BACKGROUND:How to repair bone defect has been a clinical problem for a long time.The effective ingredients of traditional Chinese medicine have good biological activity and therapeutic effect,and the combination of effective ingredients of traditional Chinese medicine and tissue engineering materials has a broad prospect in the field of bone repair.The combination of different effective ingredients of traditional Chinese medicine and scaffolds has similarities in their functional relationships. OBJECTIVE:To collect the cases of the combinations of effective ingredients of traditional Chinese medicine and scaffolds,then analogize tissue engineering scaffolds and effective ingredients of traditional Chinese medicine into two types of traditional Chinese medicine that generate compatibility relationships based on the inspiration of the compatibility of seven emotions and summarize the relationship between the two based on their functional relationships. METHODS:Relevant articles from January 1998 to January 2024 were searched in PubMed and China National Knowledge Infrastructure(CNKI),using English search terms"traditional Chinese medicine,Chinese medicine,traditional Chinese medicine monomers,bone defect,bone repair,bone tissue engineering,tissue engineering,scaffold"and Chinese search terms"traditional Chinese medicine,effective ingredients of traditional Chinese medicine,traditional Chinese medicine monomers,bone tissue engineering,bone tissue engineering scaffold,scaffold,tissue engineering,bone defect,bone repair."A total of 88 articles were included for review and analysis. RESULTS AND CONCLUSION:(1)Both tissue engineering scaffold materials and active ingredients of traditional Chinese medicine have been widely used in the field of bone repair.Although they have obvious advantages in osteogenesis,there are still many shortcomings.Many studies are dedicated to preparing composite materials from the two,hoping to exert a detoxification and synergism through the interaction between the two.(2)Some drugs and materials can promote each other in osteogenesis,antibacterial,and promoting angiogenesis,enhancing their original effects.Inspired by the traditional concept of prescription compatibility,this article summarized it as a"Mutual promotion"relationship and provided examples to support it.(3)Some drugs can enhance the strength of materials,while some materials can achieve sustained release and controlled release effects,increase drug loading and stability,or achieve targeted delivery of drugs loaded on them.The article summarized this unilateral enhancement effect as a"Mutual assistance"relationship.(4)The combination of some traditional Chinese medicine and materials can reduce the toxic side effects of the other party.The article summarizes this detoxification relationship as"Mutual restraint and detoxification."(5)The article provided a new perspective on traditional Chinese medicine composite scaffolds,inspired by the seven emotions compatibility relationship and based on the classification of action relationships.It introduced traditional Chinese medicine concepts into the field of tissue engineering,providing new research ideas for subsequent researchers of composite scaffolds,and providing certain convenience in material selection and matching.

BACKGROUND:As a common disease in middle-aged and elderly,osteoarthritis is difficult to cure,and the pathogenesis is not clear.Long non-coding RNA participates in the pathogenesis of osteoarthritis through many ways,such as regulating translation,promoting or inhibiting mRNA,and adsorbing miRNAs. OBJECTIVE:To review the types of common long non-coding RNA in osteoarthritis,and the influence of multiple long non-coding RNAs on the pathological factors related to osteoarthritis,to analyze the future application of long non-coding RNAs in osteoarthritis. METHODS:Literature retrieval was conducted in CNKI,WanFang Data,VIP database,PubMed,Web of Science and Sciencedirect databases,using the search terms of"osteoarthritis,degenerative joint disease,degenerative arthritis,OA,LncRNA,long non-coding RNA,long noncoding RNA,long intergenic non-coding RNA"in Chinese and English.All relevant literature published from 1976 and May 2024 was retrieved.After literature screening,induction,analysis and summary,93 articles were finally included for review. RESULTS AND CONCLUSION:This review collected 25 long non-coding RNAs that are well studied with osteoarthritis.Long non-coding RNAs,as a molecular sponge for miRNA,are competing endogenous RNAs to competitively adsorb miRNAs and then affect downstream targets.Long non-coding RNAs can regulate physiopathological processes such as chondrocyte apoptosis and proliferation,cartilage extracellular matrix degradation,and inflammatory responses.Long non-coding RNAs are expected to become a biomarker and potential therapeutic target for the clinical diagnosis and therapeutic prognosis of osteoarthritis,and it may become a new strategy for the clinical treatment of osteoarthritis in the future.

Previous studies have found associations between color discrimination deficits and cognitive impairments besides aging. However, investigations into the microstructural pathology of brain white matter (WM) associated with these deficits remain limited. This study aimed to examine the microstructural characteristics of WM in the non-demented population with abnormal color discrimination, utilizing Neurite Orientation Dispersion and Density Imaging (NODDI), and to explore their correlations with cognitive functions and cognition-related plasma biomarkers. The tract-based spatial statistic analysis revealed significant differences in specific brain regions between the abnormal color discrimination group and the healthy controls, characterized by increased isotropic volume fraction and decreased neurite density index and orientation dispersion index. Further analysis of region-of-interest parameters revealed that the isotropic volume fraction in the bilateral anterior thalamic radiation, superior longitudinal fasciculus, cingulum, and forceps minor was significantly correlated with poorer performance on neuropsychological assessments and to varying degrees various cognition-related plasma biomarkers. These findings provide neuroimaging evidence that WM microstructural abnormalities in non-demented individuals with abnormal color discrimination are associated with cognitive dysfunction, potentially serving as early markers for cognitive decline.
Humans ; White Matter/pathology* ; Male ; Female ; Cognitive Dysfunction/physiopathology* ; Middle Aged ; Aged ; Color Perception/physiology* ; Brain/pathology* ; Neuropsychological Tests ; Diffusion Tensor Imaging

One of the basic questions in the aging field is whether there is a fundamental difference between the aging of lower invertebrates and mammals. A major difference between the lower invertebrates and mammals is the abundancy of noncoding RNAs, most of which are not conserved. We have previously identified a noncoding RNA Terc-53 that is derived from the RNA component of telomerase Terc. To study its physiological functions, we generated two transgenic mouse models overexpressing the RNA in wild-type and early-aging Terc-/- backgrounds. Terc-53 mice showed age-related cognition decline and shortened life span, even though no developmental defects or physiological abnormality at an early age was observed, indicating its involvement in normal aging of mammals. Subsequent mechanistic study identified hyaluronan-mediated motility receptor (Hmmr) as the main effector of Terc-53. Terc-53 mediates the degradation of Hmmr, leading to an increase of inflammation in the affected tissues, accelerating organismal aging. adeno-associated virus delivered supplementation of Hmmr in the hippocampus reversed the cognition decline in Terc-53 transgenic mice. Neither Terc-53 nor Hmmr has homologs in C. elegans. Neither do arthropods express hyaluronan. These findings demonstrate the complexity of aging in mammals and open new paths for exploring noncoding RNA and Hmmr as means of treating age-related physical debilities and improving healthspan.
Animals ; Mice ; RNA, Untranslated/metabolism* ; Aging/genetics* ; Mice, Transgenic ; Telomerase/metabolism* ; RNA/genetics* ; Hippocampus/metabolism* ; Humans ; Mice, Inbred C57BL

OBJECTIVE To observe the clinical efficacy of Maitong Jun'an Decoction in treating coronary heart disease(CHD)angina of qi deficiency and blood stasis type,and preliminarily elucidate its possible mechanism of action through transcriptomics meth-ods.METHODS A total of 140 patients with CHD angina of qi deficiency and blood stasis type were included and randomly divided into a treatment group and a control group,with 70 cases in each group.During the treatment period,3 patients in the control group dropped out.The control group received basic Western medicine treatment for secondary prevention of CHD,while the treatment group received Maitong Jun'an Decoction in addition to the treatment in the control group.The treatment period for both groups was 8 weeks.Before and after treatment,the patients in both groups were evaluated for the TCM syndrome score,Canadian Cardiovascular Society(CCS)angina grading,Seattle angina questionnaire(SAQ)score,self-rating anxiety scale(SAS),self-rating depression scale(SDS)score,and adverse reactions.The peripheral blood of 9 patients before and after treatment was selected for transcriptomic sequencing based on the principle of gender,age,and disease duration matching.RESULTS After treatment,the TCM syndrome scores and total scores of the 2 groups were significantly reduced(P<0.01).The treatment group was better than the control group in improving chest pain,chest tightness,shortness of breath,fatigue and total score(P<0.05,P<0.01);the overall improvement rate of CCS angina grading in the treatment group was better than that in the control group(P<0.05);the SAQ,SAS and SDS scores of the 2 groups were significantly reduced before and after treatment(P<0.01),and the SAQ score of the treatment group was improved better than that of the control group(P<0.05,P<0.01).The transcriptomics results showed that there were 862 significantly different mR-NAs before and after treatment,including 509 up-regulated and 353 down-regulated.GO analysis showed that there were 666 biologi-cal processes in the differentially expressed mRNAs,mainly including viral gene expression,translation initiation,RNA catabolism,etc.There were 112 cell components,mainly including focal adhesion,ribosome subunit,nuclear spot,etc.There were 94 molecular functions,mainly including double-stranded RNA binding,cadherin binding,transcription co-regulatory factor activity,etc.KEGG analysis showed that the differentially expressed mRNAs enriched in 20 signaling pathways,mainly including glycerophospholipid me-tabolism pathway,AMPK signaling pathway,ribosome pathway,etc.CONCLUSION Maitong Jun'an Decoction can improve clini-cal symptoms in patients with CHD angina of qi deficiency and blood stasis type.Its mechanism of action is multi-target and multi pathway,mainly related to the regulation of glycerophospholipid metabolism pathway,AMPK signaling pathway,ribosome pathway.

Sepsis is a multi-organ dysfunction syndrome caused by infection and immune dysfunction, with a high mortality rate. It affects multiple important organs such as the heart, lungs, kidneys, liver, and brain. Establishing corresponding animal models of organ dysfunction syndrome is an essential step in clarifying its pathogenesis, researching potential effective drugs, and evaluating the effectiveness and safety of treatment plans. This article first summarizes classic modeling methods for sepsis related organ injury, including the destruction of intestinal barrier tissue integrity and the implantation of pathogens or toxic drugs. The former mainly includes cecal ligation and puncture, ascending colon stent implantation, and cecal ligation incision. The latter is divided into intraperitoneal injection, intravenous injection, and intratracheal administration based on the clinical infection route being simulated. Cecal ligation and puncture and lipopolysaccharide intraperitoneal injection are the most commonly used methods. Secondly, this article summarizes the common modeling methods and evaluation methods for animal models of sepsis-induced cardiomyopathy, acute lung injury, acute kidney injury, acute liver injury, and brain dysfunction. It points out that almost all organ injuries use classic modeling methods, and different organ injury models have additional modifications according to their different pathogenesis. For example, in addition to the classic modeling methods, lipopolysaccharide instillation in the trachea is more effective in modeling acute lung injury as it better simulates lung barrier dysfunction. Cecal ligation and puncture followed by Pseudomonas instillation in the trachea in a secondary challenge model better represents sepsis-induced acute kidney injury. Intraperitoneal injection of galactosamine is a mature modeling method of sepsis-induced acute liver injury. Intracerebral injection of lipopolysaccharide is a feasible model of sepsis-associated encephalopathy. In addition to the different modeling methods, there are differences in the administration time, dosage and experimental time points according to the different experimental purposes. This article reviews the research progress of animal experimental models for sepsis-induced cardiomyopathy, acute lung injury, acute kidney injury, acute liver injury, and brain dysfunction, aiming to provide a reference for the selection of animal experimental models and optimization of experimental design.

Objective:To investigate the clinical characteristics of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and corona virus disease 2019 (COVID-19) infection.Methods:Clinical data of AECOPD patients over 65 years old who were diagnosed in the Respiratory and Emergency Departments of the Dongzhimen Hospital, Beijing University of Chinese Medicine from September 2022 to September 2023 were collected. AECOPD patients were divided into a COVID-19 group ( n=29) and a non COVID-19 group ( n=31). The platelet count, white blood cell count, lymphocyte count, neutrophil count, neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), C-reactive protein (CRP), procalcitonin (PCT), partial pressure of oxygen (PO 2), partial pressure of carbon dioxide (PCO 2), D-dimer (D-D), and interleukin-6 (IL-6) were compared between two groups of patients upon admission Confusion, Uremia, Respiratory, BP, Age 65 Years (CURB-65) was used to compare length of hospital stay, AECOPD grading, and mortality endpoint days. Results:There was no statistically significant difference in platelet count, white blood cell count, lymphocyte count, neutrophil count, NLR, and PLR between the COVID-19 group and the non COVID-19 group (all P>0.05). The proportion of males, CRP, PCO 2, D-D, IL-6, and CURB-65 scores in the COVID-19 group were higher than those in the non COVID-19 group, while PCT and PO 2 were lower than those in the non COVID-19 group, with statistically significant difference (all P<0.05). The proportion of AECOPD grade Ⅲ in the COVID-19 group was significantly higher than that in the non COVID-19 group, and the progression rate of the disease was higher in the COVID-19 group (37.9% vs 22.6%, P<0.05). COVID-19 was an independent influencing factor for the progression of AECOPD. Conclusions:Patients over 65 years old with AECOPD infected with COVID-19 have a more pronounced inflammatory response, and CRP, IL-6, and CURB-65 scores can be used as indicators to evaluate the degree of inflammation. AECOPD infected with COVID-19 are more prone to coagulation disorders, hypoxemia, more severe illness, and easier progression, suggesting that COVID-19 infection is an independent influencing factor for the progression of AECOPD.

A lightweight residual attention enhanced Unet(LRAE-Unet)is designed for the fully automatic brain tumor segmentation.LRAE-Unet uses lightweight residual module to solve the problems of gradient disappearance and network degradation when the network layers increases,lightweight self-attention module to suppress the irrelevant areas and highlight the significant features of specific local areas,and enhanced average pooling module with a larger field of perception to reduce the space of feature map,save computing resources and avoid over-fitting.The experiment on BraTS 2019 dataset shows that the proposed method has a Dice similarity coefficient of 91.24%,88.64%and 88.32%in the segmentations of the whole tumor,tumor core and enhanced tumor,which proves its feasibility and effectiveness for brain tumor segmentation.

Objective The MMV-Net,a deep learning framework based on mammogram multiple views,was constructed to evaluate the classification performance of the model for benign and malignant masses.Methods A retrospective analysis was conduc-ted on a dataset of 1 585 breast X-ray images from Harbin Medical University Cancer Hospital from 2018 to 2020,including 806 be-nign cases and 779 malignant cases.The dataset was divided into the training set(n=1268)and the test set(n=317)according to an 8∶2 ratios,and the training set was stratified according to the 5-fold cross validation.The integrated DDSM dataset and INBreast dataset were used as external test sets(n=1645)to evaluate the model performance.Each case in the input layer contained 4 views.The MMV-Net model was constructed by removing the last two layers of the ResNet22 network structure and adding an average poo-ling layer as the feature extraction layer,as well as fully connection layer and softmax activation function as the decision layers.Bayes-ian hyperparameter optimization was used.The performance of MMV-Net,MFA Net,and ensemble inception V4 models in AUC val-ues,accuracy,precision,recall and F1 scores were compared.Results The AUC values of MMV-Net model for distinguishing benign and malignant masses on the test set were 0.913,0.882 for MFA-Net,and 0.865 for inception V4.The accuracy and precision evalu-ation metrics of the MMV-Net model were also higher than the other two models.Conclusion The deep learning MMV-Net model based on multiple views of mammogram is helpful for the classification of benign and malignant breast masses.

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.