BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.

BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.

Based on spleen deficiency-phlegm dampness as the core pathogenesis of obesity， and integrating recent advances in modern medicine regarding the key role of immune inflammation in obesity， this paper proposes a multidimensional pathogenic network of "obesity-spleen deficiency-phlegm dampness-immune imbalance". Various traditional Chinese medicine （TCM） herbs that strengthen the spleen， regulate qi， and resolve phlegm and dampness can treat obesity by improving spleen-stomach transport and transformation， promoting water-damp metabolism， and regulating immune homeostasis. This highlights immune inflammation as an important entry point to elucidate the TCM concepts of "spleen deficiency-phlegm dampness" and the therapeutic principle of "strengthening the spleen and eliminating dampness to treat obesity". By systematically analyzing the intrinsic connection between "spleen deficiency generating dampness， internal accumulation of phlegm dampness" and immune dysregulation in obesity， this paper aims to provide theoretical support for TCM treatment of obesity based on dampness.

ObjectiveTo explore the effect and mechanism of Jianpi Xiaoai prescription （JPXA） in ameliorating the 5-fluorouracil （5-FU） resistance of colon cancer. MethodsA HCT116/5-FU resistant cell line was established. Different concentrations （10%， 15%， 20%） of JPXA-containing serum and drug-free serum were used for intervention， and 10% fetal bovine serum （10% FBS）， fibroblast growth factor receptor （FGFR） inhibitor （AZD4547）， and recombinant fibroblast growth factor 2 （FGF2） were set as the control groups. Sensitive HCT116 cells were used in the FGF2 group， while HCT116/5-FU cells were used in other groups. Drug resistance， the level of FGF2 in the cell culture medium， the mRNA level of FGF2 in cells， and the protein levels of FGF2/FGFR and phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） were determined. The drug-resistant cells were transplanted into the axilla of nude mice to establish a tumor model. The modeled mice were allocated into model， JPXA （15 g·kg^-1）， 5-FU （0.02 g·kg^-1）， JPXA+5-FU （15 g·kg^-1+0.02 g·kg^-1）， AZD4547 （0.012 5 g·kg^-1）， and AZD4547+5-FU （0.012 5 g·kg^-1+0.02 g·kg^-1） groups. The tumor growth and the protein levels of FGF/FGFR and PI3K/Akt in each group were observed. ResultsThe survival rate of HCT116/5-FU cells decreased in all the JPXA groups with different concentrations. The cell survival rate was decreased most obviously in the 20% JPXA group. The level of FGF2 in the cell culture medium and the mRNA level of FGF2 in cells of each JXPA group decreased， and the decrease was the most significant in the 20% group （P<0.01）. HCT116/5-FU cells showed up-regulated protein levels of FGF2 and phosphorylated fibroblast growth factor receptor 1 （p-FGFR1）， but down-regulated protein level of FGFR1 （P<0.01）. JPXA down-regulated the expression of FGF2 and p-FGFR1 and up-regulated the expression of FGFR1 （P<0.05）. In addition， JPXA down-regulated the expression levels of phosphorylated protein kinase B （p-Akt） and phosphorylated mammalian target of rapamycin （p-mTOR）， while up-regulating the expression levels of Akt and Bcl-2-asociated death promoter （Bad） （P<0.05）. Animal experiments showed that the JPXA combined with 5-FU significantly inhibited the growth of drug-resistant tumors， reduced the protein levels of FGF2， p-FGFR1， phosphorylated phosphatidylinositol-3-kinase （p-PI3K）， p-Akt， and p-mTOR， and increased the expression of Bad. It indicated that JPXA can inhibit the FGF2/FGFR1 signaling in colon cancer and regulate PI3K/Akt and downstream signaling pathways. ConclusionJPXA can ameliorate the chemotherapy resistance of colon cancer through down-regulating FGF2 expression and inhibiting the activation of the PI3K/Akt signaling pathway.

Objective To investigate the post-discharge exercise behavior and factors influencing moderate to vigorous intensity physical activity (MVPA) in patients undergoing lung surgery. Methods A total of 2874 patients from the large prospective, observational perioperative lung symptom study cohort (CN-PRO-Lung 3) in the Department of Thoracic Surgery at Sichuan Cancer Hospital between April 7, 2021, and January 31, 2024, were selected as the survey subjects. A survey was conducted using the Investigation of Exercise Behavior after Lung Surgery questionnaire and the International Physical Activity Questionnaire-Short Form (IPAQ-SF) among patients who underwent lung surgery. Binary logistic regression was used to analyze the factors influencing patients’ engagement in MVPA. Results A total of 702 patients were surveyed, including 252 males and 450 females, with an average age of (52.4±10.2) years. Patients with lung cancer accounted for 85.9%. Only 36.0% of the patients had regular exercise habits, while 42.3% did not engage in any physical activity. The three main barriers for postoperative exercise were physical discomfort (pain, coughing, shortness of breath, etc, 54.7%), lack of professional guidance (41.7%), and concerns about the surgical wound (28.9%). The proportions of patients engaging in vigorous, moderate, and low-intensity physical activity were 5.7%, 28.2%, and 66.1%, respectively. Multivariate analysis showed that patients with a personal annual income ≥50000 yuan (OR=1.52, 95%CI 1.01-2.29, P=0.044), high school education or above (OR=1.92, 95%CI 1.33-2.76, P<0.001), and lobectomy (OR=1.44, 95%CI 1.02-2.03, P=0.037) engaged in more MVPA. Conclusion Patients undergoing lung surgery have inadequate physical activity after discharge, particularly lacking in MVPA. Patients with higher income, higher educational levels, and lobectomy are more frequently engaged in MVPA. Measures such as symptom control, providing exercise guidance, and enhancing education on wound care may potentially improve the inadequate physical activity in lung surgery patients after discharge.

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.

AIM: To investigate the abnormal conditions and change patterns of accommodative facility in patients with different refractive states before and after small incision lenticule extraction(SMILE)surgery.METHODS:A prospective clinical cohort study was conducted. A total of 59 patients(118 eyes)who underwent SMILE surgery and had visual function files established in our hospital from June to December 2023 were randomly selected, including 37 males and 22 females, aged 18-35 years(with an average age of 25.19±5.65 years). According to the preoperative spherical equivalent(SE), they were divided into two groups: the low-to-moderate myopia group(SE≥-6.00 DS)with 40 patients(80 eyes), and the high myopia group(SE<-6.00 DS)with 19 patients(38 eyes). The monocular and binocular accommodative facility before surgery and at 1 wk and 1 mo after surgery were compared, and the changes in accommodative facility before and after SMILE surgery in the two groups of patients were analyzed.RESULTS:All surgeries were completed successfully. In the low-to-moderate myopia group, 33 cases(66 eyes)completed the 1-month follow-up after surgery, with a loss to follow-up rate of 17.5%(7/40). In the high myopia group, 15 patients(30 eyes)completed the 1-month follow-up after surgery, with a loss to follow-up rate of 21.1%(4/19). After SMILE surgery, the uncorrected visual acuity and SE of both low-to-moderate myopia and high myopia were significantly improved(all P<0.05). The accommodative facility of the right eyes in all the patients at 1 mo after surgery was better than that before surgery and at 1 wk after surgery(P=0.002, 0.006), the accommodative facility of the left eyes was significantly increased at 1 mo after surgery than that at 1 wk after surgery(P=0.005), and the binocular accommodative facility at 1 mo after surgery was significantly increased compared with that before surgery(P<0.017). Furthermore, there were statistical significance in accommodative facility of the right eyes in the low-to-moderate group at 1 mo compared with that before surgery and at 1 wk after surgery(P=0.011, 0.004); it was significantly increased in the left eyes at 1 mo after surgery compared with that at 1 wk after surgery(P=0.001), and binocular accommodative facility at 1 mo after surgery was significantly better than that before surgery(P<0.001). Furthermore, there was no statistical significance in the right, left and binocular accommodative facility of patients in the high myopia group(all P>0.017).CONCLUSION: After SMILE surgery, the monocular accommodative facility shows a transient decrease and then exceeds the preoperative level at 1 mo after surgery, and the binocular accommodative facility gradually improves after surgery. SMILE surgery has a positive impact on the monocular and binocular accommodative facility in patients with low-to-moderate myopia, but has no significant impact on the accommodative facility in patients with high myopia. It is of clinical significance to strengthen the detection of monocular and binocular accommodative facility before and after SMILE surgery.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

This article reports a postcraniotomy patient with renal insufficiency and electrolyte imbalance who developed ventilator-associated pneumonia caused by extensively drug-resistant Klebsiella pneumoniae.According to the patient's pathophysiological characteristics,bacterial epidemiological characteristics,and bacterial culture results,combined with the latest guidelines and the pharmacokinetic/pharmacodynamic characteristics of antibiotics,a full-dose ceftazidime/avibactam regimen was initially suggested by the clinical pharmacist,and which was adopted by doctor.When the effect of ceftazidime/avibactam was poor and no guideline-recommended alternatives were available,the clinical pharmacist,in conjunction with clinical experience,proposed a combination therapy of colistin sulfate and tigecycline,with the implementation of adverse reaction monitoring and mucin sulfate blood concentration monitoring.Finally,the pneumonia was effectively controlled,the inflammatory indicators such as temperature and the white blood cell count returned to normal,no adverse drug reactions occurred,and the patient was successfully transferred to the rehabilitation institution.Clinical pharmacists stay updated on the latest medication knowledge both domestically and internationally,recommend advanced drug treatment protocols for clinical practice,assist in managing severe infections,and play an important role in the clinical team.