Mesa Laboratories (MLAB) Total Non-Current Liabilities (2012 - 2026)
Mesa Laboratories (MLAB) reported Total Non-Current Liabilities of $227.84 million for fiscal Q4 2026 (quarter ended Mar 31, 2026), down 12.7% from $261.05 million a year earlier and down 3.9% from the prior quarter.
Mesa Laboratories (MLAB) Total Non-Current Liabilities (2012 - 2026) Analysis & Trends
Dating back to fiscal Q3 2013, Mesa Laboratories' Total Non-Current Liabilities record includes 52 quarters.
- Total Non-Current Liabilities has a five-year compound annual growth rate of 3.2% (FY2021 to FY2026).
- By fiscal year, Total Non-Current Liabilities came in at $261.05 million in FY2025 (-8.7%), $285.79 million in FY2024 (+9.0%), $262.2 million in FY2023 (-14.2%) and $305.64 million in FY2022 (+57.1%).
- The fiscal Q4 2026 figure ranks as the lowest quarterly Total Non-Current Liabilities since fiscal Q2 2022.
- Year over year, Total Non-Current Liabilities has now declined in each of the last six quarters, with an average decline of 5.8% over the last eight quarters.
- The high point for year-over-year Total Non-Current Liabilities in five years was fiscal Q4 2022 (growth of 57.1%); the low point was fiscal Q3 2025 (a decline of 17.4%).
- Per Business Quant data, the three fiscal quarters before Q4 2026 came in at $237.2 million (Q3 2026), $240.12 million (Q2 2026) and $250.59 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 55.95 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | - |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 33.25 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | - |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 40.46 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 21.28 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 17.56 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 2.57 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 23.92 Bn |
| 10 | Mesa Laboratories | 727.12 Mn | 620.10 Mn | 39.01 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 227.84 Mn |
| Dec 31, 2025 | 237.20 Mn |
| Sep 30, 2025 | 240.12 Mn |
| Jun 30, 2025 | 250.59 Mn |
| Mar 31, 2025 | 261.05 Mn |
| Dec 31, 2024 | 265.66 Mn |
| Sep 30, 2024 | 277.99 Mn |
| Jun 30, 2024 | 283.05 Mn |
| Mar 31, 2024 | 285.79 Mn |
| Dec 31, 2023 | 321.49 Mn |
| Sep 30, 2023 | 243.99 Mn |
| Jun 30, 2023 | 248.14 Mn |
| Mar 31, 2023 | 262.20 Mn |
| Dec 31, 2022 | 267.61 Mn |
| Sep 30, 2022 | 275.17 Mn |
| Jun 30, 2022 | 298.04 Mn |
| Mar 31, 2022 | 305.64 Mn |
| Dec 31, 2021 | 317.05 Mn |
| Sep 30, 2021 | 209.25 Mn |
| Jun 30, 2021 | 212.96 Mn |
Mesa Laboratories Total Non-Current Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=MLAB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "MLAB", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=MLAB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();