Cultivating Cooperatives: Benefits And Challenges Of Co-Ops And Recommendations For Maine’s Emerging Aquaculture Industries

Two emerging Maine industries, kelp (Saccharina latissimi and Saccharina angustissima) and Atlantic sea scallop (Placopecten magellanicus) aquaculture, have enormous market, environmental, and social potential but are faced with challenges of small scale and limited operations, inadequate infrastructure, market visibility, and limited expertise. Because many industries, particularly the dairy industry, have benefited from the use of cooperatives (co-ops) to aggregate an extremely perishable product, quickly process and effectively market and distribute, this research explores the cooperative model as a potential tool for the nascent scallop and kelp industries. Aquaculture co-ops are new in Maine. The first, the Maine Aquaculture Co-op (MAC), formed in 2016 to help develop the sea scallop aquaculture industry. As more farmers come online to sell and demand grows, the co-op needs to determine its next direction. Furthermore, the lack of kelp processors in Maine is hampering that industries’ growth. To make recommendations to MAC, a theoretical kelp co-op, and aquaculture co-ops in general, this research determined the benefits and challenges of co-ops, and the important factors that influence co-op structures. Ten aquaculture, agriculture and fishery co-ops were researched through data mining, participant observation, and semi-structured interviews. The factors to consider for defining the structure of a co-op are whether: 1) the co-op will act as a distributor, 2) product will be marketed using individual member branding or co-op branding, 3) if members are required to sell through the coop or will sell individually, and 4) members’ geographic proximity to one another. The ten benefits of the co-op model are 1) shared labor and personnel, 2) group purchasing, 3) shared infrastructure, 4) community relations, 5) banking, 6) industry entry and growth, 7) market stability, 8) grants, 9) knowledge sharing, and 10) democratic membership. The challenges to co-ops are 1) member cooperation, 2) financial returns, 3) and disputes over branding. Short-term recommendations for MAC are based off findings from two small, established aquaculture co-ops that have a co-op distribution facility and mostly independently producing farmers who occasionally cooperatively farm and share farm equipment. Product is branded by member farms, but all transactions pass through the co-op. Recommendations for a kelp co-op are based off large scale marketing co-ops where raw materials are aggregated from farms, processed into value added products, and marketed and distributed

White matter hyperintensities in sporadic and familial Alzheimer's disease: investigations into their pathological basis and biomarker potential

This thesis is a detailed investigation into white matter hyperintensities (WMHs) in Alzheimer’s disease (AD). WMHs, of presumed vascular origin, are increasingly recognised in the aetiology of AD. However their underlying pathology may be variable and their relationship to the hallmark pathological features of AD is not yet fully understood. Associations of WMHs with CSF amyloid beta (Aβ ) and tau at baseline were explored in a cohort from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). A further study in ADNI was carried out exploring associations between plasma neurofilament light (NFL) and WMHs. WMH accrual across the disease course was modelled using longitudinal data from the Dominantly Inherited Alzheimer Network (DIAN) cohort. Finally, to enable exploration of the pathological basis of WMHs, an ex vivo MRI pipeline with subsequent pathological investigations was developed and carried out. Firstly, a higher WMH burden was found to associate with lower CSF Aβ across diagnostic groups, but no significant associations were found with CSF tau biomarkers. Plasma NFL was found to associate with WMHs, in an age depen- dent, but vascular-risk independent manner. Secondly, WMH accrual was found to increase throughout the disease course as demonstrated by associations with esti- mated years to onset (EYO) in the DIAN cohort. The highest rate of accrual was seen in the APP mutation group. Additionally, WMHs and brain atrophy changes were shown to track together across the disease course. Lastly, the ex vivo-histology pipeline was shown to be effective, enabling the registration of multiple modalities and revealing varying degrees of myelin loss. Abstract 4 In summary, this work extends existing knowledge about how WMHs associate with classical AD markers such as Aβ, tau and brain atrophy. Furthermore this work suggests that, instead of just reflecting vascular comorbidity, WMHs are a core feature of AD. Impact Statement Alzheimer’s disease (AD) is a neurodegenerative disease with no effective treatment or cure. Not only does AD have debilitating consequences for patients and carers, it places a huge socio-economic burden on society as a whole. Evidence suggests that AD is a multifactorial disease for which early intervention is necessary for effective treatment. It is therefore imperative that biomarkers identifying early-stage disease, as well as capturing the full spectrum of pathological changes, are identified and characterised. This thesis investigates white matter hyperintensities (WMHs) as a potential biomarker of AD. A key finding in this PhD is that WMHs associate with amyloid beta (Aβ) across the full disease course. This result aids understanding of how WMHs interact with other AD biomarkers and creates opportunities for further research into the mechanism underlying this finding. The fact that my paper on this work has been cited five times since its publication last year in 2020, shows that there is is active demand for this research. In Chapter 5 I provided evidence that WMHs are an important marker of dis- ease progression in a cohort of autosomal dominant inherited AD (ADAD) patients and their relatives. As well as being an important finding in terms of the use of WMHs as a biomarker, very little research into WMHs in ADAD has been carried out previously, meaning that this work will be important to the AD field. I also found differences in WMH accrual between mutation groups, which has important implications for future treatments in ADAD as it highlights the heterogeneous na- ture of the disease. In Chapter 6 I developed a novel MRI-histology pipeline in order to answer key Impact Statement 6 and under-researched questions about the underlying pathology of an MRI signal. The impact of the development of this methodology could be substantial, providing the starting point for a tool that could predict the underlying pathology of WMHs based on appearance and location, for eventual use in a clinical setting. WMHs have long been considered a marker of SVD, however I have shown how WMH are increased in AD and associated with key AD biomarkers, both in a cohort of low vascular risk (ADNI) and in a young ADAD cohort (DIAN). This thesis provides important evidence that WMH on their own should not automatically be taken as evidence of a vascular contribution

Predicting Cognitive Decline in Nondemented Elders Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

BACKGROUND AND OBJECTIVES: Dementia is a growing socio-economic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds (CMB), whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI), and those with MCI who later converted to an Alzheimer's disease (AD) diagnosis (MCItoAD). METHODS: Standardised baseline biomarker data from ADNI2/Go, and longitudinal diagnostic data (including ADNI3), were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up timepoints available. Models were fit for biomarkers univariately, and together in a multivariable model. Hazard Ratios (HR) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups. RESULTS: For CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = .002; fully-adjusted model: HR 1.98, p = .003), and lower hippocampal volume (individual: HR 0.54, p = .001; fully-adjusted: HR 0.40, p < .001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < .001; fully-adjusted model: HR 0.55, p < .001) and whole-brain volume (individual: HR 0.31, p < .001; fully-adjusted: HR 0.48, p = .02), increased CSF ptau (individual: HR 1.88, p < .001; fully-adjusted: HR 1.61, p < .001), and lower CSF amyloid (individual: HR 0.37, p < .001, fully-adjusted: HR 0.62, p = .008) were most strongly associated with conversion to AD individually and independently. DISCUSSION: Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, while WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathological pathway, such as vascular cognitive impairment

Automated White Matter Hyperintensity Segmentation Using Bayesian Model Selection: Assessment and Correlations with Cognitive Change.

Accurate, automated white matter hyperintensity (WMH) segmentations are needed for large-scale studies to understand contributions of WMH to neurological diseases. We evaluated Bayesian Model Selection (BaMoS), a hierarchical fully-unsupervised model selection framework for WMH segmentation. We compared BaMoS segmentations to semi-automated segmentations, and assessed whether they predicted longitudinal cognitive change in control, early Mild Cognitive Impairment (EMCI), late Mild Cognitive Impairment (LMCI), subjective/significant memory concern (SMC) and Alzheimer's (AD) participants. Data were downloaded from the Alzheimer's disease Neuroimaging Initiative (ADNI). Magnetic resonance images from 30 control and 30 AD participants were selected to incorporate multiple scanners, and were semi-automatically segmented by 4 raters and BaMoS. Segmentations were assessed using volume correlation, Dice score, and other spatial metrics. Linear mixed-effect models were fitted to 180 control, 107 SMC, 320 EMCI, 171 LMCI and 151 AD participants separately in each group, with the outcomes being cognitive change (e.g. mini-mental state examination; MMSE), and BaMoS WMH, age, sex, race and education used as predictors. There was a high level of agreement between BaMoS' WMH segmentation volumes and a consensus of rater segmentations, with a median Dice score of 0.74 and correlation coefficient of 0.96. BaMoS WMH predicted cognitive change in: control, EMCI, and SMC groups using MMSE; LMCI using clinical dementia rating scale; and EMCI using Alzheimer's disease assessment scale-cognitive subscale (p < 0.05, all tests). BaMoS compares well to semi-automated segmentation, is robust to different WMH loads and scanners, and can generate volumes which predict decline. BaMoS can be applicable to further large-scale studies

CSF amyloid is a consistent predictor of white matter hyperintensities across the disease course from aging to Alzheimer's disease.

This study investigated the relationship between white matter hyperintensities (WMH) and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers. Subjects included 180 controls, 107 individuals with a significant memory concern, 320 individuals with early mild cognitive impairment, 171 individuals with late mild cognitive impairment, and 151 individuals with AD, with 3T MRI and CSF Aβ1-42, total tau (t-tau), and phosphorylated tau (p-tau) data. Multiple linear regression models assessed the relationship between WMH and CSF Aβ1-42, t-tau, and p-tau. Directionally, a higher WMH burden was associated with lower CSF Aβ1-42 within each diagnostic group, with no evidence for a difference in the slope of the association across diagnostic groups (p = 0.4). Pooling all participants, this association was statistically significant after adjustment for t-tau, p-tau, age, diagnostic group, and APOE-ε4 status (p < 0.001). Age was the strongest predictor of WMH (partial R2~16%) compared with CSF Aβ1-42 (partial R2~5%). There was no evidence for an association with WMH and either t-tau or p-tau. These data are supportive of a link between amyloid burden and presumed vascular pathology

The potential of fosfomycin for multi-drug resistant sepsis: an analysis of in vitro activity against invasive paediatric Gram-negative bacteria.

PURPOSE: Antimicrobial resistance (AMR) is of increasing global concern, threatening to undermine recent progress in reducing child and neonatal mortality. Repurposing older antimicrobials is a prominent strategy to combat multidrug-resistant sepsis. A potential agent is fosfomycin, however, there is scarce data regarding its in vitro activity and pharmacokinetics in the paediatric population. METHODOLOGY: We analysed a contemporary, systematically collected archive of community-acquired (CA) and hospital-acquired (HA) paediatric Gram-negative bacteraemia isolates for their susceptibility to fosfomcyin. MICs were determined using agar serial dilution methods and validated by disk diffusion testing where breakpoints are available. Disk diffusion antimicrobial susceptibility testing was also conducted for current empirical therapies (ampicillin, gentamicin, ceftriaxone) and amikacin (proposed in the literature as a new combination empirical therapeutic option). RESULTS: Fosfomycin was highly active against invasive Gram-negative isolates, including 90  % (202/224) of Enterobacteriaceae and 96  % (22/23) of Pseudomonas spp. Fosfomycin showed high sensitivity against both CA isolates (94 %, 142/151) and HA isolates (81 %, 78/96; P =0.0015). CA isolates were significantly more likely to be susceptible to fosfomycin than the current first-line empirical therapy (96  % vs 59  %, P <0.0001). Extended spectrum β-lactamases (ESBL) production was detected in 34  % (85/247) of isolates with no significant difference in fosfomycin susceptibility between ESBL-positive or -negative isolates [73/85 (86  %) vs 147/162 (91  %) respectively, P =0.245]. All isolates were susceptible to a fosfomycin-amikacin combination. CONCLUSION: Gram-negative paediatric bacteraemia isolates are highly susceptible to fosfomycin, which could be combined with aminoglycosides as a new, carbapenem-sparing regimen to achieve excellent coverage to treat antimicrobial-resistant neonatal and paediatric sepsis

Predicting Cognitive Decline in Older Adults Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

Background and ObjectivesDementia is a growing socioeconomic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here, we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds, whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI) and those with MCI who later converted to an Alzheimer disease (AD) diagnosis (MCItoAD).MethodsStandardized baseline biomarker data from AD Neuroimaging Initiative 2 (ADNI2)/GO and longitudinal diagnostic data (including ADNI3) were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up time points available. Models were fit for biomarkers univariately and together in a multivariable model. Hazard ratios (HRs) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups.ResultsFor CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = 0.002; fully adjusted model: HR 1.98, p = 0.003) and lower hippocampal volume (individual: HR 0.54, p = 0.001; fully adjusted: HR 0.40, p < 0.001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < 0.001; fully adjusted model: HR 0.55, p < 0.001) and whole-brain volume (individual: HR 0.31, p < 0.001; fully adjusted: HR 0.48, p = 0.02), increased CSF ptau (individual: HR 1.88, p < 0.001; fully adjusted: HR 1.61, p < 0.001), and lower CSF amyloid (individual: HR 0.37, p < 0.001; fully adjusted: HR 0.62, p = 0.008) were most strongly associated with conversion to AD individually and independently.DiscussionLower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, whereas WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathologic pathway, such as vascular cognitive impairment

Predicting Cognitive Decline in Older Adults Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

BACKGROUND AND OBJECTIVES: Dementia is a growing socioeconomic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here, we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds, whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI) and those with MCI who later converted to an Alzheimer disease (AD) diagnosis (MCItoAD). METHODS: Standardized baseline biomarker data from AD Neuroimaging Initiative 2 (ADNI2)/GO and longitudinal diagnostic data (including ADNI3) were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up time points available. Models were fit for biomarkers univariately and together in a multivariable model. Hazard ratios (HRs) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups. RESULTS: For CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = 0.002; fully adjusted model: HR 1.98, p = 0.003) and lower hippocampal volume (individual: HR 0.54, p = 0.001; fully adjusted: HR 0.40, p < 0.001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < 0.001; fully adjusted model: HR 0.55, p < 0.001) and whole-brain volume (individual: HR 0.31, p < 0.001; fully adjusted: HR 0.48, p = 0.02), increased CSF ptau (individual: HR 1.88, p < 0.001; fully adjusted: HR 1.61, p < 0.001), and lower CSF amyloid (individual: HR 0.37, p < 0.001; fully adjusted: HR 0.62, p = 0.008) were most strongly associated with conversion to AD individually and independently. DISCUSSION: Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, whereas WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathologic pathway, such as vascular cognitive impairment

Insight into the Mechanisms of Adenovirus Capsid Disassembly from Studies of Defensin Neutralization

Defensins are effectors of the innate immune response with potent antibacterial activity. Their role in antiviral immunity, particularly for non-enveloped viruses, is poorly understood. We recently found that human alpha-defensins inhibit human adenovirus (HAdV) by preventing virus uncoating and release of the endosomalytic protein VI during cell entry. Consequently, AdV remains trapped in the endosomal/lysosomal pathway rather than trafficking to the nucleus. To gain insight into the mechanism of defensin-mediated neutralization, we analyzed the specificity of the AdV-defensin interaction. Sensitivity to alpha-defensin neutralization is a common feature of HAdV species A, B1, B2, C, and E, whereas species D and F are resistant. Thousands of defensin molecules bind with low micromolar affinity to a sensitive serotype, but only a low level of binding is observed to resistant serotypes. Neutralization is dependent upon a correctly folded defensin molecule, suggesting that specific molecular interactions occur with the virion. CryoEM structural studies and protein sequence analysis led to a hypothesis that neutralization determinants are located in a region spanning the fiber and penton base proteins. This model was supported by infectivity studies using virus chimeras comprised of capsid proteins from sensitive and resistant serotypes. These findings suggest a mechanism in which defensin binding to critical sites on the AdV capsid prevents vertex removal and thereby blocks subsequent steps in uncoating that are required for release of protein VI and endosomalysis during infection. In addition to informing the mechanism of defensin-mediated neutralization of a non-enveloped virus, these studies provide insight into the mechanism of AdV uncoating and suggest new strategies to disrupt this process and inhibit infection

Presumed small vessel disease, imaging and cognition markers in the Alzheimer's Disease Neuroimaging Initiative.

MRI-derived features of presumed cerebral small vessel disease are frequently found in Alzheimer's disease. Influences of such markers on disease-progression measures are poorly understood. We measured markers of presumed small vessel disease (white matter hyperintensity volumes; cerebral microbleeds) on baseline images of newly enrolled individuals in the Alzheimer's Disease Neuroimaging Initiative cohort (GO and 2) and used linear mixed models to relate these to subsequent atrophy and neuropsychological score change. We also assessed heterogeneity in white matter hyperintensity positioning within biomarker abnormality sequences, driven by the data, using the Subtype and Stage Inference algorithm. This study recruited both sexes and included: controls: [n = 159, mean(SD) age = 74(6) years]; early and late mild cognitive impairment [ns = 265 and 139, respectively, mean(SD) ages =71(7) and 72(8) years, respectively]; Alzheimer's disease [n = 103, mean(SD) age = 75(8)] and significant memory concern [n = 72, mean(SD) age = 72(6) years]. Baseline demographic and vascular risk-factor data, and longitudinal cognitive scores (Mini-Mental State Examination; logical memory; and Trails A and B) were collected. Whole-brain and hippocampal volume change metrics were calculated. White matter hyperintensity volumes were associated with greater whole-brain and hippocampal volume changes independently of cerebral microbleeds (a doubling of baseline white matter hyperintensity was associated with an increase in atrophy rate of 0.3 ml/year for brain and 0.013 ml/year for hippocampus). Cerebral microbleeds were found in 15% of individuals and the presence of a microbleed, as opposed to none, was associated with increases in atrophy rate of 1.4 ml/year for whole brain and 0.021 ml/year for hippocampus. White matter hyperintensities were predictive of greater decline in all neuropsychological scores, while cerebral microbleeds were predictive of decline in logical memory (immediate recall) and Mini-Mental State Examination scores. We identified distinct groups with specific sequences of biomarker abnormality using continuous baseline measures and brain volume change. Four clusters were found; Group 1 showed early Alzheimer's pathology; Group 2 showed early neurodegeneration; Group 3 had early mixed Alzheimer's and cerebrovascular pathology; Group 4 had early neuropsychological score abnormalities. White matter hyperintensity volumes becoming abnormal was a late event for Groups 1 and 4 and an early event for 2 and 3. In summary, white matter hyperintensities and microbleeds were independently associated with progressive neurodegeneration (brain atrophy rates) and cognitive decline (change in neuropsychological scores). Mechanisms involving white matter hyperintensities and progression and microbleeds and progression may be partially separate. Distinct sequences of biomarker progression were found. White matter hyperintensity development was an early event in two sequences