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BACKGROUND: Glioma is a malignant brain tumor originating from glial cells, and there still a challenge to accurately predict the prognosis. Programmed cell death (PCD) plays a key role in tumorigenesis and immune response. However, the crosstalk and potential role of various PCDs in prognosis and tumor microenvironment remains unknown. Therefore, we comprehensively discussed the relationship between different models of PCD and the prognosis of glioma and provided new ideas for the optimal targeted therapy of glioma. MATERIALS AND METHODS: We compared and analyzed the role of 14 PCD patterns on the prognosis from different levels. We constructed the cell death risk score (CDRS) index and conducted a comprehensive analysis of CDRS and TME characteristics, clinical characteristics, and drug response. RESULTS: Effects of different PCDs at the genomic, functional, and immune microenvironment levels were discussed. CDRS index containing 6 gene signatures and a nomogram were established. High CDRS is associated with a worse prognosis. Through transcriptome and single-cell data, we found that patients with high CDRS showed stronger immunosuppressive characteristics. Moreover, the high-CDRS group was resistant to the traditional glioma chemotherapy drug Vincristine, but more sensitive to the Temozolomide and the clinical experimental drug Bortezomib. In addition, we identified 19 key potential therapeutic targets during malignant differentiation of tumor cells. CONCLUSION: Overall, we provide the first systematic description of the role of 14 PCDs in glioma. A new CDRS model was built to predict the prognosis and to provide a new idea for the targeted therapy of glioma.
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Neoplasias Encefálicas , Glioma , Microambiente Tumoral , Humanos , Glioma/genética , Glioma/tratamiento farmacológico , Glioma/inmunología , Glioma/patología , Glioma/mortalidad , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/tratamiento farmacológico , Neoplasias Encefálicas/inmunología , Neoplasias Encefálicas/patología , Pronóstico , Antineoplásicos/uso terapéutico , Antineoplásicos/farmacología , Resistencia a Antineoplásicos , Transcriptoma , Apoptosis/efectos de los fármacosRESUMEN
Ca-substituted Ba1-xCaxMg2Al6Si9O30 ceramics were prepared to explore the relationships among their crystal structural parameters, phase compositions, dielectric properties, and coefficients of thermal expansion and applications in C-band antenna. The maximum solubility of Ba1-xCaxMg2Al6Si9O30 was located at x = 0.25, and Ba1-xCaxMg2Al6Si9O30 ceramics (0 ≤ x ≤ 0.25) crystallized in the space group P6/mcc. In Ba1-xCaxMg2Al6Si9O30 single-phase ceramics, εr was dominated by ionic polarizability and "rattling effects" of Ba2+ and Al(2)3+; Q × f was controlled by the roundness of [Si4Al2O18] inner rings and total lattice energy; and τf was affected by the bond valence of Si/Al(1)-O(1). Notably, the low average coefficients of thermal expansion (2.668 ppm/°C) at -150 °C ≤ T ≤ 850 °C and near-zero coefficients of thermal expansion (1.254 ppm/°C) at -150 °C ≤ T ≤ 260 °C were achieved for the Ba1-xCaxMg2Al6Si9O30 (x = 0.1) ceramic. Optimum microwave and terahertz dielectric properties were obtained for the Ba1-xCaxMg2Al6Si9O30 (x = 0.1) ceramic with εr = 5.80, Q × f = 31,174 at 13.99 GHz, τf = -7.10 ppm/°C, and εr = 5.71-5.85 at 0.2 THz ≤ f ≤ 1.0 THz. Also, the Ba1-xCaxMg2Al6Si9O30 (x = 0.1) ceramic substrate had been designed as a C-band patch antenna with a high simulated radiation efficiency (87.76%) and gain (6.30 dBi) at 7.70 GHz (|S11| = -38.41 dB).
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BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive disease with a five-year survival rate of less than 40%. There is significant variability in survival time among IPF patients, but the underlying mechanisms for this are not clear yet. METHODS AND RESULTS: We collected single-cell RNA sequence data of 13,223 epithelial cells taken from 32 IPF patients and bulk RNA sequence data from 456 IPF patients in GEO. Based on unsupervised clustering analysis at the single-cell level and deconvolution algorithm at bulk RNA sequence data, we discovered a special alveolar type 2 cell subtype characterized by high expression of CCL20 (referred to as ATII-CCL20), and found that IPF patients with a higher proportion of ATII-CCL20 had worse prognoses. Furthermore, we uncovered the upregulation of immune cell infiltration and metabolic functions in IPF patients with a higher proportion of ATII-CCL20. Finally, the comprehensive decision tree and nomogram were constructed to optimize the risk stratification of IPF patients and provide a reference for accurate prognosis evaluation. CONCLUSIONS: Our study by integrating single-cell and bulk RNA sequence data from IPF patients identified a special subtype of ATII cells, ATII-CCL20, which was found to be a risk cell subtype associated with poor prognosis in IPF patients. More importantly, the ATII-CCL20 cell subtype was linked with metabolic functions and immune infiltration.
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Fibrosis Pulmonar Idiopática , Humanos , Fibrosis Pulmonar Idiopática/diagnóstico , Fibrosis Pulmonar Idiopática/genética , Fibrosis Pulmonar Idiopática/metabolismo , Células Epiteliales Alveolares/metabolismo , Células Epiteliales/metabolismo , Perfilación de la Expresión Génica , Pronóstico , TranscriptomaRESUMEN
Sense of agency (SoA) is the sensation that self-actions lead to ensuing perceptual consequences. The prospective mechanism emphasizes that SoA arises from motor prediction and its comparison with actual action outcomes, while the reconstructive mechanism stresses that SoA emerges from retrospective causal processing about the action outcomes. Consistent with the prospective mechanism, motor planning regions were identified by neuroimaging studies using the temporal binding (TB) effect, a behavioral measure often linked to implicit SoA. Yet, TB also occurs during passive observation of another's action, lending support to the reconstructive mechanism, but its neural correlates remain unexplored. Here, we employed virtual reality (VR) to modulate such observation-based SoA and examined it with functional magnetic resonance imaging (fMRI). After manipulating an avatar hand in VR, participants passively observed an avatar's "action" and showed a significant increase in TB. The binding effect was associated with the right angular gyrus and inferior parietal lobule, which are critical nodes for inferential and agency processing. These results suggest that the experience of controlling an avatar may potentiate inferential processing within the right inferior parietal cortex and give rise to the illusionary SoA without voluntary action.
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Ilusiones , Realidad Virtual , Humanos , Desempeño Psicomotor , Estudios Retrospectivos , Lóbulo ParietalRESUMEN
The phenotypes of drug action, including therapeutic actions and adverse drug reactions (ADRs), are important indicators for evaluating the druggability of new drugs and repositioning the approved drugs. Here, we provide a user-friendly database, DAPredict (http://bio-bigdata.hrbmu.edu.cn/DAPredict), in which our novel original drug action phenotypes prediction algorithm (Yang,J., Zhang,D., Liu,L. et al. (2021) Computational drug repositioning based on the relationships between substructure-indication. Brief. Bioinformatics, 22, bbaa348) was embedded. Our algorithm integrates characteristics of chemical genomics and pharmacogenomics, breaking through the limitations that traditional drug development process based on phenotype cannot analyze the mechanism of drug action. Predicting phenotypes of drug action based on the local active structures of drugs and proteins can achieve more innovative drug discovery across drug categories and simultaneously evaluate drug efficacy and safety, rather than traditional one-by-one evaluation. DAPredict contains 305 981 predicted relationships between 1748 approved drugs and 454 ADRs, 83 117 predicted relationships between 1478 approved drugs and 178 Anatomical Therapeutic Chemicals (ATC). More importantly, DAPredict provides an online prediction tool, which researchers can use to predict the action phenotypic spectrum of more than 110 000 000 compounds (including about 168 000 natural products) and corresponding proteins to analyze their potential effect mechanisms. DAPredict can also help researchers obtain the phenotype-corresponding active structures for structural optimization of new drug candidates, making it easier to evaluate the druggability of new drug candidates and develop more innovative drugs across drug categories. Database URL: http://bio-bigdata.hrbmu.edu.cn/DAPredict/.
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Algoritmos , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Humanos , Biología Computacional , Genómica , Bases de Datos Factuales , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos/genética , Fenotipo , Reposicionamiento de MedicamentosRESUMEN
Identifying drug phenotypic effects, including therapeutic effects and adverse drug reactions (ADRs), is an inseparable part for evaluating the potentiality of new drug candidates (NDCs). However, current computational methods for predicting phenotypic effects of NDCs are mainly based on the overall structure of an NDC or a related target. These approaches often lead to inconsistencies between the structures and functions and limit the prediction space of NDCs. In this study, first, we constructed quantitative associations of substructure-domain, domain-ADR, and domain-ATC (Anatomical Therapeutic Chemical Classification System code) through L1LOG and L1SVM machine learning models. These associations represent relationships between phenotypes (ADRs and ATCs) and local structures of drugs and proteins. Then, based on these established associations, substructure-phenotype relationships were constructed which were utilized to quantify drug-phenotype relationships. Thus, this approach could achieve high-throughput and effective evaluations of the druggability of NDCs by referring to the established substructure-phenotype relationships and structural information of NDCs without additional prior knowledge. Using this computational pipeline, 83,205 drug-ATC relationships (including 1,479 drugs and 178 ATCs) and 306,421 drug-ADR relationships (including 1,752 drugs and 454 ADRs) were predicted in total. The prediction results were validated at four levels: five-fold cross validation, public databases, literature, and molecular docking. Furthermore, three case studies demonstrated the feasibility of our method. 79 ATCs and 269 ADRs were predicted to be related to Maraviroc, an approved drug, including the existing antiviral effect in clinical use. Additionally, we also found risk substructures of severe ADRs, for example, SUB215 (>= 1, saturated or only aromatic carbon ring size 7) can result in shock. And we analyzed the mechanism of action (MOA) of interested drugs based on the established drug-substructure-domain-protein associations. In a word, this approach through establishing drug-substructure-phenotype relationships can achieve quantitative prediction of phenotypes for a given NDC or drug without any prior knowledge except its structure information. Using that way, we can directly obtain the relationships between substructure and phenotype of a compound, which is more convenient to analyze the phenotypic mechanism of drugs and accelerate the process of rational drug design.
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Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Humanos , Simulación del Acoplamiento Molecular , Bases de Datos Factuales , Aprendizaje Automático , FenotipoRESUMEN
Molecular fingerprints are used to represent chemical (structural, physicochemical, etc.) properties of large-scale chemical sets in a low computational cost way. They have a prominent role in transforming chemical data sets into consistent input formats (bit strings or numeric values) suitable for in silico approaches. In this review, we summarize and classify common and state-of-the-art fingerprints into eight different types (dictionary based, circular, topological, pharmacophore, protein-ligand interaction, shape based, reinforced, and multi). We also highlight applications of fingerprints in early drug research and development (R&D). Thus, this review provides a guide for the selection of appropriate fingerprints of compounds (or ligand-protein complexes) for use in drug R&D.
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ABSTRACT: Vibrio parahaemolyticus is the main foodborne pathogen worldwide that causes acute gastroenteritis. A quantitative microbiological risk assessment (QMRA) was conducted to evaluate the health risk associated with V. parahaemolyticus in shellfish in the coastal cities in the eastern part of the People's Republic of China. The QMRA framework was established from shellfish at retail to cooking at home to consumption. The prevalence and level of V. parahaemolyticus in shellfish, cooking methods, storage temperature, time after purchase, shellfish consumption frequency, and consumption amount were analyzed in the exposure assessment. The results of the exposure assessment were introduced into the beta-Poisson dose-response model, and Monte Carlo analysis was used to calculate the risk of gastroenteritis from shellfish consumption. The probability of illness caused by V. parahaemolyticus from shellfish consumption per person per year (Pill,yr) was 3.49E-05. Seasonal differences were noted in the Pill/meal; the maximum was 4.81E-06 in summer and the minimum was 2.27E-07 in winter. The sensitivity analysis revealed that the level of V. parahaemolyticus in shellfish and the amount of shellfish consumed per meal were main factors contributing to illness. This QMRA provided valuable information such as the probability of illness associated with the consumption of shellfish and reference points for prevention strategies and control standards of V. parahaemolyticus in shellfish.
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Gastroenteritis , Vibriosis , Vibrio parahaemolyticus , China , Ciudades , Gastroenteritis/epidemiología , Humanos , Medición de Riesgo , Mariscos/microbiología , Vibriosis/epidemiología , Vibriosis/microbiologíaRESUMEN
Norovirus (NoV) is a main foodborne pathogen of acute gastroenteritis in the world. A preliminary quantitative risk assessment (QRA) was conducted to evaluate the health risk caused by this virus in shellfish in the Yellow Sea and Bohai Sea of China. The QRA framework was established from the process of shellfish at retail through cooking at home to consumer consumption. The prevalence and quantity of NoVs in shellfish, cooking methods, internal temperature and time of shellfish in different cooking conditions, shellfish consumption frequency, and consumption amount were analyzed in the exposure assessment. The results of exposure assessment were introduced into the beta-Poisson dose-response model, and Monte Carlo analysis was used to calculate the risk of gastroenteritis caused by shellfish consumption in the cities around the Yellow Sea and Bohai Sea of China. The results showed that the probability of illness caused by NoVs due to shellfish consumption per year (Pill,yr) was 1.86 × 10-5. It was estimated that the annual number of patients with gastroenteritis per 1,000,000 general population (Nexp,mil) was 0.10, 1.23, 16.90, and 0.38 for population aged 0-4, 5-18, 19-64, and >65 years, respectively. This assessment provides valuable information such as the probability of illness associated with the consumption of shellfish and it also provides a reference for further in-depth QRA of NoVs in shellfish or other foods.
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Norovirus , China/epidemiología , Contaminación de Alimentos/análisis , Humanos , Medición de Riesgo , MariscosRESUMEN
At present, computational methods for drug repositioning are mainly based on the whole structures of drugs, which limits the discovery of new functions due to the similarities between local structures of drugs. In this article, we, for the first time, integrated the features of chemical-genomics (substructure-domain) and pharmaco-genomics (domain-indication) based on the assumption that drug-target interactions are mediated by the substructures of drugs and the domains of proteins to identify the relationships between substructure-indication and establish a drug-substructure-indication network for predicting all therapeutic effects of tested drugs through only information on the substructures of drugs. In total, 83 205 drug-indication relationships with different correlation scores were obtained. We used three different verification methods to indicate the accuracy of the method and the reliability of the scoring system. We predicted all indications of olaparib using our method, including the known antitumor effect and unknown antiviral effect verified by literature, and we also discovered the inhibitory mechanism of olaparib toward DNA repair through its specific sub494 (o = C-C: C), as it participates in the low synthesis of the poly subfunction of the apoptosis pathway (hsa04210) by inhibiting the Inositol 1,4,5-trisphosphate receptor(s) (ITPRs) and hydrolyzing poly (ADP ribose) polymerases. ElectroCardioGrams of four drugs (quinidine, amiodarone, milrinone and fosinopril) demonstrated the effect of anti-arrhythmia. Unlike previous studies focusing on the overall structures of drugs, our research has great potential in the search for more therapeutic effects of drugs and in predicting all potential effects and mechanisms of a drug from the local structural similarity.
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Biología Computacional , Bases de Datos Factuales , Interacciones Farmacológicas , Reposicionamiento de Medicamentos , Genómica , Humanos , Proteínas/química , Proteínas/metabolismoRESUMEN
Phantom limb pain (PLP) is a type of chronic pain that follows limb amputation, brachial plexus avulsion injury, or spinal cord injury. Treating PLP is a well-known challenge. Currently, virtual reality (VR) interventions are attracting increasing attention because they show promising analgesic effects. However, most previous studies of VR interventions were conducted with a limited number of patients in a single trial. Few studies explored questions such as how multiple VR sessions might affect pain over time, or if a patient's ability to move their phantom limb may affect their PLP. Here we recruited five PLP patients to practice two motor tasks for multiple VR sessions over 6 weeks. In VR, patients "inhabit" a virtual body or avatar, and the movements of their intact limbs are mirrored in the avatar, providing them with the illusion that their limbs respond as if they were both intact and functional. We found that repetitive exposure to our VR intervention led to reduced pain and improvements in anxiety, depression, and a sense of embodiment of the virtual body. Importantly, we also found that their ability to move their phantom limbs improved as quantified by shortened motor imagery time with the impaired limb. Although the limited sample size prevents us from performing a correlational analysis, our findings suggest that providing PLP patients with sensorimotor experience for the impaired limb in VR appears to offer long-term benefits for patients and that these benefits may be related to changes in their control of the phantom limbs' movement.