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Distorted urea levels indicate several liver, kidney, or metabolic diseases; however, traditional clinical urea detection relies on urease-based methods enslaved to well-known limitations of high-price, unstable properties, complicated sample pretreatment and analysis procedures, and difficult visual real-time monitoring. Herein, nonenzymatic paper-based fluorescent materials (UFP-BP) are strategically integrated with an on-demand fluorescent-sensor (UFP) self-aggregated nanoparticle on commercial filter paper for pre-dilution-free and visual real-time urea monitoring. The UFP is synthesized and self-aggregated into the fluorescent nanoparticles for selective urea recognition. Then, the nanoparticles are interstitially loaded on filter paper to nanoengineer the UFP-BP, achieving selective quantitative urea detection in the normal concentration range (10-1000 mm). UFP and UFP-BP can successfully monitor urea levels in real rat urine, artificial simulants, and milk. The proposed sensing platform, integrated with smartphones, offers accurate, quantitative, nonenzymatic, noninvasive, pre-dilution-free, on-site, rapid, low-cost, easy-to-operate, real-time visual urea detection in food samples and human body fluids. The designed sensing system can provide early warnings of abnormal nitrogen-based health issues.
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Previous studies have found a possible association between nickel and metabolic syndrome (MetS), but with conflicting results. No studies have determined whether nickel exposure increases the prevalence of MetS in the general U.S. population. Therefore, we used data from the National Health and Nutrition Examination Survey (NHANES) to assess the association between urinary nickel and MetS. Since urinary nickel levels were presented as a skewed distribution, they were normalized using a logarithmic transformation. Weighted multivariate logistic models, restricted cubic spline, threshold effect analysis, and subgroup analyses were used to examine the association between urinary nickel concentration and the risk of MetS and its components. Based on data from 1577 participants, individuals in the second, third, and fourth quartiles of urinary nickel had an adjusted OR for MetS of 1.42 (95% CI: 0.88, 2.28), 2.00 (95% CI: 1.22, 3.28), and 1.68 (95% CI: 1.05, 2.70), respectively, representing an inverted "L"-shaped nonlinear dose-response relationship with an inflection point at 0.2141 ng/L. Patients over the age of 40, males, less educated, and smokers are more susceptible to nickel exposure. In addition, there were significant associations between nickel and most components of the MetS, with the strongest to weakest correlations being high fasting glucose, reduced high-density lipoprotein, abdominal obesity, and elevated blood pressure; however, there was no significant correlation between nickel and hyperlipidemia. In conclusion, environmental nickel exposure increases the prevalence of MetS in U.S. adults, particularly in males over 40 years of age, those with less education, and smokers.
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Deep-learning-based classification models are increasingly used for predicting molecular properties in drug development. However, traditional classification models using the Softmax function often give overconfident mispredictions for out-of-distribution samples, highlighting a critical lack of accurate uncertainty estimation. Such limitations can result in substantial costs and should be avoided during drug development. Inspired by advances in evidential deep learning and Posterior Network, we replaced the Softmax function with a normalizing flow to enhance the uncertainty estimation ability of the model in molecular property classification. The proposed strategy was evaluated across diverse scenarios, including simulated experiments based on a synthetic dataset, ADMET predictions, and ligand-based virtual screening. The results demonstrate that compared with the vanilla model, the proposed strategy effectively alleviates the problem of giving overconfident but incorrect predictions. Our findings support the promising application of evidential deep learning in drug development and offer a valuable framework for further research.
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Polymer-based flexible conductive materials are crucial for wearable electronics, electronic skin, and other smart materials. However, their development and commercial applications have been hampered by the lack of strain tolerance in the conductive network, poor bonding with polymers, discomfort during wear, and a lack of biocompatibility. This study utilized oil-tanned leather with a natural network structure, high toughness, and high tensile deformation recovery as a structural template. A graphene (Gr) conductive network was then constructed on the collagen network of the leather, with coordination cross-linking between Gr and collagen fibers through aluminum ions (Al3+). A new flexible conductive material (Al-GL) was then constructed. Molecular dynamics simulations and experimental validation revealed the existence of physical adsorption, hydrogen bonding adsorption, and ligand bonding between Al3+, Gr, and collagen fibers. Although we established that the binding sites between Al3+ and collagen fibers were primarily on carboxyl groups (-COOH), the mechanism of chemical bonding between Gr and collagen fibers remains unclear. The Al-GL composite exhibited a high shrinkage temperature (67.4 °C) and low electrical resistance (16.1 kΩ·sq-1), as well as good softness (9.33 mN), biocompatibility, biodegradability (<60 h), and air and moisture permeability. Furthermore, the incorporation of Al3+ resulted in a heightened Gr binding strength on Al-GL, and the resistance remained comparable following 1 h of water washing. The Al-GL sensor prepared by WPU encapsulation not only demonstrated highly sensitive responses to diverse motion signals of the human body but also retained a certain degree of response to external mechanical effects underwater. Additionally, the Al-GL-based triboelectric nanogenerator (Al-GL TENG) exhibited distinct response signals to different materials. The Al-GL prepared by the one-pot method proposed in this study offers a novel approach to combining functional nanofillers and substrate materials, providing a theoretical foundation for collagen fiber-based flexible conductive materials.
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Materiais Biocompatíveis , Colágeno , Condutividade Elétrica , Grafite , Grafite/química , Materiais Biocompatíveis/química , Colágeno/química , Dispositivos Eletrônicos Vestíveis , Humanos , Alumínio/química , Simulação de Dinâmica Molecular , AnimaisRESUMO
Owing to its versatile roles in almost all aspects of plants, FERONIA (FER), a receptor-like kinase of the Catharanthus roseus receptor-like kinase 1-like (CrRLK1L) subfamily, has received extensive research interests during the past decades. Accumulating evidence has been emerged that FER homologs in horticultural crops also play crucial roles in reproductive biology and responses to environmental stimuli (abiotic and biotic stress factors). Here, we provide a review for the latest advances in the studies on FER homologs in modulating stress responses in horticultural crops, and further analyze the underlying mechanisms maintained by FER. Moreover, we also envisage the missing links in current work and provide a perspective for future studies on this star protein.
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Although vaccination remains the prevalent prophylactic means for controlling Influenza A virus (IAV) infections, novel structural antivirus small-molecule drugs with new mechanisms of action for treating IAV are highly desirable. Herein, we describe a modular biomimetic strategy to expeditiously achieve a new class of macrocycles featuring oxime, which might target the hemagglutinin (HA)-mediated IAV entry into the host cells. SAR analysis revealed that the size and linker of the macrocycles play an important role in improving potency. Particularly, as a 14-membered macrocyclic oxime, 37 exhibited potent inhibitory activity against IAV H1N1 with an EC50 value of 23 nM and low cytotoxicity, which alleviated cytopathic effects and protected cell survival obviously after H1N1 infection. Furthermore, 37 showed significant synergistic activity with neuraminidase inhibitor oseltamivir in vitro.
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Antivirais , Vírus da Influenza A Subtipo H1N1 , Compostos Macrocíclicos , Oximas , Vírus da Influenza A Subtipo H1N1/efeitos dos fármacos , Oximas/farmacologia , Oximas/química , Oximas/síntese química , Antivirais/farmacologia , Antivirais/química , Antivirais/síntese química , Relação Estrutura-Atividade , Humanos , Cães , Compostos Macrocíclicos/farmacologia , Compostos Macrocíclicos/química , Compostos Macrocíclicos/síntese química , Animais , Células Madin Darby de Rim Canino , Descoberta de Drogas , Biomimética , Oseltamivir/farmacologia , Oseltamivir/químicaRESUMO
BACKGROUND: The association between magnesium status and sleep quality is unclear. The aim of this study was to determine the relationship between renal reabsorption-related magnesium depletion score (MDS) and sleep quality. METHODS: This study was conducted through a cross-sectional survey of adults aged ≥20â¯years who participated in NHANES 2005-2014. We used weighted logistic regression to examine the association between MDS and sleep quality and performed trend tests to analyze for the presence of a dose-response relationship. Subgroup analyses were performed based on various sleep outcomes and covariates. RESULTS: A total of 20,585 participants were included in the study, with a mean age of 48.8â¯years and 50.7â¯% female. After adjusting for all covariates, we found a graded dose-response relationship between MDS and sleep trouble as well as sleep disorder. Further analyses revealed a significant positive association between MDS and sleep apnea (ORâ¯=â¯3.01; 95â¯% CI 1.37-6.62), but no association with restless legs, insomnia or insufficient sleep. In addition, subgroup analyses revealed that middle-aged, male, obese, low magnesium intake, and depressed patients were more prone to sleep trouble and sleep disorder; interestingly, MDS was positively associated with excessive sleep in subjects ≥60â¯years and without depression. CONCLUSIONS: Our study found a significant association between MDS and sleep quality, particularly sleep apnea, but adequate magnesium intake may be beneficial in mitigating this association. MDS may be associated with excessive sleep in older adults, but not with insufficient sleep or insomnia.
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Deficiência de Magnésio , Qualidade do Sono , Transtornos do Sono-Vigília , Humanos , Feminino , Masculino , Estudos Transversais , Pessoa de Meia-Idade , Deficiência de Magnésio/epidemiologia , Adulto , Transtornos do Sono-Vigília/epidemiologia , Magnésio/sangue , Inquéritos Nutricionais , Distúrbios do Início e da Manutenção do Sono/epidemiologia , Idoso , Adulto Jovem , Síndromes da Apneia do Sono/epidemiologiaRESUMO
Epstein-Barr virus (EBV) can infect both B cells and epithelial cells (ECs), causing diseases such as mononucleosis and cancer. It enters ECs via Ephrin receptor A2 (EphA2). The function of interferon-induced transmembrane protein-1 (IFITM1) in EBV infection of ECs remains elusive. Here we report that IFITM1 inhibits EphA2-mediated EBV entry into ECs. RNA-sequencing and clinical sample analysis show reduced IFITM1 in EBV-positive ECs and a negative correlation between IFITM1 level and EBV copy number. IFITM1 depletion increases EBV infection and vice versa. Exogenous soluble IFITM1 effectively prevents EBV infection in vitro and in vivo. Furthermore, three-dimensional structure prediction and site-directed mutagenesis demonstrate that IFITM1 interacts with EphA2 via its two specific residues, competitively blocking EphA2 binding to EBV glycoproteins. Finally, YTHDF3, an m6A reader, suppresses IFITM1 via degradation-related DEAD-box protein 5 (DDX5). Thus, this study underscores IFITM1's crucial role in blocking EphA2-mediated EBV entry into ECs, indicating its potential in preventing EBV infection.
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Antígenos de Diferenciação , Efrina-A2 , Células Epiteliais , Infecções por Vírus Epstein-Barr , Herpesvirus Humano 4 , Receptor EphA2 , Internalização do Vírus , Humanos , Herpesvirus Humano 4/fisiologia , Herpesvirus Humano 4/genética , Herpesvirus Humano 4/metabolismo , Células Epiteliais/virologia , Células Epiteliais/metabolismo , Infecções por Vírus Epstein-Barr/virologia , Infecções por Vírus Epstein-Barr/metabolismo , Receptor EphA2/metabolismo , Efrina-A2/metabolismo , Efrina-A2/genética , Antígenos de Diferenciação/metabolismo , Antígenos de Diferenciação/genética , Animais , Células HEK293 , Ligação Proteica , Camundongos , Linhagem CelularRESUMO
China is home to the second largest population of children and adolescents in the world. Yet demographic shifts mean that the government must manage the challenge of fewer children with the needs of an ageing population, while considering the delicate tension between economic growth and environmental sustainability. We mapped the health problems and risks of contemporary school-aged children and adolescents in China against current national health policies. We involved multidisciplinary experts, including young people, with the aim of identifying actionable strategies and specific recommendations to promote child and adolescent health and wellbeing. Notwithstanding major improvements in their health over the past few decades, contemporary Chinese children and adolescents face distinct social challenges, including high academic pressures and youth unemployment, and new health concerns including obesity, mental health issues, and sexually transmitted infections. Inequality by gender, geography, and ethnicity remains a feature of health risks and outcomes. We identified a mismatch between current health determinants, risks and outcomes, and government policies. To promote the health of children and adolescents in China, we recommend a set of strategies that target government-led initiatives across the health, education, and community sectors, which aim to build supportive and responsive families, safe communities, and engaging and respectful learning environments. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.
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Política de Saúde , Adolescente , Criança , Feminino , Humanos , Masculino , Saúde do Adolescente , Saúde da Criança , China , População do Leste Asiático , Necessidades e Demandas de Serviços de SaúdeRESUMO
[This corrects the article DOI: 10.3389/fphar.2019.01287.].
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The lipid synthesis of fatty acid (FA) represents a significant hallmark in the occurrence and progression of malignant tumor, which are associated with lymph node (LN) metastasis. Elucidation of the molecular mechanisms underlying LN metastasis could provide therapeutic strategies for cervical cancer (CCa). N6-Methyladenosine (m6A), the most prevalent and abundant RNA modification, exerts specific regulatory control over a series of oncogene expressions. This study demonstrated a clinical correlation between the upregulation of the m6A reader YTHDF3 and LN metastasis, thereby contributing to poor overall survival probability (OS) among CCa patients. The mechanistic investigation revealed that SREBF1 transcriptionally activated YTHDF3 expression by binding to its promoter. Functional experiments demonstrated that the upregulation of YTHDF3 significantly enhanced the in vitro proliferative, migratory, and invasive capacities of CCa cells, while also promoting lymphangiogenesis and facilitating LN metastasis in vivo. Mechanistically, the upregulation of LRP6 through YTHDF3-mediated m6A modification resulted in increased expression of FASN and ACC1, leading to both lipolysis of lipid droplets and synthesis of free fatty acid. Ultimately, this promoted fatty acid metabolism and enhanced LN metastasis by activating the LRP6-YAP-VEGF-C axis, which could induce lymphangiogenesis in CCa. Our study highlighted that YTHDF3 can serve as a promising therapeutic target and predictive biomarker for CCa patients with LN metastasis.
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Metabolismo dos Lipídeos , Proteína-6 Relacionada a Receptor de Lipoproteína de Baixa Densidade , Proteínas de Ligação a RNA , Neoplasias do Colo do Útero , Feminino , Humanos , Ácidos Graxos , Lipogênese , Proteína-6 Relacionada a Receptor de Lipoproteína de Baixa Densidade/genética , Metástase Linfática , Neoplasias do Colo do Útero/genética , Proteínas de Ligação a RNA/genéticaRESUMO
BACKGROUND: Over the past few decades, agonists binding to the benzodiazepine site of the GABAA receptor have been successfully developed as clinical drugs. Different modulators (agonist, antagonist, and reverse agonist) bound to benzodiazepine sites exhibit different or even opposite pharmacological effects, however, their structures are so similar that it is difficult to distinguish them based solely on molecular skeleton. This study aims to develop classification models for predicting the agonists. METHODS: 306 agonists or non-agonists were collected from literature. Six machine learning algorithms including RF, XGBoost, AdaBoost, GBoost, SVM, and ANN algorithms were employed for model development. Using six descriptors including 1D/2D Descriptors, ECFP4, 2D-Pharmacophore, MACCS, PubChem, and Estate fingerprint to characterize chemical structures. The model interpretability was explored by SHAP method. RESULTS: The best model demonstrated an AUC value of 0.905 and an MCC value of 0.808 for the test set. The PubMac-based model (PubMac-GB) achieved best AUC values of 0.935 for test set. The SHAP analysis results emphasized that MaccsFP62, ECFP_624, ECFP_724, and PubchemFP213 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. The PubMac-GB model was applied to virtual screening for potential GABAA agonists and the top 100 compounds were given. CONCLUSION: Overall, our ensemble learning-based model (PubMac-GB) achieved comparable performance and would be helpful in effectively identifying agonists of GABAA receptors.
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Agonistas de Receptores de GABA-A , Receptores de GABA-A , Receptores de GABA-A/metabolismo , Benzodiazepinas , Aprendizado de Máquina , Ácido gama-AminobutíricoRESUMO
Kinase inhibitors are crucial in cancer treatment, but drug resistance and side effects hinder the development of effective drugs. To address these challenges, it is essential to analyze the polypharmacology of kinase inhibitor and identify compound with high selectivity profile. This study presents KinomeMETA, a framework for profiling the activity of small molecule kinase inhibitors across a panel of 661 kinases. By training a meta-learner based on a graph neural network and fine-tuning it to create kinase-specific learners, KinomeMETA outperforms benchmark multi-task models and other kinase profiling models. It provides higher accuracy for understudied kinases with limited known data and broader coverage of kinase types, including important mutant kinases. Case studies on the discovery of new scaffold inhibitors for membrane-associated tyrosine- and threonine-specific cdc2-inhibitory kinase and selective inhibitors for fibroblast growth factor receptors demonstrate the role of KinomeMETA in virtual screening and kinome-wide activity profiling. Overall, KinomeMETA has the potential to accelerate kinase drug discovery by more effectively exploring the kinase polypharmacology landscape.
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Antineoplásicos , Polifarmacologia , Proteínas Serina-Treonina Quinases , Descoberta de DrogasRESUMO
Protein tyrosine phosphatase nonreceptor Type 2 (PTPN2) is an attractive target for cancer immunotherapy. PTPN2 and another subtype of PTP1B are highly similar in structure, but their biological functions are distinct. Therefore, subtype-selective targeting of PTPN2 remains a challenge for researchers. Herein, the development of small molecular PTPN2 degraders based on a thiadiazolidinone dioxide-naphthalene scaffold and a VHL E3 ligase ligand is described, and the PTPN2/PTP1B subtype-selective degradation is achieved for the first time. The linker structure modifications led to the discovery of the subtype-selective PTPN2 degrader PVD-06 (PTPN2/PTP1B selective index > 60-fold), which also exhibits excellent proteome-wide degradation selectivity. PVD-06 induces PTPN2 degradation in a ubiquitination- and proteasome-dependent manner. It efficiently promotes T cell activation and amplifies IFN-γ-mediated B16F10 cell growth inhibition. This study provides a convenient chemical knockdown tool for PTPN2-related research and a paradigm for subtype-selective PTP degradation through nonspecific substrate-mimicking ligands, demonstrating the therapeutic potential of PTPN2 subtype-selective degradation.
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Proteína Tirosina Fosfatase não Receptora Tipo 2 , Ubiquitina-Proteína Ligases , Proteína Tirosina Fosfatase não Receptora Tipo 2/genética , Proteína Tirosina Fosfatase não Receptora Tipo 2/metabolismo , Fosforilação , Ubiquitina-Proteína Ligases/metabolismo , Ubiquitinação , Complexo de Endopeptidases do Proteassoma/metabolismoRESUMO
Immunotherapy has recently emerged as the predominant therapeutic approach for cervical cancer (CCa), driven by the groundbreaking clinical achievements of immune checkpoint inhibitors (ICIs), such as anti-PD-1/PD-L1 antibodies. N4-acetylcytidine (ac4C) modification, catalyzed by NAT10, is an important posttranscriptional modification of mRNA in cancers. However, its impact on immunological dysregulation and the tumor immunotherapy response in CCa remains enigmatic. Here, a significant increase in NAT10 expression in CCa tissues is initially observed that is clinically associated with poor prognosis. Subsequently, it is found that HOXC8 activated NAT10 by binding to its promoter, thereby stimulating ac4C modification of FOXP1 mRNA and enhancing its translation efficiency, eventually leading to induction of GLUT4 and KHK expression. Moreover, NAT10/ac4C/FOXP1 axis activity resulted in increased glycolysis and a continuous increase in lactic acid secretion by CCa cells. The lactic acid-enriched tumor microenvironment (TME) further contributed to amplifying the immunosuppressive properties of tumor-infiltrating regulatory T cells (Tregs). Impressively, NAT10 knockdown enhanced the efficacy of PD-L1 blockade-mediated tumor regression in vivo. Taken together, the findings revealed the oncogenic role of NAT10 in initiating crosstalk between cancer cell glycolysis and immunosuppression, which can be a target for synergistic PD-1/PD-L1 blockade immunotherapy in CCa.
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Neoplasias do Colo do Útero , Feminino , Humanos , Neoplasias do Colo do Útero/genética , Antígeno B7-H1/metabolismo , Terapia de Imunossupressão , Glicólise , RNA Mensageiro/metabolismo , Ácido Láctico , Microambiente Tumoral , Proteínas Repressoras/metabolismo , Fatores de Transcrição Forkhead/genética , Fatores de Transcrição Forkhead/metabolismo , Acetiltransferases N-Terminal/metabolismoRESUMO
Skeletal muscle function declines in the aging process or disease; however, until now, skeletal muscle has remained one of the organs most undertreated with medication. In this study, naringenin (NAR) was found to build muscle endurance in wild-type mice of different ages by increasing oxidative myofiber numbers and aerobic metabolism, and it ameliorates muscle dysfunction in mdx mice. The transcription factor Sp1 was identified as a direct target of NAR and was shown to mediate the function of NAR on muscle. Moreover, the binding site of NAR on Sp1 was further validated as GLN-110. NAR enhances the binding of Sp1 to the CCCTGCCCTC sequence of the Esrrg promoter by promoting Sp1 phosphorylation, thus upregulating Esrrg expression. The identification of the Sp1-ERRγ transcriptional axis is of great significance in basic muscle research, and this function of NAR has potential implications for the improvement of muscle function and the prevention of muscle atrophy.
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Distrofia Muscular de Duchenne , Camundongos , Animais , Distrofia Muscular de Duchenne/metabolismo , Camundongos Endogâmicos mdx , Músculo Esquelético/metabolismo , Regiões Promotoras Genéticas/genéticaRESUMO
One of the key points of machine learning-assisted directed evolution (MLDE) is the accurate learning of the fitness landscape, a conceptual mapping from sequence variants to the desired function. Here, we describe a multi-protein training scheme that leverages the existing deep mutational scanning data from diverse proteins to aid in understanding the fitness landscape of a new protein. Proof-of-concept trials are designed to validate this training scheme in three aspects: random and positional extrapolation for single-variant effects, zero-shot fitness predictions for new proteins, and extrapolation for higher-order variant effects from single-variant effects. Moreover, our study identified previously overlooked strong baselines, and their unexpectedly good performance brings our attention to the pitfalls of MLDE. Overall, these results may improve our understanding of the association between different protein fitness profiles and shed light on developing better machine learning-assisted approaches to the directed evolution of proteins. A record of this paper's transparent peer review process is included in the supplemental information.
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Aprendizado de Máquina , Revisão por Pares , Mutação/genéticaRESUMO
Intestinal stem cell (ISC) is a promising therapeutic target for inflammatory bowel disease. Cholesterol availability is critical for ISC stemness. Low plasma cholesterol is a typical feature of Crohn's disease (CD); however, its impact on mucosal healing remains unclear. Here, we identified an essential role of sorting nexin 10 (SNX10) in maintaining the stemness of ISCs. SNX10 expression in intestinal tissues positively correlates with the severity of human CD and mouse colitis. Conditional SNX10 knockout in intestinal epithelial cells or ISCs promotes intestinal mucosal repair by maintaining the ISC population associated with increased intracellular cholesterol synthesis. Disassociation of ERLIN2 with SCAP by SNX10 deletion enhances the activation of SREBP2, resulting in increased cholesterol biosynthesis. DC-SX029, a small-molecule inhibitor of SNX10, was used to verify the druggable potential of SNX10 for the treatment of patients with CD. Our study provides a strategy for mucosal healing through SREBP2-mediated stemness restoration of ISCs.
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Doenças Inflamatórias Intestinais , Nexinas de Classificação , Animais , Humanos , Camundongos , Mucosa Intestinal , Intestinos , Nexinas de Classificação/genética , Células-TroncoRESUMO
ETHNOPHARMACOLOGICAL RELEVANCE: Spatholobi caulis (SC), the dried vine stem of Spatholobus suberectus Dunn, is known as Ji Xue Teng in China, and has long been used as traditional Chinese medicine (TCM) to treat anaemia, menstrual abnormalities, rheumatoid arthritis, purpura, etc. AIM OF THE REVIEW: The aim of this review is to provide a systematic and updated summary of the traditional uses, chemical constituents, biological activities and clinical applications of SC. In addition, several suggestions for future research on SC are also proposed. MATERIALS AND METHODS: Extensive information and data on SC were obtained from electronic databases (ScienceDirect, Web of Science, PubMed, CNKI, Baidu Scholar, Google Scholar, ResearchGate, SpringerLink and Wiley Online). Additional information was collected from Ph.D. and MSc dissertations, published books, and classic material medica. RESULTS: To date, phytochemical studies have revealed that approximately 243 chemical ingredients have been isolated from SC and identified, including flavonoids, glycosides, phenolic acids, phenylpropanoids, volatile oils, sesquiterpenoids and other compounds. Many studies have indicated that extracts and pure constituents from SC possess a wide spectrum of in vitro and in vivo pharmacological effects, such as anti-tumour, haematopoietic, anti-inflammatory, antidiabetic, antioxidant, antiviral and antibacterial effects, as well as other activities. SC could be applied to the treatment of leukopenia, aplastic anemic, endometriosis, etc. according to the clinical reports. The traditional efficacies of SC is due to the biological functions of its chemical compounds, especially flavonoids. However, research investigating the toxicological effects of SC is relatively limited. CONCLUSIONS: SC is widely used in TCM formulae and its some traditional efficacies has been confirmed by extensive recent pharmacological and clinical studies. Most the biological activities of the SC may be attributed to flavonoids. However, in-depth studies on the molecular mechanisms of the effective ingredients and extracts of SC are limited. Further systematic studies focusing on pharmacokinetics, toxicology and quality control are needed to ensure the effective and safe application of SC.
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Medicamentos de Ervas Chinesas , Medicina Tradicional Chinesa , Etnofarmacologia , Fitoterapia , Medicamentos de Ervas Chinesas/farmacologia , Medicamentos de Ervas Chinesas/uso terapêutico , Medicamentos de Ervas Chinesas/química , Compostos Fitoquímicos/farmacologia , Compostos Fitoquímicos/uso terapêutico , Flavonoides , Extratos Vegetais/farmacologia , Extratos Vegetais/uso terapêutico , Extratos Vegetais/químicaRESUMO
Background: Abuse of Synthetic Cannabinoids (SCs) has become a serious threat to public health. Due to the various structural and chemical group modified by criminals, their detection is a major challenge in forensic toxicological identification. Therefore, rapid and efficient identification of SCs is important for forensic toxicology and drug bans. The prediction of an analyte's retention time in liquid chromatography is an important index for the qualitative analysis of compounds and can provide informatics solutions for the interpretation of chromatographic data. Methods: In this study, experimental data from high-resolution mass spectrometry (HRMS) are used to construct a regression model for predicting the retention time of SCs using machine learning methods. The prediction ability of the model is improved by adopting a strategy that combines different descriptors in different independent machine-learning methods. Results: The best model was obtained with a method that combined Substructure Fingerprint Count and Finger printer features and the support vector regression (SVR) method, as it exhibited an R2 value of 0.81 for the validation set and 0.83 for the test set. In addition, 4 new SCs were predicted by the optimized model, with a prediction error within 3%. Conclusions: Our study provides a model that can predict the retention time of compounds and it can be used as a filter to reduce false-positive candidates when used in combination with LC-HRMS, especially in the absence of reference standards. This can improve the confidence of identification in non-targeted analysis and the reliability of identifying unknown substances.