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Spinal ependymomas are the most common spinal cord tumors in adults, but their intratumoral cellular heterogeneity has been less studied, and how spinal microglia are involved in tumor progression is still unknown. Here, our single-cell RNA-sequencing analyses of three spinal ependymoma subtypes dissect the microenvironmental landscape of spinal ependymomas and reveal tumor-associated macrophage (TAM) subsets with distinct functional phenotypes. CCL2 + TAMs are related to the immune response and exhibit a high capacity for apoptosis, while CD44 + TAMs are associated with tumor angiogenesis. By combining these results with those of single-cell ATAC-sequencing data analysis, we reveal that TEAD1 and EGR3 play roles in regulating the functional diversity of TAMs. We further identify diverse characteristics of both malignant cells and TAMs that might underlie the different malignant degrees of each subtype. Finally, assessment of cell-cell interactions reveal that stromal cells act as extracellular factors that mediate TAM diversity. Overall, our results reveal dual functions of TAMs in tumor progression, providing valuable insights for TAM-targeting immunotherapy. The intratumoural heterogeneity of spinal ependymomas and the role of microglia in tumour progression remain underexplored. Here, the authors perform single-cell RNA- and ATAC-sequencing data analysis of three subtypes and reveal tumour-associated macrophage subsets with distinct functional phenotypes.

Background Tumor-reactive CD8+ tumor-infiltrating lymphocytes (TILs) represent a subtype of T cells that can recognize and destroy tumor specifically. Understanding the regulatory mechanism of tumor-reactive CD8+ T cells has important therapeutic implications. Yet the DNA methylation status of this T cell subtype has not been elucidated. Results In this study, we segregate tumor-reactive and bystander CD8+ TILs, as well as naïve and effector memory CD8+ T cell subtypes as controls from colorectal cancer patients, to compare their transcriptome and methylome characteristics. Transcriptome profiling confirms previous conclusions that tumor-reactive TILs have an exhausted tissue-resident memory signature. Whole-genome methylation profiling identifies a distinct methylome pattern of tumor-reactive CD8+ T cells, with tumor-reactive markers CD39 and CD103 being specifically demethylated. In addition, dynamic changes are observed during the transition of naïve T cells into tumor-reactive CD8+ T cells. Transcription factor binding motif enrichment analysis identifies several immune-related transcription factors, including three exhaustion-related genes ( NR4A1 , BATF , and EGR2 ) and VDR , which potentially play an important regulatory role in tumor-reactive CD8+ T cells. Conclusion Our study supports the involvement of DNA methylation in shaping tumor-reactive and bystander CD8+ TILs, and provides a valuable resource for the development of novel DNA methylation markers and future therapeutics.

Dry eye is among the most prevalent complications following refractive surgery, significantly impacting the training and daily lives of recruits. While recent years we have witnessed some advancements in understanding the occurrence and progression of dry eye, the specific effects of refractive surgery on this condition remain unclear. This study aims to investigate the impact of refractive surgery on dry eye among 300 army recruits. A series of examinations specific to dry eye were conducted on the subjects using the OSDI questionnaire and the ocular surface comprehensive analyzer. The correlation between refractive surgery and dry eye was analyzed in conjunction with dry eye symptoms and related data. Additionally, optical coherence tomography (OCT) was employed to observe fundus changes in dry eye patients, comparing those with low to moderate myopia against patients with high myopia prior to surgery. The morphology of the meibomian glands in the upper eyelid was assessed using the Keratograph 5M ocular surface analyzer, where the area of meibomian gland loss was calculated and scored, facilitating an exploration of the relationship between meibomian gland loss and dry eye. Furthermore, the dry eye detection rates of Non-Invasive Break-Up Time (NIBUT), Lipid Layer Thickness Measurement (LTMH), and basal Schirmer secretion (SIT) were calculated, and the diagnostic differences among these three methods for dry eye were analyzed. According to the OSDI questionnaire, 117 (39%) patients opted for SMILE, 60 (20%) for F-LASIK, and 123 (41%) for LASIK. Among the recruits, 78 (26%) were diagnosed with dry eye following refractive surgery. Single factor and multiple logistic regression analyses indicated that LASIK may serve as an independent risk factor for the development of dry eye after refractive surgery. Furthermore, the incidence of leopard-pattern fundus was significantly higher in recruits with high myopia compared to those with low to moderate myopia. Keratograph5M assessments revealed that 52.6% of patients exhibited no meibomian gland loss; 45.5% had meibomian gland loss of less than 1/3; 1.9% experienced meibomian gland loss ranging from 1/3 to 2/3; and no patients had meibomian gland loss exceeding 2/3. These results suggest that there is no direct relationship between dry eye and meibomian gland loss following refractive surgery. Additionally, the dry eye detection rate using non-invasive tear break-up time (NIBUT) was 92.6%, while the detection rate for LTMH dry eye was 91.0%. The basal Schirmer test (SIT) yielded a dry eye detection rate of 78.2%, indicating that non-invasive tear assessment methods have a higher detection rate for dry eye. The incidence of dry eye among recruits following excimer laser corneal refractive surgery is significantly higher than that observed with other surgical methods, suggesting that it may represent an independent risk factor for dry eye post-refractive surgery. Consequently, we do not recommend the use of laser in situ keratomileusis for refractive surgery.

Recent studies indicate that the stereo-ATI carrier-envelope phase meter (CEPM) is an effective method to determine the carrier-envelope phase (CEP) of each and every single few-cycle laser pulse. In this method, a two-dimensional parametric asymmetry plot (PAP), which can be obtained with the measured data in two short time-of-flight intervals, is applied to extract the CEP. Thus, part of the data containing useful CEP information is discarded in the PAP method. In this work, an improved method was developed to effectively exploit most of the experimental data. By this method, we achieve a CEP precision of 57 mrad over the entire 2π range for 5.0 fs laser pulses.

The tumor microenvironment (TME) considerably influences colorectal cancer (CRC) progression, therapeutic response and clinical outcome, but studies of interindividual heterogeneities of the TME in CRC are lacking. Here, by integrating human colorectal single-cell transcriptomic data from approximately 200 donors, we comprehensively characterized transcriptional remodeling in the TME compared to noncancer tissues and identified a rare tumor-specific subset of endothelial cells with T cell recruitment potential. The large sample size enabled us to stratify patients based on their TME heterogeneity, revealing divergent TME subtypes in which cancer cells exploit different immune evasion mechanisms. Additionally, by associating single-cell transcriptional profiling with risk genes identified by genome-wide association studies, we determined that stromal cells are major effector cell types in CRC genetic susceptibility. In summary, our results provide valuable insights into CRC pathogenesis and might help with the development of personalized immune therapies.

Due to the OPTIONAL operator, the core fragment of the SPARQL query language is non-monotonic. That is, some solutions of a query result can be returned to the user only after having consulted all relevant parts of the queried dataset(s). This property presents an obstacle when developing query execution approaches that aim to reduce responses times rather than the overall query execution times. Reducing the response times?i.e., returning as many solutions as early as possible? is important in particular in Web-based client-server query processing scenarios in which network latencies dominate query execution times. Such scenarios are typical in the context of integration of Web data sources where a data integration component executes queries over a decentralized federation of such data sources. In this paper we introduce an alternative operator that is similar in spirit to OPTIONAL but without causing non-monotonicity. We show fundamental properties of this operator and observe that the downside of achieving the desired monotonicity property is a potentially significant increase in query result sizes. We study the extend of this trade-off in practice.

Several studies were conducted to explore the prognostic value of platelet-to-lymphocyte ratio (PLR) in pancreatic cancer and have reported contradictory results. This study aims to summarize the prognostic role of PLR in pancreatic cancer. Embase, PubMed and Cochrane Library were completely searched. The cohort studies focusing on the prognostic role of PLR in pancreatic cancer were eligible. The overall survival (OS) and progression-free survival (PFS) were analyzed. Fifteen papers containing 17 cohort studies with pancreatic cancer were identified. The results showed patients that with low PLR might have longer OS when compared to the patients with high PLR (hazard ratio=1.28, 95% CI=1.17-1.40, <0.00001; =42%). Similar results were observed in the subgroup analyses of OS, which was based on the analysis model, ethnicity, sample size and cut-off value. Further analyses based on the adjusted potential confounders were conducted, including CA199, neutrophil-to-lymphocyte ratio, modified Glasgow Prognostic Score, albumin, C-reactive protein, Eastern Cooperative Oncology Group, stage, tumor size, nodal involvement, tumor differentiation, margin status, age and gender, which confirmed that low PLR was a protective factor in pancreatic cancer. In addition, low PLR was significantly associated with longer PFS when compared to high PLR in pancreatic cancer (hazard ratio=1.27, 95% CI=1.03-1.57, =0.03; =33%). In conclusion, it was found that high PLR is an unfavorable predictor of OS and PFS in patients with pancreatic cancer, and PLR is a promising prognostic biomarker for pancreatic cancer.

Energy disaggregation, known as Non-Intrusive Load Monitoring (NILM), is a practical approach to providing device-level electrical information and can be applied to enhance various scenarios in smart grids. In recent years, with the emergence of large-scale energy consumption datasets, a growing multitude of deep learning methods have been employed to address energy disaggregation problems. However, these methods face challenges in resolving the disaggregation of multi-state devices and devices with overlapping operation cycles, especially during startup and shutdown periods. This paper addresses these challenges by proposing a load disaggregation framework based on equipment operation state. Diverging from existing methods, the load disaggregation task in this paper is divided into two stages. The first stage primarily employs load recognition methods to detect and identify the state transition information of the target appliance. The second stage, based on the identified information from target appliance events, utilizes power filling and power correction methods to achieve load disaggregation. Additionally, a data augmentation method is introduced to alleviate the issue of insufficient sample quantity in the dataset, which hinders model training. Experimental comparisons are conducted on widely used public datasets in the NILM field, namely REDD, and UKDALE, against various state-of-the-art methods. The proposed method achieves an average Mean Absolute Error (MAE) of 3.331 for disaggregating multiple appliances, reducing approximately 38% compared to existing methods. These results robustly validate the advancement of the proposed approach in this paper.

Due to the OPTIONAL operator, the core fragment of the SPARQL query language is non-monotonic. That is, some solutions of a query result can be returned to the user only after having consulted all relevant parts of the queried dataset(s). This property presents an obstacle when developing query execution approaches that aim to reduce responses times rather than the overall query execution times. Reducing the response times–i.e., returning as many solutions as early as possible– is important in particular in Web-based client-server query processing scenarios in which network latencies dominate query execution times. Such scenarios are typical in the context of integration of Web data sources where a data integration component executes queries over a decentralized federation of such data sources. In this paper we introduce an alternative operator that is similar in spirit to OPTIONAL but without causing non-monotonicity. We show fundamental properties of this operator and observe that the downside of achieving the desired monotonicity property is a potentially significant increase in query result sizes. We study the extend of this trade-off in practice. Thereafter, we introduce different algorithms to implement the new operator and evaluate them regarding their potential to reduce response times. Keywords: Semantic web, linked data, query language, optimization.