Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
8,108
result(s) for
"Li, Mi"
Sort by:
الأدوات البرونزية للصين
يعتبر ظهور الأدوات البرونزية قفزة مهمة في تاريخ الحضارة الإنسانية. وعلي الرغم من أن العصر البرونزي في الصين لم يكن الأول في تاريخ البشرية، ولكن الأدوات البرونزية في الصين القديمة قد احتلت مكانة فريدة في تاريخ الحضارة العالمية اعتمادا علي أنواعها المتنوعة وأنماطها الغنية وعملية السبك الدقيقة والدلالة التاريخية والثقافية العميقة التي يحملها كل عمل برونزي في الصين القديمة. وهذا الكتاب الذي بين يدي القارئ الكريم يعرفن بلغة واضحة وحية وبالشرح والصور على أحد اوجه الثقافة والفنون الصينية الشهيرة والتي هي ثقافة البرونز الرائعة في الصين القديمة، فمن خلال قطعة من القطع البرونزية الثمينة يمكننا أن نستمع إلي صوت العصر البرونزي من أماكن بعيدة وتجربة أسلوب فريد من نوعه في ذلك العصر الذي مازالت أسراره بعيدة عن متناول القارئ العربي والتي نحاول من خلال هذا الكتاب أن نقدمها بشكل موجز وواضح لننقل للقارئ الكريم وجها جديدا عليه من أوجه الحضارة الصينية المتميزة.
Book
Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation
This study aims to develop and validate a programmed cell death signature (PCDS) for predicting and classifying Alzheimer's disease (AD) using an integrated machine learning framework. We further explore the role of S100A4 in AD pathogenesis, particularly in microglia.
A total of one single-cell RNA sequencing (scRNA-seq) and four bulk RNA-seq datasets from multiple GEO datasets were analyzed. Weighted Gene Co-expression Network Analysis (WGCNA) was utilized to identify PCD-related genes. An integrated machine learning framework, combining 12 algorithms was used to construct a PCDS model. The performance of PCDS was validated using multiple independent cohorts.
experiments using BV2 microglia were conducted to validate the role of S100A4 in AD, including siRNA transfection, Western blot, qRT-PCR, cell viability and cytotoxicity assay, flow cytometry, and immunofluorescence.
ScRNA-seq analysis revealed higher PCD levels in microglia from AD patients. Seventy-seven PCD-related genes were identified, with 70 genes used to construct the PCDS model. The optimal model, combining Stepglm and Random Forest, achieved an average AUC of 0.832 across five cohorts. High PCDS correlated with upregulated pathways related to inflammation and immune response, while low PCDS associated with protective pathways.
, S100A4 knockdown in AbetaO-treated BV2 microglia improved cell viability, reduced LDH release, and partially alleviated apoptosis. S100A4 inhibition attenuated pro-inflammatory responses, as evidenced by the reduced expression of pro-inflammatory mediators (IL-6, iNOS, TNF-α) and promoted an anti-inflammatory state, indicated by increased expression of markers such as IL-10, ARG1, and YM1/2. Furthermore, S100A4 knockdown mitigated oxidative stress, restoring mitochondrial function and decreasing ROS levels.
This study developed a robust PCDS model for AD prediction and identified S100A4 as a potential therapeutic target. The findings highlight the importance of PCD pathways in AD pathogenesis and provide new insights for early diagnosis and intervention.
Journal Article
Federated deep reinforcement learning-based urban traffic signal optimal control
This paper proposes a cross-domain intelligent traffic signal control method based on federated Proximal-Policy Optimization (PPO) for distributed joint training of agents across domains for typical intersections, aiming at solving the problems of slow learning speed and poor model generalization when deep reinforcement learning (RL) is applied to cross-domain multi-intersection traffic signal optimization control. The proposed method improves the model generalization ability of different local models during global cross-region distributed joint training under the premise of ensuring information security and data privacy, solves the problem of non-independent and homogeneous distribution of environmental data faced by different agents in real intersection scenarios, and significantly accelerates the convergence speed of the model training phase. By reasonably designing the state, action and reward functions and determining the optimal values of several key parameters in the federated collaboration mechanism, the RL model could ensure high learning efficiency and fast convergence in the face of the gradual increase of road network size and the exponential increase of state and action space with the number of intersections. In addition, the new state interaction method and the reward function allow the agents to collaborate with each other, which greatly improves the information interaction efficiency between the federated learning local agents and the central coordinator, and improves the access efficiency of the road network and reduces the amount of communication data transmitted. Finally, through experimental comparisons, the proposed method can significantly reduce the average vehicle waiting time by up to 27.34% compared with the existing fixed timing method, and under the same convergence height, the convergence speed is up to 47.69% faster compared with the individual PPO trained in a single local environment, and up to 45.35% faster than the aggregated PPO trained jointly using all local data. The proposed method effectively optimizes intersection access efficiency with excellent robustness under various traffic flow settings.
Journal Article
Recent research progress on metabolic syndrome and risk of Parkinson’s disease
Parkinson’s disease (PD) is one of the most widespread neurodegenerative diseases. PD is associated with progressive loss of substantia nigra dopaminergic neurons, including various motor symptoms (e.g., bradykinesia, rigidity, and resting tremor), as well as non-motor symptoms (e.g., cognitive impairment, constipation, fatigue, sleep disturbance, and depression). PD involves multiple biological processes, including mitochondrial or lysosomal dysfunction, oxidative stress, insulin resistance, and neuroinflammation. Metabolic syndrome (MetS), a collection of numerous connected cerebral cardiovascular conditions, is a common and growing public health problem associated with many chronic diseases worldwide. MetS components include central/abdominal obesity, systemic hypertension, diabetes, and atherogenic dyslipidemia. MetS and PD share multiple pathophysiological processes, including insulin resistance, oxidative stress, and chronic inflammation. In recent years, MetS has been linked to an increased risk of PD, according to studies; however, the specific mechanism remains unclear. Researchers also found that some related metabolic therapies are potential therapeutic strategies to prevent and improve PD. This article reviews the epidemiological relationship between components of MetS and the risk of PD and discusses the potentially relevant mechanisms and recent progress of MetS as a risk factor for PD. Furthermore, we conclude that MetS-related therapies are beneficial for the prevention and treatment of PD.
Journal Article
Chiral recognition and enantiomer excess determination based on emission wavelength change of AIEgen rotor
Chiral recognition, such as enantioselective interactions of enzyme with chiral agents, is one of the most important issues in the natural world. But artificial chiral receptors are much less efficient than natural ones. For tackling the chiral recognition and enantiomer excess (ee) analysis, up until now all the fluorescent receptors have been developed based on fluorescence intensity changes. Here we report that the chiral recognition of a large number of chiral carboxylic acids, including chiral agrochemicals 2,4-D, is carried out based on fluorescent colour changes rather than intensity changes of AIEgen rotors. Moreover, the fluorescence wavelength of the AIEgen rotor linearly changes with ee of the carboxylic acid, enabling the ee to be accurately measured with average absolute errors (AAE) of less than 2.8%. Theoretical calculation demonstrates that the wavelength change is ascribed to the rotation of the AIEgen rotor upon interaction with different enantiomers.
Artificial receptors for chiral recognition are important in enantiomer excess analysis but current artificial detectors are based on fluorescence intensity changes only. Here the authors propose a different detection mechanism based on change of the fluorescence emission wavelength of an AIEgen rotor.
Journal Article
Bibliometric Analysis of Studies on Neuropathic Pain Associated With Depression or Anxiety Published From 2000 to 2020
Objective: Neuropathic pain (NP) associated with depression or anxiety is highly prevalent in clinical practice. Publications about NP associated with depression or anxiety increased exponentially from 2000 to 2020. However, studies that applied the bibliometric method in analyzing global scientific research about NP associated with depression or anxiety are rare. This work used the bibliometric method to analyze the publications on NP associated with depression or anxiety between 2000 and 2020. Method: Publications from 2000 and 2020 were identified from the Thomson Reuters Web of Science (WoS) database. We employed CiteSpace V to conduct the bibliometric study. Results: A total of 915 articles or reviews were obtained from the WoS database. The number of publications has increased over the last two decades. The USA was the most productive among countries or regions in the field. According to the burst key words, neuroinflammation, hippocampus, safety, and modulation were the hot global research issues in the domain. Conclusion: Publications about NP associated with depression or anxiety have remarkably increased from 2000 to 2020. These historical opinions about NP associated with depression or anxiety could be an important practical basis for further research into potential development trends.
Journal Article
Digital twin-assisted graph matching multi-task object detection method in complex traffic scenarios
Addressing the challenges of time-consuming and labor-intensive traffic data collection and annotation, along with the limitations of current deep learning models in practical applications, this paper proposes a cross-domain object detection transfer method based on digital twins. A digital twin traffic scenario is constructed using a simulation platform, generating a virtual traffic dataset. To address distributional discrepancies between virtual and real datasets, a multi-task object detection algorithm based on graph matching is introduced. The algorithm employs a graph matching module to align the feature distributions of the source and target domains, followed by a multi-task network for object detection. An attention mechanism is then applied for instance segmentation, with the two tasks exhibiting different noise patterns that mutually enhance the robustness of the learned representations. Additionally, a multi-level discriminator is designed, leveraging both low- and high-level features for adversarial training, thus enabling tasks to share useful information, which improves the performance of the proposed method in object detection tasks. Through comprehensive comparative experiments with various state-of-the-art methods, the practical value of the generated virtual dataset has been fully demonstrated. Furthermore, the effectiveness of the proposed graph-matching-based transfer method has been validated. These findings highlight the dataset’s capacity to enhance task performance and underscore the robustness and adaptability of the proposed approach in diverse scenarios.
Journal Article
Cell cycle arrest induces lipid droplet formation and confers ferroptosis resistance
How cells coordinate cell cycling with cell survival and death remains incompletely understood. Here, we show that cell cycle arrest has a potent suppressive effect on ferroptosis, a form of regulated cell death induced by overwhelming lipid peroxidation at cellular membranes. Mechanistically, cell cycle arrest induces diacylglycerol acyltransferase (DGAT)–dependent lipid droplet formation to sequester excessive polyunsaturated fatty acids (PUFAs) that accumulate in arrested cells in triacylglycerols (TAGs), resulting in ferroptosis suppression. Consequently, DGAT inhibition orchestrates a reshuffling of PUFAs from TAGs to phospholipids and re-sensitizes arrested cells to ferroptosis. We show that some slow-cycling antimitotic drug–resistant cancer cells, such as 5-fluorouracil–resistant cells, have accumulation of lipid droplets and that combined treatment with ferroptosis inducers and DGAT inhibitors effectively suppresses the growth of 5-fluorouracil–resistant tumors by inducing ferroptosis. Together, these results reveal a role for cell cycle arrest in driving ferroptosis resistance and suggest a ferroptosis-inducing therapeutic strategy to target slow-cycling therapy-resistant cancers.
How cell cycling coordinates with cell survival and death remains unclear. Here, the authors reveal a suppressive effect of cell cycle arrest on ferroptosis and propose a ferroptosis-inducing approach to treat slow-cycling, therapy-resistant cancers.
Journal Article
Single-molecular insights into the breakpoint of cellulose nanofibers assembly during saccharification
Plant cellulose microfibrils are increasingly employed to produce functional nanofibers and nanocrystals for biomaterials, but their catalytic formation and conversion mechanisms remain elusive. Here, we characterize length-reduced cellulose nanofibers assembly in situ accounting for the high density of amorphous cellulose regions in the natural rice
fragile culm 16
(
Osfc16
) mutant defective in cellulose biosynthesis using both classic and advanced atomic force microscopy (AFM) techniques equipped with a single-molecular recognition system. By employing individual types of cellulases, we observe efficient enzymatic catalysis modes in the mutant, due to amorphous and inner-broken cellulose chains elevated as breakpoints for initiating and completing cellulose hydrolyses into higher-yield fermentable sugars. Furthermore, effective chemical catalysis mode is examined in vitro for cellulose nanofibers conversion into nanocrystals with reduced dimensions. Our study addresses how plant cellulose substrates are digestible and convertible, revealing a strategy for precise engineering of cellulose substrates toward cost-effective biofuels and high-quality bioproducts.
Lignocellulose recalcitrance hampers its utilization for the production of biofuels and biosourced chemicals. Here, the authors reveal that the amorphous cellulose is the breakpoint of interact microfibrils and propose
OsFC16/CESA9
as the engineering target to increase saccharification ability.
Journal Article