Study on the Chemical Constituents, Pharmacological Activities, and Clinical Application of Taxus.

Taxus, a rare and protected genus predominantly distributed across the Northern Hemisphere's temperate regions, has garnered global attention due to its significant potential in medical research and pharmaceutical development, bolstered by advancements in cultivation techniques and medical technology. This review primarily focuses on the chemical constituents and pharmacological activities of Taxus, underscoring the progress and potential of these components in clinical applications. Recent studies have revealed that Taxus contains not only taxane active components but also flavonoids and polysaccharides with distinct activities. These compounds from Taxus exhibit potent antitumor, anti-inflammatory, immunomodulatory, antibacterial, and antidiabetic properties with evident mechanisms of action. Notably, the representative compound, paclitaxel, has demonstrated significant efficacy in treating various cancers, such as ovarian, breast, and lung cancer. This paper also reviews the basic situation of Taxus drug formulations, with extracts primarily administered orally and monomeric taxanes typically via injection, reflecting a mature development stage with ongoing research into oral formulations. Finally, this review summarizes the pharmacokinetic characteristics of crucial compounds in Taxus, including their absorption, distribution, metabolism, and excretion patterns in the human body. These pharmacokinetic profiles provide crucial guidance for evaluating the overall dosing regimen of Taxus and its components. The paper concludes with a forward-looking analysis of the potential applications of these compounds in disease treatment, envisioning their role in the future of medical and pharmaceutical advancements.

Exosome miRNA profile and mitigating effect of miR-23a-3p/Cul3 axis on apoptosis in the pathogenesis of SiO2 dust-induced lung fibrosis.

Silicosis is an irreversible interstitial lung fibrosis resulting from persistent inflammation induced by long-term inhalation of SiO2 dust. Treatment and early diagnosis are extremely challenging due to the lack of specific targets and biomarkers. MiRNAs play an important role in the early diagnosis and treatment of various diseases, due to their stability, small variations, and easy detection. Exosomes have become fashionable candidates to deliver miRNAs. However, the specific role of exosomes-loaded miRNAs in silicosis inflammation and fibrosis remains unclear. In the present study, the expression profile of serum exosomal miRNAs in the peripheral blood of silicosis patients was determined by transcritome sequencing. MiR-23a-3p was recognized as a protector against silicosis by bioinformatic analysis. The expression and regulatory axis of miR-23a-3p and its predicted target gene CUL3 were then confirmed. The therapeutic role of the miR-23a-3p/CUL3 axis and its alleviating effect on SiO2-induced apoptosis were verified in mice and in epithelial cells. Furthermore, the communication of exosomes carrying miR-23a-3p between macrophages and epithelial cells was demonstrated using a cell co-culture model. Our results suggest that exosomal miR-23a-3p could be prospective as a biomarker in early diagnose for SiO2-induced lung fibrosis, and provided new threads for the treatment of silicosis.

Canagliflozin Inhibits Palmitic Acid-Induced Vascular Cell Aging In Vitro through ROS/ERK and Ferroptosis Pathways.

Vascular aging is one of the reasons for the high incidence of cardiovascular diseases nowadays, as vascular cells age due to various internal and external factors. Among them, high fat is an important inducer. Canagliflozin (CAN) is one of the SGLT2 inhibitors that has been shown to have cardiovascular protective effects in addition to lowering blood sugar, but the specific mechanism is not clear. This study first established a vascular aging model using palmitic acid (PA), then tested the effect of CAN on PA-induced vascular aging, and finally examined the mechanism of CAN's anti-vascular aging via ROS/ERK and ferroptosis pathways. We found that CAN alleviates PA-induced vascular cell aging by inhibiting the activation of ROS/ERK and ferroptosis signaling pathways. This study reveals new mechanisms of lipid-induced vascular aging and CAN inhibition of vascular aging from the perspectives of ROS/ERK and ferroptosis pathways, which is expected to provide new ideas for the development of related drugs in the future.

Research on the Medicinal Chemistry and Pharmacology of Taxus × media.

Taxus × media, belonging to the genus Taxus of the Taxaceae family, is a unique hybrid plant derived from a natural crossbreeding between Taxus cuspidata and Taxus baccata. This distinctive hybrid variety inherits the superior traits of its parental species, exhibiting significant biological and medicinal values. This paper comprehensively analyzes Taxus × media from multiple dimensions, including its cultivation overview, chemical composition, and multifaceted applications in the medical field. In terms of chemical constituents, this study delves into the bioactive components abundant in Taxus × media and their pharmacological activities, highlighting the importance and value of these components, including paclitaxel, as the lead compounds in traditional medicine and modern drug development. Regarding its medicinal value, the article primarily discusses the potential applications of Taxus × media in combating tumors, antibacterial, anti-inflammatory, and antioxidant activities, and treating diabetes. By synthesizing clinical research and experimental data, the paper elucidates the potential and mechanisms of its primary active components in preventing and treating these diseases. In conclusion, Taxus × media demonstrates its unique value in biological research and tremendous potential in drug development.

Construction and validation of a rat model of acute necrotizing pancreatitis-associated intestinal injury.

Acute pancreatitis (AP) is an acute inflammatory reaction of the pancreatic tissue, which involves auto-digestion, edema, hemorrhage, and necrosis. AP can be categorized into mild, moderately severe, and severe AP, with severe pancreatitis also referred to as acute necrotizing pancreatitis (ANP). ANP is characterized by the accumulation of necrotic material in the peritoneal cavity. This can result in intestinal injury. However, the mechanism of ANP-associated intestinal injury remains unclear. We established an ANP-associated intestinal injury rat model (ANP-IR model) by injecting pancreatitis-associated ascites fluid (PAAF) and necrotic pancreatic tissue at various proportions into the triangular area formed by the left renal artery and ureter. The feasibility of the ANP-IR model was verified by comparing the similar changes in indicators of intestinal inflammation and barrier function between the two rat models. In addition, we detected changes in apoptosis levels and YAP protein expression in the ileal tissues of rats in each group and validated them in vitro in rat epithelial crypt cells (IEC-6) to further explore the potential injury mechanisms of ANP-associated intestinal injury. We also collected clinical data from patients with ANP to validate the effects of PAAF and pancreatic necrosis on intestinal injury. Our findings offer a theoretical basis for restricting the buildup of peritoneal necrosis in individuals with ANP, thus promoting the restoration of intestinal function and enhancing treatment efficacy. The use of the ANP-IR model in further studies can help us better understand the mechanism and treatment of ANP-associated intestinal injury.NEW & NOTEWORTHY We constructed a rat model of acute necrotizing pancreatitis-associated intestinal injury and verified its feasibility. In addition, we identified the mechanism by which necrotic pancreatic tissue and pancreatitis-associated ascites fluid (PAAF) cause intestinal injury through the HIPPO signaling pathway.

Research Progress on Taxus Extraction and Formulation Preparation Technologies.

Taxus, as a globally prevalent evergreen tree, contains a wealth of bioactive components that play a crucial role in the pharmaceutical field. Taxus extracts, defined as a collection of one or more bioactive compounds extracted from the genus Taxus spp., have become a significant focus of modern cancer treatment research. This review article aims to delve into the scientific background of Taxus extracts and their considerable value in pharmaceutical research. It meticulously sifts through and compares various advanced extraction techniques such as supercritical extraction, ultrasound extraction, microwave-assisted extraction, solid-phase extraction, high-pressure pulsed electric field extraction, and enzymatic extraction, assessing each technology's advantages and limitations across dimensions such as extraction efficiency, extraction purity, economic cost, operational time, and environmental impact, with comprehensive analysis results presented in table form. In the area of drug formulation design, this paper systematically discusses the development strategies for solid, liquid, and semi-solid dosage forms based on the unique physicochemical properties of Taxus extracts, their intended medical uses, and specific release characteristics, delving deeply into the selection of excipients and the critical technical issues in the drug preparation process. Moreover, the article looks forward to the potential directions of Taxus extracts in future research and medical applications, emphasizing the urgency and importance of continuously optimizing extraction methods and formulation design to enhance treatment efficacy, reduce production costs, and decrease environmental burdens. It provides a comprehensive set of preparation techniques and formulation optimization schemes for researchers in cancer treatment and other medical fields, promoting the application and development of Taxus extracts in pharmaceutical sciences.

Silver Nanoparticles Encapped by Dihydromyricetin: Optimization of Green Synthesis, Characterization, Toxicity, and Anti-MRSA Infection Activities for Zebrafish (Danio rerio).

To achieve the environmentally friendly and rapid green synthesis of efficient and stable AgNPs for drug-resistant bacterial infection, this study optimized the green synthesis process of silver nanoparticles (AgNPs) using Dihydromyricetin (DMY). Then, we assessed the impact of AgNPs on zebrafish embryo development, as well as their therapeutic efficacy on zebrafish infected with Methicillin-resistant Staphylococcus aureus (MRSA). Transmission electron microscopy (TEM) and dynamic light-scattering (DLS) analyses revealed that AgNPs possessed an average size of 23.6 nm, a polymer dispersity index (PDI) of 0.197 ± 0.0196, and a zeta potential of -18.1 ± 1.18 mV. Compared to other published green synthesis products, the optimized DMY-AgNPs exhibited smaller sizes, narrower size distributions, and enhanced stability. Furthermore, the minimum concentration of DMY-AgNPs required to affect zebrafish hatching and survival was determined to be 25.0 µg/mL, indicating the low toxicity of DMY-AgNPs. Following a 5-day feeding regimen with DMY-AgNP-containing food, significant improvements were observed in the recovery of the gills, intestines, and livers in MRSA-infected zebrafish. These results suggested that optimized DMY-AgNPs hold promise for application in aquacultures and offer potential for further clinical use against drug-resistant bacteria.

Research Progress on Bioactive Factors against Skin Aging.

The relentless pursuit of effective strategies against skin aging has led to significant interest in the role of bioactive factors, particularly secondary metabolites from natural sources. The purpose of this study is to meticulously explore and summarize the recent advancements in understanding and utilization of bioactive factors against skin aging, with a focus on their sources, mechanisms of action, and therapeutic potential. Skin, the largest organ of the body, directly interacts with the external environment, making it susceptible to aging influenced by factors such as UV radiation, pollution, and oxidative stress. Among various interventions, bioactive factors, including peptides, amino acids, and secondary metabolites, have shown promising anti-aging effects by modulating the biological pathways associated with skin integrity and youthfulness. This article provides a comprehensive overview of these bioactive compounds, emphasizing collagen peptides, antioxidants, and herbal extracts, and discusses their effectiveness in promoting collagen synthesis, enhancing skin barrier function, and mitigating the visible signs of aging. By presenting a synthesis of the current research, this study aims to highlight the therapeutic potential of these bioactive factors in developing innovative anti-aging skin care solutions, thereby contributing to the broader field of dermatological research and offering new perspectives for future studies. Our findings underscore the importance of the continued exploration of bioactive compounds for their potential to revolutionize anti-aging skin care and improve skin health and aesthetics.

Research Progress in Skin Aging and Immunity.

Skin aging is a complex process involving structural and functional changes and is characterized by a decrease in collagen content, reduced skin thickness, dryness, and the formation of wrinkles. This process is underpinned by multiple mechanisms including the free radical theory, inflammation theory, photoaging theory, and metabolic theory. The skin immune system, an indispensable part of the body's defense mechanism, comprises macrophages, lymphocytes, dendritic cells, and mast cells. These cells play a pivotal role in maintaining skin homeostasis and responding to injury or infection. As age advances, along with various internal and external environmental stimuli, skin immune cells may undergo senescence or accelerated aging, characterized by reduced cell division capability, increased mortality, changes in gene expression patterns and signaling pathways, and altered immune cell functions. These changes collectively impact the overall function of the immune system. This review summarizes the relationship between skin aging and immunity and explores the characteristics of skin aging, the composition and function of the skin immune system, the aging of immune cells, and the effects of these cells on immune function and skin aging. Immune dysfunction plays a significant role in skin aging, suggesting that immunoregulation may become one of the important strategies for the prevention and treatment of skin aging.

Bif­1 inhibits activation of inflammasome through autophagy regulatory mechanism.

Inflammasome activation is a crucial mechanism in inflammatory responses. Bax­interacting factor 1 (Bif­1) is required for the normal formation of autophagosomes, but its ability to exert an inflammatory regulatory effect remains unclear. The aim of the present study was to explore the role of Bif­1 in inflammation, possibly mediated through autophagy regulation. Using a lipopolysaccharide (LPS)/adenosine triphosphate (ATP)­induced inflammatory model in J774A.1 cells, the effect of Bif­1 on inflammasome activation and the underlying mechanisms involving autophagy regulation were investigated. Elevated levels of NLR family pyrin domain containing protein 3 inflammasome and interleukin­1ß (IL­1ß) proteins were observed in J774A.1 cells after LPS/ATP induction. Furthermore, Bif­1 and autophagy activity were significantly upregulated in inflammatory cells. Inhibition of autophagy resulted in inflammasome activation. Silencing Bif­1 expression significantly upregulated IL­1ß levels and inhibited autophagy activity, suggesting a potential anti­inflammatory role of Bif­1 mediated by autophagy. Additionally, inhibition of the nuclear factor­κB (NF­κB) signaling pathway downregulated Bif­1 and inhibited autophagy activity, highlighting the importance of NF­κB in the regulation of Bif­1 and autophagy. In summary, the current study revealed that Bif­1 is a critical anti­inflammatory factor against inflammasome activation mediated by a mechanism of autophagy regulation, indicating its potential as a therapeutic target for inflammatory regulation.

Advancements in the Cultivation, Active Components, and Pharmacological Activities of Taxus mairei.

Taxus mairei (Lemée and H.Lév.) S.Y.Hu, indigenous to the southern regions of China, is an evergreen tree belonging to the genus Taxus of the Taxaceae family. Owing to its content of various bioactive compounds, it exhibits multiple pharmacological activities and has been widely applied in clinical medicine. This article comprehensively discusses the current state of cultivation, chemical constituents, applications in the pharmaceutical field, and the challenges faced by T. mairei. The paper begins by detailing the ecological distribution of T. mairei, aiming to provide an in-depth understanding of its origin and cultivation overview. In terms of chemical composition, the article thoroughly summarizes the extracts and monomeric components of T. mairei, unveiling their pharmacological activities and elucidating the mechanisms of action based on the latest scientific research, as well as their potential as lead compounds in new drug development. The article also addresses the challenges in the T. mairei research, such as the difficulties in extracting and synthesizing active components and the need for sustainable utilization strategies. In summary, T. mairei is a rare species important for biodiversity conservation and demonstrates significant research and application potential in drug development and disease treatment.

Temporal topic model for clinical pathway mining from electronic medical records.

BACKGROUND: In recent years, the discovery of clinical pathways (CPs) from electronic medical records (EMRs) data has received increasing attention because it can directly support clinical doctors with explicit treatment knowledge, which is one of the key challenges in the development of intelligent healthcare services. However, the existing work has focused on topic probabilistic models, which usually produce treatment patterns with similar treatment activities, and such discovered treatment patterns do not take into account the temporal process of patient treatment which does not meet the needs of practical medical applications. METHODS: Based on the assumption that CPs can be derived from the data of EMRs which usually record the treatment process of patients, this paper proposes a new CPs mining method from EMRs, an extended form of the traditional topic model - the temporal topic model (TTM). The method can capture the treatment topics and the corresponding treatment timestamps for each treatment day. RESULTS: Experimental research conducted on a real-world dataset of patients' hospitalization processes, and the achieved results demonstrate the applicability and usefulness of the proposed methodology for CPs mining. Compared to existing benchmarks, our model shows significant improvement and robustness. CONCLUSION: Our TTM provides a more competitive way to mine potential CPs considering the temporal features of the EMR data, providing a very prospective tool to support clinical diagnostic decisions.

Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction.

Reservoir computing has attracted considerable attention due to its low training cost. However, existing neuromorphic hardware, focusing mainly on shallow-reservoir computing, faces challenges in providing adequate spatial and temporal scales characteristic for effective computing. Here, we report an ultra-short channel organic neuromorphic vertical transistor with distributed reservoir states. The carrier dynamics used to map signals are enriched by coupled multivariate physics mechanisms, while the vertical architecture employed greatly increases the feedback intensity of the device. Consequently, the device as a reservoir, effectively mapping sequential signals into distributed reservoir state space with 1152 reservoir states, and the range ratio of temporal and spatial characteristics can simultaneously reach 2640 and 650, respectively. The grouped-reservoir computing based on the device can simultaneously adapt to different spatiotemporal task, achieving recognition accuracy over 94% and prediction correlation over 95%. This work proposes a new strategy for developing high-performance reservoir computing networks.

An improved binary particle swarm optimization algorithm for clinical cancer biomarker identification in microarray data.

BACKGROUND AND OBJECTIVE: The limited number of samples and high-dimensional features in microarray data make selecting a small number of features for disease diagnosis a challenging problem. Traditional feature selection methods based on evolutionary algorithms are difficult to search for the optimal set of features in a limited time when dealing with the high-dimensional feature selection problem. New solutions are proposed to solve the above problems. METHODS: In this paper, we propose a hybrid feature selection method (C-IFBPFE) for biomarker identification in microarray data, which combines clustering and improved binary particle swarm optimization while incorporating an embedded feature elimination strategy. Firstly, an adaptive redundant feature judgment method based on correlation clustering is proposed for feature screening to reduce the search space in the subsequent stage. Secondly, we propose an improved flipping probability-based binary particle swarm optimization (IFBPSO), better applicable to the binary particle swarm optimization problem. Finally, we also design a new feature elimination (FE) strategy embedded in the binary particle swarm optimization algorithm. This strategy gradually removes poorer features during iterations to reduce the number of features and improve accuracy. RESULTS: We compared C-IFBPFE with other published hybrid feature selection methods on eight public datasets and analyzed the impact of each improvement. The proposed method outperforms other current state-of-the-art feature selection methods in terms of accuracy, number of features, sensitivity, and specificity. The ablation study of this method validates the efficacy of each component, especially the proposed feature elimination strategy significantly improves the performance of the algorithm. CONCLUSIONS: The hybrid feature selection method proposed in this paper helps address the issue of high-dimensional microarray data with few samples. It can select a small subset of features and achieve high classification accuracy on microarray datasets. Additionally, independent validation of the selected features shows that those chosen by C-IFBPFE have strong correlations with disease phenotypes and can identify important biomarkers from data related to biomedical problems.

Research Progress in Skin Aging, Metabolism, and Related Products.

In recent years, skin aging has received increasing attention. Many factors affect skin aging, and research has shown that metabolism plays a vital role in skin aging, but there needs to be a more systematic review. This article reviews the interaction between skin metabolism and aging from the perspectives of glucose, protein, and lipid metabolism and explores relevant strategies for skin metabolism regulation. We found that skin aging affects the metabolism of three major substances, which are glucose, protein, and lipids, and the metabolism of the three major substances in the skin also affects the process of skin aging. Some drugs or compounds can regulate the metabolic disorders mentioned above to exert anti-aging effects. Currently, there are a variety of products, but most of them focus on improving skin collagen levels. Skin aging is closely related to metabolism, and they interact with each other. Regulating specific metabolic disorders in the skin is an important anti-aging strategy. Research and development have focused on improving collagen levels, while the regulation of other skin glycosylation and lipid disorders including key membrane or cytoskeleton proteins is relatively rare. Further research and development are expected.

Association between systemic lupus erythematosus and inflammatory bowel disease in European and East Asian populations: a two-sample Mendelian randomization study.

Background: Previous studies have shown a coexistence phenomenon between systemic lupus erythematosus (SLE) and inflammatory bowel disease (IBD), but the causal relationship between them is still unclear. Therefore, we conducted a two-sample Mendelian randomization (MR) analysis using publicly available summary statistics data to evaluate whether there was a causal relationship between the two diseases. Methods: Summary statistics for SLE and IBD were downloaded from the Open Genome-Wide Association Study and the International Inflammatory Bowel Disease Genetics Consortium. European and East Asian populations were included in this MR work. We adopted a series of methods to select instrumental variables that are closely related to SLE and IBD. To make the conclusion more reliable, we applied a variety of different analysis methods, among which the inverse variance-weighted (IVW) method was the main method. In addition, heterogeneity, pleiotropy, and sensitivity were assessed to make the conclusions more convincing. Results: In the European population, a negative causal relationship was observed between SLE and overall IBD (OR = 0.94; 95% CI = 0.90, 0.98; P < 0.004) and ulcerative colitis (UC) (OR = 0.93; 95% CI = 0.88, 0.98; P = 0.006). After removing outliers with Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), the results remained consistent with IVW. However, there was no causal relationship between SLE and Crohn's disease. In the East Asian population, no causal relationship was found between SLE and IBD. Conclusion: Our results found that genetic susceptibility to SLE was associated with lower overall IBD risk and UC risk in European populations. In contrast, no association between SLE and IBD was found in East Asian populations. This work might enrich the previous research results, and it may provide some references for research in the future.

Coal Structure Characteristics of the 2# Coal Seam in the Jiaozuo Mining Area and Its Geological Dependence.

To clarify the coal structure, spatial distribution, and controlling factors of the 2# coal seam in Jiaozuo mining, the drilling coal samples were collected to observe the coal type and coal structure. The coal macerals were identified by a MPVSP microscope photometer, and the spatial characteristics of the coal structure were obtained through interpreting deep lateral resistivity logging, natural gamma ray logging, density logging, and acoustic logging curves. The influence of coal properties, burial depth, geological stress, and faults on the coal structure were discussed correspondingly. The results exhibit that granulitic-mylonite coal was most developed in the 2# coal seam, followed by primary coal and cataclastic coal; the coal type was dominated by semibright coal, followed by clarain and semidull coal. Granulitic-mylonite, cataclastic, and primary coals were the main components of clarain, semibright coal, and semidull coal, respectively. Higher vitrinite and organic matter contents were conducive to the development of granulitic-mylonite. The coal structure combinations were spatially varied, and the granulitic-mylonite combinations were the most common. Granulitic-mylonite coal was developed in the east and south parts of the study area, and the coal structure was fragmented with a greater burial depth and larger thickness. The geological stress is the fundamental cause of coal structure damage as well as the cutting of faults.

Transformer-Based Multi-Modal Data Fusion Method for COPD Classification and Physiological and Biochemical Indicators Identification.

As the number of modalities in biomedical data continues to increase, the significance of multi-modal data becomes evident in capturing complex relationships between biological processes, thereby complementing disease classification. However, the current multi-modal fusion methods for biomedical data require more effective exploitation of intra- and inter-modal interactions, and the application of powerful fusion methods to biomedical data is relatively rare. In this paper, we propose a novel multi-modal data fusion method that addresses these limitations. Our proposed method utilizes a graph neural network and a 3D convolutional network to identify intra-modal relationships. By doing so, we can extract meaningful features from each modality, preserving crucial information. To fuse information from different modalities, we employ the Low-rank Multi-modal Fusion method, which effectively integrates multiple modalities while reducing noise and redundancy. Additionally, our method incorporates the Cross-modal Transformer to automatically learn relationships between different modalities, facilitating enhanced information exchange and representation. We validate the effectiveness of our proposed method using lung CT imaging data and physiological and biochemical data obtained from patients diagnosed with Chronic Obstructive Pulmonary Disease (COPD). Our method demonstrates superior performance compared to various fusion methods and their variants in terms of disease classification accuracy.

Cytoplasm Hydrogelation-Mediated Cardiomyocyte Sponge Alleviated Coxsackievirus B3 Infection.

Viral myocarditis (VMC), commonly caused by coxsackievirus B3 (CVB3) infection, lacks specific treatments and leads to serious heart conditions. Current treatments, such as IFNα and ribavirin, show limited effectiveness. Herein, rather than inhibiting virus replication, this study introduces a novel cardiomyocyte sponge, intracellular gelated cardiomyocytes (GCs), to trap and neutralize CVB3 via a receptor-ligand interaction, such as CAR and CD55. By maintaining cellular morphology, GCs serve as sponges for CVB3, inhibiting infection. In vitro results revealed that GCs could inhibit CVB3 infection on HeLa cells. In vivo, GCs exhibited a strong immune escape ability and effectively inhibited CVB3-induced viral myocarditis with a high safety profile. The most significant implication of this study is to develop a universal antivirus infection strategy via intracellular gelation of the host cell, which can be employed not only for treating defined pathogenic viruses but also for a rapid response to infection outbreaks caused by mutable and unknown viruses.