Particulate matter and episodic memory decline mediated by early neuroanatomic biomarkers of Alzheimer's disease

Longitudinal associations between air pollution and incident dementia as mediated by MRI-measured brain volumes in the UK Biobank

BACKGROUND

Although there is increasing evidence that environmental exposures are associated with the risk of neurodegenerative conditions, there is still limited mechanistic evidence evaluating potential mediators in human populations.

METHODS

UK Biobank is a large long-term study of 500,000 adults enrolled from 2006 to 2010 age 40-69 years. ICD-10 classified reports of dementia cases up to 2022 (Alzheimer's disease, vascular dementia, dementia in other classified diseases, and unspecified dementia) were identified from health record linkage. Estimates of residential air pollution, traffic noise, and greenspace exposure have been modelled. Structural brain MRI was conducted from 2014 to 2022, with brain volumes relevant to dementia identified a priori. Associations between environmental exposures, brain volumes, and dementia cases (diagnosed post-MRI) were tested using linear and logistic regression and adjusted for age, sex, household income, ethnicity, education, smoking, and area-level deprivation. Mediation of exposure-outcome associations by plausible brain volumes (those associated with both environmental exposure and dementia outcomes) were modelled using the quasi-Bayesian Monte Carlo method (N = 34,817-39,772).

RESULTS

Small but significant mediating effects (2%-8% of relationships mediated) were observed between PM2.5abs exposure and dementia risk by reduced total brain volume, NOx and Alzheimer's disease risk by reduced peripheral cortical grey matter, PM2.5abs and vascular dementia risk by reduced peripheral cortical grey matter, PM2.5abs and other dementia risk by reduced total grey matter, and PM10 and other dementia risk by reduced total grey matter. Greenspace and noise were not associated with dementia outcomes in the subset of the cohort providing brain imaging data.

CONCLUSIONS

This study adds to existing evidence of associations between environmental exposures and dementia outcomes. Our findings provide novel evidence that differences in brain volume may mediate these relationships. Future research is required to prove this mechanism and establish the other mechanisms through which exposure to air pollution might increase dementia risk.

Particulate matter exposure and its consequences on hippocampal neurogenesis and cognitive function in experimental models

Exposure to air pollution is thought to cause millions of deaths globally each year. According to the Who 2018, approximately 7 million deaths annually are caused predominantly by noncommunicable diseases due to air pollution. Exposure to air particulate matter 2.5 (PM2.5) has been strongly associated with increased mortality and has significant effects on brain health. Air pollution, particularly ultrafine particulate matter, has emerged as a serious environmental concern with profound implications for human health. Studies in animal models have indicated that exposure to these pollutants during gestational development impacts prenatal and postnatal brain development. In particular, air pollution has been increasingly identified as a potential causative factor, as it affects neurogenesis in the brain's hippocampal region. The hippocampus is highly vulnerable to PM exposure, and any alteration in the structure or function of this region leads to various neurodevelopmental defects and neurodegenerative disorders via oxidative stress, microglial activation, neuronal death, and differential expression of genes. The neurogenesis process involves several steps, such as proliferation, differentiation, migration, synaptogenesis, and neuritogenesis. If any step of the neurogenesis process is hampered by environmental exposure or other factors, it can lead to neurodevelopmental defects, neurodegenerative disorders, and cognitive decline. One significant contributor to these alterations is air pollution, which ranks as the leading environmental risk factor worldwide. Some of the most common effects include oxidative stress, neuroinflammation, depressive behavior, altered cognitive processes, and microglial activation. This review explores how prenatal and postnatal PM exposure affects the hippocampal regions of the brain and the defects associated with exposure.

The enigma of mitochondrial epigenetic alterations in air pollution-induced neurodegenerative diseases

The incidence of neurodegenerative diseases is a growing concern worldwide, affecting individuals from diverse backgrounds. Although these pathologies are primarily associated with aging and genetic susceptibility, their severity varies among the affected population. Numerous studies have indicated air pollution as a significant contributor to the increasing prevalence of neurodegeneration. Cohort studies have provided compelling evidence of the association between prolonged exposure to different air toxicants and cognitive decline, behavioural deficits, memory impairment, and overall neuronal health deterioration. Furthermore, molecular research has revealed that air pollutants can disrupt the body's protective mechanisms, participate in neuroinflammatory pathways, and cause neuronal epigenetic modifications. The mitochondrial epigenome is particularly interesting to the scientific community due to its potential to significantly impact our understanding of neurodegenerative diseases' pathogenesis and their release in the peripheral circulation. While protein hallmarks have been extensively studied, the possibility of using circulating epigenetic signatures, such as methylated DNA fragments, miRNAs, and genome-associated factors, as diagnostic tools and therapeutic targets requires further groundwork. The utilization of circulating epigenetic signatures holds promise for developing novel prognostic strategies, creating paramount point-of-care devices for disease diagnosis, identifying therapeutic targets, and developing clinical data-based disease models utilizing multi-omics technologies and artificial intelligence, ultimately mitigating the threat and prevalence of neurodegeneration.

Residential blue space, cognitive function, and the role of air pollution in middle-aged and older adults: A cross-sectional study based on UK biobank

This study examines the relationship between residential exposure to blue spaces (e.g., rivers, lakes, and seas) and cognitive function in middle-aged and older adults in the United Kingdom, with a specific focus on the mediating effects of air pollution, particularly nitrogen dioxide (NO₂) and fine particulate matter (PM2.5). Cognitive function was assessed using touch screens at UK Biobank Assessment Centre, while residential blue space exposure within a 300-meter radius was estimated from land-use data. Annual average levels of air pollution, specifically NO₂ and PM2.5, were calculated through a land-use regression model. Logistic regression models analyzed the association between blue space exposure and cognitive function, and restricted cubic splines were employed to assess potential nonlinear relationships. Causal mediation analysis quantified the indirect effects of air pollution on this relationship. The study included 35,669 participants, revealing that high blue space exposure (≥75 %) was associated with a 13.2 % lower risk of cognitive impairment compared to those with low exposure (<25 %). Notably, NO₂ and PM2.5 significantly mediated this association, with indirect effects estimated at 9.5 % and 15.85 %, respectively. These findings indicate that increased residential exposure to blue spaces is linked to a reduced risk of cognitive impairment, highlighting the protective role of blue environments in the context of air pollution. This research underscores the importance of environmentally sensitive urban planning and policies to promote public health and cognitive well-being among vulnerable populations.

Assessing the Impact and Cost-Effectiveness of Exposome Interventions on Alzheimer's Disease: A Review of Agent-Based Modeling and Other Data Science Methods for Causal Inference

Background: The exposome (e.g., totality of environmental exposures) and its role in Alzheimer's Disease and Alzheimer's Disease and Related Dementias (AD/ADRD) are increasingly critical areas of study. However, little is known about how interventions on the exposome, including personal behavioral modification or policy-level interventions, may impact AD/ADRD disease burden at the population level in real-world settings and the cost-effectiveness of interventions. Methods: We performed a critical review to discuss the challenges in modeling exposome interventions on population-level AD/ADRD burden and the potential of using agent-based modeling (ABM) and other advanced data science methods for causal inference to achieve this. Results: We describe how ABM can be used for empirical causal inference modeling and provide a virtual laboratory for simulating the impacts of personal and policy-level interventions. These hypothetical experiments can provide insight into the optimal timing, targeting, and duration of interventions, identifying optimal combinations of interventions, and can be augmented with economic analyses to evaluate the cost-effectiveness of interventions. We also discuss other data science methods, including structural equation modeling and Mendelian randomization. Lastly, we discuss challenges in modeling the complex exposome, including high dimensional and sparse data, the need to account for dynamic changes over time and over the life course, and the role of exposome burden scores developed using item response theory models and artificial intelligence to address these challenges. Conclusions: This critical review highlights opportunities and challenges in modeling exposome interventions on population-level AD/ADRD disease burden while considering the cost-effectiveness of different interventions, which can be used to aid data-driven policy decisions.

Spatial regulation of NMN supplementation on brain lipid metabolism upon subacute and sub-chronic PM exposure in C57BL/6 mice

BACKGROUND

Atmospheric particulate matter (PM) exposure-induced neuroinflammation is critical in mediating nervous system impairment. However, effective intervention is yet to be developed.

RESULTS

In this study, we examine the effect of β-nicotinamide mononucleotide (NMN) supplementation on nervous system damage upon PM exposure and the mechanism of spatial regulation of lipid metabolism. 120 C57BL/6 male mice were exposed to real ambient PM for 11 days (subacute) or 16 weeks (sub-chronic). NMN supplementation boosted the level of nicotinamide adenine dinucleotide (NAD+) in the mouse brain by 2.04 times. This augmentation effectively reduced neuroinflammation, as evidenced by a marked decrease in activated microglia levels across various brain regions, ranging from 29.29 to 85.96%. Whole brain lipidomics analysis revealed that NMN intervention resulted in an less increased levels of ceramide (Cer) and lysophospholipid in the brain following subacute PM exposure, and reversed triglyceride (TG) and glycerophospholipids (GP) following sub-chronic PM exposure, which conferred mice with anti-neuroinflammation response, improved immune function, and enhanced membrane stability. In addition, we demonstrated that the hippocampus and hypothalamus might be the most sensitive brain regions in response to PM exposure and NMN supplementation. Particularly, the alteration of TG (60:10, 56:2, 60:7), diacylglycerol (DG, 42:6), and lysophosphatidylcholine (LPC, 18:3) are the most profound, which correlated with the changes in functional annotation and perturbation of pathways including oxidative stress, inflammation, and membrane instability unveiled by spatial transcriptomic analysis.

CONCLUSIONS

This study demonstrates that NMN intervention effectively reduces neuroinflammation in the hippocampus and hypothalamus after PM exposure by modulating spatial lipid metabolism. Strategies targeting the improvement of lipid homeostasis may provide significant protection against brain injury associated with air pollutant exposure.

Memory impairment and its associated risk and protective factors among older adults in Indonesia

AIMS

This study aimed to evaluate the association between memory impairment and its risk and protective factors, focusing on demographic and health-related variables among older adults in Indonesia.

METHOD

The data analyzed were the Indonesian Family Life Survey-5 (IFLS-5) using cross-sectional variables of 4236 older adults aged 60 years and over included in the 2015 round. Memory impairment was assessed by immediate word list recall from the Telephone Interview for Cognitive Status (TICS). Sociodemographic factors and multiple health variables were included as predictors. Data were analyzed using frequency analyses bivariate and stepwise logistic regression tests.

RESULT

Among 4236 older adults, 49.7% were male and 50.3% were female. Stepwise backward analyses showed that memory impairment was independently associated with older age, being female, or not in a union (unmarried, separated, divorced, or widowed), having obtained low levels of education, living in a rural area, reporting low life satisfaction, low social capital, higher dependency, and having clinical depression. Only moderate (but not high or low) physical activity levels were associated with a lower risk. Being underweight increased the risk, but being overweight/obese (as assessed by BMI) protective factors for a lower immediate recall score.

CONCLUSION

Increasing education and continued engagement of older adults in psychosocial activities, including moderate physical activity, improving mental health, preventing weight loss, and maintaining functional ability to decrease dependency, are associated with increased episodic memory, especially in non-married and older women in rural areas of Indonesia.

Toxic air pollution and cognitive decline: Untangling particulate matter

There is increasing evidence indicating air pollution is an important factor influencing the aging brain. However, much of this work measures air pollution using particulate matter (PM). Yet we know that the chemical components of PM are not consistent across space or time. Rather, the possible chemical mixtures of PM vary and are therefore not reliably measuring the same thing across studies. In this study we attempt to disentangle the effects of the components of measured PM by using estimates of concurrent exposures of 415 industrial air toxics, as well as 44 neuro- and developmental toxics. Using bivariate latent curve models, we leverage individual level panel data from the bi-annual Health and Retirement Study to test how these exposures relate to cognitive score trajectories of respondents across the years 2002-2012. We find that more exposure to neurotoxics was associated with faster rate of cognitive decline by 1.09 points (p < 0.05).

Efficacy of selective serotonin reuptake inhibitors-related antidepressants in Alzheimer's disease: a meta-analysis

OBJECTIVE

To study the effects of selective serotonin reuptake inhibitors (SSRIs) on cognitive functions, mental improvements, and adverse effects in patients with Alzheimer's disease (AD).

METHODS

Registered in INPLASY (INPLASY202450004), five drugs (citalopram, s-citalopram, quetiapine, olanzapine, and sertraline) were selected as representatives. A comprehensive search was conducted in PubMed, EMBASE, Web of Science, and the Cochrane Library up to May 15, 2024. Search terms were combined using Boolean operators, specifically 'AND' between different categories (e.g., 'Alzheimer's Disease' AND 'SSRIs') and 'OR' within the same category (e.g., 'citalopram OR s-citalopram OR quetiapine OR olanzapine OR sertraline'), to ensure a thorough retrieval of relevant studies. The selection followed rigorous inclusion and exclusion criteria for meta-analysis.

RESULTS

Fourteen articles from 1118 were selected for meta-analysis. The indicators, including Neuropsychiatric Inventory (NPI), Mini-Mental State Examination (MMSE), Brief Psychiatric Rating Scale (BPRS), and Cornell Scale for Depression in Dementia (CSDD), were used to assess the effects of the drugs on AD treatment. According to the results of NPI, CSDD, BPRS, MMSE, and security assessments, the five antidepressants have significant advantages in AD treatment compared with placebo, while the MMSE of the patient treated with the antidepressants did not show notable changes compared with patients treated only with placebo. Statistical analyses were conducted using Review Manager 5.3, employing random-effects models to account for study heterogeneity and sensitivity analyses to test the robustness of our findings.

CONCLUSION

This study suggests that SSRI-related antidepressants have great potential values in AD treatment, and further research on the application of SSRI-related antidepressants in AD treatment is necessary.

NLRP3/GSDMD mediated pyroptosis induces lung inflammation susceptibility in diesel exhaust exposed mouse strains

BACKGROUND

Genetic diversity among species influences the disease severity outcomes linked to air pollution. However, the mechanism responsible for this variability remain elusive and needs further investigation.

OBJECTIVE

To investigate the genetic factors and pathways linked with differential susceptibility in mouse strains associated with diesel exhaust exposure.

METHODS

C57BL/6 and Balb/c mice were exposed to diesel exhaust (DE) for 5 days/week for 30 min/day for 8 weeks. Body weight of mice was recorded every week and airway hyperresponsiveness towards DE exposure was recorded after 24 h of last exposure. Mice were euthanised to collect BALF, blood, lung tissues for immunobiochemical assays, structural integrity and genetic studies.

RESULTS

C57BL/6 mice showed significantly decreased body weight in comparison to Balb/c mice (p < 0.05). Both mouse strains showed lung resistance and damage to elastance upon DE exposure compared to respective controls (p < 0.05) with more pronounced effects in C57BL/6 mice. Lung histology showed increase in bronchiolar infiltration and damage to the wall in C57BL/6 mice (p < 0.05). DE exposure upregulated pro-inflammatory and Th2 cytokine levels in C57BL/6 in comparison to Balb/c mice. C57BL/6 mice showed increase in Caspase-1 and ASC expression confirming activation of downstream pathway. This showed significant activation of inflammasome pathway in C57BL/6 mice with ∼2-fold increase in NLRP3 and elevated IL-1β expression. Gasdermin-D levels were increased in C57BL/6 mice demonstrating induction of pyroptosis that corroborated with IL-1β secretion (p < 0.05). Genetic variability among both species was confirmed with sanger's sequencing suggesting presence of SNPs in 3'UTRs of IL-1β gene influencing expression between mouse strains.

CONCLUSIONS

C57BL/6 mice exhibited increased susceptibility to diesel exhaust in contrast to Balb/c mice via activation of NLRP3-related pyroptosis. Differential susceptibility between strains may be attributed via SNPs in the 3'UTRs of the IL-1β gene.

Environmental Toxins and Alzheimer's Disease: a Comprehensive Analysis of Pathogenic Mechanisms and Therapeutic Modulation

Alzheimer's disease is a leading cause of mortality worldwide. Inorganic and organic hazards, susceptibility to harmful metals, pesticides, agrochemicals, and air pollution are major environmental concerns. As merely 5% of AD cases are directly inherited indicating that these environmental factors play a major role in disease development. Long-term exposure to environmental toxins is believed to progress neuropathology, which leads to the development of AD. Numerous in-vitro and in-vivo studies have suggested the harmful impact of environmental toxins at cellular and molecular level. Common mechanisms involved in the toxicity of these environmental pollutants include oxidative stress, neuroinflammation, mitochondrial dysfunction, abnormal tau, and APP processing. Increased expression of GSK-3β, BACE-1, TNF-α, and pro-apoptotic molecules like caspases is observed upon exposure to these environmental toxins. In addition, the expression of neurotrophins like BDNF and GAP-43 have been found to be reduced as a result of toxicity. Further, modulation of signaling pathways involving PARP-1, PGC-1α, and MAPK/ERK induced by toxins have been reported to contribute in AD pathogenesis. These pathways are a promising target for developing novel AD therapeutics. Drugs like epigallocatechin-gallate, neflamapimod, salsalate, dexmedetomidine, and atabecestat are in different phases of clinical trials targeting the pathways for possible treatment of AD. This review aims to culminate the correlation between environmental toxicants and AD development. We emphasized upon the signaling pathways involved in the progression of the disease and the therapeutics under clinical trial targeting the altered pathways for possible treatment of AD.

Particulate matter constituents trigger the formation of extracellular amyloid β and Tau -containing plaques and neurite shortening in vitro

Air pollution is an environmental factor associated with an increased risk of neurodegenerative diseases, such as Alzheimer's and Parkinson's, characterized by decreased cognitive abilities and memory. The limited models of sporadic Alzheimer's disease fail to replicate all pathological hallmarks of the disease, making it challenging to uncover potential environmental causes. Environmentally driven models of Alzheimer's disease are thus timely and necessary. We used live-cell confocal fluorescent imaging combined with high-resolution stimulated emission depletion (STED) microscopy to follow the response of retinoic acid-differentiated human neuroblastoma SH-SY5Y cells to nanomaterial exposure. Here, we report that exposure of the cells to some particulate matter constituents reproduces a neurodegenerative phenotype, including extracellular amyloid beta-containing plaques and decreased neurite length. Consistent with the existing in vivo research, we observed detrimental effects, specifically a substantial reduction in neurite length and formation of amyloid beta plaques, after exposure to iron oxide and diesel exhaust particles. Conversely, after exposure to engineered cerium oxide nanoparticles, the lengths of neurites were maintained, and almost no extracellular amyloid beta plaques were formed. Although the exact mechanism behind this effect remains to be explained, the retinoic acid differentiated SH-SY5Y cell in vitro model could serve as an alternative, environmentally driven model of neurodegenerative diseases, including Alzheimer's disease.

Association Between Atopic Dermatitis and Aging: Clinical Observations and Underlying Mechanisms

As one of the most prevalent chronic inflammatory skin diseases, atopic dermatitis (AD) increasingly affects the aging population. Amid the ongoing global aging trend, it's essential to recognize the intricate relationship between AD and aging. This paper reviews existing knowledge, summarizing clinical observations of associations between AD and aging-related diseases in various systems, including endocrine, cardiovascular, and neurological. Additionally, it discusses major theories explaining the correlation, encompassing skin-mucosal barriers, systemic inflammation and stress, genes, signal transduction, and environmental and behavioral factors. The association between AD and aging holds significant importance, both in population and basic perspectives. While further research is warranted, this paper aims to inspire deeper exploration of inflammation/allergy-aging dynamics and the timely management of elderly patients with AD.

Cellular senescence mediates hexavalent chromium-associated lung function decline: Insights from a structural equation Model

There is sufficient evidence suggesting that exposure to hexavalent chromium [Cr(VI)] can cause a decline in lung function and the onset of lung diseases. However, no studies have yet explored the underlying mechanisms of these effects from various perspectives such as systemic inflammation, oxidative stress, and cellular senescence, simultaneously. This cross-sectional study was conducted among 304 workers engaged in chromate production and processing in China. Urine was used for detection of 8-hydroxy-2'-deoxyguanosine (8-OHdG) and 8-iso-prostaglandin F2α (8-iso-PGF2α), while RNA and DNA extraction from peripheral blood cells was used for detection of mRNA, telomere length, and ribosomal DNA copy numbers (rDNA CNs). A 2.7-fold elevation in blood chromate (Cr) corresponded to a 7.86% (95% CI: 2.57%, 13.42%) rise in urinary 8-OHdG and a 4.14% (0.02%, 8.42%) increase in urinary 8-iso-PGF2α, indicating that exposure to chromates can cause oxidative stress. Furthermore, strong correlations emerged between blood Cr concentration and mRNA levels of P16, P21, TP53, and P15 in the cellular senescence pathway. Simultaneously, a 2.7-fold elevation in blood Cr associated with a -5.47% (-8.72%, -2.1%) change in telomere length, while rDNA CNs (5S, 5.8S, 18S, and 28S) changed by -3.91% (-7.99%, 0.34%), -9.4% (-15.73%, -2.6%), -8.06% (-14.01%, -1.69%), and -5.86% (-10.67%, -0.78%), respectively. Structural equation model highlighted that cellular senescence exerted significant indirect effects on Cr(VI)-associated lung function decline, with a mediation proportion of 23.3%. This study provided data supporting for 8-iso-PGF2α, telomere length, and rDNA CNs as novel biomarkers of chromate exposure, emphasizing the significant role of cellular senescence in the mechanism underlying chromate-induced lung function decline.

Changes in SOD and NF-κB Levels in Substantia Nigra and the Intestine through Oxidative Stress Effects in a Wistar Rat Model of Ozone Pollution

This work aimed to elucidate how O3 pollution causes a loss of regulation in the immune response in both the brain and the intestine. In this work, we studied the effect of exposing rats to low doses of O3 based on the association between the antioxidant response of superoxide dismutase (SOD) levels and the nuclear factor kappa light chains of activated B cells (NFκB) as markers of inflammation. Method: Seventy-two Wistar rats were used, divided into six groups that received the following treatments: Control and 7, 15, 30, 60, and 90 days of O3. After treatment, tissues were extracted and processed using Western blotting, biochemical, and immunohistochemical techniques. The results indicated an increase in 4-hydroxynonenal (4HNE) and Cu/Zn-SOD and a decrease in Mn-SOD, and SOD activity in the substantia nigra, jejunum, and colon decreased. Furthermore, the translocation of NFκB to the nucleus increased in the different organs studied. In conclusion, repeated exposure to O3 alters the regulation of the antioxidant and inflammatory response in the substantia nigra and the intestine. This indicates that these factors are critical in the loss of regulation in the inflammatory response; they respond to ozone pollution, which can occur in chronic degenerative diseases.

Role of the Exposome in Neurodegenerative Disease: Recent Insights and Future Directions

Neurodegenerative diseases are increasing in prevalence and place a significant burden on society. The causes are multifactorial and complex, and increasing evidence suggests a dynamic interplay between genes and the environment, emphasizing the importance of identifying and understanding the role of lifelong exposures, known as the exposome, on the nervous system. This review provides an overview of recent advances toward defining neurodegenerative disease exposomes, focusing on Parkinson's disease, amyotrophic lateral sclerosis, and Alzheimer's disease. We present the current state of the field based on emerging data, elaborate on key themes and potential mechanisms, and conclude with limitations and future directions. ANN NEUROL 2024;95:635-652.

PM2.5 induce neurotoxicity via iron overload and redox imbalance mediated-ferroptosis in HT22 cells

PM2.5 is an important risk factor for the development and progression of cognitive impairment-related diseases. Ferroptosis, a new form of cell death driven by iron overload and lipid peroxidation, is proposed to have significant implications. To verify the possible role of ferroptosis in PM2.5-induced neurotoxicity, we investigated the cytotoxicity, intracellular iron content, iron metabolism-related genes, oxidative stress indices and indicators involving in Nrf2 and ferroptosis signaling pathways. Neurotoxicity biomarkers as well as the ferroptotic cell morphological changes were determined by Western Blot and TEM analysis. Our results revealed that PM2.5 induced cytotoxicity, lipid peroxidation, as indicated by MDA content, and neurotoxicity via Aβ deposition in a dose-related manner. Decreased cell viability and excessive iron accumulation in HT-22 cells can be partially blocked by ferroptosis inhibitors. Interestingly, GPX activity, Nrf2, and its regulated ferroptotic-related proteins (i.e. GPX4 and HO-1) were significantly up-regulated by PM2.5. Moreover, gene expression of DMT1, TfR1, IRP2 and FPN1 involved in iron homeostasis and NCOA4-dependent ferritinophagy were activated after PM2.5 exposure. The results demonstrated that PM2.5 triggered ferritinophagy-dependent ferroptotic cell death due to iron overload and redox imbalance. Activation of Nrf2 signaling pathways may confer a protective mechanism for PM2.5-induced oxidative stress and ferroptosis.

Elossaily G, Vellapandian C, Prajapati B. Investigating the Potential Impact of Air Pollution on Alzheimer's Disease and the Utility of Multidimensional Imaging for Early Detection

Pollution is ubiquitous, and much of it is anthropogenic in nature, which is a severe risk factor not only for respiratory infections or asthma sufferers but also for Alzheimer's disease, which has received a lot of attention recently. This Review aims to investigate the primary environmental risk factors and their profound impact on Alzheimer's disease. It underscores the pivotal role of multidimensional imaging in early disease identification and prevention. Conducting a comprehensive review, we delved into a plethora of literature sources available through esteemed databases, including Science Direct, Google Scholar, Scopus, Cochrane, and PubMed. Our search strategy incorporated keywords such as "Alzheimer Disease", "Alzheimer's", "Dementia", "Oxidative Stress", and "Phytotherapy" in conjunction with "Criteria Pollutants", "Imaging", "Pathology", and "Particulate Matter". Alzheimer's disease is not only a result of complex biological factors but is exacerbated by the infiltration of airborne particles and gases that surreptitiously breach the nasal defenses to traverse the brain, akin to a Trojan horse. Various imaging modalities and noninvasive techniques have been harnessed to identify disease progression in its incipient stages. However, each imaging approach possesses inherent limitations, prompting exploration of a unified technique under a single umbrella. Multidimensional imaging stands as the linchpin for detecting and forestalling the relentless march of Alzheimer's disease. Given the intricate etiology of the condition, identifying a prospective candidate for Alzheimer's disease may take decades, rendering the development of a multimodal imaging technique an imperative. This research underscores the pressing need to recognize the chronic ramifications of invisible particulate matter and to advance our understanding of the insidious environmental factors that contribute to Alzheimer's disease.

Causal relationship of genetically predicted particulate matter 2.5 level with Alzheimer's disease and the mediating effect of dehydroepiandrosterone sulphate

BACKGROUND

The causal association between particulate matter 2.5 (PM2.5) and Alzheimer's disease (AD) remains inconclusive, and the mediators of the association have yet to be explored.

AIMS

We aimed to assess the potential causal relationship between PM2.5 and AD, and to investigate the mediating role of dehydroepiandrosterone sulphate (DHEAS).

SUBJECTS AND METHODS

We implemented a two-sample Mendelian randomisation (MR) study to examine the genetic predisposition to PM2.5 exposure and its association with AD. The inverse-variance weighted (IVW) method served as the primary analytical tool to estimate the odds ratio (OR) and 95% confidence interval (95% CI).

RESULTS

There were 6 and 4 genetic variants associated with DHEAS and PM2.5, respectively. Based on the multivariable MR analysis, we found that after adjusting for DHEAS, each standard deviation increase in PM2.5 was associated with the risk of AD (OR: 2.96, 95% CI: 1.33, 6.58, p = 0.00769). The MR Egger intercept test did not detect horizontal pleiotropy for PM2.5 (P-pleiotropy = 0.879) and DHEAS(P-pleiotropy = 0.941). According to the results of the mediation analysis, DHEAS accounted for 18.3% of the association between PM2.5 and AD.

CONCLUSION

Our findings affirm a significant causal association between PM2.5 exposure and AD, with DHEAS playing a mediating role in this relationship.

Particulate Matter in Human Elderly: Higher Susceptibility to Cognitive Decline and Age-Related Diseases

This review highlights the significant impact of air quality, specifically particulate matter (PM), on cognitive decline and age-related diseases in the elderly. Despite established links to other pathologies, such as respiratory and cardiovascular illnesses, there is a pressing need for increased attention to the association between air pollution and cognitive aging, given the rising prevalence of neurocognitive disorders. PM sources are from diverse origins, including industrial activities and combustion engines, categorized into PM10, PM2.5, and ultrafine PM (UFPM), and emphasized health risks from both outdoor and indoor exposure. Long-term PM exposure, notably PM2.5, has correlated with declines in cognitive function, with a specific vulnerability observed in women. Recently, extracellular vesicles (EVs) have been explored due to the interplay between them, PM exposure, and human aging, highlighting the crucial role of EVs, especially exosomes, in mediating the complex relationship between PM exposure and chronic diseases, particularly neurological disorders. To sum up, we have compiled the pieces of evidence that show the potential contribution of PM exposure to cognitive aging and the role of EVs in mediating PM-induced cognitive impairment, which presents a promising avenue for future research and development of therapeutic strategies. Finally, this review emphasizes the need for policy changes and increased public awareness to mitigate air pollution, especially among vulnerable populations such as the elderly.

Application of machine learning in measurement of ageing and geriatric diseases: a systematic review

BACKGROUND

As the ageing population continues to grow in many countries, the prevalence of geriatric diseases is on the rise. In response, healthcare providers are exploring novel methods to enhance the quality of life for the elderly. Over the last decade, there has been a remarkable surge in the use of machine learning in geriatric diseases and care. Machine learning has emerged as a promising tool for the diagnosis, treatment, and management of these conditions. Hence, our study aims to find out the present state of research in geriatrics and the application of machine learning methods in this area.

METHODS

This systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and focused on healthy ageing in individuals aged 45 and above, with a specific emphasis on the diseases that commonly occur during this process. The study mainly focused on three areas, that are machine learning, the geriatric population, and diseases. Peer-reviewed articles were searched in the PubMed and Scopus databases with inclusion criteria of population above 45 years, must have used machine learning methods, and availability of full text. To assess the quality of the studies, Joanna Briggs Institute's (JBI) critical appraisal tool was used.

RESULTS

A total of 70 papers were selected from the 120 identified papers after going through title screening, abstract screening, and reference search. Limited research is available on predicting biological or brain age using deep learning and different supervised machine learning methods. Neurodegenerative disorders were found to be the most researched disease, in which Alzheimer's disease was focused the most. Among non-communicable diseases, diabetes mellitus, hypertension, cancer, kidney diseases, and cardiovascular diseases were included, and other rare diseases like oral health-related diseases and bone diseases were also explored in some papers. In terms of the application of machine learning, risk prediction was the most common approach. Half of the studies have used supervised machine learning algorithms, among which logistic regression, random forest, XG Boost were frequently used methods. These machine learning methods were applied to a variety of datasets including population-based surveys, hospital records, and digitally traced data.

CONCLUSION

The review identified a wide range of studies that employed machine learning algorithms to analyse various diseases and datasets. While the application of machine learning in geriatrics and care has been well-explored, there is still room for future development, particularly in validating models across diverse populations and utilizing personalized digital datasets for customized patient-centric care in older populations. Further, we suggest a scope of Machine Learning in generating comparable ageing indices such as successful ageing index.

Application of TCN-biGRU neural network in [Formula: see text] concentration prediction

Fine particulate matter ([Formula: see text]) poses a significant threat to human life and health, and therefore, accurately predicting [Formula: see text] concentration is critical for controlling air pollution. Two improved types of recurrent neural networks (RNNs), the long short-term memory (LSTM) and gated recurrent unit (GRU), have been widely used in time series data prediction due to their ability to capture temporal features. However, both degrade into random guessing as the time length increases. In order to enhance the accuracy of [Formula: see text] concentration prediction and address the issue of random guessing in RNNs neural networks, this study introduces a TCN-biGRU neural network model. This model is a hybrid prediction approach based on combining temporal convolutional networks (TCN) and bidirectional gated recurrent units (bi-GRU). TCN extracts higher-level feature information from longer time series data of [Formula: see text] concentrations, while bi-GRU captures features from past and future data to achieve more accurate predictive outcomes. This case study utilizes data from monitoring stations in Beijing in 2021 for conducting [Formula: see text] prediction experiments. The TCN-biGRU model achieves an average absolute error, root mean square error, and [Formula: see text] of 4.20, 7.71, and 0.961 in its predictive outcomes. When compared to the predictive outcomes of individual LSTM, GRU, and bi-GRU models, it is evident that the TCN-biGRU model exhibits smaller errors and superior predictive performance.

TREM2 mitigates NLRP3-mediated neuroinflammation through the NF-κB and PI3k/Akt signaling pathways in juvenile rats exposed to ambient particulate matter

Ambient particulate matter (PM) is a global public and environmental problem. PM is closely associated with several neurological disorders that typically involve neuroinflammation. There have been few studies on the effect of PM on neuroinflammation to date. In this study, we used a juvenile rat model (PM exposure was conducted at a dose of 10 mg/kg body weight per day for 4 weeks) and a BV-2 cell model (PM exposure was conducted at concentrations of 50, 100, 150, and 200 μg/ml for 24 h) to investigate PM-induced neuroinflammation mediated by NLRP3 inflammasome activation and the role of TREM2 in this process. Our findings revealed that PM exposure reduced TREM2 protein and mRNA levels in the rat hippocampus and BV-2 cells. TREM2 overexpression attenuated PM-induced spatial learning and memory deficits in rats. Moreover, we observed that TREM2 overexpression in vivo and in vitro effectively mitigated the increase in NLRP3 and pro-Caspase1 protein expression, as well as the secretion of IL-1β and IL-18. Exposure to PM increased the expression of NF-κB and decreased the phosphorylation of PI3k/Akt in vivo and in vitro, and this process was effectively reversed by overexpressing TREM2. Our results indicated that PM exposure could reduce TREM2 expression and induce NLRP3 inflammasome-mediated neuroinflammation and that TREM2 could mitigate NLRP3 inflammasome-mediated neuroinflammation by regulating the NF-κB and PI3k/Akt signaling pathways. These findings shed light on PM-induced neuroinflammation mechanisms and potential intervention targets.

Long-Term PM2.5 Exposure, Lung Function, and Cognitive Function Among Middle-Aged and Older Adults in China

BACKGROUND

Long-term exposure to PM2.5 is related to poor lung function and cognitive impairment, but less is known about the pathway involved in this association. We aimed to explore whether the effect of PM2.5 on cognitive function was mediated by lung function.

METHODS

A total of 7 915 adults older than 45 years old were derived from the China Health and Retirement Longitudinal Study (CHARLS) collected in 2011 and 2015. PM2.5 exposure was estimated using a geographically weighted regression model. Lung function was measured by peak expiratory flow (PEF). Cognitive function was evaluated through a structured questionnaire with 4 dimensions: episodic memory, attention, orientation, and visuoconstruction. Under the counterfactual framework, causal mediation analysis was applied to examine direct and indirect associations.

RESULTS

An interquartile range (IQR) increase in PM2.5 change was significantly related to an 8.480 (95% confidence interval [CI]: 3.116, 13.845) decrease in PEF change and a 0.301 (95% CI: 0.100, 0.575) decrease in global cognitive score change. The direct and indirect effects of PM2.5 exposure on global cognitive performance were -0.279 (95% CI: -0.551, -0.060) and -0.023 (95% CI: -0.041, -0.010), respectively. The proportion of the indirect effect was 7.48% (p = .010). The same significant association appeared in only 2 dimensions, episodic memory and attention, which were both mediated by PEF.

CONCLUSIONS

Lung function played a partially mediating role in the association between long-term PM2.5 exposure and cognition. More clean air actions should be undertaken to improve lung function and cognitive function in older adults.

Association between late-life air pollution exposure and medial temporal lobe atrophy in older women

Background

Ambient air pollution exposures increase risk for Alzheimer's disease (AD) and related dementias, possibly due to structural changes in the medial temporal lobe (MTL). However, existing MRI studies examining exposure effects on the MTL were cross-sectional and focused on the hippocampus, yielding mixed results.

Method

To determine whether air pollution exposures were associated with MTL atrophy over time, we conducted a longitudinal study including 653 cognitively unimpaired community-dwelling older women from the Women's Health Initiative Memory Study with two MRI brain scans (MRI-1: 2005-6; MRI-2: 2009-10; Mage at MRI-1=77.3±3.5years). Using regionalized universal kriging models, exposures at residential locations were estimated as 3-year annual averages of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) prior to MRI-1. Bilateral gray matter volumes of the hippocampus, amygdala, parahippocampal gyrus (PHG), and entorhinal cortex (ERC) were summed to operationalize the MTL. We used linear regressions to estimate exposure effects on 5-year volume changes in the MTL and its subregions, adjusting for intracranial volume, sociodemographic, lifestyle, and clinical characteristics.

Results

On average, MTL volume decreased by 0.53±1.00cm3 over 5 years. For each interquartile increase of PM2.5 (3.26μg/m3) and NO2 (6.77ppb), adjusted MTL volume had greater shrinkage by 0.32cm3 (95%CI=[-0.43, -0.21]) and 0.12cm3 (95%CI=[-0.22, -0.01]), respectively. The exposure effects did not differ by APOE ε4 genotype, sociodemographic, and cardiovascular risk factors, and remained among women with low-level PM2.5 exposure. Greater PHG atrophy was associated with higher PM2.5 (b=-0.24, 95%CI=[-0.29, -0.19]) and NO2 exposures (b=-0.09, 95%CI=[-0.14, -0.04]). Higher exposure to PM2.5 but not NO2 was also associated with greater ERC atrophy. Exposures were not associated with amygdala or hippocampal atrophy.

Conclusion

In summary, higher late-life PM2.5 and NO2 exposures were associated with greater MTL atrophy over time in cognitively unimpaired older women. The PHG and ERC - the MTL cortical subregions where AD neuropathologies likely begin, may be preferentially vulnerable to air pollution neurotoxicity.

Alzheimer's Related Neurodegeneration Mediates Air Pollution Effects on Medial Temporal Lobe Atrophy

Exposure to ambient air pollution, especially particulate matter with aerodynamic diameter <2.5 μm (PM2.5) and nitrogen dioxide (NO2), are environmental risk factors for Alzheimer's disease and related dementia. The medial temporal lobe (MTL) is an important brain region subserving episodic memory that atrophies with age, during the Alzheimer's disease continuum, and is vulnerable to the effects of cerebrovascular disease. Despite the importance of air pollution it is unclear whether exposure leads to atrophy of the MTL and by what pathways. Here we conducted a longitudinal study examining associations between ambient air pollution exposure and MTL atrophy and whether putative air pollution exposure effects resembled Alzheimer's disease-related neurodegeneration or cerebrovascular disease-related neurodegeneration. Participants included older women (n = 627; aged 71-87) who underwent two structural brain MRI scans (MRI-1: 2005-6; MRI-2: 2009-10) as part of the Women's Health Initiative Memory Study of Magnetic Resonance Imaging. Regionalized universal kriging was used to estimate annual concentrations of PM2.5 and NO2 at residential locations aggregated to 3-year averages prior to MRI-1. The outcome was 5-year standardized change in MTL volumes. Mediators included voxel-based MRI measures of the spatial pattern of neurodegeneration of Alzheimer's disease (Alzheimer's disease pattern similarity scores [AD-PS]) and whole-brain white matter small-vessel ischemic disease (WM-SVID) volume as a proxy of global cerebrovascular damage. Structural equation models were constructed to examine whether the associations between exposures with MTL atrophy were mediated by the initial level or concurrent change in AD-PS score or WM-SVID while adjusting for sociodemographic, lifestyle, clinical characteristics, and intracranial volume. Living in locations with higher PM2.5 (per interquartile range [IQR]=3.17μg/m3) or NO2 (per IQR=6.63ppb) was associated with greater MTL atrophy (βPM2.5 = -0.29, 95% confidence interval [CI]=[-0.41,-0.18]; βNO2 =-0.12, 95%CI=[-0.23,-0.02]). Greater PM2.5 was associated with larger increases in AD-PS (βPM2.5 = 0.23, 95%CI=[0.12,0.33]) over time, which partially mediated associations with MTL atrophy (indirect effect= -0.10; 95%CI=[-0.15, -0.05]), explaining approximately 32% of the total effect. NO2 was positively associated with AD-PS at MRI-1 (βNO2=0.13, 95%CI=[0.03,0.24]), which partially mediated the association with MTL atrophy (indirect effect= -0.01, 95% CI=[-0.03,-0.001]). Global WM-SVID at MRI-1 or concurrent change were not significant mediators between exposures and MTL atrophy. Findings support the mediating role of Alzheimer's disease-related neurodegeneration contributing to MTL atrophy associated with late-life exposures to air pollutants. Alzheimer's disease-related neurodegeneration only partially explained associations between exposure and MTL atrophy suggesting the role of multiple neuropathological processes underlying air pollution neurotoxicity on brain aging.

Environmental pollutants induce NLRP3 inflammasome activation and pyroptosis: Roles and mechanisms in various diseases

Environmental pollution is changing with economic development. Most environmental pollutants are characterized by stable chemical properties, strong migration, potential toxicity, and multiple exposure routes. Harmful substances are discharged excessively, and large quantities of unknown new compounds are emerging, being transmitted and amplifying in the food chain. The increasingly severe problems of environmental pollution have forced people to re-examine the relationship between environmental pollution and health. Pyroptosis and activation of the NLRP3 inflammasome are critical in maintaining the immune balance and regulating the inflammatory process. Numerous diseases caused by environmental pollutants are closely related to NLRP3 inflammasome activation and pyroptosis. We intend to systematically explain the steps and important events that are common in life but easily overlooked by which environmental pollutants activate the NLRP3 inflammasome and pyroptosis pathways. This comprehensive review also discusses the interaction network between environmental pollutants, the NLRP3 inflammasome, pyroptosis, and diseases. Thus, research progress on the impact of decreasing oxidative stress levels to inhibit the NLRP3 inflammasome and pyroptosis, thereby repairing homeostasis and reshaping health, is systematically examined. This review aims to deepen the understanding of the impact of environmental pollutants on life and health and provide a theoretical basis and potential programs for the development of corresponding treatment strategies.

Amyloid β-Oligomers Inhibit the Nuclear Ca2+ Signals and the Neuroprotective Gene Expression Induced by Gabazine in Hippocampal Neurons

Hippocampal neuronal activity generates dendritic and somatic Ca2+ signals, which, depending on stimulus intensity, rapidly propagate to the nucleus and induce the expression of transcription factors and genes with crucial roles in cognitive functions. Soluble amyloid-beta oligomers (AβOs), the main synaptotoxins engaged in the pathogenesis of Alzheimer's disease, generate aberrant Ca2+ signals in primary hippocampal neurons, increase their oxidative tone and disrupt structural plasticity. Here, we explored the effects of sub-lethal AβOs concentrations on activity-generated nuclear Ca2+ signals and on the Ca2+-dependent expression of neuroprotective genes. To induce neuronal activity, neuron-enriched primary hippocampal cultures were treated with the GABAA receptor blocker gabazine (GBZ), and nuclear Ca2+ signals were measured in AβOs-treated or control neurons transfected with a genetically encoded nuclear Ca2+ sensor. Incubation (6 h) with AβOs significantly reduced the nuclear Ca2+ signals and the enhanced phosphorylation of cyclic AMP response element-binding protein (CREB) induced by GBZ. Likewise, incubation (6 h) with AβOs significantly reduced the GBZ-induced increases in the mRNA levels of neuronal Per-Arnt-Sim domain protein 4 (Npas4), brain-derived neurotrophic factor (BDNF), ryanodine receptor type-2 (RyR2), and the antioxidant enzyme NADPH-quinone oxidoreductase (Nqo1). Based on these findings we propose that AβOs, by inhibiting the generation of activity-induced nuclear Ca2+ signals, disrupt key neuroprotective gene expression pathways required for hippocampal-dependent learning and memory processes.

Particulate matter exposure and neurodegenerative diseases: A comprehensive update on toxicity and mechanisms

Exposure to particulate matter (PM) has been associated with a range of health impacts, including neurological abnormalities that affect neurodevelopment, neuroplasticity, and behavior. Recently, there has been growing interest in investigating the possible relationship between PM exposure and the onset and progression of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis. However, the precise mechanism by which PM affects neurodegeneration is still unclear, even though several epidemiological and animal model studies have provided mechanistic insights. This article presents a review of the current research on the neurotoxicity of PM and its impact on neurodegenerative diseases. This review summarizes findings from epidemiological and animal model studies collected through searches in Google Scholar, PubMed, Web of Science, and Scopus. This review paper also discusses the reported effects of PM exposure on the central nervous system and highlights research gaps and future directions. The information presented in this review may inform public health policies aimed at reducing PM exposure and may contribute to the development of new treatments for neurodegenerative diseases. Further mechanistic and therapeutic research will be needed to fully understand the relationship between PM exposure and neurodegenerative diseases.

The association between polluted fuel use and self-reported insomnia symptoms among middle-aged and elderly Indian adults: a cross-sectional study based on LASI, wave 1

BACKGROUND

Insomnia predisposes the aging population to reduced quality of life and poor mental and physical health. Evidence of the association between polluted fuel use and insomnia symptoms is limited and is non-existent for the Indian population. Our study aimed to explore the link between polluted fuel use and insomnia symptoms in middle-aged and older (≥ 45 years) Indian populations.

METHODS

We utilized data from nationally representative Longitudinal Aging Study in India (LASI) Wave 1. Participants with complete information on fuel use, insomnia symptoms, and covariates were included. Insomnia symptoms were indicated by the presence of at least one of three symptoms: difficulty in initiating sleep (DIS), difficulty in maintaining sleep (DMS), or early morning awakening (EMA), ≥ 5 times/week. Survey-weighted multivariable logistic regression analyses were conducted to evaluate the association between polluted fuel use and insomnia symptoms. We also assessed the interaction of association in subgroups of age, gender, BMI, drinking, and smoking status.

RESULTS

Sixty thousand five hundred fifteen participants met the eligibility criteria. Twenty-eight thousand two hundred thirty-six (weighted percentage 48.04%) used polluted fuel and 5461 (weighted percentage 9.90%) reported insomnia symptoms. After full adjustment, polluted fuel use was associated with insomnia symptoms (OR 1.16; 95%CI 1.08-1.24) and was linked with DIS, DMS, and EMA (OR 1.14; 95%CI 1.05-1.24, OR 1.12; 95%CI 1.03-1.22, and OR 1.15; 95%CI 1.06-1.25, respectively). No significant interactions for polluted fuel use and insomnia symptoms were observed for analyses stratified by age, sex, BMI, drinking, or smoking.

CONCLUSIONS

Polluted fuel use was positively related to insomnia symptoms among middle-aged and older Indians. Suggestions are offered within this article for further studies to confirm our results, to explore underlying mechanisms, and to inform intervention strategies.

A study on specific factors related to inflammation and autophagy in BEAS-2B cells induced by urban particulate matter (PM, 1648a) and histological evaluation of PM-induced bronchial asthma model in mice

As particulate matter (PM) poses an increasing risk, research on its correlation with diseases is active. However, researchers often use their own PM, making it difficult to determine its components. To address this, we investigated the effects of PM with known constituents on BEAS-2B cells, examining cytokine levels, reactive oxygen species ROS production, DNA damage, and MAPK phosphorylation. Additionally, we evaluated the effects of PM on normal and OVA-induced asthmatic mice by measuring organ weight, cytokine levels, and inflammatory cells in bronchoalveolar lavage fluid, and examining histological changes. PM markedly increased levels of IL-6, GM-CSF, TNF-α, ROS, nitric oxide, and DNA damage, while surprisingly reducing IL-8 and MCP-1. Moreover, PM increased MAPK phosphorylation and inhibited mTOR and AKT phosphorylation. In vivo, lung and spleen weights, IgE, OVA-specific IgE, IL-4, IL-13, total cells, macrophages, lymphocytes, mucus generation, and LC3II were higher in the asthma group. PM treatment in asthmatic mice increased lung weight and macrophage infiltration, but decreased IL-4 and IL-13 in BALF. Meanwhile, PM treatment in the Nor group increased total cells, macrophages, lymphocytes, and mucus generation. Our study suggests that PM may induce and exacerbate lung disease by causing immune imbalance via the MAPK and autophagy pathways, resulting in decreased lung function due to increased smooth muscle thickness and mucus generation.

NEUROMETABOLOMIC IMPACTS OF MODELED WILDFIRE SMOKE AND PROTECTIVE BENEFITS OF ANTI-AGING THERAPEUTICS IN AGED FEMALE C57BL/6J MICE

Wildland fires have become progressively more extensive over the past 30 years in the US, and now routinely generate smoke that deteriorates air quality for most of the country. We explored the neurometabolomic impact that smoke derived from biomass has on older (18 months) female C57BL/6J mice, both acutely and after 10 weeks of recovery from exposures. Mice (N=6/group) were exposed to wood smoke (WS) 4 hours/day, every other day, for 2 weeks (7 exposures total) to an average concentration of 0.448mg/m 3 per exposure. One group was euthanized 24 hours after the last exposure. Other groups were then placed on 1 of 4 treatment regimens for 10 weeks after wood smoke exposures: vehicle; resveratrol in chow plus nicotinamide mononucleotide in water (RNMN); senolytics via gavage (dasatanib+quercetin; DQ); or both RNMN with DQ (RNDQ). Among the findings, the aging from 18 months to 21 months was associated with the greatest metabolic shift, including changes in nicotinamide metabolism, with WS exposure effects that were relatively modest. WS caused a reduction in NAD+ within the prefrontal cortex immediately after exposure and a long-term reduction in serotonin that persisted for 10 weeks. The serotonin reductions were corroborated by forced swim tests, which revealed an increased immobility (reduction in motivation) immediately post-exposure and persisted for 10 weeks. RNMN had the most beneficial effects after WS exposure, while RNDQ caused markers of brain aging to be upregulated within WS-exposed mice. Findings highlight the persistent neurometabolomic and behavioral effects of woodsmoke exposure in an aged mouse model.

Significance Statement

Neurological impacts of wildfire smoke are largely underexplored but include neuroinflammation and metabolic changes. The present study highlights modulation of major metabolites in the prefrontal cortex and behavioral consequences in aged (18 month) female mice that persists 10 weeks after wood smoke exposure ended. Supplements derived from the anti-aging field were able to mitigate much of the woodsmoke effect, especially a combination of resveratrol and nicotinamide mononucleotide.

Effect of acupuncture on episodic memory for amnesia-type mild cognitive impairment: study protocol of a multicenter, randomized, controlled trial

BACKGROUND

Amnesic mild cognitive impairment (aMCI) is the main subtype of mild cognitive impairment (MCI) and has the highest risk of conversion to Alzheimer's disease (AD) among all MCI subtypes. Episodic memory impairment is the early cognitive impairment of aMCI, which has become an important target for AD prevention. Previous clinical evidence has shown that acupuncture can improve the cognitive ability of MCI patients. This experiment aimed to observe the efficacy and neural mechanism of TiaoshenYizhi acupuncture on the episodic memory of patients with aMCI.

METHODS

In this multicenter, parallel-group, double-blind, randomized controlled trial, 360 aMCI participants will be recruited from six subcenters and randomly assigned to the acupuncture group, sham acupuncture group, and control group. The acupuncture group will receive TiaoshenYizhi (TSYZ) acupuncture, the sham acupuncture group will use streitberger sham acupuncture, and the control group will only receive free health education. Participants in the two acupuncture groups will receive real acupuncture treatment or placebo acupuncture three times per week, 24 sessions over 8 consecutive weeks. The primary outcome will be global cognitive ability. Secondary outcomes will be a specific cognitive domain, including episodic memory and execution ability, electroencephalogram, and functional magnetic resonance imaging data. Outcomes will be measured at baseline and the fourth and eighth weeks after randomization. Repeated measurement analysis of variance and a mixed linear model will be used to observe the intervention effect.

DISCUSSION

The protocol will give a detailed procedure to the multicenter clinical trial to further evaluate the efficacy and neural mechanism of TiaoshenYizhi acupuncture on episodic memory in patients with aMCI. From this research, we expect to provide clinical evidence for early aMCI management.

TRIAL REGISTRATION

http://www.chictr.org.cn/edit.aspx?pid=142612&htm=4 , identifier: ChiCTR2100054009.

XGBoost-SHAP-based interpretable diagnostic framework for alzheimer's disease

BACKGROUND

Due to the class imbalance issue faced when Alzheimer's disease (AD) develops from normal cognition (NC) to mild cognitive impairment (MCI), present clinical practice is met with challenges regarding the auxiliary diagnosis of AD using machine learning (ML). This leads to low diagnosis performance. We aimed to construct an interpretable framework, extreme gradient boosting-Shapley additive explanations (XGBoost-SHAP), to handle the imbalance among different AD progression statuses at the algorithmic level. We also sought to achieve multiclassification of NC, MCI, and AD.

METHODS

We obtained patient data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including clinical information, neuropsychological test results, neuroimaging-derived biomarkers, and APOE-ε4 gene statuses. First, three feature selection algorithms were applied, and they were then included in the XGBoost algorithm. Due to the imbalance among the three classes, we changed the sample weight distribution to achieve multiclassification of NC, MCI, and AD. Then, the SHAP method was linked to XGBoost to form an interpretable framework. This framework utilized attribution ideas that quantified the impacts of model predictions into numerical values and analysed them based on their directions and sizes. Subsequently, the top 10 features (optimal subset) were used to simplify the clinical decision-making process, and their performance was compared with that of a random forest (RF), Bagging, AdaBoost, and a naive Bayes (NB) classifier. Finally, the National Alzheimer's Coordinating Center (NACC) dataset was employed to assess the impact path consistency of the features within the optimal subset.

RESULTS

Compared to the RF, Bagging, AdaBoost, NB and XGBoost (unweighted), the interpretable framework had higher classification performance with accuracy improvements of 0.74%, 0.74%, 1.46%, 13.18%, and 0.83%, respectively. The framework achieved high sensitivity (81.21%/74.85%), specificity (92.18%/89.86%), accuracy (87.57%/80.52%), area under the receiver operating characteristic curve (AUC) (0.91/0.88), positive clinical utility index (0.71/0.56), and negative clinical utility index (0.75/0.68) on the ADNI and NACC datasets, respectively. In the ADNI dataset, the top 10 features were found to have varying associations with the risk of AD onset based on their SHAP values. Specifically, the higher SHAP values of CDRSB, ADAS13, ADAS11, ventricle volume, ADASQ4, and FAQ were associated with higher risks of AD onset. Conversely, the higher SHAP values of LDELTOTAL, mPACCdigit, RAVLT_immediate, and MMSE were associated with lower risks of AD onset. Similar results were found for the NACC dataset.

CONCLUSIONS

The proposed interpretable framework contributes to achieving excellent performance in imbalanced AD multiclassification tasks and provides scientific guidance (optimal subset) for clinical decision-making, thereby facilitating disease management and offering new research ideas for optimizing AD prevention and treatment programs.

Multi-omics data reveals the disturbance of glycerophospholipid metabolism and linoleic acid metabolism caused by disordered gut microbiota in PM2.5 gastrointestinal exposed rats

The relationships between fine particulate matter (PM2.5) exposure and health effects are complex and incompletely understood. Evidence suggests that PM2.5 exposure alters gut microbiota composition and metabolites, but the connections between these changes remain unclear. The aim of our study was to investigate how gut microbiota are involved in the systemic metabolic changes following PM2.5 gastrointestinal exposure. We used multi-omics approaches, including 16S rRNA sequencing and serum metabolomics, to identify alterations in gut microbes and metabolites of PM2.5-exposed rats. We then explored correlations between perturbed gut microbiota and metabolic changes, and conducted pathway analyses to determine critical metabolic pathways impacted by PM2.5 exposure. To verify links between gut microbiome and metabolome disruptions, we performed fecal microbiota transplantation (FMT) experiment. A total of 30 differential gut microbe taxa were identified between PM2.5 and control groups, primarily in Firmicutes, Acidobacteria, and Proteobacteria phyla. We also identified 30 differential metabolites, including glycerophospholipids, fatty acyls, amino acids and others. Pathway analysis revealed disruptions in glycerophospholipid metabolism, steroid hormone biosynthesis, and linoleic acid metabolism. Through FMT, we confirmed PM2.5 altered phosphatidylcholine and linoleic acid metabolism by changing specific gut bacteria. Our results suggest that PM2.5 gastrointestinal exposure triggers systemic metabolic changes by disrupting the gut microbiome, especially glycerophospholipid and linoleic acid metabolism pathways.

Neurotoxicity of the air-borne particles: From molecular events to human diseases

Exposure to PM_2.5 is associated with an increased incidence of CNS diseases in humans, as confirmed by numerous epidemiological studies. Animal models have demonstrated that PM_2.5 exposure can damage brain tissue, neurodevelopmental issues and neurodegenerative diseases. Both animal and human cell models have identified oxidative stress and inflammation as the primary toxic effects of PM_2.5 exposure. However, understanding how PM_2.5 modulates neurotoxicity has proven challenging due to its complex and variable composition. This review aims to summarize the detrimental effects of inhaled PM_2.5 on the CNS and the limited understanding of its underlying mechanism. It also highlights new frontiers in addressing these issues, such as modern laboratory and computational techniques and chemical reductionism tactics. By utilizing these approaches, we aim to fully elucidate the mechanism of PM_2.5-induced neurotoxicity, treat associated diseases, and ultimately eliminate pollution.

Association of long-term air pollution and ambient noise with cognitive decline in the heinz nixdorf recall study

Little is known about the impact of long-term ambient air pollution (AP) and noise exposure on change in cognitive function over years in the elderly. In this study, we wanted to examine the association between long-term exposure to AP and noise with the rate of cognitive decline in a population aged 50 and older and susceptible groups with mild cognitive impairment or at a genetically higher risk of Alzheimer's disease (Apolipoprotein E ε4 positive). Participants in the German population-based Heinz Nixdorf Recall study carried out five neuropsychological tests. Individual tests scores at the first (T₁ = 2006-2008) and second (T₂ = 2011-2015) follow-up for each test were used as outcomes after standardization using predicted means adjusted for age and education. Global cognitive score (GCS) was defined as sum of five standardized scores of individual tests. Long-term exposures to particulate matter (PM_2.5, PM₁₀, PM_2.5 absorbance), accumulation mode particle number (PN_acc), a proxy of ultrafine particles, and nitrogen dioxide were estimated by the land-use regression and chemistry transport models. Noise exposures were assessed as outdoor weighted nighttime road traffic noise (L_night) means. We performed linear regression analyses adjusted for sex, age, individual and neighborhood socio-economic status, and lifestyle variables. Effect modification in vulnerable groups was estimated using multiplicative interaction terms between exposure and a modifier. Overall, 2554 participants (49.5% men, median age is 63 (IQR = 12)) were included. We found weak associations between higher exposure to PM₁₀ and PM_2.5 with faster decline in the immediate verbal memory test. Adjustment for potential confounders and for co-exposures did not change the results. We saw no effects on GCS, and no effect of noise exposure. In susceptible groups, higher AP and noise exposure were tended to be associated with faster decline in GCS. Our results suggest that AP exposure may accelerate cognitive decline in older ages, particularly in susceptible groups.

Toxicological Effects of Fine Particulate Matter (PM2.5): Health Risks and Associated Systemic Injuries-Systematic Review

Previous studies focused on investigating particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) have shown the risk of disease development, and association with increased morbidity and mortality rates. The current review investigate epidemiological and experimental findings from 2016 to 2021, which enabled the systemic overview of PM2.5's toxic impacts on human health. The Web of Science database search used descriptive terms to investigate the interaction among PM2.5 exposure, systemic effects, and COVID-19 disease. Analyzed studies have indicated that cardiovascular and respiratory systems have been extensively investigated and indicated as the main air pollution targets. Nevertheless, PM2.5 reaches other organic systems and harms the renal, neurological, gastrointestinal, and reproductive systems. Pathologies onset and/or get worse due to toxicological effects associated with the exposure to this particle type, since it can trigger several reactions, such as inflammatory responses, oxidative stress generation and genotoxicity. These cellular dysfunctions lead to organ malfunctions, as shown in the current review. In addition, the correlation between COVID-19/Sars-CoV-2 and PM2.5 exposure was also assessed to help better understand the role of atmospheric pollution in the pathophysiology of this disease. Despite the significant number of studies about PM2.5's effects on organic functions, available in the literature, there are still gaps in knowledge about how this particulate matter can hinder human health. The current review aimed to approach the main findings about the effect of PM2.5 exposure on different systems, and demonstrate the likely interaction of COVID-19/Sars-CoV-2 and PM2.5.

Air Pollution: A Silent Key Driver of Dementia

In 2017, the Lancet Commission on Dementia Prevention, Intervention, and Care included air pollution in its list of potential risk factors for dementia; in 2018, the Lancet Commission on Pollution concluded that the evidence for a causal relationship between fine particulate matter (PM) and dementia is encouraging. However, few interventions exist to delay or prevent the onset of dementia. Air quality data are becoming increasingly available, and the science underlying the associated health effects is also evolving rapidly. Recent interest in this area has led to the publication of population-based cohort studies, but these studies have used different approaches to identify cases of dementia. The purpose of this article is to review recent evidence describing the association between exposure to air pollution and dementia with special emphasis on fine particulate matter of 2.5 microns or less. We also summarize here the proposed detailed mechanisms by which air pollutants reach the brain and activate the innate immune response. In addition, the article also provides a short overview of existing limitations in the treatment of dementia.

Lifetime air pollution exposure, cognitive deficits, and brain imaging outcomes: A systematic review

As the amount of air pollution and human exposure has increased, the effects on human health have become an important public health issue. A field of growing interest is how air pollution exposure affects brain structure and function underlying cognitive deficits and if structural and connectivity changes mediate the relationship between the two. We conducted a systematic review to examine the literature on air pollution, brain structure and connectivity, and cognition studies. Eleven studies matched our inclusion criteria and were included in the qualitative analysis. Results suggest significant associations between air pollution and decreased volumes of specific brain structures, cortical thickness and surface area such as in the prefrontal cortex and temporal lobe, as well as the weakening of functional connectivity pathways, largely the Default Mode (DMN) and Frontal Parietal (FPN) networks, as detected by fMRI. Associations between air pollution and cognitive outcomes were found in most of the studies (n = 9), though some studies showed stronger associations than others. For children & adolescents, these deficiencies largely involved heavy reasoning, problem solving, and logic. For young and middle-aged adults, the associations were mostly seen for executive function and visuospatial cognitive domains. To our knowledge, this is the first systematic review to consolidate findings on the associations among air pollution, brain structure, and cognitive function. In the future, it will be important to conduct further longitudinal studies that follow children who have been exposed at a young age and examine associations with brain structure and cognition throughout adulthood.

The pollutome-connectome axis: a putative mechanism to explain pollution effects on neurodegeneration

The study of pollutant effects is extremely important to address the epochal challenges we are facing, where world populations are increasingly moving from rural to urban centers, revolutionizing our world into an urban world. These transformations will exacerbate pollution, thus highlighting the necessity to unravel its effect on human health. Epidemiological studies have reported that pollution increases the risk of neurological diseases, with growing evidence on the risk of neurodegenerative disorders. Air pollution and water pollutants are the main chemicals driving this risk. These chemicals can promote inflammation, acting in synergy with genotype vulnerability. However, the biological underpinnings of this association are unknown. In this review, we focus on the link between pollution and brain network connectivity at the macro-scale level. We provide an updated overview of epidemiological findings and studies investigating brain network changes associated with pollution exposure, and discuss the mechanistic insights of pollution-induced brain changes through neural networks. We explain, in detail, the pollutome-connectome axis that might provide the functional substrate for pollution-induced processes leading to cognitive impairment and neurodegeneration. We describe this model within the framework of two pollutants, air pollution, a widely recognized threat, and polyfluoroalkyl substances, a large class of synthetic chemicals which are currently emerging as new neurotoxic source.

Particulate matter exposure and chronic cerebral hypoperfusion promote oxidative stress and induce neuronal and oligodendrocyte apoptosis in male mice

Chronic cerebral hypoperfusion (CCH) may amplify the neurotoxicity of nanoscale particulate matter (nPM), resulting in white matter injury. This study characterized the joint effects of nPM (diameter ≤ 200 nm) and CCH secondary to bilateral carotid artery stenosis (BCAS) exposure on neuronal and white matter injury in a murine model. nPM was collected near a highway and re-aerosolized for exposure. Ten-week-old C57BL/6 male mice were randomized into four groups: filtered air (FA), nPM, FA + BCAS, and nPM + BCAS. Mice were exposed to FA or nPM for 10 weeks. BCAS surgeries were performed. Markers of inflammation, oxidative stress, and apoptosis were examined. nPM + BCAS exposure increased brain hemisphere TNFα protein compared to FA. iNOS and HNE immunofluorescence were increased in the corpus callosum and cerebral cortex of nPM + BCAS mice compared to FA. While nPM exposure alone did not decrease cortical neuronal cell count, nPM decreased corpus callosum oligodendrocyte cell count. nPM exposure decreased mature oligodendrocyte cell count and increased oligodendrocyte precursor cell count in the corpus callosum. nPM + BCAS mice exhibited a 200% increase in cortical neuronal TUNEL staining and a 700% increase in corpus callosum oligodendrocyte TUNEL staining compared to FA. There was a supra-additive interaction between nPM and BCAS on cortical neuronal TUNEL staining (2.6× the additive effects of nPM + BCAS). nPM + BCAS exposure increased apoptosis, neuroinflammation, and oxidative stress in the cerebral cortex and corpus callosum. nPM + BCAS exposure increased neuronal apoptosis above the separate responses to each exposure. However, oligodendrocytes in the corpus callosum demonstrated a greater susceptibility to the combined neurotoxic effects of nPM + BCAS exposure.

Air Pollutant impacts on the brain and neuroendocrine system with implications for peripheral organs: a perspective

Air pollutants are being increasingly linked to extrapulmonary multi-organ effects. Specifically, recent studies associate air pollutants with brain disorders including psychiatric conditions, neuroinflammation and chronic diseases. Current evidence of the linkages between neuropsychiatric conditions and chronic peripheral immune and metabolic diseases provides insights on the potential role of the neuroendocrine system in mediating neural and systemic effects of inhaled pollutants (reactive particulates and gases). Autonomically-driven stress responses, involving sympathetic-adrenal-medullary and hypothalamus-pituitary-adrenal axes regulate cellular physiological processes through adrenal-derived hormones and diverse receptor systems. Recent experimental evidence demonstrates the contribution of the very stress system responding to non-chemical stressors, in mediating systemic and neural effects of reactive air pollutants. The assessment of how respiratory encounter of air pollutants induce lung and peripheral responses through brain and neuroendocrine system, and how the impairment of these stress pathways could be linked to chronic diseases will improve understanding of the causes of individual variations in susceptibility and the contribution of habituation/learning and resiliency. This review highlights effects of air pollution in the respiratory tract that impact the brain and neuroendocrine system, including the role of autonomic sensory nervous system in triggering neural stress response, the likely contribution of translocated nano particles or metal components, and biological mediators released systemically in causing effects remote to the respiratory tract. The perspective on the use of systems approaches that incorporate multiple chemical and non-chemical stressors, including environmental, physiological and psychosocial, with the assessment of interactive neural mechanisms and peripheral networks are emphasized.

Functionalized graphene-based electrochemical array sensors for the identification of distinct conformational states of Amyloid Beta in Alzheimer's disease

Aβ oligomers have been widely accepted as significant biomarkers for Alzheimer's disease (AD) detection, monitoring, and therapy since they are highly correlated with AD development. In this work, an electrochemical array-based sensing platform was successfully built using a group of functionalized graphene with different physicochemical features. Since the electro-insulated Aβ peptide species severely interfered with the electron transport on the electrode surface, the presence of Aβ led to a significant change in the electrochemical impedance signal. The resulting variety of the impedance was then classified and processed by linear discriminant analysis. The constructed sensing platform can discriminate different Aβ forms, the mixture of various Aβ forms, and different ratios of Aβ42 to Aβ40 with 100% accuracy by only the combination of dual probes. Furthermore, it also exhibited excellent performance for screening Aβ inhibitors and metal chelators. The strategy utilizes the infinitesimal general discrepancy instead of specific biomarker recognition, exhibiting the advantage of no requirement to know the exact information about the specific ligand and receptor in advance, which is promising to be widened for the other biosensing detection fields.

Air pollution and human cognition: A systematic review and meta-analysis

BACKGROUND

This systematic review summarises and evaluates the literature investigating associations between exposure to air pollution and general population cognition, which has important implications for health, social and economic inequalities, and human productivity.

METHODS

The engines MEDLINE, Embase Classic+Embase, APA PsycInfo, and SCOPUS were searched up to May 2022. Our inclusion criteria focus on the following pollutants: particulate matter, NOx, and ozone. The cognitive abilities of interest are: general/global cognition, executive function, attention, working memory, learning, memory, intelligence and IQ, reasoning, reaction times, and processing speed. The collective evidence was assessed using the NTP-OHAT framework and random-effects meta-analyses.

RESULTS

Eighty-six studies were identified, the results of which were generally supportive of associations between exposures and worsened cognition, but the literature was varied and sometimes contradictory. There was moderate certainty support for detrimental associations between PM_2.5 and general cognition in adults 40+, and PM_2.5, NOx, and PM₁₀ and executive function (especially working memory) in children. There was moderate certainty evidence against associations between ozone and general cognition in adults age 40+, and NOx and reasoning/IQ in children. Some associations were also supported by meta-analysis (N = 14 studies, all in adults aged 40+). A 1 μg/m³ increase in NO₂ was associated with reduced performance on general cognitive batteries (β = -0.02, p < 0.05) as was a 1 μg/m³ increase in PM_2.5 exposure (β = -0.02, p < 0.05). A 1μgm³ increase in PM_2.5 was significantly associated with lower verbal fluency by -0.05 words (p = 0.01) and a decrease in executive function task performance of -0.02 points (p < 0.001).

DISCUSSION

Evidence was found in support of some exposure-outcome associations, however more good quality research is required, particularly with older teenagers and young adults (14-40 years), using multi-exposure modelling, incorporating mechanistic investigation, and in South America, Africa, South Asia and Australasia.

Alzheimer's disease as a fundamental disease of information processing systems: An information theory perspective

The human brain is a dynamic multiplex of information, both neural (neurotransmitter-to-neuron, involving 1.5×10¹⁵ action potentials per minute) and immunological (cytokine-to-microglia, providing continuous immune surveillance via 1.5×10¹⁰ immunocompetent cells). This conceptualization highlights the opportunity of exploiting "information" not only in the mechanistic understanding of brain pathology, but also as a potential therapeutic modality. Arising from its parallel yet interconnected proteopathic-immunopathic pathogeneses, Alzheimer's disease (AD) enables an exploration of the mechanistic and therapeutic contributions of information as a physical process central to brain disease progression. This review first considers the definition of information and its relevance to neurobiology and thermodynamics. Then we focus on the roles of information in AD using its two classical hallmarks. We assess the pathological contributions of β-amyloid peptides to synaptic dysfunction and reconsider this as a source of noise that disrupts information transfer between presynaptic and postsynaptic neurons. Also, we treat the triggers that activate cytokine-microglial brain processes as information-rich three-dimensional patterns, including pathogen-associated molecular patterns and damage-associated molecular patterns. There are structural and functional similarities between neural and immunological information with both fundamentally contributing to brain anatomy and pathology in health and disease. Finally, the role of information as a therapeutic for AD is introduced, particularly cognitive reserve as a prophylactic protective factor and cognitive therapy as a therapeutic contributor to the comprehensive management of ongoing dementia.

Is an MRI-derived anatomical measure of dementia risk also a measure of brain aging?

Machine learning methods have been applied to estimate measures of brain aging from neuroimages. However, only rarely have these measures been examined in the context of biologic age. Here, we investigated associations of an MRI-based measure of dementia risk, the Alzheimer's disease pattern similarity (AD-PS) scores, with measures used to calculate biological age. Participants were those from visit 5 of the Atherosclerosis Risk in Communities Study with cognitive status adjudication, proteomic data, and AD-PS scores available. The AD-PS score estimation is based on previously reported machine learning methods. We evaluated associations of the AD-PS score with all-cause mortality. Sensitivity analyses using only cognitively normal (CN) individuals were performed treating CNS-related causes of death as competing risk. AD-PS score was examined in association with 32 proteins measured, using a Somalogic platform, previously reported to be associated with age. Finally, associations with a deficit accumulation index (DAI) based on a count of 38 health conditions were investigated. All analyses were adjusted for age, race, sex, education, smoking, hypertension, and diabetes. The AD-PS score was significantly associated with all-cause mortality and with levels of 9 of the 32 proteins. Growth/differentiation factor 15 (GDF-15) and pleiotrophin remained significant after accounting for multiple-testing and when restricting the analysis to CN participants. A linear regression model showed a significant association between DAI and AD-PS scores overall. While the AD-PS scores were created as a measure of dementia risk, our analyses suggest that they could also be capturing brain aging.

The mental health of women and climate change: Direct neuropsychiatric impacts and associated psychological concerns

Climate change brings exposures to heat, air pollution, poorer quality food, and infectious disease that have significant direct effects on women and their mental health. These environmental impacts are multifaceted in their consequences and raise risks of depression, suicide, violent victimization, post-traumatic stress disorder, and various other neuropsychiatric symptoms. Women also suffer increased climate psychological risks from higher rates of stillbirth, preterm birth, and developmental problems in their children. Here we review what is known about the overlap of women's individual mental health and climate change, and highlight areas where more research is needed.

Air Pollution-Related Neurotoxicity Across the Life Span

Air pollution is a complex mixture of gases and particulate matter, with adsorbed organic and inorganic contaminants, to which exposure is lifelong. Epidemiological studies increasingly associate air pollution with multiple neurodevelopmental disorders and neurodegenerative diseases, findings supported by experimental animal models. This breadth of neurotoxicity across these central nervous system diseases and disorders likely reflects shared vulnerability of their inflammatory and oxidative stress-based mechanisms and a corresponding ability to produce brain metal dyshomeo-stasis. Future research to define the responsible contaminants of air pollution underlying this neurotoxicity is critical to understanding mechanisms of these diseases and disorders and protecting public health.

CircCDR1as mediates PM2.5-induced lung cancer progression by binding to SRSF1

Research indicates that particulate matter with an aerodynamic equivalent diameter of less than or equal to 2.5 µm in ambient air may induce lung cancer progression. Circular RNAs are a special kind of endogenous noncoding RNA, and their functions are reflected in various diseases and physiological processes, but there are still few studies related to PM_2.5-induced lung cancer. Here, we identified that circCDR1as was upregulated in lung cancer cells stimulated with PM_2.5 and positively correlated with the malignant features of lung cancer. The lower expression of CircCDR1as reduced the adverse progression of lung cancer cells after PM_2.5 treatment; the lower expression of circCDR1as impaired the growth size and metastatic ability of lung cancer cells in mouse tumour models. Mechanistically, circCDR1as specifically bound to serine/arginine-rich splicing Factor 1 (SRSF1) and affected the splicing of vascular endothelial growth factor-A (VEGFA) by SRSF1. Furthermore, circCDR1as affected SRSF1 function by regulating PARK2-mediated SRSF1 ubiquitination, protein production and degradation. CircCDR1as also affected C-myc and cyclin D1 expression by regulating SRSF1 and affecting the wnt/β-catenin signalling pathway, ultimately promoting malignant behavior and inhibiting the apoptosis of lung cancer cells, thereby causing PM_2.5-induced lung cancer development.