ObjectiveTo explore the role of cucurbitacin B （CuB） in inducing ferroptosis in 4T1 cells and its mechanism. MethodsThe effects of CuB（0.2， 0.4， 0.8 μmol·L^-1）on the proliferation ability of 4T1 cells in vitro were detected using the methyl thiazolyl tetrazolium （MTT） assay. The clonogenic ability of 4T1 cells was detected by the plate cloning assay， and the levels of lactate dehydrogenase （LDH） in 4T1 cells were detected by the use of a kit. The mitochondrial membrane potential and reactive oxygen species （ROS） levels in 4T1 cells were detected by flow cytometry， and the mitochondrial ultrastructure of 4T1 cells was observed by transmission electron microscopy. The western blot was used to detect the expression of ferroptosis-related protein p53 in 4T1 cells， solute carrier family 7 member 11 （SCL7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， transferrin receptor protein 1 （TFR1）， and ferritin heavy chain 1 （FTH1）. ResultsCompared with that in the blank group， the survival rate of 4T1 cells in CuB groups was significantly decreased （P<0.05）， and the number of cell clones in CuB groups was significantly reduced （P<0.01）. In addition， compared with that in the blank group， the leakage of LDH in cells in CuB groups was significantly increased （P<0.01）， and the mitochondrial membrane potential of cells in CuB groups decreased significantly （P<0.01）. Cellular ROS levels were significantly elevated in CuB groups （P<0.01）. The mitochondria of cells in CuB groups were obviously wrinkled， and the mitochondrial cristae were reduced or even disappeared. Compared with that in the blank group， the protein expression of p53， ACSL4， and TFR1 were significantly up-regulated in CuB groups （P<0.05）， and that of SLC7A11， GPX4， and FTH1 were significantly down-regulated （P<0.05）. ConclusionCuB may inhibit SLC7A11 and GPX4 expression by up-regulating the expression of p53， which in turn regulates the p53/SLC7A11/GPX4 signaling pathway axis and accelerates the generation of lipid peroxidation substrate by up-regulating the expression of ACSL4. It up-regulates TFR1 expression to promote cellular uptake of Fe³⁺ and down-regulates the expression of FTH1 to reduce the ability of iron storage， resulting in an elevated free Fe²⁺ level. It catalyzes the Fenton reaction， generates excess ROS， imbalances the antioxidant system and iron metabolism， and then induces ferroptosis in 4T1 cells.

ObjectiveTo explore the role of cucurbitacin B （CuB） in inducing ferroptosis in 4T1 cells and its mechanism. MethodsThe effects of CuB（0.2， 0.4， 0.8 μmol·L^-1）on the proliferation ability of 4T1 cells in vitro were detected using the methyl thiazolyl tetrazolium （MTT） assay. The clonogenic ability of 4T1 cells was detected by the plate cloning assay， and the levels of lactate dehydrogenase （LDH） in 4T1 cells were detected by the use of a kit. The mitochondrial membrane potential and reactive oxygen species （ROS） levels in 4T1 cells were detected by flow cytometry， and the mitochondrial ultrastructure of 4T1 cells was observed by transmission electron microscopy. The western blot was used to detect the expression of ferroptosis-related protein p53 in 4T1 cells， solute carrier family 7 member 11 （SCL7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， transferrin receptor protein 1 （TFR1）， and ferritin heavy chain 1 （FTH1）. ResultsCompared with that in the blank group， the survival rate of 4T1 cells in CuB groups was significantly decreased （P<0.05）， and the number of cell clones in CuB groups was significantly reduced （P<0.01）. In addition， compared with that in the blank group， the leakage of LDH in cells in CuB groups was significantly increased （P<0.01）， and the mitochondrial membrane potential of cells in CuB groups decreased significantly （P<0.01）. Cellular ROS levels were significantly elevated in CuB groups （P<0.01）. The mitochondria of cells in CuB groups were obviously wrinkled， and the mitochondrial cristae were reduced or even disappeared. Compared with that in the blank group， the protein expression of p53， ACSL4， and TFR1 were significantly up-regulated in CuB groups （P<0.05）， and that of SLC7A11， GPX4， and FTH1 were significantly down-regulated （P<0.05）. ConclusionCuB may inhibit SLC7A11 and GPX4 expression by up-regulating the expression of p53， which in turn regulates the p53/SLC7A11/GPX4 signaling pathway axis and accelerates the generation of lipid peroxidation substrate by up-regulating the expression of ACSL4. It up-regulates TFR1 expression to promote cellular uptake of Fe³⁺ and down-regulates the expression of FTH1 to reduce the ability of iron storage， resulting in an elevated free Fe²⁺ level. It catalyzes the Fenton reaction， generates excess ROS， imbalances the antioxidant system and iron metabolism， and then induces ferroptosis in 4T1 cells.

Fe/Mn/Gd polymetallic nanooxide(FMGN)were prepared by one-step solvent thermal reaction by using Fe(acac)3,Mn(acac)2 and Gd(acac)3 as reaction precursors.Next,hyaluronic acid(HA)was used to modify FMGN to fabricate tumor-targeting T 1-T 2 dual-mode magnetic resonance imaging(MRI)contrast agent(HA-FMGN)for accurate diagnosis of prostate cancer.The structure and morphology of FMGN were observed by transmission electron microscope(TEM).It was found that FMGN exhibited a uniform nanocluster spherical structure when the feeding ratio of iron acetylacetonate,manganese acetylacetonate,and gadolinium acetylacetonate was 3:2:1.X-ray diffraction(XRD)analysis showed that FMGN had a typical inverse spinel structure of Mn doped Fe 3O 4,with Gd existing in the form of amorphous gadolinium oxide.The longitudinal relaxivity(r 1)and transverse relaxivity(r 2)of FMGN were 13.395 and 428.535 L/(mmol·s),respectively,measured by 0.5 T MRI analyzer,which proved that FMGN had excellent T 1-T 2 dual-mode MRI contrast capability.The cytotoxicity and hemolysis test found that HA-FMGN didn't damage red cells and induce toxicity for normal cells,indicating that HA-FMGN had excellent cell biocompatibility.The internalization efficacy of HA-FMGN was observed by CLSM,and the results showed that HA-FMGN possessed excellent prostate tumor-targeting ability.In vivo MRI experiment showed that HA-FMGN significantly enhanced T 1 and T 2 weighted MRI signal to noise ratio(SNR)of prostate tumor,which promoted the accurate diagnosis of orthotopic prostate cancer.

A method for determination and targeted screening of diflorasone components in health products using ultra performance liquid chromatography-quadrupole time of flight mass spectrometry(UPLC-Q-TOF/MS)was established.Four representative diflorasone and esters(diflorasone,diflorasone diacetate,diflorasone-17-propionate,and diflorasone-21-propionate)were selected to optimize the pretreatment conditions,and 10 mL of extraction solvent dosage,15 min of extraction time and 5 g of salting-out agent as the optimal conditions were selected by response surface methodology.The results showed that the four analytes exhibited good linearity within the concentration range of 2.0?100 μg/L with the chromatographic peak area,and the correlation coefficients(R2)were all greater than 0.9990,while the results of recovery and relative standard deviation could satisfy the requirements of determination.The common characteristic ions of diflorasone and esters werem/z121 andm/z335,and their specific structures were obtained by analyzing the cleavage pathway based on the optimized determination conditions.A targeted screening method for other esters of diflorasone based on characteristic ions guidance strategy was established.This method had many advantages such as high efficiency,high sensitivity and good reproducibility,and could be used for targeted screening of diflorasone and esters in health products.The developed characteristic ion guided strategy could be employed to construct mass spectral databases for various glucocorticoids,enabling comprehensive targeted screening across a broad range of compounds.

Incomplete debridement of chronic osteomyelitis is the main factor leading to recurrence. For the treatment of chronic osteomyelitis, the complete elimination of the source of infection is the key to preventing recurrence. This process includes not only the complete removal of infected lesions, dead bone, accreted scar tissue and granulation tissue, but also the elimination of dead space and improved local blood circulation. In these steps, debridement is a core procedure, and judging the scope of debridement is the premise of whether it could be completely debridement. This article systematically reviewed the application of different imaging techniques in evaluating the scope of chronic osteomyelitis infection, and discusses its future development trend. Although traditional plain X-ray film could preliminarily indicate osteomyelitis, it is difficult to determine the infection scope. CT scan has the function of accurate anatomic localization, which is important for preoperative assessment of the scope of bone infection, but the recognition of soft tissue information is limited. MRI, with its high sensitivity, clearly distinguishes between infected bone and soft tissue, which plays an important role in the evaluation of soft tissue infection, but may overestimate the extent of bone infection. Nuclide techniques such as 18F-FDG PET/CT and SPECT/CT show great potential for accurately assessing the extent of infection before surgery. In the future, by optimizing the combination of different imaging technologies, combining clinical symptoms, intraoperative conditions and pathological results, and developing an image analysis platform based on artificial intelligence, it will be able to more accurately assess the scope of infection, provide more effective and personalized treatment plans for patients with chronic osteomyelitis, enhance treatment effects, and significantly improve quality of life of patients.
Humans ; Osteomyelitis/diagnosis* ; Chronic Disease ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.