AIM: To screen and analyze the influencing factors of myopia among primary and secondary school students and establish a predictive model to provide ideas for the prevention and control measures of myopia among children and adolescents.METHODS:A total of 1 759 primary and secondary school students from 2 primary schools, 2 junior high schools, 2 senior high schools and 1 vocational high school in the urban area of Qingdao were sampled by means of stratified cluster sampling in September 2023. Vision screening and a questionnaire survey on influencing factors were carried out based on machine learning algorithms. The screening and determination were mainly conducted in accordance with the Standard Logarithmic Visual Acuity Chart(GB/T11533-2011)and the Specifications for Screening Myopia in Children and Adolescents. The influencing factors of myopia were analyzed and a prediction model was developed based on the machine learning algorithms LASSO in combination with XGBoost, and visualization was achieved through an interactive Nomogram. Statistical analysis was performed using R statistical software version 4.3.3.RESULTS:The screening prevalence of myopia among primary and secondary school students in the urban area of Qingdao was 70.61%(1 242 cases). The optimal predictive variables for screening were grade, gender, whether parents were myopic, daily indoor sedentary time, appropriate distance between eyes and books during reading and writing, daily sleep time, distance between eyes and TV screen when watching TV/playing video games exceeding 3 meters, the playground during breaks, total duration of tutorial classes, how often eyes are rested during near work, daily computer usage time, and average daily homework time after school, totaling 12 influencing factors. The AUCs of the training set and test set were 0.770(95%CI:0.751-0.789)and 0.732(95%CI:0.714-0.750), respectively.CONCLUSION: A machine learning-based prediction model was developed and validated to predict the risk of myopia onset in primary and secondary school students, accompanied by effective visualization techniques.

The prevalence of adolescent depressive symptoms has been rising, and maternal depression is a key predictor. This review synthesizes evidence on mechanisms of influence and on intervention research. The intergenerational transmission of risk from maternal depression appears more pronounced than that associated with paternal depression. At the biological level, genetic susceptibility and neurodevelopmental alterations underpin intergenerational transmission; at the social level, negative parenting practices and stressful family environments create a vicious cycle; at the psychological level, deficits in emotion regulation and insecure attachment amplify vulnerability to depression. Family-based interventions, including cognitive-behavioral therapy and family systems therapy, can mitigate intergenerational transmission. However, more longitudinal research is needed, and future work may integrate digital technologies to develop structured intervention protocols.
Humans ; Female ; Adolescent ; Depression/psychology* ; Family Therapy ; Mothers/psychology*

OBJECTIVES: To investigate the association between maternal depressive symptoms and adolescent suicidal ideation, and to examine the chain mediating roles of childhood trauma and ineffectiveness. METHODS: A cross-sectional online survey was administered by school psychologists to 4 157 mother-adolescent pairs from middle schools in Shanghai and Henan, China. Measures included the Center for Epidemiological Studies Depression Scale, the Childhood Trauma Questionnaire, and the Children's Depression Inventory. Using Bootstrap method to examine the chain mediating effect of childhood trauma and ineffectiveness on the relationship between maternal depression symptoms and adolescent suicidal ideation. RESULTS: The prevalence of maternal depressive symptoms was 17.68% (735/4 157); among adolescents, the prevalence of depressive symptoms was 15.49% (644/4 157), and suicidal ideation was 28.19% (1 172/4 157). Adolescent depressive symptoms and suicidal ideation were positively correlated with maternal depressive symptoms, childhood trauma, and ineffectiveness (all P<0.01). Childhood trauma significantly mediated the association between maternal and adolescent depressive symptoms (95%CI: 0.046 9-0.077 2). The chain mediation of childhood trauma and ineffectiveness in the association between maternal depressive symptoms and adolescent suicidal ideation was also significant (95%CI: 0.000 7-0.001 3). CONCLUSIONS Higher maternal depressive symptom levels are associated with a greater likelihood of adolescents' exposure to childhood trauma, which increases adolescents' ineffectiveness and, in turn, is associated with suicidal ideation. This chain effect has important implications for social interventions targeting adolescent depression.
Humans ; Suicidal Ideation ; Adolescent ; Female ; Depression/etiology* ; Cross-Sectional Studies ; Mothers/psychology* ; Male ; Child ; Adult

As the brain's resident immune cells, microglia perform crucial functions such as phagocytosis, neuronal network maintenance, and injury restoration by adopting various phenotypes. Dynamic imaging of these phenotypes is essential for accessing brain diseases and therapeutic responses. Although numerous probes are available for imaging pro-inflammatory microglia, no PET tracers have been developed specifically to visualize anti-inflammatory microglia. In this study, we present an ¹⁸F-labeled PET tracer (QTFT) that targets the P2Y₁₂, a receptor highly expressed on anti-inflammatory microglia. [¹⁸F]QTFT exhibited high binding affinity to the P2Y₁₂ (14.43 nmol/L) and superior blood-brain barrier permeability compared to other candidates. Micro-PET imaging in IL-4-induced neuroinflammation models showed higher [¹⁸F]QTFT uptake in lesions compared to the contralateral normal brain tissues. Importantly, this specific uptake could be blocked by QTFT or a P2Y₁₂ antagonist. Furthermore, [¹⁸F]QTFT visualized brain lesions in mouse models of epilepsy, glioma, and aging by targeting the aberrantly expressed P2Y₁₂ in anti-inflammatory microglia. In a pilot clinical study, [¹⁸F]QTFT successfully located epileptic foci, showing enhanced radioactive signals in a patient with epilepsy. Collectively, these studies suggest that [¹⁸F]QTFT could serve as a valuable diagnostic tool for imaging various brain disorders by targeting P2Y₁₂ overexpressed in anti-inflammatory microglia.

Objective To explore the construction and verification of the classification model for the five properties of traditional Chinese medicine:warm,cool,cold,hot,and neutral.Methods Urine samples of mice after taking Chinese medicine of different properties were selected as research objects,and Raman spectroscopy-related technology was used for detection.The obtained data set was classified into training set and test set,and the classification model was constructed using four machine learning methods:random forest,extreme gradient boosting,support vector machine,and logistic regression.The model performance was evaluated using precision,recall,F1 score,and accuracy.Results A total of 4 888 sets of spectra were collected in this study,of which 80%,totaling 3 910 sets of spectral data,were used to build the model,and the remaining 20%,totaling 978 sets of spectral data,were used to test model performance.The accuracy of the random forest model was 92%,the extreme gradient boosting model was 87%,the support vector machine model was 83%,and the logistic regression model was 75%.The Raman shifts with the highest classification weights were 872,1 012,1 108,1 190 and 1 668 cm-1.Conclusion Raman spectroscopy combined with machine learning algorithms can be used to classify the five medicinal properties of traditional Chinese medicine,among which the random forest model has the best effect.

Cerebrocardiac syndrome refers to secondary cardiac damage caused by various craniocere-bral injury lesions,which can exacerbate existing heart disease.In the practice of forensic pathology,cerebral-cardiac interaction is often ignored in cases of death with a short time after craniocerebral in-jury,especially those with underlying heart disease.This article reviews the pathogenesis of cerebrocar-diac syndrome by summarizing recent research results of cerebrocardiac syndrome at home and abroad and discusses its significance in the field of forensic medicine.The aim is to provide assistance for fo-rensic medicine practice of cerebrocardiac syndrome.

Objective To explore the effect of exposure to noise of 3.0T magnetic resonance imaging(MRI)on children's cochlear function.Methods We prospectively recruited 72 children who underwent cranial MRI examination at our hospital from May to November 2018;3M earplugs and sponge mats were used for hearing protection during MRI scanning.Noise level(dBA)of each MRI sequence was detected with a nonmagnetic microphone and a sound level meter.Distortion product otoacoustic emissions(DPOAE)test at 2-7 kHz was performed 24 hours before and 30 minutes after the MRI examination.Paired t-test or Wilcoxon signed-rank test was used to analyze differences in DPOAE amplitude before and after the MRI examination.Results The average noise level of MRI measured in the study was(107.7±3.92)dBA.Compared with that before the MRI examination,the DPOAE amplitude(dB)changed little after the MRI examination;the range of amplitude differences in each age group was as follows:left ear(-0.24-1.10)and right ear(-0.24-0.74)in the 0-1 year-old group;left ear(-0.07-0.59)and right ear(-0.57-0.75)in the 2-5 year-old group;left ear(-0.36-0.44)and right ear(-0.30-0.57)in the 6-12 year-old group.No statistically significant difference was found(correction P＞0.05).Conclusion No potential impact of 3.0T MRI noise on children's cochlear function was observed under routine hearing protection.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal hematopoietic stem cell disease caused by abnormal expression of glycosylphosphatidylinositol (GPI) on the cell membrane due to mutations in the phosphatidylinositol glycan class A(PIGA) gene. It is commonly characterized by intravascular hemolysis, repeated thrombosis, and bone marrow failure, as well as multiple systemic involvement symptoms such as renal dysfunction, pulmonary hypertension, swallowing difficulties, chest pain, abdominal pain, and erectile dysfunction. Due to the rarity of PNH and its strong heterogeneity in clinical manifestations, multidisciplinary collaboration is often required for diagnosis and treatment. Peking Union Medical College Hospital, relying on the rare disease diagnosis and treatment platform, has invited multidisciplinary clinical experts to form a unified opinion on the diagnosis and treatment of PNH, and formulated the Expert Consensus of Multidisciplinary Diagnosis and Treatment for Paroxysmal Nocturnal Hemoglobinuria (2024), with the hope of promoting the standardization of PNH diagnosis and treatment.

Objective To analyze the factors affecting the prognosis of patients with knee osteoarthritis,and to construct a nomogram prediction model in conjunction with multi-dimensional clinical indicators.Methods The clinical data of 234 pa-tients with knee osteoarthritis who were treated in our hospital from January 2015 to June 2021 were retrospectively analyzed,including 126 males and 108 females;age more than 60 years old for 135 cases,age less than 60 years old for 99 cases.Lysholm knee function score was used to evaluate the prognosis of the patients,and the patients were divided into good progno-sis group for 155 patients and poor prognosis group for 79 patients according to the prognosis.The clinical data of the subjects in the experimental cohort were analyzed by single factor and multiple factors.The patients were divided into experimental co-hort and verification cohort,the results of the multiple factor analysis were visualized to obtain a nomogram prediction model,the receiver operating characteristic curve(ROC),calibration curve and decision curve were used to evaluate the model's dis-crimination,accuracy and clinical benefit rate.Results The results of multivariate analysis showed that smoking,pre-treatment K-L grades of Ⅲto Ⅳ,and high levels of interleukin 6(IL-6)and matrix metallo proteinase-3(MMP-3)were risk factors for the prognosis of patients with knee osteoarthritis.ROC test results showed that the area under the curve of the nomogram model in the experimental cohort and validation cohort was 0.806[95％CI(0.742,0.866)]and 0.786[(95％CI(0.678,0.893)],re-spectively.The results of the calibration curve showed that the Brier values of the experimental cohort and verification cohort were 0.151 points and 0.134 points,respectively.When the threshold probability value in the decision curve was set to 31％,the clinical benefit rates of the experimental cohort and validation cohort were 51％and 56％,respectively.Conclusion The prognostic model of patients with knee osteoarthritis constructed based on multi-dimensional clinical data has both theoretical and practical significance,and can provide a reference for taking targeted measures to improve the prognosis of patients.