (MPEAA) module for cross-scale few-shot object detection to address this issue. Our model can enrich the scale information of an object and learn better multi-scale features to improve the performance of few-shot object detectors on remote sensing images.

The existing ultrasonic thickness measurement systems require high sampling frequencies for echo signal acquisition, leading to complex circuit designs and high costs. Moreover, extracting the characteristics of ultrasonic echo signals for accurate thickness measurement poses significant challenges. To address these issues, this paper proposes a method that utilizes conventional sampling frequencies to acquire high-frequency ultrasonic echo signals, overcoming the limitations of high-frequency data acquisition imposed by the Nyquist–Shannon sampling theorem. By employing an improved sampling reconstruction technique, the multi-cycle sampling signals are reconstructed and rearranged within a single cycle, effectively increasing the equivalent sampling frequency. Additionally, a combination of coarse estimation using fast Fourier transform (FFT) and precise phase extraction using the moving sine fitting algorithm is proposed for accurate thickness measurement, resolving the limitations of common thickness measurement methods such as peak detection, envelope detection, and Hilbert autocorrelation in terms of low measurement accuracy. Experimental results obtained from thickness measurements on 45 steel ultrasonic test blocks within the range of 3 mm to 20 mm indicate a measurement error of ±0.01 mm, while for thicknesses ranging from 1 mm to 50 mm, the measurement error is ±0.05 mm.

To reduce the environmental impact of offshore oil and gas, the hydrocarbon discharge regulations tend to become more stringent. One way to reduce the oil discharge is to improve the control systems by introducing new oil-in-water (OiW) sensing technologies and advanced control. De-oiling hydrocyclones are commonly used in offshore facilities for produced water treatment (PWT), but obtaining valid control-oriented models of hydrocyclones has proven challenging. Existing control-oriented models are often based on droplet trajectory analysis. While it has been demonstrated that these models can fit steady-state separation efficiency data, the dynamics of these models have either not been validated experimentally or only describe part of the dynamics. In addition to the inlet OiW concentration, they require the droplet size distribution to be measured, which complicates model validation as well as implementation. This work presents an approach to obtain validated nonlinear models of the discharge concentration, separation efficiency, and discharge rate, which do not require the droplet size distribution to be measured. An exhaustive search approach is used to identify control-oriented polynomial-type Hammerstein–Wiener (HW) models of de-oiling hydrocyclones based on concentration measurements from online OiW monitors. To demonstrate the effectiveness of this modeling approach, a PI controller is designed using the Skogestad internal model control (SIMC) tuning rules to control the discharge OiW concentration directly. The identification experiment emulates an offshore PWT system with installed OiW monitors, which is realistic with the legislative incentive to include online OiW discharge measurements. The proposed approach could enable the application of OiW-based control on existing offshore PWT facilities, resulting in improved de-oiling performance and reduced oil discharge.

In the dynamic realm of materials science, novel nanomaterials possess the transformative potential to reshape various industries, ranging from energy storage to catalysis [...]

Abstract Background Previous cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes. Methods We conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment. Results Forty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference − 0.40 [95% CI − 0.71 to − 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference − 1.6% [95% CI − 4.3% to 1.2%]; P = 0.42) between groups. Conclusions In this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness. Trial registration: ISRCTN, ISRCTN12233792 . Registered November 20th, 2017.

Abstract When and how the collision between India‐Asia occurred continue to be debated. We report new paleomagnetic data (Ds = 158.8°, Is = 7.8°, ks = 81.3, α95 = 5.1°, N = 11 sites) from limestone of the Zongpu Formation Member I in the Tingri, which indicate that the Tethyan Himalaya was situated at 3.9 ± 2.6°S during 62‐59 Ma. This implies that Greater India was ∼900 km and that Tethyan Himalaya did not break off from India, which left a ∼2,000 km Neo‐Tethys Ocean that challenges the prevailing hypothesis that the initial collision of India–Asia occurred during this period. The drift rate of the India plate, with an average rate of 160 ± 28 mm/a during 60‐50 Ma, implies that the northern margin (e.g., the Tingri, Gyangze, Gamba, and Zanskar areas) of Greater India almost simultaneously collided with Asia at ∼50 Ma, quasi‐synchronously, and closing the Neo‐Tethys Ocean.

ObjectiveTo study changes in the composition and functions of the gut microbiota (GM) in children with growth hormone deficiency (GHD) using high-throughput sequencing.MethodsThirty-three children with GHD diagnosed in Longgang District Maternity and Child Health Hospital were included in the disease group and 24 healthy children of the same age comprised the control group. Total DNA was extracted and amplified from stool samples obtained from all subjects. High-throughput sequencing was used to analyze the GM composition and functions.ResultsThe GM from the two groups of children showed significant differences in α-diversity (P

Mussels can form tough and long-lasting adhesions to organic and inorganic surfaces in saline and impactive severe aquatic environments. Similar to mussel adhesion, dentin bonding occurs in a wet environment. However, unlike mussels, it is difficult to achieve long-lasting bonds with dentin. Moreover, water is considered a major hindrance in dentin bonding. Inspired by the synergistic effect of cationic lysine (Lys) and catechol on the elimination of the hydration layer during mussel adhesion, a catechol- and Lys-functionalized polymerizable polymer (catechol–Lys–methacrylate [CLM]) was synthesized to replicate the complex synergy between amino acids and catechol. The bond-promoting potential of 5 ​mg/mL CLM primer was confirmed using an in vitro wet dentin-bonding model, which was characterized by an improvement in bond strength and durability. CLM can adhere to wet demineralized dentin, with Lys acting as a molecular vanguard to expel water. Subsequently, a myriad of interfacial interactions can be obtained by introducing the catechol group into the interface. Additionally, tough and long-lasting adhesion, similar to that formed by mussels, can be achieved by grafting CLM onto type I collagen via covalent bonds, hydrogen bonds, Van der Waals interactions, and cation–π interactions, which can enhance the mechanical and chemical stability of collagen, increase the enzymatic resistance of collagen, and provide additional physical/chemical adhesion to dentin bonds. Catechol- and cationic Lys-functionalized polymers can improve the stability of the resin–dentin interface under wet conditions.

Darkfield imaging can achieve in situ observation of marine plankton with unique advantages of high-resolution, high-contrast and colorful imaging for plankton species identification, size measurement and abundance estimation. However, existing underwater darkfield imagers have very shallow depth-of-field, leading to inefficient seawater sampling for plankton observation. We develop a data-driven method that can algorithmically refocus planktonic objects in their defocused darkfield images, equivalently achieving focus-extension for their acquisition imagers. We devise a set of dual-channel imaging apparatus to quickly capture paired images of live plankton with different defocus degrees in seawater samples, simulating the settings as in in situ darkfield plankton imaging. Through a series of registration and preprocessing operations on the raw image pairs, a dataset consisting of 55 000 pairs of defocused-focused plankter images have been constructed with an accurate defocus distance label for each defocused image. We use the dataset to train an end-to-end deep convolution neural network named IsPlanktonFE, and testify its focus-extension performance through extensive experiments. The experimental results show that IsPlanktonFE has extended the depth-of-field of a 0.5× darkfield imaging system to ~7 times of its original value. Moreover, the model has exhibited good content and instrument generalizability, and considerable accuracy improvement for a pre-trained ResNet-18 network to classify defocused plankton images. This focus-extension technology is expected to greatly enhance the sampling throughput and efficiency for the future in situ marine plankton observation systems, and promote the wide applications of darkfield plankton imaging instruments in marine ecology research and aquatic environment monitoring programs.