The Nutshell crime scene image above is by photographer Corinne May Botz, who has published a book that extensively documents Frances Lee's work. Here's a link to that book, and some other good articles about the Nutshell Studies:
!!LINK!! Lee Bmodels
NOTE: Some of the obscure models links take you to Randy Browning's website at sailboatdata.com website. John Alden 32 Motorsailor Alden 42 Offshore 44 Offshore 50 Offshore 53 Pieter Beeldsnijder Motorsailor/Trawler 52 Britton Chance Golden Wave 48 Laurent Giles Vertue (Old & New Style) Wanderer Motorsailor 32 L Francis Hereshoff Rozinante Canoe Yawl Ron Carter Cape Cod Cat Cheoy Lee (no designer) Bermuda 30 C.L. 41 Monterey Clipper Motorsailor 44 Offshore 26 Offshore 31 Offshore 33 Ketch Offshore 41 Cruisaire 30 Clipper Cruisaie 36 C.L. 28 C.L. 32 C. L. 35 Cutter/Ketch Far East 29 Mini Clipper 24 SuperKetch Gulf 40 This link is at sailboat data's website Monterey Clipper Maurice DeClerck Flying Buffalo (DeClercq) Offshore 36 - Production model of the Flying Buffalo Bill Lapworth C.L. 50 Sloop
MSA belongs to a diverse group of neurodegenerative disorders described as α-synucleinopathies, which are similar to PD and dementia with Lewy bodies (DLB). These disorders are characterized by the abnormal accumulation of α-synuclein protein aggregates22,23. α-Synuclein is a predominantly neuronal presynaptic protein present in the brain and is expressed in other tissues at various levels. It is encoded by the SNCA gene, which is linked to PD and has also been associated with an increased risk of PD, DLB, and MSA24.
Despite the many criticisms against the amyloid cascade hypothesis, accumulating evidence obtained in in vitro and in vivo models and in patients provides solid experimental support for the hypothesis, and particularly for Aβ-induced Tau-pathology. More importantly these data position Aβ as accelerator/initiator and Tau as executor of the pathogenetic process, designating their interaction as crucial triggering event in AD. In depth analysis of the mechanisms and the relation between different pathological characteristics and their role in the etiology, should allow the design of fine-tuned therapies for AD with increased efficacy. More particularly, the molecular or physical identity of the toxic form(s) of Aβ (denoted Aβ*), and of Tau (denoted Tau*), temporal and spatial localization of their action(s), (cell-autonomous or not, pre- or post-synaptic, intra- or extra-cellular), the respective contribution of amyloid and Tau to the etiology of AD, and the mechanistic link(s) between amyloid and Tau pathology should be investigated for this purpose.
We here present an overview of in vitro and in vivo models available for further analysis of Aβ-induced Tau-pathology, which remains to be mechanistically resolved unequivocally. The existence of the apparent panoply of different models and their diversity is to be considered a particular asset to delineate those mechanisms that are robustly and consistently linked with Aβ-induced Tau-alterations.
Although mechanisms linking amyloid and Tau-pathology have not been conclusively and exhaustively identified, available data support several potential mechanisms that can contribute exclusively or concomitantly. We here use a reductionist approach and limit the discussion to mechanisms which are corroborated or are consistent with experimental data in our models [52, 55] (Figure 3), thereby not excluding contributions of mechanisms not presented here. Theoretically, Aβ peptides may interact directly or indirectly with neurons to induce Tau-alterations. First, direct interactions with neurons that have been reported include specific binding to several neuronal receptors (cfr 4.1) or, because of the sticky nature of amyloid peptides, less specific interaction with membranes and proteins. Secondly, indirect mechanisms may contribute to amyloid induced Tau-pathology, including amyloid induced inflammation via glial cells (cfr 4.2). Finally, in view of the recently observed cross-seeding between misfolded protein species, we need to consider that amyloid peptides may act as direct seeds for Tau-aggregation (cfr 4.3). This latter option has not yet been experimentally explored in detail, although some data are consistent with the hypothesis that pre-aggregated misfolded Aβ peptides could seed and propagate Tau-misfolding and hence aggregation by cross-seeding.
We here presented accumulating evidence in in vitro models, in vivo models and from biomarkers in patients that supports the amyloid cascade hypothesis, particularly Aβ-induced acceleration of Tau-pathology as a critical trigger in AD. Furthermore, we presented diverse models that recapitulate Aβ-induced Tau-pathology and reviewed some potential contributing mechanisms. This mechanism may be linked to downstream effects of Aβ-induced synaptic defects, or to indirect effects mediated by amyloid induced inflammation. It thereby likely involves interactions of Aβ species with (neuronal) receptors, non-receptor proteins and/or membranes, that need to be identified. Furthermore, cross-seeding of misfolded proteins, in which Aβ cross-seeding of Tau, induces transition from mild Tau-strains to more aggressive Tau-strains and thereby triggers prion-like spreading of Tauopathy along neuronal circuitries, was suggested as a potential mechanism. This was based on the distinct spatio-temporal distribution of amyloid and Tau-pathology, which was also observed in transgenic AD models. A unifying mechanism of amyloid induced Tau-pathology still needs to be identified, which reconciles different previous data-sets, and which can be consistently and unequivocally demonstrated in different models with amyloid induced Tau-pathology. Most importantly, in depth understanding of Aβ-induced Tau-pathology in terms of identification of the exact molecular entity, exact molecular mechanism, and their respective contributions to and interrelation with associated pathological features (synaptic dysfunction, neurodegeneration, brain atrophy, inflammation) is absolutely required to define fine-tuned therapeutic strategies with a higher success in preventing or halting AD.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
In 2007, researchers from the University of Pavia led by Dr Enzo Emanuele provided evidence of a genetic basis for individual variations in Lee's love styles, with Eros being linked to the dopamine system and mania to the serotonin system.[21] In this genetic study of 350 lovers, the Eros style was found to be present more often in those bearing the TaqI A1 allele of the DRD2 3' UTR sequence and the overlapping ANKK1 exon 8. This allele has been proposed to influence a wide range of behaviors, favoring obesity and alcoholism but opposing neuroticism-anxiety and juvenile delinquency.[22] This genetic variation has been hypothesized to cause a reduced amount of pleasure to be obtained from a given action, causing people to indulge more frequently.[23]
Going beyond the qualitative changes to the viral titer time course brought about by Abs, CTLs, and IFN, Fig. 6 offers a quantitative analysis of their relative contribution to decreasing various measures related to the severity of the infection in a patient. For example, we take the peak viral titer to be an approximate measure of the degree of dissemination of the virus within the patient with higher viral loads representing a more disseminated infection. The duration of the symptomatic infection, measured here as the time spent by the viral titer curve over a titer of 0.01 (i.e., above 1% of its peak value, as used in [8], [90]), gives a measure of infection duration and helps distinguish short-lived seasonal infections from more severe or chronic infections. The area under the viral titer curve (AUC) is related to the total amount of virus shedding, and so can be linked to the person-to-person transmission rate of the infection [7], [61], [91]. Finally, the fraction of dead cells at the end of the infection measures the amount of epithelium destruction caused by the infection and can be used to assess the severity of the infection. Together, these measures provide an overview of the infection course which we use to assess how effective various immune responses are in modulating infection severity and patient outcomes. Fig. 6 presents the percent increase in each severity measure that results from the suppression of either Abs, CTLs, or IFN as determined from the experimental data (bottom row) and from the mathematical models (top row). The duration of experimental infections presented in this figure depict a minimum percent increase because the duration of infections cannot be measured exactly (see supplemental material S1), but a minimum value can be estimated. 2ff7e9595c
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