bluuebunny/crossref_metadata_2025_split huggingface dataset:
B-070 Performance Assessment of an Immunoassay for Detection of APOE4 Carriers
Authors: Shields A G , Shields M S , Jiménez-González I , Rodríguez-Martín A , Ito S , Verbel D , Snyder J 
Published: September 2023

Abstract

Background
The APOE gene corresponds to apolipoprotein E, a glycoprotein involved in lipid metabolism. There are three different versions of the APOE gene, e2, e3, and e4 where e3 is the most common allele. APOE4 has been associated with Alzheimer’s Disease (AD) and other neurological diseases. The presence of a single APOE4 allele increases the risk of AD by 3–5 fold and two copies, increase the risk by 8–12 fold. Detection of the APOE4 allele is commonly performed using genetic test methods. Studies were undertaken to evaluate the analytical performance of an immunoassay that detects the presence of APOE4 protein in and assess the discrimination of APOE4 gene carriers from non-APOE4 gene carriers.

Methods
The Biocross e4Risk® test is a latex agglutination immunoassay used for the quantitative determination of isoform E4 of the apolipoprotein E (APOE4) in human EDTA plasma samples. The test consists of one reagent with latex particles and another reagent with a mouse anti-ApoE4, which induces the latex particle agglutination when ApoE4 is present in the plasma sample. This agglutination is measured photometrically. The turbidity is proportional to APOE4 content of the sample, which can be used to infer the APOE4 genotype responsible.
The Biocross kit reagents were run on the Siemens Healthineers Atellica® Chemistry Analyzer (open channel). Stored clinical samples from Eisai’s elenbecestat Phase 3 MissionAD Studies were used in the analysis.
Results:

Conclusion
The Biocross e4Risk® test on the Atellica® Chemistry Analyzer (open channel) demonstrated good analytical performance, with sensitivity and precision comparable to manufacturer’s claims. The assay also had very good sensitivity and specificity when compared to known APOE4 genotype results. A simple blood-based robust APOE4 immunoassay test that runs on a routine clinical chemistry instrument may be a more convenient and cost-effective tool to help recruit patients for AD clinical trial programs.
B-078 Prevelance of Autoimmune Factors in Patients with Seizures of Unknown Etiology in Western China
Authors: Guo S , Meng Z , Wang M , Ying B 
Published: September 2023

Abstract

Objective
To delineate the features of autoantibody in patients with seizure of unknown etiology in Western China and to analyze other potential risk factors of an epileptic seizure.

Methods
From January 2017 to June 2022, 639 patients with unexplained seizure were assessed retrospectively. Neuronal autoantibodies were assessed in 471 individuals, including 12 common neural-specific autoantibodies, antibodies against four common pathogens associated with central nervous system infections, or neurophagocytosis, and two thyroid-related autoantibodies.

Results
Sixty-nine patients were positive for neural-specific autoantibodies in CSF and serum. Among the patients, 32 (46.38%) expressed NMDAR-Ab, 14 (20.29%) expressed GABABR-Ab, 10 (14.49%) expressed LGI1-Ab, 7 (10.14%) expressed GFAP-Ab, 3 (4.34%) expressed Yo-Ab, 2 (2.90%) expressed CASP2-Ab, and 1 (1.45%) expressed Hu-Ab. Compared to patients with non-autoimmune epileptic seizure, the positive rates of thyroid-related antibody expression and the neurophagocytosis pathogen levels of HSV-IgG and T. gondii-IgG were significantly different in patients with autoimmune epileptic seizure.

Conclusion
This study elucidated the antibody status of autoimmune epilepsy in western China, allowing for better identification and diagnosis of autoimmune epilepsy in the future.
B-083 Novel High Affinity Monoclonal Antibodies for Specific Detection of Neurofilament Light Protein in Serum and Cerebrospinal Fluid
Authors: Grönholm K , Vesilahti E , Eklin S , Hämäläinen T , Mattila M , Tuomiranta P 
Published: September 2023

Abstract

Background
Neurofilaments are very important protein components of axons, and they maintain the function of nervous system. Cerebrospinal fluid (CSF) and serum neurofilament levels elevate due to damages in nervous system making neurofilaments promising biomarkers for neural diseases and injuries, such as Alzheimer’s disease, traumatic brain injury and Multiple sclerosis. Based on their size, neurofilaments are divided in groups: Neurofilament light (NfL), neurofilament medium (NfM), neurofilament heavy (NfH), α-internexin, and peripherin. Of these, NfL is considered to be the most promising biomarker since it is the most abundant form of neurofilaments.

Methods
We have developed four mouse monoclonal antibodies against human NfL. These antibodies, designated as Anti-h NfL 12601, 12603, 12604 or 12605, were tested as pairs in sandwich fluorescence-based immunoassay (FIA) with NfL spiked serum and buffer to determine linear measuring ranges and the matrix effect. Furthermore, the ability of the antibodies to measure NfL in clinical samples was tested in sandwich FIA by testing 10 CSF samples in the range of 0 to 5 083 pg/mL. The antibodies were also compared against commercially available reference antibodies in FIA. Kinetic parameters were determined with bio-layer interferometry (BLI).

Results
In sandwich FIA, the widest linear measuring range of 10 to 40 960 pg/mL of recombinant human NfL spiked in normal serum was achieved with antibody pair 12603 and 12604. In contrast, the commercial reference antibody pair achieved a linear measuring range of 2560 to 40 960 pg/mL. Matrix effect caused by serum was negligible. With clinical samples, the best correlation with the reference method (NF-light CSF ELISA from Uman Diagnostics) with a coefficient of correlation of 0.986 was achieved with antibody pair 12604 and 12601. This pair also showed a good correlation with the commercial reference pair with a coefficient of correlation of 0.984. In kinetics measurements, none of four antibodies showed dissociation indicating very high affinity. The fastest association of 4.0 × 105 1/Ms was achieved with antibody 12605.

Conclusion
These results demonstrate that the newly developed mouse monoclonal NfL antibodies are promising tools for development of diagnostic immunoassays measuring NfL levels in human serum and CSF samples. Comparison against commercial reference antibodies indicates that higher NfL detection sensitivity and wider detection ranges can be achieved with antibody pairs developed in this study. Additionally, the kinetic measurement results forecast these antibodies to be suitable for fast reaction kinetic assay formats, such as lateral flow assays, which might become a key resolution in acute neural injury diagnostics.
B-094 Vaccination Anti-SARS-Cov2 Scheme Effect on Humoral Responses on Brazilian Cohort
Authors: Bacarov N B , Christofolini D , Sano C L , Dias R H , Bellucco F T , Soane M M , Bianco B , Barbosa C P 
Published: September 2023

Abstract

Background
Due to high spread of SARS-CoV-2, a global emergency vaccination program using diverse and new vaccines was implemented, providing protection mortality of COVID-19. In this way, populational investigation before and after vaccination is essential to understand and monitoring the effectiveness of these efforts.

Methods
Observational non-randomized study was performed using samples of 95 workers from healthcare institutions. They were vaccinated with two homologous doses of Sinovac, ChAdOx1 and Pfizer booster dose. Serum levels of anti-S1 IgA and IgG, anti-NCP IgG and neutralizing antibodies (Nabs) were measured immediately before (T0), two weeks after each dose (T1, T2), 21 days after T2 (T3) and two weeks after boost (T4). Tests were performed through commercial kits of EUROIMMUN.

Results
Results are summarized in Fig. 1. Anti-S1 IgG and IgA titles of CoronaVac samples showed a statistically significant increase after each vaccine dose (T1, T2 and T4). For ChAdOx1, statistically significant difference (SSD) was noticed between T1 and T4. Comparing anti- S1 IgG titles between both vaccines, SSD was observed between all collections, above 2500 BAU/mL on both.Anti-NCP titles increased after each CoronaVac dose, as expected since is an inactivated virus vaccine and SSD was observed from T1 to T4. NAbs at T3 and T4 showed SSD between collection times for each vaccine and between the vaccines. At T3 NAbs titles were higher for ChAdOx1 in comparison to Coronavac vaccinated. However, after the booster dose there was no difference of titles between vaccines and all participants were considered responsive.

Conclusion
The vaccine antibodies titles increased after each vaccine dose. Although there was difference of the diverse antibody titles between vaccines after 1st and 2nd doses, after booster dose all vaccinated were equally highly responsive. Such results reinforce the importance of the booster dose in the vaccination strategy against SARS-CoV-2.
B-118 Evaluation of Thirteen Commercially Available Clinical Chemistry Assays on the Alinity® c System
Authors: Li H , Li M , Wang J , Guo H 
Published: September 2023

Abstract

Background
Expansion of instrument analyte menus is often needed to accommodate country specific needs. To address specific needs in China, thirteen clinical chemistry assays have been modified for evaluation on the Alinity c system. These analytes are used in the investigation of several diseases including liver disease, hepatobiliary disease, cardiovascular and cerebrovascular disease, kidney disease, inflammation, infectious disease, alcoholism and glucose metabolism disease.

Methods
The following analytes were evaluated: a1-Microglobulin (a1-MG), Ischemia modified albumin (IMA), Glutamate Dehydrogenase (GLDH), Fibrin Degradation Products (FDP), Myeloperoxidase (MPO), Fibronectin (FN), Pyruvate (PYR), Monoamine Oxidase (MAO), Heart-type Fatty Acid-Binding Protein (H-FABP), Cholyglycine (CG), Serum Amyloid A Protein (SAA), Ethanol (EtOH) and Ferritin (Fer). Reagents from Beijing Strong Biotechnologies Inc. (BSBE) were evaluated on the ABBOTT Alinity c system. Precision, LoQ and linearity range were evaluated with guidance from CLSI documents EP15-A3, EP17-A2 and EP06-Ed2. Correlation to commercially available assays were performed using human serum/plasma/urine samples across the measuring range.

Results
The table below summarizes key performance of assays.

Conclusions
These initial results are very promising. All the assays tested exhibit good precision, linearity, anti-interference, and LOQ performances on Alinity c system. In addition, they also have excellent correlation with Jinya assays from BSBE on ARCHITECT system except SAA assay, and SAA has excellent correlation with Siemens BNII SAA assay.
B-142 Development and Clinical Validation of Artificial Intelligence Assisted Flow Cytometry Diagnosis for Acuteleukemia
Authors: Lu Z , Lyu Y E , Gao A , Yeager T S , Morita M , Wang S , Wang A , Fan G 
Published: September 2023

Abstract

Background
Flow cytometry is one of the most commonly used diagnostic tools in hematopathology. Manual flow cytometry data analysis is vulnerable to substantial inter-operator variation and typically takes a technologist 20 min to analyze a case. In the last decade, artificial intelligence (AI) technology has advanced dramatically and become widely used in image processing. Previously, we created an AI-assisted workflow for classifying white blood cell subsets in peripheral blood. The goal of this study is to evaluate the automated flow cytometry analysis system for diagnosing acute leukemia.

Methods
A total of 117 cases were retrieved from the archived diagnostic cases, consisting of three diagnostic categories: 20 normal cases, 37 acute lymphoblastic leukemia and 60 acute myeloid leukemia. Flow cytometry data manually analyzed by a pathologist is the gold standard. The same flow cytometry data was processed by the flow cytometry analysis software DeepFlow® using proprietary AI algorithm. The final diagnosis and blast cell count of AI and manual analysis are compared by Pearson correlation coefficient.

Results
The AI-assisted blast cell enumeration showed moderate correlation as compared to manual evaluation (r = 0.8, Fig. 1). Manual adjustment for enumeration of CD34 negative blast population with uncommon immunophenotype is required for 7 cases, including 4 CD34−/CD117+ acute myeloid leukemia and 3 CD34−/TDT+ lymphoblastic leukemia. The AI analysis effectively recognized cell populations and provided correct diagnoses on 94% of cases (110/117). With pathologists’ review, all cases were classified into the correct diagnostic categories.

Conclusion
Our study demonstrated that AI can accurately recognize the flow cytometry pattern of leukemia and make the proper diagnosis. Additional training for CD34 negative blast gating and other uncommon blast immunophenotypes is being conducted. Ultimately, AI will decrease the demand on manual analysis by technologists and pathologists, standardize the analysis process, and provide accurate diagnosis.
B-146 Discriminative Index: A Novel Indicator for Evaluating Machine Learning Algorithms in Laboratory Medicine
Authors: Yu J , Lin W , Lin W , Wang Y , Tseng Y , Wang H 
Published: September 2023

Abstract

Background
In clinical scenarios, incorrect predictions by machine learning (ML) models are inevitable. One way to reduce misleading predictions is to avoid reporting predictions that fall within a predefined “gray zone”. This method improves predictive performance by reporting only the less uncertain cases. However, the cost-effectiveness of applying the “gray zone” rule in an ML model is unclear without massive computation. Thus, this study aims to propose a novel metric to evaluate the effectiveness of using gray zones and validate the metric in real-world ML models.

Methods
This study defined a statistical metric called the “discriminative index” (D-index) for evaluating the effectiveness of gray zones. To calculate the D-index, the predictive outcomes of the ML model are first transformed into two probability distributions based on the truth labels (e.g., positive or negative). The D-index is then derived from the kurtosis of these two distributions. To validate the metric, we applied the D-index to three different antibiotic susceptibility-predicting ML models (namely, convolutional neural network (CNN), random forest (RF), and XGBoost (XGB)) based on mass spectrometry data. We assessed the performance and unpredicted case numbers of each model with different gray zones and correlated the results with the proposed D-index.

Results
The D-index values for the CNN, XGB, and RF models were 4.36, 0.38, and −1.66, respectively. When applying the “gray zone” rule to achieve 90% area under the receiver operating characteristic, the CNN, XGB and RF models retained up to 90%, 68%, and 62% of total cases, respectively. A higher D-index value indicates a more effective application of the gray zone rule.

Conclusion
The D-index is a simple and statistically insightful metric for evaluating the cost-effectiveness of applying gray zone rule in an ML model. This metric has been validated in three mass spectrometry-based predictive models and has shown promising results. The D-index can be a useful tool for comparing and applying different ML algorithms.
B-150 Impact of Clinical Catastrophic Events on Individual Reference Values for 20 Analytes: Results of a Six-Measurement Study.
Authors: de Almeida T F , Ferreira dos Santos Silva I F , Branchi Evans Salvia T , Shoji Hayama D , Carvalho da Silva A , Pitangueira Mangueira C L 
Published: September 2023

Abstract
Reference values are an essential aspect of clinical laboratory testing, providing a basis for comparison of results against established norms for specific patient populations. These reference values are used to evaluate diagnostic test results, monitor disease progression, and assess treatment effectiveness. The accuracy and reliability of these values are crucial to the diagnosis and treatment of disease and illness and also important in the monitoring of disease progression and treatment effectiveness. By tracking changes in test results over time, healthcare providers can assess the effectiveness of treatments and make adjustments as needed. This information is critical in the management of chronic conditions such as diabetes and hypertension. Despite their importance, reference values can be subject to variability due to a variety of factors. These include differences in laboratory testing procedures, variations in patient populations, and differences in the methods used to establish reference ranges. To address these issues, clinical laboratories can use individual references calculated based on previous test results. Nevertheless, individual reference values can be subjected to pathophysiological alterations that can modify the values of specific analytes. The aim of this study was to investigate the impact of a clinical catastrophic event, specifically troponin levels above 1000, on the calculation of individual reference values for 21 analytes. Six measurements were taken before and after the event from a sample of 5 to 450 patients. The results showed that the mean and covariance coefficient of the majority of the analytes remained unchanged despite the presence of the clinical event. Applying a Wilcoxon test to the mean before and after the event 10 out of the 21 analytes differ significantly before and after the event. These analytes included glucose, BNP, chloride, gamma GT, hematocrit, hemoglobin, potassium, C-reactive protein and urea. The mean and covariance of the remaining 11 analytes, which included platelets, creatinine, alkaline phosphatase, magnesium, sodium, AST, ALT, TSH, fibrinogen, prothrombin time, and activated partial thromboplastin time (aPTT), were not significantly impacted by the clinical event. These results suggest that despite the presence of a clinical catastrophic event, individual reference values can still be calculated for the majority of the analytes. This is important for the accurate interpretation of clinical laboratory test results, especially in the presence of acute illnesses or injuries. However, caution should be exercised when interpreting results for the three analytes that were significantly impacted by the event. Further studies are needed to determine if similar results can be obtained for other clinical catastrophic events and analytes.
B-151 Estimation of the Uric Acid Reference Interval by the Indirect Method Using an Unsupervised Machine Learning Tool and R Programming Language
Authors: Canali D G , Lopes A C , Vieira L M , Garoli G Y , Sabino C d , Dias C M , Zampieri G , Muller K G 
Published: September 2023

Abstract

Background
Determining the Reference Intervals (RI) of quantitative clinical laboratory tests is crucial for patient diagnosis, treatment, and monitoring. It is also a concern for laboratories seeking to meet accreditation requirements. Our study aimed to evaluate the manufacturer’s RI for uric acid (3.7–9.2 mg/dL) through indirect methods using a programming tool in R language in a Brazilian laboratory.

Methods
We performed a data mining study for uric acid using the laboratory’s LIS database from January to December 2021. Outpatients &gt;18 years old, analyzed on the Siemens® platform with results within linearity were included. Exclusion criteria were total cholesterol &gt;200 mg/dL, triglycerides &gt;150 mg/dL, glycemia &gt;126 mg/dL, ferritin &gt;300 ng/mL and creatinine &gt;1.5 mg/dL at any time in the patient history and CRP &gt;10 mg/dL in the same month. We used a tool that integrates different algorithms including preliminary treating, grouping, and statistical reduction of test results. The Expectation-Maximization (EM) algorithm calculates the mean, standard deviation, and weight of the distribution for each cluster. Additionally, it integrates algorithms that determine the global mean/median, modes, antimodes, kurtosis, and skewness, to find values that best represent the reference population’s distribution (Figure). Manufacturer's and estimated RI for Male and Female partitions.

Results
The final database included 49.489 subjects, partitioned in 26.439 women and 23.050 men. Statistically estimated RI were 2.8–6.7 mg/dL for women and 3.8–8.6 mg/dL for men. Considering the RI proposed by the manufacturer, 23.8% of women were outside the RI provided by the manufacturer, all of them below the lower reference value.

Conclusions
Our results confirm the importance of verification/establishment of reference intervals by clinical laboratories and suggest that estimated RI using this software is appropriate for the assisted population, demonstrating consistency with physicians’ concerns. After specialist analysis, the manufacturer´s RI has been replaced by the calculated population-specific RI.
B-152 Estimation of Creatinine Reference Interval (RI) by the Indirect Method using an Unsupervised Machine Learning Tool and R Programming Language
Authors: Canali D G , Lopes A C , Vieira L M , Santos B d , Sabino C d , Dias C M , Zampieri G 
Published: September 2023

Abstract

Background
Creatinine is widely used in diagnostic medicine as a primary renal marker. Clinical laboratory measurement of serum creatinine is not standardized, and the RI varies slightly between different manufacturers. Roche brings as reference ranges 0.5–0.9 mg/DL for women and 0.7–1.2 mg/dL for men. After clinical manifestations of elevated female results without clinical correspondence, the laboratory proceeded with reevaluation of RI.

Methods
We retrospectively studied the creatinine results of the laboratory database of samples run from January to October 2022 in two different technical areas in Brazil (São Paulo and Rio de Janeiro). The laboratory platform was Roche® 502/702, Jaffe method to creatinine. The LabRI tool was used with parametric, non-parametric, and robust statistical treatments to exclude outliers and algorithms in the R Language and latent abnormal values of outpatient patients. The partitions proposed were gender (male and female), age (18–60 years old and over 60 years old). The proposed RI for verification were those proposed by Rosenfeld, LG et al in REV BRAS EPIDEMIOL 2019; 22 (SUPPL2):E190002.SUPL.2 - F: 0.5–0.9 and M: 0.7–1.2. Exclusion criteria were patients with urea &gt;48.5 mg/dL, glycemia &gt;200 mg/dL, 24 h proteinuria &gt;150 mg/24 h, LDL &gt; 130 mg/dL, uric acid &gt; 130 mg/dL, anti-nucleus positive factor, as well as clinical data compatible with chronic renal failure or dialysis, hypertension and diabetes.

Results
After exclusion, retrieved 225 181 individuals 52% female. Between the different sites, the results of the partitions did not undergo significant changes. For women in both age partitions, the values did not vary significantly. For men, there was no significant variation in the lower limit of IR, and we had a variation of 0.20 (18–60: 0.69–1.31 and &gt;60: 0.69–1.41) in the upper limit, mainly for the age partition &gt;60 years old, below the 95% confidence interval of the proposed references.

Conclusions
The adoption of the Roche IR and the Brazilian article was approved for the female gender (0.5–0.9) with 118 100 individuals, and a new IR was defined for the male gender (0.7–1.2) with 107 081 adult individuals, including the elderly over 60 years old, for both genders.