Objective To explore the differences in heartbeat-evoked response (HER) under drug-related cues and neutral cues in individuals with heroin use disorder (HUD), and analyze the correlation between HER potentials and immediate cue-induced craving scores. Methods Fifty HUD participants were recruited from the Chang’an Compulsory Isolation Drug Rehabilitation Center in Shaanxi Province from June to September 2024. Simultaneous acquisition of 64-channel electroencephalography (EEG) and electrocardiogram signals was performed. Twenty alternating segments of drug-related and neutral cue videos were presented, and participants rated their subjective craving after each segment using visual analogue scale (VAS) scores. Scalp EEG data were source analyzed to obtain cortical EEG signals and corresponding HER. Short-time Fourier transform was used to calculate the power spectral density (PSD) of EEG within a time window from 100 ms before the R-peak to 500 ms after it, using the R-peak as the time zero point. Cluster-based permutation testing was used to analyze PSD differences between drug-related and neutral cues in the HUD individuals. Pearson correlation analysis was performed to evaluate the correlation between HER potentials and VAS scores. Results In the 350–420 ms time window, HER potentials in the left posterior parietal, temporal, and posterior cingulate cortices were significantly lower under drug-related cues compared to neutral cues (P＜0.01); in the 140–210 ms time window, HER potentials in the right prefrontal cortex were significantly higher under drug-related cues compared to neutral cues (P＜0.01). Correlation analysis showed that HER potentials in the left temporal and left posterior cingulate cortices were significantly negatively correlated with VAS scores (P＜0.05). Drug-related cues enhanced PSD of γ power (30–100 Hz) in salience network (fronto-insular), parietal and occipital regions (P＜0.05). PSD integrations of low-γ power (40–60 Hz) in parietal region (350–400 ms) and high-γ power (70–100 Hz) in left salience network (fronto-parietal) and occipital regions (300–350 ms) were positively correlated with VAS scores (P＜0.05). Conclusions Drug-related cues may modulate cortical activity related to heartbeat perception in HUD individuals, and such dynamic changes in both time and frequency domains are stably associated with subjective craving.

Objective To observe changes of white matter function in adolescent smoker(AS)with resting-state functional MRI(rs-fMRI)fractional amplitude of low-frequency fluctuation(fALFF)technique.Methods Forty-five adolescents(AS group)and 45 control subjects(control group)were prospectively enrolled,and brain rs-fMRI were acquired.Brain regions with fALFF being different between groups were observed,and the correlations with clinical indicators were analyzed.Results Compared with that in control group,fALFF of the right superior longitudinal fasciculus significantly elevated in AS group(FDR correct Q＜0.05),in which the peak of the cluster was positively correlated with score of Fagerstr?m test for nicotine dependence(FTND)(r=0.294,P=0.049).Conclusion White matter function changed in AS,presenting as significantly increased fALFF in right superior longitudinal fasciculus,which was positively correlated with nicotine dependence.

Objective:To explore the incidence of delirium in patients of advanced age hospitalized in internal medicine departments and analyze its influencing factors.Methods:A retrospective analysis was conducted on the medical records of 586 patients of advanced age hospitalized in internal medicine departments at the Beijing University of Chinese Medicine Third Affiliated Hospital from May 2023 to May 2024. Patients were divided into a delirium group and a non-delirium group based on whether delirium occurred. Univariate analysis and binary Logistic regression analysis were used to explore the factors influencing delirium in patients of advanced age hospitalized in internal medicine departments.Results:Among 586 patients of advanced age hospitalized in internal medicine departments, the incidence of delirium was 21.2% (124/586). Binary Logistic regression analysis showed that age, activities of daily living (Barthel Index), folate deficiency, sleep disorders, and indwelling catheters were factors influencing delirium in patients of advanced age hospitalized in internal medicine departments ( P<0.05) . Conclusions:The incidence of delirium is high among patients of advanced age hospitalized in internal medicine departments. Healthcare professionals should pay particular attention to elderly patients with advanced age, limited activities of daily living, folate deficiency, sleep disorders, and indwelling catheters, and should implement targeted preventive strategies as early as possible.

Objective To investigate the dynamic functional connectivity differences between insomnia patients and healthy controls in triple brain networks[the significant network(SN),the default mode network(DMN),and the executive control network(ECN)]using functional magnetic resonance imaging,and uncover their associations with cognitive ability.Methods Dynamic functional connectivity analysis was performed on functional magnetic resonance imaging data from 40 insomnia patients and 40 healthy controls.The changes in dynamic functional connectivity values were studied for SN,DMN,ECN[including the left executive control network(LECN)and the right executive control network(RECN)];the similarities and differences in time characteristic indicators such as time score,average dwell time,and conversion rate were explored;and their associations with clinical information were analyzed.Results The SN-LECN and DMN-RECN dynamic functional connectivity was significantly higher in insomnia patients than in healthy controls(P=0.013,0.047),while the RECN-LECN and RECN internal functional connectivity strength was lower in insomnia patients than in healthy controls(P<0.001).Additionally,the fractional time in state 2 in insomnia group was significantly higher than that in healthy controls(P<0.001),and it was positively correlated with the Pittsburgh sleep quality index(r=0.524,P=0.001).Conclusion Insomnia patients exhibit significant abnormalities in triple brain network dynamic functional connectivity,which may be related to abnormalities in cognitive control and sensory processing in insomnia patients.These findings provide a new perspective for further research on the neural mechanisms and potential intervention strategies for insomnia.

Objective:To explore the incidence of delirium in patients of advanced age hospitalized in internal medicine departments and analyze its influencing factors.Methods:A retrospective analysis was conducted on the medical records of 586 patients of advanced age hospitalized in internal medicine departments at the Beijing University of Chinese Medicine Third Affiliated Hospital from May 2023 to May 2024. Patients were divided into a delirium group and a non-delirium group based on whether delirium occurred. Univariate analysis and binary Logistic regression analysis were used to explore the factors influencing delirium in patients of advanced age hospitalized in internal medicine departments.Results:Among 586 patients of advanced age hospitalized in internal medicine departments, the incidence of delirium was 21.2% (124/586). Binary Logistic regression analysis showed that age, activities of daily living (Barthel Index), folate deficiency, sleep disorders, and indwelling catheters were factors influencing delirium in patients of advanced age hospitalized in internal medicine departments ( P<0.05) . Conclusions:The incidence of delirium is high among patients of advanced age hospitalized in internal medicine departments. Healthcare professionals should pay particular attention to elderly patients with advanced age, limited activities of daily living, folate deficiency, sleep disorders, and indwelling catheters, and should implement targeted preventive strategies as early as possible.

Electroencephalogram(EEG)refers to the electrical activity generated by neuronal discharges in the human brain,conventionallyrecorded on the scalp of the brain.EEG technology enables the non-invasive detection of electrophysiological activity in neuronal populations within the cerebral cortex,capturing millisecond-level changes in brain potentials with high temporal resolution.In recent years,lots of international researchers have leveraged EEG technology to investigate smoking addiction and further explore the millisecond-level electrophysiological changes in the brains of smokers.This review synthesizes recent advances in resting-state EEG and task-evoked event-related potential research among smokers,summarizing the electrophysiological activity changes associated with smoking addiction.Future researches will employ both longitudinal tracking and machine learning algorithms to further reveal the relationship between EEG signatures and smoking behaviors,thereby providing a scientific foundation for early intervention and treatment strategies targeting smoking addiction.

Objective To observe changes of white matter function in adolescent smoker(AS)with resting-state functional MRI(rs-fMRI)fractional amplitude of low-frequency fluctuation(fALFF)technique.Methods Forty-five adolescents(AS group)and 45 control subjects(control group)were prospectively enrolled,and brain rs-fMRI were acquired.Brain regions with fALFF being different between groups were observed,and the correlations with clinical indicators were analyzed.Results Compared with that in control group,fALFF of the right superior longitudinal fasciculus significantly elevated in AS group(FDR correct Q＜0.05),in which the peak of the cluster was positively correlated with score of Fagerstr?m test for nicotine dependence(FTND)(r=0.294,P=0.049).Conclusion White matter function changed in AS,presenting as significantly increased fALFF in right superior longitudinal fasciculus,which was positively correlated with nicotine dependence.

Objective To investigate the dynamic functional connectivity differences between insomnia patients and healthy controls in triple brain networks[the significant network(SN),the default mode network(DMN),and the executive control network(ECN)]using functional magnetic resonance imaging,and uncover their associations with cognitive ability.Methods Dynamic functional connectivity analysis was performed on functional magnetic resonance imaging data from 40 insomnia patients and 40 healthy controls.The changes in dynamic functional connectivity values were studied for SN,DMN,ECN[including the left executive control network(LECN)and the right executive control network(RECN)];the similarities and differences in time characteristic indicators such as time score,average dwell time,and conversion rate were explored;and their associations with clinical information were analyzed.Results The SN-LECN and DMN-RECN dynamic functional connectivity was significantly higher in insomnia patients than in healthy controls(P=0.013,0.047),while the RECN-LECN and RECN internal functional connectivity strength was lower in insomnia patients than in healthy controls(P<0.001).Additionally,the fractional time in state 2 in insomnia group was significantly higher than that in healthy controls(P<0.001),and it was positively correlated with the Pittsburgh sleep quality index(r=0.524,P=0.001).Conclusion Insomnia patients exhibit significant abnormalities in triple brain network dynamic functional connectivity,which may be related to abnormalities in cognitive control and sensory processing in insomnia patients.These findings provide a new perspective for further research on the neural mechanisms and potential intervention strategies for insomnia.

Electroencephalogram(EEG)refers to the electrical activity generated by neuronal discharges in the human brain,conventionallyrecorded on the scalp of the brain.EEG technology enables the non-invasive detection of electrophysiological activity in neuronal populations within the cerebral cortex,capturing millisecond-level changes in brain potentials with high temporal resolution.In recent years,lots of international researchers have leveraged EEG technology to investigate smoking addiction and further explore the millisecond-level electrophysiological changes in the brains of smokers.This review synthesizes recent advances in resting-state EEG and task-evoked event-related potential research among smokers,summarizing the electrophysiological activity changes associated with smoking addiction.Future researches will employ both longitudinal tracking and machine learning algorithms to further reveal the relationship between EEG signatures and smoking behaviors,thereby providing a scientific foundation for early intervention and treatment strategies targeting smoking addiction.

Objectives:To search, evaluate, and summarize the evidence related to the application management of over-the-counter (OTC) medications for constipation in the elderly, providing evidence-based support for the rational use of these medications.Methods:A systematic search was conducted through computerized decision support systems, guideline websites, professional association websites, and databases for clinical decisions, guidelines, evidence summaries, and expert consensus on the management of OTC medications for constipation in the elderly. The search period spanned from January 2018 to March 2023. The quality of the literature was independently assessed, and evidence was extracted. The 2014 version of the Joanna Briggs Institute (JBI) evidence grading system was used to determine the levels of evidence.Results:A total of 18 article were included, consisting of two clinical decisions, five guidelines, seven expert consensus statements, and four evidence summaries. These covered five areas: medication principles for elderly individuals with different characteristics, medication selection, medication monitoring, health education, and precautions, culminating in a total of 30 best evidence.Conclusions:This study summarizes the best evidence for the management of OTC medications for constipation in the elderly, providing evidence-based support for the rational application of these medications.