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Direct ethanol fuel cells have been widely investigated as nontoxic and low-corrosive energy conversion devices with high energy and power densities. It is still challenging to develop high-activity and durable catalysts for a complete ethanol oxidation reaction on the anode and accelerated oxygen reduction reaction on the cathode. The materials’ physics and chemistry at the catalytic interface play a vital role in determining the overall performance of the catalysts. Herein, we propose a Pd/Co@N-C catalyst that can be used as a model system to study the synergism and engineering at the solid-solid interface. Particularly, the transformation of amorphous carbon to highly graphitic carbon promoted by cobalt nanoparticles helps achieve the spatial confinement effect, which prevents structural degradation of the catalysts. The strong catalyst-support and electronic effects at the interface between palladium and Co@N-C endow the electron-deficient state of palladium, which enhances the electron transfer and improved activity/durability. The Pd/Co@N-C delivers a maximum power density of 438 mW cm −2 in direct ethanol fuel cells and can be operated stably for more than 1000 hours. This work presents a strategy for the ingenious catalyst structural design that will promote the development of fuel cells and other sustainable energy-related technologies. It is challenging to develop high-activity and durable catalysts for both ethanol oxidation reaction on the anode and oxygen reduction reaction on the cathode. Here in this work, authors proposed Pd/Co@N-C catalyst as a model to synergistically maximize the usage of catalyst nanoparticles and active interfaces for direct ethanol fuel cells.

The development of immunotherapies over the past decade has resulted in a paradigm shift in the treatment of cancer. However, the majority of patients do not benefit from immunotherapy, presumably owing to insufficient reprogramming of the immunosuppressive tumour microenvironment (TME) and thus limited reinvigoration of antitumour immunity. Various metabolic machineries and nutrient-sensing mechanisms orchestrate the behaviour of immune cells in response to nutrient availability in the TME. Notably, tumour-infiltrating immune cells typically experience metabolic stress as a result of the dysregulated metabolic activity of tumour cells, leading to impaired antitumour immune responses. Moreover, the immune checkpoints that are often exploited by tumour cells to evade immunosurveillance have emerging roles in modulating the metabolic and functional activity of T cells. Thus, repurposing of drugs targeting cancer metabolism might synergistically enhance immunotherapy via metabolic reprogramming of the TME. In addition, interventions targeting the metabolic circuits that impede antitumour immunity have been developed, with several clinical trials underway. Herein, we discuss how these metabolic circuits regulate antitumour immunity and the possible approaches to targeting these pathways in the context of anticancer immunotherapy. We also describe hypothetical combination treatments that could be used to better unleash the potential of adoptive cell therapies by enhancing T cell metabolism.The metabolic conditions in tumours can result in phenotypic reprogramming of non-tumour cells, including immune cells, in the tumour microenvironment. This Review provides an overview of the pathways of cancer metabolism that intersect with immunometabolism, typically resulting in immunosuppression, with a focus on how these metabolic pathways could be targeted in order to enhance anticancer immunity and immunotherapy.

Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here, we report a high-throughput system for nanoliter-scale phenotypic screening that formulates a chemical library in nanoliter droplet emulsions and automates the construction of chemical combinations en masse using parallel droplet processing. We applied this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics against Escherichia coli, a model gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against gram-positive bacteria but are not effective by themselves to resolve gram-negative infections.

Combination therapy is a fundamental strategy in cancer chemotherapy. It involves administering two or more anti-cancer agents to increase efficacy and overcome multidrug resistance compared to monotherapy. However, drug combinations can exhibit synergy, additivity, or antagonism. This study presents a machine learning framework to classify and predict cancer drug combinations. The framework utilizes several key steps including data collection and annotation from the O’Neil drug interaction dataset, data preprocessing, stratified splitting into training and test sets, construction and evaluation of classification models to categorize combinations as synergistic, additive, or antagonistic, application of regression models to predict combination sensitivity scores for enhanced predictions compared to prior work, and the last step is examination of drug features and mechanisms of action to understand synergy behaviors for optimal combinations. The models identified combination pairs most likely to synergize against different cancers. Kinase inhibitors combined with mTOR inhibitors, DNA damage-inducing drugs or HDAC inhibitors showed benefit, particularly for ovarian, melanoma, prostate, lung and colorectal carcinomas. Analysis highlighted Gemcitabine, MK-8776 and AZD1775 as frequently synergizing across cancer types. This machine learning framework provides a valuable approach to uncover more effective multi-drug regimens.

Chlorella is a green unicellular alga that is commercially produced and distributed worldwide as a dietary supplement. Chlorella products contain numerous nutrients and vitamins, including D and B12, that are absent in plant-derived food sources. Chlorella contains larger amounts of folate and iron than other plant-derived foods. Chlorella supplementation to mammals, including humans, has been reported to exhibit various pharmacological activities, including immunomodulatory, antioxidant, antidiabetic, antihypertensive, and antihyperlipidemic activities. Meta-analysis on the effects of Chlorella supplementation on cardiovascular risk factors have suggested that it improves total cholesterol levels, low-density lipoprotein cholesterol levels, systolic blood pressure, diastolic blood pressure, and fasting blood glucose levels but not triglycerides and high-density lipoprotein cholesterol levels. These beneficial effects of Chlorella might be due to synergism between multiple nutrient and antioxidant compounds. However, information regarding the bioactive compounds in Chlorella is limited.

Synthetic retinoid compounds can kill both growing and persister MRSA cells by disrupting the membrane lipid bilayer, and are effective in a mouse model of chronic MRSA infection. Drugs to beat persistence Bacterial persisters are a subpopulation of cells that can survive lethal antibiotics and other stresses. They are a major challenge for antimicrobial therapy as they cannot be killed by traditional therapeutic agents. Eleftherios Mylonakis and colleagues have developed retinoid compounds that can kill both growing and persister MRSA cells by disrupting the membrane. They develop one of these compounds with an improved cytotoxicity profile, and show that it is effective in treating a mouse model of chronic MRSA infection. Further development of these antibiotics is required to improve safety margins to move the antibiotics closer to being viable clinical candidates. A challenge in the treatment of Staphylococcus aureus infections is the high prevalence of methicillin-resistant S. aureus (MRSA) strains and the formation of non-growing, dormant ‘persister’ subpopulations that exhibit high levels of tolerance to antibiotics 1 , 2 , 3 and have a role in chronic or recurrent infections 4 , 5 . As conventional antibiotics are not effective in the treatment of infections caused by such bacteria, novel antibacterial therapeutics are urgently required. Here we used a Caenorhabditis elegans –MRSA infection screen 6 to identify two synthetic retinoids, CD437 and CD1530, which kill both growing and persister MRSA cells by disrupting lipid bilayers. CD437 and CD1530 exhibit high killing rates, synergism with gentamicin, and a low probability of resistance selection. All-atom molecular dynamics simulations demonstrated that the ability of retinoids to penetrate and embed in lipid bilayers correlates with their bactericidal ability. An analogue of CD437 was found to retain anti-persister activity and show an improved cytotoxicity profile. Both CD437 and this analogue, alone or in combination with gentamicin, exhibit considerable efficacy in a mouse model of chronic MRSA infection. With further development and optimization, synthetic retinoids have the potential to become a new class of antimicrobials for the treatment of Gram-positive bacterial infections that are currently difficult to cure.

Recently, the widespread distribution of pesticides detected in the hive has raised serious concerns about pesticide exposure on honey bee (Apis mellifera L.) health. A larval rearing method was adapted to assess the chronic oral toxicity to honey bee larvae of the four most common pesticides detected in pollen and wax--fluvalinate, coumaphos, chlorothalonil, and chloropyrifos--tested alone and in all combinations. All pesticides at hive-residue levels triggered a significant increase in larval mortality compared to untreated larvae by over two fold, with a strong increase after 3 days of exposure. Among these four pesticides, honey bee larvae were most sensitive to chlorothalonil compared to adults. Synergistic toxicity was observed in the binary mixture of chlorothalonil with fluvalinate at the concentrations of 34 mg/L and 3 mg/L, respectively; whereas, when diluted by 10 fold, the interaction switched to antagonism. Chlorothalonil at 34 mg/L was also found to synergize the miticide coumaphos at 8 mg/L. The addition of coumaphos significantly reduced the toxicity of the fluvalinate and chlorothalonil mixture, the only significant non-additive effect in all tested ternary mixtures. We also tested the common 'inert' ingredient N-methyl-2-pyrrolidone at seven concentrations, and documented its high toxicity to larval bees. We have shown that chronic dietary exposure to a fungicide, pesticide mixtures, and a formulation solvent have the potential to impact honey bee populations, and warrants further investigation. We suggest that pesticide mixtures in pollen be evaluated by adding their toxicities together, until complete data on interactions can be accumulated.

This study investigates the anticancer and antioxidant potential of a novel phytochemical combination of eugenol, a natural compound extracted from cloves, and Sanguinarine, a flavonoid from Sanguinaria canadensis. The synergistic interaction between eugenol and Sanguinarine was found to exhibit moderate cytotoxicity against MCF-7 cell lines, with an IC50 value of 147.2 μM, suggesting potential anti-cancer properties. The combination also demonstrated potent antioxidant activity, comparable to quercetin, in DPPH and H2O2 scavenging assays. The results suggest that the eugenol-Sanguinarine combination may have therapeutic applications in the prevention and treatment of oxidative stress-related diseases and cancer. Further studies are needed to fully elucidate the mechanisms of action and optimal dosing regimens. Overall, this study highlights the potential of combining natural compounds to create novel antioxidant and anti-cancer agents, and underscores the importance of continued research into the therapeutic properties of plant-derived compounds.