Objective:To explore the heterogeneity in the trajectories ofperinatal depressive symptoms and identify the related factors.Methods:A longitudinal follow-up study was conducted from January 2020 to June 2021.Baseline information,marriage satisfaction and social support status were collected at enrolment.Perinatal de-pressive symptoms were measured using the Edinburgh Postnatal Depression Scale(EPDS)at five time-points from second trimester to three-months postpartum.A Latent Class Growth Model(LCGM)was used to identify sub-groups of perinatal depressive symptoms trajectories and logistic regression was applied to examine associated risk and protective factors.Results:Two latent depression trajectory subgroups were identified A majority(72.2％,n=1 023)followed a curvilinear trajectory with low baseline scores that increased over time(curvilinear group),while 27.8％(n=393)maintained high,stable scores(linear group).Older age,higher marital satisfaction,and stronger social support were associated with a lower likelihood of belonging to the linear group(OR=0.96,0.94,0.89,re-spectively),while a personal or family history of depression increased this likelihood(OR=2.50,6.51).Conclusion:Trajectories of perinatal depressive symptoms vary significantly among individuals.The risk of persis-tent high-level symptoms is lowered by older age,stronger marital satisfaction,and greater social support,and heightened by a personal or family history of depression.

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

Purpose To investigate the value of automated segmentation technique for quantitative study of the volume of each subregion of medial temporal lobe epilepsy(MTLE)with hippocampal sclerosis(HS).Materials and Methods A total of 37 patients with unilateral HS diagnosed by MRI or pathologically confirmed in General Hospital of Ningxia Medical University from January 2021 to May 2023 were prospectively included,including 24 cases of left-sided HS(L-HS)and 13 cases of right-sided HS(R-HS),and 42 healthy volunteers matched in gender and age during the same period were included as a control group.All subjects underwent T1-weighted equal voxel three-dimensional magnetisation-prepared rapid gradient-echo(3D T1 MP-RAGE)scanning.3D T1 MP-RAGE was post-processed by Freesurfer V7 to obtain volume data of the hippocampus and its subregions.The volume data were normalized and the volume asymmetry index was calculated.Within-group and between-group comparisons were performed for standardized volumes of the hippocampus and its subregions,and between-group comparisons were performed for volume asymmetry index values.The diagnostic efficacy of the two indices was assessed and compared using the subject operating characteristic curve and area under the curve.Results The volumes of the hippocampus and its subregions on the affected side were smaller than those on the contralateral side in both the L-HS and R-HS groups,and the volumes of the left hippocampus and its subregions were smaller than those on the right side in the control group,and the differences were statistically significant(t/Z=-15.159-8.324,all P＜0.05).The volumes of the left side of the hippocampus and its subregions in the L-HS group were smaller than those of the left hippocampus and its subregions in the R-HS group and in the control group,and the volumes of the right side of the hippocampus and its subregions in the R-HS group were smaller than those of the L-HS group and the right hippocampus and its subregions of the control group,and the differences were statistically significant(P＜0.05).The differences in the volumes of the right side of the L-HS group and the left side of the R-HS group and the corresponding side of the control group were not statistically significant(P＞0.05).The differences in the volume asymmetry index values of the L-HS group compared with those of the R-HS group and the control group,and those of the R-HS group compared with those of the control group were all statistically significant(P＜0.05).Except for the diagnostic efficacy of volume asymmetry index values of the hippocampus and subiculum in the L-HS group,which was better than that of the volume,and the difference was statistically significant(Z=2.035,1.989,both P＜0.05),the comparison of the volume and volume asymmetry index values of each volume and volume asymmetry index value of the rest of the hippocampus and subregion was not statistically significant(P＞0.05).Conclusion The automatic segmentation technique is of great value for the quantitative study of hippocampus and its subregion volume in MTLE-HS,which can provide more accurate imaging reference for clinical practice.

Objective:To explore the heterogeneity in the trajectories ofperinatal depressive symptoms and identify the related factors.Methods:A longitudinal follow-up study was conducted from January 2020 to June 2021.Baseline information,marriage satisfaction and social support status were collected at enrolment.Perinatal de-pressive symptoms were measured using the Edinburgh Postnatal Depression Scale(EPDS)at five time-points from second trimester to three-months postpartum.A Latent Class Growth Model(LCGM)was used to identify sub-groups of perinatal depressive symptoms trajectories and logistic regression was applied to examine associated risk and protective factors.Results:Two latent depression trajectory subgroups were identified A majority(72.2％,n=1 023)followed a curvilinear trajectory with low baseline scores that increased over time(curvilinear group),while 27.8％(n=393)maintained high,stable scores(linear group).Older age,higher marital satisfaction,and stronger social support were associated with a lower likelihood of belonging to the linear group(OR=0.96,0.94,0.89,re-spectively),while a personal or family history of depression increased this likelihood(OR=2.50,6.51).Conclusion:Trajectories of perinatal depressive symptoms vary significantly among individuals.The risk of persis-tent high-level symptoms is lowered by older age,stronger marital satisfaction,and greater social support,and heightened by a personal or family history of depression.

Purpose To investigate the value of automated segmentation technique for quantitative study of the volume of each subregion of medial temporal lobe epilepsy(MTLE)with hippocampal sclerosis(HS).Materials and Methods A total of 37 patients with unilateral HS diagnosed by MRI or pathologically confirmed in General Hospital of Ningxia Medical University from January 2021 to May 2023 were prospectively included,including 24 cases of left-sided HS(L-HS)and 13 cases of right-sided HS(R-HS),and 42 healthy volunteers matched in gender and age during the same period were included as a control group.All subjects underwent T1-weighted equal voxel three-dimensional magnetisation-prepared rapid gradient-echo(3D T1 MP-RAGE)scanning.3D T1 MP-RAGE was post-processed by Freesurfer V7 to obtain volume data of the hippocampus and its subregions.The volume data were normalized and the volume asymmetry index was calculated.Within-group and between-group comparisons were performed for standardized volumes of the hippocampus and its subregions,and between-group comparisons were performed for volume asymmetry index values.The diagnostic efficacy of the two indices was assessed and compared using the subject operating characteristic curve and area under the curve.Results The volumes of the hippocampus and its subregions on the affected side were smaller than those on the contralateral side in both the L-HS and R-HS groups,and the volumes of the left hippocampus and its subregions were smaller than those on the right side in the control group,and the differences were statistically significant(t/Z=-15.159-8.324,all P＜0.05).The volumes of the left side of the hippocampus and its subregions in the L-HS group were smaller than those of the left hippocampus and its subregions in the R-HS group and in the control group,and the volumes of the right side of the hippocampus and its subregions in the R-HS group were smaller than those of the L-HS group and the right hippocampus and its subregions of the control group,and the differences were statistically significant(P＜0.05).The differences in the volumes of the right side of the L-HS group and the left side of the R-HS group and the corresponding side of the control group were not statistically significant(P＞0.05).The differences in the volume asymmetry index values of the L-HS group compared with those of the R-HS group and the control group,and those of the R-HS group compared with those of the control group were all statistically significant(P＜0.05).Except for the diagnostic efficacy of volume asymmetry index values of the hippocampus and subiculum in the L-HS group,which was better than that of the volume,and the difference was statistically significant(Z=2.035,1.989,both P＜0.05),the comparison of the volume and volume asymmetry index values of each volume and volume asymmetry index value of the rest of the hippocampus and subregion was not statistically significant(P＞0.05).Conclusion The automatic segmentation technique is of great value for the quantitative study of hippocampus and its subregion volume in MTLE-HS,which can provide more accurate imaging reference for clinical practice.

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

Objective To explore the value of automatic segmentation technique combined with neurite dispersion and density imaging(NODDI)for displaying volume and microstructure changes of hippocampal subregion in patients with hippocampal sclerosis medial temporal lobe epilepsy(mTLE-HS).Methods MRI data of 33 patients with left mTLE-HS(mTLE-HS group)and 35 healthy adults(control group)were retrospectively analyzed.The hippocampal subregions were automatically segmented using FreeSurfer software,the volume of cornu Ammonis(CA)1,CA2-3,CA4,granulose cell-dentate gyrus(GC-DG)and subiculum were measured,then the NODDI parameters of each subregion were obtained through post-processing.The intra-and inter-groups hippocampal subregion volumes and NODDI parameters were compared,and the correlations of parameters being significantly different with the onset age and disease courses were analyzed.Results The volume of hippocampal subregions in mTLE-HS group were all lower than those in control group(all P＜0.05).In mTLE-HS group,the neurite density index(NDI)of left CA1 and CA4 subregions were both lower,while the free-water isotropic volume fraction(fiso)of the left CA1 subregion was higher than those of the right side(all P＜0.05).The orientation dispersion index(ODI)of left CA1,CA2-3 and CA4 subregions,as well as NDI of left CA1,CA4 and GC-DG subregions in mTLE-HS group were all lower than those in control group(all P＜0.05),while fiso of left CA1,GC-DG and subiculum subregions in mTLE-HS group were all higher than those in control group(all P＜0.05).The volume of left hippocampal subregions in patients with mTLE-HS were all moderately positively correlated with the onset age(r=0.540-0.667,all P＜0.001)but weakly negatively correlated with disease courses(r=-0.492--0.386,all P＜0.05).NDI of left CA4 and GC-DG subregions in patients with mTLE-HS were both weakly negatively correlated with disease courses(r=-0.418,-0.388,both P＜0.05).Conclusion Automatic segmentation technique combined with NODDI could be used to display the volume and microstructure changes of mTLE-HS.NDI might be a biomarker of mTLE-HS being sensitive to progressive neuronal damage.

Human myelination begins in the fifth month of fetal development and continues after birth.Myelin development plays a key role in establishing and maintaining information conduction,coordination and communication within the brain,so prenatal quantitative assessment of myelin development is important.In recent years,many MRI techniques for myelin imaging have been developed and implemented,and quantitative MRI assessment of fetal myelin development has received increasing attention.In this review,we discuss the known structural and functional changes in the development of the myelin sheath of the fetal central nervous system,and review the research progress and future expectations of quantitative fetal MRI imaging.

Objective To explore the hippocampal(HC)microstructural changes in patients with unilateral temporal lobe epilepsy(TLE)by neurite orientation dispersion and density imaging(NODDI).Methods The NODDI indexes of the whole HC and HC subregions of temporal lobe epilepsy with hippocampal sclerosis(TLE-HS)patients,non-HS patients and healthy controls(control group)were calculated.The differences of NODDI indexes among and within the three groups were compared,and the correlation between the difference indexes and the clinical characteristics of the patients was analyzed.Results A total of 47 patients with TLE(27 cases of TLE-HS,20 cases of non-HS)and 22 cases of healthy controls were enrolled.In the TLE-HS group,the free-water isotropic vol-ume fraction(fiso)values of the HC and granular cell layer of dentate gyrus(GC-DG)subregions of the affected side were signifi-cantly higher than those of the contralateral side;the orientation dispersion index(ODI)values of the CA1 and CA4 subregions were significantly lower than those of the contralateral side;and the neurite density index(NDI)values of the HC,CA1,CA2-3,CA4 and GC-DG subregions of the affected side decreased significantly.There was no significant difference between the affected side and the contralateral side in the non-HS group.The fiso values of the HC and GC-DG subregions of the affected side in the TLE-HS group were significantly higher than those in the control group,the ODI values of the HC CA1 subregions of the affected side in the TLE-HS group were significantly lower than those in the control group and the non-HS group,the NDI values of the HC and subiculum(Sub),CA1,CA4 and GC-DG subregions of the affected side in the TLE-HS group were significantly lower than those in the con-trol group,and the NDI values of the HC and CA1,CA4 and GC-DG subregions of the affected side in the non-HS group were significantly lower than those in the control group.In the TLE-HS group,the NDI value of the HC CA4 subregion of the affected side was negatively correlated with the disease course,but there was no clear correlation between other subregion variables and disease course,onset frequency and duration of single onset.Conclusion NODDI technique has the ability to detect the microstructural changes of HC in patients with TLE,among which NDI is more likely to highlight neuronal damage and fiber reorganization in patients with TLE.

ObjectiveTo analyze the epidemiological characteristics of hand, foot, and mouth disease (HFMD) in Zhangjiakou City, Hebei Province from 2013 to 2022, so as to provide a basis for HFMD prevention, control, and evaluation of intervention effectiveness. MethodsHFMD data of Zhangjiakou City from 2013 to 2022 were collected. Descriptive statistics and the Joinpoint regression model were used to analyze the trend of the epidemic. ResultsThe incidence of HFMD in Zhangjiakou was predicted to decrease with APC=-14.86% in 2013‒2022. The top five regions with the highest incidence showed varying trends: Qiaodong District (APC=-26.21%), Qiaoxi District (APC=-18.29%), Xuanhua District (APC=-14.28%), Chicheng District (APC=-18.68%), and Zhuolu County (APC=51.43% in 2013‒2016, APC=-14.27% in 2016‒2022), indicating a downward trend. Three age groups showed an upward trend in incidence: the 0-year-old group (APC=-42.82% in 2013‒2016, APC=16.54% in 2016‒2022), the 7-year-old group (AAPC=9.60%), and the 9-year-old group (AAPC=12.76%). HFMD cases occurred throughout the year, peaking from June to August, with July being the most significant month. The male-to-female ratio was1.40∶1, with no statistical difference (χ²=5.932, P>0.05). A high incidence was in children under 5 years old, with those aged 1‒4 years being the main affected group. In terms of occupation, scattered children (6 245 cases, 57.65%) and preschool children (3 653 cases, 33.72%) were the most affected. A total of 504 laboratory-confirmed cases were reported, with a detection rate of 4.65% (504/10 832). The composition of confirmed cases included CoxA 16 (193 cases, 38.29%), EV71 (75 cases, 14.88%), and other enteroviruses (236 cases, 46.83%). ConclusionFrom 2013 to 2022, HFMD in Zhangjiakou City showed a downward trend with clear seasonal, regional, and occupational distributions. It is suggested that epidemic monitoring should be strengthened, etiological detection should be enhanced, and education efforts in key areas should be improved. High-incidence counties should analyze data and conduct risk assessments effectively.