RESUMEN
Given a graph G, the network collapse problem (NCP) selects a vertex subset S of minimum cardinality from G such that the difference in the values of a given measure function f(G)-f(G∖S) is greater than a predefined collapse threshold. Many graph analytic applications can be formulated as NCPs with different measure functions, which often pose a significant challenge due to their NP-hard nature. As a result, traditional greedy algorithms, which select the vertex with the highest reward at each step, may not effectively find the optimal solution. In addition, existing learning-based algorithms do not have the ability to model the sequence of actions taken during the decision-making process, making it difficult to capture the combinatorial effect of selected vertices on the final solution. This limits the performance of learning-based approaches in non-submodular NCPs. To address these limitations, we propose a unified framework called DT-NC, which adapts the Decision Transformer to the Network Collapse problems. DT-NC takes into account the historical actions taken during the decision-making process and effectively captures the combinatorial effect of selected vertices. The ability of DT-NC to model the dependency among selected vertices allows it to address the difficulties caused by the non-submodular property of measure functions in some NCPs effectively. Through extensive experiments on various NCPs and graphs of different sizes, we demonstrate that DT-NC outperforms the state-of-the-art methods and exhibits excellent transferability and generalizability.
Asunto(s)
Algoritmos , Redes Neurales de la Computación , Toma de Decisiones/fisiología , HumanosRESUMEN
BACKGROUND/AIM: Prostate cancer is currently the second most common cancer in men and chemotherapy is the main treatment for metastatic castrate-resistant prostate cancers (mCRPC). However, chemoresistance leading to treatment failure is inevitable. Thus, therapeutic approaches that can overcome chemoresistance are important areas of research for cancer chemotherapy. MATERIALS AND METHODS: In the present study, six components of tripterygium wilfordii including celastrol, triptolide, pristimerin, triptonide, demethylzeylasteral, and wilforlide A were screened for their chemosensitizing effect on drug-resistant prostate cancer cell lines PC3 and DU145. The most active compound was further investigated on its potential mechanism of action and in vivo efficacy using a SCID mouse model. RESULTS: Among the six components only wilforlide A significantly enhanced sensitivity to docetaxel (by reducing the IC50 in resistant prostate cancer cell lines). Wilforlide A inhibited P-glycoprotein efflux transporter and downregulated cyclin E2 splice variant 1 mRNA, both have been known as mechanisms of resistance. The chemosensitizing effect was further verified using a xenograft mouse model. In the high-dose treatment group, the combination of wilforlide A and docetaxel significantly retarded tumor growth of resistant prostate cancer, although neither docetaxel nor wilforlide A monotreatment groups showed any effect. CONCLUSION: Wilforlide A was found to enhance the chemosensitizing effect of docetaxel both in vitro and in vivo. Further studies are warranted to verify wilforlide A as a new drug candidate to overcome docetaxel resistance in prostate cancer.
Asunto(s)
Neoplasias de la Próstata Resistentes a la Castración , Taxoides , Animales , Línea Celular Tumoral , Docetaxel/farmacología , Humanos , Masculino , Ratones , Ratones SCID , Ácido Oleanólico/análogos & derivados , Triterpenos Pentacíclicos , Neoplasias de la Próstata Resistentes a la Castración/tratamiento farmacológico , Neoplasias de la Próstata Resistentes a la Castración/metabolismo , Neoplasias de la Próstata Resistentes a la Castración/patología , Taxoides/farmacología , Taxoides/uso terapéuticoRESUMEN
AIM: To structurally modify our existing cholic acid (CA)-based telodendrimer (TD; PEG5K-CA8) for effective micellar nanoencapsulation and delivery of the US FDA-approved members of taxane family. MATERIALS & METHODS: Generation of hybrid TDs was achieved by replacing four of the eight CAs with biocompatible organic moieties using solution-phase peptide synthesis. Drug loading was done using the standard evaporation method. RESULTS: Hybrid TDs can generate micelles with narrow size distributions, low critical micelle concentration values (1-6 µM), better hematocompatibility and lack of in vitro cytotoxicity. CONCLUSION: Along with PEG5K-CA8, CA-based hybrid nanoplatform is the first of its kind that can stably encapsulate all three FDA-approved taxanes with nearly 100% efficiency up to 20% (w/w) loading.
Asunto(s)
Antineoplásicos/administración & dosificación , Ácido Cólico/química , Portadores de Fármacos/química , Micelas , Nanopartículas/química , Taxoides/administración & dosificación , Antineoplásicos/farmacología , Hidrocarburos Aromáticos con Puentes/administración & dosificación , Línea Celular Tumoral , Docetaxel , Humanos , Neoplasias/tratamiento farmacológico , Paclitaxel/administración & dosificación , Taxoides/farmacologíaRESUMEN
The exponential inequality for weighted sums of a class of linearly negative quadrant dependent random variables is established, which extends and improves the corresponding ones obtained by Ko et al. (2007) and Jabbari et al. (2009). In addition, we also give the relevant precise asymptotics.