Objective:To investigate the effects and potential mechanisms of melatonin on cognitive dysfunction induced by long-term anesthesia with isoflurane.Methods:Male C57BL/6J mice aged 2 months were divided into control group, isoflurane group, melatonin group, and isoflurane+ melatonin group by random number table, with 6 mice in each group.Three days after anesthesia, cognitive function of mice was assessed by Y-maze and fear conditioning (FC) tests. ATP content in the hippocampus was measured by an ATP assay kit. Western blot was used to detect the expression of DRP1, pDRP1, MFN2, pAMPK and SIRT1 proteins in the hippocampus. Cultured HT-22 cells derived from mouse hippocampal neurons in vitro were divided into control group, isoflurane group, melatonin group, and isoflurane + melatonin group, and the levels of reactive oxygen species (ROS) in each group were detected by flow cytometry after intervention. Statistical analysis was performed by SPSS 22.0 software, and one-way ANOVA was used for comparisons among multiple groups.Results:(1) There was a statistically significant difference in the percentage of freezing behavior in contextual fear memory among the four groups of mice ( F=39.09, P<0.05). The percentage of freezing behavior in the isoflurane group was lower than that in the control group ((44.23±8.88)% vs (75.87±5.90)%, P<0.05), while the percentage of freezing behavior in the isoflurane+ melatonin group((67.45±14.89)%)was higher than that in the isoflurane group ( P<0.05). There was also a statistically significant difference in the percentage of exploration in the novel arm among the four groups of mice ( F=13.87, P<0.05). The percentage of exploration in the novel arm in the isoflurane group was lower than that in the control group((33.64±6.53)% vs (47.13±3.87)%, P<0.05), while the percentage of exploration in the novel arm in the isoflurane+ melatonin group((43.05±1.64)%)was higher than that in the isoflurane group ( P<0.05). (2) Statistically significant difference in the levels of ATP in the hippocampus was found among the four groups of mice ( F=49.22, P<0.05). The level of ATP in the hippocampus in the isoflurane group was lower than that in the control group((2.29±0.15)nmol/mg vs (3.58±0.12)nmol/mg, P<0.05), while the level of ATP in the hippocampus in the isoflurane+ melatonin group ((3.02±0.27)nmol/mg)was higher than that in the isoflurane group ( P<0.05). There was a statistically significant difference in the levels of ROS in HT-22 cells among the four groups ( F=18.36, P<0.05). The level of ROS in HT-22 cells in the isoflurane group was higher than that in the control group after anesthesia ( P<0.05), while the level of ROS in HT-22 cells in the isoflurane+ melatonin group was lower than that in the isoflurane group after anesthesia ( P<0.05). (3) There were statistically significant difference in the levels of pDRP1, pAMPK and SIRT1 protein in the hippocampus among the four groups of mice ( F=19.87, 21.20, 25.65, all P<0.05). The levels of pDRP1 and SIRT1 protein in the hippocampus in the isoflurane group were both lower than those in the control group (both P<0.05), while the levels of pDRP1 and SIRT1 protein in the hippocampus in the isoflurane+ melatonin group were both higher than those in the isoflurane group (both P<0.05). In the isoflurane group, the expression of pAMPK protein in the hippocampal region was higher than that in the control group ( P<0.05), while the expression of pAMPK protein in the isoflurane+ melatonin group was lower than that in the isoflurane group ( P<0.05). Conclusion:Melatonin improves long-term isoflurane anesthesia-induced cognitive dysfunction by regulating mitochondrial homeostasis through the AMPK/SIRT1 signaling pathway.

Objective To explore the distribution patterns of traditional Chinese medicine(TCM)syndromes in patients with metabolic syndrome caused by antipsychotic drugs.Methods A standardized TCM syndrome survey was performed to collect diagnostic information from 160 patients diagnosed with metabolic syndrome due to antipsychotic drug use.Subsequent frequency analysis,cluster analysis,and Bayesian network analysis were carried out.The syndrome pattern distribution was ultimately determined through relevant literatures and expert opinions.Results Five TCM syndromes were identified through frequency,cluster,and Bayesian network analyses.The most common syndrome was qi deficiency with phlegm-dampness(30％),followed by spleen deficiency with phlegm-Heat(23.75％),qi and yin deficiency Pattern(21.88％),yin deficiency with damp-heat(17.50％),and stomach fire hyperactivity pattern(6.88％).Conclusion The pathogenesis of antipsychotics-induced metabolic syndrome involves a complex interplay of deficiency and excess factors.The primary disease is mainly located at the spleen and stomach,with involvement of the liver,kidney,and heart.Pathogenic factors include qi deficiency,yin deficiency,dampness,heat,pathogenic fire,and phlegm.

Tuberculosis(TB),a chronic infectious disease caused by infection with the Mycobacterium tuberculosis complex(MTBC),has re-emerged as the leading cause of death from a single infectious agent worldwide.Because of widespread use and mis-use of anti-tuberculosis drugs,the emergence of multidrug-resistant TB(MDR-TB)and extensively drug-resistant TB(XDR-TB)is increasing,thus posing a serious threat to global health.The current problem of drug resistance is a major prevention and treatment challenge;therefore,the search for new drug targets is urgently needed.In recent years,substantial progress has been made in re-search on anti-tuberculosis drug targets and novel therapeutic strategies.Herein,we summarize recent research progress in anti-tuberculosis drug targets,primarily cell wall synthesis,nucleic acid replication and transcription,and energy metabolism.We also provide an overview of research progress regarding two novel therapeutic strategies,to provide a theoretical basis and research ideas for the development of new clinical drugs.

Childhood primary renal tubular diseases are chronic kidney diseases characterized by impaired renal tubular reabsorption. Primary renal tubular disease has diverse clinical manifestations and lacks of specificity. Laboratory tests are limited，making it prone to missed diagnosis and misdiagnosis. Based on the current knowledge of renal tubular diseases，authors propose early warning signals of renal tubular diseases such as family history of primary tubular diseases，unexplained polyhydramnios during pregnancy，polydipsia，polyuria，delayed growth and development or rickets，decreased muscle strength and tone，unexplained electrolyte disturbance，hyperuricemia，acid-base disturbance，positive urine sugar test，renal tubular proteinuria，urinary imaging examination suggesting kidney stones，calcium deposition，renal cysts and early onset of eye，ear，joint and neuron injury.Meanwhile，some universal management strategies for primary renal tubular disease are proposed，emphasizing the importance of multidisciplinary collaboration，genetic testing and individualized intervention to improve the long-term prognosis of childhood primary renal tubular diseases.

AIM:To analyze the association between mobile phone addiction and high myopia among college students.METHODS:We conducted a cross-sectional questionnaire survey in December 2022 on all students of a university in Shaanxi Province, and the questionnaire included socio-demographic characteristics, mobile phone addiction, high myopia, and lifestyle. Binary Logistic regression model was used to analyze the association between mobile phone addiction and high myopia among college students.RESULTS:A total of 19 952 college students were included. The prevalence of high myopia was 7.31%. The rate of mobile phone addiction was 25.68%, and the mobile phone addiction score was 37.59±13.38. The incidence of high myopia among college students with mobile phone addiction was higher than non-mobile phone addiction(P<0.001). After adjusting for socio-demographic characteristics and lifestyle, the risk of high myopia among college students with mobile phone addiction was 1.274 times(95%CI:1.131-1.434)higher than non-mobile phone addiction. For each point increase of total mobile phone addiction score, withdrawal symptoms score, salience score, social comfort score, and mood changes score, the risk of high myopia among college students increased by 0.9%(95%CI:1.005-1.013), 2.0%(95%CI:1.010-1.030), 2.6%(95%CI:1.010-1.043), 4.8%(95%CI:1.030-1.066), and 3.3%(95%CI:1.014-1.052), respectively.CONCLUSION:Mobile phone addiction is significantly associated with the increased risk of high myopia among college students, and early intervention of mobile phone use may reduce the risk of high myopia among college students.

Objective To explore the current status of minor children parenting concerns among young and middle-aged breast cancer patients and investigate the influencing factors based on a random forest model so as to provide references for clinical interventions.Methods A convenience sampling method was used to select breast cancer patients undergoing treatment in our hospital between April and December 2023.A self-designed general information questionnaire,the Chinese version of parenting concerns questionnaire(PCQ),perceived social support scale(PSSS),concern about recurrence scale(CARS),and the brief illness perception questionnaire(BIPQ)were used for the study.A random forest model and the least absolute shrinkage and selection operator(LASSO)were employed to prioritise variables and filtered by significance.The selected variables were then incorporated into the multiple linear regression analysis.Results A total of 260 patients completed the study.The score of minor children parenting concerns of young and middle-aged breast cancer patients was 51.1±6.4.The multiple linear regression analysis,which included variables determined by random forest and LASSO regression(and sorted by the importance of influencing factors),showed that higher disease perception,lower perceived social support,greater concern about cancer recurrence,stage IV tumors,being divorced/widowed,and having more minor children were associated with higher parenting concerns among young and middle-aged breast cancer patients(all P<0.05),accounting for 57.0%of the total variance.Conclusion The minor children parenting concerns in young and middle-aged breast cancer patients are at a moderately high level and are influenced by a variety of factors.Healthcare professionals should develop targeted measures and interventions to reduce the parenting concerns among the patients.

Objective:To evaluate the potential of IgG N-glycans as diagnostic biomarker for ankylosing spondylitis (AS) by comparing and analyzing the IgG N-glycan profiles with AS and healthy controls.Methods:A 1∶1 matched case-control study design was adopted, 81 AS patients who visited the Department of Rheumatology and Immunology at Taian City Central Hospital and the Second Affiliated Hospital of Shandong First Medical University between July 2020 and June 2021 were recruited. These patients were matched with 81 healthy individuals undergoing routine physical checkup. The levels of IgG N-glycosylation in human plasma were quantitatively measured using ultrahigh-performance liquid chromatography. Binomial logistic regression analysis was performed to identify IgG N-glycan biomarkers associated with AS.Results:A total of 14 primary glycans and 13 derived traits showed statistically significant differences between the AS case group and the control group. Binomial logistic regression analysis showed that glycan peak 4, agalactosylated glycans, fucosylated glycans, and fucosylated agalactosylated glycans were positively associated with AS[ OR(95% CI)=1.12(1.01, 1.42), 1.21(1.03, 1.43), 1.48(1.08, 2.03), and 1.27(1.04, 1.55); P=0.036, 0.022, 0.039, 0.020, respectively]. In terms of diagnostic performance, the single glycan GP4 exhibited the largest area under the ROC curve, with an AUC (95% CI) 0.751 (0.677, 0.826), while the combined glycan indicators (GP4+G0+F+FG0) achieved an AUC (95% CI) 0.768(0.697, 0.840). Conclusion:IgG N-glycans have the potentials to serve as candidate biomarkers for AS, and warrants further investigation.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

Hemorrhagic shock is a common clinical emergency that can aggravate cell injury after resuscitation. Astrocytes are crucial for the survival of neurons because they regulate the surrounding ionic microenvironment of neurons. Although hemorrhagic shock and resuscitation (HSR) injury can impair cognition, it remains unclear how this insult directly affects astrocytes. In this study, we established an HSR model by bleeding and re-transfusion in mice. The social interaction test and new object recognition test were applied to evaluate post-operative cognitive changes, and the results suggest that mice experience cognitive impairment following exposure to HSR. In the HSR group, the power spectral density of β and γ oscillations decreased, and the coupling of the θ oscillation phase and γ oscillation amplitude was abnormal, which indicated abnormal neuronal oscillation and cognitive impairment after HSR exposure. In brief, cognitive impairment in mice is strongly correlated with Ca²⁺ signal strength in lateral septum astrocytes following HSR.
Animals ; Astrocytes/metabolism* ; Shock, Hemorrhagic/metabolism* ; Resuscitation/adverse effects* ; Male ; Mice ; Calcium Signaling/physiology* ; Mice, Inbred C57BL ; Septal Nuclei/metabolism* ; Cognitive Dysfunction/etiology* ; Disease Models, Animal ; Cognition Disorders/etiology*

Acute respiratory distress syndrome(ARDS)is a key disease in the field of clinical critical illness diagnosis and treatment.Its incidence and mortality rate have always remained high.Due to its high heterogeneity of the cause,specific biomarkers are still lacking in clinical diagnosis,and targeted treatment strategies for its core pathological links still have significant limitations.In view of this,the construction of an ARDS risk prediction model based on multi-dimensional risk factors can provide key evidence-based guidance for clinical medical staff to identify high-risk groups at ARDS in the early stage.This paper aims to review the research progress of ARDS risk factors and prediction models,in order to provide new ideas and references in building more accurate prediction models for ARDS.