The implications of a changing climate on agricultural land classification in England and Wales

The agricultural land classification (ALC) of England and Wales is a formal method of assessing the quality of agricultural land and guiding future land use. It assesses several soil, site and climate criteria and classifies land according to whichever is the most limiting. A common approach is required for calculating the necessary agroclimatic parameters over time in order to determine the effects of changes in the climate on land grading. In the present paper, climatic parameters required by the ALC classification have been re-calculated from a range of primary climate data, available from the Meteorological Office's UKCP09 historical dataset, provided as 5 km rasters for every month from 1914 to 2000. Thirty-year averages of the various agroclimatic properties were created for 1921–50, 1931–60, 1941–70, 1951–80, 1961–90 and 1971–2000. Soil records from the National Soil Inventory on a 5 km grid across England and Wales were used to determine the required soil and site parameters for determining ALC grade. Over the 80-year period it was shown that the overall climate was coolest during 1951–80. However, the area of land estimated in retrospect as ‘best and most versatile (BMV) land’ (Grades 1, 2 and 3a) probably peaked in the 1951–80 period as the cooler climate resulted in fewer droughty soils, more than offsetting the land which was downgraded by the climate being too cold. Overall there has been little change in the proportions of ALC grades among the six periods once all 10 factors (climate, gradient, flooding, texture, depth, stoniness, chemical, soil wetness, droughtiness and erosion) are taken into account. This is because it is rare for changes in climate variables all to point in the same direction in terms of ALC. Thus, a reduction in rainfall could result in higher grades in wetter areas but lead to lower classification in drier areas

Down Georgia Way

https://digitalcommons.library.umaine.edu/mmb-vp/5150/thumbnail.jp

Estimation of stratospheric input to the Arctic troposphere: 7Be and 10Be in aerosols at Alert, Canada

Concentrations of 7Be and 210Pb in 2 years of weekly high-volume aerosol samples collected at Alert, Northwest Territories, Canada, showed pronounced seasonal variations. We observed a broad winter peak in 210Pb concentration and a spring peak in 7Be. These peaks were similar in magnitude and duration to previously reported results for a number of stations in the Arctic Basin. Beryllium 10 concentrations (determined only during the first year of this study) were well correlated with those of 7Be; the atom ratio 10Be/7Be was nearly constant at 2.2 throughout the year. This relatively high value of 10Be/7Be indicates that the stratosphere must constitute an important source of both Be isotopes in the Arctic troposphere throughout the year. A simple mixing model based on the small seasonal variations of 10Be/7Be indicates an approximately twofold increase of stratospheric influence in the free troposphere in late summer. The spring maxima in concentrations of both Be isotopes at the surface apparently reflect vertical mixing in rather than stratospheric injections into the troposphere. We have merged the results of the Be-based mixing model with weekly O3 soundings to assess Arctic stratospheric impact on the surface O3 budget at Alert. The resulting estimates indicate that stratospheric inputs can account for a maximum of 10-15% of the 03 at the surface in spring and for less during the rest of the year. These estimates are most uncertain during the winter. The combination of Be isotopic measurements and O3 vertical profiles could allow quantification of the contributions of O3 from the Arctic stratosphere and lower latitude regions to the O3 budget in the Arctic troposphere. Although at present the lack of a quantitative understanding of the temporal variation of O3 lifetime in the Arctic troposphere precludes making definitive calculations, qualitative examples of the power of this approach are given

C1q-targeted inhibition of the classical complement pathway prevents injury in a novel mouse model of acute motor axonal neuropathy

Introduction Guillain-Barré syndrome (GBS) is an autoimmune disease that results in acute paralysis through inflammatory attack on peripheral nerves, and currently has limited, non-specific treatment options. The pathogenesis of the acute motor axonal neuropathy (AMAN) variant is mediated by complement-fixing anti-ganglioside antibodies that directly bind and injure the axon at sites of vulnerability such as nodes of Ranvier and nerve terminals. Consequently, the complement cascade is an attractive target to reduce disease severity. Recently, C5 complement component inhibitors that block the formation of the membrane attack complex and subsequent downstream injury have been shown to be efficacious in an in vivo anti-GQ1b antibody-mediated mouse model of the GBS variant Miller Fisher syndrome (MFS). However, since gangliosides are widely expressed in neurons and glial cells, injury in this model was not targeted exclusively to the axon and there are currently no pure mouse models for AMAN. Additionally, C5 inhibition does not prevent the production of early complement fragments such as C3a and C3b that can be deleterious via their known role in immune cell and macrophage recruitment to sites of neuronal damage. Results and Conclusions In this study, we first developed a new in vivo transgenic mouse model of AMAN using mice that express complex gangliosides exclusively in neurons, thereby enabling specific targeting of axons with anti-ganglioside antibodies. Secondly, we have evaluated the efficacy of a novel anti-C1q antibody (M1) that blocks initiation of the classical complement cascade, in both the newly developed anti-GM1 antibody-mediated AMAN model and our established MFS model in vivo. Anti-C1q monoclonal antibody treatment attenuated complement cascade activation and deposition, reduced immune cell recruitment and axonal injury, in both mouse models of GBS, along with improvement in respiratory function. These results demonstrate that neutralising C1q function attenuates injury with a consequent neuroprotective effect in acute GBS models and promises to be a useful new target for human therapy

Functional Optimization in Complex Excitable Networks

We study the effect of varying wiring in excitable random networks in which connection weights change with activity to mold local resistance or facilitation due to fatigue. Dynamic attractors, corresponding to patterns of activity, are then easily destabilized according to three main modes, including one in which the activity shows chaotic hopping among the patterns. We describe phase transitions to this regime, and show a monotonous dependence of critical parameters on the heterogeneity of the wiring distribution. Such correlation between topology and functionality implies, in particular, that tasks which require unstable behavior --such as pattern recognition, family discrimination and categorization-- can be most efficiently performed on highly heterogeneous networks. It also follows a possible explanation for the abundance in nature of scale--free network topologies.Comment: 7 pages, 3 figure

Adaptive self-organization in a realistic neural network model

Information processing in complex systems is often found to be maximally efficient close to critical states associated with phase transitions. It is therefore conceivable that also neural information processing operates close to criticality. This is further supported by the observation of power-law distributions, which are a hallmark of phase transitions. An important open question is how neural networks could remain close to a critical point while undergoing a continual change in the course of development, adaptation, learning, and more. An influential contribution was made by Bornholdt and Rohlf, introducing a generic mechanism of robust self-organized criticality in adaptive networks. Here, we address the question whether this mechanism is relevant for real neural networks. We show in a realistic model that spike-time-dependent synaptic plasticity can self-organize neural networks robustly toward criticality. Our model reproduces several empirical observations and makes testable predictions on the distribution of synaptic strength, relating them to the critical state of the network. These results suggest that the interplay between dynamics and topology may be essential for neural information processing.Comment: 6 pages, 4 figure

Differential binding patterns of anti-sulfatide antibodies to glial membranes

Sulfatide is a major glycosphingolipid in myelin and a target for autoantibodies in autoimmune neuropathies. However neuropathy disease models have not been widely established, in part because currently available monoclonal antibodies to sulfatide may not represent the diversity of anti-sulfatide antibody binding patterns found in neuropathy patients. We sought to address this issue by generating and characterising a panel of new anti-sulfatide monoclonal antibodies. These antibodies have sulfatide reactivity distinct from existing antibodies in assays and in binding to peripheral nerve tissues and can be used to provide insights into the pathophysiological roles of anti-sulfatide antibodies in demyelinating neuropathies

An in vivo analysis of safe laparoscopic grasping thresholds for colorectal surgery

Background Analysis of safe laparoscopic grasping thresholds for the colon has not been performed. This study aimed to analyse tissue damage thresholds when the colon is grasped laparoscopically, correlating histological changes to mechanical compressive forces. Methods An instrumented laparoscopic grasper was used to measure the forces applied to porcine colon, with data captured and plotted as a force–time (f–t) curve. Haematoxylin and eosin histochemistry of tissue subjected to 10, 20, 40, 50 and 70 N for 5, 30 and 60 s was performed, and the area of colonic circular and longitudinal muscle was compared in grasped and un-grasped regions. The area under the f–t curve was calculated as a measure of the accumulated force applied, known as the force–time product (FTP). Results FTP ranged from 55.7 to 3793 N.s. Significant differences were observed between the muscle area of the grasped and un-grasped regions in both longitudinal and circular muscle at 50 N and above for all grasping times. For the longitudinal muscle, significant differences were observed between grasped and un-grasped areas at 20 N force for 30 s (mean difference = 59 mm2, 95% CI 41–77 mm2, P = 0.04), 20 N force for 60 s (mean difference = 31 mm2, 95% CI 21.5–40.5 mm2, P = 0.006) and 40 N force for 30 s (mean difference 37 mm2, 95% CI 27–47 mm2, P = 0.006). Changes in histology correlated with mechanical forces applied to the longitudinal muscle at a FTP over 300 N s. Conclusions This study characterizes the grasping forces that result in histological changes to the colon and correlates these with a mechanical measurement of the applied force. The findings will contribute to the development of smart laparoscopic graspers with active constraints to prevent excessive grasping and tissue injury

Examining the efficacy of six published time-lapse imaging embryo selection algorithms to predict implantation to demonstrate the need for the development of specific, in-house morphokinetic selection algorithms.

OBJECTIVE: To study the efficacy of six embryo-selection algorithms (ESAs) when applied to a large, exclusive set of known implantation embryos. DESIGN: Retrospective, observational analysis. SETTING: Fertility treatment center. PATIENT(S): Women undergoing a total of 884 in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatment cycles (977 embryos) between September 2014 and September 2015 with embryos cultured using G-TL (Vitrolife) at 5% O2, 89% N2, 6% CO2, at 37°C in EmbryoScope instruments. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Efficacy of each ESA to predict implantation defined using specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic curve (AUC), and likelihood ratio (LR), with differences in implantation rates (IR) in the categories outlined by each ESA statistically analyzed (Fisher's exact and Kruskal-Wallis tests). RESULT(S): When applied to an exclusive cohort of known implantation embryos, the PPVs of each ESA were 42.57%, 41.52%, 44.28%, 38.91%, 38.29%, and 40.45%. The NPVs were 62.12%, 68.26%, 71.35%, 76.19%, 61.10%, and 64.14%. The sensitivity was 16.70%, 75.33%, 72.94%, 98.67%, 51.19%, and 62.33% and the specificity was 85.83%, 33.33%, 42.33%, 2.67%, 48.17%, and 42.33%, The AUC were 0.584, 0.558, 0.573, 0.612, 0.543, and 0.629. Two of the ESAs resulted in statistically significant differences in the embryo classifications in terms of IR. CONCLUSION(S): These results highlight the need for the development of in-house ESAs that are specific to the patient, treatment, and environment. These data suggest that currently available ESAs may not be clinically applicable and lose their diagnostic value when externally applied