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當您使用自動化設備為您計數細胞時,請相信它的精準度和您一樣—甚至更佳。準確度代表它會正確地進行細胞計數,而精確度則表示無論操作者是誰,它每次都會產生相同的實驗結果。
導入人工智慧。Countess 3(明視野)和 Countess 3 FL(明視野和螢光模式)自動細胞計數儀值得您的信任,因為它們運用深度學習神經網路演算法(deep-learning neural network algorithm)開發,每次皆能準確計數。該演算法由專業細胞生物學家,根據觀測數百個培養盤(包含數十種不同細胞類型和樣品)後特徵學習以進行細胞辨識。
如此打造出的細胞計數儀能像細胞生物學家一樣"思考",即便是外周邊血單核細胞(PBMC)、成團細胞以及樣品碎片等具有挑戰性的細胞樣品也能輕鬆勝任。在高解析度的Countess螢幕上,您可以看到正在計數的細胞與未計數的碎片。
與手動血球計數器相比,使用Countess 3儀器進行全自動細胞計數可以減少諸多因素造成的數據錯誤及變異,包括操作者主觀性與視覺疲勞、計數區域差異和具挑戰性的樣品。Countess 3細胞計數儀兼具手動細胞計數的準確性與流式細胞儀計數的精確度,且無需流式細胞術的費用或培訓。
Figure 1. Machine-learning algorithms result in highly accurate cell counts, comparable with flow cytometer counts. CHO-K1, HeLa, HEK293, Jurkat, and human PBMCs (across a range of sizes) were counted using the Attune NxT Flow Cytometer (purple bars), a Countess 3 FL Automated Cell Counter (red bars), and a hemocytometer and microscope (manual counting, gray bars). The Countess 3 FL instrument and hemocytometer bars represent an average of 6 independent counts and are highly consistent. Error bars (standard deviation for the counts) are wider for manual counts than for Countess 3 counts or flow cytometry.
Figure 2. User variability decreased when using Countess 3 Automated Cell Counter compared to counting with a hemocytometer. A single sample of CHO K1, HeLa, HEK293, Jurkat, and PCMC cells were counted by three different operators using a Countess 3 Cell Counter and then manually with a hemocytomer and microscope. The user-to-user variability when using a hemocytometer is much higher, 20–50% standard deviation, than when using a Countess 3 cell counter, 10% or lower standard deviation.
Figure 3. Accuracy and precision in the same instrument. Seven cell types were stained and counted using the same protocols and reagents, in triplicate, on the same instrument with both technical and biological replicates. The low coefficient of variation (CV) for technical replicates (<2%) indicates high measurement precision when the same slide is counted repeatedly. In contrast, CVs of ~11% for biological replicates of the same sample reflect variability introduced during sample handling and preparation, including pipetting inconsistency, incomplete mixing, and changes in cell viability between measurements.
Figure 4. Accuracy and precision between instruments. Seven cell types were stained and counted using the same protocols and colorimetric reagents and analyzed on three different instruments. The coefficient of variation (CV) of ~5% across instruments indicates a high degree of precision between instruments. Minor variability arises because each instrument captures slightly different fields of view on the same slide as shown in the images. Overlapping regions (red box) and identical cells (red arrows) are shown for reference, while non-overlapping areas contribute to small differences in total cell counts and resulting concentration.
Time spent in the cell culture lab is precious. Countess 3 automated cell counters produce results in less than 30 seconds, allowing you to get in and out quickly with minimal training. With rapid capture, auto-lighting, autofocus, and autosave, you simply prepare the slide, enable Rapid Capture and Autosave, and insert the slide. The instrument does the rest automatically: illuminate, focus, and count. When viability stains such as SafeCount Cell Viability Stain are used, Countess 3 automated cell counters automatically report viability and concentration results as well.
In addition to speed, Countess 3 automated cell counters streamline the process of cell counting, eliminating many of the tedious steps associated with manual cell counting, including lighting and focus adjustments, calculating cell concentrations, and preparing reports. The time saved can mount quickly. If your lab counts five slides per day, you can save 10–15 hours per month (depending on the choice of slides). If you count 25 slides per day, you can save 50–75 hours.
For low-throughput users (using 5 slides per day), consider the Countess Reusable Slide to save 7.2 kg of waste per year compared to the disposable slides used with other automated cell counters.
| Step 1 | Step 2 | Step 3 |
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| Mix equal parts sample with Trypan Blue or SafeCount Cell Viability Stain. Pipet 10 μL into a Countess disposable chamber slide or a reusable slide. | Enable “Rapid Capture” from the home screen. | Insert the slide into the instrument until it clicks into position. |
使用Countess 3或Countess 3 FL自動細胞計數儀,在明視野模式下進行細胞計數,簡單又輕鬆!您僅需準備好玻片,啟用快速影像擷取和自動儲存,然後插入玻片。儀器會自動完成其餘工作:光源亮度調節、對焦和計數。
The table below compares the hands-on steps required between a manual hemocytometer and Countess 3 automated cell counters. Countess instruments count cells faster in up to 50% fewer steps than manual counting with a hemocytometer. The time saved is significant when using the Countess Reusable Slide and even more dramatic when using Countess disposable slides.
| Countess 3 Automated Cell Counter | ||
| Manual counting hemocytometer & microscope |
...with Countess Reusable Slide |
...with Countess Cell Counting Chamber Slides |
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Manual hemocytometer counting often requires a tradeoff between speed and accuracy—counting a smaller area (fewer squares) saves time but can increase variability. The Countess 3 Automated Cell Counter eliminates this compromise by analyzing a larger area (equivalent to nearly four squares), reducing the effects of uneven cell distribution to improve accuracy. The Countess 3 Automated Cell Counter delivers fast, consistent results without sacrificing data quality.
Clumped cells can be challenging to count, manually or even with automated counters, because it’s difficult to discern borders between the cells. Samples that contain debris add further complexity to counting. Countess 3 automated cell counters automatically exclude debris from cell counts and their advanced algorithms can clearly identify cell boundaries within cell clumps, resulting in highly accurate cell counts.
Gating and histogram tools help ensure that only the cells of interest are included in the final count. By visualizing cell populations based on characteristics such as size, brightness, or circularity, users can quickly distinguish true cells from debris or other unwanted cells or debris. Interactive controls allow gating parameters to be adjusted in real time, with immediate visual feedback. This data-driven approach helps improve counting accuracy and increases confidence in cell counting results.
In addition to identifying singlets within cell clumps, Countess 3 automated cell counters detect these cell clusters to further measure the total percent aggregation within a sample. The on-screen display uniquely distinguishes aggregates with a different color compared to the singlet cell to reflect the identification, and brightfield mode provides visual confirmation of cells within each aggregate.
The Countess 3 software is designed to help scientists work more efficiently while maintaining confidence in their results. The Countess 3 FL Automated Cell Counter has a distinct counting algorithm to help ensure accuracy and confidence when counting in fluorescence (FL) mode.
The Countess 3 software also includes convenient, built-in pre-dilution and cell splitting calculators, which are especially convenient for helping save time and reducing errors in cell culture work.
An on-screen high/low concentration warning alerts users when a sample may fall outside the optimal counting range. This real-time feedback helps identify potential dilution issues before results are finalized, supporting more consistent counts and greater confidence in data quality, especially when working across varying sample concentrations.
Onboard counting protocols provide preconfigured starting points for common workflows, enabling faster setup and more consistent operation across users and workflows. While these preset protocols are designed to simplify routine counting and help provide a reliable starting point, they can be easily customized as needed. Because cell types and experimental conditions vary, these protocols should be used as guides rather than fixed rules. Users can fine-tune settings to best match their specific cells, helping ensure results remain optimized for each application.
Users can quickly create and save their own protocols by selecting the count mode and light cubes, then adjusting calculations and gating parameters as needed. The result is a simple, flexible workflow that supports consistent, reproducible cell counting across users and experiments.
| Step 1 | Step 2 | Step 3 |
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| Select Protocols button on the Home screen to open protocols menu. Assign a preset or saved protocol or create a new protocol. | When creating a new protocol, select which light cubes will be used, if there are any calculations needed, and where the data should be saved. | The protocol used will be seen in the upper left corner of the screen. If there is a change to the protocol that is not saved, an asterisk* will appear. |
Easily save and access your data with flexible export and connectivity options. Cell count results, data, and images can be stored to a USB drive or uploaded to the Thermo Fisher Connect cloud platform using the Wi-Fi dongle—so your data is available when and where you need it.
Export results in CSV (spreadsheet-ready) or FCS (flow cytometry standard) formats, and save images as TIFF, PNG, or JPG files. For convenient documentation and sharing, users can also generate a printable PDF report that combines results, images, and instrument settings.
Explore the comprehensive list of cell lines verified using Countess 3 automated cell counters for performance insights and suitability for your research needs.
Cell line |
Organism |
Cell type |
3T3L1 |
Mouse |
Embryo |
769P |
Human |
Kidney |
786-O |
Human |
Kidney |
8A3B.6 |
Mouse |
Lymphocyte |
A375 |
Human |
Epithelial |
A431 |
Human |
Epithelial |
A549 |
Human |
Lung |
A673 |
Human |
Muscle |
ACHN |
Human |
Kidney |
ADSC |
Human |
Adipose |
AML12 |
Mouse |
Liver |
AML193 |
Human |
Blood |
AN3CA |
Human |
Uterus |
ARH77 |
Human |
Blood |
AsPC-1Carcinoma |
Human |
Pancreas |
B16F10 |
Mouse |
Epithelial |
BeWo |
Human |
Placenta |
BJ |
Human |
Epithelial |
BM-MSC |
Human |
Bone |
BPAE |
Bovine |
Smooth Muscle |
BT-549 |
Human |
Breast |
C2C12 |
Mouse |
Muscle |
C8D1A |
Mouse |
Brain |
CACO2 |
Human |
Intestine |
CAKI |
Human |
Kidney |
CAPAN |
Human |
Pancreas |
CAR-T |
Human |
Blood |
CHOK1 |
Hamster |
Ovary |
Colo205 |
Human |
Intestine |
Cos7 |
Monkey |
Kidney |
Daudi |
Human |
Blood |
DU145 |
Human |
Prostate |
EB2 |
Human |
Lymph Node |
EL4 |
Mouse |
Lymphoblast |
F9 |
Mouse |
Testis |
FaDu |
Human |
Pharynx |
GTL16 |
Human |
Stomach |
H1299 |
Human |
Lung |
H1975 |
Human |
Lung |
H4 |
Human |
Epithelial |
H9 |
Human |
Lymphocyte |
H9C2 |
Rat |
Heart |
HaCat |
Human |
Epithelial |
HAEC |
Human |
Aortic Endothelium |
HCASM |
Human |
Smooth Muscle |
HCT116 |
Human |
Intestine |
HEK293 |
Human |
Kidney |
HEL 92.1.7 |
Human |
Bone Marrow |
HeLa |
Human |
Cervix |
HepG2 |
Human |
Liver |
HL60 |
Human |
Blood |
HMC3 |
Human |
Brain |
HMEC-1 |
Human |
Endothelial |
HSKSM |
Human |
Muscle |
HT1080 |
Human |
Epithelial |
HT29 |
Human |
Intestine |
hTERT-RPE1 |
Human |
Epithelial |
Huh7D12 |
Human |
Liver |
Human Hepatocyte |
Human |
Liver |
Human PBMC |
Human |
Blood |
Human Splenocyte |
Human |
Spleen |
HuT78 |
Human |
Lymphocyte |
Huvec |
Human |
Endothelial |
IM9 |
Human |
Blood |
I-MEF |
Mouse |
Embryo |
IMR32 |
Human |
Adrenal Gland |
IMR90 |
Human |
Lung |
JEKO1 |
Human |
Blood |
JM1 |
Human |
Blood |
Jurkat |
Human |
Blood |
K562 |
Human |
Bone Marrow |
KARPAS |
Human |
Blood |
KASUMI |
Human |
Blood |
KATO-III |
Human |
Stomach |
KG1 |
Human |
Bone Marrow |
L6 |
Rat |
Muscle |
LNCAP |
Human |
Prostate |
LOVO |
Human |
Intestine |
M1 |
Human |
Macrophage |
MCF10A |
Human |
Breast |
MCF-7 |
Human |
Breast |
MDCK |
Dog |
Kidney |
MIAPACA2 |
Human |
Pancreas |
MJ |
Human |
Blood |
MMM |
Human |
Macrophage |
MOLT4 |
Human |
Lymphoblast |
Mouse Hepatocyte |
Mouse |
Liver |
Mouse PBMC |
Mouse |
Blood |
Mouse Spleen/T-cell Mix |
Mouse |
Spleen & Blood |
MV411 |
Human |
Macrophage |
NCCIT |
Human |
Mediastinum |
NCI-H1573 |
Human |
Lung |
NEURO2A |
Mouse |
Brain |
NIH3T3 |
Mouse |
Embryo |
NK92 |
Human |
Blood |
NMUMG |
Mouse |
Breast |
NSC |
Human |
Neural Stem Cell |
NSCLC-146 |
Human |
Lung |
NTERA2 |
Human |
Testis |
OVCAR3 |
Human |
Ovary |
P388D1 |
Mouse |
Lymphoblast |
PANC1 |
Human |
Pancreas |
PBMC |
Human |
Blood |
PC12 |
Rat |
Brain |
PC3 |
Human |
Prostate |
P-MEF |
Mouse |
Embryo |
RAJI |
Human |
Lymphocyte |
Ramos |
Human |
Blood |
Rat Hepatocyte |
Rat |
Liver |
RAW |
Mouse |
Macrophage |
RD |
Human |
Muscle |
Reh |
Human |
Lymphoblast |
RPMI8226 |
Human |
Blood |
RSC96 |
Rat |
Schwann Cell |
RT4 |
Human |
Bladder |
SaOS2 |
Human |
Bone |
SCC15 |
Human |
Tongue |
SHSY5Y |
Human |
Bone Marrow |
SIHA |
Human |
Uterus |
SJSA1 |
Human |
Bone |
SKBR-3 |
Human |
Breast |
SKES-1 |
Human |
Bone |
SKMEL-28 |
Human |
Skin |
SKMEL31 |
Human |
Skin |
SKMEL-5 |
Human |
Skin |
SKNAS |
Human |
Bone Marrow |
SKNMC |
Human |
Neuroblastoma |
SKNSH |
Human |
Bone Marrow |
SKOV3 |
Human |
Ovary |
SNU5 |
Human |
Stomach |
SP2/O |
Mouse |
Spleen |
SW480 |
Human |
Intestine |
SW620 |
Human |
Intestine |
T47D |
Human |
Breast |
T98G |
Human |
Brain |
TE4 |
Mouse |
Lymphocyte |
TF-1 |
Human |
Bone Marrow |
THP-1 |
Human |
Macrophage |
U118MG |
Human |
Brain |
U251MG |
Human |
Brain |
U2OS |
Human |
Bone |
U87MG |
Human |
Brain |
U937 |
Human |
Blood |
For Research Use Only. Not for use in diagnostic procedures.
觸控式螢幕介面讓您更輕鬆!例如,在計數時設定"gates",則可根據細胞大小、亮度、圓度和/或螢光強度排除不想要的細胞。透過選定圖標後可在長條圖中查看您的細胞。當您上下滑動控制項以調整gate參數時,可以觀察到長條圖的即時變化。為方便起見,長條圖的底部顯示平均細胞大小(於明視野計數模式)或螢光強度(於螢光計數模式)。