Bright-field Microscopy Research Articles

Sex Dependent Comparative Study of Hematological Parameters and Blood Cell Characteristics of Three Ornamental Teleosts

Aquaculture is one of the rapidly increasing food production sectors in the world. Ornamental fish culture also plays a vital role. hematological parameters serve as a tool to indicate the health of the fish. The present research investigated to acquire basic information on the importance of the size of blood cells, morphology, and hematological parameters in teleost fishes of Devil cichlid (Amphilophus labiatus), Black moor (Carassius auratus), and Koi carp (Cyprinus rubrofuscus). Blood samples from the caudal vein of fish were collected. Standard protocols were used to analyze the hematological investigations such as RBC, WBC, PCV, HB, MCV, MCH, and MCHC. The morphological characteristics of the blood cells were examined using a bright field microscope. A diverse variety of blood cell measurements were executed using a stage and an ocular micrometer. The results showed significant differences between the male and female and also between the species. But the lymphocytes of male and female, C. rubrofusus exhibited no significant difference and the blood indices showed a significant difference of (p<0.05). Therefore, the current study provides baseline information on the hematology of A, labiatus, C. auratus, and C. rubrofuscus in the assessment of these species for proper maintenance and welfare.

Dual-information and large-scale structural color patterns by laser direct writing with a low-index tailored nanostructure array

Dielectric nanostructures are widely embraced in the field of structural color design due to their low-cost characteristics, enabling sub-micron scale color printing. However, challenges still exist in the selection of structures and image encryption. In this study, we propose a method for printing dual patterns using tailored scattering structures based on two-photon polymerization. We extensively analyze the color performance of each structure in zeroth-order diffraction under cross-polarized transmission and bright-field transmission illumination. By selecting appropriate structures based on their characteristics, we prepared full-color panels and successfully utilized these panels to print both color patterns and dual patterns, achieving multi-level control of color and information. Based on the above study, a large-sale color pattern with a hidden message in an area of 3.2 cm×2.4 cm is printed, which can be directly observed. Our results demonstrate a sustainable and eco-friendly approach to color preparation, offering innovative strategies and methods for the fields of color science and steganography for information security.

Pyroptosis in Endothelial Cells and Extracellular Vesicle Release in Atherosclerosis via NF-κB-Caspase-4/5-GSDM-D Pathway

Background: Pyroptosis, an inflammatory cell death, is involved in the progression of atherosclerosis. Pyroptosis in endothelial cells (ECs) and its underlying mechanisms in atherosclerosis are poorly understood. Here, we investigated the role of a caspase-4/5-NF-κB pathway in pyroptosis in palmitic acid (PA)-stimulated ECs and EVs as players in pyroptosis. Methods: Human umbilical vein endothelial cells (HUVECs) were cultured in an endothelial cell medium, treated with Ox-LDL, PA, caspase-4/5 inhibitor, NF-κB inhibitor, and sEV release inhibitor for 24 h, respectively. The cytotoxicity of PA was determined using an MTT assay, cell migration using a scratch-wound-healing assay, cell morphology using bright field microscopy, and lipid deposition using oil red O staining. The mRNA and protein expression of GSDM-D, CASP4, CASP5, NF-κB, NLRP3, IL-1β, and IL-18 were determined with RT-PCR and Western blot. Immunofluorescence was used to determine NLRP3 and ICAM-1 expressions. Extracellular vesicles (EVs) were isolated using an exosome isolation kit and were characterized by Western blot and scanning electron microscopy. Results: PA stimulation significantly changed the morphology of the HUVECs characterized by cell swelling, plasma membrane rupture, and increased LDH release, which are features of pyroptosis. PA significantly increased lipid accumulation and reduced cell migration. PA also triggered inflammation and endothelial dysfunction, as evidenced by NLRP3 activation, upregulation of ICAM-1 (endothelial activation marker), and pyroptotic markers (NLRP3, GSDM-D, IL-1β, IL-18). Inhibition of caspase-4/5 (Ac-FLTD-CMK) and NF-κB (trifluoroacetate salt (TFA)) resulted in a significant reduction in LDH release and expression of caspase-4/5, NF-κB, and gasdermin D (GSDM-D) in PA-treated HUVECs. Furthermore, GW4869, an exosome release inhibitor, markedly reduced LDH release in PA-stimulated HUVECs. EVs derived from PA-treated HUVECs exacerbated pyroptosis, as indicated by significantly increased LDH release and augmented expression of GSDM-D, NF-κB. Conclusions: The present study revealed that inflammatory, non-canonical caspase-4/5-NF-κB signaling may be one of the crucial mechanistic pathways associated with pyroptosis in ECs, and pyroptotic EVs facilitated pyroptosis in normal ECs during atherosclerosis.

Measuring Cell Dimensions in Fission Yeast Using Machine Learning.

In fission yeast (Schizosaccharomyces pombe), cell length is a crucial indicator of cell cycle progression. Microscopy screens that examine the effect of agents or genotypes suspected of altering genomic or metabolic stability and thus cell size are crucial for studying disruptions to cell cycle dynamics. This method is based on using an automated cell segmentation algorithm to measure S. pombe cells imaged by brightfield (BF) microscopy methods. PhotoPhenosizer (PP) is a machine learning-based tool designed for automated cell measuring and dimensional analysis of morphology frequency distributions. Integration of this method into large-scale pipelines for tracking cell dimension change streamlines morphological measurements, which facilitates the examination of cellular responses to genomic and metabolic stresses. In this protocol, we use PP to observe the effect of genomic instability on cell size dynamics over a 12-day chronological lifespan assay. Our results show that relative to wild-type cells, a replication stress mutant shows larger cells during chronological aging in excess glucose media. Our results are consistent with activation of checkpoints that regulate cell morphology in response to DNA damage. This method's application highlights the relevance of its incorporation in experimental routines that require large-scale image processing and its adoption by users with routine needs in S. pombe molecular research projects.

Deep-Learning-Based Approach in Cancer-Region Assessment from HER2-SISH Breast Histopathology Whole Slide Images.

Fluorescence in situ hybridization (FISH) is widely regarded as the gold standard for evaluating human epidermal growth factor receptor 2 (HER2) status in breast cancer; however, it poses challenges such as the need for specialized training and issues related to signal degradation from dye quenching. Silver-enhanced in situ hybridization (SISH) serves as an automated alternative, employing permanent staining suitable for bright-field microscopy. Determining HER2 status involves distinguishing between "Amplified" and "Non-Amplified" regions by assessing HER2 and centromere 17 (CEN17) signals in SISH-stained slides. This study is the first to leverage deep learning for classifying Normal, Amplified, and Non-Amplified regions within HER2-SISH whole slide images (WSIs), which are notably more complex to analyze compared to hematoxylin and eosin (H&E)-stained slides. Our proposed approach consists of a two-stage process: first, we evaluate deep-learning models on annotated image regions, and then we apply the most effective model to WSIs for regional identification and localization. Subsequently, pseudo-color maps representing each class are overlaid, and the WSIs are reconstructed with these mapped regions. Using a private dataset of HER2-SISH breast cancer slides digitized at 40× magnification, we achieved a patch-level classification accuracy of 99.9% and a generalization accuracy of 78.8% by applying transfer learning with a Vision Transformer (ViT) model. The robustness of the model was further evaluated through k-fold cross-validation, yielding an average performance accuracy of 98%, with metrics reported alongside 95% confidence intervals to ensure statistical reliability. This method shows significant promise for clinical applications, particularly in assessing HER2 expression status in HER2-SISH histopathology images. It provides an automated solution that can aid pathologists in efficiently identifying HER2-amplified regions, thus enhancing diagnostic outcomes for breast cancer treatment.

Dark-field super-oscillatory microscopy with high-pass super-oscillatory filters

Super-resolution imaging of transparent objects is particularly challenging due to the interference caused by background light. This interference can significantly degrade image quality by reducing contrast and obscuring fine details. In this work, high-pass super-oscillatory masks are designed to address this issue by filtering out the background light on the Fourier plane. The resolution of the corresponding super-oscillatory point-spread function is 0.66 times the diffraction limit, enabling the resolution of transparent objects with 67% transparency at sub-wavelength scales. Additionally, the high-pass super-oscillatory masks are designed for a 1080 × 1920 liquid-crystal spatial light modulator, making future experimental implementation straightforward. This facilitates easy switching between bright-field and dark-field super-oscillatory microscopy, broadening the range of application scenarios for the system.

Dose-efficient phase-contrast imaging of thick weak phase objects via OBF STEM using a pixelated detector.

Optimum bright-field scanning transmission electron microscopy (OBF STEM) is a recently developed low-dose imaging technique that uses a segmented or pixelated detector. While we previously reported that OBF STEM with a segmented detector has a higher efficiency than conventional STEM techniques such as annular bright field (ABF), the imaging efficiency is expected to be further improved by using a pixelated detector. In this study, we adopted a pixelated detector for the OBF technique and investigated the imaging characteristics. Because OBF imaging is based on the thick weak phase object approximation (tWPOA), a non-zero crystalline sample thickness is considered in addition to the conventional WPOA, where the pixelated OBF method can be regarded as the theoretical extension of single side band (SSB) ptychography. Thus, we compared these two techniques via signal-to-noise ratio transfer functions (SNRTFs), multi-slice image simulations, and experiments, showing how the OBF technique can improve dose efficiency from the conventional WPOA-based ptychographic imaging.

Single-shot quantitative differential phase contrast microscope using a single calcite beam displacer

This paper presents the development of a single-shot, partially spatially coherent quantitative differential phase contrast microscopy (Q-DPCM) system. The optical scheme comprises a polarizer, lenses, calcite beam displacer, and analyzer, which can be seamlessly integrated to an existing bright-field microscopy system, transforming it into a Q-DPCM system. It utilizes a partially spatially coherent light source, enabling single-shot quantitative differential phase recovery of the specimens with high spatial phase sensitivity. It generates highly sensitive quantitative differential phase images of the specimens along one direction, like a gradient light interference microscopy (GLIM) system, using only a single interferogram. First, we validated the differential phase measurement capability of the system through experiments on polystyrene spheres (diameter 5.2 µm) and HeLa cells. Next, the system is utilized to generate quantitative phase maps of human red blood cells using two orthogonal differential interferograms recorded at two orientations of the calcite beam displacer. Further, the Q-DPCM system is implemented for 1-h time-lapse live cell monitoring, revealing the dynamics of intracellular granules such as nucleolus and lipids in U2OS cells.

Quasi-visualizable detection of deep sub-wavelength defects in patterned wafers by breaking the optical form birefringence

Abstract In integrated circuit (IC) manufacturing, fast, nondestructive, and precise detection of defects in patterned wafers, realized by bright-field microscopy, is one of the critical factors for ensuring the final performance and yields of chips. With the critical dimensions of IC nanostructures continuing to shrink, directly imaging or classifying deep-subwavelength defects by bright-field microscopy is challenging due to the well-known diffraction barrier, the weak scattering effect, and the faint correlation between the scattering cross-section and the defect morphology. Herein, we propose an optical far-field inspection method based on the form-birefringence scattering imaging of the defective nanostructure, which can identify and classify various defects without requiring optical super-resolution. The technique is built upon the principle of breaking the optical form birefringence of the original periodic nanostructures by the defect perturbation under the anisotropic illumination modes, such as the orthogonally polarized plane waves, then combined with the high-order difference of far-field images. We validated the feasibility and effectiveness of the proposed method in detecting deep subwavelength defects through rigid vector imaging modeling and optical detection experiments of various defective nanostructures based on polarization microscopy. On this basis, an intelligent classification algorithm for typical patterned defects based on a dual-channel AlexNet neural network has been proposed, stabilizing the classification accuracy of λ/16-sized defects with highly similar features at more than 90%. The strong classification capability of the two-channel network on typical patterned defects can be attributed to the high-order difference image and its transverse gradient being used as the network’s input, which highlights the polarization modulation difference between different patterned defects more significantly than conventional bright-field microscopy results. This work will provide a new but easy-to-operate method for detecting and classifying deep-subwavelength defects in patterned wafers or photomasks, which thus endows current online inspection equipment with more missions in advanced IC manufacturing.

Flash chromatographic isolation of garcinol and isogarcinol from Garcinia indica Choisy (kokum) fruit and evaluation of their potential antibiofilm activity

The present study describes the isolation and separation of isogarcinol and garcinol from kokum fruit by flash chromatography using water (containing 0.1 % formic acid) and methanol mixed with acetonitrile (1:1) with UV detection at 254 nm and was characterised by HR-MS and NMR studies. These were further subjected to antimicrobial studies on Staphylococcus aureus FR1722 and Listeria monocytogenes Scott A by agar diffusion assay and broth microdilution method wherein the MIC (Minimum Inhibitory Concentration) of garcinol and isogarcinol were, 20 μg/mL and 50 μg/mL for S. aureus FR1722 and 50 μg/mL and 100 μg/mL for L. monocytogenes Scott A respectively. Further, studies on the control of biofilm growth were tested using MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H tetrazolium bromide) assay followed by Crystal Violet (CV) assay, which showed up to 80 % inhibition. In addition, the biofilm eradication as evaluated by bright field microscopy and the metabolic activity were also carried out against these bacterial strains and the experimental details are presented.

EGFR-TKIs induce acneiform rash and xerosis via Caspase-3/GSDME-mediated pyroptosis of keratinocytes and sebocytes

Skin toxicities are the most common adverse effects of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). While EGFR-TKIs induce pyroptosis in lung cancer cells through Gasdermin E (GSDME) activation, it is unknown whether they can similarly affect skin cells. In this study, we used immunohistochemistry to demonstrate that in acneiform rash, the N-terminus of GSDME (GSDME-N) is predominantly expressed in the basal layer of the follicular epithelium and sebocytes, while it is absent in the interfollicular epidermis. In contrast, in cases of xerosis or secondary eczematous rash, GSDME-N was significantly expressed in the basal layer of the interfollicular epidermis and weakly or partially positive in the follicular epithelium. Bright-field microscopy of HaCaT and SZ95 cells treated with afatinib revealed cell swelling and large bubble formation, while scanning electron microscopy showed a reduction in microvilli and membrane pores formation. Transmission electron microscopy further revealed multiple membrane pores and decreased cytoplasmic density. Importantly, we found that GSDME is cleaved during afatinib-induced pyroptosis via caspase-3 activation. ELISA analysis further confirmed that afatinib-treated cells released elevated levels of HMGB1 and IL-1α. Meanwhile, inhibition of caspase-3 activity or knockdown of GSDME both suppressed afatinib-induced pyroptosis, while GSDME elimination did not affect caspase-3 activation. These results indicate that afatinib-induced pyroptosis in keratinocytes and sebocytes is mediated by the caspase-3/GSDME pathway. Our findings suggest that GSDME-dependent pyroptosis in HaCaT and SZ95 cells contributes to the development of acneiform rash and xerosis, highlighting the need for further investigation into the underlying mechanisms.

Performance of microsphere-assisted imaging in bright-field and dark-field microscopy.

In this work, we study the imaging performance of microsphere-assisted microscopy (MAM) using microspheres with different refractive indices and immersion conditions under both bright-field illumination (BFI) and dark-field illumination (DFI). The experimental results show that the position of the photonic nanojet of the microsphere plays an important role in MAM imaging. The contrast in imaging is affected by the reflection from the microsphere, the background signal without the microsphere, and the electric field on the substrate surface. In MAM, BaTiO3 glass microspheres achieve better imaging results under BFI when immersed in a polydimethylsiloxane (PDMS) film but are challenging to image under DFI. However, SiO2 and polystyrene microspheres exhibit improved imaging performance under both BFI and DFI with PDMS-covered semi-immersion, and the imaging contrast in DFI is superior to that in BFI under the same conditions. Besides, the Talbot effect is observed by MAM under DFI when imaging 300-nm-diameter hexagonally close-packed nanoparticle arrays. This work reveals the advantage of MAM under DFI in improving the contrast.

Label-free quantitative phase imaging and analysis of airborne pollen

Abstract Pollen morphology, involving the physical characteristics of pollen grains from seed plants during reproduction, plays an important role in plant biology, ecology, and evolution. High pollen concentrations in the air can degrade air quality and exacerbate respiratory conditions such as asthma. Understanding pollen morphology and its implications for air quality is significant for mitigating respiratory health risks. Conventionally, fluorescence microscopy is used for pollen imaging, but photobleaching, quenching, and phototoxicity affect the surface morphology and do not provide quantitative data on the pollen grains. For this study, we used bright field (BF) imaging and quantitative phase imaging (QPI), a label-free interferometric microscopy method, to look at differences in the shape of pollen. BF imaging provides information about the shape and size of the different pollens but has a limitation of low contrast. To obtain high-contrast images and quantitative data on the pollen grains without any exogenous agents, we employed QPI and BF imaging in the present study. QPI enables the extraction of detailed information regarding the cell wall, aperture, and thickness of pollen while also maintaining their natural state without the need for chemical treatments. In the present work, we sampled the ambient air from May 2023 to January 2024 on the IIT Delhi campus. Subsequently, QPI and BF imaging have been done for pollen identification and phase analysis of arboreal and non-arboreal pollen. Further, by utilizing the information obtained from BF microscopy and QPI, different species of pollen have been identified, and a pollen calendar has been prepared for exhibiting pollen season throughout the year. To the best of the authors’ knowledge, they have conducted the QPI of airborne pollen grains for the first time; this technique holds great potential for characterizing airborne pollens without the need for staining or sample preparation.

High contrast computational imaging with vortex phase diversity

Abstract Optical imaging systems employing spatially incoherent illumination are widely used in routine imaging applications like photography and bright-field microscopy. We describe an incoherent computational imaging system that uses an open aperture as well as a vortex phase aperture for recording the same scene. The two raw recorded images provide a diversity of information that can be effectively combined using the generalized Wiener filter. For the specific choice of aperture functions used here, the two corresponding generalized Wiener filters have nearly opposing polarity. This property leads to an effective computational PSF whose central lobe is $0.6$ times smaller compared to the diffraction-limited PSF and has a super-oscillatory character with side-lobes. The resultant computational imaging system provides images with significantly improved contrast. While our methodology requires two image records, the enhanced point spread function (PSF) with super-oscillatory character is obtained by employing bulk off-the-shelf optical elements instead of sub-wavelength structured masks. The vortex phase diversity concept along with computational image reconstructions are illustrated with both simulation and experimental data. The proposed imaging methodology may be used to improve imaging performance for wide ranging imaging systems without changing their form factor.

The Clinical Impact of Urinalysis Screened by Automated Microscopy Compared to Reference Manual Analysis

Introduction: Clinical laboratories have replaced conventional manual urine microscopy with automated urinalysis; however, concerns persist regarding its validity in detecting specific elements of urinary sediment crucial for evaluating kidney diseases. This study aimed to assess the accuracy of urinary sediment analysis performed by a large hospital laboratory compared to a standardized microscopic review, focusing on patients both with and without kidney disease. Methods: Urine samples were randomly selected from routine laboratory specimens at a university hospital. Laboratory analysis was performed using LabUmat 2 and Urised 3 PRO equipment (Abbott Diagnostics). In the automated analysis for sediment examination, technicians have the option to reclassify urinary sediment elements as necessary and, if warranted, conduct manual microscopic evaluations to validate findings. The laboratory’s analysis was compared with a “reference” analysis, which was double-blinded and conducted by two experienced technicians using bright-field and phase-contrast microscopy. Results: 503 samples were selected, with 52.3% originating from nephrology outpatient clinic patients. Overall agreement between the laboratory results and the reference analysis was 42.1%. The sensitivity (SN) of the laboratory examination for detecting pathological casts, lipiduria, and renal tubular epithelial cells was low (<50%), while specificity (SP) was high (>98%). However, for hyaline casts (SN: 50.4%; SP: 80.9%) and dysmorphic red blood cells (SN: 62.3%; SP: 96.2%), accuracy was intermediate. Performance was better for hematuria (SN: 86.1%; SP: 82.3%; intraclass correlation coefficient [ICC]: 0.703; R: 0.828) and leukocyturia (SN: 84.9%; SP: 95.1%; ICC: 0.807; R: 0.861). In patients with kidney disease (N = 248) and in samples manually reviewed by the laboratory (N = 115), accuracy for each urinary element was comparable to the overall sample findings. However, when assessing the ability to identify elements suggestive of nephropathy, only samples manually reviewed by the laboratory showed statistically similar results to those obtained by the reference analysis (p = 0.503, McNemar’s test). Conclusion: Employing automated urinalysis seems to be accurate for detecting hematuria and leukocyturia, as well as for screening patients without kidney diseases. However, clinical laboratories attending complex patients should employ personalized strategies to help decide when to perform manual review, thus avoiding misleading urinalysis results.

Nanoporous Submicron Gold Particles Enable Nanoparticle-Based Localization Optoacoustic Tomography (nanoLOT).

Localization optoacoustic tomography (LOT) has recently emerged as a transformative super-resolution technique breaking through the acoustic diffraction limit in deep-tissue optoacoustic (OA) imaging via individual localization and tracking of particles in the bloodstream. However, strong light absorption in red blood cells has previously restricted per-particle OA detection to relatively large microparticles, ≈5µm in diameter. Herein, it is demonstrated that submicron-sized porous gold nanoparticles, ≈600nm in diameter, can be individually detected for noninvasive super-resolution imaging with LOT. Ultra-high-speed bright-field microscopy revealed that these nanoparticles generate microscopic plasmonic vapor bubbles, significantly enhancing opto-acoustic energy conversion through a nano-to-micro size transformation. Comprehensive in vitro and in vivo tests further demonstrated the biocompatibility and biosafety of the particles. By reducing the detectable particle size by an order of magnitude, nanoLOT enables microangiographic imaging with a significantly reduced risk of embolisms from particle aggregation and opens new avenues to visualize how nanoparticles reach vascular and potentially extravascular targets. The performance of nanoLOT for non-invasive imaging of microvascular networks in the murine brain anticipates new insights into neurovascular coupling mechanisms and longitudinal microcirculatory changes associated with neurodegenerative diseases.

Portable, low-cost, desktop microscope

Light microscopes became essential tools in everyday lab work a long time ago. However, most commercial microscopes are costly, and they are often bulky and heavy. Therefore, microscopes are rarely seen in mobile applications or used by interested amateurs. Here, we present an affordable, portable single-lens microscope. It essentially uses a Raspberry Pi single-board computer, a camera, a touchscreen display, and an LED ring at its core. Apart from brightfield microscopy, contrast-enhancing methods by oblique, dark-field, and Rheinberg illumination are possible, as well. The microscope is ideal for applications that do not require high-end optical components. Due to its low cost and flexible use, it is also suitable for hands-on experiences of the fascinating world not visible by the human eye.

Recrystallization of amorphous AlNbCr coatings irradiated with chromium ions

Applying an AlNbCr layer on the surface of Zr alloys significantly enhances the alloy resistance to oxidation and high-temperature corrosion. However, the effects of irradiation on AlNbCr coating remain largely unexplored. This work investigates the microstructural evolution of Cr ion-irradiated AlNbCr coatings under varying temperatures, utilizing bright-field transmission electron microscopy (TEM) observations and electron diffraction pattern analyses. With increasing Cr ion irradiation dose, the coatings gradually transitioned from an initial amorphous to a crystalline state. The onset of crystallization occurred earlier at higher temperatures, indicating that the crystallization process was significantly influenced by temperature. Moreover, the dynamic crystallization process of the crystalline structure was also analyzed, as well as the different irradiation responses at the Near-Interface Area (NIA) and Far-Interface Area (FIA). These findings provide new insights for understanding and optimizing the performance of AlNbCr coatings in high-irradiation environments.

Machine Learning Accelerates Screening of Osteoclast Differentiation Inhibitors from Natural Products.

Natural products that inhibit osteoclast differentiation are promising therapeutic and preventive agents for osteoporosis. Conventionally, identifying osteoclast differentiation involves visual inspection of the microscope images of stained osteoclasts. In this study, a supervised machine learning model was developed to classify bright-field microscope images of osteoclasts without staining. The model was used to screen a compound library, and osteoclast differentiation inhibitors were identified, demonstrating the validity of our method. Next, an in-house library of fungal extracts was screened, and pinolidoxin was revealed as an inhibitor of osteoclast differentiation. Our machine learning method enabled accurate, objective, and high-throughput evaluation of osteoclast differentiation and efficient screening of the inhibitors from natural product extracts. This study represents the first machine learning classification developed to evaluate the inhibitory activity of natural products in osteoclast differentiation.

A-140 Reducing cell count bias with the GloCyte® Automated Cell Counter for CSF: an observational study at Loyola University Medical Center

Abstract Background Accurate STAT cerebrospinal fluid (CSF) cell counts are critical in supporting diagnoses of meningitis, malignancy, demyelinating disease, and hemorrhage. Limitations of automated analyzers to achieve acceptable linearity for the clinically relevant range has maintained manual CSF cell counting as the preferred method. Manual cell counting, performed with a hemocytometer and bright field microscope, is time-consuming, requires specialized skills and depends on human interpretation. This subjectivity inherently introduces the potential for non-random error in the enumeration of both total nucleated cells (TNC) and red blood cells in CSF by manual methods. The purpose of this study was to evaluate and compare the level of bias inherent in manual determination (TNC) in CSF as compared to the GloCyte Automated Cell Counter. Methods Result bias data for CSF specimens processed in the hematology lab at Loyola University Medical Center, a quaternary care 547-bed academic medical center in Maywood, IL, was analyzed for manual cell counting using a Neubauer-improved hemocytometer and GloCyte, an FDA-cleared cell counting device employing fluorescence technology to automate RBC and TNC counts in under 5 minutes, with linearity down to 0 cells/µL. Result bias was determined by defining the “expected result” for both GloCyte and hemocytometer as the initial cell count determined at a 1:5 dilution of a freshly-collected CSF sample and calculating the expected cell count for subsequent serial dilutions of 1:10, 1:20, 1:50, 1:100 for each method. The actual TNC count and the disparity of the actual result from the expected result was recorded as bias. Results Data are summarized below in the Table, and indicate a lower bias for GloCyte compared to manual counts across the range of dilutions. Conclusions This study demonstrates that GloCyte can be implemented as a means of effectively mitigating the reporting bias of CSF TNC counts performed with a Neubauer-improved hemocytometer.