BACKGROUND:The local immune microenvironment plays an important regulatory role in the process of bone formation,and the immune system is intricately linked to the skeletal system.OBJECTIVE:To systematically review the promotion of bone regeneration from three aspects:immune cell regulation of microenvironment,regulation of immune response by small extracellular vesicles,and induction of immune response by bone biomaterials,and to elucidate the immune regulatory mechanisms involved in bone regeneration.METHODS:Relevant literature was retrieved from PubMed,CNKI,WanFang Database,and VIP Database,using the search terms of"osteoimmunology,immune microenvironment,small extracellular vesicles,bone regeneration,bone tissue repair,biomaterials,and tissue engineering"in English and Chinese.Repeat and irrelevant literature was screened and removed,and 92 articles that met the criteria were selected for intensive reading and review.RESULTS AND CONCLUSION:Multiple immune cells and bone cells are in the same microenvironment,and immune cells can regulate the differentiation and activity of bone cells,collectively forming an immune microenvironment that affects bone regeneration.Neutrophils can significantly reduce local inflammatory responses in the early stages of bone injury,creating a favorable microenvironment for bone regeneration.M1 macrophages can clear foreign bodies and reduce early inflammatory responses,while M2 macrophages can promote the expression of osteogenic markers and factors,playing an important role in the repair process of bone injury.B cells and T cells can directly or indirectly affect the generation and activity of osteoblasts and osteoclasts,regulate bone metabolism,and promote bone regeneration.Extracellular vesicles of small cells regulate the local immune microenvironment through paracrine secretion,promoting bone formation and angiogenesis at the site of bone injury.The metal ions,surface hydrophilicity,porosity,pore size,surface morphology,and surface roughness on the surface of biomaterials can directly regulate local immune responses,and have anti-inflammatory,angiogenic,and osteogenic effects,thereby accelerating bone regeneration.

OBJECTIVE:To evaluate the efficacy and safety of different immunosorbent columns in the treatment of rheumatoid arthritis through a network meta-analysis,and provide evidence-based basis for clinical diagnosis and treatment.METHODS:By computer,the databases of VIP,WanFang,CNKI,PubMed,CBM,CochraneLibrary,and Web of Science were searched for published cohort studies of immunosorbent column for the treatment of rheumatoid arthritis,with a time limit until August 2024.The quality of the included randomized controlled trials was assessed using the Cochrane5.4 manual.The quality of retrospective cohort studies were evaluated via the Newcastle-Ottawa Scale(NOS).Bayesian network meta-analysis was performed using R4.1.1 software.RESULTS:A total of 13 studies were included,with a total sample size of 891 cases,and 4 immunosorbent columns were included.The results of the network meta-analysis showed that the top three orders that reduce C-reactive protein level:HA280 adsorption column+conventional Western medicine＞PH-350 adsorption column+conventional Western medicine＞A protein adsorption column;the top three orders that reduce erythrocyte sedimentation rates:leukocyte adsorption column＞HA280 adsorption column+conventional Western medicine＞PH-350 adsorption column+conventional western medicine;the top three orders that reduce swollen joint count:leukocyte adsorption column＞A protein adsorption column+conventional western medicine＞PH-350 type adsorption column+conventional Western medicine;the top three orders that reduce tenderness joint counts:leukocyte adsorption column＞A protein adsorption column+conventional western medicine＞PH-350 adsorption column+conventional Western medicine;the top three orders that reduce patients' disease activity evaluation:PH-350 adsorption column+conventional western medicine＞leukocyte adsorption column＞A protein adsorption column;the top three orders that reduce visual analogue scale scores:PH-350 adsorption column+conventional Western medicine＞A protein adsorption column＞leukocyte adsorption column;the top three orders that reduce physician's disease activity assessment:PH-350 adsorption column+conventional Western medicine＞leukocyte adsorption column＞conventional Western medicine.CONCLUSION:Based on the 13 articles,in terms of reducing C-reactive protein level,HA280 adsorption column and conventional Western medicine are the preferred choice.In terms of reducing erythrocyte sedimentation rate,swollen joint count,and tender joint count,leukocyte adsorption column is the preferred choice.In terms of reducing patient's disease activity evaluation,physician's disease activity evaluation and visual analogue scale scores,PH-350 adsorption column and conventional Western medicine are the first choice.Different immunosorbent columns can be reasonably and accurately selected according to the patient's specific conditions.

Objective: To evaluate the intervention effect of school based salt reduction health education, so as to provide a scientific basis for constructing a more effective and sustainable salt reduction intervention model for children. Methods: According to a randomized controlled trial design, in June 2022, probability proportional to size sampling was used to select 501 second grade students (248 in the control group and 253 in the intervention group) from 10 primary schools in Zhenjiang (intervention group) and 10 primary schools in Yangzhou (control group), Jiangsu Province. An one year school based salt reduction health education intervention was implemented. This included 20 online and 8 offline health education sessions, monitoring of salt consumption in the canteen, and the establishment of a salt reduction environment on campus. The control group received no additional salt reduction interventions. A questionnaire survey and 24 hour urinary sodium test were conducted before and after the intervention. The difference in differences method was used to evaluate the intervention effect. Results: After the intervention, the intervention group showed significant net intervention effects in knowledge aspects, including knowing that primary school students consume less salt than adults ( OR=3.55,95%CI =1.69-7.47), daily salt intake of primary school students ( OR=6.64,95%CI =3.71-11.87), long term high salt intake leading to hypertension ( OR=6.83,95%CI =3.93-11.91), low salt intake not causing hair graying ( OR= 1.66 ,95%CI =1.00-2.75), salt content in food labels ( OR=4.56,95%CI =2.63-7.91), and common high salt foods ( OR=3.39,95%CI =1.87-6.14) (all P <0.05). In terms of attitude, the net intervention effect for having a positive attitude toward using less salt in home cooking was significantly increased ( OR=1.88,95%CI =1.13-3.12, P <0.05). There were no statistically significant net intervention effects for salt reduction related behaviors (all P >0.05). There was no statistically significant difference in the changes of 24 hour urinary sodium between the intervention group and the control group before and after intervention ( P >0.05). Conclusions School based salt reduction health education effectively improves students salt reduction knowledge and attitudes but has a limited effect on behavior change. The home-school collaboration should be strengthened, and the dietary environment should be optimized simultaneously.

[摘 要] 目的：探讨miR-433对结直肠癌（CRC）细胞干细胞特性及5-氟尿嘧啶（5-FU）耐药性的影响，并阐明其潜在的分子调控机制。方法： 建立5-FU耐药的HCT-116细胞株。采用RT-qPCR和WB法检测miR-433及干细胞特性标志物（SOX2、OCT4、Nanog）的表达。通过双萤光素酶报告基因实验、免疫荧光和核质分离实验验证miR-433与靶基因YAP1的关系及YAP1对其亚细胞定位的影响。通过拯救实验确认miR-433/YAP1轴的功能。利用CCK-8法检测细胞对5-FU的敏感性。结果： 与亲代HCT-116/P细胞相比，耐药的HCT-116细胞株中miR-433表达显著下调（P < 0.05），而干细胞特性标志物（SOX2、OCT4、Nanog）表达上调（P < 0.05）。过表达miR-433能够抑制干细胞标志物的表达，并直接靶向YAP1，阻碍其核定位（P < 0.05）。恢复YAP1的表达能够部分逆转miR-433对干细胞标志物的抑制作用（P < 0.05）。功能上，上调miR-433显著增强了CRC细胞对5-FU的敏感性，而此效应同样可被YAP1的重新表达所削弱（P < 0.05）。结论： miR-433通过直接靶向YAP1通路，抑制CRC细胞的干细胞特性相关分子表型，并增强其对化疗药物的敏感性。miR-433/YAP1轴可能成为克服CRC 5-FU耐药的潜在新靶点。

Animal model research on spleen and stomach diseases in traditional Chinese medicine （TCM） is of great significance for elucidating the nature of diseases and syndromes and for revealing the mechanisms of action of Chinese herbal medicinals. At present， studies on classical TCM syndrome models of spleen and stomach diseases mainly focus on spleen deficiency syndrome， liver constraint syndrome， and damp-heat syndrome. Model construction is mostly based on the etiological and pathophysiological characteristics of syndrome， and model evaluation primarily involves macroscopic manifestations and physicochemical indicators. This paper summarizes the current research status of animal models integrating disease and syndrome for seven common spleen and stomach diseases， including chronic gastritis and gastric precancerous lesions， gastroesophageal reflux disease， functional dyspepsia， inflammatory bowel disease， irritable bowel syndrome， functional constipation， and functional diarrhea. The modeling methods and characteristics of disease-syndrome combined animal models for each disease are analyzed. It is proposed that future research on disease-syndrome integration in spleen and stomach diseases should move toward syste-matic， precise， and integrative development， and that interdisciplinary and cross-disciplinary research approaches should be adopted to enhance the predictive value and application efficiency of disease-syndrome combined animal models.

The brain-gut interaction theory is a multidimensional integrative concept based on the brain-gut axis， involving neural， endocrine， and immune regulatory networks as well as the gut microbiota. Zang-fu organs （脏腑） theory in traditional Chinese medicine （TCM） shows a high degree of consistency with the brain-gut interaction theory， and the core functions such as the spleen and stomach governing the ascending of the clear and descending of the turbid， the liver governing the free flow of qi， and the heart governing mental and emotional activities are closely associated with the multi-level regulatory mechanisms of the brain-gut axis. TCM therapy can modulate brain-gut interactions through multiple pathways in the treatment of spleen and stomach diseases， including the regulation of gastrointestinal hormone secretion， neurotransmitter levels， the hypothalamic-pituitary-adrenal （HPA） axis， immune homeostasis and inflammatory responses， as well as the gut microecology. However， current basic research on the brain-gut interaction theory in TCM for spleen and stomach diseases still faces several challenges， such as difficulties in integrating TCM spleen-stomach theory with modern pathophysiology， lack of innovation in research concepts， and limitations in research methodologies. It is therefore proposed that multidisciplinary collaboration， multi-omics technologies， and targeted research approaches should be adopted to provide more comprehensive methods for basic research on TCM spleen and stomach diseases， thereby promoting the in-depth development of brain-gut interaction theory.

Objective To explore the related risk factors of osteosarcopenia (OS) in elderly patients with type 2 diabetes mellitus (T2DM) and to evaluate their predictive value. Methods We selected 409 elderly patients with T2DM from our hospital between June 2021 and December 2024 as the study subjects, and divided them into an OS occurrence group and a non-occurrence group based on whether they were diagnosed with OS. Results Among the 409 elderly patients with T2DM included, 93 were diagnosed with OS, yielding a prevalence rate of 22.73%. Spearman correlation analysis revealed a significant association between lumbar spine BMD and T-scores with age, history of previous fractures, fasting plasma glucose (FPG), procollagen type I N-terminal propeptide (PINP), osteocalcin (OC), and 25-hydroxyvitamin D (25(OH)D). Gender (OR=0.193), Body Mass Index (BMI) (OR=0.254), history of previous fractures (OR=8.883), FPG (OR=0.543), Total Cholesterol (TC) (OR=3.684), High-Density Lipoprotein Cholesterol (HDL-C) (OR=86.024), PINP (OR=0.818), and OC (OR=0.526) are identified as influential factors for the occurrence of OS in elderly patients with T2DM. The combined prediction of these variables yields a sensitivity of 96.5%, a specificity of 97.8%, and an area under the curve (AUC) of 0.992 for the occurrence of OS in elderly patients with T2DM, indicating an excellent predictive performance. Conclusion The following factors—gender, BMI, history of previous fractures, FPG, TC, HDL-C, PINP, and OC—are influential in the occurrence of OS among elderly patients with T2DM. Formulating intervention measures based on these influencing factors can provide assistance in preventing and treating the occurrence of OS.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

OBJECTIVE To construct a closed-loop management model for externally dispensed intravenous prescriptions， and to provide reference for standardized management of externally dispensed intravenous prescriptions. METHODS Based on the Expert Consensus on Closed-loop Management of Externally Dispensed Intravenous Prescriptions in Guangxi Zhuang Autonomous Region previously formulated by our hospital， risk points during the entire process were systematically identified through multidisciplinary team brainstorming and a fishbone diagram. A series of strategies were subsequently formulated and implemented， including qualifying designated external dispensing pharmacies and the drug catalogs， operating and maintaining the hospital information system and the Pharmacy Intravenous Admixture Service （PIVAS） intelligent management platform， and strengthening differentiated training for staff in the whole workflow. A whole-process closed-loop management system was constructed with PIVAS as the co re hub and the daytime chemotherapy center as the safety terminal. RESULTS A total of 3 cooperating pharmacies and an initial drug list comprising 35 product specifications were selected. A closed‑loop management process encompassing hospital outpatient prescribing， patient drug purchase in designated pharmacies， PIVAS drug dispensing， and medication use in daytime chemotherapy center was successfully established. This system enabled the mandatory grouping and association of externally dispensed intravenous prescriptions with in-hospital diluents， full-process verification based on drug traceability codes， intelligent monitoring of infusion parameters， and whole-process data traceability. CONCLUSIONS The constructed model effectively resolves the coordination and safety oversight during the use of externally dispensed intravenous drugs from out-of-hospital circulation to in-hospital use， and has preliminarily enabled procedural standardization， whole-process information traceability， and proactive control of medication risks.