The Different Strategies for the Radiolabeling of [211At]-Astatinated Radiopharmaceuticals.

Astatine-211 (211At) has emerged as a promising radionuclide for targeted alpha therapy of cancer by virtue of its favorable nuclear properties. However, the limited in vivo stability of 211At-labeled radiopharmaceuticals remains a major challenge. This review provides a comprehensive overview of the current strategies for 211At radiolabeling, including nucleophilic and electrophilic substitution reactions, as well as the recent advances in the development of novel bifunctional coupling agents and labeling approaches to enhance the stability of 211At-labeled compounds. The preclinical and clinical applications of 211At-labeled radiopharmaceuticals, including small molecules, peptides, and antibodies, are also discussed. Looking forward, the identification of new molecular targets, the optimization of 211At production and quality control methods, and the continued evaluation of 211At-labeled radiopharmaceuticals in preclinical and clinical settings will be the key to realizing the full potential of 211At-based targeted alpha therapy. With the growing interest and investment in this field, 211At-labeled radiopharmaceuticals are poised to play an increasingly important role in future cancer treatment.

Recent Research Progress of Porous Graphene and Applications in Molecular Sieve, Sensor, and Supercapacitor.

Porous graphene, including 2D and 3D porous graphene, is widely researched recently. One of the most attractive features is the proper utilization of graphene defects, which combine the advantages of both graphene and porous materials, greatly enriching the applications of porous graphene in biology, chemistry, electronics, and other fields. In this review, the defects of graphene are first discussed to provide a comprehensive understanding of porous graphene. Then, the latest advancements in the preparation of 2D and 3D porous graphene are presented. The pros and cons of these preparation methods are discussed in detail, providing a direction for the fabrication of porous graphene. Moreover, various superior properties of porous graphene are described, laying the foundation for their promising applications. Owing to its abundant morphology, wide distribution of pore size, and remarkable properties benefited from porous structure, porous graphene can not only promote molecular diffusion and electron transfer but also expose more active sites. Consequently, a serious of applications containing gas sieving, liquid separation, sensors, and supercapacitors, are presented. Finally, the challenges confronted during preparation and characterization of porous graphene are discussed, offering guidance for the future development of porous graphene in fabrication, characterization, properties, and applications.

Mitigating radiation-induced brain injury via NLRP3/NLRC4/Caspase-1 pyroptosis pathway: Efficacy of memantine and hydrogen-rich water.

Radiation-induced brain injury (RIBI) is a significant challenge in radiotherapy for head and neck tumors, impacting patients' quality of life. In exploring potential treatments, this study focuses on memantine hydrochloride and hydrogen-rich water, hypothesized to mitigate RIBI through inhibiting the NLRP3/NLRC4/Caspase-1 pathway. In a controlled study involving 40 Sprague-Dawley rats, divided into five groups including a control and various treatment groups, we assessed the effects of these treatments on RIBI. Post-irradiation, all irradiated groups displayed symptoms like weight loss and salivation, with notable variations among different treatment approaches. Particularly, hydrogen-rich water showed a promising reduction in these symptoms. Histopathological analysis indicated substantial hippocampal damage in the radiation-only group, while the groups receiving memantine and/or hydrogen-rich water exhibited significant mitigation of such damage. Molecular studies, revealed a decrease in oxidative stress markers and an attenuated inflammatory response in the treatment groups. Immunohistochemistry further confirmed these molecular changes, suggesting the effectiveness of these agents. Echoing recent scientific inquiries into the protective roles of specific compounds against radiation-induced damages, our study adds to the growing body of evidence on the potential of memantine and hydrogen-rich water as novel therapeutic strategies for RIBI.

Integrative analysis of transcriptome, DNA methylome and chromatin accessibility reveals candidate therapeutic targets in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease and is characterized by primary left ventricular hypertrophy usually caused by mutations in sarcomere genes. The mechanism underlying cardiac remodeling in HCM remains incompletely understood. An investigation of HCM through integrative analysis at multi-omics levels will be helpful for treating HCM. DNA methylation and chromatin accessibility, as well as gene expression, were assessed by nucleosome occupancy and methylome sequencing (NOMe-seq) and RNA-seq, respectively, using the cardiac tissues of HCM patients. Compared with those of the controls, the transcriptome, DNA methylome and chromatin accessibility of the HCM myocardium showed multifaceted differences. At the transcriptome level, HCM hearts returned to the fetal gene program through decreased sarcomeric and metabolic gene expression and increased extracellular matrix gene expression. In the DNA methylome, hypermethylated and hypomethylated differentially methylated regions (DMRs) were identified in HCM. At the chromatin accessibility level, HCM hearts showed changes in different genome elements. Several transcription factors (TFs), including SP1 and EGR1, exhibited a fetal-like pattern of binding motifs in nucleosome-depleted regions (NDRs) in HCM. In particular, the inhibition of SP1 or EGR1 in an HCM mouse model harboring sarcomere mutations markedly alleviated the HCM phenotype of the mutant mice and reversed fetal gene reprogramming. Overall, this study not only provides a high precision multi-omics map of HCM heart tissue but also sheds light on the therapeutic strategy by intervening the fetal gene reprogramming in HCM.

Based on the prognosis model of immunogenes, the prognosis model was constructed to predict the invasion of immune genes and immune cells related to primary liver cancer and its experimental validation.

Background: Primary liver cancer (PLC) is a prevalent malignancy of the digestive system characterized by insidious symptom onset and a generally poor prognosis. Recent studies have highlighted a significant correlation between the initiation and prognosis of liver cancer and the immune function of PLC patients. Purpose: Revealing the expression of PLC-related immune genes and the characteristics of immune cell infiltration provides assistance for the analysis of clinical pathological parameters and prognosis of PLC patients. Methods: PLC-related differentially expressed genes (DEGs) with a median absolute deviation (MAD > 0.5) were identified from TCGA and GEO databases. These DEGs were intersected with immune-related genes (IRGs) from the ImmPort database to obtain PLC-related IRGs. The method of constructing a prognostic model through immune-related gene pairs (IRGPs) is used to obtain IRGPs and conduct the selection of central immune genes. The central immune genes obtained from the selection of IRGPs are validated in PLC. Subsequently, the relative proportions of 22 types of immune cells in different immune risk groups are evaluated, and the differential characteristics of PLC-related immune cells are verified through animal experiments. Results: Through database screening and the construction of an IRGP prognosis model, 84 pairs of IRGPs (P < 0.001) were ultimately obtained. Analysis of these 84 IRGPs revealed 11 central immune genes related to PLC, showing differential expression in liver cancer tissues compared to normal liver tissues. Results from the CiberSort platform indicate differential expression of immune cells such as naive B cells, macrophages, and neutrophils in different immune risk groups. Animal experiments demonstrated altered immune cell proportions in H22 tumor-bearing mice, validating findings from peripheral blood and spleen homogenate analyses. Conclusion: Our study successfully predicted and validated PLC-related IRGs and immune cells, suggesting their potential as prognostic indicators and therapeutic targets for PLC.

Single-cell analysis reveals insights into epithelial abnormalities in ovarian endometriosis.

Ovarian endometriosis is characterized by the growth of endometrial tissue within the ovary, causing infertility and chronic pain. However, its pathophysiology remains unclear. Utilizing high-precision single-cell RNA sequencing, we profile the normal, eutopic, and ectopic endometrium from 34 individuals across proliferative and secretory phases. We observe an increased proportion of ciliated cells in both eutopic and ectopic endometrium, characterized by a diminished expression of estrogen sulfotransferase, which likely confers apoptosis resistance. After translocating to ectopic lesions, endometrial epithelium upregulates nicotinamide N-methyltransferase expression that inhibits apoptosis by promoting deacetylation and subsequent nuclear exclusion of transcription factor forkhead box protein O1, thereby leading to the downregulation of the apoptotic gene BIM. Moreover, epithelial cells in ectopic lesions elevate HLA class II complex expression, which stimulates CD4+ T cells and consequently contributes to chronic inflammation. Altogether, our study provides a comprehensive atlas of ovarian endometriosis and highlights potential therapeutic targets for modulating apoptosis and inflammation.

LPI-SKMSC: Predicting LncRNA-Protein Interactions with Segmented k-mer Frequencies and Multi-space Clustering.

 Long noncoding RNAs (lncRNAs) have significant regulatory roles in gene expression. Interactions with proteins are one of the ways lncRNAs play their roles. Since experiments to determine lncRNA-protein interactions (LPIs) are expensive and time-consuming, many computational methods for predicting LPIs have been proposed as alternatives. In the LPIs prediction problem, there commonly exists the imbalance in the distribution of positive and negative samples. However, there are few existing methods that give specific consideration to this problem. In this paper, we proposed a new clustering-based LPIs prediction method using segmented k-mer frequencies and multi-space clustering (LPI-SKMSC). It was dedicated to handling the imbalance of positive and negative samples. We constructed segmented k-mer frequencies to obtain global and local features of lncRNA and protein sequences. Then, the multi-space clustering was applied to LPI-SKMSC. The convolutional neural network (CNN)-based encoders were used to map different features of a sample to different spaces. It used multiple spaces to jointly constrain the classification of samples. Finally, the distances between the output features of the encoder and the cluster center in each space were calculated. The sum of distances in all spaces was compared with the cluster radius to predict the LPIs. We performed cross-validation on 3 public datasets and LPI-SKMSC showed the best performance compared to other existing methods. Experimental results showed that LPI-SKMSC could predict LPIs more effectively when faced with imbalanced positive and negative samples. In addition, we illustrated that our model was better at uncovering potential lncRNA-protein interaction pairs.

Effect Predictor of Driver Synonymous Mutations Based on Multi-Feature Fusion and Iterative Feature Representation Learning.

Accurate identification of driver mutations is crucial in genetic studies of human cancers. While numerous cancer driver missense mutations have been identified, research into potential cancer drivers for synonymous mutations has shown limited success to date. Here, we developed a novel machine learning framework, epSMic, for predicting cancer driver synonymous mutations. epSMic employs an iterative feature representation scheme that facilitates the learning of discriminative features from various sequential models in a supervised iterative mode. We constructed the benchmark datasets and encoded the embedding sequence, physicochemical property, and basic information such as conservation and splicing feature. The evaluation results on benchmark test datasets demonstrate that epSMic outperforms existing methods, making it a valuable tool for researchers in identifying functional synonymous mutations in cancer. We hope epSMic can enable researchers to concentrate on synonymous mutations that have a functional impact on cancer.

In Situ Growth of High-Quality Single-Crystal Twisted Bilayer Graphene on Liquid Copper.

Twisted bilayer graphene (TBG) generates significant attention in the fundamental research of 2D materials due to its distinct twist-angle-dependent properties. Exploring the efficient production of TBG with a wide range of twist angles stands as one of the major frontiers in moiré materials. Here, the local space-confined chemical vapor deposition growth technique for high-quality single-crystal TBG with twist angles ranging from 0° to 30° on liquid copper substrates is reported. The clean surface, pristine interface, high crystallinity, and thermal stability of TBG are verified by using comprehensive characterization techniques including optical microscopy, electron microscopy, and secondary-ion mass spectrometry. The proportion of TBG in bilayer graphene reaches as high as 89%. In addition, the stacking structure and growth mechanism of TBG are investigated, revealing that the second graphene layer develops beneath the first one. A series of comparative experiments illustrates that the liquid copper surface, with its excellent fluidity, promotes the growth of TBG. Electrical measurements show the twist-angle-dependent electronic properties of as-grown TBG, achieving a room-temperature carrier mobility of 26640 cm2 V-1 s-1 . This work provides an approach for the in situ preparation of 2D twisted materials and facilitates the application of TBG in the fields of electronics.

Low-molecular-weight organic acids-mediated transport of neonicotinoid pesticides through saturated soil porous media: Combined effects of the molecular structures of organic acids and the chemical properties of contaminants.

Empirical information about the transport properties of neonicotinoid pesticides through the soil as affected by the ubiquitous low molecular weight organic acids (LMWOAs) is lacking. Herein, the impacts of three LMWOAs with different molecular structures, including citric acid, acetic acid, and malic acid, on the mobility characteristics of two typical neonicotinoid pesticides (Dinotefuran (DTF) and Nitenpyram (NTP)) were explored. Interestingly, under acidic conditions, different mechanisms were involved in transporting DTF and NTP by adding exogenous LMWOAs. Concretely, acetic acid and malic acid inhibited DTF transport, ascribed to the enhanced electrostatic attraction between DTF and porous media and the additional binding sites provided by the deposited LMWOAs. However, citric acid slightly enhanced DTF mobility due to the fact that the inhibitory effect was weakened by the steric hindrance effect induced by the deposited citric acid with a large molecular size. In comparison, all three LMWOAs promoted NTP transport at pH 5.0. Because the interaction between NTP with soil organic matter (e.g., via π-π stacking interaction) was masked by the LMWOAs coating on soil surfaces. Nevertheless, LMWOAs could promote the mobility of both neonicotinoid pesticides at pH 7.0 due to the steric hindrance effect caused by the deposited organic acids and the competitive retention between LMWOAs and pesticides for effective surface deposition sites of soil particles. Furthermore, the extent of the promotion effects of LMWOAs generally followed the order of citric acid > malic acid > acetic acid. This pattern was highly related to their molecular structures (e.g., number and type of functional groups and molecular size). Additionally, when the background solutions contained Ca2+, the bridging effect of cations also contributed to the transport-enhancement effects of LMWOAs. The findings provide valuable information about the mobility behaviors of neonicotinoid pesticides co-existing with LMWOAs in soil-water systems.

Controllable Synthesis and Growth Mechanism of Interlayer-Coupled Multilayer Graphene.

The potential applications of multilayer graphene in many fields, such as superconductivity and thermal conductivity, continue to emerge. However, there are still many problems in the growth mechanism of multilayer graphene. In this paper, a simple control strategy for the preparation of interlayer-coupled multilayer graphene on a liquid Cu substrate was developed. By adjusting the flow rate of a carrier gas in the CVD system, the effect for finely controlling the carbon source supply was achieved. Therefore, the carbon could diffuse from the edge of the single-layer graphene to underneath the layer of graphene and then interlayer-coupled multilayer graphene with different shapes were prepared. Through a variety of characterization methods, it was determined that the stacked mode of interlayer-coupled multilayer graphene conformed to AB-stacking structure. The small multilayer graphene domains stacked under single-layer graphene was first found, and the growth process and growth mechanism of interlayer-coupled multilayer graphene with winged and umbrella shapes were studied, respectively. This study reveals the growth mechanism of multilayer graphene grown by using a carbon source through edge diffusion, paving the way for the controllable preparation of multilayer graphene on a liquid Cu surface.

Magnetoresistance in Organic Spin Valves Based on Acid-Exfoliated 2D Covalent Organic Frameworks Thin Films.

Covalent organic frameworks (COFs), as a burgeoning class of crystalline porous materials, have made significant progress in their application to optoelectronic devices such as field-effect transistors, memristors, and photodetectors. However, the insoluble features of microcrystalline two-dimensional (2D) COF powders limit development of their thin film devices. Additionally, the exploration of spin transport properties in this category of π-conjugated skeleton materials remains vacant thus far. Herein, an imine-linked 2D Py-Np COF nanocrystalline powder was synthesized by Schiff base condensation of 4,4',4'',4'''-(pyrene-1,3,6,8-tetrayl)tetraaniline and naphthalene-2,6-dicarbaldehyde. Then, we prepared a large-scale free-standing Py-Np COF film via a top-down strategy of chemically assisted acid exfoliation. Moreover, high-quality COF films acted as active layers were transferred onto ferromagnetic La0.67 Sr0.33 MnO3 (LSMO) electrodes for the first attempt to fabricate organic spin valves (OSVs) based on 2D COF materials. This COF-based OSV device with a configuration of LSMO/Py-Np COF/Co/Au demonstrated a remarkable magnetoresistance (MR) value up to -26.5 % at 30 K. Meanwhile, the MR behavior of the COF-based OSVs exhibited a highly temperature dependence and operational stability. This work highlights the enormous application prospects of 2D COFs in organic spintronics and provides a promising approach for developing electronic and spintronic devices based on acid-exfoliated COF thin films.

Comprehensive brain tissue metabolomics and biological network technology to decipher the mechanism of hydrogen-rich water on Radiation-induced cognitive impairment in rats.

BACKGROUND: Hydrogen-rich water (HRW) has been shown to prevent cognitive impairment caused by ionizing radiation. This study aimed to investigate the pharmacological effects and mechanisms of HRW on ionizing radiation by coupling the brain metabolomics and biological target network methods. METHODS AND RESULTS: HRW significantly improves the cognitive impairment in rats exposed to ionizing radiation. Based on metabolomics and biological network results, we identified 54 differential metabolites and 93 target genes. The KEGG pathway indicates that glutathione metabolism, ascorbic acid and aldehyde acid metabolism, pentose and glucuronic acid interconversion, and glycerophospholipid metabolism play important roles in ionizing radiation therapy. CONCLUSION: Our study has systematically elucidated the molecular mechanism of HRW against ionizing radiation, which can be mediated by modulating targets, pathways and metabolite levels. This provides a new perspective for identifying the underlying pharmacological mechanism of HRW.

A Systematic Review of INGARCH Models for Integer-Valued Time Series.

Count time series are widely available in fields such as epidemiology, finance, meteorology, and sports, and thus there is a growing demand for both methodological and application-oriented research on such data. This paper reviews recent developments in integer-valued generalized autoregressive conditional heteroscedasticity (INGARCH) models over the past five years, focusing on data types including unbounded non-negative counts, bounded non-negative counts, Z-valued time series and multivariate counts. For each type of data, our review follows the three main lines of model innovation, methodological development, and expansion of application areas. We attempt to summarize the recent methodological developments of INGARCH models for each data type for the integration of the whole INGARCH modeling field and suggest some potential research topics.

CRBP-HFEF: Prediction of RBP-Binding Sites on circRNAs Based on Hierarchical Feature Expansion and Fusion.

Circular RNAs (circRNAs) participate in the regulation of biological processes by binding to specific proteins and thus influence transcriptional processes. In recent years, circRNAs have become an emerging hotspot in RNA research. Due to powerful learning ability, the various deep learning frameworks have been used to predict the binding sites of RNA-binding protein (RPB) on circRNAs. These methods usually perform only single-level feature extraction of sequence information. However, the feature acquisition may be inadequate for single-level extraction. Generally, the features of deep and shallow layers of neural network can complement each other and are both important for binding site prediction tasks. Based on this concept, we propose a method that combines deep and shallow features, namely CRBP-HFEF. Specifically, features are first extracted and expanded for different levels of network. Then, the expanded deep and shallow features are fused and fed into the classification network, which finally determines whether they are binding sites. Compared to several existing methods, the experimental results on multiple datasets show that the proposed method achieves significant improvements in a number of metrics (with an average AUC of 0.9855). Moreover, much sufficient ablation experiments are also performed to verify the effectiveness of the hierarchical feature expansion strategy.

Semiparametric pseudo-score and pseudo-likelihood for evaluating correlate of protection in vaccine trials.

In vaccine clinical trials, vaccine efficacy endpoint analysis is usually associated with in high cost or extended study duration, due to the generally low infection rate. Correlate of protection (CoP), which refers to surrogate endpoint, usually immunological response, that can reliably predict the treatment effect, provides a more efficient and less costly approach to evaluate the vaccine. To handle the challenge of the missingness in the unobserved surrogate immune biomarker, the pseudo-score (PS) method, semiparametric method and pseudo-likelihood (PL) method demonstrated their advantages on different aspects. In this article, we propose new methodologies to combine the advantages of PS and PL with semiparametric methods respectively, to achieve higher estimate efficiency, allow continuous baseline predictor variable, and handle multiple surrogate markers. The advantage of our methodologies are demonstrated by a simulation study in different settings and applied to a case study, which eventually can improve the chance of a successful trial.

ACT001 Ameliorates ionizing radiation-induced lung injury by inhibiting NLRP3 inflammasome pathway.

Radiotherapy is a prevalent treatment modality for thoracic tumors; however, it can lead to radiation-induced lung injury (RILI), which currently lacks effective interventions. ACT001, a prodrug of micheliolide, has demonstrated promising clinical application potential, yet its impact on RILI requires further validation. This study aims to investigate the radioprotective effects of ACT001 on RILI and elucidate its underlying mechanism. Sprague-Dawley rats were utilized to induce RILI following 20 Gy X-ray chest irradiation, and lung tissue inflammation and fibrosis were assessed using hematoxylin and eosin (H&E) and Masson staining. Lung injury, inflammation, and oxidative stress markers were evaluated employing commercial kits. Pyroptosis-related differentially expressed genes (DEGs) were analyzed using a microarray dataset from the Gene Expression Omnibus (GEO) database, and their functions and hub genes were identified through protein-protein interaction networks. Pyroptosis-related genes were detected via RT-qPCR, western blotting, immunofluorescence, and immunohistochemistry. The results demonstrated that ACT001 ameliorated RILI, diminished pro-inflammatory cytokine release and fibrosis, and mitigated the activation of the NLRP3 inflammasome while inhibiting pyroptosis in lung tissue. In conclusion, our study reveals that ACT001 can suppress NLRP3 inflammasome-mediated pyroptosis and improve RILI, suggesting its potential as a novel protective agent for RILI.