Performance of SOBA-AD blood test in discriminating Alzheimer's disease patients from cognitively unimpaired controls in two independent cohorts.

Amyloid-beta (Aß) toxic oligomers are critical early players in the molecular pathology of Alzheimer's disease (AD). We have developed a Soluble Oligomer Binding Assay (SOBA-AD) for detection of these Aß oligomers that contain α-sheet secondary structure that discriminates plasma samples from patients on the AD continuum from non-AD controls. We tested 265 plasma samples from two independent cohorts to investigate the performance of SOBA-AD. Testing was performed at two different sites, with different personnel, reagents, and instrumentation. Across two cohorts, SOBA-AD discriminated AD patients from cognitively unimpaired (CU) subjects with 100% sensitivity, > 95% specificity, and > 98% area under the curve (AUC) (95% CI 0.95-1.00). A SOBA-AD positive readout, reflecting α-sheet toxic oligomer burden, was found in AD patients, and not in controls, providing separation of the two populations, aside from 5 SOBA-AD positive controls. Based on an earlier SOBA-AD study, the Aß oligomers detected in these CU subjects may represent preclinical cases of AD. The results presented here support the value of SOBA-AD as a promising blood-based tool for the detection and confirmation of AD.

Interaction of blood calcium with milk yield, energy metabolites, subclinical mastitis, and reproductive performance in crossbred dairy cows.

Limited literature is available on the consequences of postpartum low blood calcium (Ca) concentration in crossbred cows. The research aimed to investigate the correlation between postpartum serum Ca levels and various parameters, including milk yield, serum energy metabolites, milk somatic cell count, and reproductive factors in crossbred cows. Following parturition, a total of 45 potential high-yielding F2 (HF × Sahiwal; Genotype: 75:25) dairy cows were enrolled . These cows were categorized based on plasma calcium concentrations into three groups: a low calcium group (Ca-L) with a calcium concentration of <5 mg/dL, a medium calcium group (Ca-M) with a calcium concentration ranging from 5 to 8.5 mg/dL, and a high calcium group (Ca-H) with a calcium concentration exceeding 8.5 mg/dL. The study parameters were measured over an 8-week period. The results indicated that overall milk yield and blood glucose were significantly higher in the Ca-H group compared to Ca-M and Ca-L (p < .01). Blood cholesterol was significantly higher in Ca-M (p < .01), while blood triglyceride was significantly lower in both Ca-M and Ca-H. Overall, blood cortisol did not show a significant change between these groups (p < .01); however, progesterone levels were higher (p < .01) in Ca-M and Ca-H cows. Furthermore, somatic cell count (SCC) significantly (p < .01) decreased in cows with Ca-H compared to Ca-L. Additionally, postpartum oestrous interval and interestrus interval decreased significantly (p < .01) in Ca-M and Ca-H compared to Ca-L. These findings suggest that cows with blood calcium levels exceeding 8.5 mg/dL exhibited significantly higher milk yield, blood metabolite levels, a lower likelihood of subclinical mastitis, and earlier reproductive activity after calving.

Reference intervals of complete blood count parameters in the adult western Sudanese population.

BACKGROUND: A complete blood count (CBC) analysis is one of the most common conventional blood tests that physicians frequently prescribe. THE OBJECTIVE: of this study was to determine the reference intervals (RIs) of CBC parameters in the population of healthy adults living in the western Sudan region. METHODS: A cross-sectional study of healthy people residing in the western area of Sudan was carried out. We assessed the CBC RIs in samples taken from 153 individuals using an automated haematology analyser (Sysmex KX-21) and a modified Box-Cox transformation procedure to transform the data into a Gaussian distribution after eliminating outliers using the Dixon method. IBM SPSS Statistics version 25 was used to analyse the data, and t tests were employed to examine variations in the mean CBC parameters according to sex and age. P was considered significant at ≤ 0.05. RESULTS: Beyond all the other measured values, the only CBC parameters that significantly differed between the sexes were haemoglobin (HGB) and white blood cell (WBC) counts. Women were found to experience more WBC counts than men did. However, they have less HGB RIs.The male participants in our study exhibited lower WBC count RIs, a significantly lower limit, and a greater upper limit of platelet RIs than did the individuals from other nations. CONCLUSIONS: Compared with males, females had higher platelet and WBC counts and lower HGB.

Gradient Hydrogels Spatially Trapped Optical Cell Profiling for Quantitative Blood Cellular Osmotic Analysis.

The quantitative exploration of cellular osmotic responses and a thorough analysis of osmotic pressure-responsive cellular behaviors are poised to offer novel clinical insights into current research. This underscores a paradigm shift in the long-standing approach of colorimetric measurements triggered by red cell lysis. In this study, we engineered a purpose-driven optofluidic platform to facilitate the goal. Specifically, creating photocurable hydrogel traps surmounts a persistent challenge─optical signal interference from fluid disturbances. This achievement ensures a stable spatial phase of cells and the acquisition of optical signals for accurate osmotic response analysis at the single-cell level. Leveraging a multigradient microfluidic system, we constructed gradient osmotic hydrogel traps and developed an imaging recognition algorithm, empowering comprehensive analysis of cellular behaviors. Notably, this system has successfully and precisely analyzed individual and clustered cellular responses within the osmotic dimension. Prospective clinical testing has further substantiated its feasibility and performance in that it demonstrates an accuracy of 92% in discriminating complete hemolysis values (n = 25) and 100% in identifying initial hemolysis values (n = 25). Foreseeably, this strategy should promise to advance osmotic pressure-related cellular response analysis, benefiting further investigation and diagnosis of related blood diseases, blood quality, drug development, etc.

Real-time evaluation and adaptation to facilitate rapid recruitment in a large, prospective cohort study.

BACKGROUND: Recruiting large cohorts efficiently can speed the translation of findings into care across a range of scientific disciplines and medical specialties. Recruitment can be hampered by factors such as financial barriers, logistical concerns, and lack of resources for patients and clinicians. These and other challenges can lead to underrepresentation in groups such as rural residents and racial and ethnic minorities. Here we discuss the implementation of various recruitment strategies for enrolling participants into a large, prospective cohort study, assessing the need for adaptations and making them in real-time, while maintaining high adherence to the protocol and high participant satisfaction. METHODS: While conducting a large, prospective trial of a multi-cancer early detection blood test at Geisinger, an integrated health system in central Pennsylvania, we monitored recruitment progress, adherence to the protocol, and participants' satisfaction. Tracking mechanisms such as paper records, electronic health records, research databases, dashboards, and electronic files were utilized to measure each outcome. We then reviewed study procedures and timelines to list the implementation strategies that were used to address barriers to recruitment, protocol adherence and participant satisfaction. RESULTS: Adaptations to methods that contributed to achieving the enrollment goal included offering multiple recruitment options, adopting group consenting, improving visit convenience, increasing the use of electronic capture and the tracking of data and source documents, staffing optimization via leveraging resources external to the study team when appropriate, and integrating the disclosure of study results into routine clinical care without adding unfunded work for clinicians. We maintained high protocol adherence and positive participant experience as exhibited by a very low rate of protocol deviations and participant complaints. CONCLUSION: Recruiting rapidly for large studies - and thereby facilitating clinical translation - requires a nimble, creative approach that marshals available resources and changes course according to data. Planning a rigorous assessment of a study's implementation outcomes prior to study recruitment can further ground study adaptations and facilitate translation into practice. This can be accomplished by proactively and continuously assessing and revising implementation strategies.

Technical Note: Comparison of Alinity c Hemoglobin A1c Immunoassay with Premier Hb9210 Automated HPLC Assay: A Preliminary Report.

OBJECTIVE: We utilized Premier Hb9210 analyzer (HPLC method; Trinity Biotech, Jamestown, NY) for measuring HBA1c in whole blood. As our laboratory is transitioning to Abbott system, we compared HbA1c values obtained by Alinity c and Premier Hb9210. METHODS: The Premier Hb9210 analyzer is based on boronate affinity high performance liquid chromatography with analytical measurement range of 3.8 to 18.5%. The Alinity c Hemoglobin A1c assay measured both total hemoglobin and HbA1c (enzymatic assay) in whole blood and then calculated %HbA1c. The analytical measurement range of this assay is 4 to 14% of HbA1c. We evaluated the analytical performance of Alinity c HbA1c by evaluating precision and also comparing 77 clinical samples with our reference HPLC method. RESULTS: Both Alinity c HbA1c and Premier HB9210 have excellent total precision. Plotting HbA1c results obtained by the Premier Hb9210 analyzer in the x-axis (currently used reference method) and the corresponding values obtained by the Alinity c assay, we observed the following regression equation: y=0.9473x+0.1548 ( n=77, r=0.99). DISCUSSION: Our result indicates that HbA1c enzymatic assay on the Alinity c analyzer showed values comparable to HPLC method. However, at the decision points (2.8% average negative bias at >6.4% and 3.3% average negative bias at 7%), HbA1c values obtained by the Alinity c analyzer were lower than the reference method. CONCLUSIONS: We conclude that HbA1c assay on the Alinity c analyzer is a viable alternative to HPLC for measuring HbA1c in clinical laboratories but values at the decision points must be interpreted with caution and if necessary should be repeated by a reference HPLC method.

Clinical implications of inaccurate potassium determination in hemolyzed pediatric blood specimens.

BACKGROUND: Analysis of whole blood specimens is rapid and saves blood, but hemolysis may go undetected and compromise the accuracy of potassium measurement. We aimed to define the frequency and magnitude of error in whole blood potassium measurement. METHODS: 34 months of whole blood and plasma potassium data were extracted from patients aged less than 2 years at the time of sample acquisition. Hemolysis was detected using the plasma "H index." The magnitude of potassium bias was estimated from the difference between paired whole blood and plasma measurement separated by less than 2 h. RESULTS: 56,000 of the 105,000 data points were from plasma and 20 % of these had significant hemolysis. Rates of hemolysis (nearing 50 %) were greatest in the neonatal nursery. Of 662 proximal whole blood and plasma paired results, 8 % had elevated whole blood potassium with a normal plasma value and 4 % had a normal whole blood potassium with reduced plasma potassium. The bias between whole blood and plasma potassium ranged from -1.0 to 4.0 mmol/L. CONCLUSIONS: The use of whole blood analysis brings with it significant risk for error in potassium measurement. Better tools to detect hemolysis in these types of specimens are indicated.

Cost-effective prognostic evaluation of breast cancer: using a STAR nomogram model based on routine blood tests.

Background: Breast cancer (BC) is the most common and prominent deadly disease among women. Predicting BC survival mainly relies on TNM staging, molecular profiling and imaging, hampered by subjectivity and expenses. This study aimed to establish an economical and reliable model using the most common preoperative routine blood tests (RT) data for survival and surveillance strategy management. Methods: We examined 2863 BC patients, dividing them into training and validation cohorts (7:3). We collected demographic features, pathomics characteristics and preoperative 24-item RT data. BC risk factors were identified through Cox regression, and a predictive nomogram was established. Its performance was assessed using C-index, area under curves (AUC), calibration curve and decision curve analysis. Kaplan-Meier curves stratified patients into different risk groups. We further compared the STAR model (utilizing HE and RT methodologies) with alternative nomograms grounded in molecular profiling (employing second-generation short-read sequencing methodologies) and imaging (utilizing PET-CT methodologies). Results: The STAR nomogram, incorporating subtype, TNM stage, age and preoperative RT data (LYM, LYM%, EOSO%, RDW-SD, P-LCR), achieved a C-index of 0.828 in the training cohort and impressive AUCs (0.847, 0.823 and 0.780) for 3-, 5- and 7-year OS rates, outperforming other nomograms. The validation cohort showed similar impressive results. The nomogram calculates a patient's total score by assigning values to each risk factor, higher scores indicating a poor prognosis. STAR promises potential cost savings by enabling less intensive surveillance in around 90% of BC patients. Compared to nomograms based on molecular profiling and imaging, STAR presents a more cost-effective, with potential savings of approximately $700-800 per breast cancer patient. Conclusion: Combining appropriate RT parameters, STAR nomogram could help in the detection of patient anemia, coagulation function, inflammation and immune status. Practical implementation of the STAR nomogram in a clinical setting is feasible, and its potential clinical impact lies in its ability to provide an early, economical and reliable tool for survival prediction and surveillance strategy management. However, our model still has limitations and requires external data validation. In subsequent studies, we plan to mitigate the potential impact on model robustness by further updating and adjusting the data and model.

Commutability and Uncertainty of Blood Hemoglobin A1c Testing Materials.

BACKGROUND: Hemoglobin A1C (HbA1C) is used to evaluate glycemic control over a three-month period. Blood matrix-based HbA1C materials are needed for quality control and evaluation of HbA1C measurements. This study investigated the commutability of blood materials (BMs) and aimed to upgrade BMs for HbA1C testing for use as proficiency test (PT) material. METHODS: We measured BMs from a DM blood donor (n = 1), an in vitro glycation procedure (n = 3), and from commercial sources (n = 2) for HbA1C in parallel with fresh unprocessed BMs (n = 3) and clinical blood samples (n = 25). Two NGSP-certified methods, including a turbidimetric and an enzymatic immunoassay, were used for HbA1C determinations. Commutability as investigated according to CLSI EP14-Ed4 guidelines. RESULTS: The commutable BMs exhibited a mean paired difference of 0% to 9% when compared to reference methods, whereas the non-commutable BMs represented a mean paired difference of 3% to 11%. Fresh, unprocessed BMs with a low HbA1C of 6.0% were more commutable than BMs with a high HbA1C. The values of HbA1C in BMs (mean and uncertainty following ISO Guide 35 for RM production) were applied to upgrade the PT material to be used as a reference material. The relative uncertainty of BM-Ndm-1 and BM-Gcb-3 were 1 and 0.4%, respectively. CONCLUSIONS: The commutability of hemoglobin in BMs is dependent on the preparation process. Blood materials with a high HbA1C content are usually less commutable versus materials with low HbA1C content when prepared by the same process. Our study showed BMs can be successfully used as quality control or PT materials.

Development and validation of prognostic machine learning models for short- and long-term mortality among acutely admitted patients based on blood tests.

Several scores predicting mortality at the emergency department have been developed. However, all with shortcomings either simple and applicable in a clinical setting, with poor performance, or advanced, with high performance, but clinically difficult to implement. This study aimed to explore if machine learning algorithms could predict all-cause short- and long-term mortality based on the routine blood test collected at admission. METHODS: We analyzed data from a retrospective cohort study, including patients > 18 years admitted to the Emergency Department (ED) of Copenhagen University Hospital Hvidovre, Denmark between November 2013 and March 2017. The primary outcomes were 3-, 10-, 30-, and 365-day mortality after admission. PyCaret, an automated machine learning library, was used to evaluate the predictive performance of fifteen machine learning algorithms using the area under the receiver operating characteristic curve (AUC). RESULTS: Data from 48,841 admissions were analyzed, of these 34,190 (70%) were randomly divided into training data, and 14,651 (30%) were in test data. Eight machine learning algorithms achieved very good to excellent results of AUC on test data in a of range 0.85-0.93. In prediction of short-term mortality, lactate dehydrogenase (LDH), leukocyte counts and differentials, Blood urea nitrogen (BUN) and mean corpuscular hemoglobin concentration (MCHC) were the best predictors, whereas prediction of long-term mortality was favored by age, LDH, soluble urokinase plasminogen activator receptor (suPAR), albumin, and blood urea nitrogen (BUN). CONCLUSION: The findings suggest that measures of biomarkers taken from one blood sample during admission to the ED can identify patients at high risk of short-and long-term mortality following emergency admissions.

A Blood Test for the Diagnosis of Multiple Sclerosis.

Multiple sclerosis (MS) is an autoimmune chronic disease characterized by inflammation and demyelination of the central nervous system (CNS). Despite numerous studies conducted, valid biomarkers enabling a definitive diagnosis of MS are not yet available. The aim of our study was to identify a marker from a blood sample to ease the diagnosis of MS. In this study, since there is evidence connecting the serotonin pathway to MS, we used an ELISA (Enzyme-Linked Immunosorbent Assay) to detect serum MS-specific auto-antibodies (auto-Ab) against the extracellular loop 1 (ECL-1) of the 5-hydroxytryptamine (5-HT) receptor subtype 2A (5-HT2A). We utilized an ELISA format employing poly-D-lysine as a pre-coating agent. The binding of 208 serum samples from controls, both healthy and pathological, and of 104 serum samples from relapsing-remitting MS (RRMS) patients was tested. We observed that the serum-binding activity in control cohort sera, including those with autoimmune and neurological diseases, was ten times lower compared to the RRMS patient cohort (p = 1.2 × 10-47), with a sensitivity and a specificity of 98% and 100%, respectively. These results show that in the serum of patients with MS there are auto-Ab against the serotonin receptor type 2A which can be successfully used in the diagnosis of MS due to their high sensitivity and specificity.

Blood transcriptome analysis uncovered COVID-19-myocarditis crosstalk.

BACKGROUND: The condition of COVID-19-related myocarditis has emerged as a prominent contributor to COVID-19 mortality. As the epidemic persists, its incidence continues to rise. Despite ongoing efforts, the elucidation of COVID-19-related myocarditis underlying molecular mechanisms still requires further investigation. METHODS: Hub genes for COVID-19-related myocarditis were screened by integrating gene expression profile analysis via differential expression in COVID-19 (GSE196822) and myocarditis (GSE148153 and GSE147517). After verification with independent datasets (GSE211979, GSE167028, GSE178491 and GSE215865), the hub genes were studied using a range of systems-biology approaches, such as ceRNA, TF-mRNA networks and PPI networks, as well as gene ontology, pathway enrichment, immune infiltration analysis and drug target identification. RESULTS: TBKBP1 and ERGIC1 were identified as COVID-19-related myocarditis hub genes via integrated bioinformatics analysis. In addition, receiver operating characteristic curves constructed based on the expression levels of TBKBP1 and ERGIC1 could effectively distinguish healthy control individuals from patients with COVID-19. Functional enrichment analysis suggested several enriched biological pathways related to inflammation and immune response. Immune cell changes correlated with TBKBP1 and ERGIC1 levels in patients with COVID-19 or patients with COVID-19 and myocarditis. Tamibarotene, methotrexate and theophylline were identified as a potential drug targeting TBKBP1 and ERGIC1. CONCLUSION: TBKBP1 and ERGIC1 were identified as crucial genes in the development of COVID-19-related myocarditis and have demonstrated a strong association with innate antiviral immunity. The present work may be helpful for further investigation of the molecular mechanisms and new therapeutic drug targets correlated with myocarditis in COVID-19.

Blood Test-Based Age Acceleration Is Inversely Associated with High-Volume Sports Activity.

PURPOSE: We develop blood test-based aging clocks and examine how these clocks reflect high-volume sports activity. METHODS: We use blood tests and body metrics data of 421 Hungarian athletes and 283 age-matched controls (mean age, 24.1 and 23.9 yr, respectively), the latter selected from a group of healthy Caucasians of the National Health and Nutrition Examination Survey (NHANES) to represent the general population ( n = 11,412). We train two age prediction models (i.e., aging clocks) using the NHANES dataset: the first model relies on blood test parameters only, whereas the second one additionally incorporates body measurements and sex. RESULTS: We find lower age acceleration among athletes compared with the age-matched controls with a median value of -1.7 and 1.4 yr, P < 0.0001. BMI is positively associated with age acceleration among the age-matched controls ( r = 0.17, P < 0.01) and the unrestricted NHANES population ( r = 0.11, P < 0.001). We find no association between BMI and age acceleration within the athlete dataset. Instead, age acceleration is positively associated with body fat percentage ( r = 0.21, P < 0.05) and negatively associated with skeletal muscle mass (Pearson r = -0.18, P < 0.05) among athletes. The most important blood test features in age predictions were serum ferritin, mean cell volume, blood urea nitrogen, and albumin levels. CONCLUSIONS: We develop and apply blood test-based aging clocks to adult athletes and healthy controls. The data suggest that high-volume sports activity is associated with slowed biological aging. Here, we propose an alternative, promising application of routine blood tests.

Toward a molecular microbial blood test for tuberculosis infection.

The World Health Organization's aim to end the global tuberculosis (TB) epidemic by 2050 cannot be achieved without taking measures to identify people with asymptomatic Mycobacterium tuberculosis (Mtb) infection and offer them an intervention to reduce the risk of disease progression, such as preventive antimicrobial therapy. Implementation of this strategy is limited by the fact that existing tests for Mtb infection, which use immunosensitization to Mtb-specific antigens as a proxy for infection, have low positive predictive value for progression to TB. A blood test that detects Mtb deoxyribonucleic acid (DNA) could allow preventive therapy to be targeted at individuals with microbiological evidence of persistent infection. In this review, we summarize recent advances in the development of molecular microbial blood tests for Mtb infection and discuss potential explanations for discordance between their results and those of immunodiagnostic tests in adults with recent exposure to an infectious index case. We also present a roadmap for further development of molecular microbial blood tests for Mtb infection, and highlight the potential for research in this area to provide novel insights into the biology of Mtb infection and yield new tools to support efforts to control the global TB epidemic.

A Retrospective Study of Factors Contributing to the Performance of an Interferon-Gamma Release Assay Blood Test for Tuberculosis Infection.

BACKGROUND: Tuberculosis (TB) remains a significant global health concern. Accurate detection of latent TB infection is crucial for effective control and prevention. We aimed to assess the performance of an interferon-gamma release assay blood test (QuantiFERON-TB Gold Plus [QFT-Plus]) in various clinical contexts and identify conditions that affect its results. METHODS: We conducted a retrospective analysis of 31 000 QFT-Plus samples collected from 26 000 subjects at a tertiary hospital in South Korea over a 4-year period and compared the rates of positivity and indeterminate results across diverse clinical situations. We also analysed the contribution of the QuantiFERON TB2 tube to the test's sensitivity and determined optimal cutoff values for 3 hematologic parameters to distinguish false-negative results. These cutoff values were validated in a separate cohort of subjects with microbiologically confirmed subclinical TB. RESULTS: Rates of QFT-Plus positivity and indeterminate results were disparate across diagnoses. The TB2 tube increased QFT-Plus sensitivity by 4.1% (95% CI, 1.1%-7.0%) in patients with subclinical TB. Absolute lymphocyte count ≤1.19 × 109/L, absolute neutrophil count ≥5.88 × 109/L, and neutrophil-to-lymphocyte ratio ≥4.33 were effective criteria to discriminate false-negative QFT-Plus results. Application of the hematologic criteria, individually or combined with mitogen response <10 IU/mL, substantially improved performance in the main study cohort and the validation cohort. CONCLUSIONS: These findings highlight the influence of clinical context and patient hematologic profiles on QFT-Plus results. To minimise neglected latent TB infections due to false-negative QFT-Plus results, serial retesting is advisable in patients with severe lymphopenia or neutrophilia, particularly when the mitogen response is <10 IU/mL.