Accurate prediction of liquid chromatographic retention times is becoming increasingly important in nontargeted screening applications. Traditional retention time approaches heavily rely on the use of standard compounds, which is limited by the speed of synthesis and manufacture of standard products, and is time-consuming and labor-intensive. Recently, machine learning and artificial intelligence algorithms have been applied to retention time prediction, which show unparalleled advantages over traditional experimental methods. However, existing retention time prediction methods usually suffer from the scarcity of comprehensive training datasets, sparsity of valid data, and lack of classification in datasets, resulting in poor generalization capability and accuracy. In this study, a dataset for 10,905 compounds was constructed including their retention times. Next, an innovative classification system was implemented, classifying 10,905 compounds into a 3-tier hierarchy across 141 classes, based on functional group weighting. Then, data augmentation was performed within each category using simplified molecular input line entry system (SMILES) enumeration combined with structural similarity expansion. Finally, by training the optimal quantitative structure–retention relationship (QSRR) models for each category of compounds and selecting the best-fitting model for prediction via discriminant analysis during the prediction period, a novel and universal high-throughput retention time prediction model was established. The results demonstrate that this model achieves an R² of 0.98 and an average prediction error of 23 s, outperforming currently published models. This study provides a scientific basis for high throughput and rapid prediction of unknown pollutants, data mining, nontargeted screening, etc.

Simulated microgravity (SMG) poses substantial challenges to astronaut health, particularly impacting osteoblast function and leading to disuse osteoporosis. This study investigates the adverse effects of SMG on osteoblasts, focusing on changes in mitochondrial dynamics and their consequent effects on cellular energy metabolism and mechanotransduction pathways. We discovered that SMG markedly reduced the expression of osteoblast differentiation markers and promoted mitochondrial fission, as indicated by an increase in punctate mitochondria, a decrease in mitochondrial length, and a reduction in cristae density. These mitochondrial alterations are linked to elevated reactive oxygen species levels, a decrease in ΔΨm, and a metabolic shift from oxidative phosphorylation to glycolysis, resulting in decreased adenosine triphosphate production, which are all indicative of mitochondrial dysfunction. Our results showed that treatment with mitochondrial division inhibitor-1 (mdivi-1), a mitochondrial fission inhibitor, effectively inhibited these SMG-induced effects, thereby maintaining mitochondrial structure and function and promoting osteoblast differentiation. Furthermore, SMG disrupted critical mechanotransduction processes, by affecting paxillin expression, the RhoA–ROCK–Myosin II pathway, and actin dynamics, which subsequently altered nuclear morphology and disrupted Yes-associated protein signaling. Notably, treatment with mdivi-1 prevented these disruptions in mechanotransduction pathways. Moreover, our study showed that SMG-induced chromatin remodeling and histone methylation, which are epigenetic barriers to osteogenic differentiation, can be reversed by targeting mitochondrial fission, further highlighting the significance of mitochondrial dynamics in osteoblast function in an SMG environment. Therefore, targeting mitochondrial fission emerges as a promising therapeutic strategy to alleviate osteoblast dysfunction under SMG conditions, providing novel approaches to maintain bone health during prolonged space missions and safeguard the astronaut well-being.

Osteoarthritis (OA) is the most prevalent joint disease, yet effective disease-modifying OA drugs (DMOADs) remain elusive. Targeting macrophage polarization has emerged as a promising avenue for OA treatment. This study identified skatole through high-throughput screening as an efficient modulator of macrophage polarization. In vivo experiments demonstrated that skatole administration markedly reduced synovitis and cartilage damage in both destabilization of medial meniscus (DMM)-induced OA mice and monosodium iodoacetate (MIA)-induced OA rats. Mechanistically, skatole activated signal transducer and activator of transcription 6 (Stat6) signaling, promoting M2 macrophage polarization, while inhibiting nuclear factor-κB (NFκB) and mitogen-activated protein kinase (MAPK) signaling pathways to suppress M1 polarization. RNA-sequencing analysis, targeted metabolomics, and mitochondrial stress tests further revealed that skatole treatment shifted macrophages toward oxidative phosphorylation for energy production. Additionally, it up-regulated genes associated with glutathione metabolism and reactive oxygen species (ROS) pathways, reducing intracellular ROS production. The CUT&Tag assay results indicated that the downstream transcription factor p65 of NFκB can directly bind to gene loci related to inflammation, oxidative phosphorylation, and glutathione metabolism, thereby modulating gene expression. This regulatory process is inhibited by skatole. At the chondrocyte level, conditional medium from skatole-treated M1 macrophages balanced anabolism and catabolism in mouse chondrocytes and inhibited apoptosis. In IL1β-treated chondrocytes, skatole suppressed inflammation and catabolism without affecting apoptosis or anabolism. Overall, skatole maintains immune microenvironment homeostasis by modulating macrophage polarization in joints and preserves cartilage function by balancing chondrocyte anabolism and catabolism, effectively alleviating OA. These findings suggest skatole's potential as a DMOAD.

Excessive gonadotropin-releasing hormone (GnRH) is considered to be an initiating factor in the etiology of polycystic ovary syndrome (PCOS). GnRH neuronal axons terminate at the hypothalamic arcuate nucleus and median eminence, where tanycytes, specialized glial cells, have been proposed to modulate GnRH secretion through plasticity. However, the precise role of the “GnRH-tanycyte unit” during the pathological state of PCOS has not been thoroughly explored. In this study, we demonstrated the architecture and distribution of GnRH neurons and tanycytes. In PCOS-like mice, retracted tanycyte processes and dysregulated GnRH-tanycyte unit may create an environment conducive to the excessive secretion of GnRH and subsequent reproductive endocrine dysfunction. Mechanistically, excessive androgens impair hypothalamic neuroglial homeostasis by acting through the androgen receptor (AR) and its downstream target integrin β1 (Itgb1), thereby suppressing the FAK/TGF-βR1/Smad2 signaling pathway. Both selective deletion of AR and overexpression of Itgb1 in tanycytes counteracted the detrimental effects of androgens, alleviating endocrine dysfunction. Collectively, this study highlights the alterations in the GnRH-tanycyte unit mediated by androgen/AR/Itgb1 signaling and provides a novel perspective for developing therapies for hypothalamic hormone secretion disorders by maintaining solid neuroglial structures in the brain.

The prevention of air pollution-related cardiopulmonary disorders has been largely overlooked despite its important burden. Extracellular vesicles (EVs) have shown great potential as carriers for drug delivery. However, the efficiency and effect of EVs derived from different sources on ambient fine particulate matter (PM2.5)-induced cardiopulmonary injury remain unknown. Using PM2.5-exposed cellular and mouse models, we investigated the prevention of air pollution-related cardiopulmonary injury via an innovative strategy based on EV delivery. By using a “2-step” method that combines bibliometric and bioinformatic analysis, we identified superoxide dismutase 2 (Sod2) as a potential target for PM2.5-induced injury. Sod2-overexpressing plasmid was constructed and loaded into human plasma-, bovine milk-, and fresh grape-derived EVs, ultimately obtaining modified nanoparticles including PEV^Sod2, MEV^Sod2, and GEV^Sod2, respectively. GEV^Sod2, especially its lyophilized GEV^Sod2 powder, exhibited superior protection against PM2.5-induced cardiopulmonary injury as compared to PEV^Sod2 and MEV^Sod2. High-sensitivity structured illumination microscopy imaging and immunoblotting showed that GEV^Sod2 powder treatment altered lysosome positioning by reducing Rab-7 expression. Our findings support the use of fruit-derived EVs as a preferred candidate for nucleic acid delivery and disease treatment, which may facilitate the translation of treatments for cardiopulmonary injuries.

Nanozymes are a class of nanomaterials that exhibit catalytic functions analogous to those of natural enzymes. They demonstrate considerable promise in the biomedical field, particularly in the treatment of bone infections, due to their distinctive physicochemical properties and adjustable catalytic activities. Bone infections (e.g., periprosthetic infections and osteomyelitis) are infections that are challenging to treat clinically. Traditional treatments often encounter issues related to drug resistance and suboptimal anti-infection outcomes. The advent of nanozymes has brought with it a new avenue of hope for the treatment of bone infections.

Understanding long-term historical changes in cloudiness is essential for elucidating Earth's climate dynamics and variability and its extremes. In this study, we present the first millennial-length reconstruction of the annual total cloud cover (TCC) in the western Mediterranean, covering the period from 969 to 2022 CE. Based on a comprehensive set of hydrological and atmospheric variables, our reconstruction reveals a nuanced pattern of cloudiness evolution over the past millennium. We observe an initial increase in cloudiness until 1600 CE, followed by a substantial decrease in TCC. This shift was driven by a confluence of factors, including the eruption of Mount Tambora in Indonesia in 1815, increased solar forcing, and a positive phase of the Atlantic Multidecadal Oscillation. These complex dynamics have brought modern warming cloud patterns closer to those observed during the medieval period before c. 1250, exceeding the background variability of the Little Ice Age (c. 1250 to 1849). In particular, recent decades have witnessed an unprecedented coupling of intense solar activity, high temperatures, and the lowest cloud cover on record. Our results highlight the importance of inter-oceanic-scale relationships between Atlantic forcing mechanisms and the TCC in shaping future trends in western Mediterranean cloudiness. This study provides valuable insights into the long-term dynamics of cloudiness and its implications for regional climate trends in the western Mediterranean and beyond.

Emerging evidence highlights the central role of gut microbiota in maintaining physiological homeostasis within the host. Disruptions in gut microbiota can destabilize systemic metabolism and inflammation, driving the onset and progression of cardiometabolic diseases. In heart failure (HF), intestinal dysfunction may induce the release of endotoxins and metabolites, leading to dysbiosis and exacerbating HF through the gut–heart axis. Understanding the relationship between gut microbiota and HF offers critical insights into disease mechanisms and therapeutic opportunities. Current research highlights promising potential to improve patient outcomes by restoring microbiota balance. In this review, we summarize the current studies in understanding the gut microbiota–HF connection and discuss avenues for future investigation.

Biomimetic dry adhesive structures, inspired by geckos' climbing abilities, have attracted research attention in recent years. However, achieving superior adhesion on a rough surface remains an important challenge, which limits practical applications. Conventional bionic adhesion methods perform well on smooth surfaces, but adhesion strength drastically decreases on rough surfaces due to the reduced contact area. Generally, various adhesive structures have been proposed to increase the contact area without assessing adhesion states, against obtaining good performance on rough surfaces. If an intelligent adhesive approach could be introduced on rough surfaces, it would be beneficial for promoting the development of gecko-inspired adhesives. However, existing adhesive structures with the sensing function usually utilize the adhesive function to support the sensing function, i.e., a sensor with an adhesive function; for other few structures, the sensing function supports adhesion, but they do not focus on improving adhesion performance on rough surfaces. Inspired by the synergistic effect of a kinematic system during the crawling process of geckos, this study proposes an intelligent adhesive structure for rough surfaces. The proposed structure combines a hierarchical bionic dry adhesive structure based on gecko paw microhairs with a flexible capacitive sensor unit. Experimental observations and analytical modeling demonstrate that incorporating mushroom-shaped bionic dry adhesive structures with inclined support micropillars can reduce interface contact stiffness, notably enhancing adhesion on rough surfaces while allowing real-time monitoring of contact states. Moreover, this innovative smart adhesive structure facilitates morphology sensing of contact interfaces, presenting potential advancements in bionic adhesion for morphology sensing applications.

Marine biofouling causes severe economical and environmental challenges to marine industries and maritime activities. Biofouling prevention has emerged as one of the most pressing issues in water-related industries. Recently, the slippery liquid-infused porous surfaces (SLIPSs) have shown great potential for biofouling prevention across a broad spectrum of fouling organisms. However, our understanding of the mechanisms by which SLIPSs prevent biofouling remains limited. In this study, we discovered that oil-infused polydimethylsiloxane elastomer (i-PDMS), a silicone-based SLIPS variant, significantly inhibited the sensory responses of the fouling mussel Mytilopsis sallei, particularly at its sensory organ, the foot. Using bioinformatics and molecular biology analyses, we demonstrated that i-PDMS disrupts larval settlement of M. sallei by interfering with the mechanosensitive transient receptor potential melastatin-subfamily member 7 (TRPM7) channel, which is highly expressed in the foot during the settlement process. Furthermore, adhesion assays and molecular dynamics simulations revealed that the secreted foot proteins of the mussel are unable to effectively interact with the i-PDMS surface due to nanoscale fluctuations at the material interface. These findings enhance our understanding of how fouling organisms sense and adhere to surfaces and provide deeper insights into the antifouling mechanisms of SLIPS.