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Background: Predicting long-term survival in intensive care unit patients with intracerebral hemorrhage (ICH) is crucial. This study aimed to develop a platelet-to-white blood cell ratio (PWR) incorporated nomogram for long-term survival prediction. Methods: A retrospective analysis was conducted on 1,728 ICH patients in the MIMIC-IV 2.2 database. The independent prognostic value of PWR for 1- year mortality was assessed. A nomogram was developed using LASSO and Cox regression to predict 1-year survival, incorporating PWR and other factors. The performance of the nomogram was evaluated through calibration curves, area under the curve, Delong test, net reclassification index, integrated discrimination improvement, and decision curve analysis. Results: The nomogram, which included age, weight, Glasgow Coma Scale (GCS) score, mechanical ventilation, glucose, red blood cell (RBC) count, blood urea nitrogen (BUN), and PWR, showed good predictive performance for 1-year survival. The C-index was 0.736 (95% CI = 0.716--0.756) for the training set and 0.766 (95% CI = 0.735--0.797) for the testing set. Higher age and ventilation increased mortality risk, while higher weight, GCS score, RBC count, and PWR decreased risk. The nomogram outperformed conventional scores. Conclusions: A nomogramincorporating PWR as a prognostic factor accurately predicts long-term survival in ICH patients. However, validation in large-scale multicenter studies and further exploration of biomarkers are needed. [ABSTRACT FROM AUTHOR]

ABSTRACT Introduction Methods Results Conclusion There is an increasing research focus on the role of machine learning in the haematology laboratory, particularly in blood cell morphologic assessment. Human‐level performance is an important baseline and goal for machine learning. This study aims to assess the interobserver variability and human‐level performance in blood cell morphologic assessment.A dataset of 1000 single white blood cell images were independently labelled by 10 doctors and morphology scientists. Interobserver variability was calculated using Fleiss' kappa. Observers' labels were then separated into consensus labels used to determine ground truth, and performance labels used to assess observer performance. A machine learning model was trained and assessed using the same cell images. Explainability images (XRAI and IG) were generated for each of the test images.The Fleiss kappa for all 10 observers was 0.608, indicating substantial agreement between observers. The accuracy of human observers was 95%, with sensitivity 72% and specificity 97%. The accuracy of the machine learning model was 95%, with sensitivity 71% and specificity 97%. The model shared similar performance across labels when compared to humans. Explainability metrics demonstrated that the machine learning model was able to differentiate between the cytoplasm and nucleus of the cells, and used these features to perform predictions.The substantial, though not perfect, agreement between human observers highlights the inherent subjectivity in white blood cell morphologic assessment. A machine learning model performed similarly to human observers in single white blood cell identification. Further research is needed to compare human‐level and machine learning performance in ways that more closely reflect the typical process of morphologic assessment. [ABSTRACT FROM AUTHOR]

Abstract Leukemia, a hematological disease affecting the bone marrow and white blood cells (WBCs), ranks among the top ten causes of mortality worldwide. Delays in decision-making often hinder the timely application of suitable medical treatments. Acute lymphoblastic leukemia (ALL) is one of the primary forms, constituting approximately 25% of childhood cancer cases. However, automated ALL diagnosis is challenging. Recently, machine learning (ML) has emerged as an important tool for building detection models. In this study, we present a hybrid detection model that improves the accuracy of the detection process by combining support vector machine (SVM) and particle swarm optimization (PSO) approaches to automatically identify ALL. We use SVM to represent a two-dimensional image and complete the classification process. PSO is employed to enhance the performance of the SVM model, reducing error rates and enhancing result accuracy. The input images are obtained from two public datasets (ALL-IDB1 and ALL-IDB2), and public online datasets are utilized for training and testing the proposed model. The results indicate that our hybrid SVM-PSO model has high accuracy, outperforming stand-alone algorithms and demonstrating superior performance, an enhanced confusion matrix, and a higher detection rate. This advancement holds promise for enhancing the quality of technical software in the medical field using machine learning.

Background: This retrospective observational study aimed to examine whether clinical inflammatory parameters were associated with the requirement dosage of unfractionated heparin (UFH) to maintain the range of ACT in veno-arterial extracorporeal membrane oxygenation (V-A ECMO) during lung transplantation surgery. Methods: Among all patients who underwent lung transplantation using V-A ECMO from January 2021 to May 2022, 27 patients were included. These patients were divided into two groups based on whether the infusion rate of UFH was increased from the initial infusion rate (7–8 units/kg/h) (increased group, n = 10) or the infusion rate was maintained or decreased (non-increased group, n = 17). The infusion rate was adjusted with an activated clotting time (ACT) target of 160–200 s. Results: At 1–2 h after starting ECMO, ACT was significantly lower (179.0 (166.5–188.5) versus 224.0 (193.0–242.0) sec, p = 0.006) and white blood cell (WBC) counts were higher in the increased group (12.6 ± 3.3 versus 9.5 ± 4.0 × 103/μL, p = 0.046). The UFH infusion rates were higher in the increased group during the surgery. The cutoff value of WBC count at 1–2 h after starting ECMO for discriminating the need for increasing the UFH dosage was determined as 10.2 × 103/μL (sensitivity 90.0%, specificity 58.8%, area under the curve 0.712) and discrimination of this cut-off value was confirmed as statistically significant (p = 0.018). Conclusion: These data suggested that WBC count was associated with the requirement of an increase in the UFH infusion rate of V-A ECMO during lung transplantation surgery. Further evaluation is necessary to clarify the role of WBC count in determining the optimal UFH dosage.

Objective To analyze the relationship between inflammatory reaction and the short-term readmission of hospitalized patients with chronic obstructive pulmonary disease （COPD） complicated with respiratory failure. Methods Ninety-one hospitalized patients with COPD complicated with respiratory failure were included in this prospective cohort study. They were divided into the occurrence group （n =17） and the non-occurrence group （n =74） according to the occurrence of complications during hospitalization. They were also divided into the readmission group （n =18） and the non-readmission group （n =73） according to the 30-d readmission situation. Another 91 patients with COPD alone were assigned into the control group. The pre-treatment inflammation indicators （white blood cell （WBC）， C-reactive protein （CRP）， tumor necrosis factor-α （TNF-α）） were compared between patients with COPD alone and COPD complicated with respiratory failure and different prognosis. The risk factors of 30-d readmission of COPD complicated with respiratory failure were identified by multivariate binary Logistic regression analysis. The receiver operating characteristic （ROC） curve was delineated to analyze the diagnostic values of these risk factors for the short-term readmission of COPD patients complicated with respiratory failure. Results After treatment， the levels of WBC， CRP， and TNF-α in COPD patients with respiratory failure and simple COPD were significantly lower than those before treatment （all P <0.05）. The levels of WBC， CRP and TNF-α in patients with COPD complicated with respiratory failure before treatment were significantly higher than those in patients with COPD alone （all P <0.05）. The levels of WBC， CRP and TNF-α in COPD patients complicated with type Ⅱ respiratory failure before treatment were significantly higher than those in patients complicated with type Ⅰ respiratory failure （all P <0.05）. The levels of CRP and TNF-α in the occurrence group before treatment were significantly higher than those in the non-occurrence group （both P <0.05）. The levels of CRP and TNF-α in the readmission group before treatment were significantly higher than those in the non-readmission group （both P <0.05）. Multivariate binary logistic regression analysis showed that there was no significant correlation between CRP and TNF-α levels and the 30-d readmission of COPD patients after adjusting for confounding factors （both P >0.05）. However， regardless of the adjustment for confounding factors， CRP and TNF-α levels were significant factors affecting the 30-d readmission of COPD patients with respiratory failure （both P <0.05）. The area under the ROC curve （AUC） of CRP， TNF-α and two combined before treatment for predicting 30-d readmission of COPD patients complicated with respiratory failure all exceeded 0.70， which had certain predictive value. Conclusions CRP and TNF-α yield high efficiency in predicting the short-term readmission of COPD patients complicated with respiratory failure. Treatment plans can be formulated according to CRP and TNF-α levels to reduce the risk of readmission.

Abstract Background Human aging and white blood cell (WBC) count are complex traits influenced by multiple genetic factors. Predictors of chronological age have been developed using epigenetic clocks. However, the bidirectional causal effects between epigenetic clocks and WBC count have not been fully examined. Methods This study employed Mendelian randomization (MR) to analyze summary statistics from four epigenetic clocks involving 34,710 participants, alongside data from the Blood Cell Consortium encompassing 563,946 individuals. We primarily explored bidirectional causal relationships using the random-effects inverse-variance weighted method, supplemented by additional MR methods for comprehensive analysis. Additionally, multivariate MR was applied to investigate independent effects of WBC count on epigenetic age acceleration. Results In the two-sample univariate MR (UVMR) analysis, we observed that a decrease in lymphocyte count markedly accelerated aging according to the PhenoAge, GrimAge, and HannumAge metrics (all P

Abstract Background Polycyclic aromatic hydrocarbons (PAHs) and metals were associated with decreased lung function, but co-exposure effects and underlying mechanism remained unknown. Methods Among 1,123 adults from National Health and Nutrition Examination Survey 2011–2012, 10 urinary PAHs, 11 urinary metals, and peripheral white blood cell (WBC) count were determined, and 5 lung function indices were measured. Least absolute shrinkage and selection operator, Bayesian kernel machine regression, and quantile-based g-computation were used to estimate co-exposure effects on lung function. Mediation analysis was used to explore mediating role of WBC. Results These models demonstrated that PAHs and metals were significantly associated with lung function impairment. Bayesian kernel machine regression models showed that comparing to all chemicals fixed at median level, forced expiratory volume in 1 s (FEV1)/forced vital capacity, peak expiratory flow, and forced expiratory flow between 25 and 75% decreased by 1.31% (95% CI: 0.72%, 1.91%), 231.62 (43.45, 419.78) mL/s, and 131.64 (37.54, 225.74) mL/s respectively, when all chemicals were at 75th percentile. In the quantile-based g-computation, each quartile increase in mixture was associated with 104.35 (95% CI: 40.67, 168.02) mL, 1.16% (2.11%, 22.40%), 294.90 (78.37, 511.43) mL/s, 168.44 (41.66, 295.22) mL/s decrease in the FEV1, FEV1/forced vital capacity, peak expiratory flow, and forced expiratory flow between 25% and 75%, respectively. 2-Hydroxyphenanthrene, 3-Hydroxyfluorene, and cadmium were leading contributors to the above associations. WBC mediated 8.22%-23.90% of association between PAHs and lung function. Conclusions Co-exposure of PAHs and metals impairs lung function, and WBC could partially mediate this relationship. Our findings elucidate co-exposure effects of environmental mixtures on respiratory health and underlying mechanisms, suggesting that focusing on highly prioritized toxicants would effectively attenuate adverse effects.

Background: Microscopic examination of peripheral blood is a standard practice in clinical medicine. Although manual examination is considered the gold standard, it presents several disadvantages, such as interobserver variability, being quite time-consuming, and requiring well-trained professionals. New automatic digital algorithms have been developed to eliminate the disadvantages of manual examination and improve the workload of clinical laboratories. Objectives: Regular analysis of peripheral blood cells and careful interpretation of their results are critical for protecting individual health and early diagnosis of diseases. Because many diseases can occur due to this, this study aims to detect white blood cells automatically. Methods: A hybrid model has been developed for this purpose. In the developed model, feature extraction has been performed with MobileNetV2 and EfficientNetb0 architectures. In the next step, the neighborhood component analysis (NCA) method eliminated unnecessary features in the feature maps so that the model could work faster. Then, different features of the same image were combined, and the extracted features were combined to increase the model's performance. Results: The optimized feature map was classified into different classifiers in the last step. The proposed model obtained a competitive accuracy value of 95.6%. Conclusions: The results obtained in the proposed model show that the proposed model can be used in the detection of white blood cells. [ABSTRACT FROM AUTHOR]

Background: This retrospective observational study aimed to examine whether clinical inflammatory parameters were associated with the requirement dosage of unfractionated heparin (UFH) to maintain the range of ACT in veno-arterial extracorporeal membrane oxygenation (V-A ECMO) during lung transplantation surgery. Methods: Among all patients who underwent lung transplantation using V-A ECMO from January 2021 to May 2022, 27 patients were included. These patients were divided into two groups based on whether the infusion rate of UFH was increased from the initial infusion rate (7-8 units/kg/h) (increased group, n = 10) or the infusion rate was maintained or decreased (non-increased group, n = 17). The infusion rate was adjusted with an activated clotting time (ACT) target of 160-200 s. Results: At 1-2 h after starting ECMO, ACT was significantly lower (179.0 (166.5-188.5) versus 224.0 (193.0-242.0) sec, p = 0.006) and white blood cell (WBC) counts were higher in the increased group (12.6 ± 3.3 versus 9.5 ± 4.0 x 103/lL, p = 0.046). The UFH infusion rates were higher in the increased group during the surgery. The cutoff value of WBC count at 1-2 h after starting ECMO for discriminating the need for increasing the UFH dosage was determined as 10.2 x 103/lL (sensitivity 90.0%, specificity 58.8%, area under the curve 0.712) and discrimination of this cut-off value was confirmed as statistically significant (p = 0.018). Conclusion: These data suggested that WBC count was associated with the requirement of an increase in the UFH infusion rate of V-A ECMO during lung transplantation surgery. Further evaluation is necessary to clarify the role of WBC count in determining the optimal UFH dosage. [ABSTRACT FROM AUTHOR]

Background: Human aging and white blood cell (WBC) count are complex traits influenced by multiple genetic factors. Predictors of chronological age have been developed using epigenetic clocks. However, the bidirectional causal effects between epigenetic clocks and WBC count have not been fully examined. Methods: This study employed Mendelian randomization (MR) to analyze summary statistics from four epigenetic clocks involving 34,710 participants, alongside data from the Blood Cell Consortium encompassing 563,946 individuals. We primarily explored bidirectional causal relationships using the random-effects inverse-variance weighted method, supplemented by additional MR methods for comprehensive analysis. Additionally, multivariate MR was applied to investigate independent effects of WBC count on epigenetic age acceleration. Results: In the two-sample univariate MR (UVMR) analysis, we observed that a decrease in lymphocyte count markedly accelerated aging according to the PhenoAge, GrimAge, and HannumAge metrics (all P < 0.01, β < 0), though it did not affect Intrinsic Epigenetic Age Acceleration (IEAA). Conversely, an increase in neutrophil count significantly elevated PhenoAge levels (β: 0.38; 95% CI 0.14, 0.61; P = 1.65E−03 < 0.01). Reverse MR revealed no significant causal impacts of epigenetic clocks on overall WBC counts. Furthermore, in multivariate MR, the impact of lymphocyte counts on epigenetic aging metrics remained statistically significant. We also identified a marked causal association between neutrophil counts and PhenoAge, GrimAge, and HannumAge, with respective results showing strong associations (PhenoAge β: 0.78; 95% CI 0.47, 1.09; P = 8.26E−07; GrimAge β: 0.55; 95% CI 0.31, 0.79; P = 5.50E−06; HannumAge β: 0.42; 95% CI 0.18, 0.67; P = 6.30E−04). Likewise, eosinophil cell count demonstrated significant association with HannumAge (β: 0.33; 95% CI 0.13, 0.53; P = 1.43E−03 < 0.01). Conclusion: These findings demonstrated that within WBCs, lymphocyte and neutrophil counts exert irreversible and independent causal effects on the acceleration of PhenoAge, GrimAge, and HannumAge. Our findings highlight the critical role of WBCs in influencing epigenetic clocks and underscore the importance of considering immune parameters when interpreting epigenetic age. [ABSTRACT FROM AUTHOR]

Background: Polycyclic aromatic hydrocarbons (PAHs) and metals were associated with decreased lung function, but co-exposure effects and underlying mechanism remained unknown. Methods: Among 1,123 adults from National Health and Nutrition Examination Survey 2011–2012, 10 urinary PAHs, 11 urinary metals, and peripheral white blood cell (WBC) count were determined, and 5 lung function indices were measured. Least absolute shrinkage and selection operator, Bayesian kernel machine regression, and quantile-based g-computation were used to estimate co-exposure effects on lung function. Mediation analysis was used to explore mediating role of WBC. Results: These models demonstrated that PAHs and metals were significantly associated with lung function impairment. Bayesian kernel machine regression models showed that comparing to all chemicals fixed at median level, forced expiratory volume in 1 s (FEV1)/forced vital capacity, peak expiratory flow, and forced expiratory flow between 25 and 75% decreased by 1.31% (95% CI: 0.72%, 1.91%), 231.62 (43.45, 419.78) mL/s, and 131.64 (37.54, 225.74) mL/s respectively, when all chemicals were at 75th percentile. In the quantile-based g-computation, each quartile increase in mixture was associated with 104.35 (95% CI: 40.67, 168.02) mL, 1.16% (2.11%, 22.40%), 294.90 (78.37, 511.43) mL/s, 168.44 (41.66, 295.22) mL/s decrease in the FEV1, FEV1/forced vital capacity, peak expiratory flow, and forced expiratory flow between 25% and 75%, respectively. 2-Hydroxyphenanthrene, 3-Hydroxyfluorene, and cadmium were leading contributors to the above associations. WBC mediated 8.22%-23.90% of association between PAHs and lung function. Conclusions: Co-exposure of PAHs and metals impairs lung function, and WBC could partially mediate this relationship. Our findings elucidate co-exposure effects of environmental mixtures on respiratory health and underlying mechanisms, suggesting that focusing on highly prioritized toxicants would effectively attenuate adverse effects. [ABSTRACT FROM AUTHOR]

Objective To analyze the relationship between inflammatory reaction and the short-term readmission of hospitalized patients with chronic obstructive pulmonary disease (COPD) complicated with respiratory failure. Methods Ninety-one hospitalized patients with COPD complicated with respiratory failure were included in this prospective cohort study. They were divided into the occurrence group n = 17) and the non-occurrence group (n = 74)according to the occurrence of complications during hospitalization. They were also divided into the readmission group (n = 18)and the non-readmission group ( n = 73 ) according to the 30-d readmission situation. Another 91 patients with COPD alone were assigned into the control group. The pre-treatment inflammation indicators (white blood cell (WBC), C-reactive protein (CRP), tumor necrosis factor-a (TNF-a)) were compared between patients with COPD alone and COPD complicated with respiratory failure and different prognosis. The risk factors of 30-d readmission of COPD complicated with respiratory failure were identified by multivariate binary Logistic regression analysis. The receiver operating characteristic (ROC) curve was delineated to analyze the diagnostic values of these risk factors for the short-term readmission of COPD patients complicated with respiratory failure. Results After treatment, the levels of WBC, CRP, and TNF-a in COPD patients with respiratory failure and simple COPD were significantly lower than those before treatment (all P < 0.05 ). The levels of WBC, CRP and TNF-a in patients with COPD complicated with respiratory failure before treatment were significantly higher than those in patients with COPD alone (all P < 0.05 ). The levels of WBC, CRP and TNF-a in COPD patients complicated with type II respiratory failure before treatment were significantly higher than those in patients complicated with type I respiratory failure (all P < 0.05 ). The levels of CRP and TNF-a in the occurrence group before treatment were significantly higher than those in the non-occurrence group (both P < 0.05 ). The levels of CRP and TNF-a in the readmission group before treatment were significantly higher than those in the non-readmission group (both P < 0.05 ). Multivariate binary logistic regression analysis showed that there was no significant correlation between CRP and TNF-a levels and the 30-d readmission of COPD patients after adjusting for confounding factors (both P > 0.05 ). However, regardless of the adjustment for confounding factors, CRP and TNF-a levels were significant factors affecting the 30-d readmission of COPD patients with respiratory failure (both P < 0.05 ). The area under the ROC curve (AUC)of CRP, TNF-a and two combined before treatment for predicting 30-d readmission of COPD patients complicated with respiratory failure all exceeded 0.70, which had certain predictive value. Conclusions CRP and TNF-a yield high efficiency in predicting the short-term readmission of COPD patients complicated with respiratory failure. Treatment plans can be formulated according to CRP and TNF-a levels to reduce the risk of readmission. [ABSTRACT FROM AUTHOR]

Objective: White blood cell (WBC) counts has been identified as a prognostic biomarker which frequently predict adverse outcomes and mortality risk in various conditions. However, evidence for the association between WBC counts and short-term outcomes after intracranial tumor resection remains limited. This study aimed to explore associations between preoperative WBC counts and thirty-day surgical mortality after craniotomy in adult intracranial tumor patients. Methods: This retrospective cohort study performed secondary analysis of 18,049 intracranial tumor craniotomy patients from the ACS NSQIP database (2012-2015). The major exposure and outcome were preoperative WBC counts and thirty-day surgical mortality, respectively. Cox regression modeling assessed the linear association between them. Non-linear associations between them were evaluated by conducting smooth curve fitting using an additive Cox proportional hazard model in conjunction with segmented linear regression modeling. Subgroup analysis and interaction testing assessed effect modification. Sensitivity analysis evaluated result robustness. Results: The total thirty-day surgical mortality after craniotomy was 2.49% (450/18,049). The mean of preoperative WBC counts was 9.501 ± 4.402 × 10-9/L. Fully adjusted model shows that elevated preoperative WBC counts was independently associated with increased thirty-day surgical mortality (HR = 1.057, 95%CI: 1.040, 1.076). Further analysis revealed a non-linear association between them: below a WBC threshold of 13.6 × 10-9/L, higher WBC counts elevated thirty-day mortality (HR = 1.117; 95%CI: 1.077, 1.158), while risk plateaued and no significant mortality rise occurred above this level (HR = 1.015, 95%CI: 0.982, 1.050). Steroid usage status has a significant effect modification on the WBCmortality association (P for interaction = 0.002). The non-linear WBC-mortality association was only present for non-steroid users (HR = 1.158, 95%CI: 1.108, 1.210) but not steroid users (HR = 1.009, 95%CI: 0.966, 1.055). The sensitivity analysis confirmed the result robustness. Conclusion: Elevated preoperative WBC counts were independently and nonlinearly associated with an increased risk of thirty-day surgical mortality in adult non-steroid use patients undergoing craniotomy for intracranial tumors. As a convenient predictor, preoperative WBC data allows improved risk profiling and personalized management in adult intracranial tumor patients. [ABSTRACT FROM AUTHOR]

The article focuses on the concepts of Cell Image Segmentation (CIS) and the gradual introduction of cell counting. Motivated by the rapid development of Machine learning (ML) methods, which is carried out in this investigation. ML is evolving from theory to practical applications, with deep neural network models extensively used in academia and business for various applications, including image counting and natural language processing. These advancements can greatly influence medical imaging technologies, data processing, diagnostics, and healthcare in general. Main objectives of the research are to provide an overview of biological cell counting methods in microscopic images and to explore deep learning (DL)-based image segmentation approaches. The study expertly describes current trends, cutting-edge learning technologies, and platforms utilized for DL approaches. Cell counting is one of the most researched and challenging subjects in computer vision systems. Academics are increasingly interested in this area due to its real-time applications in biology, biochemistry, medical diagnostics, computer vision-based cell tracking systems for large populations, and stem cell manufacturing. Counting cells in the biological field is beneficial. For instance, the ratio of white blood cells to cancer cells in the blood can help determine the origin of a disease. Biologists also need to count cells within cell cultures to monitor the time-dependent growth of cells during bacterial experiments. Numerous methods for cell counting have been developed, after addressing the challenges with Cell Counting algorithms; the article explores promising future directions in CIS and cell counting research fields. [ABSTRACT FROM AUTHOR]

AIM: To evaluate the effectiveness of heparin-binding protein (HBP) in combination with organ function indicators for early diagnosis and prognosis prediction in patients with severe trauma complicated with sepsis. METHODS: A retrospective analysis was conducted on 184 patients with multiple injuries who were admitted to the Emergency Medicine Department of the Second Affiliated Hospital of Zhejiang University Medical College between January 2019 and September 2020 and underwent HBP testing. Patients were classified according to the SEPSIS 3. 0 diagnostic criteria into a sepsis group (n=89) and a non-sepsis group (n=95). Clinical outcomes were tracked, dividing patients into a deceased group (n=43) and a survival group (n=141). HBP levels were continuously measured, and the peak values of the two groups were compared to assess the efficacy of diagnosing sepsis. Further analysis on the correlation of HBP peak value median with clinical prognosis was conducted. The effectiveness of HBP alone and in combination with total bilirubin (TBil) and white blood cell (WBC) count in prognosis assessment was evaluated. RESULTS: (1) No significant difference was found in the peak level of HBP between the sepsis group (n=89) and the non-sepsis group (n=95) (71. 7± 68. 6 vs 52. 5±56. 1, P=0. 051). (2) Among the 184 patients, the peak level of HBP was positively correlated with WBC count (r=0. 244, P<0. 01) and TBil levels (r=0. 241, P<0. 01). (3) The area under curve (AUC) for independent diagnosis of sepsis using TBil levels, WBC count, and PCT levels were 0. 618, 0.631, and 0. 718, respectively, and the combined AUC was 0. 684, with a diagnostic sensitivity of 60. 7% and specificity of 71. 6% (P<0. 05). (4) Prognostic analysis of mortality showed that patients in the high HBP level group had a significantly higher mortality rate than those in the low-level group (30. 4% vs 16. 3%, P<0. 05). The WBC count was also significantly higher in the deceased group than in the survival group (17. 5±6. 9 vs 12. 8±4. 7, P<0. 01), especially in those with sepsis (P<0. 01). The AUCs for predicting sepsis mortality prognosis using HBP peak level, TBil levels, WBC count, SOFA score, and APACHE-II score were 0. 618, 0. 603, 0. 719, 0. 823, and 0. 811, respectively. The combined AUC of HBP with TBil and WBC for assessing sepsis prognosis was 0. 750, with a sensitivity of 74. 4% and specificity of 74. 5%, showing statistically significant differences (P<0. 05). (5) The combined assessment of these three indicators showed no statistically significant difference from artificial scoring systems in predicting sepsis prognosis (P>0. 05). CONCLUSION: The combination of HBP, TBil, and WBC is highly effective in predicting the risk of sepsis in patients with multiple injuries and has significant clinical value in predicting the mortality risk of trauma patients with sepsis. [ABSTRACT FROM AUTHOR]

Recently, we identified artifactual hypoglycemia in patients with soft tissue sarcoma (STS) who received pegfilgrastim-supported chemotherapy. In the present study, we measured white blood cell count and fasting blood glucose levels after the administration of pegfilgrastim in patients with STS and showed the relationship between artifactual hypoglycemia and white blood cell count. A total of 19 patients were included in this study. The mean age of the patients was 54 years. They received chemotherapy and administration of pegfilgrastim. Pegfilgrastim was injected subcutaneously 48 h after chemotherapy. No patient had a history of diabetes mellitus. Fifty-nine cycles were administered to 19 patients. One hundred and twenty-eight samples were obtained within one week after the of pegfilgrastim administration. Hypoglycemia was observed in 38 of the 13 patients. There were no symptoms of hypoglycemia in any patient. The white blood cell count in samples from patients with hypoglycemia was significantly higher than that in samples without hypoglycemia (p < 0.001). The median white blood cell count in samples with hypoglycemia was 29,415 and 3420 in samples without hypoglycemia. Age, sex, body mass index, performance status, and red blood cell count were not associated with hypoglycemia. White blood cell count was strongly negatively correlated with fasting blood glucose levels (Pearson's r: 0.786, 95% confidence interval: 0.844–0.709, p < 0.001). Of the 38 samples with hypoglycemia, 32 were measured within 2 days after pegfilgrastim administration. If a lack of symptoms due to hypoglycemia and leukocytes is confirmed, physicians should wait and identify the normalization of the level of glucose according to the neutrophil nadir following temporal leukocytes, which prevents further invasive examination for hypoglycemia. [ABSTRACT FROM AUTHOR]

Purpose: Inflammation is thought to be a vital element in the etiology of cancer-related fatigue (CRF), and circulating blood cell parameters could be important markers of inflammatory response. However, the associations of several major blood cell counts and their derived inflammatory indices with CRF are not well described. The present study aimed to establish whether a relationship exists between the counts of three white blood cell (WBC) types, platelets, and CRF and investigate whether several systemic inflammatory indices were associated with CRF in patients with breast cancer (BC). Methods: A cross-sectional survey was conducted with a sample of 824 patients with BC undergoing chemotherapy. The cancer fatigue scale was administered to assess CRF. Hematological indicators, including neutrophils, lymphocytes, monocytes, and platelets, were retrieved from routine blood test. Network analyses were used to examine the associations among them. Results: Among 824 participants, the mean score of CRF was (27 ± 10), ranging from 0 to 57. The results of network models indicated that physical fatigue was negatively linked to lymphocyte counts (weight = − 0.161), and affective fatigue was positively associated with neutrophil counts (weight = 0.070). Additionally, physical fatigue was positively linked to the platelet-to-lymphocyte ratio (PLR) (weight = 0.049). Conclusion: There were preliminary associations of counts of three WBC types, platelet counts, and systemic inflammatory indices, with distinct dimensions of CRF in patients with BC. Findings provide empirical support for the cellular basis of fatigue-associated inflammatory states. [ABSTRACT FROM AUTHOR]

Objective To investigate clinical characteristics and risk factors of different stages of urinary tract infection after kidney transplantation. Methods Clinical data of 209 kidney transplant recipients were retrospectively analyzed. According to time points of postoperative follow-up, all recipients were divided into 3 stages: within 1 month post-kidney transplantation, 1-6 months post-kidney transplantation, and 7-12 months post-kidney transplantation. The incidence of urinary tract infection, urine culture results of recipients with urinary tract infection and drug resistance characteristics of common pathogens during different stages after kidney transplantation were analyzed. The strains of patients with recurrent urinary tract infection were identified. The risk factors of urinary tract infection and the effect of urinary tract infection on renal allograft function were analyzed. Results The urinary tract infection rate was 90.0% in the first stage, 49.3% in the second stage and 22.5% in the third stage. The urinary tract infection rates of male recipients undergoing living-related organ donation in the second and third stages were lower than those of female recipients (both P<0.05). Urine culture test yielded positive results in 60 cases, and 84 strains of pathogenic bacteria were detected, mainly Gram-negative bacteria, among which Klebsiella pneumoniae accounted for the highest proportion. Sixty-six recipients had recurrent urinary tract infection, and the detected pathogens included Klebsiella pneumoniae, Escherichia coli and Candida glabrata, etc. Univariate analysis showed that postoperative use of antithymocyte globulin was the risk factor for urinary tract infection in the first stage. Preoperative urinary tract infection and donor type were the risk factors for urinary tract infection in the second stage. Gender and age of the recipients were the risk factors for urinary tract infection in the third stage. Multivariate analysis revealed that postoperative use of antithymocyte globulin was the risk factor for urinary tract infection in the first stage. Gender and age of the recipients were the risk factors for urinary tract infection in the third stage (all P<0.05). In the third stage, 65 cases were cured and 38 cases were not cured. In the treated recipients, the serum creatinine level and white blood cell count were decreased after corresponding treatment than those before treatment (both P<0.05).Conclusions Gram-negative bacteria are the main pathogens of urinary tract infection in kidney transplant recipients, and drug resistance is relatively high. Postoperative use of antithymocyte globulin, female and old age are the risk factors for urinary tract infection in kidney transplant recipients. [ABSTRACT FROM AUTHOR]

Background: Both the high-risk human papillomavirus (HR-HPV) infection and tobacco exposure are significantly associated with cervical neoplasm risk. Immune cells play important roles in carcinogenesis. However, it is still unclear whether immune cells have a mediating effect on the HR-HPV infection and tobacco exposure with cervical neoplasm development. Aim: The aim of this study was to determine how the increased white blood cell (WBC) count affects the relationship between HR-HPV DNA load and tobacco exposure in the development of cervical neoplasia. Methods: A hospital-based case–control study design was conducted with a total of 108 cases of Taiwanese women with ≥ cervical intraepithelial neoplasia (CIN) I confirmed by biopsy, and 222 healthy Taiwanese female subjects with negative findings on a Pap smear were assigned to the control group. The study evaluated HR-HPV status and immune cell counts (WBCs, natural killer (NK) cells) and tobacco exposure by a self-construct questionnaire. Results: Both HR-HPV DNA load and tobacco exposure significantly independently increased cervical neoplasm risk (AORs: 1.28 and 1.42, respectively). Similar significant results were found for WBCs and NK cells, with respective AORs of 1.20 and 1.00. Moreover, increased WBCs (β = 0.04, 95% CI corrected: 0.01–0.07) and tobacco exposure (β = 0.02, 95% CI corrected: 0.01–0.04) mediated the relationship between the high-risk HPV DNA load and cervical neoplasm risk. Conclusions: Elevated WBC count acts as both predictor and mediator in cervical neoplasm development linked to HR-HPV DNA load. Monitoring and maintaining WBC levels within the normal range could be a preventive strategy for cervical neoplasm development. [ABSTRACT FROM AUTHOR]

Background: Inflammation is integral to diabetes pathogenesis. The novel hematological inflammatory biomarker, platelet to white blood cell ratio (PWR), is linked with various conditions such as chronic kidney disease and stroke. However, the association of this novel clinical indicator with diabetes still remains unclear, which is investigated in this study. Materials and Methods: A total of 10,973 Chinese participants were included and grouped according to the tertiles of PWR (T1, T2, and T3 groups). Diagnosis of prediabetes and diabetes adhered to American Diabetes Association criteria. Binary logistic regression was adopted to assess the relationship between PWR and both diabetes and prediabetes. The dose-response relationship of PWR and diabetes was examined using restricted cubic spline regression. Subgroup and interaction analyses were conducted to investigate potential covariate interactions. Results: Individuals with higher PWR had better lifestyles and lipid profiles (all P < 0.05). After adjusting for all the covariates, the T2 group had a 0.83-fold (95% CI: 0.73-0.93, P < 0.01) risk of diabetes and that for the T3 group was 0.68-fold (95% CI: 0.60-0.78. P < 0.001). Dose-response analysis identified non-linear PWR-diabetes associations in the general population and females (both P < 0.05), but absent in males. Participants with prediabetes in the T2 and T3 groups had lower risks of diabetes (OR = 0.80 for the T2 group, P < 0.001 and 0.68 for the T3 group, P<0.001) in the full models. All the sensitivity analysis support consistent conclusions. Conclusions: An increase in PWR significantly correlates with reduced diabetes risks. A non-linear PWR-diabetes relationship exists in the general population and females, but not in males. The correlation between PWR and diabetes indicates that PWR holds potentials in early identification and prevention of diabetes. [ABSTRACT FROM AUTHOR]

Blood is one of the human tissues in which potassium bromate (KBrO3) is hazardous. This investigation aims to assess the impact of Corchorus olitorius (C. olitorius) on KBrO3-induced haematological parameters derangement. C. olitorius leaves were extracted with a soxhlet extractor and a solvent of 95% ethanol. Groups A, B, C, and D were created from twenty-four mature male Wistar rats acclimated for seven days. Group A was given distilled water orally. In addition to the 100 mg/kg b.w of KBrO3 given to groups B, C, and D of animals, 100 and 200 mg/kg body weight of C. olitorius were also administered to groups C and D respectively. After the 28-day treatment period, blood samples were collected for examination. Animals intoxicated with KBrO3 demonstrated substantial (P<0.05) decrease in most blood parameters compared to the animals in the control group (haemoglobin level, red blood cell count, packed cell volume, total white cell count, neutrophil count, lymphocyte count, monocyte count and platelet count). The disordered haematological parameters were, however, dose-dependently corrected in the potassium bromate-intoxicated rats treated with C. olitorius. KBrO3 caused a significant decrease in haemoglobin level, red blood cell count, packed cell volume, total white blood cell count, neutrophil count, lymphocyte count, monocyte count and platelet count as well as elevated erythrocyte sedimentation rate (ESR), but C. olitorius treatment reversed these effects. Therefore, more studies are needed to further validate these findings. [ABSTRACT FROM AUTHOR]

The morphological classification of nucleated blood cells is fundamental for the diagnosis of hematological diseases. Many Deep Learning algorithms have been implemented to automatize this classification task, but most of the time they fail to classify images coming from different sources. This is known as “domain shift”. Whereas some research has been conducted in this area, domain adaptation techniques are often computationally expensive and can introduce significant modifications to initial cell images. In this article, we propose an easy-to-implement workflow where we trained a model to classify images from two datasets, and tested it on images coming from eight other datasets. An EfficientNet model was trained on a source dataset comprising images from two different datasets. It was afterwards fine-tuned on each of the eight target datasets by using 100 or less-annotated images from these datasets. Images from both the source and the target dataset underwent a color transform to put them into a standardized color style. The importance of color transform and fine-tuning was evaluated through an ablation study and visually assessed with scatter plots, and an extensive error analysis was carried out. The model achieved an accuracy higher than 80% for every dataset and exceeded 90% for more than half of the datasets. The presented workflow yielded promising results in terms of generalizability, significantly improving performance on target datasets, whereas keeping low computational cost and maintaining consistent color transformations. Source code is available at: https://github.com/mc2295/WBC_Generalization

Introduction: Post-resuscitation care of cardiac arrest patients may be complicated by systemic inflammation elicited in response to whole-body ischaemia–reperfusion injury. We assessed the association between early WBC with one-year mortality in a large, unselected population of cardiac arrest patients. Methods: We collected a retrospective multicentre cohort of ICU-treated CA patients from the Finnish national ICU registry. We used locally estimated scatterplot smoothing (LOESS) curve to assess the association between the most abnormal WBC of the first 24 h in the ICU with the likelihood of death within a year. Multivariable logistic regression analyses were performed to assess the independent association between WBC and one-year mortality. In nested cohort analysis, we tested the association of delay from collapse to return of spontaneous circulation (ROSC) with WBC in linear regression models. Results: The LOESS curve was U-shaped, with the lowest predicted mortality at 7.5 109/L WBC. Based on this cut-off value, patients were divided into high (≥ 7.5 109/L) and low (< 7.5 109/L) WBC groups. In 4229 patients with high WBC, higher WBC was independently associated with increased one-year mortality (adjusted odds ratio (OR) 1.03 per 109/L, 95 % confidence interval (CI) 1.02–1.04, p

Leukemia is a type of cancer characterized by the exponential growth of abnormal blood cells, which damages white blood cells and disrupts the function of the human body’s bone marrow. It is very challenging to classify because blood smear images are complicated, and there is a lot of variation between each class. Acute Lymphoblastic Leukemia (B-ALL) is one of the subtypes of leukemia. It is a rapidly progressing cancer that originates in B lymphocytes, characterized by the overproduction of immature B lymphoblasts. The purpose of this work is to classify different types of B-ALL subtypes such as Benign, Malignant Early Pre-B, Malignant Pre-B, and Malignant Pro-B from the peripheral blood smear images effectively. To accomplish this task, a novel deep-learning technique based on a fine-tuned ResNet-50 model has been developed. Our fine-tuned ResNet-50 model integrates several additional customized fully connected layers, including dense and dropout layers. Various data augmentation techniques such as flipping, rotation, and zooming have been applied to mitigate the risk of overfitting. In addition, a five-fold cross-validation technique has been employed to enhance the model’s generalization. The performance of our proposed technique is compared with several other methods, including VGG-16, DenseNet-121, and EfficientNetB0, as well as existing baselines, using different performance metrics. Experimental results demonstrate the superiority of the fine-tuned ResNet-50 model, achieving the highest accuracy and an F1-score of 99.38%. It also outperforms existing state-of-the-art approaches by a significant margin. The proposed fine-tuned ReNet-50 model achieves such performance without the need for microscopic image segmentation which indicates its potential utility in healthcare sectors in enhancing precise leukemia diagnosis.

Background: Multiple studies, including both humans and animals, have demonstrated that gasoline, kerosene, and diesel fuel exhaust emissions include chemical components harmful to the bone marrow, lymph nodes, and spleen. This study aimed to evaluate the impact of kerosene and naphtha vapors on several blood parameters in rats. Methods and Results: The study was conducted on 10–12-week-old male Wistar albino rats (Rattus norvegicus) (n=20) weighing 150–200g. The experimental rats were categorized into two groups, each including five animals. The rats were exposed to kerosene and naphtha vapors for 15, 30, and 45 days, with six hours of daily exposure. Two control groups of animals, each including five animals, were exposed to room air. One group of rats was allowed to inhale the vapors emitted by the evaporating kerosene. Another group underwent an identical process for the naphtha vapors. Both groups of animals were exposed to daily vapors for six hours, from 9:00 a.m. to 3:00 p.m., six days a week, for three different durations: 15, 30, and 45 days. Blood samples were tested for hematological indices using a Cell Dyn Ruby Hematology Analyzer (Abbott, USA). On days 15, 30, and 45 of the experiment, rats exposed to kerosene and naphtha vapors had an increase in the total number of leukocytes, an increase in the percentage of lymphocytes, and a decrease in the percentage of neutrophils, compared to the control group (P

Yusuke Yagi,1,2 Akito Doke,1,3 Saya Iwame,1,3 Yu Arakawa,1,4 Yuka Yamagishi1,4 1Department of Infection Prevention and Control, Kochi Medical School Hospital, Nankoku, Kochi, Japan; 2Department of Pharmacy, Kochi Medical School Hospital, Nankoku, Kochi, Japan; 3Department of Clinical Laboratory, Kochi Medical School Hospital, Nankoku, Kochi, Japan; 4Department of Clinical Infectious Diseases, Kochi Medical School, Kochi University, Nankoku, Kochi, JapanCorrespondence: Yuka Yamagishi, Department of Clinical Infectious Diseases, Kochi Medical School, Kochi University, Nankoku, Kochi, 783-8505, Japan, Tel +81 88 866 5811, Fax +81 88 880 2611, Email y.yamagishi@mac.comBackground: Methicillin-resistant Staphylococcus aureus (MRSA) enteritis is a condition in which MRSA grows abnormally in the intestine after administration of antimicrobial agents, resulting in enteritis. Patients with MRSA detected in stool culture tests are often diagnosed with MSRA enteritis. However, uncertainty remains in the diagnostic criteria; therefore, we conducted epidemiological studies to define these cases.Patients and Methods: Patients who tested positive for MRSA by stool culture using selective media 48 h after admission to Kochi Medical School Hospital between April 1, 2012, and December 31, 2022, and did not meet the exclusion criteria were included. We defined MRSA enteritis (Group A) as cases that were responsive to treatment with vancomycin hydrochloride powder, had a Bristol Stool Scale of ≥ 5, and a stool frequency of at least three times per day; all others were MRSA carriers (Group B). Multivariate analysis was performed to risk factors associated with MRSA enteritis.Results: Groups A and B included 18 (25.4%) and 53 (74.6%) patients, respectively. Multivariate logistic regression analysis showed that a white blood cell count of > 10000/μL (odds ratio [OR], 5.50; 95% confidence interval [CI], 1.12– 26.9), MRSA count of ≥ 2+ in stool cultures (OR, 8.91; 95% CI, 1.79– 44.3), and meropenem administration within 1 month of stool specimen submission (OR, 7.47; 95% CI, 1.66– 33.6) were risk factors of MRSA enteritis.Conclusion: The case definitions reviewed for MRSA enteritis may be useful as diagnostic criteria. Keywords: MRSA enteritis, diagnostic criteria, white blood cell, MRSA counts in stool cultures, meropenem

Objective: Longitudinal hematological changes throughout twin pregnancies have not been reported. This study aimed to reveal longitudinal changes in hematological indices in twin pregnancies. Materials and methods: We conducted a retrospective chart review of hematological changes in uncomplicated twin pregnancies delivered at ≥37 weeks of gestation between 2010 and 2013 and randomly selected uncomplicated singletons during the same period. A complete blood count and hemogram were performed as blood examinations in the first trimester (9–13 weeks), late second trimester (22–27 weeks), mid-third trimester (33–35 weeks, only in twin pregnancies), and late third trimester (36–38 weeks). We evaluated inter-trimester differences in hematological indices and compared the values between twin and singleton pregnancies in each trimester. Results: The final analysis group included 60 twin pregnancies and 63 singleton pregnancies. The white blood cell (WBC) count in twin pregnancies decreased throughout the pregnancy after the first trimester and became significantly lower than that in singletons in the late third trimester. The WBC count showed only a slight decrease in the third trimester in singleton pregnancies, whereas it showed a marked decrease throughout the pregnancy in twin pregnancies. The marked decrease in the total WBC count in twin pregnancies is mainly due to a decrease in neutrophils. The red blood cell count and hemoglobin and hematocrit values in twin pregnancies showed more marked decreases in the second trimester than in singletons. No decrease was observed after the second trimester of pregnancy. The platelet count decreased in the third trimester of twin pregnancies. Conclusion: We clarified the longitudinal hematological changes in twin pregnancies that showed augmentation of or differed from those of singleton pregnancies. It should be specifically mentioned that the WBC count markedly decreased through pregnancy after the first trimester, which is a characteristic change in twin pregnancies.

Abstract Acute compartment syndrome (ACS) is a severe orthopedic issue that, if left untreated, can result in lasting nerve and muscle damage or even necessitate amputation. The association between admission laboratory blood test indicators and the occurrence of ACS in patients with tibial diaphysis fractures is currently a subject of debate. The objective of this research was to identify the contributing factors for ACS in individuals suffering from tibial diaphysis fractures. In this retrospective study, we collected data on a total of 705 individuals from our hospital, comprising 86 ACS patients and 619 non-ACS patients with tibial diaphysis fractures. These participants were categorized into two distinct groups: the ACS group and the non-ACS group. Despite the inherent limitations associated with retrospective analyses, such as potential biases in data collection and interpretation, we conducted a comprehensive analysis of demographics, comorbidities, and admission lab results. Our analytical approach included univariate analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis techniques, aiming to mitigate these limitations and provide robust findings. The statistical analysis revealed several predictors of ACS, including gender (p = 0.011, OR = 3.200), crush injuries (p = 0.004, OR = 4.622), lactic dehydrogenase (LDH) levels (p

Background: Mobilization of certain immune cells may improve the ability of the immune system to combat tumor cells, but the effect of acute exercise on mobilizing immune cells has been sparsely investigated in cancer patients. Therefore, we examined how acute exercise influences circulating immune cells in breast cancer patients. Methods: Nineteen newly diagnosed breast cancer patients aged 36–68 performed 30 minutes of moderate-intensity exercise with a cycle ergometer. Blood samples were collected at various time points: at rest, at 15 (E15) and 30 minutes (E30) after onset of the exercise, and at 30 and 60 minutes postexercise. We analyzed several immune cell subsets using flow cytometry. Results: Acute exercise increased the number of total leukocytes, neutrophils, lymphocytes, monocytes, basophils, total T-cells, CD4+ T-cells, T helper (Th) 2- cells, Th 17-cells, CD8+ T-cells, CD4- CD8- T-cells, CD56+ natural killer (NK) cells, and CD14- CD16+ monocytes. Many of the changes were transient. Proportions of NK-cells and CD8+ T-cells increased, while the proportion of myeloid derived suppressor cells (MDSCs) reduced, and proportion of regulatory T-cells remained unchanged by exercise. Several associations were detected between cell mobilizations and disease state. For instance, tumor size correlated negatively with NK cell mobilization at E15, and progesterone receptor positivity correlated negatively with CD8+ T-cell mobilization. Conclusion: The findings show that the proportions of CD8+ T-cells and NK cells increased and the proportion of MDSCs proportion decreased in breast cancer patients after 30-minute exercise, suggesting a change in the profile of circulating immune cells towards more cytotoxic/anti-tumorigenic. The mobilization of some immune cells also appears to be related to the disease state. [ABSTRACT FROM AUTHOR]

Background: Neurocardiogenic injury is common after aneurysmal subarachnoid hemorrhage (aSAH) despite low prevalence of preexisting cardiac disease. Potential mechanisms include autonomic dysregulation due to excess catecholamines as well as systemic inflammation. Understanding how inflammation contributes to cardiac dysfunction may aid in identifying novel therapeutic strategies. Here, we investigated serum leukocytes as predictors of left ventricular systolic dysfunction in patients with aSAH. We also investigated increased cardiac macrophages in an animal model of SAH and whether immunomodulatory treatment could attenuate this inflammatory response. Methods: We retrospectively analyzed 256 patients with aSAH admitted to University of Illinois Hospital between 2013 and 2019. Our inclusion criteria included patients with aSAH receiving an echocardiogram within 72 h of admission. Our primary outcome was echocardiographic evidence of systolic dysfunction. We performed multinomial regression and receiver operating curve analysis. We also used the endovascular perforation model of SAH in male Sprague–Dawley rats to assess for myocardial inflammation. Two days after surgery, hearts were collected and stained for the macrophage marker Iba-1. We compared the presence and morphology of macrophages in cardiac tissue isolated from SAH animals and sham controls treated with and without the immunomodulatory agent fingolimod. Results: Of 256 patients with aSAH, 233 (91.0%) underwent echocardiography within 72 h of admission. Of 233, 81 (34.7%) had systolic dysfunction. Patients had baseline differences in the presence of hypertension, alcohol use, and admission Glasgow Coma Scale and Hunt-Hess score. On multivariable analysis, total leukocytes (odds ratio 1.312, p < 0.001), neutrophils (odds ratio 1.242, p = 0.012), and monocytes (odds ratio 6.112, p = 0.008) were independent predictors of reduced systolic function, whereas only monocytes (odds ratio 28.014, p = 0.030) predicted hyperdynamic function. Within the rodent heart, there were increased macrophages after SAH relative to controls, and this was attenuated by fingolimod treatment (p < 0.0001). Conclusions: Increased serum leukocytes are associated with abnormal left ventricular systolic function following aSAH. The strongest independent predictor of both reduced and hyperdynamic systolic function was increased monocytes. Increased cardiac macrophages after experimental SAH can also be targeted by using immunomodulatory drugs. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the efficacy of a pre-procedural white blood cell (WBC) count in the prediction of contrast-induced acute kidney injury (CI-AKI) risk in coronary artery disease patients receiving a percutaneous coronary intervention (PCI). This observational study comprises a sample of 1,013 coronary artery disease patients (including ACS and stable angina) receiving PCI, gathered from September 2015 to July 2017. CI-AKI incidence in the study population was 4.8% (49/1013). Patients in the CI-AKI group had significantly higher WBC counts than those in the non-CI-AKI group (10.41 ± 5.37 vs. 8.09 ± 3.10, p = 0.004). Logistic analysis showed that WBC count (odds ratio [OR]: 1.12, 95% CI [1.03–1.21], P = 0.006) was a significant and independent predictor of CI-AKI risk in patients receiving PCI, Receiver-operating characteristic (ROC) curve analysis found that pre-procedural WBC count ≥11.03*109/L was the optimal cut-off value in the prediction of CI-AKI risk with a sensitivity of 41.0% and a specificity of 86.5%. Patients with CI-AKI had a significantly worse 1-year survival rate than patients without CI-AKI (91.8% vs. 97.6%, P = 0.012). In summary, increased pre-procedural WBC count is associated with an increased risk of developing CI-AKI in patients receiving PCI. [ABSTRACT FROM AUTHOR]

Acute compartment syndrome (ACS) is a severe orthopedic issue that, if left untreated, can result in lasting nerve and muscle damage or even necessitate amputation. The association between admission laboratory blood test indicators and the occurrence of ACS in patients with tibial diaphysis fractures is currently a subject of debate. The objective of this research was to identify the contributing factors for ACS in individuals suffering from tibial diaphysis fractures. In this retrospective study, we collected data on a total of 705 individuals from our hospital, comprising 86 ACS patients and 619 non-ACS patients with tibial diaphysis fractures. These participants were categorized into two distinct groups: the ACS group and the non-ACS group. Despite the inherent limitations associated with retrospective analyses, such as potential biases in data collection and interpretation, we conducted a comprehensive analysis of demographics, comorbidities, and admission lab results. Our analytical approach included univariate analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis techniques, aiming to mitigate these limitations and provide robust findings. The statistical analysis revealed several predictors of ACS, including gender (p = 0.011, OR = 3.200), crush injuries (p = 0.004, OR = 4.622), lactic dehydrogenase (LDH) levels (p < 0.001, OR = 1.003), and white blood cell (WBC) count (p < 0.001, OR = 1.246). Interestingly, the study also found that certain factors, such as falls on the same level (p = 0.007, OR = 0.334) and cholinesterase (CHE) levels (p < 0.001, OR = 0.721), seem to provide a degree of protection against ACS. In order to better predict ACS, the ROC curve analysis was employed, which determined threshold values for LDH and WBC. The established cut-off points were set at 266.26 U/L for LDH and 11.7 × 109 cells per liter for WBC, respectively. Our research has successfully pinpointed gender, crush injuries, LDH levels, and white blood cell (WBC) count as crucial risk factors for the development of ACS in patients experiencing tibial diaphysis fractures. Furthermore, by establishing the cut-off values for LDH and WBC, we have facilitated a more personalized assessment of ACS risk, enabling clinical doctors to implement targeted early interventions and optimize patient outcomes. [ABSTRACT FROM AUTHOR]

White blood cell (WBC) and mean platelet volume (MPV) counts are related to stroke events, but relationship between their combined indicator (WBC count-to-MPV count ratio (WMR)) and the risk of fatal stroke occurrence is unclear so far. In this prospective analysis, we enrolled 27,163 participants aged 50 years or older without a stroke history in the Guangzhou Biobank Cohort Study. After a mean follow-up time of 15.0 (SD = 2.2) years with 389,242 personyears, 816 stroke (401 ischaemic, 259 haemorrhagic and 156 unclassified) deaths were recorded. Cox's proportional hazards regression was used to estimate the hazard ratios (HRs) and the 95% confidence intervals (CIs). Compared with those in the lowest quartile, participants with the highest WMR had different risks for fatal all stroke and fatal ischaemic stroke, respectively, although an increased risk for fatal ischaemic stroke was observed among participants in the fourth WMR quartile and further hs-CRP adjustment; those in the WMR change with 10% increase had a 36% increased risk of fatal all stroke and a 79% increased risk of fatal haemorrhagic stroke, compared to those in a stable (the WMR change between -10% and 10%). Our findings suggest that higher WMR and its longitudinal change were associated with an increased risk of fatal stroke occurrence in middle-aged to older Chinese; it may be a potential indicator for the future fatal stroke occurrence in relatively healthy elderly populations. [ABSTRACT FROM AUTHOR]

Min Cai,1,&ast; Yue Deng,2,&ast; Tianyang Hu3 1Department of Nephropathy and Rheumatism, Yongchuan Hospital of Chongqing Medical University (The Fifth Clinical College of Chongqing Medical University), Chongqing, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, The Fifth People’s Hospital of Chongqing, Chongqing, People’s Republic of China; 3Precision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Tianyang Hu, Email hutianyang@stu.cqmu.edu.cnPurpose: Acute kidney injury (AKI) is a common complication of acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and inflammation is the potential link between AKI and AECOPD. However, little is known about the incidence and risk stratification of AKI in critically ill AECOPD patients. In this study, we aimed to establish risk model based on white blood cell (WBC)-related indicators to predict AKI in critically ill AECOPD patients.Material and Methods: For the training cohort, data were taken from the Medical Information Mart for eICU Collaborative Research Database (eICU-CRD) database, and for the validation cohort, data were taken from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. The study employed logistic regression analysis to identify the major predictors of WBC-related biomarkers on AKI prediction. Subsequently, a risk model was developed by multivariate logistic regression, utilizing the identified significant indicators.Results: Finally, 3551 patients were enrolled in training cohort, 926 patients were enrolled in validation cohort. AKI occurred in 1206 (33.4%) patients in training cohort and 521 (56.3%) patients in validation cohort. According to the multivariate logistic regression analysis, four WBC-related indicators were finally included in the novel risk model, and the risk model had a relatively good accuracy for AKI in the training set (C-index, 0.764, 95% CI 0.749– 0.780) as well as in the validation set (C-index, 0.738, 95% CI: 0.706– 0.770). Even after accounting for other models, the critically ill AECOPD patients in the high-risk group (risk score > 3.44) still showed an increased risk of AKI (odds ratio: 4.74, 95% CI: 4.07– 5.54) compared to those in low-risk group (risk score ≤ 3.44). Moreover, the risk model showed outstanding calibration capability as well as therapeutic usefulness in both groups for AKI and ICU mortality and in-hospital mortality of critical ill AECOPD patients.Conclusion: The novel risk model showed good AKI prediction performance. This risk model has certain reference value for the risk stratification of AECOPD complicated with AKI in clinically.Keywords: risk model, acute kidney injury, prediction, white blood cell, acute exacerbation of chronic obstructive pulmonary disease

Introduction: Studies have linked obesity with cognitive impairment and low-grade inflammation; however, results have been inconsistent. The aim of this study was to compare global cognitive function and its relationship with indices of obesity and total and differential white blood cell (WBC) counts in obese and normal-weight undergraduates in Kano, Nigeria. Materials and Methods: Eighty participants (40 obese and 40 normal weights) were randomly recruited for this case–control descriptive study. Anthropometric indices were measured according to the World Health Organization’s Stepwise protocol; global cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), while the WBC count was performed by manual Leishman staining technique. Data were analyzed on statistical package for social science using an independent t-test, Chi-square test of association, Pearson’s correlation, and simple linear regression. Results: The mean age of the participants is 24 years, obese a year older (t = -2.2, P = 0.030). There was no significant difference in global cognitive function score (MoCA score) between the obese and normal-weight participants (t = -1.08, P = 0.283). However, 40% of the normal weight and 42% of the obese participants had mild cognitive impairment. Similarly, the two groups did not differ in total and differential WBC count except for %monocyte, which was higher in normal-weight participants (t = 2.22, P = 0.029). None of the anthropometric and WBC indices correlated with the MoCA score; however, %monocyte was negatively correlated with body mass index (BMI) (r = -0.244, P = 0.029), waist circumference (r = -0.216, P = 0.050), hip circumference (r = -0.234, P = 0.037), and wait-to-height ratio (r = -0.245, P = 0.028) among the whole while %lymphocyte was negatively correlated with BMI (r = -0.311, P = 0.050) among obese participants. Conclusion: Obesity is not associated with a decline in cognitive function and inflammation in obese and normal-weight undergraduates in Nigeria.

White blood cell (WBC) recognition is still a challenging problem because of the high variability and complexity of blood cell images. Blood cell images can vary in quality, resolution, contrast, illumination, staining, and background. Blood cells can also vary in shape, size, color, texture, and distribution. Moreover, blood cells can overlap, cluster, or deform, making them challenging to segment and identify. This paper proposed an efficient automatic illumination compensation algorithm using singular value decomposition in the cosine domain (CSVDC) to enhance WBC images in the preprocessing step. Firstly, the WBC color image is split into three color channels and then mapped to the frequency domain using the discrete cosine transform (DCT) to get their DCT coefficient matrices. Next, the compensation coefficients are constructed based on the DC terms and DCT coefficient matrices’ most significant singular values. The DCT coefficient matrices are then linearly adjusted by multiplying with the compensation coefficients. Finally, three color channels are reconstructed using the inverted DCT to get the enhanced WBC image. Experimental results for the four most common PBC_dataset_normal_DIB, Raabin-WBC, BCCD, and Munich AML Morphology datasets using state-of-art deep learning models, including VGG16, GoogLeNet, and RestNet, illustrate the effectiveness of the CSVDC algorithm. In particular, on the PBC_dataset_normal_DIB dataset, when using the ResNet, the proposed enhanced WBC images have a higher average recognition rate compared to the original, ASVDF, ASVDW, and AHOSVD images by 3.82%, 2.69%, 11.37%, and 8.62%, respectively. Experimental results show that our method dramatically improves deep learning-based WBC recognition accuracy.

Abstract Background White blood cell (WBC) count increases during pregnancy, necessitating reliable reference intervals for assessing infections and pregnancy-related complications. This study aimed to establish comprehensive reference intervals for WBC counts during pregnancy. Methods The analysis included 17,737 pregnant women, with weekly WBC count measurements from pre-pregnancy to postpartum. A threshold linear regression model determined reference intervals, while Harris and Boyd’s test partitioned the intervals. Results WBC count exhibited a significant increase during pregnancy, characterized by a rapid rise before 7 weeks of gestation, followed by a plateau. Neutrophils primarily drove this increase, showing a similar pattern. The threshold regression model and Harris and Boyd’s test supported partitioned reference intervals for WBC counts: 4.0–10.0 × 10^9/L for = 6 weeks of gestation. These reference intervals identified pregnant women with high WBC counts, who had a higher incidence of pregnancy-related complications including placenta previa, oligohydramnios, secondary uterine inertia, and intrauterine growth restriction. Conclusion This study establishes comprehensive reference intervals for WBC counts during pregnancy. Monitoring WBC counts is clinically relevant, as elevated levels are associated with an increased risk of infection and pregnancy-related complications.

Objective: To evaluate the effect of rosmarinic acid on tracheal smooth muscle responsiveness and lung pathological changes in ovalbumin-sensitized rats. Methods: Rats were randomly divided into six groups: the control group, the asthmatic group, and the asthmatic groups treated with dexamethasone (1 mg/kg; oral gavage) or three doses of rosmarinic acid (0.5, 1, and 2 mg/kg; oral gavage). For induction of asthma, rats received intraperitoneal injections and inhalation of ovalbumin. After 21 days, bronchoalveolar lavage fluid and lung samples were collected for histopathological analyses. Moreover, total and differential white blood cell counts were determined. Results: The rosmarinic acid-treated group had significantly lower tracheal smooth muscle responses to methacholine than the asthmatic group. In addition, rosmarinic acid reduced white blood cell count and the percentages of eosinophils, monocytes, and neutrophils while increasing the percentage of lymphocytes. Ovalbumin-induced lung pathological changes were significantly improved by treatment with rosmarinic acid. Conclusions: Rosmarinic acid improves tracheal smooth muscle responsiveness and lung pathological changes in ovalbumin-sensitized rats.

Combined radiation with hemorrhage (combined injury, CI) exacerbates hematopoietic acute radiation syndrome and mortality compared to radiation alone (RI). We evaluated the effects of RI or CI on blood cell depletion as a biomarker to differentiate the two. Male CD2F1 mice were exposed to 8.75 Gy γ-radiation (60Co). Within 2 h of RI, animals were bled under anesthesia 0% (RI) or 20% (CI) of total blood volume. Blood samples were collected at 4–5 h and days 1, 2, 3, 7, and 15 after RI. CI decreased WBC at 4–5 h and continued to decrease it until day 3; counts then stayed at the nadir up to day 15. CI decreased neutrophils, lymphocytes, monocytes, eosinophils, and basophils more than RI on day 1 or day 2. CI decreased RBCs, hemoglobin, and hematocrit on days 7 and 15 more than RI, whereas hemorrhage alone returned to the baseline on days 7 and 15. RBCs depleted after CI faster than post-RI. Hemorrhage alone increased platelet counts on days 2, 3, and 7, which returned to the baseline on day 15. Our data suggest that WBC depletion may be a potential biomarker within 2 days post-RI and post-CI and RBC depletion after 3 days post-RI and post-CI. For hemorrhage alone, neutrophil counts at 4–5 h and platelets for day 2 through day 7 can be used as a tool for confirmation. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effect of rosmarinic acid on tracheal smooth muscle responsiveness and lung pathological changes in ovalbumin-sensitized rats. Methods: Rats were randomly divided into six groups: the control group, the asthmatic group, and the asthmatic groups treated with dexamethasone (1 mg/kg; oral gavage) or three doses of rosmarinic acid (0.5, 1, and 2 mg/kg; oral gavage). For induction of asthma, rats received intraperitoneal injections and inhalation of ovalbumin. After 21 days, bronchoalveolar lavage fluid and lung samples were collected for histopathological analyses. Moreover, total and differential white blood cell counts were determined. Results: The rosmarinic acid-treated group had significantly lower tracheal smooth muscle responses to methacholine than the asthmatic group. In addition, rosmarinic acid reduced white blood cell count and the percentages of eosinophils, monocytes, and neutrophils while increasing the percentage of lymphocytes. Ovalbumin-induced lung pathological changes were significantly improved by treatment with rosmarinic acid. Conclusions: Rosmarinic acid improves tracheal smooth muscle responsiveness and lung pathological changes in ovalbuminsensitized rats. [ABSTRACT FROM AUTHOR]

(1) Background: The incidence of vancomycin-induced neutropenia in hospitalized patients is estimated to be around 2 to 8 percent Data surrounding vancomycin-induced neutropenia is limited as it is based on a small number of observational case reports. Additionally, it is difficult to provide generalized conclusions since patient characteristics and indications for treatment vary between reports. (2) Case Reports: We present two cases of vancomycin-induced neutropenia that occurred at our facility; a 50-year-old male who developed neutropenia after treatment with vancomycin for a gluteal abscess and a 51-year-old female who developed neutropenia after treatment with vancomycin for lumbar osteomyelitis. In both cases, neutropenia resolved within 2 days of discontinuation of vancomycin. (3) Conclusions: Vancomycin-induced neutropenia is thought to be a relatively uncommon adverse drug reaction. These two cases of neutropenia likely caused by prolonged exposure to vancomycin occurred at our facility within 3 months of each other. Additional studies are needed to better understand the true incidence of this adverse drug reaction and to identify risk factors that may predispose patients to vancomycin-induced neutropenia. [ABSTRACT FROM AUTHOR]

Background: Blood diseases such as leukemia, anemia, lymphoma, and thalassemia are hematological disorders that relate to abnormalities in the morphology and concentration of blood elements, specifically white blood cells (WBC) and red blood cells (RBC). Accurate and efficient diagnosis of these conditions significantly depends on the expertise of hematologists and pathologists. To assist the pathologist in the diagnostic process, there has been growing interest in utilizing computer-aided diagnostic (CAD) techniques, particularly those using medical image processing and machine learning algorithms. Previous surveys in this domain have been narrowly focused, often only addressing specific areas like segmentation or classification but lacking a holistic view like segmentation, classification, feature extraction, dataset utilization, evaluation matrices, etc. Methodology: This survey aims to provide a comprehensive and systematic review of existing literature and research work in the field of blood image analysis using deep learning techniques. It particularly focuses on medical image processing techniques and deep learning algorithms that excel in the morphological characterization of WBCs and RBCs. The review is structured to cover four main areas: segmentation techniques, classification methodologies, descriptive feature selection, evaluation parameters, and dataset selection for the analysis of WBCs and RBCs. Results: Our analysis reveals several interesting trends and preferences among researchers. Regarding dataset selection, approximately 50% of research related to WBC segmentation and 60% for RBC segmentation opted for manually obtaining images rather than using a predefined dataset. When it comes to classification, 45% of the previous work on WBCs chose the ALL-IDB dataset, while a significant 73% of researchers focused on RBC classification decided to manually obtain images from medical institutions instead of utilizing predefined datasets. In terms of feature selection for classification, morphological features were the most popular, being chosen in 55% and 80% of studies related to WBC and RBC classification, respectively. Conclusion: The diagnostic accuracy for blood-related diseases like leukemia, anemia, lymphoma, and thalassemia can be significantly enhanced through the effective use of CAD techniques, which have evolved considerably in recent years. This survey provides a broad and in-depth review of the techniques being employed, from image segmentation to classification, feature selection, utilization of evaluation matrices, and dataset selection. The inconsistency in dataset selection suggests a need for standardized, high-quality datasets to strengthen the diagnostic capabilities of these techniques further. Additionally, the popularity of morphological features indicates that future research could further explore and innovate in this direction. [ABSTRACT FROM AUTHOR]

Objective: Inflammation participates in the pathology and progression of secondary brain injury after intracerebral hemorrhage (ICH). This meta-analysis intended to explore the prognostic role of inflammatory indexes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), white blood cell (WBC), and C-reactive protein (CRP) in ICH patients. Methods: Embase, PubMed, Web of Science, and Cochrane Library were searched until June 2023. Two outcomes, including poor outcome and mortality were extracted and measured. Odds ratio (OR) and 95% confidence interval (CI) were presented for outcome assessment. Results: Forty-six studies with 25,928 patients were included in this metaanalysis. The high level of NLR [OR (95% CI): 1.20 (1.13–1.27), p  <  0.001], WBC [OR (95% CI): 1.11 (1.02–1.21), p  =  0.013], and CRP [OR (95% CI): 1.29 (1.08–1.54), p  =  0.005] were related to poor outcome in ICH patients. Additionally, the high level of NLR [OR (95% CI): 1.06 (1.02–1.10), p  =  0.001], WBC [OR (95% CI): 1.39 (1.16–1.66), p  <  0.001], and CRP [OR (95% CI): 1.02 (1.01–1.04), p  =  0.009] were correlated with increased mortality in ICH patients. Nevertheless, PLR was not associated with poor outcome [OR (95% CI): 1.00 (0.99–1.01), p  =  0.749] or mortality [OR (95% CI): 1.00 (0.99–1.01), p  =  0.750] in ICH patients. The total score of risk of bias assessed by Newcastle-Ottawa Scale criteria ranged from 7–9, which indicated the low risk of bias in the included studies. Publication bias was low, and stability assessed by sensitivity analysis was good. Conclusion: This meta-analysis summarizes that the high level of NLR, WBC, and CRP estimates poor outcome and higher mortality in ICH patients. [ABSTRACT FROM AUTHOR]

With the development of ultra-high-voltage (UHV) direct-current (DC) transmission, the health risk from the static electric field (SEF) generated by UHV DC transmission lines has drawn public attention. To investigate the effect of SEF exposure on white blood cell (WBC) count, mice were exposed to 56.3 kV/m SEF. Results revealed that total WBC count and lymphocyte count significantly decreased and serum levels of corticotropin-releasing hormone, adrenocorticotropic hormone and corticosterone (CORT) significantly increased after the exposure of 7d and 14d. All indices above recovered after the exposure of 21d. Analysis showed that the exposure of 7d and 14d could activate hypothalamic-pituitary-adrenal (HPA) axis. The increased CORT could bind to the glucocorticoid receptor (GR) in lymphocytes, and then promote the migration and apoptosis of lymphocytes. After the exposure of 21d, the magnitude of HPA axis activation declined through CORT-mediated negative feedback and the regulation of stress-related neural circuitry, so WBC count recovered. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the efficacy of a pre-procedural white blood cell (WBC) count in the prediction of contrast-induced acute kidney injury (CI-AKI) risk in coronary artery disease patients receiving a percutaneous coronary intervention (PCI). This observational study comprises a sample of 1,013 coronary artery disease patients (including ACS and stable angina) receiving PCI, gathered from September 2015 to July 2017. CI-AKI incidence in the study population was 4.8% (49/1013). Patients in the CI-AKI group had significantly higher WBC counts than those in the non-CI-AKI group (10.41 ± 5.37 vs. 8.09 ± 3.10, p = 0.004). Logistic analysis showed that WBC count (odds ratio [OR]: 1.12, 95% CI [1.03–1.21], P = 0.006) was a significant and independent predictor of CI-AKI risk in patients receiving PCI, Receiver-operating characteristic (ROC) curve analysis found that pre-procedural WBC count ≥11.03*109/L was the optimal cut-off value in the prediction of CI-AKI risk with a sensitivity of 41.0% and a specificity of 86.5%. Patients with CI-AKI had a significantly worse 1-year survival rate than patients without CI-AKI (91.8% vs. 97.6%, P = 0.012). In summary, increased pre-procedural WBC count is associated with an increased risk of developing CI-AKI in patients receiving PCI.

BackgroundMobilization of certain immune cells may improve the ability of the immune system to combat tumor cells, but the effect of acute exercise on mobilizing immune cells has been sparsely investigated in cancer patients. Therefore, we examined how acute exercise influences circulating immune cells in breast cancer patients.MethodsNineteen newly diagnosed breast cancer patients aged 36–68 performed 30 minutes of moderate-intensity exercise with a cycle ergometer. Blood samples were collected at various time points: at rest, at 15 (E15) and 30 minutes (E30) after onset of the exercise, and at 30 and 60 minutes post-exercise. We analyzed several immune cell subsets using flow cytometry.ResultsAcute exercise increased the number of total leukocytes, neutrophils, lymphocytes, monocytes, basophils, total T-cells, CD4+ T-cells, T helper (Th) 2-cells, Th 17-cells, CD8+ T-cells, CD4-CD8- T-cells, CD56+ natural killer (NK) cells, and CD14-CD16+ monocytes. Many of the changes were transient. Proportions of NK-cells and CD8+ T-cells increased, while the proportion of myeloid derived suppressor cells (MDSCs) reduced, and proportion of regulatory T-cells remained unchanged by exercise. Several associations were detected between cell mobilizations and disease state. For instance, tumor size correlated negatively with NK cell mobilization at E15, and progesterone receptor positivity correlated negatively with CD8+ T-cell mobilization.ConclusionThe findings show that the proportions of CD8+ T-cells and NK cells increased and the proportion of MDSCs proportion decreased in breast cancer patients after 30-minute exercise, suggesting a change in the profile of circulating immune cells towards more cytotoxic/anti-tumorigenic. The mobilization of some immune cells also appears to be related to the disease state.