Quantifying brain activity through optical imaging has the potential to improve the way the biomedical community treats neurological disorders and brain injuries. To accurately visualize and treat patients who have suffered a stroke, epileptic attack or traumatic brain injury, neuroscientists require precise imaging and measurements of brain activity.
Correlating levels of mRNA and corresponding proteins within cells provides more information linking gene function to phenotype than examining either alone. Separate measurements of RNA and protein merely provide information about two similar but separate cell populations. The ability to study both in individual cells leads to more physiologically relevant data, including information about cell-to-cell heterogeneity within a given sample.
Patience may be a virtue. But in a lab that’s bustling with scientists conducting meaningful biological research, excessive waiting can be downright frustrating. Such was the case leading up to 2012, when researchers at The University of Chicago Flow Cytometry Core Facility— known as UCFlow— would routinely wait as long as 16 days to be able to sort cells.
Induced pluripotent stem cells (iPSCs) offer strong potential for regenerative medicine, as well as disease modeling and drug screening. While researchers are using these cells for a wide range of applications, traditional methods used to generate iPSCs can be inefficient and time-consuming.
Tissue culture is a vital element of many research laboratories. Extensive experiments often stem off cultured cells and provide valuable insight. Growth of unwanted microbes and mold in tissue culture plastics impacts and pauses all future experiments. The researcher must then use valuable time and resources to obtain new cultures and avoid contamination in the future.
With so many new innovations emerging in genomics research, the evolving technology of next generation sequencing (NGS) is becoming an increasingly powerful tool, with researchers now able to simultaneously screen for thousands of disease-linked variants in a single individual.
Biomarkers play a critical role in clinical diagnostics and treatment as well as in drug screening and prognosis. Immunofluorescence and immunophenotyping are just two common techniques used to detect the relative abundance and location of protein biomarkers in fixed cells.
Analysis of one- to four-microliter size samples for nucleic acids has become routine in many life science laboratories. However, until now, available instruments require considerable manipulation of the instrument and sample; some require manually recording the data. The user must typically lower and raise the arm manually, then wipe the sample manually from the target after each analysis. And fiberoptics used in some of these instruments are subject to deterioration.
While well-understood, robust and convenient, classical batch-style 2-D culture on non-porous supports or 3-D suspension culture in other devices are really not very biologically relevant models. Cell culture conditions can affect the quality of the antibody or protein produced.
Drug discovery and testing, with their need for speed, repeatability and verification, are ideally suited to benefit from robot automation. It is therefore not surprising that robots have been at the forefront of automation developments in both these areas.
Life sciences research today is advancing exponentially, each step bringing us closer to the realization of truly personalized medicine–preventive care and treatments designed specifically for each individual. In the near future, PCPGM healthcare researchers expect to be able to use predictive genetic testing to create custom treatment plans for individuals and deliver dramatic improvements over today’s one-size-fits-all approach. But research capabilities are only part of the equation; current storage and operating capacities must also evolve to accommodate ever-expanding amounts of data before the goal of personalized medicine can be realized.
Over the years, polymerase chain reaction (PCR) has evolved into a readily automated, high throughput quantitative technology. Real-time quantitative PCR (qPCR) has become the industry standard for the detection and quantification of nucleic acids for multiple application, including quantification of RNA levels. But a lack of consensus among researchers on how to best perform and interpret qPCR experiments presents a major hurdle for advancement of the technology. This problem is exacerbated by insufficient experimental detail in published work, which impedes the ability of others to accurately evaluate or replicate reported results.
The year 2009 was marked by the emergence of a novel influenza A (H1N1) virus that infects humans. There is a need to identify the different strains of influenza virus for purposes of monitoring the H1N1 strain pandemic and for other epidemiological and scientific purposes.
Fluorescence microscopy techniques require a reliable light source at the desired wavelength or wavelengths, with minimal downtime for maintenance and alignment. Lasers are a popular light source, although the alignment and upkeep of laser combiners is a time-consuming prospect for many users.
Size-exclusion chromatography (SEC) is a popular method to separate biomolecules based on their size. Primarily, it is applied to the separation of biopolymers such as proteins and nucleic acids, i.e. water-soluble polymers.