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Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.
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Neoplasias Encefálicas , Imageamento por Ressonância Magnética , Humanos , Imageamento por Ressonância Magnética/métodos , Encéfalo/patologia , Mapeamento Encefálico/métodos , Genômica , Neoplasias Encefálicas/patologiaRESUMO
Interferon-inducible protein 16 (IFI16) plays a critical role in antiviral innate immune responses against DNA viruses. Although the acetylation of IFI16 is crucial to its cytoplasmic translocation and downstream signal transduction, the regulation of IFI16 acetylation remains unclear. In this study, we demonstrated that the NAD-dependent deacetylase silent information regulatory 1 (Sirtuin1, Sirt1) interacted with IFI16 and decreased the acetylation of IFI16, resulting in the inhibition of IFI16 cytoplasmic localization and antiviral responses against DNA virus and viral DNA in human cells. Meantime, Sirt1 could not inhibit RNA virus-triggered signal transduction. Interestingly, even p204, the murine ortholog of human IFI16, barely interacted with Sirt1. Thus, Sirt1 could not negatively regulate the acetylation of p204 and subsequent signal transduction upon herpes simplex virus 1 (HSV-1) infection in mouse cells. Taken together, our research work showed a new mechanism by which Sirt1 manipulated IFI16-mediated host defense. Our study also demonstrated a difference in the regulation of antiviral host defense between humans and mice, which might be considered in preclinical studies for antiviral treatment. IMPORTANCE DNA viruses, such as hepatitis B virus (HBV), human papillomavirus (HPV), human cytomegalovirus (HCMV), Epstein-Barr virus (EBV), and herpes simplex virus (HSV), can cause a wide range of diseases and are considered a global threat to human health. Interferon-inducible protein 16 (IFI16) binds virus DNA and triggers antiviral innate immune responses to restrict viral infection. In this study, we identified that silent information regulatory 1 (Sirtuin1, Sirt1) interacted with IFI16 and regulated IFI16-mediated innate host defense. Therefore, the activator or inhibitor of Sirt1 may have the potential to be used as a novel strategy to treat DNA virus-associated diseases. We also found that Sirt1 barely interacted with p204, the murine ortholog of human IFI16, and could not negatively regulate innate immune responses upon HSV-1 infection in mouse cells. This difference between humans and mice in the regulation of antiviral host defense might be considered in preclinical studies for antiviral treatment.
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Herpes Simples , Infecções por Herpesviridae , Proteínas Nucleares , Sirtuína 1 , Animais , Humanos , Camundongos , Infecções por Vírus Epstein-Barr , Herpesvirus Humano 4/metabolismo , Imunidade Inata , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Fosfoproteínas/genética , Fosfoproteínas/metabolismo , Sirtuína 1/genéticaRESUMO
Investigating the relationship between genetic variation and phenotypic traits is a key issue in quantitative genetics. Specifically for Alzheimer's disease, the association between genetic markers and quantitative traits remains vague while, once identified, will provide valuable guidance for the study and development of genetics-based treatment approaches. Currently, to analyze the association of two modalities, sparse canonical correlation analysis (SCCA) is commonly used to compute one sparse linear combination of the variable features for each modality, giving a pair of linear combination vectors in total that maximizes the cross-correlation between the analyzed modalities. One drawback of the plain SCCA model is that the existing findings and knowledge cannot be integrated into the model as priors to help extract interesting correlations as well as identify biologically meaningful genetic and phenotypic markers. To bridge this gap, we introduce preference matrix guided SCCA (PM-SCCA) that not only takes priors encoded as a preference matrix but also maintains computational simplicity. A simulation study and a real-data experiment are conducted to investigate the effectiveness of the model. Both experiments demonstrate that the proposed PM-SCCA model can capture not only genotype-phenotype correlation but also relevant features effectively.
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Doença de Alzheimer , Neuroimagem , Humanos , Neuroimagem/métodos , Análise de Correlação Canônica , Algoritmos , Doença de Alzheimer/diagnóstico por imagem , Doença de Alzheimer/genética , Encéfalo , Imageamento por Ressonância MagnéticaRESUMO
INTRODUCTION: Plasma proteomic analyses of unique brain atrophy patterns may illuminate peripheral drivers of neurodegeneration and identify novel biomarkers for predicting clinically relevant outcomes. METHODS: We identified proteomic signatures associated with machine learning-derived aging- and Alzheimer's disease (AD) -related brain atrophy patterns in the Baltimore Longitudinal Study of Aging (n = 815). Using data from five cohorts, we examined whether candidate proteins were associated with AD endophenotypes and long-term dementia risk. RESULTS: Plasma proteins associated with distinct patterns of age- and AD-related atrophy were also associated with plasma/cerebrospinal fluid (CSF) AD biomarkers, cognition, AD risk, as well as mid-life (20-year) and late-life (8-year) dementia risk. EFEMP1 and CXCL12 showed the most consistent associations across cohorts and were mechanistically implicated as determinants of brain structure using genetic methods, including Mendelian randomization. DISCUSSION: Our findings reveal plasma proteomic signatures of unique aging- and AD-related brain atrophy patterns and implicate EFEMP1 and CXCL12 as important molecular drivers of neurodegeneration. HIGHLIGHTS: Plasma proteomic signatures are associated with unique patterns of brain atrophy. Brain atrophy-related proteins predict clinically relevant outcomes across cohorts. Genetic variation underlying plasma EFEMP1 and CXCL12 influences brain structure. EFEMP1 and CXCL12 may be important molecular drivers of neurodegeneration.
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Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. However, the AD mechanism has not yet been fully elucidated to date, hindering the development of effective therapies. In our work, we perform a brain imaging genomics study to link genetics, single-cell gene expression data, tissue-specific gene expression data, brain imaging-derived volumetric endophenotypes, and disease diagnosis to discover potential underlying neurobiological pathways for AD. To do so, we perform brain-wide genome-wide colocalization analyses to integrate multidimensional imaging genomic biobank data. Specifically, we use (1) the individual-level imputed genotyping data and magnetic resonance imaging (MRI) data from the UK Biobank, (2) the summary statistics of the genome-wide association study (GWAS) from multiple European ancestry cohorts, and (3) the tissue-specific cis-expression quantitative trait loci (cis-eQTL) summary statistics from the GTEx project. We apply a Bayes factor colocalization framework and mediation analysis to these multi-modal imaging genomic data. As a result, we derive the brain regional level GWAS summary statistics for 145 brain regions with 482,831 single nucleotide polymorphisms (SNPs) followed by posthoc functional annotations. Our analysis yields the discovery of a potential AD causal pathway from a systems biology perspective: the SNP chr10:124165615:G>A (rs6585827) mutation upregulates the expression of BTBD16 gene in oligodendrocytes, a specialized glial cells, in the brain cortex, leading to a reduced risk of volumetric loss in the entorhinal cortex, resulting in the protective effect on AD. We substantiate our findings with multiple evidence from existing imaging, genetic and genomic studies in AD literature. Our study connects genetics, molecular and cellular signatures, regional brain morphologic endophenotypes, and AD diagnosis, providing new insights into the mechanistic understanding of the disease. Our findings can provide valuable guidance for subsequent therapeutic target identification and drug discovery in AD.
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Doença de Alzheimer , Humanos , Doença de Alzheimer/diagnóstico por imagem , Doença de Alzheimer/genética , Teorema de Bayes , Estudo de Associação Genômica Ampla , Transcriptoma , Encéfalo/diagnóstico por imagem , Córtex EntorrinalRESUMO
The flow cytometer has become a powerful and widely accepted measurement device in both biological studies and clinical diagnostics. The application of the flow cytometer in emerging point-of-care scenarios, such as instant detection in remote areas and emergency diagnosis, requires a significant reduction in physical dimension, cost, and power consumption. This requirement promotes studies to develop portable flow cytometers, mostly based on the utilization of polymer microfluidic chips. However, due to the relatively poor optical performance of polymer materials, existing microfluidic flow cytometers are incapable of accurate blood analysis, such as the four-part leukocyte differential count, which is necessary to monitor the immune system and to assess the risk of allergic inflammation or viral infection. To address this issue, an ultraportable flow cytometer based on an all-glass microfluidic chip (AG-UFCM) has been developed in this study. Compared with that of a typical commercial flow cytometer (BD FACSAria III), the volume of the AG-UFCM was reduced by 90 times (from 720 to 8 L). A two-step laser processing was employed to fabricate an all-glass microfluidic chip with a surface roughness of less than 1 nm, significantly improving the optical performance of on-chip micro-lens. The signal-to-noise ratio was enhanced by 3 dB, compared with that of polymer materials. For the first time, a four-part leukocyte differential count based on single fluorescence staining was realized using a miniaturized flow cytometer, laying a foundation for the point-of-care testing of miniaturized flow cytometers.
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Lentes , Técnicas Analíticas Microfluídicas , Microfluídica , Citometria de Fluxo/métodos , PolímerosRESUMO
INTRODUCTION: Little is known about the epidemiology of brain microbleeds in racially/ethnically diverse populations. METHODS: In the Multi-Ethnic Study of Atherosclerosis, brain microbleeds were identified from 3T magnetic resonance imaging susceptibility-weighted imaging sequences using deep learning models followed by radiologist review. RESULTS: Among 1016 participants without prior stroke (25% Black, 15% Chinese, 19% Hispanic, 41% White, mean age 72), microbleed prevalence was 20% at age 60 to 64.9 and 45% at ≥85 years. Deep microbleeds were associated with older age, hypertension, higher body mass index, and atrial fibrillation, and lobar microbleeds with male sex and atrial fibrillation. Overall, microbleeds were associated with greater white matter hyperintensity volume and lower total white matter fractional anisotropy. DISCUSSION: Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.
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Fibrilação Atrial , Hemorragia Cerebral , Humanos , Masculino , Idoso , Pessoa de Meia-Idade , Hemorragia Cerebral/diagnóstico por imagem , Hemorragia Cerebral/epidemiologia , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Imageamento por Ressonância Magnética/métodos , Fatores de Risco , CogniçãoRESUMO
Mediator of IRF3 activation (MITA, also named as STING/ERIS/MPYS/TMEM173), is essential to DNA virus- or cytosolic DNA-triggered innate immune responses. In this study, we demonstrated the negative regulatory role of RING-finger protein (RNF) 90 in innate immune responses targeting MITA. RNF90 promoted K48-linked ubiquitination of MITA and its proteasome-dependent degradation. Overexpression of RNF90 inhibited HSV-1- or cytosolic DNA-induced immune responses whereas RNF90 knockdown had the opposite effects. Moreover, RNF90-deficient bone marrow-derived dendritic cells (BMDCs), bone marrow-derived macrophages (BMMs) and mouse embryonic fibroblasts (MEFs) exhibited increased DNA virus- or cytosolic DNA-triggered signaling and RNF90 deficiency protected mice from DNA virus infection. Taken together, our findings suggested a novel function of RNF90 in innate immunity.
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Herpesvirus Humano 1/imunologia , Imunidade Inata , Proteínas de Membrana/imunologia , Proteólise , Proteínas com Motivo Tripartido/imunologia , Ubiquitina-Proteína Ligases/imunologia , Ubiquitinação/imunologia , Animais , Células da Medula Óssea/imunologia , Células da Medula Óssea/virologia , Células Dendríticas/imunologia , Células Dendríticas/virologia , Fibroblastos/imunologia , Fibroblastos/virologia , Herpesvirus Humano 1/genética , Macrófagos/imunologia , Macrófagos/virologia , Proteínas de Membrana/genética , Camundongos , Camundongos Knockout , Proteínas com Motivo Tripartido/genética , Ubiquitina-Proteína Ligases/genética , Ubiquitinação/genéticaRESUMO
OBJECTIVES: To measure heavy metal concentrations among Kenyan youth and quantify associations with sociocultural, demographic, and health factors as well as anthropometry. METHODS: Using data from a study of semi-nomadic pastoralists in Samburu County, Kenya, we measured blood concentrations of lead (Pb), mercury (Hg), and cadmium (Cd) in 161 adolescents. We identified sociocultural, demographic and health characteristics associated with each metal and quantified the association between metals and adolescent anthropometry. RESULTS: Median blood concentrations of Pb, Cd, and Hg were 1.82 µg/dL, 0.24 µg/L and 0.16 µg/L, respectively. Place of residence (highlands vs lowlands) was a determinant of metal concentrations. Hg was inversely related to anemia, and metals were not associated with anthropometry. CONCLUSIONS: In this population of Samburu adolescents, median Pb and Cd blood concentrations were higher than other North American or European biomonitoring studies. These findings motivate further investigation into the environmental sources of metals in this community.
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Anemia , Mercúrio , Metais Pesados , Adolescente , Anemia/epidemiologia , Antropometria , Cádmio , Humanos , Quênia/epidemiologia , ChumboRESUMO
The Lulun Project, a randomized controlled trial conducted in 2015, found that one egg per day for 6 months during early complementary feeding reduced stunting by 47% and increased linear growth by 0.63 length-for-age Z (LAZ). This follow-up cohort study (Lulun Project II) aimed to test whether the growth effect remained in the egg intervention group compared with the control group after approximately 2 years. Mothers or caregivers from the Lulun Project were recontacted and recruited for this study. Enumerators collected data on socio-economic and demographic factors, 24-hr frequency of dietary intakes, morbidities, and anthropometric measures of height, weight, and head circumference using World Health Organization protocols. Statistical analyses followed the same analytical plan as Lulun Project, applying generalized linear models and regression modelling to test group differences in height-for-age z (HAZ) from LAZ at Lulun Project endline, and structural equation modelling for mediation. One hundred thirty-five mother-child dyads were included in Lulun II, with 11% losses to follow-up from endline Lulun Project. Growth faltering across all children was evident with HAZ -2.07 ± 0.91 and a stunting prevelance of 50%. Regression modelling showed no difference between egg and control groups for the HAZ outcome and other anthropometric outcomes, and significant declines in HAZ from endline Lulun Project in the egg intervention are compared with control groups. Current dietary egg intake, however, was associated with reduced growth faltering in HAZ from Lulun Project endline to Lulun Project II, independent of group assignment and through mediation, explaining 8.8% of the total effect. Findings suggest the need for a longer intervention period and ongoing nutrition support to young children during early childhood.
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Antropometria/métodos , Estatura , Desenvolvimento Infantil , Dieta/métodos , Ovos , Transtornos do Crescimento/epidemiologia , Peso Corporal , Pré-Escolar , Equador/epidemiologia , Feminino , Seguimentos , Transtornos do Crescimento/prevenção & controle , Humanos , Estudos Longitudinais , MasculinoRESUMO
Hairpin DNA (hpDNA) as a novel biobarcode was conjugated with gold nanoparticles (AuNPs) and a reporter DNA (rpDNA) to form hpDNA/AuNP/rpDNA nanoparticles for the detection of an oligonucleotide sequence associated with Helicobacter pylori as a model target. The rpDNA is complementary to about a half-portion of the target DNA sequence (tDNA). A capture DNA probe (cpDNA), complementary to the other half of the tDNA, was immobilized on the surface of a gold electrode. In the presence of tDNA, a sandwich structure of (hpDNA/AuNP/rpDNA)/tDNA/cpDNA was formed on the electrode surface. The differential pulse voltammetry (DPV) detection was based on [Ru(NH3)5(3-(2-phenanthren-9-yl-vinyl)-pyridine)](2+), an electroactive complex that binds to the sandwich structure by its intercalation with the hpDNA and the double-stranded DNA (dsDNA) of the sandwich structure. The several factors--high density of biobarcode hpDNA on the surface of AuNPs, multiple electroactive complex molecules intercalated with each hpDNA and dsDNA molecule, and the intercalation binding mode of the electroactive complex with the DNA sandwich structure--contribute to the DNA sensor with highly selective and sensitive sensing properties. The DNA sensor exhibited a detection limit of 1 × 10(-15) M (i.e., 1 fM), the DNA levels in physiological samples, with linearity down to 2 × 10(-15) M. It can differentiate even one single mismatched DNA from the complementary tDNA. This novel biobarcode-based DNA sensing approach should provide a general platform for development of direct, simple, repetitive, sensitive, and selective DNA sensors for various important applications in analytical, environmental, and clinical chemistry.
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Sondas de DNA/química , DNA Bacteriano/análise , Técnicas Eletroquímicas/instrumentação , Ouro/química , Helicobacter pylori/isolamento & purificação , Nanopartículas Metálicas/química , Complexos de Coordenação/química , DNA Bacteriano/isolamento & purificação , Técnicas Eletroquímicas/métodos , Eletrodos , Desenho de Equipamento , Infecções por Helicobacter/diagnóstico , Infecções por Helicobacter/microbiologia , Humanos , Ácidos Nucleicos Imobilizados/química , Limite de Detecção , Rutênio/químicaRESUMO
Salicylic esters (SEs), the widely used ultraviolet (UV) absorbers in sunscreen products, have been found to have health risks such as skin sensitization and estrogenic effects. This study aims to design SE substitutes that maintain high UV absorbance while reducing estrogenicity. Using molecular docking and Gaussian09 software for initial assessments and further application of a combination of two-dimensional and three-dimensional quantitative structure-activity relationships (2D-QSAR and 3D-QSAR, respectively) models, we designed 73 substitutes. The best-performing molecules, ethylhexyl salicylate (EHS)-5 and EHS-15, significantly reduced estrogenicity (44.54 % and 17.60 %, respectively) and enhanced UV absorbance (249.56 % and 46.94 %, respectively). Through screening for human health risks, we found that EHS-5 and EHS-15 were free from skin sensitivity and eye irritation and exhibited reduced skin permeability compared with EHS. Furthermore, the photolysis and synthetic pathways of EHS-5 and EHS-15 were deduced, demonstrating their good photodegradability and potential synthesizability. In addition, we analyzed the mechanisms underlying the changes in estrogenic effects and UV absorption properties. We identified covalent hydrogen bond basicity and acidity Propgen value for atomic molecular properties and the highest occupied molecular orbital eigenvalue as the main factors affecting the estrogenic effect and UV absorbance of SEs, respectively. This study focuses on the design and screening of SEs, exhibiting enhanced functionality, reduced health risks, and synthetic feasibility.
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Estrogênios , Simulação de Acoplamento Molecular , Relação Quantitativa Estrutura-Atividade , Salicilatos , Protetores Solares , Protetores Solares/química , Protetores Solares/toxicidade , Salicilatos/química , Salicilatos/toxicidade , Estrogênios/química , Estrogênios/toxicidade , Humanos , Raios Ultravioleta , Fotólise , Animais , Pele/efeitos dos fármacos , Pele/efeitos da radiaçãoRESUMO
Due to the significant POPs characteristics, dioxins caused concern in public health and environmental protection. Evaluating the toxicity risk of dioxin degradation pathways is critical. OCDD, 1,2,3,4,6,7,8-HpCDD, and 1,2,3,4,6,7,8-HpCDF, which are highly abundant in the environment and have strong biodegradation capabilities, were selected as precursor molecules in this study. Firstly, their transformation pathways were deduced during the metabolism of biometabolism, microbial aerobic, microbial anaerobic, and photodegradation pathways, and density function theory (DFT) was used to calculate the Gibbs free energy to infer the possibility of the occurrence of the transformation pathway. Secondly, the carcinogenic potential of the precursors and their degradation products was evaluated using the TOPKAT modeling method. With the help of the positive indicator (0-1) normalization method and heat map analysis, a significant increase in the toxic effect of some of the transformation products was found, and it was inferred that it was related to the structure of the transformation products. Meanwhile, the strength of the endocrine disrupting effect of dioxin transformation products was quantitatively assessed using molecular docking and subjective assignment methods, and it was found that dioxin transformation products with a higher content of chlorine atoms and molecules similar to those of thyroid hormones exhibited a higher risk of endocrine disruption. Finally, the environmental health risks caused by each degradation pathway were comprehensively assessed with the help of the negative indicator (1-2) standardization method, which provides a theoretical basis for avoiding the toxicity risks caused by dioxin degradation transformation. In addition, the 3D-QSAR model was used to verify the necessity and rationality of this study. This paper provides theoretical support and reference significance for the toxicity assessment of dioxin degradation by-products from inferred degradation pathways.
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Biodegradação Ambiental , Dioxinas , Dioxinas/toxicidade , Disruptores Endócrinos/toxicidade , Poluentes Ambientais/toxicidadeRESUMO
Liquid crystal monomers (LCMs) are identified as emerging organic contaminations with largely unexplored health impacts. To elucidate their toxic mechanisms, support the establishment of environmental discharge and management standards, and promote effective LCMs control, this study constructs a database covering 20,545 potential targets of 1431 LCMs, highlighting 9 key toxic target proteins that disrupt the nervous system and metabolic functions. GO and KEGG pathway analysis suggests LCMs severely affect nervous system, linked to neurodegenerative diseases and mental health disorders, with toxicity variations driven by electronegativity and structural complexity of LCM terminal groups. To achieve tiered control of LCMs, construct toxicity risk control lists for 9 key toxic target proteins, suitable for the graded control of LCMs, management recommendations are provided based on toxicity levels. These lists were validated for reliability and offer reliable toxicity predictions for LCMs. SHAP analysis points to electronic properties, molecular shape, and structural characteristics of LCMs as primary health impact factors. As the first study integrating machine learning with computational toxicology to outline LCMs health impacts, it aims to enhance public understanding of LCM toxicity risks and support the development of environmental standards, effective management of LCM production and emissions, and reduction of public exposure risks.
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The degradation of fluoroquinolones (FQs) via advanced oxidation processes (AOPs) is a promising avenue, yet the complete mineralization of certain FQ molecules remains elusive, raising concerns about the formation of toxic by-products. This study delineates five primary AOP degradation pathways for 16 commercially available FQ molecules, inferred from existing literature. Density functional theory (DFT) was employed to calculate the bond dissociation energies within these pathways to elucidate the correlation between bond strength and molecular architecture. Subsequently, Comparative Molecular Similarity Index Analysis (CoMSIA) models were constructed for various degradation reactions, including piperazine ring cleavage, defluorination, hydroxylation, and piperazine ring hydroxylation. Three-dimensional contour maps generated from these models provide a deeper understanding of the interplay between FQ molecular structure and bond dissociation energy. Furthermore, toxicity predictions for 16 FQ molecules and their advanced oxidation intermediates, conducted using VEGA 1.2.3 software, indicate that degradation products from pathways P2 and P5 pose a heightened health risk relative to their parent compounds. Furthermore, the application of the Multwfn program to compute the Fukui function for FQ molecules discerns the disparity in degradation propensities, highlighting that N atoms with higher f0 values can augment the likelihood of piperazine ring cleavage. HOMO-LUMO distribution diagrams further confirm that methoxy substitution at the 1-position leads to a dilution of HOMOs on the piperazine ring and an increased energy gap for free radical reactions, diminishing the reactivity with hydroxyl radicals. This study elucidates the pivotal role of structural characteristics in FQ antibiotics for their degradation efficiency within AOPs and unveils the underlying mechanisms of bond dissociation energy disparities. The toxicity parameter predictions for FQ molecules and their intermediates offer unique perspectives and theoretical underpinnings for mitigating the use of high-risk FQs and for devising targeted degradation strategies to circumvent the generation of toxic intermediates in AOPs through molecular structure optimization.
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Liquid crystal monomers (LCMs), identified as emerging contaminations, have been detected in soils and plants, but their accumulation characteristics in plants haven't been studied. Therefore, this study systematically investigated the accumulation characteristics of LCMs in plants from four dimensions (i.e., plant fruit species, soil types, plant growth stages, and LCMs categories) for the first time. The LCMs concentrations (9.96 × 10-4 to 114.608 ng/g) in 22 plant fruits were predicted by the partition-limited model. Grains with the highest lipid content showed the highest LCMs accumulation propensity. Plants grown in paddy soil showed a strong LCMs accumulation capacity. Results showed that the LCMs accumulation capacity in plants from soils decreased when the soil organic matter content increased. A preferential accumulation of LCMs in plant root systems during growth was found by the molecular dynamics simulations. Compared to polychlorinated biphenyls (as the reference contaminants of LCMs), LCMs exhibit higher accumulation in plant roots and lower translocation to shoots. For the fourth dimension, lipophilicity was found to be the main reason of LCMs accumulation by intergraded stepwise linear regression with sensitivity analysis. This is the inaugural research concentrating on LCMs accumulation in plants, providing insights and theoretical guidance for future LCMs management strategies multidimensionally.
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Cristais Líquidos , Poluentes do Solo , Traqueófitas , Poluentes do Solo/análise , Plantas , Raízes de Plantas/química , Solo/químicaRESUMO
Understanding the genetic basis of biological aging in multi-organ systems is vital for elucidating age-related disease mechanisms and identifying therapeutic interventions. This study characterized the genetic architecture of the biological age gap (BAG) across nine human organ systems in 377,028 individuals of European ancestry from the UK Biobank. We discovered 393 genomic loci-BAG pairs (P-value<5×10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary, and renal systems. We observed BAG-organ specificity and inter-organ connections. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system while exerting pleiotropic effects on traits linked to multiple organ systems. A gene-drug-disease network confirmed the involvement of the metabolic BAG-associated genes in drugs targeting various metabolic disorders. Genetic correlation analyses supported Cheverud's Conjecture1 - the genetic correlation between BAGs mirrors their phenotypic correlation. A causal network revealed potential causal effects linking chronic diseases (e.g., Alzheimer's disease), body weight, and sleep duration to the BAG of multiple organ systems. Our findings shed light on promising therapeutic interventions to enhance human organ health within a complex multi-organ network, including lifestyle modifications and potential drug repositioning strategies for treating chronic diseases. All results are publicly available at https://labs-laboratory.com/medicine.
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Investigating the genetic underpinnings of human aging is essential for unraveling the etiology of and developing actionable therapies for chronic diseases. Here, we characterize the genetic architecture of the biological age gap (BAG; the difference between machine learning-predicted age and chronological age) across nine human organ systems in 377,028 participants of European ancestry from the UK Biobank. The BAGs were computed using cross-validated support vector machines, incorporating imaging, physical traits and physiological measures. We identify 393 genomic loci-BAG pairs (P < 5 × 10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary and renal systems. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system (organ specificity) while exerting pleiotropic links with other organ systems (interorgan cross-talk). We find that genetic correlation between the nine BAGs mirrors their phenotypic correlation. Further, a multiorgan causal network established from two-sample Mendelian randomization and latent causal variance models revealed potential causality between chronic diseases (for example, Alzheimer's disease and diabetes), modifiable lifestyle factors (for example, sleep duration and body weight) and multiple BAGs. Our results illustrate the potential for improving human organ health via a multiorgan network, including lifestyle interventions and drug repurposing strategies.
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Metal-organic frameworks (MOFs) have emerged as promising active electrode materials in supercapacitors for its controllable porous structure and excellent physio-chemical properties. However, the poor conductivities keep it from achieving its full capacitance potential, which greatly limits its practical application. Here, a facile pathway is reported to fabricate the GO/Ni2ZnS4@NiCo2S4 composite with large specific surface area and favorable electrical conductivity. Thanks to the novel tremella-like core-shell structure and high-efficient synergistic effects among multi-components, the designed GO/Ni2ZnS4@NiCo2S4 electrode shows a high specific capacitance of 2284 F/g at 1 A/g. Furthermore, the asymmetric supercapacitor fabricated by coupling GO/Ni2ZnS4@NiCo2S4 positive electrode with biological carbon negative electrode achieves a remarkable energy density of 120 Wh kg-1 at a power density of 750 W kg-1.
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Alzheimer's disease (AD) is a complex neurodegenerative disorder that has impacted millions of people worldwide. The neuroanatomical heterogeneity of AD has made it challenging to fully understand the disease mechanism. Identifying AD subtypes during the prodromal stage and determining their genetic basis would be immensely valuable for drug discovery and subsequent clinical treatment. Previous studies that clustered subgroups typically used unsupervised learning techniques, neglecting the survival information and potentially limiting the insights gained. To address this problem, we propose an interpretable survival analysis method called Deep Clustering Survival Machines (DCSM), which combines both discriminative and generative mechanisms. Similar to mixture models, we assume that the timing information of survival data can be generatively described by a mixture of parametric distributions, referred to as expert distributions. We learn the weights of these expert distributions for individual instances in a discriminative manner by leveraging their features. This allows us to characterize the survival information of each instance through a weighted combination of the learned expert distributions. We demonstrate the superiority of the DCSM method by applying this approach to cluster patients with mild cognitive impairment (MCI) into subgroups with different risks of converting to AD. Conventional clustering measurements for survival analysis along with genetic association studies successfully validate the effectiveness of the proposed method and characterize our clustering findings.