AIM: To compare the efficacy of highly aspherical lenslets(HAL), defocus incorporated multiple segments(DIMS), and single-vision spectacle lenses(SVL)in slowing myopia progression in children and adolescents.

METHODS: In this retrospective cohort study, myopic children and adolescents aged 6-16 y who were prescribed spectacle lenses at the hospital between January 2023 and June 2023 were included. Participants were divided into the HAL, DIMS, and SVL groups according to the correction modality voluntarily selected by participants and their guardians. The follow-up duration was 12 mo. After 12 mo of wear, changes from baseline in sphere, cylinder, spherical equivalent(SE), axial length(AL), flat corneal curvature(K1), steep corneal curvature(K2), mean corneal curvature, and binocular visual function \〖binocular cross-cylinder(BCC), negative/positive relative accommodation(NRA/PRA)\〗 were compared among the three groups after 12-month spectacle wear. Three groups were further stratified by age into age≤10 y and age>10 y subgroups to explore the effect of age on myopia control efficacy of defocus lenses.

RESULTS: A total of 159 myopic participants(159 eyes; only the right eye was included for each subject)were enrolled. In the HAL group(55 participants), there were 24 males and 31 females, with a mean age of 10.07±2.14 y. The DIMS group consisted of 60 participants(33 males, 27 females), with a mean age of 10.02±1.88 y. The SVL group included 44 participants(21 males, 23 females), with a mean age of 10.59±1.93 y. There were no significant differences in K1, K2, mean corneal curvature, NRA, BCC, and PRA among the three groups after 12-month spectacle wear(all P>0.05). There were statistically significant differences in the changes in sphere, SE, and AL(all P<0.05). The changes in sphere, cylinder, SE, and AL in the HAL and DIMS groups were significantly lower than those in the SVL group(all P<0.0167). The DIMS group showed a significantly smaller cylinder progression than the SVL group(P<0.0167). In participants aged≤10 y, the change in spherical power in the HAL group was significantly smaller than those in the DIMS group and SVL group after 12-month spectacle wear(all P<0.0167). The change in cylindrical power in the DIMS group was smaller than that in the SVL group(all P<0.0167). Among participants aged>10 y, the changes in spherical power, SE, and AL in both the HAL group and DIMS group were significantly smaller than those in the SVL group after 12-month spectacle wear(all P<0.0167).

CONCLUSION: Both HAL and DIMS lenses can effectively slow the progression of refractive error and AL elongation in children and adolescents, without significant adverse effects on binocular visual function. Among children≤10 y, HAL lenses yield superior spherical power control, whereas DIMS lenses provide better astigmatism control than SVL.

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

Hepatolenticular degeneration is a rare disease,and the number of cases of primary liver cancer occurring on the basis of liver cirrhosis caused by hepatolenticular degeneration is very small.This paper reports a case of hepatolenticular degeneration with primary liver cancer,and then reviews and summarizes current cases of this disease both domestically and internationally.
Humans ; Hepatolenticular Degeneration/complications* ; Liver Neoplasms/complications*

Xanthine oxidase (XO) is an important therapeutic target for the treatment of hyperuricemia and gout. Based on the previously identified potent XO inhibitor 1, seventeen oxadiazoles and their ring-opening analogues were designed and synthesized via the bioisostere replacement strategy. Among them, compounds 2l, 2n, and 3b showed obvious XO inhibitory activity at the concentration of 10 μmol·L^-1, and compound 3b exhibited an IC₅₀ value of 1.45 μmol·L^-1.

BACKGROUND: Our understanding of the correlation between postdischarge cancer and mortality in patients with coronary artery disease (CAD) remains incomplete. The aim of this study was to investigate the relationships between postdischarge cancers and all-cause mortality and cardiovascular mortality in CAD patients. METHODS: In this retrospective cohort study, 25% of CAD patients without prior cancer history who underwent coronary artery angiography between January 1, 2011 and December 31, 2015, were randomly enrolled using SPSS 26.0. Patients were monitored for the incidence of postdischarge cancer, which was defined as cancer diagnosed after the index hospitalization, survival status and cause of death. Cox regression analysis was used to explore the association between postdischarge cancer and all-cause mortality and cardiovascular mortality in CAD patients. RESULTS: A total of 4085 patients were included in the final analysis. During a median follow-up period of 8 years, 174 patients (4.3%) developed postdischarge cancer, and 343 patients (8.4%) died. A total of 173 patients died from cardiovascular diseases. Postdischarge cancer was associated with increased all-cause mortality risk (HR = 2.653, 95% CI: 1.727-4.076, P < 0.001) and cardiovascular mortality risk (HR = 2.756, 95% CI: 1.470-5.167, P = 0.002). Postdischarge lung cancer (HR = 5.497, 95% CI: 2.922-10.343, P < 0.001) and gastrointestinal cancer (HR = 1.984, 95% CI: 1.049-3.750, P = 0.035) were associated with all-cause mortality in CAD patients. Postdischarge lung cancer was significantly associated with cardiovascular death in CAD patients (HR = 4.979, 95% CI: 2.114-11.728, P < 0.001), and cardiovascular death was not significantly correlated with gastrointestinal cancer or other types of cancer. CONCLUSIONS Postdischarge cancer was associated with all-cause mortality and cardiovascular mortality in CAD patients. Compared with other cancers, postdischarge lung cancer had a more significant effect on all-cause mortality and cardiovascular mortality in CAD patients.

OBJECTIVE: To investigate the effects of astragaloside IV (AS-IV) on podocyte injury of diabetic nephropathy (DN) and reveal its potential mechanism. METHODS: In in vitro experiment, podocytes were divided into 4 groups, normal, high glucose (HG), inositol-requiring enzyme 1 (IRE-1) α activator (HG+thapsigargin 1 µmol/L), and IRE-1α inhibitor (HG+STF-083010, 20 µmol/L) groups. Additionally, podocytes were divided into 4 groups, including normal, HG, AS-IV (HG+AS-IV 20 µmol/L), and IRE-1α inhibitor (HG+STF-083010, 20 µmol/L) groups, respectively. After 24 h treatment, the morphology of podocytes and endoplasmic reticulum (ER) was observed by electron microscopy. The expressions of glucose-regulated protein 78 (GRP78) and IRE-1α were detected by cellular immunofluorescence. In in vivo experiment, DN rat model was established via a consecutive 3-day intraperitoneal streptozotocin (STZ) injections. A total of 40 rats were assigned into the normal, DN, AS-IV [AS-IV 40 mg/(kg·d)], and IRE-1α inhibitor [STF-083010, 10 mg/(kg·d)] groups (n=10), respectively. The general condition, 24-h urine volume, random blood glucose, urinary protein excretion rate (UAER), urea nitrogen (BUN), and serum creatinine (SCr) levels of rats were measured after 8 weeks of intervention. Pathological changes in the renal tissue were observed by hematoxylin and eosin (HE) staining. Quantitative reverse transcription-polymerase chain reaction (RT-PCR) and Western blot were used to detect the expressions of GRP78, IRE-1α, nuclear factor kappa Bp65 (NF-κBp65), interleukin (IL)-1β, NLR family pyrin domain containing 3 (NLRP3), caspase-1, gasdermin D-N (GSDMD-N), and nephrin at the mRNA and protein levels in vivo and in vitro, respectively. RESULTS: Cytoplasmic vacuolation and ER swelling were observed in the HG and IRE-1α activator groups. Podocyte morphology and ER expansion were improved in AS-IV and IRE-1α inhibitor groups compared with HG group. Cellular immunofluorescence showed that compared with the normal group, the fluorescence intensity of GRP78 and IRE-1α in the HG and IRE-1α activator groups were significantly increased whereas decreased in AS-IV and IRE-1α inhibitor groups (P<0.05). Compared with the normal group, the mRNA and protein expressions of GRP78, IRE-1α, NF-κ Bp65, IL-1β, NLRP3, caspase-1 and GSDMD-N in the HG group was increased (P<0.05). Compared with HG group, the expression of above indices was decreased in the AS-IV and IRE-1α inhibitor groups, and the expression in the IRE-1α activator group was increased (P<0.05). The expression of nephrin was decreased in the HG group, and increased in AS-IV and IRE-1α inhibitor groups (P<0.05). The in vivo experiment results revealed that compared to the normal group, the levels of blood glucose, triglyceride, total cholesterol, BUN, blood creatinine and urinary protein in the DN group were higher (P<0.05). Compared with DN group, the above indices in AS-IV and IRE-1α inhibitor groups were decreased (P<0.05). HE staining revealed glomerular hypertrophy, mesangial widening and mesangial cell proliferation in the renal tissue of the DN group. Compared with the DN group, the above pathological changes in renal tissue of AS-IV and IRE-1α inhibitor groups were alleviated. Quantitative RT-PCR and Western blot results of GRP78, IRE-1α, NF-κ Bp65, IL-1β, NLRP3, caspase-1 and GSDMD-N were consistent with immunofluorescence analysis. CONCLUSION AS-IV could reduce ERS and inflammation, improve podocyte pyroptosis, thus exerting a podocyte-protective effect in DN, through regulating IRE-1α/NF-κ B/NLRP3 signaling pathway.
Podocytes/metabolism* ; Animals ; Diabetic Nephropathies/metabolism* ; Saponins/therapeutic use* ; Triterpenes/therapeutic use* ; Signal Transduction/drug effects* ; NF-kappa B/metabolism* ; Protein Serine-Threonine Kinases/metabolism* ; Male ; Rats, Sprague-Dawley ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Endoribonucleases/metabolism* ; Endoplasmic Reticulum Chaperone BiP ; Rats ; Diabetes Mellitus, Experimental/complications* ; Endoplasmic Reticulum/metabolism* ; Multienzyme Complexes

Objective:To examine the manifestations and causes of administrative burden among primary healthcare professionals,and to explore its impact on job burnout through the mediating role of role conflict,providing theoretical and empirical support for governance-level burden-reduction strategies.Methods:An exploratory sequential mixed-methods design was employed,focusing on primary healthcare professionals in Shandong Province.In the first phase,in-depth interviews were conducted with 175 participants;in the second phase,a questionnaire survey of 1,096 participants and follow-up interviews with 107 participants were carried out.Results:The proportions of respondents who reported"heavy"or"very heavy"burdens were 62.7%for inspection,54.8%for documentation,51.8%for reporting,and 24.4%for meetings.Structural equation modeling showed that administrative burden had a direct effect on job burnout(0.150)and an indirect effect through role conflict(0.093).Qualitative findings further indicated that administrative burden largely stemmed from public health traceability requirements and medical insurance policies,and operated through both resource-based and value-based conflicts.Conclusions:Primary healthcare professionals face considerable administrative burdens,which may heighten job burnout through role conflict.Governance reforms should optimize inspection and assessment,streamline data reporting,refine record-keeping,and promote collaborative governance to break the chain of institutional pressure leading to burnout.

OBJECTIVE: To investigate the clinical features and prognosis of central nervous system (CNS) invasion in peripheral T-cell lymphoma (PTCL) and construct a risk prediction model for CNS invasion. METHODS: Clinical data of 395 patients with PTCL diagnosed and treated in the First Affiliated Hospital of Zhengzhou University from 1st January 2013 to 31st December 2022 were analyzed retrospectively. RESULTS: The median follow-up time of 395 PTCL patients was 24(1-143) months. There were 13 patients diagnosed CNS invasion, and the incidence was 3.3%. The risk of CNS invasion varied according to pathological subtype. The incidence of CNS invasion in patients with anaplastic large cell lymphoma (ALCL) was significantly higher than in patients with angioimmunoblastic T-cell lymphoma (AITL) (P <0.05). The median overall survival was significantly shorter in patients with CNS invasion than in those without CNS involvement, with a median survival time of 2.4(0.6-127) months after diagnosis of CNS invasion. The results of univariate and multivariate analysis showed that more than 1 extranodal involvement (HR=4.486, 95%CI : 1.166-17.264, P =0.029), ALCL subtype (HR=9.022, 95%CI : 2.289-35.557, P =0.002) and ECOG PS >1 (HR=15.890, 95%CI : 4.409-57.262, P <0.001) were independent risk factors for CNS invasion in PTCL patients. Each of these risk factors was assigned a value of 1 point and a new prediction model was constructed. It could stratify the patients into three distinct groups: low-risk group (0-1 point), intermediate-risk group (2 points) and high-risk group (3 points). The 1-year cumulative incidence of CNS invasion in the high-risk group was as high as 50.0%. Further evaluation of the model showed good discrimination and accuracy, and the consistency index was 0.913 (95%CI : 0.843-0.984). CONCLUSION The new model shows a precise risk assessment for CNS invasion prediction, while its specificity and sensitivity need further data validation.
Humans ; Lymphoma, T-Cell, Peripheral/pathology* ; Prognosis ; Retrospective Studies ; Central Nervous System Neoplasms/pathology* ; Neoplasm Invasiveness ; Male ; Female ; Central Nervous System/pathology* ; Middle Aged ; Adult

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.