Biochemical, Biomarker, and Behavioral Characterization of the GrnR493X Mouse Model of Frontotemporal Dementia.

Heterozygous loss-of-function mutations in the progranulin gene (GRN) are a major cause of frontotemporal dementia due to progranulin haploinsufficiency; complete deficiency of progranulin causes neuronal ceroid lipofuscinosis. Several progranulin-deficient mouse models have been generated, including both knockout mice and knockin mice harboring a common patient mutation (R493X). However, the GrnR493X mouse model has not been characterized completely. Additionally, while homozygous GrnR493X and Grn knockout mice have been extensively studied, data from heterozygous mice is still limited. Here, we performed more in-depth characterization of heterozygous and homozygous GrnR493X knockin mice, which includes biochemical assessments, behavioral studies, and analysis of fluid biomarkers. In the brains of homozygous GrnR493X mice, we found increased phosphorylated TDP-43 along with increased expression of lysosomal genes, markers of microgliosis and astrogliosis, pro-inflammatory cytokines, and complement factors. Heterozygous GrnR493X mice did not have increased TDP-43 phosphorylation but did exhibit limited increases in lysosomal and inflammatory gene expression. Behavioral studies found social and emotional deficits in GrnR493X mice that mirror those observed in Grn knockout mouse models, as well as impairment in memory and executive function. Overall, the GrnR493X knockin mouse model closely phenocopies Grn knockout models. Lastly, in contrast to homozygous knockin mice, heterozygous GrnR493X mice do not have elevated levels of fluid biomarkers previously identified in humans, including neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in both plasma and CSF. These results may help to inform pre-clinical studies that use this Grn knockin mouse model and other Grn knockout models.

Biochemical, biomarker, and behavioral characterization of the GrnR493X mouse model of frontotemporal dementia.

Heterozygous loss-of-function mutations in the progranulin gene (GRN) are a major cause of frontotemporal dementia due to progranulin haploinsufficiency; complete deficiency of progranulin causes neuronal ceroid lipofuscinosis. Several progranulin-deficient mouse models have been generated, including both knockout mice and knockin mice harboring a common patient mutation (R493X). However, the GrnR493X mouse model has not been characterized completely. Additionally, while homozygous GrnR493X and Grn knockout mice have been extensively studied, data from heterozygous mice is still limited. Here, we performed more in-depth characterization of heterozygous and homozygous GrnR493X knockin mice, which includes biochemical assessments, behavioral studies, and analysis of fluid biomarkers. In the brains of homozygous GrnR493X mice, we found increased phosphorylated TDP-43 along with increased expression of lysosomal genes, markers of microgliosis and astrogliosis, pro-inflammatory cytokines, and complement factors. Heterozygous GrnR493X mice did not have increased TDP-43 phosphorylation but did exhibit limited increases in lysosomal and inflammatory gene expression. Behavioral studies found social and emotional deficits in GrnR493X mice that mirror those observed in Grn knockout mouse models, as well as impairment in memory and executive function. Overall, the GrnR493X knockin mouse model closely phenocopies Grn knockout models. Lastly, in contrast to homozygous knockin mice, heterozygous GrnR493X mice do not have elevated levels of fluid biomarkers previously identified in humans, including neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in both plasma and CSF. These results may help to inform pre-clinical studies that use this Grn knockin mouse model and other Grn knockout models.

Low circulating adropin concentrations predict increased risk of cognitive decline in community-dwelling older adults.

The secreted peptide adropin is highly expressed in human brain tissues and correlates with RNA and proteomic risk indicators for dementia. Here we report that plasma adropin concentrations predict risk for cognitive decline in the Multidomain Alzheimer Preventive Trial (ClinicalTrials.gov Identifier, NCT00672685; mean age 75.8y, SD = 4.5 years, 60.2% female, n = 452). Cognitive ability was evaluated using a composite cognitive score (CCS) that assessed four domains: memory, language, executive function, and orientation. Relationships between plasma adropin concentrations and changes in CCS (∆CCS) were examined using Cox Proportional Hazards Regression, or by grouping into tertiles ranked low to high by adropin values and controlling for age, time between baseline and final visits, baseline CCS, and other risk factors (e.g., education, medication, APOE4 status). Risk of cognitive decline (defined as a ∆CCS of - 0.3 or more) decreased with increasing plasma adropin concentrations (hazard ratio = 0.873, 95% CI 0.780-0.977, P = 0.018). Between adropin tertiles, ∆CCS was significantly different (P = 0.01; estimated marginal mean ± SE for the 1st to 3rd tertile, - 0.317 ± 0.064; - 0.275 ± 0.063; - 0.042 ± 0.071; n = 133,146, and 130, respectively; P < 0.05 for 1st vs. 2nd and 3rd adropin tertiles). Normalized plasma Aß42/40 ratio and plasma neurofilament light chain, indicators of neurodegeneration, were significantly different between adropin tertile. These differences were consistent with reduced risk of cognitive decline with higher plasma adropin levels. Overall, these results suggest cognitive decline is reduced in community-dwelling older adults with higher circulating adropin levels. Further studies are needed to determine the underlying causes of the relationship and whether increasing adropin levels can delay cognitive decline.

Low circulating adropin levels in late-middle aged African Americans with poor cognitive performance.

We recently reported accelerated cognitive decline in Europeans aged > 70 years with low circulating adropin levels. Adropin is a small, secreted peptide that is highly expressed in the human nervous system. Expression profiling indicate relationships between adropin expression in the human brain and pathways that affect dementia risk. Moreover, increased adropin expression or treatment using synthetic adropin improves cognition in mouse models of aging. Here we report that low circulating adropin concentrations associate with poor cognition (worst quintile for a composite score derived from the MMSE and semantic fluency test) in late-middle aged community-dwelling African Americans (OR = 0.775, P < 0.05; age range 45-65 y, n = 352). The binomial logistic regression controlled for sex, age, education, cardiometabolic disease risk indicators, and obesity. Previous studies using cultured cells from the brains of human donors suggest high expression in astrocytes. In snRNA-seq data from the middle temporal gyrus (MTG) of human donors, adropin expression is higher in astrocytes relative to other cell types. Adropin expression in all cell-types declines with advance age, but is not affected by dementia status. In cultured human astrocytes, adropin expression also declines with donor age. Additional analysis indicated positive correlations between adropin and transcriptomic signatures of energy metabolism and protein synthesis that are adversely affected by donor age. Adropin expression is also suppressed by pro-inflammatory factors. Collectively, these data indicate low circulating adropin levels are a potential early risk indicator of cognitive impairment. Declining adropin expression in the brain is a plausible link between aging, neuroinflammation, and risk of cognitive decline.

Liquid Bioformulation: A Trending Approach Towards Achieving Sustainable Agriculture.

The human population is expanding at an exponential rate, and has created a great surge in the demand for food production. To intensify the rate of crop production, there is a tremendous usage of chemical pesticides and fertilizers. The practice of using these chemicals to enhance crop productivity has resulted in the degradation of soil fertility, leading to the depletion of native soil microflora. The constant application of these hazardous chemicals in the soil possesses major threat to humans and animals thereby impacting the agroecosystem severely. Hence, it is very important to hunt for certain new alternatives for enhancing crop productivity in an eco-friendly manner by using the microbial bioformulations. Microbial bioformulations can be mainly divided into two types: solid and liquid. There is a lot of information available on the subject of solid bioformulation, but the concept of liquid bioformulation is largely ignored. This article focuses on the diverse spectrum of liquid bioformulation pertaining to the market capture, its different types, potency of the product, mode of usage, and the limitations encountered. Also the authors have tried to include all the strategies required for sensitizing and making liquid bioformulation approach cost effective and as a greener strategy to succeed in developing countries.

Antisense oligonucleotides targeting the miR-29b binding site in the GRN mRNA increase progranulin translation.

Heterozygous GRN (progranulin) mutations cause frontotemporal dementia (FTD) due to haploinsufficiency, and increasing progranulin levels is a major therapeutic goal. Several microRNAs, including miR-29b, negatively regulate progranulin protein levels. Antisense oligonucleotides (ASOs) are emerging as a promising therapeutic modality for neurological diseases, but strategies for increasing target protein levels are limited. Here, we tested the efficacy of ASOs as enhancers of progranulin expression by sterically blocking the miR-29b binding site in the 3' UTR of the human GRN mRNA. We found 16 ASOs that increase progranulin protein in a dose-dependent manner in neuroglioma cells. A subset of these ASOs also increased progranulin protein in iPSC-derived neurons and in a humanized GRN mouse model. In FRET-based assays, the ASOs effectively competed for miR-29b from binding to the GRN 3' UTR RNA. The ASOs increased levels of newly synthesized progranulin protein by increasing its translation, as revealed by polysome profiling. Together, our results demonstrate that ASOs can be used to effectively increase target protein levels by partially blocking miR binding sites. This ASO strategy may be therapeutically feasible for progranulin-deficient FTD as well as other conditions of haploinsufficiency.

TNFR-1 and GDF-15 Are Associated With Plasma Neurofilament Light Chain and Progranulin Among Community-Dwelling Older Adults: A Secondary Analysis of the MAPT Study.

There is growing evidence that cognitive decline can be affected by both nutritional aspects and inflammation. Plasma neurodegenerative biomarkers stand out as minimally invasive useful measures to monitor the potential risk of cognitive decline. This study aimed to investigate the associations between biomarkers of neurodegeneration, nutrition, and inflammation among community-dwelling older adults, and to verify if associations differed according to apolipoprotein E (APOE) ε4 status. This cross-sectional analysis included 475 participants ≥70 years old from the Multidomain Alzheimer Preventive Trial (MAPT), mean age 76.8 years (SD = 4.5), 59.4% women. Biomarkers of neurodegeneration (plasma amyloid-ß 42/40-Aß 42/40, neurofilament light chain-NfL, progranulin), nutrition (erythrocyte docosahexaenoic acid, eicosapentaenoic acid, omega-3 index; plasma homocysteine-Hcy, 25 hydroxyvitamin D), inflammation (plasma tumor necrosis factor receptor 1-TNFR-1, monocyte chemoattractant protein 1-MCP-1, interleukin 6-IL-6), and cellular stress (plasma growth differentiation factor 15-GDF-15) were assessed. Linear regression analyses were performed to investigate the associations between nutritional and inflammatory biomarkers (independent variables) and neurodegenerative biomarkers (dependent variables), with adjustments for age, sex, education, body mass index, physical activity, allocation to MAPT groups, and APOE ε4 status. After adjusting for confounders, Aß 42/40 was not associated with nutritional or inflammatory markers. NfL was positively associated with GDF-15, TNFR-1, IL-6, and Hcy. Progranulin was positively associated with GDF-15, TNFR-1, and MCP-1. Analyses restricted to APOE ε4 carriers (n = 116; 26.9%) or noncarriers were mostly similar. Our cross-sectional study with community-dwelling older adults corroborates previous evidence that inflammatory pathways are associated to plasma markers of neurodegeneration. Clinical Trials Registration Number: NCT00672685.

Deficiency of the frontotemporal dementia gene GRN results in gangliosidosis.

Haploinsufficiency of GRN causes frontotemporal dementia (FTD). The GRN locus produces progranulin (PGRN), which is cleaved to lysosomal granulin polypeptides. The function of lysosomal granulins and why their absence causes neurodegeneration are unclear. Here we discover that PGRN-deficient human cells and murine brains, as well as human frontal lobes from GRN-mutation FTD patients have increased levels of gangliosides, glycosphingolipids that contain sialic acid. In these cells and tissues, levels of lysosomal enzymes that catabolize gangliosides were normal, but levels of bis(monoacylglycero)phosphates (BMP), lipids required for ganglioside catabolism, were reduced with PGRN deficiency. Our findings indicate that granulins are required to maintain BMP levels to support ganglioside catabolism, and that PGRN deficiency in lysosomes leads to gangliosidosis. Lysosomal ganglioside accumulation may contribute to neuroinflammation and neurodegeneration susceptibility observed in FTD due to PGRN deficiency and other neurodegenerative diseases.

Progranulin Preserves Autophagy Flux and Mitochondrial Function in Rat Cortical Neurons Under High Glucose Stress.

Chronic hyperglycemia in type II diabetes results in impaired autophagy function, accumulation of protein aggregates, and neurodegeneration. However, little is known about how to preserve autophagy function under hyperglycemic conditions. In this study, we tested whether progranulin (PGRN), a neurotrophic factor required for proper lysosome function, can restore autophagy function in neurons under high-glucose stress. We cultured primary cortical neurons derived from E18 Sprague-Dawley rat pups to maturity at 10 days in vitro (DIV) before incubation in high glucose medium and PGRN for 24-72 h before testing for autophagy flux, protein turnover, and mitochondrial function. We found that although PGRN by itself did not upregulate autophagy, it attenuated impairments in autophagy seen under high-glucose conditions. Additionally, buildup of the autophagosome marker light chain 3B (LC3B) and lysosome marker lysosome-associated membrane protein 2A (LAMP2A) changed in both neurons and astrocytes, indicating a possible role for glia in autophagy flux. Protein turnover, assessed by remaining advanced glycation end-product levels after a 6-h incubation, was preserved with PGRN treatment. Mitochondrial activity differed by complex, although PGRN appeared to increase overall activity in high glucose. We also found that activation of extracellular signal-regulated kinase 1/2 (ERK1/2) and glycogen synthase kinase 3ß (GSK3ß), kinases implicated in autophagy function, increased with PGRN treatment under stress. Together, our data suggest that PGRN prevents hyperglycemia-induced decreases in autophagy by increasing autophagy flux via increased ERK1/2 kinase activity in primary rat cortical neurons.

Self-Sovereignty Identity Management Model for Smart Healthcare System.

An identity management system is essential in any organisation to provide quality services to each authenticated user. The smart healthcare system should use reliable identity management to ensure timely service to authorised users. Traditional healthcare uses a paper-based identity system which is converted into centralised identity management in a smart healthcare system. Centralised identity management has security issues such as denial of service attacks, single-point failure, information breaches of patients, and many privacy issues. Decentralisedidentity management can be a robust solution to these security and privacy issues. We proposed a Self-Sovereign identity management system for the smart healthcare system (SSI-SHS), which manages the identity of each stakeholder, including medical devices or sensors, in a decentralisedmanner in the Internet of Medical Things (IoMT) Environment. The proposed system gives the user complete control of their data at each point. Further, we analysed the proposed identity management system against Allen and Cameron's identity management guidelines. We also present the performance analysis of SSI as compared to the state-of-the-art techniques.

Serum neurofilament light levels are predictive of all-cause mortality in late middle-aged individuals.

BACKGROUND: Blood biomarkers can offer valuable and easily accessible indicators of normal biological processes, pathogenic conditions, and responses to therapeutic interventions. Recent studies found that levels of neurofilament light chain (NfL) in the blood are associated with mortality in three European cohorts of older adults (median ages 73, 93, and 100 years). Whether similar associations exist in younger adults and in other ethnic groups is currently not known. METHODS: We utilized a cohort study that included 294 African Americans (baseline ages 49-65). Serum NfL levels were measured using a Meso Scale Discovery-based assay. Vital status was determined by matching through the National Death Index. FINDINGS: Seventy-two participants (24.5%) died during the 14-15 years of follow up (2000-2014). Baseline serum NfL levels were significantly higher in the decedent group (86.1±65.7 pg/ml vs. 50.1±28.0 pg/ml, p < 0·001). In binomial logistic regression models adjusted for age, gender, education, baseline smoking status, BMI, and total comorbidities (0-11), serum NfL levels remained a strong predictor of all-cause mortality, and sensitivity analyses employing multiple additional covariates did not substantively change the relationship. Further, Kaplan-Meier curves based on serum NfL quartiles showed reduced survival in groups with higher serum NfL levels. INTERPRETATION: This study found a positive association between serum NfL levels and mortality in late middle-aged and older individuals. While our findings support that serum NfL levels may be a useful biomarker for all-cause mortality, further studies are needed to understand the biological mechanisms underlying this association. FUNDING: National Institute on Aging, Saint Louis University.

Green Communication in Internet of Things: A Hybrid Bio-Inspired Intelligent Approach.

Clustering is a promising technique for optimizing energy consumption in sensor-enabled Internet of Things (IoT) networks. Uneven distribution of cluster heads (CHs) across the network, repeatedly choosing the same IoT nodes as CHs and identifying cluster heads in the communication range of other CHs are the major problems leading to higher energy consumption in IoT networks. In this paper, using fuzzy logic, bio-inspired chicken swarm optimization (CSO) and a genetic algorithm, an optimal cluster formation is presented as a Hybrid Intelligent Optimization Algorithm (HIOA) to minimize overall energy consumption in an IoT network. In HIOA, the key idea for formation of IoT nodes as clusters depends on finding chromosomes having a minimum value fitness function with relevant network parameters. The fitness function includes minimization of inter- and intra-cluster distance to reduce the interface and minimum energy consumption over communication per round. The hierarchical order classification of CSO utilizes the crossover and mutation operation of the genetic approach to increase the population diversity that ultimately solves the uneven distribution of CHs and turnout to be balanced network load. The proposed HIOA algorithm is simulated over MATLAB2019A and its performance over CSO parameters is analyzed, and it is found that the best fitness value of the proposed algorithm HIOA is obtained though setting up the parameters popsize=60, number of rooster Nr=0.3, number of hen's Nh=0.6 and swarm updating frequency θ=10. Further, comparative results proved that HIOA is more effective than traditional bio-inspired algorithms in terms of node death percentage, average residual energy and network lifetime by 12%, 19% and 23%.

Investigating the combination of plasma amyloid-beta and geroscience biomarkers on the incidence of clinically meaningful cognitive decline in older adults.

We investigated combining a core AD neuropathology measure (plasma amyloid-beta [Aß] 42/40) with five plasma markers of inflammation, cellular stress, and neurodegeneration to predict cognitive decline. Among 401 participants free of dementia (median [IQR] age, 76 [73-80] years) from the Multidomain Alzheimer Preventive Trial (MAPT), 28 (7.0%) participants developed dementia, and 137 (34.2%) had worsening of clinical dementia rating (CDR) scale over 4 years. In the models utilizing plasma Aß alone, a tenfold increased risk of incident dementia (nonsignificant) and a fivefold increased risk of worsening CDR were observed as each nature log unit increased in plasma Aß levels. Models incorporating Aß plus multiple plasma biomarkers performed similarly to models included Aß alone in predicting dementia and CDR progression. However, improving Aß model performance for composite cognitive score (CCS) decline, a proxy of dementia, was observed after including plasma monocyte chemoattractant protein 1 (MCP1) and growth differentiation factor 15 (GDF15) as covariates. Participants with abnormal Aß, GDF15, and MCP1 presented higher CCS decline (worsening cognitive function) compared to their normal-biomarker counterparts (adjusted ß [95% CI], - 0.21 [- 0.35 to - 0.06], p = 0.005). In conclusion, our study found limited added values of multi-biomarkers beyond the basic Aß models for predicting clinically meaningful cognitive decline among non-demented older adults. However, a combined assessment of inflammatory and cellular stress status with Aß pathology through measuring plasma biomarkers may improve the evaluation of cognitive performance.

Service-Centric Heterogeneous Vehicular Network Modeling for Connected Traffic Environments.

Heterogeneous vehicular communication on the Internet of connected vehicle (IoV) environment is an emerging research theme toward achieving smart transportation. It is an evolution of the existing vehicular ad hoc network architecture due to the increasingly heterogeneous nature of the various existing networks in road traffic environments that need to be integrated. The existing literature on vehicular communication is lacking in the area of network optimization for heterogeneous network environments. In this context, this paper proposes a heterogeneous network model for IoV and service-oriented network optimization. The network model focuses on three key networking entities: vehicular cloud, heterogeneous communication, and smart use cases as clients. Most traffic-related data-oriented computations are performed at cloud servers for making intelligent decisions. The connection component enables handoff-centric network communication in heterogeneous vehicular environments. The use-case-oriented smart traffic services are implemented as clients for the network model. The model is tested for various service-oriented metrics in heterogeneous vehicular communication environments with the aim of affirming several service benefits. Future challenges and issues in heterogeneous IoV environments are also highlighted.

Interactions Between Weight Loss and Plasma Neurodegenerative Markers for Determining Cognitive Decline Among Community-Dwelling Older Adults.

This study aimed to investigate the interaction between weight loss (WL) and plasma amyloid-ß 42/40 (Aß 42/40), neurofilament light chain (NfL), progranulin, and their association with cognitive decline over time among older adults. This 5-year observational approach included 470 participants from the Multidomain Alzheimer Preventive Trial, mean age 76.8 years (SD = 4.5), 59.4% women. WL was defined as ≥5% decrease over the first year. Biomarkers were measured at 12 months. Cognitive function was assessed yearly from 12 months onward by Mini-Mental State Examination (MMSE); Clinical Dementia Rating sum of boxes (CDR-SB); a composite score based on Category Naming Test; Digit Symbol Substitution Test; 10 MMSE orientation items (MMSEO) and free and total recall of the Free and Cued Selective Reminding test; and these tests individually. Twenty-seven participants (5.7%) presented WL. In adjusted analyses, combined WL + lower Aß 42/40 (≤0.103, lowest quartile) was related with more pronounced 4-year cognitive decline according to CDR-SB (p < .0001) and MMSEO (p = .021), compared with non-WL + higher Aß 42/40. WL + higher NfL (>94.55 pg/mL, highest quartile) or progranulin (>38.4 ng/mL, 3 higher quartiles) were related with higher cognitive decline according to CDR-SB, MMSE, MMSEO, and composite score (all p < .03), compared with non-WL + lower NfL or higher progranulin. Regrouping progranulin quartiles (Q1-Q3 vs Q4) revealed higher cognitive decline among the WL + lower progranulin group compared with non-WL + lower progranulin. In conclusion, 1-year WL was associated with subsequent higher 4-year cognitive decline among older adults presenting low Aß 42/40 or high NfL. Future studies combining plasma biomarker assessments and body weight surveillance may be useful for identifying people at risk of cognitive impairment. Clinical trial number: NCT00672685.

Physical Activity, Body Mass Index, and Blood Progranulin in Older Adults: Cross-Sectional Associations in the MAPT Study.

Physical activity (PA) has been shown to moderate the negative effects of obesity on pro-inflammatory cytokines but its relationship with the adipokine progranulin (PGRN) remains poorly investigated. This study aimed to examine the cross-sectional main and interactive associations of body mass index (BMI) and PA level with circulating PGRN in older adults. Five-hundred and twelve participants aged 70 years and older involved in the Multidomain Alzheimer Preventive Trial (MAPT) study who underwent plasma PGRN measurements (ng/mL) were included. Self-reported PA levels were assessed using questionnaires. People were classified into 3 BMI categories: normal weight, overweight, or obesity. Further categorization using PA tertiles was used to define highly active, moderately active, and low active individuals. Multiple linear regressions were performed in order to test the associations of BMI, PA level, and their interaction with PGRN levels. Multiple linear regressions adjusted by age, sex, diabetes mellitus status, total cholesterol, creatinine level, and MAPT group demonstrated significant interactive associations of BMI status and continuous PA such that in people without obesity, higher PA levels were associated with lower PGRN concentrations, while an opposite pattern was found in individuals with obesity. In addition, continuous BMI was positively associated with circulating PGRN in highly active individuals but not in their less active peers. This cross-sectional study demonstrated reverse patterns in older adults with obesity compared to those without obesity regarding the relationships between PA and PGRN levels. Longitudinal and experimental investigations are required to understand the mechanisms that underlie the present findings. Clinical Trials Registration Number: NCT00672685.

Associations of plasma neurofilament light chain and progranulin with frailty in older adults.

BACKGROUND: In previous studies, plasma neurofilament light chain (NfL) and progranulin (PGRN) levels are associated with cognitive and physical impairment in older individuals. However, evidence of their relationships with frailty is lacking. This study aims to explore the associations of plasma NfL and PGRN levels with frailty in community-dwelling older adults. METHODS: We included 507 older adults (mean [standard deviation] age, 76.7 [4.5] years) with plasma NfL and PGRN measurements from the Multidomain Alzheimer Preventive Trial (MAPT). The timepoint of biomarker measurements, either 12 or 24 months after study enrollment, was defined as the baseline for each participant. Frailty phenotype (robust, pre-frail, and frail) was assessed at 12, 24, 36, 48, and 60 months by Fried's frailty criteria. The cross-sectional associations between plasma neurodegenerative biomarkers and frailty severity were examined using logistic regressions. We further used Cox proportional hazard models to evaluate the associations between plasma biomarkers and incident frailty among robust or pre-frail participants at baseline (n = 403). RESULTS: At baseline, participants with high plasma NfL levels (>93.11 pg/ml [the upper quartile]) had a higher likelihood of pre-frailty or frailty compared to their normal NfL counterparts (odds ratio = 1.68; 95% confidence interval = 1.10-2.57); however, this association did not remain significant after controlling for covariates. Neither NfL nor PGRN levels showed prospective associations with incident frailty over 4 years. CONCLUSIONS: This study failed to find associations of circulating NfL and PGRN levels with frailty among community-dwelling older adults in adjusted analyses. Whether plasma neurodegenerative markers serve as potential biomarkers of frailty requires further investigation.

Grouping and Sponsoring Centric Green Coverage Model for Internet of Things.

Recently, green computing has received significant attention for Internet of Things (IoT) environments due to the growing computing demands under tiny sensor enabled smart services. The related literature on green computing majorly focuses on a cover set approach that works efficiently for target coverage, but it is not applicable in case of area coverage. In this paper, we present a new variant of a cover set approach called a grouping and sponsoring aware IoT framework (GS-IoT) that is suitable for area coverage. We achieve non-overlapping coverage for an entire sensing region employing sectorial sensing. Non-overlapping coverage not only guarantees a sufficiently good coverage in case of large number of sensors deployed randomly, but also maximizes the life span of the whole network with appropriate scheduling of sensors. A deployment model for distribution of sensors is developed to ensure a minimum threshold density of sensors in the sensing region. In particular, a fast converging grouping (FCG) algorithm is developed to group sensors in order to ensure minimal overlapping. A sponsoring aware sectorial coverage (SSC) algorithm is developed to set off redundant sensors and to balance the overall network energy consumption. GS-IoT framework effectively combines both the algorithms for smart services. The simulation experimental results attest to the benefit of the proposed framework as compared to the state-of-the-art techniques in terms of various metrics for smart IoT environments including rate of overlapping, response time, coverage, active sensors, and life span of the overall network.

Myeloperoxidase-induced modification of HDL by isolevuglandins inhibits paraoxonase-1 activity.

Reduced activity of paraoxonase 1 (PON1), a high-density lipoprotein (HDL)-associated enzyme, has been implicated in the development of atherosclerosis. Post-translational modifications of PON1 may represent important mechanisms leading to reduced PON1 activity. Under atherosclerotic conditions, myeloperoxidase (MPO) is known to associate with HDL. MPO generates the oxidants hypochlorous acid and nitrogen dioxide, which can lead to post-translational modification of PON1, including tyrosine modifications that inhibit PON1 activity. Nitrogen dioxide also drives lipid peroxidation, leading to the formation of reactive lipid dicarbonyls such as malondialdehyde and isolevuglandins, which modify HDL and could inhibit PON1 activity. Because isolevuglandins are more reactive than malondialdehyde, we used in vitro models containing HDL, PON1, and MPO to test the hypothesis that IsoLG formation by MPO and its subsequent modification of HDL contributes to MPO-mediated reductions in PON1 activity. Incubation of MPO with HDL led to modification of HDL proteins, including PON1, by IsoLG. Incubation of HDL with IsoLG reduced PON1 lactonase and antiperoxidation activities. IsoLG modification of recombinant PON1 markedly inhibited its activity, while irreversible IsoLG modification of HDL before adding recombinant PON1 only slightly inhibited the ability of HDL to enhance the catalytic activity of recombinant PON1. Together, these studies support the notion that association of MPO with HDL leads to lower PON1 activity in part via IsoLG-mediated modification of PON1, so that IsoLG modification of PON1 could contribute to increased risk for atherosclerosis, and blocking this modification might prove beneficial to reduce atherosclerosis.

Plasma neurofilament light chain is associated with cognitive decline in non-dementia older adults.

Neurofilament light chain (NfL) has been associated with cognitive status in multiple neurodegenerative conditions. Studies about plasma NfL and cognitive decline in older adults are still limited. 504 older adults (median age 75 years) who expressed memory complaints were selected from the Multidomain Alzheimer's Preventive Trial (MAPT) and were classified as normal cognition (NC) or mild cognitive impairment (MCI). Cognitive functions were measured as mini mental state examination (MMSE) and composite cognitive score (CCS) over a 4-year period. Plasma NfL was measured at the first or the second year of the MAPT. Mixed-effects linear models were performed to evaluate cross-sectional and longitudinal associations. In the whole population, higher plasma NfL was cross-sectionally associated with lower cognitive functions (MMSE: ß = - 0.007, 95% CI [- 0.013, - 0.001]; CCS: ß = - 0.003, 95% CI [- 0.006, - 0.001]). In adults with MCI, but not NC, higher plasma NfL was associated with lower CCS at the cross-sectional level (ß = - 0.003, 95% CI [- 0.005, - 0.0002]). The upper quartile NfL group further demonstrated more over time decline in CCS (ß = - 0.07, 95% CI [- 0.12, - 0.01]) under the MCI status. Plasma NfL can be a promising biomarker of progressive cognition decline in older adults with MCI.