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Effective photosensitizers are of particular importance for the widespread clinical utilization of phototherapy. However, conventional photosensitizers are usually plagued by short-wavelength absorption, inadequate photostability, low reactive oxygen species (ROS) quantum yields, and aggregation-caused ROS quenching. Here, we report a near-infrared (NIR)-supramolecular photosensitizer (RuDA) via self-assembly of an organometallic Ru(II)-arene complex in aqueous solution. RuDA can generate singlet oxygen ( 1 O 2 ) only in aggregate state, showing distinct aggregation-induced 1 O 2 generation behavior due to the greatly increased singlet-triplet intersystem crossing process. Upon 808 nm laser irradiation, RuDA with excellent photostability displays efficient 1 O 2 and heat generation in a 1 O 2 quantum yield of 16.4% (FDA-approved indocyanine green: Φ Δ  = 0.2%) together with high photothermal conversion efficiency of 24.2% (commercial gold nanorods: 21.0%, gold nanoshells: 13.0%). In addition, RuDA-NPs with good biocompatibility can be preferably accumulated at tumor sites, inducing significant tumor regression with a 95.2% tumor volume reduction in vivo during photodynamic therapy. This aggregation enhanced photodynamic therapy provides a strategy for the design of photosensitizers with promising photophysical and photochemical characteristics. Photosensitisers are used in phototherapy to kill cancer cells. Here, the authors describe an organometallic Ru(II)-arene that functions as a phtotosensitiser and produces singlet oxygen and tumour regression in mice

The combination of chemotherapy and immune checkpoint inhibitors (ICIs) represents a promising strategy for enhancing the efficacy of tumor immunotherapy. This review elaborates on its mechanisms and clinical significances. Chemotherapy-induced immunogenic cell death (ICD) serves as the foundation of this therapeutic synergy, involving the release of damage-associated molecular patterns (DAMPs) such as calreticulin, ATP, and HMGB1, which enhance immune activation in the presence of ICIs. Clinical trials have demonstrated that this combination approach markedly improves clinical outcomes across multiple tumor types, including non-small cell lung cancer, melanoma, bladder cancer, and triple-negative breast cancer. In clinical practice, this combination is increasingly adopted as a first-line or advanced-stage treatment, often guided by personalized medicine approaches. However, several challenges persist, including the management of treatment-related toxicity, high costs, and the identification of predictive biomarkers.

Accurate grape detection in orchards is a core link in realizing automated harvesting. To address the challenges in orchard environments, such as complex grape backgrounds, variable lighting conditions, and dense occlusion of fruits, this study proposes a highly robust real-time grape detection model for orchard scenarios, namely Grapevine Ultra-Lightweight YOLO (GrapeUL-YOLO). Based on YOLOv11, this model enhances detection performance through three innovative designs: firstly, it adopts a Cross-Scale Residual Feature Backbone (CSRB) as the feature extraction network, combining 16 × downsampling operation with modules such as C3k2_SP and SPPELAN, which reduces computational complexity while retaining multi-scale features of grapes from small clusters to entire clusters; secondly, it constructs an Adaptive Bidirectional Fusion Network (ABFN) in the detection Neck, and through CARAFE content-aware upsampling and a bidirectional cross-scale concatenation mechanism, it strengthens the interaction between spatial details and semantic information, thereby improving the feature fusion capability in scenes with dense occlusion; thirdly, it designs a shape-adaptive detection Head, which uses customized elliptical anchor boxes to match the natural shape of grapes and detects grape targets of different sizes according to scale division. Experimental results show that on the Embrapa WGISD dataset, the mAP@0.5 of GrapeUL-YOLO reaches 0.912, and the mAP@0.5:0.95 is 0.576, both outperforming 9 mainstream models including CenterNet and YOLOv11; meanwhile, the model has only 5.11M parameters and an average detection time of 16.9ms per image, achieving a balance between high precision and lightweight, and providing an efficient solution for automated grape detection and harvesting in orchards.

Oxidative stress and neuroinflammation are recognized as key factors in the development of neurodegenerative diseases, yet effective interventions and biomarkers to address oxidative stress and neuroinflammation in these conditions are limited. Uric acid (UA), traditionally associated with gout, is now gaining prominence as a potential target in neurodegenerative diseases. Soluble UA stands out as one of the most vital antioxidant compounds produced by the human body, accounting for up to 55% of the extracellular capacity to neutralize free radicals. While there is increasing evidence supporting the neuroprotective properties of UA in Parkinson’s disease and Alzheimer’s disease, gaps in knowledge still exist regarding the underlying mechanisms and how to effectively translate these benefits into clinical practice. Moreover, the current UA elevation therapy exhibits unstable antioxidant properties, individual variability, and even adverse effects, limiting its potential clinical applications. This review consolidates recent advancements in understanding how UA exerts neuroprotective effects on neurodegenerative diseases and emphasizes the dual roles of UA in managing oxidative stress and neuroinflammation. Additionally, the review elucidates the mechanisms through which UA confers neuroprotection. Based on this, the review underscores the significance of UA as a potential biomarker and aims to provide a comprehensive understanding of its potential as a therapeutic target, while also addressing possible challenges to clinical implementation.

It is not clear that the genes involved with flavonoids synthesis, regulation and transport in Ilex asprella. Transcriptome analysis of leaf, stem and root has uncovered 28,478 differentially expressed genes (DEGs) that are involved in various biological processes. Among these, the expression of 31 candidate synthetase genes, 19 transcription factors, and 5 transporters associated with flavonoid biosynthesis varies across tissues, encompassing seven complete biosynthetic pathways (stilbene, aurone, flavone, isoflavone, flavonol, phlobaphene, and anthocyanin) and one partial pathway (proanthocyanidin). Tissue-specific expression patterns suggest that the stilbenes, aurones, flavones and anthocyanin branches are more prominent in roots, as indicated by key genes such as STS(Ilex_044726) , CH4 ʹ GT(Ilex_047989) , FNS(Ilex_043640) and UFGT(Ilex_014720) . In leaves, the phlobaphenes and flavonols branches are dominant, determined by CHI(Ilex_005941) , FNR(Ilex_039777) and FLS(Ilex_046424) . The isoflavone pathway appears to be more active in stems due to the presence of IFS(Ilex_029360) , mirroring the accumulation of the intermediate metabolite chalcone, which is regulated by CHS(Ilex_047537) . The absence of LAR genes implies that gallocatechin, and catechin liked proanthocyanidins cannot be synthesized in I. asprella . Meanwhile, the general phenylpropanoid pathway is more active in roots, stems than in leaves, as evidenced by the expression of PAL(Ilex_042231, Ilex_014816) , C4H(Ilex_017598) , and 4CL(Ilex_042033) . Flavanone, dihydroflavonol and leucoanthocyanidin, key intermediates, accumulate more rapidly in stem, stem and root, respectively, regulated by CHI(Ilex_005941) , F3H(Ilex_004635) and DFR(Ilex_004771) . Correlation and network analyses reveal that candidate regulators and transporters are closely associated with the synthesis genes. The study provides profound snoop into flavonoids metabolism in I. asprella and offers valuable refer for medicinal plant.

Background: Postoperative nausea and vomiting (PONV) is a common complication, that can reduce patient satisfaction and may lead to serious consequences, such as wound dehiscence. Many strategies have been proposed to prevent PONV; however, it remains common, especially in high-risk surgeries such as gynecological surgery. In recent years, opioid-free anesthesia has been widely studied because it minimizes adverse reactions of opioids, such as nausea, vomiting, and itching; however, conclusions have been inconsistent. Therefore, we conducted this meta-analysis to investigate the effects of opioid-free anesthesia on PONV in patients undergoing gynecological surgery. Methods: A systematic search of the PubMed, Web of Science, Cochrane Library, and Embase databases, from inception to 28 August 2023, was performed. Keywords and other free terms were used with Boolean operators (OR and, AND) to combine searches. This review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Results: Six studies involving 514 patients who underwent gynecological surgery were included. The forest plot revealed that the incidence of PONV (risk ratio = 0.52; p < 0.00001) and consumption of postoperative antiemetics use (risk ratio = 0.64; p = 0.03) were significantly lower in the opioid-free anesthesia group. In addition, opioid-free anesthesia improved the quality of recovery (mean difference = 4.69; p < 0.0001). However, there were no significant differences in postoperative pain scores (mean difference = 0.05; p = 0.85), analgesic use (risk ratio = 1.09; p = 0.65), and the time of extubation (mean difference = −0.89; p = 0.09) between the opioid-free anesthesia and control groups. Conclusion: OFA reduces PONV and the use of antiemetic drugs. In addition, it improves the quality of postoperative recovery. However, OFA can not reduce the postoperative pain scores, analgesic use and the time of extubation. Due to the strength of the evidence, we cannot support OFA as an ideal anesthesia method in gynecological surgery, and the implementation of anesthesia strategies should be case-by-case. Systematic Review Registration: [ https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=462044 ], identifier [CRD42023462044]

The scientific community increasingly recognized that seed microbiomes are important for plant growth and nutrition. The versatile roles and modulating properties that microbiomes hold in the context of seeds seem to be an inherited approach to avert adverse conditions. These discoveries attracted extensive interest, especially in staple food crops (SFCs) where grain was consumed as food. Along with the rapid expansion of population and industrialization that posed a severe challenge to the yield of SFCs, microbiologists and botanists began to explore and engineer seed microbiomes, for safer and more fruitful grain production. To utilize seed microbiomes, we present an overall review of the most updated scientific literature on three representative SFCs (wheat, rice and maize) using the 5W1H (Which, Where, What, Why, When and How) method that provides a comprehensive understanding of the issue. These include which factors determine the composition of seed microbiomes? Where do seed microbiomes come from? What are these seed microbes? Why do these microbes choose seeds as their destination and when do microbes settle down and become seed communists? In addition, how do seed microbiomes work and can be manipulated effectively? Therefore, answering the aforementioned questions regarding SFCs seed microbiomes remain fundamental in bridging endophytic research gaps and harnessing their ecological services. To explore and engineer seed microbiomes for safer and more fruitful grain production, the article presented an updated scientific literature review of staple food crop seed microbiomes based on three representative (wheat, rice, and maize) using the 5W1H (Which, Where, What, Why, When, and How) method,

Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during 2008–2014. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the spatial distribution, but estimates from CLDAS and GLDAS are systematically higher than those from CMFD over most of mainland China. Based on our evaluation metrics, CLDAS slightly outperforms GLDAS. CLDAS is also closer than GLDAS to CMFD with respect to temporal variations in shortwave radiation anomalies, with substantial differences among the time series. Differences in temporal variations are especially pronounced south of 34° N. Our findings provide valuable guidance for a variety of stakeholders, including land-surface modelers and data providers.

Background Metacaspases ( MCA s) play important roles in regulating plant growth and development, as well as programmed cell death under stress conditions. Results Based on whole-genome information, a total of 36, 10, 12, 23, 11, nine, nine, six, eight, and five MCA genes were identified in Triticum aestivum , Hordeum vulgare , Triticum urartu , Triticum dicoccoides , Aegilops tauschii , Oryza sativa , Arabidopsis thaliana , Vitis vinifera , Solanum lycopersicum , and Cucumis sativus , respectively. The gene structures, evolutionary relationships, and potential roles of TaMCAs in wheat powdery mildew resistance were systematically analyzed. Phylogenetic analysis classified MCAs into four subgroups (Class I-1, I-2, II-1, and II-2), with members within the same subgroup exhibiting highly similar gene structures. Notably, two pairs of tandemly duplicated genes ( TaMCA1A-2 / TaMCA1A-3 and TaMCA1B-2 / TaMCA1B-3 ) were identified in wheat. Virus-induced gene silencing and qRT-PCR demonstrated that TaMCA4D-3 , as a Class I-2 gene, positively regulates resistance to wheat powdery mildew, and subcellular localization analysis indicated that TaMCA4D-3 is localized in both the nucleus and cytoplasm. Conclusions Collectively, these findings provide new insights into the classification and evolutionary relationships of the MCA gene family across plant species and elucidate the role of MCAs in wheat resistance to powdery mildew.

Background With concerns about depletion of fossil fuel and environmental pollution, synthesis of biofuels such as isobutanol from low-cost substrate by microbial cell factories has attracted more and more attention. As one of the most promising carbon sources instead of food resources, acetate can be utilized by versatile microbes and converted into numerous valuable chemicals. Results An isobutanol synthetic pathway using acetate as sole carbon source was constructed in E. coli . Pyruvate was designed to be generated via acetyl-CoA by pyruvate-ferredoxin oxidoreductase YdbK or anaplerotic pathway. Overexpression of transhydrogenase and NAD kinase increased the isobutanol titer of recombinant E. coli from 121.21 mg/L to 131.5 mg/L under batch cultivation. Further optimization of acetate supplement concentration achieved 157.05 mg/L isobutanol accumulation in WY002, representing the highest isobutanol titer by using acetate as sole carbon source. Conclusions The utilization of acetate as carbon source for microbial production of valuable chemicals such as isobutanol could reduce the consumption of food-based substrates and save production cost. Engineering strategies applied in this study will provide a useful reference for microbial production of pyruvate derived chemical compounds from acetate.