Improving drug-target affinity prediction via feature fusion and knowledge distillation.

Rapid and accurate prediction of drug-target affinity can accelerate and improve the drug discovery process. Recent studies show that deep learning models may have the potential to provide fast and accurate drug-target affinity prediction. However, the existing deep learning models still have their own disadvantages that make it difficult to complete the task satisfactorily. Complex-based models rely heavily on the time-consuming docking process, and complex-free models lacks interpretability. In this study, we introduced a novel knowledge-distillation insights drug-target affinity prediction model with feature fusion inputs to make fast, accurate and explainable predictions. We benchmarked the model on public affinity prediction and virtual screening dataset. The results show that it outperformed previous state-of-the-art models and achieved comparable performance to previous complex-based models. Finally, we study the interpretability of this model through visualization and find it can provide meaningful explanations for pairwise interaction. We believe this model can further improve the drug-target affinity prediction for its higher accuracy and reliable interpretability.

Machine Learning-Guided Prediction of Desalination Capacity and Rate of Porous Carbons for Capacitive Deionization.

Nowadays, capacitive deionization (CDI) has emerged as a prominent technology in the desalination field, typically utilizing porous carbons as electrodes. However, the precise significance of electrode properties and operational conditions in shaping desalination performance remains blurry, necessitating numerous time-consuming and resource-intensive CDI experiments. Machine learning (ML) presents an emerging solution, offering the prospect of predicting CDI performance with minimal investment in electrode material synthesis and testing. Herein, four ML models are used for predicting the CDI performance of porous carbons. Among them, the gradient boosting model delivers the best performance on test set with low root mean square error values of 2.13 mg g-1 and 0.073 mg g-1 min-1 for predicting desalination capacity and rate, respectively. Furthermore, SHapley Additive exPlanations is introduced to analyze the significance of electrode properties and operational conditions. It highlights that electrolyte concentration and specific surface area exert a substantially more influential role in determining desalination performance compared to other features. Ultimately, experimental validation employing metal-organic frameworks-derived porous carbons and biomass-derived porous carbons as CDI electrodes is conducted to affirm the prediction accuracy of ML models. This study pioneers ML techniques for predicting CDI performance, offering a compelling strategy for advancing CDI technology.

Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning.

Accurate prediction of atomic partial charges with high-level quantum mechanics (QM) methods suffers from high computational cost. Numerous feature-engineered machine learning (ML)-based predictors with favorable computability and reliability have been developed as alternatives. However, extensive expertise effort was needed for feature engineering of atom chemical environment, which may consequently introduce domain bias. In this study, SuperAtomicCharge, a data-driven deep graph learning framework, was proposed to predict three important types of partial charges (i.e. RESP, DDEC4 and DDEC78) derived from high-level QM calculations based on the structures of molecules. SuperAtomicCharge was designed to simultaneously exploit the 2D and 3D structural information of molecules, which was proved to be an effective way to improve the prediction accuracy of the model. Moreover, a simple transfer learning strategy and a multitask learning strategy based on self-supervised descriptors were also employed to further improve the prediction accuracy of the proposed model. Compared with the latest baselines, including one GNN-based predictor and two ML-based predictors, SuperAtomicCharge showed better performance on all the three external test sets and had better usability and portability. Furthermore, the QM partial charges of new molecules predicted by SuperAtomicCharge can be efficiently used in drug design applications such as structure-based virtual screening, where the predicted RESP and DDEC4 charges of new molecules showed more robust scoring and screening power than the commonly used partial charges. Finally, two tools including an online server (http://cadd.zju.edu.cn/deepchargepredictor) and the source code command lines (https://github.com/zjujdj/SuperAtomicCharge) were developed for the easy access of the SuperAtomicCharge services.

Single-cell transcriptomics dissects the transcriptome alterations of hematopoietic stem cells in myelodysplastic neoplasms.

BACKGROUND: Myelodysplastic neoplasms (MDS) are myeloid neoplasms characterized by disordered differentiation of hematopoietic stem cells and a predisposition to acute myeloid leukemia (AML). The underline pathogenesis remains unclear. METHODS: In this study, the trajectory of differentiation and mechanisms of leukemic transformation were explored through bioinformatics analysis of single-cell RNA-Seq data from hematopoietic stem and progenitor cells (HSPCs) in MDS patients. RESULTS: Among the HSPC clusters, the proportion of common myeloid progenitor (CMP) was the main cell cluster in the patients with excess blasts (EB)/ secondary AML. Cell cycle analysis indicated the CMP of MDS patients were in an active proliferative state. The genes involved in the cell proliferation, such as MAML3 and PLCB1, were up-regulated in MDS CMP. Further validation analysis indicated that the expression levels of MAML3 and PLCB1 in patients with MDS-EB were significantly higher than those without EB. Patients with high expression of PLCB1 had a higher risk of transformation to AML. PLCB1 inhibitor can suppress proliferation, induce cell cycle arrest, and activate apoptosis of leukemic cells in vitro. CONCLUSION: This study revealed the transcriptomic change of HSPCs in MDS patients along the pseudotime and indicated that PLCB1 plays a key role in the transformation of MDS into leukemia.

TrimNet: learning molecular representation from triplet messages for biomedicine.

MOTIVATION: Computational methods accelerate drug discovery and play an important role in biomedicine, such as molecular property prediction and compound-protein interaction (CPI) identification. A key challenge is to learn useful molecular representation. In the early years, molecular properties are mainly calculated by quantum mechanics or predicted by traditional machine learning methods, which requires expert knowledge and is often labor-intensive. Nowadays, graph neural networks have received significant attention because of the powerful ability to learn representation from graph data. Nevertheless, current graph-based methods have some limitations that need to be addressed, such as large-scale parameters and insufficient bond information extraction. RESULTS: In this study, we proposed a graph-based approach and employed a novel triplet message mechanism to learn molecular representation efficiently, named triplet message networks (TrimNet). We show that TrimNet can accurately complete multiple molecular representation learning tasks with significant parameter reduction, including the quantum properties, bioactivity, physiology and CPI prediction. In the experiments, TrimNet outperforms the previous state-of-the-art method by a significant margin on various datasets. Besides the few parameters and high prediction accuracy, TrimNet could focus on the atoms essential to the target properties, providing a clear interpretation of the prediction tasks. These advantages have established TrimNet as a powerful and useful computational tool in solving the challenging problem of molecular representation learning. AVAILABILITY: The quantum and drug datasets are available on the website of MoleculeNet: http://moleculenet.ai. The source code is available in GitHub: https://github.com/yvquanli/trimnet. CONTACT: xjyao@lzu.edu.cn, songsen@tsinghua.edu.cn.

A propensity score-matched analysis of neoadjuvant chemoimmunotherapy versus surgery alone for locally advanced esophageal squamous cell carcinoma.

BACKGROUND: The aim of this study was to evaluate the safety, efficacy, and oncologic outcomes of neoadjuvant immunotherapy combined with chemotherapy (NICT) group and surgery alone group in the treatment of patients with locally advanced esophageal squamous cell carcinoma (ESCC). METHODS: A series of 232 consecutive patients who underwent surgery with or without NICT from June 2019 to August 2022 were evaluated. We performed propensity score matching between the NICT and surgery alone groups on the basis of estimated propensity scores for each patient. RESULTS: After propensity score matching, data of 137 patients with clinical stages II-IV ESCC, including 85 receiving surgery alone and 52 receiving NICT, were analyzed. Compared with the surgery alone group (301.7 ± 94.4 min), the operation time was significantly longer in the NICT group (333.4 ± 79.7 min). However, there was no significant difference between the two groups in the postoperative complications, intraoperative blood loss, thoracic fluid volume, chest tube duration, lengths of intensive care unit stay and postoperative hospitalization. Additionally, 90-day mortality rate and 30-day readmission were similar in both groups. CONCLUSIONS: Overall, NICT followed by esophagectomy appears to be safe and feasible for locally advanced ESCC. However, further multicenter prospective clinical trials are needed to validate our results.

CODD-Pred: A Web Server for Efficient Target Identification and Bioactivity Prediction of Small Molecules.

Target identification and bioactivity prediction are critical steps in the drug discovery process. Here we introduce CODD-Pred (COmprehensive Drug Design Predictor), an online web server with well-curated data sets from the GOSTAR database, which is designed with a dual purpose of predicting potential protein drug targets and computing bioactivity values of small molecules. We first designed a double molecular graph perception (DMGP) framework for target prediction based on a large library of 646 498 small molecules interacting with 640 human targets. The framework achieved a top-5 accuracy of over 80% for hitting at least one target on both external validation sets. Additionally, its performance on the external validation set comprising 200 molecules surpassed that of four existing target prediction servers. Second, we collected 56 targets closely related to the occurrence and development of cancer, metabolic diseases, and inflammatory immune diseases and developed a multi-model self-validation activity prediction (MSAP) framework that enables accurate bioactivity quantification predictions for small-molecule ligands of these 56 targets. CODD-Pred is a handy tool for rapid evaluation and optimization of small molecules with specific target activity. CODD-Pred is freely accessible at http://codd.iddd.group/.

Several non-salt and solid thienopyridine derivatives as oral P2Y12 receptor inhibitors with good stability.

A series of novel thienopyridine derivatives were designed and synthesized as P2Y12 receptor inhibitors. Several solid compounds were assessed for inhibitory effect where they exhibited stronger potency than clopidogrel. Compound 6b and 6g were evaluated for metabolism to verify that they could overcome clopidogrel resistance and for toxicity where they showed lower toxicity than prasugrel. Compound 6b exhibited lower risk of bleeding than prasugrel and showed good stability under stress testing. Overall, as a promising antiplatelet agent, representative compound 6b showed the following advantages: (1) no drug resistance for CYP2C19 poor metabolizers; (2) higher potency than clopidogrel; (3) lower toxicity than prasugrel; (4) lower risk of bleeding than prasugrel; (5) good stability as a non-salt solid.

Acute ammonia stress-induced oxidative and heat shock responses modulated by transcription factors in Litopenaeus vannamei.

The present study aimed to examine the effects of short-term exposure to ammonia on stress and oxidative responses in shrimp (Litopenaeus vannamei) and to determine whether the antioxidant system related to the regulatory role of transcription factors and stress proteins was activated. Shrimp were exposed ammonia-N at four concentrations: 0 (control), 5, 10, and 15 mg/L, for 48 h. The hepatopancreas was sampled to measure the levels of glutathione (GSH), malondialdehyde (MDA), nitric oxide (NO); the activities of superoxide dismutase (SOD), catalase (CAT), nitric oxide synthase (NOS); and the expression levels of GSH-px (encoding glutathione peroxidase), GST (encoding glutathione-S-transferase), HSP70 (encoding heat shock protein 70), HSP90 (encoding heat shock protein 90), p53, RELISH, and AKIRIN. We observed that exposure to a high ammonia content increased the abundance of oxidative factors (MDA, CAT, SOD, NOS, and NO), reduced the levels of GSH, and upregulated the mRNA expression levels of antioxidant genes (GSH-px and GST), stress-related genes (HSP70 and HSP90), and transcription factor genes (p53, RELISH, and AKIRIN). These results indicated that ammonia induced oxidative stress and inflammation. Both enzymatic and nonenzymatic antioxidant defense systems are involved, which might be regulated by HSPs, as well as certain transcription factors, such as p53 and nuclear factor kappa B (NF-κB), thus mounting an adaptive response to help rebalance redox homoeostasis.

Circulating extracellular vesicles from patients with valvular heart disease induce neutrophil chemotaxis via FOXO3a and the inhibiting role of dexmedetomidine.

We previously demonstrated that circulating extracellular vesicles (EVs) from patients with valvular heart disease (VHD; vEVs) contain inflammatory components and inhibit endothelium-dependent vasodilation. Neutrophil chemotaxis plays a key role in renal dysfunction, and dexmedetomidine (DEX) can reduce renal dysfunction in cardiac surgery. However, the roles of vEVs in neutrophil chemotaxis and effects of DEX on vEVs are unknown. Here, we investigated the impact of vEVs on neutrophil chemotaxis in kidneys and the influence of DEX on vEVs. Circulating EVs were isolated from healthy subjects and patients with VHD. The effects of EVs on chemokine generation, forkhead box protein O3a (FOXO3a) pathway activation and neutrophil chemotaxis on cultured human umbilical vein endothelial cells (HUVECs) and kidneys in mice and the influence of DEX on EVs were detected. vEVs increased FOXO3a expression, decreased phosphorylation of Akt and FOXO3a, promoted FOXO3a nuclear translocation, and activated the FOXO3a signaling pathway in vitro. DEX pretreatment reduced vEV-induced CXCL4 and CCL5 expression and neutrophil chemotaxis in cultured HUVECs via the FOXO3a signaling pathway. vEVs were also found to suppress Akt phosphorylation and activate FOXO3a signaling to increase plasma levels of CXCL4 and CCL5 and neutrophil accumulation in kidney. The overall mechanism was inhibited in vivo with DEX pretreatment. Our data demonstrated that vEVs induced CXCL4-CCL5 to stimulate neutrophil infiltration in kidney, which can be inhibited by DEX via the FOXO3a signaling. Our findings reveal a unique mechanism involving vEVs in inducing neutrophils chemotaxis and may provide a novel basis for using DEX in reducing renal dysfunction in valvular heart surgery.

Overexpression of inducible nitric oxide synthase in the diabetic heart compromises ischemic postconditioning.

Ischemia postconditioning (PTC) can reduce myocardial ischemia/reperfusion injury. However, the effectiveness of PTC cardioprotection is reduced or lost in diabetes and the mechanisms are largely unclear. Hyperglycemia can induce overexpression of inducible nitric oxide synthesis (iNOS) in the myocardium of diabetic subjects. However, it is unknown whether or not iNOS especially its overexpression plays an important role in the loss of cardioprotection of PTC in diabetes. C57BL6 and iNOS-/- mice were treated with streptozotocin to induce diabetes. Part of diabetic C57BL6 mice were also treated with an iNOS specific inhibitor, 1400 W. Mice were subjected to myocardial ischemia/ reperfusion with/without PTC. The hemodynamic parameters, plasma levels of cardiac troponin T (cTnT), TNF-α, IL-6 and nitric oxide (NO) were monitored. The myocardial infarct size, superoxide anion (O2-) generation, nitrotyrosine production and apoptosis were measured. The expression of phosphorylated Akt, endothelial NOS (eNOS), iNOS and Erk1/2 in ischemic heart were detected by immunoblot analysis. In diabetic C57BL6 and iNOS-/- mice, the post-ischemic hemodynamics were impaired, the cTnT, TNF-α, IL-6 level, myocardial infarct size, apoptotic index, O2- and nitrotyrosine generation were increased and the Akt/eNOS signal pathways were inhibited. PTC improved hemodynamic parameters, reduced cTnT level, myocardial infarct size, apoptotic index, O2- and nitrotyrosine generation and activated Akt/eNOS and Erk1/2 signal pathways in both non-diabetic C57BL6 and iNOS-/- mice as well as diabetic iNOS-/- mice, but not in diabetic C57BL6 mice. PTC also increased NO production in both non-diabetic and diabetic C57BL6 and iNOS-/- mice, and enhanced iNOS expression in non-diabetic C57BL6 mice. 1400 W restored the cardioprotection of PTC in diabetic C57BL6 mice. Our data demonstrated that PTC reduced myocardial ischemia/reperfusion injury in non-diabetic mice but not C57BL6 diabetic mice. Deletion of iNOS restored the cardioprotection of PTC in diabetic mice. Our findings suggest that iNOS plays a key role in the reduction of cardioprotection of PTC in diabetes and may provide a therapeutic target for diabetic patients.

Dietary supplementation of biofloc influences growth performance, physiological stress, antioxidant status and immune response of juvenile sea cucumber Apostichopus japonicus (Selenka).

Bioflocs are rich in various probiotics and bioactive compounds, which play an important role in improving growth and health status of aquatic organisms. A 60-day experiment was conducted to investigate the effects of dietary supplementation of biofloc on growth performance, digestive enzyme activity, physiological stress, antioxidant status, expression of immune-related genes and disease resistance of sea cucumber Apostichopus japonicus. Juvenile sea cucumbers were fed five experimental diets containing graded levels of biofloc from 0% to 20% (referred as B0, B5, B10, B15 and B20, respectively). The results showed that the sea cucumbers at dietary supplementation levels of 10%-15% biofloc had significantly higher specific growth rate (SGR) compared to control group (diet B0). Digestive enzyme activity increased with the increasing of dietary biofloc level, while no significant difference was found between diets B15 and B20. Dietary supplementation of biofloc also had significant influences on physiological stress parameters except for lactate. There was no significant discrepancy in total coelomocytes counts (TCC) in coelomic fluid of sea cucumber between the treatments. Phagocytosis and respiratory burst of cellular immune at 15% and 20% biofloc levels were significantly higher than those of control group. Significant increases in superoxide dismutase (SOD), total nitric oxide synthase (T-NOS), lysozyme (LSZ), acid phosphatase (ACP) and alkaline phosphatase (AKP) activities of sea cucumber were found at highest dietary supplementation level of 20% biofloc. The expression patterns of immune-related genes (i.e., Hsp90, Hsp70, p105, Rel, NOS and LSZ) in tissues of sea cucumber were analyzed between the experimental diets, and a general trend of up-regulation was observed at higher biofloc levels. Furthermore, dietary 10%-20% biofloc significantly reduced cumulative mortality of sea cucumber after being challenged with Vibrio splendidus. In conclusion, dietary supplementation of biofloc could improve growth performance of A. japonicus, by increasing digestive enzyme activity, releasing physiological stress, enhancing immune response and disease resistance of sea cucumber. The suitable supplemental level of approximately 15% biofloc was recommended in the present study.

Regulation of growth, intestinal microbiota, non-specific immune response and disease resistance of sea cucumber Apostichopus japonicus (Selenka) in biofloc systems.

Bioflocs are not only a source of supplemental nutrition but also provide substantial probiotic bacteria and bioactive compounds, which play an important role in improving physiological health of aquatic organisms. A 60-day experiment was conducted to investigate the growth, intestinal microbiota, non-specific immune response and disease resistance of sea cucumber in biofloc systems with different carbon sources (glucose, sucrose and starch). Control (no biofloc) and three biofloc systems were set up, and each group has three replicates. The results showed that biofloc volume (BFV) and total suspended solids (TSS) increased in the sequences of glucose > sucrose > starch and green sea cucumber > white sea cucumber during the experiment. The highest specific growth rates (SGRs) were observed in biofloc system with glucose as carbon source, which also had relatively lower glucose, lactate and cortisol levels in coelomic fluid and higher glycogen content in muscle compared to other groups. There were significant increased Bacillus and Lactobacillus counts of sea cucumber intestine in biofloc systems, and the activities of superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) also showed obvious ascending trends. Significant increases in total coelomocytes counts (TCC), phagocytosis, respiratory burst, complement C3 content and lysozyme (LSZ) and acid phosphatase (ACP) activities of sea cucumber were all found in biofloc system (glucose). The expression patterns of most immune-related genes (i.e. Hsp90, Hsp70, c-type lectin (CL), toll-like receptor (TLR)) were up-regulated, suggesting the promotion of pathogen recognition ability and immune signaling pathways activation by biofloc. Furthermore, green and white sea cucumber had significantly higher survival rates in biofloc systems during the 14-day challenge test. In conclusion, biofloc technology could improve growth and physiological health of A. japonicus, by optimizing intestinal microbiota, strengthening antioxidant ability, enhancing non-specific immune response and disease resistance against pathogens, meanwhile glucose was recommended as optimal carbon source in biofloc system of sea cucumber culturing.

Synthesis of a Novel Series of Amino Acid Prodrugs Based on Thienopyridine Scaffolds and Evaluation of Their Antiplatelet Activity.

The thienopyridines class of drugs used as P2Y12 receptor antagonists plays a vital role in antiplatelet therapy. To further optimized this compound class, we designed and synthesized a series of amino acid prodrugs of 2-hydroxytetrahydrothienopyridine. All compounds were then evaluated for their inhibitory effect on ADP-induced platelet aggregation in rats and then ED50 and bleeding time of the most potent compounds were compared with commercial drugs. The results showed compound 5c could be a potent and safe candidate for further research.

Hierarchically Porous Carbon Derived from PolyHIPE for Supercapacitor and Deionization Applications.

Hierarchically porous carbon (HPC) materials with interconnected porous texture are produced from a porous poly(divinylbenzene) precursor, which is synthesized by polymerizing high-internal-phase emulsions. After carbonation, the macroporous structures of the poly(divinylbenzene) precursor are preserved and enormous micro-/mesopores via carbonation with KOH are produced, resulting in an interconnected hierarchically porous network. The prepared HPC has a maximum specific surface area of 2189 m2 g-1. The electrode materials for supercapacitors and capacitive deionization devices employing the formed HPC exhibit a high specific capacity of 88 mA h g-1 through a voltage range of 1 V (319 F g-1 at 1 A g-1) and a superior electrosorption capacity of 21.3 mg g-1 in 500 mg L-1 NaCl solution. The excellent capacitive performance could be ascribed to the combination of high specific surface area and favorable hierarchically porous structure.

Tbx18-dependent differentiation of brown adipose tissue-derived stem cells toward cardiac pacemaker cells.

A cell-sourced biological pacemaker is a promising therapeutic approach for sick sinus syndrome (SSS) or severe atrial ventricular block (AVB). Adipose tissue-derived stem cells (ATSCs), which are optimal candidate cells for possible use in regenerative therapy for acute or chronic myocardial injury, have the potential to differentiate into spontaneous beating cardiomyocytes. However, the pacemaker characteristics of the beating cells need to be confirmed, and little is known about the underlying differential mechanism. In this study, we found that brown adipose tissue-derived stem cells (BATSCs) in mice could differentiate into spontaneous beating cells in 15% FBS Dulbecco's modified Eagle's medium (DMEM) without additional treatment. Subsequently, we provide additional evidence, including data regarding ultrastructure, protein expression, electrophysiology, and pharmacology, to support the differentiation of BATSCs into a cardiac pacemaker phenotype during the course of early cultivation. Furthermore, we found that silencing Tbx18, a key transcription factor in the development of pacemaker cells, terminated the differentiation of BATSCs into a pacemaker phenotype, suggesting that Tbx18 is required to direct BATSCs toward a cardiac pacemaker fate. The expression of Tbx3 and shox2, the other two important transcription factors in the development of pacemaker cells, was decreased by silencing Tbx18, which suggests that Tbx18 mediates the differentiation of BATSCs into a pacemaker phenotype via these two downstream transcription factors.

Dissociative photoionization of ß-pinene: an experimental and theoretical study.

We investigated the photoionization and dissociation photoionization of the ß-pinene molecular using time-of-flight mass spectrometry with a tunable vacuum ultraviolet source in the region from 8.00eV to 15.50eV. The experimental ionization energy (IE) value is 8.60eV using electron impact as the ionization source which is not in good agreement with theoretical value (8.41 eV) with a G3MP2 method. We obtained the accurate IE of ß-pinene (8.45 ± 0.03eV) derived from the efficiency spectrum which is in good agreement with the theoretical value (8.38eV) of the CBS-QB3 method. We elucidated the dissociation pathways of primary fragment ions from the ß-pinene cation on the basis of experimental observations in combination with theoretical calculations. Most of the dissociation pathways occur via a rearrangement reaction prior to dissociation. We also determined the structures of the transition states and intermediates for those isomerization processes.

Exosomes promote pre-metastatic niche formation in colorectal cancer.

It is well known that colorectal cancer (CRC) has a high morbidity rate, a poor prognosis when metastasized, and a greatly shortened 5-year survival rate. Therefore, understanding the mechanism of tumor metastasis is still important. Based on the "seed and soil" theory, the concept of " premetastatic niche (PMN)" was introduced by Kaplan et al. The complex interaction between primary tumors and the metastatic organ provides a beneficial microenvironment for tumor cells to colonize at a distance. With further exploration of the PMN, exosomes have gradually attracted interest from researchers. Exosomes are extracellular vesicles secreted from cells that include various biological information and are involved in communication between cells. As a key molecule in the PMN, exosomes are closely related to tumor metastasis. In this article, we obtained information by conducting a comprehensive search across academic databases including PubMed and Web of Science using relevant keywords. Only recent, peer-reviewed articles published in the English language were considered for inclusion. This study aims to explore in depth how exosomes promote the formation of pre-metastatic microenvironment (PMN) in colorectal cancer and its related mechanisms.

Progress of lymphocyte activation gene 3 and programmed cell death protein 1 antibodies for cancer treatment: A review.

The application of immune checkpoint inhibitors has proven to be an effective treatment for cancer. Immune checkpoints such as programmed cell death protein 1/programmed cell death protein 1 ligand 1 (PD-1/PD-L1), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), T-cell immunoglobulin-3 (TIM-3), T-cell immunoglobulin and ITIM domain (TIGIT), and lymphocyte activation gene-3 (LAG-3) have received extensive attention, and the efficacy of antibodies or inhibitors against these checkpoints (either alone or in combination) has been evaluated in many tumors. This paper provides a brief overview of the PD-1 and LAG-3 checkpoints, and then shifts focus to the combined use of PD-1 and LAG-3 antibodies in both in vivo and in vitro experiments. In the in vitro experiments, we examined the correlation between the expression and activation of these inhibitors on T cells, and also assessed toxicity in animals in preparation for in vivo experiments. The effects of the combined use of PD-1 and LAG-3 antibodies were then summarized in animal models of melanoma, MC38 carcinoma, and other tumors. In clinical studies, the combined application of these antibodies was assessed in patients with melanoma, colorectal, breast, and renal cell cancers, as well as other solid tumors. In general, the combination of PD-1 and LAG-3 antibodies has shown promising results in both in vivo and in vitro studies.

Heterointerface regulation of covalent organic framework-anchored graphene via a solvent-free strategy for high-performance supercapacitor and hybrid capacitive deionization electrodes.

Covalent organic frameworks (COFs) with customizable geometry and redox centers are an ideal candidate for supercapacitors and hybrid capacitive deionization (HCDI). However, their poor intrinsic conductivity and micropore-dominated pore structures severely impair their electrochemical performance, and the synthesis process using organic solvents brings serious environmental and cost issues. Herein, a 2D redox-active pyrazine-based COF (BAHC-COF) was anchored on the surface of graphene in a solvent-free strategy for heterointerface regulation. The as-prepared BAHC-COF/graphene (BAHCGO) nanohybrid materials possess high-speed charge transport offered by the graphene carrier and accelerated electrolyte ion migration within the BAHC-COF, allowing ions to effectively occupy ion storage sites inside BAHC. As a result, the BAHCGO//activated carbon asymmetric supercapacitor achieves a high energy output of 61.2 W h kg-1 and a satisfactory long-term cycling life. More importantly, BAHCGO-based HCDI possesses a high salt adsorption capacity (SAC) of 67.5 mg g-1 and excellent long-term desalination/regeneration stability. This work accelerates the application of COF-based materials in the fields of energy storage and water treatment.