Automatic Cell Analyzer Research Articles

Molecular and Clinical Spectrum of Hemoglobin D: An Experience at a Tertiary Care Diagnostic Center

Objective: To determine the clinical and molecular pattern of Hemoglobin D in patients presenting at tertiary care hospital. Study Design: Cross-sectional study. Place and Duration of study: Department of Hematology, Armed Forces Institute of Pathology, Rawalpindi Pakistan, from Jul 2020 to Mar 2021. Methodology: An automated cell analyzer was used to determine the whole blood count and red cell indices. D-10 BIORAD HPLC was used for quantitative assessment of Hb A, Hb F, Hb D and Hb A2. Where D-10 BIORAD HPLC showed an abnormal Hb D, capillary electrophoresis was performed using Sebia Capillary 2 Flex Piercing. Chelex DNA Extraction method was used. Molecular analyses for the confirmation of homozygosity and heterozygosity were done using Polymerase Chain Reaction (PCR) amplification. The clinical symptoms of the patients such as anemia, jaundice, pallor, weakness, hepatomegaly and splenomegaly were also noted Results: Among 90 patients, Hemoglobin D trait was found in 78(80.4%) of the patients out of which HbD-Punjab was seen in 57(73%) and HbD-Iran was found in 21(27%). Compound Heterozygotes (HbD/β) was found in 17(17.5%) and Compound Homozygous HbD/D was found in 02 (2.1%). All HbD-Punjab and HbD-Iran traits patients were asymptomatic, and few clinical symptoms were found in Compound Heterozygotes (HbD/β) and Homozygous HbD/D. Conclusion: Collective clinical history records, full blood count and electrophoresis and molecular results allow for the conclusive detection of the variant of Hemoglobin D. More multicenter, organized and detailed studies with larger sample size are required to draw concrete conclusions.

Effect of CAT gene polymorphism on sensitivity of human lymphocytes to genotoxic effect of organochlorine pesticide in vitro

Introduction. Over recent decades, toxicogenetic studies have focused on the issues of genome instability under the action of genotoxicants, taking into account biomarkers of sensitivity. The question about the genotoxic potential of chlorpyrifos remains open, since both positive and negative effects have been revealed in various tests. The aim of the study is the investigation of sensitivity of donor peripheral blood lymphocytes to chlorpyrifos in vitro and evaluation of the contribution of polymorphism of antioxidant defense system genes (CAT (rs1001179), SOD2 (rs4880)) to the response of human cells to the action of genotoxicant. Materials and methods. The DNA damaging effect of chlorpyrifos was assessed on lymphocytes from fifty two donors using DNA-comet assay with metabolic activation (+S9) and without it (–S9). The study of cytotoxic effects of chlorpyrifos on human lymphocytes was carried out using an automatic fluorescent cell analyzer ADAMII LS. Results. Chlorpyrifos had a pronounced cytotoxic effect on lymphocytes in most donors in the absence of metabolic activation system. With increasing concentration of the pesticide in the medium and time of cultivation, the viability of lymphocytes decreased, and the proportion of cells in late apoptosis and necrosis increased. Positive genotoxic effects were found on the cells of 33 donors (-S9). In the presence of the S9, mild but statistically significant effects were detected only on cells from 2 donors. % DNA values in the comet tail after exposure to the pesticide varied for cells from different donors. In the absence of metabolic activation, a statistically significant increase in the level of DNA damage was found in cells of individuals with genotype AA (homozygote for the minor allele) for the CAT G262A catalase gene (rs1001179), compared with homozygote for the dominant GG allele. Limitations. The genotoxicity of chlorpyryfos was studied in vitro. Conclusion. The results of the study shown cytotoxic and genotoxic effects of chlorpyrifos. The sensitivity of lymphocytes from different donors to the pesticide was found to be significantly different. The association of the level of DNA damage under exposure of chlorpyrifos in vitro with the G262A polymorphism of the catalase gene was found. The research also confirms the possibility of using a model test-system with peripheral blood lymphocytes to assess the potential genetic risk for humans and to study the contribution of gene polymorphism to individual sensitivity to the action of genotoxicants.

Establishment and verification of reference intervals for blood cell analysis in extremely high altitude.

This study aimed to establish the reference intervals for complete blood count (CBC) in healthy adults at very high altitudes. This study recruited 4,863 healthy adults (3,598 males and 1,265 females) who received routine health check-ups at Ali District People's Hospital from January 2019 to December 2021 through the LIS system. CBC was detected by the XT-4000i automatic cell analyzer and statistically analyzed by SPSS 23.0 software (between-groups comparison, diagnostic concordance comparison). In addition, 20 health check samples were collected in 2022 to validate the established reference intervals. The CBC count showed a non-normal distribution in each item separately. The white blood cell (WBC), neutrophil (NEUT), lymphocyte (LYMPH), monocyte (MONO), eosinophil (EO), basophil (BASO), red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean hemoglobin content (MCH), and mean erythrocyte hemoglobin concentration (MCHC) levels of healthy adults were significantly different from the national clinical reference range (p < 0.05). There were significant differences between males and females in RBC, HGB, and HCT levels (p < 0.05). The new reference intervals were less consistent with the expert consensus CBC reference intervals (p < 0.05). Compared with the other reference intervals, the diagnostic value of the reference screening interval established was significantly higher in this study (p < 0.05). The reference range established is verified by 20 independent samples from 2022, and the results are acceptable. This study preliminarily established reference intervals for complete blood counts of healthy adults at high altitudes in the Ali region of Tibet to provide a reference point for understanding routine blood markers in permanent residents of high-altitude environments and illustrate the need for regular establishment of laboratory reference intervals on a regular basis.

Deep learning-based cell segmentation for rapid optical cytopathology of thyroid cancer

Fluorescence polarization (Fpol) imaging of methylene blue (MB) is a promising quantitative approach to thyroid cancer detection. Clinical translation of MB Fpol technology requires reduction of the data analysis time that can be achieved via deep learning-based automated cell segmentation with a 2D U-Net convolutional neural network. The model was trained and tested using images of pathologically diverse human thyroid cells and evaluated by comparing the number of cells selected, segmented areas, and Fpol values obtained using automated (AU) and manual (MA) data processing methods. Overall, the model segmented 15.8% more cells than the human operator. Differences in AU and MA segmented cell areas varied between − 55.2 and + 31.0%, whereas differences in Fpol values varied from − 20.7 and + 10.7%. No statistically significant differences between AU and MA derived Fpol data were observed. The largest differences in Fpol values correlated with greatest discrepancies in AU versus MA segmented cell areas. Time required for auto-processing was reduced to 10 s versus one hour required for MA data processing. Implementation of the automated cell analysis makes quantitative fluorescence polarization-based diagnosis clinically feasible.

Siamese deep learning video flow cytometry for automatic and label-free clinical cervical cancer cell analysis.

Automatic and label-free screening methods may help to reduce cervical cancer mortality rates, especially in developing regions. The latest advances of deep learning in the biomedical optics field provide a more automatic approach to solving clinical dilemmas. However, existing deep learning methods face challenges, such as the requirement of manually annotated training sets for clinical sample analysis. Here, we develop Siamese deep learning video flow cytometry for the analysis of clinical cervical cancer cell samples in a smear-free manner. High-content light scattering images of label-free single cells are obtained via the video flow cytometer. Siamese deep learning, a self-supervised method, is built to introduce cell lineage cells into an analysis of clinical cells, which utilizes generated similarity metrics as label annotations for clinical cells. Compared with other deep learning methods, Siamese deep learning achieves a higher accuracy of up to 87.11%, with about 5.62% improvement for label-free clinical cervical cancer cell classification. The Siamese deep learning video flow cytometry demonstrated here is promising for automatic, label-free analysis of many types of cells from clinical samples without cell smears.

Deep Learning-Based Microscopic Cell Detection using Inverse Distance Transform and Auxiliary Counting.

Microscopic cell detection is a challenging task due to significant inter-cell occlusions in dense clusters and diverse cell morphologies. This paper introduces a novel framework designed to enhance automated cell detection. The proposed approach integrates a deep learning model that produces an inverse distance transform-based detection map from the given image, accompanied by a secondary network designed to regress a cell density map from the same input. The inverse distance transform-based map effectively highlights each cell instance in the densely populated areas, while the density map accurately estimates the total cell count in the image. Then, a custom counting-aided cell center extraction strategy leverages the cell count obtained by integrating over the density map to refine the detection process, significantly reducing false responses and thereby boosting overall accuracy. The proposed framework demonstrated superior performance with F-scores of 96.93%, 91.21%, and 92.00% on the VGG, MBM, and ADI datasets, respectively, surpassing existing state-of-the-art methods. It also achieved the lowest distance error, further validating the effectiveness of the proposed approach. These results demonstrate significant potential for automated cell analysis in biomedical applications.

Erythropoietin inhibits neutrophil extracellular traps formation to ameliorate lung injury in a pneumonia model

Background: Severe pneumonia is a kind of disease that develops from lung inflammation, and new drugs are still required to treat the same. Erythropoietin (EPO) is widely used to treat anemia in patients. However, there are fewer studies on the role of EPO in neutrophil extracellular trappings (NETs) and pneumonia, and the mechanism is unclear.Objective: To investigate the possible effects of EPO on the formation of NETs and progression of pneumonia.Methods: Mice pneumonia model was induced by tracheal lipopolysaccharide (LPS) administration. Hematoxylin and eosin (H&amp;E) staining and automatic blood cell analysis were performed in this model to confirm the effects of EPO on lung injury. Flow cytometry, enzyme-linked immunosorbent serological assay, and immunostaining assay were conducted to detect theeffects of EPO on the inflammation as well as formation of NETs in mice. Immunoblot was further conducted to confirm the mechanism.Results: EPO alleviated LPS-induced lung injury. EPO reduced the release of inflammatory factors induced by LPS. In addition, EPO inhibited the formation of NETs. Mechanically, EPO inhibited tumor necrosis factor (TNF) receptor associated factor 2 (TRAF2)/nuclear factor kappa-B (NF-κB) activity in mouse models, and therefore suppressed the progression of pneumonia.

Erythropoietin inhibits neutrophil extracellular traps formation to ameliorate lung injury in a pneumonia model

Background: Severe pneumonia is a kind of disease that develops from lung inflammation, and new drugs are still required to treat the same. Erythropoietin (EPO) is widely used to treat anemia in patients. However, there are fewer studies on the role of EPO in neutrophil extracellular trappings (NETs) and pneumonia, and the mechanism is unclear. Objective: To investigate the possible effects of EPO on the formation of NETs and progression of pneumonia. Methods: Mice pneumonia model was induced by tracheal lipopolysaccharide (LPS) administration. Hematoxylin and eosin (H&amp;E) staining and automatic blood cell analysis were performed in this model to confirm the effects of EPO on lung injury. Flow cytometry, enzyme-linked immunosorbent serological assay, and immunostaining assay were conducted to detect the effects of EPO on the inflammation as well as formation of NETs in mice. Immunoblot was further conducted to confirm the mechanism. Results: EPO alleviated LPS-induced lung injury. EPO reduced the release of inflammatory factors induced by LPS. In addition, EPO inhibited the formation of NETs. Mechanically, EPO inhibited tumor necrosis factor (TNF) receptor associated factor 2 (TRAF2)/nuclear factor kappa-B (NF-κB) activity in mouse models, and therefore suppressed the progression of pneumonia. Conclusion: EPO inhibited formation of NETs to ameliorate lung injury in a pneumonia model, and could serve as a drug of pneumonia.

CORRELATION OF PERIPHERAL SMEAR WITH RBC INDICES AND RBC HISTOGRAM IN THE DIAGNOSIS OF ANAEMIA IN TERTIARY CARE CENTRE

Introduction : Anaemia is a decrease in the oxygen-carrying capacity of the blood. RBC histogram is a standard part and is routinely generated by automated cell analyzers. The well-known Coulter principle of counting and sizing the cells provides a basis for generating a histogram. The peripheral blood smear has been the main diagnostic aid in establishing the etiology of anaemia. Examining the blood lms routinely has facilitated the interpretation of various haematological disorders. Materials and Methods: The present study was carried out in the haematology laboratory of Kamineni Institute of Medical Sciences, Narketpally over a period of 3 months. EDTA blood samples from 100 anaemic patients were run in a six-part Sysmex analyzer and peripheral smears were prepared and examined. Results: A total of 100 patients with peripheral blood smear and RBC histogram from automated analyzer were studied. Out of 100 patients, 60% were females and 40% were males. Normocytic normochromic anaemia (50%) was the most commonly observed anaemia in the present study followed by microcytic hypochromic anaemia (40%). Most common histogram pattern observed was normal bellshaped curve. In normocytic normochromic anaemia (50%), the majority of the cases show a normal bell-shaped curve (37%) and the remaining 13% of cases showed broad-based curve. In microcytic hypochromic anaemia (40%) most common histogram pattern observed was shift to the left. In dimorphic anaemia (8%) histogram pattern observed was bimodal peak with a broad base. In macrocytic anaemia (2%) most commonly seen histogram pattern was shift to the right. Conclusion: Histogram plays an additional role with peripheral smear for diagnosing RBCs disorders. Even in the age of molecular analysis, the blood smear examination remains an important diagnostic tool.

Erythropoietin inhibits neutrophil extracellular traps formation to ameliorate lung injury in a pneumonia model.

Severe pneumonia is a kind of disease that develops from lung inflammation, and new drugs are still required to treat the same. Erythropoietin (EPO) is widely used to treat anemia in patients. However, there are fewer studies on the role of EPO in neutrophil extracellular trappings (NETs) and pneumonia, and the mechanism is unclear. To investigate the possible effects of EPO on the formation of NETs and progression of pneumonia. Mice pneumonia model was induced by tracheal lipopolysaccharide (LPS) administration. Hematoxylin and eosin (H&E) staining and automatic blood cell analysis were performed in this model to confirm the effects of EPO on lung injury. Flow cytometry, enzyme-linked immunosorbent serological assay, and immunostaining assay were conducted to detect the effects of EPO on the inflammation as well as formation of NETs in mice. Immunoblot was further conducted to confirm the mechanism. EPO alleviated LPS-induced lung injury. EPO reduced the release of inflammatory factors induced by LPS. In addition, EPO inhibited the formation of NETs. Mechanically, EPO inhibited tumor necrosis factor (TNF) receptor associated factor 2 (TRAF2)/nuclear factor kappa-B (NF-κB) activity in mouse models, and therefore suppressed the progression of pneumonia. EPO inhibited formation of NETs to ameliorate lung injury in a pneumonia model, and could serve as a drug of pneumonia.

Automated analysers underestimate atypical basophil count in myeloid neoplasms

Recent data suggest basophils can adopt an atypical appearance in myeloid disorders including myeloproliferative neoplasms (MPNs) and myeloproliferative/myelodysplastic disease. We hypothesized that automated analysers may not accurately quantitate basophils in myeloid neoplasms based on scatter properties. This study examined basophil counts and properties in myeloid disorders by automated cell analyser, manual differential, and flow cytometry. Patients with myeloid neoplasms and control patients with no myeloid disorder diagnosis at a tertiary care centre were identified. Basophil percentage was compared for automated analyser counts (Sysmex XN9000), manual differential, and flow cytometry. Basophil scatter properties in MPNs were examined using flow cytometry. Thirty-one patients with myeloid neoplasms were included: 58% were male, mean age was 70.2 (±20.7) years, 32% had a diagnosis of chronic myeloid leukaemia with the remaining patients divided among various other forms of myeloid disease (including: essential thrombocythemia, polycythemia vera, unclassifiable MPN, myelodysplastic syndromes). For these patients, mean basophil percentage by automated analyser was significantly lower than manual differential (2.7 ± 2.9 vs. 7.1 ± 4.6, respectively, p< 0.001). No significant difference was found between automated versus manual differential for basophils in control subjects (p= 0.373). For myeloid neoplasm patients, mean basophil percentage was not significantly different between manual differential and flow cytometry (p= 0.116); mean basophil percentage by automated analyser was significantly lower than flow cytometry (2.7 ± 2.9 vs. 5.3 ± 3.7, respectively, p= 0.003). Automated analysers underestimate basophil counts in patients with myeloid neoplasms. Manual differential and flow cytometry are recommended for more accurate quantitation and characterization of aberrant basophils.

Comparison of haemoglobin estimation of blood donors by specific gravity method, HemoCue method and automated haematology cell analyzer

Introduction: Pre-donation haemoglobin (Hb) screening is among the foremost test done on blood donors to determine whether an individual is fit to donate with the intention of preventing inadvertent donation from an anaemic donor. The aim of the study was to compare the efficacy of the three common Hb estimation methods, namely, copper sulphate (CuSO4) method, HemoCue photometer and automated cell counter in reporting the Hb levels of blood donors. Materials and Methods: CuSo4 specific gravity method, HemoCue and automated cell analyzer (Sysmex XN-550) were used to determine the Hb levels in blood samples of 500 donors. Descriptive statistics were used to analyse the demographic details of the donor. Kappa statistics were used to determine the level of agreement between the three methods of Hb estimation. Results: HemoCue was found to be more sensitive (86.21%), whereas CuSo4 (97.88%) was found to be more specific. Kappa agreement was good between CuSo4 and Sysmex XN-550 (0.703), whereas it was moderate between HemoCue and Sysmex XN-550 (0.458). Conclusions: The CuSO4 method is still viable for Hb estimation among blood donors. Thus, it can be utilised as the primary screening method; however, follow-up testing with HemoCue or automated cell analyzer can be done to minimise unnecessary deferrals and false acceptance.

Detection of nucleated red blood cells using the Mindray BC-6800Plus hematology analyzer: a clinical performance evaluation.

With the development of instrument technology, the functions and detection methods of automatic blood cell analyzers have become more complex. To ensure optimal clinical applicability, it is crucial to select an automatic blood cell analyzer with excellent clinical detection performance. This study evaluated the latest Mindray BC-6800Plus automatic blood cell analyzer and assessed its performance in the detection of nucleated red blood cells (NRBCs). A total of 490 clinical blood samples were used to assess the performance of the instrument, including parameters such as precision, linearity, conformity rate of manual microscopic examination, carryover, and limit of quantitation. The instrument showed a small carryover (≤0.02) and excellent linearity (R2≥0.9986). The reproducibility of the sample tests was satisfactory, and the coefficient of variation (CV) of the test results [0.98-1.72% and 0.62-6.97% for white blood cells (WBCs) and NRBCs, respectively] were significantly lower than that declared by the manufacturer (2.5% and 20% for WBCs and NRBCs, respectively). Thus, the BC-6800Plus satisfies the requirements of clinical testing. Two separate Mindray BC-6800Plus machines were tested and found to be in good agreement with each other and with manual microscopy methods. Furthermore, WBC and NRBC counts were highly consistent with results obtained using the XN-9100 blood analyzer. The Mindray BC-6800Plus is an excellent analyzer that can provide timely and accurate reports for clinical laboratory detection of NRBC.

HologLev: A Hybrid Magnetic Levitation Platform Integrated with Lensless Holographic Microscopy for Density-Based Cell Analysis.

In clinical practice, a variety of diagnostic applications require the identification of target cells. Density has been used as a physical marker to distinguish cell populations since metabolic activities could alter the cell densities. Magnetic levitation offers great promise for separating cells at the single cell level within heterogeneous populations with respect to cell densities. Traditional magnetic levitation platforms need bulky and precise optical microscopes to visualize levitated cells. Moreover, the evaluation process of cell densities is cumbersome, which also requires trained personnel for operation. In this work, we introduce a device (HologLev) as a fusion of the magnetic levitation principle and lensless digital inline holographic microscopy (LDIHM). LDIHM provides ease of use by getting rid of bulky and expensive optics. By placing an imaging sensor just beneath the microcapillary channel without any lenses, recorded holograms are processed for determining cell densities through a fully automated digital image processing scheme. The device costs less than $100 and has a compact design that can fit into a pocket. We perform viability tests on the device by levitating three different cell lines (MDA-MB-231, U937, D1 ORL UVA) and comparing them against their dead correspondents. We also tested the differentiation of mouse osteoblastic (7F2) cells by monitoring characteristic variations in their density. Last, the response of MDA-MB-231 cancer cells to a chemotherapy drug was demonstrated in our platform. HologLev provides cost-effective, label-free, fully automated cell analysis in a compact design that could be highly desirable for laboratory and point-of-care testing applications.

Plasma Cells Leukemia Masquerading as Lymphocyte-Monocyte Peak on Automated Cell Analyzer

Plasma Cells Leukemia Masquerading as Lymphocyte-Monocyte Peak on Automated Cell Analyzer

Discrimination and quantification of live/dead rat brain cells using a non-linear segmentation model.

The automatic cell analysis method is capable of segmenting the cells and can detect the number of live/dead cells present in the body. This study proposed a novel non-linear segmentation model (NSM) for the segmentation and quantification of live/dead cells present in the body. This work also reveals the aspects of electromagnetic radiation on the cell body. The bright images of the hippocampal CA3 region of the rat brain under the resolution of 60 × objective are used to analyze the effects called NISSL-stained dataset. The proposed non-linear segmentation model segments the foreground cells from the cell images based on the linear regression analysis. These foreground cells further get discriminated as live/dead cells and quantified using shape descriptors and geometric method, respectively. The proposed segmentation model is showing promising results (accuracy, 82.82%) in comparison with the existing renowned approaches. The counting analysis of live and dead cells using the proposed method is far better than the manual counts. Therefore, the proposed segmentation model and quantifying procedure is an amalgamated method for cell quantification that yields better segmentation results and provides pithy insights into the analysis of neuronal anomalies at a microscopic level. Graphical Abstract Resultant View of the overall proposed approach.

Correlation of Various Methods of Hematopoietic Progenitor Cell (HPC) Estimation with Standard Flowcytometric CD34 Enumeration

Background and Objectives: Enumeration of Hematopoietic Progenitor Cell (HPC) is vital to decide the Time To Initiate Harvest (TTIH) and Adequacy Of Harvest Dose (AOHD). Standard of care used for HPC enumeration is flowcytometric CD34+ enumeration, but it is expensive, time-consuming and requires skilled staff to perform the test. Alternatively, HPC-count by advanced automated cell analyzer is cheaper, quicker and easy-to-perform test. Our objective was to find correlation of HPC count with CD34+ enumeration in leukapheresis. Materials and Methods: An observational, prospective study was conducted in the year 2018-2019. A total of 126 samples were included in the study, the peripheral blood group comprised of 42 samples and apheresis group of 84 samples. The samples were simultaneously tested for CD34+ expression and complete blood count (CBC) which included the HPC count, WBC count, MNC count and IG (Immature Granulocyte) index and correlation analysis was performed with CD34 + flowcytometric count. The cut-off of peripheral blood HPC count for the target dose of 5*106 CD34+ cells/kg was established using Receiver Operator Curve. Results: The correlation coefficient (r) of HPC with CD34+ count was 0.617 and 0.699 for peripheral blood and apheresis sample respectively, which was statistically significant. The correlation with MNC, IG and WBC count was not very significant. A cut-off value of PB HPC was established to be 66 HPC/µL with a positive predictive value of 94.12%.The cost of CD34+ flow cytometric enumeration was six times that of HPC enumeration by analyzer. Conclusion: The HPC count is a cheaper, rapid and easy test and can be clinically applied to predict TTIH. Funding Statement: None. Declaration of Interests: None. Ethics Approval Statement: The study was approved by Institutional Review Board. (MICR-849/2018).

Abstract P3-01-18: Kinase D interacting substrate 220 (Kidins220) and disease progression of breast cancer, the role of heat shock protein90 (HSP90)

Abstract Background: Kidins220 (Kinase D Interacting Substrate 220) is a transmembrane scaffold protein and was initially found as the substrate of Protein Kinase D. It has several binding partners and plays an important role in neuronal activities and attribute to the occurrence of neuronal disease. Moreover, emerging evidence has revealed the involvement of Kidins220 in regulating cancer development including melanoma, neuroblastoma, and prostate cancer. Our current study investigated the role of Kidins220 in breast cancer and the biological implications on breast cancer cells. Method: A panel of human breast cancer cell lines were used in the biological studies. Kidin220 Knockdown cell model was established using lentivirus anti-Kidins220 shRNA and the knockdown of Kidins220 was verified in gene and protein levels. Cell matrix attachment and cell migration assay were determined using an automated cell analyser (ECIS). The growth of breast cancer cells was evaluated using colorimetric method. Human breast tumours (n=106) together with adjacent background tissues were collected immediately after surgery. Transcription level of Kidins220 and HSPs in the fresh tissues was determined using quantitative transcript analyses. Results: In the clinical cohort of breast cancer, an increase in expression of Kidins220 was found in tumour tissues in comparison with adjacent normal tissues. Patients with poor prognosis (NPI&amp;gt;5.4) had the lowest expression of Kidins220 compared with patients with good and moderate prognosis. Likewise, high grade tumours had markedly reduced level of Kidins220. Furthermore, patients remain disease free had the highest Kidins220 level when compared with those who had breast cancer-related incidence. Kaplan-Meier plot showed high level of Kidins220 was linked to longer survival. Our database also revealed that the levels of expression of Kidins200 were significantly correlated with that of HSP90A (Heat Shock Protein-90A) (r=0.37, p&amp;lt;0.001), but not HSP90B. Moreover, breast cancer cells (MDA MB-231 and MCF-7) after losing Kidins220 by way of knockdown showed an increase in cellular migration and cell matrix adhesion, with little changes in cell growth compared with control cells. In these cell based models, HSP90 inhibitor was found to affect Kidins220 mediated changes in matrix adhesion. It was also noteworthy that cells with Kidins220 knockdown had dramatically reduced expression of HSP90, particularly HSP90A. Conclusion: Kidins220 may act as a tumour suppressor in regulating the disease progression of breast cancer and has a correlation with the survival of patients with breast cancer. Kidins220 regulates the aggressive property including migration and cell matrix attachment of breast cancer with the involvement of HSP90A. Citation Format: Zhe Zhao, Tracey A. Martin, Johannes Benedikt, Shuo Cai, Lin Ye, Eleri Davies, Robert E Mansel, Wen G. Jiang. Kinase D interacting substrate 220 (Kidins220) and disease progression of breast cancer, the role of heat shock protein90 (HSP90) [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-01-18.

Abstract P2-07-01: Kidins220 (kinase D interacting substrate 220) has a connection with neutrotrophic related factors, BDNF and NGF, in human breast cancer

Abstract Background: Kidins220 (Kinase D Interacting Substrate 220) also known as ARMS (ankyrin repeat-rich membrane spanning) is a transmembrane protein that plays a significant role in neuronal development. It acts as the common downstream effector of neuronal signalling regulated by neurotrophin family including nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF). Expression abnormalities of Kidins220 have been identified in certain solid tumours, but the role played remains controversial. The present study aimed to examine the correlation between Kidins220 and BDNF, factor known to be aberrantly expressed in breast cancer cells (1,2), together with NGF and NGF receptor (BGFR). The involvement of Kidins220 in the chain event of cells response to BDNF, in particular the role played by phospholipase-gamma (PLC- γ) were also been determined. Method: Human breast cancer tissues were collected immediately after surgery. The transcription levels of Kidins220 and the neurotrophic factors and their receptors were determined using quantitative transcript analyses. The correlations between Kidins220 with BDNF, NGF, and NGFR were analysed against the clinical and pathological parameters in the clinical breast cancer cohort. Kidins220 knockdown cell models, using MDA MB-231 and MCF-7 cells, were created by employing anti-Kidins220 shRNA lentiviral technologies. Cell matrix attachment, cellular migration and cell growth were determined in breast cancer cells treated with BDNF and PLC- γ specific inhibitors and analysed using an automated cell analyser (ECIS) and crystal violet method, respectively. Result: The analyses of the clinical cohort demonstrated reduced expression of NGF and NGFR in high grade and node positive breast tumours, which is in contrast to the the reported pattern seen with BDNF expression. Furthermore, the expressions of NGF and NGFR were reduced in patients with poor prognosis and clinical outcomes. Interestingly, Kidins220 was found to have a significant negative correlation with BDNF (r=-0.429, p&amp;lt;0.001), but positive correlation with NGF (r=0.269, p&amp;lt;0.01) and NGFR (r=0.211, p&amp;lt;0.01). Knockdown of Kidins220 increased cellular migration in MDA-MB-231 and MCF-7 breast cells. In vitro, breast cancer cells responded to BDNF and exhibited changes in cellular migration, after knocking down Kidins220 in the cells. Loss of Kidins220 also resulted in cells which were more responsive to BDNF treatment when compared with the controls. Moreover, breast cancer cells exhibited a marked response to PLC-γ inhibitor, in the presence of BDNF, this was particularly so when they lost Kidins220. Conclusion: Our observations suggest that Kidins220 is involved in the metastasis of breast cancer, and it is a potential regulator in the response chain to neurotrophic factors including BDNF. Furthermore, it down-regulates the cells in response to BDNF, which is connected to PLC-γ.

Point Supervised Extended Scenario Nuclear Analysis Framework Based on LSTM-CFCN

Cells and cell like particles detection and segmentation are of significant interest to many biological and clinical studies. Traditionally, these tasks are usually performed by visual inspection, which is time consuming, labor intensity and prone to induce subjective bias between different people. These make automatic cell analysis protocols essential for large-scale and objective studies. In recent years, imaging technical has been significantly advanced following the great success by computer vision. In addition, these technologies enable the cross module microscopy analysis, and make the task of cell analysis extremely challenging. Over these decades, computer aided cell detection, counting and segmentation have evolved from earlier filter based methods to the state-of-art deep learning protocols. However, there are still few suitable frameworks that can process multiple source cell images at the same time. In this paper, we seek a different route and propose a novel efficient framework for robust cell analysis based on Long Short Term Memory Channeled Fully Convolution Neural Networks (LSTM-CFCN). The results demonstrates that our framework is able to perform most of cell detection, counting and segmentation tasks from different cell type, and it can also cover most kinds of microscopy images scenarios including dark field, bright field, pathological and electron images. We have perform substantial experiments on several benchmark datasets, the LSTM-CFCN achieves the highest or at least top-2 performance in terms of F1-score, compared with other state-of-the-art methods.