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Volatile components in red orange essential oil extracted by two cold pressing processes (cup pressing and lime method) were analyzed by gas chromatography quadrupole time-of-flight mass spectrometry (GC-Q/TOF). A total of 93 components were identified, 89 and 84 compounds were identified for the two types of red orange essential oils, respectively. Among the 93 components, there were 29 terpenes, 20 alcohols, 20 aldehydes, 5 esters, 2 ketones, 12 hydrocarbons, and 5 other compounds. There were 80 compounds shared by the two essential oils. The total volatile component content of red orange essential oil by cup pressing method was significantly higher than that by lime method. The highest content of these compounds was terpenes which total content was over 80%. In addition, the compounds with higher content were D-limonene, γ-terpinene, β-myrcene, linalool and α-pinene. According to principal component analysis (PCA), there was a significant difference in the volatile components of the two types of red orange essential oils. The relative odor activity value (ROAV) method indicated that linalool was the most important aroma component of the two red orange essential oils. And the citrus aroma properties of red orange essential oil extracted by cup pressing method was significantly stronger than that extracted by lime method. Linalool, thymol, β-myrcene, D-limonene, citronellal, and γ-terpinene were confirmed to the key aroma components of the red orange essential oils.

Hyperspectral datasets captured by airborne are one of the important data sources in the field of hyperspectral image fusion. However, the limited number of data samples often hinders the optimal performance of deep learning-based methods on these datasets. Domain adaptation is expected to alleviate the issue of data scarcity. However, there are two issues that need to be addressed in applying domain adaptation to hyperspectral image fusion, which are the heterogeneity and spatial degradation diversity of hyperspectral data. In this paper, we propose a domain adaptation hyperspectral image fusion network based on spatial-spectral domain separation. The model, constructed with three-dimensional convolutional layers, effectively addresses the challenge of hyperspectral data heterogeneity. Compared with 2D convolution, 3D convolution is able to consider both spatial and spectral dimensions and extract spatial-spectral features efficiently. Based on this, we design a domain-separation architecture to extract domain-invariant and domain-private features in the spatial-spectral domain. The architecture achieves domain adaptation by extracting domain-invariant features from both datasets to obtain the prior knowledge in the source dataset and apply it to the target dataset. Additionally, the spatial degradation of different datasets varies due to distinct shooting conditions during the acquisition. Therefore, the fusion algorithms should be robust to various degradation scenarios. To tackle this challenge, we design the Observation Module to predict degradation information and the Degradation Information Modulation Module to apply it to the input, thereby enhancing the network’s robustness. Experiments on various datasets demonstrate that our method is qualitatively and quantitatively superior to state-of-the-art methods.

Abstract Researchers have investigated the potential of leveraging pre-trained language models, such as CodeBERT, to enhance source code-related tasks. Previous methodologies have relied on CodeBERT’s ‘[CLS]’ token as the embedding representation of input sequences for task performance, necessitating additional neural network layers to enhance feature representation, which in turn increases computational expenses. These approaches have also failed to fully leverage the comprehensive knowledge inherent within the source code and its associated text, potentially limiting classification efficacy. We propose CodeClassPrompt, a text classification technique that harnesses prompt learning to extract rich knowledge associated with input sequences from pre-trained models, thereby eliminating the need for additional layers and lowering computational costs. By applying an attention mechanism, we synthesize multi-layered knowledge into task-specific features, enhancing classification accuracy. Our comprehensive experimentation across four distinct source code-related tasks reveals that CodeClassPrompt achieves competitive performance while significantly reducing computational overhead.

Abstract Continued evolution of SARS-CoV-2 generates variants to challenge antibody immunity established by infection and vaccination. A connection between population immunity and genesis of virus variants has long been suggested but its molecular basis remains poorly understood. Here, we identify a class of SARS-CoV-2 neutralizing public antibodies defined by their shared usage of VL6-57 light chains. Although heavy chains of diverse genotypes are utilized, convergent HCDR3 rearrangements have been observed among these public antibodies to cooperate with germline VL6-57 LCDRs to target a convergent epitope defined by RBD residues S371-S373-S375. Antibody repertoire analysis identifies that this class of VL6-57 antibodies is present in SARS-CoV-2-naive individuals and is clonally expanded in most COVID-19 patients. We confirm that Omicron-specific substitutions at S371, S373 and S375 mediate escape of antibodies of the VL6-57 class. These findings support that this class of public antibodies constitutes a potential immune pressure promoting the introduction of S371L/F-S373P-S375F in Omicron variants. The results provide further molecular evidence to support that antigenic evolution of SARS-CoV-2 is driven by antibody mediated population immunity.

Marine renewable energy has broad application prospects. Compared with the single energy utilization device, the floating multi-energy combined power generation device can better realize the optimal allocation of resources and reduce the development cost of energy. In order to fully understand the development prospects of multi-energy combined power generation devices, this paper starts with the multi-energy combined power generation integration scheme, analyzes the differences between different types of combined power generation devices, and summarizes their technical characteristics. Next, the research progress of each module analysis method and multi-module coupling dynamics analysis method of the floating multi-energy combined power generation device is clarified and summarized in such aspects as theoretical research and simulation. Finally, the applicable scenarios of the various methods are analyzed and the development trends, problems, and challenges of floating multi-energy combined power generation devices are discussed, aiming to provide references for the subsequent construction of economically feasible floating multi-energy combined power generation devices.

Abstract Objective Traditional Chinese exercises (Taichi, Wuqinxi, Liuzijue, and Baduanjin) are considered effective alternative treatments for improving symptoms in the stable phase of COPD. However, the most effective exercise remains unknown. This study compared the effectiveness of different traditional Chinese exercises on pulmonary function in patients with stable chronic obstructive pulmonary disease (COPD) using a network meta-analysis. Methods From database establishment until September 2023, eligible randomized controlled trials (RCTs) were searched. Two reviewers performed the risk of bias assessment of the included studies using the Cochrane Collaboration tool, and the evidence level was suggested using the GRADE system. Results Fifty-seven studies comprising 4294 patients were included. The results of the network meta-analysis show that Baduanjin was most effective in improving the forced expiratory volume in the first second (FEV1). However, Liuzijue significantly improved the first–second forced vital capacity percentage of expected value (FEV1%) and the ratio of the forced expiratory volume in the first second to the forced vital capacity (FEV1/FVC). The probability ranking results indicated that Liuzijue was the most effective, followed by Baduanjin, Wuqinxi, and Taichi. Subgroup analysis in conjunction with intervention duration revealed that Liuzijue had a significant advantage over other interventions for improving FEV1, FEV1%, and FEV1/FVC within 6 months and improved FEV1% and FEV1/FVC for ≥ 6 months. Moreover, Subgroup analysis based on baseline pulmonary function revealed that Liuzijue had a significant advantage over other interventions for improving FEV1% within severe and moderate groups. Finally, Subgroup analysis based on the frequency of interventions showed that Liuzijue was still more effective in improving FEV1, FEV1%, and FEV1/FVC in the ≥ three times one week. Conclusion Liuzijue was more effective than Taichi, Wuqinxi, Liuzijue, and Baduanjin in improving pulmonary function in patients with stable COPD.

Abstract To enhance the drilling efficiency and extend the service life of PDC (Polycrystalline Diamond Composite) bits in shale formations, this study delves into the rock-breaking mechanisms of special-shaped cutters through a comprehensive experimental approach. This involves optimizing the cutter designs, conducting laboratory experiment and field testing. Among the various cutter geometries considered, concave, axe, planar, and triangular cutters are chosen as the focal points for unit rock-breaking experiments. These tests aim to assess their cutting loads and cutting specific energy to gain a deeper understanding of their performance characteristics. Based on experimental, the debris characteristics are analyzed. Based on the understanding of the shale-breaking characteristics of special-shaped cutters, field testing is performed using a novel PDC bit with a special-shaped cutter. Compared with planar cutters, the concave cutter and the triangular cutter generate lower cutting loads and cutting specific energy. Under identical conditions, the average cutting force and cutting specific energy of concave cutter at different cutting depths are reduced by 16.1% and 19.6% Specifically, the concave cutter generates the largest debris when operated under similar conditions, which is beneficial for increasing rock-breaking efficiency. Laboratory experiment indicate that compared to conventional drill bits, the novel drill bit experiences an increase in torque of approximately 9.8% with increasing WOB (weight on bit). Under high WOB, the ROP (rate of penetration) increases by about 75.4%, while the mechanical specific energy decreases by nearly 40%. Additionally, the novel bit vibration characteristics remain superior to conventional drill bits. Field testing shows that the average ROP of the novel bit and total footage drilled increase by up to 13.3% and 27.2%, respectively, in comparison with those for the conventional bit. The research results are helpful to speed up the efficiency of shale gas drilling.

Abstract Hepatocellular carcinoma (HCC) is one of the most common fatal cancers worldwide, and the identification of novel treatment targets and prognostic biomarkers is urgently needed because of its unsatisfactory prognosis. Regulator of G-protein signaling 19 (RGS19) is a multifunctional protein that regulates the progression of various cancers. However, the specific function of RGS19 in HCC remains unclear. The expression of RGS19 was determined in clinical HCC samples. Functional and molecular biology experiments involving RGS19 were performed to explore the potential mechanisms of RGS19 in HCC. The results showed that the expression of RGS19 is upregulated in HCC tissues and is significantly associated with poor prognosis in HCC patients. RGS19 promotes the proliferation and metastasis of HCC cells in vitro and in vivo. Mechanistically, RGS19, via its RGS domain, stabilizes the MYH9 protein by directly inhibiting the interaction of MYH9 with STUB1, which has been identified as an E3 ligase of MYH9. Moreover, RGS19 activates β-catenin/c-Myc signaling via MYH9, and RGS19 is also a transcriptional target gene of c-Myc. A positive feedback loop formed by RGS19, MYH9, and the β-catenin/c-Myc axis was found in HCC. In conclusion, our research revealed that competition between RGS19 and STUB1 is a critical mechanism of MYH9 regulation and that the RGS19/MYH9/β-catenin/c-Myc feedback loop may represent a promising strategy for HCC therapy.

Abstract Background Liver ischemia–reperfusion injury (LIRI) is closely associated with immune infiltration, which commonly occurs after liver surgery, especially liver transplantation. Therefore, it is crucial to identify the genes responsible for LIRI and develop effective therapeutic strategies that target immune response. Methylation modifications in mRNA play various crucial roles in different diseases. This study aimed to identify potential methylation-related markers in patients with LIRI and evaluate the corresponding immune infiltration. Methods Two Gene Expression Omnibus datasets containing human liver transplantation data (GSE12720 and GSE151648) were downloaded for integrated analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted to investigate the functional enrichment of differentially expressed genes (DEGs). Differentially expressed methylation-related genes (DEMRGs) were identified by overlapping DEG sets and 65 genes related to N6-methyladenosine (m6A), 7-methylguanine (m7G), 5-methylcytosine (m5C), and N1-methyladenosine (m1A). To evaluate the relationship between DEMRGs, a protein–protein interaction (PPI) network was utilized. The core DEMRGs were screened using three machine learning algorithms: least absolute shrinkage and selection operator, random forest, and support vector machine-recursive feature elimination. After verifying the diagnostic efficacy using the receiver operating characteristic curve, we validated the expression of the core DEMRGs in clinical samples and performed relative cell biology experiments. Additionally, the immune status of LIRI was comprehensively assessed using the single sample gene set enrichment analysis algorithm. The upstream microRNA and transcription factors of the core DEMRGs were also predicted. Results In total, 2165 upregulated and 3191 downregulated DEGs were identified, mainly enriched in LIRI-related pathways. The intersection of DEGs and methylation-related genes yielded 28 DEMRGs, showing high interaction in the PPI network. Additionally, the core DEMRGs YTHDC1, METTL3, WTAP, and NUDT3 demonstrated satisfactory diagnostic efficacy and significant differential expression and corresponding function based on cell biology experiments. Furthermore, immune infiltration analyses indicated that several immune cells correlated with all core DEMRGs in the LIRI process to varying extents. Conclusions We identified core DEMRGs (YTHDC1, METTL3, WTAP, and NUDT3) associated with immune infiltration in LIRI through bioinformatics and validated them experimentally. This study may provide potential methylation-related gene targets for LIRI immunotherapy.

ObjectiveTo explore the biomechanical factors affecting the stability of athletes in the 143D balance phase of competitive Tai Chi.MethodThe Vicon 3D motion capture system, Kistler 3D force platform, and Noraxon surface electromyography (sEMG) system were used to measure the joint angle, joint moment, center of gravity, ground reaction force, and sEMG data of athletes. The stability index was then calculated according to the formula. Pearson’s or Spearman’s correlation tests were used to analyze the associations between the biomechanical factors and stability index.Results(1) Medial lateral stability index (MLSI): A significant negative correlation was found between the ankle inversion angle of the supporting leg (SL) and MLSI (p < 0.05). (2) Anterior posterior stability index (APSI): Significant negative correlations were observed between the ankle intorsion angle, integrated electromyography (iEMG) of the gastrocnemius, and muscle contribution rates of the tibialis anterior, external oblique, and gastrocnemius of the non-supporting leg (NL) with the APSI (p < 0.05). The ankle dorsiflexion moment, iEMG of the rectus femoris and tibialis anterior, muscle contribution rate of the biceps femoris, and root mean-squared (RMS) amplitude of the gluteus maximus of the SL also showed significant negative correlations with the APSI (p < 0.05). Strong and significant negative correlations were also identified between the hip intorsion angle, iEMG of the tibialis anterior, and RMS amplitude of the rectus femoris of the NL with the APSI (p < 0.01). Further strong and significant negative correlation was also found between the RMS amplitude of the biceps femoris of the SL and APSI (p < 0.01). The knee extorsion angle of the NL was positively correlated with the APSI (p < 0.05). (3) Dynamic postural stability index (DPSI): The knee adduction angle, iEMG of the tibialis anterior, and RMS amplitude of the erector spinae of the NL were significantly positively correlated with the DPSI (p < 0.05). The knee abduction and hip extension moments of the SL were also significantly positively correlated with the DPSI (p < 0.05).ConclusionThe ankle inversion angle of the SL impacts left–right stability, while the NL’s hip and ankle intorsion angles, knee extorsion angle, and exertion on the core muscle and SL’s main muscles, as well as exertion of specific muscles of the NL affect anterior–posterior stability. The hip extension and knee abduction moments of the SL, knee adduction angle, exertion on the tibialis anterior, and activation of the erector spinae of the NL significantly affect the overall stability of an athlete.

Abstract Programmed cell death-ligand 1 (PD-L1) has a significant role in tumor progression and metastasis, facilitating tumor cell evasion from immune surveillance. PD-L1 can be detected in the tumor cell nucleus and exert an oncogenic effect by nuclear translocation. Colorectal cancer (CRC) progression and liver metastasis (CCLM) are among the most lethal diseases worldwide, but the mechanism of PD-L1 nuclear translocation in CRC and CCLM remains to be fully understood. In this study, using CRISPR-Cas9-based genome-wide screening combined with RNA-seq, we found that the oncogenic factor NUP43 impacted the process of PD-L1 nuclear translocation by regulating the expression level of the PD-L1 chaperone protein IPO5. Subsequent investigation revealed that this process could stimulate the expression of tumor-promoting factor TM4SF1 and further activate the JAK/STAT3 signaling pathway, which ultimately enhanced the transcription of PD-L1, thus establishing a PD-L1-nPD-L1-PD-L1 feedback loop that ultimately promoted CRC progression and CCLM. In conclusion, our study reveals a novel role for nPD-L1 in CRC, identifies the PD-L1-nPD-L1-PD-L1 feedback loop in CRC, and provides a therapeutic strategy for CRC patients.

Abstract As a solid energy source, CH4 hydrate will inevitably break down physically as the result of geological movement or exploitation. Here, the molecular dynamics method was employed to simulate the uniaxial-deformation behavior of structure I (sI type) CH4 hydrate under stress. The stress increases regardless of whether the hydrate is stretched or squeezed, and other physical parameters also changed, such as hydrate cage numbers, order parameters, and the number of water molecules. A noticeable difference is observed between the two systems. Upon stretching, the stress immediately recovers to 0 GPa once the hydrate is completely stretched apart. During the squeeze process, the stress is ultimately not zero since solid and liquid are always in contact. When the hydrate is stretched apart, about 5% of water molecules change from solid to liquid, about 7.8% of CH4 molecules lose their shelter and become free due to the disintegration of water cages. While in the squeezing process, large cages (51262) are crushed more easily than small cages (512); in the end, about 93.5% of large cages and 73% of small cages are crushed, and approximately 87.5% CH4 is released from the cages. In mining CH4 hydrates, caution must be exercised, as if the hydrates break as a result of stress, a large release of CH4 may pose a security risk.

Abstract Background From the perspective of graft protection and early rehabilitation during the maturation and remodeling phases of graft healing, suture augmentation (SA) for anterior cruciate ligament reconstruction (ACLR) has attracted more and more attention. Study Design Retrospective study. Purpose To determine whether the additional SA affects clinical results, graft maturation and graft-bone interface healing during two years follow-up after ACLR. Methods 20 ACLRs with additional SA (ACLR-SA group) and 20 ACLRs without additional SA (ACLR group) were performed between January 2020 and December 2021 by the same surgeon and were retrospectively analyzed. Pre- and postoperative International Knee Documentation Committee (IKDC) scores, Lysholm scores, graft failure and reoperation were evaluated. The signal/noise quotient (SNQ) of autografts and the signal intensity of graft-bone interface were analyzed. All 40 patients in ACLR-SA group and ACLR group completed 2-years follow-up. Results There was no patient in the two cohorts experienced graft failure and reoperation. The postoperative IKDC and Lysholm scores have been significantly improved compared with preoperative scored in both ACLR-SA group and ACLR group, however, there was no significant difference between two groups. The SNQ of proximal graft of ACLR-SA group (14.78 ± 8.62 vs. 8.1 ± 5.5, p = 0.041) was significantly greater while the grades of graft-bone interface healing of posterior tibial was significantly lower than that of ACLR group at 1-year postoperatively (p = 0.03), respectively. There were no significant differences between the two groups of the SNQ of proximal, distal medial graft segments, and the graft-bone interface healing grades of anterior femoral, posterior femoral, anterior tibial and posterior tibial at other time points (p>0.05). Conclusions The additional SA in ACLR had no effect on IKDC scores, Lysholm scores, graft maturation and graft-bone interface healing at 2-year postoperatively. Our research does not support the routine use of SA in ACLR.

Abstract Background Previous studies have proven the positive relationship between healthy lifestyles and cognitive function in older adults. However, the specific impacts and mechanisms require further investigation. Therefore, this study aimed to investigate whether healthy lifestyles and cognitive function were associated with Chinese older adults and whether depressive symptoms mediated their association. Methods 8272 valid samples were included using the latest data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Pearson’s test was applied to investigate the relationship between the key variables. Regression models were employed to examine the mediating effects of healthy lifestyles, using Sobel’s test and the bootstrap method to confirm path effects. Results There was a significant correlation between healthy lifestyles, depressive symptoms, and cognitive function (p

To facilitate and even complete the peritectic transformation, the ultrasonic vibration (USV) and isothermal treatment were applied to the solidification process of Cu–70Sn alloy. It was found that the peritectic transformation was difficult to carry out due to the limited atomic diffusion under the normal solidification condition. With the single isothermal treatment, the peritectic transformation could be enhanced to some extent, with a small amount of η phase (Cu6Sn5) formed relying on the coarse elongated primary ε phase (Cu3Sn), but the further prolongation of isothermal time led to the abnormally coarsening of microstructure. When the molten alloy was subjected to 1500W USV and 30 min isothermal treatment, the peritectic transformation was dramatically facilitated. The ultrasonic-induced effects of cavitation and acoustic streaming play an important role in the remarkable reduction in the curvature radius of primary ε phase, thereby enhancing the diffusion of Sn solute atoms from the liquid phase to the interior of ε phase at the following isothermal stage. Accordingly, the transformation degree of ε phase to η phase was increased up to 77 %, and there was a high volume fraction of primary ε phase could thoroughly complete the peritectic transformation.

The design of mooring line parameter for a floating offshore wind turbine (FOWT) should consider the ultimate limit state. Typhoons should be considered as a threatening condition for mooring design, and the characteristics of transient changing wind should be studied. Currently, few extreme value predictions consider gust features, and extreme mooring tensions may be underestimated in practical FOWT design. We conducted the simulations of the 5 MW wind turbine from the National Renewable Energy Laboratory (NREL) in the environmental conditions of extreme gusts, waves, and currents. Extreme gusts were found to cause dramatic increases in mooring tensions under 100-year typhoon conditions. The average conditional exceedance rate (ACER) method is used to predict extreme mooring tensions. The impacts of simulation duration and sample size on the prediction results are then discussed. The results show that in extreme gust conditions, the tail data of the average conditional exceedance rate of mooring tension presents a different extrapolation trend from stable wind conditions. Short-term predicted values in gust conditions are 14–20% larger than those in stable wind conditions. The research shows the necessity of considering threatening gust conditions in the ultimate limit state design of mooring system of FOWT.

The indoor thermal environment has a direct impact on human thermal comfort and health. In order to assess the status of the indoor thermal environment of typical sports buildings in hot summer and cold winter climate zones in China, 14 badminton halls in 10 cities in Hubei Province (including 5 venues in Wuhan) in this climate zone are chosen as research objects for field testing of indoor thermal environment parameters in 4 seasons. All the tested stadiums are naturally ventilated in non-event conditions. The results reveal that the average indoor temperature of badminton halls in summer is excessively high (i.e., 31.89 °C), which is higher than the regulation specified in JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in summer, (i.e., (26–28 °C) or (22–28 °C), respectively). The average indoor temperature of badminton halls in winter is too low (i.e., 12.95 °C), and it is lower than the recommendations of JGJ31-2003 or GB-T18883-2022 on the reference interval of the indoor air temperature of venues in winter (i.e., (16–18 °C) or (16–24 °C), respectively), relative humidity and air velocity are in the thermal comfort interval for all seasons, and the indoor thermal environment factors of badminton courts in spring and autumn meet the comfort requirements. The indoor and outdoor temperatures and the relative humidity of badminton courts are highly correlated. The indoor temperature and relative humidity vary according to changes in those factors outdoors, whereas the air velocity is not affected by outdoor changes. In the hot summer and cold winter climate zones, some discrepancies in the indoor temperature variation patterns of badminton halls at various altitudes are detectable. The results of this study aim to provide a solid basis for the development of indoor thermal-comfort standards for sports stadiums in China.

This study addresses the complexities of applying criminal law during public health emergencies, particularly under the shadow of scientific uncertainty, and explores the challenge of balancing public health protection with individual rights. The primary aim is to dissect the application of criminal law in the context of the COVID-19 pandemic in China, focusing on the impact of scientific uncertainty on legal decision-making and the efficacy of criminal law interventions in public health crises. This study utilized a doctrinal method combined with case studies, integrating theoretical frameworks on risk and uncertainty with an analysis of China's legal responses to COVID-19. It involved assessing legislative and policy documents alongside judicial decisions, focusing on their alignment with evolving scientific understanding and public health strategies. The study reveals significant hurdles, including the limitations of empirical rules in judicial judgments, the emergence of technocratic bureaucracy, and the complexities surrounding risk mitigation and legal attribution under uncertain conditions. It highlights the inadequacy of traditional criminal law mechanisms to respond dynamically to the evolving landscape of public health emergencies. To address these challenges, the study recommends the development of temporary criminal legislation tailored to public health emergencies, the adoption of risk-based criminal law approaches, and the refinement of individualized risk assessment procedures. These measures aim to provide a more flexible and effective legal framework capable of safeguarding public health while ensuring the protection of individual liberties during crises.

Fatty infiltration denotes the anomalous accrual of adipocytes in non-adipose tissue, thereby generating toxic substances with the capacity to impede the ordinary physiological functions of various organs. With aging, the musculoskeletal system undergoes pronounced degenerative alterations, prompting heightened scrutiny regarding the contributory role of fatty infiltration in its pathophysiology. Several studies have demonstrated that fatty infiltration affects the normal metabolism of the musculoskeletal system, leading to substantial tissue damage. Nevertheless, a definitive and universally accepted generalization concerning the comprehensive effects of fatty infiltration on the musculoskeletal system remains elusive. As a result, this review summarizes the characteristics of different types of adipose tissue, the pathological mechanisms associated with fatty infiltration in bone, muscle, and the entirety of the musculoskeletal system, examines relevant clinical diseases, and explores potential therapeutic modalities. This review is intended to give researchers a better understanding of fatty infiltration and to contribute new ideas to the prevention and treatment of clinical musculoskeletal diseases.

PurposeLymph node-based staging protocols are frequently employed to evaluate the prognosis of esophageal cancer, yet their accuracy remains contentious. The present study was conducted to assess the prognostic significance of three lymph node staging systems, namely N stage, lymph node rate (LNR), and log odds of positive lymph nodes (LODDS), in patients diagnosed with advanced (T2-T4) esophageal squamous cell carcinoma (ESCC).MethodsThis cohort comprised 319 eligible patients, with an additional 409 individuals retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, forming the validation cohort. Differences in overall survival (OS) of patients between groups were assessed using the log-rank test. Prognostic independent risk variables were identified, and lymph nodes (LN) prognostic models were built using multivariate Cox regression analysis. Besides, the predictive accuracy of each model was evaluated utilizing the (-2) log-likelihood ratio (-2LLR), the likelihood ratio χ2 score (LRχ2), the Akaike information criterion (AIC), and Harrell’s concordance index (C-index). To further evaluate the potential superiority of the model, a nomogram was constructed for comparison with the conventional Tumor Node Metastasis (TNM) staging approach.ResultsIndependent prognostic factors for advanced ESCC include the N stage, LNR, and LODDS. Herein, LODDS presented higher values for C-index and LRχ2, and lower values for AIC and -2LLR in OS compared to the others. Consequently, a nomogram was constructed based on LODDS. Calibration curves exhibited strong agreement, and assessment through C-index, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA) demonstrated promising clinical applicability.ConclusionLODDS emerges as a promising future prognostic indicator. After surgery, the proposed model holds the potential to provide valuable treatment recommendations for patients with advanced ESCC.

Objective: The purpose of this study is to analyze the inherent relationship between the score values and the biomechanical characteristics of the forward kicking motion, we aim to identify the fundamental variables influencing the score values of the forward kicking motion and establish the key biomechanical factors that effectively trigger scoring in the forward kicking motion.Methods: The DaeDo electronic scoring system was used with the Vicon optical motion capture system and the Kistler 3D force platform to obtain kinematic and kinetic variables of the front roundhouse kick motion. Linear bivariate correlation analysis and principal component analysis were used to analyze the associations between kinematic, kinetic variables, and scoring values, and summarize key biomechanical factors for effectively scoring.Results: The peak ankle plantar flexion angle and knee extension torque of the kicking leg showed a significant negative correlation with scoring values (r < 0, p < 0.05), while other variables showed no statistical significance. The peak knee flexion angle and hip extension angular velocity of the supporting leg showed a significant positive correlation with scoring values (r > 0, p < 0.01), while the peak ankle plantar flexion torque showed a significant negative correlation with scoring values (r < 0, p < 0.05), and other variables showed no statistically significant correlation. The absolute values of eigenvectors of the first and second principal components, which included hip angular velocity, ankle angle, knee torque, and hip torque, were relatively large, indicating their strong influence on effective scoring triggering.Conclusion: Maintaining ankle dorsiflexion and a larger knee flexion angle in the kicking leg is favorable for triggering scoring. Higher knee flexion angle and hip extension angular velocity in the supporting leg are also advantageous for triggering scoring. “Body posture” and “Strength” are key factors that effectively trigger scoring.

Abstract The indoor air quality has a direct impact on human health. In order to obtain the current status of indoor air quality in typical sports buildings in hot summer and cold winter climate zones in China, indoor badminton courts in 10 cities in Hubei Province in this climate zone were selected as research objects for field testing of indoor environmental parameters in spring and autumn, and predict air quality parameters for non-testing times. All the tested stadiums are naturally ventilated in non-event conditions, and the average daily indoor CO2 concentration was 526.78 ppm in spring and 527.63 ppm in autumn, and the average daily PM2.5 concentration was 0.035 mg/m3 in spring and 0.024 mg/m3 in autumn, all of which met the requirements of GB/T 18883-2022, the average concentration of CO2 ≤ 1000 ppm and PM2.5 ≤ 0.05 mg/m3. The indoor CO2 concentration and PM2.5 concentration of the tested badminton halls under natural ventilation gradually increased with the accumulation of exercise time, making the indoor air quality of the badminton halls decrease, which would negatively affect the health of the people exercising in this environment.

Abstract The mood index $$r$$ r was used to describe evaluator attitudes regarding the progress of a project that formed the basis of a construction period prediction model. The degrees of pessimism $$\alpha$$ α and optimism $$\beta$$ β were introduced, and an analysis model was established using $$\alpha$$ α and $$\beta$$ β to predict the construction period and completion probability Firstly, the absolute construction period of each process of tunnel No. 2 can be obtained according to the measured daily average footage of each process of tunnel No. 1. Secondly, the probability of the stoppage caused by different factors can be obtained after the statistical analysis of the factors responsible for the stoppage of tunnel No. 1. Finally, the expected construction period and completion probability of tunnel No. 2 under different pessimism and optimism conditions are obtained by using the progress risk analysis theory of emotional models and the program evaluation and review technique method. An engineering application showed that the expected construction period increased, and the completion probability decreased considerably with increasing pessimism; the opposite trend occurred as optimism increased. During the process of risk management and control, the prediction model can be used to perform precise quantitative analysis of the expected construction period and completion probability, reduce the blindness of construction management, control decisions of complex giant tunnel projects, and provide a more accurate basis for decision makers to judge risks. The findings of this study can be applied to hydraulic tunnels and can provide a reference for traffic tunnels, railway tunnels, and other similar projects.

Abstract The uncertain stability of deep reinforcement learning training on complex tasks impedes its development and deployment, especially in intelligent vehicles, such as intelligent surface vessels and self-driving cars. Complex and varied environmental states puzzle training of decision-making networks. Here we propose an elastic adaptive deep reinforcement learning algorithm to address these challenges and achieve autonomous navigation in intelligent vehicles. Our method trains the decision-making network over the function and optimization learning stages, in which the state space and action space of autonomous navigation tasks are pruned by choosing classic states and actions to reduce data similarity, facilitating more stable training. We introduce a task-adaptive observed behaviour classification technique in the function learning stage to divide state and action spaces into subspaces and identify classic states and actions. In which the classic states and actions are accumulated as the training dataset that enhances its training efficiency. In the subsequent optimization learning stage, the decision-making network is refined through meticulous exploration and accumulation of datasets. The proposed elastic adaptive deep reinforcement learning enables the decision-making network to effectively learn from complex state and action spaces, leading to more efficient training compared to traditional deep reinforcement learning approaches. Simulation results demonstrate the remarkable effectiveness of our method in training decision-making networks for intelligent vehicles. The findings validate that our method provides reliable and efficient training for decision-making networks in intelligent vehicles. Moreover, our method exhibits stability in training other tasks characterized by continuous state and action spaces.

Abstract Programmed cell death 1 ligand 1 (PDL1)/programmed cell death 1 (PD1) blockade immunotherapy provides a prospective strategy for the treatment of colorectal cancer (CRC), but various constraints on the effectiveness of the treatment are still remaining. As reported in previous studies, follistatin-like 3 (FSTL3) could mediate inflammatory response in macrophages by induction lipid accumulation. Herein, we revealed that FSTL3 were overexpressed in malignant cells in the CRC microenvironment, notably, the expression level of FSTL3 was related to tumor immune evasion and the clinical efficacy of anti-PD1 therapy. Further studies determined that hypoxic tumor microenvironment induced the FSTL3 expression via HIF1α in CRC cells, FSTL3 could bind to the transcription factor c-Myc (354–406 amino acids) to suppress the latter’s ubiquitination and increase its stability, thereby to up-regulated the expression of PDL1 and indoleamine 2,3-dioxygenase 1 (IDO1). The results in the immunocompetent tumor models verified that FSLT3 knockout in tumor cells increased the proportion of CD8+ T cells in the tumor microenvironment, reduced the proportion of regulatory T cells (CD25+ Foxp3+) and exhausted T cells (PD1+ CD8+), and synergistically improved the anti-PD1 therapy efficacy. To sum up, FSTL3 enhanced c-Myc-mediated transcriptional regulation to promote immune evasion and attenuates response to anti-PD1 therapy in CRC, suggesting the potential of FSTL3 as a biomarker of immunotherapeutic efficacy as well as a novel immunotherapeutic target in CRC.

The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles. Traditional rotary motion deblurring methods suffer from ringing artifacts and noise, especially for large blur extents. To solve the above problems, we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage. In the first stage, we design an adaptive blur extents factor (BE factor) to balance noise suppression and details reconstruction. And a novel deconvolution model is proposed based on BE factor. In the second stage, a triple-scale deformable module CNN(TDM-CNN) is designed to reduce the ringing artifacts, which can exploit the 2D information of an image and adaptively adjust spatial sampling locations. To establish a standard evaluation benchmark, a real-world rotary motion blur dataset is proposed and released, which includes rotary blurred images and corresponding ground truth images with different blur angles. Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets. The code and dataset are available at https://github.com/Jinhui-Qin/RotaryDeblurring.

Abstract Acoustic scene classification (ASC) is the process of identifying the acoustic environment or scene from which an audio signal is recorded. In this work, we propose an encoder-decoder-based approach to ASC, which is borrowed from the SegNet in image semantic segmentation tasks. We also propose a novel feature normalization method named Mixup Normalization, which combines channel-wise instance normalization and the Mixup method to learn useful information for scene and discard specific information related to different devices. In addition, we propose an event extraction block, which can extract the accurate semantic segmentation region from the segmentation network, to imitate the effect of image segmentation on audio features. With four data augmentation techniques, our best single system achieved an average accuracy of 71.26% on different devices in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 ASC Task 1A dataset. The result indicates a minimum margin of 17% against the DCASE 2020 challenge Task 1A baseline system. It has lower complexity and higher performance compared with other state-of-the-art CNN models, without using any supplementary data other than the official challenge dataset.

Extracting small targets from complex backgrounds is the eventual goal of single-frame infrared small target detection, which has many potential applications in defense security and marine rescue. Recently, methods utilizing deep learning have shown their superiority over traditional theoretical approaches. However, they do not consider both the global semantics and specific shape information, thereby limiting their performance. To overcome this proplem, we propose a gated-shaped TransUnet (GSTUnet), designed to fully utilize shape information while detecting small target detection. Specifically, we have proposed a multiscale encoder branch to extract global features of small targets at different scales. Then, the extracted global features are passed through a gated-shaped stream branch that focuses on the shape information of small targets through gate convolutions. Finally, we fuse their features to obtain the final result. Our GSTUnet learns both global and shape information through the aforementioned two branches, establishing global relationships between different feature scales. The GSTUnet demonstrates excellent evaluation metrics on various datasets, outperforming current state-of-the-art methods.

ABSTRACTInspired by macroscale 3D pixel mechanical metamaterials and microscale straw-like carbon nanotube, we propose a design of multi-stable straw-like carbon nanotubes (MSCNT) via optimizing the structure of a unit to obtain multiple stable states under displacement loading by molecular dynamics. The unit of MSCNT is mirror-symmetrically connected two truncated graphene cones with specific apex angles. By switching the LJ term in AIREBO potential, we verify that the bistability of unit is co-determined by snap-through instability and microscale adhesions. Moreover, we examine the validity of the multi-stability of the unit cells arranged in series and in parallels. Simulation results indicate that the MSCNT can achieve mechanical programmability in microscale, which triggers many potential applications in need of customizing nanoscale mechanical behaviors.

Abstract This study used the consistency-constrained double-difference tomography method to invert 3D fine structure models of Vp, Vs, Vp/Vs at depths above 60 km, and precise relocation parameters of earthquakes in the Bohai Sea. According to the results, the velocity structures of P-wave and S-wave in the Bohai Sea area were highly similar and demonstrated noticeable lateral non-uniformity. The crust beneath the Tanlu Fault displayed a clear stratification structure, with a continuous velocity transition in the middle of the crust. The intricate crustal structure beneath the Zhangpeng Fault displayed high-velocity bodies in the crust and low-velocity anomalous zones connected to the top of the mantle in the lower section of the crust. The structural pattern in the deep crust of the Bohai Sea controls the occurrence characteristics of the Zhangpeng Fault and the Tanlu Fault. The earthquakes in the Bohai Sea area were concentrated mainly in the southern part near the Zhangpeng Fault. There is a good correspondence between the relocated earthquakes and velocity structure. There are many significant differences in crustal structure between the north and south of the Bohai Strait, and there are obvious velocity anomalies in the middle and upper crust. The distribution shape of high Vp/Vs value indicates that mantle material migration has occurred at the bottom of the crust. This paper provided important reference for further research on the relationship between deep tectonic features and tectonic activity in the North China Craton.

Abstract Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, with complex etiology and mechanism, and a high mortality rate. Tumor‐associated macrophages (TAMs) are an important part of the HCC tumor microenvironment. Studies in recent years have shown that TAMs are involved in multiple stages of HCC and are related to treatment and prognosis in HCC. The specific mechanisms between TAMs and HCC are gradually being revealed. This paper reviews recent advances in the mechanisms associated with TAMs in HCC, concentrating on an overview of effects of TAMs on drug resistance in HCC and the signaling pathways linked with HCC, providing clues for the treatment and prognosis determination of HCC.

AbstractContext Wen-Shen-Tong-Luo-Zhi-Tong (WSTLZT) Decoction is a Chinese prescription with antiosteoporosis effects, especially in patients with abnormal lipid metabolism.Objective To explore the effect and mechanism of WSTLZT on osteoporosis (OP) through adipocyte-derived exosomes.Materials and methods Adipocyte-derived exosomes with or without WSTLZT treated were identified by transmission electron microscopy, nanoparticle tracking analysis (NTA) and western blotting (WB). Co-culture experiments for bone marrow mesenchymal stem cells (BMSCs) and exosomes were performed to examine the uptake and effect of exosome in osteogenesis and adipogenic differentiation of BMSC. MicroRNA profiles, luciferase and IP were used for exploring specific mechanisms of exosome on BMSC. In vivo, 80 Balb/c mice were randomly divided into four groups: Sham, Ovx, Exo (30 μg exosomes), Exo-WSTLZT (30 μg WSTLZT-exosomes), tail vein injection every week. After 12 weeks, the bone microstructure and marrow fat distribution were analysed by micro-CT.Results ALP, Alizarin red and Oil red staining showed that WSTLZT-induced exosomes from adipocyte can regulate osteoblastic and adipogenic differentiation of BMSC. MicroRNA profiles observed that WSTLZT treatment resulted in 87 differentially expressed miRNAs (p

IntroductionArithmetic calculation is a fundamental skill for mathematical learning and daily life. However, elementary school students often make errors in practice.MethodsGrounded in the schema theory and the memory retrieval theory of mental arithmetic, this study employs a controlled experiment to investigate the effect of a schema-based method in correcting persistent errors in mental arithmetic, specifically in the context of simple addition operations. The experimental group utilizes a schema-based method to help participants rectify incorrect answers in memory retrieval, while the control group did not receive this treatment.ResultsThe results showed that significant differences emerged between the experimental and control groups in both the post-test performance and the reduction of persistent error count, indicating that the experimental group had rectified incorrect answers in memory; and persistent errors in simple addition were indeed caused by interference from incorrect answers during memory retrieval; and the schema-based method proves to be effective.DiscussionThe findings of this study contribute to enhancing practical mental arithmetic instruction, assisting students in correcting relevant errors, and improving their mental arithmetic abilities. Not only does it offer directive guidance for teaching practices, but it also provides an enlightening reference for promoting innovative teaching methods.

Osteoporosis, characterized by low bone mass and bone microarchitecture breakdown, has become a growing public health problem. The increase in oxidative stress could lead to an imbalance between osteoblasts-mediated osteogenesis and osteoclast-mediated bone resorption, which gives rise to osteoporosis. Nrf2 is a master transcription factor that regulates oxidative stress and has recently been reported to take part in the development of osteoporosis. Icariin, a leading active flavonoid in herbal Epimedium pubescens, has significant antioxidant activity in and is widely applied for treating bone diseases. In this study, we aimed to explore the effect of icariin on osteoclastogenesis and its potential mechanism from the perspective of oxidative stress inhibition, using ovariectomized (OVX) rats and RANKL-induced RAW264.7 cells. Our results demonstrated that icariin-treated OVX rats exhibited higher bone density, fewer tartrate-resistant acid phosphatase (TRAP)-positive osteoclasts, and lower ROS levels in bone tissues than vehicle-treated OVX rats. Also, icariin suppressed osteoclast differentiation and inhibited the expression of osteoclastogenesis-related genes, such as NFATc1, Ctsk, Trap, and c-Fos, in RANKL-induced RAW264.7 cells. Icariin also reduced intracellular ROS levels by increasing the expression of nuclear Nrf2 and HO-1. Further mechanistic studies showed icariin inhibited Cullin 3 expression and could delay Nrf2 degradation by reducing the ubiquitination of endogenous Nrf2 in RANKL-stimulated RAW264.7 cells, and these effects were markedly reversed by cullin three overexpression. These findings suggest icariin alleviated osteoporosis by suppressing osteoclastogenesis via targeting the Cullin 3/Nrf2/OH signaling pathway. Our study implied that icariin may be a potential candidate to treat osteoporosis.

Long-term urban traffic flow prediction is an important task in the field of intelligent transportation, as it can help optimize traffic management and improve travel efficiency. To improve prediction accuracy, a crucial issue is how to model spatiotemporal dependency in urban traffic data. In recent years, many studies have adopted spatiotemporal neural networks to extract key information from traffic data. However, most models ignore the semantic spatial similarity between long-distance areas when mining spatial dependency. They also ignore the impact of predicted time steps on the next unpredicted time step for making long-term predictions. Moreover, these models lack a comprehensive data embedding process to represent complex spatiotemporal dependency. This paper proposes a multi-scale persistent spatiotemporal transformer (MSPSTT) model to perform accurate long-term traffic flow prediction in cities. MSPSTT adopts an encoder-decoder structure and incorporates temporal, periodic, and spatial features to fully embed urban traffic data to address these issues. The model consists of a spatiotemporal encoder and a spatiotemporal decoder, which rely on temporal, geospatial, and semantic space multi-head attention modules to dynamically extract temporal, geospatial, and semantic characteristics. The spatiotemporal decoder combines the context information provided by the encoder, integrates the predicted time step information, and is iteratively updated to learn the correlation between different time steps in the broader time range to improve the model's accuracy for long-term prediction. Experiments on four public transportation datasets demonstrate that MSPSTT outperforms the existing models by up to 9.5% on three common metrics.

BackgroundHemorrhagic transformation (HT) after intravenous thrombolysis (IVT) might worsen the clinical outcomes, and a reliable predictive system is needed to identify the risk of hemorrhagic transformation after IVT.MethodsRetrospective collection of patients with acute cerebral infarction treated with intravenous thrombolysis in our hospital from 2018 to 2022. 197 patients were included in the research study. Multivariate logistic regression analysis was used to screen the factors in the predictive nomogram. The performance of nomogram was assessed on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots and decision curve analysis (DCA).ResultsA total of 197 patients were recruited, of whom 24 (12.1%) developed HT. In multivariate logistic regression model National Institute of Health Stroke Scale (NIHSS) (OR, 1.362; 95% CI, 1.161–1.652; p = 0.001), N-terminal pro-brain natriuretic peptide (NT-pro BNP) (OR, 1.012; 95% CI, 1.004–1.020; p = 0.003), neutrophil to lymphocyte ratio (NLR) (OR, 3.430; 95% CI, 2.082–6.262; p

Abstract Background The endoplasmic reticulum (ER) regulates critical processes, including lipid synthesis, which are affected by transmembrane proteins localized in the ER membrane. One such protein, transmembrane protein 147 (TMEM147), has recently been implicated for its role in hepatocellular carcinoma (HCC) tumorigenesis; however, the mechanisms remain unclear. We investigated the role of TMEM147 in HCC and the underlying mechanisms. Methods TMEM147 expression was examined in human HCC cells and adjacent non-tumorous tissues using quantitative reverse transcription-polymerase chain reaction, western blotting, and immunohistochemistry. In vitro and in vivo studies were conducted to investigate the impact of TMEM147 on the progression of HCC. Proteins interacting with TMEM147 were identified via RNA-seq, immunoprecipitation, and mass spectrometry analyses. Lipidomic analysis and enzyme-linked immunosorbent assay (ELISA) were employed to determine and analyze cholesterol and 27-hydroxycholesterol (27HC) contents. Extensive experimental techniques were used to study ferroptosis in HCC cells. The fatty acid content of macrophages affected by TMEM147 was quantified using ELISA. Macrophage phenotypes were determined using immunofluorescence assay and flow cytometric analysis. Results TMEM147 mRNA and protein levels were increased in HCC cells, and the increased TMEM147 expression was associated with a poor survival. TMEM147 promoted tumor cell proliferation and metastases in vitro and in vivo. The protein was found to interact with the key enzyme 7-dehydrocholesterol reductase (DHCR7), which affected cellular cholesterol homeostasis and increased the extracellular levels of 27HC in HCC cells. TMEM147 also promoted the expression of DHCR7 by enhancing the activity of signal transducer and activator of transcription 2. 27HC expression upregulated glutathione peroxidase 4 in HCC, leading to ferroptosis resistance and promotion of HCC proliferation. HCC cell-derived 27HC expression increased the lipid metabolism in macrophages and activated peroxisome proliferator-activated receptor-γ signaling, thereby activating M2 macrophage polarization and promoting HCC cell invasion and migration. Conclusions Our results indicate that TMEM147 confers ferroptosis resistance and M2 macrophage polarization, which are primarily dependent on the upregulation of cellular cholesterol homeostasis and 27HC secretion, leading to cancer growth and metastasis. These findings suggest that the TMEM147/STAT2/DHCR7/27HC axis in the tumor microenvironment may serve as a promising therapeutic target for HCC. Graphical Abstract

Marine salinity affects mainly the roots, stems and leaves of coastal plants through groundwater intrusion, splashing and salt spray. Two-year-old Nerium indicum L. seedlings with good growth were used to carry out the salt tolerance experiments in their roots and leaves by setting multiple concentration gradients of control 0%, 0.3%, 0.6%, 1.0%, 2.0% and 3.0%. Normal watering for 4 weeks was followed by 13 weeks of salt stress treatment. The net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs) and water use efficiency (WUE) were measured at the end of salt stress and after normal irrigation. At the same time, physical and chemical indices, such as the cell membrane permeability and water saturation deficit (WSD) of leaves, were measured. The results showed that both soil salt stress and foliar salt stress affected the morphology and growth of Nerium indicum. When the soil salt stress was ≥1.0%, the growth status of Nerium indicum decreased irreversibly to less than 2, while under foliar salt stress ≤3.0%, the growth status of Nerium indicum was generally greater than 2. Soil salt stress significantly reduced the Pn, Tr and Gs of Nerium indicum leaves. Foliar salt stress had significant effects on Pn and WUE but no significant effects on Tr and Gs. There was a significant correlation between Tr and Gs; under high-concentration soil salt stress, stomatal factors had a more significant effect on the photosynthesis of Nerium indicum. Under foliar salt stress, the cell membrane permeability and WSD of Nerium indicum did not change significantly. Under high-concentration soil salt stress, the cell membrane permeability and WSD of Nerium indicum changed irreversibly, corresponding well with the results of growth status and photosynthetic responses, indicating that the damage to the membrane system in turn affected the growth and photosynthesis of Nerium indicum. In general, Nerium indicum can tolerate less than 3.0% foliar salt stress and less than 1.0% soil salt stress. Studying the salt tolerance characteristics of roots and leaves can provide theoretical guidance for the application of Nerium indicum in coastal ecology and vegetation restoration.

Abstract PM2.5 is a nonhomogeneous mixture of complex components produced from multiple sources, and different components of this mixture have different chemical and biological toxicities, which results in the fact that the toxicity and hazards of PM2.5 may vary even for the same mass of PM2.5. Previous studies on PM2.5 and ischemic stroke have reached different or even opposing conclusions, and considering the heterogeneity of PM2.5 has led researchers to focus on the health effects of specific PM2.5 components. However, due to the complexity of PM2.5 constituents, assessing the association between exposure to specific PM2.5 constituents and ischemic stroke presents significant challenges. Therefore, this paper reviews and analyzes studies related to PM2.5 and its different components and ischemic stroke, aiming to understand the composition of PM2.5 and identify its harmful components, elucidate their relationship with ischemic stroke, and thus provide some insights and considerations for studying the biological mechanisms by which they affect ischemic stroke and for the prevention and treatment of ischemic stroke associated with different components of PM2.5.

Abstract Pancreatic cancer is one of the tumors with the worst prognosis, causing serious harm to human health. The RNA network and immune response play an important role in tumor progression. While a systematic RNA network linked to the tumor immune response remains to be further explored in pancreatic cancer. Based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, the MIR600HG/hsa-miR-342-3p/ANLN network was determined. WB and IHC were used to confirm the high expression of ANLN in pancreatic cancer. The prognostic model based on the RNA network could effectively predict the survival prognosis of patients. The analysis of immune infiltration showed that the MIR600HG/hsa-miR-342-3p/ANLN network altered the level of infiltration of T helper 2 (Th2) and effector memory T (Tem) cells. Furthermore, we found that the chemokines chemokine ligand (CCL) 5 and CCL14 may play a key role in immune cell infiltration mediated by the RNA network. In conclusion, this study constructed a prognostic model based on the MIR600HG/hsa-miR-342-3p/ANLN network and found that it may function in tumor immunity.

Abstract Background Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with the initiation and progression of Triple-negative breast cancer (TNBC). The publicly available TCGA database of breast cancer data was used to analyze the OTUD deubiquitinating family members that were correlated with survival of breast cancer and ovarian tumor domain-containing 2 (OTUD-2), or YOD1 was identified. The aim of present study was to assess YOD1 expression and function in human TNBC and then explored the underlying molecular events. Methods We detected the expression of YOD1 in 32 TNBC and 44 NTNBC samples by qRT-PCR, Western blot and immunohistochemistry. Manipulation of YOD1 expression was assessed in vitro and in vivo for TNBC cell proliferation, migration, invasion, cell-cycle and drug resistance, using colony formation assay, transwell assay, CCK8 assay, TUNEL assay, flow cytometric analysis and xenograft tumor assay. Next, proteomic analysis, Western blot, proximity ligation assay, Immunoprecipitation, and Immunofluorescence were conducted to assess downstream targets. Results It was found that YOD1 was significantly upregulated in TNBC tissues compared with non-triple-negative breast cancer (NTNBC), which was positively correlated with poor survival in TNBC patients. Knockdown of YOD1 effectively inhibited TNBC cell migration, proliferation, cell cycle and resistance to cisplatin and paclitaxel. Mechanistically, YOD1 promoted TNBC progression in a manner dependent on its catalytic activity through binding with CDK1, leading to de-polyubiquitylation of CDK1 and upregulation of CDK1 expression. In addition, YOD1 overexpression was found to be correlated with CDK1 overexpression in human TNBC specimens. Finally, in vivo study demonstrated that YOD1 knockdown or YOD1 inhibitor could inhibit CDK1 expression and suppress the growth and metastasis of TNBC tumors. Conclusion Our study highlights that YOD1 functions as an oncogene in TNBC via binding to CDK1 and mediated its stability and oncogenic activity. Interfering with YOD1 expression or YOD1 inhibitor could suppress TNBC cells in vitro and in vivo, suggesting that YOD1 may prove to be a promising therapeutic target for TNBC.

Surgical smoke is a byproduct of aerosols containing several components produced by energy equipment. The characteristics of surgical smoke components produced by different types of tissues or using different kinds of energy devices vary. For example, the average diameter of smoke particles produced by electrocautery is smaller, and the possibility of viable cells and pathogens in surgical smoke produced by an ultrasonic knife is higher. According to the characteristics of its composition, surgical smoke may be an important risk factor affecting the health and safety of operating room staff and patients. The use of surgical masks, suction devices and portable smoke evacuation systems can reduce this risk to some extent. However, most operating room staff members do not implement corresponding measures to protect themselves. In this paper, the characteristics of surgical smoke and the research progress in protective measures are briefly reviewed.

The animal gut harbors diverse microbes that play an essential role in the well-being of their host. Specific diets, such as those rich in dietary fiber, are vital in disease prevention and treatment because they affect intestinal flora and have a positive impact on the metabolism, immunity, and intestinal function of the host. Dietary fiber can provide energy to colonic epithelial cells, regulate the structure and metabolism of intestinal flora, promote the production of intestinal mucosa, stimulate intestinal motility, improve glycemic and lipid responses, and regulate the digestion and absorption of nutrients, which is mainly attributed to short-chain fatty acids (SCFA), which is the metabolite of dietary fiber. By binding with G protein-coupled receptors (including GPR41, GPR43 and GPR109A) and inhibiting the activity of histone deacetylases, SCFA regulate appetite and glucolipid metabolism, promote the function of the intestinal barrier, alleviate oxidative stress, suppress inflammation, and maintain immune system homeostasis. This paper reviews the physicochemical properties of dietary fiber, the interaction between dietary fiber and intestinal microorganisms, the role of dietary fiber in maintaining intestinal health, and the function of SCFA, the metabolite of dietary fiber, in inhibiting inflammation. Furthermore, we consider the effects of dietary fiber on the intestinal health of pigs, the reproduction and lactation performance of sows, and the growth performance and meat quality of pigs.

Nighttime light (NTL) remote sensing has emerged as a powerful tool in various fields such as urban expansion, socio-economic estimation, light pollution, and energy domains. However, current annual NTL products suffer from several critical limitations, including poor consistency, severe background noise, and limited comparability. These issues have significantly interfered with the research of long-term NTL trends and diminished the accuracy of related findings. Therefore, this study developed a de-difference smoothing algorithm for producing high-quality annual NTL products based on monthly National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data. It enabled the construction of a continuous global high-quality NTL dataset, named the De-Difference Smoothed Nighttime Light (DDSNL), covering the period from 2012 to 2023. Comparative analyses were conducted to validate the accuracy and availability of the DDSNL product against the benchmark EOG NPP-VIIRS and NPP-VIIRS-like NTL datasets. The results showed that DDSNL products had strong correlation with the NTL distribution of EOG NPP-VIIRS, but little correlation with NPP-VIIRS-like. Notably, DDSNL demonstrated better background noise reduction and higher separability between NTL and non-NTL areas compared to EOG NPP-VIIRS NTL. In contrast to the complete exclusion of background in NPP-VIIRS-Like, the retention of background values in DDSNL leads to more reasonable representation in the urban fringes. In the analysis of NTL changes matching impervious surface changes, the DDSNL product demonstrated the least interference from noise, resulting in the smallest segmentation threshold and the highest matching accuracy. This indirectly demonstrates the spatial and temporal consistency of the annual DDSNL product, ensuring its reliability in change detection-related studies. The annual DDSNL product developed in this research exhibits high fidelity, strong consistency, and improved comparability, and can provide reliable data reference for applications in electrification and urban studies.

Accurate recognition and prediction of the multi-level handling complexity in automated container terminals (referred to as “automated terminals”) is a prerequisite for improving the effectiveness of scheduling and realizing intelligent operation and maintenance. According to the operating characteristics of the automated terminal equipment, the operating network is constructed of automated terminals that describe the characteristics of operating complexity. We use K-medoids and a light gradient boosting machine (LightGBM) to construct a K-LightGBM model that recognizes multi-level handling complexity. The key lies in the reasonable construction of prediction models. A hyper-heuristic autoregressive integrated moving average (ARIMA) model is proposed to address the problem that the ARIMA is ineffective in predicting nonlinear data. We combine ARIMA and the LightGBM model to establish an ARIMA-LightGBM model to predict multi-level handling and residuals. To improve accuracy, we propose the two residual prediction strategies of direct prediction and limited residual boundary prediction based on the residuals generated by ARIMA. We propose a hyper-heuristic algorithm based on a gradient descent-trust region (GD-TR) to compute the weights of predicted values under the two strategies, which improves the global search capability by GD and TR. The particle swarm optimization algorithm, simulated annealing algorithm, and ant colony optimization algorithm are low-level heuristics. Simulation results show that the proposed model possesses the lowest root mean square error on all characteristics compared to ARIMA, E-ARIMA, and ARIMA-LSTM. Therefore, the proposed model is very effective in improving the accuracy of predicting the multi-level handling complexity at automated terminals.

Abstract We used social media data from “covid19positive” subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021–09/2021) and Omicron (12/2021–03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The top five common symptoms extracted in the early period were coughing (57%), fever (55%), loss of sense of smell (41%), headache (40%), and sore throat (40%). During the Delta period, these symptoms remained as the top five symptoms with percent authors reporting symptoms reduced to half or fewer than the early period. During the Omicron period, loss of sense of smell was reported less while sore throat was reported more. Our study demonstrated that NLP can be used to identify COVID-19 cases accurately and extracted symptoms efficiently.

Abstract The development of natural membranes as coatings for nanoparticles to traverse the blood-brain barrier (BBB) presents an effective approach for treating central nervous system (CNS) disorders. In this study, we have designed a nanogel loaded with PACAP and estrogen (E2), sheathed with exosomes and responsive to reactive oxygen species (ROS), denoted as HA NGs@exosomes. The objective of this novel design is to serve as a potent drug carrier for the targeted treatment of perimenopausal depression. The efficient cellular uptake and BBB penetration of HA NGs@exosomes has been demonstrated in vitro and in vivo. Following intranasal intervention with HA NGs@exosomes, ovariectomized mice under chronic unpredictable mild stress (CUMS) have shown improved behavioral performance, indicating that HA NGs@exosomes produced a rapid-onset antidepressant effect. Moreover, HA NGs@exosomes exhibit notable antioxidant and anti-inflammatory properties and may regulate the expression of pivotal proteins in the PACAP/PAC1 pathway to promote synaptic plasticity. Our results serve as a proof-of-concept for the utility of exosome-sheathed ROS-responsive nanogel as a promising drug carrier for the treatment of perimenopausal depression. Graphical Abstract