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Abstract Background The log odds of positive lymph nodes (LODDS) was considered a superior staging system to N stage in colon cancer, yet its value in determining the optimal duration of adjuvant chemotherapy for stage III colon cancer patients has not been evaluated. This study aims to assess the prognostic value of a model that combines LODDS with clinicopathological information for stage III colon cancer patients and aims to stratify these patients using the model, identifying individuals who could benefit from varying durations of adjuvant chemotherapy. Method A total of 663 consecutive patients diagnosed with stage III colon cancer, who underwent colon tumor resection between November 2007 and June 2020 at Sun Yat-sen University Cancer Center and Longyan First Affiliated Hospital of Fujian Medical University, were enrolled in this study. Survival outcomes were analyzed using Kaplan–Meier, Cox regression. Nomograms were developed to forecast patient DFS, with the Area Under the Curve (AUC) values of time-dependent Receiver Operating Characteristic (timeROC) and calibration plots utilized to assess the accuracy and reliability of the nomograms. Results Multivariate analysis revealed that perineural invasion (HR = 1.776, 95% CI: 1.052–3.003, P = 0.032), poor tumor differentiation (HR = 1.638, 95% CI: 1.084–2.475, P = 0.019), and LODDS groupings of 2 and 1 (HR = 1.920, 95% CI: 1.297–2.842, P = 0.001) were independent predictors of disease-free survival (DFS) in the training cohort. Nomograms constructed from LODDS, perineural invasion, and poor tumor differentiation demonstrated robust predictive performance for 3-year and 5-year DFS in both training (3-year AUC = 0.706, 5-year AUC = 0.678) and validation cohorts (3-year AUC = 0.744, 5-year AUC = 0.762). Stratification according to this model showed that patients in the high-risk group derived significant benefit from completing 8 cycles of chemotherapy (training cohort, 82.97% vs 67.17%, P = 0.013; validation cohort, 89.49% vs 63.97%, P = 0.030). Conclusion The prognostic model, integrating LODDS, pathological differentiation, and neural invasion, demonstrates strong predictive accuracy for stage III colon cancer prognosis. Moreover, stratification via this model offers valuable insights into optimal durations of postoperative adjuvant chemotherapy.

Abstract Deep learning-based inpainting models have achieved success in restoring natural images, yet their application to ancient paintings encounters challenges due to the loss of texture, lines, and color. To address these issues, we introduce an ancient painting inpainting model based on dual encoders and contextual information to overcome the lack of feature extraction and detail texture recovery when restoring ancient paintings. Specifically, the proposed model employs a gated encoding branch that aims to minimize information loss and effectively capture semantic information from ancient paintings. A dense multi-scale feature fusion module is designed to extract texture and detail information at various scales, while dilated depthwise separable convolutions are utilized to reduce parameters and enhance computational efficiency. Furthermore, a contextual feature aggregation module is incorporated to extract contextual features, enhancing the overall consistency of the inpainting results. Finally, a color loss function is introduced to ensure color consistency in the restored area, harmonizing it with the surrounding region. The experimental results indicate that the proposed model effectively restores the texture details of ancient paintings, outperforming other methods both qualitatively and quantitatively. Additionally, the model is tested on real damaged ancient paintings to validate its practicality and efficacy.

Abstract Background The emergence of metagenomic next-generation sequencing (mNGS) may provide a promising tool for early and comprehensive identification of the causative pathogen in community-acquired pneumonia (CAP). In this study, we aim to further evaluate the etiological diagnostic value of mNGS in suspected CAP. Methods A total of 555 bronchoalveolar lavage fluid (BALF) samples were collected for pathogen detection by mNGS from 541 patients with suspected CAP. The clinical value was assessed based on infection diagnosis and treatment guidance. The diagnostic performance for pathogen identification by mNGS and sputum culture and for tuberculosis (TB) by mNGS and X-pert MTB/RIF were compared. To evaluate the potential for treatment guidance, we analyzed the treatment regimen of patients with suspected CAP, including imaging changes of lung after empirical antibacterial therapy, intensified regimen, antifungal treatment, and a 1-year follow up for patients with unconfirmed diagnosis and non-improvement imaging after anti-infective treatment and patients with high suspicion of TB or NTM infection who were transferred to the Wuhan Pulmonary Hospital for further diagnosis and even anti-mycobacterium therapy. Results Of the 516 BALF samples that were analyzed by both mNGS and sputum culture, the positivity rate of mNGS was significantly higher than that of sputum culture (79.1% vs. 11.4%, P = 0.001). A total of 48 samples from patients with confirmed TB were analyzed by both mNGS and X-pert MTB/RIF, and the sensitivity of mNGS for the diagnosis of active TB was significantly lower than that of X-pert MTB/RIF (64.6% vs. 85.4%, P = 0.031). Of the 106 pathogen-negative cases, 48 were ultimately considered non-infectious diseases, with a negative predictive value of 45.3%. Of the 381 pathogen-positive cases, 311 were eventually diagnosed as CAP, with a positive predictive value of 81.6%. A total of 487 patients were included in the evaluation of the therapeutic effect, and 67.1% improved with initial empirical antibiotic treatment. Of the 163 patients in which bacteria were detected, 77.9% improved with antibacterial therapy; of the 85 patients in which fungi were detected, 12.9% achieved remission after antifungal therapy. Conclusions Overall, mNGS had unique advantages in the detection of suspected CAP pathogens. However, mNGS was not superior to X-pert MTB/RIF for the diagnosis of TB. In addition, mNGS was not necessary as a routine test for all patients admitted with suspected CAP. Furthermore, when fungi are detected by mNGS, antifungal therapy should be cautious.

Depression is a psychological disorder associated with prolonged stress, which involves abnormal activation of the hypothalamic-pituitary-adrenal (HPA) axis, leading to elevated levels of glucocorticoids (GC). Excessive GC can cause damage to the structure and function of the hippocampus, thereby triggering depressive symptoms. Studies suggest that the bile acid receptor farnesoid X receptor (FXR) may play a role in adrenal GC synthesis. This study aimed to explore the potential therapeutic effects of dried bear bile (DBB) on depression and its mechanism. We used the chronic unpredictable mild stress (CUMS) mouse model and FXR agonist GW4064 stimulated mice, as well as H295R human adrenal cortical carcinoma cells, employing behavioral tests, biochemical analysis, and gene expression analysis to assess the effects of DBB treatment on depressive behavior, serum corticosterone (CORT) levels, and adrenal FXR and steroid biosynthesis-related gene expression. The results showed that in both CUMS and GW4064-stimulated mice, DBB treatment significantly improved depressive-like behaviors and reversed serum CORT levels. Additionally, DBB suppressed the expression of steroidogenic regulatory genes in the adrenal glands of CUMS mice. In H295R cells, DBB treatment effectively reduced cortisol secretion induced by Forskolin, inhibited the expression of steroid biosynthesis-related genes, and suppressed cortisol production and HSD3B2 expression under conditions of FXR overexpression and FXR activation. Our findings suggest that DBB regulates adrenal FXR to modulate glucocorticoid synthesis and exerts antidepressant effects. DBB may serve as a potential therapeutic agent for depression by regulating GC levels and steroidogenesis pathway. Further research is underway to test the antidepressant effects of each DBB component to understand their specific contribution.

Background: Ocular neovascular diseases, which contribute significantly to vision loss, lack effective preventive treatments. Recent studies have highlighted the significant involvement of immune cells in neovascular retinopathy. Myeloid-derived suppressor cells (MDSCs) promote the development of neovascularization, but it is unknown whether they participate in pathological neovascularization and whether they are expected to be a therapeutic target. Method: We investigated the role of MDSCs in promoting pathological angiogenesis using an oxygen-induced retinopathy (OIR) model, employing flow cytometry, immunofluorescence, and smart-seq analysis. Then, we evaluated the proportion of MDSCs in patient blood samples using flow cytometry. Additionally, we assessed the effect of MDSC depletion using an anti-Gr-1 monoclonal antibody on retinal vasculopathy and alterations in retinal microglia. Results: In the OIR model, an elevated ratio of MDSCs was observed in both blood and retinal tissue during phase II (Neovascularization). The depletion of MDSCs resulted in reduced retinal neovascularization and vaso-obliteration, along with a decrease in microglia within the neovascularization area. Furthermore, analysis of gene transcripts associated with MDSCs indicated activation of vascular endothelial growth factor (VEGF) regulation and inflammation. Importantly, infants with ROP exhibited a higher proportion of MDSCs in their blood samples. Conclusion: Our results suggested that excessive MDSCs represent an unrecognized feature of ocular neovascular diseases and be responsible for the retinal vascular inflammation and angiogenesis, providing opportunities for new therapeutic approaches to ocular neovascular disease.

Abstract To address several common problems of finger vein recognition, a lightweight finger vein recognition algorithm by means of a small sample has been proposed in this study. First of all, a Gabor filter is applied to deal with the images for the purpose of that these processed images can simulate a kind of situation of finger vein at low temperature, such that the generalization ability of the algorithm model can be improved as well. By cutting down the amount of convolutional layers and fully connected layers in VGG-19, a lightweight network can be given. Meanwhile, the activation function of some convolutional layers is replaced to protect the network weight that can be updated successfully. After then, a multi-attention mechanism is introduced to the modified network architecture to result in improving the ability of extracting important features. Finally, a strategy based on transfer learning has been used to reduce the training time in the model training phase. Honestly, it is obvious that the proposed finger vein recognition algorithm has a good performance in recognition accuracy, robustness and speed. The experimental results show that the recognition accuracy can arrive at about 98.45%, which has had better performance in comparison with some existing algorithms.

Abstract To enable high performance of all solid-state batteries, a catholyte should demonstrate high ionic conductivity, good compressibility and oxidative stability. Here, a LaCl3-based Na+ superionic conductor (Na1 − x Zr x La1 − x Cl4) with high ionic conductivity of 2.9 × 10−4 S cm−1 (30 °C), good compressibility and high oxidative potential (3.80 V vs. Na2Sn) is prepared via solid state reaction combining mechanochemical method. X-ray diffraction reveals a hexagonal structure (P6 3 /m) of Na1 − x Zr x La1 − x Cl4, with Na+ ions forming a one-dimensional diffusion channel along the c-axis. First-principle calculations combining with X-ray absorption fine structure characterization etc. reveal that the ionic conductivity of Na1 − x Zr x La1 − x Cl4 is mainly determined by the size of Na+-channels and the Na+/La3+ mixing in the one-dimensional diffusion channels. When applied as a catholyte, the NaCrO2||Na0.7Zr0.3La0.7Cl4||Na3PS4||Na2Sn all-solid-state batteries demonstrate an initial capacity of 114 mA h g−1 and 88% retention after 70 cycles at 0.3 C. In addition, a high capacity of 94 mA h g−1 can be maintained at 1 C current density.

Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory demyelination occurring in the central nervous system (CNS). Inulin is a common prebiotic that can improve metabolic disorders by modulating the gut microbiota. However, its capacity to affect CNS autoimmunity is poorly recognized. Experimental autoimmune encephalomyelitis (EAE) is a classical mouse model of MS. Herein, we found that oral administration of inulin ameliorated the severity EAE in mice, accompanied by reductions in inflammatory cell infiltration and demyelination in the CNS. These reductions were associated with decreased proportion and numbers of Th17 cells in brain and spleen. Consistent with the findings, the serum concentrations of IL-17, IL-6, and TNF-α were reduced in inulin treated EAE mice. Moreover, the proliferation of auto-reactive lymphocytes, against MOG35-55 antigen, was attenuated ex vivo. Mechanistically, inulin treatment altered the composition of gut microbiota. It increased Lactobacillus and Dubosiella whereas decreased g_Prevotellaceae_NK3B31_group at the genus level, alongside with elevated concentration of butyric acid in fecal content and serum. In vitro, butyrate, but not inulin, could inhibit the activation of MOG35-55 stimulated lymphocytes. Furthermore, fecal microbiota transplantation assay confirmed that fecal contents of inulin-treated normal mice had an ameliorative effect on EAE mice. In contrast, antibiotic cocktail (ABX) treatment diminished the therapeutic effect of inulin in EAE mice as well as the reduction of Th17 cells, while supplementation with Lactobacillus reuteri restored the amelioration effect. These results confirmed that the attenuation of inulin on Th17 cells and inflammatory demyelination in EAE mice was dependent on its modulation on gut microbiota and metabolites. Our findings provide a potential therapeutic regimen for prebiotic inulin supplementation in patients with multiple sclerosis.

Introduction Individualized treatment of colorectal cancer liver metastases (CRLM) remains challenging due to differences in the severity of metastatic disease and tumour biology. Exploring specific prognostic risk subgroups is urgently needed. The current study aimed to investigate the prognostic value of chromosomal instability (CIN) in patients with initially resectable CRLM and the predictive value of CIN for the efficacy of bevacizumab.Methods Ninety-one consecutive patients with initially resectable CRLM who underwent curative liver resection from 2006 to 2018 at Sun Yat-sen University Cancer Center were selected for analysis. CIN was evaluated by automated digital imaging systems. Immunohistochemistry (IHC) was performed to detect interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA) and CD31 expression in paraffin-embedded specimens. Recurrence-free survival (RFS) and overall survival (OS) were analysed using the Kaplan–Meier method and Cox regression models.Results Patients with high chromosomal instability (CIN-H) had a worse 3-year RFS rate (HR, 1.953; 95% CI, 1.001–3.810; p = 0.049) and a worse 3-year OS rate (HR, 2.449; 95% CI, 1.150–5.213; p = 0.016) than those with low chromosomal instability (CIN-L). CIN-H was identified as an independent prognostic factor for RFS (HR, 2.569; 95% CI, 1.078–6.121; p = 0.033) and OS (HR, 3.852; 95% CI, 1.173–12.645; p = 0.026) in the multivariate analysis. The protein levels of IL-6, VEGFA and CD31 were upregulated in patients in the CIN-H group compared to those in the CIN-L group in both primary tumour and liver metastases tissues. Among them, 22 patients with recurrent tumours were treated with first-line bevacizumab treatment and based on the clinical response assessment, disease control rates were adversely associated with chromosomal instability (p = 0.043).Conclusions Our study showed that high chromosomal instability is a negative prognostic factor for patients with initially resectable CRLM after liver resection. CIN may have positive correlations with angiogenesis through expression of IL-6–VEGFA axis and be used as a potential predictor of efficacy of bevacizumab.

Introduction: DNA ploidy (P), stroma fraction (S), and nucleotyping (N) collectively known as PSN, have proven prognostic accuracy in stage II colorectal cancer (CRC). However, few studies have reported on the prognostic value of the PSN panel in stage III colon cancer patients receiving capecitabine and oxaliplatin adjuvant chemotherapy. Objectives: This study aimed to validate PSN’s prognostic impact on stage III colon cancer, identifying candidates for optimized adjuvant chemotherapy duration. Design: A retrospective analysis was conducted on a cohort of stage III colon cancer patients from April 2008 to June 2020. Methods: Postoperative pathological samples from stage III colon cancer patients who underwent radical surgery and postoperative adjuvant chemotherapy at Sun Yat-sen University Cancer Center were retrospectively collected. Automated digital imaging assessed PSN, categorizing risk groups. Kaplan–Meier, Cox regression, and time-dependent receiver operating characteristic analysis compared model validity. Results: Significant differences in 5-year disease-free survival (DFS) and overall survival (OS) were noted among PSN-based low-, moderate-, and high-risk groups (DFS: 92.10% versus 83.62% versus 79.80%, p = 0.029; OS: 96.69% versus 93.99% versus 90.12%, p = 0.016). PSN emerged as an independent prognostic factor for DFS [hazard ratio (HR) = 1.409, 95% confidence interval (CI): 1.002–1.981, p = 0.049] and OS (HR = 1.720, 95% CI: 1.127–2.624, p = 0.012). The PSN model, incorporating perineural invasion and tumor location, displayed superior area under the curve for 5-year (0.692 versus 0.553, p = 0.020) and 10-year (0.694 versus 0.532, p = 0.006) DFS than TNM stage. In the PSN high-risk group, completing eight cycles of adjuvant chemotherapy significantly improved 5-year DFS and OS compared to four to seven cycles (DFS: 89.43% versus 71.52%, p = 0.026; OS: 96.77% versus 85.46%, p = 0.007). Conclusion: The PSN panel effectively stratifies stage III colon cancer, aiding in optimized adjuvant chemotherapy duration determination.

Abstract Dielectric capacitors with a fast charging/discharging rate, high power density, and long‐term stability are essential components in modern electrical devices. However, miniaturizing and integrating capacitors face a persistent challenge in improving their energy density (Wrec) to satisfy the specifications of advanced electronic systems and applications. In this work, leveraging phase‐field simulations, we judiciously designed a novel lead‐free relaxor ferroelectric material for enhanced energy storage performance, featuring flexible distributed weakly polar endotaxial nanostructures (ENs) embedded within a strongly polar fluctuation matrix. The matrix contributes to substantially enhanced polarization under an external electric field, and the randomly dispersed ENs effectively optimize breakdown phase proportion and provide a strong restoring force, which are advantageous in bolstering breakdown strength and minimizing hysteresis. Remarkably, this relaxor ferroelectric system incorporating ENs achieves an exceptionally high Wrec value of 10.3 J/cm3, accompanied by a large energy storage efficiency (η) of 85.4%. This work introduces a promising avenue for designing new relaxor materials capable of capacitive energy storage with exceptional performance characteristics.

Parkinson’s disease (PD) is a common neurodegenerative disorder with no cure. Astragalus membranaceus is used in Chinese culture as a food supplement to boost immunity. The present study aimed to explore the neuroprotective effects of total flavonoids extracted from A. membranaceus (TFA) and their protective mechanisms. TFA offered neuroprotection against 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) in the mouse model of Parkinsonism, by improving behavior performance in the gait analysis and pole test, and inhibiting the decline of tyrosine hydroxylase (TH) positive neurons and TH protein expression in substantia nigra of mice. TFA also prevented 1-methyl-4-phenylpyridinium (MPP+) induced neurotoxicity in SH-SY5Y cells, by increasing GSH and GSH/GSSG ratio, and reducing reactive oxygen species. In addition, the neuroprotective effects of TFA were associated with its ability to restore MPTP/MPP+ induced downregulation of SLC7A11 and glutathione peroxidase 4 (GPX-4). In conclusion, we demonstrated that TFA exerted significant neuroprotection against MPTP/MPP+ induced neurodegeneration by inhibiting ferroptosis through the regulation of SLC7A11/GPX-4 axis, suggesting the use of TFA as a possible food supplement in the prevention of PD.

Abstract The objective of this study was to compare and evaluate the changes in periodontal pathogens and periodontal status within 6 months of wearing three orthodontic retainers, namely, vacuum-formed retainer (VFR), Hawley retainer (HR), and lingual fixed retainer (LR). In total, 48 patients who underwent orthodontic treatment with ordinary metal brackets were divided into VFR, HR, and LR groups (n = 16 per group). Saliva samples were collected at the time of debonding (T0) and after 1 month (T1), 3 months (T2), and 6 months (T3). Porphyromonas gingivalis (Pg) and Aggregatibacter actinomycetemcomitans (Aa) were quantitatively analyzed using real-time PCR. Gingival index (GI), plaque index (PLI), and probing depth (PD) were measured at the four time points to evaluate changes in periodontal state. SPSS20.0 software was used to analyze the data, and P

Abstract Background The pathological tumor burden score (TBS) has been proven to be a better risk stratification tool for liver metastasis of colorectal cancer than the traditional clinical risk score (CRS). The aim of this study was to evaluate the prognostic value of the pathological tumor burden score in patients with or without neoadjuvant chemotherapy (NAC). Methods A total of 348 patients with colorectal liver metastases (CRLM) who underwent curative hepatic resection were retrospectively enrolled from September 1999 to December 2016. Univariable and multivariable Cox regression analyses were conducted to identify the independent predictors of prognosis. Kaplan–Meier curves and log-rank tests were used to determine whether TBS has enough discriminatory ability under certain grouping. Results Patients who received NAC had a higher median TBS than patients who did not receive NAC (4.07 vs. 2.69, P 3 showed a significantly worse 3-year RFS (41.1% vs. 63.6%, P 3 showed comparable 3-year RFS (33.3% vs. 26.4%, P = 0.400) and 3-year OS rates (76.5% vs. 58.2%, P = 0.064) to those who did not. Regardless of the regimen and response to NAC, there was no significant difference about 3-year RFS and 3-year OS rates between the TBS ≤ 3 and TBS > 3 groups. Conclusion Pathological TBS can be applied to predict the RFS and OS of patients suffering from CRLM who did not receive NAC. However, pathological TBS might not be regard as prognosis in patients who did receive NAC.

Abstract The ideal mechanical properties and behaviors of materials without the influence of defects are of great fundamental and engineering significance but considered inaccessible. Here, we use single-atom-thin isotopically pure hexagonal boron nitride (hBN) to demonstrate that two-dimensional (2D) materials offer us close-to ideal experimental platforms to study intrinsic mechanical phenomena. The highly delicate isotope effect on the mechanical properties of monolayer hBN is directly measured by indentation: lighter 10B gives rise to higher elasticity and strength than heavier 11B. This anomalous isotope effect establishes that the intrinsic mechanical properties without the effect of defects could be measured, and the so-called ultrafine and normally neglected isotopic perturbation in nuclear charge distribution sometimes plays a more critical role than the isotopic mass effect in the mechanical and other physical properties of materials.

Music emotion recognition is becoming an important research direction due to its great significance for music information retrieval, music recommendation, and so on. In the task of music emotion recognition, the key to achieving accurate emotion recognition lies in how to extract the affect-salient features fully. In this paper, we propose an end-to-end spatial-temporal feature extraction method named FFA-BiGRU for music emotion classification. Taking the log Mel-spectrogram of music audio as the input, this method employs an attention-based convolutional residual module named FFA, which serves as a spatial feature learning module to obtain multi-scale spatial features. In the FFA module, three group architecture blocks extract multi-level spatial features, each of which consists of a stack of multiple channel-spatial attention-based residual blocks. Then, the output features from FFA are fed into the bidirectional gated recurrent units (BiGRU) module to capture the temporal features of music further. In order to make full use of the extracted spatial and temporal features, the output feature maps of FFA and those of the BiGRU are concatenated in the channel dimension. Finally, the concatenated features are passed through fully connected layers to predict the emotion classification results. The experimental results of the EMOPIA dataset show that the proposed model achieves better classification accuracy than the existing baselines. Meanwhile, the ablation experiments also demonstrate the effectiveness of each part of the proposed method.

Inspired by the fact that flying insects improve their power conversion efficiency through resonance, many soft robots driven by dielectric elastomer actuators (DEAs) have achieved optimal performance via first-order modal resonance. Besides first-order resonance, DEAs contribute to multiple innovative functions such as pumps that can make sounds when using multimodal resonances. This study presents the multimodal resonance of a rectangular planar DEA (RPDEA) with a central mass bias. Using a combination of experiments and finite element modeling (FEM), it was discerned that under a prestretch of 1.0 × 1.1, the first-, second-, and third-order resonances corresponded to vertical vibration, rotation along the long axis, and rotation along the short axis, respectively. In first-order resonance, superharmonic, harmonic, and subharmonic responses were activated, while only harmonic and subharmonic responses were observed in the second- and third-order resonances. Further investigations revealed that prestretching tended to inhibit third-order resonance but could elevate the resonance frequencies of the first and second orders. Conveniently, both the experimental and FEM results showed that the frequencies and amplitudes of the multimodal resonances could be tuned by adjusting the amplitudes of the excitation signals, referring to the direct current (DC) amplitude and alternating current (AC) amplitude, respectively. Moreover, instead of linear vibration, we found another novel approach that used rotation vibration to drive a robot with soft bristles via hopping locomotion, showcasing a higher speed compared to the first-order resonance in our robot.

Elymus magellanicus (É.Desv.) Á.Löve is a foliage accent plant that found in South America. In this study, the mitochondrial genome of E. magellanicus was sequenced, assembled, and annotated. The complete circular mitogenome of E. magellanicus is 583,450 bp in length and the overall G + C content of mitogenome is 42.27%. It harbors 39 protein-coding genes, 64 transfer RNA genes, eight ribosomal RNA genes, and 20 simple sequence repeats. Phylogenetic analysis indicates a relatively close relationship of E. magellanicus to Hordeum vulgare subsp. Spontaneum, Aegilops speltoides, Triticum aestivum, and T. aestivum cv. Chinese Yumai.

Abstract Corneal keratoconus (KC) is a dilated (ectatic) corneal disease characterized by a central thinning of the cornea, which causes protrusion into a conical shape that seriously affects vision. However, due to the complex etiology of keratoconus, its entire mechanism remains unclear and there is no mechanism-directed treatment method. Ferroptosis is a novel programmed cell death mechanism related to lipid peroxidation, stress, and amino acid metabolism, which plays a crucial role in various diseases. This study aimed to explore the relationship between keratoconus and ferroptosis, to provide new insights into the mechanism of keratoconus development, and potential treatment options based on further elucidation of this mechanism. The corresponding mRNA microarray expression matrix data of KC patients were obtained from GEO database (GSE204791). Weighted co-expression network analysis (WGCNA) and support vector machine recursive feature elimination (SVM-RFE) were selected to screen hub genes, which were overlapped with ferroptosis genes (FRGs) from FerrDb. GO and GSEA were performed to analyze differential pathways, ssGSEA was used to determine immune status, and then, feasible drugs were predicted by gene-drug network. Additionally, we predicted the miRNA and IncRNA of hub genes to identify the underlying mechanism of disease so as to predict treatment for the disease. The epithelial transcriptome from keratoconus tissue mRNA microarray data (GSE204791) was extracted for the main analysis, including eight epithelial cells and eight epithelial control cells. The differential genes that were overlapped by WGCAN, SVM-RFE and FRGs were mainly related to oxidative stress, immune regulation, cellular inflammation, and metal ion transport. Through further analysis, aldo–keto reductase family 1 member C3 (AKR1C3) was selected, and negatively correlated with mature CD56 natural killer (NK) cells and macrophages. Then, gene-drug interaction network analysis and miRNA prediction were performed through the website. It was concluded that four immune-related drugs (INDOMETHACIN, DAUNORUBICIN, DOXORUBICIN, DOCETAXEL) and a miRNA (has-miR-184) were screened to predict potential drugs and targets for disease treatment. To our knowledge, this was the first report of KC being associated with ferroptosis and prompted search for differential genes to predict drug targets of gene immunotherapy. Our findings provided insight and a solid basis for the analysis and treatment of KC.

Aegilops tauschii is considered as an important gene source for improving common wheat, which has wide distribution and rich genetic variation. In order to understand genetic diverstity and population structure of A. tauschii from different origins, ISSR markers were used to evaluate genetic diversity and population structure of 56 A. tauschii accessions. The results were as follows：(1) The 170 polymorphic bands were detected by 16 ISSR primers, and polymorphic bands of each ISSR primer ranged from 3 to 18, with an average of 10.63. The variation of polymorphism information content（PIC）ranged from 0.17 to 0.85, with an averaged of 0.67. (2) The comparison among four populations indicated that the population genetic diversity of Central Asia was the highest (He=0.225 4, I=0.355 7) and gene flow between populations was relatively low (Nm=1.638 6). (3)The clustering results showed that 56 A. tauschii accessions were divided into two groups at the genetic similarity coefficient 0.67, of which eight accessions from Tajikistan and Turkmenistan were clustered in Group 2. And, the Group 1 including 48 accessions could be further divided into three sub-groups, which indicated that A. tauschii accessions with clustering together have the same origin. (4) Based on population structure analysis, 56 A. tauschii accessions were divided into five populations, of which the V population from Iran in West Asia had relatively consistent genetic background and relatively low degree of hybridization. Furthermore, the Q value analysis of populations showed that the genetic relationship of IV population were relatively complex, producing the most abundant genetic diversity. The results of this study can provide an important reference for analysis of genetic relationship, protection of biodiversity, and lay a foundation for the scientific utilization and evolution research of A. tauschii.

Abstract Unlike conventional αβT cells, invariant natural killer T (iNKT) cells complete their terminal differentiation to functional iNKT1/2/17 cells in the thymus. However, underlying molecular programs that guide iNKT subset differentiation remain unclear. Here, we profiled the transcriptomes of over 17,000 iNKT cells and the chromatin accessibility states of over 39,000 iNKT cells across four thymic iNKT developmental stages using single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to define their developmental trajectories. Our study discovered novel features for iNKT precursors and different iNKT subsets and indicated that iNKT2 and iNKT17 lineage commitment may occur as early as stage 0 (ST0) by two distinct programs, while iNKT1 commitments may occur post ST0. Both iNKT1 and iNKT2 cells exhibit extensive phenotypic and functional heterogeneity, while iNKT17 cells are relatively homogenous. Furthermore, we identified that a novel transcription factor, Cbfβ, was highly expressed in iNKT progenitor commitment checkpoint, which showed a similar expression trajectory with other known transcription factors for iNKT cells development, Zbtb16 and Egr2, and could direct iNKT cells fate and drive their effector phenotype differentiation. Conditional deletion of Cbfβ blocked early iNKT cell development and led to severe impairment of iNKT1/2/17 cell differentiation. Overall, our findings uncovered distinct iNKT developmental programs as well as their cellular heterogeneity, and identified a novel transcription factor Cbfβ as a key regulator for early iNKT cell commitment.

Abstract Developing highly efficient, selective and low-overpotential electrocatalysts for carbon dioxide (CO2) reduction is crucial. This study reports an efficient Ni single-atom catalyst coordinated with pyrrolic nitrogen and pyridinic nitrogen for CO2 reduction to carbon monoxide (CO). In flow cell experiments, the catalyst achieves a CO partial current density of 20.1 mA cmgeo −2 at −0.15 V vs. reversible hydrogen electrode (VRHE). It exhibits a high turnover frequency of over 274,000 site−1 h−1 at −1.0 VRHE and maintains high Faradaic efficiency of CO (FECO) exceeding 90% within −0.15 to −0.9 VRHE. Operando synchrotron-based infrared and X-ray absorption spectra, and theoretical calculations reveal that mono CO-adsorbed Ni single sites formed during electrochemical processes contribute to the balance between key intermediates formation and CO desorption, providing insights into the catalyst’s origin of catalytic activity. Overall, this work presents a Ni single-atom catalyst with good selectivity and activity for CO2 reduction while shedding light on its underlying mechanism.

Abstract Background Standard treatment of locally advanced rectal cancer (LARC) was neoadjuvant chemoradiotherapy (CRT), followed by total mesorectal excision (TME). Total neoadjuvant treatment (TNT), a new concept, attempts to deliver both systemic chemotherapy and neoadjuvant CRT prior to surgery. Patients treated with neoadjuvant chemotherapy were more likely to show higher tumor regression. The objective of this trial was to increase complete clinical rate (cCR) for LARC patients by optimizing tumor response, using TNT regimen as compared to conventional chemoradiotherapy. TESS, a prospective, open‐label, multicenter, single‐arm, phase 2 study, is underway. Methods Main inclusion criteria include cT3‐4aNany or cT1‐4aN+ rectal adenocarcinoma aged 18‐70y; Eastern Cooperative Oncology Group (ECOG) performance 0–1; location ≤5 cm from anal verge. Ninety‐eight patients will receive 2 cycles of neoadjuvant chemotherapy Capeox (capecitabine + oxaliplatin) before, during, and after radiotherapy 50Gy/25 fractions, before TME (or other treatment decisions, such as Watch and Wait strategy) and adjuvant chemotherapy capecitabine 2 cycles. Primary endpoint is the cCR rate. Secondary endpoints include ratio of sphincter preservation strategy; pathological complete response rate and tumor regression grade distribution; local recurrence or metastasis; disease‐free survival; locoregional recurrence‐free survival; acute toxicity; surgical complications; long‐term anal function; late toxicity; adverse effect, ECOG standard score, and quality of life. Adverse events are graded per Common Terminology Criteria for Adverse Events V5.0. Acute toxicity will be monitored during antitumor treatment, and late toxicity will be monitored for 3 years from the end of the first course of antitumor treatment. Discussion The TESS trial aims to explore a new TNT strategy, which is expected to increase the rate of cCR and sphincter preservation rate. This study will provide new options and evidence for a new sandwich TNT strategy in patients with distal LARC.

Abstract Citrus fruit has long been considered a healthy food, but its role and detailed mechanism in lifespan extension are not clear. Here, by using the nematode C. elegans, we identified that nomilin, a bitter-taste limoloid that is enriched in citrus, significantly extended the animals’ lifespan, healthspan, and toxin resistance. Further analyses indicate that this ageing inhibiting activity depended on the insulin-like pathway DAF-2/DAF-16 and nuclear hormone receptors NHR-8/DAF-12. Moreover, the human pregnane X receptor (hPXR) was identified as the mammalian counterpart of NHR-8/DAF-12 and X-ray crystallography showed that nomilin directly binds with hPXR. The hPXR mutations that prevented nomilin binding blocked the activity of nomilin both in mammalian cells and in C. elegans. Finally, dietary nomilin supplementation improved healthspan and lifespan in D-galactose- and doxorubicin-induced senescent mice as well as in male senescence accelerated mice prone 8 (SAMP8) mice, and induced a longevity gene signature similar to that of most longevity interventions in the liver of bile-duct-ligation male mice. Taken together, we identified that nomilin may extend lifespan and healthspan in animals via the activation of PXR mediated detoxification functions.

To address the problems of current mainstream semantic segmentation network such as rough edge segmentation of navel oranges defects, poor accuracy of small target defect segmentation and insufficient deep-level semantic extraction of defects, feature information will be lost, a multi-class segmentation model based on improved DeepLabv3+ is proposed to detect the surface defects of navel oranges. The Coordinate Attention Mechanism is embedded into the DeepLabv3+ network for better semantic segmentation performance, while the dilated convolution of Atrous Spatial Pyramid Pooling structure is replaced with deformable empty convolution to improve the fitting ability of the network to target shape changes and irregular defects. In addition, a BiFPN-based feature fusion branch is introduced at the DeepLabv3+ encoder side to realize multi-scale feature fusion and enrich feature space and semantic information. The experimental results show that the average intersection ratio and average pixel intersection ratio accuracies of the improved DeepLabv3+ model on the navel orange surface defect dataset are 77.32% and 86.38%, which are 3.81% and 5.29% higher than the original DeepLabv3+ network, respectively, improving the extraction capability of navel orange defect features and having better segmentation performance.

Abstract Chemotherapy is widely used to treat colorectal cancer (CRC). Despite its substantial benefits, the development of drug resistance and adverse effects remain challenging. This study aimed to elucidate a novel role of glucagon in anti‐cancer therapy. In a series of in vitro experiments, glucagon inhibited cell migration and tube formation in both endothelial and tumor cells. In vivo studies demonstrated decreased tumor blood vessels and fewer pseudo‐vessels in mice treated with glucagon. The combination of glucagon and chemotherapy exhibited enhanced tumor inhibition. Mechanistic studies demonstrated that glucagon increased the permeability of blood vessels, leading to a pronounced disruption of vessel morphology. Signaling pathway analysis identified a VEGF/VEGFR‐dependent mechanism whereby glucagon attenuated angiogenesis through its receptor. Clinical data analysis revealed a positive correlation between elevated glucagon expression and chemotherapy response. This is the first study to reveal a role for glucagon in inhibiting angiogenesis and vascular mimicry. Additionally, the delivery of glucagon‐encapsulated PEGylated liposomes to tumor‐bearing mice amplified the inhibition of angiogenesis and vascular mimicry, consequently reinforcing chemotherapy efficacy. Collectively, the findings demonstrate the role of glucagon in inhibiting tumor vessel network and suggest the potential utility of glucagon as a promising predictive marker for patients with CRC receiving chemotherapy.

Intense terahertz (THz) radiation in free space has immense potential for regulating material state, accelerating electrons, producing biological effects, and so on. However, the high cost and challenges involved in constructing strong-field THz sources have limited their developments, making it difficult for the potential applications of strong-field THz radiation to be widely adopted. Spintronic THz emitters (STEs) with numerous merits such as high efficiency, ultrabroadband, ease of integration, and low cost have become ubiquitous, but the majority of these emitters require stable operation in the presence of external magnets, limiting their applications, particularly in generating strong fields that necessitate large-sized samples. Here, we demonstrate the feasibility of generating strong-field THz radiation in 4-inch antiferromagnetic material–ferromagnetic metal (IrMn3 [2 nm]/Co20Fe60B20 [2 nm]/W [2 nm]) without external magnetic field driving. Under the excitation of a Ti:sapphire femtosecond laser amplifier with a 35-fs pulse duration and a 1-kHz repetition rate, we obtain strong-field THz radiation from our STEs with a pulse duration of ~110 fs, and a spectrum covering up to ~10 THz. Further scaling up the pump laser energy up to 55 mJ with a pulse duration of ~20 fs and a repetition rate of 100 Hz provided by the Synergetic Extreme Condition User Facility, the radiated THz electric field strength from the external-magnetic-free 4-inch STEs can exceed 242 kV/cm with a pulse duration of ~230 fs, a spectrum covering up to ~14 THz, and a single pulse energy of 8.6 nJ measured by a calibrated pyroelectric detector. Our demonstrated external-magnetic-field-free high-field STEs have some unique applications such as producing sub-cycle ultrashort strong THz fields in huge size emitters under the excitation of high-energy light sources, accelerating the development of THz science and applications.

Background: Fruit freshness detection by computer vision is essential for many agricultural applications, e.g., automatic harvesting and supply chain monitoring. This paper proposes to use the multi-task learning (MTL) paradigm to build a deep convolutional neural work for fruit freshness detection. Results: We design an MTL model that optimizes the freshness detection (T1) and fruit type classification (T2) tasks in parallel. The model uses a shared CNN (convolutional neural network) subnet and two FC (fully connected) task heads. The shared CNN acts as a feature extraction module and feeds the two task heads with common semantic features. Based on an open fruit image dataset, we conducted a comparative study of MTL and single-task learning (STL) paradigms. The STL models use the same CNN subnet with only one specific task head. In the MTL scenario, the T1 and T2 mean accuracies on the test set are 93.24% and 88.66%, respectively. Meanwhile, for STL, the two accuracies are 92.50% and 87.22%. Statistical tests report significant differences between MTL and STL on T1 and T2 test accuracies. We further investigated the extracted feature vectors (semantic embeddings) from the two STL models. The vectors have an averaged 0.7 cosine similarity on the entire dataset, with most values lying in the 0.6–0.8 range. This indicates a between-task correlation and justifies the effectiveness of the proposed MTL approach. Conclusion: This study proves that MTL exploits the mutual correlation between two or more relevant tasks and can maximally share their underlying feature extraction process. we envision this approach to be extended to other domains that involve multiple interconnected tasks.

ABSTRACTThis study aimed to validate the prognostic value of Immunoscore (IS) in stage II colorectal cancer (CRC), and explore the roles of IS and circulating tumor DNA (ctDNA) in the adjuvant treatment for early-stage CRC. Resected tumor samples from stage II CRC patients were collected from the Sun Yat-sen University Cancer Center. The densities of CD3+ and CD8+ lymphocytes were quantified and converted to IS and classified into Low, Intermediate (Int), and High groups according to predefined cutoffs. A total of 113 patients were included in the study. Patients with IS-High, Int, and Low were 43 (38%), 62 (55%), and 8 (7%), respectively. Patients with IS-High had an excellent clinical outcome, with none recurring during a median follow-up of 3 years, including 15 (35%) clinical high-risk patients. The 3-year disease-free survival (DFS) was 100% for IS-High, 76% for IS-Int, and 47% for IS-Low (P

To address the problems of slow convergence speed and low accuracy of the chimp optimization algorithm (ChOA), and to prevent falling into the local optimum, a chaos somersault foraging ChOA (CSFChOA) is proposed. First, the cat chaotic sequence is introduced to generate the initial solutions, and then opposition-based learning is used to select better solutions to form the initial population, which can ensure the diversity of the algorithm at the beginning and improve the convergence speed and optimum searching accuracy. Considering that the algorithm is likely to fall into local optimum in the final stage, by taking the optimal solution as the pivot, chimps with better adaptation at the mirror image position replace chimps from the original population using the somersault foraging strategy, which can increase the population diversity and expand the search scope. The optimization search tests were performed on 23 standard test functions and CEC2019 test functions, and the Wilcoxon rank sum test was used for statistical analysis. The CSFChOA was compared with the ChOA and other improved intelligent optimization algorithms. The experimental results show that the CSFChOA outperforms most of the other algorithms in terms of mean and standard deviation, which indicates that the CSFChOA performs well in terms of the convergence accuracy, convergence speed and robustness of global optimization in both low-dimensional and high-dimensional experiments. Finally, through the test and analysis comparison of two complex engineering design problems, the CSFChOA was shown to outperform other algorithms in terms of optimal cost. For the design of the speed reducer, the performance of the CSFChOA is 100% better than other algorithms in terms of optimal cost; and, for the design of a three-bar truss, the performance of the CSFChOA is 6.77% better than other algorithms in terms of optimal cost, which verifies the feasibility, applicability and superiority of the CSFChOA in practical engineering problems.

The public health emergencies have had a significant impact on the world economy, and the sports industry has been no exception. This study employed StataMP-64 software and event study methodologies to examine the reaction of the Chinese sports industry's capital markets to the outbreak of public health emergencies. The event study method, which is becoming increasingly popular in the field of economics and management, is well-suited for evaluating the impact of specific events on stock returns in the capital market. This method has also garnered significant interest in the sports industry. In this study, the expected return is calculated using the classical market model, and the cumulative abnormal return and average cumulative abnormal return were calculated for each sports company during the period of the Wuhan "city closure" event and the inflection point event. The Wilcoxon non-parametric test has been used to examine the significance of the abnormal return. The results indicate that the event study method, applied to a procedural market model, is effective in analyzing the capital market's response to the public health emergencies outbreak in the Chinese sports industry.

Given the randomness inherent in fluid dynamics problems and limitations in human cognition, Computational Fluid Dynamics (CFD) modeling and simulation are afflicted with non-negligible uncertainties, casting doubts on the credibility of CFD. Scientifically and rigorously quantifying the uncertainty of CFD is paramount for assessing its credibility and informing engineering decisions. In order to quantify the uncertainty of multidimensional flow field responses stemming from uncertain model parameters, this paper proposes a method based on Gappy Proper Orthogonal Decomposition (POD) for supplementing high-fidelity flow field data within a framework that leverages POD and surrogate models. This approach enables the generation of corresponding high-fidelity flow fields from low-fidelity ones, significantly reducing the cost of high-fidelity flow field computation in uncertainty propagation modeling. Through an analysis of the impact of uncertainty in the coefficients of the Spalart–Allmaras (SA) turbulence model on the distribution of wall friction coefficients for the NACA0012 airfoil and pressure coefficients for the M6 wing, the proposed multi-fidelity modeling approach is demonstrated to offer significant advancements in both accuracy and efficiency compared to single-fidelity methods, providing a robust and efficient prediction model for large-scale random sampling.

Text input using hand gestures is an essential component of human–computer interaction technology, providing users with a more natural and enriching interaction experience. Nevertheless, the current gesture input methods have a variety of issues, including a high learning cost for users, poor input performance, and reliance on hardware. To solve these problems and better meet the interaction requirements, a hand recognition-based text input method called iHand is proposed in this paper. In iHand, a two-branch hand recognition algorithm combining a landmark model and a lightweight convolutional neural network is used. The landmark model is used as the backbone network to extract hand landmarks, and then an optimized classification head, which can preserve the space structure of landmarks, is designed to classify gestures. When the landmark model fails to extract hand landmarks, a lightweight convolutional neural network is employed for classification. Regarding the way letters are entered, to reduce the learning cost, the sequence of letters is mapped as a two-dimensional layout, and users can type with seven simple hand gestures. Experimental results on the public datasets show that the proposed hand recognition algorithm achieves high robustness compared to state-of-the-art approaches. Furthermore, we tested the performance of users’ initial use of iHand for text input. The results showed that the iHand’s average input speed was 5.6 words per minute, with the average input error rate was only 1.79%.

The gated recurrent unit (GRU) network can effectively capture temporal information for 1D signals, such as electroencephalography and event-related brain potential, and it has been widely used in the field of EEG emotion recognition. However, multi-domain features, including the spatial, frequency, and temporal features of EEG signals, contribute to emotion recognition, while GRUs show some limitations in capturing frequency–spatial features. Thus, we proposed a hybrid architecture of convolutional neural networks and GRUs (CGRU) to effectively capture the complementary temporal features and spatial–frequency features hidden in signal channels. In addition, to investigate the interactions among different brain regions during emotional information processing, we considered the functional connectivity relationship of the brain by introducing a phase-locking value to calculate the phase difference between the EEG channels to gain spatial information based on functional connectivity. Then, in the classification module, we incorporated attention constraints to address the issue of the uneven recognition contribution of EEG signal features. Finally, we conducted experiments on the DEAP and DREAMER databases. The results demonstrated that our model outperforms the other models with remarkable recognition accuracy of 99.51%, 99.60%, and 99.59% (58.67%, 65.74%, and 67.05%) on DEAP and 98.63%, 98.7%, and 98.71% (75.65%, 75.89%, and 71.71%) on DREAMER in a subject-dependent experiment (subject-independent experiment) for arousal, valence, and dominance.

The eradication of cancer stem cells (CSCs) with drug resistance confers the probability of local tumor control after chemotherapy or targeted therapy. As the main drug resistance marker, ABCG2 is also critical for colorectal cancer (CRC) evolution, in particular cancer stem-like traits expansion. Hitherto, the knowledge about the expression regulation of ABCG2, in particular its upstream transcriptional regulatory mechanisms, remains limited in cancer, including CRC. Here, ABCG2 was found to be markedly up-regulated in CRC CSCs (cCSCs) expansion and chemo-resistant CRC tissues and closely associated with CRC recurrence. Mechanistically, TOX3 was identified as a specific transcriptional factor to drive ABCG2 expression and subsequent cCSCs expansion and chemoresistance by binding to -261 to -141 segments of the ABCG2 promoter region. Moreover, we found that TOX3 recruited WDR5 to promote tri-methylation of H3K4 at the ABCG2 promoter in cCSCs, which further confers stem-like traits and chemoresistance to CRC by co-regulating the transcription of ABCG2. In line with this observation, TOX3, WDR5, and ABCG2 showed abnormal activation in chemo-resistant tumor tissues of in situ CRC mouse model and clinical investigation further demonstrated the comprehensive assessment of TOX3, WDR5, and ABCG2 could be a more efficient strategy for survival prediction of CRC patients with recurrence or metastasis. Thus, our study found that TOX3-WDR5/ABCG2 signaling axis plays a critical role in regulating CRC stem-like traits and chemoresistance, and a combination of chemotherapy with WDR5 inhibitors may induce synthetic lethality in ABCG2-deregulated tumors.

Matrix permeability is the primary transport property for shale gas recovery, due to the special production process of gas from matrix to wellbore. With the micro pore size of shale matrix, it is necessary to consider micro transport mechanisms for the obtained permeability from macro experimental techniques. In this study, the macro experimental permeability was investigated in micro way, by the analyzation of pressure drop curves of shale matrix at high- and low-pressure experimental conditions, with modified numerical model containing micro transport mechanisms. As selected parameters, porosity, pore radius and tortuosity were regressed to obtain apparent permeabilities of three samples. The analysis shows that, tortuosity is much higher than macro one, and has been proved to be necessary and reasonable. The Knudsen diffusion and slippage effect control the micro transport of shale matrix at low and high pressure, separately, which is the main difference of macro and micro transports. Slippage flow weight factor helps to increase of slippage flow proportion with pressure. Higher pore radius and tortuosity both could weaken the effect of Knudsen diffusion, and slippage flow appears positive relationship with pore size at high pressure. This research provides an inspiration to shale transport study and a micro perspective theoretical guidance for the macro recovery of in-site shale gas reservoir.

Abstract Background Lymphovascular invasion (LVI) and perineural invasion (PNI) can indicate poor survival outcomes in colorectal cancer, but few studies have focused on stage III colon cancer. The current study aimed to confirm the prognostic value of LVI and PNI and identify patients who could benefit from a complete duration of adjuvant chemotherapy based on the two pathological factors. Methods We enrolled 402 consecutive patients with stage III colon cancer who received colon tumor resection from November 2007 to June 2016 at Sun Yat-sen University Cancer Center. Survival analyses were performed by using Kaplan–Meier method with log-rank tests. Risk factors related to disease-free survival (DFS) and overall survival (OS) were identified through Cox proportional hazards analysis. Results 141 (35.1%) patients presented with LVI, and 108 (26.9%) patients with PNI. The LVI-positive group was associated with poorer 3-year DFS (86.5% vs. 76.3%, P = 0.001) and OS (96.0% vs. 89.1%, P = 0.003) rates compared with the LVI-negative group. The PNI-positive group showed a worse outcome compared with the PNI-negative group in 3-year DFS rate (72.5% vs. 86.7%, P

Zwitterionic hydrogels are nonfouling and hemocompatibility but several key challenges such as weak mechanical strength and low adhesion hamper their application as coating materials for devices. Here, the authors report a microgel reinforced zwitterionic hydrogel with excellent mechanical robustness and anti-swelling properties.

BackgroundStudies have found that sleep disturbance is associated with obsessive–compulsive symptoms. This study aimed to elaborate on the mediating and moderating mechanisms between these two variables. We hypothesized that repetitive negative thinking plays a mediating role in the relationship between sleep disturbance and obsessive–compulsive symptoms, and experiential avoidance plays a moderating role.MethodThis study included 639 Chinese adults. A questionnaire survey was used to assess sleep quality, obsessive–compulsive symptoms, experiential avoidance, repetitive negative thinking, and depression symptoms. A moderated mediation model was established.ResultsAfter controlling for depressive symptoms, repetitive negative thinking partially mediated the positive correlation between sleep disturbance and obsessive–compulsive symptoms. This indirect relationship was significant in individuals with lower experiential avoidance levels. Particularly, the relationship between sleep disturbance and repetitive negative thinking was significant among individuals with lower experiential avoidance levels, but not among individuals with higher experiential avoidance levels.ConclusionThis study demonstrated that repetitive negative thinking partially mediated the impact of sleep disturbance on obsessive–compulsive symptoms. The findings suggest that when providing support to individuals with sleep disturbance and obsessive–compulsive symptoms, assessing their level of experiential avoidance is necessary for performing targeted interventions. Individuals with low experiential avoidance may benefit from a clinical intervention targeting repetitive negative thinking to improve sleep quality and obsessive–compulsive symptoms.

Salmonella Typhimurium (S. Typhimurium) is a zoonotic pathogen posing a threat to animal husbandry and public health. Due to the emergence of antibiotic-resistant strains, alternative prevention and control strategies are needed. Live attenuated vaccines are an ideal option that provide protection against an S. Typhimurium pandemic. To develop a safe and effective vaccine, double-gene mutations are recommended to attenuate virulence. In this study, we chose aroA and luxS genes, whose deletion significantly attenuates S. Typhimurium’s virulence and enhances immunogenicity, to construct the double-gene mutant vaccine strain SAT52ΔaroAΔluxS. The results show that the mutant strain’s growth rate, adherence and invasion of susceptible cells are comparable to a wild-type strain, but the intracellular survival, virulence and host persistence are significantly attenuated. Immunization assay showed that 106 colony-forming units (CFUs) of SAT52ΔaroAΔluxS conferred 100% protection against wild-type challenges; the bacteria persistence in liver and spleen were significantly reduced, and no obvious pathological lesions were observed. Therefore, the double-gene mutant strain SAT52ΔaroAΔluxS exhibits potential as a live attenuated vaccine candidate against S. Typhimurium infection.

As one of the precious cultural heritages, Chinese landscape painting has developed unique styles and techniques. Researching the intelligent generation of Chinese landscape paintings from photos can benefit the inheritance of traditional Chinese culture. To address detail loss, blurred outlines, and poor style transfer in present generated results, a model for generating Chinese landscape paintings from photos named Paint-CUT is proposed. In order to solve the problem of detail loss, the SA-ResBlock module is proposed by combining shuffle attention with the resblocks in the generator, which is used to enhance the generator’s ability to extract the main scene information and texture features. In order to solve the problem of poor style transfer, perceptual loss is introduced to constrain the model in terms of content and style. The pre-trained VGG is used to extract the content and style features to calculate the perceptual loss and, then, the loss can guide the model to generate landscape paintings with similar content to landscape photos and a similar style to target landscape paintings. In order to solve the problem of blurred outlines in generated landscape paintings, edge loss is proposed to the model. The Canny edge detection is used to generate edge maps and, then, the edge loss between edge maps of landscape photos and generated landscape paintings is calculated. The generated landscape paintings have clear outlines and details by adding edge loss. Comparison experiments and ablation experiments are performed on the proposed model. Experiments show that the proposed model can generate Chinese landscape paintings with clear outlines, rich details, and realistic style. Generated paintings not only retain the details of landscape photos, such as texture and outlines of mountains, but also have similar styles to the target paintings, such as colors and brush strokes. So, the generation quality of Chinese landscape paintings has improved.

Abstract Invariant natural killer T cell (iNKT) subsets are differentially distributed in various immune organs. However, it remains unclear whether iNKT cells exhibit phenotypical and functional differences in different peripheral organs and how thymic iNKT cells emigrate to peripheral organs. Here, we used single-cell RNA-seq to map iNKT cells from peripheral organs. iNKT1 cells from liver, spleen, and lymph node appear to have distinct phenotypic profiles and functional capabilities. However, iNKT17 transcriptomes were comparable across peripheral organs. In addition, by integrating data with a thymic iNKT cell study, we uncovered a transient population of recent thymic emigrants, a cluster of peripheral iNKT cells with high expression of transcription factor Kruppel-like factor 2 (Klf2). Deletion of Klf2 led to a severe impairment of iNKT differentiation and migration. Our study revealed that iNKT subsets are uniquely distributed in peripheral organs with some inter-local tissue variation, especially for iNKT1 cell, and identified Klf2 as a rheostat for iNKT cell migration and differentiation.

Abstract Intelligent sensor management is generally required for efficient and accurate data processing when the multi-sensor system is used for multi-target tracking (MTT). However, this is theoretically and computationally challenging. To deal with this problem, we propose a novel sensor management approach based on efficient multi-objective optimization for MTT under the framework of partially observed Markov decision process. The multi-Bernoulli filter is used in conjunction with two objective functions. To simplify the multi-objective optimization problem, we use the Euclidean distance (ED) between the feasible and utopian solution vectors as a measure of the objectives and then sequentially select sensors from the candidates. For the selected sensors, we rank them according to the obtained ED measure and implement the iterated-corrector fusion scheme after the ranking. Numerical studies demonstrate the effectiveness and efficiency of our approach in multi-sensor MTT scenarios.

Abstract The field of research on pain originating from various bone diseases is expanding rapidly, with new mechanisms and targets asserting both peripheral and central sites of action. The scope of research is broadening from bone biology to neuroscience, neuroendocrinology, and immunology. In particular, the roles of primary sensory neurons and non-neuronal cells in the peripheral tissues as important targets for bone pain treatment are under extensive investigation in both pre-clinical and clinical settings. An understanding of the peripheral mechanisms underlying pain conditions associated with various bone diseases will aid in the appropriate application and development of optimal strategies for not only managing bone pain symptoms but also improving bone repairing and remodeling, which potentially cures the underlying etiology for long-term functional recovery. In this review, we focus on advances in important preclinical studies of significant bone pain conditions in the past 5 years that indicated new peripheral neuronal and non-neuronal mechanisms, novel targets for potential clinical interventions, and future directions of research.

Joint destruction is the major clinic burden in patients with rheumatoid arthritis (RA). It is unclear, though, how this autoimmune disease progresses to the point of deterioration of the joint. Here, we report that in a mouse model of RA the upregulation of TLR2 expression and its α(2,3) sialylation in RANK+ myeloid monocytes mediate the transition from autoimmunity to osteoclast fusion and bone resorption, resulting in joint destruction. The expression of α(2,3) sialyltransferases was significantly increased in RANK+TLR2+ myeloid monocytes, and their inhibition or treatment with a TLR2 inhibitor blocked osteoclast fusion. Notably, analysis of our single-cell RNA-sequencing (scRNA-seq) libraries generated from RA mice revealed a novel RANK+TLR2− a subset that negatively regulated osteoclast fusion. Importantly, the RANK+TLR2+ subset was significantly diminished with the treatments, whereas the RANK+TLR2− subset was expanded. Moreover, the RANK+TLR2− subset could differentiate into a TRAP+ osteoclast lineage, but the resulting cells did not fuse to form osteoclasts. Our scRNA-seq data showed that Maf is highly expressed in the RANK+TLR2− subset, and the α(2,3) sialyltransferase inhibitor-induced Maf expression in the RANK+TLR2+ subset. The identification of a RANK+TLR2− subset provides a potential explanation for TRAP+ mononuclear cells in bone and their anabolic activity. Further, TLR2 expression and its α(2,3) sialylation in the RANK+ myeloid monocytes could be effective targets to prevent autoimmune-mediated joint destruction.

With the rapid development of the era of artificial intelligence, the application ability of programming is also highlighted. As one of the necessary abilities of social talents in the future, primary and secondary schools pay more and more attention to this, and programming education is also in full swing. Therefore, based on previous studies, this paper further clarifies the current situation when the current situation of programming education in primary and secondary schools is ambiguous. This paper is aimed at a wide range of primary and secondary school teachers. With 1500 teachers who participated in the online training class for programming teachers as the object in Chinese primary, middle and high school stages, mainly from the three levels of schools, teachers, and students. The questionnaire with good reliability and validity test was used as the research method, the survey data were statistically described and analyzed, and differences were analyzed using Microsoft Excel2019, SPSS26.0 and so on, it investigates and analyzes the current situation of programming education in primary and secondary schools. Results indicate that the overall quality of programming education offerings in elementary and secondary schools is subpar, and the construction of programming education curriculum in schools requires improvement. Nevertheless, schools prioritize improving students' comprehensive abilities, and teachers hold a positive attitude towards programming education and teaching. Although students demonstrate a strong interest in learning, their foundation is weak, resulting in poor learning outcomes. Consequently, the author provides specific recommendations regarding programming education's working mechanism, curriculum standard system, teacher training, and educational resources sharing to better develop programming education in primary and secondary schools.

Background: Whether to escalate imatinib dosage or directly switch to sunitinib in gastrointestinal stromal tumors (GISTs) failing on standard dose 400 mg/d of imatinib is still controversial. Methods: We evaluated progression-free survival (PFS), overall survival (OS), and time to sunitinib failure (TTSF) of patients selecting imatinib dose escalation or directly switching to sunitinib after the failure of imatinib 400 mg/d therapy from 3 tertery referring centers between January 2008 to December 2016. Results: A total of 240 patients receiving sunitinib (37.5 mg continuous daily dose or 50 mg 4 weeks on with 2 weeks off) for at least 8 weeks were examined. After failure on imatinib 400 mg/d, 100 (49.3%) patients had dose escalation to 600 mg or 800 mg per day (IM group, imatinib group), and 103 (50.7%) directly switched to sunitinib (SU group, sunitinib group). The PFS in the SU and IM groups was 12 months and 5.0 months (P

The complicated multielectron and multiphase electrocatalytic sulfur reduction reaction (SRR) occurring in the Li–S battery is demonstrated, which strongly influences the performances of this battery chemistry. Effective candidates for SRR are often based on heteroatom‐doped carbon‐based electrocatalysts. However, the electrocatalytic sulfur reduction activity of these catalysts is so far insufficiently explored. Herein, a series of graphene doped with nonmetal elements (nitrogen, phosphorus, and sulfur) are designed and synthesized. It is shown that nitrogen‐doped graphene has a superior SRR catalytic activity with highest electrochemical reversibility and best electrochemical kinetics for the liquid–solid two‐phase conversion from long‐chain soluble Li2Sx (4 ≤ x ≤ 8) and the solid‐state Li2S2 to Li2S conversion. The considerably improved kinetics of the liquid–solid and solid–solid phases conversion reduces the continued accumulation of lithium polysulfides in electrolyte and the passivation of the electrode, thus resulting in a significant improvement in electrochemical performance of Li–S cells. Density‐functional theory calculations demonstrates that the highest SRR performance of N/G is originated from the strongest adsorption of the sulfur species and lowest energy barriers for Li2S decomposition among three doped graphene samples. This study is believed to guide the design of efficient electrocatalysts to exceed the performance of the benchmark for Li–S battery.