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Acute ischemic stroke (AIS) is the most prevalent type of stroke, and due to its high incidence, disability rate, and mortality rate, it imposes a significant burden on the health care system. Amino acids constitute one of the most crucial metabolic products within the human body, and alterations in their metabolic pathways have been identified in the microenvironment of AIS, thereby influencing the pathogenesis, severity, and prognosis of AIS. The amino acid metabolism characteristics in AIS are complex. On one hand, the dynamic progression of AIS continuously reshapes the amino acid metabolism pattern. Conversely, changes in the amino acid metabolism pattern also exert a double-edged effect on AIS. This interaction is bidirectional, dynamic, heterogeneous, and dose-specific. Therefore, the distinctive metabolic reprogramming features surrounding amino acids during the AIS process are systematically summarized in this paper, aiming to provide potential investigative strategies for the early diagnosis, treatment approaches, and prognostic enhancement of AIS.

In the pursuit of economic growth, the role of innovation has become increasingly important, posing dilemmas for subnational governments as they navigate the balance between expenditure competition and long-term investments in innovation. This study aimed to investigate the intricate relationship between fiscal pressures and the pursuit of innovation goals faced by regional authorities. To achieve this, a systematic literature review was conducted, synthesizing more than 150 studies published within the past 15 years. Keyword searches were conducted across multiple databases, and additional scholarly articles were incorporated through citation tracking. Rigorous qualitative analysis techniques, including inductive coding and thematic analysis, were employed to distill conceptual insights from the literature. The analysis performed in this review reveals extensive discussions regarding the influence of competition on innovation outcomes, encompassing a wide range of perspectives. The potential advantages of localization are emphasized by some viewpoints, while others caution against the risks of inadequate investment. The effective coordination of policies across multiple levels of governance to maximize synergies between national and subnational innovation systems emerges as a complex yet crucial challenge. It is observed that collaborative networks, which facilitate knowledge exchange through industrial clustering and public-private linkages, play a significant role in leveraging regional innovation assets. Strategic approaches that successfully balance competition with long-term capacity development have been demonstrated by leading jurisdictions. These findings highlight the significance of tailored policy frameworks that account for the unique contexts of each region, providing opportunities to harness competitive motivations while sustaining investments in innovation. Ongoing coordination is essential to strike a balance between responsiveness and coherence across diverse territories. This study offers practical guidance and academic insights on strategies to align decentralized imperatives, aiming to optimize prosperity through knowledge creation within evolving multi-level innovation systems. By shedding light on these strategies, the research contributes to both practical and academic understandings of how to effectively navigate and capitalize on the dynamics of such systems.

The convergence of Information Technology (IT), Operational Technology (OT), and Educational Technology (ET) has led to the emergence of the fourth industrial revolution. As a result, a new concept has emerged known as Digital Twins (DT), which is defined as “a virtual representation of various objects or systems that receive data from physical objects/systems to make changes and corrections”. In the aviation industry, numerous attempts have been made to utilize DT in the design, manufacturing, and condition monitoring of aircraft fleets. Among these research efforts, real-time, accurate, fast, and predictive condition monitoring methods play a crucial role in ensuring the safe and efficient performance of aircraft. Using DT for condition and fleet monitoring not only enhances the reliability and safety of aircraft but also reduces operational and maintenance costs. In this paper, the conducted studies on the applications of DT systems for condition monitoring of aircraft units and the aerospace sector are discussed and reviewed. The aim of this review paper is to analyse the current developments of DT systems in the aviation industry as well as explain the remaining challenges of DT systems. Then Finally, future trends of DT systems along with aircraft are presented. Among reviewed papers, most of them have used computational fluid dynamics, finite element methods, and artificial intelligence techniques for developing DT models for aircraft. At the same time, most of these analyses are dedicated to the failure and crack detection body of aircraft as well as engine fault detection. Life prediction is another popular application for using DT in aircraft units that could help the engineers predict the maintenance required for different parts of the aircraft. Finally, the application of DT in marine, power systems, and space programs has been also reviewed and the lessons learned from them have been translated to the aviation sector.

Dendrocalamus farinosus bamboo shoots, a species with rich nutritional value, are important in Southwest China. Lignin is an important factor affecting the postharvest flavor quality of bamboo shoots; however, the underlying mechanism of lignin deposition in D. farinosus bamboo shoots during cold storage is still not fully understood. In this study, the mutant D. farinosus XK4 with low lignin content at 3.11% and the cultivated variety ZPX at 4.47% were used as experimental materials. The lignin content of D. farinosus XK4 and ZPX, as well as the gene expression differences between them, were compared and analyzed during cold storage using transcriptomic and physiological methods. Our analysis revealed several key genes and found that D. farinosus CCoAOMT1 plays a key role in the regulatory network of bamboo shoots during cold storage. Tobacco heterologous transformation experiments demonstrated that overexpression of DfCCoAOMT1 significantly increases lignin content. This study provides a novel foundation for future research aimed at improving the postharvest quality and flavor of D. farinosus bamboo shoots through targeted genetic manipulation during cold storage.

In this study, the prediction of n-value (index-value) surfaces—a key indicator of the field and temperature dependence of critical current density in superconductors—across various high-temperature superconducting materials is addressed using a deep learning modeling approach. As superconductors play a crucial role in advanced technological applications in aerospace and fusion energy sectors, improving their performance model is essential for both practical and academic research purposes. The feed-forward deep learning network technique is employed for the predictive modeling of n-value surfaces, utilizing a comprehensive dataset that includes experimental data on material properties and operational conditions affecting superconductors’ behavior. The model demonstrates enhanced accuracy in predicting n-value surfaces when compared to traditional regression methods by a 99.62% goodness of fit to the experimental data for unseen data points. In this paper, we have demonstrated both the interpolation and extrapolation capabilities of our proposed DFFNN technique. This research advances intelligent modeling in the field of superconductivity and provides a foundation for further exploration into deep learning predictive models for different superconducting devices.

To construct large-scale superconducting devices, it is critical to enhance the current carrying capability of superconducting coils. One practical approach is to utilise assembled cables, composed of multiple strands, for the winding. There have only been a few investigations of the dependence of current distribution among the strands on the AC losses of the cables and coils wound with these cables. In this work, we studied three types of cables; 1) 8/2 (eight 2 mm-wide strands) Roebel cable, 8/2 Roebel; 2) two parallel stacks (TPS) which have the same geometrical dimensions as the Roebel cable, 8/2 TPS; and 3) an equivalent four-conductor stack (ES) comprising four 4 mm-wide conductors, 4/4 ES. We proposed a new numerical approach that can achieve equal current sharing and free current sharing among the strands. We examined the loss behaviour of all three types of straight cables and two coil assemblies comprising two, and eight, stacks of double pancakes (DPCs) wound with these cables, respectively. 2D FEM analysis was carried out in COMSOL Multiphysics using the $H$ – formulation. The stacks were modelled in parallel connection, with the same electric field applied to all strands, so that current is distributed between the conductors. Simulated transport AC loss results in the straight 8/2 Roebel cable, 8/2 TPS and 4/4 ES were compared with previously measured results as well as each other. The numerical AC loss results in two coil windings 2-DPC and 8-DPC wound with the 8/2 Roebel cables were compared with the results in coil windings wound with the 8/2 TPS and 4/4 ES. No transposition was introduced at the connection between double pancakes, in order that current can be shared among the strands in the 8/2 TPS and 4/4 ES. The results indicate that AC loss in the straight 8/2 TPS and 4/4 ES is larger than that in the 8/2 Roebel cable. Current is more concentrated in the outer strands for the straight 8/2 TPS and 4/4 ES than the 8/2 Roebel cable and causes greater AC loss than the 8/2 Roebel cable. The 8-DPC coil winding wound with the 8/2 Roebel cable has the smallest loss and the coil winding wound with the 8/2 TPS has the greatest loss at two current amplitudes investigated. At 113 A, the AC loss value in the 8-DPC coil winding wound with the 8/2 TPS is 2.2 times of that wound with the 8/2 Roebel cable.

Abstract Introduction : Previous studies have revealed abnormal resting‐state brain activity in patients with end‐stage renal disease (ESRD); however, the results are inconsistent. Thus, we conducted a coordinate‐based meta‐analysis of whole‐brain resting‐state functional neuroimaging studies in ESRD to identify the most consistent neural activity alterations in ESRD patients and explore their relation to serological indicators. Methods : A comprehensive literature search strategy was applied to select pertinent studies up to December 2022 in PubMed, Web of Science, and Embase databases. Voxel‐wise meta‐analysis was conducted via the latest meta‐analytic algorithm, seed‐based d mapping with permutation of subject images software. Meta‐regression analyses were also conducted to explore the potential effect of clinical variables on resting‐state neural activity. Results : Eleven studies comprising 304 patients with ESRD and 296 healthy controls (HCs) were included. Compared with HCs, ESRD patients showed decreased brain activity in the default mode network (DMN) regions, including the bilateral anterior cingulate cortex/medial prefrontal cortex, bilateral midcingulate cortex/posterior cingulate cortex, bilateral precuneus, and right angular gyrus. The neural activities in the bilateral midcingulate cortex, bilateral midcingulate cortex/posterior cingulate cortex, and right angular gyrus were significantly associated with serological indexes including hemoglobin, urea, and creatinine levels. Conclusion : The present study provides a quantitative overview of brain activity alterations in patients with ESRD, and the results confirm the essential role of the DMN in ESRD patients, which may be the potential neural basis of their cognitive deficits. Additionally, some serological indicators may be used as predictive markers for progressive impairment of brain function.

The evaluation and estimation of the electric and magnetic field (EMF) intensity in the vicinity of overhead transmission lines (OHTL) is of paramount importance for residents’ healthcare and industrial monitoring purposes. Using artificial intelligence (AI) techniques makes researchers able to estimate EMF with extremely high accuracy in a significantly short time. In this paper, two models based on the Artificial Neural Network (ANN) have been developed for estimating electric and magnetic fields, i.e., feed-forward neural network (FFNN) and cascade-forward neural network (CFNN). By performing the sensitivity analysis on controlling/hyper-parameters of these two ANN models, the best setup resulting in the highest possible accuracy considering their response time has been chosen. Overall, the CFNN achieved a significant 56% reduction in Root Mean Squared Error (RMSE) for the electric field and a 5% reduction for the magnetic field, compared to the FFNN. This indicates that the CFNN model provided more accurate predictions, particularly for the electric field than the proposed methods in other recent works, making it a promising choice for this application. When the model is trained, it will be tested by a different dataset. Then, the accuracy and response time of the model for new data points of that layout will be evaluated through this process. The model can predict the fields with an accuracy near 99.999% of the actual values in times under 10 ms. Also, the results of sensitivity analysis indicated that the CFNN models with triple and double hidden layers are the best options for the electric and magnetic field estimation, respectively.

The traction transformer is a critical electrical component in high-speed-trains. We are currently building a 6.5 MVA superconducting traction transformer which will increase transformer efficiency to 99%, halve the weight, and avoid the fire risk of the conventional transformer system. AC loss from the transformer windings cannot exceed 2 kW to meet both the efficiency and weight targets. There are significant high frequency harmonics, particularly the $13^{\mathrm {th}}$ harmonic at 650 Hz, on the traction side of the transformer. Our previous work has shown the estimated AC loss in the transformer windings almost doubled with the addition of a 650 Hz harmonic current at the 8% level specified, which is not acceptable. Therefore, it is critical to reduce AC loss in the transformer due to high harmonics. In this study, we explored the role of flux diverters positioned at the outer ends of the high voltage (HV) and low voltage (LV) windings in restraining AC loss in the windings carrying high-order harmonic currents below 2 kW. Five different ring-shaped flux diverter designs were modelled in this work, utilizing the previously developed 2D axisymmetric model using the $H$ formulation. Simulations were carried out to study the influence of the phase of the 13th harmonic, either in phase or out of phase with respect to the fundamental current, and of the inclusion of multiple harmonics on the loss. The simulation results show that placing flux diverters near the end of the windings leads to a magnetic flux distribution in the windings with reduced radial field, and hence significantly reduces the loss. Three of the flux diverter designs achieve the loss target by limiting the AC loss to below 2 kW, with a wide/thin design having the minimum weight and a wide/thick design achieving only 6% less loss, despite being almost four times heavier.

Rivers play an important role in receiving and transporting the resistome among different environmental compartments. However, the difference in resistome and mobilome between the water and sediment and their underlying mechanisms were still poorly understood. In this study, the Ili River, an important water source in the arid area of Central Asia, was selected as the studied target. The comprehensive profile of resistome and mobilome and their host in water and sediment were studied based on metagenomic binning and assembled genome (MAG) analysis. The relative abundance of resistome and mobilome in sediment were 28.0 – 67.8 × /Gb and 46.5 – 121.1 × /Gb, respectively, which were significantly higher than those in water (23.1 – 52.8 ×/Gb and 25.3 – 67.7 ×/Gb). Multidrug and macrolides-lincosamides-streptogramin (MLS) resistance genes were the main ARG types in both water and sediment from relative abundance. Transposases dominated the relative abundance of mobilome, followed by insert elements and integrases. Strong correlations were found between the relative abundance of resistome and mobilome (r > 0.6 and p

Lung cancer is a malignant disease with a high mortality rate and a poor prognosis, which is easy to metastasis and recurrence. Topotecan (TPT), an inhibitor of topoisomerase I (Topo I), is mainly used to treat metastatic small cell lung cancer, and it has shown effective treatment for non-small cell lung cancer (NSCLC). However, the inhibitory effect and mechanism of TPT on NSCLC have not been described. In this study, we examined the effect of TPT on the proliferation of three types of NSCLC (H1299, H1975 and HCC827 ​cells) by MTT and colony formation assays. The migration capacity of lung cancer cells treated with TPT was detected by wound healing assay. We also tested the cell apoptosis induced by TPT using flow cytometry and the related proteins by Western blot. TPT treatment inhibited the proliferation of lung cancer cells with IC50 values of 12.67 ​± ​0.44 ​μM, 0.44 ​± ​0.083 ​μM and 2.89 ​± ​0.46 ​μM for H1299, H1975 and HCC827 ​cells, respectively. TPT promoted cell apoptosis by upregulating the expression of Bax and downregulating the expression of Bcl-xL and Bcl-2. Topotecan suppressed the metastatic phenotype of epithelial mesenchymal transition (EMT) in lung cancer cells by regulating E-cadherin, N-cadherin, vimentin and transcription factors Snail, MMP-2 and MMP-9. Our study found that TPT could inhibit the proliferation and migration of NSCLC by inducing cell apoptosis and regulating EMT. It was provided further favorable evidence for TPT in the treatment of patients with metastatic NSCLC.

As the main component of plant cell walls, lignin can not only provide mechanical strength and physical defense for plants, but can also be an important indicator affecting the properties and quality of wood and bamboo. Dendrocalamus farinosus is an important economic bamboo species for both shoots and timber in southwest China, with the advantages of fast growth, high yield and slender fiber. Caffeoyl-coenzyme A-O-methyltransferase (CCoAOMT) is a key rate-limiting enzyme in the lignin biosynthesis pathway, but little is known about it in D. farinosus. Here, a total of 17 DfCCoAOMT genes were identified based on the D. farinosus whole genome. DfCCoAOMT1/14/15/16 were homologs of AtCCoAOMT1. DfCCoAOMT6/9/14/15/16 were highly expressed in stems of D. farinosus; this is consistent with the trend of lignin accumulation during bamboo shoot elongation, especially DfCCoAOMT14. The analysis of promoter cis-acting elements suggested that DfCCoAOMTs might be important for photosynthesis, ABA/MeJA responses, drought stress and lignin synthesis. We then confirmed that the expression levels of DfCCoAOMT2/5/6/8/9/14/15 were regulated by ABA/MeJA signaling. In addition, overexpression of DfCCoAOMT14 in transgenic plants significantly increased the lignin content, xylem thickness and drought resistance of plants. Our findings revealed that DfCCoAOMT14 can be a candidate gene that is involved in the drought response and lignin synthesis pathway in plants, which could contribute to the genetic improvement of many important traits in D. farinosus and other species.

Previous studies on magnetization AC loss of high temperature superconducting (HTS) coated conductors (CCs) taken into account the ideally sinusoidal external magnetic field, or non-sinusoidal by considering only the harmonics in phase with the fundamental component. However, realistically magnetic field often contains harmonics with different phase angles and amplitudes. In this paper, magnetization AC loss in HTS CC was studied, considering the phase angle $\varphi $ of each harmonic; assuming superconductor is subjected to external magnetic field which is distorted by the $3^{\mathrm {rd}}$ and the $5^{\mathrm {th}}$ harmonics. Phase angle of each harmonic was considered in the range of 0 to $\pi $ and amplitude of fundamental magnetic field, was assumed as 10, 20, 50, and 100 mT. Different distortion level of magnetic field was considered too. It is concluded that phase angle of field harmonic has a significant effect on magnetization loss of HTS CCs.

Current is no longer sinusoidal in modern electric networks because of widespread use of power electronic-based equipments and nonlinear loads. Usually AC loss is calculated for pure sinusoidal current, while it is no longer accurate when current is nonsinusoidal. On the other hand, efficiency of cooling system in large scale power devices is dependent on accurate estimation and prediction of the heat load caused by AC loss in design stage. Therefore, estimation of nonsinusoidal AC loss of high temperature superconducting (HTS) material would be of great interest for designers of large-scale superconducting devices. In this paper, at first nonsinusoidal AC loss of a typical HTS tape was calculated under distorted currents using H-formulation finite element method. Then, a range of artificial intelligence (AI) models were implemented to predict AC loss of a typical HTS tape. In order to find the best and more adaptive AI model for nonsinusoidal AC loss prediction, different regression models are evaluated using Support Vector Machine regression model, Generalized Linear regression model, Decision Tree regression model, Feed Forward Neural Network based model, Adaptive Neuro Fuzzy Inference System based model, and Radial Basis Function Neural Network (RBFNN) based model. In order to evaluate robustness of developed models cross-validation technique is implemented on experimental data. To compare the performance of different AI models, four prediction measures were used: Theil's U coefficients (U_Accuracy and U_Quality), Root Mean Square Error (RMSE) and Regression value (R-value). Obtained results show that best performance belongs to RBFNN based model and then ANFIS based model. U coefficients and RMSE values are obtained less than 0.005 and R-Value is become close to one by using RBFNN based model for testing data, which indicates high accuracy prediction performance.

Fluctuations in the critical current along the length of high-temperature superconducting (HTS) tapes manufactured in the form of coated conductors is a common manufacturing phenomenon. These fluctuations originate in the generation of weak points through the length of HTS tapes that may cause quenching later. By means of the propagation of quenches in HTS tapes, the reliability, stability, and the performance of the device and the system that contain HTS tapes could be seriously degraded. In this study, an artificial intelligence technique based on artificial neural networks (ANN) was proposed to estimate the probability of quenches in HTS tapes caused by weak points. For this purpose, six different HTS tapes were considered with different widths, total thicknesses, and thicknesses of sub-layers. Then, for each one of these tapes, different operating conditions were considered, where the operating temperature changed from 40 K to 80 K, in 1 K steps. Under each operating temperature, different operating currents were considered from 50% to 100% of tape critical current. All of these resulted in more than 5000 different data points. Then, for each of these data points, analytical modelling was performed to provide initial inputs and outputs for the ANN model. It should be noted that the performed simulations were conducted based on an analytical method that was experimentally validated in the literature. After that, a sensitivity analysis was conducted to select the hyperparameters and structure of the ANN-based model. The last step was to take advantage of the trained model, as a function in the MATLAB software package to estimate the probability of quenches in different case studies. The significant feature of the proposed model is the capability for estimating the probability of quenches under different operating temperatures and currents for different types of HTS tapes.

Cultured meat is an innovative meat-production technology that does not rely on animal husbandry. As a new food component, cultured fat is of great significance to cultured meat. In this study, we isolated adipose-derived stem cells (ADSCs) and identified the purity by immunofluorescence staining of ADSC-specific surface marker proteins CD44 and CD29 and showed that most of the cells were positive for CD29 and CD44. In addition, we detected the expression of FABP4 and Plin1 to confirm that ADSCs differentiated into mature adipocytes at 10 days post-induction. Subsequently, the culture conditions of ADSCs on microcarriers (MCs) were optimized and showed that cell density of living cells reached their highest after 5 days when continuously stirring at 50 rpm. Finally, the expression of FABP4 and PPARγ was detected to confirm the adipogenic differentiation ability of ADSCs on 2D and 3D culture systems and showed that ADSCs maintained their adipogenic differentiation ability after expansion on MCs. In conclusion, this research demonstrated that reliance on MCs to expand ADSCs was a promising approach for production of cultured fat.

A global survey was performed with 122 aquatic metagenomic DNA datasets (92 lake water and 30 seawater) obtained from the Sequence Read Archive (SRA). Antibiotic resistance genes (ARGs) and metal resistance genes (MRGs) were derived from the dataset sequences via bioinformatic analysis. The relative abundances of ARGs and MRGs in lake samples were in the ranges ND (not detected)–1.34 × 100 and 1.22 × 10−3–1.98 × 10−1 copies per 16S rRNA, which were higher than those in seawater samples. Among ARGs, multidrug resistance genes and bacitracin resistance genes had high relative abundances in both lake and sea water samples. Multi-metal resistance genes, mercury resistance genes and copper resistance genes had the greatest relative abundance for MRGs. No significant difference was found between epilimnion and hypolimnion in abundance or the Shannon diversity index for ARGs and MRGs. Principal coordinates analysis and permutational multivariate analysis of variance (PERMANOVA) test showed that stratification and geography had significant influence on the composition of ARGs and MRGs in lakes (p

Plastics have been accumulated offshore and in the deep oceans at an unprecedented scale. Microbial communities have colonized the plastisphere, which has become a reservoir for both antibiotic and metal resistance genes (ARGs and MRGs). This is the first analysis of the diversity, abundance, and co-occurrence of ARGs and MRGs, and their relationships within the microbial community, using metagenomic data of plastic particles observed in the North Pacific Gyre obtained from the National Centre for Biotechnology Information Sequence Read Archive database. The abundance of ARGs and MRGs in microbial communities on the plastics were in the ranges 7.07 × 10−4–1.21 × 10−2 and 5.51 × 10−3–4.82 × 10−2 copies per 16S rRNA, respectively. Both the Shannon-Wiener indices and richness of ARGs and MRGs in plastics microbiota were significantly greater than those of ARGs and MRGs in seawater microbiota in the North Pacific Gyre via one-way analysis of variance. Multidrug resistance genes and multi-metal resistance genes were the main classes of genes detected in plastic microbiota. There were no significant differences in the abundance or diversity of ARGs and MRGs between macroplastics biota and microplastics biota, indicating that particle size had no effect on resistance genes. Procrustes analysis suggested that microbial community composition was the determining factor of the ARG profile but not for MRG. Some ARGs and MRGs had a higher incidence of non-random co-occurrence, suggesting that the co-effects of selection for antibiotic or metal resistance are important factors influencing the resistome of the microbiota on the plastic particles. Keywords: Metagenomic analysis, Pacific Ocean, Microplastics, Macroplastics, Resistance genes

Objective. To evaluate the effect of transcutaneous electrical nerve stimulation (C-TENS) in the rehabilitation of rotator cuff injury. Methods. A total of 60 patients diagnosed with mild to moderate rotator cuff injury were randomly divided into the control group and test group. Both groups received conventional rehabilitation treatment including physical therapy, joint mobilization, interventional therapy, and family recovery training. The test group additionally received TENS treatment on the upper area 4 or 5 of the wrist, based on the wrist-ankle acupuncture (WAA) theory. The results of the visual analogue scale (VAS), shoulder range of motion (ROM), and Constant-Murley score (CMs) were collected before and after the 1st treatment and after the 5th treatment. The differences of those indicators between the two groups were analyzed statistically. Results. The VAS scores of measurement points after treatment were all improved compared with those at baseline. There was a significant difference between the two groups after the 1st and the 5th treatment (p

Myocardial infarction with nonobstructive coronary arteries (MINOCA) is a potentially multipathogenic syndrome that affects a subgroup of patients who present with acute myocardial infarction yet have no significant coronary artery disease on angiography. We herein describe a 71-year-old man with typical angina who showed inferior ST-segment elevation on electrocardiography and an increased troponin-I level. Emergency coronary angiography showed no angiographic stenosis. Cardiac magnetic resonance imaging (CMR) and myocardial contrast echocardiography (MCE) with two-dimensional speckle tracking imaging (2D-STI) were performed after coronary angiography. Good consistency was observed between the CMR findings and MCE with 2D-STI findings in identifying the potential causes of MINOCA. We explored an imaging method that is potentially more effective and accurate than CMR, namely MCE combined with 2D-STI, to identify myocardial abnormalities when angiography reveals no obstruction. This application of MCE with 2D-STI may optimize timely treatment. MINOCA has various causes, and the patient in this case was discharged with aspirin, verapamil, and atorvastatin on the presumption that the infarct had arisen from either plaque disruption or coronary spasm. In this study, we analyzed the etiology, clinical diagnosis, and treatment of MINOCA with reference to the relevant literature.

Involution of the mammary gland is a complex process controlled by various endocrine hormones and cytokine. As a novel adipocytokine, Chemerin not only plays a pivotal role in physiological and pathological processes such as immune response and lipid metabolism, but is also involved in the regulation of programmed cell death, including autophagy and apoptosis. The purpose of the present study was to elucidate whether autophagy and apoptosis of bovine mammary epithelial cells (BMECs) was triggered by Chemerin. BMECs were cultured and treated with Chemerin in vitro. The expression of autophagosome-forming marker, microtubule-associated protein 1 light chain 3 II (LC3-II) and sequestosome-1 (SQSTM 1, best known as p62), a substrate of autophagosome degradation were detected. The result showed that Chemerin significantly decreased the expression of p62 and markedly induced the conversion of LC3-I to LC3-II. The ratio of Bcl2-associated X and B-cell lymphoma-2 (Bax/Bcl-2) and the activity of caspase-3 were up-regulated after being treated by Chemerin, and the apoptotic rate was also significantly increased. These results suggested that Chemerin promoted the occurrence of autophagy and apoptosis in BMECs. Chloroquine (CQ), which is an inhibitor of autophagy. To explore effects of Chemerin on apoptosis, we prevented Chemerin-induced autophagy by pre-adding CQ in BMECs. Interestingly, this part of the experiment helped us find that all effects of Chemerin on apoptosis of BMECs could be enhanced with the inhibition of autophagy. Our study demonstrates that Chemerin-induced autophagy and apoptosis are mutually regulated in BMECs, but the specific mechanism remains to be further researched.

The effects of UV-B radiation (UVBR) on photosynthetic activity (Fv/Fm) of aquatic Synechocystis sp. and desert Chroococcus minutus and effects on composition and fluorescence property of extracellular polymeric substances (EPS) from Synechocystis sp. and Chroococcus minutus were comparatively investigated. The desert cyanobacterium species C. minutus showed higher tolerance of PSII activity (Fv/Fm) to UVBR than the aquatic Synechocystis sp., and the inhibited PSII activity of C. minutus could be fully recovered while that of Synechocystis sp. could be partly recovered. UVBR had significant effect on the yield and biochemical composition of EPS of both species. Protein-like and humic acid-like substances were detected in EPS from Synechocystis sp., and protein-like and phenol-like fluorescent compounds were detected in EPS from C. minutus. Proteins in EPS of desert and aquatic species were significantly decomposed under UVBR, and the latter was more easily decomposed. The polysaccharides were much more resistant to UVBR than the proteins for both species. Polysacchrides of Synechocystis sp. was degraded slightly but those of C. minutus was little decomposed. The higher tolerance to UVBR of the desert cyanobacterium can be attributed to the higher resistance of its EPS to photodegradation induced by UVBR in comparison with the aquatic species

The mobility of economic factors across jurisdictions has led to increased fiscal competition among decentralized subnational governments. This study examines the relationship between fiscal competition and long-term investment in innovation at the local government level. Panel data analysis, encompassing expenditures, taxes, and innovation inputs from 18 municipalities over a 10-year period, is employed using fixed effects regression. The results reveal a negative correlation between fiscal competition and expenditure on innovation, indicating that intensified competition for mobile capital diverts resources away from essential long-term investments crucial for knowledge-driven growth. Even after controlling for economic and institutional factors, a one standard deviation increase in competition corresponds to an average decline of 25% in per capita innovation investment. These findings highlight the unintended trade-off resulting from heightened competition and underscore the need for policy frameworks that promote localized flexibility while curbing uncoordinated competition that undermines innovation capacity. While fiscal decentralization aims to foster competitive governance, this study provides empirical evidence that short-term expenditure incentives often displace long-term innovation objectives without sufficient coordination. The insights contribute significant empirical evidence on the concealed costs of fiscal competition for regional development. Consequently, a re-evaluation of conventional perspectives on decentralization and competition is warranted, emphasizing the importance of developing cooperative policy solutions that strike a delicate balance between decentralized decision autonomy and strategic coordination. Adopting such an approach is essential to fully leverage the advantages of competitive governance while simultaneously nurturing innovation ecosystems. [ABSTRACT FROM AUTHOR]