Lead-based perovskite nanocrystals (NCs) have outstanding optical properties and cheap synthesis conferring them a tremendous potential in the field of optoelectronic devices. However, two critical problems are still unresolved and hindering their commercial applications: one is the fact of being lead-based and the other is the poor stability. Lead-free all-inorganic perovskite Cs Bi X (X=Cl, Br, I) NCs are synthesized with emission wavelength ranging from 400 to 560 nm synthesized by a facile room temperature reaction. The ligand-free Cs Bi Br NCs exhibit blue emission with photoluminescence quantum efficiency (PLQE) about 0.2 %. The PLQE can be increased to 4.5 % when extra surfactant (oleic acid) is added during the synthesis processes. This improvement stems from passivation of the fast trapping process (2-20 ps). Notably, the trap states can also be passivated under humid conditions, and the NCs exhibited high stability towards air exposure exceeding 30 days.

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Near-infrared light-responsive inorganic nanoparticles have been shown to enhance the efficacy of cancer photothermal ablation therapy. However, current nanoparticle-mediated photothermal ablation is more effective in treating local cancer at the primary site than metastatic cancer. Here, we report the design of a near-infrared light-induced transformative nanoparticle platform that combines photothermal ablation with immunotherapy. The design is based on chitosan-coated hollow CuS nanoparticles that assemble the immunoadjuvants oligodeoxynucleotides containing the cytosine-guanine (CpG) motifs. Interestingly, these structures break down after laser excitation, reassemble, and transform into polymer complexes that improve tumor retention of the immunotherapy. In this “photothermal immunotherapy” approach, photothermal ablation-induced tumor cell death reduces tumor growth and releases tumor antigens into the surrounding milieu, while the immunoadjuvants potentiate host antitumor immunity. Our results indicated that combined photothermal immunotherapy is more effective than either immunotherapy or photothermal therapy alone against primary treated and distant untreated tumors in a mouse breast cancer model. These hollow CuS nanoparticles are biodegradable and can be eliminated from the body after laser excitation.

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.