Objective To explore the regularity of incidence of agonal respiration (AR) and agonal respiration frequency rate (ARFR) during untreated cardiac arrest (CA) after ventricular fibrillation (VF) in a swine model.Methods Ten healthy male domestic pigs weighing (25.0± 3.0) kg were employed in this experiment.VF was induced by intraventricular shock with alternating current without treatment for 8 minutes.The incidence of AR and ARFR per minute were recorded for 8 minutes.Statistical analysis was performed using SPSS 19.0 system software.Results AR occurred in all animals after VF induced CA within 8 minutes.There was 1 animal showed AR at the first minute with ARFR (0.2±0.1) times/min,4 animals showed AR at the second minute with ARFR (1.2 ± 1.0) times/min,7 animals showed AR at the third minute with ARFR (2.7 ± 1.4) times/min,all animals showed AR at the fourth to fifth minute with ARFR (3.7 ± 1.6) times/min and (3.2 ± 1.9) times/min,7 animals showed AR at the sixth minute with ARFR (1.3 ± 1.0) times/min,no animal showed AR at the seventh minute,and 1 animal showed AR at the eighth minute with ARFR (0.2±0.1) times/min.The first and the last AR were observed at (2.02±0.84) minutes and (5.21 ± 1.12) minutes respectively.Occurrence of AR reached its peak at the fourth to fifth minute,and it was absent at the seventh minute.ARFR after CA showed a crescendo-decrescendo pattern,which increased from (0.2±0.1) times/min to (3.7±1.6) times/min followed by a fall to (0.2±0.1) times/min.Conclusions AR is one of the symbolic signs after CA.AR occurred in all animals during untreated VF,and it reaches its peak at the fomrth to fifth minute,with a crescendo-decrescendo pattern of ARFR.Effective identification and treatment in victim with AR timely can help to improve the success rate of cardiopulmonary resuscitation and survival rate.

Objective To analyze differentially expressed microRNAs(DEmiRNAs)in osteoporosis(OP)and chronic obstructive pulmonary disease(COPD)using bioinformatics tools,and to explore the interrelationship between these two diseases.Methods Gene expression microarrays for OP and COPD were retrieved from the GEO database.Differential analysis was conducted using the limma pack-age in R software version 4.1.0,identifying DEmiRNAs between OP and COPD.The selected DEmiRNAs were then subjected to target gene prediction using the miRDB and TargetScan databases.Predicted target genes were analyzed for transcription factor predictions using KOBAS,followed by GO and KEGG pathway analyses.Protein-protein interaction(PPI)network data for the target genes were down-loaded from the STRING database and analyzed and visualized using Cytoscape to construct a PPI network and model.Results Four DEmiRNAs were identified as differentially expressed between OP and COPD microarrays:hsa-miR-631,hsa-miR-940,hsa-miR-508-5p and hsa-miR-1470.PPI network analysis revealed seven core genes:UBA52,UBE2I,UBE2N,STAM,IPO5,CD28 and STX6.Conclusion The interconnection between OP and COPD may be mediated through a series of physiological and pathological responses such as hypoxia,chronic inflammation,oxidative stress,calcium ion reabsorption,and mitochondrial autophagy.Of these,hsa-miR-940 exhibits the closest relationship between the two diseases,suggesting a pivotal role in linking their pathogenesis.

Objective To compare the difference and effectiveness between Tetra-ataxiametry and Berg balance scale (BBS) in predicting the risk for fall in the elderly inpatients.Methods A total of 401 elderly inpatients were randomly selected using convenience sampling in a class III grade A hospital. Tetra-ataxiametry and BBS were used to monitor the risk for falls of elderly patients in two groups: group with or without fall histories.Results Fall histories were set as the standard. The area ratios under receiver operating characteristic (ROC) of Tetra-ataxiametry fall index (FI) and BBS were 0.762 and 0.705. Youden index showed that the predicted value, the sensibility and the specificity of Tetra-ataxiametry FI were 41, 80.5% and 60.2%; while those for BBS were 46, 67.1% and 65.8%. No statistically significant difference in the area under the curve (AUC) between Tetra-ataxiametry and BBS was observed(P=0.0587).Conclusions There is no statistically significant difference in predicting the risk for fall in the elderly inpatients between Tetra-ataxiametry and BBS, suggesting that Tetra-ataxiametry can replace BBS to evaluate the fall risk, and is better than BBS, since Tetra-ataxiametry has higher sensitivity in objective data provision, body weight and BMI (body mass index).