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The prodrug design strategy offers a potent solution for improving therapeutic index and expanding drug targets. However, current prodrug activation designs are mainly responsive to endogenous stimuli, resulting in unintended drug release and systemic toxicity. In this study, we introduce 3-vinyl-6-oxymethyl-tetrazine (voTz) as an all-in-one reagent for modular preparation of tetrazine-caged prodrugs and chemoselective labeling peptides to produce bioorthogonal activable peptide-prodrug conjugates. These stable prodrugs can selectively bind to target cells, facilitating cellular uptake. Subsequent bioorthogonal cleavage reactions trigger prodrug activation, significantly boosting potency against tumor cells while maintaining exceptional off-target safety for normal cells. In vivo studies demonstrate the therapeutic efficacy and safety of this prodrug design approach. Given the broad applicability of functional groups and labeling versatility with voTz, we foresee that this strategy will offer a versatile solution to enhance the therapeutic range of cytotoxic agents and facilitate the development of bioorthogonal activatable biopharmaceuticals and biomaterials. Prodrugs have the potential for improving therapeutic index and expanding drug targets, but current prodrug activation strategies that are responsive to endogenous stimuli can result in unintended drug release and systemic toxicity. Here, the authors report 3-vinyl−6-oxymethyltetrazine (voTz) as an all-in-one reagent for modular preparation of tetrazine-caged prodrugs and chemoselective labeling of peptides to produce bioorthogonal activable peptide-prodrug conjugates.

Protein translation is a tightly regulated cellular process that is essential for gene expression and protein synthesis. The deregulation of this process is increasingly recognized as a critical factor in the pathogenesis of various human diseases. In this review, we discuss how deregulated translation can lead to aberrant protein synthesis, altered cellular functions, and disease progression. We explore the key mechanisms contributing to the deregulation of protein translation, including functional alterations in translation factors, tRNA, mRNA, and ribosome function. Deregulated translation leads to abnormal protein expression, disrupted cellular signaling, and perturbed cellular functions- all of which contribute to disease pathogenesis. The development of ribosome profiling techniques along with mass spectrometry-based proteomics, mRNA sequencing and single-cell approaches have opened new avenues for detecting diseases related to translation errors. Importantly, we highlight recent advances in therapies targeting translation-related disorders and their potential applications in neurodegenerative diseases, cancer, infectious diseases, and cardiovascular diseases. Moreover, the growing interest lies in targeted therapies aimed at restoring precise control over translation in diseased cells is discussed. In conclusion, this comprehensive review underscores the critical role of protein translation in disease and its potential as a therapeutic target. Advancements in understanding the molecular mechanisms of protein translation deregulation, coupled with the development of targeted therapies, offer promising avenues for improving disease outcomes in various human diseases. Additionally, it will unlock doors to the possibility of precision medicine by offering personalized therapies and a deeper understanding of the molecular underpinnings of diseases in the future.

Background Biomedical event extraction is a fundamental task in biomedical text mining, which provides inspiration for medicine research and disease prevention. Biomedical events include simple events and complex events. Existing biomedical event extraction methods usually deal with simple events and complex events uniformly, and the performance of complex event extraction is relatively low. Results In this paper, we propose a fine-grained Bidirectional Long Short Term Memory method for biomedical event extraction, which designs different argument detection models for simple and complex events respectively. In addition, multi-level attention is designed to improve the performance of complex event extraction, and sentence embeddings are integrated to obtain sentence level information which can resolve the ambiguities for some types of events. Our method achieves state-of-the-art performance on the commonly used dataset Multi-Level Event Extraction. Conclusions The sentence embeddings enrich the global sentence-level information. The fine-grained argument detection model improves the performance of complex biomedical event extraction. Furthermore, the multi-level attention mechanism enhances the interactions among relevant arguments. The experimental results demonstrate the effectiveness of the proposed method for biomedical event extraction.

Hepatocellular carcinoma (HCC) is a prevalent malignancy and there is a lack of effective biomarkers for HCC diagnosis. Living organisms are complex, and different omics molecules interact with each other to implement various biological functions. Genomics and metabolomics, which are the top and bottom of systems biology, play an important role in HCC clinical management. Fatty acid metabolism is associated with malignancy, prognosis, and immune phenotype in cancer, which is a potential hallmark in malignant tumors. In this study, the genes and metabolites related to fatty acid metabolism were thoroughly investigated by a dynamic network construction algorithm named EWS-DDA for the early diagnosis and prognosis of HCC. Three gene ratios and eight metabolite ratios were identified by EWS-DDA as potential biomarkers for HCC clinical management. Further analysis using biological analysis, statistical analysis and document validation in the discovery and validation sets suggested that the selected potential biomarkers had great clinical prognostic value and helped to achieve effective early diagnosis of HCC. Experimental results suggested that in-depth evaluation of fatty acid metabolism from different omics viewpoints can facilitate the further understanding of pathological alterations associated with HCC characteristics, improving the performance of early diagnosis and clinical prognosis.

In arid and semi-arid regions of northwest China, the ecological environment is fragile and fire occurs frequently. Fire has an important impact on the regional ecological environment. The last glacial period is the most recent glacial period, and the climate is unstable, characterized by millennial oscillations. The research reveals regional fire evolution and driving mechanism of the last glacial period in arid and semi-arid regions of northwest China. The research can provide important theoretical reference for regional fire prevention and control in the future. Therefore, a sediment core was drilled from the southwestern part of the Hetao Basin. In this study, we extended the study sequence to 23.68-m-long, and reconstructed the history of fire during the last glacial period (MIS4 ~ MIS2). The results are as follows: (1) 72.2 ~ 59.5 ka BP: The regional fire activity was low. 59.5 ~ 49.8 ka BP: The regional fire activity was relatively higher than the previous stage. 49.8 ~ 36.9 ka BP: The regional fire activity had little change than the previous stage. 36.9 ~ 26.6 ka BP: The regional fire activity was relatively higher than the previous stage. 26.6 ~ 18.9 ka BP: The regional fire activity was relatively lower than the previous stage. 18.9 ~ 15.7 ka BP: The regional fire activity was low. (2) The regional fire activity was low during the Heinrich events in the Hetao Basin. (3) The more fire activity in the last glacial period in the Hetao Basin was due to the warm and wet climatic conditions, which promoted better regional vegetation development and increased regional biomass, which provided sufficient fuel for the occurrence of fire activity.

Background Mental fatigue in class is a common phenomenon among university students in China. However, there is limited research exploring the impact of QI-pathological constitution on mental fatigue in university students. Methods We employed a convenience sampling method to survey 588 students aged 17 to 24 from a western university in China in May 2024. The study measured QI-pathological constitution and mental fatigue among these students. Additionally, diet quality, physical exercise, sleep quality, and academic pressure were assessed as controlled variables. Descriptive statistics, Pearson correlation, and structural equation modeling were utilized to analyze these cross-sectional data. Results The results showed that university students experience low levels of mental fatigue in class ( M  = 2.41, SD  = 0.75) and a slight QI-pathological constitution ( M  = 1.96, SD  = 0.71 for QI stagnation and M  = 2.41, SD  = 0.91 for QI deficiency) on a 5-point Likert scale ranging from 1(never) to 5(often). Pearson correlation analysis revealed a weak positive association between QI-pathological constitution ( r  = 0.205, p  < 0.01 for QI stagnation; and r  = 0.256, p  < 0.01 for QI deficiency) and mental fatigue in class. Controlling for diet quality, physical exercise, sleep quality, and academic pressure in the structural equation model showed that QI-pathological constitution has a significantly positive effect on mental fatigue in class ( β  = 0.228, p  < 0.01). Conclusion The study identified a low level of mental fatigue in class and a slight presence of QI-pathological constitution among university students. The QI-pathological constitution has a significantly positive impact on the level of mental fatigue experienced by university students in the classroom.

A large number of economic forests, especially apple orchards (AOs) in the Loess Plateau region of China, have been planted to develop the local economy and increase the income of farmers. The two main constraints preventing AOs on the Loess Plateau from developing sustainably and producing a high and steady yield are soil moisture content (SMC) and soil organic carbon (SOC). Nevertheless, little is currently known about the contributions of roots to these changes in the soil profile and the temporal modes of the SMC-SOC coupled effects. In our research, we analyzed the dynamic changes in SMC and SOC in AOs of various years in northern Shaanxi Province, as well as the coupled relationship between the two, and attempted to describe the function of roots in these changes. Research have shown: (1) As the age of the AOs increased, the SMC continued to decline throughout the 0–500 cm profile, especially at depths of 100–500 cm. SMC depletion mainly occurred in AOs aged 20 years (30.02%/year) and 30 years (31.18%/year). (2) Compared with abandoned land (AL), all the AOs except for the 6-year-old AO showed a carbon sequestration effect, and the carbon sequestration effect increased with age. The carbon sequestration rate of the 12-year-old AO was the highest and then decreased with age. Both surface and deeper soils showed better carbon sequestration, with a large amount of SOC being sequestered in deeper soil layers (> 100 cm). (3) The coupled effects of SMC and SOC varied with age and depth. The SMC in the deeper layers was significantly negatively correlated with SOC. Root dry weight density (RDWD) was significantly negatively correlated with SMC and significantly positively correlated with SOC. Path analysis suggested that SMC directly affects SOC at different soil depths, and regulates SOC by affecting RDWD, but these effects are significantly different at different depths. Therefore, we propose that management of AO should focus on the moisture deficit and carbon sequestration capabilities of deeper soils to ensure the sustainability of water use in AOs and the stability of agricultural carbon sequestration on the Loess Plateau.

Atmospheric carbon dioxide in mole fraction (XCO2) is one of the key parameters in estimating CO2 fluxes at the air–sea interface. Satellite-derived column-averaged XCO2 has been widely used in the estimates of air–sea CO2 fluxes, yet the uncertainties induced by using column-averaged XCO2 instead of atmospheric XCO2 in the ocean boundary layer have been generally unknown. In this study, based on an extensive dataset of atmospheric XCO2 measured in the ocean boundary layer from global ocean mooring arrays (N = 945,243) and historical cruises (N = 170,000) between 2002 and 2024, for the first time, we quantitatively evaluated the performance of four satellites, including the Greenhouse gases Observing SATellite (GOSAT and GOSAT-2), the Orbiting Carbon Observatory-2 (OCO-2), and the Atmospheric InfraRed Sounder (AIRS), in monitoring the atmospheric XCO2 over oceanic regions. The atmospheric XCO2 has been increasing from 375 ppm in 2002 to 417 ppm in 2024 based on the longest data record from AIRS. We found that the column-averaged atmospheric XCO2 can serve as a good proxy for atmospheric XCO2 in the ocean boundary layer, with associated uncertainties of 2.48 ppm (0.46%) for GOSAT, 1.01 ppm (0.24%) for GOSAT-2, 2.45 ppm (0.45%) for OCO-2, and 4.22 ppm (0.83%) for AIRS. We also investigated the consistency of these satellites in monitoring the growth rates of atmospheric XCO2 in the global ocean basins. Based on the longest data record from AIRS, the atmospheric XCO2 has been increasing at a rate of 1.87–1.97 ppm year−1 over oceanic regions in the past two decades. These findings contribute to improving the reliability of satellite-derived column-averaged XCO2 observations in the estimates of air–sea CO2 fluxes and support future efforts in monitoring ocean carbon dynamics through satellite remote sensing.

Immune checkpoint blockade therapies targeting the PD-L1/PD-1 axis have demonstrated clear clinical benefits. Improved understanding of the underlying regulatory mechanisms might contribute new insights into immunotherapy. Here, we identify transmembrane and ubiquitin-like domain-containing protein 1 (TMUB1) as a modulator of PD-L1 post-translational modifications in tumor cells. Mechanistically, TMUB1 competes with HECT, UBA and WWE domain-containing protein 1 (HUWE1), a E3 ubiquitin ligase, to interact with PD-L1 and inhibit its polyubiquitination at K281 in the endoplasmic reticulum. Moreover, TMUB1 enhances PD-L1 N-glycosylation and stability by recruiting STT3A, thereby promoting PD-L1 maturation and tumor immune evasion. TMUB1 protein levels correlate with PD-L1 expression in human tumor tissue, with high expression being associated with poor patient survival rates. A synthetic peptide engineered to compete with TMUB1 significantly promotes antitumor immunity and suppresses tumor growth in mice. These findings identify TMUB1 as a promising immunotherapeutic target. Cancer cells exploit immune checkpoint pathways, such as PD-1/PD-L1, to evade elimination by the immune system. Here, the authors demonstrate that TMUB1 regulates post-translational modifications of PD-L1 and that targeting the TMUB1/PD-L1 interaction promotes anti-tumour T cells responses

Researchers have delved into noninvasive diagnostic methods of renal fibrosis (RF) in chronic kidney disease, including ultrasound (US), magnetic resonance imaging (MRI), and radiomics. However, the value of these diagnostic methods in the noninvasive diagnosis of RF remains contentious. Consequently, the present study aimed to systematically delineate the accuracy of the noninvasive diagnosis of RF. A systematic search covering PubMed, Embase, Cochrane Library, and Web of Science databases for all data available up to 28 July 2023 was conducted for eligible studies. We included 21 studies covering 4885 participants. Among them, nine studies utilized US as a noninvasive diagnostic method, eight studies used MRI, and four articles employed radiomics. The sensitivity and specificity of US for detecting RF were 0.81 (95% CI: 0.76-0.86) and 0.79 (95% CI: 0.72-0.84). The sensitivity and specificity of MRI were 0.77 (95% CI: 0.70-0.83) and 0.92 (95% CI: 0.85-0.96). The sensitivity and specificity of radiomics were 0.69 (95% CI: 0.59-0.77) and 0.78 (95% CI: 0.68-0.85). The current early noninvasive diagnostic methods for RF include US, MRI, and radiomics. However, this study demonstrates that US has a higher sensitivity for the detection of RF compared to MRI. Compared to US, radiomics studies based on US did not show superior advantages. Therefore, challenges still exist in the current radiomics approaches for diagnosing RF, and further exploration of optimized artificial intelligence (AI) algorithms and technologies is needed.