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This document is a correction notice for an article titled "4,5-Dimethoxycanthin-6-one is a novel LSD1 inhibitor that inhibits proliferation of glioblastoma cells and induces apoptosis and pyroptosis" published in Cancer Cell International. The correction states that there were errors in the WB band for mTOR in Fig. 3B and the Control group of T98G cells in Fig. 4A. The corrected figures are provided in the document. The correction notice also includes a note from the publisher stating their neutrality regarding jurisdictional claims and institutional affiliations. The authors of the article are Wei Li, Bai-Sheng Huang, Yuan-Yuan Xiong, Li-Jian Yang, and Li-Xiang Wu. [Extracted from the article]

The matrix product state (MPS) Ansatz offers a promising approach for finding the ground state of molecular Hamiltonians and solving quantum chemistry problems. Building on this concept, the proposed technique of quantum circuit MPS (QCMPS) enables the simulation of chemical systems using a relatively small number of qubits. In this study, we enhance the optimization performance of the QCMPS Ansatz by employing the variational quantum imaginary time evolution (VarQITE) approach. Guided by McLachlan's variational principle, the VarQITE method provides analytical metrics and gradients, resulting in improved convergence efficiency and robustness of the QCMPS. We validate these improvements numerically through simulations of H2, H4, and LiH molecules. In addition, given that VarQITE is applicable to non-Hermitian Hamiltonians, we evaluate its effectiveness in preparing the ground state of transcorrelated Hamiltonians. This approach yields energy estimates comparable to the complete basis set (CBS) limit while using even fewer qubits. In particular, we perform simulations of the beryllium atom and LiH molecule using only three qubits, maintaining high fidelity with the CBS ground state energy of these systems. This qubit reduction is achieved through the combined advantages of both the QCMPS Ansatz and transcorrelation. Our findings demonstrate the potential practicality of this quantum chemistry algorithm on near-term quantum devices. [ABSTRACT FROM AUTHOR]

Background: To assess the associations of replacing sedentary behavior with different types of physical activity with mortality among the US adults of varying diabetes statuses. Methods: This prospective cohort study included 21,637 participants (mean age, 48.5 y) from the National Health and Nutrition Examination Survey 2007–2018. Physical activity including leisure-time moderate-vigorous-intensity activity (MVPA), walking/bicycling, worktime MVPA, and sedentary behavior. We conducted an isotemporal substitution analysis using Cox regression to estimate the associations between replacements and mortality risks. Results: We found significant protective associations between replacing 30 minutes per day sedentary behavior with 3 types of physical activity and all-cause, cardiovascular disease (CVD) mortality risk (except worktime MVPA for CVD mortality) among total participants, with hazard ratio (HR; 95% confidence interval [CI]) ranging from 0.86 (0.77–0.95) to 0.96 (0.94–0.98). Among participants with diagnosed diabetes, replacing sedentary behavior with leisure-time MVPA was associated with a lower all-cause mortality risk (HR 0.81, 95% CI, 0.70–0.94), which was also observed in other subgroups, with HRs (95% CI) ranging from 0.87 (0.80–0.94) to 0.89 (0.81–0.99). Among those with prediabetes/undiagnosed diabetes, replacing sedentary behavior with walking/bicycling was associated with lower CVD mortality risk, and replacement to work-time MVPA was associated with lower all-cause and CVD mortality risk, with HRs (95% CI) ranging from 0.72 (0.63–0.83) to 0.96 (0.92–0.99). Conclusions: Replacing sedentary behaviors with 30 minutes per day leisure-time MVPA was associated with lower all-cause mortality, regardless of diabetes statuses. Among people with prediabetes/undiagnosed diabetes, walking/bicycling was additionally associated with lower CVD mortality, and worktime MVPA was associated with lower all-cause and CVD mortality. [ABSTRACT FROM AUTHOR]

Copyright of Info DaF: Informationen Deutsch als Fremdsprache is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The advent of Neural-network Quantum States (NQS) has significantly advanced wave function ansatz research, sparking a resurgence in orbital space variational Monte Carlo (VMC) exploration. This work introduces three algorithmic enhancements to reduce computational demands of VMC optimization using NQS: an adaptive learning rate algorithm, constrained optimization, and block optimization. We evaluate the refined algorithm on complex multireference bond stretches of H2O and N2 within the cc-pVDZ basis set and calculate the ground-state energy of the strongly correlated chromium dimer (Cr2) in the Ahlrichs SV basis set. Our results achieve superior accuracy compared to coupled cluster theory at a relatively modest CPU cost. This work demonstrates how to enhance optimization efficiency and robustness using these strategies, opening a new path to optimize large-scale restricted Boltzmann machine-based NQS more effectively and marking a substantial advancement in NQS's practical quantum chemistry applications. [ABSTRACT FROM AUTHOR]

Accurately predicting stock returns is a conundrum in financial market. Solving this conundrum can bring huge economic benefits for investors and also attract the attention of all circles of people. In this paper the authors combine semi-varying coefficient model with technical analysis and statistical learning, and propose semi-varying coefficient panel data model with individual effects to explore the dynamic relations between the stock returns from five companies: CVX, DFS, EMN, LYB, and MET and five technical indicators: CCI, EMV, MOM, ln ATR, ln RSI as well as closing price (ln CP), combine semi-parametric fixed effects estimator, semi-parametric random effects estimator with the testing procedure to distinguish fixed effects (FE) from random effects (RE), and finally apply the estimated dynamic relations and the testing set to predict stock returns in December 2020 for the five companies. The proposed method can accommodate the varying relationship and the interactive relationship between the different technical indicators, and further enhance the prediction accuracy to stock returns. [ABSTRACT FROM AUTHOR]

Inadequate tendon healing and heterotopic bone formation result in substantial pain and disability, yet the specific cells responsible for tendon healing remain uncertain. Here we identify a CD26+ tendon stem/progenitor cells residing in peritendon, which constitutes a primitive stem cell population with self-renewal and multipotent differentiation potentials. CD26+ tendon stem/progenitor cells migrate into the tendon midsubstance and differentiation into tenocytes during tendon healing, while ablation of these cells led to insufficient tendon healing. Additionally, CD26+ tendon stem/progenitor cells contribute to heterotopic ossification and Tenascin-C-Hippo signaling is involved in this process. Targeting Tenascin-C significantly suppresses chondrogenesis of CD26+ tendon stem/progenitor cells and subsequent heterotopic ossification. Our findings provide insights into the identification of tendon stem/progenitor cells and illustrate the essential role of CD26+ tendon stem/progenitor cells in tendon healing and heterotopic bone formation. Chen, et al identify peritendon CD26 expressing tendon stem/progenitor cells that contribute to tendon healing, as well as Tenascin-C/YAP dependent heterotopic ossification. [ABSTRACT FROM AUTHOR]

The corrosion resistance of nickel–titanium nitride (Ni/TiN) composites is significantly influenced by the operation parameters during the jet pulse electrodeposition (JPE) process. The effect of current density, jet rate, TiN concentration, and duty cycle impact on the anti-corrosion property of Ni/TiN composites were investigated and optimized using the response surface method (RSM). After the optimization of the operation parameters, the corrosion current of Ni/TiN composites decreased from 9.52 × 10−5 A/cm2 to 4.63 × 10−5 A/cm2. The corrosion current of Ni/TiN composites decreased initially and then increased with an increase in current density, jet rate, TiN concentration, and duty cycle. During the jet electrodeposition process, the influence of the duty cycle on the corrosion current of Ni/TiN composites was comparatively insignificant, whereas the concentration of TiN had a significant effect on the corrosion current. The error rate between the predicted value and the measured result from the corrosion current of Ni/TiN composites was only 0.64%, indicating the high accuracy of fitting the model. Furthermore, X-ray diffraction (XRD) patterns and scanning electron microscope (SEM) images revealed that the optimized Ni/TiN composites comprised significant Ti content, fine nickel gain, and a compact, smooth structure. In addition, the electrochemical measured results demonstrated that the optimized Ni/TiN composites possessed a low self-corrosion current and high self-corrosion potential. These findings show that the optimized composites have a substantially greater corrosion resistance compared to two other unoptimized Ni/TiN composites. [ABSTRACT FROM AUTHOR]

Aiming at the uncertainty problem caused by the time-varying modeling parameters associated with ship speed in the course tracking control of underactuated surface vessels (USVs), this paper proposes a control algorithm based on the dynamic neural fuzzy model (DNFM). The DNFM simultaneously adjusts the structure and parameters during learning and fully approximates the inverse dynamics of ships. Online identification and modeling lays the model foundation for ship motion control. The trained DNFM, serving as an inverse controller, is connected in parallel with the fractional-order PIλDμ controller to be used for the tracking control of the ship's course. Moreover, the weights of the model can be further adjusted during the course tracking. Taking the actual ship data of a 5446 TEU large container ship, simulation experiments are conducted, respectively, for course tracking, course tracking under wind and wave interferences, and comparison with five different controllers. This proposed controller can overcome the influence of the uncertainty of modeling parameters, tracking the desired course quickly and effectively. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to investigate risk factors for new-onset atrial fibrillation (NOAF) post-percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI), aiming to develop a predictive nomogram for NOAF risk. Methods: A retrospective cohort study involving 397 AMI patients who underwent PCI at a tertiary hospital in Anhui, China, from January 2021 to July 2022 was performed. Patients were divided into NOAF (n = 63) and non-NOAF (n = 334) groups based on post-PCI outcomes. Clinical data were extracted from the hospital information system (HIS) and analyzed using univariate and multivariate logistic regression to identify independent risk factors. A nomogram was generated utilizing R software (version 3.6.1), with its performance evaluated through receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and Bootstrap resampling. Results: Independent risk factors for NOAF included age, left atrial diameter (LAD), Gensini score, N-terminal pro-B-type natriuretic peptide (NT-proBNP), alanine transaminase (ALT), low-density lipoprotein cholesterol (LDL-C), left ventricular end-systolic diameter (LVESD), and ventricular rate (P < 0.05). The nomogram's ROC curve demonstrated an area under the curve (AUC) of 0.925 (95% CI: 0.887–0.963), supported by a Bootstrap-verified AUC of 0.924 (95% CI: 0.883–0.954), reflecting strong discriminative capability. The calibration curve indicated a mean absolute error (MAE) of 0.031 and 0.017 prior to and following Bootstrap verification, respectively, signifying robust calibration. The DCA curve illustrated that the nomogram offered optimal clinical net benefit for patients with a threshold probability of NOAF ranging from 0.01 to 0.99. Conclusion: The nomogram developed from independent risk factors for NOAF exhibits significant predictive accuracy and clinical relevance for evaluating the risk of NOAF in AMI patients following PCI, thereby enabling the identification of high-risk individuals for targeted interventions. [ABSTRACT FROM AUTHOR]

Water flooding is an important way to improve recovery in low‐permeability sandstone oil reservoirs. How to decouple the water flooding process using dynamic and static information is a hot topic. In this paper, taking the Paleocene low‐permeability oil sandstone, BY area, eastern Nanxiang Basin as an example, the microscopic water flooding process in the low‐permeability sandstone matrix was systematically investigated, and the characteristics of water channeling under the conditions of fracture existence were analyzed using the dynamic and static monitoring data. The results show that the target layer mainly develops frequently thin stacked composite sand bodies. Under the combined influence of matrix and fracture seepage, the low‐permeability sandstone developed by water flooding shows that there is a single direction of efficiency. The direction of advantageous water advancement is 45° north–east, and the speed of water flooding advancement is 2.57 m/day. Microscopic water‐drive oil experiments show that bound water is mainly distributed in the original low‐permeability sandstone as a membrane in the pore wall and as short rods in the throat. Differences in pore structure and petrophysical properties affect the residual oil content and degree of oil recovery. For sandstones with good petrophysical properties, mild water flooding can improve crude oil recovery. The increase in oil production is mainly concentrated in the early stage of water flooding development, and the increase in oil recovery degree is not significant with the increase in injection multiples in the middle and late stages. However, for sandstones with relatively poor petrophysical properties, water flooding is more effective in the early and late stages than in the middle stages. Therefore, it is necessary to adjust the water flooding measures according to the differences in the petrophysical properties of the sand body. Local tectonics and natural fracture strikes are important factors affecting the direction of the expansion of water flooding fractures. Overall, the prevention of water channeling in low‐permeability sandstones has to take into account the complex coupling between water flooding fractures, natural fractures, and hydraulic fractures. [ABSTRACT FROM AUTHOR]

Knowledge about the neuronal dynamics and the projectome are both essential for understanding how the neuronal network functions in concert. However, it remains challenging to obtain the neural activity and the brain-wide projectome for the same neurons, especially for neurons in subcortical brain regions. Here, by combining in vivo microscopy and high-definition fluorescence micro-optical sectioning tomography, we have developed strategies for mapping the brain-wide projectome of functionally relevant neurons in the somatosensory cortex, the dorsal hippocampus, and the substantia nigra pars compacta. More importantly, we also developed a strategy to achieve acquiring the neural dynamic and brain-wide projectome of the molecularly defined neuronal subtype. The strategies developed in this study solved the essential problem of linking brain-wide projectome to neuronal dynamics for neurons in subcortical structures and provided valuable approaches for understanding how the brain is functionally organized via intricate connectivity patterns. [ABSTRACT FROM AUTHOR]

Objective: To construct and verify a risk prediction model for sleep disturbance in elderly patients with hypertension, aiming to offer guidance for sleep management in this demographic. Methods: A cohort of 6,708 elderly hypertensive patients from the NHANES database, spanning 2005 to 2018, met the inclusion criteria and were selected for this study. Participants were randomly assigned to a development group (n = 4,696) and a verification group (n = 2,012) in a 7:3 ratio. The occurrence of sleep disturbance was assessed across the subjects. Independent risk factors for sleep disturbance were analyzed using weighted multivariate logistic regression within the development group. A predictive model for sleep disturbance risk in elderly hypertensive patients was developed and verified using Stata 17.0. The model's predictive accuracy and stability were evaluated using the verification group's data. Results: Of the 6,708 subjects, 2,014 (30.02%) were identified with sleep disturbance, and the weighted prevalence of sleep disturbance among elderly hypertensive patients was 33.283%. Weighted multivariate logistic regression analysis in the development group revealed that six factors were independently associated with sleep disturbance: higher total depression scores, higher education level, asthma, overweight, arthritis, and work restriction (OR > 1 and P < 0.05). The area under the receiver operating characteristic (ROC) curve (AUC) for the nomogram prediction model was 0.709 in the development group and 0.707 in the verification group, indicating good discrimination ability. Brier scores for the nomogram model were 0.185 in the development group and 0.189 in the verification group, both below 0.25, suggesting good calibration. Decision Curve Analysis (DCA) determined that the nomogram's clinical net benefit was maximized when the threshold probability for sleep disturbance in elderly hypertensive patients was 0.13–0.67 in the development group and 0.14–0.61 in the verification group, highlighting the model's clinical utility. Limitations: This study is not without its limitations, including issues with data collection, the absence of external validation, and the non-extrapolation of results. Conclusion: The prevalence of sleep disturbance among elderly hypertensive patients stands at 33.283%. The nomogram model, based on identified risk factors for sleep disturbance in this population, has demonstrated good predictive efficiency and clinical relevance. It serves as a valuable tool to assist healthcare providers in identifying elderly hypertensive patients at high risk for sleep disturbance. [ABSTRACT FROM AUTHOR]

The NLR family pyrin domain containing 3 (NLRP3) inflammasome in microglia is intimately linked to the pathogenesis of Alzheimer's disease (AD). Although NLRP3 inflammasome activity is regulated by cellular metabolism, the underlying mechanism remains elusive. Here, we found that under the pathological conditions of AD, the activation of NLRP3 inflammasome in microglia is accompanied by increased glutamine metabolism. Suppression of glutaminase, the rate limiting enzyme in glutamine metabolism, attenuated the NLRP3 inflammasome activation both in the microglia of AD mice and cultured inflammatory microglia. Mechanistically, inhibiting glutaminase blocked the anaplerotic flux of glutamine to the tricarboxylic acid cycle and amino acid synthesis, down-regulated mTORC1 signaling by phosphorylating AMPK, which stimulated mitophagy and limited the accumulation of intracellular reactive oxygen species, ultimately prevented the activation of NLRP3 inflammasomes in activated microglia during AD. Taken together, our findings suggest that glutamine metabolism regulates the activation of NLRP3 inflammasome through mitophagy in microglia, thus providing a potential therapeutic target for AD treatment. [ABSTRACT FROM AUTHOR]

Objective To investigate the determinants of linezolid-associated neurological adverse reactions in patients with multidrug-resistant tuberculosis and develop a risk prediction model for such adverse events. Methods A prospective cohort study design was employed to select 120 patients with drug-resistant pulmonary tuberculosis who received a chemotherapy regimen containing linezolid at Guangzhou Chest Hospital from April 2023 to January 2024 as the study population. Clinical data, adverse reactions, and plasma concentration of linezolid were collected during fasting and at 2 hours post-medication. Univariate analysis and multivariate logistic regression were conducted to identify factors influencing linezolid-related neurological adverse reactions. Furthermore, a prediction model for such adverse reactions was developed, and its predictive efficacy and calibration ability were evaluated using ROC analysis. Results Re-treatment (OR = 2.540, P =0.028), coexistence of cavities (OR = 4.092, P = 0.021), anemia (OR = 10.921,P = 0.005), and Cmin 5 0.7665 mg/L (OR = 6.813,P < 0.001) are independent risk factors for the occurrence of linezolid-related neurological adverse reactions. The prediction model, based on these four factors, exhibits an AUC of 0.851 (95% CI:0.774 ~ 0.929), accompanied by a Youden index of 0.590, a sensitivity of 66.7%, and a specificity of 92.3%. Moreover, the prediction model demonstrates excellent calibration ability. (Hosmer-lemeshow X² = 8.719, P = 0.273). Conclusion In MDR/RR-TB patients, the presence of cavitation, retreatment, and anemia may confer a heightened risk of linezolid-related neurological adverse reactions. A risk prediction model incorporating these four indicators demonstrates significant predictive value for the occurrence of such adverse events. [ABSTRACT FROM AUTHOR]

With the increase in air pollutants and bacteria hazards, conventional melt-blown cloth of polypropylene (PP), which is widely used as the filtering medium, can no longer meet people's needs due to its insufficient filtration efficiency, lack of antibacterial function, etc. In this study, the nanoparticles of the zinc and cobalt imidazolate framework (ZnCo-ZIF) were synthesized and directly incorporated into polylactide (PLA) to prepare PLA/ZnCo-ZIF fibrous membranes through electrospinning methodology. The addition of ZnCo-ZIF resulted in a decrease in the average diameter of fiber from 1.01 μm of pure PLA membrane to 0.72 μm of PLA/ZnCo-ZIF (3 wt%) membrane. The PM filtration and antimicrobial properties of PLA/ZnCo-ZIF fibrous membranes were tested. The PLA/ZnCo-ZIF (2 wt%) membrane displayed great filtration ability, and the filtration efficiencies for PM2.5 and PM10 were 90.88% and 93.00%, compared to 75.76% and 79.37% of PP melt-blown cloth. In addition, the antibacterial rates of the PLA/ZnCo-ZIF (3 wt%) membrane reached 100% and 93.24% against E. coli and S. aureus, which were higher than 85.80% and 90.59% of the PLA/ZIF-8 (3 wt%) membrane. The prepared membranes could be used in the field of masks instead of PP melt-blown fabric, and they solved the problem of the non-degradability and non-functionalization of melt-blown fabric. [ABSTRACT FROM AUTHOR]

Background: Clinical nurses face high-pressure situations requiring rapid decision-making and skilled intervention, impacting their psychological responses and emergency capabilities. Understanding the relationships between psychological factors like gratitude and meaning in life is crucial for improving nurses' performance in emergencies. This study explores the mediating role of gratitude and meaning in life in the impact of psychological responses on clinical nurses' emergency capabilities, aiming to enhance their effectiveness in such situations. Methods: This study is a multi-center cross-sectional survey. A questionnaire survey was conducted among 1833 clinical nurses in five tertiary hospitals in Anhui Province, China including general information questionnaire, nurses' emergency capability scale, Meaning in life scale, Gratitude scale and Psychological response questionnaire. According to the results of the questionnaire survey, a chain mediating model was constructed and tested. Results: The total score of emergency capability of 1833 clinical nurses was (71.65 ± 10.77), the total score of meaning in life was (50.67 ± 9.04), the total score of gratitude was (30.96 ± 3.57), and the total score of psychological response was 13.00 (6.00, 20.00). The emergency capability of subjects was positively correlated with the meaning in life, the total score of gratitude scale and the scores of each dimension of the two scales, and negatively correlated with the total score of psychological response scale and each dimension of this scale (all P < 0.05). The total effect coefficient, direct effect coefficient and indirect effect coefficient of psychological response on nurses' emergency capability are − 0.230, -0.110 and − 0.120 respectively, that is, the indirect effect accounts for 52.17% of the total effect. Among the indirect effects, the specific mediating effects of gratitude and meaning in life account for 22.50% and 62.50% respectively, and the chain mediating effects of gratitude and meaning in life account for 15.00%. Conclusion: Gratitude and meaning in life have multiple mediating roles in the mechanism of psychological response that affecting clinical nurses' emergency capability. Therefore, it is very important to pay attention to dynamically evaluating the psychological response level of clinical nurses, and strive to improve their gratitude and meaning in life, so as to further enhance their emergency response ability. [ABSTRACT FROM AUTHOR]

Sweet potato (Ipomoea batatas L.) is an important food, feed, and industrial raw material and new energy crop. Its rich nutritional value and health effects are increasingly being recognized by consumers, and the demand is increasing. However, due to the continuous cultivation of sweet potato over many years, the degeneration of seedlings and the accumulation of viral diseases are important factors affecting the yield and quality of sweet potatoes. This article provides an overview and analysis of the types and hazards of sweet potato virus diseases, the advantages of virus-free sweet potatoes, the scale of virus-free sweet potato cultivation, sweet potato stem tip virus-free production technology, its development status, and the existing problems. Combined with the development of the sweet potato industry across China, relevant development suggestions are proposed to provide a reference for promoting the healthy, stable, sustainable, high-quality, and efficient development of the sweet potato industry. [ABSTRACT FROM AUTHOR]

It is recognized that the introduction of ceramic particles has been used to produce composite coating in laser cladding to enhance the hardness of Ti6Al4V titanium alloy. In this study, (nano WC + micron TiC)/Ti6Al4V coatings with different composite ceramic contents were manufactured on Ti6Al4V substrate by laser cladding. The effects of the multi-scale composite ceramics on the macroscopic morphology, microstructure, and microhardness of coatings were comprehensively analyzed. The results showed that the coatings were mainly composed of α-Ti and (Ti, W)C1 − x. The partial melting of TiC and WC ceramics resulted in the dissolution of C atoms in the matrix of the coatings, thereby strengthening the coatings through solid solution formation. Meanwhile, the growth of (Ti, W)C1 − x was inhibited, owing to the pinning force exerted by nano WC at the grain boundaries. When the content of nano WC was 1.5 wt%, (Ti, W)C1 − x in the coating exhibited micron-scale dendritic and submicron granular structures. The average size of the (Ti, W)C1 − x was approximately 0.31 µm. Moreover, the optimal microhardness of the coating reached 459.99 HV, representing a 35.99% increase compared to the microhardness of the Ti6Al4V substrate. The enhancement in microhardness was primarily attributed to three key strengthening mechanisms: fine-grain strengthening, Orowan strengthening, and solid-solution strengthening, which were effects induced by the ceramic particles. [ABSTRACT FROM AUTHOR]

Accurately quantifying the complexity of nodes in a network is crucial for revealing their roles and network complexity, as well as predicting network emergent phenomena. In this paper, we propose three novel complexity metrics for nodes to reflect the extent to which they participate in organized, structured interactions in higher-order networks. Our higher-order network is built using the BuildHON+ model, where communities are detected using the Infomap algorithm. Since a physical node may contain one or more higher-order nodes in higher-order networks, it may simultaneously exist in one or more communities. The complexity of a physical node is defined by the number and size of the communities to which it belongs, as well as the number of higher-order nodes it contains within the same community. Empirical flow datasets are used to evaluate the effectiveness of the proposed metrics, and the results demonstrate their efficacy in characterizing node complexity in higher-order networks. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is a prevalent primary liver cancer often associated with chronic hepatitis B virus infection (CHB) and liver cirrhosis (LC), underscoring the critical need for biomarker discovery to improve patient outcomes. Emerging as a promising avenue for biomarker development, proteomic technology leveraging liquid biopsy from small extracellular vesicles (sEV) offers new insights. Here, we evaluated various methods for sEV isolation and identified polysaccharide chitosan (CS) as an optimal approach. Subsequently, we employed optimized CS‐based magnetic beads (Mag‐CS) for sEV separation from serum samples of healthy controls, CHB, LC, and HBV‐HCC patients. Leveraging data‐independent acquisition mass spectrometry coupled with machine learning, we uncovered potential vesicular protein biomarker signatures (KNG1, F11, KLKB1, CAPNS1, CDH1, CPN2, NME2) capable of distinguishing HBV‐HCC from CHB, LC, and non‐HCC conditions. Collectively, our findings highlight the utility of Mag‐CS‐based sEV isolation for identifying early detection biomarkers in HBV‐HCC. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central South University is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Planning Education & Research is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In mammals, global passive demethylation contributes to epigenetic reprogramming during early embryonic development. At this stage, the majority of DNA-methyltransferase 1 (DNMT1) protein is excluded from nucleus, which is considered the primary cause. However, whether the remaining nuclear activity of DNMT1 is regulated by additional mechanisms is unclear. Here, we report that nuclear DNMT1 abundance is finetuned through proteasomal degradation in mouse zygotes. We identify a maternal factor, Pramel15, which targets DNMT1 for degradation via Cullin-RING E3 ligases. Loss of Pramel15 elevates DNMT1 levels in the zygote pronuclei, impairs zygotic DNA demethylation, and causes a stochastic gain of DNA methylation in early embryos. Thus, Pramel15 can modulate the residual level of DNMT1 in the nucleus during zygotic DNA replication, thereby ensuring efficient DNA methylation reprogramming in early embryos. Epigenetic reprogramming involves global loss of DNA methylation, but how this is regulated is not completely understood. Here, Tan et al. run a reverse genetic screen and report that nuclear DNMT1 is finetuned by maternal factor Pramel15 through proteasomal degradation in mouse zygotes. [ABSTRACT FROM AUTHOR]

Background: Aging is an inevitable biological process. Accelerated aging renders adults more susceptible to chronic diseases and increases their mortality rates. Previous studies have reported the relationship between lifestyle factors and phenotypic aging. However, the relationship between intrinsic factors, such as reproductive factors, and phenotypic aging remains unclear. Methods: This study utilized data from the National Health and Nutrition Examination Survey (NHANES), spanning from 1999 to 2010 and 2015–2018, with 14,736 adult women. Random forest imputation was used to handle missing covariate values in the final cohort. Weighted linear regression was utilized to analyze the relationship between women-specific reproductive factors and PhenoAgeAccel. Considering the potential impact of menopausal status on the results, additional analyses were conducted on premenopausal and postmenopausal participants. Additionally, the Life's Essential 8 (LE8) was used to investigate the impact of healthy lifestyle and other factors on the relationship between women-specific reproductive factors and PhenoAgeAccel. Stratified analyses were conducted based on significant interaction p-values. Results: In the fully adjusted models, delayed menarche and gynecological surgery were associated with increased PhenoAgeAccel, whereas pregnancy history were associated with a decrease. Additionally, early or late ages of menopause, first live birth, and last live birth can all negatively impact PhenoAgeAccel. The relationship between women-specific reproductive factors and PhenoAgeAccel differs between premenopausal and postmenopausal women. High LE8 scores positively impacted the relationship between certain reproductive factors (age at menarche, age at menopause, age at first live birth, and age at last live birth) and phenotypic age acceleration. Stratified analysis showed significant interactions for the following variables: BMI with age at menarche, pregnancy history, and age at menopause; ethnicity with age at menopause, age at first live birth, and parity; smoking status with use of contraceptive pills and gynecologic surgery; hypertension with use of contraceptive pills, pregnancy history, and age at menopause. Conclusion: Delayed menarche, gynecological surgery, and early or late ages of menopause, first live birth, and last live birth are associated with accelerated phenotypic aging. High LE8 score may alleviate the adverse effects of reproductive factors on phenotypic aging. [ABSTRACT FROM AUTHOR]

For nearly 80 years, the study of National Political Assembly (Guo Min Can Zheng Hui) has been a hot topic among scholars in mainland China. However there's a scarcity of deep research regarding the reasons and roles of National Political Assembly. This study aims to identify the reasons behind the establishment of National Political Assembly and to explore National Political Assembly’s role in uniting the Chinese. A qualitative research approach was employed, involving collecting primary and secondary historical materials in archives and libraries of China for literature analysis and case studies of representative events or proposals. The findings show that its establishment was related to Japan's aggression, the foreign policies of the United States, Britain, the Soviet Union and other countries, as well as the domestic anti-Japanese parties represented by the Kuomintang and the Communist Party of China, and the people of all walks of life across the country. This paper concludes that in the early days of its establishment, it played a positive role in China's unity against Japan, democratic politics, and economic stability. This research is extremely valuable for studying the history of China's Second Sino-Japanese War and the Second KMT-CPC Collaboration, as well as the economic policies, political proposals, and military strategies of the Kuomintang, the Communist Party of China, and other parties involved in the Second Sino-Japanese War, as well as the history of the Communist Party of China, the Republic of China, and modern Chinese history. [ABSTRACT FROM AUTHOR]

Daylily (Hemerocallis citrina) is a perennial herb of the genus Hemerocallis of Liliaceae. It is also an economically important crop and is widely cultivated. Daylily has nutritional, medicinal and ornamental values. The research literature shows that daylily is a high-quality food raw material rich in soluble sugars, ascorbic acid, flavonoids, dietary fiber, carotenoids, mineral elements, polyphenols and other nutrients, which are effective in clearing heat and diuresis, resolving bruises and stopping bleeding, strengthening the stomach and brain, and reducing serum cholesterol levels. This article reviews the main nutrients of daylily and summarizes the drying process of daylily. In addition, due to the existence of active ingredients, daylily also has a variety of biological activities that are beneficial to human health. This article also highlights the nutritional quality of daylily, the research progress of dried vegetable rehydration technology and dried daylily. In the end, the undeveloped molecular mechanism and functional research status of daylily worldwide are introduced in order to provide reference for the nutritional quality research and dried processing industry of daylily. [ABSTRACT FROM AUTHOR]

Spin gapless semiconductor (SGS) has attracted much attention since its theoretical prediction, while concrete experimental hints are still lacking in the relevant Heusler alloys. Here in this work, by preparing the series alloys of Mn2CoGa1−xAlx (x = 0, 0.25, 0.5, 0.75, and 1), we identified the vanishing of the anomalous Hall effect in the ferromagnetic Mn2CoGa (or x = 0.25) alloy in a wide temperature interval, accompanying with growing contribution from the ordinary Hall effect. As a result, comparatively low carrier density (1020 cm−3) and high carrier mobility (150 cm2/V s) are obtained in the Mn2CoGa (or x = 0.25) alloy in the temperature range of 10–200 K. These also lead to a large dip in the related magnetoresistance at low fields. However, in a high Al content, although the magnetization behavior is not altered significantly, the Hall resistivity is, instead, dominated by the anomalous one, just analogous to that widely reported in Mn2CoAl. The distinct electrical-transport behavior of x = 0 and x = 0.75 (or 1) is presently understood by their possible different scattering mechanism of the anomalous Hall effect due to the differences in the atomic order and conductivity. Our work can expand the existing understanding of the SGS properties and offer a better SGS candidate with higher carrier mobility that can facilitate the application in the spin-injected related devices. [ABSTRACT FROM AUTHOR]

Unraveling the origin of Helmholtz capacitance is of paramount importance for understanding the interfacial structure and electrostatic potential distribution of electric double layers (EDL). In this work, we combined the methods of ab initio molecular dynamics and classical molecular dynamics and modeled electrified Cu(100)/electrolyte and graphene/electrolyte interfaces for comparison. It was proposed that the Helmholtz capacitance is composed of three parts connected in series: the usual solvent capacitance, water chemisorption induced capacitance, and Pauling repulsion caused gap capacitance. We found the Helmholtz capacitance of graphene is significantly lower than that of Cu(100), which was attributed to two intrinsic factors. One is that graphene has a wider gap layer at interface, and the other is that graphene is less active for water chemisorption. Finally, based on our findings, we provide suggestions for how to increase the EDL capacitance of graphene-based materials in future work, and we also suggest that the new understanding of the potential distribution across the Helmholtz layer may help explain some experimental phenomena of electrocatalysis. [ABSTRACT FROM AUTHOR]

A high-efficiency oxygen-evolution reaction (OER) catalyst (FeOOH@CoFeOS/NF) was synthesized on nickel foam (NF), utilizing an intermolecular synergistic effect. The optimized FeOOH@CoFeOS/NF catalyst demonstrated outstanding alkaline OER performance, exhibiting a low overpotential of 212 mV at 10 mA cm−2 (η10) (25 °C), along with a small Tafel slope of 62.8 mV dec−1. Notably, FeOOH@CoFeOS/NF maintained its stability in 1.0 M KOH for 38 h. The achieved results surpassed those of the majority of transition metal oxide sulfide catalysts. This research contributes a valuable methodology for leveraging intermolecular cooperative effects and the development of high-performance OER electrocatalysts. [ABSTRACT FROM AUTHOR]

Fat mass and obesity-associated protein (FTO) was the first m6A demethylase identified, which is responsible for eliminating m6A modifications in target RNAs. While it is well-established that numerous cytosolic and nuclear proteins undergo O-GlcNAcylation, the possibility of FTO being O-GlcNAcylated and its functional implications remain unclear. This study found that a negative correlation between FTO expression and O-GlcNAcylation in patients with myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The decreased O-GlcNAcylation on FTO can result in diminished m6A modification of SRY-related high mobility group box 4 (SOX4). This led to the promotion of cell apoptosis and inhibition of cell proliferation in MDS/AML. The O-GlcNAcylation of FTO stabilized SOX4 transcripts in an m6A-dependent manner, resulting in increased AKT and MAPK phosphorylation and decreased cell apoptosis. Inhibiting FTO O-GlcNAcylation significantly slowed AML progression in vitro, a finding supported by clinical data in MDS/AML patients. In conclusion, our study highlights the crucial role of FTO O-GlcNAcylation in RNA m6A methylation and the progression of MDS/AML, thereby providing a potential therapeutic avenue for these formidable diseases. [ABSTRACT FROM AUTHOR]

Background: Cancer-associated fibroblasts (CAFs) are a pivotal component of the tumor microenvironment (TME), playing key roles in tumor initiation, metastasis, and chemoresistance. While glycosylation is known to regulate various cellular processes, its impact on CAFs activation remains insufficiently explored. Methods: We assessed the correlation between bisecting GlcNAc levels and CAFs markers (α-SMA, PDGFRA, PDGFRB) in breast cancer tissues. The effects of small extracellular vesicles (sEVs) derived from MDA-MB-231/OEvec and MDA-MB-231/OEMGAT3 cells on CAFs activation were examined using western blotting, transwell, and collagen contraction assays. Proteomic analysis was performed to identify dysregulated proteins in sEVs from different cell lines. The role of GAS6 in CAFs activation was validated through in vitro and in vivo experiments. The impact of bisecting GlcNAc modification on GAS6 expression and function was analyzed through protein degradation and N-glycosylation site mutation. The effect of activated CAFs on breast cancer metastasis was evaluated using western blotting and transwell assays. Results: We found that low bisecting GlcNAc levels were associated with CAFs activation within the TME of breast cancer. Breast cancer-derived sEVs stimulated the conversion of normal fibroblasts to CAFs, with GAS6 in sEVs playing a key role by interacting with AXL receptors on fibroblasts. Introducing GAS6 into normal fibroblasts induced their conversion into CAFs, which enhanced breast cancer cell metastasis. Notably, GAS6 was decorated with bisecting GlcNAc, which promoted its degradation in donor cells, leading to reduced GAS6 levels in sEVs and attenuating GAS6-mediated CAFs activation. Conclusion: Taken together, our findings provide new insights into the functional role of bisecting GlcNAc on GAS6-mediated CAFs activation in breast cancer. [ABSTRACT FROM AUTHOR]

Background: Not all breast cancer (BC) patients can benefit from neoadjuvant therapy (NAT). A poor response may result in patients missing the best opportunity for treatment, ultimately leading to a poor prognosis. Thus, to identify an effective predictor that can assess and predict patient response at early time points, we focused on circulating tumor DNA (ctDNA), which is a vital noninvasive liquid biopsy biomarker. We performed a meta-analysis to explore the predictive value of response by monitoring ctDNA at four time points of NAT using pathologic complete response (pCR) and residual cancer burden (RCB). Methods: By searching Embase, PubMed, the Cochrane Library, and the Web of Science until December 24, 2023, we selected studies concerning the relationship between ctDNA and response or prognosis. We analysed the results at the following various time points: baseline (T0), first cycle of NAT (T1), mid-treatment (MT), and end of NAT (EOT). pCR and RCB were used to evaluate the response as the primary endpoint. The secondary endpoint was to investigate the relationship between ctDNA and prognosis. Odds ratios (ORs) and hazard ratios (HRs) were used as effect indicators. Results: Thirteen reports from twelve studies were eligible for inclusion in this meta-analysis. The results demonstrated that ctDNA negativity was associated with pCR at T1 (OR = 0.34; 95% CI: 0.21–0.57), MT (OR = 0.35; 95% CI: 0.20–0.60), and EOT (OR = 0.38; 95% CI: 0.22–0.66). When RCB was used to evaluate responses, ctDNA negativity was associated with RCB-0/I at the MT (OR = 0.34; 95% CI: 0.21–0.55) and EOT (OR = 0.26; 95% CI: 0.15–0.46). Furthermore, ctDNA positivity at T1 predicted a worse prognosis for patients (HR = 2.73; 95% CI: 1.29–5.75). We also performed a subgroup analysis to more accurately assess the predictive value of ctDNA for triple-negative breast cancer. Conclusions: Our meta-analysis suggested that the ctDNA status at the early stage of NAT can predict patient response, which provides evidence for adjusting personalized treatment strategies and improving patient survival. Prospero registration number: CRD42024496465. [ABSTRACT FROM AUTHOR]

Light provides the necessary energy for plant photosynthesis, which allows plants to produce organic matter and energy conversion, during plant growth and development. Light provides material energy to plants as the basis for cell division and differentiation, chlorophyll synthesis, tissue growth and stomatal movement, and light intensity, photoperiod, and light quality play important roles in these processes. There are several regulatory mechanisms involved in sugar metabolism in plants, and light, as one of the regulatory factors, affects cell wall composition, starch granules, sucrose synthesis, and vascular bundle formation. Similarly, sugar species and genes are affected in the context of light-regulated sugar metabolism. We searched the available databases and found that there are fewer relevant reviews. Therefore, this paper provides a summary of the effects of light on plant growth and development and sugar metabolism, further elaborates on the mechanisms of light effects on plants, and provides some new insights for a better understanding of how plant growth is regulated under different light conditions. [ABSTRACT FROM AUTHOR]

Autoimmune polyendocrine syndromes (APS) is a rare group of disorders caused by impaired function of multiple endocrine glands due to disruption of immune tolerance. Of which, type 2 (APS-2) is the most common. Glutamic acid decarboxylase (GAD) is the rate-limiting enzyme for the synthesis of gamma-aminobutyric acid (GABA). Anti-GAD antibodies are associated with various neurological disorders, including stiff person syndrome (SPS). SPS is characterized by axial muscle stiffness, rigidity, and intermittent painful muscle spasms, with a prevalence of one to two in a million, making it an extremely rare neurological disorder. The comorbidity of APS-2 with SPS is even rarer. Most practicing neurologists encounter only one or two cases of APS-2 combined with anti-GAD65 antibody-associated SPS in their careers, resulting in underdiagnosis and undertreatment, leading to severe disability and suffering. This case report describes a young male who initially exhibited hair loss, vitiligo, and previously unreported eosinophilia. Before his diagnosis, he was admitted multiple times, with symptoms improving following the addition of intravenous immunoglobulin (IVIG) therapy to a poor treatment regimen. This paper aims to increase physicians' awareness of this condition, enhancing the likelihood of early diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI). State-of-the-art X-ray snapshots lack high spatial resolution because of weak diffraction signal. Bleaching effects from photo-ionization significantly restrain image brightness scaling. We find that non-linear transient ion resonances can overcome this barrier if X-ray laser pulses are shorter than in most experiments. We compared snapshots from individual ≈ 100 nm Xe nanoparticles as a function of pulse duration and incoming X-ray fluence. Our experimental results and Monte Carlo simulations suggest that transient resonances can increase ionic scattering cross sections significantly beyond literature values. This provides a novel avenue towards substantial improvement of the spatial resolution in CDI in combination with sub-femtosecond temporal precision at the nanoscale. Diffraction-before-destruction of ultrashort X-ray pulses can visualize non-equilibrium processes at the nanoscale with sub-femtosecond precision. Here, the authors demonstrate how the brightness and the spatial resolution of such snapshots can be substantially increased despite ionization. [ABSTRACT FROM AUTHOR]

Introduction: Hepatocellular carcinoma (HCC) is the most prevalent liver cancer and a leading cause of cancer-related deaths worldwide. Heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) plays a critical role in RNA metabolism, including alternative splicing, which is linked to cancer progression. Our study investigated the role of hnRNPA1 in HCC and its potential as a therapeutic target. Methods: We analyzed hnRNPA1 expression in HCC tissues compared to non-tumor tissues using RNA-seq and immunohistochemistry. hnRNPA1 was knocked down in Hep G2 cells to assess its impact on cell proliferation, migration, and apoptosis using scratch assays, flow cytometry, qPCR, and Western blot. We also explored the interaction between hnRNPA1 and ZNF207, as well as its splicing effects and downstream signaling pathways by RIP assay, bioinformatics, qPCR and Western blot. Results: hnRNPA1 was significantly upregulated in HCC tissues compared to normal tissues, correlating with poor patient survival. hnRNPA1 knockdown reduced Hep G2 cell proliferation and migration while increasing apoptosis. We identified that hnRNPA1 bound to ZNF207 and regulated its exon 9 skipping, influencing ZNF207 splicing and the PI3K/Akt/mTOR pathway, key regulators of cell growth and survival. Conclusion: Our findings demonstrate that hnRNPA1 promotes HCC progression by regulating ZNF207 splicing and the PI3K/Akt/mTOR pathway. hnRNPA1-ZNF207 interaction represents a potential therapeutic target for HCC, providing insights into the molecular mechanisms underlying HCC progression. [ABSTRACT FROM AUTHOR]

The growth of dendrites and water-induced side reactions on the zinc (Zn) metal anode surface present significant challenges to the practical application of aqueous zinc ion batteries (AZIBs). To address these challenges, 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM]PF6) was employed as a multifunctional ionic liquid additive. First-principles calculations and molecular dynamics simulations reveal that [BMIM]+ cations preferentially adsorb onto the protrusions of the Zn metal anode surface due to its high adsorption energy, promoting homogeneous Zn2+ ion deposition and effectively mitigating the "tip effect". Simultaneously, the PF6− anions participate in the solvation structure of hydrated Zn2+ ions to minimize the solvation effect by reducing the number of surrounding water (H2O) molecules. This suppresses unexpected side reactions caused by active H2O molecules entering the Helmholtz Plane (HP), thereby optimizing the diffusion and nucleation behaviour of Zn2+ ions. Therefore, the Zn//Zn symmetric cell achieved an extended cycle lifetime of over 1000 h at a high current density of 4 mA cm−2 and a capacity of 0.5 mA h cm−2. Meanwhile, even after 3000 cycles at a high current density of 10 A g−1, the Zn//NH4V4O10 full cell exhibited an impressive capacity retention of 92.7%. The practical application of flexibility further demonstrates that the designed AZIBs exhibit promising potential for large-scale energy storage and provide valuable insights for future studies. [ABSTRACT FROM AUTHOR]

Background: Immunotherapy and radiotherapy play crucial roles in the transformation therapy of locally advanced pancreatic cancer; however, the exploration of effective predictive biomarkers has been unsatisfactory. With the rapid development of radiomics, next-generation sequencing, and machine learning, there is hope to identify biomarkers that can predict the efficacy of transformative treatment for locally advanced pancreatic cancer through simple and non-invasive clinical methods. Our study focuses on using computed tomography (CT), positron emission tomography/computed tomography (PET/CT), gene mutations, and baseline carbohydrate antigen 199 (CA199) to identify biomarkers for predicting the efficacy of transformative treatment. Methods: We retrospectively collected data from 70 patients with locally advanced pancreatic cancer who had undergone a biopsy for pathological diagnosis. These patients had complete baseline enhanced CT images and baseline CA199 results. Among them, 65 patients had efficacy evaluation results after 4 treatment cycles, 54 patients had complete baseline PET/CT images, 51 patients had complete DNA mutation detection results, and 34 patients had both complete PET/CT images and DNA mutation detection results. Additionally, 47 patients had complete available CT images at baseline, after 2 treatment cycles, and after 4 treatment cycles. We extracted radiomic features from the original lesion-enhanced CT images (including baseline and subsequent follow-up CT scans), radiomic features from baseline 18F-fluoro-2-deoxy-2-D-glucose (18F-FDG) PET, and patient-specific features related to abdominal and visceral fat. We used short-term and long-term treatment efficacy as the prediction outcomes and performed statistical and machine learning-based feature selection and COX regression analysis to identify potentially predictive features. Subsequently, we separately or in combination modeled the CT features, PET features, baseline CA199, and gene mutation data to construct efficacy prediction models. Finally, we investigated the mixed effects model of the dynamic changes in CT features at baseline, after 2 treatment cycles, and after 4 treatment cycles on the prediction of short-term treatment efficacy. Results: We found that a combination of CT radiomic features, including F1_ gray level co-occurrence matrix (GLCM), F2_gray level run length matrix (GLRLM), F5_neighboring gray tone difference matrix (NGTDM), and F6_Shape, PET radiomic features such as visceral adipose tissue (VAT), tumor-to-liver ratio (T/L), standardized uptake value mean (SUVmean), and GLCM, as well as baseline CA199, can be used to predict short-term treatment efficacy. Baseline CA199, GLCM, IntensityDirect, Shape, and PET/CT features are independent factors for long-term treatment efficacy. In constructing the short-term treatment efficacy prediction model, ensemble learning methods such as adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and RandomForest performed the best. However, in terms of model interpretability, decision tree methods provide the most intuitive display of the predictive details of the model. For the time series data of patients' baseline CT, CT after 2 treatment cycles, and CT after 4 treatment cycles, long short-term memory (LSTM) modeling yielded better predictive models. Conclusion: A multimodal combination of radiomics, DNA mutations, and baseline CA199 can predict the efficacy of transformative treatment in locally advanced pancreatic cancer. Various feature selection methods and multimodal fusion approaches contribute to guiding personalized and precise treatment for pancreatic cancer. [ABSTRACT FROM AUTHOR]

Background: Abdominal aortic aneurysm (AAA) is one of the most dangerous types of vascular diseases worldwide. Metabolic disturbance affects disease risk and provide underlying therapeutic targets. Previous studies have reported an association between metabolic disorders and AAA. However, evidence of a causal relationship between blood metabolites and AAA is still lacking at present. Methods: Using Mendelian randomization (MR), we assessed the causal association between 1,400 serum metabolites and AAA. The inverse variance weighted method (IVW), weighted median, MR-Egger regression, simple mode, as well as weighted mode methods were used for evaluating the causality between blood metabolites and AAA. Pleiotropy and heterogeneity tests were further conducted. Results: Through strict screening, 17 known metabolites, 7 unknown metabolites and 5 metabolite ratios related to AAA were identified. Among all the metabolites, 24 were found to have negative associations, while 5 exhibited positive associations. The top five metabolites associated with an increased risk of AAA were Oleoyl-linoleoyl-glycerol (18:1/18:2) [2], Glycosyl-N-(2-hydroxynervonoyl)-sphingosine (d18:1/24:1(2OH)), Glycochenodeoxycholate 3-sulfate, X-21441 and X-24328. In contrast, the top five metabolites that were linked to a reduced risk of AAA included Uridine to pseudouridine ratio, Octadecanedioate, Phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2) [2] ratio, 1-(1-enyl-palmitoyl)-GPE (p-16:0), and 1-stearoyl-GPG (18:0). Conclusion: Among the 1,400 blood metabolites, we identified 17 known metabolites, 7 unknown metabolites, and 5 metabolite ratios associated with AAA. This MR study may provide a novel significant insight for the screening and prevention of AAA. [ABSTRACT FROM AUTHOR]

Background: The Apoptosis-Stimulating Protein of P53 (ASPP) family contributes to apoptosis regulation and tumor suppression, with ASPP1 influencing processes like cancer cell proliferation, invasion, and migration. Its expression varies across cancer types, suggesting a potential role in oncogenesis. Methods: This study investigates ASPP1's role across various cancers using a comprehensive bioinformatics approach. Data were extracted from public resources, including The Cancer Genome Atlas (TCGA), GTEx, and the Human Protein Atlas, and analyzed via tools such as cBioPortal, GEPIA, and TIMER2. Statistical and network analyses were performed with R, Cytoscape, and Hiplot. ASPP1's function in colorectal cancer was further explored through in vitro assays, including qRT-PCR, Western blotting, colony formation, Transwell, and wound healing. Results: ASPP1 expression exhibited significant variability across different cancer types, with marked associations with patient outcomes, particularly overall survival (OS) and disease-specific survival (DSS) across several cancer types. In-depth protein-protein interaction (PPI) analysis revealed ASPP1's involvement in apoptosis and cancer progression networks. Functional enrichment analysis further linked ASPP1 to key apoptotic signaling pathways and transcriptional regulatory processes, underscoring its potential impact on tumor biology. Additionally, the expression of ASPP1 correlates with immune cell infiltration patterns, including cancer-associated fibroblasts and various immune markers, suggesting roles in immune response modulation. In vitro assays with colorectal cancer cell lines revealed significantly lower ASPP1 expression levels compared to normal colon cells (HCM460), and ASPP1 overexpression experiments showed a marked reduction in colorectal cancer cell proliferation, colony formation, invasion, and migration abilities. These cellular findings align with the bioinformatics predictions, highlighting ASPP1's role as a suppressor of metastatic traits in colorectal cancer. Conclusion: This study highlights ASPP1 as a forecasting biomarker in the colorectal cancers and potentially across other cancers. The findings support ASPP1's involvement in tumor biology, particularly regarding cell proliferation and metastatic potential, establishing a foundation for further investigation into its therapeutic relevance. [ABSTRACT FROM AUTHOR]

Glycosylation plays a critical role in various biological processes, yet identifying specific glycosyltransferase substrates remains a challenge due to the complexity of glycosylation. Here, we employ proximity labeling with biotin ligases BASU and TurboID to map the proximitome of MGAT3, a glycosyltransferase responsible for the biosynthesis of the bisecting GlcNAc structure, in HEK293T cells. This approach enriched 116 and 189 proteins, respectively, identifying 17 common substrates shared with bisecting GlcNAc-bearing proteome obtained via intact glycopeptide enrichment methods. Gene ontology analysis revealed that the enriched proteins were predominantly localized in the exosome, endoplasmic reticulum, and Golgi apparatus, consistent with subcellular localization of MGAT3 substrates. Notably, four novel substrates, GOLM2, CCDC134, ASPH, and ERO1A, were confirmed to bear bisecting GlcNAc modification, validating the utility of the proximity labeling method. Furthermore, we observed that bisecting GlcNAc modification inhibits breast cancer progression by promoting the degradation of α-galactosidase A (GLA). These findings demonstrate the efficacy of proximity labeling in identifying glycosyltransferase substrates and provide insights into the functional impact of bisecting GlcNAc modification. [ABSTRACT FROM AUTHOR]

In recent years, firefighter accidents and people injured by the collapse of steel structures during a fire have occurred frequently, which has attracted the attention of the National Emergency Management Department and the Fire and Rescue Bureau. It is urgent to carry out research on early warning systems for building collapse during a fire. Existing early warning methods mainly use characteristic parameters such as temperature, vibration, and structural deformation. Due to the complexity of an actual fire, it is difficult to accurately predict the critical temperature of fire−induced instability in columns and the failure mode after the instability, and there are deviations in the collapse warnings. In this study, changes in ultrasonic transverse and longitudinal wave velocities at high temperatures are used to monitor the stiffness degradation of columns in fire in real time and improve the accuracy of early warning systems. In this study, four common collapse modes of portal frames are obtained by using the results of parametric numerical analysis. According to key displacements and the displacement rates of simple key measuring points, the elastic modulus threshold of a three−level early warning for portal frame collapse with different collapse modes is obtained. Combined with an ultrasonic experiment, the theoretical relationships between the transverse and longitudinal wave velocities and the elastic modulus of steel at high temperatures are verified, and the relationship between the transverse and longitudinal wave velocities and the overall damage of the portal frame is further constructed; then, a new early warning method for portal frame stability during a fire is proposed. Based on the change in wave velocity, a three-level early warning index for predicting portal frame stability during a fire is determined. When the collapse mode of a portal frame is an overall inward collapse, transverse and longitudinal wave velocities are reduced to 2635 m/s and 5308 m/s, respectively. At a second-level warning, they are reduced to 2035 m/s and 4176 m/s, respectively. At 1504 m/s and 3030 m/s, respectively, third-level warnings are issued. This research shows that the real−time monitoring of wave velocities provides an effective way for early warning systems to identify structural collapse. The proposed early warning method can be used as a quick and efficient early warning system for the collapse of portal frames during a fire, and its accuracy and applicability are verified by experiments. [ABSTRACT FROM AUTHOR]