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Background: Studies have confirmed that osteoporosis has been considered as one of the complications of diabetes, and the health hazards to patients are more obvious. This study is mainly based on the Taiwan National Health Insurance Database (TNHID). Through the analysis of TNHID, it is shown that the combined treatment of traditional Chinese medicine (TCM) medicine in patients of diabetes with osteoporosis (T2DOP) with lower related risks. Methods: According to the study design, 3131 patients selected from TNHID who received TCM treatment were matched by 1-fold propensity score according to gender, age, and inclusion date as the control group. Cox proportional hazards analyzes were performed to compare fracture surgery, hospitalization, and all-cause mortality during a mean follow-up from 2000 to 2015. Results: A total of 1055/1469/715 subjects (16.85%/23.46%/11.42%) had fracture surgery/inpatient/all-cause mortality of which 433/624/318 (13.83%/19.93%/10.16%) were in the TCM group) and 622/845/397 (19.87%/26.99%/12.68%) in the control group. Cox proportional hazards regression analysis showed that subjects in the TCM group had lower rates of fracture surgery, inpatient and all-cause mortality (adjusted HR = 0.467; 95% CI = 0.225–0.680, P<0.001; adjusted HR = 0.556; 95% CI = 0.330–0.751, P<0.001; adjusted HR = 0.704; 95% CI = 0.476–0.923, P = 0.012). Kaplan-Meier analysis showed that the cumulative risk of fracture surgery, inpatient and all-cause mortality was significantly different between the case and control groups (all log-rank p<0.001). Conclusion: This study provides longitudinal evidence through a cohort study of the value of integrated TCM for T2DOP. More research is needed to fully understand the clinical significance of these results. [ABSTRACT FROM AUTHOR]

The challenges of respiratory infections persist as a global health crisis, placing substantial stress on healthcare infrastructures and necessitating ongoing investigation into efficacious treatment modalities. The persistent challenge of respiratory infections, including COVID-19, underscores the critical need for enhanced diagnostic methodologies to support early treatment interventions. This study introduces an innovative two-stage data analytics framework that leverages deep learning algorithms through a strategic combinatorial fusion technique, aimed at refining the accuracy of early-stage diagnosis of such infections. Utilizing a comprehensive dataset compiled from publicly available lung X-ray images, the research employs advanced pre-trained deep learning models to navigate the complexities of disease classification, addressing inherent data imbalances through methodical validation processes. The core contribution of this work lies in its novel application of combinatorial fusion, integrating select models to significantly elevate diagnostic precision. This approach not only showcases the adaptability and strength of deep learning in navigating the intricacies of medical imaging but also marks a significant step forward in the utilization of artificial intelligence to improve outcomes in healthcare diagnostics. The study's findings illuminate the path toward leveraging technological advancements in enhancing diagnostic accuracies, ultimately contributing to the timely and effective treatment of respiratory diseases. [ABSTRACT FROM AUTHOR]

This study used the submerged arc discharge method (SADM) to produce metal fluid containing nanoparticles and submicron particles, whereby the energy focused by an electric arc was used to disintegrate silver (Ag) metal in deionized water (DW). No additional chemical substances were required throughout the process, which enabled production to be fast and straightforward. This study proposed using colorimetry to define the interrelation between concentration and nano Ag as well as the Ag ions (Ag+) within a nano silver colloid (NSC) of a specific dilution factor, involving ultraviolet-visible (UV-Vis) spectroscopy and the measuring of electrical conductivity. The results showed that Ag+ activity increased under various dilution conditions, displaying an upward trend in activity with an increase in the dilution factor. The absorption values of Ag+ and nanoparticles increased over time, and the Ag+ activity increased by up to a factor of two after its dilution. Therefore, the Ag+ and nanoparticles demonstrated an interdependence between each other.

Electric Discharge Method (EDM) was used to prepare graphene in deionized water which CO2 had been dissolved in advance. According to law of mass conservation, the chemical equation of EDM was balanced to prove the component was graphene. Tyndall effect, ultraviolet-visible spectroscopy (UV-Vis), Zetasizer, Transmission Electron Microscope and Raman were used for the identification of graphene. Then the impact of CO2 concentration on graphene preparation was discussed. The results showed that carbon atoms assemble into forming graphene. And zeta potential of graphene was − 31.6 mV, which indicated good suspension of graphene. [ABSTRACT FROM AUTHOR]

A case study of 59-year-old man is presented with abnormal chest radiograph, and history of compression fracture and traumatic spondylolisthesis because of a car accident. Treatment included percutaneous vertebroplasty and pedicle screw augmentation. Examination showed multiple linear hyperdense foreign bodies at the pulmonary arteries bilaterally and vertebroplasty with cement migration. He was suggested for patient anticoagulation treatment.

Electric Discharge Method (EDM) was used to prepare graphene in deionized water which CO2 had been dissolved in advance. According to law of mass conservation, the chemical equation of EDM was balanced to prove the component was graphene. Tyndall effect, ultraviolet-visible spectroscopy (UV-Vis), Zetasizer, Transmission Electron Microscope and Raman were used for the identification of graphene. Then the impact of CO2 concentration on graphene preparation was discussed. The results showed that carbon atoms assemble into forming graphene. And zeta potential of graphene was − 31.6 mV, which indicated good suspension of graphene. [ABSTRACT FROM AUTHOR]