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Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE01486G, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Xuzheng Liu, Michael Rienäcker, Mohammad Gholipoor, Lingyi Fang, Tonghan Zhao, Benjamin Hacene, Julian Petermann, Ruijun Cai, Hang Hu, Thomas Feeney, Faranak Sadegh, Paul Fassl, Renjun Guo, Uli Lemmer, Robby Peibst, Ulrich Wilhelm Paetzold
Integrating wide-bandgap organic-inorganic lead halide perovskite absorber layers with Si bottom solar cells into tandem architectures offers significant potential for increasing power conversion efficiency (PCE). However, achieving high-performance monolithic tandem...
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Kintsugi: A Decentralized E2EE Key Recovery Protocol

Key recovery is the process of regaining access to end-to-end encrypted data after the user has lost their device, but still has their password. Existing E2EE key recovery methods, such as those deployed by Signal and WhatsApp, centralize trust by relying on servers administered by a single provider.

In this talk, we share our recent work on Kintsugi, a decentralized recovery protocol that distributes trust over multiple recovery nodes. This talk will cover how we developed Kintsugi and its unique security properties, as well as compare it to prior E2EE key recovery work.

Zoom link: https://cam-ac-uk.zoom.us/j/84072830114?pwd=3zxgIngk7X6zSPiEM6SMsziQWBW07y.1

• Speaker: Emilie Ma
• Tuesday 06 May 2025, 14:00-15:00
• Venue: Webinar (via Zoom online).
• Series: Computer Laboratory Security Seminar; organiser: Anna Talas.

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Global modelling of ice-nucleating particles and their impact on cirrus clouds and the climate system

Abstract: Ice-nucleating particles (INPs) have important influences on cirrus clouds and the climate system; however, the understanding of their global impacts is still uncertain. We perform numerical simulations with a global aerosol–climate model to analyse INP -induced cirrus modifications and the resulting climate impacts. We evaluate various sources of uncertainties, e.g. the ice-nucleating ability of INPs and the role of model dynamics, and provide a new estimate for the global INP –cirrus effect.

Biography: Study of Physics (Bachelors and Masters) at Ludwig Maximilian University of Munich (2010-2016) PhD student at the German Aerospace Center (DLR); Institute of Atmospheric Physics, Earth System Modelling Department, Oberpfaffenhofen (2017-2021); Dissertation title: “Global modelling of ice nucleating particles and their effects on cirrus clouds” Postdoc at DLR (since 2021)

https://teams.microsoft.com/l/meetup-join/19%3ameeting_MmUxMWIxYTgtZDM3OS00MTYzLTg1NGQtYzEzNWZhZDRhNDlh%40thread.v2/0?context=%7b%22Tid%22%3a%2249a50445-bdfa-4b79-ade3-547b4f3986e9%22%2c%22Oid%22%3a%228b208bd5-8570-491b-abae-83a85a1ca025%22%7d

• Speaker: Dr. Christof Beer
• Tuesday 10 June 2025, 11:00-12:00
• Venue: Chemistry Dept, Unilever Lecture Theatre and Teams.
• Series: Centre for Atmospheric Science seminars, Chemistry Dept.; organiser: Yao Ge.

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When fire plumes glow in the dark: Tracing organic aerosol chemical regime dominance clues via light-absorbing species

Abstract: Wildfire events have increased in frequency in recent years, especially in regions dominated by elevated temperatures, dry and windy conditions (Donahue et al., 2009; Hodshire et al., 2019). During such events, the generated fire plume contains a mixture of gaseous and particulate species (Figure 1), driving the chemical processing both during the initial and aging stage (Hodshire et al., 2019). Organic aerosols (OA) comprise a large portion of the available chemical species inside a fire plume and their evolution is primarily determined by two competing regimes (Garofalo et al., 2019): (1) oxidation-driven condensation and (2) dilution-driven evaporation. Key components of OA are light-absorbing species (LAS), notably black and brown carbon. Although LAS are not a traditional metric of OA chemical regime identification, their concentrations, together with key gas-phase tracers and water soluble organic carbon, provide crucial insights into the dominant in-plume chemical regime. We evaluated the relationship between fuel type, LAS levels, and fire tracers to assess their connection regime prevalence. Data obtained from the 2019 FIREX -AQ campaign (Warneke et al. 2022) were used to analyse 13 fire plumes across seven flights in late July and early August over the northwestern United States. All flights were conducted at night, restricting the sunlight-driven photochemistry and thus quenching rapid oxidation by hydroxyl radicals. Thus, the fuel composition emerges as the primary driver of LAS and OA regime evolution within the fire plumes.

Biography: Dr. Eleni Dovrou is currently a Postdoctoral Researcher at the Technical University of Crete in the School of Environmental and Chemical Engineering in the Atmospheric Environment and Climate Change Laboratory (Voulgarakis Group). She is an environmental engineer with specialization in atmospheric chemistry and health effects. She obtained her PhD from Harvard University (Keutsch Group), where she focused on molecular level reactions in the troposphere. Upon completion of her PhD, in 2020, she worked as a Postdoctoral Fellow at the Max Planck Institute of Chemistry (Poeschl Group) focusing on laboratory and modeling studies of the effect of atmospheric reactive species on the respiratory and circulatory system. In 2022 she obtained a Postdoc position at the Foundation for Research and Technology Hellas (Pandis Group), where she worked on indoor air quality. She has experimental, field and modeling experience. Her current research focuses on understanding the effect of extreme events, and especially fires, targeting the potential chemical mechanisms that dominate and influence future air quality. Starting this fall, she will be an Assistant Professor in Chemistry at the University of Crete.

https://teams.microsoft.com/l/meetup-join/19%3ameeting_MWYzYmRiMDctNzNkNi00N2JmLTk4NDUtYzBiMDM4YjgyNjI1%40thread.v2/0?context=%7b%22Tid%22%3a%2249a50445-bdfa-4b79-ade3-547b4f3986e9%22%2c%22Oid%22%3a%228b208bd5-8570-491b-abae-83a85a1ca025%22%7d

• Speaker: Dr. Eleni Dovrou, Technical University of Crete
• Tuesday 27 May 2025, 11:00-12:00
• Venue: Chemistry Dept, Unilever Lecture Theatre and Teams.
• Series: Centre for Atmospheric Science seminars, Chemistry Dept.; organiser: Yao Ge.

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Interpreting multimodel ensembles

Abstract: Ensembles of simulations from multiple climate models (‘simulators’) underpin much of our understanding of the climate system, and in particular the potential evolution of future climate in response to different scenarios of socioeconomic development and the associated greenhouse gas emissions. No simulator is perfect, however; and ensemble outputs contain structured variation reflecting simulator inter-relationships, as well as shared discrepancies between the simulators and the real climate system. This structure must be accounted for when using ensembles to learn about aspects of the real climate, especially when defensible assessments of uncertainty are needed to support decision-making. This talk will discuss the issues involved, and describe a statistical framework for addressing the problem. A theoretical analysis leads to a mathematical result with major implications for the design and analysis of multimodel ensembles; whilst the practical application of the framework will be demonstrated using future climate projections for the United Kingdom from two contrasting ensembles (UKCP18 and EuroCORDEX). These ensembles have different structures and properties: the approach is shown to reconcile the substantial differences between the original ensemble outputs, in terms of both the real-world climate of the future and the associated uncertainties.

Biography: Richard is a Professor in the Department of Statistical Science at University College London, where he has worked since completing his PhD at UMIST in 1994. He has extensive experience of developing and applying statistical methods for the environmental sciences. Particular interests include the analysis of time series and space-time data, with application areas including hydrology and the impacts of climate change. Other areas of interest include the assessment of uncertainty when interpreting model outputs; the use of mis-specified models; and the use of nonprobability samples to draw population inferences in ecology.

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• Speaker: Prof Richard Chandler, UCL
• Tuesday 13 May 2025, 11:00-12:00
• Venue: Chemistry Dept, Unilever Lecture Theatre and Teams.
• Series: Centre for Atmospheric Science seminars, Chemistry Dept.; organiser: Yao Ge.

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Quantitative Biology Seminar

Abstract not available

• Speaker: Shohei Koide, NYU Langone Health
• Monday 16 June 2025, 12:30-13:30
• Venue: CRUK CI Lecture Theatre.
• Series: Seminars on Quantitative Biology @ CRUK Cambridge Institute ; organiser: .

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Quantitative Biology Seminar

Abstract not available

• Speaker: David Savage, UC Berkeley
• Monday 19 May 2025, 12:30-13:30
• Venue: CRUK CI Lecture Theatre.
• Series: Seminars on Quantitative Biology @ CRUK Cambridge Institute ; organiser: Kate Davenport.

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Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE01110H, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Hui Li, Davide Regaldo, Chunsheng Jack Wu, Mirko Prato, Antonella Treglia, Heyong Wang, Wolfram Hempel, Michele Sessolo, Yang Zhou, Andrea Olivati, Annamaria Petrozza
The interfaces between the charge extraction layers and the perovskite layer are critical in defining the performance and stability of wide-bandgap (WBG) perovskite solar cells (PSCs). They govern multiple critical...
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Energy Environ. Sci., 2025, Advance Article
DOI: 10.1039/D5EE00492F, PaperQianwei Zhou, Linyu Hu, Huajun Zhang, Dongxu Hu, Guoqiang Liu, Maowen Xu, Hong Jin Fan, Zhimeng Liu, Chunlong Dai, Xin He
The effect of anions on the reversibility of Cu electrodes has been systematically investigated. Perchlorate (ClO4−) demonstrates the best reversibility and fastest plating/stripping kinetics by inhibiting the formation of the Cu2O by-product.
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Energy Environ. Sci., 2025, Advance Article
DOI: 10.1039/D5EE00640F, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Jihoo Lim, Seungmin Lee, Hongjae Shim, Lei Wang, Hyeonah Cho, Jincheol Kim, Claudio Cazorla, Yong-Jin Kim, Hanul Min, Minwoo Lee, Xiaojing Hao, S. Ravi P. Silva, Jan Seidel, Dohyung Kim, Jun Hong Noh, Jae Sung Yun
Ferroelectric properties can be utilized for efficient charge carrier separation by spontaneous electric polarization.
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Modelling Building Thermal Dynamics – From Data Generation to Transfer Learning

Abstract

Building operations contribute approximately one-third of global CO₂ emissions. Advanced control strategies can reduce these emissions by up to 30%. Such control requires accurate mathematical models that capture the building’s thermal dynamics. Data-driven modeling has emerged as the most scalable approach for this purpose. However, the availability of high-quality building data remains limited. To address this challenge, we propose two methods: (1) a data generation framework that synthesizes realistic building operation data, and (2) a general Transfer Learning model that serves as an effective initialization for modeling new target buildings.

Bio

Fabian is a second-year PhD student in the Department of Energy Management Technologies at the Technical University of Munich, supervised by Prof. Dr. Christoph Goebel. His research focuses on using Machine Learning to model building thermal dynamics. Such models are necessary for enabling Model Predictive Control of the building, which can reduce CO₂ emissions by up to 30%.

• Speaker: Fabian Raisch, Technical University of Munich
• Thursday 15 May 2025, 13:00-14:00
• Venue: Room GS15 at the William Gates Building and on Zoom: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon .
• Series: Energy and Environment Group, Department of CST; organiser: lyr24.

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Biocomputation with Motile Agents in Networks

Abstract The solution space of Non-deterministic Polynomial (NP) complete problems grows exponentially with input size. Consequently, large NP complete problems cannot be solved in an acceptable time by fast, but sequential electronic computers, nor presently by alternative, parallel computing approaches. Here, we report that the bacterial exploration of microfluidic networks that encode instances of the Subset Sum Problem (SSP) is equivalent to solving this NP-complete problem. Significantly, the ability of bacteria to multiply in confined environments translates in the amplification of the computational parallelism, with computing resources growing naturally to match the size of a given combinatorial problem. A scaling analysis of the time needed by bacteria to solve SSP problems encoded in microfluidic networks identifies the point where they are theoretically expected to outperform fast solid-state computers. These results, namely massively parallel, design-driven low error operation, low energy requirement for computing, and exponentially growing computing resources, suggest that bacterial-driven biocomputation on networks holds the potential to scale up successfully.

• Speaker: Professor Dan V Nicolau, McGill University
• Friday 16 May 2025, 14:00-15:00
• Venue: Oatley 1 Meeting Room, Department of Engineering.
• Series: Engineering - Mechanics and Materials Seminar Series; organiser: div-c.

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Cryo-EM reveals Zingibroside R1 (ZR1) undergoes self-assemble helical nanofibrils. The hydrogen-bonding interface between ZR1 nanofibrils and glucan compromises membrane integrity, inhibiting C. albicans proliferation in vitro and in vulvovaginal candidiasis (VVC) model mice in vivo. ZR1 gel could also deliver probiotic Lactobacillus to restore the vaginal microenvironment, synergistically inhibiting VVC.

Abstract

Natural products are a crucial resource for drug discovery, but poor understanding of the molecular-scale mechanisms of their self-assembly into soluble, bioavailable hydrogels limits their applications and therapeutic potential. It is demonstrated that Zingibroside R1 (ZR1), derived from Panax notoginseng, undergoes spontaneous self-assemble into a hydrogel comprising helical nanofibrils with potent antifungal activity lacking in its monomeric state. Cryogenic electron microscopy (cryo-EM) revealed an intricate hydrogen-bonding network that facilitates ZR1 nanofibril formation, characterized by a hydrophobic core and hydrophilic exterior architecture, which underpin its binding activity with cell wall in the vulvovaginal candidiasis (VVC) pathogen, C. albicans. The hydrogen-bonding interface between ZR1 gel and glucan compromises membrane integrity, inhibiting C. albicans proliferation in vitro and in VVC model mice in vivo. ZR1 gel could also deliver probiotic Lactobacillus, synergistically inhibiting VVC and restoring the vaginal microenvironment. This study advances the mechanistic understanding of ZR1's structure-function relationships, offering valuable insights into the rational design and therapeutic optimization of natural product-based hydrogels.

A new kind of “crosslinked hetero-chain polymeric CEI” (CHP-CEI) is particularly tailored for LRMO cathode. This CHP-CEI is homogeneous and shows a balanced combination of high robustness, flexibility, and mechanical energy dissipation ability, which can not be achieved by conventional additives. Therefore, the cracking of LRMO cathode, gas release, and transition metal dissolution are largely mitigated during cycling at aggressive voltages.

Abstract

The lithium-rich manganese-based layered oxide (LRMO) cathode shows grar promise for high-energy density and environment-friendly batteries due to its cation and anion redox. However, it suffers from continuous electrolyte consumption and capacity decay, especially at high mass loadings (>10 mg cm−2). Conventional electrolyte/interphase strategies fail to address the structural characteristics of LRMO, limiting its practical application. Here, we reveal the specific requirements for cathode electrolyte interphase (CEI) of LRMO and accordingly design a non-fluorinated additive, 2,4,6-trivinyl-2,4,6-trimethylcyclotrisiloxane (TVTMS). TVTMS could form a crosslinked hetero-chain polymeric CEI (CHP-CEI) through ring-opening polymerization and ethylene group crosslinking, offering a unique balance of high robustness, flexibility, and mechanical energy dissipation, which could not be achieved by conventional additives. Therefore, the cracking of LRMO cathode, gas release and transition metal dissolution were effectively mitigated. It should be noted that, for the first time to our knowledge, we employed the single-particle aerosol mass spectrometry (SPAMS) to study CEI components, especially the organic/polymer species. The Li|LRMO cells based on CHP-CEI display a lifespan >825 cycles with remained capacity of 204 mAh g−1 and the cells with high-loading cathode (12 mg cm−2) achieve stable cycling >145 cycles with 80% capacity retention, which surpasses the performance of previously reported electrolytes.

Light-induced membraneless organelles (MLOs) are formed in artificial cells upon light irradiation. The enrichment of iNOS+ in MLOs increases the production rate of NO 3.2 times of that without MLOs. Artificial cells containing light-induced MLOs are utilized to treat melanoma efficiently.

Abstract

Membraneless organelles (MLOs) formed by liquid–liquid phase separation exhibit diverse important biofunctions in cells. The construction of artificial cells containing MLOs with enhanced complexity and functions is still challenging. Here a light-responsive protein, Cry2olig-IDRs, is designed and purified to form MLOs upon light (488 nm) irradiation. They are capable of rapidly recruiting positively charged inducible nitric oxide synthase (iNOS+) from surroundings to regulate its activity for NO production. NO-artificial cells are constructed by encapsulating Cry2olig-IDRs and iNOS+ into giant unilamellar vesicles, which are capable of rapid production of NO with high concentration due to the formation of MLOs upon light irradiation. NO-artificial cells are confirmed to possess the ability for melanoma tumor therapy in mice. These findings provide an efficient method for remotely regulating enzyme activity inside artificial cells, paving the path to build more sophisticated artificial cells for their biomedical applications.

A vaccine (Bif-OVA-Ocur) is designed to target gut-associated lymphoid tissues, promoting the maturation of dendritic cells (DCs) and the expansion of cytotoxic T lymphocytes (CTLs) at mucosal sites. This targeted approach strengthens both mucosal and systemic immunes responses. These immune responses enable the immune system to specifically recognize and destroy tumor cells, thereby inhibiting tumor growth and progression.

Abstract

Gut-associated lymphoid tissue (GALT) possesses a highly specialized immune system and is rational as a foothold for oral tumor vaccines. Here, a noninvasive oral vaccine (Bif-OVA-Ocur) is designed to engage GALT, inducing both intestinal mucosal and systemic immunity for tumor therapeutics. The vaccine uses Bifidobacterium (Bif) as a delivery vehicle for tumor antigen peptides, which are coated with antigen peptides (OVA) and oxidized curdlan (Ocur) in a layer-by-layer (LBL) manner. Upon oral administration, Bif-OVA-Ocur is efficiently directed to Peyer's patches (PPs) in the intestines and further presented to antigen-presenting cells (APCs), which then migrate to the mesenteric lymph nodes (MLNs) to evoke specific T cell responses. In mouse models, Bif-OVA-Ocur effectively boosts the production of secretory immunoglobin A (SIgA) and promotes a strong mucosal and systemic immune response, leading to significant tumor suppression and resistance to tumor challenges. Importantly, the vaccine shows no systemic toxicity. This approach to harnessing the intestinal mucosal immune system offers valuable insights for the development of other non-invasive oral vaccines and therapeutic agents.

Two enantiomeric pairs of alloy clusters composed of two Pt2Ag4 monomer are synthesized. Chiral structural transformations occurred in response to solvent stimuli, concomitant with high-contrast chiroptical switching. By manipulation of such chiral clusters, a chiral cubic lattice with high-efficiency circularly polarized luminescence is achieved. Further, the application in the information encryptions is explored.

Abstract

Establishing atom-precise and controllable self-assembly of metal clusters to achieve high-efficiency circularly polarized luminescence (CPL) is especially fascinating, yet it creates considerable challenges. Here, two enantiomeric pairs of dimer clusters R/S-Pt4Ag8-green and R/S-Pt4Ag8-orange composed of two octahedral Pt2Ag4 monomers through Pt–Pt bonds are constructed, which show a 28-fold increase in photoluminescence quantum yield (PLQY) compared with the reported monomer in solution. The solid-state chiral dimer R/S-Pt4Ag8-orange shows a PLQY of 87% without an aggregation-caused quenching effect. The intercluster distances and arrangements of the chiral cluster can be modulated through the ligand configuration and solvent stimuli, giving rise to the reversible transformations between chiral single crystals, concomitant with high-contrast optical/chiroptical switching. Additionally, by further assembling chiral Pt-Ag clusters with Ag+, a chiral 3D cubic lattice with high-efficiency red-emitting CPL is achieved. Furthermore, high-efficiency luminescence, intrinsic chirality, and the adjustable assembly behaviors of these chiral cluster assemblies bestow them with excellent smart CPL switching properties. This work opens a new avenue for high-efficiency CPL-active metal clusters by regulating metal-metal interactions.

Porous carbons with tunable pore sizes are synthesized to investigate the impact of pore size on charge storage in Zn-ion hybrid capacitors. An unusual multi-stage charge storage mechanism is revealed, involving a transition from capacitive Zn2+ ion storage to faradaic Had adsorption on the carbon surface, providing new insights into Zn-ion electrochemistry.

Abstract

Zn-ion hybrid capacitors (ZIHCs) are promising high-power energy storage devices. However, the underlying charge storage mechanisms, especially the influence of proton storage, remain poorly understood. Herein, the model porous carbons are synthesized having similar specific surface areas (SSAs) and surface chemistry but different pore sizes. They highlight the role of supermicropores and small mesopores (0.86–4 nm) enabling a high capacity of 198 mAh g−1 (capacitance of 446 F g−1), while larger mesopores (4–13 nm) significantly enhance cycling stability, exceeding 0.6 million cycles. Electrochemical studies, including EQCM analysis, reveal a 4-stage charge-storage process under cathodic polarization, comprising adsorption and desolvation of hydrated Zn2+ ions, followed by water reduction, catalyzed by Zn2+, and formation of Had. The rising pH leads to the formation of insoluble zinc hydroxysulfate hydrates (ZHS). Depending on the pore architecture, the precipitation of ZHS has different effects on the overall stability of cycling. The study overall: (i) presents a simplified method for pore control in carbon synthesis; (ii) discuss the effect of pore size on charge storage and cycling stability in respect of ZHS formation; (iii) sheds light on the charge storage mechanism indicating the important contribution of cation effect known from electrocatalysis on faradaic charge storage mechanism.

A machine learning procedure combined with an artificial intelligence (AI) model are used to accelerate the generation of ammonium ligands (ALs) in 2D perovskites. The relationship between the carrier transport barrier and the structure of ALs is explored. Utilizing the AI-designed ALs significantly enhances the carrier transport of the 2D perovskites, leading to high-efficiency and stable 2D/3D perovskite solar cells.

Abstract

The 2D/3D heterojunction perovskite solar cells (PSCs) exhibit remarkable stability, but the quantum well in the 2D perovskite capping layer hinders the carrier transport, thereby lowering the power conversion efficiency (PCE). The relationship between the transport barrier and the complex structure of ammonium ligands (ALs) is currently poorly understood, thus leading to the one-sided approach and inefficient process in the development of 2D perovskite. Here, a machine learning procedure is established to comprehensively explore the relationship and combined it with an artificial intelligence (AI) model based on reinforcement learning algorithm to accelerate the generation of ALs. Finally, the AI-designed ALs improved the carrier transport performance of the 2D perovskite capping layer, and we achieved a certified PCE of 26.12% in inverted PSCs. The devices retained 96.79% of the initial PCE after 2000 h operation in maximum power point tracking under 1-sun illumination at 85°C.

This study develops a light-responsive liposome Lip-CuRA that synergizes photothermal therapy (CuS/980 nm) with dual NLGN3 regulation: RuBi-GABA/UCNPs suppress NLGN3 synthesis via Cl⁻ channels, while GI254023X inhibits ADAM10-mediated release. In glioma models, this strategy blocks PI3K/Wnt pathways, reduces stemness, and prolongs survival through combined neuromodulation-photothermal effects.

Abstract

Neuronal activity is shown to potentiate glioma initiation, progression, and/or metastasis. A key mechanism in neural regulation of brain cancer involves the activity-dependent cleavage and release of the synaptic adhesion molecule neuroligin-3 (NLGN3). Here, this report describes the preparation of optogenetics-like liposome Lip-CuRA, which is used to regulate the content of NLGN3 in neurons and mediate phototherapy in cancer cells. Lip-CuRA contains upconversion nanoparticles encapsulating CuS (CuS@PUCNPs), a visible light-activated neurotransmitter prodrug RuBi-GABA, and a disintegrin and metalloproteinase (ADAM10) inhibitors GI254023X. Upon 980 nm laser irradiation, the photothermal conversion of CuS not only induces tumor cell apoptosis, but also destroys liposome structure, releasing Rubi-GABA and GI254023X. The UCNPs convert the 980 nm laser into 540 nm, activating RuBi-GABA into GABA. GABA selectively opens Cl⁻ channels in nerve cells, reducing the expression of NLGN3 and the degree of axonal connections. GI254023X inhibits the activity of the ADAM10 enzyme on the nerve surface, reducing the release of NLGN3, thereby blocking the transmission of proliferation and stemness signals. In the GL261-luc orthotopic glioma model, C6-luc orthotopic glioma model, and glioma patient-derived xenograft (PDX) model, Lip-CuRA effectively inhibits tumor recurrence, reduces glioma stemness, and extends survival through a synergistic photothermal and NLGN3-regulating therapy.