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Military burn pits, used for waste disposal in combat zones, involve the open-air burning of waste materials, including plastics, metals, chemicals, and medical waste. The pits release a complex mixture of occupational toxic substances, including particulate matter (PM), volatile organic compounds (VOCs), heavy metals, dioxins, and polycyclic aromatic hydrocarbons (PAHs). Air pollution significantly impacts brain health through mechanisms involving neuroinflammation. Pollutants penetrate the respiratory system, enter the bloodstream, and cross the blood-brain barrier (BBB), triggering inflammatory responses in the central nervous system (CNS). Chronic environmental exposures result in sustained inflammation, oxidative stress, and neuronal damage, contributing to neurodegenerative diseases and cognitive impairment. Veterans exposed to burn pit toxins are particularly at risk, reporting higher rates of respiratory issues, neurological conditions, cognitive impairments, and mental health disorders. Studies demonstrate that Veterans exposed to these toxins have higher rates of neuroinflammatory markers, accelerated cognitive decline, and increased risks of neurodegenerative diseases. This narrative review synthesizes the research linking airborne pollutants such as PM, VOCs, and heavy metals to neuroinflammatory processes and cognitive effects. There is a need for targeted interventions to mitigate the harmful and escalating effects of environmental air pollution exposures on the CNS, improving public health outcomes for vulnerable populations, especially for Veterans exposed to military burn pit toxins.

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease., Competing Interests: Declaration of interests M.P.S. is a co-founder and the scientific advisory board member of Personalis, Qbio, January, SensOmics, Filtricine, Akna, Protos, Mirvie, NiMo, Onza, Oralome, Marble Therapeutics, and Iollo. He is also on the scientific advisory board of Danaher, Genapsys, and Jupiter. A.H. is a founder and shareholder of Arxeon. Y.Z. and G.M.W. are co-founders of General Biomics., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Across all domains of human social life, positive perceptions of conversational listening (i.e., feeling heard) predict well-being, professional success, and interpersonal flourishing. However, a fundamental question remains: Are perceptions of listening accurate? Prior research has not empirically tested the extent to which humans can detect others' cognitive engagement (attentiveness) during live conversation. Across five studies (total N = 1,225), using a combination of correlational and experimental methods, we find that perceivers struggle to distinguish between attentive and inattentive conversational listening. Though people's listening fluctuated naturally throughout their conversations (people's minds wandered away from the conversation 24% of the time), they were able to adjust their listening in line with instructions and incentives-by either listening attentively, inattentively, or dividing their attention-and their conversation partners struggled to detect these differences. Specifically, speakers consistently overestimated their conversation partners' attentiveness-often believing their partners were listening when they were not. Our results suggest this overestimation is (at least partly) due to the largely indistinguishable behavior of inattentive and attentive listeners. It appears that people can (and do) divide their attention during conversation and successfully feign attentiveness. Overestimating others' attentiveness extended to third-party observers who were not immersed in the conversation, listeners who looked back on their own listening, and people interacting with partners who could not hear their words (but were incentivized to act like they could). Our work calls for a reexamination of a fundamental social behavior-listening-and underscores the distinction between feeling heard and being heard during live conversation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Introduction: Rate-limiting enzymes (RLEs) are innate slow points in metabolic pathways, and many function in bio-processes related to nutrient sensing. Many RLEs carry causal mutations relevant to inherited metabolic disorders. Because the activity of RLEs in cardiovascular health is poorly characterized, our objective was to assess their involvement in cardiometabolic health and disease and where altered biophysical and biochemical functions can promote disease., Methods: A dataset of 380 human RLEs was compared to protein and gene datasets for factors likely to contribute to cardiometabolic disease, including proteins showing significant age-related altered expression in blood and genetic loci with variants that associate with common cardiometabolic phenotypes. The biochemical reactions catalyzed by RLEs were evaluated for metabolites enriched in RLE subsets associating with various cardiometabolic phenotypes. Most significance tests were based on Z-score enrichment converted to p values with a normal distribution function., Results: Of 380 RLEs analyzed, 112 function in mitochondria, and 53 are assigned to inherited metabolic disorders. There was a depletion of RLE proteins known as aging biomarkers. At the gene level, RLEs were assessed for common genetic variants that associated with important cardiometabolic traits of LDL-cholesterol or any of the five outcomes pertinent to metabolic syndrome. This revealed several RLEs with links to cardiometabolic traits, from a minimum of 26 for HDL-cholesterol to a maximum of 45 for plasma glucose. Analysis of these GWAS-linked RLEs for enrichment of the molecular constituents of the catalyzed reactions disclosed a number of significant phenotype-metabolite links. These included blood pressure with acetate (p = 2.2 × 10-4) and NADP+ (p = 0.0091), plasma HDL-cholesterol and triglyceride with diacylglycerol (p = 2.6 × 10-5, 6.4 × 10-5, respectively) and diolein (p = 2.2 × 10-6, 5.9 × 10-6), and waist circumference with d-glucosamine-6-phosphate (p = 1.8 × 10-4)., Conclusion: In the context of cardiometabolic health, aging, and disease, these results highlight key diet-derived metabolites that are central to specific rate-limited processes that are linked to cardiometabolic health. These metabolites include acetate and diacylglycerol, pertinent to blood pressure and triglycerides, respectively, as well as diacylglycerol and HDL-cholesterol., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

Background: Large-scale gut microbiome sequencing has revealed key links between microbiome dysfunction and metabolic diseases such as type 2 diabetes (T2D). To date, these efforts have largely focused on Western populations, with few studies assessing T2D microbiota associations in Middle Eastern communities where T2D prevalence is now over 20%. We analyzed the composition of stool 16S rRNA from 461 T2D and 119 non-T2D participants from the Eastern Province of Saudi Arabia. We quantified the abundance of microbial communities to examine any significant differences between subpopulations of samples based on diabetes status and glucose level., Results: In this study we performed the largest microbiome study ever conducted in Saudi Arabia, as well as the first-ever characterization of gut microbiota T2D versus non-T2D in this population. We observed overall positive enrichment within diabetics compared to healthy individuals and amongst diabetic participants; those with high glucose levels exhibited slightly more positive enrichment compared to those at lower risk of fasting hyperglycemia. In particular, the genus Firmicutes was upregulated in diabetic individuals compared to non-diabetic individuals, and T2D was associated with an elevated Firmicutes/Bacteroidetes ratio, consistent with previous findings., Conclusion: Based on diabetes status and glucose levels of Saudi participants, relatively stable differences in stool composition were perceived by differential abundance and alpha diversity measures. However, community level differences are evident in the Saudi population between T2D and non-T2D individuals, and diversity patterns appear to vary from well-characterized microbiota from Western cohorts. Comparing overlapping and varying patterns in gut microbiota with other studies is critical to assessing novel treatment options in light of a rapidly growing T2D health epidemic in the region. As a rapidly emerging chronic condition in Saudi Arabia and the Middle East, T2D burdens have grown more quickly and affect larger proportions of the population than any other global region, making a regional reference T2D-microbiome dataset critical to understanding the nuances of disease development on a global scale., (© 2022. The Author(s).)

We document a link between the relational diversity of one's social portfolio-the richness and evenness of relationship types across one's social interactions-and well-being. Across four distinct samples, respondents from the United States who completed a preregistered survey ( n = 578), respondents to the American Time Use Survey ( n = 19,197), respondents to the World Health Organization's Study on Global Aging and Adult Health ( n = 10,447), and users of a French mobile application ( n = 21,644), specification curve analyses show that the positive relationship between social portfolio diversity and well-being is robust across different metrics of well-being, different categorizations of relationship types, and the inclusion of a wide range of covariates. Over and above people's total amount of social interaction and the diversity of activities they engage in, the relational diversity of their social portfolio is a unique predictor of well-being, both between individuals and within individuals over time.

Many diseases linked with ethnic health disparities associate with changes in microbial communities in the United States, but the causes and persistence of ethnicity-associated microbiome variation are not understood. For instance, microbiome studies that strictly control for diet across ethnically diverse populations are lacking. Here, we performed multiomic profiling over a 9-day period that included a 4-day controlled vegetarian diet intervention in a defined geographic location across 36 healthy Black and White females of similar age, weight, habitual diets, and health status. We demonstrate that individuality and ethnicity account for roughly 70% to 88% and 2% to 10% of taxonomic variation, respectively, eclipsing the effects a short-term diet intervention in shaping gut and oral microbiomes and gut viromes. Persistent variation between ethnicities occurs for microbial and viral taxa and various metagenomic functions, including several gut KEGG orthologs, oral carbohydrate active enzyme categories, cluster of orthologous groups of proteins, and antibiotic-resistant gene categories. In contrast to the gut and oral microbiome data, the urine and plasma metabolites tend to decouple from ethnicity and more strongly associate with diet. These longitudinal, multiomic profiles paired with a dietary intervention illuminate previously unrecognized associations of ethnicity with metagenomic and viromic features across body sites and cohorts within a single geographic location, highlighting the importance of accounting for human microbiome variation in research, health determinants, and eventual therapies. Trial Registration: ClinicalTrials.gov ClinicalTrials.gov Identifier: NCT03314194., Competing Interests: The authors have declared that no competing interests exist.

The meaning of success in conversation depends on people's goals. Often, individuals pursue multiple goals simultaneously, such as establishing shared understanding, making a favorable impression, having fun, or persuading a conversation partner. In this article, we introduce a novel theoretical framework, the Conversational Circumplex, to classify conversational motives along two key dimensions: 1) informational: the extent to which a speaker's motive focuses on giving and/or receiving accurate information; and 2) relational: the extent to which a speaker's motive focuses on building the relationship. We use the Conversational Circumplex to underscore the multiplicity of conversational goals that people hold and highlight the potential for individuals to have conflicting conversational goals (both intrapersonally and interpersonally) that make successful conversation a difficult challenge., Competing Interests: Conflict of interest statement Nothing declared., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Early detection of infectious diseases is crucial for reducing transmission and facilitating early intervention. In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. In a cohort of 3,318 participants, of whom 84 were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this system generated alerts for pre-symptomatic and asymptomatic SARS-CoV-2 infection in 67 (80%) of the infected individuals. Pre-symptomatic signals were observed at a median of 3 days before symptom onset. Examination of detailed survey responses provided by the participants revealed that other respiratory infections as well as events not associated with infection, such as stress, alcohol consumption and travel, could also trigger alerts, albeit at a much lower mean frequency (1.15 alert days per person compared to 3.42 alert days per person for coronavirus disease 2019 cases). Thus, analysis of smartwatch signals by an online detection algorithm provides advance warning of SARS-CoV-2 infection in a high percentage of cases. This study shows that a real-time alerting system can be used for early detection of infection and other stressors and employed on an open-source platform that is scalable to millions of users., (© 2021. The Author(s).)