Look@NanoSIMS (abbreviated as LANS) is a software tool for the analysis of NanoSIMS image data acquired by the Cameca NanoSIMS 50L instrument. Although the software itself is free, it is distributed as a Matlab code and thus requires a working installation of Matlab (proprietary software) to run.

The software is written and maintained by Lubos Polerecky (LP). The development started in 2008, at the time when LP worked at the Max-Planck Institute for Marine Microbiology in Bremen, Germany. Since 2013, LP continues with the development of the program as part of his permanent employment at Utrecht University in the Netherlands.

Although LANS has matured pretty well over the years, it may still contain bugs or lack features that you might find useful. If you experience problems, find a bug, or would like to have a new feature added to LANS, you can contact LP via email - he will be happy to work with you to fix them and improve the program. Contact detail: l (dot) polerecky (at) uu (dot) nl

Current version: 2023-08-03

1. Loading of secondary ion counts (SIC) image data (Cameca im files)

   • all planes and masses (default)
   • selected planes and masses
   • planes in blocks
   • merging multiple im files into one dataset
   • corrections for dead-time and QSA
   • compressed data (im.zip files, roughly 10% size of the original im files)
   • data previously processed and exported by LANS (mat)

2. Drift-correction and accumulation of planes

   • based on a specific mass and area within the image

3. Regions of interest (ROIs)

   • manual and semi-automated ROI definition
   • manual and semi-automated ROI classification (e.g., based on a logical expression)

4. Quantification and export of isotope and element ratios

   • ratios defined through an expression (e.g., 13C/12C, 13C/(12C+13C))
   • scatter plots of ROI-specific ratios (color-coded based on ROI classification)
   • ratio images (various colormaps, ROI outlines can be included, hue intensity can be modulated)
   • lateral and depth profiles (incl. depth variation along a lateral profile)
   • histograms
   • image overlays (combined into an RGB image or a 3D surface plot)
   • results exported as text and graphics

5. Statistical analysis of data in ROIs

   • comparison of ROIs
   • comparison of ROI classes
   • comparison of treatments or experimental time-points

6. Processing of multiple nanoSIMS datasets (aka "metafile processing")

   • scatter plots (interactive)
   • images and image overlays
   • statistical analysis of ROIs, ROI classes, and treatments
   • depth profiles in ROIs
   • automated reprocessing of previously processed datasets

7. Import of external (third-party) images (e.g., TEM, SEM, AFM, fluorescence)

   • image alignment done within LANS
   • resampling of NanoSIMS images to match the resolution of the external image

LANS manuals are available from this Dropbox folder.

Although the original manual (LANS-manual.pdf) is rather old (written in 2011), it is still the best starting point for you to learn about LANS. Once you have learned about the basic approaches described there, you can proceed by reading the following web-pages that describe extra features and functions of LANS:

• New features in LANS
• Good to know

There is also a possibility of contacting LP if you have questions about LANS, experience problems while running LANS, or wish to include new features in the software.

• For convenience, the compressed file containing the latest version of LANS is stored in this Dropbox folder. Click on the program folder and then download the file LANS-latest-src.zip.
• If you are already using LANS, updating it to the newest version is much easier: just enter lans_webupdate in the Matlab console.
• Of course, you can download LANS by pulling the source code from this repository; the complete source code is in the src folder.

1. Install Matlab.

   • LANS requires Matlab, version 2019b or newer (available from www.mathworks.com). Using the Matlab version 2019b is most recommended to ensure that all features of LANS work correctly.
   • When installing Matlab, you will need the core Matlab. Additionally, although Matlab comes with many toolboxes, you will only need these two: image processing and statistics and machine learning.
   • You will need a license to install and run Matlab. It may be that your institution has a site-license, thus it is useful to check whether this is the case (e.g., your university may have one for all students and academic staff).

2. Install LaTeX.

   • This software is required to enable export of graphical output as tagged PDF documents. This is a free software.
   • To install LaTeX, use one of the well-known LaTeX distributions for your operating system, as described on this website (e.g., texlive for Linux, MikTeX for Windows, MacTex for MacOS; note that the on-line LaTeX service, such as Overleaf, is insufficient).
   • To correctly integrate LaTeX with LANS, you will need the following executables and packages installed and working:
     • executables: epstopdf, pdflatex
     • packages: graphicx, geometry, hyperref

3. Install software for decompressing zip files.

   • This software is required to enable loading of compressed datasets (im.zip files) by LANS. This is a useful feature because im.zip files have roughly a 10-fold lower size than the original im files.
   • 7-Zip (freeware) is recommended for Windows.
   • unzip is available by default on Linux and MacOS systems.

4. Install and run LANS

   • Download LANS as described above.
   • Unzip LANS-latest-src.zip to a folder of your choice.
   • Start Matlab and set the current folder to the folder where you installed LANS.
   • Enter lookatnanosims in Matlab console. This should open the main LANS graphical user interface, as shown below. You can start from there, as explained in the manual.

Please include the following citation if you used LANS in your work.

• L. Polerecky, B. Adam, J. Milucka, N. Musat, T. Vagner, M. M. M. Kuypers (2012). Look@NanoSIMS – a tool for the analysis of nanoSIMS data in environmental microbiology. Environmental Microbiology 14 (4): 1009–1023. DOI:10.1111/j.1462-2920.2011.02681.x