To guide transfusion practice in critically ill children who often need plasma and platelet transfusions, the Transfusion and Anemia Expertise Initiative-Control/Avoidance of Bleeding (TAXI-CAB) developed Recommendations and Expert Consensus for Plasma and Platelet Transfusion Practice in Critically Ill Children. This guideline addresses 53 recommendations related to plasma and platelet transfusion in critically ill children with 8 kinds of diseases, laboratory testing, selection/treatment of plasma and platelet components, and research priorities. This paper introduces the specific methods and results of the recommendation formation of the guideline.

Objective: To compare the biological characteristics of human induced pluripotent stem cell-derived platelet exosomes (hiPSC-Plt-Exos) with those of conventional apheresis platelet exosomes (Plt-Exos), specifically focusing on their differential abilities to enhance the proliferation and migration of human umbilical cord mesenchymal stem cells (hUC-MSCs). Methods: Exosomes were isolated from hiPSC-derived Plt and apheresis Plt concentrate using size exclusion chromatography. These exosomes were then characterized through nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), and Western blotting. Co-culture experiments into hUC-MSCs were conducted with hiPSC-Plt-Exos and apheresis Plt-Exos, respectively. Their effects on the proliferation and migration of hUC-MSCs were assessed via cell proliferation assays and scratch tests. Results: hiPSC-Plt-Exos and apheresis Plt-Exos exhibited comparable particle sizes, morphological features (such as the characteristic cup-shaped structure), and surface markers (including CD9 and HSP70). Notably, hiPSC-Plt-Exos demonstrated a significantly greater ability to enhance the proliferation and migration of hUC-MSCs compared to apheresis Plt-Exos (P<0.05). These differences provide critical comparative data for their application in various clinical contexts. Conclusion: This study establishes a theoretical foundation for developing precise therapeutic strategies based on hiPSC-Plt-Exos. Furthermore, it underscores the necessity of selecting the appropriate type of exosomes according to the specific disease microenvironment to achieve optimal therapeutic outcomes.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.

Objective To observe the value of MRI for differential diagnosis of ovarian granulosa cell tumor(OGCT)and ovarian thecoma-fibroma(OTF).Methods Data of 37 females with OGCT(OGCT group)and 74 with OTF(OTF group)were retrospectively analyzed.MRI parameters were compared between groups.Multiple logistic regression analysis was performed,and the efficacy of each parameter alone and their combination for distinguishing OGCT and OTF were observed.Results Significant differences of cystic-solid classification,degree of cystic changes,the maximum diameter of cyst area of lesions,T2WI signal,enhancement degree and apparent diffusion coefficient(ADC)of the solid part of lesions,presence of honeycomb sign/cheese sign,presence of tumor blood vessels and bleeding were found between groups(all P＜0.05).Degree of cystic changes,ADC and presence of honeycomb sign/cheese sign were impact factors of MRI for distinguishing OGCT and OTF.The area under the curve(AUC)of the above three for distinguishing OGCT and OTF was 0.834,0.868 and 0.744,respectively,and of the combination was 0.934,greater than any alone(all P＜0.05).Conclusion MRI features such as degree of cystic changes,ADC and presence of honeycomb sign/cheese sign were helpful for distinguishing OGCT and OTF.

A good social network can ensure the safety of women during pregnancy and reduce the incidence of adverse pregnancy outcomes. However, there is currently relatively little research on the overall social network of pregnant women, and the influencing factors of the overall social network of pregnant women are not yet clear. This paper reviews the current situation, influencing factors, and measurement tools of the social network in pregnant women, aiming to improve their social network, help them access high-quality nursing resources, ensure the health of pregnant women and infants, and decrease the incidence of adverse pregnancy outcomes.

Objective:To translate the Illness Identity Questionnaire (IIQ) into Chinese and test its reliability and validity.Methods:The English version of IIQ was translated into Chinese and back-translated according to the Brislin model. The item of the Chinese version was determined after cross-cultural adaptation and pre-experiment. A total of 368 patients with IBD treated in the First Affiliated Hospital with Nanjing Medical University from September 2022 to March 2023 were selected for a questionnaire survey to evaluate the reliability and validity of the questionnaire.Results:The Chinese version of IIQ contained 24 items in four dimensions. Four common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 64.025%. Confirmatory factor analysis showed that each fitting index of the modified model was within the acceptable range. The Cronbach's α coefficients of rejection, acceptance, engulfing, and enrichment in Chinese IIQ were respectively 0.780, 0.800, 0.921, and 0.917. The split-half reliability coefficients were 0.824, 0.818, 0.943, and 0.929; the retest reliability coefficients were 0.695, 0.667, 0.725, and 0.572, respectively.Conclusions:The Chinese version of IIQ is reliable and valid and can be used to assess illness identity in patients with chronic diseases.

Pseudorabies virus(PRV)is the etiological agent of pseudorabies in pigs,which is char-acterized by dyspnea,reproductive disorders,and neurological diseases,and it spreads widely a-round the world.Since 2011,the newly emerged PRV variants have resulted in poor immunity pro-tection of traditional vaccine strains,and the original method of vaccine strain preparation is time-consuming and labor-intensive.Therefore,it is urgently needed to develop an efficient screening method of the vaccine strain at present.Using CRISPR/Cas9 gene editing technology in this study,two single guide RNAs(sgRNA)were designed targeting the virulence gene TK of PRV variant strain CH/JX/2016,and then the enhanced green fluorescent protein the reporter(EGFP)gene was inserted at the TK locus by a homologous repair plasmid.After multiple rounds of plaque puri-fication,the rPRV-ΔTK/EGFP strain was obtained.The results showed the cleavage efficiency of the two sgRNAs was extremely high.The preparation of rPRV-ΔTK/EGFP strain was succeed af-ter only three rounds of purification,and the EGFP expressed normally.The CRISPR/Cas9 system can edit the PRV gene simply,rapidly,and efficiently,and exhibits great potential in the construction of vaccine candidate strains.Meanwhile,the rescued rPRV-ΔTK/EGFP strain not only could be used as a tracer strain in PRV variant infection progresses,but also for subsequent antivi-ral drug screening.

Objective To analyze the correlation between cumulative fluid balance volume and increasing plasma volume and aggravated clinical congestion symptoms in patients with heart failure on admission for 1～7 d,and to explore the application value of cumulative fluid balance volume in predicting volume overload.Methods Using the convenience sampling method,235 heart failure patients hospitalized from October 2022 to February 2023 in a total of 3 tertiary hospitals in Nanjing,Lianyungang,Jiangsu Province,and Zhumadian,Henan Province,were selected and classified into an increasing/decreasing plasma volume group and an aggravated/alleviated clinical congestion symptoms group.General information,clinical characteristics,and 1～7 d cumulative fluid balance volume of the study subjects were collected to compare the differences in cumulative fluid balance volume between the 2 groups.Logistic regression was used to analyze the effect of cumulative fluid balance volume on plasma volume and clinical congestion symptoms.Receiver operating characteristic curves were used to analyze the optimal cutoff value of cumulative fluid balance volume for predicting increasing plasma volume and aggravated clinical congestion symptoms.Results Excluding 15 pat ients who were discharged early and 3 patients with inaccurate records of fluid intake and excretion,a total of 217 patients were included.The incidence of positive fluid balance was lowest on day 1,at 65.90%,with the smallest cumulative volume of(0.235±0.983)L;the highest incidence of positive balance occurred on day 6,at 75.58%,with the largest cumulative volume of(2.444±5.445)L.The cumulative fluid balance at 4～7 d in the increasing plasma volume group was higher than that in the decreasing plasma volume group,and the difference was statistically significant(P<0.05);the cumulative fluid balance at 4～7 d was an independent risk factor for plasma volume elevation,and a cumulative fluid balance of 2.308,3.361,3.518,and 3.702 L at 4～7 d was predictive of a plasma volume elevation,and areas under receiver operating characteristic curve were 0.686,0.721,0.647,and 0.766,respectively.The cumulative fluid balance for 4～7 d in the aggravated clinical congestion symptoms group was higher than that in the alleviated clinical congestion symptoms group,and the difference was statistically significant(P<0.05);the cumulative fluid balance for 4～7 d was an independent risk factor for the aggravated clinical congestion symptoms,and a cumulative fluid balance for 4～7 d of 2.574,3.383,4.995,and 4.235 L predicted aggravated clinical congestion symptoms,and area under receiver operating characteristic curve was 0.640,0.693,0.654,and 0.720,respectively.Conclusion The incidence of cumulative positive fluid balance in heart failure patients is high,and the amount of cumulative fluid balance can better predict the occurrence of volume overload,and the increase of plasma volume precedes the appearance of clinical congestion symptoms.It is suggested that heart failure patients with more than 3 d of cumulative positive balance should be closely monitored,and when the cumulative positive balance exceeds 2.308 L,measures should be taken in time to drain excessive fluid,so as to avoid the incidence of volume overload.