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Mast cells are a major component of the immune microenvironment in tumour tissues and modulate tumour progression by releasing pro‐tumorigenic and antitumorigenic molecules. Regarding the impact of mast cells on the outcomes of patients with lung adenocarcinoma (LUAD) patient, several published studies have shown contradictory results. Here, we aimed at elucidating the role of mast cells in early‐stage LUAD. We found that high mast cell abundance was correlated with prolonged survival in early‐stage LUAD patients. The mast cell‐related gene signature and gene mutation data sets were used to stratify early‐stage LUAD patients into two molecular subtypes (subtype 1 and subtype 2). The neural network‐based framework constructed with the mast cell‐related signature showed high accuracy in predicting response to immunotherapy. Importantly, the prognostic mast cell‐related signature predicted the survival probability and the potential relationship between TP53 mutation, c‐MYC activation and mast cell activities. The meta‐analysis confirmed the prognostic value of the mast cell‐related gene signature. In summary, this study might improve our understanding of the role of mast cells in early‐stage LUAD and aid in the development of immunotherapy and personalized treatments for early‐stage LUAD patients. Mast cell abundance and a mast cell‐related signature were correlated with survival in early‐stage lung adenocarcinoma patients. The mast cell‐related signature‐based neural network showed high accuracy in predicting response to immunotherapy.

Background Breast cancer is the most common malignancy in female patients worldwide. Because of its heterogeneity in terms of prognosis and therapeutic response, biomarkers with the potential to predict survival or assist in making treatment decisions in breast cancer patients are essential for an individualised therapy. Epigenetic alterations in the genome of the cancer cells, such as changes in DNA methylation pattern, could be a novel marker with an important role in the initiation and progression of breast cancer. Method DNA methylation and RNA-seq datasets from The Cancer Genome Atlas (TCGA) were analysed using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox model. Applying gene ontology (GO) and single sample gene set enrichment analysis (ssGSEA) an epigenetic signature associated with the survival of breast cancer patients was constructed that yields the best discrimination between tumour and normal breast tissue. A predictive nomogram was built for the optimal strategy to distinguish between high- and low-risk cases. Results The combination of mRNA-expression and of DNA methylation datasets yielded a 13-gene epigenetic signature that identified subset of breast cancer patients with low overall survival. This high-risk group of tumor cases was marked by upregulation of known cancer-related pathways (e.g. mTOR signalling). Subgroup analysis indicated that this epigenetic signature could distinguish high and low-risk patients also in different molecular or histological tumour subtypes (by Her2-, EGFR- or ER expression or different tumour grades). Using Gene Expression Omnibus (GEO) the 13-gene signature was confirmed in four external breast cancer cohorts. Conclusion An epigenetic signature was discovered that effectively stratifies breast cancer patients into low and high-risk groups. Since its efficiency appears independent of other known classifiers (such as staging, histology, metastasis status, receptor status), it has a high potential to further improve likely individualised therapy in breast cancer.

Immune checkpoints play key roles in maintaining self-tolerance. Targeted potentiation of the checkpoint molecule PD-L1 through in situ manipulation offers clinical promise for patients with autoimmune diseases. However, the therapeutic effects of these approaches are often compromised by limited specificity and inadequate expression. Here, we report a two-step dual-anchor coupling strategy for enhanced immobilization of PD-L1 on target endogenous cells by integrating bioorthogonal chemistry and physical insertion of the cell membrane. In both type 1 diabetes and rheumatoid arthritis mouse models, we demonstrate that this approach leads to elevated and sustained conjugation of PD-L1 on target cells, resulting in significant suppression of autoreactive immune cell activation, recruitment of regulatory T cells, and systematic reshaping of the immune environment. Furthermore, it restores glucose homeostasis in type 1 diabetic mice for over 100 days. This specific in situ bioengineering approach potentiates the functions of PD-L1 and represents its translational potential. Immune checkpoints are critical in maintaining self-tolerance and their therapeutic modulation can be achieved in autoimmune diseases. Here the authors present an in situ dual-anchoring approach that targets PD-L1 and show effects in animal models of autoimmunity.

Phototherapy of deep tumors still suffers from many obstacles, such as limited near-infrared (NIR) tissue penetration depth and low accumulation efficiency within the target sites. Herein, stimuli-sensitive tumor-targeted photodynamic nanoparticles (STPNs) with persistent luminescence for the treatment of deep tumors are reported. Purpurin 18 (Pu18), a porphyrin derivative, is utilized as a photosensitizer to produce persistent luminescence in STPNs, while lanthanide-doped upconversion nanoparticles (UCNPs) exhibit bioimaging properties and possess high photostability that can enhance photosensitizer efficacy. STPNs are initially stimulated by NIR irradiation before intravenous administration and accumulate at the tumor site to enter the cells through the HER2 receptor. Due to Pu18 afterglow luminescence properties, STPNs can continuously generate ROS to inhibit NFκB nuclear translocation, leading to tumor cell apoptosis. Moreover, STPNs can be used for diagnostic purposes through MRI and intraoperative NIR navigation. STPNs exceptional antitumor properties combined the advantages of UCNPs and persistent luminescence, representing a promising phototherapeutic strategy for deep tumors. Phototherapy of deep tumors suffers from many obstacles, such as limited near-infrared tissue penetration depth and low accumulation efficiency within the target sites. Here, the authors report stimuli sensitive tumor-targeted photodynamic nanoparticles with persistent luminescence for the treatment of deep tumors.

To explore an appropriate time interval between oocyte retrieval and intracytoplasmic sperm injection (ICSI) for optimal embryological and clinical outcomes in ICSI cycles over 40 years of maternal age. A retrospective analysis of 1476 ICSI fresh cycles from women aged over 40 years, was performed at the Reproduction Medicine Research Center of the Sixth Affiliated Hospital of Sun Yat-sen University, between December 2013 and August 2020. The fertilization rate and clinical pregnancy rate were the main outcomes. Multivariate linear regression and logistic regression analysis of factors showed that fertilization rate ( P  = 0.024) and clinical pregnancy rate ( P  = 0.011) were significantly associated with oocyte pick up (OPU)-ICSI interval. A longer OPU-ICSI interval (no more than 6 h) was associated with a higher fertilization rate but significantly decreased the clinical pregnancy rate when the OPU-ICSI interval was over 4 h ( P  < 0.05). The optimal OPU-ICSI interval is between 3 and 4 h for excellent embryological and clinical outcomes in ICSI cycles over 40 years of maternal age.

Single rich-stimuli-responsive organometallic polymers are considered to be the candidate for ultrahigh information storage and anti-counterfeiting security. However, their controllable synthesis has been an unsolved challenge. Here, we report the rapidly sequence-controlled electrosynthesis of organometallic polymers with exquisite insertion of multiple and distinct monomers. Electrosynthesis relies on the use of oxidative and reductive C–C couplings with the respective reaction time of 1 min. Single-monomer-precision propagation does not need protecting and deprotecting steps used in solid-phase synthesis, while enabling the uniform synthesis and sequence-defined possibilities monitored by both UV–vis spectra and cyclic voltammetry. Highly efficient electrosynthesis possessing potentially automated production can incorporate an amount of available metal and ligand species into a single organometallic polymer with complex architectures and functional versatility, which is proposed to have ultrahigh information storage and anti-counterfeiting security with low-cost coding and decoding processes at the single organometallic polymer level. The controllable synthesis of organometallic polymers that can be used in ultrahigh information storage and anti-counterfeiting security has been an unsolved challenge. Here, the authors show sequence-controlled electrosynthesis of organometallic polymers with exquisite insertion of multiple and distinct monomers.

This study investigated the association between inflammatory cytokines and major depressive disorder. Plasma biomarkers were measured by enzyme-linked immunosorbent assay (ELISA). Statistical analysis of baseline biomarkers in the major depression disorder (MDD) group and healthy controls (HC) group, and differences in biomarkers before and after treatment. Spearman analysis was performed to correlate baseline and after treatment MDD biomarkers with the 17-item Hamilton Depression Rating Scale (HAMD-17) total scores. Receiver operator characteristic (ROC) curves were analyzed for the effect of biomarkers on MDD and HC classification and diagnosis. Tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) levels were significantly higher in the MDD group than in the HC group, while high mobility group protein 1 (HMGB1) levels were significantly lower in the MDD group. The AUCs for HMGB1, TNF-α, and IL-6 were 0.375, 0.733, and 0.783, respectively, according to the ROC curves. MDD patients with brain-derived neurotrophic factor precursor (proBDNF) levels were positively correlated with total HAMD-17 scores. The levels of proBDNF levels were positively correlated with the total HAMD-17 score in male MDD patients, and brain-derived neurotrophic factor (BDNF) and interleukin 18 (IL-18) levels were negatively correlated with the total HAMD-17 score in female MDD patients. Inflammatory cytokines are associated with the severity of MDD, and TNF-α and IL-6 have the potential as objective biomarkers to aid in the diagnosis of MDD.

The spatial resolution of remote sensing images directly affects the accuracy, efficiency, and computational cost of extracting the fractional vegetation cover (FVC). Taking the Liyang woodland region, Jiangsu Province, as the study area, FVCs with varying spatial resolutions were extracted separately from Sentinel-2, Landsat-8, MOD13Q1, and MOD13A1. The variations in FVCs extracted from remote sensing images with varying spatial resolutions were analyzed at one specific time and time series within a year. The results show that (i) the overall mean FVC values of the four spatial resolution images did not differ substantially; however, FVCs with varying spatial resolutions present with a regular pattern of overestimation or underestimation at different vegetation levels. (ii) Taking the 10 m spatial resolution FVC as the reference, the accuracy values of FVC extraction at 30 m, 250 m, and 500 m resolutions were 91.0%, 76.3%, and 76.7%, respectively. The differences in the spatial distribution of FVCs are the most obvious at water–land interfaces and at the edge of each woodland patch. (iii) The highest accuracy of time-series FVC extraction from lower-resolution images is in the range of 0.6~0.7 for FVC. The degree of variation in FVC of time series varying spatial resolutions depends on the season and vegetation cover conditions. In summary, there are considerable differences in the need to monitor high-resolution images depending on the FVC level of the land surface. This study provides a reference for selection and accuracy research of remote sensing images for FVC extraction.

The NAC gene family is one of the important plant-specific transcription factor families involved in variety of physiological processes. It has been found in several plant species; however, little is known about the gene family in ginseng, Panax ginseng C.A. Meyer. Here we report identification and systematic analysis of this gene family in ginseng. A total of 89 NAC genes, designated PgNAC01 to PgNAC89, are identified. These genes are alternatively spliced into 251 transcripts at fruiting stage of a four-year-old ginseng plant. The genes of this gene family have five conserved motifs and are clustered into 11 subfamilies, all of which are shared with the genes of the NAC gene families identified in the dicot and monocot model plant species, Arabidopsis and rice. This result indicates that the PgNAC gene family is an ancient and evolutionarily inactive gene family. Gene ontology (GO) analysis shows that the functions of the PgNAC gene family have been substantially differentiated; nevertheless, over 86% the PgNAC transcripts remain functionally correlated. Finally, five of the PgNAC genes, PgNAC05-2, PgNAC41-2, PgNAC48, PgNAC56-1, and PgNAC59, are identified to be involved in plant response to cold stress, suggesting that this gene family plays roles in response to cold stress in ginseng. These results, therefore, provide new insights into functional differentiation and evolution of a gene family in plants and gene resources necessary to comprehensively determine the functions of the PgNAC gene family in response to cold and other abiotic stresses in ginseng.

Rheum pumilum stands as both a quintessential alpine plant and a significant traditional Chinese and Tibetan medicinal herb. Unraveling the molecular intricacies of seed germination in Rh. pumilum not only unveils the genetic foundations of plant seed germination strategies in high-altitude environments but also offers insights for cultivating Rh. pumilum medicinal materials. Employing transcriptome sequencing and the Weighted Gene Co-expression Network Analysis, this study delved into the shifts in gene expression levels across various stages of seed germination in Rh. pumilum . The process of seed germination in Rh. pumilum entails a cascade of complex physiological events. Six hormones (ABA, IAA, ETH, GA, BR, CK) emerged as pivotal players in seeds breaking in shells and the facilitation of rapid seed germination in Rh. pumilum . Fourteen transcription factor families (LOB, GRAS, B3, bHLH, bZIP, EIL, MYB, MYB related, NAC, TCP, WRKY, HSF, PLATZ, and SBP) along with four key genes (E2.4.1.13, EIN3, BZR, and BIN2) were identified that may be associated with both biotic and abiotic environmental stress. The ETR, ACACA and ATPeV0C genes were linked with energy accumulation during the initial stages of seed germination, CYP707A may play an important role in breaking seed dormancy, while the BRI1 gene may be correlated with swift seed germination. Additionally, several unidentified genes were recognized to play key roles in seed germination of Rh. pumilum , warranting further investigation. Moreover, Rh. pumilum demonstrates full activation of crucial physiological functions such as energy metabolism, signal transduction, and responses to biological and abiotic stresses during the seed breaking in shells. This study provides molecular evidence elucidating the swift seed germination strategies adopted by alpine plants to thrive in high-altitude environments. Furthermore, it serves as a foundational reference for enhancing seed germination rates and breeding practices to promote the sustainable development of Rh. pumilum medicinal materials.