Nanolive EVE ANALYTICS User Manual (Analysis & Translation)

Product: Nanolive EVE ANALYTICS (companion analytics software for 3D Cell Explorer)
Original manufacturer: Nanolive SA (Lausanne, Switzerland) — www.nanolive.ch
Structure: 11 chapters / 21 pages / 19 figures (17 selected)

1. What is it? 🤔

EVE ANALYTICS (EA) is Nanolive's digital staining analytics software for processing .xvol/.seg files output by 3D Cell Explorer. Core functions:

Cell segmentation (multi-threshold RI-based)
13 morphometric/quantitative metrics (Area, Perimeter, Compactness, Ellipticity, etc.)
Dry mass quantification (RI → dry mass conversion formula)
Batch analysis (image clustering + auto-grouping + sensitivity selection)
CSV/TIFF batch export (per-analysis metrics + MIPs + masks + overlays)

1.1 Relationship with 3D Cell Explorer / STEVE

Software	Stage	Role
3D Cell Explorer	Acquisition	Hardware — produces `.xvol` raw data
STEVE	Digital staining	Real-time — RI digital staining + interactive single-cell exploration during acquisition
EVE ANALYTICS (EA)	Batch analysis	Offline — large-scale automated morphometric/dry-mass quantification post-acquisition

Why need EA? STEVE is the artist's tool (view + stain); EA is the scientist's tool (batch process + statistics + export).

1.2 Workflow overview

.xvol raw data
    ↓
EA import → ANALYZE button → generates .seg file
    ↓
Settings page (select protocol + parameters + groups)
    ↓
Clustering (auto-group similar images) + preview build
    ↓
Sensitivity parameter selection
    ↓
Visualization page (review results + adjust groups + view metrics)
    ↓
Export (CSV + TIFF)

2. After acquisition — first step ▶️

Fig 1 — ANALYZE button location

Fig 1 — Find the ANALYZE button in STEVE/EA. Clicking it generates a .seg file (containing all data needed for analysis). This .seg file can be transferred to another PC for analysis (no need to bring raw data).

3. Settings page ⚙️

Fig 2 — Settings page: protocol selection + parameters

Fig 2 — Settings page has 6 core sections: ① analysis name (no special chars); ② protocol; ③ parameters; ④ cycle length/frequency; ⑤ acquisition groups (read-only here); ⑥ PLAYER tab preview. Only after filling ①②③ can you click GO TO PREVIEW.

3.1 Protocol & parameters (Table 1)

Protocol	Effect	Parameter	Use case
Standard analysis	Segment cells + extract morphometric/functional metrics	Compact/Discrete	Small/dense cells (RBCs, Dictyostelium)
		Spread/Extended	Most adherent cells (standard mammalian cell culture)

4. Image clustering 🔀

EA's core intelligent feature — automatic grouping of similar images.

4.1 Scientific background

To perform relevant quantification, capture cell signal with enough sensitivity to include all cell details; but not too much to exclude background.

EA guides single-cell segmentation via multi-threshold approach. User selects best sensitivity for each experiment.

Two-step process:

Clustering: group "similar" images (regardless of position/timepoint)
Sensitivity selection: tune each cluster independently

4.2 Clustering definition

"Similar" = similar refractive index (RI) signal on maximum intensity projection (MIP)
Purpose: ① optimize computation time; ② easier UX; ③ higher segmentation quality

5. Step 1: Clustering 🔢

Fig 4 — Clustering grouping example

Fig 4 — 4 image groups: 2 represent distribution extremes + 2 represent middle. Each cluster can be kept or discarded; software shows percentage of each group in total images.

5.1 3-cluster example

Fig 5a — Out of focus
Fig 5b — Biologically meaningful
Fig 5c — Artifact contamination

Fig 5 — Three typical clustering cases: 5a out of focus (discard) / 5b biologically meaningful (keep) / 5c artifact-contaminated (discard). User decides per group based on representativeness.

6. Preview page build ⏳

Fig 6 — Preview building

Fig 6 — After cluster selection, preview build starts showing estimated time remaining. Build time depends on acquisition file size + workstation compute power. 10×10 grid scan may take considerable time to provide fully reconstructed preview (hours).

7. Sensitivity parameter selection 🎚️

Fig 7/Fig 8 — Sensitivity parameter adjustment

Fig 7 (left) + Fig 8 (right) — Sensitivity parameter adjusters on preview page. If initial segmentation preview is unsatisfactory, click "refine" or "extend" buttons to dynamically adjust sensitivity value count. After sensitivity selection for each cluster, click START ANALYSIS. Fig 8 shows estimated analysis time.

8. Visualization page 📊

Fig 9 — Visualization page overview
Fig 10 — PLAYER tab

Fig 9 + Fig 10 — After analysis completion, enter visualization page with 3 operations: ① define analysis groups; ② visualize time-lapse + evaluate segmentation quality (Fig 10 PLAYER tab provides contrast/brightness/MIP mask transparency adjustment); ③ explore analysis results.

8.1 Analysis group definition

Analysis groups are independent of acquisition groups — to create different analysis groups, must first delete acquisition groups
Max 12 groups
3 ways to create groups: ① drag area to wells; ② double-click wells; ③ click "create a group" then click wells
Can edit groups (delete unwanted wells), can create non-adjacent well groups

8.2 PLAYER tab (Fig 10)

Contrast adjustment: change displayed RI image contrast (does not affect raw data)
Brightness adjustment: same
MIP mask overlay: change mask transparency

9. Metrics shown by EA 📐

EA's soul — 13 morphometric/quantitative/global metrics.

9.1 Metrics overview

Fig 12 — Metrics schematic in EA

Fig 12 — All metrics displayed in EA with formulas and parameter schematic: RI (MIP), Segmentation mask, Area, Perimeter, Mean squared distance, Bounding box, Principal axes.

9.2 13 metrics — complete definitions

Morphometric metrics

Metric	Unit	Definition
Area	μm²	ROI pixels × 0.04
Perimeter	μm	Total pixels × 0.2
Compactness	-	(mean squared distance to centroid)/Area (Fig 13)
Extent	-	Area / bounding box area (Fig 14)
Ellipticity	-	Ellipse focal distance / major axis length (Fig 15, 0=circle, 1=line segment)
Form factor (circularity)	-	(4π × Area) / Perimeter²

Quantitative metrics

Metric	Unit	Definition
Mean RI	-	Overall RI average
Average dry mass density	pg/μm³	Average dry mass estimate
Dry mass	pg	Total dry mass estimate
Granularity	-	RI variation at 5×5 pixel scale (reflects organelle organization)

Global metrics (per field of view)

Metric	Unit	Definition
Cell count	Number	Object count
Confluency	%	(Total detected object area) / (FoV area)
Total dry mass	pg	Total dry mass of detected objects

9.3 Geometric meaning of Compactness, Extent, Ellipticity

Fig 13 — Compactness geometric meaning

Fig 13 — Compactness = (mean squared distance to centroid)/Area. Computation: after cell segmentation (A), place a circle with same area at cell center (B), measure each pixel distance from mask perimeter to circle circumference (C), calculate mean squared distance and divide by circle area.

= 1 = round cell
higher = "spiky" cell (e.g. multi-axon neuron)

Fig 14 (Extent): pixel ratio inside bounding box that is also inside region. =1 round/linear; ≈0 spreading.

Fig 15 (Ellipticity): ellipse focal distance to major axis length ratio. 0=circle; 1=line segment. References ellipse with same second moment as segmented cell.

10. Dry mass measurement ⚖️

EA's exclusive capability — label-free dry mass quantification based on RI.

10.1 Physical principle

Dry mass = total content in cell excluding water (proteins, lipids, etc.). Holographic tomography-measured RI has direct relationship with dry mass (reference: P.A.Sandoz et al., PLOS, 2019).

10.2 Formula

Measured RI = water RI × [α × C + 1]
where C is dry mass (g/dL)

Reorganize:
C = [(Measured RI / 1.33) - 1] × (1.33 / 0.002)

Parameters:
  α = 0.002 / 1.33
  Water RI = 1.33

10.3 Three dry mass definitions

Metric	Use case
Dry mass	Single cell — dry mass content
Total dry mass	Whole group — sum of all cells' dry mass
Average dry mass density	Flat cells (use 20-layer -5~+15 narrow projection for mean projection approximation) — pg/μm³

11. Export all results 💾

Fig 16 — Export button

Fig 16 — EXPORT ALL RESULTS button (first click shows warning: "you have no export results yet" — ignore).

11.1 Default 4 file types exported

File type	Format	Description
MIP	TIFF stack	Max intensity projection per position
Mask	TIFF stack	Segmentation mask per analysis position
Overlay	TIFF stack	MIP + mask overlay
Metrics	CSV	Digital analysis results

11.2 3 CSV files per analysis run

CSV 1 — Cell metrics (sorted by well/cycle/cell index)

Cell area μm²
Cell compactness
Cell area %
Cell ellipticity
Cell perimeter μm
Mean RI
Cell circularity
Average dry mass density pg/μm³
Cell extent
Dry mass pg

CSV 2 — Cell metric statistics (sorted by well/cycle, with statistics)

Statistic	Meaning
Mean	Average
Standard deviation	Within-group dispersion
Coefficient of variation (CV)	SD/Mean (when Mean > 0)
2.5 / 25 / 75 / 97.5 quantiles	Distribution shape

Each metric calculates the above 4 statistics.

CSV 3 — Per-FoV metrics (sorted by well/cycle)

Cell count
Confluency %
Total Dry mass pg

12. Visualization page plot management buttons 🎨

Visualization page provides 8 plot management buttons:

#	Button	Function
①	Zoom	Select sub-range of current image (x and/or y)
②	PAN	Navigate on image (especially after zoom)
③	Zoom in / out	Auto-zoom
④	Reset Axes	Reset axes
⑤	Toggle Spike Lines	Report hover focus point position on axes
⑥	Download plot as png	Screenshot
⑦	Show legend	Show/hide legend
⑧	Show standard deviation	Show within-group dispersion info

13. FAQ ❓

5 common questions, official answers:

Q	A
Can I speed up analysis by selecting only some metrics?	No. Programming processes entire dataset.
If dataset is not fully reconstructed, can analysis run?	No. Dataset must be fully reconstructed.
Can I overwrite existing analysis results?	No. Restart creates a second analysis result (old is kept).
If .seg file is lost, can analysis be redone?	Yes. Recreate .seg from raw data.
Can same .xvol have two different analysis results?	Yes. Can save any number.

14. EVE ANALYTICS positioning in the 9X Bio portfolio 🎯

14.1 Three-product complementarity

Dimension	CelVivo ClinoStar	3D Cell Explorer + STEVE + EVE ANALYTICS
Principle	Rotating suspension culture	Holographic tomography + digital staining + batch analysis
Time dimension	Days-weeks	0.5 fps real-time + offline batch
Data readout	Spheroid morphology (visual/staining)	13 morphometric metrics + dry mass quantification (label-free)
Invasiveness	None	None (extremely low phototoxicity)

14.2 Typical scenarios

Drug screening + morphometric quantification: CelVivo culture spheroids → EVE ANALYTICS monitor post-dose morphology changes (label-free, no sectioning, batch analyze 13 metrics)
Cell QC: 3D Cell Explorer acquisition → EVE ANALYTICS outputs 13 metrics + dry mass (used as batch QC)
Dry mass quantification experiments: Direct EA; simpler than traditional qBSA (quantitative buoyant mass) / microscale interferometry

14.3 Sales Q&A

Customer question	Answer
"Need to label cells?"	No. RI-based label-free analysis.
"How many samples simultaneously?"	Depends on experiment design — max 12 analysis groups × any cycle count.
"Data format?"	CSV + TIFF. Direct to Excel/GraphPad Prism/ImageJ.
"Add custom metrics?"	No. EA has built-in 13 metrics, not customizable.
"Dry mass measurement accurate?"	Based on P.A.Sandoz 2019 PLOS validation, highly consistent with qBSA.
"Need STEVE?"	Yes — EA is STEVE's offline analytics extension, must acquire in STEVE + ANALYZE to generate .seg.
"Analysis speed?"	Depends on acquisition size + workstation compute (GPU-accelerated). 10×10 grid scan hours.
"Computer requirements?"	Same as 3D Cell Explorer (NVIDIA discrete 8GB is hard threshold).

15. Key resources 🔗

Nanolive official: http://nanolive.ch
Nanolive applications: http://nanolive.ch/applications
Dry mass formula reference: P.A.Sandoz et al., PLOS, 2019
Customer registration + software download: https://www.nanolive.ch/register
EVE Analytics detailed tutorial: contact supplier

📥 Original PDF

📄 EVE ANALYTICS User Manual PDF (Chinese version, 21 pages, 1.4 MB)

Contact｜Li Dongwei (李东伟)
📞 18045130660
🌐 Website: https://www.biokingdom.top