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BACKGROUND: The treatment of unresectable hepatocellular carcinoma (uHCC) challenging due to unfulfilled clinical requirements. OBJECTIVE: To evaluate the safety and efficacy of combining transarterial chemoembolization (TACE) with sintilimab and lenvatinib in the treatment of uHCC. METHODS: We retrospectively analyzed the data of patients with uHCC who were treated with a combination of TACE, sintilimab, and lenvatinib between May 2019 and December 2021 at the Chinese PLA General Hospital. Systemic treatment was started 1 week after TACE was performed. Sintilimab was administered intravenously at a dosage of 200 mg every three weeks, and lenvatinib was given orally at dosages of 8 mg or 12 mg daily, contingent upon the weight of the patients. The primary endpoint was the objective response rate (ORR) as per the mRECIST. Secondary endpoints were disease control rate (DCR), progression-free survival (PFS), overall survival (OS) and treatment-related adverse events (tr-AEs). RESULTS: A total of 32 patients were enrolled in the study. Among them, 9 patients were classified as Barcelona Clinic Liver Cancer-B (BCLC-B), 23 patients were classified as BCLC-C, 14 patients diagnosed with portal vein tumors, and 12 patients were diagnosed with extra hepatic metastases. The ORR and DCR were 75% and 90.6% respectively, with 4 patients exhibiting (12.5%) complete response, 20 patients exhibiting (62.5%) partial response, 5 patients exhibiting (15.6%) stable disease, and 3 patients exhibiting (9.4%) progressive disease. With a median follow-up time of 19.6 months, the median PFS was 9.9 months, and the median OS was 33.3 months. A total of 31 patients experienced different degrees of tr-AEs, of which 2 were grade 3 tr-AEs. CONCLUSION: The combination therapy of TACE, sintilimab, and lenvatinib demonstrates satisfactory efficacy in the treatment of uHCC with manageable tr-AEs.
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Anticorpos Monoclonais Humanizados , Protocolos de Quimioterapia Combinada Antineoplásica , Carcinoma Hepatocelular , Quimioembolização Terapêutica , Neoplasias Hepáticas , Compostos de Fenilureia , Quinolinas , Humanos , Carcinoma Hepatocelular/tratamento farmacológico , Carcinoma Hepatocelular/patologia , Carcinoma Hepatocelular/terapia , Neoplasias Hepáticas/tratamento farmacológico , Neoplasias Hepáticas/terapia , Neoplasias Hepáticas/patologia , Masculino , Quinolinas/administração & dosagem , Quinolinas/uso terapêutico , Estudos Retrospectivos , Pessoa de Meia-Idade , Feminino , Quimioembolização Terapêutica/métodos , Compostos de Fenilureia/administração & dosagem , Compostos de Fenilureia/uso terapêutico , Idoso , Anticorpos Monoclonais Humanizados/administração & dosagem , Anticorpos Monoclonais Humanizados/efeitos adversos , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , AdultoRESUMO
OBJECTIVE: To analyze the influence of childhood abuse experience, recent life events and coping styles on depression symptoms of medical students based on the model of "vulnerability-stress-coping". METHODS: A longitudinal study design was adopted to select freshmen from Hefei City and Anqing City in Anhui province by cluster sampling. A total of 4211 questionnaires were collected at baseline from November to December 2019. Follow-up surveys were conducted in November to December 2020, and a total of 3662 medical students were finally included in this study. The childhood trauma questionnaire, adolescent self-rating life events checklist, coping style questionnaire and self-rating depression scale were used to evaluate childhood abuse experience, recent life events, coping styles and depression symptoms of medical students. The PROCESS software model 1(double interaction analysis) and model 3(triple interaction analysis) were used to investigate the independent and interactive effects of childhood abuse experience, recent life events, and different coping styles on depressive symptoms of medical students during follow-up. RESULTS: Among the 3662 medical students, 976 were male and 2686 were female, with an average age of(19.2±1.0) years. Spearman correlation analysis showed that childhood abuse experience, recent life events, self-blame, fantasy, problem avoidance, and rationalization coping style were positively related to depressive symptoms(P<0.05). The coping style of problem solving and seeking help was negatively related to depressive symptoms(P<0.05). In model 1, both childhood abuse experience(ß=0.097, 95%CI 0.065-0.129) and recent life events(ß=0.102, 95%CI 0.073-0.132) had a positive predictive effect on depressive symptoms, and they also had positive interaction on depressive symptoms(ß=0.030, 95%CI 0.025-0.004). In model 3, there was a negative interaction between childhood abuse, recent life events and seeking help(ß=-0.034, 95%CI-0.061--0.007) or fantasy(ß=-0.039, 95%CI-0.065--0.013) coping styles on depressive symptoms. CONCLUSION: Childhood abuse experience and recent life events are the predisposition factors for depressive symptoms of medical students, and they can mutually promote depression, while seeking help and fantasy coping styles could weaken the promoting effects of both.
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Adaptação Psicológica , Depressão , Estudantes de Medicina , Humanos , Feminino , Masculino , Estudantes de Medicina/psicologia , Depressão/psicologia , Depressão/etiologia , Inquéritos e Questionários , Estudos Longitudinais , Adulto Jovem , Adolescente , China , Acontecimentos que Mudam a Vida , Maus-Tratos Infantis/psicologia , Experiências Adversas da Infância/psicologia , Estresse Psicológico/psicologia , CriançaRESUMO
Emerging clinical evidence indicates that selective CDK9 inhibition may provide clinical benefits in the management of certain cancers. Many CDK9 selective inhibitors have entered clinical developments, and are being investigated. No clear winner has emerged because of unforeseen toxicity often observed in clinic with these agents. Therefore, a novel agent with differentiated profiles is still desirable. Herein, we report our design, syntheses of a novel azaindole series of selective CDK9 inhibitors. SAR studies led to a preclinical candidate YK-2168. YK2168 exhibited improved CDK9 selectivity over AZD4573 and BAY1251152; also showed differentiated intravenous PK profile and remarkable solid tumor efficacy in a mouse gastric cancer SNU16 CDX model in preclinical studies. YK-2168 is currently in clinical development in China (CTR20212900).
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Quinase 9 Dependente de Ciclina , Inibidores de Proteínas Quinases , Quinase 9 Dependente de Ciclina/antagonistas & inibidores , Quinase 9 Dependente de Ciclina/metabolismo , Animais , Humanos , Relação Estrutura-Atividade , Camundongos , Inibidores de Proteínas Quinases/farmacologia , Inibidores de Proteínas Quinases/química , Inibidores de Proteínas Quinases/síntese química , Estrutura Molecular , Antineoplásicos/farmacologia , Antineoplásicos/química , Antineoplásicos/síntese química , Descoberta de Drogas , Relação Dose-Resposta a Droga , Linhagem Celular Tumoral , Ensaios de Seleção de Medicamentos Antitumorais , Proliferação de Células/efeitos dos fármacosRESUMO
The molecular generation models based on protein structures represent a cutting-edge research direction in artificial intelligence-assisted drug discovery. This article aims to comprehensively summarize the research methods and developments by analyzing a series of novel molecular generation models predicated on protein structures. Initially, we categorize the molecular generation models based on protein structures and highlight the architectural frameworks utilized in these models. Subsequently, we detail the design and implementation of protein structure-based molecular generation models by introducing different specific examples. Lastly, we outline the current opportunities and challenges encountered in this field, intending to offer guidance and a referential framework for developing and studying new models in related fields in the future.
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Inteligência Artificial , Modelos Moleculares , Proteínas , Proteínas/química , Conformação Proteica , Descoberta de Drogas , HumanosRESUMO
The deep molecular generative model has recently become a research hotspot in pharmacy. This paper analyzes a large number of recent reports and reviews these models. In the central part of this paper, four compound databases and two molecular representation methods are compared. Five model architectures and applications for deep molecular generative models are emphatically introduced. Three evaluation metrics for model evaluation are listed. Finally, the limitations and challenges in this field are discussed to provide a reference and basis for developing and researching new models published in future.
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Resistance to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) has emerged as a significant obstacle in managing patients with EGFR-mutant non-small-cell lung cancer (NSCLC), necessitating the exploration of novel therapeutic approaches. Tanreqing injection (TRQ) is a kind of Chinese patent medicine known for its heat-clearing and detoxifying properties. Studies have shown a correlation between tumor drug resistance and enrichment of cancer stem cells (CSCs). We aim to investigate the feasibility of TRQ enhancing sensitivity to gefitinib by targeting CSCs and reactive oxygen species (ROS). In our study, TRQ significantly inhibited cell proliferation in gefitinib-resistant non-small-cell lung cancer (NSCLC) models including 2D cell lines, 3D cell spheres, tumor-bearing animal and organoids. Compared with the gefitinib group alone, addition of TRQ elevated ROS levels, attenuated upregulation of the protein levels of sex-determining region Y-box 2 (SOX2) and aldehyde dehydrogenase 1 family member A1 (ALDH1A1) induced by gefitinib treatment, and inhibited the phosphorylation of signal transducer and activator of transcription 3 (STAT3). Scavenging ROS could restore tumor stemness, attenuate the inhibitory effect on the phosphorylation of STAT3, and promote cell proliferation. These results suggested that TRQ could enhance sensitivity of NSCLC models to gefitinib, providing a new combined treatment strategy.
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Teleosts are the most prolific vertebrates, occupying the vast majority of aquatic environments, and their pectoral fins have undergone remarkable physiological transformations throughout their evolution. Studying early teleost fishes, such as those belonging to the Osteoglossiformes order, could offer crucial insights into the adaptive evolution of pectoral fins within this group. In this study, we have assembled a chromosomal-level genome for the Clown featherback (Chitala ornata), achieving the highest quality genome assembly for Osteoglossiformes to date, with a contig N50 of 32.78 Mb and a scaffold N50 of 40.73 Mb. By combining phylogenetic analysis, we determined that the Clown featherback diverged approximately 202 to 203 million years ago (Ma), aligning with continental separation events. Our analysis revealed the intriguing discovery that a unique deletion of regulatory elements is adjacent to the Gli3 gene, specifically in teleosts. This deletion might be tied to the specialized adaptation of their pectoral fins. Furthermore, our findings indicate that specific contractions and expansions of transposable elements (TEs) in teleosts, including the Clown featherback, could be connected to their adaptive evolution. In essence, this study not only provides a high-quality genomic resource for Osteoglossiformes but also sheds light on the evolutionary trajectory of early teleosts.
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In drug candidate design, clearance is one of the most crucial pharmacokinetic parameters to consider. Recent advancements in machine learning techniques coupled with the growing accumulation of drug data have paved the way for the construction of computational models to predict drug clearance. However, concerns persist regarding the reliability of data collected from public sources, and a majority of current in silico quantitative structure-property relationship models tend to neglect the influence of molecular chirality. In this study, we meticulously examined human liver microsome (HLM) data from public databases and constructed two distinct data sets with varying HLM data quantity and quality. Two baseline models (RF and DNN) and three chirality-focused GNNs (DMPNN, TetraDMPNN, and ChIRo) were proposed, and their performance on HLM data was evaluated and compared with each other. The TetraDMPNN model, which leverages chirality from 2D structure, exhibited the best performance with a test R2 of 0.639 and a test root-mean-squared error of 0.429. The applicability domain of the model was also defined by using a molecular similarity-based method. Our research indicates that graph neural networks capable of capturing molecular chirality have significant potential for practical application and can deliver superior performance.
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Microssomos Hepáticos , Redes Neurais de Computação , Humanos , Microssomos Hepáticos/metabolismo , Estereoisomerismo , Relação Quantitativa Estrutura-Atividade , Aprendizado de Máquina , Preparações Farmacêuticas/química , Preparações Farmacêuticas/metabolismoRESUMO
Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) emerges as a key single-chain transmembrane glycoprotein predominantly expressed in effector T cells and regulatory T cells. It plays a crucial role in tumor immunity by modulating T cell responses. Specifically, CTLA-4 dampens T cell activation and proliferation while bolstering the survival of regulatory T cell through its competitive interaction with B7 family molecules, thereby aiding tumor cells in eluding immune detection. Given CTLA-4's significant influence on tumor immune dynamics, an array of anti-CTLA-4 antibody therapeutics have been clinically developed to combat various malignancies, including melanoma, renal cell carcinoma, colorectal carcinoma, hepatocellular carcinoma, non-small cell lung carcinoma, and pleural mesothelioma, demonstrating notable clinical therapeutic effects. This paper aims to delve into CTLA-4's integral role in tumor immunity and to encapsulate the latest advancements in the clinical research of anti-CTLA-4 antibody.
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Objective: Numerous studies have reported that metformin can reduce the risk of tumor development. However, some of the results of these studies are conflicting, necessitating a more reliable evaluation. Methods: We conducted a Mendelian randomization phenome-wide association study (MR-PheWAS) of tumors to explore the causal relationship between metformin and tumors. Two cohorts of patients taking metformin were obtained from the UK Biobank. Complete phenotype data of the tumors were obtained from FinnGen_R10. We elucidated the causal relationship using a two-sample Mendelian randomization (MR) analysis. More importantly, we conducted a meta-analysis to ensure relatively unbiased results. In the MR analysis, we used the inverse-variance weighted (IVW) method as the main outcome indicator. Subsequently, two cohorts were integrated for the meta-analysis. Finally, we investigated the mechanisms through mediational MR analysis. Results: MR analysis revealed that metformin might have a causal relationship with 13 tumor-associated phenotypes in the training cohort. Four phenotypes were validated in the testing cohort. In the training and testing cohorts, metformin exhibited a protective effect against brain meningiomas and malignant neoplasms of the breast (HER-positive), oral cavity, tonsils, and the base of the tongue. Intriguingly, after integrating the results of the two cohorts for the meta-analysis, 12 results were statistically significant. Mediational MR analysis suggested that the effects of metformin on brain meningiomas may be weakened by the presence of the family Oxalobacteraceae. Conclusion: Metformin exhibits potential preventive and therapeutic effects on four types of tumors: brain meningioma, malignant neoplasms of the breast (HER-positive), oral cavity and tonsils, and the base of the tongue. Large randomized controlled trials are required to confirm these findings.
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The assessment of compound blood-brain barrier (BBB) permeability poses a significant challenge in the discovery of drugs targeting the central nervous system. Conventional experimental approaches to measure BBB permeability are labor-intensive, cost-ineffective, and time-consuming. In this study, we constructed six machine learning classification models by combining various machine learning algorithms and molecular representations. The model based on ExtraTree algorithm and random partitioning strategy obtains the best prediction result, with AUC value of 0.932±0.004 and balanced accuracy (BA) of 0.837±0.010 for the test set. We employed the SHAP method to identify important features associated with BBB permeability. In addition, matched molecular pair (MMP) analysis and representative substructure derivation method were utilized to uncover the transformation rules and distinctive structural features of BBB permeable compounds. The machine learning models proposed in this work can serve as an effective tool for assessing BBB permeability in the drug discovery for central nervous system disease.
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Droplet impact behavior is ubiquitous in various fields. However, the dynamics and spreading mechanisms of micro- and nanoscale droplet impact on curved surfaces, particularly in the case of multiple droplets, have yet to be fully elucidated. In this study, molecular dynamics (MD) methods are employed to investigate the dynamic evolution of double nanodroplet impact on a nano cylindrical wall. The effects of droplet spacing, initial impact velocity, and wall wettability on droplet impact characteristics are analyzed. The results demonstrate that there are five impact modes of nanoscale double-droplet impacts with nanocylinders: spreading-partial wrapping-splitting-complete detachment (SPSC), spreading-complete wrapping-complete attachment (SCC), spreading-partial wrapping-complete attachment (SPC), spreading-partial wrapping-partial attachment (SPP), and spreading-partial wrapping-fragmentation-partial attachment (SPFP). The droplet spacing has an insignificant effect on the impact modes but affects the droplets' spreading shape in both the axial and radial directions. The initial velocity and wall wettability have significant impacts on the droplet impact modes and liquid film spreading characteristics. As the initial velocity increases, the liquid film's radial and axial spreading distances gradually increase. Under hydrophobic conditions, the spreading of the droplet is dominant in the radial direction, while under hydrophilic conditions, the spreading is dominant in the axial direction. Properly reducing the droplet spacing, increasing the impact velocity, and enhancing the wall hydrophobicity can promote detaching the droplet from the cylindrical wall.
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Selenium (Se) is an essential trace element for human physiological metabolism. The application of organic Se as a source to cultivate Se-rich plants for micronutrient supplementation has been receiving increasing attention. In our study, a bacterial strain named H1 was isolated from the soil in Heilongjiang Province, China, and under optimal culture conditions, the unit Se content could reach 3000 µg·g-1 and its 16S ribosomal DNA sequence seemed to be a new molecular record of an Enterobacter species. After the domestication of Se tolerance and Se-rich experiments, H1 can be used as a Se source for cultivation of Se-rich Auricularia auricula. The results showed that soluble protein, soluble sugar, free amino acid and vitamin C contents in Auricularia auricula were notably increased by 28.7%, 21.8%, 32.5% and 39.2% under the treatment of Se concentration of 0.24 mg·kg-1, respectively. These findings enhance our understanding that H1 is more conducive to Se uptake and nutrient accumulation.
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The gut microbiota constitutes a complex ecosystem that has an important impact on host health. In this study, genetically engineered zebrafish with inducible nitric oxide synthase (iNOS or NOS2) knockout were used as a model to investigate the effects of nos2a/nos2b gene single knockout and nos2 gene double knockout on intestinal microbiome composition and function. Extensive 16S rRNA sequencing revealed substantial changes in microbial diversity and specific taxonomic abundances, yet it did not affect the functional structure of the intestinal tissues. Notably, iNOS-deficient zebrafish demonstrated a decrease in Vibrio species and an increase in Aeromonas species, with more pronounced effects observed in double knockouts. Further transcriptomic analysis of the gut in double iNOS knockout zebrafish indicated significant alterations in immune-related and metabolic pathways, including the complement and PPAR signaling pathways. These findings underscore the crucial interplay between host genetics and gut microbiota, indicating that iNOS plays a key role in modulating the gut microbial ecology, host immune system, and metabolic responses.
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Wee1 is a kinase that regulates cell cycle arrest in response to DNA damage. Wee1 inhibition is a potential strategy to suppress the growth of tumors with defective p53 or DNA repair pathways. However, the development of Wee1 inhibitors faces some challenges. AZD1775, the first-in-class Wee1 inhibitor, has poor kinase selectivity and dose-limiting toxicity. Here, we report the discovery of 12h, a highly selective and potent Wee1 inhibitor with a favorable pharmacokinetic profile. 12h showed strong antiproliferative effects against Lovo cells, a colorectal cancer cell line, both in vitro and in vivo. Moreover, 12h showed a clean kinase profile and effectively induced cell apoptosis. Our results suggest that 12h is a promising drug candidate for further development as a novel anticancer agent.
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Antineoplásicos , Proteínas de Ciclo Celular , Proliferação de Células , Desenho de Fármacos , Inibidores de Proteínas Quinases , Proteínas Tirosina Quinases , Humanos , Proteínas Tirosina Quinases/antagonistas & inibidores , Proteínas Tirosina Quinases/metabolismo , Proteínas de Ciclo Celular/antagonistas & inibidores , Proteínas de Ciclo Celular/metabolismo , Antineoplásicos/síntese química , Antineoplásicos/farmacologia , Antineoplásicos/farmacocinética , Antineoplásicos/química , Animais , Linhagem Celular Tumoral , Inibidores de Proteínas Quinases/farmacologia , Inibidores de Proteínas Quinases/síntese química , Inibidores de Proteínas Quinases/farmacocinética , Inibidores de Proteínas Quinases/química , Proliferação de Células/efeitos dos fármacos , Apoptose/efeitos dos fármacos , Camundongos , Relação Estrutura-Atividade , Camundongos NusRESUMO
Objective: Given the significant impact of long-term traditional Chinese medicine (TCM) treatment on the prognosis of patients with non-small cell lung cancer (NSCLC), we aimed to develop nomograms, with or without consideration of TCM treatment duration, to accurately predict the overall survival (OS) of patients with stage IIIB/IV NSCLC treated with TCM. Methods: Nomograms were developed from a training cohort comprised of 292 patients diagnosed with NSCLC, using univariate and multivariate Cox regression analyses to screen for various prognostic factors with and without TCM treatment. The nomograms were evaluated using the concordance index (C-index), calibration curve, and decision curve analysis (DCA), after which they were validated, using the bootstrap self-sampling method for internal validation, and a validation cohort comprised of 175 patients for external validation. Bootstrap validation is a resampling technique that involves randomly selecting and replacing data from the original dataset to make statistical inferences, thereby circumventing the issue of sample reduction that can arise from cross-validation. Results: We identified seven significant prognostic factors for OS. For nomogram A (excluding TCM treatment time), the C-indexes (95 % confidence interval [CI]) were 0.674 (0.635-0.712) and 0.660 (0.596-0.724) for the training and validation cohorts, respectively. For nomogram B (including TCM treatment time), the C-indices (95 % CI) were 0.846 (0.822-0.870) and 0.783 (0.730-0.894), for the training and validation cohorts, respectively, indicating that nomogram B was superior to nomogram A. Both the calibration curves and DCA results exhibited favorable clinical concordance and usefulness. Conclusion: The nomogram B yielded precise prognostic predictions for patients with advanced NSCLC treated with TCM.
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The technology of water plugging and increasing production in high water cut reservoirs of low permeability is a common problem in the industry. Epoxy resin, displaying excellent mechanical properties and adherent performance, can easily inject a tiny crack, forming a long-term blocking barrier. This study aimed to investigate an easily injectable degradable epoxy resin sealing material. The injectable performance, long-term stability, and mechanical and plugging properties were comparatively analyzed in the fractured core, and the degradable performance was discussed in the degrading solution. The result showed that the range of R (R is the ratio of EOG and MHHPA) from 1 to 1.1 and the mass fraction range of EMI from 0.01 to 4 wt % are the optimal formulations (EOGM). The curing time from 1 to 12 h could be regulated by adjusting the dosage of EMI, as well as the strength being more than 60 MPa. The plugging agent's initial viscosity is lower than 100 MPa s at 20 °C and injecting pressure is lower than 0.1 MPa. After curing for 24 h, compressive strength was more than 72.76 MPa, 3.6 times higher than that of cement, and the adhesion strength was 4.41 MPa when the contact area was 75.93 cm3. Breakthrough pressures for sealing 1-5 mm fractures were all more than 10 MPa, and the breakthrough pressure for 1 mm crack even reached 29.4 MPa. Epoxy resin/acid anhydride system could be degraded in a mixed solution of phenol-potassium salt-heavy aromatics within 7 days at 60-100 °C, which reduced the plugging well risk of the epoxy resin plugging agent. These results suggest that an epoxy resin/acid anhydride plugging agent can be employed effectively and safely for the injection of tiny cracks, which is of great engineering significance.
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Second-generation AR antagonists, such as enzalutamide, are the primary therapeutic agents for advanced prostate cancer. However, the development of both primary and secondary drug resistance leads to treatment failures and patient mortality. Bifunctional agents that simultaneously antagonize and degrade AR block the AR signaling pathway more completely and exhibit excellent antiproliferative activity against wild-type and drug-resistant prostate cancer cells. Here, we reported the discovery and optimization of a series of biphenyl derivatives as androgen receptor antagonists and degraders. These biphenyl derivatives exhibited potent antiproliferative activity against LNCaP and 22Rv1 cells. Our discoveries enrich the diversity of small molecule AR degraders and offer insights for the development of novel AR degraders for the treatment of enzalutamide-resistant prostate cancer.
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Antagonistas de Receptores de Andrógenos , Antineoplásicos , Benzamidas , Compostos de Bifenilo , Proliferação de Células , Resistencia a Medicamentos Antineoplásicos , Nitrilas , Feniltioidantoína , Neoplasias da Próstata , Receptores Androgênicos , Humanos , Masculino , Benzamidas/farmacologia , Benzamidas/química , Benzamidas/síntese química , Nitrilas/química , Nitrilas/farmacologia , Feniltioidantoína/farmacologia , Feniltioidantoína/análogos & derivados , Feniltioidantoína/química , Compostos de Bifenilo/farmacologia , Compostos de Bifenilo/antagonistas & inibidores , Receptores Androgênicos/metabolismo , Antineoplásicos/farmacologia , Antineoplásicos/química , Antineoplásicos/síntese química , Proliferação de Células/efeitos dos fármacos , Relação Estrutura-Atividade , Neoplasias da Próstata/tratamento farmacológico , Neoplasias da Próstata/patologia , Neoplasias da Próstata/metabolismo , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Estrutura Molecular , Antagonistas de Receptores de Andrógenos/farmacologia , Antagonistas de Receptores de Andrógenos/química , Antagonistas de Receptores de Andrógenos/síntese química , Antagonistas de Receptores de Andrógenos/uso terapêutico , Descoberta de Drogas , Ensaios de Seleção de Medicamentos Antitumorais , Relação Dose-Resposta a Droga , Linhagem Celular TumoralRESUMO
Electroencephalogram (EEG) analysis plays an indispensable role across contemporary medical applications, which encompasses diagnosis, monitoring, drug discovery, and therapeutic assessment. This work puts forth an end-to-end deep learning framework that is uniquely tailored for versatile EEG analysis tasks by directly operating on raw waveform inputs. It aims to address the challenges of manual feature engineering and the neglect of spatial interrelationships in existing methodologies. Specifically, a spatial channel attention module is introduced to emphasize the critical inter-channel dependencies in EEG signals through channel statistics aggregation and multi-layer perceptron operations. Furthermore, a sparse transformer encoder is used to leverage selective sparse attention in order to efficiently process long EEG sequences while reducing computational complexity. Distilling convolutional layers further concatenates the temporal features and retains only the salient patterns. As it was rigorously evaluated on key EEG datasets, our model consistently accomplished a superior performance over the current approaches in detection and classification assignments. By accounting for both spatial and temporal relationships in an end-to-end paradigm, this work facilitates a versatile, automated EEG understanding across diseases, subjects, and objectives through a singular yet customizable architecture. Extensive empirical validation and further architectural refinement may promote broader clinical adoption prospects.
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Muscarinic acetylcholine receptors (mAChRs) play a significant role in the pathophysiology of schizophrenia. Although activating mAChRs holds potential in addressing the full range of schizophrenia symptoms, clinical application of many non-selective mAChR agonists in cognitive deficits, positive and negative symptoms is hindered by peripheral side effects (gastrointestinal disturbances and cardiovascular effects) and dosage restrictions. Ligands binding to the allosteric sites of mAChRs, particularly the M1 and M4 subtypes, demonstrate activity in improving cognitive function and amelioration of positive and negative symptoms associated with schizophrenia, enhancing our understanding of schizophrenia. The article aims to critically examine current design concepts and clinical advancements in synthesizing and designing small molecules targeting M1/M4, providing theoretical insights and empirical support for future research in this field.