In silico discovery and anti-tumor bioactivities validation of an algal lectin from Kappaphycus alvarezii genome.

Lectins are proteins that bind specifically and reversibly to carbohydrates, and some of them have significant anti-tumor activities. Compared to those of lectins from land plants, there are far fewer studies on algal lectins, despite of the high biodiversity of algae. However, canonical strategies based on chromatographic feature-oriented screening cannot satisfy the requirement for algal lectin discovery. In this study, prospecting for novel OAAH family lectins throughout 358 genomes of red algae and cyanobacteria was conducted. Then 35 candidate lectins and 1843 of their simulated mutated forms were virtually screened based on predicted binding specificities to characteristic carbohydrates on cancer cells inferred by a deep learning model. A new lectin, named Siye, was discovered in Kappaphycus alvarezii genome and further verified on different cancer cells. Without causing agglutination of erythrocytes, Siye showed significant cytotoxicity to four human cancer cell lines (IC50 values ranging from 0.11 to 3.95 µg/mL), including breast adenocarcinoma HCC1937, lung carcinoma A549, liver cancer HepG2 and romyelocytic leukemia HL60. And the cytotoxicity was induced through promoting apoptosis by regulating the caspase and the p53 pathway within 24 h. This study testifies the feasibility and efficiency of the genome mining guided by evolutionary theory and artificial intelligence in the discovery of algal lectins.

Bridging Nickel-MOF and Copper Single Atoms/Clusters with H-Substituted Graphdiyne for the Tandem Catalysis of Nitrate to Ammonia.

Interfacial engineering of synergistic catalysts is one of the keys to achieving multiple proton-coupled electron transfer processes in nitrate-to-ammonia conversion. Herein, by joining ultrathin nickel-based metal-organic framework (denoted Ni-MOF) nanosheets with few-layered hydrogen-substituted graphdiyne-supported copper single atoms and clusters (denoted HsGDY@Cu), a tandem catalyst of Ni-MOFs@HsGDY@Cu with dual-active interfaces was developed for the concerted catalysis of nitrate-to-ammonia. In such a system, the sandwiched HsGDY layer could serve as a bridge to connect the coordinated unsaturated Ni2+ sites with Cu single atoms/clusters in a limited range of 0 to 3.6 nm. From Ni2+ to Cu, via the hydrogen spillover process, the hydrogen radicals (H⋅) generated at the unsaturated Ni2+ sites could migrate across HsGDY to the Cu sites to participate in the transformation of *HNO3 to NH3. From Cu to Ni2+, bypassing the higher reaction energy for *HNO3 formation on the Ni2+ sites, the NO2 - detached from the Cu sites could diffuse onto the unsaturated Ni2+ sites to form NH3 as well. The combined results make this hybrid a tandem catalyst with dual active sites for the catalysis of nitrate-to-ammonia conversion with improved Faradaic efficiency at lower overpotentials.

Ecological barriers: An approach to ecological conservation and restoration in China.

The Chinese government has pursued comprehensive ecological conservation and restoration by establishing an ecological barrier system. However, the majority of international research tends to focus on the connectivity between habitats, overlooking the functions that ecological barriers play in ecological conservation and restoration. The existing literature lacks a systematic exploration of the theory and practice of ecological barriers. This study employed the literature analysis tool CiteSpace to present the theoretical and developmental trends in ecological barriers from various perspectives, including research fields, historical evolution, research hotspots, and major research nations. By analyzing the differences in the understanding of ecological barriers between China and other countries, examining the ecological barriers construction history in China, and exploring the types and functions of ecological barriers, this study summarizes the framework of China's ecological barriers construction system as "features-functions-problems." Constructing an ecological barrier system can help achieve ecological conservation and restoration goals in China.

The unfolded protein response pathway as a possible link in the pathogenesis of COVID-19 and sepsis.

The global impact of the COVID-19 pandemic has been substantial. Emerging evidence underscores a strong clinical connection between COVID-19 and sepsis. Numerous studies have identified the unfolded protein response (UPR) pathway as a crucial pathogenic pathway for both COVID-19 and sepsis, but it remains to be investigated whether this signaling pathway operates as a common pathogenic mechanism for both COVID-19 and sepsis. In this study, single-cell RNA-seq data and transcriptome data for COVID-19 and sepsis cases were downloaded from GEO (Gene Expression Omnibus). By analyzing the single-cell transcriptome data, we identified B cells as the critical cell subset and the UPR pathway as the critical signaling pathway. Based on the transcriptome data, a machine learning diagnostic model was then constructed using the interleaved genes of B-cell-related and UPR-pathway-related genes. We validated the diagnostic model using both internal and external datasets and found the accuracy and stability of this model to be extremely strong. Even after integrating our algorithmic model with the patient's clinical status, it continued to yield identical results, further emphasizing the reliability of this model. This study provides a novel molecular perspective on the pathogenesis of sepsis and COVID-19 at the single-cell level and suggests that these two diseases may share a common mechanism.

Hybrid nanoarrays of Cu-MOFs@H-substituted graphdiyne with various levels of Lewis acidity for nitrate electroreduction.

To mimic enzymes in nature, a set of hybrid nanoarrays of Cu-MOFs sealed in hydrogen-substituted graphdiyne has been developed in order to serve as Lewis-acid-promoted catalysts. By regulating the electron-withdrawing capability of the ligands bridging Cu2+ sites, these Cu-MOFs provided different levels of Lewis acidity toward nitrate affinity, a feature crucial for nitrate-to-ammonia conversion.

Interfacial Engineering of Bimetallic Ni/Co-MOFs with H-Substituted Graphdiyne for Ammonia Electrosynthesis from Nitrate.

The electrochemical synthesis of ammonia is highly dependent on the coupling reaction between nitrate and water, for which an electrocatalyst with a multifunctional interface is anticipated to promote the deoxygenation and hydrogenation of nitrate with water. Herein, by engineering the surface of bimetallic Ni/Co-MOFs (NiCoBDC) with hydrogen-substituted graphdiyne (HsGDY), a hybrid nanoarray of NiCoBDC@HsGDY with a multifunctional interface has been achieved toward scale-up of the nitrate-to-ammonia conversion. On the one hand, a partial electron transfers from Ni2+ to the coordinatively unsaturated Co2+ on the surface of NiCoBDC, which not only promotes the deoxygenation of *NO3 on Co2+ but also activates the water-dissociation to *H on Ni2+. On the other hand, the conformal coated HsGDY facilitates both electrons and NO3- ions gathering on the interface between NiCoBDC and HsGDY, which moves forward the rate-determining step from the deoxygenation of *NO3 to the hydrogenation of *N with both *H on Ni2+ and *H2O on Co2+. As a result, such a NiCoBDC@HsGDY nanoarray delivers high NH3 yield rates with Faradaic efficiency above 90% over both wide potential and pH windows. When assembled into a galvanic Zn-NO3- battery, a power density of 3.66 mW cm-2 is achieved, suggesting its potential in the area of aqueous Zn-based batteries.

A systematic and comprehensive analysis of T cell exhaustion related to therapy in lung adenocarcinoma tumor microenvironment.

Background: T cell exhaustion (TEX) is an important immune escape mechanism, and an in-depth understanding of it can help improve cancer immunotherapy. However, the prognostic role of TEX in malignant lung adenocarcinoma (LUAD) remains unclear. Methods: Through TCGA and GEO datasets, we enrolled a total of 498 LUAD patients. The patients in TCGA-LUAD were unsupervised clustered into four clusters according to TEX signaling pathway. WGCNA analysis, survival random forest analysis and lasso regression analysis were used to select five differentially expressed genes among different clusters to construct a TEX risk model. The risk model was subsequently validated with GEO31210. By analyzing signaling pathways, immune cells and immune checkpoints using GSEA, GSVA and Cibersortx, the relationship between TEX risk score and these variables was evaluated. In addition, we further analyzed the expression of CCL20 at the level of single-cell RNA-seq and verified it in cell experiments. Results: According to TEX signaling pathway, people with better prognosis can be distinguished. The risk model constructed by CD109, CCL20, DKK1, TNS4, and TRIM29 genes could further accurately identify the population with poor prognosis. Subsequently, it was found that dendritic cells, CD44 and risk score were closely related. The final single-cell sequencing suggested that CCL2O is a potential therapeutic target of TEX, and the interaction between TEX and CD8 + T is closely related. Conclusion: The classification of T cell depletion plays a crucial role in the clinical decision-making of lung adenocarcinoma and needs to be further deepened.

ER stress-related mRNA-lncRNA co-expression gene signature predicts the prognosis and immune implications of esophageal cancer.

BACKGROUND: Esophageal cancer (EC) is one of the most common malignant cancers in the world. Endoplasmic reticulum (ER) stress is an adaptive response to various stress conditions and has been implicated in the development of various types of cancer. Long noncoding RNAs (lncRNAs) refer to a group of noncoding RNAs (ncRNAs), which regulate gene expression by interacting with DNA, RNA and proteins. Accumulating evidence suggests that lncRNAs are critical regulators of gene expression in development, differentiation, and human diseases, such as cancers and heart diseases. However, the prognostic model of EC based on ER stress-related mRNA and lncRNA has not been reported. METHODS: Firstly, we downloaded RNA expression profiles from The Cancer Genome Atlas (TCGA) and obtained ER stress-related genes from the Molecular Signature Database (MSigDB). Next, Weighted Correlation Network Analysis (WGCNA) co-expression analysis was used to identify survival-related ER stress-related modules. Prognostic models were developed using univariate and Least absolute shrinkage and selection operator (LASSO) regression analyses on the training set and validated on the test set. Afterwards, The Receiver Operating Characteristic (ROC) curve and nomogram were used to evaluate the performance of risk prediction models. Differentially expressed gene (DEG) and enrichment analysis were performed between different groups in order to identify the biological processes correlated with the risk score. Finally, the fraction of immune cell infiltration and the difference of tumor microenvironment were identified in high-risk and low-risk groups. RESULTS: The WGCNA co-expression analysis identified 49 ER genes that are highly associated with EC prognosis. Using univariate Cox regression and LASSO regression analysis, we developed prognostic risk models based on nine signature genes (four mRNAs and five lncRNAs). Both in the training and in the test sets, the overall survival (OS) of EC patients in the high-risk group was significantly lower than that in the low-risk group. The Kaplan-Meier curve and the ROC curve demonstrate the prognostic model we built can precisely predict the survival with more than 70% accuracy. The correlation analysis between the risk score and the infiltration of immune cells showed that the model can indicate the state of the immune microenvironment in EC. CONCLUSION: In this study, we developed a novel prognostic model for esophageal cancer based on ER stress-related mRNA-lncRNA co-expression profiles that could predict the prognosis, immune cell infiltration, and immunotherapy response in patients with EC. Our results also may provide clinicians with a quantitative tool to predict the survival time of patients and help them individualize treatment strategies for the patients with EC.

System analysis based on the ER stress-related genes identifies WFS1 as a novel therapy target for colon cancer.

BACKGROUND: Colon cancer (COAD) is the third-largest common malignant tumor and the fourth major cause of cancer death in the world. Endoplasmic reticulum (ER) stress has a great influence on cell growth, migration, proliferation, invasion, angiogenesis, and chemoresistance of massive tumors. Although ER stress is known to play an important role in various types of cancer, the prognostic model based on ER stress-related genes (ERSRGs) in colon cancer has not been constructed yet. In this study, we established an ERSRGs prognostic risk model to assess the survival of COAD patients. METHODS: The COAD gene expression profile and clinical information data of the training set were obtained from the GEO database (GSE40967) and the test set COAD gene expression profile and clinical informative data were downloaded from the TCGA database. The endoplasmic reticulum stress-related genes (ERSRGs) were obtained from Gene Set Enrichment Analysis (GSEA) website. Differentially expressed ERSRGs between normal samples and COAD samples were identified by R "limma" package. Based on the univariate, lasso, and multivariate Cox regression analysis, we developed an ERSRGs prognostic risk model to predict survival in COAD patients. Finally, we verified the function of WFS1 in COAD through in vitro experiments. RESULTS: We built a 9-gene prognostic risk model based on the univariate, lasso, and multivariate Cox regression analysis. Kaplan-Meier survival analysis and Receiver operating characteristic (ROC) curve revealed that the prognostic risk model has good predictive performance. Subsequently, we screened 60 compounds with significant differences in the estimated half-maximal inhibitory concentration (IC50) between high-risk and low-risk groups. In addition, we found that the ERSRGs prognostic risk model was related to immune cell infiltration and the expression of immune checkpoint molecules. Finally, we determined that knockdown of the expression of WFS1 inhibits the proliferation of colon cancer cells. CONCLUSIONS: The prognostic risk model we built may help clinicians accurately predict the survival of patients with COAD. Our findings provide valuable insights into the role of ERSRGs in COAD and may provide new targets for COAD therapy.

System analysis based on the cuproptosis-related genes identifies LIPT1 as a novel therapy target for liver hepatocellular carcinoma.

BACKGROUND: Liver hepatocellular carcinoma (LIHC) ranks sixth among the most common types of cancer with a high mortality rate. Cuproptosis is a newly discovered type of cell death in tumor, which is characterized by accumulation of intracellular copper leading to the aggregation of mitochondrial lipoproteins and destabilization of proteins. Thus, understanding the exact effects of cuproptosis-related genes in LIHC and determining their prognosticvalue is critical. However, the prognostic model of LIHC based on cuproptosis-related genes has not been reported. METHODS: Firstly, we downloaded transcriptome data and clinical information of LIHC patients from TCGA and GEO (GSE76427), respectively. We then extracted the expression of cuproptosis-related genes and established a prognostic model by lasso cox regression analysis. Afterwards, the prediction performance of the model was evaluated by Kaplan-Meier survival analysis and receiver operating characteristic curve (ROC). Then, the prognostic model and the expression levels of the three genes were validated using the dataset from GEO. Subsequently, we divided LIHC patients into two subtypes by non-negative matrix factorization (NMF) classification and performed survival analysis. We constructed a Sankey plot linking different subtypes and prognostic models. Next, we calculate the drug sensitivity of each sample from patients in the high-risk group and low-risk group by the R package pRRophetic. Finally, we verified the function of LIPT1 in LIHC. RESULTS: Using lasso cox regression analysis, we developed a prognostic risk model based on three cuproptosis-related genes (GCSH, LIPT1 and CDKN2A). Both in the training and in the test sets, the overall survival (OS) of LIHC patients in the low-risk group was significantly longer than that in the high-risk group. By performing NMF cluster, we identified two molecular subtypes of LIHC (C1 and C2), with C1 subtype having significantly longer OS and PFS than C2 subtype. The ROC analysis indicated that our model had a precisely predictive capacity for patients with LIHC. The multivariate Cox regression analysis indicated that the risk score is an independent predictor. Subsequently, we identified 71 compounds with IC50 values that differed between the high-risk and low-risk groups. Finally, we determined that knockdown of LIPT1 gene expression inhibited proliferation and invasion of hepatoma cells. CONCLUSION: In this study, we developed a novel prognostic model for hepatocellular carcinoma based on cuproptosis-related genes that can effectively predict the prognosis of LIHC patients. The model may be helpful for clinicians to make clinical decisions for patients with LIHC and provide valuable insights for individualized treatment. Two distinct subtypes of LIHC were identified based on cuproptosis-related genes, with different prognosis and immune characteristics. In addition, we verified that LIPT1 may promote proliferation, invasion and migration of LIHC cells. LIPT1 might be a new potential target for therapy of LIHC.

Empirical study and model simulation of global stock market dynamics during COVID-19.

At the beginning of 2020, COVID-19 swept the world and changed various aspects of human society, such as economy and finance, life and health, migration and population. We first empirically study how the dynamic behaviors of stock markets are affected by COVID-19, and focus on the large volatility dynamics, variation-fluctuation correlation function and epidemic-fluctuation correlation function. Then we generalize the Heston model to simulate the global stock market dynamics, and an epidemic index computed from empirical data is directly taken as the external force in the modelling.

Polymer Encapsulation Strategy toward 3D Printable, Sustainable, and Reliable Form-Stable Phase Change Materials for Advanced Thermal Energy Storage.

Form-stable phase change materials (PCMs) have garnered tremendous attention in thermal energy storage (TES) owing to their remarkable latent heat. However, the integration of intelligent manufacturing, recycling, and optimized multifunction is considered not feasible for form-stable PCMs due to the restriction of encapsulation technology. Here, an excellent polymer encapsulation strategy is proposed to prepare 3D printable, sustainable, and reliable form-stable PCMs (SiPCM-x), which are universal for petroleum-based and biobased long alkyl compounds. SiPCM-x have top-class latent heat, and the phase-change temperatures are tunable from body temperature to high temperature. The in situ formative bottlebrush phase-change polysiloxane networks are used as supporting materials, and the encapsulation mechanism is clarified. Sirbw-250 can be degraded and re-encapsulated to achieve recycling. Besides, Sirbw-250 is fabricated as the customer-designed objects with shape-changing behavior via 3D printing. By introducing the metal foams and nano-coatings, the resulting phase-change composites simultaneously exhibit excellent superhydrophobicity, mechanical properties, thermal conductivity, electromagnetic interference shielding behavior, and solar-, electric-, and magnetic-to-thermal energy conversion ability. Besides, S-Ni-SiPCM-250 can be applied in the wearable functional devices and movable solar-thermal charging. This strategy will lead to huge renovation in the TES field and provide an efficient guideline for designing advanced form-stable PCMs.

Robust, Multiresponsive, Superhydrophobic, and Oleophobic Nanocomposites via a Highly Efficient Multifluorination Strategy.

Artificial superhydrophobic surfaces are garnering constant attention due to their wide applications. However, it is a great challenge for superhydrophobic materials to simultaneously achieve good oil repellency, mechanochemical robustness, adhesion, thermomechanical properties, and multiresponsive ability. Herein, we propose a highly efficient multifluorination strategy to prepare superhydrophobic nanocomposites with the above features, which can be used as monoliths or coatings on various substrates. In this strategy, long-chain perfluorinated epoxy (PFEP) provides outstanding water/oil repellency, tetrafluorophenyl-based epoxy (FEP) possesses good thermodynamic compatibility with PFEP and increases the mechanical performance of the matrix, and carbon nanotubes grafted with perfluorinated segments and flexible spacers (FCNTs) tailor the surface roughness as well as impart multiple functions and ensure good binding interfaces. Notedly, all of the applications of constrained long-chain perfluorinated compounds are achieved via thiol-ene click chemistry, following the ethos of atom economy. The resultant PFEP30/FCNTs40 exhibits superhydrophobicity and oleophobicity, thermal conductivity (1.33 W·m-1·K-1), electronic conductivity (232 S m-1), and electromagnetic interference shielding properties (∼30 dB at 8.2-12.4 GHz, 200 µm). Importantly, after different extreme physical/chemical tests, the PFEP30/FCNTs40 coating still shows outstanding water/oil repellency. In addition, the coating exhibits good photo/electrothermal conversion ability and shows the potential for sensor application. Moreover, the novel strategy provides an efficient guideline for large-scale preparation of robust, multiresponsive, superhydrophobic, and oleophobic materials.

Cryo-EM structure of S-Trimer, a subunit vaccine candidate for COVID-19.

Within a year after its emergence, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 100 million people worldwide with a death toll over 2 million. Vaccination remains the best hope to ultimately put this pandemic to an end. Here, using Trimer-Tag technology, we produced both wild-type (WT) and furin site mutant (MT) S-Trimers for COVID-19 vaccine studies. Cryo-EM structures of the WT and MT S-Trimers, determined at 3.2 Å and 2.6 Å respectively, revealed that both antigens adopt a tightly closed conformation and their structures are essentially identical to that of the previously solved full-length WT S protein in detergent. The tightly closed conformation is stabilized by fatty acid and polysorbate 80 binding at the receptor binding domains (RBDs) and the N terminal domains (NTDs) respectively. Additionally, we identified an important pH switch in the WT S-Trimer that shows dramatic conformational change and accounts for its increased stability at lower pH. These results validate Trimer-Tag as a platform technology in production of metastable WT S-Trimer as a candidate for COVID-19 subunit vaccine.IMPORTANCEEffective vaccine against SARS-CoV-2 is critical to end the COVID-19 pandemic. Here, using Trimer-Tag technology, we are able to produce stable and large quantities of WT S-Trimer, a subunit vaccine candidate for COVID-19 with high safety and efficacy from animal and Phase 1 clinical trial studies. Cryo-EM structures of the S-Trimer subunit vaccine candidate show that it predominately adopts tightly closed pre-fusion state, and resembles that of the native and full-length spike in detergent, confirming its structural integrity. WT S-Trimer is currently being evaluated in global Phase 2/3 clinical trial. Combining with published structures of the S protein, we also propose a model to dissect the conformation change of the spike protein before receptor binding.

Construction of sequence-defined polytriazoles by IrAAC and CuAAC reactions.

Here we report the first synthesis of sequence-defined polytriazoles, in which different side groups are sequentially anchored to the C-5 position of 1,2,3-triazole rings. By using efficient synthetic strategies based on IrAAC and CuAAC, different monodispersed polytriazoles with up to ∼5.3 kDa and 31-mer were constructed. Structural characterization via NMR, SEC, MALDI-TOF-MS, tandem MS and FTICR-MS evidenced the formation of polytriazoles with the desired specified sequences and exact chain lengths.