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Abstract Background Breast cancer (BC) is a great clinical challenge because of its aggressiveness and poor prognosis. Zinc Finger Protein 64 (ZFP64), as a transcriptional factor, is responsible for the development and progression of cancers. This study aims to investigate whether ZFP64 regulates stem cell-like properties and tumorigenesis in BC by the glycolytic pathway. Results It was demonstrated that ZFP64 was overexpressed in BC specimens compared to adjacent normal tissues, and patients with high ZFP64 expression had shorter overall survival and disease-free survival. The analysis of the association of ZFP64 expression with clinicopathological characteristics showed that high ZFP64 expression is closely associated with N stage, TNM stage, and progesterone receptor status. Knockdown of ZFP64 suppressed the viability and colony formation capacity of BC cells by CCK8 and colony formation assays. The subcutaneous xenograft models revealed that ZFP64 knockdown reduced the volume of formatted tumors, and decreased Ki67 expression in tumors. The opposite effects on cell proliferation and tumorigenesis were demonstrated by ZFP64 overexpression. Furthermore, we suggested that the stem cell-like properties of BC cells were inhibited by ZFP64 depletion, as evidenced by the decreased size and number of formatted mammospheres, the downregulated expressions of OCT4, Nanog, and SOX2 proteins, as well as the reduced proportion of CD44+/CD24− subpopulations. Mechanistically, glycolysis was revealed to mediate the effect of ZFP64 using mRNA-seq analysis. Results showed that ZFP64 knockdown blocked the glycolytic process, as indicated by decreasing glycolytic metabolites, inhibiting glucose consumption, and reducing lactate and ATP production. As a transcription factor, we identified that ZFP64 was directly bound to the promoters of glycolysis-related genes (ALDOC, ENO2, HK2, and SPAG4), and induced the transcription of these genes by ChIP and dual-luciferase reporter assays. Blocking the glycolytic pathway by the inhibition of glycolytic enzymes ENO2/HK2 suppressed the high proliferation and stem cell-like properties of BC cells induced by ZFP64 overexpression. Conclusions These data support that ZFP64 promotes stem cell-like properties and tumorigenesis of BC by activating glycolysis in a transcriptional mechanism.

Abstract Bacteria often evolve antibiotic resistance through mutagenesis. However, the processes causing the mutagenesis have not been fully resolved. Here, we find that a broad range of ribosome-targeting antibiotics cause mutations through an underexplored pathway. Focusing on the clinically important aminoglycoside gentamicin, we find that the translation inhibitor causes genome-wide premature stalling of RNA polymerase (RNAP) in a loci-dependent manner. Further analysis shows that the stalling is caused by the disruption of transcription-translation coupling. Anti-intuitively, the stalled RNAPs subsequently induce lesions to the DNA via transcription-coupled repair. While most of the bacteria are killed by genotoxicity, a small subpopulation acquires mutations via SOS-induced mutagenesis. Given that these processes are triggered shortly after antibiotic addition, resistance rapidly emerges in the population. Our work reveals a mechanism of action of ribosomal antibiotics, illustrates the importance of dissecting the complex interplay between multiple molecular processes in understanding antibiotic efficacy, and suggests new strategies for countering the development of resistance.

Background: The climate change scenario has witnessed an increase in extreme temperature events (ETEs), including heat waves and cold spells, and a heightened occurrence of compounding with fine particulate matter (PM2.5). However, the impact of this phenomenon on the sensitivity to thyroid hormones (THs) in humans is unclear, especially in a group as specific as schizophrenia. Methods: A longitudinal study was constructed using longitudinal measurements of thyroid function in schizophrenia in the Anhui Mental Health Center. The latent growth mixture model was applied to assess the optimal trajectory of change in impaired THs sensitivity. We then used logistic regression to explore associations between heat waves, cold spells, and PM2.5 with impaired THs sensitivity trajectories in the total population and different gender and age subgroups. Furthermore, the effect of the frequency, intensity, and duration of ETEs in the above associations was explored, as well as an assessment of the interaction between ETEs and PM2.5. Results: Among 931 participants, we identified two classifications of trajectories of impaired THs sensitivity: “Low-stable” (n = 836, 89.80 %) and “Rise-slight down” (n = 95, 10.20 %). Logistic regression showed significant associations between each additional day of heat waves (≥3 days with temperature thresholds above the 95th percentile) and cold spells (≥3 days with temperature thresholds below the 5th percentile) and “Rise-slight down” trajectory, with odds ratios (95 % confidence intervals) of 1.06 (1.02, 1.10) and 1.19 (1.14, 1.24), respectively, and the strength of this association increased with the intensity and duration of ETEs. Subgroup analyses indicated that the association was more pronounced in males and the age group above 40 years. Furthermore, PM2.5 was found to interact with heat waves, with high concentrations exacerbating the effects of heat waves. Conclusions: Our findings suggest that mitigating both ETEs and PM2.5 exposures may bring health co-benefits in preventing thyroid impairment in schizophrenia.

Abstract Rice blast caused by Pyricularia oryzae (syn., Magnaporthe oryzae) was one of the most destructive diseases of rice throughout the world. Genome assembly was fundamental to genetic variation identification and critically impacted the understanding of its ability to overcome host resistance. Here, we report a gapless genome assembly of rice blast fungus P. oryzae strain P131 using PacBio, Illumina and high throughput chromatin conformation capture (Hi-C) sequencing data. This assembly contained seven complete chromosomes (43,237,743 bp) and a circular mitochondrial genome (34,866 bp). Approximately 14.31% of this assembly carried repeat sequences, significantly greater than its previous assembled version. This assembly had a 99.9% complement in BUSCO evaluation. A total of 14,982 genes protein-coding genes were predicted. In summary, we assembled the first telomere-to-telomere gapless genome of P. oryzae, which would be a valuable genome resource for future research on the genome evolution and host adaptation.

High-locality and hidden landslides, due to its significant characteristics of being difficult to access, identify, and monitor, have strong suddenness and destructiveness when they occur. Continuous monitoring and risk assessment of these landslides are of great significance. Traditional artificial ground survey methods and ground monitoring equipment have the characteristics of high risk, low efficiency, easy damage to equipment, and frequent offline false alarms. Thus, based on unmanned aerial vehicle (UAV) tilt photogrammetry, this study attempts to provide a digital twin method to characterize high-locality and hidden landslides by monitoring and analyzing the deformation and spatiotemporal evolution of geological disasters. This study uses UAV tilt photogrammetry technology to obtain 10 periods of aerial survey data of the Baige landslide on the Jinsha River in Tibet as the research area from April 2019 to September 2021. A multi-temporal digital twin landslide body is constructed, and high-precision quantitative monitoring of multi-dimensional factors, such as the overall sliding characteristics, local micro deformation, and collapse volume of the Baige landslide, is achieved, which are applied to the monitoring and warning of Baige landslide. The results show that there are signs of continuous deformation in the Baige landslide during the monitoring period from 2019 to 2021, and strong deformation mainly occurs at both sides and rear edges of the landslide, gradually expanding, and posing a risk of collapse and river blockage. The multi-temporal digital twin method and application of landslide deformation monitoring on qualitative and quantitative characteristics description and risk assessment of geological disasters are further analyzed. The method in this study has the advantages of fast and flexible, comprehensive coverage, and not limited by complex and dangerous terrain conditions, which could provide information for the large gradient deformation monitoring and engineering practice of slope disasters, such as high-locality and hidden landslides.

Abstract Anisotropic pressure sensors are gaining increasing attention for next‐generation wearable electronics and intelligent infrastructure owing to their sensitivity in identifying different directional forces. 3D printing technologies have unparalleled advantages in the design of anisotropic pressure sensors with customized 3D structures for realizing tunable anisotropy. 3D printing has demonstrated few successes in utilizing piezoelectric nanocomposites for anisotropic recognition. However, 3D‐printed anisotropic piezoresistive pressure sensors (PPSs) remain unexplored despite their convenience in saving the poling process. This study pioneers the development of an aqueous printable ink containing waterborne polyurethane elastomer. An anisotropic PPS featuring tailorable flexibility in macroscopic 3D structures and microscopic pore morphologies is created by adopting direct ink writing 3D printing technology. Consequently, the desired directional force perception is achieved by programming the printing schemes. Notably, the printed PPS demonstrated excellent deformability, with a relative sensitivity of 1.22 (kPa*wt. %)−1 over a substantial pressure range (2.8 to 8.1 kPa), approximately fivefold than that of a state‐of‐the‐art carbon‐based PPS. This study underscores the versatility of 3D printing in customizing highly sensitive anisotropic pressure sensors for advanced sensing applications that are difficult to achieve using conventional measures.

Phthalates are positioned as potential risk factors for health-related diseases. However, the effects of exposure to phthalates on accelerated aging and the potential modifications of physical activity remain unclear. A total of 2317 participants containing complete study-related information from the National Health and Nutrition Examination Survey 2007–2010 were included in the current study. We used two indicators, the Klemera-Doubal method biological age acceleration (BioAgeAccel) and phenotypic age acceleration (PhenoAgeAccel), to assess the accelerated aging status of the subjects. Multiple linear regression (single pollutant models), weighted quantile sum (WQS) regression, Quantile g-computation, and Bayesian kernel machine regression (BKMR) models were utilized to explore the associations between urinary phthalate metabolites and accelerated aging. Three groups of physical activity with different intensities were used to evaluate the modifying effects on the above associations. Results indicated that most phthalate metabolites were significantly associated with BioAgeAccel and PhenoAgeAccel, with effect values (β) ranging from 0.16 to 0.21 and 0.16–0.37, respectively. The WQS indices were positively associated with BioAgeAccel (0.33, 95% CI: 0.11, 0.54) and PhenoAgeAccel (0.50, 95% CI: 0.19, 0.82). Quantile g-computation indicated that phthalate mixtures were associated with accelerated aging, with effect values of 0.15 (95% CI: 0.02, 0.28) for BioAgeAccel and 0.39 (95% CI: 0.12, 0.67) for PhenoAgeAccel respectively. The BKMR models indicated a significant positive association between the concentrations of urinary phthalate mixtures with the two indicators. In addition, we found that most phthalate metabolites showed the strongest effects on accelerated aging in the no physical activity group and that the effects decreased gradually with increasing levels of physical activity (P < 0.05 for trend). Similar results were also observed in the mixed exposure models (WQS and Quantile g-computation). This study indicates that phthalates exposure is associated with accelerated aging, while physical activity may be a crucial barrier against phthalates exposure-related aging.

Endorheic basins are important geomorphological and ecological units on the Qinghai-Tibet Plateau (QTP), which is undergoing a rapid evolution of its lake system structure and drainage reorganization that is threatening local ecology, infrastructures and residuals owing to climate change. This dataset provides a detailed delineation and classification of endorheic basins on the QTP for understanding the complex dynamics under climate changes. A newly-developed algorithm, namely the Joint Elevation-Area Threshold (JEAT) algorithm (Liu et al, 2024), is applied for delineating endorheic basins based on digital elevation model (DEM). A total of 184 endorheic basins were divided, of which the permanent divide lines were characterized. All the endorheic basins were further categorized into five groups based on the hydraulic connectivity attributes, which have been commonly observed since 2000. The dataset also includes basic information such as drainage area, water surface area, and water storage volume of each endorheic basin. It is particularly beneficial for digital watershed analysis towards ecological restoration and water resource management on the environmentally vulnerable QTP.

Abstract Background The cation/proton antiporter (CPA) superfamily plays a crucial role in regulating ion homeostasis and pH in plant cells, contributing to stress resistance. However, in potato (Solanum tuberosum L.), systematic identification and analysis of CPA genes are lacking. Results A total of 33 StCPA members were identified and classified into StNHX (n = 7), StKEA (n = 6), and StCHX (n = 20) subfamilies. StCHX owned the highest number of conserved motifs, followed by StKEA and StNHX. The StNHX and StKEA subfamilies owned more exons than StCHX. NaCl stress induced the differentially expression of 19 genes in roots or leaves, among which StCHX14 and StCHX16 were specifically induced in leaves, while StCHX2 and StCHX19 were specifically expressed in the roots. A total of 11 strongly responded genes were further verified by qPCR. Six CPA family members, StNHX1, StNHX2, StNHX3, StNHX5, StNHX6 and StCHX19, were proved to transport Na+ through yeast complementation experiments. Conclusions This study provides comprehensive insights into StCPAs and their response to NaCl stress, facilitating further functional characterization.

Abstract Background Rye (Secale cereale), one of the drought and cold-tolerant crops, is an important component of the Triticae Dumortier family of Gramineae plants. Basic helix-loop-helix (bHLH), an important family of transcription factors, has played pivotal roles in regulating numerous intriguing biological processes in plant development and abiotic stress responses. However, no systemic analysis of the bHLH transcription factor family has yet been reported in rye. Results In this study, 220 bHLH genes in S. cereale (ScbHLHs) were identified and named based on the chromosomal location. The evolutionary relationships, classifications, gene structures, motif compositions, chromosome localization, and gene replication events in these ScbHLH genes are systematically analyzed. These 220 ScbHLH members are divided into 21 subfamilies and one unclassified gene. Throughout evolution, the subfamilies 5, 9, and 18 may have experienced stronger expansion. The segmental duplications may have contributed significantly to the expansion of the bHLH family. To systematically analyze the evolutionary relationships of the bHLH family in different plants, we constructed six comparative genomic maps of homologous genes between rye and different representative monocotyledonous and dicotyledonous plants. Finally, the gene expression response characteristics of 22 ScbHLH genes in various biological processes and stress responses were analyzed. Some candidate genes, such as ScbHLH11, ScbHLH48, and ScbHLH172, related to tissue developments and environmental stresses were screened. Conclusions The results indicate that these ScbHLH genes exhibit characteristic expression in different tissues, grain development stages, and stress treatments. These findings provided a basis for a comprehensive understanding of the bHLH family in rye.

Real-time estimation of fish biomass plays a crucial role in real-world fishery production, as it helps formulate feeding strategies and other management decisions. In this paper, a dense fish counting network called Swin-CSRNet is proposed. Specifically, the VGG16 layer in the front-end is replaced with the Swin transformer to extract image features more efficiently. Additionally, a squeeze-and-excitation (SE) module is introduced to enhance feature representation by dynamically adjusting the importance of each channel through “squeeze” and “excitation”, making the extracted features more focused and effective. Finally, a multi-scale fusion (MSF) module is added after the back-end to fully utilize the multi-scale feature information, enhancing the model’s ability to capture multi-scale details. The experiment demonstrates that Swin-CSRNet achieved excellent results with MAE, RMSE, and MAPE and a correlation coefficient R2 of 11.22, 15.32, 5.18%, and 0.954, respectively. Meanwhile, compared to the original network, the parameter size and computational complexity of Swin-CSRNet were reduced by 70.17% and 79.05%, respectively. Therefore, the proposed method not only counts the number of fish with higher speed and accuracy but also contributes to advancing the automation of aquaculture.

Abstract The optimal selection of pinning nodes for multi-agent flocking is a challenging NP-hard problem. Current pinning node selection strategies mainly rely on centrality measures of complex networks, which lack rigorous mathematical proof for effective flocking control. This paper proposes a pinning node selection strategy based on matrix eigenvalue theory. First, the effect of the pinning node on the eigenvalue of the Laplacian matrix is analyzed. Then, a synchronization index representing the topology uniformity of the multi-agent system is proposed to exert maximum influence on the system synchronizability. A practical optimal pinning node selection method based on the synchronization index is proposed and analyzed using the eigenvalue perturbation method. Finally, simulations demonstrate that the convergence rate of the system obtained using the optimal synchronizability pinning node selection method is better than that achieved with the maximum degree centrality node selection strategy.

The real-time classification of fish feeding behavior plays a crucial role in aquaculture, which is closely related to feeding cost and environmental preservation. In this paper, a Fish Feeding Intensity classification model based on the improved Vision Transformer (CFFI-Vit) is proposed, which is capable of quantifying the feeding behaviors of rainbow trout (Oncorhynchus mykiss) into three intensities: strong, moderate, and weak. The process is outlined as follows: firstly, we obtained 2685 raw feeding images of rainbow trout from recorded videos and classified them into three categories: strong, moderate, and weak. Secondly, the number of transformer encoder blocks in the internal structure of the ViT was reduced from 12 to 4, which can greatly reduce the computational load of the model, facilitating its deployment on mobile devices. And finally, a residual module was added to the head of the ViT, enhancing the model’s ability to extract features. The proposed CFFI-Vit has a computational load of 5.81 G (Giga) Floating Point Operations per Second (FLOPs). Compared to the original ViT model, it reduces computational demands by 65.54% and improves classification accuracy on the validation set by 5.4 percentage points. On the test set, the model achieves precision, recall, and F1 score of 93.47%, 93.44%, and 93.42%, respectively. Additionally, compared to state-of-the-art models such as ResNet34, MobileNetv2, VGG16, and GoogLeNet, the CFFI-Vit model’s classification accuracy is higher by 6.87, 8.43, 7.03, and 5.65 percentage points, respectively. Therefore, the proposed CFFI-Vit can achieve higher classification accuracy while significantly reducing computational demands. This provides a foundation for deploying lightweight deep network models on edge devices with limited hardware capabilities.

Maize, as one of the most important crops in the world, faces severe challenges from various diseases and pests. The timely and accurate identification of maize leaf diseases and pests is of great significance for ensuring agricultural production. Currently, the identification of maize leaf diseases and pests faces two key challenges: (1) In the actual process of identifying leaf diseases and pests, complex backgrounds can interfere with the identification effect. (2) The subtle features of diseases and pests are difficult to accurately extract. To address these challenges, this study proposes a maize leaf disease and pest identification model called LFMNet. Firstly, the localized multi-scale inverted residual convolutional block (LMSB) is proposed to perform preliminary down-sampling on the image, preserving important feature information for the subsequent extraction of fine disease and pest features in the model structure. Then, the feature localization bottleneck (FLB) is proposed to improve the model’s ability to focus on and locate disease and pest characteristics and to reduce interference from complex backgrounds. Subsequently, the multi-hop local-feature fusion architecture (MLFFA) is proposed, which effectively addresses the problem of extracting subtle features by enhancing the extraction and fusion of global and local disease and pest features in images. After training and testing on a dataset containing 19,451 images of maize leaf diseases and pests, the LFMNet model demonstrated excellent performance, with an average identification accuracy of 95.68%, a precision of 95.91%, a recall of 95.78%, and an F1 score of 95.83%. Compared to existing models, it exhibits significant advantages, offering robust technical support for the precise identification of maize diseases and pests.

Abstract The rate of convergence is a vital factor in determining the outcome of the mission execution of unmanned aerial vehicle (UAV) swarms. However, the difficulty of developing a rapid convergence strategy increases dramatically with the growth of swarm scale. In the present work, a novel fractional-order flocking algorithm (FOFA) is proposed for large-scale UAV swarms. First, based on the interaction rules of repulsion, attraction and alignment among swarm individuals, fractional calculus is introduced to replace traditional integer-order velocity updating, which enables UAVs to utilize historical information during flight. Subsequently, the convergence of the algorithm is theoretically analyzed. Some sufficient convergence conditions for the FOFA are presented by exploiting graph theory. Finally, the simulation results validate that our proposed FOFA performs much better than traditional flocking algorithms in terms of convergence rate. Meanwhile, the relationships between the fractional order of the FOFA and the convergence time of the UAV swarm are discussed. We find that under certain conditions, the fractional order is strongly correlated with the convergence rate of the UAV swarm; that is, a small fractional order (more consideration of historical information) leads to better performance. Moreover, the fractional order can be used as an important parameter to control the convergence rate of a large-scale UAV swarm.

The temporally asymmetric effects of vegetation growth response to climate, e.g., time-lag, time-accumulation, and their combination effects, have been widely reported. However, their elevation-dependent spatial distribution patterns in alpine basins of the Qinghai-Tibet Plateau remain unclear, especially in different seasons. This study investigated the temporal response of vegetation to precipitation and temperature throughout the whole growing season and its two subphases (growth phase and senescence phase) in the Lhasa River Basin (LRB). The results showed that alpine vegetation responds to climate in all seasons with obvious time-accumulation and relatively weak time-lag, and during the senescence phase and whole growing season, there is no significant lag in vegetation response to both precipitation and temperature, while the accumulation is about 3 ∼ 4 weeks and 2 weeks, respectively. Comparatively, there are enhanced lag and accumulation during the growth phase, with a similar lag of about 2 weeks, and 6-week and 4-week accumulation for precipitation and temperature, respectively. The whole LRB is subdivided into four elevation zones, each with different hydrothermal condition and temporal response characteristic. Across different elevation zones, it is found that stronger water-deficit stress on vegetation results in shorter lag and longer accumulation to precipitation, while stronger heat-deficit stress leads to shorter lag and accumulation to temperature, which is determined by both the vegetation’s hydrothermal demands and ambient environment. These findings shed light on the relationship between vegetation and climate and provide potential theoretical support for vegetation conservation in alpine basins.

Background: In the era characterized by global environmental and climatic changes, understanding the effects of PM2.5 components and heatwaves on schizophrenia (SCZ) is essential for implementing environmental interventions at the population level. However, research in this area remains limited, which highlights the need for further research and effort. We aim to assess the association between exposure to PM2.5 components and hospitalizations for SCZ under different heatwave characteristics. Methods: We conducted a 16 municipalities-wide, individual exposure-based, time-stratified, case-crossover study from January 1, 2017, to December 31, 2020, encompassing 160736 hospitalizations in Anhui Province, China. Daily concentrations of PM2.5 components were obtained from the Tracking Air Pollution in China dataset. Conditional logistic regression models were used to investigate the association between PM2.5 components and hospitalizations. Additionally, restricted cubic spline models were used to identify protective thresholds of residential environment in response to environmental and climate change. Results: Our findings indicate a positive correlation between PM2.5 and its components and hospitalizations. Significantly, a 1 μg/m3 increase in black carbon (BC) was associated with the highest risk, at 1.58% (95%CI: 0.95–2.25). Exposure to heatwaves synergistically enhanced the impact of PM2.5 components on hospitalization risks, and the interaction varied with the intensity and duration of heatwaves. Under the 99th percentile heatwave events, the impact of PM2.5 and its components on hospitalizations was most pronounced, which were PM2.5 (2–4d: 4.59%, 5.09%, and 5.09%), sulfate (2–4d: 21.73%, 23.23%, and 25.25%), nitrate (2–4d: 17.51%, 16.93%, and 20.31%), ammonium (2–4d: 27.49%, 31.03%, and 32.41%), organic matter (2–4d: 32.07%, 25.42%, and 24.48%), and BC (2–4d: 259.36%, 288.21%, and 152.52%), respectively. Encouragingly, a protective effect was observed when green and blue spaces comprised more than 17.6% of the residential environment. Discussion: PM2.5 components and heatwave exposure were positively associated with an increased risk of hospitalizations, although green and blue spaces provided a mitigating effect.

Spectral imaging is performed primarily using reflective devices, but for transparent objects, especially transparent liquids, a transmission-based device is required to obtain more effective spectral imaging data. For this purpose, a transmitted spectral imaging data acquisition device based on a miniature multispectral spectrometer was developed and demonstrated its capability in the analysis of transparent liquids. This device allows rapid and noncontact acquisition of spectral imaging signals from transparent liquid samples. The design of the device mainly includes two parts: a shooting system and a master computer, and the optical path is optimized by selecting the appropriate diffusion plate. As an application example, a concentration-absorbance model of liquid samples at characteristic wavelengths was established and used to predict the concentrations of different liquid samples. Experimental results showed that the relative error of the predicted concentration values was within 4%, indicating excellent detection performance. Therefore, the design of the device demonstrates favorable feasibility and wide applicability in liquid detection systems.

Background Tumor-infiltrating lymphocytes (TILs) exist in various malignancies, and have been viewed as a promising biomarker to predict the efficacy and outcome of treatment. However, the marked inter- and intra-tumor heterogeneity of TILs has resulted in some confusion regarding their impact on the prognosis of colorectal cancer (CRC). Methods In this study, 78 CRC patients were enrolled and the CD3+ and CD8+ TILs densities at the tumor center (TC), the invasive margin (IM) and the tumor stroma (TS) were assessed by immunohistochemical staining. Their associations with clinicopathological features and progression free survival (PFS) were analyzed to evaluate the predictive and prognostic values of TILs. Results TILs were mainly distributed along the invasive margin. High density of TILs in tumor center and invasive margin was associated with smaller tumor size (CD3+TILsIM), reduced tumor invasion (CD3+TILsIM), absence of lymph node metastasis (CD3+TILsIM and CD8+TILsTC), earlier stage (CD3+TILsIM and CD8+TILsIM), and lower tumor grade (CD3+TILsIM and CD8+TILsTC). However, stromal TILs were not associated with any clinicopathological features. Kaplan–Meier survival analysis revealed that high densities of TILs always correlated with prolonged patient survival. The pathological N stage, CD3+ TILsIM and CD8+ TILsTC were found to be independent prognostic indicators. Additionally, early-stage CRC patients who developed recurrence after surgery, showed a higher CD3+/CD8+ TILs ratio in invasive margin. In the present study, it was clarified that CD3+ and CD8+ TILs were heterogeneously distributed in tumor tissues of CRC. The increase in intratumoral and peritumoral TILs had been shown to be strongly predictive of improved clinical outcome. More importantly, the immune signatures enabled to stratify early-stage CRC patients with high risk of recurrence, highlighting the prognostic power of TILs.

High volume fly ash concrete (HVFAC) has been widely used, and the mix proportion of HVFAC is usually designed based on the required compressive strength. Therefore, the research of HVFAC under the condition of equal strength has more engineering application value. However, in the current mix proportion design standard, there is no special discussion on the mix proportion design method of HVFAC. In this study, the compressive strength of HVFAC affected by four factors (water-binder ratio, FA content, curing method and curing age) was systematically studied. Based on 594 sets of strength data obtained from experiments, the method to determine the key mix proportion parameters (water-binder ratio and FA content) of equal strength HVFAC was proposed through machine learning algorithms (ML). Two ML methods (i.e., a multiple linear regression (MLR) and an artificial neural networks (ANN)) were developed to predict the HVFAC compressive strength and then their performances were compared. Through comparison, it was found that the mean absolute error and root mean squared error of the ANN model were both lower than the MLR model, and the ANN model has lower error and higher accuracy. In addition, the reliability of the proposed ANN model was verified with data in other literatures, the results showed the errors between the predicted values and the measured values are lower than 25%. The weight contribution rate of each factor to the strength was calculated. Among the four factors, the curing age had the greatest impact on the compressive strength, which contributes up to 60.3%. The influence degree of FA content is greater than that of water-binder ratio. With the development of curing age, the influence degree of FA content and water-binder ratio on the strength gradually decreases while the curing method increases. Finally, according to the ANN prediction results, the key mix parameters design method for equal strength HVFAC under multi-factor conditions was proposed, which provide guidance for concrete preparation in actual engineering.

Abstract Background Excessive oxidative stress plays a critical role in the progression of various diseases, including intervertebral disk degeneration (IVDD). Recent studies have found that anemonin (ANE) possesses antioxidant and anti-inflammatory effects. However, the role of ANE in IVDD is still unclear. Therefore, this study investigated the effect and mechanism of ANE on H2O2 induced degeneration of nucleus pulposus cells (NPCs). Methods NPCs were pretreated with ANE, and then treated with H2O2. NOX4 was upregulated by transfection of pcDNA-NOX4 into NPCs. Cytotoxicity was detected by MTT, oxidative stress-related indicators and inflammatory factors were measured by ELISA, mRNA expression was assessed by RT-PCR, and protein expression was tested by western blot. Results ANE attenuated H2O2-induced inhibition of NPCs activity. H2O2 enhanced oxidative stress, namely, increased ROS and MDA levels and decreased SOD level. However, these were suppressed and pretreated by ANE. ANE treatment repressed the expression of inflammatory factors (IL-6, IL-1β and TNF-α) in H2O2-induced NPCs. ANE treatment also prevented the degradation of extracellular matrix induced by H2O2, showing the downregulation of MMP-3, 13 and ADAMTS-4, 5 and the upregulation of collagen II. NOX4 is a key factor regulating oxidative stress. Our study confirmed that ANE could restrain NOX4 and p-NF-κB. In addition, overexpression of NOX4 counteracted the antioxidant and anti-inflammatory activities of ANE in H2O2-induced NPCs, and the inhibition of the degradation of extracellular matrix induced by ANE was also reversed by overexpression of NOX4. Conclusion ANE repressed oxidative stress, inflammation and extracellular matrix degradation in H2O2-induced NPCs by inhibiting NOX4/NF-κB pathway. Our study indicated that ANE might be a candidate drug for the treatment of IVDD.

Abstract Study objectives To assess the effect of dexmedetomidine (DEX) on postoperative sleep quality using polysomnography (PSG) to identify possible interventions for postoperative sleep disturbances. Methods An electronic search of PubMed/MEDLINE, EMBASE, Cochrane Library and Web of Science was conducted from database inception to November 20, 2022. Randomized controlled trials (RCTs) on the effect of DEX administration on postoperative sleep quality using PSG or its derivatives were included. No language restrictions were applied. The sleep efficiency index (SEI), arousal index (AI), percentages of stage N1, N2 and N3 of non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep were measured in our meta-analysis. Results Five studies, involving 381 participants were included. Administration of DEX significantly improved SEI, lowered AI, decreased the duration of stage N1 sleep and increased the duration of stage N2 sleep compared to placebo groups. There were no significant differences in the duration of stage N3 sleep and REM sleep. DEX administration lowered the postoperative Visual Analogue Scale (VAS) score and improved the Ramsay sedation score with no adverse effect on postoperative delirium (POD). However, high heterogeneity was observed in most of the primary and secondary outcomes. Conclusions Our study provides support for the perioperative administration of DEX to improve postoperative sleep quality. The optimal dosage and overall effect of DEX on postoperative sleep quality require further investigation using large-scale randomized controlled trials.

This present study explores the effect of social support on career decision-making difficulties, with the chain mediation of psychological capital and career decision-making self-efficacy. A total of 770 college students were recruited to complete the survey, which included a social support, career decision-making self-efficacy, psychological capital scale, and career decision-making difficulties scales. Significant correlations were found between social support, career decision-making difficulties, psychological capital, and career decision making self-efficacy. Path analysis indicated that the direct effect of social support on career decision-making difficulty was non-significant; social support affected career decision-making difficulties indirectly through not only the mediating effect of psychological capital but also through the chain mediation of psychological capital and career decision-making self-efficacy. Overall, the results show that social support could exert an effect on career decision-making difficulties through the mediational chains of career decision-making self-efficacy and psychological capital; the implications of this are discussed.

Background: Epidemiological studies show that outdoor artificial light at night (ALAN) is linked to metabolic hazards, but its association with metabolic syndrome (MetS) remains unclear. We aimed to investigate the association of outdoor ALAN with MetS in middle-aged and elderly Chinese. Methods: From 2017–2020, we conducted a cross-sectional study in a total of 109,452 participants living in ten cities of eastern China. MetS was defined by fasting blood glucose (FG), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), blood pressure (BP), and waist circumference (WC). In 2021, we followed up 4395 participants without MetS at the baseline. Each participant's five-year average exposure to outdoor ALAN, as well as their exposure to green space type, were measured through matching to their address. Generalized linear models were used to assess the associations of outdoor ALAN with MetS. Stratified analyses were performed by sex, age, region, physical activity, and exposure to green space. Results: In the cross-sectional study, compared to the first quantile (Q1) of outdoor ALAN exposure, the odds ratios (ORs) of MetS were 1.156 [95 % confidence interval (CI): 1.111–1.203] and 1.073 (95 %CI: 1.021–1.128) respectively in the third and fourth quantiles (Q3, Q4) of outdoor ALAN exposure. The follow-up study found that, compared to the first quantile (Q1) of outdoor ALAN exposure, the OR of MetS in Q4 of ALAN exposure was 1.204 (95 %CI: 1.019–1.422). Adverse associations of ALAN with MetS components, including high FG, high TG, and obesity, were also found. Greater associations of ALAN with MetS were found in males, the elderly, urban residents, those with low frequency of physical activity, and those living in areas with low levels of grass cover and tree cover. Conclusions: Outdoor ALAN exposure is associated with an increased MetS risk, especially in males, the elderly, urban residents, those lacking physical activity, and those living in lower levels of grass cover and tree cover.

Abstract Intelligent and coordinated unmanned aerial vehicle (UAV) swarm combat will be the main mode of warfare in the future, and mechanistic design of autonomous cooperation within swarms is the key to enhancing combat effectiveness. Exploration of the essential features and patterns of autonomous collaboration in unmanned swarms has become the focus of scientific research and technological applications, in keeping with the evolving conceptions of the military theatre. However, given the unique attributes of the military and the novelty of the warfare mode of unmanned swarms, few achievements have been reported in the existing research. In this study, we analysed the military requirements of unmanned swarm operations and proposed an analytic framework for autonomous collaboration. Then, a literature review addressing swarm evolution dynamics, game-based swarm collaboration, and collaborative evolution on complex networks was conducted. Next, on the basis of the above work, we designed a community network for unmanned swarm cooperation and constructed a collaborative evolution model based on the multiplayer public goods game (PGG). Furthermore, according to the “network” and “model”, the dynamic evolution process of swarm collaboration was formally deduced. Finally, a simulation was conducted to analyse the influence of relevant parameters (i.e., swarm size, degree distribution, cost, multiplication factor) on the collaborative behaviour of unmanned swarms. According to the simulation results, some reasonable suggestions for collaborative management and control in swarm operation are given, which can provide theoretical reference and decision-making support for the design of coordination mechanisms and improved combat effectiveness in unmanned swarm operation.

Summary: As highly organized consortia of bacteria, biofilms have long been implicated in aggravating inflammation. However, our understanding regarding in vivo host-biofilm interactions in the complex tissue environments remains limited. Here, we show a unique pattern of crypt occupation by mucus-associated biofilms during the early stage of colitis, which is genetically dependent on bacterial biofilm-forming capacity and restricted by host epithelial α1,2-fucosylation. α1,2-Fucosylation deficiency leads to markedly augmented crypt occupation by biofilms originated from pathogenic Salmonella Typhimurium or indigenous Escherichia coli, resulting in exacerbated intestinal inflammation. Mechanistically, α1,2-fucosylation-mediated restriction of biofilms relies on interactions between bacteria and liberated fucose from biofilm-occupied mucus. Fucose represses biofilm formation and biofilm-related genes in vitro and in vivo. Finally, fucose administration ameliorates experimental colitis, suggesting therapeutic potential of fucose for biofilm-related disorders. This work illustrates host-biofilm interactions during gut inflammation and identifies fucosylation as a physiological strategy for restraining biofilm formation.

The digital image method of monitoring structural displacement is receiving more attention today, especially in non-contact structure health monitoring. Some obvious advantages of this method, such as economy and convenience, were shown while it was used to monitor the deformation of the bridge structure during the service period. The image processing technology was used to extract structural deformation feature information from surveillance video images containing structural displacement in order to realize a new non-contact online monitoring method in this paper. The influence of different imaging distances and angles on the conversion coefficient (η) that converts the pixel coordinates to the actual displacement was first studied experimentally. Then, the measuring and tracking of bridge structural displacement based on surveillance video images was investigated by laboratory-scale experiments under idealized conditions. The results showed that the video imaging accuracy can be affected by changes in the relative position of the imaging device and measured structure, which is embodied in the change in η (actual size of individual pixel) on the structured image. The increase in distance between the measured structure and the monitoring equipment will have a significant effect on the change in the η value. The value of η varies linearly with the change in shooting distance. The value of η will be affected by the changes in shooting angle. The millimeter-level online monitoring of the structure displacement can be realized using images based on surveillance video images. The feasibility of measuring and tracking structural displacement based on surveillance video images was confirmed by a laboratory-scale experiment.

Abstract Cyber‐attack has become one of the main threats to the safe operation of the load control system in the distribution network. Currently, a large number of methods are developed to detect cyber‐attacks. However, most of these methods make decisions based on information from a single cyber layer or physical layer. If the decision is wrong, there is no way to verify it. Therefore, if the separate decisions can be made in the cyber layer and physical layer at the same time, and a final judgment is received throughout the two decisions, then the accuracy and credibility of cyber‐attack detection can be improved. First, the particle swarm optimization‐based backpropagation neural network is adopted to detect attacks in the cyber layer, at the same time, the criteria importance though intercrieria correlation‐based grey relational analysis is adopted for the assessment of node risk level in the physical layer. Then, based on the incidence matrix model between the cyber layer and the physical layer, a crosscheck mechanism is proposed to detect the cyber‐attack through the verification of the two decisions. Finally, taking the IEEE 33‐node system as an example, the validity of the proposed method to detect the denial of service attack is verified.

We investigated the spin–orbit torque (SOT) and unidirectional spin Hall magnetoresistance (USMR) in Pt/CoFe/Ta trilayer as well as Pt/CoFe and CoFe/Ta bilayers with in-plane magnetic anisotropy by performing transverse and longitudinal second harmonic resistance measurements. Compared to the two bilayers, we found that the trilayer exhibits enhanced SOT and USMR due to the opposite spin Hall angles of Pt and Ta, which work together to enhance the spin accumulation in the trilayer. Furthermore, we found that thermal annealing has a significant influence on the magnitude and sign of the SOT and USMR in the Pt/CoFe/Ta trilayers. Specifically, we observed that both the damping-like SOT and USMR of the trilayer decrease as the annealing temperature increases, and they even change signs at an annealing temperature between 235 and 265 °C. In contrast, the sign change of the SOT and USMR upon annealing is absent in the Pt/CoFe and CoFe/Ta bilayers. These findings suggest that the sign of the SOT and USMR in the Pt/CoFe/Ta trilayer can be easily manipulated by using an appropriate thermal annealing treatment, which has important implications for the development of novel spintronic devices.

BackgroundParasternal intercostal nerve block has been increasingly used for postoperative analgesia and has shown that this technique can provide effective postoperative analgesia. This study aimed to investigate the effect of preemptive parasternal intercostal nerve block on the opioid and vasoactive drug dose required for intraoperative hemodynamic stability and postoperative analgesia in patients undergoing off-pump coronary artery bypass grafting.MethodsIn this prospective, randomized controlled study, 64 participants aged 45–75 years scheduled for off-pump coronary artery bypass grafting at The Second Xiangya Hospital of Central South University. Patients were randomized into two groups and preoperatively administered ropivacaine (group R) and saline (group S), in the parasternal intercostal spaces with ultrasound-guided bilateral nerve block.ResultsThe primary outcome was intraoperative sufentanil and vasopressor dosage. The secondary outcomes were intraoperative hemodynamics, postoperative pain scores, and anesthesia recovery, postoperative use of rescue dezocine, stay in intensive care unit, and length of hospital stay. The consumption of intraoperative sufentanil and vasopressor was significantly lower in group R than in group S. The visual analog score in group R was significantly lower than that in group S up to 12 h postoperatively. The time to anesthesia recovery was significantly less in group R than in group S. Most patients in group S required rescue dezocine, whereas most patients in group R did not. The hemodynamic variables were stable in all patients.ConclusionsA preemptive parasternal intercostal nerve block effectively reduced the required intraoperative sufentanil and norepinephrine dose and provided adequate analgesia for the first 12 h after surgery. Therefore, a preemptive parasternal intercostal nerve block is a good option for patients undergoing off-pump coronary artery bypass grafting.Clinical trial registrationchictr.org.cn, identifier ChiCTR1800017210.

Bisphenol F (BPF), BPS and BPAF are gaining popularity as main substitutes to BPA, but there is no clear evidence that these compounds disrupt glycemic homeostasis in the same way. In this study, four bisphenols were administered to C57BL/6 J mice, and showed that the serum insulin was elevated in the BPA and BPS exposed mice, whereas BPF exposed mice exhibited lower serum insulin and higher blood glucose. BPF decreased oxidized glutathione/reduced glutathione ratio (GSSG/GSH) and N6–methyladenosine (m6A) levels, which was responsible for pancreatic apoptosis in mice. Additionally, the downregulation of Nrf2 and the aberrant regulation of the p53-lncRNA H19 signaling pathway further increased miR-200 family in the BPF-exposed pancreas. The miR-200 family directly suppressed Mettl14 and Xiap by targeting their 3' UTR, leading to islet apoptosis. Antioxidant treatment not only elevated m6A levels and insulin contents but also suppressed the miR-200 family in the pancreas, ultimately improving BPF-induced hyperglycemia. Taken together, miR-200 family could serve as a potential oxidative stress-responsive regulator in the pancreas. And moreover, we demonstrated a novel toxicological mechanism in that BPF disrupted the Keap1-Nrf2 redox system to upregulate miR-141/200b/c which controlled pancreatic insulin production and apoptosis via Mettl14 and Xiap, respectively. As the major surrogates of BPA in various applications, BPF was also diabetogenic, which warrants attention in future research.

Measurement(s) train operation data of China high-speed railway network • locations of railway stations • weather and temperature and wind power Technology Type(s) web scraping with python • Geographic Information System Factor Type(s) high-speed train departure delay time • high-speed train arrival delay time • various external factors affecting train operation • bad weather exposure time of railway stations • railway station community size Sample Characteristic - Organism high-speed train Sample Characteristic - Environment railway system Sample Characteristic - Location China

Straw return (SR) plus nitrogen (N) fertilizer has become a practical field management mode to improve soil fertility and crop yield in North China. This study aims to explore the relationship among organic waste, mineral nutrient utilization, and crop yield under SRN mode. The fertilizer treatments included unfertilized (CK), SR (straws from wheat and corn), N fertilizer (N), and SR plus N fertilizer (SRN). SRN treatment not only significantly increased the grain yield, net photosynthetic rate, and transpiration rate but also enhanced the contents of chlorophyll, soluble sugar, and soluble protein and increased the activities of antioxidant enzymes but reduced intercellular CO2 concentration and malondialdehyde (MDA) content when compared to other treatments. There were 2572, 1258, and 3395 differentially expressed genes (DEGs) identified from the paired comparisons of SRvsCK, NvsCK, and SRNvsCK, respectively. The transcript levels of many promising genes involved in the transport and assimilation of potassium, phosphate, and nitrogen, as well as the metabolisms of sugar, lipid, and protein, were down-regulated by straw returning under N treatment. SRN treatment maintained the maximum maize grain yield by regulating a series of genes’ expressions to reduce nutrient shortage stress and to enhance the photosynthesis of ear leaves at the maize grain filling stage. This study would deepen the understanding of complex molecular mechanisms among organic waste, mineral nutrient utilization, crop yield, and quality.

A 1550 nm all-fiber dual-polarization coherent Doppler lidar (DPCDL) was constructed to measure the depolarization ratio of atmospheric aerosols. In lidar systems, the polarization state of the laser source is typically required to be that of linearly parallel polarization. However, due to the influence of the fiber-optical transmission and the large-mode field output of the telescope, the laser polarization state changes. Hence, a polarizer was mounted to the emitting channel of the telescope to eliminate the depolarization effect. A fiber-optical polarization beam splitter divided the backscattered light into components with parallel and perpendicular polarization. The DPCDL used two coherent channels to receive each of these two polarization components. A calibration procedure was designed for the depolarization ratio to determine the differences in gain and non-responsiveness in the two polarization channels. The calibration factor was found to be 1.13. Additionally, the systematic error and the measured random error of the DPCDL were estimated to evaluate the performance of the system. The DPCDL’s systematic error was found to be about 0.0024, and the standard deviation was lower than 0.0048. The Allan deviations of a 1-min averaging window with a low SNR of 19 dB and a high SNR of 27 dB were 0.0104 and 0.0031, respectively. The random errors at different measured heights were mainly distributed below 0.015. To confirm the authenticity of the atmospheric depolarization ratio measured with the DPCDL, two field observations were conducted with the use of a co-located DPCDL and micro-pulse polarization lidar to perform a comparison. The results showed that the correlation coefficients of the aerosol depolarization ratios were 0.73 and 0.77, respectively. Moreover, the two continuous observations demonstrated the robustness and stability of the DPCDL. The depolarization ratios were detected in different weather conditions.

Global glacial chemical denudation is one of the largest contributors to global elemental cycles and, amplified by climate warming, will significantly impact nutrient loads in downstream ecosystems.

Comparative analysis of the impacts of precipitation and land use on streamflow from adjacent catchments is critical to exploring pathways toward water security and sustainable development. In this work, two adjacent catchments (the Mayinghe and Xidahe, abbreviated as MYC and XDC, respectively) in northwestern China were selected to compare the impacts of precipitation change and land use alteration on streamflow change during 1956–2019 using field observation streamflow data and satellite data. An opposite trend of streamflow was found for the two catchments from 1956 to 2019: the streamflow decreased significantly in the MYC (-0.63 × 107m3/10a, p < 0.05), while it increased in the XDC (0.71 × 107m3/10a, p < 0.05). Land conversion dominated the streamflow reduction in the MYC, with a contribution of about 68.3%. In the XDC, precipitation was confirmed to be the major factor driving the increase in streamflow. The streamflow for farmland irrigation reached 27.97 × 104 m3/km2 in the MYC, which was the leading factor of streamflow reduction in the basin. The findings obtained from this work can shed light on the quantitative understanding of streamflow changes in small catchments and offer a scientific basis for sustainable water management in other inland river basins.

ABSTRACT The Cre/lox system is a fundamental tool for functional genomic studies, and a number of Cre lines have been generated to target genes of interest spatially and temporally in defined cells or tissues; this approach has greatly expanded our knowledge of gene functions. However, the limitations of this system have recently been recognized, and we must address the challenge of so‐called nonspecific/off‐target effects when a Cre line is utilized to investigate a gene of interest. For example, cathepsin K (Ctsk) has been used as a specific osteoclast marker, and Cre driven by its promoter is widely utilized for osteoclast investigations. However, Ctsk‐Cre expression has recently been identified in other cell types, such as osteocytes, periosteal stem cells, and tenocytes. To better understand Ctsk‐Cre expression and ensure appropriate use of this Cre line, we performed a comprehensive analysis of Ctsk‐Cre expression at the single‐cell level in major organs and tissues using two green fluorescent protein (GFP) reporters (ROSA nT‐nG and ROSA tdT) and a tissue clearing technique in young and aging mice. The expression profile was further verified by immunofluorescence staining and droplet digital RT‐PCR. The results demonstrate that Ctsk‐Cre is expressed not only in osteoclasts but also at various levels in osteoblast lineage cells and other major organs/tissues, particularly in the brain, kidney, pancreas, and blood vessels. Furthermore, Ctsk‐Cre expression increases markedly in the bone marrow, skeletal muscle, and intervertebral discs in aging mice. These data will be valuable for accurately interpreting data obtained from in vivo studies using Ctsk‐Cre mice to avoid potentially misleading conclusions. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Abstract Grain weight and grain number, the two important yield traits, are mainly determined by grain size and panicle architecture in rice. Herein, we report the identification and functional analysis of OsSPL4 in panicle and grain development of rice. Using CRISPR/Cas9 system, two elite alleles of OsSPL4 were obtained, which exhibited an increasing number of grains per panicle and grain size, resulting in increase of rice yield. Cytological analysis showed that OsSPL4 could regulate spikelet development by promoting cell division. The results of RNA-seq and qRT-PCR validations also demonstrated that several MADS-box and cell-cycle genes were up-regulated in the mutation lines. Co-expression network revealed that many yield-related genes were involved in the regulation network of OsSPL4. In addition, OsSPL4 could be cleaved by the osa-miR156 in vivo, and the OsmiR156-OsSPL4 module might regulate the grain size in rice. Further analysis indicated that the large-grain allele of OsSPL4 in indica rice might introgress from aus varieties under artificial selection. Taken together, our findings suggested that OsSPL4 could be as a key regulator of grain size by acting on cell division control and provided a strategy for panicle architecture and grain size modification for yield improvement in rice.

Purpose: To examine the differences in gene expression between ruptured and non-ruptured nucleus pulposus tissues of the intervertebral discs using gene chip technology.Methods: A total of 8 patients with nucleus pulposus from a lumbar disc herniation (LDH) undergoing discectomy in our hospital were selected, including 4 ruptured and 4 non-ruptured herniated nucleus pulposus cases. Total RNA was extracted from cells by using TRIzol reagent. Nucleus pulposus cDNA probes of the two groups were obtained by the single marker method and hybridized with a human gene expression profiling chip (Agilent). The fluorescence signal images were scanned by a laser, and the obtained genes were analyzed by bioinformatics.Results: There were 75 differentially expressed genes with more than 2-fold-changes, of which 56 were up-regulated and 19 were down-regulated. The differential expression of THSD7A, which was up-regulated 18 times, was the most significant, followed by CCL5, AQP3 and SDC4.Conclusion: THSD7A can be used as a characteristic differentially expressed gene in human ruptured nucleus pulposus. Moreover, CCL5, AQP3 and SDC4 may improve the chemotaxis of stem cell migration for self-healing of damaged disc tissue, increase water uptake by nucleus accumbens cells, and inhibit the inflammatory response, thus delaying the process of intervertebral disc degeneration.

Bacterial biofilms play essential roles in ecological environments and in human health. The spatial heterogeneity of biofilms is crucial to their resistance and collective behavior, while quantitative analysis of these biofilm‐specific features is limited. Here, a microfluidic approach is developed to address this issue. Through a special design of microfluidic chamber and spatially controllable bacteria seeding, biofilms are cultivated with customized semi‐2D structure, which enables quantitative measurements of spatially heterogeneous features with time‐lapse microscopy. The advantages of the proposed method are demonstrated via two examples on biofilm homeostasis and stress response, respectively, where the functionally important spatiotemporal dynamics is delineated. In homeostasis, it is found that Pseudomonas aeruginosa biofilms use spatially organized extracellular matrix to preserve iron chelators within their boundaries while maximizing free sharing within the community. In stress response, the spatial distribution of antibiotics in biofilms and how a change in energy metabolism leads to redistribution of drugs over space are elucidated. The proposed method enables cultivating biofilms formed by a wide range of species and even multiple biofilms, which provides a tractable approach to understanding the spatiotemporal features of biofilms formed by environmentally and clinically important bacteria.

Driver fatigue is an important contributor to traffic accidents, and driver fatigue is significant for the safety of people’s lives. Aiming to prevent traffic accidents caused by driver fatigue, a series of real driving experiments was carried out in the present work. First, based on an analysis with respect to distortion energy density (DED) theory and the experimental results, the upper trapezius at 6th neck vertebrae is more sensitive to driver fatigue and easier to fatigue than that at 7th neck vertebrae in a real driving. And then 2 cm from the 6th vertebrae on both sides were selected as the locations of data acquisition for electromyography (EMG) signal. The experimental results show that the approximate entropy (ApEn) from the electroencephalography (EEG), EMG, and respiration (RESP) signals decreases with increasing driving time, indicating that the degree of fatigue increases. After approximately 90 min, the rate of decrease in ApEn becomes slow, indicating deeper driver fatigue. According to three-D analysis, principal component analysis, and fuzzy C-means clustering analysis, the EEG-EMG combination effectively reflects the state of drivers. Finally, the ApEns from EEG and EMG were selected as independent variables, and a discriminant model of driver fatigue based on Mahalanobis distance theory was built. The accuracy of the model is up to 90.92% by 10-fold cross validation. The reasons for the high accuracy are the reasonable selection of the locations of EMG data acquisition and better degree of discrimination of EEG and EMG. The main contributions of this study are to provide a theoretical foundation for establishing internationally recognized standard locations for neck EMG data acquisition, and to provide a feasible method for discriminating driver fatigue in real driving tasks.

In recent years, residual learning has shown excellent performance on convolutional neural network (CNN)-based single-image super-resolution (SISR) tasks. However, CNN-based SISR approaches have focused mainly on the design of deep architectures, and the rectified linear units (ReLUs) used in these networks hinder shallow-to-deep information transfer. As a result, these methods are unable to utilize some shallow information, and improving model performance is difficult. To solve the above issues, this paper proposes an image SR reconstruction method based on a generative adversarial network with a residual dense architecture. First, before ReLU activation, the number of feature channels is expanded by a factor of 6~9 using a 1 × 1 convolutional layer, which improves the utilization of shallow information. Next, the original discriminator is replaced with a relativistic average discriminator, thereby improving the authenticity of the discriminative network. Finally, preactivation features are used to improve the perceptual loss, thus providing stronger monitoring for brightness consistency and texture restoration. Experimental results show that the proposed algorithm improves the utilization of shallow information in a deep network. Structural similarity (SSIM) index evaluations show that the overall utilization of shallow information is increased by 105.52%. In addition, the average runtime is 0.42 sec/frame, nearly 3.6 times faster than those of traditional methods. Moreover, the recovered images have an average natural image quality evaluator value of 3.4 and high perceptual quality, showing that the proposed method is suitable for image reconstruction applications in fields such as agriculture and medicine.

Stock prediction is a challenging task concerned by researchers due to its considerable returns. It is difficult because of the high randomness in the stock market. Stock price movement is mainly related to the capital situation and hot events. In recent years, researchers improved prediction accuracy with news and social media. However, the existing methods do not take into account the different influences of events. To solve this problem, we propose a multi-element hierarchical attention capsule network, which consists of two components. The former component, multi-element hierarchical attention, quantifies the importance of valuable information contained in multiple news and social media through its weights assignment process. And the latter component, capsule network, learns more context information from the events through its vector representation in the hidden layer. Moreover, we construct a combined data set to maintain the complementarity between social media and news. Finally, we achieve better results than baselines, and experiments show that our model improves prediction accuracy by quantifying the different influences of events.

We have studied annealing-induced oxygen migration at CoFe/MgO and CoFe/HfO2 interfaces and its effect on the magnetic anisotropy of Ta/CoFe/MgO (HfO2) films. Through x-ray photoelectron spectroscopy, we found that the Fe–O bonds exist at both CoFe/MgO and CoFe/HfO2 interfaces at the as-deposited state due to the oxidation of interfacial Fe atoms during the deposition of the MgO and HfO2 layers. After annealing, the amount of the Fe–O bonds at the CoFe/MgO interface decreases, whereas at the CoFe/HfO2 interface, it increases, indicating that the oxygen atoms migrate from Fe–O bonds to MgO layers at the CoFe/MgO interface, whereas they migrate from the HfO2 layer to Fe–O bonds at the CoFe/HfO2 interface. Correspondingly, the magnetic anisotropy energy decreases in the Ta/CoFe/MgO film but increases in the Ta/CoFe/HfO2 film after annealing. We attributed these results to interfacial Fe 3d–O 2p orbital hybridization modulated by different oxygen migration behaviors. Our results may improve the understanding of the oxygen migration effect on magnetic anisotropy and anomalous Hall sensitivity in ferromagnet/oxide heterostructures.

Train station delay prediction is always one of the core research issues in high-speed railway dispatching. Reliable prediction of station delay can help dispatchers to accurately estimate the train operation status and make reasonable dispatching decisions to improve the operation and service quality of rail transit. The delay of one station is affected by many factors, such as spatiotemporal factor, speed limitation or suspension caused by strong wind or bad weather, and high passenger flow caused by major holiday. But previous studies have not fully combined the spatiotemporal characteristics of station delay and the impact of external factors. This paper makes good use of the train operation data, proposes the multiattention mechanism to capture the spatiotemporal characteristics of train operation data and process the external factors, and establishes a Multiattention Train Station Delay Graph Convolution Network (MATGCN) model to predict the train delay at high-speed railway stations, so as to provide references for train dispatching and emergency plan. This paper uses real train operation data coming from China high-speed railway network to prove that our model is superior to ANN, SVR, LSTM, RF, and TSTGCN models in the prediction effect of MAE, RMSE, and MAPE.

By relying on the advantages of a uniform site distribution and continuous observation of the Continuously Operating Reference Stations (CORS) system, real-time high-precision Global Navigation Satellite System/Precipitable Water Vapor (GNSS/PWV) data interpretation can be carried out to achieve accurate monitoring of regional water vapor changes. The study of the atmospheric water vapor content and distribution changes is the basis for the realization of rainfall forecasting and water vapor circulation research. Such research can provide data support for the effective forecasting of regional precipitation in megacities and the construction of a more sensitive flood prevention and warning system. Nowadays, a single model is often adopted for GNSS/PWV time series. This makes it challenging to match the high randomness characteristic of water vapor change. This study proposes a hybrid model that takes into account the linear and nonlinear aspects of water vapor data by using complete empirical mode decomposition (CEEMDAN) of adaptive noise, differential autoregressive integrated moving average (ARIMA), and the long-short-term memory network (LSTM). The CEEMDAN is used to decompose the water vapor data series. Then, the high- and low-frequency data are modeled separately, reducing the sequence’s complexity and non-stationarity. In selecting the prediction model, we use the ARIMA model for the high-frequency series and the ARIMA–GWO–LSTM ensemble model for the low-frequency sub-series and residual series. The model is verified using GNSS/PWV time series data collected at the Hong Kong CORS station in July 2021. The results show the following: (1) The LSTM model optimized by the grey wolf optimization algorithm (GWO) is comparable with the single LSTM model in the low-frequency sequence prediction process, and the error items are reduced by 30% after calculation. (2) During the process from CEEMDAN decomposition to the use of the combination model for prediction, the accuracy evaluation indexes of the station increase by more than 20%. The interpolation method can accurately determine the regional water vapor spatial variation, which is of practical significance for local rainfall forecasting. High-frequency data obtained by CEEMDAN decomposition demonstrate the dramatic changes in water vapor before and after the rainfall, which can provide ideas for improving the accuracy of rainfall forecasting.

Autophagy has been proved to occur in rats with intervertebral disc degeneration (IVDD). Yiqi Huoxue recipe (YQHXR), an effective therapy of traditional Chinese medicine, was widely used for ruptured lumbar disc herniation under clinical observation. More importantly, YQHXR positively regulated the expression of autophagy-related proteins. However, little is known about the significance of YQHXR in the pathologic process of IVDD. Therefore, this study explored the protective effect of YQHXR based on IVDD rat model through magnetic resonance imaging and histopathologic analysis. Then we evaluated the formation of autophagosomes in the degenerated intervertebral disc by transmission electron microscope. Real-time PCR was used to detect the changes of autophagy-related genes. Western blot and immunoprecipitation were used to assess the protein expression of the autophagy-related pathway. We found that YQHXR-induced autophagy attenuated the release of inflammatory factors. In addition, YQHXR promoted the formation of Beclin1-VPS34 complex to activate autophagy through not only activation of the upstream protein AMPK and upregulation of the deubiquitinase USP13, thus in turn alleviating the development of IVDD. We proposed the potential molecular mechanism of YQHXR on autophagy for the first time, so as to provide a theoretical and experimental basis for the clinical application of YQHXR in the treatment of IVDD-related diseases.

Psychological capital (PsyCap) is documented to be positive in influencing employees’ behavior. However, little attention has been paid to its role in maintaining a sustainable workforce in underprivileged rural areas. Also less known is the complex relations between PsyCap and other consequence variables. Moreover, previous studies in this field did not adequately address the cross-cultural applications of positive resources, though many facets of PsyCap are culture related. To address the gaps, the current study explored the complex relationships linking PsyCap and organizational commitment in a sample of public civil servants (gongwuyuan cadres, n=583) at the township level in the rural areas of northwestern China. Two types of PsyCap, task-oriented PsyCap, which is similar to the PsyCap in the west, and guanxi-oriented PsyCap, which is unique in the Chinese culture, were measured. Task-oriented PsyCap is composed of enterprise-diligence, resiliency-perseverance, optimism-hope, and confidence-courage. Guanxi-oriented PsyCap is composed of toleration-forgiveness, modesty-prudence, thanksgiving-dedication, and respect-courtesy. AMOS 23.0 software was used to establish structural equation models. The results show that both types of PsyCap were positive predictors of organizational commitment. Vocational identity and job satisfaction mediated the relation between task-oriented PsyCap/guanxi-oriented PsyCap and organizational commitment. The chained relationship from the two types of PsyCap to vocational identity, job satisfaction, and organizational commitment was also significant. These results and their implications for workforce stability are discussed.

Microplastic (MP) is an emerging environmental pollutant and exposure to MPs has been associated with numerous adverse health outcomes in both wild and laboratory animals. The toxicity of MPs depends on concentration, exposure time, chemical composition and size distribution, but the impacts of particle size remain inconclusive yet. In this study, adult marine medaka (Oryzias melastigma) were exposed to different size of polystyrene MPs (PS-MPs) with concentration of 10 mg/L for 60 days and the growth performance, lipid metabolism, immune parameters and gut microbiome were determined. Results indicated that particle size is a dominant factor causing lipid metabolism disorders and hepatic toxicity in PS-MPs-exposed fish. The bodyweight, adipocyte size and hepatic lipid contents were significantly increased in 200 μm PS-MPs-exposed fish, while 2 and 10 μm PS-MPs-exposed fish exhibited liver injury principally manifested as the presence of little fibrosis and inflammation. Given that larger particles could not enter the circulatory system, the impacts of PS-MPs on intestinal microbial biota homeostasis were further investigated. The results not only showed the characterization of gut microbial communities in Oryzias melastigma, but also indicated that microbial diversity and composition were altered in gut of fish exposed to PS-MPs, in particular 200 μm PS-MPs. The differentially abundant bacterial taxa in PS-MPs-exposed fish mainly belonged to the phylum Verrucomicrobia, Firmicutes and Fusobacteria. And furthermore, increased abundance of Verrucomicrobia and Firmicutes/Bacteroidetes ratio and decreased Fusobacteria were correlated with the increased bodyweight. Intestinal microbiome should play a critical role in regulating host lipid metabolism in fish exposed to lager size of PS-MPs.