As the important source of bone cells, osteoblasts are involved in bone formation and repair, and play a key role in maintaining bone balance. If the osteogenic differentiation process in vivo is disrupted, a variety of bone-related diseases may occur. Natural products, which have a wide range of sources, a wide variety of physiological activities, and few toxic side-effects, have been found in recent years to be able to regulate osteoblast differentiation. Based on the sources of natural products, this paper reviews the intervention of natural products from plant, animal and microbial sources on osteogenic differentiation, aiming to provide a theoretical basis for natural products in the treatment of bone diseases.

Uncaria rhynchophylla (Miq.)Miq. ex Havil (Gouteng) is a dry and hooked stem branch of Rubiaceae, which contains chemical components including alkaloids, terpenoids, flavonoids and organic acids. It has antioxidant, anti-inflammatory, and potential therapeutic effects on various diseases. The characteristics of network pharmacology are multi-component, multi-target and multi-channel, which can analyze the complex mechanism of the active ingredient group of traditional Chinese medicine and the disease markers, and clarify the relationship between drugs, targets and diseases. This review summarises the research progress of the intervention of Gouteng in neurological disorders, cardiovascular diseases, inflammation, and other diseases based on network pharmacology and provides a theoretical foundation for the clinical application of Gouteng.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

Objective To compare the effect of 8-week high-intensity interval training(HIIT)and moderate-intensity continuous training(MICT)on body composition and cardiovascular risk biomarkers in middle-aged and elderly obese women,so as to provide theoretical and practical basis for future in-tervention.Methods Thirty-four middle-aged and elderly obese women were randomly divided into an HIIT group(n=13),a MICT group(n=12)and a CON group(n=9).All subjects underwent a laboratory VO2max test before intervention to determine their corresponding exercise load.Then,HIIT group rode a power bicycle for 2 minutes at 80%～85%VO2max intensity and 1 minute at 30%VO2max intensity,re-peated 10 times,while MICT group rode at 65%VO2max intensity for 30 minutes,3 times a week for 8 weeks.CON group did exercise.Before and after intervention,all groups were measured their body weight,body fat,muscle mass,body fat rate,as well as the serum levels of high-sensitivity c-reac-tive protein(hs-CRP),endothelin-1(ET-1),lipoprotein(a)[Lp(a)]and homocysteine(Hcy).Results Af-ter intervention,there was a significant decrease in the body fat and body fat rate(P<0.05)and a sig-nificant increase in muscle mass(P<0.05)in the HIIT group,while there were no significant changes in the above three values in the MICT group(P>0.05).Moreover,there was a significant decrease in hs-CRP and ET-1 of the HIIT group(P<0.01),and a significant increase in Hcy and Lp(a)of the CON group(P<0.01).Meanwhile,the decrease in hs-CRP(P<0.05),Lp(a)(P<0.05)and Hcy(P<0.01)of the HIIT group,as well as that in Hcy(P<0.05)of the MICT group were significantly higher than the CON group.What's more,no significant differences were observed between HIIT and MICT groups in their effects(P>0.05).Conclusions HIIT is superior to MICT in improving body composition and reducing serum levels of hs-CRP and ET-1 in middle-aged and elderly obese women.Moreover,it has a positive effect on improving chronic inflammatory state and vascular endothelial function,to a certain extent,and lowering their risk of suffering from cardiovascular diseases.

The long-term presence of non-steroidal anti-inflammatory drugs (NSAIDs) in the environmental water samples not only affects the life safety of aquatic organisms and disturbs the ecoenvironment, but also poses a serious threat to human health. In this study, amino-functionalized Fe3O4 nanoparticles (Fe3O4-NH2) were firstly prepared by solvothermal method. Subsequently, polyethyleneimine (PEI) with a branched chain structure was successfully grafted onto Fe3O4 nanoparticles by Schiff base reaction in aqueous solution at room temperature using glutaraldehyde as a cross-linking agent, and a recyclable PEI-grafted magnetic nano-sorbent (Fe3O4@PEI) was synthesized and applied for the detection of NSAIDs in the environmental water samples. The compositional properties of Fe3O4@PEI were investigated by different characterization methods and the parameters affecting the extraction of NSAIDs were optimized. Due to high adsorption of Fe3O4@PEI for NSAIDs, the quantitative analysis of four NSAIDs in the environmental water samples, ketoprofen, naproxen, diclofenac and tolfenamic acid, was performed in combination with high-performance liquid chromatography. A good linear relationship between the chromatographic peak area and concentration was observed in the range of 1−500 µg/mL. The recoveries of the samples at three different spiked levels ranged from 85.6% to 107.8%; the intra-day precision was less than 7.8% (n=6); and the inter-day precision was less than 9.5% (n=3). The method is simple, rapid, accurate and reliable, and can be used for the analysis of NSAIDs in the environmental water samples．

Objective To comapre and analyze the differences and commonalities of expression profiles of serum exosomal microRNA between patients with thyroid nodules and healthy persons at different iodine levels,and then provide evidence for screening early diag-nostic markers of thyroid nodules at different iodine levels.Methods The peripheral blood samples from 10 patients with thyroid nod-ules and healthy volunteers at different iodine levels were collected.Their serum iodine levels were measured by the arsenic cerium cat-alytic spectrophotometry.Serum exosomal microRNA were extracted and the expression levels of microRNA were determined by the high-throughput sequencing technology.The differential target genes were predicted and further performed Gene ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis.Results Compared with healthy volunteers,there were 6 downreg-ulated miRNAs in the patients with thyroid nodules at different iodine levels,namely miR-324-5p,miR-6511b-3p,miR-9903,miR-550a-3p,miR-5001-3p,and miR-3688-3p.Differentially expressed exosomal microRNA could regulate the MAPK signaling path-way,PI3K-AKT signaling pathway,VEGF signaling pathway,and NF-κB signaling pathway.Conclusion Six differentially expressed microRNAs is identified,which may serve as biological markers for the early diagnosis of thyroid nodules at different iodine levels.

Objective To evaluate the prediction of microvascular invasion(MVI)and its grading in patients with hepatocellular carcinoma(HCC)by computed tomography(CT)and magnetic resonance imaging(MRI)features combined with laboratory indices.Methods Using plain and enhanced CT and MRI scan to examine the participants preoperatively,the features of tumor length diam-eter,shape,number,margin and tumor capsule,whether multiple nodules are fused,whether external convex nodules are visible locally,whether blood supply vessels are visible inside or degeneration or necrosis exists,and whether low density or signal exists around the tumor that are extracted from the examination results,combined with clinical indicators,such as age,preoperative alpha-fetoprotein(AFP)level,and presence of hepatitis B surface and e antigens to analyze the occurrence of MVI in patients with HCC.Results Patients with HCC and MVI were more likely to have elevated AFP;the larger the tumor length and diameter,the higher the incidence of MVI.CT and MRI showed that the features of blurred tumor edges and incomplete local capsule were independent risk factors for MVI of HCC.All the extracted image features and clinical indicators had no predictive value for MVI grading.Conclusion A few imaging features and clin-ical indicators of HCC have definite predictive value for the occurrence of MVI.

ObjectiveIn order to improve the recognition accuracy of named entities in medical record texts and realize the effective mining and utilization of medical record knowledge， a Bert-Radical-Lexicon（BRL） neural network model is constructed to recognize medical record entities with respect to the characteristics of medical record texts. MethodWe selected 408 medical records related to hypertension from the the Complete Library of Famous Medical Records of Chinese Dynasties and constructed a dataset consisting of 1 672 medical records by manually labeling. Then， we randomly divided the dataset into three subsets， including the training set（1 004 cases）， the testing set （334 cases） and the validation set（334 cases）. Based on this dataset， we built a BRL model that fused various text features of medical records， as well as its variants BRL-B， BRL-L and BRL-R， and a baseline model Base for experiments. During the model training phase， we trained the above models using the training set to reduce the risk of overfitting. We continuously monitored the performance of each model on the validation set during training and saved the model with the best performance. Finally， we evaluated the performance of these models on the testing set. ResultCompared with other models， the BRL model had the best performance in the medical records named entity recognition task， with an overall recognition precision of 90.09%， a recall of 90.61%， and the harmonic mean of the precision and recall（F1） of 90.35% for eight types of entities， including disease， symptom， tongue manifestation， pulse condition， syndrome， method of treatment， prescription and traditional Chinese medicine（TCM）. Compared with the Base model， the BRL model improved the overall F1 value of entity recognition by 5.22%， and the F1 value of pulse condition entity increased by 6.92%， which was the largest increase. ConclusionBy incorporating a variety of medical record text features in the embedding layer， the BRL neural network model has stronger named entity recognition ability， and thus extracts more accurate and reliable TCM clinical information.

Objective: To investigate the epidemiological characteristics of respiratory syncytial virus (RSV) in hospitalized children in Ningbo City, so as to provide insights into developing prevention and control strategies for RSV. Methods: Basic information, clinical data and throat swab samples were collected from hospitalized children with respiratory infection in Ningbo University Affiliated Women and Children's Hospital from July 2019 to December 2023. Multiple fluorescence PCR-capillary electrophoresis was employed to detect nucleic acids of 11 non-bacterial respiratory pathogens. RSV detection in hospitalized children by time, gender and age was descriptively analyzed. Results: A total of 49 449 throat swab samples of hospitalized children with respiratory infections were detected. There were 4 310 samples positive for RSV, with a detection rate of 8.72%. The detection of positive specimens peaked from November to February in 2019 and 2020, from August to October in 2021, and from May to September in 2023. The RSV detection rate in boys was higher than that in girls (9.25% vs. 8.04%, P<0.05). The detection rate of RSV was highest in the children under 1 year of age (16.37%). The RSV detection rate tended to decrease with age (P<0.05). Among the specimens with positive RSV detection, 3 407 were positive for RSV alone (79.05%), while 903 were detected as mixed infections (20.95%). The non-bacterial pathogens with higher percentages of mixed detection were human rhinovirus, Mycoplasma pneumoniae and human parainfluenza virus. Conclusion Atypical seasonal epidemic of RSV infections appeared in 2021 and 2023 among hospitalized children in Ningbo City, with high detection rates in boys and children under 1 year of age, and a certain percentage of mixed infections.

To analyze the infection and drug-resistant gene 23S rRNA mutations of mycoplasma pneumoniae (Mp) in hospitalized children aged 0-17 in Ningbo City from 2019 to 2023. Throat swabs were collected from hospitalized children with respiratory tract infections in Ningbo University Affiliated Women and Children′s Hospital from 2019 to 2023. They were subjected to real-time fluorescence quantitative polymerase chain reaction detection to analyze Mp infection and drug-resistant gene (23S rRNA) mutations. Intergroup comparisons were made by the Chi-square test or Fisher′s exact probability method. A total of 18 968 hospitalized children were included, with a total positive rate of 30.37% (5 760/18 968). The total positive rate of drug-resistant gene mutations was 82.45% (4 749/5 760). The positive rate of Mp in male children was 29.26%, which was lower than that in female children (31.67%, χ 2=12.948, P<0.001). The positive rate of Mp drug-resistant gene mutations in male children was 82.52%, which was higher than that in female children(82.37%, χ 2=0.021, P=0.885). The positive rates of Mp increased with age ( χ 2=1 722.21, P<0.001). The positive rates of Mp drug-resistant gene mutations also increased with age ( χ 2=13.152, P<0.001). In the four seasons, the total positive rate of Mp in summer and autumn was significantly higher than that in winter and spring ( χ 2=1 085.149, P<0.001). Among them, the Mp positive rates in the summer and autumn of 2019 were as high as 38.26% and 34.49%, while in the summer and autumn of 2020, the Mp positive rates were 2.55% and 1.65%, respectively, which were the lowest in previous years. In the summer and autumn of 2023, the Mp positive rates increased to 47.22% and 51.06%. There was no statistically significant difference in the detection rate of Mp drug-resistant gene mutations among the four seasons. In Conclusion, Mp infection was more prevalent in the summer and autumn in Ningbo city and females and children aged 7-17 were more susceptible. The epidemic of Mp infection in Ningbo occurred in the summer of 2019. After the COVID-19 pandemic in 2020, the positive rate of Mp rapidly decreased and later remained in a low incidence state. After the lifting of restrictive prevention and control measures in 2023, the Mp positive rate returned to an epidemic state. The positive rate of Mp drug-resistant gene (23S rRNA) mutations was relatively high.