Objective To evaluate the methodological quality and measurement attribute quality of the evaluation tool for pediatric palliative care quality assessment tools,and to provide references for medical staff to select the best assessment tools.Methods The PubMed,Embase,Cochrane Library,Web of Science,CINAHL,Scopus,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Database,Chinese Biomedical Literature Database,GIN,NGC,NICE,NRAO,medlive,WHO,AAHPM,WHPCA,APHN were searched from inception to March 28,2024.Data were screened and extracted independently by 2 researchers.The consensus-based standards for the selection of health measurement instruments(COSMIN)checklist and quality criteria were employed to evaluate the methodological quality and psychometric properties of the included pediatric palliative care quality assessment tools.Finally,recommendations were formulated based on these evaluations.Results A total of 13 articles were included,involving 9 pediatric palliative care quality assessment tools.Among them,the PICU-QODD,PaPEQu and QCPCI demonstrated good content validity and internal consistency,and are recommended as Grade A.The remaining assessment tools are recommended as Grade B or C.Conclusion The PICU-QODD,PaPEQu and QCPCI are recommended for use,but further validation of their psychometric properties is still needed.

Objective To systematically review the application and effectiveness of deep learning(DL)in diagnosis of mild cogni-tive impairment(MCI)among older adults.Methods PubMed,Web of Science,CNKI and Wanfang databases were searched for literatures related to the application of DL in MCI among older adults,from database inception to December,2024.A scoping review was conducted.The literature screening process followed the Scoping Review Report Specification list,and the quality assess-ment was conducted using the cross-sectional study quality evaluation tool developed by the Evidence-based Health Care Center.Results A total of eleven papers were included,from Italy,USA,South Korea,China,India and Switzerland,involving 11 829 elderly participants,publicated mainly between 2014 and 2024,reflecting the rapid development trend of the field in the last decade,which was in line with the timing of the development of DL technology.The quality scores of the included literatures were all six to seven.The types of studies were all cross-sectional studies with significant cross-disciplinary characteristics,mainly originating from the fields of clinical medicine,biology and neuroimaging.The literature data were mainly based on the Alzheimer's disease Neuroimaging Program database and integrated other data resources.In terms of data type,in addition to brain imaging data,one study based on text data was also included.In terms of models used,five of the studies were mainly based on convolutional neu-ral networks,and the rest used different DL modeling frameworks.The task types contained binary and triple classification.In terms of prediction results,the DL models constructed on multimodal data,such as brain imag-es,could be used to construct high-precision prediction models for MCI classification,and the models were all good,with accuracy more than 70%and AUC values more than 0.7.The diagnostic accuracy of some of the mod-els was more than 90%,and the model with the highest prediction accuracy was the one that used the Biceph-Net lightweight framework,with accuracy close to 100%,and the text analysis model based on Transformer made the AUC value of 0.846,which provided new ideas for the diagnosis of non-imaging data.Conclusion DL can not only provide strong support for the accurate identification of MCI in the elderly,but also provide auxiliary prediction tools for clinicians,which can help delay the progression of the disease and improve the prognosis of patients.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.

Objective To evaluate the methodological quality and measurement attribute quality of the evaluation tool for pediatric palliative care quality assessment tools,and to provide references for medical staff to select the best assessment tools.Methods The PubMed,Embase,Cochrane Library,Web of Science,CINAHL,Scopus,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Database,Chinese Biomedical Literature Database,GIN,NGC,NICE,NRAO,medlive,WHO,AAHPM,WHPCA,APHN were searched from inception to March 28,2024.Data were screened and extracted independently by 2 researchers.The consensus-based standards for the selection of health measurement instruments(COSMIN)checklist and quality criteria were employed to evaluate the methodological quality and psychometric properties of the included pediatric palliative care quality assessment tools.Finally,recommendations were formulated based on these evaluations.Results A total of 13 articles were included,involving 9 pediatric palliative care quality assessment tools.Among them,the PICU-QODD,PaPEQu and QCPCI demonstrated good content validity and internal consistency,and are recommended as Grade A.The remaining assessment tools are recommended as Grade B or C.Conclusion The PICU-QODD,PaPEQu and QCPCI are recommended for use,but further validation of their psychometric properties is still needed.

Objective To systematically review the application and effectiveness of deep learning(DL)in diagnosis of mild cogni-tive impairment(MCI)among older adults.Methods PubMed,Web of Science,CNKI and Wanfang databases were searched for literatures related to the application of DL in MCI among older adults,from database inception to December,2024.A scoping review was conducted.The literature screening process followed the Scoping Review Report Specification list,and the quality assess-ment was conducted using the cross-sectional study quality evaluation tool developed by the Evidence-based Health Care Center.Results A total of eleven papers were included,from Italy,USA,South Korea,China,India and Switzerland,involving 11 829 elderly participants,publicated mainly between 2014 and 2024,reflecting the rapid development trend of the field in the last decade,which was in line with the timing of the development of DL technology.The quality scores of the included literatures were all six to seven.The types of studies were all cross-sectional studies with significant cross-disciplinary characteristics,mainly originating from the fields of clinical medicine,biology and neuroimaging.The literature data were mainly based on the Alzheimer's disease Neuroimaging Program database and integrated other data resources.In terms of data type,in addition to brain imaging data,one study based on text data was also included.In terms of models used,five of the studies were mainly based on convolutional neu-ral networks,and the rest used different DL modeling frameworks.The task types contained binary and triple classification.In terms of prediction results,the DL models constructed on multimodal data,such as brain imag-es,could be used to construct high-precision prediction models for MCI classification,and the models were all good,with accuracy more than 70%and AUC values more than 0.7.The diagnostic accuracy of some of the mod-els was more than 90%,and the model with the highest prediction accuracy was the one that used the Biceph-Net lightweight framework,with accuracy close to 100%,and the text analysis model based on Transformer made the AUC value of 0.846,which provided new ideas for the diagnosis of non-imaging data.Conclusion DL can not only provide strong support for the accurate identification of MCI in the elderly,but also provide auxiliary prediction tools for clinicians,which can help delay the progression of the disease and improve the prognosis of patients.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.

Objective:To evaluate the risk of bias and applicability of the risk prediction models for pancreatic fistula after pancreaticoduodenectomy (PD).Methods:The relevant studies were systematically searched from Chinese database (Chinese medical journals database, CNKI, Wanfang, Weipu, Sinomed) and English databases (PubMed, Embase, Web of Science, Cochrane Library, CINAHL Database) and the retrieval time limit was from the establishment of the database to December 31, 2023. Based on the risk of bias assessment tool of the predictive model study, the risk of bias and applicability of the model were evaluated, and the predictors with high repetition rate in the model were meta-analyzed by RevMan 5.4 software.Results:A total of 23 studies involving 30 models were included. The incidence of pancreatic fistula was 11.4%-41.7%. nineteen studies reported the discrimination index of model construction and/or validation, and the area under the curve (AUC) was 0.62-0.94. The other four studies reported the consistency index (c-index). The predictive performance of the 23 studies is good, but there is a high risk of bias. The main reasons are that the sample size is not saturated, the research object from the appropriate source is not selected, the continuous variables are not properly processed, and the predictive factors are screened by single factor analysis. Eight studies were rated as " high risk" for applicability due to inconsistencies between the included study subjects and outcome measures and the systematic review study questions. The meta-analysis results showed that the dilation of main pancreatic duct (>3 mm) ( OR=0.70, 95% CI: 0.65-0.76), soft pancreas texture ( OR=5.18, 95% CI: 3.90-6.88), and body mass index ≥25 kg/m 2 ( OR=1.12, 95% CI: 1.07-1.17) were effective predictors of postoperative pancreatic fistula (POPF). Conclusion:The existing predictive models for pancreatic fistula risk in patients undergoing PD both domestically and internationally have good predictive performance, but there is a certain risk of bias and some models have poor applicability. Predictors such as dilation of main pancreatic duct, soft pancreas texture, and body mass index≥25 kg/m 2 should be more emphasized in future predictive models.

Objective:To conduct visual analysis of neonatal hospice care based on Web of Science database and explore the research hotspots and frontiers, so as to provide reference for the development of neonatal hospice care in China.Methods:The literatures related to neonatal hospice care included in the core collection of Web of Science from 1991 to 2023 were retrieved and screened. CiteSpace 6.1.R6 was used for visual analysis from the aspects of author, country/region, institution, journal co-citation frequency, keyword knowledge map and so on.Results:A total of 1 452 articles were included, and the number of articles was on the rise. The United States, the United Kingdom and Canada occupied the core position of neonatal hospice care related research. Research hotspots included hospice care for different stages and types of diseases, key links in neonatal intensive care unit hospice care, innovation in neonatal hospice care service models, the needs and psychological support strategies of family members and medical staff. The forefront of research focused on the role and challenges of healthcare professionals in hospice care, disease diagnosis and ethical dilemmas related to decision-making.Conclusions:China can learn from international research hotspots and frontiers to explore the applicability of different hospice service models, enrich research types, strengthen guidance at the level of laws and policies, improve education and training systems and build a neonatal hospice service system that conforms to national conditions and culture in China.

Objective To establish a scientific training program that takes into account both anaerobic and aerobic training for pilots,and to explore the appropriate ratio of aerobic and anaerobic training.Methods According to the physical examination standards for pilots,a total of 16 healthy subjects aged 18-24 were selected from two batches.The two batches of subjects were trained with different aerobic and anaerobic ratios.Training period was 3 months.The changes in cardiopulmonary function of the subjects before and after training were evaluated using the cardiopulmonary function exercise testing system(CPET),and the changes in anaerobic capacity were evaluated using changes in strength as an indicator.Results After training,the weight load of the subjects in the two training programs,including barbell squats,leg flexion and hard pull,and barbell under 10RM and 3RM,was significantly increased(P<0.001),and there was no statistically significant difference in anaerobic strength growth between the two groups.The results of CPET showed that the maximum load,maximum heart rate,and respiratory quotient in the two groups were significantly increased after than before the training(P<0.01).The maximum load(Experiment group 1:29.12±19.69,Experiment group 2:72.00±46.24)and respiratory quotient(Experiment grouop 1:0.11±0.09,Experiment group 2:0.28±0.16)of the subjects in experiment group 2 before and after training were greater than those in experiment group 1.The difference was statistically significant(P<0.05).Conclusion The anaerobic and aerobic capacities of the subjects in the experiment group 2 are effectively improved,indicating that ratio of aerobic and anaerobic of the training scheme is better.

Objective:To investigate the mediating effect of spiritual health between emotional intelligence and humanistic care ability of nursing undergraduates, and to provide reference for cultivating humanistic care ability of nursing undergraduates.Methods:From May to July, 2023, the nursing undergraduates from Hunan University of Traditional Chinese Medicine, Hunan Normal University, Xi'an Medical College were selected as the research objects by convenient sampling method, and they were investigated by general information questionnaire, spiritual health scale, emotional intelligence scale and humanistic care ability scale.Using AMOS 29.0 to construct a structural equation model, this paper explored the mediating effect of spiritual health between emotional intelligence and humanistic care ability of nursing undergraduates.Results:Finally, 1 126 valid questionnaires were collected. Among 1 126 nursing undergraduates, there were 229 males and 897 females. The total scores of spiritual health, emotional intelligence and humanistic care ability of nursing undergraduates were (90.60 ± 11.02), (126.01 ± 11.90), (174.27 ± 15.16) points, respectively. The humanistic care ability of nursing undergraduates was positively correlated with spiritual health and emotional intelligence ( r=0.441, 0.417; both P<0.01), emotional intelligence and spiritual health were positively correlated ( r=0.397, P<0.01). Spiritual health had some mediating effects between emotional intelligence and humanistic care ability, and the amount of mediating effects was 32.24%. Conclusions:The humanistic care ability of nursing undergraduates is at a medium level, and emotional intelligence can influence humanistic care ability through spiritual health. Therefore, it is suggested that nursing educators should add courses and practical activities related to spiritual health in the training plan of nursing students to promote their emotional intelligence and humanistic care ability.