Objective:To study the correlations of hippocampal subfield volumes with cerebrospinal fluid (CSF) biomarkers in Alzheimer's disease (AD) patients.Methods:Forty-nine patients with cognitive impairment, including 30 AD patients and 19 non-AD patients, were recruited in Department of Neurology, Drum Tower Clinical College, Nanjing University of Chinese Medicine from May 2017 to December 2021. Concentrations of Aβ 1-42, total tau protein and phosphorylated tau protein in CSF were analyzed by enzyme-linked immunosorbent assay (ELISA). Volumes of 12 hippocampal subfields were calculated using FreeSurfer image analysis. Differences of clinical data, neuropsychological scores and CSF biomarker concentrations between the 2 groups were compared. Partial correlation was performed to analyze the correlations of volumes of hippocampal subfields with CSF biomarker concentrations. Results:AD patients had significantly lower Mini-mental State Examination (MMSE) scores and Aβ 1-42 concentration in CSF than non-AD patients ( P<0.05); AD patients had significantly lower volumes of the right hippocampal parasitulum, dentate gyrus and CA4 than non-AD group ( P<0.05); the right parasubiculum volume was negatively correlated with CSF Aβ 1-42 ( r=-0.445, P=0.023) and positively correlated with CSF P-tau ( r=0.393, P=0.047) in AD patients. Volumes of left hippocampus tail, parasubiculum, CA1, molecular layer, dentate gyrus, CA3 and CA4 were negatively correlated with CSF total tau ( P<0.05). No significant correlation was noted between hippocampal subfield volumes and CSF biomarker concentrations in non-AD patients. Conclusion:Some right hippocampal subfields in AD patients atrophy compared with those in non-AD patients with cognitive impairment; the right parasubiculum may play a compensatory role in disease process, while volumes of the left hippocampus decreased with increased CSF total tau.

Objective:To explore the correlations of brain network functional connectivity (FC) alterations with cerebrospinal fluid (CSF) pathological biomarkers in patients with Alzheimer's disease (AD).Methods:A total of 39 patients with cognitive impairment, admitted to Department of Neurology, Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from January 2020 to December 2022 were recruited; 23 patients were with AD and 16 with non-AD. Clinical data were compared between the 2 groups. Resting-state functional MRI (rs-fMRI) data were collected, and FC differences between brain networks and FC differences within brain networks were compared by independent component analysis. Correlations of FC differences between brain networks and FC differences within brain networks with concentrations of β-amyloid protein 1-42 (Aβ 1-42) and Tau protein in CSF were analyzed. Results:Compared with the non-AD group, AD group had significantly lower Aβ 1-42 in CSF ( P<0.05). Compared with those in the non-AD group, FC alterations between the left frontoparietal network (lFPN) and anterior default mode network (aDMN) and between the visual network (VN) and posterior cingulate cortex (PCC), as well as FC alterations in lFPN, were significantly increased in AD group ( P<0.05). Compared with those in the non-AD group, FC alterations between lFPN and cerebellar network (CEN), and FC alterations in aDMN, sensorimotor network (SMN) and VN were significantly decreased in AD group ( P<0.05). In AD group, FC in SMN was positively correlated with total Tau and phosphorylated-Tau181 in CSF ( P<0.05); FC between VN and PCC was positively correlated with total Tau in CSF ( P<0.05). CSF Aβ 1-42 was positively correlated with FC alterations in aDMN and VN, but negatively correlated with FC in FPN ( P<0.05). Conclusion:In AD patients, characteristic changes in FC within and between multiple brain networks are noted, which are related to changes of Tau protein and Aβ 1-42 in CSF.

Background Improper settings of outdoor smoking points in public places may increase the risk of secondhand smoke exposure among the population. Conducting research on air pollution in and around smoking spots and related influencing factors can provide valuable insights for optimizing the setting of outdoor smoking points. Objective To investigate the influence of the number of smokers at outdoor smoking points and the distance on the diffusion characteristics of surrounding air pollutants, in order to optimize the setting of outdoor smoking points. Methods Surrounding the exhibition halls in the China International Import Expo (CIIE), two outdoor smoking points were randomly selected, one on the first floor (ground level) and the other on the second floor (16 m above ground), respectively. At 0, 3, 6, and 9 m from the smoking points in the same direction, validated portable air pollutant monitors were used to measure the real-time fine particulate matter (PM_2.5) and carbon dioxide (CO₂) concentrations for consecutive 5 d during the exhibition, as well as the environmental meteorological factors at 0 m with weather meters including wind speed, wind direction, and air pressure. An open outdoor atmospheric background sampling point was selected on each of the two floors to carry out parallel sampling. Simultaneously, the number of smokers at each smoking point were double recorded per minute. The relationships between the number of smokers, distance from the smoking points, and ambient PM_2.5 and CO₂ concentrations were evaluated by generalized additive regression models for time-series data after adjustment of confounders such as temperature, relative humidity, and wind speed. Results The median numbers of smokers at smoking points on the first and second floors were 6 [interquartile range (IQR): 3, 9] and 9 (IQR: 6, 13), respectively. Windless (wind speed <0.6 m·s⁻¹) occupied most of the time (85.9%) at both locations. The average concentration of ambient PM_2.5 at the smoking points (0 m) [mean ± standard deviation, (106±114) μg·m⁻³] was 4.2 times higher than that of the atmospheric background [(25±7) μg·m⁻³], the PM_2.5 concentration showed a gradient decline with the increase of distance from the smoking points, and the average PM_2.5 concentration at 9 m points [(35±22) μg·m⁻³] was close to the background level (1.4 times higher). The maximum concentration of CO₂ [(628±23) μmol·mol⁻¹] was observed at 0 m, and its average value was 1.3 times higher than that of the atmospheric background [(481±40) μmol·mol⁻¹], and there was no gradient decrease in CO₂ concentration with increasing distance at 0, 3, 6, and 9 m points. The regression analyses showed that, taking smoking point as the reference, every 3 m increase in distance was associated with a decrease of ambient PM_2.5 by 24.6 [95% confidence interval (95%CI): 23.5, 25.8] μg·m⁻³ (23.2%) and CO₂ by 54.1 (95%CI: 53.1, 55.1) μmol·mol⁻¹ (8.6%). Every one extra smoker at the smoking point was associated with an average increase of PM_2.5 and CO₂ by 2.0 (95%CI: 1.7, 2.8) μg·m⁻³ and 1.0 (95%CI: 0.7，1.2) μmol·mol⁻¹, respectively. The sensitivity analysis indicated that, under windless conditions, the concentrations of PM_2.5 and CO₂ at the smoking points were even higher but the decreasing and dispersion characteristics remained consistent. Conclusion Outdoor smoking points could significantly increase the PM_2.5 concentrations in the surrounding air and the risks of secondhand smoke exposure, despite of the noticeable decreasing trend with increasing distance. Considering the inevitable poor dispersion conditions such as windless and light wind, outdoor smoking points are recommended to be set at least 9 m or farther away from non-smoking areas.