BACKGROUND:Human periodontal ligament stem cells are potential functional cells for periodontal tissue engineering.However,long-term in vitro culture may lead to reduced stemness and replicative senescence of periodontal ligament stem cells,which may impair the therapeutic effect of human periodontal ligament stem cells. OBJECTIVE:To investigate the effect of oxymatrine on the stemness maintenance and osteogenic differentiation of periodontal ligament stem cells in vitro,and to explore the potential mechanism. METHODS:Periodontal ligament stem cells were isolated from human periodontal ligament tissues by tissue explant enzyme digestion and cultured.The surface markers of mesenchymal cells were identified by flow cytometry.Periodontal ligament stem cells were incubated with 0,2.5,5,and 10 μg/mL oxymatrine.The effect of oxymatrine on the proliferation activity of periodontal ligament stem cells was detected by CCK8 assay.The appropriate drug concentration for subsequent experiments was screened.Western blot assay was used to detect the expression of stem cell non-specific proteins SOX2 and OCT4 in periodontal ligament stem cells.qRT-PCR and western blot assay were used to detect the expression levels of related osteogenic genes and proteins in periodontal ligament stem cells. RESULTS AND CONCLUSION:(1)The results of CCK8 assay showed that 2.5 μg/mL oxymatrine significantly enhanced the proliferative activity of periodontal stem cells,and the subsequent experiment selected 2.5 μg/mL oxymatrine to intervene.(2)Compared with the blank control group,the protein expression level of SOX2,a stem marker of periodontal ligament stem cells in the oxymatrine group did not change significantly(P>0.05),and the expression of OCT4 was significantly up-regulated(P<0.05).(3)Compared with the osteogenic induction group,the osteogenic genes ALP,RUNX2 mRNA expression and their osteogenic associated protein ALP protein expression of periodontal ligament stem cells were significantly down-regulated in the oxymatrine+osteogenic induction group(P<0.05).(4)The oxymatrine up-regulated the expression of stemness markers of periodontal ligament stem cells and inhibited the bone differentiation of periodontal ligament stem cells,and the results of high-throughput sequencing showed that it may be associated with WNT2,WNT16,COMP,and BMP6.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

With the completion of the "Human Genome Project" and the smooth progress of the "Herbal Genome Project", the research wave of RNAomics is gradually advancing, opening the research gateway for the modernization of traditional Chinese medicine (TCM) and initiating the post-genome era of medicinal plant RNA research. Therefore, this article proposes for the first time the concept of HerbRNomes, which involves constructing databases of medicinal plant, medicinal fungus, and medicinal animal RNA at different stages, from different origins, and in different organs. This research aims to explore the role of HerbRNA in self-genetic information transmission, functional regulation, as well as cross-species regulation functional mechanisms and key technologies. It also investigates application scenarios, providing a theoretical basis and research ideas for the resistance of TCM or medicinal plants to adversity and stress, molecular assistant breeding, and the development of small nucleic acid drugs. This article reviews recent research progress in elucidating the molecular mechanisms of the transmission and expression of genetic information, self-regulation and cross-species regulation of herbs at the RNA level, along with key technologies. It proposes a development strategy for small nucleic acid drugs based on HerbRNomes, providing theoretical support and guidance for the modernization of TCM based on HerbRNomes research.

Objective: To analyze the demographic characteristics of patients with red blood cell transfusion reactions, the usage of red blood cell preparations, and the differences in the composition ratio of adverse reactions based on multi-center data from the Haemovigilance Network, in order to reveal the clinical characteristics of red blood cell transfusion and its underlying issues. Methods: Clinical data of patients who experienced transfusion reactions after red blood cell transfusion in the Haemovigilance Network from 2018 to 2023 were collected. The demographic characteristics of patients who experienced transfusion reactions with different types of red blood cell preparations, the utilization of these preparations, and the differences of the composition ratios of transfusion reactions were analyzed. Count data were expressed as numbers (n) or percentages (%), and comparisons between groups were performed using the Chi-square test. Results: Red blood cell transfusion reactions were more common in females (53.56%), with the majority of patients aged 50-69 years (35.54%). The Han polulation accounted for the vast majority of patients (92.77%), and patients in the hematology and obstetrics/gynecology departments had a relatively high proportion of transfusion reactions (13.26% and 14.26%, respectively). Leukocyte-reduced red blood cells and suspended red blood cells were the most common types of transfusion reactions reported among red blood cell preparations. Allergic reactions and non-hemolytic febrile reactions were the most common transfusion reactions, and there were significant differences in the composition ratios of allergic reactions (χ =869.89, P<0.05) and non-hemolytic febrile reactions (χ =812.75, P<0.05) across various types of red blood cell preparations. Conclusion: There are differences in the demographic characteristics and composition ratio of transfusion reactions among different red blood cell preparations. The management of red blood cell transfusion reactions should be tailored to patient characteristics and conditions, and the selection and use of blood products should be optimized to reduce or avoid the occurrence of transfusion reactions, such as considering the use of washed red blood cells for patients with a history of transfusion allergies or those prone to allergies.

Colorectal cancer(CRC) is one of the most common malignant tumors worldwide, primarily originating from recurrent inflammatory bowel disease(IBD). Therefore, blocking the inflammation-cancer transformation in the colon has become a focus in the early prevention and treatment of CRC. The inflammation-cancer transformation in the colon involves multiple types of cells and complex pathological processes, including inflammatory responses and tumorigenesis. In this complex pathological process, immune cells(including non-specific and specific immune cells) and non-immune cells(such as tumor cells and fibroblasts) interact with each other, collectively promoting the progression of the disease. In traditional Chinese medicine(TCM), inflammation-cancer transformation in the colon belongs to the categories of dysentery and diarrhea, with the main pathogenesis being cold and heat in complexity. This paper first elaborates on the complex molecular mechanisms involved in the inflammation-cancer transformation process in the colon from the perspectives of inflammation, cancer, and their mutual influences. Subsequently, by comparing the pathogenic characteristics and clinical manifestations between inflammation-cancer transformation and the TCM pathogenesis of cold and heat in complexity, this paper explores the intrinsic connections between the two. Furthermore, based on the correlation between inflammation-cancer transformation in the colon and the TCM pathogenesis, this paper delves into the importance of the interaction between inflammation and cancer. Finally, it summarizes and discusses the clinical and basic research progress in the TCM intervention in the inflammation-cancer transformation process, providing a theoretical basis and treatment strategy for the treatment of CRC with integrated traditional Chinese and Western medicine.
Humans ; Colon/pathology* ; Integrative Medicine ; Animals ; Cold Temperature ; Cell Transformation, Neoplastic/drug effects* ; Medicine, Chinese Traditional ; Hot Temperature ; Inflammation ; Drugs, Chinese Herbal/therapeutic use* ; Colonic Neoplasms/drug therapy*

This study aims to explore the mechanism of Buyang Huanwu Decoction(BHD) in promoting angiogenesis after oxygen-glucose deprivation/reoxygenation(OGD/R) of mouse brain microvascular endothelial cell line(brain-derived Endothelial cells.3, bEnd.3) based on the caveolin-1(Cav1)/Yes-associated protein 1(YAP1)/hypoxia-inducible factor-1α(HIF-1α) signaling pathway. Ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was used to analyze the blood components of BHD. The cell counting kit-8(CCK-8) method was used to detect the optimal intervention concentration of drug-containing serum of BHD after OGD/R injury of bEnd.3. The lentiviral transfection method was used to construct a Cav1 silent stable strain, and Western blot and polymerase chain reaction(PCR) methods were used to verify the silencing efficiency. The control bEnd.3 cells were divided into a normal group(sh-NC control group), an OGD/R model + blank serum group(sh-NC OGD/R group), and an OGD/R model + drug-containing serum group(sh-NC BHD group). Cav1 silent cells were divided into an OGD/R model + blank serum group(sh-Cav1 OGD/R group) and an OGD/R model + drug-containing serum group(sh-Cav1 BHD group). The cell survival rate was detected by the CCK-8 method. The cell migration ability was detected by a cell migration assay. The lumen formation ability was detected by an angiogenesis assay. The apoptosis rate was detected by flow cytometry, and the expression of YAP1/HIF-1α signaling pathway-related proteins in each group was detected by Western blot. Finally, co-immunoprecipitation was used to verify the interaction between YAP1 and HIF-1α. The results showed astragaloside Ⅳ, formononetin, ferulic acid, and albiflorin in BHD can all enter the blood. The drug-containing serum of BHD at a mass fraction of 10% may be the optimal intervention concentration for OGD/R-induced injury of bEnd.3 cells. Compared with the sh-NC control group, the sh-NC OGD/R group showed significantly decreased cell survival rate, cell migration rate, mesh number, node number, and lumen length, significantly increased cell apoptotic rate, significantly lowered phosphorylation level of YAP1 at S127 site, and significantly elevated nuclear displacement level of YAP1 and protein expression of HIF-1α, vascular endothelial growth factor(VEGF), and vascular endothelial growth factor receptor 2(VEGFR2). Compared with the same type of OGD/R group, the sh-NC BHD group and sh-Cav1 BHD group had significantly increased cell survival rate, cell migration rate, mesh number, node number, and lumen length, a significantly decreased cell apoptotic rate, a further decreased phosphorylation level of YAP1 at S127 site, and significantly increased nuclear displacement level of YAP1 and protein expression of HIF-1α, VEGF, and VEGFR2. Compared with the sh-NC OGD/R group, the sh-Cav1 OGD/R group exhibited significantly decreased cell survival rate, cell migration rate, mesh number, node number, and lumen length, a significantly increased cell apoptotic rate, a significantly increased phosphorylation level of YAP1 at S127 site, and significantly decreased nuclear displacement level of YAP1 and protein expression of HIF-1α, VEGF, and VEGFR2. Compared with the sh-NC BHD group, the sh-Cav1 BHD group showed significantly decreased cell survival rate, cell migration rate, mesh number, node number, and lumen length, a significantly increased cell apoptotic rate, a significantly increased phosphorylation level of YAP1 at the S127 site, and significantly decreased nuclear displacement level of YAP1 and protein expression of HIF-1α, VEGF, and VEGFR2. YAP1 protein was present in the protein complex precipitated by the HIF-1α antibody, and HIF-1α protein was also present in the protein complex precipitated by the YAP1 antibody. The results confirmed that the drug-containing serum of BHD can increase the activity of YAP1/HIF-1α pathway in bEnd.3 cells damaged by OGD/R through Cav1 and promote angiogenesis in vitro.
Drugs, Chinese Herbal/pharmacology* ; Animals ; Mice ; Signal Transduction/drug effects* ; Glucose/metabolism* ; Caveolin 1/genetics* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; YAP-Signaling Proteins ; Oxygen/metabolism* ; Endothelial Cells/metabolism* ; Cell Line ; Adaptor Proteins, Signal Transducing/genetics* ; Neovascularization, Physiologic/drug effects* ; Cell Hypoxia/drug effects* ; Angiogenesis

This study aimed to investigate the effect and mechanism of Buyang Huanwu Decoction in regulating endoplasmic reticulum stress via the inositol-requiring enzyme 1α(IRE1α)/apoptosis signal-regulating kinase 1(ASK1)/c-Jun N-terminal kinase(JNK) pathway to improve neurological function in rats with cerebral ischemia/reperfusion injury(CIRI). SPF-grade male sprague-dawley(SD) rats were randomly divided into Sham group, model group, Buyang Huanwu Decoction group, and edaravone group. Except for the Sham group, the other groups were subjected to the modified suture method to establish a middle cerebral artery occlusion/reperfusion(MCAO/R) model. After treatment, neurological function was assessed using the Zea Longa scoring system. Gait analysis was used to detect the motor function. Detection of relative infarct area in brain tissue using 2,3,5-triphenyltetrazolium chloride(TTC) staining. Nissl staining was used to observe the structure of neuronal cells. Western blot and real-time fluorescence quantitative PCR(RT-qPCR) were used to detect IRE1α, ASK1, JNK, B cell lymphoma-2(Bcl-2), Bcl-2 related X protein(Bax), and Caspase-3 in the brain tissue. Immunohistochemistry was used to detect the positive expression of IRE1α, ASK1, and JNK. Immunofluorescence was used to detect the fluorescence expression levels of Bax, Bcl-2, and Caspase-3. The results showed that compared with the Sham group, the model group exhibited increased neurological scores(P<0.01), increased ratio of ground contact area and strength in both forelimbs(P<0.01), enlarged relative infarct area of brain tissue(P<0.05), and a reduced number of Nissl staining-positive cells(P<0.01). The protein and mRNA expression levels of IRE1α, ASK1, JNK, Bax, and Caspase-3 in brain tissue were significantly elevated, while those of Bcl-2 were decreased(P<0.05). Compared with the model group, both the Buyang Huanwu Decoction group and edaravone group showed reduced neurological scores(P<0.05), decreased ratio of ground contact area and strength in both forelimbs(P<0.05), smaller relative infarct area(P<0.05), alleviated neuronal damage, and increased number of Nissl staining-positive cells(P<0.05). The expression levels of IRE1α, ASK1, JNK, Bax, and Caspase-3 protein and mRNA in brain tissue were significantly reduced, while those of Bcl-2 were significantly increased(P<0.05). The results indicated that Buyang Huanwu Decoction can effectively improve brain injury in CIRI rats, and its mechanism of action may be related to regulating the endoplasmic reticulum stress IRE1α/ASK1/JNK signaling pathway.
Animals ; Male ; Rats, Sprague-Dawley ; Protein Serine-Threonine Kinases/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; MAP Kinase Kinase Kinase 5/genetics* ; Ischemic Stroke/physiopathology* ; Humans ; MAP Kinase Signaling System/drug effects* ; Apoptosis/drug effects* ; Endoribonucleases/genetics* ; JNK Mitogen-Activated Protein Kinases/genetics* ; Endoplasmic Reticulum Stress/drug effects* ; Multienzyme Complexes

With the continuous advancement of medical research, it is increasingly recognized that the human body functions as a highly coordinated complex system, and the development of diseases often involves intricate interactions among multiple subsystems, including organs, tissues, and cells. Conventional pharmacological research, which primarily focuses on isolated subsystems, tends to emphasize direct interactions between drugs and the molecular targets in diseased organs. However, this approach often falls short in addressing the multifaceted challenges posed by complex diseases such as metabolic disorders, autoimmune diseases, cancers, and aging. In recent years, inter-organ cross-talk and its role in diseases progression, as well as cross-organ effects of drug intervention, have gained significant attention. This has highlighted the potential for treating complex diseases through holistic regulation of multiple organs. Traditional Chinese medicine(TCM) has long embraced a holistic and systemic approach for treatment, with concepts such as the interdependence and mutual restraint of the five Zang organs, the interconnection of Zang organs and Fu organs, treating the Zang organ diseases by regulating the Fu organs, treating the child organ diseases to cure the parent organs, and treating upper organ diseases by regulating lower organs. These concepts provide valuable insights into exploring the pathways and molecular mechanisms underlying inter-organ cross-talk. Building on our previous work on indirect actions of TCM, this paper introduces the concept of indirect pharmacology mediated by intermediate substances, as a new extension of classical pharmacology. This approach aims to offer new perspectives and innovative ideas for understanding inter-organ cross-talk and discovering cross-organ therapeutic strategies.
Humans ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology* ; Animals

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.