Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats.

Chronic social isolation (CSIS) generates two stress-related phenotypes: resilience and susceptibility. However, the molecular mechanisms underlying CSIS resilience remain unclear. We identified altered proteome components and biochemical pathways and processes in the prefrontal cortex cytosolic fraction in CSIS-resilient rats compared to CSIS-susceptible and control rats using liquid chromatography coupled with tandem mass spectrometry followed by label-free quantification and STRING bioinformatics. A sucrose preference test was performed to distinguish rat phenotypes. Potential predictive proteins discriminating between the CSIS-resilient and CSIS-susceptible groups were identified using machine learning (ML) algorithms: support vector machine-based sequential feature selection and random forest-based feature importance scores. Predominantly, decreased levels of some glycolytic enzymes, G protein-coupled receptor proteins, the Ras subfamily of GTPases proteins, and antioxidant proteins were found in the CSIS-resilient vs. CSIS-susceptible groups. Altered levels of Gapdh, microtubular, cytoskeletal, and calcium-binding proteins were identified between the two phenotypes. Increased levels of proteins involved in GABA synthesis, the proteasome system, nitrogen metabolism, and chaperone-mediated protein folding were identified. Predictive proteins make CSIS-resilient vs. CSIS-susceptible groups linearly separable, whereby a 100% validation accuracy was achieved by ML models. The overall ratio of significantly up- and downregulated cytosolic proteins suggests adaptive cellular alterations as part of the stress-coping process specific for the CSIS-resilient phenotype.

Prefrontal cortical synaptoproteome profile combined with machine learning predicts resilience towards chronic social isolation in rats.

Chronic social isolation (CSIS) of rats serves as an animal model of depression and generates CSIS-resilient and CSIS-susceptible phenotypes. We aimed to investigate the prefrontal cortical synaptoproteome profile of CSIS-resilient, CSIS-susceptible, and control rats to delineate biochemical pathways and predictive biomarker proteins characteristic for the resilient phenotype. A sucrose preference test was performed to distinguish rat phenotypes. Class separation and machine learning (ML) algorithms support vector machine with greedy forward search and random forest were then used for discriminating CSIS-resilient from CSIS-susceptible and control rats. CSIS-resilient compared to CSIS-susceptible rat proteome analysis revealed, among other proteins, downregulated glycolysis intermediate fructose-bisphosphate aldolase C (Aldoc), and upregulated clathrin heavy chain 1 (Cltc), calcium/calmodulin-dependent protein kinase type II (Cam2a), synaptophysin (Syp) and fatty acid synthase (Fasn) that are involved in neuronal transmission, synaptic vesicular trafficking, and fatty acid synthesis. Comparison of CSIS-resilient and control rats identified downregulated mitochondrial proteins ATP synthase subunit beta (Atp5f1b) and citrate synthase (Cs), and upregulated protein kinase C gamma type (Prkcg), vesicular glutamate transporter 1 (Slc17a7), and synaptic vesicle glycoprotein 2 A (Sv2a) involved in signal transduction and synaptic trafficking. The combined protein differences make the rat groups linearly separable, and 100% validation accuracy is achieved by standard ML models. ML algorithms resulted in four panels of discriminative proteins. Proteomics-data-driven class separation and ML algorithms can provide a platform for accessing predictive features and insight into the molecular mechanisms underlying synaptic neurotransmission involved in stress resilience.

Chronic fluoxetine treatment in socially-isolated rats modulates the prefrontal cortex synaptoproteome.

Exposure to chronic social isolation (CSIS) and synapse dysfunction have been implicated in the etiology of major depressive disorder (MDD). Fluoxetine (Flx) has been widely used to treat MDD, but its mechanisms of action remain elusive. We employed comparative synaptoproteomics to investigate the changes in the levels of proteins and molecular signaling pathways in prefrontal cortical samples of adult male Wistar rats exposed to CSIS, a rat model of depression, and CSIS rats treated with chronic Flx and controls, using liquid chromatography coupled to tandem mass spectrometry. Flx-treated control rats showed a decreased level of proteins involved in vesicle-mediated transport, and a predominantly increased level of exocytosis-associated proteins. CSIS significantly reduced the level of proteins involved in the ATP metabolic process, clathrin-dependent endocytosis, and proteolysis. Flx treatment in CSIS rats stimulated synaptic vesicle trafficking by increasing the regulation of exo/endocytosis-associated proteins, proteins involved in synaptic plasticity including neurogenesis, Cox5a, mitochondria-associated proteins involved in oxidative phosphorylation, and ion transport proteins (Slc8a2, Atp1b2). Flx treatment resulted in an increased synaptic vesicle dynamic, plasticity and mitochondrial functionality, and a suppression of CSIS-induced impairment of these processes. BIOLOGICAL SIGNIFICANCE: Identifying biomarkers of MDD and treatment response is the goal of many studies. Contemporary studies have shown that many molecular alterations associated with the pathophysiology of MDD reside within the synapse. As part of this research, a growing importance is the use of proteomics, as monitoring the changes in protein levels enables the identification of (possible) biochemical pathways and processes of importance for the development of depressive-like behavior and the efficacy of antidepressant treatments. We profiled proteomic changes representative of the development of CSIS-induced depressive-like behavior and the antidepressant effects of Flx. Our study has identified synaptosomal proteins and altered molecular pathways that may be potential markers of prefrontal cortical synaptic dysfunction associated with depressive-like behavior, and further clarified the mechanisms of depressive-like behavior and mode of action of Flx. Our findings indicate potential PFC synaptic targets for antidepressant treatment.

Infant exposure to parabens, triclosan, and triclocarban via breastfeeding and formula supplementing in southern China.

Parabens, triclosan (TCS), and triclocarban (TCC) are antimicrobial additives that are widely used in personal care products (PCPs) and may dysregulate infant gut microbiota and induce a series of chronic diseases. Dietary intake may be an underestimated exposure route of such antimicrobial additives in infants, but relevant data remain scarce. Therefore, this study determined five common preservatives, including methyl- (MeP), ethyl- (EtP), propyl- (PrP), butyl- (BuP), and benzyl-paraben (BeP), and two antimicrobials TCS and TCC, in major infant food sources (breastmilk, milk-based infant formula [MIF], and cereal-based complementary food [CCF]) in southern China. The health risks associated with dietary exposure among infants across different months of age were also evaluated. The results demonstrated a high incidence of MeP, EtP, PrP, and BeP in processed infant food products, while TCS and TCC were mainly detected in maternal breastmilk. Notably, MeP and EtP were found in all of the MIFs tested, while MeP, EtP, and BeP were detected in 85.6 %-100 % of the CCFs. By incorporating the human equivalent dose and an additional 10-fold margin of safety for infants into the health risk assessment, the 95th percentile hazard quotient of PrP via the ingestion of breastmilk among neonates exceeded 1. For the first time, the results showed that exposure to PrP via breastmilk intake may pose a considerable health risk to urban neonates in southern China. The health risks caused by antimicrobial exposure via ingesting MIF and CCF among infants were negligible. Thus, we recommend breastfeeding women reduce their consumption of PCPs and processed food, especially during the first month after delivery.

Chronic Fluoxetine Treatment of Socially Isolated Rats Modulates Prefrontal Cortex Proteome.

Fluoxetine (Flx) is the most commonly used antidepressant to treat major depressive disorder. However, its molecular mechanisms of action are not defined as yet. A comparative proteomic approach was used to identify proteome changes in the prefrontal cortex (PFC) cytosolic and non-synaptic mitochondria (NSM)-enriched fractions of adult male Wistar rats following chronic social isolation (CSIS), a rat model of depression, and Flx treatment in CSIS and control rats, using liquid chromatography online tandem mass spectrometry. Flx reversed CSIS-induced depressive - like behavior according to preference for sucrose and immobility in the forced swim test, indicating its antidepressant effect. Flx treatment in controls led to an increase of the expression of cytosolic proteins involved in the microtubule cytoskeleton and intracellular calcium homeostasis and of enzymes involved in bioenergetic and transmembrane transport in NSM. CSIS downregulated the cytosolic proteins involved in proteasome pathway, and glutathione antioxidative system, and upregulated the expression of enzymes participating in mitochondrial-energy metabolism and transport. The presence of cytochrome c in the cytosol may suggest compromised mitochondrial membrane integrity. Flx treatment in CSIS rats downregulated protein involved in oxidative phosphorylation, such as complex III and manganese superoxide dismutase, and upregulated vesicle-mediated transport and synaptic signaling proteins in the cytosol, and neuronal calcium-binding protein 1 in NSM. Our study identified PFC modulated proteins and affected biochemical pathways that may represent potential markers/targets underlying CSIS-induced depression and effective Flx treatment, and highlights the role of protein systems involved in NSM and various metabolic pathways potentially involved in neuronal plasticity.

Associations of dietary anthocyanidins intake with body composition in Chinese children: a cross-sectional study.

BACKGROUND: Previous animal and in vitro studies indicated that anthocyanidins might contribute to the prevention of obesity, while epidemiological evidences were scarce and had not been conducted in children. OBJECTIVE: We explored the associations between anthocyanidins and body composition in children. DESIGN: A cross-sectional study involving 452 children aged 6-9 years in Guangzhou, China, was carried out. Dietary information was collected using a 79-items food frequency questionnaire. Fat mass (FM), lean mass (LM), and fat mass percentage (FMP) at multi-sites (whole body, trunk, limbs, android area, and gynoid area) were measured using a dual-energy X-ray scan. Abdominal obesity was defined as an age- and sex-specific abdominal FM ≥ 85th percentile. Handgrip strength was measured using a hydraulic hand dynamometer. RESULTS: After adjusted for several potential covariates, higher dietary intake of anthocyanidin (per one standard deviation increase) was associated with a 0.013-0.223 kg increase of LM, a 0.024-0.134 kg decrease of FM, and a 0.63-0.76% decrease of FMP at multi-sites (P < 0.05). Results were similar and more pronounced for delphinidin and cyanidin, but less significant for peonidin. Higher dietary anthocyanidin intake (per standard deviation increase) was associated with a 41.0% (OR: 0.59, 95%CI: 0.37, 0.94) decreased risk of abdominal obesity. However, no significant associations were observed between anthocyanidin and handgrip strengths. CONCLUSIONS: Higher dietary intake of anthocyanidin and its components tended to be associated with better body composition, but not handgrip strength, in Chinese children at early age.

A simple physical-activity-based model for managing children's activities against exposure to air pollutants.

Air pollution has been a major health concern worldwide, such that there is an urgent need for exposure assessments of human exposure to air pollutants. As children are more active and may experience more exposure events than adults, it is more challenging to conduct exposure assessments for children. To obtain a general understanding of the impact that children's activity, associated with their respiratory rate (IR), has on estimated exposure risks, we adopted a simple model to narrow down children's exposure behaviors to four categories, which integrated children's regular schedules and the indoor-outdoor ratio (rI/O) of air pollutants. Although outdoor play only occupies approximately 8.6% of the total weekly time, the results indicate that, in general, outdoor play contributes to over 50% of the total exposure to air pollutants when rI/O is less than 0.1, which is due to children's relatively large IR during high-intensity activities. When air pollutants mainly originate from indoor sources (i.e., rI/O=3.0), indoor sitting (28%) and sleeping (36%) account for the major portion of the total exposure due to the longer exposure duration while outdoor events, including playing, walking, and sitting, account for ~15% of the total exposure. In addition, we applied a ratio function (RM/C) to compare our simple model to a common basic model, revealing that our simulated results are consistent with the basic model, i.e., 0.94≤RM/C≤1.12, if the rI/O of air pollutants falls in the range between 0.5 and 1.5. The sensitivity analysis indicates that indoor or outdoor play has a larger impact on the output results than other activity-related variables because of the correspondingly largest IR. We also incorporated weather factors to adjust children's activity schedules for winter and non-winter days showing the change in the contributions of children's activities to total exposure. For example, the contribution differential of outdoor play to the total exposure between winter and non-winter days is ~8% for air pollutants with an rI/O value of 0.1. Although other factors, such as the activity intensity level and concentration of air pollutant in the microenvironment, must be refined in future studies, our simple model can be applied as a convenient approach to arrange children's activity schedules against possible air pollutant exposure.

Associations between Seven Common Cytokine Gene Polymorphisms and Coronary Artery Disease: Evidence from a Meta-Analysis.

BACKGROUND: Associations of polymorphisms in interferon-gamma (IFNG), interleukin-10 (IL-10), and interleukin-18 (IL-18) with coronary artery disease (CAD) have already been investigated by many studies, yet the findings of these studies have been somewhat inconsistent. OBJECTIVES: The aim of this meta-analysis was to better clarify associations between polymorphisms in IFNG/IL-10/IL-18 and CAD by combing the results of all relevant articles. METHODS: Eligible articles were searched from PubMed, EMBASE, WOS, and CNKI. We used Review Manager to combine the results of indi-vidual studies. RESULTS: Fifty-one studies were included in this meta-analysis. Combined results revealed that IFNG rs243056, IL-10rs1800871, IL-18rs187238, IL-18rs1946518, and IL-18rs1946519 polymorphisms were all significantly associated with CAD in the general population. We also obtained similar significant results for IFNG rs243056, IL-10rs1800871, IL-10 rs1800896, IL-18rs187238, IL-18rs1946518, and IL-18rs1946519 polymorphisms in Asians in further subgroup analyses. CONCLUSIONS: Collectively, this meta-analysis proved that IFNG rs243056, IL-10rs1800871, IL-10 rs1800896, IL-18rs187238, IL-18rs1946518, and IL-18rs1946519 polymorphisms may confer susceptibility to CAD for Asians.

Metagenomic Taxonomy-Guided Database-Searching Strategy for Improving Metaproteomic Analysis.

Metaproteomics provides a direct measure of the functional information by investigating all proteins expressed by a microbiota. However, due to the complexity and heterogeneity of microbial communities, it is very hard to construct a sequence database suitable for a metaproteomic study. Using a public database, researchers might not be able to identify proteins from poorly characterized microbial species, while a sequencing-based metagenomic database may not provide adequate coverage for all potentially expressed protein sequences. To address this challenge, we propose a metagenomic taxonomy-guided database-search strategy (MT), in which a merged database is employed, consisting of both taxonomy-guided reference protein sequences from public databases and proteins from metagenome assembly. By applying our MT strategy to a mock microbial mixture, about two times as many peptides were detected as with the metagenomic database only. According to the evaluation of the reliability of taxonomic attribution, the rate of misassignments was comparable to that obtained using an a priori matched database. We also evaluated the MT strategy with a human gut microbial sample, and we found 1.7 times as many peptides as using a standard metagenomic database. In conclusion, our MT strategy allows the construction of databases able to provide high sensitivity and precision in peptide identification in metaproteomic studies, enabling the detection of proteins from poorly characterized species within the microbiota.

Novel Magnetic-to-Thermal Conversion and Thermal Energy Management Composite Phase Change Material.

Superparamagnetic materials have elicited increasing interest due to their high-efficiency magnetothermal conversion. However, it is difficult to effectively manage the magnetothermal energy due to the continuous magnetothermal effect at present. In this study, we designed and synthesized a novel Fe3O4/PEG/SiO2 composite phase change material (PCM) that can simultaneously realize magnetic-to-thermal conversion and thermal energy management because of outstanding thermal energy storage ability of PCM. The composite was fabricated by in situ doping of superparamagnetic Fe3O4 nanoclusters through a simple sol⁻gel method. The synthesized Fe3O4/PEG/SiO2 PCM exhibited good thermal stability, high phase change enthalpy, and excellent shape-stabilized property. This study provides an additional promising route for application of the magnetothermal effect.