Javascript must be enabled to continue!
ASTM Symposium on the Recovery and Enumeration of Mycobacteria from the Metalworking Fluid Environment
View through CrossRef
Abstract
Since 1994, when the first documented hypersensitivity pneumonitis cluster was reported at a metalworking plant, there have been approximately 200 diagnosed cases of hypersensitivity pneumonitis within the metalworking industry. Although there are a variety of bacterial and fungal etiologic agents associated with hypersensitivity pneumonitis, metalworking industry stakeholders have focused their attention on a hypothesis that links Mycobacterium immunogenum exposure to the disease.
A number of barriers confound attempts to test this hypothesis. Today's symposium opens a dialogue on two significant barriers. There is no consensus practice for sampling and recovering Mycobacterium immunogenum from either bulk metalworking fluids or metalworking fluid aerosols. There is no consensus method for quantifying mycobacteria that may be present in either bulk fluid or aerosol samples.
This paper provides a context for the symposium's other presentations. After offering a brief overview of the history of hypersensitivity pneumonitis in the metalworking environment, the author will address the current state of knowledge regarding Mycobacterium immunogenum distribution in metalworking fluids. Finally, the author will summarize the three primary strategies for enumerating mycobacteria: microscopic examination of acid-fast stained preparations, viable counts, and non-conventional methods.
Title: ASTM Symposium on the Recovery and Enumeration of Mycobacteria from the Metalworking Fluid Environment
Description:
Abstract
Since 1994, when the first documented hypersensitivity pneumonitis cluster was reported at a metalworking plant, there have been approximately 200 diagnosed cases of hypersensitivity pneumonitis within the metalworking industry.
Although there are a variety of bacterial and fungal etiologic agents associated with hypersensitivity pneumonitis, metalworking industry stakeholders have focused their attention on a hypothesis that links Mycobacterium immunogenum exposure to the disease.
A number of barriers confound attempts to test this hypothesis.
Today's symposium opens a dialogue on two significant barriers.
There is no consensus practice for sampling and recovering Mycobacterium immunogenum from either bulk metalworking fluids or metalworking fluid aerosols.
There is no consensus method for quantifying mycobacteria that may be present in either bulk fluid or aerosol samples.
This paper provides a context for the symposium's other presentations.
After offering a brief overview of the history of hypersensitivity pneumonitis in the metalworking environment, the author will address the current state of knowledge regarding Mycobacterium immunogenum distribution in metalworking fluids.
Finally, the author will summarize the three primary strategies for enumerating mycobacteria: microscopic examination of acid-fast stained preparations, viable counts, and non-conventional methods.
Related Results
Plasma Cell Enumeration By Manual and Automated Methods to Establish a Standard Pictorial Reference
Plasma Cell Enumeration By Manual and Automated Methods to Establish a Standard Pictorial Reference
Background
The diagnosis of plasma cell dyscrasias requires accurate, reliable enumeration of bone marrow plasma cell burden. This is typically assessed by manual...
Current therapeutic strategies for erectile function recovery after radical prostatectomy – literature review and meta-analysis
Current therapeutic strategies for erectile function recovery after radical prostatectomy – literature review and meta-analysis
Radical prostatectomy is the most commonly performed treatment option for localised prostate cancer. In the last decades the surgical technique has been improved and modified in or...
Experimental Investigation of Permeability and Fluid Loss Properties of Water Based Mud Under High Pressure-High Temperature Conditions
Experimental Investigation of Permeability and Fluid Loss Properties of Water Based Mud Under High Pressure-High Temperature Conditions
Drilling in deeper formations and in high pressure and high temperature (HPHT) environments is a new frontier for the oil industry. Fifty years ago, no one would have imagined dril...
Mycobacterium Tuberculosis and Nontuberculous Mycobacteria Isolates from Presumptive Pulmonary Tuberculosis Patients Attending A Tertiary Hospital in Addis Ababa, Ethiopia
Mycobacterium Tuberculosis and Nontuberculous Mycobacteria Isolates from Presumptive Pulmonary Tuberculosis Patients Attending A Tertiary Hospital in Addis Ababa, Ethiopia
BACKGROUND፡ Mycobacterial infections are known to cause a public health problem globally. The burden of pulmonary disease from nontuberculous mycobacteria is reportedly on the rise...
Physical Properties of New Formulation of Hybrid Nanofluid-based Minimum Quantity Lubrication (MQL) from Modified Jatropha Oil as Metalworking Fluid
Physical Properties of New Formulation of Hybrid Nanofluid-based Minimum Quantity Lubrication (MQL) from Modified Jatropha Oil as Metalworking Fluid
As a metalworking fluid, vegetable-based crude jatropha oil (CJO) was used in place of petroleum-based oil. The use of petroleum-oil-based metalworking fluids poses significant env...
Identification Of Nontuberculous Mycobacterium Isolates in Suspected Pulmonary Tuberculosis Patients
Identification Of Nontuberculous Mycobacterium Isolates in Suspected Pulmonary Tuberculosis Patients
According to World Health Organization, in the global tuberculosis ranking Pakistan is in 5th position. Mycobacterium tuberculosis bacterium is responsible for this dreadful diseas...
Efficient enumeration algorithms for minimal graph completions and deletions
Efficient enumeration algorithms for minimal graph completions and deletions
Algorithmes d'énumération efficaces pour les complétions et délétions minimales de graphes
Cette thèse porte sur la théorie des graphes et plus particulièrement les...
Predict Reservoir Fluid Properties from Advanced Mud Gas Data
Predict Reservoir Fluid Properties from Advanced Mud Gas Data
Abstract
In a recent paper, we published a machine learning method to quantitatively predict reservoir fluid gas oil ratio (GOR) from advanced mud gas (AMG) data. Th...

