Brain-wide functional connectivity alterations and their cognitive correlates in subjective cognitive decline.

Background: Individuals with subjective cognitive decline (SCD) are at risk of developing Alzheimer's Disease (AD). Traditional seed-based analysis has shown biased functional connectivity (FC) in SCD individuals. To investigate unbiased altered FC by the brain-wide association study (BWAS) and to determine its association with cognition in SCD individuals. Methods: Measure of association (MA) analysis was applied to detect significant voxels with FC changes. Based on these changes, we identified regions of interest (ROIs) and conducted ROI-wise FC analyses. Correlation analyses were then performed between these FC circuits and cognition. Results: MA analysis identified 10 ROIs with significantly altered voxels. ROI-wise FC analyses revealed 14 strengthened FC, predominantly parietal-occipital link alterations. The FC between the right superior occipital gyrus and the right postcentral gyrus correlated positively with executive function, while the FC between the right middle occipital gyrus and the left angular gyrus correlated positively with episodic memory in SCD individuals. Conclusion: SCD involves multifocal impairments, of which regions of default mode network (DMN) and occipital lobe should be specially focused. Cross-hemispheric alterations indicate an internal interactive impairment pattern in SCD. The reduced FC between the right superior occipital gyrus and the right postcentral gyrus, and between the right middle occipital gyrus and the left angular gyrus, which correlate with specific cognitive functions, could serve as potential biomarkers for SCD diagnosis.

CT radiomics-based biomarkers can predict response to immunotherapy in hepatocellular carcinoma.

Hepatocellular Carcinoma (HCC) remains a leading cause of cancer deaths. Despite the rise of immunotherapies, many HCC patients don't benefit. There's a clear need for biomarkers to guide treatment decisions. This research aims to identify such biomarkers by combining radiological data and machine learning. We analyzed clinical and CT imaging data of 54 HCC patients undergoing immunotherapy. Radiologic features were examined to develop a model predicting short-term immunotherapy effects. We utilized 9 machine learning and 2 ensemble learning techniques using RapidMiner for model construction. We conducted the validation of the above feature combination using 29 HCC patients who received immunotherapy from another hospital, and tested and validated it using XGBoost combined with a genetic algorithm. In 54 HCC patients, radiomics features varied significantly between those with partial response (PR) and stable disease (SD). Key features in Gray Level Run Length Matrix (GLRLM) and in adjacent tissues' Intensity Direct, Neighborhood Gray Tone Difference Matrix (NGTDM), and Shape correlated with short-term immunotherapy efficacy. Selected feature combinations of 15, 19, and 8/15 features yielded better outcomes. Deep learning, random forest, and naive bayes outperformed other methods, with Bagging being more reliable than Adaboost. In the validation set of 29 HCC patients, the mentioned feature combination also demonstrated favorable performance. Furthermore, we achieved improved results when employing XGBoost in conjunction with a genetic algorithm for testing and validation. The machine learning model built with CT image features derived from GLCM, GLRLM, IntensityDirect, NGTDM, and Shape can accurately forecast the short-term efficacy of immunotherapy for HCC.

Exposure to multiple ambient air pollutants changes white matter microstructure during early adolescence with sex-specific differences.

BACKGROUND: Air pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex. METHODS: We investigate sex-stratified effects of annual exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at ages 9-10 years on longitudinal patterns of white matter microstructure over a 2-year period. Diffusion-weighted imaging was collected on 3T MRI scanners for 8182 participants (1-2 scans per subject; 45% with two scans) from the Adolescent Brain Cognitive Development (ABCD) Study®. Restriction spectrum imaging was performed to quantify intracellular isotropic (RNI) and directional (RND) diffusion. Ensemble-based air pollution concentrations were assigned to each child's primary residential address. Multi-pollutant, sex-stratified linear mixed-effect models assessed associations between pollutants and RNI/RND with age over time, adjusting for sociodemographic factors. RESULTS: Here we show higher PM2.5 exposure is associated with higher RND at age 9 in both sexes, with no significant effects of PM2.5 on RNI/RND change over time. Higher NO2 exposure is associated with higher RNI at age 9 in both sexes, as well as attenuating RNI over time in females. Higher O3 exposure is associated with differences in RND and RNI at age 9, as well as changes in RND and RNI over time in both sexes. CONCLUSIONS: Criteria air pollutants influence patterns of white matter maturation between 9-13 years old, with some sex-specific differences in the magnitude and anatomical locations of affected tracts. This occurs at concentrations that are below current U.S. standards, suggesting exposure to low-level pollution during adolescence may have long-term consequences.

Air pollution is known to affect health, but it is unclear whether it affects the growing human brain. We investigated whether there were differences in the development of white matter connections, which allow for faster communication between different brain regions, in children aged 9-13 years living in areas with relatively low or high air pollution in the USA. In a large group of U.S. teens, we find that polluted air is linked to differences in white matter at ages 9-10 years old and over the next two years. In some cases, males and females showed differences in the part of the brain showing changes and the amount of white matter change. Our study suggests that air pollution levels that are deemed acceptable under current regulations in the USA could have long-term effects on how a child's brain grows. Further studies are needed to better understand the impact of these changes.

The Association between Exposure to Fine Particulate Matter and MRI-Assessed Locus Coeruleus Integrity in the Vietnam Era Twin Study of Aging (VETSA).

BACKGROUND: Increased exposure to ambient air pollution, especially fine particulate matter ≤2.5µm (PM2.5) is associated with poorer brain health and increased risk for Alzheimer's disease (AD) and related dementias. The locus coeruleus (LC), located in the brainstem, is one of the earliest regions affected by tau pathology seen in AD. Its diffuse projections throughout the brain include afferents to olfactory areas that are hypothesized conduits of cerebral particle deposition. Additionally, extensive contact of the LC with the cerebrovascular system may present an additional route of exposure to environmental toxicants. OBJECTIVE: Our aim was to investigate if exposure to PM2.5 was associated with LC integrity in a nationwide sample of men in early old age, potentially representing one pathway through which air pollution can contribute to increased risk for AD dementia. METHODS: We examined the relationship between PM2.5 and in vivo magnetic resonance imaging (MRI) estimates of LC structural integrity indexed by contrast to noise ratio (LCCNR) in 381 men [mean age=67.3; standard deviation (SD)=2.6] from the Vietnam Era Twin Study of Aging (VETSA). Exposure to PM2.5 was taken as a 3-year average over the most recent period for which data were available (average of 5.6 years prior to the MRI scan). We focused on LCCNR in the rostral-middle portion of LC due to its stronger associations with aging and AD than the caudal LC. Associations between PM2.5 exposures and LC integrity were tested using linear mixed effects models adjusted for age, scanner, education, household income, and interval between exposure and MRI. A co-twin control analysis was also performed to investigate whether associations remained after controlling for genetic confounding and rearing environment. RESULTS: Multiple linear regressions revealed a significant association between PM2.5 and rostral-middle LCCNR (ß=-0.16; p=0.02), whereby higher exposure to PM2.5 was associated with lower LCCNR. A co-twin control analysis found that, within monozygotic pairs, individuals with higher PM2.5 exposure showed lower LCCNR (ß=-0.11; p=0.02), indicating associations were not driven by genetic or shared environmental confounds. There were no associations between PM2.5 and caudal LCCNR or hippocampal volume, suggesting a degree of specificity to the rostral-middle portion of the LC. DISCUSSION: Given previous findings that loss of LC integrity is associated with increased accumulation of AD-related amyloid and tau pathology, impacts on LC integrity may represent a potential pathway through which exposure to air pollution increases AD risk. https://doi.org/10.1289/EHP14344.

Twin-Field Quantum Key Distribution with Local Frequency Reference.

Twin-field quantum key distribution (TFQKD) overcomes the linear rate-loss limit, which promises a boost of secure key rate over long distance. However, the complexity of eliminating the frequency differences between the independent laser sources hinders its practical application. We analyzed and determined the frequency stability requirements for implementing TFQKD using frequency-stabilized lasers. Based on this analysis, we proposed and demonstrated a simple and practical approach that utilizes the saturated absorption spectroscopy of acetylene as an absolute reference, eliminating the need for fast frequency locking to achieve TFQKD. Adopting the 4-intensity sending-or-not-sending TFQKD protocol, we experimentally demonstrated the TFQKD over 502, 301, and 201 km ultralow-loss optical fiber, respectively. We expect this high-performance scheme will find widespread usage in future intercity and free-space quantum communication networks.

ADSC-derived exosomes provide neuroprotection in sepsis-associated encephalopathy by regulating hippocampal pyroptosis.

AIMS: Adipose-derived stem cell (ADSC)-derived exosomes have been recognized for their neuroprotective effects in various neurological diseases. This study investigates the potential neuroprotective effects of ADSC-derived exosomes in sepsis-associated encephalopathy (SAE). METHODS: Behavioral cognitive functions were evaluated using the open field test, Y-maze test, and novel object recognition test. Brain activity was assessed through functional magnetic resonance imaging (fMRI). Pyroptosis was measured using immunofluorescence staining and western blotting. RESULTS: Our findings indicate that ADSC-derived exosomes mitigate cognitive impairment, improve survival rates, and prevent weight loss in SAE mice. Additionally, exosomes protect hippocampal function in SAE mice, as demonstrated by fMRI evaluations. Furthermore, SAE mice exhibit neuronal damage and infiltration of inflammatory cells in the hippocampus, conditions which are reversed by exosome treatment. Moreover, our study highlights the downstream regulatory role of the NLRP3/caspase-1/GSDMD signaling pathway as a crucial mechanism in alleviating hippocampal inflammation. CONCLUSION: ADSC-derived exosomes confer neuroprotection in SAE models by mediating the NLRP3/caspase-1/GSDMD pathway, thereby ameliorating cognitive impairment.

Yearly change in air pollution and brain aging among older adults: A community-based study in Taiwan.

BACKGROUND: Air pollution is recognized as a modifiable risk factor for dementia, and recent evidence suggests that improving air quality could attenuate cognitive decline and reduce dementia risk. However, studies have yet to explore the effects of improved air quality on brain structures. This study aims to investigate the impact of air pollution reduction on cognitive functions and structural brain differences among cognitively normal older adults. METHODS: Four hundred and thirty-one cognitively normal older adults were from the Epidemiology of Mild Cognitive Impairment study in Taiwan (EMCIT), a community-based cohort of adults aged 60 and older, between year 2017- 2021. Annual concentrations of PM2.5, NO2, O3, and PM10 at participants' residential addresses during the 10 years before enrollment were estimated using ensemble mixed spatial models. The yearly rate of change (slope) in air pollutants was estimated for each participant. Cognitive functions and structural brain images were collected during enrollment. The relationships between the rate of air pollution change and cognitive functions were examined using linear regression models. For air pollutants with significant findings in relation to cognitive function, we further explored the association with brain structure. RESULTS: Overall, all pollutant concentrations, except O3, decreased over the 10-year period. The yearly rates of change (slopes) in PM2.5 and NO2 were correlated with better attention (PM2.5: r = -0.1, p = 0.047; NO2: r = -0.1, p = 0.03) and higher white matter integrity in several brain regions. These regions included anterior thalamic radiation, superior longitudinal fasciculus, inferior longitudinal fasciculus, corticospinal tract, and inferior fronto-occipital fasciculus. CONCLUSIONS: Greater rate of reduction in air pollution was associated with better attention and attention-related white matter integrity. These results provide insight into the mechanism underlying the relationship between air pollution, brain health, and cognitive aging among older adults.

Downregulation of DIP2B as a prognostic marker inhibited cancer proliferation and migration and was associated with immune infiltration in lung adenocarcinoma via CCND1 and MMP2.

Background: DIP2B is related to cancer progression. This study investigated the roles and pathways of DIP2B in lung adenocarcinoma (LUAD). Methods: DIP2B expression and the relationship between survival time of cancer patients and DIP2B expression were analyzed. The relationship between DIP2B expression and survival time in LUAD patients was evaluated by a meta-analysis. Cox and survival analyses were used to evaluate the prognostic factors and construct a prognostic nomogram. The mechanisms and effects of DIP2B and the relationship between DIP2B expression and the immune microenvironment were investigated using bioinformatics, CCK-8, western blotting, and transwell experiments. Results: DIP2B was overexpressed in LUAD tissues. DIP2B overexpression was associated with shorter prognosis and was an unfavorable risk factor for prognosis in LUAD patients. DIP2B co-expressed genes were involved in cell division, DNA repair, cell cycle, and others. Inhibition of DIP2B expression could downregulate the proliferation, migration, and invasion of LUAD A549 and H1299 cells, which was related to the decrease in CCND1 and MMP2 protein expression. BRCA1 overexpression was associated with short prognosis, and the nomogram formed by DIP2B and BRCA1 was associated with a poor prognosis in LUAD patients. DIP2B expression correlated with immune cells (such as CD8 T cells, Tcm, and iDCs) and cell markers. Conclusion: DIP2B is a potential biomarker of poor prognosis and the immune microenvironment in LUAD. Inhibition of DIP2B expression downregulated cancer cell proliferation, migration, and invasion, which might be related to the decrease in CCND1 and MMP2 protein expression. DIP2B-related nomograms might be useful tools for predicting the prognosis of LUAD patients.

Gene expression profiling of venous malformations identifies the role of SDC1 in venous endothelial cells.

Objective: To obtain insight into the molecular process implicated in venous malformations (VMs) and identify potential targets for treatment of VMs, this study profiled the gene expression pattern in VMs, investigated alterations of syndecan-1 (SDC1) expression in VMs, and tested the hypothesis that aberrant SDC1 expression triggers abnormal angiogenesis and VM development. Methods: Microarray analysis was performed to identify differentially expressed genes (DEGs) on a transcriptome-wide level in VMs and conjunctive normal. Gene Ontology molecular functional analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out to establish enhancement of biological signaling pathways involved in VMs. Among the DEGs, we focused on SDC1, which is involved in matrix remodeling, cell proliferation and invasion, and angiogenesis. SDC1 expression in VMs was verified by qRT-PCR, western blotting, and immunohistochemistry. Loss-of-function of SDC1 was achieved in human umbilical vein endothelial cells (HUVECs) by siRNA to investigate the roles of SDC1 in cell migration, invasion, and angiogenesis. Results: Compared with control tissue, the transcriptome study identified 274 upregulated DEGs and 3 downregulated DEGs. The transcript and protein levels of SDC1 were significantly decreased in VMs compared with normal tissue. Inhibition of SDC1 enhanced HUVEC migration, invasion, and angiogenesis. Conclusion: Our genome-wide microarray analysis suggests the involvement of numerous genes in VMs. Among them, SDC1 plays a substantial role in the process of angiogenesis and development of VMs. SDC1 may represent a potential target for a molecular therapy for VMs.

Cortical and subcortical gray matter abnormalities in mild cognitive impairment.

Gray matter changes are thought to be closely related to cognitive decline in mild cognitive impairment (MCI) patients. The study aimed to explore cortical and subcortical structural alterations in MCI and their association with cognitive assessment. 24 MCI patients and 22 normal controls (NCs) were included. Voxel-based morphometry (VBM), vertex-based shape analysis and surface-based morphometry (SBM) analysis were applied to explore subcortical nuclei volume, shape and cortical morphology. Correlations between structural changes and cognition were explored using spearman correlation analysis. Support vector machine (SVM) classification evaluated MCI identification accuracy. MCI patients showed significant atrophy in the left thalamus, left hippocampus, left amygdala, right pallidum, right hippocampus, along with inward deformation in the left amygdala. SBM analysis revealed that MCI group exhibited shallower sulci depth in the left hemisphere and increased cortical gyrification index (GI) in the right frontal gyrus. Correlation analysis showed the positive correlation between right hippocampus volume and episodic memory, while negative correlation between the altered GI and memory performance in MCI group. SVM analysis demonstrated superior performance of sulci depth and GI derived from SBM in MCI identification. When combined with cortical and subcortical metrics, SVM achieved a peak accuracy of 89 % in distinguishing MCI from NC. The study reveals significant gray matter structural changes in MCI, suggesting their potential role in underlying functional differences and neural mechanisms behind memory impairment in MCI.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development.

Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development.

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Down-regulation of KLRB1 is associated with increased cell growth, metastasis, poor prognosis, as well as a dysfunctional immune microenvironment in LUAD.

Killer cell lectin-like receptor B1 (KLRB1) is implicated in cancer progression and immunity. In this study, we aimed to evaluate the expression levels of KLRB1 in lung adenocarcinoma (LUAD) and analyze the relationship between KLRB1 expression levels, LUAD progression, and the tumor immune microenvironment. KLRB1 levels in LUAD were analyzed using data from the TCGA and XENA databases. Additionally, the diagnostic values of KLRB1 were analyzed in patients with LUAD. Survival and meta-analyses were employed to investigate the relationship between KLRB1 levels and other prognostic factors in patients with LUAD. Bioinformatics and cellular experiments were used to understand the functions and mechanisms of KLRB1. In addition, correlation analysis was used to investigate the relationship between KLRB1 levels and the immune microenvironment in LUAD. Reduced KLRB1 expression in LUAD was found to positively correlate with tumor size, distant metastasis, pathological stage, age, overall survival, diagnostic value, and disease-specific survival in patients with LUAD (P < 0.05). Conversely, increased KLRB1 expression was found to positively correlate with the overall survival and disease-specific survival in patients with LUAD (P < 0.05). We also found that the overexpression of KLRB1 can inhibit the proliferation, migration, and invasion of LUAD cells and promote apoptosis. KLRB1 was involved in immune cell differentiation, NF-kB, PD-L1, and PD-1 checkpoint pathways and others. Additionally, KLRB1 expression was linked to tumor purity, stromal, immune, and estimate scores, the levels of immune cells including B cells, CD8+ T cells, and CD4+ T cells, and immune cell markers in LUAD. Reduced KLRB1 expression has a significant positive correlation with diagnosis, poor prognosis, and immunity to cancer in patients with LUAD. KLRB1 inhibited cell proliferation and migration in patients with LUAD. These results suggest that KLRB1 may serve as a potential therapeutic target in patients with LUAD.

Safety and efficacy of Yaobitong capsules for lumbar disc herniation: A multicenter, randomized, double-blinded, parallel, positive-controlled clinical trial.

BACKGROUND: Lumbar disc herniation (LDH) is one of the most common diseases and is a global medical and socioeconomic problem characterized by leg or back pain, weakness in the lower extremities and paresthesia. OBJECTIVES: A multicenter, randomized, double-blinded, parallel, positive-controlled clinical trial was conducted to evaluate the efficacy and safety of Yaobitong capsules (YBT) for LDH. MATERIAL AND METHODS: Patients (n = 479) were recruited and randomized into YBT and Jingyaokang capsule (JYK) groups (the positive control), and received YBT or JYK at a dose of 3 capsules 3 times per day after a meal for 30 days. The primary efficacy outcome was the Oswestry Disability Index (ODI), with the visual analogue scale (VAS) used as the secondary efficacy outcome. The adverse events and adverse reactions were also evaluated. RESULTS: There was no significant difference in baseline characteristics between YBT (n = 358) and JYK groups (n = 120), and no difference was observed between groups for mean ODI score at day 0 (p = 0.064) or day 7 (p = 0.196), but there were differences at days 14, 21 and 30 (p < 0.001). The YBT showed more decline from baseline, and the decreased ODI score was substantially different from JYK (p < 0.001). The differences in decreased VAS scores between YBT and JYK were also significant at each time point (days 7, 14, 21, and 30), with better scores in the YBT group than in the JYK group (p < 0.001). In terms of safety, there was no obvious disparity in adverse events or adverse reactions between the 2 groups (p > 0.05). CONCLUSIONS: Yaobitong was better than JYK for LDH treatment, with no significant difference in safety. The study suggests that YBT is a promising and effective treatment for LDH.

Repeatability assessment of anterior segment measurements in myopic patients using an anterior segment OCT with placido corneal topography and agreement with a swept-source OCT.

BACKGROUND: The precision of anterior segment biometric measurements in eyes has become increasingly important in refractive surgery. The purpose of this study is to assess the repeatability of the automatic measurements provided by a new spectral-domain optical coherence tomograph (SD-OCT)/Placido topographer (MS-39, CSO) and its agreement with a swept-source OCT (SS-OCT) biometer (CASIA SS-1000, Tomey) in patients with myopia. METHODS: The right eye of 235 subjects was scanned 3 times with both devices. The evaluated parameters included central corneal radius of the steep meridian, central corneal radius of the flat meridian, mean central corneal radius, thinnest corneal thickness, central corneal thickness, anterior chamber depth, corneal volume and diameter. The intraobserver repeatability of the MS-39 measurements was calculated using intraclass correlation coefficient (ICC), within subject standard deviation, coefficient of repeatability, coefficient of variation and repeated-measures analysis of variance of the 3 repeated measurements. The agreement between the two devices was evaluated by 95% limits of agreement (LoA). RESULTS: The majority of the parameters acquired from MS-39 showed high repeatability. The repeatability of corneal diameter was slightly lower than the other measurements, although the ICC remained high. Agreement with the CASIA SS-1000 was good, indicated by the Bland-Altman plots with narrow 95% LoA values for all parameters assessed. CONCLUSIONS: The high repeatability of automatic measurements by the new device supports its clinical application in eyes with myopia, and the good agreement between the two devices indicates they could be used interchangeably for the parameters evaluated.

The Impact of Modified Body Mass Index on Clinical Prognosis in the Elderly With Acute Ischemic Stroke.

OBJECTIVES: The modified body mass index (mBMI) combines the body mass index and serum albumin, accurately reflecting the nutritional status. It remains uncertain whether modified body mass index influences neurological function and clinical prognosis in elderly patients with acute ischemic stroke. METHODS: We divided the cohort into quartiles of mBMI (1 to 4). The primary outcome was analyzed using the percentage of patients with a 90-day modified Rankin scale (mRS) score of 0 to 1. There were 7 secondary outcomes, including the disability level at 90 days and the National Institute of Health Stroke Scale (NIHSS) score at 14 and 90 days. RESULTS: mBMI was negatively associated with clinical prognosis at 90-day mRS score in the primary outcome (ß=-0.167; 95% CI -0.311 to 0.023, P=0.023). Moreover, mBMI1 (<896.72) and primary outcomes (ß=0.438; 95% CI: -0.018 to 0.894) were positively correlated with higher mBMI. Moreover, the number and percentage of patients completing all the duties and activities are also higher. Age-adjusted Charlson comorbidity index (aCCI) and posterior circulation lesion were positively associated with the clinical prognosis 90-day mRS score in the primary outcome (ß=2.218; 95% CI: 1.144-4.300, ß=2.771; 95% CI: 1.700-4.516). However, BMI and serum albumin were not associated the with clinical prognosis primary outcome. BMI negatively correlates with secondary outcomes (NIHSS at discharge, ß=-0.023; 95% CI: -0.102 to 0.057). CONCLUSIONS: Our study revealed that mBMI and not BMI could be a better primary outcome predictor in the elderly with acute ischemic stroke, and lower mBMI showed a worse prognosis.

Association between particulate air pollution and hypertensive disorders in pregnancy: A retrospective cohort study.

BACKGROUND: Epidemiological findings regarding the association of particulate matter ≤2.5 µm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. METHODS AND FINDINGS: A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly PM2.5 exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 µg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochran's Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. CONCLUSIONS: Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently.

20-year depressive symptoms, dementia, and structural neuropathology in older women.

INTRODUCTION: The course of depressive symptoms and dementia risk is unclear, as are potential structural neuropathological common causes. METHODS: Utilizing joint latent class mixture models, we identified longitudinal trajectories of annually assessed depressive symptoms and dementia risk over 21 years in 957 older women (baseline age 72.7 years old) from the Women's Health Initiative Memory Study. In a subsample of 569 women who underwent structural magnetic resonance imaging, we examined whether estimates of cerebrovascular disease and Alzheimer's disease (AD)-related neurodegeneration were associated with identified trajectories. RESULTS: Five trajectories of depressive symptoms and dementia risk were identified. Compared to women with minimal symptoms, women who reported mild and stable and emerging depressive symptoms were at the highest risk of developing dementia and had more cerebrovascular disease and AD-related neurodegeneration. DISCUSSION: There are heterogeneous profiles of depressive symptoms and dementia risk. Common neuropathological factors may contribute to both depression and dementia. Highlights The progression of depressive symptoms and concurrent dementia risk is heterogeneous. Emerging depressive symptoms may be a prodromal symptom of dementia. Cerebrovascular disease and AD are potentially shared neuropathological factors.

Olfactory deficit: a potential functional marker across the Alzheimer's disease continuum.

Alzheimer's disease (AD) is a prevalent form of dementia that affects an estimated 32 million individuals globally. Identifying early indicators is vital for screening at-risk populations and implementing timely interventions. At present, there is an urgent need for early and sensitive biomarkers to screen individuals at risk of AD. Among all sensory biomarkers, olfaction is currently one of the most promising indicators for AD. Olfactory dysfunction signifies a decline in the ability to detect, identify, or remember odors. Within the spectrum of AD, impairment in olfactory identification precedes detectable cognitive impairments, including mild cognitive impairment (MCI) and even the stage of subjective cognitive decline (SCD), by several years. Olfactory impairment is closely linked to the clinical symptoms and neuropathological biomarkers of AD, accompanied by significant structural and functional abnormalities in the brain. Olfactory behavior examination can subjectively evaluate the abilities of olfactory identification, threshold, and discrimination. Olfactory functional magnetic resonance imaging (fMRI) can provide a relatively objective assessment of olfactory capabilities, with the potential to become a promising tool for exploring the neural mechanisms of olfactory damage in AD. Here, we provide a timely review of recent literature on the characteristics, neuropathology, and examination of olfactory dysfunction in the AD continuum. We focus on the early changes in olfactory indicators detected by behavioral and fMRI assessments and discuss the potential of these techniques in MCI and preclinical AD. Despite the challenges and limitations of existing research, olfactory dysfunction has demonstrated its value in assessing neurodegenerative diseases and may serve as an early indicator of AD in the future.