Protection against methylglyoxal-derived AGEs by regulation of glyoxalase 1 prevents retinal neuroglial and vasodegenerative pathology.

Aims/hypothesis
Methylglyoxal (MG) is an important precursor for AGEs. Normally, MG is detoxified by the glyoxalase (GLO) enzyme system (including component enzymes GLO1 and GLO2). Enhanced glycolytic metabolism in many cells during diabetes may overpower detoxification capacity and lead to AGE-related pathology. Using a transgenic rat model that overexpresses GLO1, we investigated if this enzyme can inhibit retinal AGE formation and prevent key lesions of diabetic retinopathy.
Methods
Transgenic rats were developed by overexpression of full length GLO1. Diabetes was induced in wild-type (WT) and GLO1 rats and the animals were killed after 12 or 24 weeks of hyperglycaemia. N e-(Carboxyethyl)lysine (CEL), N e-(carboxymethyl)lysine (CML) and MG-derived-hydroimidazalone-1 (MG-H1) were determined by immunohistochemistry and by ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MSMS). Müller glia dysfunction was determined by glial fibrillary acidic protein (GFAP) immunoreactivity and by spatial localisation of the potassium channel Kir4.1. Acellular capillaries were quantified in retinal flat mounts.
Results
GLO1 overexpression prevented CEL and MG-H1 accumulation in the diabetic retina when compared with WT diabetic counterparts (p?<?0.01). Diabetes-related increases in Müller glial GFAP levels and loss of Kir4.1 at the vascular end-feet were significantly prevented by GLO1 overexpression (p?<?0.05) at both 12- and 24-week time points. GLO1 diabetic animals showed fewer acellular capillaries than WT diabetic animals (p?<?0.001) at 24 weeks’ diabetes.
Conclusions/interpretation
Detoxification of MG reduces AGE adduct accumulation, which, in turn, can prevent formation of key retinal neuroglial and vascular lesions as diabetes progresses. MG-derived AGEs play an important role in diabetic retinopathy.

Raman spectroscopy for the detection of AGEs/ALEs

Raman spectroscopy is a noninvasive, nondestructive tool for capturing multiplexed biochemical information across diverse molecular species including proteins, lipids, DNA, and mineralizations. Based on light scattering from molecules, cells, and tissues, it is possible to detect molecular fingerprints and discriminate between subtly different members of each biochemical class. Raman spectroscopy is ideal for detecting perturbations from the expected molecular structure such as those occurring during senescence and the modification of long-lived proteins by metabolic intermediates as we age. Here, we describe the sample preparation, data acquisition, signal processing, data analysis and interpretation involved in using Raman spectroscopy for detecting age-related protein modifications in complex biological tissues.

Ages of 24 widespread tephras erupted since 30,000 years ago in New Zealand, with re-evaluation of the timing and palaeoclimatic implications of the Lateglacial cool episode recorded at Kaipo bog

Tephras are important for the NZ-INTIMATE project because they link all three records comprising the composite inter-regional stratotype developed for the New Zealand climate event stratigraphy (NZ-CES). Here we firstly report new calendar ages for 24 widespread marker tephras erupted since 30,000 calendar (cal.) years ago in New Zealand to help facilitate their use as chronostratigraphic dating tools for the NZ-CES and for other palaeoenvironmental and geological applications. The selected tephras comprise 12 rhyolitic tephras from Taupo, nine rhyolitic tephras from Okataina, one peralkaline rhyolitic tephra from Tuhua, and one andesitic tephra each from Tongariro and Egmont/Taranaki volcanic centres. Age models for the tephras were obtained using three methods: (i) C-based wiggle-match dating of wood from trees killed by volcanic eruptions (these dates published previously); (ii) flexible depositional modelling of a high-resolution C-dated age-depth sequence at Kaipo bog using two Bayesian-based modelling programs, Bacon and OxCal's P_Sequence function, and the IntCal09 data set (with SH offset correction-44±17yr); and (iii) calibration of C ages using OxCal's Tau_Boundary function and the SHCal04 and IntCal09 data sets. Our preferred dates or calibrated ages for the 24 tephras are as follows (youngest to oldest, all mid-point or mean ages of 95% probability ranges): Kaharoa AD 1314±12; Taupo (Unit Y) AD 232±10; Mapara (Unit X) 2059±118cal.yrBP; Whakaipo (Unit V) 2800±60cal.yrBP; Waimihia (Unit S) 3401±108cal.yrBP; Stent (Unit Q) 4322±112cal.yrBP; Unit K 5111±210cal.yrBP; Whakatane 5526±145cal.yrBP; Tuhua 6577±547cal.yrBP; Mamaku 7940±257cal.yrBP; Rotoma 9423±120cal.yrBP; Opepe (Unit E) 9991±160cal.yrBP; Poronui (Unit C) 11,170±115cal.yrBP; Karapiti (Unit B) 11,460±172cal.yrBP; Okupata 11,767±192cal.yrBP; Konini (bed b) 11,880±183cal.yrBP; Waiohau 14,009±155cal.yrBP; Rotorua 15,635±412cal.yrBP; Rerewhakaaitu 17,496±462cal.yrBP; Okareka 21,858±290cal.yrBP; Te Rere 25,171±964cal.yrBP; Kawakawa/Oruanui 25,358±162cal.yrBP; Poihipi 28,446±670cal.yrBP; and Okaia 28,621±1428cal.yrBP.Secondly, we have re-dated the start and end of the Lateglacial cool episode (climate event NZce-3 in theNZ-CES), previously referred to as the Lateglacial climate reversal, as defined at Kaipo bog in eastern North Island, New Zealand, using both Bacon and OxCal P_Sequence modelling with the IntCal09 data set. The ca1200-yr-long cool episode, indicated by a lithostratigraphic change in the Kaipo peat sequence to grey mudwith lowered carbon content, and a high-resolution pollen-derived cooling signal, began 13,739±125cal.yrBP and ended 12,550±140cal.yrBP (mid-point ages of the 95% highest posterior density regions, Bacon modelling). The OxCal modelling, generating almost identical ages, confirmed these ages. The Lateglacial cool episode (ca 13.8-12.6cal.kaBP) thus overlaps a large part of the entire Antarctic Cold Reversal chronozone (ca 14.1-12.4cal.kaBP or ca 14.6-12.8cal.kaBP), and an early part of the Greenland Stadial-1 (Younger Dryas) chronozone (ca 12.9-11.7cal.kaBP). The timing of the Lateglacial cool episode at Kaipo is broadly consistent with the latitudinal patterns in the Antarctic Cold Reversal signal suggested for the New Zealand archipelago from marine and terrestrial records, and with records from southern South America. © 2012 Elsevier Ltd.

Predicting the ecological impacts of a new freshwater invader:Functional responses and prey selectivity of the 'killer shrimp', Dikerogammarus villosus, compared to the native Gammarus pulex

The ability to predict the likely ecological impacts of invasive species in fresh waters is a pressing research requirement. Whilst comparisons of species traits and considerations of invasion history have some efficacy in this respect, we require robust methods that can compare the effects of native and invasive species. Here, we utilise comparative functional responses and prey selectivity experiments to understand and predict the ecological impact of an invader as compared to a native. We compared the predatory functional responses of an emerging invasive species in Europe, the 'killer shrimp', Dikerogammarus villosus, and an analogous native species, Gammarus pulex, towards three representative prey species: Asellus aquaticus, Daphnia magna and Chironomus sp. Furthermore, as ecological impact may be greater for invasive species with more indiscriminate feeding habits, we compared the selectivity for the three prey types between the invasive and native species. In both the presence and absence of experimental habitats, large D. villosus, and those matched for body size with G. pulex, generally showed higher (Type II) functional responses than G. pulex, with the invasive species exhibiting higher maximum feeding rates. Further, D. villosus exhibited significantly more indiscriminate prey selection compared with G. pulex, a trait that became more evident as the invader increased in size. Differences in functional responses and prey selectivity were prey species specific, with higher to lower predicted impacts in the order A. aquaticus, D. magna and Chironomus sp. This is in accord with the impact of this invasive species on macroinvertebrates in the field. We thus provide understanding of the known ecological impact of D. villosus and discuss the utility of the phenomenological use of comparative functional responses and resource use as a tool through which the potential ecological impacts of invasive species may be identified. © 2013 John Wiley & Sons Ltd.

North Atlantic marine radiocarbon reservoir ages through Heinrich event H4: A new method for marine age model construction

Cooling and sinking of dense saline water in the Norwegian–Greenland Sea is essential for the formation of North Atlantic Deep Water. The convection in the Norwegian–Greenland Sea allows for a northward flow of warm surface water and southward transport of cold saline water. This circulation system is highly sensitive to climate change and has been shown to operate in different modes. In ice cores the last glacial period is characterized by millennial-scale Dansgaard–Oeschger (D–O) events of warm interstadials and cold stadials. Similar millennial-scale variability (linked to D–O events) is evident from oceanic cores, suggesting a strong coupling of the atmospheric and oceanic circulations system. Particularly long-lasting cold stadials correlate with North Atlantic Heinrich events, where icebergs released from the continents caused a spread of meltwater over the northern North Atlantic and Nordic seas. The meltwater layer is believed to have caused a stop or near-stop in the deep convection, leading to cold climate. The spreading of meltwater and changes in oceanic circulation have a large influence on the carbon exchange between atmosphere and the deep ocean and lead to profound changes in the 14C activity of the surface ocean. Here we demonstrate marine 14C reservoir ages (R) of up to c. 2000 years for Heinrich event H4. Our R estimates are based on a new method for age model construction using identified tephra layers and tie-points based on abrupt interstadial warmings.