- [Resource Hub](/) - [Field Guide](/?resource-type=field-guide#library) - The Suboptimal Resolution Problem: Why Your Cell Populations Look Merged # The Suboptimal Resolution Problem: Why Your Cell Populations Look Merged The Bottom Line Up Front: Using an aperture much larger than necessary reduces sizing resolution by creating smaller signal differences between cell sizes. Cell populations that should be distinguishable appear merged when the aperture is too large for the cells being measured. Target 15-40% of aperture diameter for optimal resolution. If you're counting lymphocytes on M+ or M cassettes because it works, you're sacrificing the sizing resolution that S+ or S cassettes would provide. WHICH CASSETTES FOR YOUR INSTRUMENT Moxi V and Moxi GO II use S+ and M+ cassettes. Moxi Z uses S and M cassettes. Same sizing principles, same selection logic — just match the cassette type to your instrument. All recommendations in this guide apply across the Moxi family. ## Understanding Sizing Resolution in Coulter Counting The Coulter principle measures cell volume through the resistance change when cells displace conductive fluid in an aperture. The absolute signal magnitude depends on volume displaced - but your ability to distinguish different sizes depends on the signal ratio between them. When cells occupy only a small fraction of the aperture, all cells - regardless of their actual size differences - produce similarly small signals. Resolution degrades even though you're still detecting cells. ### TL;DR - Resolution Optimization Essentials - Oversized apertures compress signal differences between cell sizes, reducing resolution - Target cells at 15-40% of aperture diameter for optimal sizing resolution - S+ or S cassettes for cells under 15 μm, M+ or M for cells over 15 μm - Merged populations, broad peaks, and lost subpopulations indicate resolution problems - Resolution matters beyond counting - size tracking, population identification, QC all depend on it ## Maximizing Your Sizing Resolution Learn why aperture size determines resolution, how to recognize poor resolution in your data, and applications where resolution is critical. The Physics: Why Aperture Size Determines Resolution The Coulter principle measures cell volume through the resistance change when cells displace conductive fluid in an aperture. The absolute signal magnitude depends on volume displaced - but your ability to distinguish different sizes depends on the signal ratio between them. When cells occupy only a small fraction of the aperture, all cells - regardless of their actual size differences - produce similarly small signals. A 6 μm lymphocyte and an 8 μm lymphocyte both generate weak signals in an M+ aperture, with the absolute difference between them being difficult to resolve. Target cells should ideally be 15 to 40% of the aperture diameter for optimal sizing resolution. In this range, cell volume differences translate to clearly distinguishable signal differences. Below this range, resolution degrades even though you're still detecting cells. Resolution vs. Detection: Understanding the Difference You can detect a cell without accurately resolving its size. This distinction is critical for understanding why cassette selection matters beyond simple counting. Detection: Did the instrument register that a cell passed through? This has a signal threshold - weak signals may not be detected at all, or may be confused with noise. Resolution: Given that you detected the cell, how accurately can you measure its size? This depends on the signal quality and the relative magnitude of size-based signal differences. An undersized cell in an oversized aperture may be detected (crossing the detection threshold) while providing poor resolution (weak signal with compressed size differences). You get a count, but your sizing data is degraded. Important Distinction If you only care about counts, resolution compromise might seem acceptable. But most applications depend on sizing data too - and resolution problems cascade through all downstream analysis. What Poor Resolution Looks Like in Data Resolution problems manifest in recognizable patterns: Merged populations: Two cell populations that should appear as distinct peaks instead appear as one broad distribution. The instrument detected all the cells, but couldn't resolve the size difference between populations. Artificially broad peaks: A homogeneous cell population appears to have wider size variance than it actually does. Poor resolution spreads the measurements around the true size. Lost subpopulations: Minor subpopulations that exist within your sample don't appear in the data. They're being counted but binned into the main population due to insufficient resolution. Poor CV for sizing: Coefficient of variation for size measurements is worse than expected for your cell type. This directly reflects the resolution limits of your aperture/cell combination. Applications Where Resolution Is Critical Some workflows depend heavily on sizing resolution: Cell size tracking over time: Monitoring cell size changes during culture requires resolution sufficient to detect gradual shifts. Poor resolution masks changes until they're dramatic. Population identification: Distinguishing cell types by size requires clear separation between size distributions. Poor resolution makes populations overlap that shouldn't. QC acceptance criteria: If your QC spec includes size parameters, resolution determines whether you can actually measure against those specs or just approximate them. Apoptosis detection: Apoptotic cells shrink before they die. Detecting this size change early requires resolution to see the shift from normal size ranges. Activation monitoring: Some cells enlarge upon activation. Tracking this response quantitatively needs resolution to measure the change accurately. Cassette Selection for Optimal Resolution The 15 μm boundary guides cassette selection for resolution as well as detection: Cells under 15 μm → S+ or S cassettes: Lymphocytes, PBMCs, Jurkat, K562. The smaller aperture ensures these cells occupy 15-40% of diameter, maximizing resolution. Cells over 15 μm → M+ or M cassettes: CHO, HEK293, HeLa, adherent cells. The larger aperture provides appropriate sizing without clogging while maintaining optimal cell-to-aperture ratio. Resolution Trade-Off Using M+ for small cells "because it works" sacrifices resolution for convenience. Using S+ for large cells risks clogging. Match cassette to cell size, and resolution optimization comes automatically. ## Troubleshooting Guide Two cell types appear as one broad peak Solution: Likely resolution issue from mismatched cassette. Switch to size-appropriate cassette and re-run - if populations separate, aperture mismatch was hiding the distinction. Size CV worse than expected for homogeneous cell line Solution: Poor resolution inflates apparent size variance. S+ or S cassettes for small cells provide tighter distributions through better signal quality. Can't detect expected size changes over time Solution: Resolution may be insufficient to see gradual shifts. Optimize cassette selection for your cell type, then establish baseline with improved resolution to track changes. Subpopulations visible on other instruments don't appear Solution: Check cassette/cell size matching. Minor populations require resolution to separate from main peak - undersized cells in oversized apertures lose this capability. ## Frequently Asked Questions Why does aperture size affect sizing resolution? The Coulter principle measures volume by detecting resistance change when cells displace conductive fluid. Cells that are small relative to the aperture produce smaller resistance changes with proportionally smaller differences between sizes. When cells occupy 15-40% of aperture diameter, size differences produce clearly distinguishable signals. Below this range, resolution degrades. How do I maximize sizing resolution for my cells? Match your cassette to your cell size range. Target cells at 15-40% of aperture diameter for optimal sizing resolution. For cells under 15 micrometers, use S+ or S cassettes. For cells over 15 micrometers, use M+ or M cassettes. The correctly sized aperture maximizes the signal difference between cell sizes. What are the signs of poor sizing resolution? Poor resolution manifests as cell populations that should be distinguishable appearing merged into broad peaks, difficulty identifying subpopulations, loss of ability to track size changes over time, and size distributions that look compressed or have poor coefficient of variation. If switching cassettes reveals populations you couldn't see before, resolution was the issue. Can I use M+ cassettes for small cells if clogging isn't a concern? You can, but at the cost of sizing resolution. Small cells through large apertures generate weak signals with small differences between sizes. While you'll get counts, your ability to distinguish cell populations and track size changes will be compromised. For research requiring sizing data, S+ or S cassettes provide meaningfully better resolution for small cells. ### Key Takeaway Resolution isn't automatic - it requires aperture optimization. Cell populations that should be distinct appear merged when apertures are oversized for the cells being measured. Target 15-40% of aperture diameter by selecting the cassette that matches your cell size. Every measurement you make includes sizing data; cassette selection determines whether that data has the resolution to be useful or is just approximation. [Back to all resources](/#library) ## Similar resources [Field Guide](/resources/04-coincidence-artifact/) Moxi GO II Moxi V Moxi Z 2026 ### The Coincidence Artifact: When Two Cells Count as One Coincidence - multiple cells in the aperture simultaneously - causes two cells to be counted as one, corrupting both count and size data. Optimal aperture utilization means targeting 15-40% of aperture diameter so cells generate strong signals while avoiding coincidence artifacts. Match your cassette to your cell size, stay within concentration guidelines, and coincidence becomes a non-issue. [Read Field Guide](/resources/04-coincidence-artifact/) [Field Guide](/resources/06-fifteen-micron-boundary/) Moxi GO II Moxi V Moxi Z 2026 ### The 15-Micrometer Decision: A Practical Cassette Selection Framework The 15 μm boundary provides clear selection criterion: cells under 15 micrometers use S+ cassettes, cells over 15 micrometers use M+ cassettes. This boundary isn't arbitrary - it's where each aperture size achieves the optimal 15-40% cell-to-aperture ratio for signal quality and sizing resolution. Know your cell size, follow the boundary, and cassette selection becomes automatic. [Read Field Guide](/resources/06-fifteen-micron-boundary/) [Field Guide](/resources/03-mixed-population-dilemma/) Moxi GO II Moxi V Moxi Z 2026 ### The Mixed Population Dilemma: When One Cassette Can't Capture Everything When your sample contains both small and large cells, no single cassette optimizes measurement for both populations. The solution: run the same sample twice - once with S+ to get accurate small cell counts, once with M+ to get accurate large cell counts. This dual-cassette workflow delivers accurate data for both populations rather than compromised data for everyone. [Read Field Guide](/resources/03-mixed-population-dilemma/) [Ebook](/resources/your-cell-count-is-a-safeguard/) Moxi GO II Moxi V Moxi Z 2026 ### Your Cell Count is a Safeguard The debris problem: Membrane fragments, aggregates, media residue, and lysed cell debris are present in virtually every biological preparation. How does your counting method distinguish a cell from a piece of debris? [Read Ebook](/resources/your-cell-count-is-a-safeguard/) [App Note](https://precisioncellsystems.com/wp-content/uploads/2026/02/Moxi-Applications-Compendium.pdf) Moxi GO II Moxi V Moxi Z 2026 ### Applications Compendium Scientists are concerned with speed, accuracy, and convenience, and those running the lab and industries are concerned with the cost typically associated with high-performing instruments. Our proprietary Coulter Principle-based system delivers on all three accounts, and is therefore a perfect fit for any cell biology benchtop. [Download App Note](https://precisioncellsystems.com/wp-content/uploads/2026/02/Moxi-Applications-Compendium.pdf) [Field Guide](/resources/01-optimization-burden/) Moxi GO II Moxi V 2026 ### The Optimization Burden: Hours Wasted on Viability Protocol Development Every hour spent optimizing viability dye concentrations is an hour not spent on your actual experiments. It's optimized for use - that's the important thing. You don't have to optimize it as a customer. Pre-optimized viability reagents eliminate the titration experiments, the incubation testing, the cell-type-specific protocol development. Why spend time optimizing when validated performance is available from the first use? [Read Field Guide](/resources/01-optimization-burden/) [Field Guide](/resources/02-unknown-product/) Moxi GO II Moxi V 2026 ### The Unknown Product: Most Moxi Users Don't Know This Exists Most of the issue with viability reagents is that most people don't even know they exist. If you're running viability assays on Moxi V or Moxi GO II with generic dyes you optimized yourself, there's a better option you may not have heard about: pre-optimized, ready-to-use viability reagents designed specifically for your instrument. Now you know. [Read Field Guide](/resources/02-unknown-product/) [Field Guide](/resources/04-protocol-hunt/) Moxi GO II Moxi V 2026 ### The Protocol Hunt: Searching for Methods That Already Exist Searching for viability protocols, adapting literature methods, trial-and-error until something works - this is time you don't need to spend. The user manual is designed to be super easy. Concentration-based instructions tell you exactly what to do: put X amount of viability reagent and put X amount of sample, incubate and go. No protocol hunting required. [Read Field Guide](/resources/04-protocol-hunt/) [Field Guide](/resources/05-diy-mentality/) Moxi GO II Moxi V 2026 ### The DIY Mentality: When Making Your Own Viability Reagent No Longer Makes Sense That's why people - including me - just buy premixed gel loading dye and don't make my own from powder like my PI wanted me to. The same logic applies to viability reagents. Buy the damn gels rather than making them - consistency and data. When convenience and consistency matter more than tradition, pre-made beats DIY. [Read Field Guide](/resources/05-diy-mentality/) [Field Guide](/resources/06-batch-consistency/) Moxi GO II Moxi V 2026 ### Viability Reagent Batch-to-Batch Consistency: Why Your Results Vary Over Time When you make your own viability reagents, every batch is different. When you buy pre-optimized reagents with QC'd lot consistency, every lot performs the same. Long-term experiments need long-term consistency - and that consistency comes from manufacturing quality control, not from hoping your technique stays identical over months of work. [Read Field Guide](/resources/06-batch-consistency/) [Field Guide](/resources/07-til-immune-killing-optimization/) Moxi GO II Moxi V Moxi Z 2026 ### TIL Counting and Immune Cell Killing: Dual-Cassette Optimization Guide TIL counting and immune cell killing assays are immediate applications for dual-cassette workflows. Cancer cells are large, T cells are small - no single cassette optimizes both. Run S+ for accurate T cell counts, M+ for accurate tumor/target counts. The extra run takes minutes but delivers publication-quality E:T ratios and killing percentages. [Read Field Guide](/resources/07-til-immune-killing-optimization/) [Field Guide](/resources/07-training-new-users/) Moxi GO II Moxi V 2026 ### Training New Users: Why Pre-Optimized Reagents Simplify Onboarding New lab members need to generate valid data quickly. Teaching protocol optimization takes weeks. Teaching protocol execution takes minutes. The user manual is designed to be super easy - put X amount of viability reagent, put X amount of sample, incubate and go. When reagents are pre-optimized, training focuses on execution, not development. [Read Field Guide](/resources/07-training-new-users/)