GNNGL-PPI: multi-category prediction of protein-protein interactions using graph neural networks based on global graphs and local subgraphs.

Most proteins exert their functions by interacting with other proteins, making the identification of protein-protein interactions (PPI) crucial for understanding biological activities, pathological mechanisms, and clinical therapies. Developing effective and reliable computational methods for predicting PPI can significantly reduce the time-consuming and labor-intensive associated traditional biological experiments. However, accurately identifying the specific categories of protein-protein interactions and improving the prediction accuracy of the computational methods remain dual challenges. To tackle these challenges, we proposed a novel graph neural network method called GNNGL-PPI for multi-category prediction of PPI based on global graphs and local subgraphs. GNNGL-PPI consisted of two main components: using Graph Isomorphism Network (GIN) to extract global graph features from PPI network graph, and employing GIN As Kernel (GIN-AK) to extract local subgraph features from the subgraphs of protein vertices. Additionally, considering the imbalanced distribution of samples in each category within the benchmark datasets, we introduced an Asymmetric Loss (ASL) function to further enhance the predictive performance of the method. Through evaluations on six benchmark test sets formed by three different dataset partitioning algorithms (Random, BFS, DFS), GNNGL-PPI outperformed the state-of-the-art multi-category prediction methods of PPI, as measured by the comprehensive performance evaluation metric F1-measure. Furthermore, interpretability analysis confirmed the effectiveness of GNNGL-PPI as a reliable multi-category prediction method for predicting protein-protein interactions.

Identification of a linear B-cell epitope on the "puff" loop of the Senecavirus A VP2 protein involved in receptor binding.

Senecavirus A (SVA) is an important emerging swine pathogen that causes vesicular lesions in swine and acute death in newborn piglets. VP2 plays a significant role in the production of antibodies, which can be used in development of diagnostic tools and vaccines. Herein, the aim of the current study was to identify B-cell epitopes (BCEs) of SVA for generation of epitope-based SVA marker vaccine. Three monoclonal antibodies (mAbs), named 2E4, 1B8, and 2C7, against the SVA VP2 protein were obtained, and two novel linear BCEs, 177SLGTYYR183 and 266SPYFNGL272, were identified by peptide scanning. The epitope 177SLGTYYR183 was recognized by the mAb 1B8 and was fully exposed on the VP2 surface, and alanine scanning analysis revealed that it contained a high continuity of key amino acids. Importantly, we confirmed that 177SLGTYYR183 locates on "the puff" region within the VP2 EF loop, and contains three key amino acid residues involved in receptor binding. Moreover, a single mutation, Y182A, blocked the interaction of the mutant virus with the mAb 1B8, indicating that this mutation is the pivotal point for antibody recognition. In summary, the BCEs that identified in this study could be used to develop diagnostic tools and an epitope-based SVA marker vaccine.

Extraction, characterization and intestinal anti-inflammatory and anti-oxidative activities of polysaccharide from stems and leaves of Chuanminshen violaceum M. L. Sheh & R. H. Shan.

ETHNOPHARMACOLOGICAL RELEVANCE: Chuanminshen violaceum M. L. Sheh & R. H. Shan (CV) is used as a medicine with roots, which have the effects of benefiting the lungs, harmonizing the stomach, resolving phlegm and detoxifying. Polysaccharide is one of its main active components and has various pharmacological activities, but the structural characterization and pharmacological activities of polysaccharide from the stems and leaves parts of CV are still unclear. AIM OF THE STUDY: The aim of this study was to investigate the optimal extraction conditions for ultrasound-assisted extraction of polysaccharide from CV stems and leaves, and to carry out preliminary structural analyses, anti-inflammatory and antioxidant effects of the obtained polysaccharide and to elucidate the underlying mechanisms. MATERIALS AND METHODS: The ultrasonic-assisted extraction of CV stems and leaves polysaccharides was carried out, and the response surface methodology (RSM) was used to optimize the extraction process to obtain CV polysaccharides (CVP) under the optimal conditions. Subsequently, we isolated and purified CVP to obtain the homogeneous polysaccharide CVP-AP-I, and evaluated the composition, molecular weight, and structural features of CVP-AP-I using a variety of technical methods. Finally, we tested the pharmacological activity of CVP-AP-Ⅰ in an LPS-induced model of oxidative stress and inflammation in intestinal porcine epithelial cells (IPEC-J2) and explored its possible mechanism of action. RESULTS: The crude polysaccharide was obtained under optimal extraction conditions and subsequently isolated and purified to obtain CVP-AP-Ⅰ (35.34 kDa), and the structural characterization indicated that CVP-AP-Ⅰ was mainly composed of galactose, galactose, rhamnose and glucose, which was a typical pectic polysaccharide. In addition, CVP-AP-Ⅰ attenuates LPS-induced inflammation and oxidative stress by inhibiting the expression of pro-inflammatory factor genes and proteins and up-regulating the expression of antioxidant enzyme-related genes and proteins in IPEC-J2, by a mechanism related to the activation of the Nrf2/Keap1 signaling pathway. CONCLUSION: The results of this study suggest that the polysaccharide isolated from CV stems and leaves was a pectic polysaccharide with similar pharmacological activities as CV roots, exhibiting strong anti-inflammatory and antioxidant activities, suggesting that CV stems and leaves could possess the same traditional efficacy as CV roots, which is expected to be used in the treatment of intestinal diseases.

Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of "interaction-affinity-binding sites". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning.

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing. However, traditional machine learning methods for calculating DTA often lack accuracy, posing a significant challenge in accurately predicting DTA. Fortunately, deep learning has emerged as a promising approach in computational biology, leading to the development of various deep learning-based methods for DTA prediction. To support researchers in developing novel and highly precision methods, we have provided a comprehensive review of recent advances in predicting DTA using deep learning. We firstly conducted a statistical analysis of commonly used public datasets, providing essential information and introducing the used fields of these datasets. We further explored the common representations of sequences and structures of drugs and targets. These analyses served as the foundation for constructing DTA prediction methods based on deep learning. Next, we focused on explaining how deep learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer, and Graph Neural Networks (GNNs), were effectively employed in specific DTA prediction methods. We highlighted the unique advantages and applications of these models in the context of DTA prediction. Finally, we conducted a performance analysis of multiple state-of-the-art methods for predicting DTA based on deep learning. The comprehensive review aimed to help researchers understand the shortcomings and advantages of existing methods, and further develop high-precision DTA prediction tool to promote the development of drug discovery.

Ultrasonic-assisted extraction of polysaccharide from Paeoniae Radix alba: Extraction optimization, structural characterization and antioxidant mechanism in vitro.

Paeoniae Radix alba is used in Traditional Chinese Medicine for the treatment of gastrointestinal disorders, immunomodulatory, cancer, and other diseases. In the current study, the yield of Paeoniae Radix alba polysaccharide (PRP) was significantly increased with optimal ultrasound-assisted extraction compared to hot water extraction. Further, an acidic polysaccharide (PRP-AP) was isolated from PRP after chromatographic separation and was characterized as a typical pectic polysaccharide with side chains of arabinogalactans types I and II. Moreover, it showed antioxidant effects on LPS-induced damage on IPEC-J2 cells determined by qRT-PCR and ELISA, including decreasing the pro-inflammatory factors' expressions and increasing the antioxidant enzymes activities, which was shown to be related to the Nrf2/Keap1 pathway modulated by PRP-AP. The metabolites change (such as itaconate, cholesterol sulfate, etc.) detected by untargeted metabolomic analysis in cells was also shown to be modulated by PRP-AP, and these metabolites were further utilized and protected cells damaged by LPS. These results revealed the cellular active mechanism of the macromolecular PRP-AP on protecting cells, and supported the hypothesis that PRP-AP has strong benefits as an alternative dietary supplement for the prevention of intestinal oxidative stress by modulating cellular metabolism.

The compensation effect of competence frustration and its behavioral manifestations.

The frustration of competence, one of the three basic psychological needs proposed by self-determination theory, has been widely demonstrated to negatively influence one's motivation and well-being in both work and life. However, research on the recovery mechanism of competence is still in the nascent stage. In this study, a two-stage behavioral experiment was conducted to examine the restoration of competence and the potential moderating role of resilience. Results showed that individuals who were asked to recall experience of competence frustration performed better on subsequent tasks, manifesting their behavioral efforts of competence restoration. However, resilience does not play a significant moderating role in competence restoration. Through convergent behavioral evidence, findings of this study demonstrate the compensation effect of competence frustration.

Roles of mechanosensitive ion channel PIEZO1 in the pathogenesis of brain injury after experimental intracerebral hemorrhage.

Secondary brain injury after intracerebral hemorrhage (ICH) is the main cause of poor prognosis in ICH patients, but the underlying mechanisms remain less known. The involvement of Piezo1 in brain injury after ICH was studied in a mouse model of ICH. ICH was established by injecting autologous arterial blood into the basal ganglia in mice. After vehicle, Piezo1 blocker, GsMTx4, Piezo1 activator, Yoda-1, or together with mannitol (tail vein injection) was injected into the left lateral ventricle of mouse brain, Piezo1 level and the roles of Piezo1 in neuronal injury, brain edema, and neurological dysfunctions after ICH were determined by the various indicated methods. Piezo1 protein level in neurons was significantly upregulated 24 h after ICH in vivo (human and mice). Piezo1 protein level was also dramatically upregulated in HT22 cells (a murine neuron cell line) cultured in vitro 24 h after hemin treatment as an in vitro ICH model. GsMTx4 treatment or together with mannitol significantly downregulated Piezo1 and AQP4 levels, markedly increased Bcl2 level, maintained more neurons alive, considerably restored brain blood flow, remarkably relieved brain edema, substantially decreased serum IL-6 level, and almost fully reversed the neurological dysfunctions at ICH 24 h group mice. In contrast, Yoda-1 treatment achieved the opposite effects. In conclusion, Piezo1 plays a crucial role in the pathogenesis of brain injury after ICH and may be a target for clinical treatment of ICH.

Berberine promotes the degradation of phenylacetic acid to prevent thrombosis by modulating gut microbiota.

BACKGROUND: Berberine is the main bioactive constituent of Coptis chinensis, a quaternary ammonium alkaloid. While berberine's cardiovascular benefits are well-documented, its impact on thrombosis remains not fully understood. PURPOSE: This study investigates the potential of intestinal microbiota as a novel target for preventing thrombosis, with a focus on berberine, a natural compound known for its effectiveness in managing cardiovascular conditions. METHODS: Intraperitoneal injection of carrageenan induces the secretion of chemical mediators such as histamine and serotonin from mast cells to promote thrombosis. This model can directly and visually observe the progression of thrombosis in a time-dependent manner. Thrombosis was induced by intravenous injection of 1 % carrageenan solution (20 mg/kg) to all mice except the vehicle control group. Quantitative analysis of gut microbiota metabolites through LC/MS. Then, the gut microbiota of mice was analyzed using 16S rRNA sequencing to assess the changes. Finally, the effects of gut microbiota on thrombosis were explored by fecal microbiota transplantation. RESULTS: Our research shows that berberine inhibits thrombosis by altering intestinal microbiota composition and related metabolites. Notably, berberine curtails the biosynthesis of phenylacetylglycine, a thrombosis-promoting coproduct of the host-intestinal microbiota, by promoting phenylacetic acid degradation. This research underscores the significance of phenylacetylglycine as a thrombosis-promoting risk factor, as evidenced by the ability of intraperitoneal phenylacetylglycine injection to reverse berberine's efficacy. Fecal microbiota transplantation experiment confirms the crucial role of intestinal microbiota in thrombus formation. CONCLUSION: Initiating our investigation from the perspective of the gut microbiota, we have, for the first time, unveiled that berberine inhibits thrombus formation by promoting the degradation of phenylacetic acid, consequently suppressing the biosynthesis of PAG. This discovery further substantiates the intricate interplay between the gut microbiota and thrombosis. Our study advances the understanding that intestinal microbiota plays a crucial role in thrombosis development and highlights berberine-mediated intestinal microbiota modulation as a promising therapeutic approach for thrombosis prevention.

Ligation of cervical lymphatic vessels decelerates blood clearance and worsens outcomes after experimental subarachnoid hemorrhage.

Subarachnoid hemorrhage (SAH) is characterized by the extravasation of blood into the subarachnoid space, in which erythrocyte lysis is the primary contributor to cell death and brain injuries. New evidence has indicated that meningeal lymphatic vessels (mLVs) are essential in guiding fluid and macromolecular waste from cerebrospinal fluid (CSF) into deep cervical lymph nodes (dCLNs). However, the role of mLVs in clearing erythrocytes after SAH has not been completely elucidated. Hence, we conducted a cross-species study. Autologous blood was injected into the subarachnoid space of rabbits and rats to induce SAH. Erythrocytes in the CSF were measured with/without deep cervical lymph vessels (dCLVs) ligation. Additionally, prior to inducing SAH, we administered rats with vascular endothelial growth factor C (VEGF-C), which is essential for meningeal lymphangiogenesis and maintaining integrity and survival of lymphatic vessels. The results showed that the blood clearance rate was significantly lower after dCLVs ligation in both the rat and rabbit models. DCLVs ligation aggravated neuroinflammation, neuronal damage, brain edema, and behavioral impairment after SAH. Conversely, the treatment of VEGF-C enhanced meningeal lymphatic drainage of erythrocytes and improved outcomes in SAH. In summary, our research highlights the indispensable role of the meningeal lymphatic pathway in the clearance of blood and mediating consequences after SAH.

Contact-Free Atrial Fibrillation Screening with Attention Network.

Atrial Fibrillation (AF) screening from face videos has become popular with the trend of telemedicine and telehealth in recent years. In this study, the largest facial image database for camera-based AF detection is proposed. There are 657 participants from two clinical sites and each of them is recorded for about 10 minutes of video data, which can be further processed as over 10,000 segments around 30 seconds, where the duration setting is referred to the guideline of AF diagnosis. It is also worth noting that, 2,979 segments are segment-wise labeled, that is, every rhythm is independently labeled with AF or not. Besides, all labels are confirmed by the cardiologist manually. Various environments, talking, facial expressions, and head movements are involved in data collection, which meets the situations in practical usage. Specific to camera-based AF screening, a novel CNN-based architecture equipped with an attention mechanism is proposed. It is capable of fusing heartbeat consistency, heart rate variability derived from remote photoplethysmography, and motion features simultaneously to reliable outputs. With the proposed model, the performance of intra-database evaluation comes up to 96.62% of sensitivity, 90.61% of specificity, and 0.96 of AUC. Furthermore, to check the capability of adaptation of the proposed method thoroughly, the cross-database evaluation is also conducted, and the performance also reaches about 90% on average with the AUCs being over 0.94 in both clinical sites.

Contribution of Matrix Metalloproteinase-2 Genotypes to Taiwan Pterygium Risk.

BACKGROUND/AIM: In the literature, the studies about the role of matrix metalloproteinase-2 (MMP-2) in pterygium diagnosis are mainly based on its protein expression. The role of MMP-2 variants has never been examined. The aim of this study was to examine the association of MMP-2 genotypes with pterygium risk. MATERIALS AND METHODS: MMP-2 rs243865 and rs2285053 were genotyped in 140 pterygium cases and 280 non-pterygium controls by typical polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) genotyping technology. RESULTS: The genotypic frequency of MMP-2 rs243865 CC, CT and TT were 86.4%, 12.9% and 0.7% in the pterygium group and 81.1%, 17.1% and 1.8% in the non-pterygium group (p for trend=0.3389). The variant CT and TT carriers had a 0.70- and 0.38-fold pterygium risk (95%CI=0.39-1.26 and 0.04-3.25, p=0.2982 and 0.6686, respectively). As for MMP-2 rs2285053, the genotypic frequency of CC, CT and TT were 67.1%, 28.6% and 4.3% in the pterygium group, non-significantly different from those in non-pterygium group (p for trend=0.7081). The CT and TT carriers had a 0.88- and 0.71-fold pterygium risk (95%CI=0.56-1.38 and 0.27-1.88, p=0.6612 and 0.6456, respectively). The allelic analysis results showed that MMP-2 rs243865 variant T allele was not associated with pterygium risk (7.1% versus 10.4%, OR=0.67, 95%CI=0.39-1.13, p=0.1649). As for MMP-2 rs2285053, the T allele was not associated with pterygium risk either (18.6% versus 21.1%, OR=0.85, 95%CI=0.59-1.23, p=0.4136). CONCLUSION: The genotypes at MMP-2 rs243865 or rs2285053 played minor role in determining individual susceptibility for pterygium among Taiwanese.

OXCT1 regulates hippocampal neurogenesis and alleviates cognitive impairment via the Akt/GSK-3ß/ß-catenin pathway after subarachnoid hemorrhage.

BACKGROUND: Subarachnoid hemorrhage (SAH) is a life-threatening neurological disease that usually has a poor prognosis. Neurogenesis is a potential therapeutic target for brain injury. Ketone metabolism also plays neuroprotective roles in many neurological disorders. OXCT1 (3-Oxoacid CoA-Transferase 1) is the rate-limiting enzyme of ketone body oxidation. In this study, we explored whether increasing ketone oxidation by upregulating OXCT1 in neurons could promote neurogenesis after SAH, and evaluated the potential mechanism involved in this process. METHODS: The ß-hydroxybutyrate content was measured using an enzymatic colorimetric assay. Adeno-associated virus targeting neurons was injected to overexpress OXCT1, and the expression and localization of proteins were evaluated by western blotting and immunofluorescence staining. Adult hippocampal neurogenesis was evaluated by dual staining with doublecortin and 5-Ethynyl-2'-Deoxyuridine. LY294002 was intracerebroventricularly administered to inhibit Akt activity. The Morris water maze and Y-maze tests were employed to assess cognitive function after SAH. RESULTS: The results showed that OXCT1 expression and hippocampal neurogenesis significantly decreased in the early stage of SAH. Overexpression of OXCT1 successfully increased hippocampal neurogenesis via activation of Akt/GSK-3ß/ß-catenin signaling and improved cognitive function, both of which were reversed by administration of LY294002. CONCLUSIONS: OXCT1 regulated hippocampal ketone body metabolism and increased neurogenesis through mechanisms mediated by the Akt/GSK-3ß/ß-catenin pathway, improving cognitive impairment after SAH.

Molecular phylogenetic relationships based on mitochondrial genomes of novel deep-sea corals (Octocorallia: Alcyonacea): Insights into slow evolution and adaptation to extreme deep-sea environments.

A total of 10 specimens of Alcyonacea corals were collected at depths ranging from 905 m to 1 633 m by the manned submersible Shenhai Yongshi during two cruises in the South China Sea (SCS). Based on mitochondrial genomic characteristics, morphological examination, and sclerite scanning electron microscopy, the samples were categorized into four suborders (Calcaxonia, Holaxonia, Scleraxonia, and Stolonifera), and identified as 9 possible new cold-water coral species. Assessments of GC-skew dissimilarity, phylogenetic distance, and average nucleotide identity (ANI) revealed a slow evolutionary rate for the octocoral mitochondrial sequences. The nonsynonymous ( Ka) to synonymous ( Ks) substitution ratio ( Ka/ Ks) suggested that the 14 protein-coding genes (PCGs) were under purifying selection, likely due to specific deep-sea environmental pressures. Correlation analysis of the median Ka/ Ks values of five gene families and environmental factors indicated that the genes encoding cytochrome b (cyt b) and DNA mismatch repair protein ( mutS) may be influenced by environmental factors in the context of deep-sea species formation. This study highlights the slow evolutionary pace and adaptive mechanisms of deep-sea corals.

Biotransformation of 5-methoxy-N-isopropyl-N-methyltryptamine by zebrafish and human liver microsome with high-resolution mass spectrometry.

To explore the metabolites of 5-Methoxy-N-isopropyl-N-methyltryptamine (5-MeO-MiPT) and unveil its toxicological effects, we examined its metabolic profiles using zebrafish and human liver microsome models. Employing ultra-high-performance liquid chromatography Q Exactive hybrid quadrupole-Orbitrap high-resolution mass spectrometry (UPLC-QE-HRMS), we analyzed samples from intoxicated zebrafish and human liver microsomes. In the zebrafish model, we identified a total of six metabolites. Primary phase I metabolic pathways involved N-Demethylation and Indole-hydroxylation reactions, while phase II metabolism included Glucoside conjugation directly, Glucoside conjugation after Indole-hydroxylation, and Sulfonation following Indole-hydroxylation. In the human liver microsome model, nine metabolites were generated. Major phase I metabolic pathways encompassed N-Demethylation, 5-O-Demethylation, and N-Depropylation, N-Oxidation, Indole-hydroxylation, N-Demethylation combined with Indole-hydroxylation, and 5-O-Methylation-carboxylation. Phase II metabolism involved Glucoside conjugation after Indole-hydroxylation, as well as Glucoside conjugation after 5-O-Demethylation. Proposed phase I metabolites, such as 5-MeO-MiPT-N-Demethylation (5-MeO-NiPT) and 5-MeO-MiPT-Indole-hydroxylation, alongside the phase II metabolite OH&Glucoside conjugation-5-MeO-MiPT, were identified as effective markers for screening 5-MeO-MiPT intake. This study systematically delineates the phase I and II metabolites of 5-MeO-MiPT, confirming their pathways through in vivo and in vitro extrapolation. Additionally, inclusion of the parent drug itself and OH&Glucoside conjugation-5-MeO-MiPT could serve as valuable confirmation tools.

Nontargeted metabolomic insights into the behavioral effects of 5-MeO-MiPT in zebrafish (Danio rerio).

5-Methoxy-N-methyl-N-isopropyltryptamine (5-MeO-MiPT) is a novel psychoactive substance exhibiting a tryptamine structure. Despite its increasing prevalence, the environmental impact of 5-MeO-MiPT remains unexplored. Our prior investigation revealed that 5-MeO-MiPT induced inhibited spontaneous movement and prompted anxiety-like behavior in adult zebrafish-a validated toxicological model. To elucidate this phenomenon and establish a correlation between metabolomics and behavioral changes induced by 5-MeO-MiPT, zebrafish were administered varying drug concentrations. Zebrafishes were subjected to injections of different 5-MeO-MiPT concentrations. Subsequent metabolomic analysis of endogenous metabolites affected by the drug unveiled substantial variations in metabolic levels between the control group and the drug-injected cohorts. A total of 22 distinct metabolites emerged as potential biomarkers. Further scrutiny identified seven pathways significantly influenced by 5-MeO-MiPT. A focused exploration into amino acid metabolism, lipid metabolism, and energy metabolism unveiled that the metabolic repercussions of 5-MeO-MiPT on zebrafish resulted in observable brain damage. Notably, the study identified a consequential disruption in the liver-brain pathway. The comprehensive metabolomic approach employed herein effectively discerned the impact of 5-MeO-MiPT on zebrafish metabolism. This approach also shed light on the mechanism underpinning the anxiety-like behavior observed in zebrafish post-drug injection. Specifically, our findings indicate that 5-MeO-MiPT induces brain damage, particularly within the liver-brain pathway.

MMDTA: A Multimodal Deep Model for Drug-Target Affinity with a Hybrid Fusion Strategy.

The prediction of the drug-target affinity (DTA) plays an important role in evaluating molecular druggability. Although deep learning-based models for DTA prediction have been extensively attempted, there are rare reports on multimodal models that leverage various fusion strategies to exploit heterogeneous information from multiple different modalities of drugs and targets. In this study, we proposed a multimodal deep model named MMDTA, which integrated the heterogeneous information from various modalities of drugs and targets using a hybrid fusion strategy to enhance DTA prediction. To achieve this, MMDTA first employed convolutional neural networks (CNNs) and graph convolutional networks (GCNs) to extract diverse heterogeneous information from the sequences and structures of drugs and targets. It then utilized a hybrid fusion strategy to combine and complement the extracted heterogeneous information, resulting in the fused modal information for predicting drug-target affinity through the fully connected (FC) layers. Experimental results demonstrated that MMDTA outperformed the competitive state-of-the-art deep learning models on the widely used benchmark data sets, particularly with a significantly improved key evaluation metric, Root Mean Square Error (RMSE). Furthermore, MMDTA exhibited excellent generalization and practical application performance on multiple different data sets. These findings highlighted MMDTA's accuracy and reliability in predicting the drug-target binding affinity. For researchers interested in the source data and code, they are accessible at http://github.com/dldxzx/MMDTA.

Electrochemical-enhanced nanoscale oxygen-vacancy CuFe2O4 to activate persulfate (E/oxygen-vacancy CuFe2O4/PS) for separation of Ebselen from wastewater.

To enhance the catalytic activity of CuFe2O4 on PS, a nanoscale oxygen-vacancy CuFe2O4 was prepared by hydrogenation reduction technique to construct an advanced oxidation system of electrochemical-enhanced nanoscale oxygen-vacancy CuFe2O4-activated persulfate. Using Ebselen (EBS) as a model pollutant, the degradation efficiency, activation mechanism and degradation pathway were studied. The oxygen-vacancy CuFe2O4 was characterized and analysed by FESEM, EDS and XPS. The results show that under the optimal reaction conditions (PS = 0.8 g/L, oxygen-vacancy CuFe2O4 = 0.3 g/L, initial pH = 6.5), the removal rate of 20 mg/L EBS can reach 92% after reaction for 60 min, which proves that the formation of oxygen-vacancy changed the catalytic inertness of CuFe2O4 on PS. It is speculated that in the E/oxygen-vacancy CuFe2O4/PS system, the existence of oxygen holes enhances the electron transfer ability and reducibility of the catalyst, so the oxygen-vacancy CuFe2O4 can efficiently activate PS to degrade EBS. The quenching experiments show that both SO4⋅- and ⋅OH are involved in the oxidation reaction as reactive radicals in the system, with SO4⋅- being the main reactive radical. In addition, both dissolved oxygen (DO) and anions in the solution inhibit the oxidative degradation of EBS by oxygen-vacancy CuFe2O4/PS system. Through GC-MS detection, a possible degradation pathway is proposed.

Astrocyte-derived hepcidin aggravates neuronal iron accumulation after subarachnoid hemorrhage by decreasing neuronal ferroportin1.

Iron accumulation is one of the most essential pathological events after subarachnoid hemorrhage (SAH). Ferroportin1 (FPN1) is the only transmembrane protein responsible for exporting iron. Hepcidin, as the major regulator of FPN1, is responsible for its degradation. Our study investigated how the interaction between FPN1 and hepcidin contributes to iron accumulation after SAH. We found that iron accumulation aggravated after SAH, along with decreased FPN1 in neurons and increased hepcidin in astrocytes. After knocking down hepcidin in astrocytes, the neuronal FPN1 significantly elevated, thus attenuating iron accumulation. After SAH, p-Smad1/5 and Smad4 tended to translocate into the nucleus. Moreover, Smad4 combined more fragments of the promoter region of Hamp after OxyHb stimulation. By knocking down Smad1/5 or Smad4 in astrocytes, FPN1 level restored and iron overload attenuated, leading to alleviated neuronal cell death and improved neurological function. However, the protective role disappeared after recombinant hepcidin administration. Therefore, our study suggests that owing to the nuclear translocation of transcription factors p-Smad1/5 and Smad4, astrocyte-derived hepcidin increased significantly after SAH, leading to a decreased level of neuronal FPN1, aggravation of iron accumulation, and worse neurological outcome.

Aloperine targets lysosomes to inhibit late autophagy and induces cell death through apoptosis and paraptosis in glioblastoma.

Glioblastoma (GBM) is an aggressive intracranial tumour, and current chemotherapy regimens have limited efficacy. Aloperine (ALO), a natural alkaline compound, has shown potential as an antitumor agent. However, the effect of ALO against GBM remains unclear. This study aimed to investigate the function of ALO in treating GBM. U87, A172, and GL261 cell lines were used for in vitro experiments, and GL261 was also used to establish in vivo models. The results showed that ALO inhibited the proliferation of GBM cells by cell cycle arrest and apoptosis. Furthermore, autophagy was found to play a critical role, suggested by observation of autophagosomes under the transmission electron microscopy. It was discovered for the first time that ALO targeted lysosomes directly in glioma cells, tested by fluo-rescence-labelled ALO and organelle-localizing probes. In addition, ALO inhibited late autophagy and induced paraptosis in GBM, verified by classical gene expression changes in qPCR and western blotting. Also, ALO inhibited tumour growth and acted synergistically with temozolomide in intracranial glioma mice models in vivo. Our findings suggest that ALO targets lysosomes to inhibit late autophagy in GBM, inducing cell cycle arrest, paraptosis, and apoptosis. ALO may therefore be a promising therapeutic agent for the treatment of GBM.