Objective To investigate the status quo of application of fall risk factors assessment scale in nurses of different position in geriatric ward . Method Eighty-six nurses in different position were investigated by fall risk factors assessment scale . Results About 89 . 5%of the nurses could assess the fall risk factors on time and 80 . 2%could do it accurately , and only 62 . 8%of them worked out their nursing orders based on the possible falls. In terms of the accuracy in using fall risk factors assessment, the primary nurses was poorer than the senior nurses, with statistically significant difference between them (P<0.05). Yet there were no significant differences between them in timeliness and pertinence at working out nursing orders (P>0.05). Conclusion We should strengthen the training to the clinical nurses in correctly using the fall assessment scale , in order to exert the diagnostic value of the fall assessment scale, reduce the incidence of falls and ensure the safety of the patients.

Objective:To develop an artificial intelligence (AI) quality control model of fetal heart in the first trimester and verify its effectiveness.Methods:A total of 18 694 images of the four-chamber view(4CV) and three-vessel and tracheal view(3VT) of fetal heart in the first trimester were selected from Shenzhen Maternal and Child Health Hospital Affiliated to Southern Medical University since January 2022 to December 2022. A total of 14 432 images were manually annotated. The one-stage target detection algorithm YOLO V5 was used to train the AI quality control model in the first trimester of fetal heart, and 4 262 images (golden standard set by expert group) were used to evaluate the application effectiveness of AI quality control model. Kappa consistency test was used to compare the results of section classification and standard degree judgment from AI quality control model, Doctor 1(D1) and Doctor 2(D2).Results:①Precision of the AI quality control model was 0.895, recall was 0.852, mean average precision (mAP 50) was 0.873.The average precision(AP) of the AI quality control model for section classification was 0.907 (4CV) and 0.989 (3VT), respectively. ②Compared with the gold standard, the overall coincidence rate and consistency of section classification of AI quality control model, D1 and D2 were 99.91% (Kappa=0.998), 100% (Kappa=1.000), 100% (Kappa=1.000), respectively. The coincidence rate and consistency of the plane standard degree evaluation from the AI quality control model, D1 and D2 were 97.46% (Weighted Kappa=0.932), 93.73% (Weighted Kappa=0.847), and 93.12% (Weighted Kappa=0.832), respectively. Strong consistency was displayed. Moreover, AI quality control model showed the highest coincidence rate and the strongest consistency in judging section standard degree, which was superior to manual quality control. The time-consuming of AI quality control (0.012 s/sheet) was significantly less than the way of manual quality control (4.76-6.11 s/sheet)( Z=-8.079, P<0.001). Conclusions:The use of artificial intelligent fetal heart quality control model in the first trimester can effectively and accurately control the image quality.

Objective To observe the correlations of pontine biological indicators on fetal brain median sagittal MRI with gestational week.Methods Data of head MRI of 226 normal fetuses without obvious abnormalities of central nervous system(normal group)and 17 fetuses with abnormalities(abnormal group)at gestational age of 23 to 38 weeks were retrospectively analyzed.Pontine biological indicators based on median sagittal MRI were obtained,including pons anteroposterior diameter(PAD),total pons area(TPA),pontine basal anteroposterior length(AP),pontine basal cranio-caudal length(CC),basis pontis area(BPA)and pontine angle of midbrain(MAP).According to the gestational week,the fetuses of normal group were divided into 8 subgroups.The distributing ranges of pontine biological indicators at different gestational weeks were analyzed,and the correlations of pontine biological indicators with gestational week in normal group were explored,and the developmental status of fetal pons in abnormal group were assessed.Results In normal group,PAD,TPA,AP,CC and BPA all showed linear positive correlation(r=0.887,0.914,0.787,0.866,0.865,all P＜0.001),while MAP was not significantly correlated with gestational week(P＞0.05).Among 17 fetuses in abnormal group,abnormal PAD or TPA was found each in 8 fetuses,abnormal AP was observed in 14,abnormal CC was noticed in 3 and abnormal BPA was found in 11 fetuses.Conclusion Fetal pontine biological indicators such as PAD,TPA,AP,CC and BPA on median sagittal MRI were positively correlated with gestational week,hence being able to be used for evaluating fetal pontine development.

OBJECTIVE: To observe the effects of a traditional Chinese medicine (TCM) capsule for replenishing qi, nourishing yin and activating blood on Notch/Hes1 signaling pathway in the renal tissue and vascular endothelial CD34 and CD144 expressions in a rat model of diabetic nephropathy. METHODS: Rat models of early-stage diabetic nephropathy were established by left nephrectomy and high- fat and high- sugar feeding combined with intraperitoneal injection of STZ. The rats were randomized into model group, benazepril group, and high-, moderate-, and low-dose TCM capsule groups for corresponding treatments, with 6 normal rats as the control group. After 8 weeks of drug treatment, blood glucose and 24-h urinary albumin of the rats were measured, and the renal histopathology was observed with HE staining; Hes1 expression in the renal tissue was detected with immunohistochemical staining, and the renal expressions of CD34 and CD144 were detected using Western blotting. RESULTS: Compared with the normal control group, the rat models of diabetic nephropathy showed obvious abnormalities in 24- h urinary albumin and expressions of Hes1, CD34 and CD144d. The TCM capsule at both the high and moderate doses significantly reduced 24-h urinary albumin in the rats; the renal expressions of Hes1 and CD34 was significantly reduced in all the dose groups, and the expression of CD144 was significantly reduced in the high- dose group. Compared with benazepril group, the TCM capsule obviously reduced CD34 expression at all the 3 doses and lowered CD144 expression at the low dose. Histopathologically, the rats in the model group showed glomerular hypertrophy, increased mesenteric matrix, thickening and widening of the mesenteric membrane, and nodular hyperplasia. These pathologies were obviously alleviated by treatment with the TCM capsule at the high and moderate doses. CONCLUSIONS The Traditional Chinese medicine (TCM) capsule for replenishing qi, nourishing yin and activating blood can reduce Hes1, CD34 and CD144 in kidney tissue of model rats, play a protective role on kidney function and delay the development of DN.
Animals ; Diabetic Nephropathies ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional ; Qi ; Rats ; Signal Transduction ; Transcription Factor HES-1