In this paper, a new method based on the nonlinear chaos theory was proposed to study the arrhythmia with the combination of the correlation dimension and largest Lyapunov exponent, through computing and analyzing these two parameters of 30 cases normal heart sound and 30 cases with arrhythmia. The results showed that the two parameters of the heart sounds with arrhythmia were higher than those with the normal, and there was significant difference between these two kinds of heart sounds. That is probably due to the irregularity of the arrhythmia which causes the decrease of predictability, and it's more complex than the normal heart sound. Therefore, the correlation dimension and the largest Lyapunov exponent can be used to analyze the arrhythmia and for its feature extraction.
Arrhythmias, Cardiac ; diagnosis ; physiopathology ; Heart Sounds ; physiology ; Humans ; Logistic Models ; Nonlinear Dynamics ; Phonocardiography ; Signal Processing, Computer-Assisted

Objective:To evaluate the value of synthetic MRI combined with DWI in the diagnosis of benign and malignant breast lesions.Methods:The data of 184 consecutive patients with suspected breast lesions in Yunnan Cancer Hospital from July to September 2019 were prospectively analyzed. All patients were randomly assigned to training group ( n=110) and validation group ( n=74), and underwent conventional MRI and synthetic MRI respectively before and after contrast injection. At the maximum slice of the lesion, the ROI was drawn along the edge and recorded as "tumor". In the solid area with the most obvious tumor enhancement, the second ROI was drawn and recorded as "local". At the same time, ADC values (ADC local and ADC tumor) and relaxation time values (T local and T tumor) were measured. T and T + represented the relaxation time value of the ROI pre-and post-contrast scanning. ΔT% represented the relative change rate in T value between pre-and post-contrast scanning.The rank sum test was used to test the quantitative parameters of benign and malignant breast lesions in the training group and the validation group, and the variables with P<0.05 were included in the binary logistic regression analysis to screen the independent variables and establish the prediction model. The area under ROC curve was used to evaluate the discrimination of parameters and models. The clinical applicability of model was analyzed by decision curve analysis (DCA). Results:In the training group, univariate analysis showed that there were significant differences in T 1tumor, T 1+tumor, ΔT 1% tumor, T 2local, T 2+local, T 2tumor and T 2+tumor, ADC local, ADC tumor between benign and malignant breast lesions ( P<0.05). Multivariate logistic regression analysis showed that T 1+tumor, ΔT 1% tumor, T 2tumor, ADC local, ADC tumor were independent variables in the diagnosis of breast cancer. The relaxation time model (model A: T 1+tumor, ΔT 1% tumor, T 2tumor) and ADC model (model B: ADC local, ADC tumor) established by combining the above variables had the same diagnostic efficiency (AUC=0.905, 0.914, Z=-1.874, P=0.062), and the multi-parameter combination model (model C: T 1+tumor, ΔT 1% tumor, T 2tumor, ADC local, ADC tumor) had the highest diagnostic efficiency (AUC=0.965). DCA analysis showed that when the threshold probability ranges between 21%-99% (training cohort) and 15%-99% (validation cohort), the net benefit of model C was better than model A and B. Conclusion:The multi-parameter combined prediction model established based on the relaxation time value and ADC can identify breast cancer efficiently and can be used as an auxiliary diagnostic tool.

Objective To analyze how enterovirus D68 (EV-D68) protease 2A affects the anti-vi-ral interferon typeⅠ(IFN-Ⅰ) pathway in 293T cells following infection. Methods Western blot was used to detect the expression of recombinant protease 2A, IFN-α and signal transducers and activators of tran-scription 1 (STAT1) at protein level. Expression of EV-D68 viral protein (VP1) and protease 2A was ana-lyzed by immunofluorescence at different time points. Cytopathic effects were recorded to calculate 50％ cell culture infective dose ( CCID50 ) . Expression of the genes involved in the anti-viral IFN-Ⅰ pathway was measured by real-time PCR (RT-PCR). Results The recombinant plasmid pCLIPf-2A was successfully constructed and the expression of recombinant protease 2A could be detected by Western blot 24 h after transfection. The recombinant protease 2A promoted the proliferation of EV-D68 at the late stage of infection and induced the production of IFN-α. Expression of the genes involved in the anti-viral IFN-Ⅰ pathway at mRNA level was up- or down-regulated to different degrees with various trends in different groups following infection. Expression of STAT1 was enhanced in all groups. Conclusions EV-D68 protease 2A promoted the activation of anti-viral IFN-Ⅰpathway in response to viral infection and enhanced the proliferation of virus at the late stage of infection.

Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2018 to December 2019. Antibiotic susceptibility tests were conducted with agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 14 778 bacterial strains were collected from 50 hospitals, of which 4 117 (27.9%) were Gram-positive bacteria and 10 661(72.1%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.2%), Klebsiella pneumoniae (17.0%), Staphylococcus aureus (9.7%), coagulase-negative Staphylococci (8.7%), Pseudomonas aeruginosa (3.7%), Enterococcus faecium (3.4%), Acinetobacter baumannii(3.4%), Enterobacter cloacae (2.9%), Streptococci(2.8%) and Enterococcus faecalis (2.3%). The the prevalence of methicillin-resistant S. aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus were 27.4% (394/1 438) and 70.4% (905/1 285), respectively. No glycopeptide-resistant Staphylococcus was detected. More than 95% of S. aureus were sensitive to amikacin, rifampicin and SMZco. The resistance rate of E. faecium to vancomycin was 0.4% (2/504), and no vancomycin-resistant E. faecalis was detected. The ESBLs-producing rates in no carbapenem-resistance E. coli, carbapenem sensitive K. pneumoniae and Proteus were 50.4% (2 731/5 415), 24.6% (493/2001) and 35.2% (31/88), respectively. The prevalence of carbapenem-resistance in E. coli and K. pneumoniae were 1.5% (85/5 500), 20.6% (518/2 519), respectively. 8.3% (27/325) of carbapenem-resistance K. pneumoniae was resistant to ceftazidime/avibactam combination. The resistance rates of A. baumannii to polymyxin and tigecycline were 2.8% (14/501) and 3.4% (17/501) respectively, and that of P. aeruginosa to carbapenem were 18.9% (103/546). Conclusions:The surveillance results from 2018 to 2019 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while E. coli was the most common pathogen, and ESBLs-producing strains were in majority; the MRSA incidence is getting lower in China; carbapenem-resistant E. coli keeps at a low level, while carbapenem-resistant K. pneumoniae is on the rise obviously.

Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2016 to December 2017. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI) 2019. WHONET 5.6 was used to analyze data.Results:During the study period, 8 154 bacterial strains were collected from 33 hospitals, of which 2 325 (28.5%) were Gram-positive bacteria and 5 829 (71.5%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (34.7%), Klebsiella pneumoniae (15.8%), Staphylococcus aureus (11.3%), coagulase-negative Staphylococci (7.4%), Acinetobacter baumannii (4.6%), Pseudomonas aeruginosa (3.9%), Enterococcus faecium (3.8%), Streptococci (2.9%), Enterobacter cloacae (2.7%) and Enterococcus faecalis (2.5%). Methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus (MRCNS) accounted for 34.2%(315/922) and 77.7%(470/605), respectively. No vancomycin-resistant Staphylococcus was detected. The resistance rate of Enterococcus faecium to vancomycin was 0.6%(2/312), and no vancomycin-resistant Enterococcus faecium was detected. The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus were 55.7%(1 576/2 831), 29.9%(386/1 289) and 38.5%(15/39), respectively. The incidences of carbapenem-resistance in Escherichia coli, Klebsiella pneumoniae were 1.2%(33/2 831), 17.5%(226/1 289), respectively. The resistance rates of Acinetobacter baumannii to polymyxin and tigecycline were 14.8%(55/372) and 5.9%(22/372) respectively, and those of Pseudomonas aeruginosa to polymyxin and carbapenem were 1.3%(4/315) and 18.7%(59/315), respectively. Conclusion:The surveillance results from 2016 to 2017 showed that the main pathogens of blood stream infection in China were gram-negative bacteria, while Escherichia coli was the most common pathogen; the MRSA incidence was lower than other surveillance data in the same period in China; carbapenem-resistant Escherichia coli was at a low level during this surveillance, while carbapenem-resistant Klebsiella pneumoniae is on the rise.

ObjectiveTo investigate the acute effects of compound air pollution on children’s respiratory function. MethodsUsing panel group study design， 223 students in five classes of grade 4 from two primary schools （a， b） in Xuhui and Hongkou districts of Shanghai were randomly selected to measure pulmonary function and exhaled nitric oxide （FeNO）. The first three tests were carried out from May to June in 2020， and the fourth test was carried out from September to December in 2021. At the same time， the daily and hourly mean values of PM_2.5， PM₁₀， SO₂， NO₂， O₃ and CO was collected from the nearby air quality monitoring points of the two schools during the same period ， as well as meteorological monitoring data （temperature， humidity， wind speed and atmospheric pressure）. The linear mixed effect model was used to analyze the effects of air pollution on pulmonary function and respiratory inflammation in the summer. ResultsThe results of single pollutant model showed that PM_2.5， PM_10， SO₂ and NO₂ were positively correlated with FeNO， and the effect was reflected in lag0， lag1 and lag3 （P<0.05）. PM_2.5， PM₁₀ and NO₂ were negatively correlated with the changes of lung function FEF_25%， FEF_50%， FEF_75%， FeF_25%-75%， PEF， FVC， FEV1 and FEV1/FVC， and the effect was reflected in lag0 to lag3 days （P<0.05）. The results of the dual pollutant model showed that the concentration changes of SO₂ and NO₂ were significantly correlated with the decrease of FEV1 when combined with O₃ or PM_2.5 （P<0.01）， and the concentration changes of PM_2.5 was significantly correlated with the increase of FeNO when O₃， SO₂ and NO₂ were combined respectively （P<0.01）. The effects of the dual pollutant model were greater than the effect of PM_2.5 single pollutant model. ConclusionThe health effects of different air pollutants on children’s respiratory tract function indexes in summer are different. The combined effects of two pollutants on the lung function of children increased to different degrees. Although air pollution is light in summer， it still has an impact on children’s respiratory tract function index and inflammation index， and the combined effect of dual pollutants is more significant than that of single pollutant.

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In this study, we aimed to develop a machine learning model for sarcopenia diagnosis using clinical characteristics and laboratory indicators of aging cohorts. METHODS: We developed models of sarcopenia using the baseline data from the West China Health and Aging Trend (WCHAT) study. For external validation, we used the Xiamen Aging Trend (XMAT) cohort. We compared the support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGB), and Wide and Deep (W&D) models. The area under the receiver operating curve (AUC) and accuracy (ACC) were used to evaluate the diagnostic efficiency of the models. RESULTS: The WCHAT cohort, which included a total of 4057 participants for the training and testing datasets, and the XMAT cohort, which consisted of 553 participants for the external validation dataset, were enrolled in this study. Among the four models, W&D had the best performance (AUC = 0.916 ± 0.006, ACC = 0.882 ± 0.006), followed by SVM (AUC =0.907 ± 0.004, ACC = 0.877 ± 0.006), XGB (AUC = 0.877 ± 0.005, ACC = 0.868 ± 0.005), and RF (AUC = 0.843 ± 0.031, ACC = 0.836 ± 0.024) in the training dataset. Meanwhile, in the testing dataset, the diagnostic efficiency of the models from large to small was W&D (AUC = 0.881, ACC = 0.862), XGB (AUC = 0.858, ACC = 0.861), RF (AUC = 0.843, ACC = 0.836), and SVM (AUC = 0.829, ACC = 0.857). In the external validation dataset, the performance of W&D (AUC = 0.970, ACC = 0.911) was the best among the four models, followed by RF (AUC = 0.830, ACC = 0.769), SVM (AUC = 0.766, ACC = 0.738), and XGB (AUC = 0.722, ACC = 0.749). CONCLUSIONS: The W&D model not only had excellent diagnostic performance for sarcopenia but also showed good economic efficiency and timeliness. It could be widely used in primary health care institutions or developing areas with an aging population. TRIAL REGISTRATION Chictr.org, ChiCTR 1800018895.
Humans ; Aged ; Sarcopenia/diagnosis* ; Deep Learning ; Aging ; Algorithms ; Biomarkers

Pyroptosis, an inflammatory caspase-dependent programmed cell death, plays a vital role in maintaining tissue homeostasis and activating inflammatory responses. Orthodontic tooth movement (OTM) is an aseptic force-induced inflammatory bone remodeling process mediated by the activation of periodontal ligament (PDL) progenitor cells. However, whether and how force induces PDL progenitor cell pyroptosis, thereby influencing OTM and alveolar bone remodeling remains unknown. In this study, we found that mechanical force induced the expression of pyroptosis-related markers in rat OTM and alveolar bone remodeling process. Blocking or enhancing pyroptosis level could suppress or promote OTM and alveolar bone remodeling respectively. Using Caspase-1^-/- mice, we further demonstrated that the functional role of the force-induced pyroptosis in PDL progenitor cells depended on Caspase-1. Moreover, mechanical force could also induce pyroptosis in human ex-vivo force-treated PDL progenitor cells and in compressive force-loaded PDL progenitor cells in vitro, which influenced osteoclastogenesis. Mechanistically, transient receptor potential subfamily V member 4 signaling was involved in force-induced Caspase-1-dependent pyroptosis in PDL progenitor cells. Overall, this study suggested a novel mechanism contributing to the modulation of osteoclastogenesis and alveolar bone remodeling under mechanical stimuli, indicating a promising approach to accelerate OTM by targeting Caspase-1.
Animals ; Humans ; Mice ; Rats ; Bone Remodeling/physiology* ; Caspase 1 ; Periodontal Ligament ; Pyroptosis ; Tooth Movement Techniques