Data augmentation of ultrasound imaging for non-invasive white blood cell in vitro peritoneal dialysis

The limited amount of data in the healthcare domain and the necessity of training samples for increased performance of deep learning models is a recurrent challenge,especially in medical imaging.Newborn Solutions aims to enhance its non-invasive white blood cell counting device,Neosonics,by creating synthetic in vitro ultrasound images to facilitate a more efficient image generation process.This study addresses the data scarcity issue by designing and evaluating a continuous scalar conditional Generative Adversarial Network(GAN)to augment in vitro peritoneal dialysis ultrasound images,increasing both the volume and variability of training samples.The developed GAN architecture incorporates novel design features:varying kernel sizes in the generator’s transposed convolutional layers and a latent intermediate space,projecting noise and condition values for enhanced image resolution and specificity.The experimental results show that the GAN successfully generated diverse images of high visual quality,closely resembling real ultrasound samples.While visual results were promising,the use of GAN-based data augmentation did not consistently improve the performance of an image regressor in distinguishing features specific to varied white blood cell concentrations.Ultimately,while this continuous scalar conditional GAN model made strides in generating realistic images,further work is needed to achieve consistent gains in regression tasks,aiming for robust model generalization.

Automated White Blood Cell Disease Recognition Using Lightweight Deep Learning

White blood cells(WBC)are immune system cells,which is why they are also known as immune cells.They protect the human body from a variety of dangerous diseases and outside invaders.The majority of WBCs come from red bone marrow,although some come from other important organs in the body.Because manual diagnosis of blood disorders is difficult,it is necessary to design a computerized technique.Researchers have introduced various automated strategies in recent years,but they still face several obstacles,such as imbalanced datasets,incorrect feature selection,and incorrect deep model selection.We proposed an automated deep learning approach for classifying white blood disorders in this paper.The data augmentation approach is initially used to increase the size of a dataset.Then,a Darknet-53 pre-trained deep learning model is used and finetuned according to the nature of the chosen dataset.On the fine-tuned model,transfer learning is used,and features engineering is done on the global average pooling layer.The retrieved characteristics are subsequently improved with a specified number of iterations using a hybrid reformed binary grey wolf optimization technique.Following that,machine learning classifiers are used to classify the selected best features for final classification.The experiment was carried out using a dataset of increased blood diseases imaging and resulted in an improved accuracy of over 99%.

White Blood Cells Detection Using Spectral Tresholding

The study of the morphology of White Blood Cells (WBCs) further contributes to the clinical diagnosis of blood diseases. In this research paper, we come up with an image segmentation enhancement by combining Fourier Fast Transform on smear blood capture and classical thresholding. The Fast Fourier Transform (FFT) is a very powerful tool in image processing and it was used to segment and extract the WBCs. Our image processing method uses a Fast Fourier Transform combined with filtering and an Inverse Fast Fourier Transform for the extraction and visualization of the high frequency region of the image. In order to remove residual Red Blood Cells acting as noise in the expected result, a final thresholding step is added at the end of the processing. The results presented in this article report the tests performed using our mathematical implementation. Moreover, we were able to detect and differentiate the sub-families of WBCs.

A Novel Meta-Heuristic Optimization Algorithm in White Blood Cells Classification

Some human diseases are recognized through of each type of White Blood Cell(WBC)count,so detecting and classifying each type is important for human healthcare.The main aim of this paper is to propose a computer-aided WBCs utility analysis tool designed,developed,and evaluated to classify WBCs into five types namely neutrophils,eosinophils,lymphocytes,monocytes,and basophils.Using a computer-artificial model reduces resource and time consumption.Various pre-trained deep learning models have been used to extract features,including AlexNet,Visual Geometry Group(VGG),Residual Network(ResNet),which belong to different taxonomy types of deep learning architectures.Also,Binary Border Collie Optimization(BBCO)is introduced as an updated version of Border Collie Optimization(BCO)for feature reduction based on maximizing classification accuracy.The proposed computer aid diagnosis tool merges transfer deep learning ResNet101,BBCO feature reduction,and Support Vector Machine(SVM)classifier to forma hybridmodelResNet101-BBCO-SVM an accurate and fast model for classifying WBCs.As a result,the ResNet101-BBCO-SVM scores the best accuracy at 99.21%,compared to recent studies in the benchmark.The model showed that the addition of the BBCO algorithm increased the detection accuracy,and at the same time,decreased the classification time consumption.The effectiveness of the ResNet101-BBCO-SVM model has been demonstrated and beaten in reasonable ratios in recent literary studies and end-to-end transfer learning of pre-trained models.

Automated Artificial Intelligence Empowered White Blood Cells Classification Model

White blood cells (WBC) or leukocytes are a vital component ofthe blood which forms the immune system, which is accountable to fightforeign elements. The WBC images can be exposed to different data analysisapproaches which categorize different kinds of WBC. Conventionally, laboratorytests are carried out to determine the kind of WBC which is erroneousand time consuming. Recently, deep learning (DL) models can be employedfor automated investigation of WBC images in short duration. Therefore,this paper introduces an Aquila Optimizer with Transfer Learning basedAutomated White Blood Cells Classification (AOTL-WBCC) technique. Thepresented AOTL-WBCC model executes data normalization and data augmentationprocess (rotation and zooming) at the initial stage. In addition,the residual network (ResNet) approach was used for feature extraction inwhich the initial hyperparameter values of the ResNet model are tuned by theuse of AO algorithm. Finally, Bayesian neural network (BNN) classificationtechnique has been implied for the identification of WBC images into distinctclasses. The experimental validation of the AOTL-WBCC methodology isperformed with the help of Kaggle dataset. The experimental results foundthat the AOTL-WBCC model has outperformed other techniques which arebased on image processing and manual feature engineering approaches underdifferent dimensions.

NEW METHOD FOR WHITE BLOOD CELL DETECTION BASED ON RELEVANCE VECTOR MACHINE

A new method for the white blood cell （WBC） detection is presented based on the relevance vector machine （RVM）. Firstly,the sparse relevance vectors （RVs） are obtained while fitting the 1-D histogram by RVM. Then,the needed threshold value is directly selected from these limited RVs. Finally,the entire connective WBC regions are segmented from the original image. The method is used for the WBC detection. It reduces the interference induced by the illumination and the staining. It has advantages of the high computation efficiency and the no extra parameter setting. Experimental results demonstrate good performances of the method.

Admission white blood cell count predicts short-term clinical outcomes in patients with uncomplicated Stanford type B acute aortic dissection

Objectives Inflammation has been shown to be related with acute aortic dissection （AAD）. The present study aimed to evaluate the association of white blood cell counts （WI3Cc） on admission with both in-hospital and long-term all-cause mortality in patients with uncom- plicated Stanford type B AAD. Methods From 2008 to 2010, a total of 377 consecutive patients with uncomplicated type B AAD were enrolled and then followed up. Clinical data and WBCc on admission were collected. The primary end points were in-hospital death and long-term all-cause death. Results The in-hospital death rate was 4.2%, and the long-term all-cause mortality rate was 6.9% during a median follow-up of 18.9 months. WBCc on admission was identified as a risk factor for in-hospital death by univariate Cox regression analysis as both a continuous variable and a categorical variable using a cut off of 11.0 × 109 cell/L （all P 〈 0.05）. After adjusting for age, sex and other risk factors, elevated admission WBCc was still a significant predictor for in-hospital death as both a continuous variable [hazard ratio （HR）： 1.052, 95% CI： 1.024-1.336, P = 0.002] and a categorical variable using a cut off of 11.0 × 109 cell/L （HR： 2.056, 95% CI： 1.673-5.253, P = 0.034）. No relationship was observed between WBCc on admission and long-term all-cause death. Conclusions Our results indicate that elevated WBCc upon admission might be used as a predictor for increased risk of in-hospital death in uncomplicated type B AAD. There might be no predictive value of WBCc for the long-term survival of type B AAD.

Elevated White Blood Cell Count Is Associated with an Increased Risk of Insulin Resistance among Non-Diabetic Taxi-Motorbike Drivers Working in Cotonou, Benin

High white blood cell count (WBC) and insulin resistance (IR) are interrelated events that contribute to non-communicable diseases (NCDs), including type-2 diabetes (T2D). However, associations between IR and hematological parameters have never been explored in populations of Benin. The aims of this study were to determine the prevalence of IR and associated hematological parameters in taxi-motorbike drivers (TMDs) working in Cotonou. A total of 133 participants were analyzed in this cross-sectional study. Complete blood count, including WBC and platelet, as well as fasting plasma glucose and insulin, were performed by standard procedures. IR was assessed using the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). Factors associated with IR, their odds ratios (ORs) and 95% confidence intervals (CIs) were determined by logistic regression analysis. The mean age of the study participants was 39.3 years. The HOMA-IR cut-off (75th percentile) for IR was 5.9. The overall prevalence of IR was 24.1%. IR increased with the increase of exposure duration and WBC levels. Logistic regression analysis revealed that the risk of IR increased significantly with higher total WBC, with adjusted ORs (95% CI) for the second and third tertiles of 3.56 (1.10 - 11.58) and 4.01 (1.21 - 13.31), respectively. Similar patterns of associations were observed in an analysis restricted to non-drinkers, although these estimates lacked statistical significance. BMI > 24.2 kg/m2 was independently associated with an increased risk of IR (OR = 3.82, 95% CI: 1.33 - 11.03, P = 0.013). In conclusion, the prevalence of IR in TMDs was 24.1%. IR was significantly associated with elevated WBC count and BMI. WBC may serve as a biomarker to identify individuals at the greatest IR risk.

Monitoring the changes in plasm C-reactive protein,fibrinogen and blood white cell in patients with primary hypertension combined with acute cerebral infarction

BACKGROUND： Inflammatory reaction and the increased level of its accompanying active protein play an important role in the occurrence and development of cerebral infarction. C-reactive protein, fibrinogen and white blood cell, as the monitoring index of inflammatory reaction, are very important in the occurrence and development of acute cerebral infarction. OBJECTIVE： To make a comparison between patients with primary hypertension accompanied with acute cerebral infarction and with simple primary hypertension by observing the changes in plasma C-reactive protein and fibrinogen levels as well as white blood cell and differential counts and analyzing their significances. DESIGN ： Controlled observation SETTING ： Ward Building for VIP, Shenzhen Hospital, Peking University. PARTICIPANTS： Totally 133 patients with primary hypertension were selected from Ward Building for VIP, Shenzhen Hospital, Peking University during September 2003 to September 2005, The diagnostic criteria were based on the hypertension diagnosis criteria formulated by the 7^th World Health Organization-International Society of Hypertension Guidelines （WHO-ISH） in 1998. The informed consents were obtained from all the participants. The involved patients were assigned into two groups： primary hypertension group, in which, there were 65 patients with primary hypertension （ degree 2）, including 42 males and 23 females, with mean age of （61 ±14）years and mean blood pressure of （162.7±6.8）/（94.2±8.4） mm Hg （1 mm Hg =0.133 kPa）, and primary hypertension combined with cerebral infarction group, in which, there were 68 patients with primary hypertension combined with cerebral infarction （ meeting the diagnostic criteria formulated in the 4^th National Cerebrovascular Diseases Meeting in 1995 and diagnosed by skull CT or MRI to exclude the patients with lacunar infarction）, including 42 males and 26 females, with mean age of （56±15） years and mean blood pressure of （176.4±9.2）/（96.3±9.7） mm Hg. METHODS： Plasm C-reactive protein and fibrinogen levels, and white blood cell and differential counts of patients in the two groups were examined 24 hours after stroke. The above indexes were re-examined in the primary hypertension combined with cerebral infarction group 72 hours after stroke. White blood cell and differential counts were performed with laser method （East Asia FE-95001 RAM-1, Japan）. The level of C-reactive protein was measured with turbidimetry （BNII Automatic Systems For Analysis, USA）. The level of fibrinogen was measured with algorithm method when prothrombin time was normal and with Clauss method when prothrombin time was abnormal （ACL Automatic Coagulation Analyzer, USA）. MAIN OUTCOME MEASURES： The plasm C-reactive protein and flbrinogen levels, and white blood cell and differential counts 24 hours after stroke in two groups and 72 hours after stroke in primary hypertension combined with cerebral infarction group. RESULTS： All the 133 involved patients participated in the result analysis. The plasm C-reactive protein and fibrinogen levels, and white blood cell and neutrophil counts in patients with primary hypertension were all within the normal range. The plasm C-reactive protein and fibrinogen levels, and white blood cell and neu- trophil counts in patients with primary hypertension combined with cerebral infarction were significantly higher than those in patients with primary hypertension 24 hours after stroke and 72 hours after stroke respectively[24 hours after stroke：（32.12±11.76） mg/L vs. （5.02±3.21 ） mg/L;（4.64±0.75） g/L vs. （3.12±0.49） g/L; （9.32±81）×10^9 L^- 1 vs. （5.78±1.32）×10^9L^- 1 （7.85±2.38）×10^9 L^- 1 vs.（3.49±1.28）×10^9 L^-1,t =7.094, 5.759,4.106,5.491, respectively,all P〈 0.01; 72 hours after stroke： （47.62±18.43） mg/L vs. （32.12±11.76） mg/L; （5.08±0.82） g/L vs. （4.64±0.75） g/L, t =2.864,2.220, respectively, both P 〈 0.05]. CONCLUSION： The increase in fibrinogen level and white blood cell count are the important index in monitoring primary hypertension combined with acute cerebral infarction. The increase in plasm C-reactive protein and fibrinogen levels 72 hours after stroke indicates that plasma C-reactive protein and fibrinogen are very important in the development of disease.

The Influence of Apple-or Red-Grape Pomace Enriched Piglet Diet on Blood Parameters,Bacterial Colonisation,and Marker Gene Expression in Piglet White Blood Cells

Proanthocyanidins and flavanoids, both subfamilies of the polyphenols, are highly concentrated in different fruits and berries as well as in fruit pomace. They have shown to exhibit anti-cancer, anti-microbial, anti-oxidative, and im- mune-modulatory effects in vertebrates. Herein the effect of additional apple pomace or red-grape pomace in conven- tional piglet starter feeds were investigated in 36 young growing piglets. Immunological marker gene expression was quantified by quantitative real-time RT-PCR in white blood cells, and intestinal bacterial flora was investigated from weaning to three weeks post weaning. Polyphenol content in red-grape pomace, gut content and tissues were analyzed with HPLC. Flavan-3-ols (epicatechin and catechin) and proanthocyanidins (B1, B2 and C1) were identified in the gas- tro-intestinal tract content, whereas only traces could be detected in various piglet organs. The blood parameters, he- moglobin and hematocrit, were affected and down-regulated in all groups over testing period. In both pomace treated groups more thrombocytes were present compared to the standard feeding group. It turns out, that the pomace diets had greatest impact on the bacterial content in the colon. Results demonstrate that feeding apple pomace and red- grape pomace tended to increase the number of total colonic bacteria. Steptococci/Enterococci increased in the red- grape pomace. C. perfringens was not detectable at the second time point. The number of lactobacilli increased in both applied diets. The number of Clostridium perfringens decreased with the age of the piglets. Trends of mRNA expression changes were found in white blood cell (WBC) between different feeding regimens, since the expression variability in the groups was very high. Between the different time points there were significant differences within the apple pomace group, where TNF? (p = 0.033), NF?B (p = 0.024) and Caspase 3 (p = 0.019) mRNA expression increased signifi- cantly during treatment. We conclude that both polyphenol rich feedings have the potential to positively influence the intestinal flora, blood parameters, and WBC mRNA gene expression pattern of immunological marker genes.

Histogram-Based Decision Support System for Extraction and Classification of Leukemia in Blood Smear Images

An abnormality that develops in white blood cells is called leukemia.The diagnosis of leukemia is made possible by microscopic investigation of the smear in the periphery.Prior training is necessary to complete the morphological examination of the blood smear for leukemia diagnosis.This paper proposes a Histogram Threshold Segmentation Classifier(HTsC)for a decision support system.The proposed HTsC is evaluated based on the color and brightness variation in the dataset of blood smear images.Arithmetic operations are used to crop the nucleus based on automated approximation.White Blood Cell(WBC)segmentation is calculated using the active contour model to determine the contrast between image regions using the color transfer approach.Through entropy-adaptive mask generation,WBCs accurately detect the circularity region for identification of the nucleus.The proposed HTsC addressed the cytoplasm region based on variations in size and shape concerning addition and rotation operations.Variation in WBC imaging characteristics depends on the cytoplasmic and nuclear regions.The computation of the variation between image features in the cytoplasm and nuclei regions of the WBCs is used to classify blood smear images.The classification of the blood smear is performed with conventional machine-learning techniques integrated with the features of the deep-learning regression classifier.The designed HTsC classifier comprises the binary classifier with the classification of the lymphocytes,monocytes,neutrophils,eosinophils,and abnormalities in the WBCs.The proposed HTsC identifies the abnormal activity in the WBC,considering the color and shape features.It exhibits a higher classification accuracy value of 99.6%when combined with the other classifiers.The comparative analysis expressed that the proposed HTsC model exhibits an overall accuracy value of 98%,which is approximately 3%–12%higher than the conventional technique.

MicroRNAs as potential biomarkers for diagnosis of attention deficit hyperactivity disorder

Inappropriate levels of hyperactivity,impulsivity,and inattention characterize attention deficit hyperactivity disorder,a common childhood-onset neuropsychiatric disorder.The cognitive function and learning ability of children with attention deficit hyperactivity disorder are affected,and these symptoms may persist to adulthood if they are not treated.The diagnosis of attention deficit hyperactivity disorder is only based on symptoms and objective tests for attention deficit hyperactivity disorder are missing.Treatments for attention deficit hyperactivity disorder in children include medications,behavior therapy,counseling,and education services which can relieve many of the symptoms of attention deficit hyperactivity disorder but cannot cure it.There is a need for a molecular biomarker to distinguish attention deficit hyperactivity disorder from healthy subjects and other neurological conditions,which would allow for an earlier and more accurate diagnosis and appropriate treatment to be initiated.Abnormal expression of microRNAs is connected to brain development and disease and could provide novel biomarkers for the diagnosis and prognosis of attention deficit hyperactivity disorder.The recent studies reviewed had performed microRNA profiling in whole blood,white blood cells,blood plasma,and blood serum of children with attention deficit hyperactivity disorder.A large number of microRNAs were dysregulated when compared to healthy controls and with some overlap between individual studies.From the studies that had included a validation set of patients and controls,potential candidate biomarkers for attention deficit hyperactivity disorder in children could be miR-140-3p,let-7g-5p,-30e-5p,-223-3p,-142-5p,-486-5p,-151a-3p,-151a-5p,and-126-5p in total white blood cells,and miR-4516,-6090,-4763-3p,-4281,-4466,-101-3p,-130a-3p,-138-5p,-195-5p,and-106b-5p in blood serum.Further studies are warranted with children and adults with attention deficit hyperactivity disorder,and consideration should be given to utilizing rat models of attention deficit hyperactivity disorder.Animal studies could be used to confirm microRNA findings in human patients and to test the effects of targeting specific microRNAs on disease progression and behavior.

Engineering white blood cell membrane-camouflaged nanocarriers for inflammation-related therapeutics

White blood cells(WBCs)play essential roles against inflammatory disorders,bacterial infections,and cancers.Inspired by nature,WBC membrane-camouflaged nanocarriers(WBC-NCs)have been developed to mimic the“dynamic”functions of WBCs,such as transendothelial migration,adhesion to injured blood vessels,etc,which make them promising for diverse medical applications.WBC-NCs inherit the cell membrane antigens of WBCs,while still exhibiting the robust inflammation-related therapeutic potential of synthetic nanocarriers with excellent(bio)physicochemical performance.This review summarizes the proposed concept of cell membrane engineering,which utilizes physical engineering,chemical modification,and biological functionalization technologies to endow the natural cell membrane with abundant functionalities.In addition,it highlights the recent progress and applications of WBC-NCs for inflammation targeting,biological neutralization,and immune modulation.Finally,the challenges and opportunities in realizing the full potential of WBC-NCs for the manipulation of inflammation-related therapeutics are discussed.

Rosmarinic acid improves tracheal smooth muscle responsiveness and lung pathological changes in ovalbumin-sensitized rats

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.

Clinical comprehensive treatment protocol for managing diabetic foot ulcers:A retrospective cohort study

BACKGROUND Diabetic foot ulcers(DFUs)are a common complication of diabetes,often leading to severe infections,amputations,and reduced quality of life.The current standard treatment protocols for DFUs have limitations in promoting efficient wound healing and preventing complications.A comprehensive treatment approach targeting multiple aspects of wound care may offer improved outcomes for patients with DFUs.The hypothesis of this study is that a comprehensive treatment protocol for DFUs will result in faster wound healing,reduced amputation rates,and improved overall patient outcomes compared to standard treatment protocols.AIM To compare the efficacy and safety of a comprehensive treatment protocol for DFUs with those of the standard treatment protocol.METHODS This retrospective study included 62 patients with DFUs,enrolled between January 2022 and January 2024,randomly assigned to the experimental(n=32)or control(n=30)group.The experimental group received a comprehensive treatment comprising blood circulation improvement,debridement,vacuum sealing drainage,recombinant human epidermal growth factor and anti-inflammatory dressing,and skin grafting.The control group received standard treatment,which included wound cleaning and dressing,antibiotics administration,and surgical debridement or amputation,if necessary.Time taken to reduce the white blood cell count,number of dressing changes,wound healing rate and time,and amputation rate were assessed.RESULTS The experimental group exhibited significantly better outcomes than those of the control group in terms of the wound healing rate,wound healing time,and amputation rate.Additionally,the comprehensive treatment protocol was safe and well tolerated by the patients.CONCLUSION Comprehensive treatment for DFUs is more effective than standard treatment,promoting granulation tissue growth,shortening hospitalization time,reducing pain and amputation rate,improving wound healing,and enhancing quality of life.

New advances in hepatocellular carcinoma

AIM: To determine if gene-specific DNA methylation in prospectively collected blood samples is associated with later development of hepatocellular carcinoma(HCC).METHODS: Comparing genome-wide DNA methylation profiles using Illumina Human methylation 450 K arrays, we previously identified a list of loci that were differentially methylated between tumor and adjacent nontumor tissues. To examine if dysregulation of DNAmethylation patterns observed in tumor tissues can be detected in white blood cell(WBC) DNA, we conducted a prospective case-control study nested within a community-based cancer screening cohort in Taiwan with 16 years of follow up. We measured methylation levels in ninety-six loci that were aberrant in DNA methylation in HCC tumor tissues compared to adjacent tissues. Baseline WBC DNA from 159 HCC cases and 312 matched controls were bisulfite treated and assayed by Illumina Bead Array. We used the χ2 test for categorical variables and student's t-test for continuous variables to assess the difference in selected characteristics between cases and controls. To estimate associations with HCC risk, we used conditional logistic regression models stratified on the matching factors to calculate odds ratios(OR) and 95%CI. RESULTS: We found that high methylation level in cg10272601 in WNK2 was associated with increased risk of HCC, with an OR of 1.91(95%CI: 1.27-2.86). High methylation levels in both cg12680131 in TPO and cg22511877 in MYT1 L, however, were associated with decreased risk. The ORs(95%CI) were 0.59(0.39-0.87) and 0.50(0.33-0.77), respectively, for those with methylation levels of cg12680131 and cg22511877 above the median compared with those with levels below the median. These associations were still statistically significant in multivariable conditional logistic regression models after adjusting for hepatitis B virus infection and alcohol consumption. CONCLUSION: These findings support the measurement of methylation markers in WBC DNA as biomarkers of HCC susceptibility but should be replicated in additional prospective studies.

Can mean platelet volume play a role in evaluating the severity of acute pancreatitis?

AIM To investigate serum mean platelet volume(MPV) levels in acute pancreatitis(AP) patients and assess whether MPV effectively predicts the disease severity of AP.METHODS We included 117 consecutive patients with AP as the AP group and 34 consecutive patients with colorectal polyps(before endoscopic treatment) as the control group. Complete blood counts, liver function, platelet indices(MPV), coagulation parameters, lactate dehydrogenase(LDH) and C-reactive protein(CRP) were measured on days 1, 2, 3 and 7 after admission. Receiver operating characteristic curves were used to compare the sensitivity and specificity of MPV, white blood cell(WBC), LDH and CRP in predicting AP severity. The Modified Glasgow Prognostic Score(m GPS) and the 2012 revised Atlanta criteria were used to evaluate disease severity in AP.RESULTS MPV levels were significantly lower in the AP group than in the control group on day 1(P = 0.000), day 2(P = 0.029) and day 3(P = 0.001) after admission.In addition, MPV values were lower on day 1 after admission than on day 2(P = 0.012), day 3(P = 0.000) and day 7(P = 0.002) in all AP patients. Based on the m GPS, 78 patients(66.7%) were diagnosed with mild and 39 patients(33.3%) with severe AP. There was no significant difference in mean MPV levels between patients diagnosed with mild and severe AP based on the m GPS(P = 0.424). According to the 2012 revised Atlanta criteria, there were 98 patients(83.8%) without persistent organ failure(OF) [non-severe acute pancreatitis(non-SAP) group] and 19 patients(16.2%) with persistent OF(SAP group). MPV levels were significantly lower in the SAP group than in the non-SAP group on day 1 after admission(P = 0.002). On day 1 after admission using a cut-off value of 6.65 f L, the overall accuracy of MPV for predicting SAP according to the 2012 revised Atlanta criteria(AUC = 0.716) had a sensitivity of 91.8% and a specificity of 47.4% and was superior to the accuracy of the traditional markers WBC(AUC = 0.700) and LDH(AUC = 0.697).CONCLUSION MPV can be used at no additional cost as a useful, noninvasive biomarker that distinguishes AP with persistent OF from AP without persistent OF on day 1 of hospital admission.

Changes in Blood Constituents in Rats after Benzene Inhalation

The toxicity of benzene was attributed to the formation of free radical. In this study, a method of measuring lipid peroxidation(LPO)in white blood cells(WBC)was reported. After the rats inhaled benzene in different concentrations (6.310\+9, 71.810\+9 and 459.510\+\{-9\} g/L) for 30 days and in concentration of 71.810\+\{-9\} g/L for 10, 20 and 30 days,indicators reflecting toxicity of blood free radicals such as leukocyte LPO, plasma LPO, erythrocyte superoxide dismutase(SOD), erythrocyte glutathione were measured. After 30 day administration, level of leukocyte LPO in all rats of the exposed groups was remarkably higher than that in the control group. Leukopenia occurred only in 71.810\+\{-9\} g/L and 459.510\+\{-9\} g/L groups. The level of leukocyte LPO also increased in 71.810\+\{-9\} g/L group 20 day administration group. Other biochemical indicators had no significant change. It was suggested that the decrease of peripheral leukocytes following benzene exposure might result from, at least in lipid peroxidation, toxic \{effectpart, membrane lipid peroxidation and the determination of leukocyte LPO level is more sensitive than leukocyte count. \;

CASE REPORT OF NEUROLEPTIC MALIGNANT SYNDROME WITH RISING BLOOD SUGAR

Objective To report one case of neuroleptic malignant syndrome （NMS） with raising blood sugar. Methods The patient was studied clinically with biochemistry, white blood cells, psychiatric symptoms, and creatine phosphokinase （CPK） observations. Results The male patient with a history of taking antipsychot- ics more 30 years and his age of onset was about 20 years. He had severe muscular rigidity, altered consciousness and autonomic disturbance associated with elevation of serum CPK levels （max 3755 U/ L ） and leucocytosis （max 13.3 × 10^9/L）, especially granular leukocytosis（ max 90% ） and lymphocytopenia （rain 8% ）. In addition, high blood sugar emerged along with the variation of white blood cells （ max 9. 0 mmol/L）. Conclusion The manifestations of the patient was in conformity with those of the NMS. The patient had catatonic signs such as mutism, drinking difficulty, etc. and excess of saliva. Developmental observation with CPK and white blood cells is able to reveal the severity level of NMS. Raising blood sugar should be also monitoring item.

Role of plasma C-reactive protein and white blood cell count in predicting in-hospital clinical events of acute type A aortic dissection

Background A few recent studies have reported that inflammation is associated with the prognosis of acute aortic dissection （AD）. There is, however, no systemic investigation regarding the role of plasma C-reactive protein （CRP） and white blood cell （WBC） levels in predicting in-hospital clinical events of acute type AAD. Methods The levels of high-sensitivity CRP and WBC counts were systemically determined after admission in 36 patients with acute type A AD. The variations of plasma CRP and WBC levels in different time windows （admission, 1, 2, 3, 4, 6, 8 days） in patients with acute type AAD were analyzed between patients with events and without events. Results During hospitalization, five patients died, and increased levels of CRP and WBC were found in patients died with acute type A AD compared with patients survived （P 〈0.01, respectively）. Medical treatment may significantly decrease inflammatory response in survived patients with acute type A AD. Additionally, patients with complication of pleural effusion showed higher CRP and WBC levers （P=0.046, P=-0.018, respectively）. Lower WBC levels were found in survived patients treated medically （P=-0.001）. Moreover, mean CRP and WBC levels had positive correlations with aortic diameter （r=0.364, P--0.000; r=0.333, P=0.000, respectively） and age （r=0.270, P=0.000, respectively）, while negative correlations with the time from onset of symptoms to hospital admission （r= -0.229, P=0.000, r= -0.200, P=0.002, respectively）. Univariate analysis showed that age 〉65 years, CRP zl 2.05 rag/L, WBC 〉12.16×10^9/L, aortic diameter 〉48 mm, pleural effusion and diastolic blood pressure 〉105 mmHg were associated with hospital mortality. While CRP 〉12.05 mg/L, WBC ≥12.16×10^9/L, aortic diameter 〉48 mm were strongly associated with hospital mortality in multiple Logistic regression analysis. Conclusions The results suggested that CRP and WBC were preferred markers for predicting the clinical events in patients with acute type A AD, especially death during hospitalization. Therefore, further study enrolling larger cohort, prospective study would be warranted.