Search

Accurate wind power forecasting (WPF) is critical in optimizing grid operations and efficiently managing wind energy resources. Challenges arise from the inherent volatility and non-stationarity of wind data, particularly in short-to-medium-term WPF, which extends to longer forecast horizons. To address these challenges, this study introduces a novel model that integrates Improved Empirical Mode Decomposition (IEMD) with an enhanced Transformer called TransIEMD. TransIEMD begins by decomposing the wind speed into Intrinsic Mode Functions (IMFs) using IEMD, transforming the scalar wind speed into a vector form that enriches the input data to reveal hidden temporal dynamics. Each IMF is then processed with channel attention, embedding, and positional encoding to prepare inputs for an enhanced Transformer. The Direct Embedding Module (DEM) provides an alternative viewpoint on the input data. The distinctive perspectives of IEMD and DEM offer interaction through cross-attention within the encoder, significantly enhancing the ability to capture dynamic wind patterns. By combining cross-attention and self-attention within the encoder–decoder structure, TransIEMD demonstrates enhanced proficiency in detecting and leveraging long-range dependencies and dynamic wind patterns, improving the forecasting precision. Extensive evaluations on a publicly available dataset from the National Renewable Energy Laboratory (NREL) demonstrate that TransIEMD significantly improves the forecasting accuracy across multiple horizons of 4, 8, 16, and 24 h. Specifically, at the 24 h forecast horizon, TransIEMD achieves reductions in the normalized mean absolute error and root mean square error of 4.24% and 4.37%, respectively, compared to the traditional Transformer. These results confirm the efficacy of integrating IEMD with attention mechanisms to enhance the accuracy of WPF.

Ionizing radiation has its unique popularity as a non-thermal decontamination technique treating with protein-rich foodstuffs to ensure the microbial and sensory quality, particularly for shell eggs. However, the changes in the functional properties of egg protein fractions such as liquid egg white (LEW) with macro/microstructural information are still controversial. Hence, this study was designed to elaborate the foaming and heat-set gelation functionality of LEW following different γ-ray irradiation dose treatments (0, 1, 3 or 5 kGy). For such, the physicochemical properties (active sulfhydryl and the hydrophobicity of protein moieties), structural characteristics (through X-ray diffraction, Fourier-transform infrared spectroscopy and differential scanning calorimetry) and interfacial activities (rheological viscosity, interfacial tension, microrheological performance) were investigated. Then, the thermal gelation of LEW in relation to the texture profile and microstructure (by means of a scanning electron microscope) was evaluated followed by the swelling potency analysis of LEW gel in enzyme-free simulated gastric juice. The results indicated that irradiation significantly increased the hydrophobicity of liquid egg white proteins (LEWPs) (p < 0.05) by exposing non-polar groups and the interfacial rearrangement from a β-sheet to linear and smaller crystal structure, leading to an enhanced foaming capacity. Microstructural analysis revealed that the higher dose irradiation (up to 5 kGy) could promote the proteins’ oxidation of LEW alongside protein aggregates formed in the amorphous region, which favored heat-set gelation. As evidenced in microrheology, ≤3 kGy irradiation provided an improved viscoelastic interface film of LEW during gelatinization. Particularly, the LEW gel treated with 1 kGy irradiation had evident swelling resistance during the times of acidification at pH 1.2. These results gave new insight into the irradiation-assisted enhancement of foaming and heat-set gelation properties of LEW.

In this study, we developed a green and multifunctional bioactive nanoemulsion (BBG-NEs) of Blumea balsamifera oil using Bletilla striata polysaccharide (BSP) and glycyrrhizic acid (GA) as natural emulsifiers. The process parameters were optimized using particle size, PDI, and zeta potential as evaluation parameters. The physicochemical properties, stability, transdermal properties, and bioactivities of the BBG-NEs under optimal operating conditions were investigated. Finally, network pharmacology and molecular docking were used to elucidate the potential molecular mechanism underlying its wound-healing properties. After parameter optimization, BBG-NEs exhibited excellent stability and demonstrated favorable in vitro transdermal properties. Furthermore, it displayed enhanced antioxidant and wound-healing effects. SD rats wound-healing experiments demonstrated improved scab formation and accelerated healing in the BBG-NE treatment relative to BBO and emulsifier groups. Pharmacological network analyses showed that AKT1, CXCL8, and EGFR may be key targets of BBG-NEs in wound repair. The results of a scratch assay and Western blotting assay also demonstrated that BBG-NEs could effectively promote cell migration and inhibit inflammatory responses. These results indicate the potential of the developed BBG-NEs for antioxidant and skin wound applications, expanding the utility of natural emulsifiers. Meanwhile, this study provided a preliminary explanation of the potential mechanism of BBG-NEs to promote wound healing through network pharmacology and molecular docking, which provided a basis for the mechanistic study of green multifunctional nanoemulsions.

Bacterial infection is a thorny problem, and it is of great significance to developing green and efficient biological antibacterial agents that can replace antibiotics. This study aimed to rapidly prepare a new type of green antibacterial nanoemulsion containing silver nanoparticles in one step by using Blumea balsamifera oil (BBO) as an oil phase and tea saponin (TS) as a natural emulsifier and reducing agent. The optimum preparation conditions of the AgNPs@BBO-TS NE were determined, as well as its physicochemical properties and antibacterial activity in vitro being investigated. The results showed that the average particle size of the AgNPs@BBO-TS NE was 249.47 ± 6.23 nm, the PDI was 0.239 ± 0.003, and the zeta potential was −35.82 ± 4.26 mV. The produced AgNPs@BBO-TS NE showed good stability after centrifugation and 30-day storage. Moreover, the AgNPs@BBO-TS NE had an excellent antimicrobial effect on Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. These results demonstrated that the AgNPs@BBO-TS NE produced in this study can be used as an efficient and green antibacterial agent in the biomedical field.

Background: Xianlian Jiedu Decoction (XLJDD) is a clinical effective prescription for the treatment of colorectal cancer (CRC) for several decades. However, the effective mechanism and targets of action of XLJDD are still unclear. This study aims to discover the pharmacological mechanism of XLJDD by employing a combination of network pharmacology, molecular docking and in vitro and in vivo experimental validation. Methods: Multiple databases, including TCMSP, Swiss Target Prediction, Drugbank, Geencards, Malacards, Therapeutic Target Database (TTD) and Disgenet, were searched and identified the targets of ingredients from XLJDD and the targets associated with CRC. The common targets of ingredients and disease were analyzed, and the visualization network of protein-protein interaction (PPI) were constructed using STRING database and to identified the core targets based on Cytoscape software. Metascape database was employed for GO and KEGG enrichment analysis of common targets. The active ingredients of XLJDD and core targets were verified through molecular docking test. Subsequently, in vitro and in vivo experiments were performed to validate the analysis results using CT-26 and HCT116 cell lines and AOM/DSS mice model. Results: A total of 36 active components and 122 targets were identified for XLJDD, while 1728 targets associated with CRC were obtained. Among them, there were 71 common targets between ingredients and disease. And 19 core targets (AKT1, TNF, PTGS2, CASP3, EGFR, ESR1, MMP9, IL1B, CCND1, PPARG, ERBB2, SIRT1, MMP2, BCL2L1, MAPK1, PPARA, PGR, AR and SERPINE1.) were finally screened from PPI network. GO analysis enriched a total of 99 entries, with 74 related to biological processes, 20 to molecular functions, and 5 to cellular components. The KEGG enrichment pathway analysis demonstrated that the biological discrepancy was mainly focused on the tumorigenesis-, inflammation-, and mechanism-related pathways. Molecular docking presented the great bonding ability of 19 key targets with 17 active constituents. Experiments based on CT-26 and HCT116 cells verified that XLJDD could inhibit the proliferation of colorectal cancer cells. In addition, XLJDD inhibited tumor progression in mice. Finally, the results of molecular biology experiments showed that XLJDD could activate the colorectal cancer-related PTEN/AKT/FoXO1 pathway, and up-regulate the expression levels of key genes such as AKT1, TNF, PTGS2 and down-regulate the expression levels of CASP3. Conclusions: This study revealed comprehensively the targets and mechanism for the efficacy of XLJDD in treatment of CRC. Furthermore, the results were achieved through in vitro experiment of CT-26 and HCT116 cell lines, and in vivo experiment of AOM/DSS mice.

In the context of the continuous development of Internet technology and international logistics, the impact of cross-border e-commerce is expanding. Cross-border e-commerce transactions are characterized by a wide variety of products, low prices, and short procurement times. As a result, consumers are increasingly intention to shop on cross-border e-commerce platforms. The number of consumers placing orders is also increasing. Simultaneously, consumer perception, trust and attitude play crucial roles in influencing consumers' shopping behavior on cross-border e-commerce platforms. This study employs structural equation and intermediary effect analysis to explore the mechanism through which various factors influence consumers' purchase intention. The authors examine the relationship between five components: consumer perception, trust, attitude, and purchase intention. The findings reveal the following: (1) The improvement of consumers' perceived value and subjective display intention positively influences their purchase intention. Conversely, a decrease in these factors hampers consumers' intention to buy. (2) When the level of shopping risk increases, consumers' purchase intention tends to decrease. Conversely, when the risk of shopping is reduced, consumers' intention to buy shows an increase. (3) Consumer trust and attitude play a significant mediating role in the relationship between independent variables and dependent variables. This study lays an important theoretical foundation for future research in this field. It expands the application scenarios of related research methods. Additionally, the conclusions of this study provide valuable references for managers of cross-border e-commerce enterprises in making informed management decisions.

Background: Since the COVID-19 outbreak, the severity of college student's mental health has increased, with depression being the most prominent. This study's primary purpose was to explore (1) whether the perceived stress of COVID-19 was associated with depression through sequential mediation of mindfulness and dysexecutive function and also (2) the temporal association among mindfulness, dysexecutive function and depression. Methods: We performed two studies to evaluate dysexecutive function as a mechanism through which mindfulness impacts depression under the stress of the COVID-19 pandemic. Study 1 used a sequential mediation model to test the mediating role of mindfulness and dysexecutive function between the perceived stress of COVID-19 and depression based on 1,665 emerging adults. Study 2 used a random-effect, cross-lagged panel model (RE-CLPM) to test the directionality among mindfulness, dysexecutive function, and depression based on 370 emerging adults. Results: The cross-sectional study showed that perceived stress of COVID-19 was positively associated with depression through the sequential mediation of mindfulness and dysexecutive function (effect: 0.08, 95%CI = [0.07, 0.10]), also through the mediation of mindfulness (effect: 0.05, 95%CI = [0.03, 0.06]) and dysexecutive function (effect: 0.08, 95%CI = [0.06, 0.10]) separately. The RE-CLPM study indicated that dysexecutive function mediates the reciprocal relation between mindfulness and depression at the within-person level. Conclusion: These results suggest that dysexecutive function is an intermediate psychological mechanism that exacerbates depression under pandemic-related stress. Mindfulness can predict dysexecutive function and subsequently improve depression. As depression under pandemic-related stress can weaken the mindful state, long-term mindfulness practices are needed to maintain mental health during COVID-19.

BackgroundMild cognitive impairment (MCI) is a transitory yet reversible stage of dementia. Systematic, scientific and population-wide early screening system for MCI is lacking. This study aimed to construct prediction models using longitudinal data to identify potential MCI patients and explore its critical features among Chinese older adults.MethodsA total of 2,128 participants were selected from wave 5–8 of Chinese Longitudinal Healthy Longevity Study. Cognitive function was measured using the Chinese version of Mini-Mental State Examination. Long- short-term memory (LSTM) and three machine learning techniques, including 8 sociodemographic features and 12 health behavior and health status features, were used to predict individual risk of MCI in the next year. Performances of prediction models were evaluated through receiver operating curve and decision curve analysis. The importance of predictors in prediction models were explored using Shapley Additive explanation (SHAP) model.ResultsThe area under the curve values of three models were around 0.90 and decision curve analysis indicated that the net benefit of XGboost and Random Forest were approximate when threshold is lower than 0.8. SHAP models showed that age, education, respiratory disease, gastrointestinal ulcer and self-rated health are the five most important predictors of MCI.ConclusionThis screening method of MCI, combining LSTM and machine learning, successfully predicted the risk of MCI using longitudinal datasets, and enables health care providers to implement early intervention to delay the process from MCI to dementia, reducing the incidence and treatment cost of dementia ultimately.

Abstract Background Metabolic syndrome and obesity are risk factors for gallstones. However, these two factors often occur together, and few studies have focused on the association between metabolically healthy overweight/obesity (MHOW/MHO) and gallstones. We hypothesized that MHO individuals would be associated with the prevalence of gallstones. Methods This cross-sectional study included 125,668 participants aged 18–80 years at the Health Promotion Center of Run Run Run Shaw Hospital, Zhejiang University School of Medicine during 2017–2019 years. Each participant underwent a comprehensive health checkup. Gallstones were diagnosed by abdominal ultrasonography. Metabolically health was defined as not meeting the diagnostic criteria for metabolic syndrome (MetS). Obesity was measured by BMI. MetS and weight stratification were combined to classify the metabolism-obesity phenotypes. Logistic regression models were used to estimate adjusted odds ratios (ORs) and 95% CIs. Results Among 125,668 participants, 5486 (4.4%) had gallstones. 21407 (17.0%) were MHOW individuals, and 3322 (2.6%) were MHO individuals. MHOW (OR 1.40; 95%CI: 1.29–1.53) and MHO (OR 1.80; 95%CI: 1.53–2.12) participants were at higher risk of gallstones and had larger and more numerous gallstones than metabolically healthy normal weight participants. Obesity, MetS, premenopausal women and advanced age were significantly associated with the prevalence of gallstones. Conclusions MHOW/MHO individuals exhibited a higher risk of gallstones. In metabolically healthy individuals, the risk of gallstones increased with increasing BMI. Thus, obesity was associated with the prevalence of gallstones, even in relatively metabolically healthy adults.

Abstract Background Schizophrenia (SZ) arises from a complex interplay involving genetic and molecular factors. Early intervention of SZ hinges upon understanding its vulnerability and resiliency factors in study of SZ and genetic high risk for SZ (GHR). Methods Herein, using integrative and multimodal strategies, we first performed a longitudinal study of neural function as measured by amplitude of low frequency function (ALFF) in 21 SZ, 26 GHR, and 39 healthy controls to characterize neurodevelopmental trajectories of SZ and GHR. Then, we examined the relationship between polygenic risk score for SZ (SZ-PRS), lipid metabolism, and ALFF in 78 SZ, and 75 GHR in cross-sectional design to understand its genetic and molecular substrates. Results Across time, SZ and GHR diverge in ALFF alterations of the left medial orbital frontal cortex (MOF). At baseline, both SZ and GHR had increased left MOF ALFF compared to HC (P

Diabetes is a complex metabolic disease. In recent years, diabetes and its chronic complications have become a health hotspot of global concern. I t is very important to find promising therapeutic targets and directions. Ferroptosis is a new type of programmed cell death that is different from cell necrosis, apoptosis, and autop hagy. Ferroptosis is mainly characterized by iron-dependent lipid peroxidation. With the reduction of the anti-oxidative capacity of cells, the accumulated reactive lipid oxygen species will cause oxidative cell death and lead to ferroptosis at lethal levels. Recent studies have shown that ferroptosis plays an important regulatory role in the initiation and development of diabetes, as well as various complications of diabetes. In this review, we will summ arize new findings related to ferroptosis and diabetic complications and propose ferroptosis as a potential target for treating diabetic complications.

Abstract Emerging evidence showed that epigenetic regulation plays important role in the pathogenesis of HCC. N4-acetocytidine (ac4C) was an acetylation chemical modification of mRNA, and NAT10 is reported to regulate ac4C modification and enhance endoplasmic reticulum stress (ERS) in tumor metastasis. Here, we report a novel mechanism by which NAT10-mediated mRNA ac4C-modified HSP90AA1 regulates metastasis and tumor resistance in ERS of HCC. Immunohistochemical, bioinformatics analyses, and in vitro and in vivo experiments, e.g., acRIP-Seq, RNA-Seq, and double luciferase reporter experiment, were employed to investigate the effect of NAT10 on metastasis and drug resistance in HCC. The increased expression of NAT10 was associated with HCC risk and poor prognosis. Cell and animal experiments showed that NAT10 enhanced the metastasis ability and apoptosis resistance of HCC cells in ERS and ERS state. NAT10 could upregulate the modification level of HSP90AA1 mRNA ac4C, maintain the stability of HSP90AA1, and upregulate the expression of HSP90AA1, which further promotes the metastasis of ERS hepatoma cells and the resistance to apoptosis of Lenvatinib. This study proposes a novel mechanism by which NAT10-mediated mRNA ac4C modification regulates tumor metastasis. In addition, we demonstrated the regulatory effect of NAT10-HSP90AA1 on metastasis and drug resistance of ERS in HCC cells.

Abstract Background To compare the clinical and radiologic outcomes after anterior cervical dynamic or static plate fixation for short segment cervical degenerative disc diseases (DDD) for more than 5 years. Methods Sixty-four patients who underwent anterior cervical one level discectomy or corpectomy with an anterior cervical plate system were followed for an average of 6.8 years for clinical and radiographic outcomes. Among the sixty-four patients, thirty-eight patients were fixed with a static plate (ORION and CSLP plate system) and the other twenty-six patients were fixed with a dynamic plate (ABC plate). Radiographic data were collected included the global sagittal alignment of the cervical spine (C2–C7), the local height and angle of the operated level pre-operatively, postoperatively and at last follow-up. A clinical assessment was performed at pre-operatively, three months postoperatively and final follow-up using the Japanese Orthopedic Association (JOA) /Visual Analogue Score(VAS)/ Neck Disablility Index(NDI) scoring system. Results The mean follow-up time was 6.8 years. At final review, there were two cases of suspicious pseudarthrosis which were from ABC plate fixation group while the other cases all gained solid fusion. The height of fusion segment gained significantly improvement for both dynamic and static plate group post-operation, and all groups demonstrated a significant loss in height postoperatively. Generally, for the one level ACDF group, the height decrease was 0.5 mm for static plate and 1.6 mm for dynamic group which was significantly different(p

Abstract Background During October 2021, China experienced localized outbreaks of COVID-19 in many cities. We analyzed the small local outbreak in Zunyi (Guizhou Province), a major city in southwestern China, and modeled the effects of different interventions on this outbreak. Methods Data on infections and contacts, provided by the Health Commission of Guizhou Province, were used to analyze the epidemiological characteristics of the outbreak and calculate the effectiveness of vaccination. A branching process model was used to simulate the outbreak. This model considered the time interval from exposure of the initial case to confirmation, the number of potential infections caused by the initial case, and the effects of the different interventions. Results From 18 to 25 October 2021, there were 12 patients with COVID-19 in Zunyi. Overall, the average age was 67.17 years-old, 8 patients were females, and 1 patient had an asymptomatic infection. The effectiveness of two-dose inactivated vaccine against SARS-CoV-2 infection was 16.7% (95% CI: 2.8% to 99.7%). The initial case was infected on 11 or 12 October 2021, 6.40 (95% CI: 6.37, 6.42; IQR: 4.92, 7.63) days before confirmation while the travelling in Lanzhou (Gansu Province). There were 10.07 (95% CI: 10.04, 10.09; IQR: 7.86, 11.93) potential secondary cases. When the effective vaccine coverage reached 60%, the probability of cumulative cases exceeding 20 was less than 8.77%, even if contact tracing was relaxed or eliminated. However, if the probability of tracing contacts decreased, earlier initiation of nucleic acid testing was necessary to control the outbreak. Conclusions The COVID-19 outbreak in Zunyi was controlled quickly due to moderately effective vaccine coverage and rapid contact tracing. For controlling localized outbreaks, vaccination and contact tracing seemed to be more effective than massive nucleic acid testing in the initial phase of transmission. However, if there is low effective vaccine coverage or insufficient contact tracing, nucleic acid testing should start earlier.

Abstract Background From 20 July to 26 August 2021, local outbreaks of COVID-19 occurred in Nanjing City and Yangzhou City (Jiangsu Province, China). We analyzed the characteristics of these outbreaks in an effort to develop specific and effective intervention strategies. Methods Publicly available data on the characteristics of the COVID-19 outbreaks in Jiangsu Province were collected. Logistic regression was used to assess the association of age and sex with clinical severity. Analysis of onset dates, generation time distributions, and locations were used to estimate the mean transmission distance. A branching process model was used to evaluate different management strategies. Results From 20 July to 26 August 2021, 820 patients were diagnosed with COVID-19 in Jiangsu Province, with 235 patients (28.7%) from Nanjing, 570 (69.5%) from Yangzhou, and 15 (1.8%) from other cities. Overall, 57.9% of the patients were female, 13.7% were under 20 years-old, and 58.3% had moderate disease status. The mean transmission distance was 4.12 km, and closed-loop management of the area within 2.23 km of cases seemed sufficient to control an outbreak. The model predicted that the cumulative cases in Yangzhou would increase from 311 to 642 if the interval between rounds of nucleic acid amplification testing (NAAT) increased from 1 to 6 days. It also predicted there would be 44.7% more patients if the NAAT started 10 days (rather than 0 days) after diagnosis of the first case. The proportion of cases detected by NAAT would increase from 11.16 to 44.12% when the rounds of NAAT increased from 1 to 7 within 17 days. When the effective vaccine coverage was 50%, the outbreak would be controlled even when using the most relaxed non-pharmaceutical interventions. Conclusions The model predicted that a timely closed-loop management of a 2.23 km area around positive COVID-19 cases was sufficient to control the outbreak. Prompt serial NAAT is likely to contain an outbreak quickly, and our model results indicated that three rounds of NAAT sufficiently controlled local transmission. Trial registration We did not involve clinical trial.

The use of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) is the first line treatment for EGFR-mutant advanced non-small cell lung cancer (NSCLC), but drug resistance will be acquired within 1-2 years, and the following treatment efficacy is poor. The invention of programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) inhibitors has dramatically changed the situation of tumor treatment. PD-1/PD-L1 inhibitors are less effective in patients with NSCLC harboring EGFR mutation. It is a challenge to make patients with EGFR-mutated advanced NSCLC benefit from anti-PD-1/PD-L1 therapy. In this paper, the research progress on the impact of EGFR mutation on the immune status of NSCLC and related clinical studies in recent 5 years are reviewed.

Abstract Background Leukocyte phytohemagglutinin (PHA-L), derived from the L4 tetramer of PHA, has been frequently employed as a mitogen to induce T lymphocyte proliferation in vitro. The biological application of PHA-L in cancer diagnosis and treatment has gained traction in recent years. However, it has been noted that PHA-L obtained using traditional procedures has a massive amount of impurities or toxic components, which interfere with the activity of PHA-L. Preparation of a monoclonal antibody against active PHA-L is a significant tool for studying PHA-L's function and therapeutic potential. Results We successfully prepared monoclonal antibodies against the active components of PHA-L based on the whole PHA-L protein as an antigen, and found that monoclonal antibody 3C1C6G11 can be employed in western blot, immunofluorescence, and immunohistochemistry detection. Importantly, preliminary result shows that the mAb 3C1C6G11 may prevent PHA-L-induced cell aggregation and AICD (activation-induced cell death). Conclusions The monoclonal antibody mAb 3C1C6G11 prepared in this study can be used as an effective tool for detecting PHA-L active components, investigating PHA-L's function and antineoplastic application.

Fractional vortex beams have attracted increasing attention due to their complex yet intriguing physical properties, such as radial notch intensity distribution and higher degrees of modulation in orbital angular momentum. In this study, we experimentally investigated and compared the beam spread and beam wander characteristics of fractional-order vortex beams with those of integer-order vortex beams after passing through a turbulent atmosphere simulator with varying turbulence intensities. Our results revealed that the beam spread of both fractional-order and integer-order vortex beams increased in a stepwise manner with the topological charge number, indicating that a larger topological charge number resulted in more severe beam spread. Interestingly, we observed that the beam radius of fractional-order vortex beams between two adjacent integer orders initially grew slowly and then rapidly before finally stabilizing into a curvilinear growth trend. This is in contrast to the linear growth trend exhibited by the beam radius of integer-order vortex beams. Furthermore, we found that the growth of the beam radius of half-integer-order vortex beams followed the linear growth trend of the beam radius of integer-order vortex beams. When the integer part of the topological charge was fixed, we observed that stronger turbulence resulted in more severe beam wander for both integer-order and fractional-order vortex beams, with the variance of the center-of-mass drift following the same growth curve. However, when the turbulence intensity is constant, both integer-order and fractional-order vortex beams exhibit a weaker beam wander effect with increasing topological charge. Our findings may provide valuable insights for applications such as optical communication and optical measurement using fractional-order vortex beams.

Lycii Fructus (LF) is a medicinal-edible homology material frequently used for treating age-related macular degeneration (AMD) in Chinese medicine. Abundant of literatures verified the retina protection effect of LF on AMD-like animal models. However, previous studies on LF attenuating retinal damage mainly focused on its protection effect on pigment epithelial cells and optic ganglion cells while few reports on Müller cells. In the current study, we found that LF extracts attenuated oxidation damages and inhibited cell apoptosis of retina on a mouse retinal injury model induced by sodium iodate. LF extracts also increased expressions of Müller cell biomarker glutamine synthetase of eyeballs of model mice, which indicated that LF extract protected Müller cell from oxidation injury induced by sodium iodate. In Müller cell MIO-M1 cultures, LF also significantly inhibited cellular apoptosis induced by NaIO3 by regulating Nrf2/HO-1 signaling pathway and the aqueous extracts exerted better active tendency than ethanol extracts. These data implied that the antioxidant effect of LF on protecting Müller cell might contribute to its retina repair function, thereby providing more scientific evidences for the development of LF as an alternative therapy or preventive measures for AMD.

PurposeThe primary objective is to optimize the population eligible for Mammotome Minimally Invasive Surgery (MIS) by refining selection criteria. This involves maximizing procedure benefits, minimizing malignancy risk, and reducing the rate of malignant outcomes.Patients and methodsA total of 1158 female patients who came to our hospital from November 2016 to August 2021 for the Mammotome MIS were analyzed retrospectively. Following χ2 tests to screen for risk variables, binary logistic regression analysis was used to determine the independent predictors of malignant lesions. In addition, the correlation between age and lesion diameter was investigated for BI-RADS ultrasound (US) category 4a lesions in order to better understand the relationship between these variables.ResultsThe malignancy rates of BI-RADS US category 3, category 4a and category 4b patients who underwent the Mammotome MIS were 0.6% (9/1562), 6.4% (37/578) and 8.3% (2/24) respectively. Malignant lesions were more common in patients over the age of 40, have visible blood supply, and BI-RADS category 4 of mammography. In BI-RADS US category 4a lesions, the diameter of malignant tumor was highly correlated with age, and this correlation was strengthened in patients over the age of 40 and with BI-RADS category 4 of mammography.ConclusionThe results of this study demonstrate that the clinical data and imaging results, particularly age, blood supply, and mammography classification, offer valuable insights to optimize patients’ surgical options and decrease the incidence of malignant outcomes.

In this work, a modeling approach has been developed for describing component separation by selective membrane systems. The developed modeling strategy in this research is based on computational fluid dynamics (CFD) integrated with machine learning (ML) approach to reduce the computational costs and evaluate the possibility of ML model for integration to CFD models. The considered case study is a membrane-based molecular separation for removal of species from water. CFD was performed to solve mass transfer equations, and the data in form of concentration profiles have been used for ML computations. The data set in this research has about two thousand data vectors, each of which contains two inputs r and z and one output C which is the species concentration in the feed channel of membrane. Three models, Multi-Layer Perceptron (MLP), Support Vector Machines with RBF kernel (RBF-SVM), and Decision Tree (DT) were chosen for modeling since they were anticipated to perform well on the provided data by adjusting their hyper-parameters. After optimizing the models, their results were carefully checked with different criteria. All three models showed acceptable results with R2 score criteria higher than 0.9. MAPE decreased to 3.57 × 10−3 and improved to 3.6 with the RMSE criterion. We can introduce the best model in this research as the MLP model for description of the mass transfer in the membrane.

In the handling or processing process, fruits are easily crushed by external loads. This type of damage in fruit often leads to the internal pulp browning and rotting, with the severity largely dependent on the fruit tissue’s geometric and mechanical properties. In kiwifruits, with their thin skin and dark-colored flesh, it is particularly challenging to observe and analyze the damage caused by extrusion through traditional experimental methods. The objective of this research is to construct a multi-scale finite element model encompassing the skin, flesh, and core by measuring the geometric and mechanical properties of kiwifruit, to assess and predict the damage characteristics under compression, and to verify the accuracy of the finite element model through experiments. The results indicated that kiwifruits demonstrated different compressive strengths in different directions during compression. The compressive strength in the axial direction was higher than that in the radial direction, and there was little difference between the long and short radial directions. The flesh tissue is the most vulnerable to mechanical damage under external compression, followed by the core. At strain levels below 5%, there was no noticeable damage in the axial or radial directions of the kiwifruit. However, when strain exceeded 5%, damage began to manifest in some of the flesh tissue. To maintain fruit quality during storage and transportation, the stacking height should not exceed 77 fruits in the axial direction, 48 in the long direction, and 53 in the short direction. The finite element analysis showed that the established model can effectively simulate and predict the internal damage behavior of kiwifruits under compression loads, which is helpful for a deeper understanding of the mechanical properties of fruits and provides a theoretical basis and technical guidance for minimizing mechanical damage during fruit handling.

Hyperlipidemia, characterized by elevated serum lipid concentrations resulting from lipid metabolism dysfunction, represents a prevalent global health concern. Ginsenoside Rb1, compound K (CK), and 20(S)-protopanaxadiol (PPD), bioactive constituents derived from Panax ginseng, have shown promise in mitigating lipid metabolism disorders. However, the comparative efficacy and underlying mechanisms of these compounds in hyperlipidemia prevention remain inadequately explored. This study investigates the impact of ginsenoside Rb1, CK, and PPD supplementation on hyperlipidemia in rats induced by a high-fat diet. Our findings demonstrate that ginsenoside Rb1 significantly decreased body weight and body weight gain, ameliorated hepatic steatosis, and improved dyslipidemia in HFD-fed rats, outperforming CK and PPD. Moreover, ginsenoside Rb1, CK, and PPD distinctly modified gut microbiota composition and function. Ginsenoside Rb1 increased the relative abundance of Blautia and Eubacterium, while PPD elevated Akkermansia levels. Both CK and PPD increased Prevotella and Bacteroides, whereas Clostridium-sensu-stricto and Lactobacillus were reduced following treatment with all three compounds. Notably, only ginsenoside Rb1 enhanced lipid metabolism by modulating the PPARγ/ACC/FAS signaling pathway and promoting fatty acid β-oxidation. Additionally, all three ginsenosides markedly improved bile acid enterohepatic circulation via the FXR/CYP7A1 pathway, reducing hepatic and serum total bile acids and modulating bile acid pool composition by decreasing primary/unconjugated bile acids (CA, CDCA, and β-MCA) and increasing conjugated bile acids (TCDCA, GCDCA, GDCA, and TUDCA), correlated with gut microbiota changes. In conclusion, our results suggest that ginsenoside Rb1, CK, and PPD supplementation offer promising prebiotic interventions for managing HFD-induced hyperlipidemia in rats, with ginsenoside Rb1 demonstrating superior efficacy.

Breast cancer, characterized by its molecular intricacy, has witnessed a surge in targeted therapeutics owing to the rise of small-molecule drugs. These entities, derived from cutting-edge synthetic routes, often encompassing multistage reactions and chiral synthesis, target a spectrum of oncogenic pathways. Their mechanisms of action range from modulating hormone receptor signaling and inhibiting kinase activity, to impeding DNA damage repair mechanisms. Clinical applications of these drugs have resulted in enhanced patient survival rates, reduction in disease recurrence, and improved overall therapeutic indices. Notably, certain molecules have showcased efficacy in drug-resistant breast cancer phenotypes, highlighting their potential in addressing treatment challenges. The evolution and approval of small-molecule drugs have ushered in a new era for breast cancer therapeutics. Their tailored synthetic pathways and defined mechanisms of action have augmented the precision and efficacy of treatment regimens, paving the way for improved patient outcomes in the face of this pervasive malignancy. The present review embarks on a detailed exploration of small-molecule drugs that have secured regulatory approval for breast cancer treatment, emphasizing their clinical applications, synthetic pathways, and distinct mechanisms of action.

The rail is an important factor in railway traffic safety. Surface defects in the rail head comprise a common type of rail damage, and magnetic flux leakage (MFL) technology is applied for its detection. MFL detection is influenced by various factors, resulting in high noise and a low signal-to-noise ratio (SNR) in the collected MFL signal, which influence defect assessment. This article improves the empirical wavelet transform (EWT) to apply it to rail surface-defect MFL signal filtering. A boundary optimization method based on mutual information (MI) is proposed to reduce the boundary redundancy caused by adaptive spectrum division. A method for component selection based on MI and kurtosis is proposed to select the suitable components from the decomposed components for signal reconstruction. The experimental results show that the method can effectively filter out the interference in the MFL signal, and the effectiveness is superior to the traditional methods, such as complementary ensemble empirical mode decomposition (CEEMD) and wavelet transform (WT).

AimsWe aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism.MethodsFive datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature.ResultsWe identified three PMOP-related subtypes and four core modules. The muscle system process, muscle contraction, and actin filament-based movement were more active in the hub genes. We obtained five feature genes related to PMOP. Our analysis verified that the gene signature had good predictive power and applicability. The outcomes of the GSE56815 cohort were found to be consistent with the results of the earlier studies. qRT-PCR results showed that RAB2A and FYCO1 were amplified in clinical samples.ConclusionThe PMOP-related gene signature we developed and verified can accurately predict the risk of PMOP in patients. These results can elucidate the molecular mechanism of RAB2A and FYCO1 underlying PMOP, and yield new and improved treatment strategies, ultimately helping PMOP monitoring.Cite this article: Bone Joint Res 2022;11(8):548–560.

Abstract Background Postoperative delirium (POD), one of the most common complications following major surgery, imposes a heavy burden on patients and society. The objective of this exploratory study was to conduct a secondary analysis to identify whether there exist novel and reliable serum biomarkers for the prediction of POD. Methods A total of 131 adult patients (≥ 65 years) undergoing lower extremity orthopedic surgery with were enrolled in this study. Cognitive function was assessed preoperatively with Mini-Mental State Examination (MMSE). Delirium was diagnosed according to the Confusion Assessment Method (CAM) criteria on preoperative day and postoperative days 1–3. The preoperative serum levels of a panel of 16 biochemical parameters were measured by ELISA. Results Thirty-five patients developed POD, with an incidence of 26.7%. Patients in POD group were older (P = 0.001) and had lower preoperative MMSE scores (P = 0.001). Preoperative serum levels of prostaglandin E2 (PGE2, P

Abstract Endoplasmic reticulum (ER) stress is widely involved in the drug resistance of hepatocellular carcinoma (HCC), but the mechanism of ER stress-induced drug resistance involves multiple signaling pathways that cannot be fully explained. Exploring genes associated with ER stress could yield a novel therapeutic target for ER stress-induced drug resistance. By analyzing RNA-sequencing, ATAC-sequencing, and Chip-sequencing data of Tunicamycin (TM)-treated or untreated HCC cells, we found that Rho guanine nucleotide exchange factor 2 (ARHGEF2) is upregulated in HCC cells with ER stress. ARHGEF2 plays an active role in tumor malignant progression. Notwithstanding, no research has been done on the link between ER stress and ARHGEF2. The function of ARHGEF2 as a novel downstream effector of ER stress in the angiogenesis and treatment resistance of HCC was revealed in this work. ARHGEF2 overexpression was linked to malignant development and a poor prognosis in HCC. ER stress stimulates the expression of ARHGEF2 through upregulation of ZNF263. Elevated ARHGEF2 accelerates HCC angiogenesis via the EDN1 pathway, enhances HCC cell proliferation and tumor growth both in vitro and in vivo, and contributes to ER stress-related treatment resistance. HCC cell growth was more inhibited when ARHGEF2 knockdown was paired with targeted medicines. Collectively, we uncovered a previously hidden mechanism where ARHGEF2/EDN1 pathway promotes angiogenesis and participates in ER stress-related drug resistance in HCC.

BackgroundDi(2-ethylhexyl)phthalate (DEHP) and dibutyl phthalate (DBP) are representative environmental endocrine disruptors of phthalate esters (PAEs). Some studies have shown that PAEs exposure may have an impact on lipid metabolism.ObjectiveTo investigate the effects of DEHP and/or DBP on lipid metabolism in rats and their possible mechanisms of action. MethodsThirty-six weaned healthy SD male rats, 3 weeks old, weighing 50-70 g, were divided into four groups, i.e., a corn oil control group, a DEHP (750 mg·kg−1) group, a DBP (500 mg·kg−1) group, and a DEHP+DBP (750 mg·kg−1+500 mg·kg−1) group. The rats were exposed to DEHP and/or DBP by oral gavage for 8 weeks, and weighed once a week. The rats were anesthetized 24 h after the last dose, and blood was taken from the apical part of the heart. Serum high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), total cholesterol (TC), and triglyceride (TG) were detected. Liver tissues and perigenital adipose tissues were collected, weighed, and one portion of the tissues was fixed in 10% neutral formalin for pathomorphological observation, and another portion was used for mRNA detection of lipid metabolism-related genes such as Janus kinase 3 (JAK3), signal transducer and activator of transcription 5b (STAT5b), and peroxisome proliferator-activated receptor γ (PPARγ). ResultsDuring the DEHP and/or DBP exposure period, the rats in all groups were free to eat and drink without death or injury observed. Compared with the control group: The body weight gain in the DEHP+DBP group was lower at all time points from the 2nd week onwards (P

Abstract Stiffness is an important physical property of biomaterials that determines stem cell fate. Guiding stem cell differentiation via stiffness modulation has been considered in tissue engineering. However, the mechanism by which material stiffness regulates stem cell differentiation into the tendon lineage remains controversial. Increasing evidence demonstrates that immune cells interact with implanted biomaterials and regulate stem cell behaviors via paracrine signaling; however, the role of this mechanism in tendon differentiation is not clear. In this study, polydimethylsiloxane (PDMS) substrates with different stiffnesses are developed, and the tenogenic differentiation of mesenchymal stem cells (MSCs) exposed to different stiffnesses and macrophage paracrine signals is investigated. The results reveal that lower stiffnesses facilitates tenogenic differentiation of MSCs, while macrophage paracrine signals at these stiffnesses suppress the differentiation. When exposed to these two stimuli, MSCs still exhibit enhanced tendon differentiation, which is further elucidated by global proteomic analysis. Following subcutaneous implantation in rats for 2 weeks, soft biomaterial induces only low inflammation and promotes tendon‐like tissue formation. In conclusion, the study demonstrates that soft, rather than stiff, material has a greater potential to guide tenogenic differentiation of stem cells, which provides comprehensive evidence for optimized bioactive scaffold design in tendon tissue engineering.