Aggregating these respective themes, I felt it important to review the different opinions offered at the Conference. Consolidating the various themes and propositions presented can in turn allow for discussion of potential strategies to build more effective solutions to the problem of research integrity.

The Problem: Fabrication or Dishonesty?

In discussing the issue of “Research Integrity”, it was first essential to define the parameters of the discussion.

For many of the attendees, the problems surrounding research integrity were narrowly defined as those conducive to misconduct, including fabrication, falsification, and plagiarism (FFP). At one point Jim Kroll, the Head of Administrative Investigations at the NSF Office of Inspector General, contended that the NSF was solely focused on examining research misconduct, not research quality.

Such a blatant and over-arching focus on FFP behaviors has its limitations, and may be seen as an ineffective approach when such behaviors are not clearly defined. Daniele Fanelli, research fellow at the University of Edinburgh, has written explicitly about this issue (Redefine Misconduct as Distorted Reporting, Nature), stating that research misconduct needs to be more broadly defined to encompass issues such as selective reporting of data. Such selective reporting, Fanelli contends, contribute much more to the problem than fabrication or even plagiarism, which are only committed be a few big actors a year.

This same point was made by Dan Ariely, professor of behavioral economics at Duke University and author of The (Honest) Truth About Dishonesty. In his studies on dishonesty, Ariely noted that most people cheated a little bit, and very few people cheated a lot. The very few big cheaters cost ~$200, compared with the many small cheaters who collectively cost $20,000. In turn it could be seen that our own strategies for ensuring research integrity consist of trying to catch the few ‘big cheaters’, when in reality such problems exist in a pool of ‘small cheaters’ who cause much more damage to the integrity of research produced.

Misaligned Solutions: Whistleblowers, Punishment, and Training

A number of solutions were proposed at the Conference to tackle concerns of research integrity.

Past strategies have focused on catching big cheaters through a reliance on whistleblowers, many of who are students in the labs of the ‘big cheaters’. Understandably, it is incredibly difficult for a student in this position to report such behavior, questioning its actual efficacy. And even if an alternative source of whistleblowers could be found, an allegation-based system is hardly effective in ‘policing’ the entire research system.

Other punitive measures were also proposed, such as required prison sentences for research misconduct. But such solutions ignore the fact that long-term penalties have consistently proven to be ineffective deterrents to immediate misconduct. Ariely gave the poignant example of how long-term penalties such as corporal punishment have had no proven effect in deterring violent crime, where states incorporating the death penalty actually having higher rates of crime than those without.

Another strategy that was widely discussed at the Conference was better research training, but this again ignores the underlying problems systemic to misconduct. Donald Kornfeld of Columbia University examined 146 Office of Research Integrity reports from 1992-2003 (Research Misconduct: The Search For A Remedy, Acad Med), and found all researchers involved in research misconduct knew what they were doing was ‘wrong’. They didn’t need training to tell them not to fabricate, or falsify and plagiarize work.

On the question of plagiarism though, it is important to note it as a different form of misconduct, to be classified differently from fabrication and falsification. It is likely possible to educate or train people about plagiarism and how to correctly cite their work. It is also fairly easy to catch bad actors with software like iThenticate, which is already in widespread use. So it is really solutions that address fabrication and falsification that need to be addressed, where training may not be effective in preventing such actions.

Improving The Research Culture

To promote sustainable solutions to research integrity, it is more effective to take a step back and think about why we have such problems to begin with.

Ultimately it comes down to the incentive system, which in the case of academic research rewards scientists for publishing lots of positive results, with little incentive to prove reproducibility or robustness of outcomes. John Ioannidis, Professor of Epidemiology at Stanford University who showed that over 90% of oncology studies only report positive outcomes (Almost All Articles on Cancer Prognostic Markers Report Statistically Significant Results, EJC), succinctly noted that: “If you reward researchers for publishing positive results, that’s all you get”. Researchers will selectively report, manipulate or even fabricate data to get there, and at a shockingly high rate. Daniele Fanelli noted in a recent study that 1.97% of scientists admitted to fabricating or falsifying their data at least once, and up to 33.7% admitted other questionable practices (How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta Analysis of Survey Data, PLOS ONE). When asked about their colleagues, 14.12% of scientist respondents reported falsification, and up to 72% claimed other questionable research practices.

Accordingly, a sustainable strategy to solve the problem of research integrity is to change the incentive structure of research culture to reward integrity, a point firmly noted by Dan Ariely as well. In Ariely’s studies, he noted that by simply producing a culture where people witnessed cheating more openly, participants were much more likely to cheat, and to cheat more. Combined with Fanelli’s reports of scientists witnessing 72% of their colleagues engaged in questionable research practices, it is no wonder that concerns of FFP have become systemic in scientific research.

The current research environment could by consequence be compared to an environment that encourages ‘cheating’. Researchers who publish lots of papers in top journals are rewarded, leading to a high incidence of ‘sloppy’ results (Must Try Harder, Nature) and irreproducible outcomes (Why Most Published Research Findings Are False, PLOS ONE). There is really no upside or incentive for a researcher to focus on publishing validated or robust research, given the heavy emphasis on novel or exciting outcomes that lead to top publications, and in turn top faculty positions.

Further, there is a very small downside to publishing papers with sloppy or irreproducible outcomes. Retractions may be a major ‘red letter’ to most scientists, and perceived as an indication of fraud, but their scarcity in occurrence leaves for little impact on curbing sloppy work. David Vaux from the Walter+Eliza Hall Institute for Medical Research noted at the Conference that there were ~1 million publications indexed by PubMed last year, ~900,000 showing a lack of reproducible outcomes (according to Ioannidis), and only about 300 overall retractions. Retractions are clearly not a way to identify or prevent publication of unreliable research results.

Implementing an Audit System

So how do we change the research culture? Michael Farthing, Vice Chancellor of the University of Sussex, proposed a bold solution in the form of an audit system. The idea shows promise, in so much as providing a framework to change the incentive systems to reward high quality reproducible research. Audit systems have been notably and effectively utilized in other frameworks already, such as random drug testing in sports, speed cameras, and tax audits. The Open Science Framework, through its Reproducibility Project, is leading one such effort in driving replication studies in the social sciences.

Another practical way to implement such an audit system may come in the form of the Reproducibility Initiative, which I am co-directing on behalf of Science Exchange, with participation from PLOS ONE, Nature Publishing Group, Mendeley, and Figshare. The Initiative can leverage professional experimental service providers such as university core facilities or commercial service providers on the Science Exchange network, to conduct a validation service. Professional service providers are highly skilled experts in their techniques, and operate purely on a fee-for-service basis, carrying no incentive for positive or null results. They also operate outside the academic network of grants and publications, and are thus less at risk for retaliation by their peers.

In structuring the Reproducibility Initiative as an opt-in, reward based program, we can address the systemic concerns of research misconduct through positive incentive structures. Rather than being penalized for a lack of robust outcomes, which Vaux, Ioannidis, and Ariely noted as having minimal impact, all studies submitted and selected for validation will receive a publication in PLOS ONE, providing the reproduced data in an open-access format. Participating journals who in turn published the original study may reward scientists with a ‘Badge’ of reproducibility, to distinguish those papers that took the effort to validate their findings.

Combined, audit systems in the form of the Reproducibility Project and Reproducibility Initiative may serve as forward-looking solutions to the problem of research integrity, promoting a reward-based rather than a punitive-based culture for research integrity.

About the author

Elizabeth Iorns is Co-Founder & CEO of Science Exchange. Elizabeth conceived the idea for Science Exchange while an Assistant Professor at the University of Miami and as CEO she drives the company’s vision, strategy and growth. She is passionate about creating a new way to foster scientific collaboration that will break down existing silos, democratize access to scientific expertise and accelerate the speed of scientific discovery. Elizabeth has a B.S. in Biomedical Science from the University of Auckland, a Ph.D. in Cancer Biology from the Institute of Cancer Research in London, and conducted postdoctoral research in Cancer Biology from the University of Miami’s Miller School of Medicine where her research focused on identifying mechanisms of breast cancer development and progression.

Upon finishing my Ph.D. in December, I was quickly confronted with the loss of journal, publication, and general program access.

Within an academic institution, we are privileged in access to a wide array of resources and traditionally subscription-based service. And while there are far more open-access resources than ever before, with Wikipedia and PLOS as significant examples, it is important to recognize some of the other commonly available resources which can assist scientists who are set to graduate this summer from their institutions.

Below I highlight some of the references, software, and literature I myself am using that are all free, open access, and ready to use. And as the discussion about open access scientific literature makes significant strides, I think it is important to start thinking about what other resources and expertise should be available for scientists to freely access and use.

1. Making the Right Moves and Entering Mentoring

The Howard Hughes Medical Institute (HHMI) offers free lab management books that can be ordered from their website. Both Making the Right Moves and Entering Mentoring are guidebook resources for mentors at every level.

Website: http://www.hhmi.org/resources/scientists.html

2.  Biochemistry Free and Easy

Dr. Kevin Ahern and Dr. Indira Rajagopal of Oregon State University provide their biochemistry textbook with a free PDF version and links to over 100 video lectures on the iPad full-featured version. They also offer three free online courses through Apple iTunes U- Biochemistry for Pre-Meds, Elementary Biochemistry, and the Pre-Med Primer- Getting Into Medical School.

Website: http://biochem.science.oregonstate.edu/biochemistry-free-and-easy

iTunes U: https://itunes.apple.com/us/course/biochemistry-for-pre-meds/id556410409

PDF: http://biochem.science.oregonstate.edu/files/bbnew/images/BiochemistryFreeEasy1.pdf

3. Organic Chemistry with a Biological Emphasis

Dr. Tim Soderberg of University of Minnesota, Morris, provides free eBook downloads of his organic chemistry textbook through the UC Davis ChemWiki project. Focusing students that are majoring in biology, biochemistry, or health sciences, Soderberg teaches ‘the chemistry of life’ through reactions relevant to those related to a living cell.

Website: http://chemwiki.ucdavis.edu/Organic_Chemistry/Organic_Chemistry_With_a_Biological_Emphasis

PDF Chapters 1-9: http://www.lulu.com/shop/tim-soderberg/organic-chemistry-with-a-biological-emphasis-volume-i/ebook/product-18905202.html

PDF Chapters 10-17: http://www.lulu.com/shop/tim-soderberg/organic-chemistry-with-a-biological-emphasis-volume-ii/ebook/product-18921698.html

Solutions Manual: http://www.lulu.com/shop/tim-soderberg/solutions-manual-for-organic-chemistry-with-a-biological-emphasis/ebook/product-18921729.html

4.  Science Careers Tools & Tips: How-To Series

In this series, Science Careers gives practical tips, such as How to Get Funding, How to Interview, and How to Build Your Network. Many of these are older documents, from when granting cycles were not quite so competitive or getting a job was not so difficult, but the principles are solid and apply now more than ever.

Website: http://sciencecareers.sciencemag.org/tools_tips/how_to_series

5. HHMI Bulletin

Available for free in either the print or online versions, the HHMI Bulletin offers quarterly reports on biomedical research and science education by HHMI Investigators and other HHMI funding efforts. I prefer the print version for just some at home or beach reading when I am relaxing off of the computer.

Website: http://www.hhmi.org/bulletin/subscribe/index.php

6. Accelerators and Beams: Tools of Discovery and Innovation

This fun little text, published by the Division of Physics of Beams of the American Physical Society, offers a no-stress read (with lots of pictures) all about accelerators and their applications.

Website: http://www.aps.org/units/dpb/upload/accel_beams_mar13.pdf

7. LyX

LyX is a document processor with a Microsoft Word-like interface that sits on top of LaTeX so that documents with LaTeX’s polish and specificity can be generated without writing code. It is available for Mac, Windows, and Linux and generates LaTeX source code to submit to journals.

Website: http://www.lyx.org/

8. Why So Few? Women in Science, Technology, Engineering, and Mathematics

Why So Few? presents the 2010 report of American Association of University Women (AAUW) to figure out why women, while increasing in other careers, are not increasing in science at a similar rate. A must read for any mentor, advisor, and student, the AAUW hits on eight points where women meet barriers and how to surpass them.

Website: http://www.aauw.org/research/why-so-few/

PDF: http://www.aauw.org/files/2013/02/Why-So-Few-Women-in-Science-Technology-Engineering-and-Mathematics.pdf

9. Nautilus Magazine

This brand-new literary science magazine is all available online. Each issue covers one topic from a variety of scientific perspectives. The first issue, What Makes You So Special, follows through biology, matter, and culture perspectives to develop a complete picture. Divided into the first two chapters “Less Than You Think” and “More Than you Know,” Nautilus is new, fun, and I look forward to seeing where this magazine goes in the future!

Website: http://nautil.us/

10. Wolfram Alpha

Wolfram Alpha is my favorite new find online. It is computation knowledge engine that you can enter pretty much anything into for results. You can solve equations, retrieve statistical data, fundamental constants, unit conversions, and combine these capabilities to answer surprisingly profound theories.

Website: http://www.wolframalpha.com/

And one final one…

Enthought Python Distribution Free

Many research groups use MATLAB to do their scientific computing because, although expensive, it is fast for certain calculations and makes pretty figures and many groups have legacy code. Python is an easier language to code in and is free with free distribution, so it is easy to work with and is a great resource for new research groups without legacy code. Enthought Python Distribution incorporates libraries that allow one to replicate both the numeric processing that MatLab does efficiently as well as the plotting functions.There remains some specialized info that this can’t do, for the most part, this replicates most of the average functions that most scientists need.

Website: https://www.enthought.com/products/epd/free/

Flow Cytometry is a powerful technique that enables researchers to conduct a rapid and multi-parametric analysis of single cells simultaneously.

Of late, it has become an indispensable tool in basic cell biology and medical research, immunological studies, drug discovery, and even diagnosis of diseases. The applications vary as well, from cell sorting of heterogeneous populations, DNA abnormalities, apoptosis assays, cell cycle analyses, immunophenotyping, protein modifications, proliferation assays, and cell signaling.

Below is a broad overview of the technique platform, how it works in these applications, and new technological developments.

Flow Cytometry Platform

The Flow Cytometry platform is composed of four basic components, including a fluidic system, optics, electronics, and computer software.

The fluidic system contains a sheath fluid to keep the cells to be analyzed suspended, and allow for alignment of a single file of cells as it passes through an optics system. The optics system is comprised of a laser diode that provides the source of light. The system also includes lenses that can focus the laser beam on cells, and optical mirrors and filters that help to route scattered light or fluorescence into appropriate detectors.

The electronics components convert the data of the detectors, amplify them, and convert them into electrical signals or voltage. Computer software than digitally converts these signals, storing the data in a Flow Cytometry Standard (FCS) format, and permitting for analysis conducted with any accompanying software.

How Flow Cytometry Works

The 4-component based Flow Cytometry system can in turn exploits varying optical and fluorescent characteristics of single cells.

With the fluidic system used to analyze a cell suspension, and hydro-dynamically focused, single cells may pass rapidly in front of a focused-laser diode. The cells scatter the light that is collected by the detectors: one placed in line with the laser, which computes a cell’s relative size (Forward scatter) and others placed at right angles to the laser path, which determine a cell’s interior complexity (e.g. cell granularity, organelles etc.) or fluorescence (Side Scatter).

Flow Cytometry also allows for specific protein antigens of cells, on surface or within it, to be detected using specific antibodies conjugated to fluorescent dyes. In this case, the laser excites the fluorescent molecules to a higher energy state, and the emission of light energy at different wavelengths allows several parameters of cells to be analyzed simultaneously.

Lastly, scattered light signals are passed through specific filters and collected by appropriate detectors. The signals are then amplified and converted into electrical signals (voltage) to be analyzed by a computer.

Applications & New Technologies

One of the most common and important applications of using such a platform is to study expression of protein antigens of cells. During my Ph.D., I routinely used Flow Cytometry to analyze the expression of receptor tyrosine kinases (RTK) on surface and within the cells (Read my paper).

As technology continues to improve though, new generation of flow cytometers will emerge with additional applications. A flow cytometer analyzer by BD sciences for instance has up to 5 lasers and allows for studying of 20 parameters simultaneously. Such a flow cytometer would be critical to analyze properties of extremely rare cell populations and lead to important medical and basic science discoveries.

One of the caveats of standard Flow Cytometry is the lack of information about the localization of protein antigens and antigen-interactions. The advent of new generation of flow cytomers such as Amnis imaging flow cytometers, which combine power of digital microscopy and Flow Cytometry, has made it possible to visualize localization of antigens while also gathering its expression level at the same time. Such simultaneous acquisition of quantitative and qualitative data will greatly increase the scope and efficiency of research.

If you want to order Flow Cytometry for your own study, check out the 33 facilities who offer the service on Science Exchange: https://www.scienceexchange.com/services/flow-cytometry

About the author

Roshan Karki is a Postdoctoral Research Associate at Danbury Hospital (part of the Western Connecticut Health Network). His research is focused on developing biomarkers for gynecological cancers. He is also a member of the Science Advocate program and believes Science Exchange has the potential to impact scientific research and facilitate medical and drug discoveries. Previously, Roshan completed a Ph.D. in Experimental Pathology at Yale University.

This is the third in a series of posts on scientific techniques, and how to use them in your research

Inductively Coupled Plasma (ICP), usually coupled with optical emission spectrometer (OES), atomic emission spectrometer (AES), or mass spectrometer (MS), has been most commonly used by environmental chemists to detect metals in soil or watershed, but it is becoming more and more popular as a technique for inorganic or biological chemists to determine what amounts of which metals are in their systems.

Sample Prep with ICP

ICP injects a liquid (a digested, dissolved, and usually diluted) sample into an argon plasma flame (~6000 K). The plasma is the source of positively charged ions, which are sent to an OES, AES, or MS detector, and concentration is determined onto a computer output. Samples must be digested, usually in nitric acid, so they can be effectively sprayed into the detector.

While most samples can be thoroughly digested with nitric acid (proteins, dendrimers, or other biological material), some nanoparticles are more difficult to digest. Since heavy molecules might be too heavy to reach the detector, not digesting particles fully can alter the results. Gold and platinum nanoparticles, for example, require digestion in aqua regia (1:3 concentrated nitric acid: concentrated hydrocholoric acid) for accurate ICP results. The method of digestion is usually included in the experimental section of publications.

Benefits of Using ICP

ICP is especially useful because it is extremely sensitive (> ppb) and requires only trace amounts of sample. ICP is such a sensitive technique for low metal concentrations that care must be provided is sample preparation. Only Millipore or similar water should be used for dilution, and for digestion and dilution, trace metal grade nitric acid in plastic bottles should be used. Since glass can leach metals, only plastic bottles, spatulas, pipettes, and the like should be used. Any contact to metal can distort results, so samples should be properly digested to break down macromolecules and carefully prepared in metal-free environments.

There are no apparent pitfalls with ICP technology, but it is not very frequently used by inorganic chemists for characterization, where it could give as much data as elemental analysis in some cases. EA requires about 5 mg of sample, whereas ICP requires trace amounts.

Most metals can be tested, provided that a standard of that metal is evaluated prior to sample analysis. ICP can be used to determine trace amounts of one metal in a complex or test many metals on an unknown sample.

Other Use Cases for ICP

In my research on MRI Contrast Agents, I look for relaxivity (a parameter of efficiency) per metal ion. Gadolinium(III), with seven unpaired electrons, is most commonly used for MRI, so I tested a sample for overall relaxivity with a relaxometer, then used ICP to get the exact Gd(III) concentration. I then calculated the relaxivity per Gd ion in solution.

Another method of use for ICP is to get the loading onto a macromolecule. MRI Contrast Agents are more efficient with a larger molecular weight, so a common method utilized is to conjugate the small molecule Gd contrast agents to a macromolecule. Quantifying loading can be difficult, but if loading onto a silica particle or gold nanoparticle, a ratio can be determined of Gd in solution as compared to Si or Au and an approximate loading can be determined.

Most ICP instruments also have an autosampler, so many samples can be evaluated for many different metals without much supervision or time and effort on the part of the researcher. It is a very efficient technique for using a little sample to get a lot of data quickly.

If you want to order Inductively coupled plasma experiments for your own study, check out the facilities who offer the service on Science Exchange: www.scienceexchange.com/services/inductively-coupled-plasma-icp

About the author

Piper J. Klemm (Twitter: @piperjklemm) is a Ph.D. Candidate in Chemistry at University of California, Berkeley, studying the next generation of MRI contrast agents in the laboratory of Professor Kenneth N. Raymond. She is also the National Social Media Coordinator for Iota Sigma Pi (the women’s honors society in chemistry), an Associate Language Editor for Molecular Imprinting (a Versita open-access journal), as well as being part of the Science Exchange Advocate program. She received her B.S. with Honors in Chemistry from Trinity College (Hartford, CT).

In the past, I’ve discussed some Innovative Research Awards for Young Investigators. However, awards and conferences can benefit more than just faculty. They are of special importance to graduate students and post-docs, who can effectively use them to determine career choices, network with colleagues in their field, and gain the research expertise in conversational knowledge to give more effective lectures and interviews of their own. (And it can also just be a nice break from endless hours at the bench.)

This post is a focus on Graduate Student Awards and Conferences with upcoming deadlines, and most of these are open to postdocs as well. Profiled below is the SciFinder Future Leader in Chemistry Award, which includes a conference; the Keck Bioscience Management Bootcamp for scientists to explore business; a Materials in 3D workshop from the International Center for Materials Research; the Materials Research Society Fall Meeting and Graduate Student Awards; and a Photovoltaic Workshop. All of these offer significant opportunities to current Graduate Students in a variety of scientific fields.

SciFinder Future Leaders in Chemistry

In its 4^th year, the SciFinder Future Leaders in Chemistry program brings together scientists from around the world to explore their use of scientific data, learn about career options, and have a lot of fun. This fully funded week (September 7-14, 2013) takes place at the SciFinder campus in Columbus, OH, and the American Chemical Society (ACS) meeting in Indianapolis, IN. I did this program in 2012 and met many fantastic people – both other Future Leaders and the exceptional people the program brought in to speak and work with us, including scientists and entrepreneurs from TechColumbus, Batelle Memorial Institute, and The Ohio State University. The Future Leaders are from all over the world; 2012 included: South Africa, Australia, China, Brazil, Austria, India, Japan, France, and Sweden, and the opportunity to learn about so many different chemical cultures was valuable.

• Eligible: Graduate students and postdocs.
• Application Due Date: May 5, 2013
• Materials Required: Recommendation, CV, and essay.
• Apply online: http://www.cas.org/products/scifinder/futureleaders

Keck Bioscience Management Bootcamp

“Bridging the Gap” Bioscience Management Bootcamp invites 40 students to attend a two-week (July 8-20, 2013) bootcamp at the Keck Graduate Institute (KGI) in Claremont, CA, to introduce Ph.D. scientists to the business side of life science companies. The program will consist of a short course in bioscience management, career-oriented workshops, and a 4-5 person team-based project. Accepted students are provided housing, most meals, and $400 for travel costs.

• Eligible: Graduate students and postdocs.
• Application Due Date: April 30, 2013
• Materials Required: Cover letter, CV, and recommendation.
• Apply online: http://www.kgi.edu/academic-programs/bioscience-management-bootcamp.html

International Center for Materials Research (ICMR), Materials in 3D: Modeling and Imaging at Multiple Length Scale

In this workshop at University of California, Santa Barbara, from August 19-30, 2013, participants can learn advances in experimental techniques for imaging materials and survey the modeling of materials across multiple length scales. Boarding and lodging are covered for all participants and partial travel funding is available.

• Eligible: Graduate students, postdocs, and young faculty.
• Application Due Date: May 15, 2013
• Materials Required: A one-page CV, publication list, and recommendation.
• Apply Online: http://www.icmr.ucsb.edu/programs/upcoming.html
• Workshop Date/Location: August 19-30, 2013, Santa Barbara, California (UCSB)

Materials Research Society Fall Meeting and Exhibit

The Materials Research Society (MRS) Fall Meeting and Exhibit will be December 1-6, 2013, in Boston, MA. This huge meeting brings in materials scientists from all over the world for thousands of lectures, posters, and courses. Graduate students can apply for Graduate Student Awards, which are presented at every MRS National Meeting (Spring in San Francisco, Fall in Boston). Other awards are available for materials scientists at all career levels.

• Abstract Due Date: June 19, 2013
• Abstract Submission Link: www.mrs.org/fall2013
• Graduate Student Award Deadline: August 15, 2013
• Graduate Student Award Online Application: http://www.mrs.org/gsa/

Photovoltaic Materials and Manufacturing Issues III Workshop

This three-day workshop, the third in a series of PV workshops organized by MRS, will be September 10-13, 2013 in Golden, CO. The focus will be on improving photovoltaic materials from low cost production of solar cells and modules, and how to reach the next generation of solar cells capable of higher efficiencies. Organizers are Bhushan Sopori (National Renewable Energy Laboratory), Koichi Kakimoto (Kyushu University, Japan), and Bulent Basol (EncoreSolar, Inc).

• Abstract Due Date: June 17, 2013.
• Abstract Submission: http://www.mrs.org/photovoltaic-workshop-2013/

About the author

Piper J. Klemm (Twitter: @piperjklemm) is a Ph.D. Candidate in Chemistry at University of California, Berkeley, studying the next generation of MRI contrast agents in the laboratory of Professor Kenneth N. Raymond. She is also the National Social Media Coordinator for Iota Sigma Pi (the women’s honors society in chemistry), an Associate Language Editor for Molecular Imprinting (a Versita open-access journal), as well as being part of the Science Exchange Advocate program. She received her B.S. with Honors in Chemistry from Trinity College (Hartford, CT).

This is the second in a series of posts on scientific techniques, and how to use them in your research.

Confocal microscopy is an essential tool in modern cell biology with a wide range of applications. It can be used to study cellular structures and subcellular components of organisms ranging from yeast to zebrafish.

The underlying principle of this imaging technique is the use of a pinhole to eliminate out-of-focus background light, providing a clearer image of the specimen at a particular focal plane. An important advantage of the instrument is its capacity to construct a 3D image of the specimen. The confocal microscope is hooked up to a computer that processes the overall image as several slices (z-stacks) of the object are taken, using the microscope and an attached digital camera.

Setting Up A Question 

Let’s say you want to study the localization of a particular protein tagged with green fluorescent protein (GFP) in an organism— for example, the localization of tubulin-tagged GFP in yeast cells with abnormal cell morphology.

Using a regular fluorescence microscope will allow you to visualize the protein, but only on a two-dimensional level. You might be able see the tubulin-GFP as a stretched line in a budding yeast cell: at best, you’d confirm whether protein is present or absent. But a confocal microscope will give you a more in-depth view of tubulin in a defined area of the cell.

Getting Started With Confocal Microscopy

Using the confocal’s automated objective lens, you can focus on the yeast cell and choose the depth range in which you want to acquire a 3D image (using a focal plane from where the tubulin-GFP is first visible till its disappearance).

A key point to decide is the number of slices you’d like to capture within the chosen depth range: if you want enhanced resolution of your protein of interest, or to capture an intricate structure in the cell, you may want to increase the number of slices the software package directs the microscope to acquire. Using other control keys, you can adjust the background light so that the specimen is clearly visible.

Once the desired settings have been programmed, a digital camera attached to the confocal microscope captures images at the specified focal planes. Imaging software can then compile all z-stacks to render the image in 3D.

Interpreting The Data

Once the image of the tubulin-GFP is generated, the localization of the protein can be studied in reference to the 3D structure of the yeast cell. Instead of just seeing the stretched line of tubulin-GFP usually captured by a fluorescence microscope, the confocal will allow you to see, for example, a triangular formation of tubulin pointing towards the bud neck region of the yeast cell (i.e, the junction between mother and daughter in a dividing cell).

This image provides additional information over that acquired by other microscopes. For example, a triangular tubulin pattern would clearly indicate an aberration. Also, since the tubulin is positioned toward the bud neck, this might mean that, although there is a defect in cell morphology and tubulin formation, the segregation of DNA by tubulin from mother to daughter is taking place as expected.

The Value of Confocal Microscopy

Confocal microscopy allows a more precise understanding of an organism’s cellular components. Construction of a 3D image permits the development of an advanced understanding of the specimen or protein of interest, so this innovative technology takes science one step further.

If you want to order confocal microscopy for your own study, check out the 25 facilities who offer the service on Science Exchange: https://www.scienceexchange.com/services/confocal-microscopy

About the author

Mamata Thapa works at JOVE: Journal of Visualized Experiments. She previously received her PhD in Molecular and Cell Biology from the University of Maryland, Baltimore County, and researched the role of ribosomal proteins in cell cycle progression and its implication in tumorgenesis, and is also a member of the Science Exchange Advocate program.

This is the first in a series of posts on scientific techniques, and how to use them in your research.

The brain is comprised of billions of individual neurons. Cells in the brain are densely packed with intermixed, often overlapping types. An excitatory neuron for instance may be surrounded by dozens of inhibitory interneurons and glia. So how can you tell which cell is which?

The classic approach has been to classify cells based on their shape, chemistry, or connectivity. However, this old tradition ignores the enormous diversity within a broad class of cells. These are important questions scientists are just now starting to explore with new tools. This post explores some of these newer techniques, including immunohistochemistry and RT-PCR.

The Need for More Accurate Techniques

Past scientific techniques focused on describing “principal neurons” and “secondary neurons” of a certain brain region, with descriptions based on physiology or anatomy alone. These data are now insufficient given our modern molecular tools, and even can be misleading. Moreover, heterogeneity within cell populations like “dopamine neurons” and new molecular techniques allow a far more accurate description of neurons based on their molecular properties [Ungless and Grace, 2012].

Questions regarding the identity of the cell recorded, what kind of neurotransmitter or peptide does it release, and which enzymes synthesize that chemical require even more precise techniques. Further queries regarding the types of receptors a cell expresses, how it differs from surrounding cells, are noteworthy as well.

A modern approach would take take into account the molecular profile of the neuron, and requires measurement of mRNA and protein expression.

Identifying Neurons with RT-PCR and Immunohistochemistry

Identifying the specific neurons recorded from brain slice preparations can be difficult. Their electrophysiological properties alone are insufficient to correctly identify a cell type. And unless you have a transgenic animal with expression of GFP or other fluorophore in a specific cell type, you have no basis for verifying what type of neuron you recorded.

A better experiment would begin with an acute slice preparation of brain tissue followed by whole-cell patch-clamp recording of individual neurons [Davie et al 2006]. After this characterization, the brain slices can be further processed through two popular methods for molecular characterization of neurons: single-cell reverse transcriptase polymerase chain reaction (RT-PCR) or Immunohistochemistry.

RT-PCR

Start with mRNA from single cells (via aspiration through recording pipette of living cell, or via laser capture microdissection from sectioned tissue), described in [Lin et al 2007]. A typical study employing these methods for the amygdala, a brain region responsible for fear learning, was done by [Sosulina et al 2010].

If you want to order this analysis for your own study, check out the 58 facilities who offer RT-PCR on Science Exchange: https://www.scienceexchange.com/services/real-time-qpcr

Immunohistochemistry

Immunohistochemistry (IHC) can also be used for this procedure, labeling tissue with antibodies for a molecule of interest, and visualizing with a fluorescent secondary antibody or a reactive dark precipitate stain.

At the beginning of this protocol, the electrophysiologist must perform recordings with a pipette filled with dye (e.g. 0.1% biocytin, or a fluorescent dye such as rhodamine dextran) for sufficient length of time to fill cell (at least 30 minutes).

After recording, brain slices are fixed overnight in paraformaldehyde (4%) and cyroprotected in sucrose (30%) for further sectioning (typically 30-40 microns) and staining.

If you want to order this analysis for your own study, check out the 27 facilities who offer IHC on Science Exchange: https://www.scienceexchange.com/services/immunohistochemistry

Troubleshooting Techniques

PCR: Contamination of mRNA from nearby cells will prevent an accurate identification of mRNA from the neuron of interest. To prevent this problem, all the buffers, solutions, and glass pipettes used for mRNA extraction must be kept sterile during procedure. The use of dissociated cells (via mechanical trituration or enzymatic digestion) may be superior for isolating individual neurons as compared to acute brain slices in which cells are much more densely packed [Hodne et al 2010] [Kay and Krupa 2001].

Immunohistochemistry: The challenge is finding a selective antibody at the appropriate concentration to get the best signal with low background staining. This is a matter of trial and error because multiple vendors manufacture antibodies of varying specificity (e.g. a monoclonal primary antibody is more selective than a polyclonal antibody) and several dilutions must be tested. The labeled protein of interest can be visualized with a fluorescent secondary antibody or dark precipitate staining such as DAB.

A second problem may be in recovering the dye-filled cell of interest after the staining procedure. There are many cutting and washing steps along the way, and a single section containing your dye-filled neuron can easily be lost. It is critical to recover all sections (only 30 microns thick) during these steps.

About the author

Ana Mrejeru (Twitter: Miss_Anamaria) is a postdoctoral scientist at the Columbia University Medical Center. Her focus of research is on healthcare technologies for brain disorders, building neuroscience apps for improved learning, and is also a member of the Science Exchange Advocate program.

Towards the aim of continually improving this process, we reached out to our user base earlier this year for their thoughts on outsourcing of experiments. Of the 160 users that responded to a 5-minute survey, we came upon some interesting insights into how research is currently outsourced and how Science Exchange could be optimized to help.

Below are some select figures from our survey, showing insights into why scientists choose to outsource, which services they tend to select, and the most important factor when selecting a service provider.

Lack of Equipment and Expertise Drive Outsourcing 

We asked our users prominently why they would choose to work with a service provider, rather than conduct an experiment themselves (respondents could select more than one option). Not surprisingly, the most common response had to do with a lack of resources.

89 respondents noted they would outsource a service because they lacked the equipment at their own lab. 82 respondents said they would work with an expert service provider because they lacked the expertise.

This matched closely with our own reasons for creating Science Exchange, which has been optimized around searching for specific equipment platforms such as Affymetrix RNA Microarray and Illumina Next Generation Sequencing.

Bioinformatics and Analysis are Commonly Outsourced 

Understanding that scientists tend to seek services they lack equipment or expertise for, we wanted to know which services they actually tend to outsource. Outside of regularly commoditized microarray and sequencing, we asked respondents to select from a range of possible service types (able to select more than one option again).

By far the most popular service selected was statistical analysis and bioinformatics (84 and 63 respondents, respectively). Also quite common were mass spectrometry (53 respondents) and microscopy (35 respondents).

One response we found interesting was clinical studies, which 49 respondents expressed interest in. While clinical studies are routinely conducted through outside experts, we were interested to find it take equal precedence as Mass Spectrometry and Microscopy services.

This was helpful for us to know, as though we already have 68 service providers bioinformatics and mass spectrometry, there was room for more clinical services. We look forward to bolstering these services in the coming year.

Location is the Most Important Factor

We lastly sought to understand for those respondents who routinely outsourced, what went into their choice of a service provider. Did they prioritize price, location, or testimonials?

The results surprised us. 68 respondents said the most important factor in selecting a vendor was the location, with a preference for local facilities (no one prioritized off-site vendors, understandably). The factors we though would take precedence, price and turn-around time, had 36 respondents and 29 responses respectively.

This was helpful for us to know, as we had been working on a new feature to help our users better find the services they needed by location. We recently launched a new ‘View by Map’ feature on our Search Results page, so users could find those facilities or labs in their own country or state.

Overall, the responses from the survey helped us to better understand our user’s needs, and re-affirm our vision for an efficient marketplace for scientific services. We look forward to continuing to optimize the platform this coming year.

This is a guest post from Aarthi Rao and Soma Ghoshal, program officers at the Center for Global Health R&D Policy Assessment

In the health R&D space, we are bombarded with jargon. When discussing collaborative approaches to health R&D, it is even more difficult to decipher tough terms. What’s the difference between open source and crowdsourcing? Are open and humanitarian licenses the same? How does open access work?

Beyond knowing the terms, it’s important for researchers and product developers to understand what value collaborative R&D approaches can add and how they differ. Sometimes posting a question online might just help you solve the problem you’ve been struggling with for months. Other times, it might make more sense to simply hire a top expert to tackle it for you.

To help bring precision to the language of collaborative health R&D and to layout different considerations around the various models of collaboration, we at the Center for Global Health R&D Policy Assessment just launched a simple web-based primer that organizes these concepts.

Center for Global Health R&D Policy Assessment

The Center for Global Health R&D Policy Assessment assesses new policy and financing ideas that have been put forward to advance the development of drugs, vaccines, and diagnostics for neglected diseases.

We’ve always felt that collaborative approaches to R&D could be a powerful tool for developing products for neglected disease. One of our earlier policy reports, “Open Source for Neglected Diseases: Magic Bullet or Mirage?”, explored the potential of open source models in health R&D and discussed how they depart from their IT predecessors.  The authors also laid out practical steps for moving the global health community toward a knowledge commons for neglected disease R&D. The report was well received, but it was clear that open source was just one part of a much larger picture.

Collaborative Health R&D Primer

Our new Collaborative Health R&D Primer builds upon this initial work and takes a broader look at collaborative approaches to health innovation. It aims to clarify the approaches to collaborative health R&D, review important considerations for each model, and highlight opportunities for moving the collaborative health R&D field forward.

It’s designed for scientists, product developers, funders, and the policy community, and the best way to experience the primer is to browse through its contents and find the opportunities and programs that are most relevant to you. It organizes existing models into tactics and tools for collaborative health R&D. It further differentiates them by whether they represent fully open collaboration or more targeted controlled collaboration. If one of the models catches your eye and feels promising for your own work, take a look at our “Questions to Consider.” These questions point out important considerations for anyone interested in adopting a particular approach.

This primer isn’t just for those carrying out R&D—it’s also designed to inform policymakers and funders. If you are interested in helping to grow the collaborative R&D field, our “Opportunities” page showcases how funders, scientists and the policy community can help scale up and strengthen collaborative R&D for health.

Here are ten of these opportunities to ponder—opportunities that we feel are feasible, not yet popular, and potentially catalytic.

Opportunities as a Health R&D Funder:

1. Adopt open collaboration policies and expand data sharing requirements for grantees. Fund the needed supporting infrastructure, including dedicated collaboration managers. (Example: Matt Todd interview.)
2. Start a demand-driven website to focus discussion currently occurring in many disparate forums, and to seed connections among experts and enthusiasts. Incorporate a group blog on collaborative health R&D, where the contributors are respected and insightful insiders in the community. (Example: NextBillion.)
3. Establish buy-in and joint commitments of high-profile leaders and institutions for initiatives tackling a well-defined set of collaborative R&D challenges. (Example: Grand Challenges in Global Health.)

Opportunities as a Scientist or Product Developer:

1. Start an online Q&A site specialized to collaborative health R&D. (Example: Stack Exchange.)
2. Devise better ways of dividing complex health R&D problems into manageable subproblems in order to enable the kind of mass-collaborative approach that has worked in many online systems. (Example: Gene Wiki.)
3. With engagement from industry, science, and funding stakeholders, advance a new networked initiative for pre-competitive collaboration to create new preventive and therapeutic health solutions. Incorporate realistic incentives for diverse parties to collaborate, including pharmaceutical companies, PDPs, research consortia, and individual scientists – and design this collaboration to result in new health solutions developed with less time and cost. (Example: Aled Edwards interview.)
4. Estimate benefits of collaborative health R&D for reducing risk, cost, and duplication of research and clinical trials. (Example: Arch2POCM Business Model.)

Opportunities as a Policy Maker or Researcher:

1. Provide a detailed profiling platform of collaborative initiatives for health R&D, summarizing which initiatives are active, what types of collaborators they are seeking, and what they and previous projects have achieved. Include a matchmaking service for scientists, funders, and citizens who are seeking to contribute to a collaborative initiative. (Example: Center for Health Market Innovations.)
2. Build a widely-used information utility that measures one’s achievement as part of a collaboration, thus providing more incentives to participate. Incorporate metrics which recognize collaboration, engagement, and impact, and which provide professional value for contributions to collaborative initiatives—for example, to allow aggregating one’s contributions into a cumulative “score” for use with granting agencies and promotion committees, similar to how publication metrics are used today. (Example: Leslie Chan interview.)
3. With strong engagement from end users, draw together research and practice to develop an accessible, periodically-updated, and practical collaborative health R&D toolkit or handbook – one suggesting where and how to apply particular collaborative approaches. (Example: IP Handbook.)

Although the Primer is in its pilot stages, we hope it is a useful and practical tool for those interested in collaborative R&D. In addition, the Primer is looking for an organization that wishes to evolve the site and transform it into a full-fledged online community for collaborative health R&D—one providing ongoing advice, tools, thought leadership, and coordination to the biomedical community.

About the author

Aarthi Rao joined the Results for Development team in June 2009. She has worked across various projects including the Ministerial Leadership Initiative, the Center for Global Health R&D Policy Assessment, and the Health Financing Task Force. She is now helping to lead a study of the biomedical innovation system in India and assessing its role in advancing global health technologies. Ms. Rao has worked in both India and Nepal in addition to U.S.-based non-profit organizations. She holds a B.A. in Public Health from the Johns Hopkins University where she studied Public Health and International Development.

Science is often considered a rich country industry.  It requires large investments in expensive and unique buildings, educational systems to produce scientists that can perform cutting-edge research, and infrastructure to deliver costly reagents in a time efficient manner.

Although some of the best science still occurs in developed countries like the United States, Europe, and parts of Asia, developing countries are quickly devoting resources towards science and technology, and subsequent commercialization of the research.

Here is a brief summary of a few science hotspots in the developing world.

India

One reason to promote science in the developing world is that the problems developing countries need to confront are often different than the health problems in developed countries.  In the United States a majority of research is focused on cancer, diabetes, cardiac health, and stem cells.  In many parts of the world, people die from simple bacterial infections or malnutrition long before cancer has an ability to develop.  Large American pharmaceutical companies have little incentive to create drugs for the world’s poor, but India is trying to achieve some of their immediate scientific goals, like eradication of tuberculosis and improved monsoon prediction, with increased science funding.

The Prime Minister of India, Manmohan Singh, is trying to double R&D expenditures to 2% of GDP by 2017, as well as creative incentives for private investment in the sciences.  The government has also created the National Science and Engineering Research Board, modeled after the National Science Foundation in the United States, which aims to fund its first grants this year.  With a $1.2 billion budget over 5 years, it is likely to play an important role in supporting Indian research.

Like in the United States, many smart Indian students reject a career in science for other higher paying areas, like information technology.  The Indian government is attempting to lure talented students towards the sciences through grants for high school students.

Contributing to this lack of talent, India suffers from postdocs going abroad to study in the United States and Europe yet failing to return home to start labs in India.  To reverse the flow of scientists out of the country, the Indian government is trying to attract overseas talent with fellowships and the promise of a higher living standard as an assistant professor in India than in the United States.

Certainly there is much to be done towards improving biomedical research in India, including relieving the pressures of Indian bureaucracy, decreasing shipment times for reagents, and updating facilities, but India is on track to take advantage of its vast population to build a stronger scientific research community.

Brazil

One of the products Brazil is best known for is sugarcane, which uniquely positions Brazil to be heavily involved in ethanol and biofuel research and production.  Although ethanol production has recently faced difficulty including high prices for transportation and a failure of widespread adoption, Brazil remains an important testing ground for the latest biofuel-based technologies, such as experimenting with different crops and the possibility for cellulosic ethanol.

Furthermore, Brazil is investing in a burgeoning tech sector.  For example, Brazil’s national development bank BNDES (Banco Nacional do Desenvolvimento) started a fund called Criatec, which is a 100 million reais ($48 million) fund aimed at investing in technology startups in Brazil.  Although foreign investment firms are still a little hesitant to invest substantially in Brazilian startups, but that may change with the Criatec effort, highlighting a possible area of growth for innovation in South America.

To fuel the innovation, Brazil has recognized the need for more scientists.  Towards the goal of increasing the number of scientists, Brazil is heavily investing in education.  The Ciência sem Fronteiras (CsF) program, which is a unique hybrid of public and private money, offers scholarships to send Brazilian researchers abroad as well as incentives for researchers to return to Brazil, through visiting scientist programs. These efforts underscore Brazil’s attempts to become a startup hub of South America, but they’ll have some competition from another competitor in Chile.

Chile

Chile is the highest ranked South American country on the Innovation Capacity Index, which ranks countries by a number of factors that take into account the government infrastructure and environment, as well as human capital and R&D money.

Recently the Chilean government has undertaken vast efforts to turn Chile into the Silicon Valley of Latin America with its Startup Chile Incubator program designed to attract the world’s best entrepreneurship talent to build their companies in Chile.  Startup Chile tends to prefer ideas with global potential and they provide $40,000 USD in equity-free capital to help entrepreneurs start their companies.

Not only is the Chilean government investing in startups and technology, the population, especially scientists are demanding more support from the government for basic research.  A movement called More Science for Chile, started by a Chilean Ph.D. student, calls for the government to invest more in scientific research and develop independent government infrastructure to oversee the development of science in the country.

Science for development

The efforts by developing countries to encourage organic research communities described above highlight the intertwined relationship between government investment in science, citizen desire for science, and the commercialization of new technologies.

Increasingly, governments around the world, including the United States, are acutely aware that investment in science and technology (often in the form of startups) is a prerequisite for national economic development.  With the purposeful expansion of scientific hubs in the developing world, it is important to remember that science is truly a global endeavor.

About the author

Rachel Senturia is a postdoctoral researcher and biochemist at the University of California, Berkeley, where her research focuses on RNA-based technology for gene regulation in plants. She is also the founder of STEMsocks, a company focused on public science advocacy, and worked in the Office of Intellectual Property at UCLA.