The therapeutic value of vacuum external fixation in polytrauma patients with multiple ribs fracture.

BACKGROUND: Multiple displaced rib fractures often result in a poor prognosis. Open reduction and internal fixation has been shown to provide benefits for patients with displaced rib fractures and flail chest. Nevertheless, for patients who are unwilling or unsuitable for surgery, the therapeutic options are limited. We developed a novel plastic vacuum device for rib fractures external stabilization. This study aims to compare the therapeutic efficacy of this device against a traditional chest strap in polytrauma patients with multiple rib fractures. METHODS: A retrospective investigation was conducted on polytrauma patients with multiple rib fractures admitted to our trauma center between March 2020 and March 2023. Patients were categorized into two groups: vacuum external fixation and chest strap. Comparative analysis was conducted on baseline parameters, injury characteristics, and clinical outcomes between the two groups. RESULTS: In this study, 54 patients were included, with 28 receiving chest strap and 26 undergoing vacuum external fixation. Results showed that, at 3 days and 7 days postintervention, the vacuum external fixation group had significantly lower visual analog scale scores during deep breathing and coughing (P < .05). Vacuum external fixation also reduced pleural drainage duration and volume, as well as lowered the risk of pneumonia and other complications (P < .05). Furthermore, the vacuum external fixation group demonstrated notable improvements in vital capacity, tidal volume, blood-gas test results, and a shorter hospital length of stay. CONCLUSIONS: According to the study findings, vacuum external fixation appears to offer benefits to patients with multiple rib fractures, potentially reducing the risk of complications and improving overall clinical outcomes.

Development and validation of a deep learning model for breast lesion segmentation and characterization in multiparametric MRI.

Importance: The utilization of artificial intelligence for the differentiation of benign and malignant breast lesions in multiparametric MRI (mpMRI) assists radiologists to improve diagnostic performance. Objectives: To develop an automated deep learning model for breast lesion segmentation and characterization and to evaluate the characterization performance of AI models and radiologists. Materials and methods: For lesion segmentation, 2,823 patients were used for the training, validation, and testing of the VNet-based segmentation models, and the average Dice similarity coefficient (DSC) between the manual segmentation by radiologists and the mask generated by VNet was calculated. For lesion characterization, 3,303 female patients with 3,607 pathologically confirmed lesions (2,213 malignant and 1,394 benign lesions) were used for the three ResNet-based characterization models (two single-input and one multi-input models). Histopathology was used as the diagnostic criterion standard to assess the characterization performance of the AI models and the BI-RADS categorized by the radiologists, in terms of sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). An additional 123 patients with 136 lesions (81 malignant and 55 benign lesions) from another institution were available for external testing. Results: Of the 5,811 patients included in the study, the mean age was 46.14 (range 11-89) years. In the segmentation task, a DSC of 0.860 was obtained between the VNet-generated mask and manual segmentation by radiologists. In the characterization task, the AUCs of the multi-input and the other two single-input models were 0.927, 0.821, and 0.795, respectively. Compared to the single-input DWI or DCE model, the multi-input DCE and DWI model obtained a significant increase in sensitivity, specificity, and accuracy (0.831 vs. 0.772/0.776, 0.874 vs. 0.630/0.709, 0.846 vs. 0.721/0.752). Furthermore, the specificity of the multi-input model was higher than that of the radiologists, whether using BI-RADS category 3 or 4 as a cutoff point (0.874 vs. 0.404/0.841), and the accuracy was intermediate between the two assessment methods (0.846 vs. 0.773/0.882). For the external testing, the performance of the three models remained robust with AUCs of 0.812, 0.831, and 0.885, respectively. Conclusions: Combining DCE with DWI was superior to applying a single sequence for breast lesion characterization. The deep learning computer-aided diagnosis (CADx) model we developed significantly improved specificity and achieved comparable accuracy to the radiologists with promise for clinical application to provide preliminary diagnoses.

Method Comparison and Bias Estimation of Blood Urea Nitrogen (BUN), Creatinine (Cr), and Uric Acid (UA) Measurements between Two Analytical Methods.

BACKGROUND: A comparison of any two methods is of great importance in a clinical laboratory. In this study, our aim is to compare the assay results of blood urea nitrogen (BUN), creatinine (Cr), and uric acid (UA) obtained through two distinct methods and then assess the analytical agreement of the two methods. METHODS: A test method (Vitros5600 system) measuring BUN, Cr, and UA analytes was compared with a reference method (Hitachi7600 system). The Clinical and Laboratory Standards Institute (CLSI) document EP9-A2 guidelines were followed to evaluate the method comparison and bias using 40 patient samples. RESULTS: A high correlation between the two methods was found for all of the samples (R2 > 0.990). The regression parameters were BUN (R2 = 0.9996, slope = 1.025, intercept = 0.1156), Cr (R2 = 0.9993, slope = 0.9993, intercept = 4.661), and UA (R2 = 0.9971, slope = 1.011, intercept = 1.311). Compared with the Hitachi7600 reference method, the Vitros5600 test method showed that the 95% confidence interval for the predicted bias at medical decision levels was less than the acceptable error. More importantly, Bland-Altman plots indicated that a minimal positive bias (mean ± SD) was observed: BUN (0.352 ± 0.289 mmol/L), Cr (2.702 ± 7.683 µmol/L), UA (5.398 ± 7.086 µmol/L). CONCLUSIONS: The Vitros5600 and Hitachi7600 systems have good correlation and bias for detecting BUN, Cr, and UA analytes. The two systems have a high method agreement.

Tripterygium glycosides inhibit inflammatory mediators in the rat synovial RSC-364 cell line stimulated with interleukin-1ß.

Tripterygium glycosides (TG) are extracted from a traditional Chinese medicinal herb. Using the compound, progress has been made in the treatment of rheumatoid arthritis (RA), but the underlying mechanism of its action is poorly understood. The purpose of the present study was to investigate the role of TG in preventing inflammatory arthritis. An inflammatory cell model was established in the rat synovial RSC-364 cell line via induction with interleukin (IL)-1ß. The expression of IL-32 and matrix metalloproteinases (MMP-1 and MMP-9) was determined using an enzyme-linked immunosorbent assay. Compared with the control group (without IL-1ß), IL-1ß in the treatment group induced the expression of IL-32, MMP-1 and MMP-9 in RSC-364 cells. When a different dose of TG was added to RSC-364 cells stimulated with IL-1ß, TG decreased the expression levels of IL-32, MMP-1 and MMP-9 in a dose-dependent manner. These results indicated that TG suppressed the inflammation response in RSC-364 cells. Taken together, these findings may contribute to a better understanding of the role of TG in the anti-inflammatory therapeutics for RA.

Quantitative Proteomic Analysis of Peripheral Blood Mononuclear Cells in Ankylosing Spondylitis by iTRAQ.

This study was designed to identify and quantify the different proteins expression levels in ankylosing spondylitis (AS) and to explore the pathogenesis of AS. We performed isobaric tags for relative and absolute quantitation (iTRAQ) coupled with multiple chromatographic fractionation and tandem mass spectrometry to detect the proteins profiling in peripheral blood mononuclear cells (PBMCs) from AS patients and healthy controls. Mascot software and the International Protein Index and the Gene Ontology (GO) database were used to conduct the bioinformatics analysis. The differentially expressed proteins were validated by enzyme-linked immunosorbent assay (ELISA). A total of 1,232 proteins were identified by iTRAQ, of which 183 showed differential expression and 18 differentially expressed proteins were acute phase reactants. Upon mapping of the differentially expressed proteins to GO database, we found four differentially expressed proteins involved in the biological process of cell killing, including up-regulated cathepsin G (CTSG), neutrophil defensin3 (DEFA3), protein tyrosine phosphatase receptor type C (PTPRC), and down-regulated peroxiredoxin-1(PRDX1),which were consistent with the verified results of ELISA. Our proteomic analyses suggested that the proteins involved in the biological process of cell killing might play an important role in the pathogenesis of AS.

Solvothermal synthesis of functional magnetic nanoparticles for biocatalyst.

A facile and simple one-step solvothermal method has been developed to synthesize polyethyleneimine (PEI)-modified magnetic nanoparticles. Characterization of morphology, surface charges, crystal structure, and magnetic property confirmed the efficiency of this facile synthesis route. Lipase immobilized on the PEI-modified magnetic nanoparticles was used to synthesize vitamin A palmitate from vitamin A acetate and palmitic acid. The reuse of immobilized lipase can be extended to eight times by removing water during esterification with a conversion rate above 80 % for 12 h.

Enhancing trimethylolpropane esters synthesis through lipase immobilized on surface hydrophobic modified support and appropriate substrate feeding methods.

Candida sp. 99-125 lipase immobilized on surface hydrophobic modified support and appropriate substrate feeding methods were used to improve the synthesis of tri-substituted trimethylolpropane (TMP) esters, which can be used as raw materials for biodegradable lubricants. The proposed novel production method is environmentally friendly. Lipase was adsorbed on surface hydrophobic silk fibers that were pretreated by amino-modified polydimethylsiloxane. A 5-level-4-factors central composite model, including reaction time, temperature, enzyme amount, and molar ratio of fatty acid to TMP, was designed to evaluate the interaction of process variables in the enzymatic esterification. The water activity was kept constant using a LiCl-saturated salt solution. Under the optimum conditions with 30% enzyme amount and substrates molar ratio 8.4 at 45°C for 47h, the total conversion of caprylic acid is 97.3% and the yield of tri-substituted TMP esters is 95.5%. The surface hydrophobic treatment resulted in less cluster water accumulated on the surface immobilized lipase, which was demonstrated by near-infrared spectra. Consequently, the optimum temperature and water tolerance of immobilized lipase were increased. Two TMP-feeding methods were used to maintain high molar ratio of fatty acid to TMP, and increase the final tri-substituted TMP esters content exceeding 85% (w/w) in reactant.

Animations, games, and virtual reality for the Jing-Hang Grand Canal.

Digital heritage, an effective method to preserve and present natural and cultural heritage, is engaging many heritage preservation specialists and computer scientists. In particular, computer graphics researchers have become involved, and digital heritage has employed many CG techniques. For example, Daniel Pletinckx and his colleagues employed VR in a real museum at Ename, Belgium, and Zhigeng Pan and his colleagues applied it to construct a virtual Olympics museum. Soo-Chang Pei and his colleagues focused on restoring ancient Chinese paintings. Here, we describe how we've applied animations, computer games, and VR to China's famous Jing-Hang Grand Canal.