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Abstract The abnormal structure of tumor vascular seriously hinders the delivery and deep penetration of drug in tumor therapy. Herein, an integrated and tumor microenvironment (TME)-responsive nanocarrier is designed, which can dilate vessle and improve the drug penetration by in situ releasing nitric oxide (NO). Briefly, S-nitroso-glutathione (GSNO) and curcumin (Cur) were encapsulatd into the Cu-doped zeolite imidazole framework-8 (Cu-ZIF-8) and modified with hyaluronic acid. The nanocarrier degradation in the weakly acidic of TME releases Cu2+, then deplete overexpressed intratumourally glutathione and transformed into Cu+, thus disrupting the balance between nicotinamide adenine dinucleotide phosphate and flavin adenine dinucleotide (NADPH/FAD) during the metabolism homeostasis of tumor. The Cu+ can generate highly toxic hydroxyl radical through the Fenton-like reaction, enhancing the chemodynamic therapeutic effect. In addition, Cu+ also decomposes GSNO to release NO by ionic reduction, leading to vasodilation and increased vascular permeability, significantly promoting the deep penetration of Cur in tumor. Afterwards, the orderly operation of cell cycle is disrupted and arrested in the S-phase to induce tumor cell apoptosis. Deep-hypothermia potentiated 2D/3D fluorescence imaging demonstrated nanocarrier regulated endogenous metabolism homeostasis of tumor. The cascade-catalysed multifunctional nanocarrier provides an approach to treat orthotopic tumor.

Abstract The vacancy effect in quantum spin liquid (QSL) has been extensively studied. A finite density of random vacancies in the Kitaev model can lead to a pileup of low-energy density of states (DOS), which is generally experimentally determined by a scaling behavior of thermodynamic or magnetization quantities. Here, we report detailed muon spin relaxation (μSR) results of H3LiIr2O6, a Kitaev QSL candidate with vacancies. The absence of magnetic order is confirmed down to 80 mK, and the spin fluctuations are found to be persistent at low temperatures. Intriguingly, the time-field scaling law of longitudinal-field (LF)-μSR polarization is observed down to 0.1 K. This indicates a dynamical scaling, whose critical exponent of 0.46 is excellently consistent with the scaling behavior of specific heat and magnetization data. All the observations point to the finite DOS with the form $$N(E)\sim {E}^{-\nu }$$ N ( E ) ∼ E − ν , which is expected for the Kitaev QSL in the presence of vacancies. Our μSR study provides a dynamical fingerprint of the power-law low-energy DOS and introduces a crucial new insight into the vacancy effect in QSL.

Aegilops tauschii is a wild diploid goat-grass which occupies a vast range in Central Eurasia and comprises three different gene-pools: TauL1, TauL2, and TauL3. Multivariate statistical analysis of the transcriptomes from the leaf tissue of 40 A. tauschii accessions, 18 of TauL1, 20 of TauL2, and 2 of TauL3, revealed that the gene-pools of A. tauschii distinctly and essentially differ in their genetic expression patterns. Statistically significant differential gene expression of 2349, 376, and 272 were observed between TauL1 and TauL2; TauL1 and TauL3; TauL2 and TauL3, respectively. These findings indicate substantial adaptive intraspecies divergence in A. tauschii.

Objective We aimed to screen and construct a predictive model for pregnancy loss in polycystic ovary syndrome (PCOS) patients through machine learning methods.Methods We obtained the endometrial samples from 33 PCOS patients and 7 healthy controls at the Reproductive Center of the Second Hospital of Lanzhou University from September 2019 to September 2020. Liquid chromatography tandem mass spectrometry (LCMS/MS) was conducted to identify the differentially expressed proteins (DEPs) of the two groups. Gene Ontology (GO) as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to analyze the related pathways and functions of the DEPs. Then, we used machine learning methods to screen the feature proteins. Multivariate Cox regression analysis was also conducted to establish the prognostic models. The performance of the prognostic model was then evaluated by the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). In addition, the Bootstrap method was conducted to verify the generalization ability of the model. Finally, linear correlation analysis was performed to figure out the correlation between the feature proteins and clinical data.Results Four hundred and fifty DEPs in PCOS and controls were screened out, and we obtained some pathways and functions. A prognostic model for the pregnancy loss of PCOS was established, which has good discrimination and generalization ability based on two feature proteins (TIA1, COL5A1). Strong correlation between clinical data and proteins were identified to predict the reproductive outcome in PCOS.Conclusion The model based on the TIA1 and COL5A1 protein could effectively predict the occurrence of pregnancy loss in PCOS patients and provide a good theoretical foundation for subsequent research.

Abstract Establishing prediction models of pregnancy outcomes for recurrent pregnancy loss women at specific gestational weeks will provide patients and physicians with more precise information, ultimately leading to time and cost savings associated with unnecessary revisits. Therefore, our aim was to develop a prediction model for first trimester pregnancy loss in RPL patients. We used ultrasound indices during the first trimester of pregnancy in combination with demographic characteristics and commonly used serum markers. The independent risk factors for each week were as follows: age and P in the fifth week; age, mGSD and CRL in the sixth week; age, hCG and CRL in the seventh week; CRL in the eighth week; mGSD and CRL in ninth week. The corresponding AUC was 0.671, 0.796, 0.872, 0.871, 0.813, respectively. There is a linear relationship between age and first trimester pregnancy loss. hCG 48.3 mm in ninth gestational week was associated with a higher risk of pregnancy loss. These models and thresholds may help physicians and patients make more informed decisions together. Further studies are needed to confirm the results.

A tight sandstone gas reservoir is characterized by low porosity and permeability. The existence of fractures can improve the permeability of the reservoir, and fractures are a vital storage space and migration channel of oil and gas. The development of fractures is also conducive to forming a fracture network during hydraulic fracturing. The prediction of fractures can provide an essential basis for developing tight sandstone gas reservoirs. The variation of seismic amplitude with azimuth can provide information on vertical fractures in the reservoir. This study proposed an improved inversion method of azimuth amplitude difference for the HTI (transversely isotropy with a horizontal axis) medium and combined with the rock physical theory, predicted fracture weakness parameter, characterizing the fracture properties. Conventional inversion methods invert elastic and fracture parameters simultaneously. The improved azimuth amplitude difference method introduces a reference azimuth, builds the track set of azimuth amplitude difference to eliminate the isotropic background, and inverts only the fracture weakness parameters related to the anisotropic terms. Using the only azimuth anisotropic response, the sensitivity of fracture identification and the accuracy of fracture parameter inversion are improved. The application of the field data shows that the sensitivity of the proposed inversion method to the prediction of fracture parameters is improved compared with the conventional inversion method, and the predicted fracture weakness is consistent with the permeability well logs and has a significant correlation with the gas production of tight sandstone gas reservoirs. Therefore, the prediction of fracture distribution and development degree based on the proposed method can provide a reliable indicator for the identification and development of gas-bearing favorable areas in tight sandstone reservoirs.

Abstract Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. However, effective diagnostic, therapeutic and prognostic biomarkers are still lacking. Our research group previously revealed through high-throughput sequencing that the serum exosomes miR-133a-3p, miR-206, and miR-549a-3p differ significantly in severe TBI (sTBI), mild or moderate TBI (mTBI), and control groups. However, convincing experimental evidence is lacking. To solve this problem, we used qPCR in this study to further verify the expression levels of serum exosomes miR-133a-3p, miR-206 and miR-549a-3p in TBI patients. The results showed that the serum exosomes miR-206 and miR-549a-3p showed good predictive value as biomarkers of TBI. In addition, in order to further verify whether serum exosomes miR-206 and miR-549a-3p can be used as potential biomarkers in patients with TBI and to understand the mechanism of their possible effects, we further determined the contents of SOD, BDNF, VEGF, VEGI, NSE and S100β in the serum of TBI patients. The results showed that, serum exosomes miR-206 and miR-549a-3p showed good correlation with BDNF, NSE and S100β. In conclusion, serum exosomes miR-206 and miR-549a-3p have the potential to serve as potential biomarkers in patients with TBI.

ObjectOsteosarcoma is a malignant tumor originating from the bones, commonly found in children and adolescents, especially in rapidly growing bone areas such as the knees and upper arms. In this study, we aim to delineate the evolution and convergence of research themes in osteosarcoma metabolomics over the past decade, identify major contributors, and forecast emerging trends that could direct future research efforts.MethodThe bibliometric method has been applied to systematically analyze the literature in the field of osteosarcoma metabolomics. The relevant literatures were collected from the Web of Science Core Collection, spanning from January 1, 2014, to December 31, 2023. Tools such as CiteSpace, Bibliometrix, and VOSviewer were used for the visual analysis of the collected literatures. The focused information includes institutions, journals, countries, authors, keywords, and citations.ResultVarious aspects in the field of osteosarcoma metabolism were analyzed. Shanghai Jiao Tong University has published the most papers in the past ten years, followed by Central South University and Zhejiang University. Among the sources, the international journal of molecular sciences publishes the most articles, and oncotarget is the journal with the highest H index. According to Bradford’s law, there are 34 core journals identified. A total of 5501 authors participated in the creation of papers in this field. The distribution of authors follows Lotka`s Law, and 85.3% of authors have only one article. 46% of the corresponding authors are from China, but most of these corresponding authors are not good at international cooperation. China also has the largest number of publications, followed by the United States. It can be confirmed that China dominates this field. Among the keywords, “expression” is the keyword that has received the most attention in the past ten years. All keywords can be divided into 9 clusters. Based on the explosive words and hot topics each year, we speculate that future research will focus on the tumor microenvironment, molecular mechanisms and autophagy, targeted therapies and inhibitors.ConclusionIn summary, this study comprehensively analyzed the current state of research in the field of osteosarcoma metabolism through bibliometric methods. The findings revealed the development trends and research hotspots in this field, which may provide valuable references for future research directions.

BackgroundOsteosarcoma (OS), a bone tumor with high ability of invasion and metastasis, has seriously affected the health of children and adolescents. Many studies have suggested a connection between OS and the epithelial-mesenchymal transition (EMT). We aimed to integrate EMT-Related genes (EMT-RGs) to predict the prognosis, immune infiltration, and therapeutic response of patients with OS.MethodsWe used consensus clustering to identify potential EMT-Related OS molecular subtypes. Somatic mutation, tumor immune microenvironment, and functional enrichment analyses were performed for each subtype. We next constructed an EMT-Related risk signature and evaluated it by Kaplan-Meier (K-M) analysis survival and receiver operating characteristic (ROC) curves. Moreover, we constructed a nomogram to more accurately predict OS patients’ clinical outcomes. Response effects of immunotherapy in OS patients was analyzed by Tumor Immune Dysfunction and Exclusion (TIDE) analysis, while sensitivity for chemotherapeutic agents was analyzed using oncoPredict. Finally, the expression patterns of hub genes were investigated by single-cell RNA sequencing (scRNA-seq) data analysis.ResultsA total of 53 EMT-RDGs related to prognosis were identified, separating OS samples into two separate subgroups. The EMT-high subgroup showed favourable overall survival and more active immune response. Significant correlations were found between EMT-Related DEGs and functions as well as pathways linked to the development of OS. Additionally, a risk signature was established and OS patients were divided into two categories based on the risk scores. The signature presented a good predictive performance and could be recognized as an independent predictive factor for OS. Furthermore, patients with higher risk scores exhibited better sensitivity for five drugs, while no significant difference existed in immunotherapy response between the two risk subgroups. scRNA-seq data analysis displayed different expression patterns of the hub genes.ConclusionWe developed a novel EMT-Related risk signature that can be considered as an independent predictor for OS, which may help improve clinical outcome prediction and guide personalized treatments for patients with OS.

Abstract Background The HAP, Six-and-Twelve, Up to Seven, and ALBI scores have been substantiated as reliable prognostic markers in patients presenting with intermediate and advanced hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) treatment. Given this premise, our research aims to assess the predictive efficacy of these models in patients with intermediate and advanced HCC receiving a combination of TACE and Apatinib. Additionally, we have conducted a meticulous comparative analysis of these four scoring systems to discern their respective predictive capacities and efficacies in combined therapy. Methods Performing a retrospective analysis on the clinical data from 200 patients with intermediate and advanced HCC, we studied those who received TACE combined with Apatinib at the First Affiliated Hospital of the University of Science and Technology of China between June 2018 and December 2022. To identify the factors affecting survival, the study performed univariate and multivariate Cox regression analyses, with calculations of four different scores: HAP, Six-and-Twelve, Up to Seven, and ALBI. Lastly, Harrell’s C-index was employed to compare the prognostic abilities of these scores. Results Cox proportional hazards model results revealed that the ALBI score, presence of portal vein tumor thrombus (PVTT, )and tumor size are independent determinants of prognostic survival. The Kaplan-Meier analyses showed significant differences in survival rates among patients classified by the HAP, Six-and-Twelve, Up to Seven, and ALBI scoring methods. Of the evaluated systems, the HAP scoring demonstrated greater prognostic precision, with a Harrell’s C-index of 0.742, surpassing the alternative models (P

Abstract Background Glycogen storage disease type Ib (GSD Ib) is a rare disorder characterized by impaired glucose homeostasis caused by mutations in the SLC37A4 gene. It is a severe inherited metabolic disease associated with hypoglycemia, hyperlipidemia, lactic acidosis, hepatomegaly, and neutropenia. Traditional treatment consists of feeding raw cornstarch which can help to adjust energy metabolism but has no positive effect on neutropenia, which is fatal for these patients. Recently, the pathophysiologic mechanism of the neutrophil dysfunction and neutropenia in GSD Ib has been found, and the treatment with the SGLT2 inhibitor empaglifozin is now well established. In 2020, SGLT2 inhibitor empagliflozin started to be used as a promising efficient remover of 1,5AG6P in neutrophil of GSD Ib patients worldwide. However, it is necessary to consider long-term utility and safety of a novel treatment. Results In this study, we retrospectively examined the clinical manifestations, biochemical examination results, genotypes, long-term outcomes and follow-up of thirty-five GSD Ib children who visited our department since 2009. Fourteen patients among them underwent empagliflozin treatment since 2020. This study is the largest cohort of pediatric GSD Ib patients in China as well as the largest cohort of pediatric GSD Ib patients treated with empagliflozin in a single center to date. The study also discussed the experience of long-term management on pediatric GSD Ib patients. Conclusion Empagliflozin treatment for pediatric GSD Ib patients is efficient and safe. Increase of urine glucose is a signal for pharmaceutical effect, however attention to urinary infection and hypoglycemia is suggested.

Abstract Osteoporosis is a major public health concern that significantly increases the risk of fractures. The aim of this study was to develop a Machine Learning based predictive model to screen individuals at high risk of osteoporosis based on chronic disease data, thus facilitating early detection and personalized management. A total of 10,000 complete patient records of primary healthcare data in the German Disease Analyzer database (IMS HEALTH) were included, of which 1293 diagnosed with osteoporosis and 8707 without the condition. The demographic characteristics and chronic disease data, including age, gender, lipid disorder, cancer, COPD, hypertension, heart failure, CHD, diabetes, chronic kidney disease, and stroke were collected from electronic health records. Ten different machine learning algorithms were employed to construct the predictive mode. The performance of the model was further validated and the relative importance of features in the model was analyzed. Out of the ten machine learning algorithms, the Stacker model based on Logistic Regression, AdaBoost Classifier, and Gradient Boosting Classifier demonstrated superior performance. The Stacker model demonstrated excellent performance through ten-fold cross-validation on the training set and ROC curve analysis on the test set. The confusion matrix, lift curve and calibration curves indicated that the Stacker model had optimal clinical utility. Further analysis on feature importance highlighted age, gender, lipid metabolism disorders, cancer, and COPD as the top five influential variables. In this study, a predictive model for osteoporosis based on chronic disease data was developed using machine learning. The model shows great potential in early detection and risk stratification of osteoporosis, ultimately facilitating personalized prevention and management strategies.

Abstract Quantum confinement is a restriction on the motion of electrons in a material to specific region, resulting in discrete energy levels rather than continuous energy bands. In certain materials, quantum confinement could dramatically reshape the electronic structure and properties of the surface with respect to the bulk. Here, in the recently discovered kagome superconductors CsV3Sb5, we unveil the dominant role of quantum confinement in determining their surface electronic structure. Combining angle-resolved photoemission spectroscopy (ARPES) measurement and density-functional theory simulation, we report the observations of two-dimensional quantum well states due to the confinement of bulk electron pocket and Dirac cone to the nearly isolated surface layer. The theoretical calculations on the slab model also suggest that the ARPES observed spectra are almost entirely contributed by the top two layers. Our results not only explain the disagreement of band structures between the recent experiments and calculations, but also suggest an equally important role played by quantum confinement, together with strong correlation and band topology, in shaping the electronic properties of this material.

Abstract Objective We aimed to investigate the significance of autophagy proteins and their association with clinical data on pregnancy loss in polycystic ovary syndrome (PCOS), while also constructing predictive models. Methods This study was a secondary analysis. we collected endometrial samples from 33 patients with polycystic ovary syndrome (PCOS) and 7 patients with successful pregnancy control women at the Reproductive Center of the Second Hospital of Lanzhou University between September 2019 and September 2020. Liquid chromatography tandem mass spectrometry was employed to identify expressed proteins in the endometrium of 40 patients. R was use to identify differential expression proteins(DEPs). Subsequently, Metascape was utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Multivariate Cox analysis was performed to analyze autophagy proteins associated with reproductive outcomes, while logistic regression was used for analyzing clinical data. Linear correlation analysis was conducted to examine the relationship between autophagy proteins and clinical data. We established prognostic models and constructed the nomograms based on proteome data and clinical data respectively. The performance of the prognostic model was evaluated by the receiver operating characteristic curve (ROC) and decision curve analysis (DCA). Results A total of 5331 proteins were identified, with 450 proteins exhibiting significant differential expression between the PCOS and control groups. A prognostic model for autophagy protein was developed based on three autophagy proteins (ARSA, ITGB1, and GABARAPL2). Additionally, another prognostic model for clinical data was established using insulin, TSH, TPOAB, and VD3. Our findings revealed a significant positive correlation between insulin and ARSA (R = 0.49), as well as ITGB1 (R = 0.3). Conversely, TSH exhibited a negative correlation with both ARSA (-0.33) and ITGB1 (R = -0.26). Conclusion Our research could effectively predict the occurrence of pregnancy loss in PCOS patients and provide a basis for subsequent research.

The Arxan Volcanic Field (AVF) is an active volcanic region in Northeast Asia, and its last eruption occurred approximately 2000 years ago. Its eruption mechanism remains unknown. To investigate the shallow magma system beneath the volcanic cones in the AVF, we deployed a dense seismic array consisting of 227 portable seismographs and conducted high-resolution ambient noise tomography (ANT). The results of checkerboard test (CRT) and restoring resolution test (RRT) demonstrate that our imaging results are reliable. These results reveale significant slow-velocity anomalies at depths of 5~9 km below the Tianchi caldera and GD1213 volcano in Arxan, with the highest anomaly reaching up to approximately 15%. These anomalies suggest partial melting in a shallow magma chamber, indicating ongoing volcanic activity in the AVF. The velocity of the magma chamber corresponding to a melt fraction of approximately 7.4~12.9%. Therefore, the presence of the magma chamber poses potential hazards to the Arxan region, including volcanic eruptions and their associated risks.

Understanding the impact of creep on the long-term mechanical features of concrete is crucial, and constructing an accurate prediction model is the key to exploring the development of concrete creep under long-term loads. Therefore, in this study, three machine learning (ML) models, a Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Machine (XGBoost), are constructed, and the Hybrid Snake Optimization Algorithm (HSOA) is proposed, which can reduce the risk of the ML model falling into the local optimum while improving its prediction performance. Simultaneously, the contributions of the input features are ranked, and the optimal model’s prediction outcomes are explained through SHapley Additive exPlanations (SHAP). The research results show that the optimized SVM, RF, and XGBoost models increase their accuracies on the test set by 9.927%, 9.58%, and 14.1%, respectively, and the XGBoost has the highest precision in forecasting the concrete creep. The verification results of four scenarios confirm that the optimized model can precisely capture the compliance changes in long-term creep, meeting the requirements for forecasting the nature of concrete creep.

Osteosarcoma, as the most prevalent primary malignant bone tumor, has consistently shown suboptimal clinical treatment outcomes. In this manuscript, we proposed an efficacious and novel phototherapy strategy for osteosarcoma based on a photoresponsive near-infrared (NIR) material, CaCO3-ICG-DDP-PEG-PT (CIDP-PT), which contained calcium carbonate (CaCO3) and Cisplatin (DDP) via the gas dispersion method, and indocyanine green (ICG) was encapsulated through a nanoprecipitation reaction by employing DSPE-PEG2000-COOH to enhance the stability and hydrophilicity. The targeting oligopeptide (PT) for osteosarcoma cells was inserted into the outer membrane of nanoparticles, thereby further enhancing the tumor-targeting capability through receptor-mediated binding. The prepared CIDP-PT nanoparticles exhibited high targeting efficiency and multifunctionality. In vitro and in vivo experiments demonstrated that CIDP-PT significantly enhanced the therapeutic efficacy for osteosarcoma via the NIR-II photoresponsive and tumor-targeting approach. It achieves efficient tumor cell eradication through multiple modalities while maintaining an exceptional level of biocompatibility. Hence, the CIDP-PT nanocarriers possess considerable practical value for future clinical applications in adjunct osteosarcoma phototherapy.

Abstract The synthesis of allenyl boronates is an important yet challenging topic in organic synthesis. Reported herein is an NHC‐gold‐catalyzed 1,3‐H shift toward allenyl boronates synthesis from simple propargylic B(MIDA)s. Mechanistic studies suggest dual roles of the boryl moiety in the reaction: to activate the substrate for isomerization and at the same time, to prevent the allene product from further isomerization. These effects should be a result of α‐anion stabilization and α‐cation destabilization conferred by the B(MIDA) moiety, respectively. The NHC‐Au catalyst, which is commercially available, is also found to be reactive in alkyne‐to‐1,3‐diene isomerization reactions in an atom‐economic and base‐free manner.

Abstract To investigate the biomechanical properties of posterior cruciate ligament avulsion fractures of the tibia fixed using four different methods, including triple tibial channel net suture fixation. In 40 porcine knees, a standardized bony avulsion of the posterior cruciate ligament was generated. Double tibial bone channel suture fixation was performed in group A, double-head hollow compression screw fixation was performed in group B, triple tibial bone channel net suture fixation was performed in group C, and cortical suspension EndoButton fixation was performed in group D. The constructs were cyclically loaded 500 times (10 to 100 N) to measure the initial displacement and stiffness values. Subsequently, loading to failure was performed, and the yield load and peak load were measured. The results were analysed by one-way ANOVA, with significance set at P

The Changbai volcano, a globally recognized hotspot of volcanic activity, has garnered significant attention due to its persistent seismicity and ongoing magma activity. The volcano’s discontinuities and magma dynamics have raised concerns about the likelihood of future eruptions, which would likely result in substantial ecological, climatic, and economic impacts. Consequently, a comprehensive understanding of the Changbai volcanic system is essential for mitigating the risks associated with volcanic activity. In recent years, the P-wave coda autocorrelation method has gained popularity in lithosphere exploration as a reliable technique for detecting reflection coefficients. Additionally, the Common Reflection Point stacking approach has been employed to superimpose reflection signals in a spatial grid, enabling continuous observation of reflection coefficients in the study area. However, the accuracy of this approach is heavily reliant on better spatial data coverage. To better understand the internal dynamics of the Changbai volcano, we applied this approach to a densely packed short-period seismic array with an average station spacing of less than 1 km. Our results were constrained using waveform data of reflection coefficients and Moho dip angles. Our findings revealed a discontinuity in the Moho, which may indicate a conduit for mantle magma entering the crust. Furthermore, we identified two low-velocity anomalies within the crust, likely representing a magma chamber comprising molten and crystallized magma. Notably, our results also provided a clear definition of the lithosphere–asthenosphere boundary.

Abstract Background The relationship between Mg (magnesium), Cu (copper), and K (potassium) intakes and the risk of rheumatoid arthritis (RA) remains limited. The aim of present study was to examine the associations between Mg, Cu and K intakes with RA. Methods Using data from the National Health and Nutrition Examination Survey (NHANES) 2003–2018, we examined the association between Mg, Cu and K intakes and the risk of RA among US adults. After adjustment for age, sex, race, BMI, educational level, smoking history, alcohol consumption, family Poverty Income Ratio (PIR), diabetes and total daily energy intake, logistic regression models and smooth curve fitting were applied to examine the associations of Mg, Cu and K intakes with RA. Results A total of 18,338 participants were included (1,008 participants with RA). The multivariate adjusted ORs (95% CI) of RA were [0.66 (0.51, 0.84)], [0.76 (0.60, 0.97)], and [0.75 (0.58, 0.97)] in the highest versus lowest quartile of magnesium intakes, respectively. A nonlinear association between Cu intakes and RA was found. When Cu intake (ln) was between 0.6–2.2 mg, the risk of RA reduced by 26% for every 1 mg increase of intake in Cu [0.74 (0.58, 0.96)]. Conclusions Higher Mg, Cu and K intakes may be inversely associated with the risk of RA among US adults, and an inverse L-shaped association between dietary Cu and RA was found.

Lung cancer ranks among the primary contributors to cancer-related fatalities on a global scale. Multiple research investigations have demonstrated that there exists a dysbiosis within the intestinal bacteria and short-chain fatty acids (SCFAs) is linked with immune responses in lung cancer. Qingfei mixture (QFM) has been widely used in treating lung cancer, yet the active ingredients and roles of the QFM on immune responses by targeting gut microbiota remain to be elucidated. The chemical constituents of QFM were qualitatively examined by UPLC/Q-TOF-MS. Additionally, we evaluated the therapeutic impact of the organic substance QFM on lung cancer, aiming to elucidate its mechanisms for improving the tumor-immune microenvironment. Herein, we constructed a Lewis lung carcinoma (LLC)-bearing mice model with QFM treatment to observe tumor growth and immune cell changes. Then, the feces were collected and a combinatory study using metagenomes, non-targeted metabonomics, and targeted metabonomics of SCFAs was performed. In vitro experiments have been conducted to estimate the roles of acetate and sodium propionate in CD8+ T cells. Furthermore, we treated tumor-bearing mice with QFM, QFM + MHY1485 (an mTOR activator), and QFM + an antibiotic mixture (ABX) to explore the potential therapeutic benefit of regulation of the tumor microenvironment. A total of 96 compounds were obtained from QFM by UPLC/Q-TOF-MS. Besides, the findings demonstrated that QFM exhibited significant efficacy against lung cancer, manifesting in reduced tumor growth and improved immune responses. In investigating its mechanisms, we integrated gut microbiota sequencing and fecal metabolomics, revealing that QFM effectively restored disruptions in gut microbiota and SCFAs in mice with lung cancer. QFM, acetate, or sodium propionate contributed to the up-regulation of IFN-γ, Gzms-B, perforin, IL-17, IL-6, IL-12, TNF-α expressions and decreased HDAC and IL-10 levels in vitro and in vivo. Moreover, MHY1485 and ABX weakened the effects of QFM on immunomodulation. Collectively, these results suggest that QFM may facilitate immune responses in the LLC-bearing mice via regulating the gut microbiota-derived SCFAs at least partially through targeting the mTOR signaling pathway.

Abstract The application of novel bioorganic fertilizer (BIO) has been established as a weed biocontrol strategy, and reduce herbicides pollution and negatively effects on agricultural ecosystems. However, its long-term influences on soil bacterial communities are unknown. Here, 16 S rRNA sequencing to identify the changes that occur in soil bacterial community and enzyme under BIO treatments after five years in a field experiment. BIO application effectively controlled weeds, however no obvious differences between treatments were observed under BIO-50, BIO-100, BIO-200 and BIO-400 treatment. Anaeromyxobacter and Clostridium_ sensu_ stricto_1 were the two dominant genera among BIO-treated soil samples. The BIO-800 treatment had a slight influence on the species diversity index, which was more remarkable after five years. The seven significantly-different genera between BIO-800 treatment and untreated soils included C._sensu_stricto_1, Syntrophorhabdus, Candidatus_Koribacter, Rhodanobacter, Bryobacter, Haliangium, Anaeromyxobacter. In addition, BIO application had different effects on soil enzymatic activities and chemical properties. The extractable P and pH saliency correlated with Haliangium and C._Koribacter, and C._sensu_stricto_1 observably correlated with exchangeable K, hydrolytic N and organic matter. Taken together, our data suggest that BIO application effectively controlled weeds and a slight influence on soil bacterial communities and enzymes. These findings expand our knowledge of the application of BIO as widely used as a sustainable weed control in rice paddy.

Abstract Space groups describing the symmetry of lattice structure allow the emergence of fermionic quasiparticles with various degeneracy in the band structure. Theoretical efforts have predicted many materials hosting fermions with the highest degeneracy, i.e., eightfold fermions, yet lacking experimental realization. Here, we explore the band degeneracies in TaCo2Te2 crystals. Through systematic experimental and theoretical analyses, we establish TaCo2Te2 as a nonsymmorphic crystal with negligible spin–orbit coupling (SOC) and long-range magnetic order. These critical properties guarantee the realization of practical eightfold fermions and fourfold van Hove singularity, as directly observed by photoemission spectroscopy. TaCo2Te2 serves as a topological quantum critical platform, which can be tuned into various magnetic, topologically trivial, and nontrivial phases by adding strain, magnetic field, or SOC. The latter is demonstrated by our first-principles calculations, which show that enhancing SOC in TaCo2Te2 will promote the experimental observation of bulk hourglass fermions. Our results establish TaCo2Te2 as a platform to explore the interplay between symmetry and band topology.

Abstract Objective Local combined systemic therapy has been an important method for the treatment of unresectable hepatocellular carcinoma (HCC).The purpose of this study was to compare the effectiveness and safety of transarterial chemoembolization (TACE) plus Sorafenib versus TACE plus Apatinib for treating patients with unresectable HCC. Methods The clinical data of patients with unresectable HCC who were treated with TACE plus Sorafenib or TACE plus Apatinib at 5 Chinese medical centers between January 2016 and December 2020 were retrospectively analyzed. Propensity score matching (PSM) was applied to reduce the bias from confounding factors. Results A total of 380 patients were enrolled, of whom 129 cases were treated with TACE plus Sorafenib and 251 cases with TACE plus Apatinib. After the 1:1 PSM, 116 pairs of patients were involved in this study. The results showed that the PFS and OS in the TACE-Sorafenib group were significantly longer than those in the TACE-Apatinib group (PFS: 16.79 ± 6.45 vs. 14.76 ± 6.98 months, P = 0.049; OS: 20.66 ± 6.98 vs. 17.69 ± 6.72 months, P = 0.013). However, the ORR in the TACE-Apatinib group was markedly higher than that in the TACE-Sorafenib group (70.69% vs. 56.03%, P = 0.021). There were more patients with adverse events (AEs) in the TACE-Apatinib group than those in the TACE-Sorafenib group before dose adjustment (87 vs. 63, P = 0.001); however, the number of patients who suffered from AEs was not significantly different between the two groups after the dose adjustment (62 vs. 55, P = 0.148). No treatment-related death was found in the two groups. Subgroup analysis revealed that patients with unresectable HCC could better benefit from regular doses than reduced doses (Sorafenib, 22.59 vs. 18.02, P

BackgroundDespite the crucial role of Chest pain centers (CPCs) in acute myocardial infarction (AMI) management, China's mortality rate for ST-segment elevation myocardial infarction (STEMI) has remained stagnant. This study evaluates the influence of CPC quality control indicators on mortality risk in STEMI patients receiving primary percutaneous coronary intervention (PPCI) during the COVID-19 pandemic.MethodsA cohort of 664 consecutive STEMI patients undergoing PPCI from 2020 to 2022 was analyzed using Cox proportional hazards regression models. The cohort was stratified by Killip classification at admission (Class 1: n = 402, Class ≥2: n = 262).ResultsAt a median follow-up of 17 months, 35 deaths were recorded. In Class ≥2, longer door-to-balloon (D-to-B) time, PCI informed consent time, catheterization laboratory activation time, and diagnosis-to-loading dose dual antiplatelet therapy (DAPT) time were associated with increased mortality risk. In Class 1, consultation time (notice to arrival) under 10 min reduced death risk. In Class ≥2, PCI informed consent time under 20 min decreased mortality risk.ConclusionCPC quality control metrics affect STEMI mortality based on Killip class. Key factors include time indicators and standardization of CPC management. The study provides guidance for quality care during COVID-19.

Abstract ADP‐ribosylation factor 1 (Arf1) is a small GTPase belonging to the Arf family. As a molecular switch, Arf1 is found to regulate retrograde and intra‐Golgi transport, plasma membrane signaling, and organelle function during mitosis. This study aimed to explore the noncanonical roles of Arf1 in cell cycle regulation and cytoskeleton dynamics in meiosis with a mouse oocyte model. Arf1 accumulated in microtubules during oocyte meiosis, and the depletion of Arf1 led to the failure of polar body extrusion. Unlike mitosis, it finds that Arf1 affected Myt1 activity for cyclin B1/CDK1‐based G2/M transition, which disturbed oocyte meiotic resumption. Besides, Arf1 modulated GM130 for the dynamic changes in the Golgi apparatus and Rab35‐based vesicle transport during meiosis. Moreover, Arf1 is associated with Ran GTPase for TPX2 expression, further regulating the Aurora A–polo‐like kinase 1 pathway for meiotic spindle assembly and microtubule stability in oocytes. Further, exogenous Arf1 mRNA supplementation can significantly rescue these defects. In conclusion, results reported the noncanonical functions of Arf1 in G2/M transition and meiotic spindle organization in mouse oocytes.

Indolines, characterized by their diverse biological activities and structural significance, have garnered considerable attention in the realms of natural product synthesis and drug discovery. Concurrently, the incorporation of fluorine atoms into organic molecules has emerged as a powerful strategy to enhance their pharmacological properties. Herein, we report a robust and diastereoselective approach for the synthesis of 2,3-difluorinated indolines through the iodine(I/III)-catalyzed dearomatization of readily available indoles. The protocol operates under mild conditions, displaying excellent functional group tolerance and remarkable diastereoselectivity. By employing this developed protocol, vicinal-difluorinated analogues of indole-containing drugs can be efficiently accessed. Theoretical calculations have shed light on the underlying reaction mechanism, proposing the formation of a β-fluorine-substituted carbocation intermediate. It is postulated that the observed high diastereoselectivity can be attributed to the dipole-dipole interactions facilitated by the C–F bond. Crystallographic analysis has revealed the profound impact of fluorine atom introduction on the conformational preferences of the indoline core. Given the unique structural characteristics and pharmacological significance of 2,3-difluorinated indolines, we anticipate their widespread application in medicinal chemistry and drug discovery endeavors.

Red Monascus pigments (MPs) are a large group of polyketides from the fungus Monascus which have been widely used as food colorants. In this study, a variety of red MPs congeners were prepared to explore promising water-soluble candidates for application in liquid food formulations. The results showed that by combining the two-stage, low-pH fermentation strategy with a downstream purification step of fractional crystallization, precursors of red MPs, namely monascorubrin and rubropunctatin, were obtained with a purity of 91.9%. Then, via the azaphilic addition reaction, 18 types of red MPs congeners carrying different amino acid moieties (MPs-aa) were semi-synthesized. Compared to rubropunctamine and monascorubramine, the water solubility, pH and thermal stability of MPs-aa were improved greatly. MPs-His, MPs-Phe, MPs-Tyr and MPs-Trp were identified to be the most resistant to pasteurization. These findings provide water-soluble red MPs candidates with high thermal stability and an attractive approach for their large scale production.