Increased neutrophil to lymphocyte ratio as a possible marker to detect neuroinflammation in patients with narcolepsy type 1.

STUDY OBJECTIVES: Narcolepsy type 1 (NT1) is an autoimmune disease caused by the selective attack of orexin-producing neurons. However, the pathophysiology of narcolepsy type 2 (NT2) and idiopathic hypersomnia (IH) remains controversial. The neutrophil-to-lymphocyte ratio (NLR) is an easily calculated parameter from the white blood cell (WBC) count, which has already been extensively used as an inflammatory marker in immunological disorders. In this study, by examining the WBC counts of patients with NT1, NT2, and IH compared to controls, and evaluated the NLR to test the possibility of identifying an easy biofluid marker for detecting inflammation and distinguishing patients from healthy controls (HC). METHODS: WBC counts and NLR were compared in 28 NT1, 17 NT2, and 11 IH patients, in addition to 21 sex/age-matched HC. These parameters were correlated with cerebrospinal fluid (CSF) levels of orexin-A, the CSF/serum albumin ratio (as a marker of blood-brain barrier integrity), and polysomnographic parameters. RESULTS: NT1 (2.01±0.44) patients showed higher NLR than NT2 (1.59±0.53), IH (1.48±0.37), and HC (1.48±0.43), with no significant difference between NT2 and IH patients. The ROC curve analysis detected an optimal cut-off value to discriminate patients with NT1 from NT2, IH, and HC for values of NLR≥1.60, 1.62, 1.59, respectively. CONCLUSIONS: Patients with NT1 showed a higher NLR than those with NT2, IH, and HC, possibly reflecting lymphocyte migration within the CNS, supporting the hypothesis of a neuroinflammatory attack of lymphocytes on orexin-producing neurons. Considering its sensitivity, this easily obtainable biofluid marker could help to screen NT1 patients.

Complicated Inguinal Hernia Incidentally Detected on a Radiolabelled Autologous White Blood Cell Scan.

A 73-year-old male with left hip prosthesis infection performed a 99mTc HMPAO-labelled autologous WBC (WBC) scan to evaluate the response to antibiotic therapy. Since the early planar scan, an area of increased activity was visible extending from the left groin region to the ipsilateral flank. At late planar images, the area progressively focused in the left groin, site of a painful inguinal hernia. The contextual tomographic acquisition showed increased activity partly referable to non-specific intestinal contents and partly localized at the parietal wall of the herniated intestinal loop. Our case suggests that the incidental detection of increased accumulation of WBC in correspondence of the intestinal wall of an inguinal hernia may indicate inflammatory involvement and subsequent further complications.

Genetic variants associated with white blood cell count amongst individuals with sickle cell disease.

BACKGROUND: Sickle cell disease (SCD) is a Mendelian disorder characterized by a point mutation in the ß-globin gene that leads to sickling of erythrocytes. Several studies have shown that absolute neutrophil count is strongly associated with clinical severity of SCD, suggesting an apparent role of white blood cells (WBC) in SCD pathology. However, the mechanism by which genetic variants lead to WBC count differences in SCD patients remains unclear. METHODS: Genome-wide association (GWA) analyses were carried out amongst a cohort of 2409 Brazil SCD participants. Association of WBC count and genetic markers were investigated in homozygous sickle cell anaemia participants and compound heterozygous sickle cell haemoglobin C participants. RESULTS: GWA analysis showed that variants in genes TERT, ACKR1, and FAM3C are associated with WBC count variation. The well-studied association between WBC count and Duffy null phenotype (variant in ACKR1) in healthy populations was replicated, reinforcing the influence of the SNP rs2814778 (T>C) in WBC count. CONCLUSION: Genetics plays an important role in regulating WBC count in patients with SCD. Our results point to possible mechanisms involved in WBC count variation and as increased WBC count is associated with more severe SCD, these results could suggest potential therapeutic targets for individuals with SCD.

Development and evaluation of a radiolabelling agent for white blood cell scans.

Radiolabelled autologous leukocytes have been used for the clinical diagnosis of inflammation and infection. To develop a stable and efficient radiopharmaceutical for labelling leukocytes, we prepared a novel radioiodinated cell-penetrating peptide, 125I-TAT, using a bi-functional linker. 125I-TAT was stable for two days under three different temperature conditions of -20 °C, 4 °C, and 40 °C, with its radiochemical purity remaining over 99%. Iodinated TAT was non-toxic to leukocytes with an IC50 value of over 100 µM. The labelling efficiency of 125I-TAT using 1ｘ107 cells ranged from 27% to 53% when the three leukocyte cell lines were pre-treated with DMSO. This is comparable to the labelling efficiency recommended by the guideline for conventional labelling agents using 2ｘ108 cells. Radioiodinated cell-penetrating peptide may be an improved radiopharmaceutical for white blood cell scans by further optimization.

Magnetic Resonance Imaging and 99Tc WBC-SPECT/CT Scanning in Differential Diagnosis between Osteomyelitis and Charcot Neuroarthropathy: A Case Series.

BACKGROUND: Distinguishing between Charcot Neuroarthropathy (CN), osteomyelitis (OM), and CN complicated with superimposed OM in diabetic patients is crucial for the treatment choice. Given that current diagnostic methods lack specificity, advanced techniques, e.g., magnetic resonance imaging (MRI) and 99mTc-HMPAO-WBC Single Photon Emission Computed Tomography (SPECT/CT), are needed. This study addresses the challenges in distinguishing OM and CN. METHODS: We included diabetic patients with CN and soft tissue ulceration. MRI and 99mTc-HMPAO-WBC SPECT/CT were used for the diagnosis. The patients were classified into three probability levels for OM (i.e., Definite, Probable, and Unlikely) according to the Consensus Criteria for Diabetic Foot Osteomyelitis (CC-DFO). RESULTS: Eight patients met the eligibility criteria. MRI, supported by SPECT-CT and CC-DFO, showed consistency with the OM diagnosis in three cases. The key diagnostic features included the location of signal abnormalities and secondary features such as skin ulcers, sinus tracts, and abscesses. Notably, cases with inconclusive MRI were clarified by SPECT/CT, emphasizing its efficacy in challenging scenarios. CONCLUSIONS: The primary objective of this study was to compare the results of MRI and 99mTc-HMPAO-WBC SPECT/CT with the CC-DFO score in the diabetic foot with CN and suspected OM. Advanced imaging offers a complementary approach to distinguish between CN and OM. This can help delineate the limits of the disease for presurgical planning. While MRI is valuable, 99mTc-HMPAO-WBC SPECT/CT provides additional clarity, especially in challenging cases or when metallic implants affect MRI accuracy.

Exploring the relationship between blood platelet and other components utilizing count regression: A cross-sectional study in Bangladesh.

Background and Aims: Blood, vital for transporting nutrients and maintaining balance, comprises red blood cells, white blood cells, and platelets, each pivotal. Imbalances lead to issues-low red cells cause fatigue (anemia), high white cells hint at infection, low counts raise infection risks. Using trendy statistical approaches, investigating the complex link between platelet counts and numerous blood components. Our investigation, leveraging count regression approaches, revealed deep insights into the interaction between platelet counts and other important hematological markers. Methods: A cross-sectional study utilized data from 3120 individuals, including both male and female participants, who visited these hospitals between June 16, 2022 and December 17, 2022, to assess their blood samples through testing by using convenience non-parametric sampling framework. Platelet count was taken into account as a measure of outcome in this research. This specific study region was chosen for its easy accessibility, which helped the seamless execution of the data-gathering technique. Count regression, negative binomial regression, and quasi-Poisson regression techniques have been employed for examining relationship of the data sets. Results: Three different count regression models were utilized to assess the proper association between the response and the relevant covariates and we found negative binomial count regression model (Akaike information criterion = 76.55, Bayesian information criterion = 76.59, and deviance = 3.14) was providing comparatively better performance than others. Based on the chosen model we found white blood cell, erythrocyte sedimentation rate, and eosinophils are significant but neutrophil, monocyte, and lymphocyte are not significant. We have also gone through proper model adequacy checking for our selected model and we found enough evidence to justify our model. Conclusion: From the result, we found insightful remarks into the mechanisms involved in platelet production and regulation, which can aid in developing increased effective treatments and interventions to maintain optimal platelet levels and prevent health problems related to abnormal platelet counts.

Detection of corneal pathology among Indians using WBC count as inflammatory marker.

The multifaceted role of NLR as a biomarker in corneal pathologies, aiming to enhance clinicians' understanding for better patient outcomes is of interest. An extensive ophthalmic assessment was conducted. Patients with corneal pathologies were identified as cases and those with healthy cornea as controls. A complete WBC blood count was performed using Automated Flow Cytometric method and the counts of white blood cells, neutrophils, platelets, and lymphocytes where recorded. NLR, PLR, and MLR were calculated by dividing the Neutrophil/Platelet/Monocyte counts by the lymphocyte counts. The study revealed that the Neutrophil-to-Lymphocyte Ratio (NLR), Monocyte-to-Lymphocyte Ratio (MLR), and Platelet-to-Lymphocyte Ratio (PLR) were significantly higher in the case group compared to the control group. N/L proved the best predictor among inflammatory markers, followed by M/L and P/L, highlighting the intricate immune response in corneal diseases, urging customized assessments in ocular health research.

Innovative Hematology Analysis Using Menstrual Blood.

Purpose: The main aim of this study was to compare and analyze hematological profiles using menstrual blood, as an alternative to peripheral blood. Patients and Methods: This study used menstrual and peripheral blood samples from women who were menstruating. The design of this research is analytical observational. Results: Menstrual blood can show an overall hematological profile similar to peripheral blood. Data shows the detection of blood component parameters, white blood cells and reticulocytes in MB with a range within and outside normal blood. Data on MB that show higher values (WBC, MCH, MCHC, PLT, RDW-CV, PDW, MPV, P-LCR, PCT, neutrophils, lymphocytes, monocytes, basophils, reticulocytes, LFR, Ret-He) and lower values lower (RBC, HGB, HCT, MVC, RDW-SD, Eosinophils, IRF, MFR, HFR) when compared with peripheral blood controls. The hematological profiles of Menstrual and peripheral blood showed significant differences (p < 0.01) for several parameters, while several other parameters did not show significant differences (p > 0.05) according to the Wilcoxon test. Conclusion: All hematological profile parameters were detected in menstrual blood. The new concept that menstrual blood can be used as a supporting medium for hematological examinations opens up opportunities for developing independent hematological detection tools in productive women.

The MACROD2 rs6110695 A>G Polymorphism and the Metabolites Indoleacrylic Acid and Butyrylcarnitine Potentially Have Clinical Relevance to WBC Count Prediction.

Our previous study suggested that the Mono-ADP ribosylhydrolase 2 (MACROD2) rs6110695 A>G polymorphism is significantly associated with white blood cell (WBC) count in the Korean population. The present study aimed to evaluate the clinical relevance of the MACROD2 rs6110695 A>G polymorphism for predicting WBC count by utilizing plasma metabolites and a single-nucleotide polymorphism (SNP). Two groups were characterized by MACROD2 rs6110695 A>G SNP genotypes among 139 healthy subjects based on the genetic information provided in our previous work: rs6110695 AA genotype group (n = 129) and rs6110695 AG genotype group (n = 10). Plasma global metabolic profiling was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). To estimate the predictive abilities of WBC count models using the rs6110695 genotype and/or significant differential metabolites, multiple linear regression analysis and receiver operating characteristic (ROC) curve analysis were conducted. The AG genotype had greater WBC-to-apolipoprotein (apo) A-I ratios; counts of WBCs, lymphocytes, monocytes, and granulocytes; monocyte-to-lymphocyte ratio (MLR); and monocyte-to-platelet ratio (MPR) than the AA genotype. In terms of metabolic profile, indoleacetic acid, and butyrylcarnitine levels were considerably distinct between the two groups, and these metabolites were considered to be meaningful prognostic variables for the rs6110695 genotype. Finally, ROC curve analysis demonstrated that the model containing the rs6110695 genotype and the two main metabolites was reliable. The present study revealed that individuals carrying the rs6110695 AG genotype with high plasma indoleacrylic acid and butyrylcarnitine levels might have elevated WBC counts. The rs6110695 genotype and the concentrations of indoleacrylic acid and butyrylcarnitine could contribute to reducing the risk of chronic diseases in the future.

Post-COVID-19: Hematological Factors Changes in Patients at Three-- time Intervals.

INTRODUCTION: Hematological parameters are crucial factors in disease severity and chronic condition pathogenesis. We aimed to evaluate the hematological factors in different severity stages of COVID-19 at different time intervals. METHODS: Serum samples were collected from 470 patients (235 men and 235 women) with a confirmed RT-qPCR COVID-19 test exhibiting moderate, severe, and critical symptoms based on WHO criteria. Samples were collected at three-time intervals, including the first: the 1st days of infection, 2nd: the one month after, and 3rd: the three months after disease onset. Total WBC, neutrophil, lymphocyte, monocyte, eosinophil, RBC counting, Hb, HCT, MCV, MCH, MCHC, hsCRP levels, G6PD deficiency, and hemoglobinopathies were determined in all patients. RESULTS: Total WBC, neutrophil, lymphocyte, platelet, RBC counting, Hb, HCT, MCV, MCH, and hsCRP levels were significantly changed with different disease severity (p<0.0001). Also, there were significant differences between different time intervals for WBC and RBC parameters (p<0.0001) except for monocytes and eosinophils. At all time intervals, there are significant changes in levels of hematological and hsCRP based on gender. Moreover, a significant correlation was observed between disease severity, age, and BMI (p<0.0001). CONCLUSION: Significant differences in hematological parameter and inflammatory parameter levels based on disease severity, time intervals, and gender revealed the importance of evaluating these factors in the management of infectious diseases, such as COVID-19, in patients during and post-disease times.

Evaluation of White Blood Cell Count, Lymphocyte Percentage, Neutrophil Percentage, and Elevated Temperature as Predictors of Wound Infection in Burn Patients.

INTRODUCTION: Infection remains a chief cause of morbidity and mortality among burn patients. The burn wound surface is initially sterile after a thermal injury but eventually gets colonized by microorganisms. A burn wound is considered infected upon the presence of high concentrations of microorganisms in the wound and scab. Burn wound infections can lead to a delay in epidermal maturation, higher scar formation, and sepsis. However, burn patients are commonly misclassified as septic due to the manifestation of systemic inflammatory response syndrome (SIRS) after their injury, despite the presence or absence of an infection. METHODS: This is a retrospective review of medical records of patients admitted to the burn unit in Salmaniya Medical Complex in Manama, Bahrain, between the years 2018 and 2020. Demographic data, total body surface area (TBSA), initial temperature, white blood cell count, lymphocyte percentage, neutrophil percentage, and wound cultures were obtained for all subjects. Logistic regression analysis was performed to compare the presence or absence of wound infection by the aforementioned parameters. RESULTS: Of 412 cases, 68.2% were male patients, with a mean age for the studied population of 25.1 years (standard deviation (SD)=20.7). Staphylococcus aureus was the most prevalent organism across all of the study population (n=31)(34.4%). Staphylococcus aureus was the most prevalent organism in patients under the age of five, while Pseudomonas aeruginosa was the most common organism among adults older than 65 years of age. TBSA was not found to be a good predictor of wound infection. There was no statistically significant relation between initial temperature and wound culture (p-value=0.056). However, logistic regression revealed that the initial temperature increases the likelihood of positive wound culture by almost three times. CONCLUSION: White blood cell count, lymphocyte percentage, and neutrophil percentage were not clinically reliable in predicting burn wound infection. However, initial temperature might be a helpful predictor. Further research is needed to identify reliable clinical parameters of burn wound infections.

Circulating white blood cell traits and prolonged night shifts: a cross-sectional study based on nurses in Guangxi.

This study aimed to elucidate the effects of long day and night shifts on immune cells in a population of nurses. This cross-sectional study in December 2019 was based on a group of nurses. 1568 physically healthy caregivers were included, including 1540 women and 28 men. 1093 nurses had long-term shift work (working in a rotating system for > 1 year). The receiver operating characteristic curve, Ensemble Learning, and Logistic regression analyses were used to evaluate factors related to long-term shift work. The night shift group nurses had significantly higher MPV, PLCR, and WBC and significantly lower BASO%, ELR, MCHC, PLR, RDW-CV, and RDW-SD (P < 0.01). ROC curves showed that WBC, PLR, ELR, RDW_CV, and BASO% were more related to the night shift. Ensemble Learning, combined with the LASSO model, finally filtered out three indicators of night shifts related to ELR, WBC, and RDW_SD. Finally, logistic regression analysis showed that the nurses' night shift situation greatly influenced two peripheral blood ELR and WBC indicators (ELR: log (OR) = - 3.9, 95% CI: - 5.8- - 2.0; WBC: log (OR) = 0.25, 95% CI: 0.18-0.32). Finally, we showed that, unlike WBC, the relative riskiness of ELR showed opposite results among junior nurses and middle-senior nurses (log (OR) 6.5 (95% CI: 1.2, 13) and - 7.1 (95% CI: - 10, - 3.8), respectively). Our study found that prolonged night shifts were associated with abnormal WBC and ELR, but after strict age matching, WBC remained significantly different. These findings help to confirm that COVID-19 and tumorigenesis (e.g., breast cancer) are significantly associated with circadian rhythm disruption. However, more detailed studies are needed to confirm this.

Label-free white blood cells classification using a deep feature fusion neural network.

White blood cell (WBC) classification is a valuable diagnostic approach for identifying diseases. However, conventional methods for WBC detection, such as flow cytometers, have limitations in terms of their high cost, large system size, and laborious staining procedures. As a result, deep learning-based label-free WBC image analysis methods are gaining popularity. Nevertheless, most existing deep learning WBC classification techniques fail to effectively utilize the subtle differences in the internal structures of WBCs observed under a microscope. To address this issue, we propose a neural network with feature fusion in this study, which enables the detection of label-free WBCs. Unlike conventional convolutional neural networks (CNNs), our approach combines low-level features extracted by shallow layers with high-level features extracted by deep layers, generating fused features for accurate bright-field WBC identification. Our method achieves an accuracy of 80.3 % on the testing set, demonstrating a potential solution for deep-learning-based biomedical diagnoses. Considering the proposed method simplifies the cell detection process and eliminates the need for complex operations like fluorescent staining, we anticipate that this automatic and label-free WBC classification network could facilitate more precise and effective analysis, and it could contribute to the future adoption of miniatured flow cytometers for point-of-care (POC) diagnostics applications.

Admission Total Leukocyte Count as a Predictor of Mortality in Cardiac Intensive Care Unit Patients.

Background: Inflammation is a sequela of cardiovascular critical illness and a risk factor for mortality. Objectives: This study aimed to evaluate the association between white blood cell count (WBC) and mortality in a broad population of patients admitted to the cardiac intensive care unit (CICU). Methods: This retrospective cohort study included patients admitted to the Mayo Clinic CICU between 2007 and 2018. We analyzed WBC as a continuous variable and then categorized WBC as low (<4.0 × 103/mL), normal (≥4.0 to <11.0 × 103/mL), high (≥11.0 to <22.0 × 103/mL), or very high (≥22.0 × 103/mL). The association between WBC and in-hospital mortality was evaluated using multivariable logistic regression and random forest models. Results: We included 11,699 patients with a median age of 69.3 years (37.6% females). Median WBC was 9.6 (IQR: 7.4-12.7). Mortality was higher in the low (10.5%), high (12.0%), and very high (33.3%) WBC groups relative to the normal WBC group (5.3%). A rising WBC was incrementally associated with higher in-hospital mortality after adjustment (AICc adjusted OR: 1.03 [95% CI: 1.02-1.04] per 1 × 103 increase in WBC). After adjustment, only the high (AICc adjusted OR: 1.37 [95% CI: 1.15-1.64]) and very high (AICc adjusted OR: 1.99 [1.47-2.71]) WBC groups remained associated with increased risk of in-hospital mortality. Conclusions: Leukocytosis is associated with an increased mortality risk in a diverse cohort of CICU patients. This readily available marker of systemic inflammation may be useful for risk stratification within the increasingly complex CICU patient population.

White blood cell count nadir to zero following intensive chemotherapy as a predictive factor for patients with acute myeloid leukemia.

Predictors for response to intensive therapy in AML have focused on baseline factors: percent leukemic blasts in marrow, cytogenetic/molecular genetic abnormalities, and presence of secondary AML. Non-baseline dynamic factors, occurring after induction but before response, may be useful for decisions related to salvage chemotherapy. We hypothesized white blood cell (WBC) count nadir after induction may be a real time indicator of treatment efficacy. We also examined whether time to stem cell transplant (SCT) or baseline molecular genetic abnormalities are associated with a low nadir. Data showed WBC nadir = 0 was a negative predictor for response to intensive induction and was correlated with reduced overall survival and progression free survival. Patients with WBC nadir = 0 did not have a significantly longer time to SCT, and none of the mutations increased the likelihood of reaching WBC nadir = 0. WBC nadir may be a useful real-time monitor in AML patients receiving intensive induction chemotherapy.

Plasma chitotriosidase enzyme activity as a novel therapeutic monitor for cysteamine treatment in nephropathic cystinosis: A retrospective validation study.

BACKGROUND: Cystine-depleting therapy in nephropathic cystinosis is currently monitored via the white blood cell cystine assay, although its application and usefulness are limited by practical and technical issues. Therefore, alternative biomarkers that are widely available, more economical and less technically demanding, while reliably reflecting long-term adherence to cysteamine treatment, are desirable. Recently, we proposed chitotriosidase enzyme activity as a potential novel biomarker for the therapeutic monitoring of cysteamine treatment in cystinosis. In this study, we aimed to validate our previous findings and to confirm the value of chitotriosidase in the management of cystinosis therapy. MATERIALS & METHODS: A retrospective study was conducted on 12 patients treated at the National Institutes of Health Clinical Center and followed up for at least 2 years. Plasma chitotriosidase enzyme activity was correlated with corresponding clinical and biochemical data. RESULTS: Plasma chitotriosidase enzyme activity significantly correlated with WBC cystine levels, cysteamine total daily dosage and a Composite compliance score. Moreover, plasma chitotriosidase was a significant independent predictor for WBC cystine levels, and cut-off values were established in both non-kidney transplanted and kidney transplanted cystinosis patients to distinguish patients with a good versus poor compliance with cysteamine treatment. Our observations are consistent with those of our previous study and validate our findings. CONCLUSIONS: Chitotriosidase enzyme activity is a valid potential alternative biomarker for monitoring cysteamine treatment in nephropathic cystinosis patients. SYNOPSIS: Chitotriosidase enzyme activity is a valid potential alternative biomarker for monitoring cysteamine treatment in nephropathic cystinosis patients.

Epigenetic age oscillates during the day.

Since their introduction, epigenetic clocks have been extensively used in aging, human disease, and rejuvenation studies. In this article, we report an intriguing pattern: epigenetic age predictions display a 24-h periodicity. We tested a circadian blood sample collection using 17 epigenetic clocks addressing different aspects of aging. Thirteen clocks exhibited significant oscillations with the youngest and oldest age estimates around midnight and noon, respectively. In addition, daily oscillations were consistent with the changes of epigenetic age across different times of day observed in an independant populational dataset. While these oscillations can in part be attributed to variations in white blood cell type composition, cell count correction methods might not fully resolve the issue. Furthermore, some epigenetic clocks exhibited 24-h periodicity even in the purified fraction of neutrophils pointing at plausible contributions of intracellular epigenomic oscillations. Evidence for circadian variation in epigenetic clocks emphasizes the importance of the time-of-day for obtaining accurate estimates of epigenetic age.

Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network.

Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of diseases such as malaria, leukemia, AIDS, and other viral infections. WBCs detection and classification in blood smears offers insights to pathologists, aiding diagnosis across medical conditions. Traditional techniques, including manual counting, detection, classification, and visual inspection of microscopic images by medical professionals, pose challenges due to their labor-intensive nature. However, traditional methods are time consuming and sometimes susceptible to errors. Here, we propose a high-performance convolutional neural network (CNN) coupled with a dual-attention network that efficiently detects and classifies WBCs in microscopic thick smear images. The main aim of this study was to enhance clinical hematology systems and expedite medical diagnostic processes. In the proposed technique, we utilized a deep convolutional generative adversarial network (DCGAN) to overcome the limitations imposed by limited training data and employed a dual attention mechanism to improve accuracy, efficiency, and generalization. The proposed technique achieved overall accuracy rates of 99.83%, 99.35%, and 99.60% for the peripheral blood cell (PBC), leukocyte images for segmentation and classification (LISC), and Raabin-WBC benchmark datasets, respectively. Our proposed approach outperforms state-of-the-art methods in terms of accuracy, highlighting the effectiveness of the strategies employed and their potential to enhance diagnostic capabilities and advance real-world healthcare practices and diagnostic systems.

Highly Sensitive and Linear Resonator-Based Biosensor for White Blood Cell Counting: Feasible Measurement Method and Intrinsic Mechanism Exploration.

Since different quantities of white blood cells (WBCs) in solution possess an adaptive osmotic pressure of cells, the WBCs themselves and in solution have similar concentrations, resulting in them having similar dielectric properties. Therefore, a microwave sensor could have difficulty in sensing the quantity variation when WBCs are in solution. This paper presents a highly sensitive, linear permittivity-inspired microwave biosensor for WBCs, counting through the evaporation method. Such a measurement method is proposed to record measurements after the cell solution is dripped onto the chip and is completely evaporated naturally. The proposed biosensor consists of an air-bridged asymmetric differential inductor and a centrally located circular fork-finger capacitor fabricated on a GaAs substrate using integrated passive fabrication technology. It is optimized to feature a larger sensitive area and improved Q-factor, which increases the effective area of interaction between cells and the electromagnetic field and facilitates the detection of their changes in number. The sensing relies on the dielectric properties of the cells and the change in the dielectric constant for different concentrations, and the change in resonance properties, which mainly represents the frequency shift, corresponds to the macroscopic change in the concentration of the cells. The microwave biosensors are used to measure biological samples with concentrations ranging from 0.25 × 106 to 8 × 106 cells per mL in a temperature (26.00 ± 0.40 °C) and humidity (54.40 ± 3.90 RH%) environment. The measurement results show a high sensitivity of 25.06 Hz/cells·mL-1 with a highly linear response of r2 = 0.99748. In addition, a mathematical modeling of individual cells in suspension is performed to estimate the dielectric constant of individual cells and further explain the working mechanism of the proposed microwave biosensor.