Integrative eQTL-based analyses reveal the biology of breast cancer risk loci.

Germline determinants of gene expression in tumors are infrequently studied due to the complexity of transcript regulation caused by somatically acquired alterations. We performed expression quantitative trait locus (eQTL)-based analyses using the multi-level information provided in The Cancer Genome Atlas (TCGA). Of the factors we measured, cis-acting eQTLs accounted for 1.2% of the total variation of tumor gene expression, while somatic copy-number alteration and CpG methylation accounted for 7.3% and 3.3%, respectively. eQTL analyses of 15 previously reported breast cancer risk loci resulted in the discovery of three variants that are significantly associated with transcript levels (false discovery rate [FDR] < 0.1). Our trans-based analysis identified an additional three risk loci to act through ESR1, MYC, and KLF4. These findings provide a more comprehensive picture of gene expression determinants in breast cancer as well as insights into the underlying biology of breast cancer risk loci.

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.

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.

Electrocatalytic Aromatic Alcohols Splitting to Aldehydes and H2 Gas.

Selective electrocatalytic transformation of alcohols to aldehydes offers an efficient and environmentally friendly platform for the simultaneous production of fine chemicals and pure hydrogen gas. However, traditional alcohol oxidation reactions (AORs) in aqueous electrolyte unavoidably face competitive reactions (e.g., water oxidation and overoxidations reactions) for the presence of active oxygen species from water oxidation, causing an unwanted decrease in final efficiency and selectivity. Here, we developed an integrated all-solid proton generator-transfer electrolyzer to trigger the pure alcohol splitting reaction (ASR). In this splitting process, only O-H and C-H bonds can be cleaved at the proton generator (Pt nanoparticles), thereby completely avoiding all competitive reactions involving oxygen active species to give a > 99% selectivity to aldehydes. The as-generated protons are transported to the cathode by a three-dimensional (3D) conducting network (assemblies of ionomers and carbon spheres) for efficient hydrogen production. Unlike the poor selectivity (<22%) and durability (<3 h) of a conventional AOR electrolyzer, this ASR electrolyzer could be continuously operated at a low cell voltage of 1.2 V for at least 10 days to give a high Faradaic efficiency of 80-93% for aldehyde production.

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.

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.

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.

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.

Aminophenylboronic acid-modified nitrogen-doped graphene quantum dots and their applications in lysine sensing based on interplaying fluorescent mechanisms.

Using nitrogen-doped graphene quantum dots (N-GQDs) and 3-aminophenylboronic acid (APBA), a novel fluorescence nanosensor was developed. This nanosensor exhibits high selectivity and sensitivity for lysine detection. Its sensing mechanism involves the suppression of electron transfer from APBA to the N-GQDs unit, thereby inhibiting photoinduced electron transfer and initiating internal charge transfer. At an optimal pH of 7, the protonated α-amine and ε-amine groups of lysine interact with the amide and boronic acid moieties, respectively. This interaction results in a redshift of fluorescence, substantially enhancing the response signal. A linear response was observed within a concentration range 0.40-3.01 µM, with the detection limit being 0.005 µM. A similar linear range was also achieved for the determination of lysine in human serum. Density functional theory calculations correlating molecular orbits and geometries support UV-vis and fluorescence findings. Additionally, the nanosensor was successfully applied to detect lysine in living cells and real samples, including milk and honey. For practical application, we construct a lysine-specific sensing platform using a commercial chip (TCS34725) that collects red, blue, and green signals, thereby facilitating the convenient use of the nanosensor. Overall, this study offers new perspectives on the development and application of fluorescent nanosensors for detecting individual amino acids.