Nature-Inspired Photocatalytic Azo Bond Cleavage with Red Light.

The emerging field of photoredox catalysis in mammalian cells enables spatiotemporal regulation of a wealth of biological processes. However, the selective cleavage of stable covalent bonds driven by low-energy visible light remains a great challenge. Herein, we report that red light excitation of a commercially available dye, abbreviated NMB+, leads to catalytic cleavage of stable azo bonds in both aqueous solutions and hypoxic cells and hence a means to photodeliver drugs or functional molecules. Detailed mechanistic studies reveal that azo bond cleavage is triggered by a previously unknown consecutive two-photon process. The first photon generates a triplet excited state, 3NMB+*, that is reductively quenched by an electron donor to generate a protonated NMBH•+. The NMBH•+ undergoes a disproportionation reaction that yields the initial NMB+ and two-electron-reduced NMBH (i.e., leuco-NMB, abbreviated as LNMB). Interestingly, LNMB forms a charge transfer complex with all four azo substrates that possess an intense absorption band in the red region. A second red photon induces electron transfer from LNMB to the azo substrate, resulting in azo bond cleavage. The charge transfer complex mediated two-photon catalytic mechanism reported herein is reminiscent of the flavin-dependent natural photoenzyme that catalyzes bond cleavage reactions with high-energy photons. The red-light-driven photocatalytic strategy offers a new approach to bioorthogonal azo bond cleavage for photodelivery of drugs or functional molecules.

Engineering a Dual-Receptor Targeted Multivalent Probe for Enhanced Magnetic Resonance Imaging of Metastatic Cancer.

Noninvasive monitoring of cancer metastasis is essential to improving clinical outcomes. Molecular MRI (mMRI) is a special implementation of noninvasive molecular imaging that promises to offer a powerful means for early detection and analysis of pathological states of cancer by tracking molecular markers. However, this is often hindered by the challenging issue of obtaining transformable mMRI contrast agents with high sensitivity, specificity, and broad applicability, given the high tumor heterogeneity and complex metastatic features. Herein, we present a dual-receptor targeted, multivalent recognition strategy and report a new class of mMRI probes for enhanced imaging of metastatic cancer. This probe is designed by covalently conjugating Gd-chelate with phenylboronic acid and an aptamer via an affordable polymerization chemistry to concurrently target two different cell-membrane receptors that are commonly overexpressed and highly implicated in both tumorigenesis and metastasis. Moreover, the polymerization chemistry allows the probe to contain a bunch of targeting ligands and signal reporters in a single chain, which not only leads to more than 2-fold enhancement in T1 relaxivity at 1.5 T compared to the commercial contrast agent but also enables it to actively target tumor cells in a multivalent recognition manner, contributing to a much higher imaging contrast than single-receptor targeted probes and the commercial agent in mouse models with lung metastases, yet without inducing systemic side effects. We expect this study to offer a useful molecular tool to promote transformable applications of mMRI and a better understanding of molecular mechanisms involved in cancer development.

Aptamer Conjugate-Based Ratiometric Fluorescent Probe for Precise Imaging of Therapy-Induced Cancer Senescence.

Therapy-induced cellular senescence has been increasingly recognized as a key mechanism to promote various aspects of carcinogenesis in a nonautonomous manner. Thus, real-time imaging monitoring of cellular senescence during cancer therapy is imperative not only to further elucidate its roles in cancer progression but also to provide guidance for medical management of cancer. However, it has long been a challenging task due to the lack of effective imaging molecule tools with high specificity and accuracy toward cancer senescence. Herein, we report the rational design, synthesis, and evaluation of an aptamer conjugate-based ratiometric fluorescent probe for precise imaging of therapy-induced cancer senescence. Unlike traditional senescence imaging systems, our probe targets two senescence-associated markers at both cellular and subcellular dimensions, namely, aptamer-mediated membrane marker recognition for active cell targeting and lysosomal marker-triggered ratiometric fluorescence changes of two cyanine dyes for site-specific, high-contrast imaging. Moreover, such a two-channel fluorescence response is activated after a one-step reaction and at the same location, avoiding the diffusion-caused signal decay previously encountered in dual-marker activated probes, contributing to spatiotemporally specific imaging of therapy-induced cancer senescence in living cells and three-dimensional multicellular tumor spheroids. This work may offer a valuable tool for a basic understanding of cellular senescence in cancer biology and interventions.

Topological Single-stranded DNA Encoding and Programmable Assembly of Molecular Nanostructures for NIR-II Cancer Theranostics.

Molecular nanotechnology promises to offer privileged access to developing NIR-II materials with precise structural and functional manipulation for transformable theranostic applications. However, the lack of an affordable, yet general, method makes this goal currently inaccessible. By virtue of the intriguing nucleic acid chemistry, here we present an artificial base-directed topological single-strand DNA encoding design that enables one-step synthesis of valence-controlled NIR-II molecular nanostructures and spatial assembly of these nanostructures to modulate their behaviors in living systems. As proof-of-concept studies, we construct ultrasmall Ag2 S quantum dots and pH-responsive, size-tunable CuS assemblies for in vivo NIR-II fluorescence imaging and deep tumor photothermal therapy. This work paves a new way for creating functionally diversified architectures and broadens the scope of DNA-encoded material engineering.

Regulating Lateral Adsorbate Interaction for Efficient Electroreforming of Bio-polyols.

Tailoring the selectivity at the electrode-electrolyte interface is one of the greatest challenges for heterogeneous electrocatalysis, and complementary strategies to catalyst structural designs need to be developed. Herein, we proposed a new strategy of controlling the electrocatalytic pathways by lateral adsorbate interaction for the bio-polyol oxidation. Redox-innocent 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) anion possesses the alcoholic property that facilely adsorbs on the nickel oxyhydroxide catalyst, but is resistant to oxidation due to the electron-withdrawing trifluoromethyl groups. The alien HFIP adsorbents can compete with bio-polyols and form a mixed adsorbate layer that creates lateral adsorbate interaction via hydrogen bonding, which achieved a >2-fold enhancement of the oxalate selectivity to 55 % for the representative glycerol oxidation and can be extended to various bio-polyol substrates. Through in situ spectroscopic analysis and DFT calculation on the glycerol oxidation, we reveal that the hydrogen-bonded adsorbate interaction can effectively tune the adsorption energies and tailor the oxidation capabilities toward the targeted products. This work offers an additional perspective of tuning electrocatalytic reactions via introducing redox-innocent adsorbates to create lateral adsorbate interactions.

Dual-Parameter Recognition-Directed Design of the Activatable Fluorescence Probe for Precise Imaging of Cellular Senescence.

Specific imaging of cellular senescence emerges as a promising strategy for early diagnosis and treatment of various age-related diseases. The currently available imaging probes are routinely designed by targeting a single senescence-related marker. However, the inherently high heterogeneity of senescence makes them inaccessible to achieve specific and accurate detection of broad-spectrum cellular senescence. Here, we report the design of a dual-parameter recognition fluorescent probe for precise imaging of cellular senescence. This probe remains silent in non-senescent cells, yet produces bright fluorescence after sequential responses to two senescence-associated markers, namely, SA-ß-gal and MAO-A. In-depth studies reveal that this probe allows for high-contrast imaging of senescence, independent of the cell source or stress type. More impressively, such dual-parameter recognition design further allows it to distinguish senescence-associated SA-ß-gal/MAO-A from cancer-related ß-gal/MAO-A, compared to commercial or previous single-marker detection probes. This study offers a valuable molecular tool for imaging cellular senescence, which is expected to significantly expand the basic studies on senescence and facilitate advances of senescence-related disease theranostics.

Recent Advances in Strategies for Imaging Detection and Intervention of Cellular Senescence.

Cellular senescence is a stable cell cycle arrest state that can be triggered by a wide range of intrinsic or extrinsic stresses. Increased burden of senescent cells in various tissues is thought to contribute to aging and age-related diseases. Thus, the detection and interventions of senescent cells are critical for longevity and treatment of disease. However, the highly heterogeneous feature of senescence makes it challenging for precise detection and selective clearance of senescent cells in different age-related diseases. To address this issue, considerable efforts have been devoted to developing senescence-targeting molecular theranostic strategies, based on the potential biomarkers of cellular senescence. Herein, we review recent advances in the field of anti-senescence research and highlight the specific visualization and elimination of senescent cells. Additionally, the challenges in this emerging field are outlined.

Engineering Hierarchical Recognition-Mediated Senolytics for Reliable Regulation of Cellular Senescence and Anti-Atherosclerosis Therapy.

Precise regulation of vascular senescence represents a far-reaching strategy to combat age-related diseases. However, the high heterogeneity of senescence, alongside the lack of targeting and potent senolytics, makes it very challenging. Here we report a molecular design to tackle this challenge through multidimensional, hierarchical recognition of three hallmarks commonly shared among senescence, namely, aptamer-mediated recognition of a membrane marker for active cell targeting, a self-immolative linker responsive to lysosomal enzymes for switchable drug release, and a compound against antiapoptotic signaling for clearance. Such senolytic can target and trigger severe cell apoptosis in broad-spectrum senescent endothelial cells, and importantly, distinguish them from the quiescent state. Its potential for in vivo treatment of vascular diseases is successfully illustrated in a model of atherosclerosis, with effective suppression of the plaque progression yet negligible side effects.

Relationship between the dietary inflammatory index and kidney stone prevalence.

PURPOSE: This study aimed to investigate the association between the dietary inflammatory index and lifetime kidney stone prevalence. METHODS: We performed a cross-sectional study utilizing the 2013-2014 National Health and Nutrition Examination Survey data. Data were available on 2192 participants aged > 20 years with a complete kidney stone history and 24 h dietary intake interview. Weighted multivariable linear regression, subgroup analyses, and interaction terms were employed. Covariates including age, race, sex, energy and protein intake, total serum calcium, serum iron, PIR, phosphorus, serum/urine creatinine, HDL, glucose, diastolic and systolic pressure, education level, eGFR, BMI, albuminuria, diabetes, smoking status, and marital status were hierarchically adjusted in three different models. RESULTS: The average dietary inflammatory index for 2192 participants was - 0.11 ± 1.73, ranging from - 4.52 to 4.28. In the fully adjusted model, participants in the highest dietary inflammatory index tertile (the most proinflammatory) had 72% higher odds of the lifetime prevalence of kidney stones than those in tertile 1 (OR = 1.72, 95% CI: 1.03, 2.88, P = 0.0367). Subgroup analysis showed that the association between the dietary inflammatory index and kidney stone history was only statistically significant in the younger age (age ≥ 60), female, Mexican American groups, married people or people without diabetes, hypertension, low eGFR, and albuminuria. CONCLUSIONS: There is a positive association between the dietary inflammatory index and self-reported kidney stones in US adults, which indicates that dietary patterns could greatly impact kidney stone prevalence.

Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study.

BACKGROUND: Heart failure (HF) is a common disease and a major public health problem. HF mortality prediction is critical for developing individualized prevention and treatment plans. However, due to their lack of interpretability, most HF mortality prediction models have not yet reached clinical practice. OBJECTIVE: We aimed to develop an interpretable model to predict the mortality risk for patients with HF in intensive care units (ICUs) and used the SHapley Additive exPlanation (SHAP) method to explain the extreme gradient boosting (XGBoost) model and explore prognostic factors for HF. METHODS: In this retrospective cohort study, we achieved model development and performance comparison on the eICU Collaborative Research Database (eICU-CRD). We extracted data during the first 24 hours of each ICU admission, and the data set was randomly divided, with 70% used for model training and 30% used for model validation. The prediction performance of the XGBoost model was compared with three other machine learning models by the area under the curve. We used the SHAP method to explain the XGBoost model. RESULTS: A total of 2798 eligible patients with HF were included in the final cohort for this study. The observed in-hospital mortality of patients with HF was 9.97%. Comparatively, the XGBoost model had the highest predictive performance among four models with an area under the curve (AUC) of 0.824 (95% CI 0.7766-0.8708), whereas support vector machine had the poorest generalization ability (AUC=0.701, 95% CI 0.6433-0.7582). The decision curve showed that the net benefit of the XGBoost model surpassed those of other machine learning models at 10%~28% threshold probabilities. The SHAP method reveals the top 20 predictors of HF according to the importance ranking, and the average of the blood urea nitrogen was recognized as the most important predictor variable. CONCLUSIONS: The interpretable predictive model helps physicians more accurately predict the mortality risk in ICU patients with HF, and therefore, provides better treatment plans and optimal resource allocation for their patients. In addition, the interpretable framework can increase the transparency of the model and facilitate understanding the reliability of the predictive model for the physicians.

Effectiveness of eHealth Self-management Interventions in Patients With Heart Failure: Systematic Review and Meta-analysis.

BACKGROUND: Heart failure (HF) is a common clinical syndrome associated with substantial morbidity, a heavy economic burden, and high risk of readmission. eHealth self-management interventions may be an effective way to improve HF clinical outcomes. OBJECTIVE: The aim of this study was to systematically review the evidence for the effectiveness of eHealth self-management in patients with HF. METHODS: This study included only randomized controlled trials (RCTs) that compared the effects of eHealth interventions with usual care in adult patients with HF using searches of the EMBASE, PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL databases from January 1, 2011, to July 12, 2022. The Cochrane Risk of Bias tool (RoB 2) was used to assess the risk of bias for each study. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria were used to rate the certainty of the evidence for each outcome of interest. Meta-analyses were performed using Review Manager (RevMan v.5.4) and R (v.4.1.0 x64) software. RESULTS: In total, 24 RCTs with 9634 participants met the inclusion criteria. Compared with the usual-care group, eHealth self-management interventions could significantly reduce all-cause mortality (odds ratio [OR] 0.83, 95% CI 0.71-0.98, P=.03; GRADE: low quality) and cardiovascular mortality (OR 0.74, 95% CI 0.59-0.92, P=.008; GRADE: moderate quality), as well as all-cause readmissions (OR 0.82, 95% CI 0.73-0.93, P=.002; GRADE: low quality) and HF-related readmissions (OR 0.77, 95% CI 0.66-0.90, P<.001; GRADE: moderate quality). The meta-analyses also showed that eHealth interventions could increase patients' knowledge of HF and improve their quality of life, but there were no statistically significant effects. However, eHealth interventions could significantly increase medication adherence (OR 1.82, 95% CI 1.42-2.34, P<.001; GRADE: low quality) and improve self-care behaviors (standardized mean difference -1.34, 95% CI -2.46 to -0.22, P=.02; GRADE: very low quality). A subgroup analysis of primary outcomes regarding the enrolled population setting found that eHealth interventions were more effective in patients with HF after discharge compared with those in the ambulatory clinic setting. CONCLUSIONS: eHealth self-management interventions could benefit the health of patients with HF in various ways. However, the clinical effects of eHealth interventions in patients with HF are affected by multiple aspects, and more high-quality studies are needed to demonstrate effectiveness.

Spatially Confined Intervention of Cellular Senescence by a Lysosomal Metabolism Targeting Molecular Prodrug for Broad-Spectrum Senotherapy.

Specific intervention of senescent cells (SnCs) is emerging as a powerful means to counteract aging and age-related diseases. Canonical methods are generally designed to target SnC-associated signaling pathways, which are however dynamically changing and highly heterogeneous in SnCs, significantly limiting the effectiveness. Here, we present a tailor-made molecular prodrug targeting lysosome dysfunction, a unique feature shared by virtually all types of SnCs. The prodrug comprises three modules all targeting the altered lysosomal programs in SnCs, namely, a recognizing unit towards the elevated lysosome content, a linker cleavable by the activated lysosomal enzyme, and a lysosomotropic agent targeting the increased lysosomal membrane sensitivity. This spatially confined design enables killing broad-spectrum SnCs, with high specificity over non-SnCs. Along with in vivo benefits, this work offers a way to significantly expand the applicability of senotherapy in a wide range of diseases.

Steering the Glycerol Electro-Reforming Selectivity via Cation-Intermediate Interactions.

Electro-reforming of renewable biomass resources is an alternative technology for sustainable pure H2 production. Herein, we discovered an unconventional cation effect on the concurrent formate and H2 production via glycerol electro-reforming. In stark contrast to the cation effect via forming double layers in cathodic reactions, residual cations at the anode were discovered to interact with the glycerol oxidation intermediates to steer its product selectivity. Through a combination of product analysis, transient kinetics, crown ether trapping experiments, in situ IRRAS and DFT calculations, the aldehyde intermediates were discovered to be stabilized by the Li+ cations to favor the non-oxidative C-C cleavage for formate production. The maximal formate efficiency could reach 81.3 % under ≈60 mA cm-2 in LiOH. This work emphasizes the significance of engineering the microenvironment at the electrode-electrolyte interface for efficient electrolytic processes.

Na doping into Li-rich layered single crystal nanoparticles for high-performance lithium-ion batteries cathodes.

Lithium-rich layered manganese-based cathodes (LRLMOs) with first-class energy density (∼1000 W h kg-1) have attracted wide attention. Nevertheless, the weak cycle stability and bad rate capability obstruct their large-scale commercial application. Here, single crystal Li1.2-xNaxNi0.2Mn0.6O2(x = 0, 0.05, 0.1, 0.15) nanoparticles are designed and successfully synthesized due to the single crystal structure with smaller internal stress and larger ionic radius of Na. The synergistic advantages of single crystal structure and Na doping are authenticated as cathodes for Li ion batteries (LIBs), which can consolidate the crystallographic structure and be benefit for migration of lithium ion. Among all the Na doping single crystals, Li1.1Na0.1Ni0.2Mn0.6O2cathode possesses supreme cycling life and discharge capacity at large current density. To be more specific, it exhibits a discharge capacity of 264.2 mAh g-1after 50 charge and discharge cycles, higher than that of undoped material (214.9 mAh g-1). The discharge capacity of Li1.1Na0.1Ni0.2Mn0.6O2cathode at 10 C (1 C = 200 mA g-1) is enhanced to 160.4 mAh g-1(106.7 mAh g-1forx = 0 sample). The creative strategy of Na doping single crystal LRLMOs might furnish an idea to create cathode materials with high energy and power density for next generation LIBs.

Leveraging Transfer Learning to Analyze Opinions, Attitudes, and Behavioral Intentions Toward COVID-19 Vaccines: Social Media Content and Temporal Analysis.

BACKGROUND: The COVID-19 vaccine is considered to be the most promising approach to alleviate the pandemic. However, in recent surveys, acceptance of the COVID-19 vaccine has been low. To design more effective outreach interventions, there is an urgent need to understand public perceptions of COVID-19 vaccines. OBJECTIVE: Our objective was to analyze the potential of leveraging transfer learning to detect tweets containing opinions, attitudes, and behavioral intentions toward COVID-19 vaccines, and to explore temporal trends as well as automatically extract topics across a large number of tweets. METHODS: We developed machine learning and transfer learning models to classify tweets, followed by temporal analysis and topic modeling on a dataset of COVID-19 vaccine-related tweets posted from November 1, 2020 to January 31, 2021. We used the F1 values as the primary outcome to compare the performance of machine learning and transfer learning models. The statistical values and P values from the Augmented Dickey-Fuller test were used to assess whether users' perceptions changed over time. The main topics in tweets were extracted by latent Dirichlet allocation analysis. RESULTS: We collected 2,678,372 tweets related to COVID-19 vaccines from 841,978 unique users and annotated 5000 tweets. The F1 values of transfer learning models were 0.792 (95% CI 0.789-0.795), 0.578 (95% CI 0.572-0.584), and 0.614 (95% CI 0.606-0.622) for these three tasks, which significantly outperformed the machine learning models (logistic regression, random forest, and support vector machine). The prevalence of tweets containing attitudes and behavioral intentions varied significantly over time. Specifically, tweets containing positive behavioral intentions increased significantly in December 2020. In addition, we selected tweets in the following categories: positive attitudes, negative attitudes, positive behavioral intentions, and negative behavioral intentions. We then identified 10 main topics and relevant terms for each category. CONCLUSIONS: Overall, we provided a method to automatically analyze the public understanding of COVID-19 vaccines from real-time data in social media, which can be used to tailor educational programs and other interventions to effectively promote the public acceptance of COVID-19 vaccines.

Deciphering and Suppressing Over-Oxidized Nitrogen in Nickel-Catalyzed Urea Electrolysis.

Urea electrolysis is a prospective technology for simultaneous H2 production and nitrogen suppression in the process of water being used for energy production. Its sustainability is currently founded on innocuous N2 products; however, we discovered that prevalent nickel-based catalysts could generally over-oxidize urea into NO2 - products with ≈80 % Faradaic efficiencies, posing potential secondary hazards to the environment. Trace amounts of over-oxidized NO3 - and N2 O were also detected. Using 15 N isotopes and urea analogues, we derived a nitrogen-fate network involving a NO2 - -formation pathway via OH- -assisted C-N cleavage and two N2 -formation pathways via intra- and intermolecular coupling. DFT calculations confirmed that C-N cleavage is energetically more favorable. Inspired by the mechanism, a polyaniline-coating strategy was developed to locally enrich urea for increasing N2 production by a factor of two. These findings provide complementary insights into the nitrogen fate in water-energy nexus systems.

Radiosensitivity enhancement by Co-NMS-mediated mitochondrial impairment in glioblastoma.

We investigated the radiosensitizing effects of Co-NMS, a derivative of nimesulide based on a cobalt carbonyl complex, on malignant glioma cells. In the zebrafish exposed to Co-NMS ranging from 5 to 20 µM, cell death and heat shock protein 70 expression in the brain and neurobehavioral performance were evaluated. Our data showed that Co-NMS at 5 µM did not cause the appreciable neurotoxicity, and thereby was given as a novel radiation sensitizer in further study. In the U251 cells, Co-NMS combined with irradiation treatment resulted in significant inhibition of cell growth and clonogenic capability as well as remarkable increases of G2/M arrest and apoptotic cell population compared to the irradiation alone treatment. This demonstrated that the Co-NMS administration exerted a strong potential of sensitizing effect on the irradiated cells. With regard to the tumor radiosensitization of Co-NMS, it could be primarily attributed to the Co-NMS-derived mitochondrial impairment, reflected by the loss of mitochondrial membrane potential, the disruption of mitochondrial fusion and fission balance as well as redox homeostasis. Furthermore, the energy metabolism of the U251 cells was obviously suppressed by cotreatment with Co-NMS and irradiation through repressing mitochondrial function. Taken together, our findings suggested that Co-NMS could be a desirable drug to enhance the radiotherapeutic effects in glioblastoma patients.

Knockout of ALOX12 protects against spinal cord injury-mediated nerve injury by inhibition of inflammation and apoptosis.

Spinal cord injury (SCI) is terrible damage leading to the deficiencies and results in infinite inconvenience to sufferers. The effective treatment for SCI still meets a larger number of problems. Herein, the underlying molecular mechanism and novel therapy of SCI are urgently to investigate. Arachidonate 12-lipoxygenase (ALOX12) is widely expressed in various cell types and plays important role in modulating different cellular processes, such as platelet aggregation, cell migration and cancer cell proliferation. Nevertheless, the effects of ALOX12 on SCI are unclear. In the study, SCI model was established in wild type (WT) mice and ALOX12 knockout mice. First, ALOX12 expression was up-regulated in spinal cord tissues of WT mice after SCI. ALOX12-knockout mice exhibited improved behavior after SCI operation. Glial activation triggered by SCI was also alleviated in mice with the loss of ALOX12, as evidenced by the down-regulated expression of glial fibrillary acidic protein (GFAP) and Iba-1 in spinal cord samples. Further, SCI-induced inflammation was markedly prevented in ALOX12-knockout mice through blocking inhibitor of NF-κB α (IκBα)/nuclear factor-κB (NF-κB) pathway signaling. Additionally, reducing ALOX12 expression attenuated apoptosis in spinal cord tissues of SCI mice by decreasing Cyto-c, cleaved Caspase-3 and poly (ADP-ribose) polymerases (PARP) expression. The protective role of ALOX12-decrease against SCI was verified in LPS-incubated glial cells through repressing inflammatory response and apoptotic formation. Moreover, transgenic mice with ALOX12 over-expression showed accelerated SCI, associated with intensified inflammation and apoptosis. Based on these results, strategies for inhibiting ALOX12 could be used to prevent SCI development by repressing inflammation and apoptosis.

Synthesis, toxicity and antitumor activity of cobalt carbonyl complexes targeting hepatocellular carcinoma.

Based on our previous research, a series of targeting hepatocellular carcinoma complexes, [R-Glycyrrhetinic acid-CH2C2H-[Co2(CO)6] (R = H, 1; R = NSAIDs-COOH, 2-4; R = Aromatic acid, 5-7; R = Amino acid, 8-10), were synthesized. The test showed they are slow CO releasers. Using HeLa, A549, HT-29, SMMC7721 and HepG2 cells as models, their activities against tumor cell proliferation were firstly evaluated. The resulting data show all the complexes displayed a good anti-proliferation activity against the HepG2 and SMMC-7721 liver cancer cells, and their IC50 values were in the range of 10.07-66.06 µM; compared with cis-platin (DDP), their activities were comparable or even better under the same condition. Among them, complexes 3, 4, 6 and 9 exhibited higher anti-proliferation activities against HepG2 and SMMC-7721 cell lines than the other cell lines. To confirm further these complexes have selectivity to the liver cells, the uptakes of complexes 3, 4, 6 and 9 by HepG2, HT-29, A549 and SMMC7721 cell lines were studied. The results show the cell uptake rates of the complexes by HepG2 cells and SMMC7721 cells were much greater than by other cells under the same condition. In following tests, the tested complexes displayed higher activities in inhibiting NF-kB, COX-2 and iNOS; and they induced HepG2 cells apoptosis by mitochondrial pathway, which assessed by staining with different fluorescent reagent DAPI, PI, Mito-Tracker Green and DCFH-DA. Meanwhile, the tested complexes up-regulated the expression levels of caspase-3 and Bax, down-regulated the Bcl-2 expression. In addition, they had no effect on zebrafish embryo survival, embryo hatching, embryonic movement, zebrafish malformation and zebrafish movement at below 0.5 µM. This suggests the complexes are potential candidates to be used in clinic for liver cancers.

Anti-atherosclerosis effect of H2S donors based on nicotinic acid and chlorfibrate structures.

Based on the structures of nicotinic acid and chlorfibrate, a series of new H2S donors were synthesized and their anti-atherosclerosis activities using Ox-LDL RAW 264.6 cells as model were evaluated. The release test showed that all the compounds could release H2S effectively and showed low cytotoxicity. In the bioactivity experiments, compounds 1, 3, 9 and 14 increased the survival rate of HUVEC cells treated by ox-LDL; among four compounds, compounds 1 and 3 displayed higher activity than the others. In the foam cell model, compounds 1 and 3 were found to inhibit the formation of foam cells and significantly reduced the content of TC and FC in foam cells. They had more obvious effects on lipid reduction than those of nicotinic acid and chlorfibrate. In anti-oxidation, compounds 1 and 3 significantly reduced ROS and MDA and increased the expression level of SOD, whereas the precursor compounds, niacin and chlorfibrate had little antioxidant effect. In addition, both compounds also inhibited the inflammatory response in foam cells, with reducing pro-inflammatory factor TNF-α and increasing anti-inflammatory cytokine IL-10. WB assay showed that the tested compounds inhibited the expression levels PI3K, Akt and NF-κb proteins. In conclusion, the compounds as H2S donors could protect HUVEC cells from damage and inhibit the formation of foam cells by inhibiting PI3K/Akt/NF-κb signal pathway. All these suggest the compounds have potential to be candidate for anti-atherosclerosis medicines.