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Objective The present study evaluated the effect of flaxseed meal degraded by a protease, Lactobacillus plantarum, or both on the growth performance, nutrient digestibility, and health status of broilers. Methods There were four diets containing flaxseed meals in its non-degraded form (control, CON), degraded with 3,000 U/kg of protease (enzymatic, ELM), 1.0×109 CFU/kg of Lactobacillus plantarum (fermented, FLM), or both (dual-degraded, DLM). Each form of flaxseed meals was added at 15% of diet. A total of 480 yellow-feathered broilers at 22 d of age were distributed into 4 groups with 6 replicates of 20 chickens each. The feeding trial lasted for 42 d. Growth performance, apparent fecal digestibility (dry matter, energy, crude protein, and ash), and serum immunoglobins and antioxidases were determined at 42 and 63 d of age. Results Results showed that ELM, FLM, and DLM increased (p

Abstract Despite the success of immunotherapy in treating hepatocellular carcinoma (HCC), HCC remains a severe threat to health. Here, a crucial transcription factor, SOX12, is revealed that induces the immunosuppression of liver tumor microenvironment. Overexpressing SOX12 in HCC syngeneic models increases intratumoral regulatory T‐cell (Treg) infiltration, decreases CD8+T‐cell infiltration, and hastens HCC metastasis. Hepatocyte‐specific SOX12 knockout attenuates DEN/CCl4‐induced HCC progression and metastasis, whereas hepatocyte‐specific SOX12 knock‐in accelerates these effects. Mechanistically, SOX12 transcriptionally activates C‐C motif chemokine ligand 22 (CCL22) expression to promote the recruitment and suppressive activity of Tregs. Moreover, SOX12 transcriptionally upregulates CD274 expression to suppress CD8+T‐cell infiltration. Either knockdown of CCL22 or PD‐L1 dampens SOX12‐mediated HCC metastasis. Blocking of CC chemokine receptor 4 (CCR4), a receptor for CCL22, by inhibitor C‐021 or Treg‐specific knockout of CCR4 inhibits SOX12‐mediated HCC metastasis. Transforming growth factor‐β1 (TGF‐β1)/TGFβR1‐Smad2/3/4 is identified as a key upstream signaling for SOX12 overexpression in HCC cells. Combining C‐021 or TGFβR1 inhibitor galunisertib with anti‐PD‐L1 exhibits an enhanced antitumor effect in two HCC models. Collectively, the findings demonstrate that SOX12 contributes to HCC immunosuppression through the CCL22/CCR4‐Treg and PD‐L1‐CD8+T axes. Blocking of CCR4 or TGFβR1 improves the efficacy of anti‐PD‐L1 in SOX12‐mediated HCC.

ObjectiveTo assess the risk factors of cervical lymph node metastasis in elderly patients aged 65 years and older diagnosed with papillary thyroid cancer (PTC).Design and methodIn this retrospective analysis, we included a total of 328 elderly patients aged 65 years and older diagnosed with PTC. We thoroughly examined clinical features from these patients. Utilizing univariate and multivariate logistic regression analyses, we aimed to identify factors contributing to the risk of central and lateral lymph node metastasis (CLNM/LLNM) in this specific population of PTC patients aged 65 years and older.ResultsIn the univariate analysis, CLNM was significantly associated with tumor size, multifocality, bilaterality, and microcalcification, while only tumor size ≥ 1cm (OR = 0.530, P = 0.019, 95% CI = 0.311 – 0.900) and multifocality (OR = 0.291, P < 0.001, 95% CI = 0.148 - 0.574) remained as risk factors in the multivariate analysis. LLNM was confirmed to be associated with male (OR = 0.454, P < 0.020, 95% CI = 0.233 - 0.884), tumor size ≥ 1cm (OR = 0.471, P = 0.030, 95% CI = 0.239 – 0.928), age ≥ 70 (OR = 0.489, P = 0.032, 95% CI = 0.254 – 0.941), and microcalcification (OR = 0.384, P = 0.008, 95% CI = 0.189 – 0.781) in the multivariate analysis. In elderly PTC patients with CLNM, male gender (OR = 0.350, P = 0.021, 95% CI = 0.143 – 0.855), age ≥ 70 (OR = 0.339, P = 0.015, 95% CI = 0.142 – 0.810), and bilaterality (OR = 0.320, P = 0.012, 95% CI = 0.131 – 0.779) were closely associated with concomitant LLNM in both univariate and multivariate analyses.ConclusionFor elderly PTC patients aged 65 and older, tumor size ≥ 1cm and multifocality are significant risk factors for CLNM. Meanwhile, male, tumor size ≥ 1cm, age ≥ 70, and microcalcification are crucial predictors for LLNM. In patients already diagnosed with CLNM, male, age ≥ 70, and bilaterality increase the risk of LLNM.

Large-grained UO2 is considered a potential accident-tolerant fuel (ATF) due to its superior fission gas retention capabilities. Irradiation experiments for cerium dioxide (CeO2), used as a surrogate fuel, is a common approach for evaluating the performance of UO2. In this work, spark plasma sintered CeO2 pellets with varying grain sizes (145 nm, 353 nm, and 101 μm) and a relative density greater than 93.83% were irradiated with 4 MeV Xe ions at a fluence of 2 × 1015 ions/cm2 at room temperature, followed by annealing at 600 °C for 3 h. Microstructure, including dislocation loops and bubble morphology of the irradiated samples, has been characterized. The average size of dislocation loops increases with increasing grain size. Large-sized dislocation loops are absent near the grain boundary because the boundary absorbs surrounding defects and prevents the dislocation loops from coalescing and expanding. The distribution of bubbles within the grain is uniform, whereas the large-sized and irregularly shaped xenon bubbles observed in the small grain exhibit pipe diffusion along the grain boundaries. The bubble diameter in the large-grained pellet is the smallest. As the grain size increases, the volumetric swelling of the irradiated pellets decreases while the areal density of Xe bubbles increases. Elemental segregation, which tends to occur at dislocation loops and grain boundaries, has been analyzed. Large-grained CeO2 pellet with lower-density grain boundaries exhibits better resistance to volumetric swelling and elemental segregation, suggesting that large-grained UO2 pellets could serve as a potential ATF.

Background The incidence of papillary thyroid cancer (PTC) continues to rise all over the world, 10–15% of the patients have a poor prognosis. Although immunotherapy has been applied in clinical practice, its therapeutic efficacy remains far from satisfactory, necessitating further investigation of the mechanism of PTC immune remodeling and exploration of novel treatment targets.Methods This study conducted a single-cell RNA sequencing (scRNA-seq) analysis using 18 surgical tissue specimens procured from 14 patients diagnosed with adjacent tissues, non-progressive PTC or progressive PTC. Key findings were authenticated through spatial transcriptomics RNA sequencing, immunohistochemistry, multiplex immunohistochemistry, and an independent bulk RNA-seq data set containing 502 samples.Results A total of 151,238 individual cells derived from 18 adjacent tissues, non-progressive PTC and progressive PTC specimens underwent scRNA-seq analysis. We found that progressive PTC exhibits the following characteristics: a significant decrease in overall immune cells, enhanced immune evasion of tumor cells, and disrupted antigen presentation function. Moreover, we identified a subpopulation of lysosomal associated membrane protein 3 (LAMP3+) dendritic cells (DCs) exhibiting heightened infiltration in progressive PTC and associated with advanced T stage and poor prognosis of PTC. LAMP3+ DCs promote CD8+ T cells exhaustion (mediated by NECTIN2-TIGIT) and increase infiltration abundance of regulatory T cells (mediated by chemokine (C-C motif) ligand 17 (CCL17)-chemokine (C-C motif) receptor 4 (CCR4)) establishing an immune-suppressive microenvironment. Ultimately, we unveiled that progressive PTC tumor cells facilitate the retention of LAMP3+ DCs within the tumor microenvironment through NECTIN3-NECTIN2 interactions, thereby rendering tumor cells more susceptible to immune evasion.Conclusion Our findings expound valuable insights into the role of the interaction between LAMP3+ DCs and T-cell subpopulations and offer new and effective ideas and strategies for immunotherapy in patients with progressive PTC.

In autonomous driving systems, perception is pivotal, relying chiefly on sensors like LiDAR and cameras for environmental awareness. LiDAR, celebrated for its detailed depth perception, is being increasingly integrated into autonomous vehicles. In this article, we analyze the robustness of four LiDAR-included models against adversarial points under physical constraints. We first introduce an attack technique that, by simply adding a limited number of physically constrained adversarial points above a vehicle, can make the vehicle undetectable by the LiDAR-included models. Experiments reveal that adversarial points adversely affect the detection capabilities of both LiDAR-only and LiDAR–camera fusion models, with a tendency for more adversarial points to escalate attack success rates. Notably, voxel-based models are more susceptible to deception by these adversarial points. We also investigated the impact of the distance and angle of the added adversarial points on the attack success rate. Typically, the farther the victim object to be hidden and the closer to the front of the LiDAR, the higher the attack success rate. Additionally, we have experimentally proven that our generated adversarial points possess good cross-model adversarial transferability and validated the effectiveness of our proposed optimization method through ablation studies. Furthermore, we propose a new plug-and-play, model-agnostic defense method based on the concept of point smoothness. The ROC curve of this defense method shows an AUC value of approximately 0.909, demonstrating its effectiveness.

Abstract Background The unfolding protein response is a critical biological process implicated in a variety of physiological functions and disease states across eukaryotes. Despite its significance, the role and underlying mechanisms of the response in the context of ischemic stroke remain elusive. Hence, this study endeavors to shed light on the mechanisms and role of the unfolding protein response in the context of ischemic stroke. Methods In this study, mRNA expression patterns were extracted from the GSE58294 and GSE16561 datasets in the GEO database. The screening and validation of protein response-related biomarkers in stroke patients, as well as the analysis of the immune effects of the pathway, were carried out. To identify the key genes in the unfolded protein response, we constructed diagnostic models using both random forest and support vector machine-recursive feature elimination methods. The internal validation was performed using a bootstrapping approach based on a random sample of 1,000 iterations. Lastly, the target gene was validated by RT-PCR using clinical samples. We utilized two algorithms, CIBERSORT and MCPcounter, to investigate the relationship between the model genes and immune cells. Additionally, we performed uniform clustering of ischemic stroke samples based on expression of genes related to the UPR pathway and analyzed the relationship between different clusters and clinical traits. The weighted gene co-expression network analysis was conducted to identify the core genes in various clusters, followed by enrichment analysis and protein profiling for the hub genes from different clusters. Results Our differential analysis revealed 44 genes related to the UPR pathway to be statistically significant. The integration of both machine learning algorithms resulted in the identification of 7 key genes, namely ATF6, EXOSC5, EEF2, LSM4, NOLC1, BANF1, and DNAJC3. These genes served as the foundation for a diagnostic model, with an area under the curve of 0.972. Following 1000 rounds of internal validation via randomized sampling, the model was confirmed to exhibit high levels of both specificity and sensitivity. Furthermore, the expression of these genes was found to be linked with the infiltration of immune cells such as neutrophils and CD8 T cells. The cluster analysis of ischemic stroke samples revealed three distinct groups, each with differential expression of most genes related to the UPR pathway, immune cell infiltration, and inflammatory factor secretion. The weighted gene co-expression network analysis showed that all three clusters were associated with the unfolded protein response, as evidenced by gene enrichment analysis and the protein landscape of each cluster. The results showed that the expression of the target gene in blood was consistent with the previous analysis. Conclusion The study of the relationship between UPR and ischemic stroke can help to better understand the underlying mechanisms of the disease and provide new targets for therapeutic intervention. For example, targeting the UPR pathway by blocking excessive autophagy or inducing moderate UPR could potentially reduce tissue injury and promote cell survival after ischemic stroke. In addition, the results of this study suggest that the use of UPR gene expression levels as biomarkers could improve the accuracy of early diagnosis and prognosis of ischemic stroke, leading to more personalized treatment strategies. Overall, this study highlights the importance of the UPR pathway in the pathology of ischemic stroke and provides a foundation for future studies in this field.

Abstract Interlayer decoupling plays an essential role in realizing unprecedented properties in atomically thin materials, but it remains relatively unexplored in the bulk. It is unclear how to realize a large crystal that behaves as its monolayer counterpart by artificial manipulation. Here, we construct a superlattice consisting of alternating layers of NbSe2 and highly porous hydroxide, as a proof of principle for realizing interlayer decoupling in bulk materials. In (NaOH)0.5NbSe2, the electric decoupling is manifested by an ideal 1D insulating state along the interlayer direction. Vibration decoupling is demonstrated through the absence of interlayer models in the Raman spectrum, dominant local modes in heat capacity, low interlayer coupling energy and out-of-plane thermal conductivity (0.28 W/mK at RT) that are reduced to a few percent of NbSe2’s. Consequently, a drastic enhancement of CDW transition temperature (>110 K) and Pauling-breaking 2D superconductivity is observed, suggesting that the bulk crystal behaves similarly to an exfoliated NbSe2 monolayer. Our findings provide a route to achieve intrinsic 2D properties on a large-scale without exfoliation.

Muscle-invasive urothelial cancer (MUC), characterized by high aggressiveness and significant heterogeneity, is currently lacking highly precise individualized treatment options. We used a computational pipeline to synthesize multiomics data from MUC patients using 10 clustering algorithms, which were then combined with 10 machine learning algorithms to identify molecular subgroups of high resolution and develop a robust consensus machine learning-driven signature (CMLS). Through multiomics clustering, we identified three cancer subtypes (CSs) that are related to prognosis, with CS2 exhibiting the most favorable prognostic outcome. Subsequent screening enabled identification of 12 hub genes that constitute a CMLS with robust predictive power for prognosis. The low-CMLS group exhibited a more favorable prognosis and greater responsiveness to immunotherapy and was more likely to exhibit the “hot tumor” phenotype. The high-CMLS group had a poor prognosis and lower likelihood of benefitting from immunotherapy, but dasatinib and romidepsin may serve as promising treatments for them. Comprehensive analysis of multiomics data can offer important insights and further refine the molecular classification of MUC. Identification of CMLS represents a valuable tool for early prediction of patient prognosis and for screening potential candidates likely to benefit from immunotherapy, with broad implications for clinical practice.

Astaxanthin (Ax) and lutein are important fat-soluble pigments and essential nutrients for human and animal health. Haematococcus pluvialis microalga and Phaffia rhodozyma yeast are ideal species for commercial Ax production. Marigold flowers are a main source of commercial lutein. Dynamics of dietary Ax and lutein in the gastrointestinal tract are similar to lipids, but their activities are tremendously challenged by many physiological and dietary factors; few data are available about these in poultry. Dietary Ax and lutein have insignificant effects on egg production and egg physical properties, but have pronounced effects on yolk color, nutrition, and functionality. The two pigments can also enhance antioxidative capacity and immune function of laying hens. A few studies have shown that Ax and lutein can improve fertilization and hatchability of laying hens. Considering the pigmentation and health benefits of Ax and lutein from hen feed to human food, the commercial availability, chicken yolk improvement, and immune function of Ax and lutein are the focuses of this review. The potential roles of carotenoids in the cytokine storm and gut microbiota are also briefly presented. The bioavailability, metabolism, and deposition of Ax and lutein in laying hens are suggested for future research.

Abstract Objectives A classification system for endocervical adenocarcinoma (ECA) based on high‐risk human papillomavirus (HPV) status has been established; however, the immunohistochemical markers distinguishing HPV‐independent and HPV‐associated ECAs have not been fully described. Here, we aimed to characterize ECA immunopathological features. Methods We evaluated the immunohistochemical profile of CLDN18, CDX2, PAX8, p16, p53, and CEA in 60 ECAs comprising 10 HPV‐independent ECAs and 50 HPV‐associated ECAs. Both the membranous and nuclear expression levels of CLDN18 were analyzed. Results Membranous CLDN18 (CLDN18 [M]) was found to be expressed in the mucinous epithelium of all HPV‐independent ECAs, including eight gastric‐type ECAs (G‐ECAs), one endometrioid ECA, and one clear cell ECA, but no nuclear CLDN18 (CLDN18 [N]) expression was detected in HPV‐independent ECAs. Among HPV‐associated ECAs, CLDN18 (M) expression levels in intestinal‐type (I‐ECAs) and usual‐type ECAs (U‐ECAs) were significantly different from those in invasive stratified mucin‐producing (iSMILE) carcinomas (p = 0.036). Positive CLDN18 (M) staining was present in 55.6% (5/9) of intestinal‐type and 39.4% (13/33) of usual‐type ECAs and was not present in iSMILE ECAs. Silva pattern C cancers expressed higher levels of CLDN18 (M) than Silva pattern A and B cancers (p = 0.004), whereas the CLDN18 (N) expression levels in cancers showing Silva pattern A were significantly higher than those in cancers exhibiting Silva patterns B and C (p

Abstract Background Metastasis is a major determinant of death in patients with hepatocellular carcinoma (HCC). Dissecting key molecular mediators that promote this malignant feature may help yield novel therapeutic insights. Here, we investigated the role of E-twenty-six transformation-specific variant 1 (ETV1), a member of the E-twenty-six transformation-specific (ETS) family, in HCC metastasis. Methods The clinical significance of ETV1 and its target genes in two independent cohorts of HCC patients who underwent curative resection were assessed by Kaplan–Meier analysis and Multivariate Cox proportional hazards model. Luciferase reporter assay and chromatin immunoprecipitation assay were used to detect the transcriptional regulation of target gene promoters by ETV1. The effect of ETV1 on invasiveness and metastasis of HCC were detected by transwell assays and the orthotopically metastatic model. Results ETV1 expression was frequently elevated in human HCC specimens. Increased ETV1 expression was associated with the malignant biological characteristics and poor prognosis of HCC patients. ETV1 facilitated invasion and metastasis of HCC cells in vitro and in vivo. Mechanistically, ETV1 promoted HCC metastasis via upregulating metastasis-related genes, including protein tyrosine kinase 2 (PTK2) and MET. Down-regulated the expression of PTK2 or tyrosine protein kinase Met (c-MET) decreased ETV1-mediated HCC metastasis. Hepatocyte growth factor (HGF) upregulated ETV1 expression through activating c-MET-ERK1/2-ELK1 pathway. Notably, in two independent cohorts, patients with positive coexpression of ETV1/PTK2 or ETV1/c-MET had worse prognosis. Furthermore, the combination of PTK2 inhibitor defactinib and c-MET inhibitor capmatinib significantly suppressed HCC metastasis induced by ETV1. Conclusion This study uncovers functional and prognostic roles for ETV1 in HCC and exposes a positive feedback loop of HGF-ERK1/2-ETV1-c-MET. Targeting this pathway may provide a potential therapeutic intervention for ETV1-overexpressing HCC.

In the past decade, research on ultrasound therapy in obstetrics and gynecology has rapidly developed. Currently, high-intensity ultrasound has been widely used in clinical practice, while low-intensity ultrasound has gradually emerged as a new trend of transitioning from pre-clinical research to clinical applications. Low-intensity pulsed ultrasound (LIPUS), characterized by a non-invasive low-intensity pulse wave stimulation method, employs its non-thermal effects to achieve safe, economical, and convenient therapeutic outcomes. LIPUS converts into biochemical signals within cells through pathways such as cavitation, acoustic flow, and mechanical stimulation, regulating molecular biological mechanisms and exerting various biological effects. The molecular biology mechanisms underlying the application of LIPUS in obstetrics and gynecology mainly include signaling pathways, key gene expression, angiogenesis, inflammation inhibition, and stem cell differentiation. LIPUS plays a positive role in promoting soft tissue regeneration, bone regeneration, nerve regulation, and changes in cell membrane permeability. LIPUS can improve the treatment benefit of premature ovarian failure, pelvic floor dysfunction, nerve damage caused by intrauterine growth restriction, ovariectomized osteoporosis, and incomplete uterine involution through the above biological effects, and it also has application value in the adjuvant treatment of malignant tumors such as ovarian cancer and cervical cancer. This study outlines the biological mechanisms and applications of LIPUS in treating various obstetric and gynecologic diseases, aiming to promote its precise application and provide a theoretical basis for its use in the field.

The MASSIVE dataset is a spoken-language comprehension resource package for slot filling, intent classification, and virtual assistant evaluation tasks. It contains multi-language utterances from human beings communicating with a virtual assistant. In this paper, we exploited the relationship between intent classification and slot filling to improve the exact match accuracy by proposing five models with hierarchical and bidirectional architectures. There are two variants for hierarchical architectures and three variants for bidirectional architectures. These are the hierarchical concatenation model, the hierarchical attention-based model, the bidirectional max-pooling model, the bidirectional LSTM model, and the bidirectional attention-based model. The results of our models showed a significant improvement in the averaged exact match accuracy. The hierarchical attention-based model improved the accuracy by 1.01 points for the full training dataset. As for the zero-shot setup, we observed that the exact match accuracy increased from 53.43 to 53.91. In this study, we observed that, for multi-task problems, utilizing the relevance between different tasks can help in improving the model’s overall performance.

Disruption risks exacerbate the complexity of low-carbon supply chain network design in an uncertain supply chain environment. Considering the low frequency and non-repeatability of these disruption events makes it impossible to collect data to obtain their probabilities. In this study, supply disruptions were regarded as uncertain events; supply chain uncertain disruption risk is defined and quantified based on the uncertainty theory, in which uncertain disruptions are characterized by the belief degree on account of expert estimation with duality, i.e., symmetry. Optimization models were constructed with the objective of minimizing expected carbon emissions and costs, which optimizes the selection of suppliers with uncertain disruptions, and the assignment of manufacturers and customers. The properties of the model were analyzed, and the models were solved separately using different methods according to different decision criteria. Finally, the validity of the proposed models and algorithm were verified using a real case study of a glass manufacturing company. The findings exhibit promising insights for designing a sustainable and resilient supply chain network in an uncertain environment.

Abstract Background N6-methyladenosine (m6A) modification is the most common chemical modification in mammalian mRNAs, and it plays important roles by regulating several cellular processes. Previous studies report that m6A is implicated in modulating tumorigenesis and progression. However, dysregulation of m6A modification and effect of m6A demethylase fat-mass and obesity-associated protein (FTO) on glucose metabolism has not been fully elucidated in papillary thyroid cancer (PTC). Methods Quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry were performed to explore the expression profile of FTO in PTC tissues and adjacent non-cancerous thyroid tissues. Effects of FTO on PTC glycolysis and growth were investigated through in vitro and in vivo experiments. Mechanism of FTO-mediated m6A modification was explored through transcriptome-sequencing (RNA-seq), methylated RNA immunoprecipitation sequencing (MeRIP-seq), MeRIP-qPCR, luciferase reporter assays, RNA stability assay and RNA immunoprecipitation assay. Results FTO expression was significantly downregulated in PTC tissues. Functional analysis showed that FTO inhibited PTC glycolysis and growth. Further analyses were conducted to explore FTO-mediated m6A modification profile in PTC cells and Apolipoprotein E (APOE) was identified as the target gene for FTO-mediated m6A modification using RNA-seq and MeRIP-seq. FTO knockdown significantly increased APOE mRNA m6A modification and upregulated its expression. FTO-mediated m6A modification of APOE mRNA was recognized and stabilized by the m6A reader IGF2BP2. The findings showed that APOE also promoted tumor growth through glycolysis in PTC. Analysis showed that FTO/APOE axis inhibits PTC glycolysis by modulating IL-6/JAK2/STAT3 signaling pathway. Conclusion FTO acts as a tumor suppressor to inhibit tumor glycolysis in PTC. The findings of the current study showed that FTO inhibited expression of APOE through IGF2BP2-mediated m6A modification and may inhibit glycolytic metabolism in PTC by modulating IL-6/JAK2/STAT3 signaling pathway, thus abrogating tumor growth.

Wumei San (WMS) is a traditional Chinese medicine that has been widely applied in the treatment of piglet diarrhea (PD). However, the mechanism of WMS in PD has not been investigated. In this study, the main active compounds of WMS and the target proteins were obtained from the Traditional Chinese Medicine Systematic Pharmacology, PubChem, and SwissTargetPrediction databases. The molecular targets of PD were identified using GeneCards, OMIM, and NCBI databases. The common targets of WMS and PD were screened out and converted into UniProt gene symbols. PD-related target genes were constructed into a protein-protein interaction network, which was further analyzed by the STRING online database. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to construct the component-target gene-disease network. Molecular docking was then used to examine the relationship between the core compounds and proteins. As a result, a total of 32 active compounds and 638 target genes of WMS were identified, and a WMS-compound-target network was successfully constructed. Through network pharmacology analysis, 14 core compounds in WMS that showed an effect on PD were identified. The targets revealed by GO and KEGG enrichment analysis were associated with the AGE-RAGE signaling pathway, PI3K-Akt signaling pathway, TNF signaling pathway, NOD-like receptor signaling pathway, IL-17 signaling pathway, and other pathways and physiological processes. Molecular docking analysis revealed that the active compounds in WMS spontaneously bind to their targets. The results indicated that WMS may regulate the local immune response and inflammatory factors mainly through the TNF signaling pathway, IL-17 signaling pathway, and other pathways. WMS is a promising treatment strategy for PD. This study provides new insights into the potential mechanism of WMS in PD.

PurposeTo analyze and predict the possibility of visual field (VF) recovery after endoscopic transsphenoidal surgery (ETSS) in patients with pituitary adenoma, we investigated the factors affecting the improvement of the visual field defect (VFD) and built a nomogram predictive model based on these risk factors. We further investigated specific recovery regions of VF associated with the improvement of VFD.MethodsThe clinical data of patients who underwent ETSS for pituitary adenomas at a single center between the January 2021 and April 2022 were retrospectively analyzed. Univariate and multivariate analyses were used to determine the predictive factors affecting the improvement in the VF defect and specific recovery regions in patients with pituitary adenomas after ETSS.ResultsWe enrolled 28 patients (56 eyes) who were hospitalized at our institution. Four clinical features, including compression of the optic chiasm, preoperative mean defect (MD), diffuse defect, and duration of the visual symptom, were chosen from the least absolute shrinkage and selection operator regression analysis to establish the predictive nomogram. The nomogram’s area under the curve (AUC) was 0.912, indicating a good degree of differentiation. A calibration plot was used to evaluate the predictive model’s calibration, and a decision curve was used to evaluate its clinical application value. The VF defects were improved in the 270–300° range (270–300: RR = 361.00, 95% CI: 21.01–6,202.41).ConclusionWe developed a predictive nomogram model based on significant visual field improvement-associated factors after ETSS in patients with pituitary adenoma. Postoperative visual field improvement is likely to begin at 270–300° in the inferior temporal quadrant. This improvement would enable personalized counselling for individual patients by precisely predicting the visual field recovery after surgery.

Background: Cuproptosis is a newly defined form of cell death, whether cuproptosis involved in hepatocellular carcinoma (HCC) remains elusive.Method: We obtained patients’ RNA expression data and follow-up information from University of California Santa Cruz (UCSC) and The Cancer Genome Atlas (TCGA). We analyzed the mRNA level of Cuproptosis-related genes (CRGs) and performed univariate Cox analysis. Liver hepatocellular carcinoma (LIHC) was chosen for further investigation. Real-Time quantitative PCR (RT-qPCR), Western blotting (WB), Immunohistochemical (IHC), and Transwell assays were used to determine expression patterns and functions of CRGs in LIHC. Next, we identified CRGs-related lncRNAs (CRLs) and differentially expressed CRLs between HCC and normal cases. Univariate Cox analysis, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to construct the prognostic model. Univariate and multivariate Cox analysis was used to assess whether the risk model can act as an independent risk factor of overall survival duration. Different risk groups performed immune correlation analysis, tumor mutation burden (TMB), and Gene Set Enrichment Analysis (GSEA) analysis were performed in different risk groups. Finally, we assessed the performance of the predictive model in drug sensitivity.Results: CRGs expression levels have significant differences between tumor and normal tissues. High expression of Dihydrolipoamide S-Acetyltransferase (DLAT) correlated to metastasis of HCC cells and indicated poor prognosis for HCC patients. Our prognostic model consisted of four cuproptosis-related lncRNA (AC011476.3, AC026412.3, NRAV, MKLN1-AS). The prognostic model performed well in predicting survival rates. The results from Cox regression analysis suggested that risk score can serve as an independent prognostic element for survival durations. Survival analysis revealed that low risk patients have extended survival periods compared with those with high risk. The results of the immune analysis indicated that risk score has a positive correlation with B cell and CD4+ T cell Th2, while has a negative relationship with endothelial cell and hematopoietic cells. Besides, immune checkpoint genes have higher expression folds in the high-risk set than in the low-risk set. The high-risk group had higher rates of genetic mutation than the low-risk set while having a shorter survival time. GSEA revealed the signaling pathways enriched in the high-risk group were mostly immune-related, while metabolic-related pathways were enriched in the low-risk group. Drugs sensitivity analysis indicated that our model has the ability to predict the efficacy of clinical treatment.Conclusion: The Cuproptosis-related lncRNAs prognostic formula is a novel predictor of HCC patients’ prognosis and drug sensitivity.

IntroductionNecroptosis, a type of programmed cell death, has recently been extensively studied as an important pathway regulating tumor development, metastasis, and immunity. However, the expression patterns of necroptosis-related genes (NRGs) in colorectal cancer (CRC) and their potential roles in the tumor microenvironment (TME) have not been elucidated.MethodsWe explored the expression patterns of NRGs in 1247 colorectal cancer samples from genetics and transcriptional perspective. Based on a consensus clustering algorithm, we identified NRG molecular subtypes and gene subtypes, respectively. Furthermore, we constructed a necroptosis-related signature for predicting overall survival time and verified the predictive ability of the model. Using the ESTIMATE, CIBERSORT, and ssGSEA algorithms, we assessed the association between the above subtypes, scores and immune infiltration. ResultsMost NRGs were differentially expressed between CRC tissues and normal tissues. We found that distinct subtypes exhibited different NRGs expression, patients’ prognosis, immune checkpoint gene expression, and immune infiltration characteristics. The scores calculated from the necroptosis-related signature can be used to classify patients into high-risk and low-risk groups, with the high-risk group corresponding to reduced immune cell infiltration and immune function, and a greater risk of immune dysfunction and immune escape. DiscussionOur comprehensive analysis of NRGs in CRC demonstrated their potential role in clinicopathological features, prognosis, and immune infiltration in the TME. These findings help us deepen our understanding of NRGs and the tumor microenvironment landscape, and lay a foundation for effectively assessing patient outcomes and promoting more effective immunotherapy.

Abstract Metastasis is the predominant reason for high mortality of hepatocellular carcinoma (HCC) patients. It is critical to explore the molecular mechanism underlying HCC metastasis. Here, we reported that transcription factor One Cut homeobox 2 (ONECUT2) functioned as an oncogene to facilitate HCC metastasis. Elevated ONECUT2 expression was positively correlated with increased tumor number, tumor encapsulation loss, microvascular invasion, poor tumor differentiation, and advanced TNM stage. Mechanistically, ONECUT2 directly bound to the promoters of fibroblast growth factor 2 (FGF2) and ATP citrate lyase (ACLY) and transcriptionally upregulated their expression. Knockdown of FGF2 and ACLY inhibited ONECUT2-mediated HCC metastasis, whereas upregulation of FGF2 and ACLY rescued ONECUT2 knockdown-induced suppression of HCC metastasis. ONECUT2 expression was positively correlated with FGF2 and ACLY expression in human HCC tissues. HCC patients with positive coexpression of ONECUT2/FGF2 or ONECUT2/ACLY exhibited the worst prognosis. In addition, FGF2 upregulated ONECUT2 expression through the FGFR1/ERK/ELK1 pathway, which formed an FGF2-FGFR1-ONECUT2 positive feedback loop. Knockdown of ONECUT2 inhibited FGF2-induced HCC metastasis. Furthermore, the combination of FGFR1 inhibitor PD173074 with ACLY inhibitor ETC-1002 markedly suppressed ONECUT2-mediated HCC metastasis. In summary, ONECUT2 was a potential prognostic biomarker in HCC and targeting this oncogenic signaling pathway may provide an efficient therapeutic strategy against HCC metastasis.

The GRAS gene family is a plant-specific family of transcription factors and play a vital role in many plant growth processes and abiotic stress responses. Nevertheless, the functions of the GRAS gene family in woody plants, especially in Betula platyphylla (birch), are hardly known. In this study, we performed a genome-wide analysis of 40 BpGRAS genes (BpGRASs) and identified typical GRAS domains of most BpGRASs. The BpGRASs were unevenly distributed on 14 chromosomes of birch and the phylogenetic analysis of six species facilitated the clustering of 265 GRAS proteins into 17 subfamilies. We observed that closely related GRAS homologs had similar conserved motifs according to motif analysis. Besides, an analysis of the expression patterns of 26 BpGRASs showed that most BpGRASs were highly expressed in the leaves and responded to salt stress. Six BpGRASs were selected for cis-acting element analysis because of their significant upregulation under salt treatment, indicating that many elements were involved in the response to abiotic stress. This result further confirmed that these BpGRASs might participate in response to abiotic stress. Transiently transfected birch plants with transiently overexpressed 6 BpGRASs and RNAi-silenced 6 BpGRASs were generated for gain- and loss-of-function analysis, respectively. In addition, overexpression of BpGRAS34 showed phenotype resistant to salt stress, decreased the cell death and enhanced the reactive oxygen species (ROS) scavenging capabilities and proline content under salt treatment, consistent with the results in transiently transformed birch plants. This study is a systematic analysis of the GRAS gene family in birch plants, and the results provide insight into the molecular mechanism of the GRAS gene family responding to abiotic stress in birch plants.

Background: Necroptosis, a type of programmed cell death, has been implicated in a variety of cancer-related biological processes. However, the roles of necroptosis-related genes in thyroid cancer yet remain unknown.Methods: A necroptosis-related gene signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis. The predictive value of the prognostic signature was validated in an internal cohort. Additionally, the single-sample gene set enrichment analysis (ssGSEA) was used to examine the relationships between necroptosis and immune cells, immunological functions, and immune checkpoints. Next, the modeled genes expressions were validated in 96 pairs of clinical tumor and normal tissue samples. Finally, the effects of modeled genes on PTC cells were studied by RNA interference approaches in vitro.Results: In this study, the risk signature of seven necroptosis-related genes was created to predict the prognosis of papillary thyroid cancer (PTC) patients, and all patients were divided into high- and low-risk groups. Patients in the high-risk group fared worse in terms of overall survival than those in the low-risk group. The area under the curve (AUC) of the receiving operating characteristic (ROC) curves proved the predictive capability of created signature. The risk score was found to be an independent risk factor for prognosis in multivariate Cox analysis. The low-risk group showed increased immune cell infiltration and immunological activity, implying that they might respond better to immune checkpoint inhibitor medication. Next, GEO database and qRT-PCR in 96 pairs of matched tumorous and non-tumorous tissues were used to validate the expression of the seven modeled genes in PTCs, and the results were compatible with TCGA database. Finally, overexpression of IPMK, KLF9, SPATA2 could significantly inhibit the proliferation, invasion and migration of PTC cells.Conclusion: The created necroptosis associated risk signature has the potential to have prognostic capability in PTC for patient outcome. The findings of this study could pave the way for further research into the link between necroptosis and tumor immunotherapy.

Background: Multiple targeted therapeutics are available for radioiodine-refractory differentiated thyroid cancer (RAIR-DTC), but it remains unclear which treatment is optimal to achieve long-term survival.Methods: A systematic search of the PubMed, Embase, and ClinicalTrials.gov databases was conducted to identify eligible randomized controlled trials (RCTs) comparing the efficacy and safety of targeted treatments for patients with RAIR-DTC from inception to April, 2022. Data were extracted by following the recommendations of the Preferred Reporting Items for Systematic Review and Meta-analysis guidelines. We calculated the odds ratio (OR) or hazard ratio (HR), its corresponding 95% credible intervals (CrI), and the surface under the cumulative ranking curve (SUCRA) to indicate ranking probability using Bayesian network meta-analyses. The primary outcome was progression-free survival (PFS). The secondary outcomes were overall survival (OS), objective response rate (ORR), disease control rate (DCR), and grade 3 or higher adverse events.Results: A total of 12 eligible RCTs involved 1,959 patients and 13 treatments: apatinib, cabozantinib, anlotinib, nintedanib, lenvatinib, lenvatinib with low dose (LD), sorafenib, sorafenib plus everolimus, donafenib (200 mg), donafenib (300 mg), pazopanib (continuous), pazopanib (intermittent), and vandetanib. Pooled analyses indicated that targeted therapeutics significantly prolonged PFS and OS in patients with RAIR-DTC (0.31, 0.21–0.41; 0.69, 0.53–0.85, respectively) compared with placebo. Network meta-analyses indicated that lenvatinib showed the most favorable PFS, with significant differences versus sorafenib (0.33, 0.23-0.48), vandetanib (0.31, 0.20–0.49), nintedanib (0.30, 0.15–0.60), and placebo (0.19, 0.15–0.25), while apatinib was most likely to be ranked first for prolonging OS with a SUCRA of 0.90. Lenvatinib showed the highest ORR (66%, 61%–70%), followed by anlotinib (59%, 48%–70%) and apatinib (54%, 40%–69%). Lenvatinib caused the most adverse events of grade 3 or higher, followed by lenvatinib (LD) and apatinib. Different toxicity profiles of individual treatment were also revealed.Conclusion: This network meta-analysis suggests that lenvatinib and apatinib were associated with the best progression-free survival and overall survival benefits, respectively, for patients with RAIR-DTC, compared with other targeted therapeutics. Patients who received lenvatinib or apatinib also had more grade 3 or higher adverse events.Systematic Review Registration: [https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=302249], identifier [CRD42022302249].

Pregnancy toxemia is a nutritional metabolic disease during late gestation in small ruminants. The condition is characterized by disorders in carbohydrate and fat metabolism. Obese and multiparous ewes are particularly susceptible to pregnancy toxemia, which may lead to maternal death, abortion, or premature birth. Highly productive multiparous meat ewes are major breeding animals, which has led to an increased incidence of the disease. However, the pathogenesis of pregnancy toxemia remains unclear and adequate disease prevention and treatment strategies are absent. Investigating the pathogenesis of pregnancy toxemia, especially the metabolic pathways of hepatic lipids, is key to an improved understanding of the condition. This review provides a snapshot of the genes that are associated with lipid metabolism in the ovine liver, including genes involved in fatty acid oxidation, acetyl coenzyme metabolism, and triglyceride synthesis; describes the interrelationships between these genes; and summarizes the diagnosis, prevention, and treatment of pregnancy toxemia.

The water-sediment regulation scheme (WSRS) of dams influences the desorption, resuspension, and deposition processes of riparian sediments, which in turn affect the spatial-temporal variations of heavy metals (HMs) in riparian sediments and leads to severe degradation of soil and water quality. However, the difference between the trapping effect of dams and the redistribution effects of the WSRS on HMs in riparian sediments, as well as the consecutively seasonal change of HMs after the WSRS, are rarely reported. To fill this gap, the concentrations of six HMs including Cd, Cr, Cu, Ni, Pb, and Zn in riparian sediments along the Xiaolangdi Dam (XLD) Reservoir and its downstream reach were investigated, and the contamination level and potential ecological risk of HMs were assessed, to differentiate the effects of the XLD and its WSRS on the concentration, contamination level, and potential ecological risks of HMs. The results indicated that the mean HM concentrations in riparian sediments were higher than the background values in the study area and showed significant spatial and temporal variations. However, the regional differences of HM concentrations caused by the trapping effect of the XLD were less than the seasonal differences caused by the redistribution effects of the WSRS. The contamination and ecological risk assessment indicated that riparian sediments in the study area were contaminated by the six HMs, particularly by Cd and Pb, which overall exhibited a high and moderate ecological risk, respectively. The sources for Pb were likely agricultural inputs, while the sources for Cd should be attributed to both industrial and agricultural inputs. Overall, the trapping effect of the XLD led to the accumulation of HMs in riparian sediments along the reservoir area, while the regulation effects of the WSRS resulted in the redistribution of HMs in riparian sediments from the reservoir area to the downstream reach.

The tumor microenvironment (TME) is mainly composed of tumor cells, tumor-infiltrating immune cells, and stromal components. It plays an essential role in the prognosis and therapeutic response of patients. Nonetheless, the TME landscape of urothelial cancer (UC) has not been fully elucidated. In this study, we systematically analyzed several UC cohorts, and three types of TME patterns (stromal-activation subtype, immune-enriched subtype and immune-suppressive subtype) were defined. The tumor microenvironment signature (TMSig) was constructed by modified Lasso penalized regression. Patients were stratified into high- and low-TMSig score groups. The low-score group had a better prognosis (p < 0.0001), higher M1 macrophage infiltration (p < 0.01), better response to immunotherapy (p < 0.05), and more similar molecular characteristics to the luminal (differentiated) subtype. The accuracy of the TMSig for predicting the immunotherapy response was also verified in three independent cohorts. We highlighted that the TMSig is an effective predictor of patient prognosis and immunotherapy response. Quantitative evaluation of a single sample is valuable for us to combine histopathological and molecular characteristics to comprehensively evaluate the status of the patient. Targeted macrophage treatment has great potential for the individualized precision therapy of UC patients.

Train speed is increasing due to the development of high-speed railway technology. However, high-speed trains generate more noise and discomfort for residents, enclosed housing for sound emission alleviation is needed to further reduce noise. Because these enclosed housings for sound emission alleviation restrain the air flow, strong and complicated aerodynamic pressures are generated inside the housing for sound emission alleviation when a train passes through at a high speed. This train-induced aerodynamic pressure, particularly its dynamic characteristics, is a key parameter in structural design. In the present study, the train-induced unsteady aerodynamic pressure in an enclosed housing for sound emission alleviation is simulated using the dynamic mesh method, and the dynamic characteristics of the aerodynamic pressure are investigated. The simulation results show that when the train is running in the enclosed housing for sound emission alleviation, the unsteady aerodynamic pressure is complicated and aperiodic, and after the train leaves the housing for sound emission alleviation, the aerodynamic pressure reverts to periodic decay curves. Two new terms, the duration of the extreme aerodynamic pressure and the pressure change rate, are proposed to evaluate the dynamic characteristics when the train passes through the barrier. The dominant frequency and decay rate are adopted to express the dynamic characteristics after the train exits. When the train runs in the enclosed housing for sound emission alleviation, the longest durations of the positive and negative extreme aerodynamic pressures are in the middle section, and the maximum change rate of aerodynamic pressure occurs at the entrance area. After the train exits the housing for sound emission alleviation, the pressure amplitude at the central region is always higher than those close to the entrance/exit. The dominant frequency of the aerodynamic pressure is identified and explained using wave propagation theory, the decay rate of the aerodynamic pressure at all sections is close.

Impact cratering process is the major geologic activity on the surface of the Moon, and the spatial distribution and size-frequency distribution of lunar craters are indicative to the bombardment history of the Solar System. The substantial efforts on the development of automated crater detection algorithms (CDAs) have been carried out on the images from the remote sensing observations. Recently, CDAs via convolutional neural network (CNN) on digital elevation model (DEM) has been developed as it can combine the discrimination ability of CNN with the robust characteristic of the DEM data. However, most of the existing algorithms adopt a traditional two-stage detection pipeline including an edge segmentation and a template matching step. In this paper, we attempt to reduce the gap between the existing DEM-based CDAs and the advanced CNN methods for object detection, and propose a complete workflow including an end-to-end deep learning pipeline for lunar crater detection, in particular for craters smaller than 50 km in diameter. Based on the workflow, we benchmark nine representative CNN models involving three popular types of detection architectures. Moreover, we elaborate on the practical application of the proposed workflow, and provide an example method to demonstrate the performance advantage in terms of the precision (82.97%) and recall (79.39%). Furthermore, we develop a crater verification tool to manually validate the detection results, and the visualization results show that our detected craters are reasonable and can be used as a supplement to the existing hand-labeled datasets.