Background Volatile organic compounds (VOCs) in exhaled breath are closely associated with respiratory diseases and are linked to various metabolic reactions in the human body. A quantitative analytical method can provide technical support for studying VOCs related to various diseases. Objective To establish a thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) method for the determination of 27 VOCs in exhaled breath. Methods VOCs in exhaled breath were collected using a Bio-VOC sampler and enriched with Tenax TA thermal desorption tubes before TD-GC-MS analysis. Standards were collected using thermal desorption tubes and optimized for thermal desorption conditions as well as chromatographic and mass spectrometric conditions: The separation of the 27 VOCs was achieved by an optimized temperature program, the improvement of sensitivity by optimizing quantitative ions, and the increase of VOCs desorption efficiency by optimizing thermal desorption time and temperature. Limit of detection, limit of quantification, accuracy, precision, and stability of the proposed method were investigated by spiking with a blank gas bag, and exhaled breath samples from 20 healthy individuals were collected for an application study of the proposed method. Results The thermal desorption temperature was 280 ℃, and desorption time was 6 min. A VF-624ms chromatographic column was selected for the separation of target substances. The initial temperature of heating program was 35 ℃, maintained for 1 min, and then increased to 100 ℃ at a heating rate of 3 ℃·min⁻¹ for 1 min, followed by increasing to 210 ℃ at a heating rate of 28 ℃·min⁻¹ for 5 min. A quantitative analysis was conducted with a single ion monitoring (SIM) mode. Under these conditions, the 27 VOCs showed good linear relationships in their respective concentration ranges and the correlation coefficients were higher than 0.9990. The limits of detection of the method were in the range of 0.01-0.13 nmol·mol⁻¹, the limits of quantification were in the range of 0.02-0.44 nmol·mol⁻¹, and the spiked recoveries were in the range of 80.1%-120.5%, with intra-batch and inter-batch precision ≤ 18.8% and 17.9% respectively. All substances can be stored at room temperature (23-28 °C) for 7 d and at 4 °C for 14 d. The proposed method was applied to exhaled breath samples from 20 subjects with detection rates≥ 80% (except for trans-2-pentene and decane) and a concentration range of 0.00-465.50 nmol·mol⁻¹. Conclusion The established TD-GC-MS method for quantification of VOCs in exhaled breath is characterized by high sensitivity and good accuracy, and is suitable for quantitative determination of VOCs in exhaled breath, which can provide technical support for the study of exhaled breath VOCs.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Objective:To analyze and explore the possible mechanism of anti-tumor metastasis of Notoginseng Radix et Rhizoma using Internet pharmacology. Methods:The active components and targets of Notoginseng Radix et Rhizoma were screened by retrieving Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). GeneCards database was used to screen the anti-tumor metastasis-related targets, and compounds and disease targets were under mapping analysis. Key targets of Notoginseng Radix et Rhizoma for anti-tumor metastasis were screened through Venn map. With the help of Cytoscape 3.7.2 software, a compound-disease network diagram was constructed. String platform was used to build a PPI network. Bioconductor was used to enrich the target genes for KEGG signaling pathway and GO biological process analysis. Results:Totally 119 active components were selected from Notoginseng Radix et Rhizoma. There were 8 eligible active components, corresponding to 162 related targets, 121 targets related to anti-tumor metastasis, and 30 key targets screened by PPI network, including AKT1, MAPK1, JUN, RELA, IL6, etc. GO enrichment analysis mainly involved biological processes such as cytokine receptor binding, heme binding, RNA polymerase Ⅱ transcription factor binding, ubiquitin protein ligase binding, and steroid hormone receptor activity. 149 signal pathways related to Notoginseng Radix et Rhizoma anti-tumor metastasis were obtained by KEGG enrichment analysis, mainly involving multiple signal pathways, such as AGE-RAGE and PI3K-Akt, and hepatitis B, Kaposi's sarcoma-associated herpes virus infection, human cytomegalovirus infection and other viral infections and various tumors. Conclusion:Notoginseng Radix et Rhizoma can pass multiple active components, such as ginsenoside f2, ginsenoside rh2 β-, sitosterol, stigmasterol and quercetin, and multiple targets, such as AKT1, MAPK1, JUN, RELA and IL6, acting on multiple pathways such as PI3K-Akt, thereby playing the role of anti-tumor metastasis.

Objective:To compare the short-term efficacy between our self-designed intelligent robot-assisted minimally invasive reduction system and conventional freehand reduction assisted by fluoroscopy in the treatment of unstable pelvic fractures by robot or fluoroscopy-assisted internal fixation with percutaneous screws.Methods:A prospective randomized controlled trial was conducted to include eligible 35 patients with unstable pelvic fracture who were admitted to Department of Orthopaedic Trauma, Beijing Jishuitan Hospital from December 2021 to October 2022. They were randomized into 2 groups. The observation group[17 cases, 10 males and 7 females with an age of (44.0±17.4) years] was treated with robot-assisted minimally invasive reduction, followed by robot-assisted or fluoroscopic internal fixation with percutaneous screws; the control group[18 cases, 12 males and 6 females with an age of (38.8±15.0) years] was treated with freehand reduction assisted by fluoroscopy, followed by robot-assisted or fluoroscopic internal fixation with percutaneous screws. The 2 groups were compared in terms of operation time, intraoperative bleeding, successful reduction, reduction quality, incidence of surgical complications and postoperative functional scores.Results:The 2 groups were comparable because there were no significant differences in the preoperative general data between them ( P>0.05). The intraoperative fluoroscopy frequency[(32.4±17.5) times] and fluoroscopy time [(19.8±10.4) s] in the observation group were significantly lower or shorter than those in the control group [(60.8±26.6) times and (38.2±16.1) s], and the rate of successful reduction in the observation group was 100.0% (17/17), significantly higher than that in the control group[72.2% (13/18)] ( P<0.05). There was no significant difference between the 2 groups in intraoperative bleeding, operation time, reduction error, excellent and good rate of reduction after operation by Matta scoring, or Majeed functional score at 12 weeks after operation ( P>0.05). Conclusion:In the treatment of unstable pelvic fractures, since our self-designed intelligent robot-assisted minimally invasive reduction system can plan autonomously the reduction paths and accomplish minimally invasive reduction of the fracture with 3D images real-time monitoring, it is advantageous over conventional reduction methods in a higher success rate and less radiation exposure.

Bioactive glass (BG) has been widely used in the preparation of artificial bone scaffolds due to its excellent biological properties and non-cytotoxicity, which can promote bone and soft tissue regeneration. However, due to the brittleness, poor mechanical strength, easy agglomeration and uncontrollable structure of glass material, its application in various fields is limited. In this regard, most current researches mainly focus on mixing BG with organic or inorganic materials by freeze-drying method, sol-gel method, etc., to improve its mechanical properties and brittleness, so as to increase its clinical application and expand its application field. This review introduces the combination of BG with natural organic materials, metallic materials and non-metallic materials, and demonstrates the latest technology and future prospects of BG composite materials through the development of scaffolds, injectable fillers, membranes, hydrogels and coatings. The previous studies show that the addition of BG improves the mechanical properties, biological activity and regeneration potential of the composites, and broadens the application of BG in the field of bone tissue engineering. By reviewing the recent BG researches on bone regeneration, the research potential of new materials is demonstrated, in order to provide a reference for future related research.
Bone Regeneration ; Bone and Bones ; Freeze Drying ; Glass ; Hydrogels

Objective:To evaluate a self-designed intelligent robot-assisted minimally invasive reduction system in the reduction of unstable pelvic fractures by a cadaveric anatomic study.Methods:Ten unembalmed cadavers (7 male and 3 female ones) were used in this study. In each cadaveric specimen an unstable pelvic fracture was created in accordance with clinical case models (3 cases of type B1, 4 cases of type B2 and 3 cases of type C1 by the Tile classification). A self-designed intelligent robot-assisted minimally invasive reduction system was used to assist the reduction in the cadaveric models. Intraoperative registration and navigation time, autonomous reduction time, total operation time and reduction error were measured.Results:Effective reduction was completed in 10 bone models with the assistance of our self-designed intelligent robot-assisted minimally invasive reduction system. The time for intraoperative registration and navigation averaged 47.4 min (from 32 to 74 min), the autonomous reduction time 73.9 min (from 48 to 96 min), and the total operation time 121.3 min (from 83 to 170 min). The reduction error averaged 2.02 mm (from 1.67 to 2.62 mm), and the reduction results met the clinical requirements.Conclusion:Our self-designed intelligent robot-assisted minimally invasive reduction system is a new clinical solution for unstable pelvic fractures, showing advantages of agreement with clinical operative procedures, high reduction accuracy and operational feasibility, and reduced radiation exposure compared to a conventional operation.

Objective:To explore the clinical effect of Intensive Care Unit (ICU) catheter whole life cycle management system.Methods:An ICU catheter whole life cycle management system was constructed and applied in clinical practice. This study collected data on catheter management and hospital infection of patients in ICU of Zhejiang Hospital before the application of the catheter whole life cycle management system from April to December 2019 and after the application of the catheter whole life cycle management system from April to December 2020. The accuracy of catheter recording, the compliance rate of daily catheter nursing quality, and the incidence of major catheter-associated infections were compared before and after the application of the ICU catheter whole life cycle management system. The time-consuming of catheter information recording under the two methods of applying the ICU catheter whole life cycle management system and computer manual input was analyzed, and the nurses' experience of using the ICU catheter whole life cycle management system was investigated through semi-structured interviews.Results:After the application of the ICU catheter whole life cycle management system, the accuracy rate of catheter recording increased from 89.96% (22 491/25 001) to 96.09% (30 897/32 155) , and the difference was statistically significant ( P<0.05) . The compliance rate of daily catheter nursing quality increased from 89.81% (22 453/25 001) to 95.94% (30 849/32 155) , and the difference was statistically significant ( P<0.05) . There was no significant difference in the incidence of major catheter-associated infections before and after system application ( P>0.05) . In addition, the time-consuming of catheter recording by nurses using the ICU catheter whole life cycle management system was less than that of manual input by computer, and the difference was statistically significant [ (0.98±0.28) min vs. (1.78±0.50) min, P<0.05] . The semi-structured interview results showed that nurses had a good experience in using the ICU catheter whole life cycle management system. Conclusions:The ICU catheter whole life cycle management system provides nurses with a systematic, convenient and standardized catheter management method. The system has a good user experience, can improve the accuracy of nurse catheter recording and the catheter nursing quality, and shorten catheter recording time. However, further studies are needed to confirm whether it helps to reduce the incidence of major catheter-associated infections.

Objective:To compare the biomechanical properties of traditional surface hip prosthesis and bionic surface hip prosthesis.Methods:The Sawbone digital model (#3908, Left, Medium) was selected as the research object. Mimics 21.0 software was used to reconstruct the physical model of femur. Solidworks 16.0 software was used to build the model of prostheses, including the traditional and bionic (type 1-4) protheses and their assembly. The distances from the screw cross position to the top of pressure screw of type 1 to type 4 protheses were 20.22 mm, 30.12 mm, 32.17 mm and 37.76 mm, respectively. The mechanical distribution characteristics of the whole model were measured and the stress distribution cloud map was obtained.Results:The peak stresses at bone-stem junction of traditional prosthesis and type 1-4 hip prostheses were 32.18 MPa, 13.80 MPa, 15.01 MPa, 23.46 MPa and 34.51 MPa, respectively. With the fulcrums away from the top of the femur, the peak stresses at the fulcrums of type 1-4 hip protheses were 37.98 MPa, 48.60 MPa, 54.80 MPa, and 53.87 MPa, respectively. The maximum stress above femoral neck of traditional prosthesis and type 1-4 hip prostheses were 8.00 MPa, 7.80 MPa, 7.04 MPa, 7.03 MPa and 7.51 MPa, respectively. The maximum stresses under femoral neck was 15.38 MPa, 14.20 MPa, 11.11 MPa, 13.10 MPa and 12.18 MPa, respectively. The maximum stresses in the greater trochanter region of femur were 13.08 MPa, 11.61 MPa, 13.09 MPa, 11.02 MPa and 39.51 MPa, respectively.Conclusion:Compared with the traditional surface hip prosthesis, the type I bionic surface hip prosthesis is designed based on the lever balance reconstruction theory. With the bionic reconstruction of the tension trabeculae and compression trabeculae through reasonable screw placement angles and the inward movement of the fulcrum closer to the center of the femoral head, the new type prothesis make up for the design defects of the traditional surface hip prosthesis, optimize the stress distribution in the proximal femur, and improve the stability of the prosthesis after replacement, which help reduce the risk of femoral neck fracture and prosthesis loosening, and extend the service life of the prosthesis.