This article investigates the economic efficiency of farm households, with an application to The Gambia. The efficiency analysis is conducted not at the farm level but at the household level, thus capturing the importance of off-farm activities. Output-based measures of technical, allocative, and scale efficiency are generated using nonparametric measurements. An econometric analysis of factors affecting the efficiency indexes is then conducted using a Tobit model. Technical efficiency is fairly high indicating that access to technology is not a severe constraint for most farm households. The cost of scale inefficiency is modest. Allocative inefficiency by contrast is found to be important for the majority of farm households. On the basis of the Tobit results, imperfections in markets for financial capital and nonfarm employment contribute to significant allocative inefficiency. Copyright 2005, Oxford University Press.

The human proteome is a highly complex extension of the genome wherein a single gene often produces distinct protein forms due to alternative splicing, RNA editing, polymorphisms, and posttranslational modifications. Due to the presence of polymorphisms, alternative splicing, and posttranslational modifications (PTMs) 1 the human proteome is highly complex, often encoding multiple protein forms for a given gene (1). This biological complexity poses a significant analytical and bioinformatic challenge to the detailed analysis of mammalian proteomes by MS and is exacerbated by the presence of gene families sharing high sequence identity (2, 3). Protein modifications are often indicative of changes in cellular or tissue dynamics and therefore play central roles in regulation of the cell cycle or development of disease. Whether for new diagnostics or understanding molecular mechanisms in cell biology, protein identification using tryptic peptides has revolutionized the analysis of complex mixtures by mass spectrometry (1, 4). High throughput platforms based on MALDI (5) and ESI use MS/MS engines capable of spectral acquisition at a rate of Ͼ10 4 /week (6, 7). Recent studies indicate significant inefficiencies associated with such large scale "bottom up" analyses in mammalian systems including imperfect enzymatic cleavage (8, 9) and some MS/MS spectra requiring manual interpretation/validation for identification. Despite the lingering difficulties with peptide analysis, it provides the best and most general method for large scale protein identification today with information on nonsynonymous coding single nucleotide polymorphisms (cSNPs), alternative splicing (10), and PTMs challenging to obtain (2).Recent developments by MacCoss et al. (11), Wu et al. (12), and Zhu et al. (13) use three proteases and multidimensional protein identification technology ("MudPIT") or isoelectric focusing, reversed-phase chromatography, and three mass spectrometers (13), respectively, to obtain mass information on ϳ70 -99% of the primary protein structure. Combining intact protein measurement with near exhaustive peptide analysis of five proteins from human cells allowed detection of N-terminal modifications and one alternatively spliced transcript (13). Although cSNP analysis of abundant blood proteins is possible (14), a general informatic strategy has yet to systematically integrate DNA and RNA level data with the MS-based interrogation of the human proteome. This is accomplished here using a data base of human proteins tailored

Proteomics has grown significantly with the aid of new technologies that consistently are becoming more streamlined. While processing of proteins from a whole cell lysate is typically done in a bottom-up fashion utilizing MS/MS of peptides from enzymatically digested proteins, top-down proteomics is becoming a viable alternative that until recently has been limited largely to offline analysis by tandem mass spectrometry. Here we describe a method for high-resolution tandem mass spectrometery of intact proteins on a chromatographic time scale. In a single liquid chromatography-tandem mass spectrometry (LC-MS/MS) run, we have identified 22 yeast proteins with molecular weights from 14 to 35 kDa. Using anion exchange chromatography to fractionate a whole cell lysate before online LC-MS/MS, we have detected 231 metabolically labeled (14N/15N) protein pairs from Saccharomyces cerevisiae. Thirty-nine additional proteins were identified and characterized from LC-MS/MS of selected anion exchange fractions. Automated localization of multiple acetylations on Histone H4 was also accomplished on an LC time scale from a complex protein mixture. To our knowledge, this is the first demonstration of top-down proteomics (i.e., many identifications) on linear ion trap Fourier transform (LTQ FT) systems using high-resolution MS/MS data obtained on a chromatographic time scale.

The basis set of protein forms expressed by human cells from the H2B gene family was determined by Top Down Mass Spectrometry. Using Electron Capture Dissociation for MS/MS of H2B isoforms, direct evidence for the expression of unmodified H2B.Q, H2B.A, H2B.K/T, H2B.J, H2B.E, H2B.B, H2B.F, and monoacetylated H2B.A was obtained from asynchronous HeLa cells. H2B.A was the most abundant form, with the overall expression profile not changing significantly in cells arrested in mitosis by colchicine or during mid-S, mid-G2, G2/M, and mid-G1 phases of the cell cycle. Modest hyperacetylation of H2B family members was observed after sodium butyrate treatment.