Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis.

Hepatocellular carcinoma (HCC) is a common malignancy with poor survival and requires long-term follow-up. Hence, we collected information on patients with Primary Hepatocellular Carcinoma in the United States from the Surveillance, Epidemiology, and EndResults (SEER) database. We used this information to establish a deep learning with a multilayer neural network (the NMTLR model) for predicting the survival rate of patients with Primary Hepatocellular Carcinoma. HCC patients pathologically diagnosed between January 2011 and December 2015 in the SEER (Surveillance, Epidemiology, and End Results) database of the National Cancer Institute of the United States were selected as study subjects. We utilized two deep learning-based algorithms (DeepSurv and Neural Multi-Task Logistic Regression [NMTLR]) and a machine learning-based algorithm (Random Survival Forest [RSF]) for model training. A multivariable Cox Proportional Hazards (CoxPH) model was also constructed for comparison. The dataset was randomly divided into a training set and a test set in a 7:3 ratio. The training dataset underwent hyperparameter tuning through 1000 iterations of random search and fivefold cross-validation. Model performance was assessed using the concordance index (C-index), Brier score, and Integrated Brier Score (IBS). The accuracy of predicting 1-year, 3-year, and 5-year survival rates was evaluated using Receiver Operating Characteristic (ROC) curves, calibration plots, and Area Under the Curve (AUC). The primary outcomes were the 1-year, 3-year, and 5-year overall survival rates. Models were developed using DeepSurv, NMTLR, RSF, and Cox Proportional Hazards regression. Model differentiation was evaluated using the C-index, calibration with concordance plots, and risk stratification capability with the log-rank test. The study included 2197 HCC patients, randomly divided into a training cohort (70%, n = 1537) and a testing cohort (30%, n = 660). Clinical characteristics between the two cohorts showed no significant statistical difference (p > 0.05). The deep learning models outperformed both RSF and CoxPH models, with C-indices of 0.735 (NMTLR) and 0.731 (DeepSurv) in the test dataset. The NMTLR model demonstrated enhanced accuracy and well-calibrated survival estimates, achieving an Area Under the Curve (AUC) of 0.824 for 1-year survival predictions, 0.813 for 3-year, and 0.803 for 5-year survival rates. This model's superior calibration and discriminative ability enhance its utility for clinical prognostication in Primary Hepatocellular Carcinoma. We deployed the NMTLR model as a web application for clinical practice. The NMTLR model have potential advantages over traditional linear models in prognostic assessment and treatment recommendations. This novel analytical approach may provide reliable information on individual survival and treatment recommendations for patients with primary liver cancer.

An integrated economic, energy, and environmental analysis to optimize evaluation of carbon reduction strategies at the regional level: A case study in Zhejiang, China.

China plays a crucial role in responding to global climate change. Provinces are the main sources of energy consumption and greenhouse gas emissions in China's economic and social development. However, it is still unclear how to achieve dual-carbon goals by formulating and implementing local policies to adapt to climate change. In this study, we take Zhejiang Province in China as the research object, based on the LEAP (Low Emissions Analysis Platform) model to construct four social scenarios under different policies, comprehensively considering regional economic characteristics, population, and energy consumption patterns. The results show that to achieve Zhejiang Province's goal of carbon peaking by 2030 while maintaining steady economic growth, additional measures are required to reduce energy consumption intensity or improve the power generation structure. Otherwise, energy demand will increase to 228.06 million tonnes of coal equivalent and carbon emissions will be 487.76 million tonnes in 2050. Moreover, developing clean energy and promoting CCUS technology can continuously reduce carbon emissions to 293.59 and 210.76 million tonnes respectively. The economic viability of CCUS power generation is contingent upon the development of carbon taxes in the future. Once the growth rate reaches 7.2%, power cost will be 167.77 billion RMB and CCUS will become economically advantageous in 2050.

Effect of Poly(ethylene glycol) (PEG) Surface Density on the Fate and Antitumor Efficacy of Redox-Sensitive Hybrid Nanoparticles.

The effects of poly(ethylene glycol) (PEG) on improving the biological compatibility and circulation time of nanocarriers are determined by the surface density of PEG on nanoparticles. PEG with high surface density on nanocarriers has greater accumulation in tumor tissues. However, this impairs the release of drugs loaded in the nanoparticles in the tumor tissues. The relations and internal regularities between the controlled stripping of PEG of nanoparticles and its fate and antitumor efficacy in vivo remain unsolved. Redox-sensitive hybrid nanoparticles coated with varied PEG densities were prepared by blending a redox-sensitive polymer of DLPE-SS-MPEG. To keep identical nanoproperties, these nanoparticles were prepared with a similar size distribution of around 100 nm. The effects of controlled stripping of PEG on antitumor activities of nanoparticles were then investigated. As the PEG surface density increased, lower cellular internalization by tumor cells was observed. However, nanoparticles with higher controlled stripping of PEG showed greater accumulation in tumor tissues and advanced antitumor activities in vivo.

A one-dimensional infinite silver alkynyl assembly [Ag8(C[triple bond, length as m-dash]C t Bu)5(CF3COO)3(CH3CN)] n : synthesis, crystal structure and properties.

A high-yield silver alkynyl assembly [Ag8(C[triple bond, length as m-dash]C t Bu)5(CF3COO)3(CH3CN)] n (1) constructed from [AgC[triple bond, length as m-dash]C t Bu] n ligand, CF3COOAg and CH3CN auxiliary ligands with a one-dimensional infinite chain structure has been obtained in one pot. Compound 1 has been well-defined and characterized. The photocurrent properties and the temperature-sensitive luminescent properties of 1 have been investigated.

Synergistic antitumour effects of triptolide plus gemcitabine in bladder cancer.

BACKGROUND AND OBJECTIVE: Gemcitabine (GEM) effectively inhibits bladder cancer progression in the clinic, but novel combination treatments using multiple drugs are needed. MATERIALS AND METHODS: The bladder cancer cell lines EJ and UMUC3 were treated with triptolide (TPL) and/or GEM. Tumour cell viability and proliferation were measured using MTT and clonogenic assays, respectively. Flow cytometry and western blotting were used to detect the cell cycle phase, apoptosis, reactive oxygen species (ROS) and the levels of specific relevant proteins. The AKT/GSK3ß signalling pathway proteins were also measured by immunofluorescence and western blotting. RESULTS: The cytotoxicity of the GEM plus TPL combination treatment was stronger than that of GEM or TPL alone. In bladder cancer cell lines, GEM plus TPL induced cell cycle arrest at the G1 phase via suppression of CDK4, CDK6 and cyclins A1 and A2. Significantly increased apoptosis and increases in apoptosis-related proteins (caspase 8 and Bcl-xL) were observed in cells treated with GEM plus TPL. While ROS increased, certain ROS-related proteins (catalase and SOD2) clearly decreased in cells treated with a combination of GEM plus TPL. The AKT/GSK3ß signalling pathway was also inhibited more significantly in cells treated with the GEM plus TPL combination than in cells treated with either agent alone. CONCLUSION: The combination of GEM plus TPL showed significantly enhanced anticancer effects compared to those of GEM or TPL alone.

Redox-triggered activation of nanocarriers for mitochondria-targeting cancer chemotherapy.

The importance of mitochondrial delivery of an anticancer drug to cancer cells has been recognized to improve therapeutic efficacy. The introduction of lipophilic cations, such as triphenylphosphonium (TPP), onto the surface of nanocarriers was utilized to target mitochondria via strong electrostatic interactions between positively charged TPP and the negatively charged mitochondrial membrane. However, the highly positive charge nature of TPP leads to rapid clearance from the blood, decrease of circulation lifetime, and nonspecific targeting of mitochondria of cells. Here, we report a strategy for improving the anticancer efficacy of paclitaxel via redox triggered intracellular activation of mitochondria-targeting. The lipid-polymer hybrid nanoparticles (LPNPs) are composed of poly(d,l-lactide-co-glycolide) (PLGA), a TPP-containing amphiphilic polymer (C18-PEG2000-TPP) and a reduction-responsive amphiphilic polymer (DLPE-S-S-mPEG4000). The charges of TPP in LPNPs were almost completely shielded by surface coating of a PEG4000 layer, ensuring high tumor accumulation. After uptake by cancer cells, the surface charges of LPNPs were recovered due to the detachment of PEG4000 under intracellular reductive conditions, resulting in rapid and precise localization in mitochondria. This kind of simple, easy and practicable mitochondria-targeting nanoplatform showed high anticancer activity, and the activatable strategy is valuable for developing a variety of nanocarriers for application in the delivery of other drugs.

Codelivery of doxorubicin and triptolide with reduction-sensitive lipid-polymer hybrid nanoparticles for in vitro and in vivo synergistic cancer treatment.

Codelivery is a promising strategy to overcome the limitations of single chemotherapeutic agents in cancer treatment. Despite progress, codelivery of two or more different functional drugs to increase anticancer efficiency still remains a challenge. Here, reduction-sensitive lipid-polymer hybrid nanoparticles (LPNPs) drug delivery system composed of monomethoxy-poly(ethylene glycol)-S-S-hexadecyl (mPEG-S-S-C16), soybean lecithin, and poly(D,L-lactide-co-glycolide) (PLGA) was used for codelivery of doxorubicin (DOX) and a Chinese herb extract triptolide (TPL). Hydrophobic DOX and TPL could be successfully loaded in LPNPs by self-assembly. More importantly, drug release and cellular uptake experiments demonstrated that the two drugs were reduction sensitive, released simultaneously from LPNPs, and taken up effectively by the tumor cells. DOX/TPL-coloaded LPNPs (DOX/TPL-LPNPs) exhibited a high level of synergistic activation with low combination index (CI) in vitro and in vivo. Moreover, the highest synergistic therapeutic effect was achieved at the ratio of 1:0.2 DOX/TPL. Further experiments showed that TPL enhanced the uptake of DOX by human oral cavity squamous cell carcinoma cells (KB cells). Overall, DOX/TPL-coencapsulated reduction-sensitive nanoparticles will be a promising strategy for cancer treatment.

Two-component reduction-sensitive lipid-polymer hybrid nanoparticles for triggered drug release and enhanced in vitro and in vivo anti-tumor efficacy.

An amphiphilic polymer DLPE-S-S-MPEG was synthesized and employed with PCL to prepare two-component reduction-sensitive lipid-polymer hybrid nanoparticles (SLPNPs) for in vitro and in vivo delivery of a hydrophobic anticancer drug (Doxorubicin, DOX). Insensitive lipid-polymer hybrid nanoparticles (ILPNPs) were prepared as a control. The mean sizes of the LPNPs ranged from 100 nm to 120 nm. The TEM observations showed that the LPNPs have spherical morphologies with homogeneous distribution. The disulfide bond of DLPE-S-S-MPEG was cleaved by dithiothreitol (DTT), which resulted in the disassembly of SLPNPs and triggered the release of encapsulated DOX. The in vitro cytotoxicities of DOX/LPNPs against HeLa cells, HepG2 cells and COS-7 cells were studied. It was demonstrated that DOX/SLPNPs showed higher cytotoxicity against HeLa cells and HepG2 cells than DOX/ILPNPs, but showed a slight difference in the case of COS-7 cells. CLSM observation and FCM measurement further confirmed that the introduction of S-S bonds caused fast intracellular release of DOX from SLPNPs. Moreover, compared with DOX/ILPNPs and free DOX, DOX/SLPNPs exhibited higher antitumor activity. Both DOX/SLPNPs and DOX/ILPNPs showed lower cardiac toxicity and kidney toxicity than free DOX, which were confirmed by histological and immunohistochemical analyses. The tissue distribution of DOX in mice exhibited that two kinds of DOX/LPNPs accumulated extensively in the liver and spleen, while free DOX accumulated mainly in the heart and kidney 12 h after injection. Two-component SLPNPs may be a promising drug delivery carrier for reduction-triggered delivery of DOX.

Mitochondria-targeted drug delivery system for cancer treatment.

Mitochondria are one type of the major organelles in the cell, participating in a variety of important physiological and biochemical processes, such as tricarboxylic acid cycle, fatty acid metabolism and oxidative phosphorylation. Meanwhile, it also happens to be the key regulator of apoptosis by triggering the complex cell-death processes through a variety of mechanisms. Since it plays a pivotal role in cell-death, a mitochondria-targeted treatment strategy could be promising for cancer therapy. In this comprehensive review, we focused on the mechanisms of mitochondrial targeting and a variety of strategies to realize the purpose of mitochondrial targeting, including that based on the use of lipophilic cations, and mitochondrial targeting signal peptides (MTS) as well as cell-penetrating peptides (CPPs). Then on this basis we present some several developed strategies for multifunctional mitochondria-targeted agents so as to achieve the good anti-cancer therapeutic effects.

Hierarchical targeted hepatocyte mitochondrial multifunctional chitosan nanoparticles for anticancer drug delivery.

The overwhelming majority of drugs exert their pharmacological effects after reaching their target sites of action, however, these target sites are mainly located in the cytosol or intracellular organelles. Consequently, delivering drugs to the specific organelle is the key to achieve maximum therapeutic effects and minimum side-effects. In the work reported here, we designed, synthesized, and evaluated a novel mitochondrial-targeted multifunctional nanoparticles (MNPs) based on chitosan derivatives according to the physiological environment of the tumor and the requirement of mitochondrial targeting drug delivery. The intelligent chitosan nanoparticles possess various functions such as stealth, hepatocyte targeting, multistage pH-response, lysosomal escape and mitochondrial targeting, which lead to targeted drug release after the progressively shedding of functional groups, thus realize the efficient intracellular delivery and mitochondrial localization, inhibit the growth of tumor, elevate the antitumor efficacy, and reduce the toxicity of anticancer drugs. It provides a safe and efficient nanocarrier platform for mitochondria targeting anticancer drug delivery.

Folic acid-conjugated iron oxide porous nanorods loaded with doxorubicin for targeted drug delivery.

Iron oxide porous nanorods (IOPNR) with lengths ranging from 40nm to 60nm and pore diameters ranging from 5nm to 10nm were prepared, and further modified with NH2-PEG-FA (FA-PEG-IOPNR) for ligand targeting and modified with NH2-PEG-OCH3 (PEG-IOPNR) as a control. Instead of chemical bonding, doxorubicin (DOX), a low water solubility anticancer drug, was loaded in the pores of the modified IOPNR because of their porous structure and high porosity. The release of DOX in acidic PBS solution (pH 5.3) was faster than that in neutral (pH 7.4) solution. The analysis results from TEM, inductively coupled plasma emission spectroscopy, confocal laser scanning microscopy, and flow cytometry analyses indicated that the presence of FA on the surface of the nanorods increase the cellular uptake of nanorods in the case of HeLa cells, a folate receptor (FR)-positive cell line. In contrast, for COS 7 cells, a FR-negative cell line, FA ligand on the surface of the nanorods showed no effect on the cellular uptake. MTT assay indicated that the cytotoxicity of DOX loaded in FA-PEG-IOPNR to HeLa cells was higher than that of DOX in PEG-IOPNR. In the case of COS 7 cells, no significant difference between the cytotoxicity of DOX loaded in FA-PEG-IOPNR and PEG-IOPNR was found. These results suggested that FA-PEG-IOPNR had the potential for target delivery of chemotherapeutic into cancer cells.