Developing site-specific nutrient criteria from empirical models

Empirical models based on classification and regression tree analysis (CART model) or fuzzy logic (FL model) were used to forecast leaf wetness duration (LWD) 24 h into the future, using site-specific weather data estimates as inputs. Forecasted LWD and air temperature then were used as inputs to simulate performance of the Melcast and TOM-CAST disease-warning systems. Overall, the CART and FL models underpredicted LWD with a mean error (ME) of 2.3 and 3.9 h day-1, respectively. The CFL model, a corrected version of the FL model using a weight value, reduced ME in LWD forecasts to -1.1 h day-1. In the Melcast and TOM-CAST simulations, the CART and CFL models predicted timing of occurrence of action thresholds similarly to thresholds derived from on-site weather data measurements. Both models forecasted the exact spray dates for approximately 45% of advisories derived from measurements. When hindcast and forecast estimates derived from site-specific estimates provided by SkyBit Inc. were used as inputs, the CART and CFL models forecasted spray advisories within 3 days for approximately 70% of simulation periods for the Melcast and TOM-CAST disease-warning systems. The results demonstrate that these models substantially enhance the accuracy of commercial site-specific LWD estimates and, therefore, can enhance performance of disease-warning systems using LWD as an input.

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Large-cluster and combined fluorescent and gold immunoprobes

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100166920 ◽

1996 ◽

Vol 54 ◽

pp. 892-893

Author(s):

Richard D. Powell ◽

James F. Hainfeld ◽

Carol M. R. Halsey ◽

David L. Spector ◽

Shelley Kaurin ◽

...

Keyword(s):

Metal Cluster ◽

Sulfonyl Chloride ◽

Gel Filtration ◽

Cross Linking ◽

Site Specific ◽

Fab Fragments ◽

Cluster Label ◽

Covalently Linked ◽

Texas Red ◽

Fold Excess

Two new types of covalently linked, site-specific immunoprobes have been prepared using metal cluster labels, and used to stain components of cells. Combined fluorescein and 1.4 nm “Nanogold” labels were prepared by using the fluorescein-conjugated tris (aryl) phosphine ligand and the amino-substituted ligand in the synthesis of the Nanogold cluster. This cluster label was activated by reaction with a 60-fold excess of (sulfo-Succinimidyl-4-N-maleiniido-cyclohexane-l-carboxylate (sulfo-SMCC) at pH 7.5, separated from excess cross-linking reagent by gel filtration, and mixed in ten-fold excess with Goat Fab’ fragments against mouse IgG (obtained by reduction of F(ab’)2 fragments with 50 mM mercaptoethylamine hydrochloride). Labeled Fab’ fragments were isolated by gel filtration HPLC (Superose-12, Pharmacia). A combined Nanogold and Texas Red label was also prepared, using a Nanogold cluster derivatized with both and its protected analog: the cluster was reacted with an eight-fold excess of Texas Red sulfonyl chloride at pH 9.0, separated from excess Texas Red by gel filtration, then deprotected with HC1 in methanol to yield the amino-substituted label.

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The challenge of detecting modifications on proteins

Essays in Biochemistry ◽

10.1042/ebc20190055 ◽

2020 ◽

Vol 64 (1) ◽

pp. 135-153 ◽

Cited By ~ 1

Author(s):

Lauren Elizabeth Smith ◽

Adelina Rogowska-Wrzesinska

Keyword(s):

Mass Spectrometry ◽

Protein Function ◽

Chemical Properties ◽

Lysine Acetylation ◽

Mass Determination ◽

Post Translational Modifications ◽

Site Specific ◽

The Common

Abstract Post-translational modifications (PTMs) are integral to the regulation of protein function, characterising their role in this process is vital to understanding how cells work in both healthy and diseased states. Mass spectrometry (MS) facilitates the mass determination and sequencing of peptides, and thereby also the detection of site-specific PTMs. However, numerous challenges in this field continue to persist. The diverse chemical properties, low abundance, labile nature and instability of many PTMs, in combination with the more practical issues of compatibility with MS and bioinformatics challenges, contribute to the arduous nature of their analysis. In this review, we present an overview of the established MS-based approaches for analysing PTMs and the common complications associated with their investigation, including examples of specific challenges focusing on phosphorylation, lysine acetylation and redox modifications.

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