Routine Clinical Laboratory Research Articles

Simultaneous Quantification of Serum Symmetric Dimethylarginine, Asymmetric Dimethylarginine and Creatinine for Use in a Routine Clinical Laboratory.

Background Symmetric dimethylarginine (SDMA) and asymmetric dimethylarginine (ADMA) are naturally occurring amino acids classed as uremic toxins by the EUTOX working group. SDMA is principally excreted through the kidneys and is a well-known renal function marker, ADMA is a potent inhibitor of nitric oxide production. Here, we describe the development of a rapid and sensitive liquid chromatography tandem mass spectrometry method for simultaneous measurement of SDMA, ADMA and creatinine. Method Serum samples were prepared by protein precipitation and dilution with acetonitrile prior to injection onto a Waters TQS-Micro. Multiple reaction monitoring was used to detect SDMA, ADMA, creatinine, and their corresponding internal standard transitions after separation with a HILIC analytical column. Sample stability and intra-individual variation studies were also assessed following ethical approval. Results The retention time for creatinine was 0.43, SDMA 1.10 and ADMA 1.14 minutes. Mean recovery for creatinine was 103%, SDMA was 100% and ADMA was 103%, matrix effects were minimal (<6%). Lower limit of quantitation for creatinine and SDMA/ADMA was 17.5 µmol/L and 0.1 µmol/L respectively. Analytical imprecision showed a coefficient of variation <10% for all analytes across the working range of the assays. Intra-individual variation for creatinine was 4.7%, SDMA 7.5% and ADMA 7.6%. Discussion We have developed a rapid assay for LC-MS/MS measurement of SDMA, ADMA and creatinine in a routine clinical laboratory. It is simple, reproducible, and easy to perform. The stability of SDMA and ADMA pre- and post-centrifugation allows for their routine use without any special sample handling requirements.

B-034 Performance Evaluation of the Total Bile Acids (TBA) Assay on Mindray BS-2800M Analyzer

Abstract Background Bile acids (BA) are synthesized in the liver and secreted into bile. The function of BA is to promote absorption of lipids including fat-soluble vitamins. During liver diseases such as viral hepatitis and liver injury by hepatotoxic drugs, and cholestasis condition, BA secretion to bile is impaired, causing serum BA level to rise. Therefore, the determination of serum BA can be used as a sensitive indicator of liver function. TBA reagent contains NADH that requires pH ≥ 9 to be stable that is usually difficult to be maintained during reagent opened and stored on the analyzer. Meanwhile, 3α-Hydroxysteroid Dehydrogenase (3α-HSD) is required for the reaction. 3α-HSD is sensitive to pH condition. Minor changes in pH results in significant changes of enzyme activity. We formulated our TBA reagent with prolonged stability when reagent is onboard on the analyzer. This study evaluated the performance of the new Mindray TBA assay on Mindray BS-2800M. Methods TBA assay was based on the method with coupled Thio-NAD and NADH reaction for BA. The R1 contains Thio-NAD. The R2 contains NADH and 3α-HSD. R1 is incubated with serum sample containing BA for 5 min at 37°C and R2 is then added. During further incubation in the presence of Thio-NAD, 3α-HSD converts BA to 3-ketosteroids and Thio-NADH. The reaction is reversible, and 3α-HSD can convert 3-keto steroids and Thio-NADH to BA and Thio-NAD. In the presence of excess NADH, enzyme cycling occurs efficiently and the rate of formation of Thio-NADH is determined by measuring specific change of absorbance at 412 nm. Two-point-line calibration is used by this assay. The TBA concentrations for the test samples are obtained by the absorbances of test samples from the calibration line. The performances of precision, linearity, onboard stability, interference (hemolysis, lipid and bilirubin), correlation are evaluated following CLSI protocols. Results The precision study was run according to EP05A3 with two commercial controls (about 21 and 36μmol/L) and two serum sample pools(about 9.9 and 24.2 μmol/L)on the Mindray BS-2800M system. The repeatability and within-lab CVs ranged from 0.74% to 1.97%, respectively. The linearity of the assay was determined as from 2.0 μmol/L to 180 μmol/L. The reagent onboard stability is for 28 days without recalibration that is superior to TBA reagents from other manufacturers. The interference of hemolysis, lipid and bilirubin are with less than ±10% impact with hemolysate Hemoglobin up to 500 mg/dL, Intralipids up to 500 mg/dL, and Conjugated bilirubin up to 30 mg/dL, Unconjugated bilirubin up to 30mg/dL. This assay (Y) also correlated well with SEKISUI TBA assay (x), (Y = 0.9965X + 0.2694, r= 0.9993). Conclusions From this evaluation, we concluded that Mindray TBA assay can measure serum TBA precisely and accurately with good performances, especially for onboard stability. It is suitable for use in routine clinical laboratories.

A-095 A New CO2 Assay with Concentrated Reagent Having Superior Onboard Stability on Mindray BS-2800M Analyzer

Abstract Background Measurement of total content of CO2 in serum or plasma can be used to assist in the diagnosis of various acid-base disorders. There are small amounts (about 0.04%) CO2 in the earth’s atmosphere, or more in an enclosed clinical laboratory space. The environmental CO2 could be dissolved into the CO2 reagent continuously, in particular at lowered temperature when it is opened and stored on the system, which leads an impact on CO2 assay performance. Presently, competitors mainly use additional inserts or with small opening of the reagent container to reduce the contact with air from reagent, to improve its onboard stability. Here, we designed a new CO2 assay by optimizing the reagent formulation with a new protection mechanism to reduce the amount of CO2 absorption to the reagent and improved its onboard stability. This study evaluated performances of the new CO2 assay on Mindray BS-2800M analyzer. Methods Mindray CO2 assay with concentrated reagent is based on PEPC (Phosphoenolpyruvate Carboxylase) enzymatic method. It is designed with an innovative mechanism of reagent formulations with a protective layer of chemical(s) on top of the reagent that prevents CO2 from entering the reagent and reduced its impact to its on-board stability. The onboard stability was conducted with a constant reagent consumption mode to simulate as it in clinical lab use. The onboard study used two levels of Quality Control materials and serum pools. According to CLSI protocols, the following assay performances were evaluated: onboard stability, precision, method comparison, linearity, and interference. Results On Mindray BS-2800M analyzer, Mindray CO2 assay demonstrated an excellent onboard stability. With uncapped reagent on the system, the stability is for 21 days without recalibration, with less than ± 5% deviation from day zero. In parallel onboard stability studies, with Roche CO2 reagent on Cobas c701 system, the relative deviation from day zero was found to be within ±10%; and other three manufacturers` results with deviation exceeded ±10% vs. day zero in 7 days. The linearity of Mindray CO2 assay was determined as from 2.0 to 50.0 mmol/L. Our CO2 assay correlated well with Roche CO2 on Cobas c701 (Mindray = 1.0032 * Roche - 0.0186, r≥0.99). The repeatability and with-lab CVs were ranged from 0.64% to 3.41%, respectively. There was no significant interference (&amp;lt;±10%), at CO2 concentration of 15 mmol/L with bilirubin up to 60 mg/dL,hemolysate up to 800 mg/dL, Intralipid up to 1000 mg/dL, triglycerides up to 1000 mg/dL. Conclusions On Mindray BS-2800M analyzer, the new CO2 assay demonstrated a good ability against environmental CO2 inference in 21 days of onboard time. The new CO2 assay also shown good performances in precision, correlation (accuracy) and anti-interference from endogenous substances. Therefore, we conclude that the new Mindray CO2 assay is suitable for routine clinical laboratory use.

B-102 The Impact of Protein / Protein Interactions on Serum Free Light Chain Assay Calibration

Abstract Background Since 2001, Serum Free Light Chain measurements have become established as routine clinical laboratory tests. Katzmann (2002) published a reference interval based on 282 normal samples establishing a ratio reference range 0.26-1.65. Whilst kappa and lambda measurements are of little diagnostic value, kappa/lambda ratio gives a strong indication of monoclonal gammopathy. In recent years, it has been suggested that the ratio may have changed. Here we present investigations identifying protein/protein interactions that may account for the discrepancies between QC release and real-world data; identifying a remediation step which will allow verification of the published ratio. Methods The manufacturers QC release data was reviewed for kappa, lambda and kappa/lambda ratio for all lots from 2018-2023, and compared to published data. To mimic field observation, an accelerated stability study was performed on standard calibrators and protein/protein interactions identified using western blot. Subsequently, calibrators were depleted of alpha-1 antitrypsin (A1AT) and other serum proteins using specific affinity chromatography; accelerated stability was repeated. A calibrator of pure polyclonal free light chains (FLC) in human serum albumin was produced in the presence/absence of A1AT and additional interfering serum proteins. Results At release, the average kappa reference range was 7.2-29.5 mg/L (62 kits, 9 different US blood donor sera collections and 3852 data points) and 7.7-24 mg/L for lambda (78 kits, 9 different US blood donor sera and 4664 data points), with a kappa/lambda ratio of 0.45-1.69. There was minimal change over 5yrs to these measurements. Analysis of FLC calibrators during an accelerated stability identified interactions between kappa FLC and ubiquitous serum proteins, including A1AT. The standard calibrator activity declined by 14.9±0.1% (mean±SEM) over a 4-month accelerated period @22oC, equivalent to 16 months real time. Calibrators depleted of A1AT and specific additional serum proteins showed significantly less decline in activity 1.4±1.4%, p&amp;lt;0.001. When blood donor sera were analysed using the standard calibrators following 4 months at 22oC, the results showed an increase in the reported kappa concentrations compared to those generated from frozen calibrators (19.0[15.4-22.5] to 21.3[17.0-26.0] mg/L, 12.5±3.8%, p&amp;lt;0.001). This observation was mirrored in kappa/lambda ratio (1.3[1.1-1.5] to 1.4[1.2-1.7] mg/L, 12.5±3.8%, p&amp;lt;0.001) and when clinical patient samples were assessed (30.1[14.0-47.1] to 34.3[15.5-56.9] mg/L, 13.8±1.4%, p&amp;lt;0.001). The depleted calibrator did not report an increase in sample results. FLC+HSA calibrators, when spiked with either physiological concentrations of A1AT or other serum proteins, showed a 16.7% and 15.3% decrease in activity respectively, compared to FLC+HSA calibrators without additional proteins. Conclusions At release, US blood donor sera have different absolute kappa mg/L compared to the published reference interval, but these changes do not invalidate the published kappa/lambda ratio, in contrast to recent reports and have not changed since 2018. An unpredictable kappa/protein interaction was observed, particularly with A1AT in a time dependent fashion, which correlated to a reduction in calibrator activity. Removal of A1AT and other specific serum proteins remediated the issue, and the kappa/lambda ratio was verified irrespective of the age of the calibrator.

Serum Procalcitonin, Hematology Parameters, and Cell Morphology in Multiple Clinical Conditions and Sepsis.

The clinical value of procalcitonin (PCT) in infection diagnosis and antibiotic stewardship is still unclear. This study aimed to investigate the association between serum PCT and different clinical conditions as well as other infectious/inflammatory parameters in different septic patients in order to elucidate the value of PCT detection in infection management. Chemiluminescence immunoassay was used for serum PCT analysis. Hematology analysis was used for complete blood cell count. Digital automated cell morphology analysis was used for blood cell morphology examination. Blood, urine, and stool cultures were performed according to routine clinical laboratory standard operating procedures. C-reactive protein (CRP) was analyzed by immunoturbidimetry. Erythrocyte sedimentation rate test was performed using natural sedimentation methods. Outpatients, ICU patients, and patients under 2 years of age with respiratory infections had higher serum PCT levels. Septic patients had the highest-serum PCT levels and other infection indexes. PCT levels in the blood, urine, and stool culture-positive patients were significantly higher than in culture-negative patients. The neutrophil granulation and reactive lymphocytes were observed together with the PCT-level increments in different septic patients, and these alterations were lessened after treatment. There was no significant change in monocyte morphology between pre- and posttreatment septic patients. Serum PCT is associated with neutrophil cytotoxicity and lymphocyte morphology changes in sepsis; thus, the combination of neutrophil and lymphocyte digital cell morphology evaluations with PCT detection may be a useful examination for guiding the clinical management of sepsis.

Reduced heart rate variability is associated with altered clinical laboratory profile in people living with HIV

BackgroundWe compared heart rate variability (HRV) indices between people living with HIV (PLWH) and HIV-negative individuals to ascertain the independent association between HIV infection and reduced HRV, and further investigated whether distinct clinical laboratory profiles exist between PLWH with and without reduced HRV. MethodsThis cross-sectional analysis included 304 PLWH and 147 HIV-negative individuals with comparable age and sex. Thirty-two routine clinical laboratory indices (including hematology and biochemistry) closest to the survey were extracted from the Electronic Medical Record System. HRV indices were divided into two categories: low (lowest quartile, Q1) and moderate-to-high (combined, Q2‒Q4). ResultsThe time domain indices, ln(SDNN), ln(RMSSD), and ln(PNN50), as well as the frequency domain indices, ln(HF), ln(LF), and ln(VLF), were all significantly reduced in PLWH versus HIV-negative individuals (all p < 0.05). These associations remained for ln(SDNN), ln(PNN50), ln(HF) and ln(LF) even after adjusting for potential confounders in multivariable models. PLWH with low HRV indices exhibited distinct clinical laboratory profiles that were characterized by an elevation in fasting plasma glucose, white blood cell count, neutrophil count, neutrophil%, and a reduction in albumin, total protein, urine creatinine, lymphocyte%, red blood cell count (RBC) and nadir CD4 count. The final stepwise logistic regression models for low SDNN included older age, decreased total cholesterol levels, elevated neutrophil count, and the use of antidiabetic medications, whereas the final model for low LF included older age, reduced RBC and the use of antidiabetic medications. ConclusionPLWH exhibit impaired parasympathetic activity, as evidenced by reduced SDNN, PNN50, LF and HF. Furthermore, PLWH who have reduced HRV indices exhibits distinct clinical laboratory profiles that are related to systematic inflammatory response and diabetes.

Surveillance of In Vitro Activity of Cefiderocol Against Carbapenem-Resistant Gram-Negative Clinical Isolates in a Tertiary Care Hospital.

Antibiotic resistance among Gram-negative bacterial isolates is increasingly observed. With the emergence of carbapenem-resistant and pan-resistant pathogens, treating these resistant infections is becoming more challenging due to the limited number of effective drugs. There is a desperate need for the discovery of new antibiotics with novel mechanisms of action. Cefiderocol is one such novel antibiotic with a unique siderophore-based mechanism of action, which has been recently approved for clinical use against drug-resistant pathogens. The present study aims to identify the in vitro activity of cefiderocol against major carbapenem-resistant clinical isolates, including those resistant to colistin. One hundred and one carbapenem-resistant clinical isolates were included in the study. Identification and antibiotic susceptibility testing were performed using the automated VITEK® 2 Compact (bioMérieux SA, Marcy-l'Étoile, France) identification and susceptibility testing system, except for colistin and cefiderocol. Colistin resistance in Enterobacterales and Pseudomonas aeruginosa was assessed using the agar dilution minimum inhibitory concentration method, while for Acinetobacter baumannii, broth microdilution method was employed. Cefiderocol susceptibility testing was conducted using the Kirby-Bauer disc diffusion method with 30 µg discs on standard Mueller-Hinton agar plates. For selected isolates, cefiderocol minimum inhibitory concentration detection was performed using broth microdilution with iron-depleted cation-adjusted Mueller-Hinton broth. Of the total 101 isolates, the majority (75, 74.25%) were Enterobacterales which includedKlebsiella pneumonia (42, 41.58%) and Escherichia coli (33, 32.67%), followed by Pseudomonas aeruginosa (13, 12.87%) and Acinetobacter baumannii (10, 9.9%). Only three (2.97%)of the isolates were Stenotrophomonas maltophilia. Most of the isolates were susceptible to cefiderocol, with only four (3.96%) isolates showing resistance. Colistin resistance was observed in six (6.12%) of the isolates. There was a good correlation between disc diffusion testing and broth microdilution testing for the detection of cefiderocol-resistant isolates. No cross-resistance with colistin was observed, as all colistin-resistant isolates were uniformly susceptible to cefiderocol Conclusion: Cefiderocol is highly effective with good in vitro activity against the majority of carbapenem-resistant pathogens. While some isolates do show resistance, it is relatively uncommon. Given its safety profile compared to colistin, cefiderocol can serve as an alternative to colistin to treat carbapenem-resistant infections and it may be considered even for the management of colistin-resistant cases. Disc diffusion testing is a reliable method for identifying cefiderocol-resistant isolates in routine clinical and diagnostic laboratories, especially in resource-limited settings.

Potential roles for artificial intelligence in clinical microbiology from improved diagnostic accuracy to solving the staffing crisis.

This review summarizes the current and potential uses of artificial intelligence (AI) in the current state of clinical microbiology with a focus on replacement of labor-intensive tasks. A search was conducted on PubMed using the key terms clinical microbiology and artificial intelligence. Studies were reviewed for relevance to clinical microbiology, current diagnostic techniques, and potential advantages of AI in routine microbiology workflows. Numerous studies highlight potential labor, as well as diagnostic accuracy, benefits to the implementation of AI for slide-based and macroscopic digital image analyses. These range from Gram stain interpretation to categorization and quantitation of culture growth. Artificial intelligence applications in clinical microbiology significantly enhance diagnostic accuracy and efficiency, offering promising solutions to labor-intensive tasks and staffing shortages. More research efforts and US Food and Drug Administration clearance are still required to fully incorporate these AI applications into routine clinical laboratory practices.

Differentiation of Prior SARS-CoV-2 Infection and Postacute Sequelae by Standard Clinical Laboratory Measurements in the RECOVER Cohort.

There are currently no validated clinical biomarkers of postacute sequelae of SARS-CoV-2 infection (PASC). To investigate clinical laboratory markers of SARS-CoV-2 and PASC. Propensity score-weighted linear regression models were fitted to evaluate differences in mean laboratory measures by prior infection and PASC index (≥12 vs. 0). (ClinicalTrials.gov: NCT05172024). 83 enrolling sites. RECOVER-Adult cohort participants with or without SARS-CoV-2 infection with a study visit and laboratory measures 6 months after the index date (or at enrollment if >6 months after the index date). Participants were excluded if the 6-month visit occurred within 30 days of reinfection. Participants completed questionnaires and standard clinical laboratory tests. Among 10 094 participants, 8746 had prior SARS-CoV-2 infection, 1348 were uninfected, 1880 had a PASC index of 12 or higher, and 3351 had a PASC index of zero. After propensity score adjustment, participants with prior infection had a lower mean platelet count (265.9 × 109 cells/L [95% CI, 264.5 to 267.4 × 109 cells/L]) than participants without known prior infection (275.2 × 109 cells/L [CI, 268.5 to 282.0 × 109 cells/L]), as well as higher mean hemoglobin A1c (HbA1c) level (5.58% [CI, 5.56% to 5.60%] vs. 5.46% [CI, 5.40% to 5.51%]) and urinary albumin-creatinine ratio (81.9 mg/g [CI, 67.5 to 96.2 mg/g] vs. 43.0 mg/g [CI, 25.4 to 60.6 mg/g]), although differences were of modest clinical significance. The difference in HbA1c levels was attenuated after participants with preexisting diabetes were excluded. Among participants with prior infection, no meaningful differences in mean laboratory values were found between those with a PASC index of 12 or higher and those with a PASC index of zero. Whether differences in laboratory markers represent consequences of or risk factors for SARS-CoV-2 infection could not be determined. Overall, no evidence was found that any of the 25 routine clinical laboratory values assessed in this study could serve as a clinically useful biomarker of PASC. National Institutes of Health.

Risk of low levels of blood group antibodies mediating hemolysis in ABO-incompatible neonates with negative three hemolysis tests.

To explore the risk of low-level blood group antibody-mediated hemolysis in ABO-incompatible newborns with negative three hemolysis tests, aiming to assist in the identification and management of neonatal jaundice. A retrospective case-control study was performed in 892 children with jaundice. The patients were divided into three groups: group I, ABO compatible, negative three hemolysis tests; group II, ABO incompatible, negative three hemolysis tests; and group III, ABO incompatible, positive three hemolysis tests. We analyzed the differences in clinical data, blood routine and biochemical laboratory results. (1) Patients in group II had higher levels of mean corpuscular volume (MCV), standard deviation of red blood cell volume distribution width (RDW-SD), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and bile acid (BA) than those in group I (P < 0.05). However, there were no statistically significant differences in the MCV, ALT, ALP and BA levels between groups II and III (P > 0.05). (2) Mean corpuscular hemoglobin concentration (MCHC) >359.5 g/L, cell volume distribution width (RDW-CV) >15.95%, and reticulocyte count (RET) >4.235% were identified as independent predictors of positive hemolysis test results (P < 0.001). The combination of MCHC, RDW-CV, and RET% yielded an AUC of 0.841. Low-level blood group antibody-mediated hemolysis may occur in ABO-incompatible neonates even when three hemolysis tests are negative. Changes in liver function parameters must be monitored. The combination of MCHC, RDW-CV, and RET% can be used to improve the detection rate of HDN.

Rapid detection of imipenem/relebactam susceptibility/resistance in Pseudomonas aeruginosa

ObjectivesImipenem-relebactam (IPR) has been reported to exhibit a good activity against non-metallo-ß-lactamase carbapenem-resistant Pseudomonas aeruginosa (CRPA), and the rapid detection of susceptibility/resistance to this new therapeutic alternative may be crucial. Therefore, the Rapid IPR Pseudomonas NP test was developed to quickly identify IPR susceptibility/resistance among multidrug-resistant P. aeruginosa. MethodsThe principle of the Rapid IPR Pseudomonas NP test is based on visually detecting glucose metabolization by observing (or not) a color change from yellow to red or orange of the red phenol pH indicator in the presence of imipenem at 2 mg/L and relebactam at 4 mg/L A total of 80 clinical Pseudomonas aeruginosa isolates were analyzed, among which 42 isolates were IPR resistant according to EUCAST guidelines (MICs, susceptible ≤2 mg/L, resistant >2 mg/L). Results obtained with the Rapid IPR Pseudomonas NP test were compared with the reference broth microdilution (BMD). ResultsThe sensitivity, specificity and accuracy of the test were found to be 100 %, 89.5 % and 95 %, respectively, using the BMD reference method as a comparator. Moreover, five out of the IPR-susceptible isolates (n = 38) exhibiting an MIC of IPR close to the breakpoint (MIC = 1 mg/L, n = 2; MIC = 2 mg/L, n = 3) yielded to a major error result, namely a positive result with the rapid IPR Pseudomonas NP test (resistance). By contrast, all IPR-resistant isolates (n = 42) were all correctly categorized. ConclusionsThe Rapid IPR Pseudomonas NP test is sensitive, specific, and easy to perform and interpret. Therefore, it is suitable for implementation in routine clinical laboratories.

Machine Learning for Early Discrimination Between Lung Cancer and Benign Nodules Using Routine Clinical and Laboratory Data.

Lung cancer poses a global health threat necessitating early detection and precise staging for improved patient outcomes. This study focuses on developing and validating a machine learning-based risk model for early lung cancer screening and staging, using routine clinical data. Two medical center, observational, retrospective studies were conducted, involving 2312 lung cancer patients and 653 patients with benign nodules. Machine learning techniques, including differential analysis and feature selection, were employed to identify key factors for modeling. The study focused on variables such as nodule density, carcinoembryonic antigen (CEA), age, and lifestyle habits. The Logistic Regression model was utilized for early diagnoses, and the XGBoost model was utilized for staging based on selected features. For early diagnoses, the Logistic Regression model achieved an area under the curve (AUC) of 0.716 (95% confidence interval [CI] 0.607-0.826), with 0.703 sensitivity and 0.654 specificity. The XGBoost model excelled in distinguishing late-stage from early-stage lung cancer, exhibiting an AUC of 0.913 (95% CI 0.862-0.963), with 0.909 sensitivity and 0.814 specificity. These findings highlight the model's potential for enhancing diagnostic accuracy and staging in lung cancer. This study introduces a novel machine learning-based risk model for early lung cancer screening and staging, leveraging routine clinical information and laboratory data. The model shows promise in enhancing accuracy, mitigating overdiagnosis, and improving patient outcomes.

Unlocking a New Path: An Autophagometer that Measures Flux Using a Non-Fluorescent Immunohistochemistry Method.

Macroautophagy/autophagy, a crucial cellular process, is typically measured using fluorescence-based techniques, which can be costly, complex, and impractical for clinical settings. In this paper, we introduce a novel, cost-effective, non-fluorescent immunohistochemistry (IHC) method for evaluating autophagy flux. This technique, based on antigen-antibody reactions and chromogenic detection, provides clear, quantifiable results under standard light microscopy, eliminating the need for expensive equipment and specialized reagents. Our method simplifies technical requirements, making it accessible to routine clinical laboratories and research settings with limited resources. By comparing our approach with traditional fluorescence methods, we demonstrate its superior effectiveness, cost-efficiency, and applicability to patient samples. This innovative technique has the potential to significantly advance autophagy research and improve clinical diagnostics, offering a practical and robust tool for studying autophagy mechanisms in diseases such as cancer and neurodegenerative disorders. Our non-fluorescent IHC method represents a significant step forward in evaluating autophagy flux, making it more accessible and reliable, with the promise of enhancing our understanding and treatment of autophagy-related diseases.

Integration of artificial intelligence in clinical laboratory medicine: Advancements and challenges

AbstractArtificial intelligence (AI)‐driven analysis of comprehensive clinical parameters is bringing about a significant transformation in traditional routine clinical laboratory testing. This transformation impacts the prediction, prevention, diagnosis, and prognosis of human diseases. AI possesses the capability to efficiently analyze and process vast and intricate datasets, thereby facilitating the development of diverse and efficient diagnostic or predictive models. This advancement is fueling significant improvements in laboratory quality, automation, and the accuracy of diagnoses. In this context, we conducted a thorough review and discussion on the progression of AI applications in clinical laboratory medicine, encompassing advancements, implementation, and challenges. Our conclusion underscores that integrating AI into clinical laboratory testing will notably propel personalized precision medicine forward and enhance diagnostic accuracy, especially benefiting patients for whom accurate diagnoses are elusive through traditional laboratory testing systems.

How to verify the analytical and clinical performance of ELISA immunoanalysis in the real laboratory practice. PCSK9 as an example

BackgroundManufacturers and diagnostic companies often recommend on-site verification of analytical performance in the clinical laboratory. The validation process used by manufacturers is rarely described in detail, and certain information on analytical performance is missing from the product sheet, especially for immunoanalytical methods. We describe an approach to the detailed validation of an ELISA method for the measurement of proprotein convertase subtilisin/kexin type 9 (PCSK9) plasma concentrations. We compared manufacturers' claims of analytical performance with data obtained in the field laboratory using several approaches. MethodsWe used the Human Proprotein Convertase 9/PCSK9 Quantikine ELISA diagnostic kit (R&D systems, Bio-Techne Ltd., Abingdon Science Park, Abingdon, UK) and three levels of quality control solution Quantikine Immunoassay Control Group 235 (R&D systems, Bio-Techne Ltd., Abingdon Science Park, Abingdon, UK) to verify precision. We measured the concentration of PCSK9 using the DS2 ELISA Reader (Dynex Technologies GmbH, Denkendorf, Germany). We used analysis of variance (ANOVA) and the R statistical package (R core team, version 1.4.5). Statistical analysis and terminology were performed according to protocol CLSI EP15-A3, and the reference interval was checked according to CLSI/IFCC C28-A3c. ResultsWe found a significant difference between the manufacturer's claims of analytical performance and real data measured in the routine clinical laboratory. The calculated CV (%) for repeatability (calculated by simple estimation of the mean and SD, as used by the manufacturer) was between 5.5% and 7.4%, but the manufacturer's claim was between 4.1% and 6.5%. Using ANOVA, the true repeatability was between 5.0% and 6.9%. Similarly, ANOVA revealed values of CV (%) for within-laboratory imprecision between 6.5% and 9.1%, while the manufacturer's claims were between 4.1% and 5.9%. The recovery ranged from 105.5% to 121.8%. The manufacturer's recommended reference interval was checked and we didn't find any significant difference between men and women. ConclusionsWe describe a comprehensive approach to verify the analytical performance of an ELISA method using the measurement of PCSK9 plasma concentration as an example. We found differences between the results of this approach based on the CLSI EP15-A3 protocol and data provided by the manufacturer. We recommend the verification of analytical performance by more complex statistical tools in laboratory practice.

Serum proteomics reveals hemophagocytic lymphohistiocytosis-like phenotype in a subset of patients with multisystem inflammatory syndrome in children

Children with Multisystem Inflammatory Syndrome in Children (MIS-C) can present with thrombocytopenia, which is a key feature of hemophagocytic lymphohistiocytosis (HLH). We hypothesized that thrombocytopenic MIS-C patients have more features of HLH. Clinical characteristics and routine laboratory parameters were collected from 228 MIS-C patients, of whom 85 (37%) were thrombocytopenic. Thrombocytopenic patients had increased ferritin levels; reduced leukocyte subsets; and elevated levels of ASAT and ALAT. Soluble IL-2RA was higher in thrombocytopenic children than in non-thrombocytopenic children. T-cell activation, TNF-alpha and IFN-gamma signaling markers were inversely correlated with thrombocyte levels, consistent with a more pronounced cytokine storm syndrome. Thrombocytopenia was not associated with severity of MIS-C and no pathogenic variants were identified in HLH-related genes. This suggests that thrombocytopenia in MIS-C is not a feature of a more severe disease phenotype, but the consequence of a distinct hyperinflammatory immunopathological process in a subset of children.

Detection of Biofilm Production and Antibiotic Susceptibility Pattern among Clinically Isolated Staphylococcus aureus.

The increasing antibiotic resistance and the ability to form biofilms in medical devices have become the leading cause of severe infections associated with Staphylococcus aureus (S. aureus). Since the bacteria living in biofilms can exhibit 10- to 1,000-fold increase in antibiotic resistance and implicate chronic infectious diseases, the detection of S. aureus ability to form biofilms is of great importance for managing, minimizing, and effectively treating infections caused by it. This study aimed to compare the tube and tissue culture methods to detect biofilm production and antibiotic susceptibility in MRSA and MSSA. The S. aureus isolates were identified by the examination of the colony morphology, Gram staining, and various biochemical tests. Antimicrobial susceptibility testing of all isolates was performed by the modified Kirby-Bauer disc diffusion method as recommended by CLSI guidelines. MRSA screening was performed phenotypically using a cefoxitin disc (30 µg). Isolates were tested for inducible resistance using the D-test, and two phenotypic methods detected biofilm formation. Among 982 nonrepeated clinical specimens, S. aureus was isolated from 103 (10.48%). Among 103 clinical isolates of S. aureus, 54 (52.42%) isolates were MRSA, and 49 (47.57%) were MSSA. Among 54 MRSA isolates, the inducible MLSB phenotype was observed in 23/54 (42.59%) with a positive D-test. By TCP method, 26 (48.1%) MRSA isolates were strong biofilm producers, whereas, among all MSSA isolates, only 6 (12.2%) were strong biofilm producers. MRSA showed strong biofilm production in comparison with MSSA. The TCP method is a recommended reliable method to detect the biofilm among S. aureus isolates, and the TM method could be useful for the screening of biofilm production in S. aureus in the routine clinical laboratory.

First-episode psychiatric disorder risk from SARS-CoV-2 infection, a clinical analysis with Chinese psychiatric inpatients.

The extensive spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout China in late 2022 has underscored the correlation between this virus and severe psychiatric disorders. Nevertheless, there remains a dearth of reported corresponding clinical and pathological features. Accordingly, we retrospectively reviewed the electronic medical records of psychiatric inpatients for seven days from early January 2023. Twenty-one inpatients who developed first-episode psychiatric disorders within two weeks after SARS-CoV-2 infection were recruited, while 24 uninfected the first-episode psychiatric inpatients were selected as controls. Comparative analyses of clinical manifestations, routine laboratory, and imaging examinations were performed. Our investigation revealed a 330% increase in first-episode psychiatric inpatients incidence after SARS-CoV-2 infection in 2023 compared to the preceding year without infections. Most cases exhibited psychiatric symptoms within a week of infection, resolving about two weeks with no residual symptoms after a three month. One-way ANOVA analysis between inpatients characterized by psychotic symptoms and hyperthermia was significant. Infected inpatients displayed elevated cytokine levels of interleukin-4, interleukin-8, and interferon-α, and decreased levels of eosinophils and basophils. These finding suggested that SARS-CoV-2 may contribute to the development of psychiatric disorders, likely mediated by the virus-induced inflammatory response and neuronal dysfunction in the context of psychological distress.

Using machine learning algorithms based on patient admission laboratory parameters to predict adverse outcomes in COVID-19 patients

Amidst the global COVID-19 pandemic, the urgent need for timely and precise patient prognosis assessment underscores the significance of leveraging machine learning techniques. In this study, we present a novel predictive model centered on routine clinical laboratory test data to swiftly forecast patient survival outcomes upon admission. Our model integrates feature selection algorithms and binary classification algorithms, optimizing algorithmic selection through meticulous parameter control. Notably, we developed an algorithm coupling Lasso and SVM methodologies, achieving a remarkable area under the ROC curve of 0.9277 with the use of merely 8 clinical laboratory parameters collected upon admission. Our primary contribution lies in the utilization of straightforward laboratory parameters for prognostication, circumventing data processing intricacies, and furnishing clinicians with an expeditious and precise prognostic assessment tool.

MSDeepAMR: antimicrobial resistance prediction based on deep neural networks and transfer learning.

Antimicrobial resistance (AMR) is a global health problem that requires early and effective treatments to prevent the indiscriminate use of antimicrobial drugs and the outcome of infections. Mass Spectrometry (MS), and more particularly MALDI-TOF, have been widely adopted by routine clinical microbiology laboratories to identify bacterial species and detect AMR. The analysis of AMR with deep learning is still recent, and most models depend on filters and preprocessing techniques manually applied on spectra. This study propose a deep neural network, MSDeepAMR, to learn from raw mass spectra to predict AMR. MSDeepAMR model was implemented for Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus under different antibiotic resistance profiles. Additionally, a transfer learning test was performed to study the benefits of adapting the previously trained models to external data. MSDeepAMR models showed a good classification performance to detect antibiotic resistance. The AUROC of the model was above 0.83 in most cases studied, improving the results of previous investigations by over 10%. The adapted models improved the AUROC by up to 20% when compared to a model trained only with external data. This study demonstrate the potential of the MSDeepAMR model to predict antibiotic resistance and their use on external MS data. This allow the extrapolation of the MSDeepAMR model to de used in different laboratories that need to study AMR and do not have the capacity for an extensive sample collection.