Precisely Activating cGAS-STING Pathway with a Novel Peptide-Based Nanoagonist to Potentiate Immune Checkpoint Blockade Cancer Immunotherapy

As an essential intracellular immune activation pathway, the cGAS-STING pathway has attracted broad attention in cancer treatment. However, low bioavailability, nonspecificity, and adverse effects of small molecule STING agonists severely limit their therapeutic efficacy and in vivo application. In this study, a peptide-based STING agonist is first proposed, and KLA is screened out to activate the cGAS-STING pathway by promoting mitochondrial DNA (mtDNA) leakage. To precisely activate the cGAS-STING pathway and block the PD-1/PD-L1 pathway, a multi-stimuli activatable peptide nanodrug (MAPN) is developed for the effective delivery of KLA and PD-L1 antagonist peptide (CVR). With rational design, MAPN achieved the site-specific release of KLA and CVR in response to multiple endogenous stimuli, simultaneously activating the cGAS-STING pathway and blocking PD-1/PD-L1 pathway, ultimately initiating robust and durable T cell anti-tumor immunity with a tumor growth inhibition rate of 78% and extending the median survival time of B16F10 tumor-bearing mice to 40 days. Overall, antimicrobial peptides, which can promote mtDNA leakage through damaging mitochondrial membranes, may be potential alternatives for small molecule STING agonists and giving a new insight for the design of novel STING agonists. Furthermore, MAPN presents a universal delivery platform for the effective synergy of multiple peptides.

Transfer learning from rating prediction to Top-k recommendation

Recommender system has made great strides in two major research fields, rating prediction and Top-k recommendation. In essence, rating prediction is a regression task, which aims to predict users scores on other items, while Top-k is a classification task selecting the items that users have the most potential to interact with. Both characterize users and items, but the optimization of parameters varies widely for their respective tasks. Inspired by the idea of transfer learning, we consider extracting the information learned from rating prediction models for serving for Top-k tasks. To this end, we propose a universal transfer model for recommender systems. The transfer model consists of two sub-components: quadruple-based Bayesian Converter (BC) and Prediction-based Multi-Layer Perceptron (PMLP). As the main part, BC is responsible for transforming the feature vectors extracted from the rating prediction model. Meanwhile, PMLP extracts the prediction ratings, constructs the prediction rating matrix, and uses multi-layer perceptron to enhance the final performance. On four benchmark datasets, we use the information extracted from the singular value decomposition plus plus (SVD++) model to demonstrate the effectiveness of BC-PMLP, comparing to classical and state-of-the-art baselines. We also conduct extra experiments to verify the utility of BC, and performance within different parameter values.

Full-length transcriptome profiling of Acanthopanax gracilistylus provides new insight into the kaurenoic acid biosynthesis pathway

Acanthopanax gracilistylus is a deciduous plant in the family Araliaceae, which is commonly used in Chinese herbal medicine, as the root bark has functions of nourishing the liver and kidneys, removing dampness and expelling wind, and strengthening the bones and tendons. Kaurenoic acid (KA) is the main effective substance in the root bark of A. gracilistylus with strong anti-inflammatory effects. To elucidate the KA biosynthesis pathway, second-generation (DNA nanoball) and third-generation (Pacific Biosciences) sequencing were performed to analyze the transcriptomes of the A. gracilistylus leaves, roots, and stems. Among the total 505,880 isoforms, 408,954 were annotated by seven major databases. Sixty isoforms with complete open reading frames encoding 11 key enzymes involved in the KA biosynthesis pathway were identified. Correlation analysis between isoform expression and KA content identified a total of eight key genes. Six key enzyme genes involved in KA biosynthesis were validated by real-time quantitative polymerase chain reaction. Based on the sequence analysis, the spatial structure of ent-kaurene oxidase was modeled, which plays roles in the three continuous oxidations steps of KA biosynthesis. This study greatly enriches the transcriptome data of A. gracilistylus and facilitates further analysis of the function and regulation mechanism of key enzymes in the KA biosynthesis pathway.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-024-01436-7.

Ultrahigh Enzyme Loading Metal-Organic Frameworks for Deep Tissue Pancreatic Cancer Photoimmunotherapy

Protein drugs hold promise in treating multiple complex diseases, including cancer. The priority of protein drug application is precise delivery of substantial bioactive protein into tumor site. Metal-organic-framework (MOF) is widely considered as a promising carrier to encapsulate protein drug owing to the noncovalent interaction between carrier and protein. However, limited loading efficiency and potential toxicity of metal ion in MOF restrict its application in clinical research. Herein, a tumor targeted collagenase-encapsulating MOF via protein-metal ion-organic ligand coordination (PMOCol ) for refining deep tissue pancreatic cancer photoimmunotherapy is developed. By an expedient method in which the ratio of metal ion, histidine residues of protein and ligand is precisely controlled, PMOCol is constructed with ultrahigh encapsulation efficiency (80.3 wt%) and can release collagenase with high enzymatic activity for tumor extracellular matrix (ECM) regulation after reaching tumor microenvironment (TME). Moreover, PMOcol exhibits intensively poorer toxicity than the zeolitic imidazolate framework-8 biomineralized protein. After treatment, the pancreatic tumor with abundant ECM shows enhanced immunocyte infiltration owing to extracellular matrix degradation that improves suppressive TME. By integrating hyperthermia agent with strong near-infrared absorption (1064 nm), PMOCol can induce acute immunogenicity to host immunity activation and systemic immune memory production to prevent tumor development and recurrence.

Advances in Fatigue Performance of Metal Materials with Additive Manufacturing Based on Crystal Plasticity: A Comprehensive Review

Using metal additive manufacturing processes can make up for traditional forging technologies when forming complex-shaped parts. At the same time, metal additive manufacturing has a fast forming speed and excellent manufacturing flexibility, so it is widely used in the aerospace industry and other fields. The fatigue strength of metal additive manufacturing is related to the microstructure of the epitaxially grown columnar grains and crystallographic texture. The crystal plasticity finite element method is widely used in the numerical simulation of the microstructure and macro-mechanical response of materials, which provides a strengthening and toughening treatment and can reveal the inner rules of material deformation. This paper briefly introduces common metal additive manufacturing processes. In terms of additive manufacturing fatigue, crystal plasticity simulations are summarized and discussed with regard to several important influencing factors, such as the microstructure, defects, surface quality, and residual stress.

Exploring CCL11 in breast cancer: unraveling its anticancer potential and immune modulatory effects involving the Akt-S6 signaling

BACKGROUND

CCL11, a chemokine known for recruiting immune cells to the tumor microenvironment (TME), has an unclear role in the context of its expression, patient prognosis, and the presence of tumor-infiltrating immune cells (TILs) in breast cancer.

METHODS

The expression of CCL11 in invasive breast cancer (BRCA) was analyzed using TCGA database. Survival curve and Cox regression analysis determined the potential of CCL11 as an independent prognostic indicator. GSEA performed functional analysis on genes related to CCL11. CIBERSORT algorithm quantified the infiltration level of immune cells with varying CCL11 expression. Lastly, the correlation between CCL11 expression and anticancer drug sensitivity was examined. Immunohistochemistry (IHC) and qRT-PCR confirmed CCL11 expression in clinical tissue samples. The anti-tumor efficacy of CCL11 was investigated using CCK-8, plate formation, transwell assay, and Western blot.

RESULTS

CCL11 expression was elevated in BRCA tumor tissues compared to adjacent normal tissues. Recurrence-free survival (RFS) was longer in patients with high expression of CCL11. Enrichment and co-expression analyses revealed CCL11's association with numerous immune-related signaling pathways and genes. Validation studies confirmed high CCL11 expression in breast cancer tissues. In vitro experiments substantiated CCL11's anticancer effects in BRCA.

CONCLUSION

CCL11 expression correlates with immune cell infiltration in breast cancer, indicating its potential as a prognostic biomarker for BRCA.

Prediction of linear B-cell epitopes based on protein sequence features and BERT embeddings

Linear B-cell epitopes (BCEs) play a key role in the development of peptide vaccines and immunodiagnostic reagents. Therefore, the accurate identification of linear BCEs is of great importance in the prevention of infectious diseases and the diagnosis of related diseases. The experimental methods used to identify BCEs are both expensive and time-consuming and they do not meet the demand for identification of large-scale protein sequence data. As a result, there is a need to develop an efficient and accurate computational method to rapidly identify linear BCE sequences. In this work, we developed the new linear BCE prediction method LBCE-BERT. This method is based on peptide chain sequence information and natural language model BERT embedding information, using an XGBoost classifier. The models were trained on three benchmark datasets. The model was training on three benchmark datasets for hyperparameter selection and was subsequently evaluated on several test datasets. The result indicate that our proposed method outperforms others in terms of AUROC and accuracy. The LBCE-BERT model is publicly available at: https://github.com/Lfang111/LBCE-BERT .

Targeted liposomes for macrophages-mediated pulmonary fibrosis therapy

Pulmonary fibrosis (PF) is a horrible lung disease that causes pulmonary ventilation dysfunction and respiratory failure, severely impacting sufferers' physical and mental health. Existing drugs can only partially control the condition and are prone to toxic side effects. Anti-inflammatory treatment is the committed step to alleviate PF. Celastrol (CLT) has significant anti-inflammatory effects and can reverse M1-type transformation of macrophages. In this study, we have developed liposomes loaded with CLT, modified with folate (FA), designated FA-CLT-Lips, which facilitate drug delivery by targeting macrophages. FA-CLT-Lips were shown to be more readily absorbed by macrophages in vitro and to encourage the transition of M1 macrophages into M2 macrophages. In addition, FA-CLT-Lips can inhibit the phosphorylation of Smad2/3, effectively reducing the deposition of extracellular matrix (ECM) and the production of inflammatory factors. This showed that FA-CLT-Lips can ameliorate early lung fibrosis by lowering inflammation. In vivo studies have shown that FA-CLT-Lips accumulate in lung tissue to better attenuate lung injury and collagen deposition, with less toxicity compared to free CLT. In summary, FA receptor-targeting liposomes loaded with CLT provide a secure and reliable PF therapy.

Genome-wide characterization of SDR gene family and its potential role in seed dormancy of Brassica napus L

Rapeseed (Brassica napus L.) with short or no dormancy period are easy to germinate before harvest (pre-harvest sprouting, PHS). PHS has seriously decreased seed weight and oil content in B. napus. Short-chain dehydrogenase/ reductase (SDR) genes have been found to related to seed dormancy by promoting ABA biosynthesis in rice and Arabidopsis. In order to clarify whether SDR genes are the key factor of seed dormancy in B. napus, homology sequence blast, protein physicochemical properties, conserved motif, gene structure, cis-acting element, gene expression and variation analysis were conducted in present study. Results shown that 142 BnaSDR genes, unevenly distributed on 19 chromosomes, have been identified in B. napus genome. Among them, four BnaSDR gene clusters present in chromosome A04、A05、C03、C04 were also identified. These 142 BnaSDR genes were divided into four subfamilies on phylogenetic tree. Members of the same subgroup have similar protein characters, conserved motifs, gene structure, cis-acting elements and tissue expression profiles. Specially, the expression levels of genes in subgroup A, B and C were gradually decreased, but increased in subgroup D with the development of seeds. Among seven higher expressed genes in group D, six BnaSDR genes were significantly higher expressed in weak dormancy line than that in nondormancy line. And the significant effects of BnaC01T0313900ZS and BnaC03T0300500ZS variation on seed dormancy were also demonstrated in present study. These findings provide a key information for investigating the function of BnaSDRs on seed dormancy in B. napus.

The Zn Vacancy-Mediated De-Accumulation Based Process for Hydrogen Production Performance Promotion of 1D Zn─Cd─S Nanorods

Due to their anisotropy, 1D semiconductor nanorod-based materials have attracted much attention in the process of hydrogen production by solar energy. Nevertheless, the rational design of 1D heterojunction materials and the modulation of photo-generated electron-hole transfer paths remain a challenge. Herein, a Znx Cd1-x S@ZnS/MoS2 core-shell nanorod heterojunction is precisely constructed via in situ growth of discontinuous ZnS shell and MoS2 NCs on the Zn─Cd─S nanorods. Among them, the Zn vacancy in the ZnS shell builds the defect level, and the nanoroelded MoS2 builds the electron transport site. The optimized photocatalyst shows significant photocatalytic activity without Platinum as an auxiliary catalyst, mainly due to the new interfacial charge transfer channel constructed by the shell vacancy level, the vertical separation and the de-accumulation process of photo-generated electrons and photo-generated holes. At the same time, spectral analysis, and density functional theory (DFT) calculations fully prove that shortening difference of speed between the photogenerated electron and hole movement process is another key factor to enhance the photocatalytic performance. This study provides a new path for the kinetic design of enhanced carrier density by shortening the carrier retention time of 1D heterojunction photocatalysts with improved photocatalytic performance.

Comparative transcriptome analysis of different tissues of Solanum khasianum reveals candidate genes involved in steroidal glycoalkaloid biosynthesis

Fruits and leaves of Solanum khasianum C. B. Clarke have long been used as a common Chinese herbal medicine. Steroidal glycoalkaloids (SGAs), the main active ingredient in S. khasianum, exhibit various pharmacological effects. However, genes involved in the SGA biosynthetic pathway in S. khasianum have not yet been identified. Genes encoding potential key SGA biosynthesis enzymes were identified through comprehensive RNA sequencing analysis (RNA-seq) of S. khasianum leaves, stems, and fruits. A total of 123,704 unigenes were obtained, of which 109,775 (88.74%) were annotated in seven public databases. Among these, 54 unigenes potentially involved in SGA biosynthesis were identified. Additionally, 23,636 differentially expressed genes were identified by comparing gene expression levels among the fruits, stems, and leaves of S. khasianum. The structural characteristics and phylogenetic relationship of cycloartenol synthase involved in SGA biosynthesis were further analyzed. Solasodine constituent was detected by high-performance liquid chromatography. This is the first study to report the comparative transcriptome analysis of different tissues of S. khasianum that identifies valuable genes potentially involved in SGA biosynthesis in this species.

Full-length transcriptome analysis provides insights into flavonoid biosynthesis in Ranunculus japonicus

Ranunculus japonicus Thunb. is a traditional Chinese herb. Plants in the genus Ranunculus are generally rich in flavonoids, which have antibacterial, anti-infective, and other pharmacological effects. However, owing to the lack of reference genomes, little is known about the flavonoid biosynthetic pathway in R. japonicus. In this study, PacBio isoform sequencing (PacBio iso-seq) and DNA nanoball sequencing (DNB-seq) were combined to build a full-length transcriptome database for three different tissues of R. japonicus. A total of 395,402 full-length transcripts were obtained, of which 308,474 were successfully annotated. A Kyoto Encyclopedia of Genes and Genomes analysis identified 29 differentially expressed genes encoding nine key enzymes for flavonoid biosynthesis. Correlation analysis indicated that flavanone 3-hydroxylase and flavonol synthase genes might have key roles in the accumulation of flavonoid substances in the different tissues of R. japonicus. The structures of chalcone synthase and chalcone isomerase enzymes were spatially modeled. Reverse-transcription quantitative PCR was used to verify gene expression levels of key enzymes associated with flavonoid biosynthesis. In addition, 22 MYB transcription factors involved in flavonoid biosynthesis and phenylpropanoid biosynthesis were discovered. The reliable transcriptomic data from this study provide genetic information about R. japonicus as well as insights into the molecular mechanism of flavonoid biosynthesis. The results also provide a basis for developing the medicinal value R. japonicus.

Occurrence and source analysis of heavy metals and dissolved organic matter in Nanyi Lake, Anhui Province

Nanyi Lake is a tributary in the lower reaches of the Yangtze River and the largest freshwater lake in southern Anhui. Anthropogenic activities have significantly affected the lake with the rapid development of the surrounding economy in recent years. This study collected a total of 39 × 2 water samples of surface water and overlying water, detected the heavy metal concentrations (As, Cr, Cu, Mn, Ni, Pb, Sb, Zn, Fe, Cd), and analyzed the spectral characteristics of the dissolved organic matter (DOM). The results demonstrated that the concentrations of heavy metals (As, Cr, Cu, Mn, Ni, Pb, Sb, Zn, Fe, Cd) in the surface water were 1.00-7.78, 0.40-5.59, 0.20-4.52, 20.00-269.50, 0.40-5.56, 0.20-5.06, 1.00-7.64, 20.00-252.50, 60.00-590.00, and 0.04-0.60, respectively (unit: μg L^-1). The risk assessment showed that the carcinogenic risks of heavy metals (As, Cr, Cd) through drinking water were ranged from 10^-7 to 10^-4a^-1 in Nanyi Lake, and Cr was the main carcinogen which should be the focus of environmental health risk management. The average personal non-carcinogenic risks of heavy metals (Cu, Mn, Ni, Pb, Sb, Zn, Fe) were ranged from 10^-9 to 10^-13a^-1, and considered to be acceptable risk level. The contour map of spatial distribution demonstrated different degrees of heavy metals (except Zn) enrichment near the Langchuan River in the East Lake District. Parallel factor analysis showed that the main components of DOM in Nanyi Lake were tryptophan like, fulvic acid like, and tyrosine like, and the dissolved organic matter was primarily derived from autogenous endogenous sources. The heavy metals Cr, Ni, Pb, Fe, Cd, and HIX in the surface water of West Lake were significantly positively correlated, among which Ni, Fe and C2 were significantly negatively correlated (P < 0.05), Mn and BIX demonstrated extremely significant positive correlations (P < 0.01), while no significant correlation was observed between heavy metals and the DOM indexes in the surface water of the East Lake. The principal component and correlation analysis showed that the heavy metals in Nanyi Lake were primarily derived from the production wastewater discharged by the surrounding industrial and mining enterprises through the rivers input, followed by the non-point source runoff input of the surrounding agricultural production and lake aquaculture.

Deciphering the pharmacological mechanisms of Fraxini Cortex for ulcerative colitis treatment based on network pharmacology and in vivo studies

BACKGROUND

Ulcerative colitis (UC) is a common type of inflammatory bowel disease. Due to the elusive pathogenesis, safe and effective treatment strategies are still lacking. Fraxini Cortex (FC) has been widely used as a medicinal herb to treat some diseases. However, the pharmacological mechanisms of FC for UC treatment are still unclear.

METHODS

An integrated platform combining network pharmacology and experimental studies was introduced to decipher the mechanism of FC against UC. The active compounds, therapeutic targets, and the molecular mechanism of action were acquired by network pharmacology, and the interaction between the compounds and target proteins were verified by molecular docking. Dextran sulfate sodium (DSS)-induced colitis model was employed to assess the therapeutic effect of FC on UC, and validate the molecular mechanisms of action predicted by network pharmacology.

RESULTS

A total of 20 bioactive compounds were retrieved, and 115 targets were predicted by using the online databases. Ursolic acid, fraxetin, beta-sitosterol, and esculetin were identified as the main active compounds of FC against UC. PPI network analysis identified 28 FC-UC hub genes that were mainly enriched in the IL-17 signaling pathway, the TNF signaling pathway, and pathways in cancer. Molecular docking confirmed that the active compounds had high binding affinities to the predicted target proteins. GEO dataset analysis showed that these target genes were highly expressed in the UC clinical samples compared with that in the healthy controls. Experimental studies showed that FC alleviated DSS-induced colitis symptoms, reduced inflammatory cytokines release, and suppressed the expression levels of IL1β, COX2, MMP3, IL-17 and RORγt in colon tissues.

CONCLUSION

FC exhibits anti-UC properties through regulating multi-targets and multi-pathways with multi-components. In vivo results demonstrated that FC alleviated DSS-induced colitis.

CD1C is associated with breast cancer prognosis and immune infiltrates

BACKGROUND

The tumor microenvironment (TME) in breast cancer plays a vital role in occurrence, development, and therapeutic responses. However, immune and stroma constituents in the TME are major obstacles to understanding and treating breast cancer. We evaluated the significance of TME-related genes in breast cancer.

METHODS

Invasive breast cancer (BRCA) samples were retrieved from the TCGA and GEO databases. Stroma and immune scores of samples as well as the proportion of tumor infiltrating immune cells (TICs) were calculated using the ESTIMATE and CIBERSORT algorithms. TME-related differentially expressed genes (DEGs) were analyzed by a protein interaction (PPI) network and univariate Cox regression to determine CD1C as a hub gene. Subsequently, the prognostic value of CD1C, its response to immunotherapy, and its mechanism in the TME were further studied.

RESULTS

In BRCA, DEGs were determined to identify CD1C as a hub gene. The expression level of CD1C in BRCA patients was verified based on the TCGA database, polymerase chain reaction (PCR) results, and western blot analysis. Immunohistochemical staining (IHC) results revealed a correlation between prognosis, clinical features, and CD1C expression in BRCA. Enrichment analysis of GSEA and GSVA showed that CD1C participates in immune-associated signaling pathways. CIBERSORT showed that CD1C levels were associated with tumor immune infiltrating cells (TILs), such as different kinds of T cells. Gene co-expression analysis showed that CD1C and the majority of immune-associated genes were co-expressed in BRCA. In renal cell carcinoma, patients with a high expression of CD1C had a better immunotherapy effect.

CONCLUSION

CD1C is an important part of the TME and participates in immune activity regulation in breast tumors. CD1C is expected to become a prognostic marker and a new treatment target for breast cancer.

Transcriptome analyses reveal the expression profile of genes related to lignan biosynthesis in Anthriscus sylvestris L. Hoffm. Gen

Anthriscus sylvestris L. Hoffm. Gen (A. sylvestris) is a perennial herb widely used for antitussive and diuretic purposes in traditional Korean and Chinese medicine. Lignans are critical secondary metabolites with widely pharmacological activities in A. sylvestris. Using transcriptome data of A. sylvestris, we identified genes related to lignan biosynthesis. In all, 123,852 unigenes were obtained from the flowers, leaves, roots, and stems of A. sylvestris with the Illumina HiSeq 4000 platform. The average length of unigenes was 1,123 bp and 91,217 (73.65%) of them were annotated in public databases. Differentially expressed genes and root-specific genes were analyzed between roots and the other three tissue types by comparing gene expression profiles. Specifically, the key enzyme genes involved in lignan biosynthesis were identified and analyzed. The expression levels of some of these genes were highest in the roots, consistent with the accumulation of deoxypodophyllotoxin. These expression levels were experimentally verified via quantitative real-time polymerase chain reaction (qRT-PCR). This research provides valuable information on the transcriptome data of A. sylvestris and the identification of candidate genes associated with the biosynthesis of lignans, laying the foundation for further research on genomics in A. sylvestris and related species.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-022-01156-w.