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Abstract Bystander‐killing payloads can significantly overcome the tumor heterogeneity issue and enhance the clinical potential of antibody‐drug conjugates (ADC), but the rational design and identification of effective bystander warheads constrain the broader implementation of this strategy. Here, graph attention networks (GAT) are constructed for a rational bystander killing scoring model and ADC construction workflow for the first time. To generate efficient bystander‐killing payloads, this model is utilized for score‐directed exatecan derivatives design. Among them, Ed9, the most potent payload with satisfactory permeability and bioactivity, is further used to construct ADC. Through linker optimization and conjugation, novel ADCs are constructed that perform excellent anti‐tumor efficacy and bystander‐killing effect in vivo and in vitro. The optimal conjugate T‐VEd9 exhibited therapeutic efficacy superior to DS‐8201 against heterogeneous tumors. These results demonstrate that the effective scoring approach can pave the way for the discovery of novel ADC with promising bystander payloads to combat tumor heterogeneity.

Abstract The power generation of the photovoltaic plant is related to the cleanliness of the photovoltaic modules. The accumulation of natural dust is the main source of pollution, which is affected by human activities and meteorological factors such as temperature, humidity, wind speed, and rainfall concentration in the current region. On the basis of particle swarm optimization (PSO) and the least‐squares support vector machine (LSSVM), the density of dust on photovoltaic modules was estimated. The authors proposed that the inertia weight decreased as a concave function to improve the efficiency of optimization and let the two positive constants change dynamically to improve convergence performance. The dust accumulation prediction model was established considering natural rainfall and the authors obtained the attenuation rate of the photovoltaic power output. Finally, the experiments in Hangzhou showed that the model can predict the density of accumulated dust quickly, which provides a theory for predicting PV power generation and managing the cleaning frequency.

Abstract Cetirizine hydrochloride (CTZ), an antiallergic drug, is a new‐generation H1 receptor antagonist and a second‐generation H1 antihistamine. We aimed to prepare cetirizine hydrochloride liposomes, based on which cetirizine hydrochloride liposomal (CTZL) in situ gel (ISG) was prepared, to improve the retention time in the eye. CTZL were prepared by the ethanol injection method combined with the ammonium sulfate gradient method. A CTZ liposomal temperature‐sensitive gel was prepared using the cold dissolution method. Large‐eared white rabbits were used in retention and irritation experiments. The liposomes were small single‐chambered liposomes, spherical or sphere‐like, with a vesicle size of 187.03 ± 6.20 nm, an encapsulation efficiency of 70.39 ± 1.13%, and a drug loading capacity of 4.63 ± 0.06%. The gelling temperatures before and after dilution by simulated tear fluid were 26.1 ± 0.2°C and 34.2 ± 0.2°C, the vesicle size was 184.94 ± 7.28 nm, and the liposomes were spherical or sphere‐like in the gel matrix. The in vitro dissolution and release experiments indicate that the gel was released upon dissolution and exhibited a zero‐level release pattern. Preparation into liposomes and liposomal gels prolonged the ocular retention time of the formulation without ocular irritation.