Search

Lens autofluorescence ratio (LFR) is a novel approach to detect advanced glycation end products in a time-saving and non-invasive manner. However, its associations with glycemia and diabetes remain unclear. We conducted this study to address this issue in Chinese adults. We enrolled a total of 4,705 participants aged 20-70 years in China between May 2020 and January 2021 in a cross-sectional study. LFR was determined by biomicroscopy (ClearPath DS-120). Diabetes was ascertained by oral glucose tolerance test, self-reported history, and/or antidiabetic medication use. Correlation and logistic regression analyses were performed. LFR was higher in participants with diabetes than those without (23.27 ± 6.51 vs. 19.45 ± 5.08, p < 0.001). LFR correlated with fasting plasma glucose and hemoglobin A1c in the overall and diabetes-stratified populations. The odds of diabetes was increased by 6% per one percent higher of LFR after multivariable-adjustment (odds ratio (OR) 1.06, 95% CI 1.04-1.08, p < 0.001). Participants in the highest quartile of LFR had higher odds of diabetes compared with those in the lowest quartile (OR 1.83, 95% CI 1.33-2.52, p < 0.001). Mediation analysis showed that, insulin resistance, as assessed by triglyceride-glucose index, may underline the relationship between high LFR and increased odds of diabetes. LFR, a non-invasive indirect measure of advanced glycation end products, appears to be associated with glycemia and the risk of developing diabetes in Chinese adults.

The association between bioimpedance analysis (BIA) parameters and the outcomes of critically ill patients was explored through a retrospective investigation.The study enrolled patients in the intensive care units of our hospital who had a record of BIA measurements as well as disease severity scores assessed by Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II) and Sequential Organ Failure Assessment (SOFA). The associations between clinical conditions, outcomes and BIA parameters were analysed. The relationship between individual bioimpedance values and the current frequencies fit well to a natural logarithmic function, providing a regression coefficient S value. Other parameters obtained from the BIA measurements included phase angle (PA), the ratio of bioimpedance at high and low frequencies (IR), extracellular water (ECW), intracellular water (ICW) and total body water (TBW).Among 201 enrolled patients, the 90-day in-hospital mortality was 35.8%. Compared to the survivors at 7-days, for the non-survivors, the IR, S value, ratio of ECW/weight and ratio of ECW/TBW were higher, and the PA was lower (P 0.05). Compared to the survivors at 90-days, for the non-survivors, the IR, S value and ratio of ECW/weight were higher, and the PA was lower (P 0.05). Multinomial logistic regression analysis results showed that only SAPS II and S value were independent risk factors for 7-day and 90-day death (P 0.01). When analysed by ROC, the AUC of the S value for predicting 7-day and 90-day death was non-significantly lower than SAPS II (S vs. SAPS II, 0.729 vs. 0.747 (7-day); 0.701 vs. 0.779 (90-day), P 0.05). Importantly, both the 7-day and the 90-day mortality in patients with S values ≤-25.5 were 0; for the others, the mortality increased with the rise of S value. For patients with SAPS II ≤33, the mortality varied minimally; and for patients with SAPS II55, the mortality was 100%.The S value and SAPS II are independent risk factors for 7-day and 90-day death in critically ill patients; the former may have a greater negative predictive value, while the latter may have a greater positive predictive value.

Neuroimaging studies have shown topological disruptions of both functional and structural whole-brain networks in major depressive disorder (MDD). This study examined common and specific alterations between these two types of networks and whether the alterations were differentially involved in the two hemispheres. Multimodal MRI data were collected from 35 MDD patients and 35 healthy controls, whose functional and structural hemispheric networks were constructed, characterized, and compared. We found that functional brain networks were profoundly altered at multiple levels, while structural brain networks were largely intact in patients with MDD. Specifically, the functional alterations included decreases in intra-hemispheric (left and right) and inter-hemispheric (heterotopic) functional connectivity; decreases in local, global and normalized global efficiency for both hemispheric networks; increases in normalized local efficiency for the left hemispheric networks; and decreases in intra-hemispheric integration and inter-hemispheric communication in the dorsolateral superior frontal gyrus, anterior cingulate gyrus and hippocampus. Regarding hemispheric asymmetry, largely similar patterns were observed between the functional and structural networks: the right hemisphere was over-connected and more efficient than the left hemisphere globally; the occipital and partial regions exhibited leftward asymmetry, and the frontal and temporal sites showed rightward lateralization with regard to regional connectivity profiles locally. Finally, the functional–structural coupling of intra-hemispheric connections was significantly decreased and correlated with the disease severity in the patients. Overall, this study demonstrates modality- and hemisphere-dependent and invariant network alterations in MDD, which are helpful for understanding elaborate and characteristic patterns of integrative dysfunction in this disease.

OBJECTIVE: To investigate the relationship between sleep parameters and suicidal ideation in patients with late-life depression (LLD). METHODS: Seventy-seven LLD patients over 60 years old from Sir Run Run Shaw Hospital of Zhejiang University during July 2017 and July 2018 were included in the study. All patients were assessed with Hamilton Depression Rating Scale (HAMD) and polysomnography (PSG) overnight. The suicidal score of item 3 in HAMD (HAM-D3)was used to define whether there was a suicidal ideation. Participants were subsequently grouped according to endorsement of presence (HAM-D3 score ≥1, n=46) versus absence (HAM-D3 score=0, n=31) of suicidal ideation symptoms. The sleep efficiency, total sleep time, wakefulness after sleep onset, rapid eye movement percent/latency, and non-rapid eye movement sleep stages 1-3 (N1-N3) were assessed. ANOVA analyses were conducted to explore the correlation of sleep parameters with suicidal ideation between the groups with and without suicidal ideation. In model 1, the HAM-D3 constituted the independent variable in separate ANOVA tests; in model 2 the impact of depressive symptoms were assessed as a covariate with sleep parameters. RESULTS: There was less stage N3 [(55±41)min, t=-4.731, P < 0.05] and the reduced percentage of N3 [(15±11)%, t=-4.194, P < 0.05] in LLD patients with suicidal ideation, compared with the LLD patients without suicidal ideation [(104±49) min, (26±11)%]. Correlation analyses revealed that there was a significant correlation between the suicidal ideation and the percentage of stage N3 and sleep time of stage N3 (both P < 0.05). CONCLUSION: Suicidal ideation is associated with less N3 sleep in LLD patients.

Accumulating evidence suggests that early improvement after two‐week antidepressant treatment is predictive of later outcomes of patients with major depressive disorder (MDD); however, whether this early improvement is associated with baseline neural architecture remains largely unknown. Utilizing resting‐state functional MRI data and graph‐based network approaches, this study calculated voxel‐wise degree centrality maps for 24 MDD patients at baseline and linked them with changes in the Hamilton Rating Scale for Depression (HAMD) scores after two weeks of medication. Six clusters exhibited significant correlations of their baseline degree centrality with treatment‐induced HAMD changes for the patients, which were mainly categorized into the posterior default‐mode network (i.e., the left precuneus, supramarginal gyrus, middle temporal gyrus, and right angular gyrus) and frontal regions. Receiver operating characteristic curve and logistic regression analyses convergently revealed excellent performance of these regions in discriminating the early improvement status for the patients, especially the angular gyrus (sensitivity and specificity of 100%). Moreover, the angular gyrus was identified as the optimal regressor as determined by stepwise regression. Interestingly, these regions possessed higher centrality than others in the brain (P