TransC-ac4C: Identification of N4-acetylcytidine (ac4C) sites in mRNA using deep learning.

N4-acetylcytidine (ac4C) is a post-transcriptional modification in mRNA that is critical in mRNA translation in terms of stability and regulation. In the past few years, numerous approaches employing convolutional neural networks (CNN) and Transformer have been proposed for the identification of ac4C sites, with each variety of approaches processing distinct characteristics. CNN-based methods excels at extracting local features and positional information, whereas Transformer-based ones stands out in establishing long-range dependencies and generating global representations. Given the importance of both local and global features in mRNA ac4C sites identification, we propose a novel method termed TransC-ac4C which combines CNN and Transformer together for enhancing the feature extraction capability and improving the identification accuracy. Five different feature encoding strategies (One-hot, NCP, ND, EIIP, and K-mer) are employed to generate the mRNA sequence representations, in which way the sequence attributes and physical and chemical properties of the sequences can be embedded. To strengthen the relevance of features, we construct a novel feature fusion method. Firstly, the CNN is employed to process five single features, stitch them together and feed them to the Transformer layer. Then, our approach employs CNN to extract local features and Transformer subsequently to establish global long-range dependencies among extracted features. We use 5-fold cross-validation to evaluate the model, and the evaluation indicators are significantly improved. The prediction accuracy of the two datasets is as high as 81.42.

Host proteins interact with viral elements and affect the life cycle of highly pathogenic avian influenza A virus H7N9.

Host-virus interactions can significantly impact the viral life cycle and pathogenesis; however, our understanding of the specific host factors involved in highly pathogenic avian influenza A virus H7N9 (HPAI H7N9) infection is currently restricted. Herein, we designed and synthesized 65 small interfering RNAs targeting host genes potentially associated with various aspects of RNA virus life cycles. Afterward, HPAI H7N9 viruses were isolated and RNA interference was used to screen for host factors likely to be involved in the life cycle of HPAI H7N9. Moreover, the research entailed assessing the associations between host proteins and HPAI H7N9 proteins. Twelve key host proteins were identified: Annexin A (ANXA)2, ANXA5, adaptor related protein complex 2 subunit sigma 1 (AP2S1), adaptor related protein complex 3 subunit sigma 1 (AP3S1), ATP synthase F1 subunit alpha (ATP5A1), COPI coat complex subunit alpha (COP)A, COPG1, heat shock protein family A (Hsp70) member 1A (HSPA)1A, HSPA8, heat shock protein 90 alpha family class A member 1 (HSP90AA1), RAB11B, and RAB18. Co-immunoprecipitation revealed intricate interactions between viral proteins (hemagglutinin, matrix 1 protein, neuraminidase, nucleoprotein, polymerase basic 1, and polymerase basic 2) and these host proteins, presumably playing a crucial role in modulating the life cycle of HPAI H7N9. Notably, ANXA5, AP2S1, AP3S1, ATP5A1, HSP90A1, and RAB18, were identified as novel interactors with HPAI H7N9 proteins rather than other influenza A viruses (IAVs). These findings underscore the significance of host-viral protein interactions in shaping the dynamics of HPAI H7N9 infection, while highlighting subtle variations compared with other IAVs. Deeper understanding of these interactions holds promise to advance disease treatment and prevention strategies.

Comparison of prognosis and postoperative morbidities between standard pancreaticoduodenectomy and the TRIANGLE technique for resectable pancreatic ductal adenocarcinoma.

BACKGROUND: Radical surgery combined with systemic chemotherapy offers the possibility of long-term survival or even cure for patients with pancreatic ductal adenocarcinoma (PDAC), although tumor recurrence, especially locally, still inhibits the treatment efficacy. The TRIANGLE technique was introduced as an extended dissection procedure to improve the R0 resection rate of borderline resectable or locally advanced PDAC. However, there was a lack of studies concerning postoperative complications and long-term outcomes of this procedure on patients with resectable PDAC. AIM: To compare the prognosis and postoperative morbidities between standard pancreaticoduodenectomy (PD) and the TRIANGLE technique for resectable PDAC. METHODS: Patients with resectable PDAC eligible for PD from our hospital between June 2018 and December 2021 were enrolled in this retrospective cohort study. All the patients were divided into PDstandard and PDTRIANGLE groups according to the surgical procedure. Baseline characteristics, surgical data, and postoperative morbidities were recorded. All of the patients were followed up, and the date and location of tumor recurrence, and death were recorded. The Kaplan-Meier method and log-rank test were used for the survival analysis. RESULTS: There were 93 patients included in the study and 37 underwent the TRIANGLE technique. Duration of operation was longer in the PDTRIANGLE group compared with the PDstandard group [440 (410-480) min vs 320 (265-427) min] (P = 0.001). Intraoperative blood loss [700 (500-1200) mL vs 500 (300-800) mL] (P = 0.009) and blood transfusion [975 (0-1250) mL vs 400 (0-800) mL] (P = 0.009) were higher in the PDTRIANGLE group. There was a higher incidence of surgical site infection (43.2% vs 12.5%) (P = 0.001) and postoperative diarrhea (54.1% vs 12.5%) (P = 0.001) in the PDTRIANGLE group. The rates of R0 resection and local recurrence, overall survival, and disease-free survival did not differ significantly between the two groups. CONCLUSION: The TRIANGLE technique is safe, with acceptable postoperative morbidities compared with standardized PD, but it does not improve prognosis for patients with resectable PDAC.

Evaluation of drug interactions of Saposhnikoviae Radix and its major components with astragaloside IV and paeoniflorin using in vitro and in vivo experiments.

Saposhnikoviae Radix (SR) may enhance the pharmacodynamics of Huangqi Chifeng Tang (HQCFT) in the treatment of cerebral infarction according to our previous research, but the underlying mechanism is unknown. Herein, an in vivo pharmacokinetic assay in rats and in vitro MDCK-MDR1 cell assays were used to investigate the possible mechanism of SR, its main components, and its interactions with Astragali Radix (AR) and Paeoniae Radix (PR). An ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC‒MS/MS)-based analytical method for quantifying astragaloside IV (ASIV) and paeoniflorin (PAE) in microdialysis and transport samples was developed. The pharmacokinetic parameters of SR were determined using noncompartmental analyses CCK-8 assays were used to detect the cytotoxicity of ASIV, PAE, cimifugin (CIM), prim-o-glucosylcimifugin (POG) and their combinations. Moreover, drug transport was studied using MDCK-MDR1 cells. Western blotting was performed to measure the protein expression levels of P-GP and MRP1. Claudin-5, ZO-1, and F-actin expression was determined via immunohistochemical staining of MDCK-MDR1 cells. harmacokinetic studies revealed that, compared with those of Huangqi Chifeng Tang-Saposhnikoviae Radix (HQCFT-SR), the Tmax of ASIV increased by 11.11 %, and the MRT0-t and Tmax of PAE increased by 11.19 % and 20 %, respectively, in the HQCFT group. Transport studies revealed that when ASIV was coincubated with 28 µM CIM or POG, the apparent permeability coefficient (Papp) increased by 71.52 % and 50.33 %, respectively. Coincubation of PAE with 120 µM CIM or POG increased the Papp by 87.62 % and 60.95 %, respectively. Moreover, CIM and POG significantly downregulated P-gp and MRP1 (P < 0.05), inhibited the expression of Claudin-5, ZO-1, and F-actin (P < 0.05), and affected intercellular tight junctions (TJs). In conclusion, our study successfully established a selective, sensitive and reproducible UPLC‒MS/MS analytical method to detect drug‒drug interactions between SR, AR and PR in vivo and in vitro, which is beneficial for enhancing the therapeutic efficacies of AR and PR. Moreover, this study provides a theoretical basis for further research on the use of SR as a drug carrier.

Review of predicting protein stability changes upon variations.

Forecasting alterations in protein stability caused by variations holds immense importance. Improving the thermal stability of proteins is important for biomedical and industrial applications. This review discusses the latest methods for predicting the effects of mutations on protein stability, databases containing protein mutations and thermodynamic parameters, and experimental techniques for efficiently assessing protein stability in high-throughput settings. Various publicly available databases for protein stability prediction are introduced. Furthermore, state-of-the-art computational approaches for anticipating protein stability changes due to variants are reviewed. Each method's types of features, base algorithm, and prediction results are also detailed. Additionally, some experimental approaches for verifying the prediction results of computational methods are introduced. Finally, the review summarizes the progress and challenges of protein stability prediction and discusses potential models for future research directions.

Hydrogen sulfide mitigates memory impairments via the restoration of glutamatergic neurons in a mouse model of hemorrhage shock and resuscitation.

Impaired long-term memory, a complication of traumatic stress including hemorrhage shock and resuscitation (HSR), has been reported to be associated with multiple neurodegenerations. The ventral tegmental area (VTA) participates in both learned appetitive and aversive behaviors. In addition to being prospective targets for the therapy of addiction, depression, and other stress-related diseases, VTA glutamatergic neurons are becoming more widely acknowledged as powerful regulators of reward and aversion. This study revealed that HSR exposure induces memory impairments and decreases the activation in glutamatergic neurons, and decreased ß power in the VTA. We also found that optogenetic activation of glutamatergic neurons in the VTA mitigated HSR-induced memory impairments, and restored ß power. Moreover, hydrogen sulfide (H2S), a gasotransmitter with pleiotropic roles, has neuroprotective functions at physiological concentrations. In vivo, H2S administration improved HSR-induced memory deficits, elevated c-fos-positive vesicular glutamate transporters (Vglut2) neurons, increased ß power, and restored the balance of γ-aminobutyric acid (GABA) and glutamate in the VTA. This work suggests that glutamatergic neuron stimulation via optogenetic assay and exogenous H2S may be useful therapeutic approaches for improving memory deficits following HSR.

Resveratrol ameliorates glioblastoma inflammatory response by reducing NLRP3 inflammasome activation through inhibition of the JAK2/STAT3 pathway.

OBJECTIVES: The aim of this study was to investigate the anti-tumor effect of resveratrol (RSV) on glioblastoma (GBM) and its specific mechanism in improving the inflammatory response of the tumor microenvironment. The tumor microenvironment of GBM is highly neuroinflammatory, inducing tumor immunosuppression. Therefore, ameliorating the inflammatory response is an important focus for anti-tumor research. METHODS: The anti-tumor effect of RSV on GBM was demonstrated through in vitro cellular assays, including CCK-8, EdU, PI staining, Transwell, wound healing assay, and flow cytometry. Potential mechanisms of RSV's anti-GBM effects were identified through network pharmacological analysis. In addition, the relationship of RSV with the JAK2/STAT3 signaling pathway and the inflammasome NLRP3 was verified using Western blot. RESULTS: RSV significantly inhibited cell viability in GBM cell lines LN-229 and U87-MG. Furthermore, it inhibited the proliferation and invasive migration ability of GBM cells, while promoting apoptosis. Network pharmacological analysis revealed a close association between the anti-GBM effects of RSV and the JAK/STAT signaling pathway, as well as inflammatory responses. Western blot analysis confirmed that RSV inhibited the over-activation of the inflammasome NLRP3 through the JAK2/STAT3 signaling pathway. Partial reversal of RSV's inhibition of inflammasome NLRP3 was observed with the addition of the JAK/STAT agonist RO8191. CONCLUSIONS: In vitro, RSV can exert anti-tumor effects on GBM and improve the inflammatory response in the GBM microenvironment by inhibiting the activation of the JAK2/STAT3 signaling pathway. These findings provide new insights into potential therapeutic targets for GBM.

Glucose regulates the HMGB1 signaling pathway through SIRT1 in glioma.

BACKGROUND: Glucose is a fundamental substance for numerous cancers, including glioma. However, its influence on tumor cells regulatory mechanisms remains uncertain. SIRT1 is a regulator of deacetylation and a key player in the progression of malignant tumors. The objective of this study was to examine the role of glucose and SIRT1 in glioma. METHODS: This study investigated the association of SIRT1 expression with clinicopathological features and prognosis in glioma patients using the TCGA database. The Western blotting technique was used to identify the expression of SIRT1 protein in glioma cells. The study also examined the impact of differing glucose concentrations on the biological functions of glioma cells. The study investigated the expression of SIRT1 and HMGB1 signaling pathways in glioma. Additionally, resilience experiments were conducted utilizing SRT1720. RESULTS: SIRT1 is a gene that suppresses tumors and is low expressed in gliomas. Low expression of this gene is strongly linked to a poor prognosis in patients with glioma. High concentrations of glucose can promote the proliferation, migration, and invasion of glioma cells, while also inhibiting apoptosis. The findings of this mechanistic study provide evidence that glucose can down-regulate SIRT1 expression, leading to increased levels of acetylated HMGB1. This in turn promotes the ex-nuclear activation of HMGB1 and associated signaling pathways, ultimately driving glioma malignancy. CONCLUSION: Glucose has the ability to regulate the HMGB1 associated signaling pathway through SIRT1, thus promoting glioma progression. This holds significant research value.

Uncovering Microbial Composition of the Tissue Microenvironment in Bladder Cancer using RNA Sequencing Data.

Purpose: Bladder cancer (BC) is one of the top 10 common tumors in the world. It has been reported that microbiota can colonize tissues and play important roles in tumorigenesis and progression. However, the current understanding of microorganisms in the BC tissue microenvironment remains unclear. Methods: In this study, we integrated the RNA-seq data of 479 BC tissue samples from seven datasets combined with a range of bioinformatics tools to explore the landscape of microbiome in the BC tissue microenvironment. Results: The pan-microbiome was estimated to surpass 1,400 genera. A total of seven core microbiota (Bacillus, Corynebacterium, Cutibacterium, Escherichia, Halomonas, Pasteurella, and Streptomyces) were identified. Among them, Bacillus was widely distributed in all datasets with a high relative abundance (10.11% of all samples on average). Moreover, some biological factors, including tissue source and tumor grade, were found significant effects on the microbial composition of the bladder tissue. Pseudomonas, Porphyrobacter, and Acinetobacter were enriched in tumor tissues, while Mycolicibacterium and Streptomyces were enriched in patients who showed durable response to BCG therapy. In addition, we established microbial co-occurrence networks and found that the BCG therapy may attenuate the microbiological interactions. Conclusions: This study clearly provided a microbial landscape of the BC tissue microenvironment, which was important for exploring the interactions between microorganisms and BC tissues. The identified specific taxa might be potential biomarkers for BC.

Integrins regulation of wound healing processes: insights for chronic skin wound therapeutics.

Integrins are heterodimers composed of non-covalently associated alpha and beta subunits that mediate the dynamic linkage between extracellular adhesion molecules and the intracellular actin cytoskeleton. Integrins are present in various tissues and organs and are involved in different physiological and pathological molecular responses in vivo. Wound healing is an important process in the recovery from traumatic diseases and consists of three overlapping phases: inflammation, proliferation, and remodeling. Integrin regulation acts throughout the wound healing process to promote wound healing. Prolonged inflammation may lead to failure of wound healing, such as wound chronicity. One of the main causes of chronic wound formation is bacterial colonization of the wound. In this review, we review the role of integrins in the regulation of wound healing processes such as angiogenesis and re-epithelialization, as well as the role of integrins in mediating bacterial infections during wound chronicity, and the challenges and prospects of integrins as therapeutic targets for infected wound healing.

Theoretical and experimental study of attenuation in cancellous bone.

Significance: Photoacoustic (PA) technology shows great potential for bone assessment. However, the PA signals in cancellous bone are complex due to its complex composition and porous structure, making such signals challenging to apply directly in bone analysis. Aim: We introduce a photoacoustic differential attenuation spectrum (PA-DAS) method to separate the contribution of the acoustic propagation path to the PA signal from that of the source, and theoretically and experimentally investigate the propagation attenuation characteristics of cancellous bone. Approach: We modified Biot's theory by accounting for the high frequency and viscosity. In parallel with the rabbit osteoporosis model, we build an experimental PA-DAS system featuring an eccentric excitation differential detection mechanism. Moreover, we extract a PA-DAS quantization parameter-slope-to quantify the attenuation of high- and low-frequency components. Results: The results show that the porosity of cancellous bone can be evaluated by fast longitude wave attenuation at different frequencies and the PA-DAS slope of the osteoporotic group is significantly lower compared with the normal group (**p<0.01). Conclusions: Findings demonstrate that PA-DAS effectively differentiates osteoporotic bone from healthy bone, facilitating quantitative assessment of bone mineral density, and osteoporosis diagnosis.

Development of an Open Droplet Microchannel-Based Magnetosensor for Immunofluorometric Assay of Trimethoprim in Chicken and Pork Samples with a Wide Linear Range.

Trimethoprim (TMP), functioning as a synergistic antibacterial agent, is utilized in diagnosing and treating diseases affecting livestock and poultry. Human consumption of the medication indirectly may lead to its drug accumulation in the body and increase drug resistance due to its prolonged metabolic duration in livestock and poultry, presenting significant health hazards. Most reported immunoassay techniques, such as ELISA and immunochromatographic assay (ICA), find it challenging to achieve the dual advantages of high sensitivity, simplicity of operation, and a wide detection range. Consequently, an open droplet microchannel-based magnetosensor for immunofluorometric assay (OMM-IFA) of trimethoprim was created, featuring a gel imager to provide a signal output derived from the highly specific antibody (Ab) targeting trimethoprim. The method exhibited high sensitivity in chicken and pork samples, with LODs of 0.300 and 0.017 ng/mL, respectively, and a wide linear range, covering trimethoprim's total maximum residue limits (MRLs). Additionally, the spiked recoveries in chicken and pork specimens varied between 81.6% and 107.9%, maintaining an acceptable variation coefficient below 15%, aligning well with the findings from the ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technique. The developed method achieved a much wider linear range of about 5 orders of magnitude of 10-2-103 levels with grayscale signals as the output signal, which exhibited high sensitivity, excellent applicability and simple operability based on magnetic automation.

Effects of increasing sensitizing doses of ovalbumin on airway hyperresponsiveness in asthmatic mice.

BACKGROUND: The dosage of ovalbumin (OVA) during the sensitization stage is considered a crucial factor in the development of airway hyperresponsiveness (AHR). However, the inconsistent dosages of sensitizing OVA used in current studies and the lack of research on their impact on AHR are notable limitations. METHODS: We examined the impact of increasing sensitizing doses of OVA in a murine asthma model, which entailed initial sensitization with OVA followed by repeated exposure to OVA aerosols. BALB/c mice were primed with doses of OVA (0, 10, 20, 50, and 100 µg) plus 1 mg Alum on Days 0 and 7, and were challenged with OVA aerosols (10 mg/mL for 30 min) between Days 14 and 17. Antigen-induced AHR to methacholine (MCh), as well as histological changes, eosinophilic infiltration, and epithelial injury were assessed. RESULTS: The result indicated that there are striking OVA dose-related differences in antigen-induced AHR to MCh. The most intense antigen-induced AHR to MCh was observed with sensitization at 50 µg, while weaker responses were seen at 10, 20, and 100 µg. Meanwhile, there was a significant increase in eosinophil count with sensitization at 50 µg. The changes of AHR were correlated with total cells count, lymphocytes count, eosinophils count, and basophils count in bronchoalveolar lavage fluid; however, it did not correlate with histological changes such as cellular infiltration into bronchovascular bundles and goblet cell hyperplasia of the bronchial epithelium. CONCLUSION: Overall, this study demonstrated that sensitization with 50 µg of OVA resulted in the most significant AHR compared to other dosages. These findings may offer valuable insights for future research on mouse asthma modeling protocols.

Prediction of protein-ATP binding residues using multi-view feature learning via contextual-based co-attention network.

Accurately predicting protein-ATP binding residues is critical for protein function annotation and drug discovery. Computational methods dedicated to the prediction of binding residues based on protein sequence information have exhibited notable advancements in predictive accuracy. Nevertheless, these methods continue to grapple with several formidable challenges, including limited means of extracting more discriminative features and inadequate algorithms for integrating protein and residue information. To address the problems, we propose ATP-Deep, a novel protein-ATP binding residues predictor. ATP-Deep harnesses the capabilities of unsupervised pre-trained language models and incorporates domain-specific evolutionary context information from homologous sequences. It further refines the embedding at the residue level through integration with corresponding protein-level information and employs a contextual-based co-attention mechanism to adeptly fuse multiple sources of features. The performance evaluation results on the benchmark datasets reveal that ATP-Deep achieves an AUC of 0.954 and 0.951, respectively, surpassing the performance of the state-of-the-art model. These findings underscore the effectiveness of assimilating protein-level information and deploying a contextual-based co-attention mechanism grounded in context to bolster the prediction performance of protein-ATP binding residues.

Clonal integration of stress signal induces morphological and physiological response of root within clonal network.

Clonal integration of defense or stress signal induced systemic resistance in leaf of interconnected ramets. However, similar effects of stress signal in root are poorly understood within clonal network. Clonal fragments of Centella asiaticas with first-young, second-mature, third-old and fourth-oldest ramets were used to investigate transportation or sharing of stress signal among interconnected ramets suffering from low water availability. Compared with control, oxidative stress in root of the first-young, second-mature and third-old ramets was significantly alleviated by exogenous ABA application to the fourth-oldest ramets as well as enhancement of antioxidant enzyme (SOD, POD, CAT and APX) activities and osmoregulation ability. Surface area and volume in root of the first-young ramets were significantly increased and total length in root of the third-old ramets was significantly decreased. POD activity in root of the fourth-oldest and third-old ramets was significantly enhanced by exogenous ABA application to the first-young ramets. Meanwhile, total length and surface area in root of the fourth-oldest and third-old ramets were significantly decreased. Ratio of belowground to aboveground biomass in the whole clonal fragments was significantly increased by exogenous ABA application to the fourth-oldest or first-young ramets. It is suggested that transportation or sharing of stress signal may induce systemic resistance in root of interconnected ramets. Specially, transportation or sharing of stress signal against phloem flow was observed in the experiment. Possible explanation is that rapid recovery of foliar photosynthesis in first-young ramets subjected to exogenous ABA application can partially reverse phloem flow within clonal network. Thus, our experiment provides insight into ecological implication on clonal integration of stress signal.

Immune to temperature interference sensor of carbon dioxide gas concentration based on a single modified fiber Bragg grating.

In this study, a novel method that can detect carbon dioxide (CO2) concentration and realize temperature immunity based on only one fiber Bragg grating (FBG) is proposed. The outstanding contribution lies in solving the temperature crosstalk issue of FBG and ensuring the accuracy of detection results under the condition of anti-temperature interference. To achieve immunity to temperature interference without changing the initial structure of FBG, the optical fiber cladding of FBG and adjacent optical fiber cladding at both ends of FBG are modified by a polymer coating. Moreover, a universal immune temperature demodulation algorithm is derived. The experimental results demonstrate that the temperature response sensitivity of the improved FBG is controlled within the range of 0.00407 nm/°C. Compared with the initial FBG (the temperature sensitivity of the initial FBG is 0.04 nm/°C), it decreases by nearly 10 times. Besides, the gas response sensitivity of FBG reaches 1.6 pm/ppm and has overwhelmingly ideal linearity. The detection error results manifest that the gas concentration error in 20 groups of data does not exceed 3.16 ppm. The final reproducibility research shows that the difference in detection sensitivity between the two sensors is 0.08 pm/ppm, and the relative error of linearity is 1.07%. In a word, the proposed method can accurately detect the concentration of CO2 gas and is efficiently immune to temperature interference. The sensor we proposed has the advantages of a simple production process, low cost, and satisfactory reproducibility. It also has the prospect of mass production.

Identification of Protein-Protein Interaction Associated Functions Based on Gene Ontology.

Protein-protein interactions (PPIs) involve the physical or functional contact between two or more proteins. Generally, proteins that can interact with each other always have special relationships. Some previous studies have reported that gene ontology (GO) terms are related to the determination of PPIs, suggesting the special patterns on the GO terms of proteins in PPIs. In this study, we explored the special GO term patterns on human PPIs, trying to uncover the underlying functional mechanism of PPIs. The experimental validated human PPIs were retrieved from STRING database, which were termed as positive samples. Additionally, we randomly paired proteins occurring in positive samples, yielding lots of negative samples. A simple calculation was conducted to count the number of positive samples for each GO term pair, where proteins in samples were annotated by GO terms in the pair individually. The similar number for negative samples was also counted and further adjusted due to the great gap between the numbers of positive and negative samples. The difference of the above two numbers and the relative ratio compared with the number on positive samples were calculated. This ratio provided a precise evaluation of the occurrence of GO term pairs for positive samples and negative samples, indicating the latent GO term patterns for PPIs. Our analysis unveiled several nuclear biological processes, including gene transcription, cell proliferation, and nutrient metabolism, as key biological functions. Interactions between major proliferative or metabolic GO terms consistently correspond with significantly reported PPIs in recent literature.

MINDG: a drug-target interaction prediction method based on an integrated learning algorithm.

MOTIVATION: Drug-target interaction (DTI) prediction refers to the prediction of whether a given drug molecule will bind to a specific target and thus exert a targeted therapeutic effect. Although intelligent computational approaches for drug target prediction have received much attention and made many advances, they are still a challenging task that requires further research. The main challenges are manifested as follows: (i) most graph neural network-based methods only consider the information of the first-order neighboring nodes (drug and target) in the graph, without learning deeper and richer structural features from the higher-order neighboring nodes. (ii) Existing methods do not consider both the sequence and structural features of drugs and targets, and each method is independent of each other, and cannot combine the advantages of sequence and structural features to improve the interactive learning effect. RESULTS: To address the above challenges, a Multi-view Integrated learning Network that integrates Deep learning and Graph Learning (MINDG) is proposed in this study, which consists of the following parts: (i) a mixed deep network is used to extract sequence features of drugs and targets, (ii) a higher-order graph attention convolutional network is proposed to better extract and capture structural features, and (iii) a multi-view adaptive integrated decision module is used to improve and complement the initial prediction results of the above two networks to enhance the prediction performance. We evaluate MINDG on two dataset and show it improved DTI prediction performance compared to state-of-the-art baselines. AVAILABILITY AND IMPLEMENTATION: https://github.com/jnuaipr/MINDG.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning.

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

Cyclo[2]pyridine[8]pyrrole: An Expanded Porphyrinoid with Three Closed-Shell Oxidation States.

We report here an expanded porphyrinoid, cyclo[2]pyridine[8]pyrrole, 1, that can exist at three closed-shell oxidation levels. Macrocycle 1 was synthesized via the oxidative coupling of two open chain precursors and fully characterized by means of NMR and UV-vis spectroscopies, MS, and X-ray crystallography. Reduction of the fully oxidized form (1, blue) with NaBH4 produced either the half-oxidized (2, teal) or fully reduced forms (3, pale yellow), depending on the amount of reducing agent used and the presence or absence of air. Reduced products 2 or 3 can be oxidized to 1 by various oxidants (quinones, FeCl3, and AgPF6). Macrocycle 1 also undergoes proton-coupled reductions with I-, Br-, Cl-, SO32-, or S2O32- in the presence of an acid. Certain thiol-containing compounds likewise reduce 1 to 2 or 3. This conversion is accompanied by a readily discernible color change, making cyclo[2]pyridine[8]pyrrole 1 able to differentiate biothiols, such as cysteine (Cys), homocysteine (Hcy), and glutathione (GSH).