Materials Advances in Photocatalytic Solar Hydrogen Production: Integrating Systems and Economics for a Sustainable Future.

Photocatalytic solar hydrogen generation, encompassing both overall water splitting and organic reforming, presents a promising avenue for green hydrogen production. This technology holds the potential for reduced capital costs in comparison to competing methods like photovoltaic-electrocatalysis and photoelectrocatalysis, owing to its simplicity and fewer auxiliary components. However, the current solar-to-hydrogen efficiency of photocatalytic solar hydrogen production has predominantly remained low at ≈1-2% or lower, mainly due to curtailed access to the entire solar spectrum, thus impeding practical application of photocatalytic solar hydrogen production. This review offers an integrated, multidisciplinary perspective on photocatalytic solar hydrogen production. Specifically, the review presents the existing approaches in photocatalyst and system designs aimed at significantly boosting the solar-to-hydrogen efficiency, while also considering factors of cost and scalability of each approach. In-depth discussions extending beyond the efficacy of material and system design strategies are particularly vital to identify potential hurdles in translating photocatalysis research to large-scale applications. Ultimately, this review aims to provide understanding and perspective of feasible pathways for commercializing photocatalytic solar hydrogen production technology, considering both engineering and economic standpoints.

Electron Divergence of Cuδ- and Pdδ+ in Cu3Pd Alloy-Based Heterojunctions Boosts Concerted C≡C Bond Binding and the Volmer Step for Alkynol Semihydrogenation.

Electrocatalytic semihydrogenation of alkynols presents a sustainable alternative to conventional thermal methodologies for the high-value production of alkenols. The design of efficient catalysts with superior catalytic and energy efficiency for semihydrogenation poses a significant challenge. Here, we present the application of an electron-divergent Cu3Pd alloy-based heterojunction in promoting the electrocatalytic semihydrogenation of alkynols to alkenols using water as the proton source. The tunable electron divergence of Cuδ- and Pdδ+, modulated by rectifying contact with nitrogen-rich carbons, enables the concerted binding of active H species from the Volmer step of water dissociation and the C≡C bond of alkynols on Pdδ+ sites. Simultaneously, the pronounced electron divergence of Cu3Pd facilitates the universal adsorption of OH species from the Volmer step and alkynols on the Cuδ- sites. The electron-divergent dual-center substantially boosts water dissociation and inhibition of completing hydrogen evolution to give a turnover frequency of 2412 h-1, outperforming the reported electrocatalysts' value of 7.3. Moreover, the continuous production of alkenols at industrial-related current density (-200 mA cm-2) over the efficient and durable Cu3Pd-based electrolyzer could achieve a cathodic energy efficiency of 45 mol kW·h-1, 1.7 times the bench-marked reactors, promising great potential for sustainable industrial synthesis.

Realization of monolayer ZrTe5 topological insulators with wide band gaps.

Two-dimensional topological insulators hosting the quantum spin Hall effect have application potential in dissipationless electronics. To observe the quantum spin Hall effect at elevated temperatures, a wide band gap is indispensable to efficiently suppress bulk conduction. Yet, most candidate materials exhibit narrow or even negative band gaps. Here, via elegant control of van der Waals epitaxy, we have successfully grown monolayer ZrTe5 on a bilayer graphene/SiC substrate. The epitaxial ZrTe5 monolayer crystalizes in two allotrope isomers with different intralayer alignments of ZrTe3 prisms. Our scanning tunneling microscopy/spectroscopy characterization unveils an intrinsic full band gap as large as 254 meV and one-dimensional edge states localized along the periphery of the ZrTe5 monolayer. First-principles calculations further confirm that the large band gap originates from strong spin-orbit coupling, and the edge states are topologically nontrivial. These findings thus provide a highly desirable material platform for the exploration of the high-temperature quantum spin Hall effect.

Case report: Lymph node metastasis of pelvic alveolar rhabdomyosarcoma diagnosed by fine needle aspiration cytology.

Rhabdomyosarcoma (RMS) is a common soft tissue malignant tumor, especially in young patients. Alveolar rhabdomyosarcoma (ARMS) is a subtype of RMS that is prevalent in adolescents. This malignant tumor usually develops in the extremities and can also involve the trunk, perineum, and pelvis. Now, we report a rare case of pelvic lymph node metastatic alveolar RMS in a young patient, which was determined by fine needle aspiration cytology (FNAC). To the best of our knowledge, this is the first case in which the definite diagnosis of ARMS was initially made by FNAC.

DNA methylation signatures provide novel diagnostic biomarkers and predict responses of immune therapy for breast cancer.

Breast cancer (BRCA) is one of the most common malignant tumors affecting women worldwide. DNA methylation modifications can influence oncogenic pathways and provide potential diagnostic and therapeutic targets for precision oncology. In this study, we used non-parametric permutation tests to identify differentially methylated positions (DMPs) between paired tumor and normal BRCA tissue samples from the Cancer Genome Atlas (TCGA) database. Then, we applied non-negative matrix factorization (NMF) to the DMPs to derive eight distinct DNA methylation signatures. Among them, signatures Hyper-S3 and Hypo-S4 signatures were associated with later tumor stages, while Hyper-S1 and Hypo-S3 exhibited higher methylation levels in earlier stages. Signature Hyper-S3 displayed an effect on overall survival. We further validated the four stage-associated signatures using an independent BRCA DNA methylation dataset from peripheral blood samples. Results demonstrated that 24 commonly hypomethylated sites in Hypo-S4 showed lower methylation in BRCA patients compared to healthy individuals, suggesting its potential as an early diagnostic biomarker. Furthermore, we found that methylation of 23 probes from four stage-related signatures exhibited predictive power for immune therapy response. Notably, methylation levels of all three probes from the Hypo-S4 and activity of the Hypo-S4 demonstrated highly positive relevance to PD-L1 gene expression, implying their significant predictive values for immunotherapy outcomes. GO and KEGG pathway enrichment analysis revealed that genes with these 23 immunotherapy-related methylation probes are mainly involved in glycan degradation or protein deglycosylation. These methylation signatures and probes may serve as novel epigenetic biomarkers for predicting tumor immunotherapy response. Our findings provide new insights into precision oncology approaches for BRCA.

From bits to green: Unraveling the digital economy's influence on natural resource efficiency.

This study explores the impact of the digital economy (DE) on natural resource efficiency (NRE) across 275 Chinese cities between 2011 and 2021. Through a comprehensive empirical analysis, we find that the DE significantly positively affects NRE. A key moderating factor in this relationship is green technological innovation (GTI), focusing on the quality rather than the quantity of green technology. Our study also uncovers regional variations of moderating effect. Additionally, we identify several mechanisms through which the DE contributes to enhanced NRE, including the transformation of industrial structure and improvements in green total factor productivity. A detailed heterogeneity analysis shows that the DE's impact on NRE varies according to city-specific factors such as natural resource endowment, city size, environmental regulations, and administrative levels. These findings provide a more nuanced understanding of how the DE influences NRE at the urban level, contributing to the broader discourse on sustainable development in the digital age. Our research offers policy recommendations and potential pathways for cities to leverage the DE for greater natural resource efficiency.

Dual Starvations Induce Pyroptosis for Orthotopic Pancreatic Cancer Therapy through Simultaneous Deprivation of Glucose and Glutamine.

Pancreatic cancer is a highly fatal disease, and existing treatment methods are ineffective, so it is urgent to develop new effective treatment strategies. The high dependence of pancreatic cancer cells on glucose and glutamine suggests that disrupting this dependency could serve as an alternative strategy for pancreatic cancer therapy. We identified the vital genes glucose transporter 1 (GLUT1) and alanine-serine-cysteine transporter 2 (ASCT2) through bioinformatics analysis, which regulate glucose and glutamine metabolism in pancreatic cancer, respectively. Human serum albumin nanoparticles (HSA NPs) for delivery of GLUT1 and ASCT2 inhibitors, BAY-876/V-9302@HSA NPs, were prepared by a self-assembly process. This nanodrug inhibits glucose and glutamine uptake of pancreatic cancer cells through the released BAY-876 and V-9302, leading to nutrition deprivation and oxidative stress. The inhibition of glutamine leads to the inhibition of the synthesis of the glutathione, which further aggravates oxidative stress. Both of them lead to a significant increase in reactive oxygen species, activating caspase 1 and GSDMD and finally inducing pyroptosis. This study provides a new effective strategy for orthotopic pancreatic cancer treatment by dual starvation-induced pyroptosis. The study for screening metabolic targets using bioinformatics analysis followed by constructing nanodrugs loaded with inhibitors will inspire future targeted metabolic therapy for pancreatic cancer.

Silver Recovery from Crystalline Silicon Photovoltaic Solar Cells Using Continuous Stirred-Tank Reactors.

Silver can be recycled from the end-of-life crystalline silicon photovoltaic (PV), yet the recycling and its technology scale-up are still at an early stage especially in continuously operations e.g., continoursely stirred tank reactors (CSTR). Here, the silver recovery from the solar cells is technically understood and optimized in the CSTR system from the point of view of silver recovery efficiency, through integrating experimental and numerical investigations. Specifically, based on the experiments, a kinetics model is developed and scanning electron microscopy surface morphology is characterized; and a computational fluid dynamics-discrete element method (CFD-DEM) particle-scale model is integrated with the kinetics model and validated against the fluid-flow pattern and silver leaching performance results from lab measurements. The validated CFD-DEM model is then applied to understand the particle-scale behavior of silver leaching in the CSTR system in terms of hydrodynamics and AgNO3 distribution under different impeller speeds. The simulation results show that the silver leaching performance is improved in an improved CSTR design with a lower impeller position and doubled impeller layers. This work reveals the effectiveness and underlying hydrodynamics of silver leaching in CSTR systems and lays a foundation for improving silver recovery in PV recycling.

A CT-based radiomics nomogram for predicting histologic grade and outcome in chondrosarcoma.

OBJECTIVE: The preoperative identification of tumor grade in chondrosarcoma (CS) is crucial for devising effective treatment strategies and predicting outcomes. The study aims to build and validate a CT-based radiomics nomogram (RN) for the preoperative identification of tumor grade in CS, and to evaluate the correlation between the RN-predicted tumor grade and postoperative outcome. METHODS: A total of 196 patients (139 in the training cohort and 57 in the external validation cohort) were derived from three different centers. A clinical model, radiomics signature (RS) and RN (which combines significant clinical factors and RS) were developed and validated to assess their ability to distinguish low-grade from high-grade CS with area under the curve (AUC). Additionally, Kaplan-Meier survival analysis was applied to examine the association between RN-predicted tumor grade and recurrence-free survival (RFS) of CS. The predictive accuracy of the RN was evaluated using Harrell's concordance index (C-index), hazard ratio (HR) and AUC. RESULTS: Size, endosteal scalloping and active periostitis were selected to build the clinical model. Three radiomics features, based on CT images, were selected to construct the RS. Both the RN (AUC, 0.842) and RS (AUC, 0.835) were superior to the clinical model (AUC, 0.776) in the validation set (P = 0.003, 0.040, respectively). A correlation between Nomogram score (Nomo-score, derived from RN) and RFS was observed through Kaplan-Meier survival analysis in the training and test cohorts (log-rank P < 0.050). Patients with high Nomo-score tumors were 2.669 times more likely to suffer recurrence than those with low Nomo-score tumors (HR, 2.669, P < 0.001). CONCLUSIONS: The CT-based RN performed well in predicting both the histologic grade and outcome of CS.

Antisolvent precipitation for the synergistic preparation of ultrafine particles of nobiletin under ultrasonication-homogenization and evaluation of the inhibitory effects of α-glucosidase and porcine pancreatic lipase in vitro.

To further enhance the application of nobiletin (an important active ingredient in Citrus fruits), we used ultrasonic homogenization-assisted antisolvent precipitation to create ultrafine particles of nobiletin (UPN). DMSO was used as the solvent, and deionized water was used as the antisolvent. When ultrasonication (670 W) and homogenization (16000 r/min) were synergistic, the solution concentration was 57 mg/mL, and the minimum particle size of UPN was 521.02 nm. The UPN samples outperformed the RN samples in terms of the inhibition of porcine pancreatic lipase, which was inhibited (by 500 mg/mL) by 68.41 % in the raw sample, 90.34 % in the ultrafine sample, and 83.59 % in the positive control, according to the data. Fourier transform infrared spectroscopy analysis revealed no chemical changes in the samples before or after preparation. However, the crystallinity of the processed ultrafine nobiletin particles decreased. Thus, this work offers significant relevance for applications in the realm of food chemistry and indirectly illustrates the expanded application potential of nobiletin.

Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response.

BACKGROUND: Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes. METHODS: We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts. RESULTS: We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment. CONCLUSIONS: Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.

CDSKNNXMBD: a novel clustering framework for large-scale single-cell data based on a stable graph structure.

BACKGROUND: Accurate and efficient cell grouping is essential for analyzing single-cell transcriptome sequencing (scRNA-seq) data. However, the existing clustering techniques often struggle to provide timely and accurate cell type groupings when dealing with datasets with large-scale or imbalanced cell types. Therefore, there is a need for improved methods that can handle the increasing size of scRNA-seq datasets while maintaining high accuracy and efficiency. METHODS: We propose CDSKNNXMBD (Community Detection based on a Stable K-Nearest Neighbor Graph Structure), a novel single-cell clustering framework integrating partition clustering algorithm and community detection algorithm, which achieves accurate and fast cell type grouping by finding a stable graph structure. RESULTS: We evaluated the effectiveness of our approach by analyzing 15 tissues from the human fetal atlas. Compared to existing methods, CDSKNN effectively counteracts the high imbalance in single-cell data, enabling effective clustering. Furthermore, we conducted comparisons across multiple single-cell datasets from different studies and sequencing techniques. CDSKNN is of high applicability and robustness, and capable of balancing the complexities of across diverse types of data. Most importantly, CDSKNN exhibits higher operational efficiency on datasets at the million-cell scale, requiring an average of only 6.33 min for clustering 1.46 million single cells, saving 33.3% to 99% of running time compared to those of existing methods. CONCLUSIONS: The CDSKNN is a flexible, resilient, and promising clustering tool that is particularly suitable for clustering imbalanced data and demonstrates high efficiency on large-scale scRNA-seq datasets.

Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues.

Expression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125 489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence and epigenomic characteristics. Based on these classifications, we developed a machine-learning model, E-SpotFinder, for augmented discovery of tissue- or cell-type-specific eQTL-hotspots. We applied this model to 36 tissues or cell types. Using augmented eQTL-hotspots, we recovered 655 402 eSNPs and reconstructed a comprehensive regulatory network of 2 725 380 cis-interactions among eQTL-hotspots. We further identified 52 012 modules representing transcriptional programs with unique functional backgrounds. In summary, our study provided a framework of epigenome-augmented eQTL analysis and thereby constructed comprehensive genome-wide networks of cis-regulations across diverse human tissues or cell types.

The dysfunction of CD8+ T cells triggered by endometriotic stromal cells promotes the immune survival of endometriosis.

Endometriosis is defined as an oestrogen-dependent and inflammatory gynaecological disease of which the pathogenesis remains unclear. This study aimed to investigate the cellular heterogeneity and reveal the effect of CD8+ T cells on the progress of endometriosis. Three ovarian endometriosis patients were collected, and single-cell RNA sequencing (scRNA-seq) progressed and delineated the cellular landscape of endometriosis containing five cell clusters. The endometrial cells (EMCs) were the major component, of which the mesenchymal cells were preponderant and characterized with increased inflammation and oestrogen synthesis in endometriosis. The proportion of T cells, mainly CD8+ T cells rather than CD4+, was reduced in endometriotic lesions, and the cytokines and cytotoxicity of ectopic T cells were depressed. CD8+ T cells depressed the proliferation of ESCs through inhibiting CDK1/CCNB1 pathway to arrest the cell cycle and triggered inflammation through activating STAT1 pathway. Correspondingly, the coculture with ESCs resulted in the dysfunction of CD8+ T cells through upregulating STAT1/PDCD1 pathway and glycolysis-promoted metabolism reprogramming. The endometriotic lesions were larger in nude mouse models with T-cell deficiency than the normal mouse models. The inhibition of T cells via CD90.2 or CD8A antibody increased the endometriotic lesions in mouse models, and the supplement of T cells to nude mouse models diminished the lesion sizes. In conclusion, this study revealed the global cellular variation of endometriosis among which the cellular count and physiology of EMCs and T cells were significantly changed. The depressed cytotoxicity and aberrant metabolism of CD8+ T cells were induced by ESCs with the activation of STAT1/PDCD1 pathway resulting in immune survival to promote endometriosis.

Ct-based intratumoral and peritumoral radiomics for predicting prognosis in osteosarcoma: A multicenter study.

PURPOSE: To evaluate the performance of CT-based intratumoral, peritumoral and combined radiomics signatures in predicting prognosis in patients with osteosarcoma. METHODS: The data of 202 patients (training cohort:102, testing cohort:100) with osteosarcoma admitted to the two hospitals from August 2008 to February 2022 were retrospectively analyzed. Progression free survival (PFS) and overall survival (OS) were used as the end points. The radiomics features were extracted from CT images, three radiomics signatures（RSintratumoral, RSperitumoral, RScombined）were constructed based on intratumoral, peritumoral and combined radiomics features, respectively, and the radiomics score (Rad-score) were calculated. Kaplan-Meier survival analysis was used to evaluate the relationship between the Rad-score with PFS and OS, the Harrell's concordance index (C-index) was used to evaluate the predictive performance of the radiomics signatures. RESULTS: Finally, 8, 6, and 21 features were selected for the establishment of RSintratumoral, RSperitumoral, and RScombined, respectively. Kaplan-Meier survival analysis confirmed that the Rad-scores of the three RSs were significantly correlated with the PFS and OS of patients with osteosarcoma. Among the three radiomics signatures, RScombined had better predictive performance, the C-index of PSF prediction was 0.833 in the training cohort and 0.814 in the testing cohort, the C-index of OS prediction was 0.796 in the training cohort and 0.764 in the testing cohort. CONCLUSIONS: CT-based intratumoral, peritumoral and combined radiomics signatures can predict the prognosis of patients with osteosarcoma, which may assist in individualized treatment and improving the prognosis of osteosarcoma patients.

Whole-genome shotgun sequencing unravels the influence of environmental microbial co-infections on the treatment efficacy for severe pediatric infectious diseases.

Background: The microbiome plays a pivotal role in mediating immune deviation during the development of early-life viral infections. Recurrent infections in children are considered a risk factor for disease development. This study delves into the metagenomics of the microbiome in children suffering from severe infections, seeking to identify potential sources of these infections. Aims: The aim of this study was to identify the specific microorganisms and factors that significantly influence the treatment duration in patients suffering from severe infections. We sought to understand how these microbial communities and other variables may affect the treatment duration and the use of antibiotics of these patients with severe infections. Method: Whole-genome shotgun sequencing was conducted on samples collected from children aged 0-14 years with severe infections, admitted to the Pediatrics Department of Xiamen First Hospital. The Kraken2 algorithm was used for taxonomic identification from sequence reads, and linear mixed models were employed to identify significant microorganisms influencing treatment duration. Colwellia, Cryptococcus, and Citrobacter were found to significantly correlate with the duration of clinical treatment. Further analysis using propensity score matching (PSM) and rank-sum test identified clinical indicators significantly associated with the presence of these microorganisms. Results: Using a linear mixed model after removed the outliers, we identified that the abundance of Colwellia, Cryptococcus, and Citrobacter significantly influences the treatment duration. The presence of these microorganisms is associated with a longer treatment duration for patients. Furthermore, these microorganisms were found to impact various clinical measures. Notably, an increase in hospitalization durations and medication costs was observed in patients with these microorganisms. In patients with Colwellia, Cryptococcus, and Citrobacter, we discover significant differences in platelets levels. We also find that in patients with Cryptococcus, white blood cells, hemoglobin, and neutrophils levels are lower. Conclusion: These findings suggest that Colwellia, Cryptococcus, and Citrobacter, particularly Cryptococcus, could potentially contribute to the severity of infections observed in this cohort, possibly as co-infections. These microorganisms warrant further investigation into their pathogenic roles and mechanisms of action, as their presence in combination with disease-causing organisms may have a synergistic effect on disease severity. Understanding the interplay between these microorganisms and pathogenic agents could provide valuable insights into the complex nature of severe pediatric infections and guide the development of targeted therapeutic strategies.

Prenatal EGCG consumption impacts hepatic glycogen synthesis and lipid metabolism in adult mice.

In this study, the impact of prenatal exposure to Epigallocatechin gallate (EGCG) on the liver of adult offspring mice was investigated. While EGCG is known for its health benefits, its effects of prenatal exposure on the liver remain unclear. Pregnant C57BL/6 J mice were exposed to 1 mg/kg of EGCG for 16 days to assess hepatotoxicity effects of adult offspring. Transcriptomics and metabolomics were employed to elucidate the hepatotoxicity mechanisms. The findings revealed that prenatal EGCG exposure led to a decrease in liver somatic index, enhanced inflammatory responses and disrupted liver function through increased glycogen accumulation in adult mice. The integrated omics analysis revealed significant alterations in key pathways involved in liver glucose lipid metabolism, such as gluconeogenesis, dysregulation of insulin signaling, and induction of liver inflammation. Furthermore, the study found a negative correlation between the promoter methylation levels of Ppara and their mRNA levels, suggesting that EGCG could reduce hepatic lipid content through epigenetic modifications. The findings suggest that prenatal EGCG exposure can have detrimental impacts on the liver among adult individuals and emphasize the need for a comprehensive evaluation of the potential risks associated with EGCG consumption during pregnancy.

Intratumoral and peritumoral CT radiomics in predicting prognosis in patients with chondrosarcoma: a multicenter study.

OBJECTIVE: To evaluate the efficacy of the CT-based intratumoral, peritumoral, and combined radiomics signatures in predicting progression-free survival (PFS) of patients with chondrosarcoma (CS). METHODS: In this study, patients diagnosed with CS between January 2009 and January 2022 were retrospectively screened, and 214 patients with CS from two centers were respectively enrolled into the training cohorts (institution 1, n = 113) and test cohorts (institution 2, n = 101). The intratumoral and peritumoral radiomics features were extracted from CT images. The intratumoral, peritumoral, and combined radiomics signatures were constructed respectively, and their radiomics scores (Rad-score) were calculated. The performance of intratumoral, peritumoral, and combined radiomics signatures in PFS prediction in patients with CS was evaluated by C-index, time-dependent area under the receiver operating characteristics curve (time-AUC), and time-dependent C-index (time C-index). RESULTS: Eleven, 7, and 16 features were used to construct the intratumoral, peritumoral, and combined radiomics signatures, respectively. The combined radiomics signature showed the best prediction ability in the training cohort (C-index, 0.835; 95%; confidence interval [CI], 0.764-0.905) and the test cohort (C-index, 0.800; 95% CI, 0.681-0.920). Time-AUC and time C-index showed that the combined signature outperformed the intratumoral and peritumoral radiomics signatures in the prediction of PFS. CONCLUSION: The CT-based combined signature incorporating intratumoral and peritumoral radiomics features can predict PFS in patients with CS, which might assist clinicians in selecting individualized surveillance and treatment plans for CS patients. CRITICAL RELEVANCE STATEMENT: Develop and validate CT-based intratumoral, peritumoral, and combined radiomics signatures to evaluate the efficacy in predicting prognosis of patients with CS. KEY POINTS: • Reliable prognostic models for preoperative chondrosarcoma are lacking. • Combined radiomics signature incorporating intratumoral and peritumoral features can predict progression-free survival in patients with chondrosarcoma. • Combined radiomics signature may facilitate individualized stratification and management of patients with chondrosarcoma.

Unveiling the potent effect of vitamin D: harnessing Nrf2/HO-1 signaling pathways as molecular targets to alleviate urban particulate matter-induced asthma inflammation.

BACKGROUND: Asthma is the most common allergic disease characterized by an inflammatory response in the airways. Mechanismly, urban particulate matter (PM) is the most widely air pollutant associated with increased asthma morbidity and airway inflammation. Current research found that vitamin D is an essential vitamin with anti-inflammatory, antioxidant and other medical efficacy. Inadequate or deficient vitamin D often leads to the pathogenesis and stability of asthma. NGF exacerbates airway inflammation in asthma by promoting smooth muscle cell proliferation and inducing the Th2 immune response. Activation of the Nrf2/HO-1 signaling pathway can exert a protective effect on the inflammatory response in bronchial asthma. However, the specific mechanism of this pathway in PM-involved asthmatic airway smooth muscle cells remains unclear. METHODS: Mice were sensitized and challenged with Ovalbumin (OVA) to establish an asthma model. They were then exposed to either PM, vitamin D or a combination of both, and inflammatory responses were observed. Including, acetylcholine stimulation at different concentrations measured airway hyperresponsiveness in mice. Bronchoalveolar lavage fluid (BALF) and serum were collected for TNF-α, IL-1ß, IL-6, and Nerve growth factor (NGF) analysis. Additionally, lung tissues underwent histopathological examination to observe alveolar structure and inflammatory cell infiltration. Specific ELISA kits were utilized to determine the levels of the inflammatory factors TNF-α, IL-1ß, IL-6, and Nerve growth factor (NGF). Nrf2/HO-1 signaling pathways were examined by western blot analysis. Meanwhile, we constructed a cell system with low HO-1 expression by lentiviral transfection of airway smooth muscle cells. The changes of Nrf2, HO-1, and NGF were observed after the treatment of OVA, PM, and Vit D were given. RESULTS: The in vivo results showed that vitamin D significantly alleviated pathological changes in lung tissue of PM-exposed mice models. Mechanismly, vitamin D decreased substantial inflammatory cell infiltration in lung tissue, as well as the number of inflammatory cells in BALF. Furthermore, vitamin D reduced the heightened inflammatory factors including of TNF-α, IL-1ß, IL-6, and NGF caused by PM exposure, and triggered the activity of nucleus Nrf2 and HO-1 in PM-exposed asthmatic mice. Notably, knockdown HO-1 weakens the Vitamin D- mediated inhibition to pollution toxicity in asthma. Importantly, in vitro experiments on OVA-stimulated mice airway smooth muscle cells, the results showed that OVA and PM, respectively, reduced Nrf2/HO-1 and increased NGF's expression, while vitamin D reversed the process. And in the HO-1 knockdown cell line of Lenti-si-HO-1 ASMCs, OVA and PM reduced Nrf2's expression, while HO-1 and NGF's expression were unchanged. CONCLUSIONS: The above results demastrate that vitamin D downregulated the inflammatory response and the expression of NGF by regulating the Nrf2/HO-1 signaling pathways in airway smooth muscle cells, thereby showing potent anti-inflammatory activity in asthma.

Verteporfin regulates corneal neovascularization through inhibition of YAP protein activation.

Corneal neovascularization (CNV) is a vision-threatening disease that is becoming a growing public health concern. While Yes-associated protein (YAP) plays a critical role in neovascular disease and allow for the sprouting angiogenesis. Verteporfin (VP) is a classical inhibitor of the YAP-TEAD complex, which is used for clinical treatment of neovascular macular degeneration through photodynamic therapy. The purpose of this study is to explore the effect of verteporfin (VP) on the inhibition of CNV and its potential mechanism. Rat CNV model were established by suturing in the central cornea and randomly divided into three groups (control, CNV and VP group). Neovascularization was observed by slit lamp to extend along the corneal limbus to the suture line. RNA-sequencing was used to reveal the related pathways on the CNV and the results revealed the vasculature development process and genes related with angiogenesis in CNV. In CNV group, we detected the nuclear translocation of YAP and the expression of CD31 in corneal neovascular endothelial cells through immunofluorescence. After the application of VP, the proliferation, migration and the tube formation of HUVECs were significantly inhibited. Furthermore, VP showed the CNV inhibition by tail vein injection without photoactivation. Then we found that the expression of phosphorylated YAP significantly decreased, and its downstream target protein connective tissue growth factor (CTGF) increased in the CNV group, while the expression was just opposite in other groups. Besides, both the expression of vascular endothelial growth factor receptor 2 (VEGFR2) and cofilin significantly increased in CNV group, and decreased after VP treatment. Therefore, we conclude that Verteporfin could significantly inhibited the CNV without photoactivation by regulating the activation of YAP.