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In the realm of conventional affordance detection, the primary objective is to provide insights into the potential uses of objects. However, a significant limitation remains as these conventional methods merely treat affordance detection as a semantic segmentation task, disregarding the crucial aspect of interpreting affordances for actions that can be performed by manipulator. To address this critical gap, we present a novel pipeline incorporating the Intelligent Action Library (IAL) concept. This framework enables affordance interpretation for various manipulation tasks, allowing robots to be taught and guided on how to execute specific actions based on the detected affordances and human-robot interaction. Through real-world experiments, we have demonstrated the ingenuity and dependability of our pipeline, effectively bridging the gap between affordance detection and manipulation task planning and execution. The integration of IAL facilitates a seamless connection between understanding affordances and empowering robots to perform tasks with precision and efficiency. The demo link is available to the public: https://youtu.be/_oBAer2Vl8k

Understanding the tissue-specific genetic controls of protein levels is essential to uncover mechanisms of post-transcriptional gene regulation. In this study, we generated a genomic atlas of protein levels in three tissues relevant to neurological disorders (brain, cerebrospinal fluid and plasma) by profiling thousands of proteins from participants with and without Alzheimer’s disease. We identified 274, 127 and 32 protein quantitative trait loci (pQTLs) for cerebrospinal fluid, plasma and brain, respectively. cis-pQTLs were more likely to be tissue shared, but trans-pQTLs tended to be tissue specific. Between 48.0% and 76.6% of pQTLs did not co-localize with expression, splicing, DNA methylation or histone acetylation QTLs. Using Mendelian randomization, we nominated proteins implicated in neurological diseases, including Alzheimer’s disease, Parkinson’s disease and stroke. This first multi-tissue study will be instrumental to map signals from genome-wide association studies onto functional genes, to discover pathways and to identify drug targets for neurological diseases. Yang et al. generated a genomic atlas of protein levels in brain, cerebrospinal fluid and plasma and used human genetics approaches to identify proteins implicated in neurological diseases as well as druggable targets.

Given the global prevalence of prostate cancer in men, it is crucial to explore more effective treatment strategies. Recently, immunotherapy has emerged as a promising cancer treatment due to its unique mechanism of action and potential long-term effectiveness. However, its limited efficacy in prostate cancer has prompted renewed interest in developing strategies to improve immunotherapy outcomes. Nanomedicine offers a novel perspective on cancer treatment with its unique size effects and surface properties. By employing targeted delivery, controlled release, and enhanced immunogenicity, nanoparticles can be synergized with nanomedicine platforms to amplify the effectiveness of immunotherapy in treating prostate cancer. Simultaneously, nanotechnology can address the limitations of immunotherapy and the challenges of immune escape and tumor microenvironment regulation. Additionally, the synergistic effects of combining nanomedicine with other therapies offer promising clinical outcomes. Innovative applications of nanomedicine include smart nanocarriers, stimulus-responsive systems, and precision medicine approaches to overcome translational obstacles in prostate cancer immunotherapy. This review highlights the transformative potential of nanomedicine in enhancing prostate cancer immunotherapy and emphasizes the need for interdisciplinary collaboration to drive research and clinical applications forward.

Osteosarcoma is the predominant primary malignant bone tumor that poses a significant global health challenge. MicroRNAs (miRNAs) that regulate gene expression are associated with osteosarcoma pathogenesis. Thus, miRNAs are potential therapeutic targets for osteosarcoma. Nanoparticles, widely used for targeted drug delivery, facilitate miRNA-based osteosarcoma treatment. Numerous studies have focused on miRNA delivery using nanoparticles to inhibit the progress of osteosarcoma. Polymer-based, lipid-based, inorganic-based nanoparticles and extracellular vesicles were used to deliver miRNAs for the treatment of osteosarcoma. They can be modified to enhance drug loading and delivery capabilities. Also, miRNA delivery was combined with traditional therapies, for example chemotherapy, to treat osteosarcoma. Consequently, miRNA delivery offers promising therapeutic avenues for osteosarcoma, providing renewed hope for patients. This review emphasizes the studies utilizing nanoparticles for miRNA delivery in osteosarcoma treatment, then introduced and summarized the nanoparticles in detail. And it also discusses the prospects for clinical applications.

Disseminated intravascular coagulation (DIC) is an acquired disorder characterized by systemic activation of blood coagulation, which can arise from various causes. Owing to its abrupt onset, rapid progression, and high mortality rate, DIC presents a major clinical challenge. Anticoagulant drugs, such as heparin or low-molecular-weight heparin, are the current gold standard of treatment; however, these interventions pose considerable bleeding risks. Thus, safer and more effective therapeutic strategies are urgently required. Owing to their strong anti-inflammatory and tissue repair capabilities, mesenchymal stem cell-derived exosomes (MSC-Exos) have gained considerable attention as novel therapeutic options for numerous disorders, including DIC. Their stability in diverse pathological states highlights their potential as promising candidates for DIC therapy. This review presents the latest insights on the pathogenesis of DIC and anti-inflammatory and anticoagulant properties of MSC-Exos. We aimed to elucidate the potential mechanisms by which MSC-Exos influence DIC pathogenesis. We speculate that MSC-Exos offer a multifaceted approach to DIC treatment by attenuating neutrophil extracellular trap formation, modulating M1/M2 macrophage polarization, altering Nrf2/NF-κB signalling pathway to downregulate pro-inflammatory factors, and correcting imbalances in the coagulation-fibrinolysis system through anticoagulant routes. This suggests that MSC-Exos are a potential paradigm in DIC therapy, offering novel targets and treatment modalities for DIC management.

The absence of a compiled large-scale catchment characteristics dataset is a key obstacle limiting the development of large-sample hydrology research in China. We introduce the first large-scale catchment attribute dataset in China. We compiled diverse data sources, including soil, land cover, climate, topography, and geology, to develop the dataset. The dataset also includes catchment-scale 31-year meteorological time series from 1990 to 2020 for each basin. Potential evapotranspiration time series based on Penman's equation are derived for each basin. The 4911 catchments included in the dataset cover all of China. We introduced several new indicators that describe the catchment geography and the underlying surface differently from previously proposed datasets. The resulting dataset has a total of 125 catchment attributes and includes a separate HydroMLYR (hydrology dataset for machine learning in the Yellow River Basin) dataset containing standardized weekly averaged streamflow for 102 basins in the Yellow River Basin. The standardized streamflow data should be able to support machine learning hydrology research in the Yellow River Basin. The dataset is freely available at https://doi.org/10.5281/zenodo.5729444 (Zhen et al., 2021). In addition, the accompanying code used to generate the dataset is freely available at https://github.com/haozhen315/CCAM-China-Catchment-Attributes-and-Meteorology-dataset (last access: 26 November 2021) and supports the generation of catchment characteristics for any custom basin boundaries. Compiled data for the 4911 basins covering all of China and the open-source code should be able to support the study of any selected basins rather than being limited to only a few basins.

The homeobox gene 5 ( ) encodes a transcription factor that regulates the embryonic development of the central nervous system. Notably, its expression pattern and prognostic role in glioma remain unelucidated. This study identified the relationship between HOXB5 and glioma by investigating expression data from The Cancer Genome Atlas and the Genotype Tissue Expression databases and validating the obtained data using the Chinese Glioma Genome Atlas database. Western blots were used to identify HOXB5 expression levels in glioma cells and clinical samples. Kaplan-Meier and multivariate Cox regression analyses were performed to assess the prognostic value of HOXB5. The key functions and signaling pathways related to HOXB5 were analyzed using GO, KEGG, and GSEA. Immune infiltration was calculated using the microenvironment cell populations-counter, estimate the proportion of immune and cancer, and ESTIMATE algorithms. The expression of HOXB5 was upregulated in glioma and generally increased with malignancy. HOXB5 was an independent prognostic factor for glioma patients. A nomogram was further built that integrated HOXB5, and it showed stratifying prediction accuracy and efficiency. HOXB5 was associated with the regulation of cell growth, endothelial cell growth, and the IL-6/JAK-STAT3 pathway, and was determined to possibly promote stomatal specimen enrichment and angiogenesis. HOXB5 protein is overexpressed in glioma and might serve as a good predictive factor of this disease.

Purpose. In our study, we aimed to screen the risk factors that affect overall survival (OS) and cancer-specific survival (CSS) in adult glioma patients and to develop and evaluate nomograms. Methods. Primary high-grade gliomas patients being retrieved from the surveillance, epidemiology and end results (SEER) database, between 2004 and 2015, then they randomly assigned to a training group and a validation group. Univariate and multivariate Cox analysis models were used to choose the variables significantly correlated with the prognosis of high-grade glioma patients. And these variables were used to construct the nomograms. Next, concordance index (C-index), calibration plot and receiver operating characteristics (ROCs) curve were used to evaluate the accuracy of the nomogram model. In addition, the decision curve analysis (DCA) was used to analyze the benefit of nomogram and prognostic indicators commonly used in clinical practice. Results. A total of 6395 confirmed glioma patients were selected from the SEER database, divided into training set (n =3166) and validation set (n =3229). Age at diagnosis, tumor grade, tumor size, histological type, surgical type, radiotherapy and chemotherapy were screened out by Cox analysis model. For OS nomogram, the C-index of the training set was 0.741 (95% CI: 0.751-0.731), and the validation set was 0.738 (95% CI: 0.748-0.728). For CSS nomogram, the C-index of the training set was 0.739 (95% CI: 0.749-0.729), and the validation set was 0.738 (95% CI: 0.748-0.728). The net benefit and net reduction in inverventions of nomograms in the decision curve analysis (DCA) was higher than histological type. Conclusions. We developed nomograms to predict 3- and 5-year OS rates and 3- and 5-year CSS rates in adult high-grade glioma patients. Both the training set and the validation set showed good calibration and validation, indicating the clinical applicability of the nomogram and good predictive results.

Despite tremendous efforts in the past decades, relationships among main avian lineages remain heavily debated without a clear resolution. Discrepancies have been attributed to diversity of species sampled, phylogenetic method and the choice of genomic regions13. Here we address these issues by analysing the genomes of363 bird species4 (218 taxonomic families, 92% of total). Using intergenic regions and coalescent methods, we present a well-supported tree but also a marked degree of discordance. The tree confirms that Neoaves experienced rapid radiation at or near the Cretaceous-Palaeogene boundary. Sufficient loci rather than extensive taxon sampling were more effective in resolving difficult nodes. Remaining recalcitrant nodes involve species that are a challenge to model due to either extreme DNA composition, variable substitution rates, incomplete lineage sorting or complex evolutionary events such as ancient hybridization. Assessment of the effects of different genomic partitions showed high heterogeneity across the genome. We discovered sharp increases in effective population size, substitution rates and relative brain size following the Cretaceous-Palaeogene extinction event, supporting the hypothesis that emerging ecological opportunities catalysed the diversification of modern birds. The resulting phylogenetic estimate offers fresh insights into the rapid radiation of modern birds and provides a taxon-rich backbone tree for future comparative studies.