Indigo: a natural molecular passivator for efficient perovskite solar cells

Organic–inorganic hybrid lead halide perovskite solar cells have made unprecedented progress in improving photovoltaic efficiency during the past decade, while still facing critical stability challenges. Herein, the natural organic dye Indigo is explored for the first time to be an efficient molecular passivator that assists in the preparation of high-quality hybrid perovskite film with reduced defects and enhanced stability. The Indigo molecule with both carbonyl and amino groups can provide bifunctional chemical passivation for defects. In-depth theoretical and experimental studies show that the Indigo molecules firmly binds to the perovskite surfaces, enhancing the crystallization of perovskite films with improved morphology. Consequently, the Indigo-passivated perovskite film exhibits increased grain size with better uniformity, reduced grain boundaries, lowered defect density, and retarded ion migration, boosting the device efficiency up to 23.22%, and ˜21% for large-area device (1 cm2). Furthermore, the Indigo passivation can enhance device stability in terms of both humidity and thermal stress. These results provide not only new insights into the multipassivation role of natural organic dyes but also a simple and low-cost strategy to prepare high-quality hybrid perovskite films for optoelectronic applications based on Indigo derivatives.Peer ReviewedPostprint (author's final draft

Integrating transcriptomics and metabolomics to analyze the mechanism of hypertension-induced hippocampal injury

ObjectiveHypertension is a public health challenge worldwide due to its high prevalence and multiple complications. Hypertension-induced damage to the hippocampus leads to behavioral changes and various brain diseases. Despite the multifaceted effects of hypertension on the hippocampus, the mechanisms underlying hippocampal lesions are still unclear.MethodsThe 32-week-old spontaneously hypertensive rats (SHR) and Wistar-Kyoto (WKY) rats were selected as the study subjects. Behavioral experiments such as an open field test (OFT), an elevated plus maze (EPM) test, and the Morris water maze (MWM) test were performed to show the behavioral characteristics of the rats. A comprehensive transcriptomic and metabolomic analysis was performed to understand the changes in the hippocampus at the metabolic and genetic levels.ResultsBehavioral tests showed that, compared to WKY rats, SHR showed not only reduced memory capacity but more hyperactive and impulsive behavior. In addition, transcriptomic analysis screened for 103 differentially expressed genes. Metabolomic analysis screened 56 metabolites with significant differences, including various amino acids and their related metabolites.ConclusionComprehensive analysis showed that hypertension-induced hippocampal lesions are closely associated with differential metabolites and differential genes detected in this study. The results provide a basis for analyzing the mechanisms of hypertension-induced hippocampal damage

Interaction between microbiota and immunity and its implication in colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer-related death in the world. Besides genetic causes, colonic inflammation is one of the major risk factors for CRC development, which is synergistically regulated by multiple components, including innate and adaptive immune cells, cytokine signaling, and microbiota. The complex interaction between CRC and the gut microbiome has emerged as an important area of current CRC research. Metagenomic profiling has identified a number of prominent CRC-associated bacteria that are enriched in CRC patients, linking the microbiota composition to colitis and cancer development. Some microbiota species have been reported to promote colitis and CRC development in preclinical models, while a few others are identified as immune modulators to induce potent protective immunity against colitis and CRC. Mechanistically, microbiota regulates the activation of different immune cell populations, inflammation, and CRC via crosstalk between innate and adaptive immune signaling pathways, including nuclear factor kappa B (NF-κB), type I interferon, and inflammasome. In this review, we provide an overview of the potential interactions between gut microbiota and host immunity and how their crosstalk could synergistically regulate inflammation and CRC, thus highlighting the potential roles and mechanisms of gut microbiota in the development of microbiota-based therapies to prevent or alleviate colitis and CRC

Cancer Stem Cells and Immunosuppressive Microenvironment in Glioma

Glioma is one of the most common malignant tumors of the central nervous system and is characterized by extensive infiltrative growth, neovascularization, and resistance to various combined therapies. In addition to heterogenous populations of tumor cells, the glioma stem cells (GSCs) and other nontumor cells present in the glioma microenvironment serve as critical regulators of tumor progression and recurrence. In this review, we discuss the role of several resident or peripheral factors with distinct tumor-promoting features and their dynamic interactions in the development of glioma. Localized antitumor factors could be silenced or even converted to suppressive phenotypes, due to stemness-related cell reprogramming and immunosuppressive mediators in glioma-derived microenvironment. Furthermore, we summarize the latest knowledge on GSCs and key microenvironment components, and discuss the emerging immunotherapeutic strategies to cure this disease

The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition

In the realm of autonomous driving, robust perception under out-of-distribution conditions is paramount for the safe deployment of vehicles. Challenges such as adverse weather, sensor malfunctions, and environmental unpredictability can severely impact the performance of autonomous systems. The 2024 RoboDrive Challenge was crafted to propel the development of driving perception technologies that can withstand and adapt to these real-world variabilities. Focusing on four pivotal tasks -- BEV detection, map segmentation, semantic occupancy prediction, and multi-view depth estimation -- the competition laid down a gauntlet to innovate and enhance system resilience against typical and atypical disturbances. This year's challenge consisted of five distinct tracks and attracted 140 registered teams from 93 institutes across 11 countries, resulting in nearly one thousand submissions evaluated through our servers. The competition culminated in 15 top-performing solutions, which introduced a range of innovative approaches including advanced data augmentation, multi-sensor fusion, self-supervised learning for error correction, and new algorithmic strategies to enhance sensor robustness. These contributions significantly advanced the state of the art, particularly in handling sensor inconsistencies and environmental variability. Participants, through collaborative efforts, pushed the boundaries of current technologies, showcasing their potential in real-world scenarios. Extensive evaluations and analyses provided insights into the effectiveness of these solutions, highlighting key trends and successful strategies for improving the resilience of driving perception systems. This challenge has set a new benchmark in the field, providing a rich repository of techniques expected to guide future research in this field.Comment: ICRA 2024; 32 pages, 24 figures, 5 tables; Code at https://robodrive-24.github.io

Multi-Objective Optimization of Envelope Structures for Rural Dwellings in Qianbei Region, China: Synergistic Enhancement of Energy Efficiency, Thermal Comfort, and Economic Viability

In China, retrofitting rural dwellings is a crucial step toward enhancing living conditions and lowering energy waste. One of the most important ways to enhance building performance is to retrofit the building envelope. The Qianbei Region’s (Northern Guizhou Province, China) rural dwellings are the subject of this study. It identifies the persistent issue of inadequate thermal comfort in local rural dwellings through indoor thermal environment measurements and questionnaire surveys. Using a parametric modelling tool (Rhino-Grasshopper-Ladybug Tools), multi-objective optimization was performed using a non-dominated sorting genetic algorithm (NSGA-II), with the types of external windows, walls, and roof insulation as optimization variables, and building energy consumption (E), annual thermal discomfort hours (TDT), and life cycle cost increment (ΔLCC) as optimization objectives. After the retrofitting, the building’s energy consumption was reduced from the baseline value of 96.41 kWh/m2 to 42.40 kWh/m2 (a 56% reduction), and the annual duration of thermal discomfort decreased from 6173 h to 5078 h (a 17.7% decrease). This resulted in a positive economic return, with a cost saving of ΔLCC = −56,329.87 CNY. The research proposes a scientific method for the energy-saving retrofitting of rural dwellings in the Qianbei Region, which also serves as a guide for the optimization of building performance in comparable climate zones