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Development of photothermal materials which are able to harness sunlight and convert it to thermal energy seems attractive. Besides carbon-based nanomaterials, conjugated polymers are emerging promising photothermal materials but their facile syntheses remain challenging. In this work, by modification of a CBT-Cys click condensation reaction and rational design of the starting materials, we facilely synthesize conjugated polymers poly-2-phenyl-benzobisthiazole (PPBBT) and its dihexyl derivative with good photothermal properties. Under the irradiation of either sunlight-mimicking Xe light or near-infrared laser, we verify that PPBBT has comparable photothermal heating-up speed to that of star material single-wall carbon nanotube. Moreover, PPBBT is used to fabricate water-soluble NP PPBBT nanoparticles which maintain excellent photothermal properties in vitro and photothermal therapy effect on the tumours exposed to laser irradiation. We envision that our synthetic method provides a facile approach to fabricate conjugated polymers for more promising applications in biomedicine or photovoltaics in the near future. Conjugated polymers are of interest for photothermal applications; however, synthesis of these polymers can be complex. Here, the authors report on a facile synthesis method that uses a modified CBT-Cys click reaction to make conjugated polymers and test these polymers for photothermal therapy applications.

Orbital inflammation is a prevalent and prolonged ocular disease that poses a significant challenge to clinicians. Glucocorticoid Dexamethasone sodium phosphate (Dex) has demonstrated efficacy in the clinical treatment of nonspecific orbital inflammation. However, frequent administration is required due to the short half-life of Dex, which may lead to drug waste and adverse side effects. In this study, we co-assembled Dex with a weak acid responsive hydrogelator Py-Phe-Phe-Lys-Lys-OH (K) to obtain a novel supramolecular hydrogel Dex/K that could release Dex in a slow manner to treat orbital inflammation. The therapeutic effect of Gel Dex/K on orbital inflammation was verified by and experiments. experiments indicated that co-assembly of Dex with K significantly increased mechanic strength of the hydrogel, enabling a continuous release of 40% of total Dex within 7 days. experiments further demonstrated that sustained release of Dex from Gel Dex/K could effectively alleviate the infiltration of inflammatory cells and the release of inflammatory factors in the orbit of mice, improving symptoms such as increased intraocular pressure and proptosis. Additionally, Gel Dex/K mitigated the degree of tissue fibrosis and fatty infiltration by reducing the development of local inflammation in the orbit. Our research results indicate that Gel Dex/K could more efficiently achieve responsive drug release in orbit, providing an innovative method for treating orbital inflammation.

Alzheimer’s disease (AD) is the most common cause of dementia characterized by amyloid-β (Aβ) deposition, tau hyperphosphorylation, and neuroinflammation. Naringenin (NRG), a natural flavonoid widely present in citrus fruits, has been reported can penetrate the blood-brain barrier and exert anti-inflammatory effects in the central nervous system. Here, we investigate the protective effects of long-term NRG treatment on AD. The novel object recognition test and Morris water maze test reveal that NRG treatment can improve the learning and memory ability of APP/PS1 mice. Besides, we find that NRG can significantly reduce Aβ deposition, microglial and astrocytic activation, and pro-inflammatory cytokine levels in APP/PS1 mice. Results further show that NRG effectively decreases pro-inflammatory cytokines in LPS/Aβ-stimulated BV2 cells. Lastly, the molecular mechanistic study reveals that NRG attenuates neuroinflammatory responses via inhibition of the MAPK signaling pathway in vivo and in vitro. Overall, NRG may emerge as a promising compound for the prevention and treatment of AD. A study reveals the protective effects of long-term naringenin treatment on Alzheimer’s disease, including reducing Aβ deposition, decreasing neuroinflammatory responses, and improving cognitive function

Straw return plays a pivotal role in sustaining soil fertility and crop production, but the interaction between straw return and consecutive fertilizer applications on yield sustainability and soil quality under climate change are unclear. Therefore, a long-term field experiment (2005–2022) was conducted to examine how straw return and fertilizer application improve soil properties, increase crop production, enhance the ability to resist climatic changes, and thus improve yield sustainability in a rice (Oryza sativa L.)–wheat (Triticum aestivum L.) cropping system. This study established five treatments, including the control, NPK treatment, S treatment, NPK + 1/2S treatment, and NPK + S treatment. Compared with the control, the treatments involving chemical fertilization combined with straw return increased on average rice and wheat yield by 52.9% and 95.4%, respectively, with higher values of the sustainable yield index (SYI) and lower values of the coefficient of variance (CV) for the two crops. Moreover, the treatments that combined chemical fertilization with straw return improved soil quality by increasing soil organic matter (SOM), total N, total P, and available K contents and presented a higher soil quality index (SQI) value compared to the other three treatments. The crop yield, SYI, and apparent nutrient balance increased with increasing SQI. The SOM and AP were identified as the most crucial soil fertility indices, exerting a significant impact on crop yields. Meanwhile, precipitation emerged as the key meteorological factor restricting the yield of winter wheat. The PLS-SEM suggested that fertilizer application, climatic conditions, and soil properties strongly influenced crop yield, and the magnitude of this influence varies between rice and wheat. In conclusion, the long-term fertilization combined with straw return represents an effective strategy to safeguard the sustainability of crop yields under climate change.

Abstract The early diagnosis of colon cancer is crucial for enhancing patient survival rates. Computer-aided image segmentation technology offers a significant tool for assisting physicians in quickly and accurately identifying cancerous tissues, serving as an effective means of auxiliary diagnosis. However, traditional image segmentation algorithms often encounter limitations in their optimization capabilities when processing complex images, struggling to meet the requirements for efficiency and precision. This study introduces an improved multiverse optimization algorithm, which, by incorporating information-sharing search and spiraling communication and collaboration strategies, aims to enhance the search efficiency and solution quality of the algorithm, thereby more effectively addressing the challenges of colon cancer image segmentation. Initially, using the CEC 2017 benchmark function test set, the proposed algorithm was compared to 11 meta-heuristics and 11 state-of-the-art algorithms, respectively, achieving the best rankings of 2.22 and 2.72 for the Friedman test. Subsequently, the proposed algorithm was applied to the task of multithreshold segmentation of colon cancer images. Compared to existing algorithms, the proposed algorithm achieved higher quality image segmentation results and stronger robustness at both high and low thresholds using feature similarity index, peak signal-to-noise ratio, and structural similarity index. This validates the effectiveness and superiority of the proposed algorithm in addressing the challenges of colon cancer image segmentation. Graphical Abstract Graphical Abstract Multiverse optimization with information sharing and spiraling communication for colon cancer image segmentation

Aging impairs skeletal muscle mass and function, but the cell‐type–resolved transcriptional states and intercellular signaling changes in human muscle aging remain incompletely mapped. Here, we constructed a single‐nucleus RNA sequencing (snRNA‐seq) atlas of human vastus lateralis muscle from adult (22–60 years) and elderly (99–101 years) male donors. We identified a comprehensive cellular census and discovered a profound reorganization of the myofiber transcriptional landscape. Aging was characterized by a shift from robust “young” states (MYLK4+ type II, LRP1B+ type I fibers) to dysfunctional “old” states (RYR3+ type II, RYR3+ type I fibers), accompanied by a marked emergence of hybrid fiber subtypes. We mechanistically linked these hybrid fibers to key aging pathologies: RUNX1+ hybrid fibers displayed a transcriptional signature of denervation, while SAA1+ hybrid fibers exhibited features of fatty infiltration, correlated with an expansion of fibro/adipogenic progenitors (FAPs). Pseudotime trajectory analysis supported the progression from young to degenerative or adipogenic fates. The aged microenvironment was globally altered, featuring impaired metabolic activity in muscle stem cells, compromised immune surveillance and function decline of vascular compartments. Critically, cell–cell communication analysis revealed enhanced BMP and Laminin signaling from FAPs to myofibers in aged tissue. Our work provided a high‐resolution roadmap of human skeletal muscle aging, establishing denervation and FAP‐driven fatty infiltration as key cellular mechanisms driving functional decline, and revealing novel targets for therapeutic intervention. Aging was characterized by a state transition, accompanied by denervation and fatty infiltration. The aged microenvironment was globally altered. BMP and Laminin signaling were involved in enhanced FAPs communicating to myofibers.

In order to deal with the global energy crisis and environmental problems, reducing carbon dioxide through artificial photosynthesis has become a hot topic. Lead halide perovskite is attracted people's attention because of its excellent photoelectric properties, but the toxicity and long‐term instability prompt people to search for new photocatalysts. Herein, a series of inorganic double perovskites Cs4Mn1‐xCuxSb2Cl12 microcrystals (x = 0, 0.1, 0.2, 0.3, 0.4, and 0.5) are synthesized and characterized. Among them, Cs4Mn0.7Cu0.3Sb2Cl12 microcrystals have the best photocatalytic performance, and the yields of CO and CH4 are 503.86 and 68.35 µmol g−1, respectively, after 3 h irradiation, which are the highest among pure phase perovskites reported so far. In addition, in situ Fourier transform infrared (FT‐IR) spectroscopy and electron spin resonance (ESR) spectroscopy are used to explore the mechanism of the photocatalytic reaction. The results highlight the potential of this class of materials for photocatalytic reduction reactions. In this paper, a series of inorganic double perovskite Cs4Mn1‐xCuxSb2Cl12 microcrystals are synthesized, and their photocatalytic efficiency is improved by introducing Cu element, and their photoelectric properties are significantly enhanced. After various stability tests, the photocatalyst maintained good stability. Furthermore, in situ FT‐IR spectroscopy and ESR spectroscopy are adopted to precisely unraveled active sites, reaction intermediates, and photocatalytic reduction process.

Due to the varieties, random distributions, and rich visual characteristics of the volcanic disaster scene, traditional methods fail to fully express the complex features of volcanic disaster scenes in remote sensing images. To tackle this problem, a new multi-instance network framework with the Shift Windows Transformer (i.e., Swin-T) and attention mechanism is used to classify the volcanic disaster scene from remote sensing images (MI-STA). Firstly, via aggregating the global contextual information of remote sensing image features, the Swin-T extracts the multi-scale hierarchical features of volcano disaster scenes from remote sensing images. Secondly, the channel attention module and spatial attention module fuse to extract the features of volcanic disaster scene to enhance the description and representation for the local details and global information in volcanic disaster scenes. Last, the importance weight of different example characteristics is scored to calculate the attributive probabilities of each instance. This study elaborates an experiment on the xBD dataset and gives comparisons with the commonly used deep network models. The results show that the overall classification accuracy of the proposed method achieves 92.46% and has good performance on the test dataset. Then, we further utilize our model to classify the volcanic disaster scenes of the specific Hunga Tonga-Hunga Ha’apai on January 15, 2022, and the classification images have good consistency with the existing literature. It provides a new approach for volcanic disaster monitoring by means of remote sensing image and has broad application prospects.

Straw return plays a pivotal role in sustaining soil fertility and crop production, but the interaction between straw return and consecutive fertilizer applications on yield sustainability and soil quality under climate change are unclear. Therefore, a long-term field experiment (2005–2022) was conducted to examine how straw return and fertilizer application improve soil properties, increase crop production, enhance the ability to resist climatic changes, and thus improve yield sustainability in a rice (Oryza sativa L.)–wheat (Triticum aestivum L.) cropping system. This study established five treatments, including the control, NPK treatment, S treatment, NPK + 1/2S treatment, and NPK + S treatment. Compared with the control, the treatments involving chemical fertilization combined with straw return increased on average rice and wheat yield by 52.9% and 95.4%, respectively, with higher values of the sustainable yield index (SYI) and lower values of the coefficient of variance (CV) for the two crops. Moreover, the treatments that combined chemical fertilization with straw return improved soil quality by increasing soil organic matter (SOM), total N, total P, and available K contents and presented a higher soil quality index (SQI) value compared to the other three treatments. The crop yield, SYI, and apparent nutrient balance increased with increasing SQI. The SOM and AP were identified as the most crucial soil fertility indices, exerting a significant impact on crop yields. Meanwhile, precipitation emerged as the key meteorological factor restricting the yield of winter wheat. The PLS-SEM suggested that fertilizer application, climatic conditions, and soil properties strongly influenced crop yield, and the magnitude of this influence varies between rice and wheat. In conclusion, the long-term fertilization combined with straw return represents an effective strategy to safeguard the sustainability of crop yields under climate change.

We propose a novel approach for low-light image enhancement. Based on illumination-reflection model, the guided image filter is employed to extract the illumination component of the underlying image. Afterwards, we obtain the reflection component and enhance it by nonlinear functions, sigmoid and gamma, respectively. We use the first-order edge-aware constraint in the gradient domain to achieve good edge preserving features of enhanced images and to eliminate halo artefact effectively. Moreover, the resulting images have high contrast and ample details due to the enhanced illumination and reflection component. We evaluate our method by operating on a large amount of low-light images, with comparison with other popular methods. The experimental results show that our approach outperforms the others in terms of visual perception and objective evaluation.