BackgroundThe middle school stage represents a crucial period for the development of borderline personality features. Negative parenting styles and emotional regulation strategies are associated with the formation of borderline personality features. However， the moderating role of emotional regulation strategies between negative parenting styles and borderline personality features among middle school students remains unclear. ObjectiveTo explore the moderating influence of emotional regulation strategies in the relationship between negative parenting styles and borderline personality features among middle school students， and to provide references for the intervention of borderline personality features. MethodsIn October 2023， a total of 5 965 middle school students from three middle schools in Nanning， Guangxi Zhuang Autonomous Region were selected by cluster sampling， and assessed by the Borderline Personality Features Scale for Children （BPFS-C）， the Egna Minnen Barndoms Uppfostran （EMBU）， and the Emotion Regulation Questionnaire-Chinese Revised Version （ERQ-CRV）. Pearson correlation analysis was used to test the correlation between the scores of each scale， and the model 1 of the Process macro program was used to conduct the moderating effect test. ResultsA total of 5 572 middle school students （93.41%） completed this study， and 1 388 of them （24.91%） were identified as having high borderline personality features. The BPFS-C score of middle school students was positively correlated with the score of the negative parenting style dimension of EMBU （r=0.367， P<0.01）， negatively correlated with the score of the cognitive reappraisal dimension of ERQ-CRV （r=-0.168， P<0.01）， and positively correlated with the score of the expression inhibition dimension of ERQ-CRV （r=0.344， P<0.01）. Cognitive reappraisal played a negative moderating effect between negative parenting styles and borderline personality features （β=-0.072， 95% CI： -0.104–-0.041， P<0.01）， while expressive suppression played a positive moderating effect （β=0.076， 95% CI： 0.055–0.097， P<0.01）. ConclusionCognitive reappraisal strategy may help mitigate the negative influence of negative parenting styles on middle school students' borderline personality features， while expressive suppression may exacerbate the harm of negative parenting styles to the borderline personality features of middle school students.

ObjectiveTo reveal the mechanism of Zuogui Jiangtang Jieyu prescription against damage to hippocampal synaptic microenvironment via suppressing glutamate receptor 2 （GluR2）/Parkin signal-mediated mitophagy in rats with diabetes-related depression （DD）. MethodsEighty male SD rats underwent adaptive feeding for 5 days before the study. Ten rats were randomly assigned to the normal group. The model of DD rats was established with the rest by 2-week high-fat diet + streptozotocin （STZ） tail intravenous injection + 28 days of chronic unpredictable mild stress （CUMS） combined with isolation. The rats were randomly divided into a normal group， a model group， a GluR2 blocker group （5 μg·kg^-1）， a GluR2 agonist group （10 μg·kg^-1）， a metformin + fluoxetine group （0.18 g·kg^-1 metformin + 1.8 mg·kg^-1 fluoxetine）， and high- and low-dose Zuogui Jiangtang Jieyu prescription groups （20.52 and 10.26 g·kg^-1， respectively）. The rats in the GluR2 blocker group and the GluR2 agonist group were continuously injected with CNQX and Cl-HIBO in the dentate gyrus of the hippocampus once a week starting from stress modeling， respectively， while the metformin + fluoxetine group and the high- and low-dose Zuogui Jiangtang Jieyu prescription groups were continuously given intragastric administration for 28 d at the same time of stress modeling. Depression-like behavior was evaluated by open field and forced swimming experiments. The levels of serum insulin and adenosine triphosphate （ATP） in hippocampus were detected by biochemical analysis. The levels of 5-hydroxytryptamine （5-HT） and dopamine （DA） in hippocampus were detected by enzyme-linked immunosorbent assay （ELISA）. The autophagosomes of hippocampal neurons were observed by transmission electron microscopy. The morphology and structure of dendrites and spines of hippocampal neurons were evaluated by Golgi staining. Western blot detected the expression levels of GluR2 and Parkin proteins in hippocampus. The expression levels of GluR2， Parkin， regulating synaptic membrane exocytosis protein 3 （RIMS3）， and postsynaptic density protein 95 （PSD95） in the dentate gyrus of the hippocampus were detected by immunofluorescence. ResultsCompared with the normal group， the model group exhibited reduced total activity distance in the open field and increased immobility time in forced swimming （P<0.01）， lowered levels of serum insulin and ATP， 5-HT， and DA in hippocampus （P<0.01）， increased autophagosomes of hippocampal neurons， significantly damaged morphology and structure of dendrites and spines of hippocampal neurons， decreased expression levels of GluR2， RIMS3， and PSD95 in hippocampus， and an increased Parkin expression level （P<0.05， P<0.01）. Compared with the model group， the GluR2 blocker group and the GluR2 agonist group showed aggravation and alleviation of the above abnormal changes， respectively （P<0.05， P<0.01）. The above depression-like behavior was significantly improved in the high- and low-dose Zuogui Jiangtang Jieyu prescription groups to different degrees. Specifically， the two groups saw elevated levels of serum insulin and ATP， 5-HT， and DA in hippocampus （P<0.05， P<0.01）， restrained increase in autophagosomes and damage to morphology and structure of dendrites and spines of hippocampal neurons， up-regulated protein expression levels of GluR2， RIMS3， and PSD95， and down-regulated Parkin expression level （P<0.05， P<0.01）. ConclusionZuogui Jiangtong Jieyu prescription can ameliorate the mitophagy-mediated damage to hippocampal synaptic microenvironment in DD rats， the mechanism of which might be related to the regulation of GluR2/Parkin signaling pathway.

AIM: To observe the changes of retinal nerve fiber layer(RNFL)thickness and radial peripheral capillary(RPC)density in patients with unilateral branch retinal vein occlusion(BRVO), and further analyze the correlation between RPC density and RNFL thickness.METHODS: Observational study. Totally 37 patients with unilateral BRVO diagnosed at the ophthalmology department of First Hospital of Qinhuangdao from October 2020 to January 2022 were selected, the 37 affected eyes were the unilateral BRVO group, and 37 fellow healthy eyes were the contralateral unaffected group, and 35 healthy individuals(35 right eyes were selected)without ocular diseases during the same period were selected as the normal control group. The best corrected visual acuity, intraocular pressure, anterior segment, fundus and optical coherence tomography angiography(OCTA)were examined in both eyes of all BRVO patients and healthy individuals. The central macular thickness(CMT), the RNFL thickness, and the optic disc-AV crossing distance(DAVD)were measured by built-in software of the OCTA equipment. The optimized U-net algorithm was used to eliminate the large blood vessels, and then the RPC density was calculated. The CMT, RNFL thickness and RPC density were compared among the three groups. And the correlations of the RPC density with the CMT, RNFL thickness, and the DAVD were investigated.RESULTS: Compared with the contralateral unaffected group and the normal control group, the CMT and the RNFL thickness were significantly thickened in the unilateral BRVO group(all P<0.05); there were no statistical differences in the CMT and the RNFL thickness between the contralateral unaffected group and the normal control group(all P>0.05). The RPC density in the unilateral BRVO group increased compared with the contralateral unaffected group and decreased compared with the normal control group, but there was no statistically difference(all P>0.05). However, the RPC density in the contralateral unaffected group decreased compared with the normal control group(P<0.05). The RPC density in the unilateral BRVO group was not correlated with the CMT(P=0.960), but positively correlated with the RNFL thickness(r=0.401, P=0.014)and negatively correlated with the DAVD(r=-0.339, P=0.040).CONCLUSION: The RNFL thickened significantly and the RPC density did not change significantly in the optic disc area of BRVO patients. The RPC density is positively correlated with the RNFL thickness, indicating that the RNFL thickness can be used as a monitoring indicator to analyze and study the damage degree of the RPC density.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective To investigate the trends in the global burden due to cystic echinococcosis from 1990 to 2021, and to predict the global burden of cystic echinococcosis from 2022 to 2035, so as to provide insights into formulation of the cystic echinococcosis control strategy. Methods The global age-standardized prevalence, mortality, disability-adjusted life years (DALYs) rates and their 95% uncertainty intervals (UI) of cystic echinococcosis from 1990 to 2021 were captured from the Global Burden of Disease Study 2021 (GBD 2021) database, and the trends in the global burden of cystic echinococcosis from 1990 to 2021 were analyzed using the Joinpoint regression model. The associations between the global burden of cystic echinococcosis and socio-demographic index (SDI) were examined using a smoothing spline model and frontier analysis, and the global burden of cystic echinococcosis was projected from 2022 to 2035 using the Bayesian age-period-cohort (BAPC) model. Results The global agestandardized prevalence, mortality and DALYs rates of cystic echinococcosis were 7.69/10⁵ [95% UI: (6.27/10⁵, 9.51/10⁵)], 0.02/10⁵ [95% UI: (0.01/10⁵, 0.02/10⁵)], and 1.32/10⁵ [95% UI: (0.99/10⁵, 1.69/10⁵)] in 2021. The global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a rise by 0.14% per year from 1990 to 2021, and the global age-standardized mortality and DALYs rates of cystic echinococcosis appeared a tendency towards a decline by 4.68% and 4.01% per year from 1990 to 2021, respectively. Joinpoint regression analysis showed that global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a decline from 1990 to 2000 [annual percent change (APC) = −0.66%, 95% confidence interval (CI): (−0.70%, −0.61%)] and from 2005 to 2015 [APC = −0.88%, 95% CI: (−0.93%, −0.82%)], and towards a rise from 2000 to 2005 [APC = 3.68%, 95% CI: (3.49%, 3.87%)] and from 2015 to 2021 [APC=0.30%, 95%CI: (0.19%, 0.40%)].Theagestandardized prevalence (r = −0.17, P < 0.05), mortality (r = −0.67, P < 0.05) and DALYs rates of cystic echinococcosis (r = −0.60, P < 0.05) all correlated negatively with SDI across 21 geographical regions from 1990 to 2021, and the age-standardized mortality (r = −0.61, P < 0.05) and DALYs rates (r = −0.44, P < 0.05) both correlated negatively with SDI across 204 countries and territories in 2021. Frontier analysis revealed that the age-standardized DALYs rate of cystic echinococcosis was still not in line with the frontier in some high-SDI countries or territories. In addition, the global age-standardized prevalence was projected with the BAPC model to appear a tendency towards a rise among both men [estimated annual percent change (EAPC) = 0.18%, 95% CI: (0.13%, 0.23%)] and women [EAPC = 0.29%, 95% CI: (0.24%, 0.34%)] from 2022 to 2035, and the global age-standardized mortality [men: EAPC = −4.71%, 95% CI: (−4.71%, −4.37%); women: EAPC = −4.74%, 95% CI: (−4.74%, −4.74%)] and DALYs rates [men: EAPC = −3.35%, 95% CI: (−3.36%, −3.34%); women: EAPC = −3.17%, 95% CI: (−3.18%, −3.16%)] were projected to appear a tendency towards a decline among both men and women. Conclusions The global burden of cystic echinococcosis appeared an overall tendency towards a decline from 1990 to 2021; however, the global prevalence of cystic echinococcosis is projected to appear a tendency towards a rise from 2022 to 2035. Intensified cystic echinococcosis control programmes are recommended.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size