Aggregation-Induced Emission (AIE), Life and Health

Light has profoundly impacted modern medicine and healthcare, with numerous luminescent agents and imaging techniques currently being used to assess health and treat diseases. As an emerging concept in luminescence, aggregation-induced emission (AIE) has shown great potential in biological applications due to its advantages in terms of brightness, biocompatibility, photostability, and positive correlation with concentration. This review provides a comprehensive summary of AIE luminogens applied in imaging of biological structure and dynamic physiological processes, disease diagnosis and treatment, and detection and monitoring of specific analytes, followed by representative works. Discussions on critical issues and perspectives on future directions are also included. This review aims to stimulate the interest of researchers from different fields, including chemistry, biology, materials science, medicine, etc., thus promoting the development of AIE in the fields of life and health

Accelerating thermokarst lake changes on the Qinghai–Tibetan Plateau

Abstract As significant evidence of ice-rich permafrost degradation due to climate warming, thermokarst lake was developing and undergoing substantial changes. Thermokarst lake was an essential ecosystem component, which significantly impacted the global carbon cycle, hydrology process and the stability of the Qinghai–Tibet Engineering Corridor. In this paper, based on Sentinel-2 (2021) and Landsat (1988–2020) images, thermokarst lakes within a 5000 m range along both sides of Qinghai–Tibet Highway were extracted to analyse the spatio-temporal variations. The results showed that the number and area of thermokarst lake in 2021 were 3965 and 4038.6 ha (1 ha = 10,000 m $$^{2}$$ 2 ), with an average size of 1.0186 ha. Small thermokarst lakes ( $$\,$$ > 10 ha) occupied for 44.92% of the whole lake area. In all sub-regions, the number of small lake far exceeds 75% of the total lake number in each sub-region. R1 sub-region (around Wudaoliang region) had the maximum number density of thermokarst lakes with 0.0071, and R6 sub-region (around Anduo region) had the minimum number density with 0.0032. Thermokarst lakes were mainly distributed within elevation range of 4300 m–5000 m a.s.l. (94.27% and 97.13% of the total number and size), on flat terrain with slopes less than 3 $$^\circ$$ ∘ (99.17% and 98.47% of the total number and surface) and in the north, south, and southeast aspects (51.98% and 50.00% of the total number and area). Thermokarst lakes were significantly developed in warm permafrost region with mean annual ground temperature (MAGT) > − 1.5  $$^\circ$$ ∘ C, accounting for 47.39% and 54.38% of the total count and coverage, respectively. From 1988 to 2020, in spite of shrinkage or even drain of small portion of thermokarst lake, there was a general expansion trend of thermokarst lake with increase in number of 195 (8.58%) and area of 1160.19 ha (41.36%), which decreased during 1988–1995 (− 702 each year and − 706.27 ha/yr) and then increased during 1995–2020 (184.96–702 each year and 360.82 ha/yr). This significant expansion was attributed to ground ice melting as rising air temperature at a rate of 0.03–0.04  $$^\circ$$ ∘ C/yr. Followed by the increasing precipitation (1.76–3.07 mm/yr) that accelerated the injection of water into lake

Modular characterization of SARS-CoV-2 nucleocapsid protein domain functions in nucleocapsid-like assembly

Abstract SARS-CoV-2 and its variants, with the Omicron subvariant XBB currently prevailing the global infections, continue to pose threats on public health worldwide. This non-segmented positive-stranded RNA virus encodes the multi-functional nucleocapsid protein (N) that plays key roles in viral infection, replication, genome packaging and budding. N protein consists of two structural domains, NTD and CTD, and three intrinsically disordered regions (IDRs) including the NIDR, the serine/arginine rich motif (SRIDR), and the CIDR. Previous studies revealed functions of N protein in RNA binding, oligomerization, and liquid–liquid phase separation (LLPS), however, characterizations of individual domains and their dissected contributions to N protein functions remain incomplete. In particular, little is known about N protein assembly that may play essential roles in viral replication and genome packing. Here, we present a modular approach to dissect functional roles of individual domains in SARS-CoV-2 N protein that reveals inhibitory or augmented modulations of protein assembly and LLPS in the presence of viral RNAs. Intriguingly, full-length N protein (NFL) assembles into ring-like architecture whereas the truncated SRIDR-CTD-CIDR (N182-419) promotes filamentous assembly. Moreover, LLPS droplets of NFL and N182-419 are significantly enlarged in the presence of viral RNAs, and we observed filamentous structures in the N182-419 droplets using correlative light and electron microscopy (CLEM), suggesting that the formation of LLPS droplets may promote higher-order assembly of N protein for transcription, replication and packaging. Together this study expands our understanding of the multiple functions of N protein in SARS-CoV-2

RNA target highlights in CASP15: Evaluation of predicted models by structure providers

The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures. For one target, experimentalists were able to phase their x-ray diffraction data by molecular replacement, showing a potential application of structure predictions for RNA structural biologists. Recommended areas for improvement include: enhancing the accuracy in local interaction predictions and increased consideration of the experimental conditions such as multimerization, structure determination method, and time along folding pathways. The prediction of RNA-protein complexes remains the most significant challenge. Finally, given the intrinsic flexibility of many RNAs, we propose the consideration of ensemble models