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.

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 investigate the impact of bone mass and volume of low-density zones beneath the tibial plateau on the maximum von Mises stresses experienced by the cartilage and meniscus in the knee joint. METHODS: The study included one healthy adult volunteer, from whom CT scans were obtained, and one patient diagnosed with knee osteoarthrisis (KOA), for whom X-ray films were acquired. A static model of the knee joint featuring a low-density zone was established based on a normal knee model. In the finite element analysis, axial loads of 1 000 N and 1 800 N were applied to the weight-bearing region of the upper surface of the femoral head for model validation and subsequent finite element studies, respectively. The maximum von Mises stresses in the femoral cartilage, as well as the medial and lateral tibial cartilage and menisci, were observed, and the stress percentage of the medial and lateral components were concurrently analyzed. Additionally, HE staining, as well as alkaline magenta staining, were performed on the pathological specimens of patients with KOA in various low-density regions. RESULTS: The results of model validation indicated that the model was consistent with normal anatomical structures and correlated with previous calculations documented in the literature. Static analysis revealed that the maximum von Mises stress in the medial component of the normal knee was the lowest and increased with the advancement of the hypointensity zone. In contrast, the lateral component exhibited an opposing trend, with the maximum von Mises stress in the lateral component being the highest and decreasing as the hypointensity zone progressed. Additionally, the medial component experienced an increasing proportion of stress within the overall knee joint. HE staining demonstrated that the chondrocyte layer progressively deteriorated and may even disappear as the hypointensity zone expanded. Furthermore, alkaline magenta staining indicated that the severity of microfractures in the trabecular bone increased concurrently with the expansion of the hypointensity zone. CONCLUSION The presence of subtalar plateau low-density zone may aggravate joint degeneration. In clinical practice, it is necessary to pay attention to the changes in the subtalar plateau low-density zone and actively take effective measures to strengthen the bone status of the subtalar plateau low-density zone and restore the complete biomechanical function of the knee joint, in order to slow down or reverse the progression of osteoarthritis.
Humans ; Finite Element Analysis ; Knee Joint/physiology* ; Tibia/anatomy & histology* ; Cartilage, Articular/physiology* ; Menisci, Tibial/physiopathology* ; Tomography, X-Ray Computed ; Osteoarthritis, Knee/diagnostic imaging* ; Weight-Bearing ; Bone Density ; Adult ; Stress, Mechanical ; Male ; Middle Aged ; Biomechanical Phenomena ; Female

OBJECTIVE: To investigate the differential efficacy and safety profiles of oral mucosa (OM) grafts compared with acellular dermal matrix (ADM) grafts in the surgical management of long-segment urethral strictures. METHODS: A retrospective cohort study was conducted involving 27 patients who underwent graft urethroplasty for long-segment urethral strictures in Peking University First Hospital, spanning from May 2010 to September 2023. The patient cohort comprised 14 individuals who received OM grafts and 13 who underwent ADM grafts. The participants were stratified into two groups based on the type of grafts material utilized during surgery. The demographic and clinical baseline characteristics included an average age of (43.3±14.0) years in the OM group and (54.2±15.9) years in the ADM group. The mean body mass index (BMI) for the respective groups were (24.7±4.3) kg/m² for OM and (25.4±4.8) kg/m² for ADM. Etiological differences were noted, with idiopathic causes predominantly in the OM cohort and lichen sclerosus in the ADM cohort. RESULTS: The surgical interventions were successfully executed for all the patients. The median stricture length was 4.5 (2.5, 9.0) cm for the OM group and 5.0 (2.0, 14.0) cm for the ADM group (P=0.555). The median operative duration was 160 (71, 221) min for the OM group and 134 (112, 274) min for the ADM group (P=0.065). The catheterization durations was 1.5 (1.0, 6.0) months for the OM group and 3.0 (1.0, 3.0) months for the ADM group. The median postoperative follow-up duration was 12.5 (1.0, 170.0) months for the OM group and 59.0 (3.0, 142.0) months for the ADM group. The surgical success rates were 50.00% in the OM group and 53.85% in the ADM group. No statistically significant differences were observed in postoperative quality of life (QoL) or international prostate symptom score (IPSS) at the final follow-up. The stricture-free survival rates did not differ significantly (HR=0.875, 95%CI: 0.507-1.511, P=0.6). In terms of safety, three patients in the OM group experienced sexual dysfunction, and two had oral complications, whereas the ADM group had one case of postoperative infection. CONCLUSION The findings suggest that ADM grafts are comparable to OM grafts in terms of efficacy and safety for the treatment of long-segment urethral strictures, including complex cases attributed to lichen sclerosus. However, given the small sample size of this study, the above conclusions may have certain limitations. Larger cohort studies will be needed in the future to further validate these findings.
Humans ; Urethral Stricture/surgery* ; Acellular Dermis ; Mouth Mucosa/transplantation* ; Retrospective Studies ; Middle Aged ; Male ; Adult ; Treatment Outcome ; Skin Transplantation/methods* ; Aged

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

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.

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 compare the outcomes of transvaginal natural orifice transluminal endoscopic surgery(vNOTES)and laparoendoscopic single-site surgery(LESS)for total uterine excision in obese patients with benign uterine lesions,and to investigate the utility of vNOTES in this patient population.Methods A total of 100 obese patients(BMI>28.0 kg/m2)diagnosed with benign uterine lesions requiring total uterine and bilateral salpingectomy between January 2022 and January 2023 were included in this study.They were randomly assigned to two groups:the LESS group(n=51)and the vNOTES group(n=49).Patient demographics,surgical duration,intraoperative blood loss,changes in hemoglobin levels,pain scores,time to first flatus postoperatively,length of hospital stay,pelvic floor function,sexual quality of life,and postoperative complications were compared between the two groups.Results The two groups did not show any statistically significant differences in terms of blood loss,pre-and postoperative hemoglobin changes,pelvic floor function,sexual quality of life,or postoperative complications(P>0.05).However,the vNOTES group exhibited shorter surgical durations,time to first flatus postoperatively,and length of hospital stay compared to the LESS group(P<0.05).Additionally,the vNOTES group demonstrated lower intraoperative pain scores than the LESS group.(P<0.05).Conclusions In obese patients with benign uterine lesions,vNOTES total uterine excision surgery demonstrated shorter surgical durations and postoperative hospital stays,lower postoperative pain scores,and better adherence to the principles of en-hanced recovery after surgery(ERAS),indicating its potential for broader application.

ObjectiveTo investigate the identification of kidney Yang deficiency syndrome of patients with osteoporosis（OP）， and to form the clinical syndrome identification rules of traditional Chinese medicine（TCM）. MethodBasic information， etiology， clinical symptoms and other characteristics of 982 OP patients were included， and statistical tests were used to screen the variables associated with kidney Yang deficiency syndrome. Taking the decision tree as the base model， bootstrap aggregation algorithm（Bagging algorithm） was utilized to establish the classification model of kidney Yang deficiency syndrome in OP， generating numerous rules and removing redundancy. Combining least absolute shrinkage and selection operator（LASSO） regression to screen key rules and integrate them to construct an identification model， achieving the identification of kidney Yang deficiency syndrome in OP patients. ResultEighteen key identification rules were screened out， and of these， where 11 rules with regression coefficients>0 correlated positively with the kidney Yang deficiency syndrome， the rule with the highest coefficient was chilliness（present）&feverish sensation over the palm and sole（absent）. The other 7 rules with regression coefficients<0 correlated negatively with the syndrome， the rule with the lowest coefficient was reddish tongue（present）&diarrhea（absent）&deficiency of endowment（absent）. According to the regression coefficients of each key rule， variables with importance>0.2 were ranked as chilliness， reddish tongue， feverish sensation over the palm and sole， cold limbs， clear urine， diarrhea， deficiency of endowment， prolonged illness. The results of the partial dependence analysis of the identification model showed that compared to OP patients without chilliness， those with chilliness（present） had a 0.266 8 higher probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identification of the syndrome. Similarly， compared to OP patients without reddish tongue， those with reddish tongue had a 0.141 9 lower probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identifying non-kidney Yang deficiency syndrome. The accuracy， sensitivity， specificity and area under receiver operating characteristic curve（AUC） of the established kidney Yang deficiency syndrome identification model in the test set were 0.865 9， 0.853 7， 0.872 0 and 0.931 5， respectively. ConclusionA precise identification model of OP kidney Yang deficiency syndrome is conducted basing on the rule ensemble method of Bagging combining LASSO regression， and the screened key rules can explain the identification process of kidney Yang deficiency syndrome. In this research， according to the regression coefficients of rules， the importance and partial dependence of variables， combined with the thinking of TCM， the influence of patient characteristics on the identification of syndromes is described， so as to reveal the primary and secondary syndromes of identification and assist the clinical identification of kidney Yang deficiency syndrome.

Objective:To study the phenotype and genotype distribution of Yersinia pestis ( Y. pestis) in different natural foci of plague in China, so as to provide scientific basis for plague prevention and control. Methods:A total of 2 184 strains of Y. pestis isolated from different time periods, regions, hosts and vectors in 11 plague natural foci of China since 1943 were selected for biochemical type identification, glycolysis test, virulence factor test [capsule antigen (F1), pesticin Ⅰ (Pst Ⅰ), virulence antigen factor (VWa), pigmentation factor (Pgm)], different region (DFR) typing and clustered regularly interspaced short palindromic repeats (CRISPR) typing. Results:There were 16 biochemical types of Y. pestis in the natural foci of plague in China, and each biochemical type showed obvious regional distribution in each foci. Most strains were positive for ass hide glue glycolysis (89.79%, 1 961/2 184), maltose (80.13%, 1 750/2 184), glycerol (94.23%, 2 058/2 184), and denitrification (82.78%, 1 808/2 184), and negative for rhamnose (88.78%, 1 939/2 184) and melibiose (85.62%, 1 870/2 184). Virulence factor test results showed that 99.95% (2 183/2 184) of Y. pestis were F1 positive; 99.73% (2 178/2 184) of Y. pestis can produce Pst Ⅰ; 73.31% (1 601/2 184) of Y. pestis were VWa positive and 26.69% (583/2 184) were VWa negative; Pgm positive strains accounted for 72.62% (1 586/2 184), Pgm negative strains accounted for 21.52% (470/2 184), and Pgm mixed type strains accounted for 5.86% (128/2 184). According to DFR typing results, there were 52 genotypes in 2 184 strains of Y. pestis, of which 19 were major genotypes and 33 were minor genotypes. CRISPR typing revealed 16 major genotypes, of which 7 were newly discovered. Conclusion:The phenotypes and genotypes of Y. pestis in various natural foci of plague in China are diverse and have geographical distribution characteristics.