51 research outputs found
Sample treatment for tissue proteomics in cancer, toxicology, and forensics
Since the birth of proteomics science in the 1990, the number of applications and of sample preparation methods has grown exponentially, making a huge contribution to the knowledge in life science disciplines. Continuous improvements in the sample treatment strategies unlock and reveal the fine details of disease mechanisms, drug potency, and toxicity as well as enable new disciplines to be investigated such as forensic science. This chapter will cover the most recent developments in sample preparation strategies for tissue proteomics in three areas, namely, cancer, toxicology, and forensics, thus also demonstrating breath of application within the domain of health and well-being, pharmaceuticals, and secure societies. In particular, in the area of cancer (human tumor biomarkers), the most efficient and multi-informative proteomic strategies will be covered in relation to the subsequent application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and liquid extraction surface analysis (LESA), due to their ability to provide molecular localization of tumor biomarkers albeit with different spatial resolution. With respect to toxicology, methodologies applied in toxicoproteomics will be illustrated with examples from its use in two important areas: the study of drug-induced liver injury (DILI) and studies of effects of chemical and environmental insults on skin, i.e., the effects of irritants, sensitizers, and ionizing radiation. Within this chapter, mainly tissue proteomics sample preparation methods for LC-MS/MS analysis will be discussed as (i) the use of LC-MS/MS is majorly represented in the research efforts of the bioanalytical community in this area and (ii) LC-MS/MS still is the gold standard for quantification studies. Finally, the use of proteomics will also be discussed in forensic science with respect to the information that can be recovered from blood and fingerprint evidence which are commonly encountered at the scene of the crime. The application of proteomic strategies for the analysis of blood and fingerprints is novel and proteomic preparation methods will be reported in relation to the subsequent use of mass spectrometry without any hyphenation. While generally yielding more information, hyphenated methods are often more laborious and time-consuming; since forensic investigations need quick turnaround, without compromising validity of the information, the prospect to develop methods for the application of quick forensic mass spectrometry techniques such as MALDI-MS (in imaging or profiling mode) is of great interest
Investigation of Pedestrian Crossing Speeds at Signalized Intersections with Heavy Pedestrian Volumes
Delay Model for Right-Turn Lanes at Signalized Intersections with Uniform Arrivals and Right Turns on Red
A randomized controlled trial to study the effects of an automated premilking stimulation system on milking performance, teat tissue condition, and udder health in Holstein dairy cows
ABSTRACT: The objectives were to examine the effect of an automated premilking stimulation (APS) by means of a high pulsation frequency (300 cycles/min) without a reduction of the vacuum in the pulsation chamber or claw piece on (1) milking performance, (2) teat tissue condition, and (3) udder health in dairy cows. In a randomized controlled field study, Holstein cows (n = 427) from 1 commercial dairy farm with a milking schedule of 3 times per day were assigned to treatment and control groups over a 90-d period. Treatments consisted of a maximum of 80 s (APS80) or 99 s (APS99) of mechanical stimulation at a pulsation rate of 300 pulses per minute and a ratio of 25:75 (no reduction of the pulsation chamber or milking vacuum). Cows in the control group (CON) received traditional premilking stimulation by means of manual forestripping for 8 s. Milking characteristics were documented with on-farm milk meters. Short- and long-term changes in teat tissue condition induced by machine milking were assessed visually on a weekly basis. Composite milk samples were analyzed once per month to determine somatic cell count. Generalized linear mixed models were used to study the effect of the treatment on the outcome variables. We observed no meaningful differences in milk yield or milking unit-on time. Least squares means and their 95% confidence intervals (95% CI) for cows in the APS80, APS99, and CON groups were 13.5 (13.1–14.0), 13.2 (12.8–13.7), and 13.2 (12.8–13.7) kg for milk yield and 222 (213–231), 219 (210–228), and 223 (214–232) s for milking unit-on time, respectively. The effect of treatment on bimodality was modified by milk yield such that the odds of bimodality increased in the treatment groups with increasing milk yield. Compared with cows in the CON group, the odds ratios (95% CI) of bimodality were 1.08 (0.62–1.89) in the APS80 group and 0.89 (0.55–1.42) in the APS99 group at a milk yield of 11 kg and 2.0 (1.24–3.22) in the APS80 group and 2.08 (1.29–3.35) in the APS99 group at a milk yield of 16 kg. We observed differences in short- and long-term changes in teat tissue condition between the treatment and control groups. Compared with cows in the CON group, the odds (95% CI) of short-term changes were 1.87 (1.35–2.58) for the APS80 group and 1.49 (1.08–2.07) for the APS99 group, and the odds of long-term changes were 1.52 (1.24–1.85) for cows in the APS80 group and 1.59 (1.31–1.94) for cows in the APS99 group. The least squares means (95% CI) for somatic cell counts (log10-transformed) were 4.74 (4.68–4.81) for the APS80 group, 4.77 (4.71–4.83) for the APS99 group, and 4.79 (4.73–4.86) for the CON group. We conclude that the APS system tested here had no negative effects on milk yield or milking unit-on time. However, differences in bimodality and teat tissue condition suggest that the APS system did not provide sufficient stimulation to facilitate a gentle milk harvest and adversely affects teat tissue condition
Right-Turn-on-Red Volume Estimation and Incremental Capacity Models for Shared Lanes at Signalized Intersections
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