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BackgroundCannabis is increasingly used both medically and recreationally. With widespread use, there is growing concern about how to identify cannabis-impaired drivers.MethodsA placebo-controlled randomized double-blinded protocol was conducted to study the effects of cannabis on driving performance. One hundred ninety-one participants were randomized to smoke ad libitum a cannabis cigarette containing placebo or delta-9-tetrahydrocannabinol (THC) (5.9% or 13.4%). Blood, oral fluid (OF), and breath samples were collected along with longitudinal driving performance on a simulator (standard deviation of lateral position [SDLP] and car following [coherence]) over a 5-hour period. Law enforcement officers performed field sobriety tests (FSTs) to determine if participants were impaired.ResultsThere was no relationship between THC concentrations measured in blood, OF, or breath and SDLP or coherence at any of the timepoints studied (P > 0.05). FSTs were significant (P < 0.05) for classifying participants into the THC group vs the placebo group up to 188 minutes after smoking. Seventy-one minutes after smoking, FSTs classified 81% of the participants who received active drug as being impaired. However, 49% of participants who smoked placebo (controls) were also deemed impaired at this same timepoint. Combining a 2 ng/mL THC cutoff in OF with positive findings on FSTs reduced the number of controls classified as impaired to zero, 86 minutes after smoking the placebo.ConclusionsRequiring a positive toxicology result in addition to the FST observations substantially improved the classification accuracy regarding possible driving under the influence of THC by decreasing the percentage of controls classified as impaired.

BackgroundThe current methodology used to detect, diagnose, and monitor many types of cancers requires invasive tissue biopsy testing. Recently, liquid biopsy using blood, plasma, urine, saliva, and various other bodily fluids has shown utility to solve many issues associated with tissue biopsy. Blood/plasma has received most of the attention within the liquid biopsy field, however, obtaining blood samples from patients is still somewhat invasive and requires trained professionals. Using urine to detect cell-free DNA cancer biomarkers offers a truly non-invasive sampling method that can be easily and reproducibly conducted by patients.ContentNovel technologies and approaches have made the detection of small quantities of cell-free tumor DNA of varying lengths possible. Recent studies using urine circulating tumor DNA to detect cancer mutations and other biomarkers have shown sensitivity comparable to blood/plasma cell-free DNA liquid biopsy for many cancer types. Thus, urine cell-free DNA liquid biopsy may replace or provide supplementary information to tissue/blood biopsies. Further investigation with larger patient cohorts and standardization of pre-analytical factors is necessary to determine the utility of urine cell-free DNA liquid biopsy for cancer detection, diagnosis, and monitoring in a clinical setting.SummaryIn this mini-review we discuss the biological aspects of cell-free DNA in urine, numerous studies using urine cell-free DNA to detect urological cancers, and recent studies using urine cell-free DNA to detect and monitor non-urological cancers including lung, breast, colorectal, and other cancers.

BackgroundThe SARS-CoV-2 virus has mutated and evolved since the inception of the COVID-19 pandemic bringing into question the future effectiveness of current vaccines and antibody therapeutics. With evolution of the virus updated methods for the evaluation of the immune response in infected and vaccinated individuals are required to determine the durability of the immune response to SARS-CoV-2 variants.MethodsWe developed a multiplexed surrogate virus neutralization test (plex-sVNT) that simultaneously measures the ability of antibodies in serum to inhibit binding between angiotensin converting enzyme-2 (ACE2) and 7 SARS-CoV-2 trimeric spike protein variants, including wild type, B.1.1.7(α), B.1.351(β), P.1(γ), B.1.617.2(δ), B.1.617.1(κ), and B.1.429(ε). The assay was validated against a plaque reduction neutralization test (PRNT).We evaluated 170 samples from 97 COVID-19 patients and 281 samples from 188 individuals that received the Pfizer-BioNTech or Moderna mRNA vaccines.ResultsThe plex-sVNT demonstrated >96% concordance with PRNT. Antibody neutralization activity was significantly reduced for all SARS-CoV-2 variants compared to wild type in both the infected and vaccinated cohorts. There was a decline in overall antibody neutralization activity, within both cohorts, out to 5 months post infection or vaccination, with the rate of decline being more significant for the vaccinated.ConclusionsThe plex-sVNT provides a correlative measure to PRNT and a convenient approach for evaluating antibody neutralization against SARS-CoV-2 variants. Neutralization of SARS-CoV-2 variants is reduced compared to wild type and declines over the ensuing months after exposure or vaccination within each cohort, however it is still unknown what degree of neutralizing capacity is protective.

BackgroundArtificial intelligence (AI) and machine learning (ML) are poised to transform infectious disease testing. Uniquely, infectious disease testing is technologically diverse spaces in laboratory medicine, where multiple platforms and approaches may be required to support clinical decision-making. Despite advances in laboratory informatics, the vast array of infectious disease data is constrained by human analytical limitations. Machine learning can exploit multiple data streams, including but not limited to laboratory information and overcome human limitations to provide physicians with predictive and actionable results. As a quickly evolving area of computer science, laboratory professionals should become aware of AI/ML applications for infectious disease testing as more platforms are become commercially available.ContentIn this review we: (a) define both AI/ML, (b) provide an overview of common ML approaches used in laboratory medicine, (c) describe the current AI/ML landscape as it relates infectious disease testing, and (d) discuss the future evolution AI/ML for infectious disease testing in both laboratory and point-of-care applications.SummaryThe review provides an important educational overview of AI/ML technique in the context of infectious disease testing. This includes supervised ML approaches, which are frequently used in laboratory medicine applications including infectious diseases, such as COVID-19, sepsis, hepatitis, malaria, meningitis, Lyme disease, and tuberculosis. We also apply the concept of "data fusion" describing the future of laboratory testing where multiple data streams are integrated by AI/ML to provide actionable clinical knowledge.

BackgroundBiomarkers have been widely explored for coronavirus disease 2019 diagnosis. Both viral RNA or antigens (Ag) in the respiratory system and antibodies (Ab) in blood are used to identify active infection, transmission risk, and immune response but have limitations. This study investigated the diagnostic utility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein (N-Ag) in serum.MethodsWe retrospectively studied 208 randomly selected cases with SARS-CoV-2 infection confirmed by viral RNA test in swabs. N-Ag concentrations were measured in remnant serum samples, compared to viral RNA or Ab results, and correlated to electronic health records for clinical value evaluation.ResultsSerum N-Ag was detected during active infection as early as day 2 from symptom onset with a diagnostic sensitivity of 81.5%. Within 1 week of symptom onset, the diagnostic sensitivity and specificity reached 90.9% (95% CI, 85.1%-94.6%) and 98.3% (95% CI, 91.1%-99.9%), respectively. Moreover, serum N-Ag concentration closely correlated to disease severity, reflected by highest level of care, medical interventions, chest imaging, and the length of hospital stays. Longitudinal analysis revealed the simultaneous increase of Abs and decline of N-Ag.ConclusionsSerum N-Ag is a biomarker for SARS-CoV-2 acute infection with high diagnostic sensitivity and specificity compared to viral RNA in the respiratory system. There is a correlation between serum N-Ag concentrations and disease severity and an inverse relationship of N-Ag and Abs. The diagnostic value of serum N-Ag, as well as technical and practical advantages it could offer, may meet unsatisfied diagnostic and prognostic needs during the pandemic.

BackgroundClonal immunoglobulin and T-cell receptor rearrangements serve as tumor-specific markers that have become mainstays of the diagnosis and monitoring of lymphoid malignancy. Next-generation sequencing (NGS) techniques targeting these loci have been successfully applied to lymphoblastic leukemia and multiple myeloma for minimal residual disease detection. However, adoption of NGS for primary diagnosis remains limited.MethodsWe addressed the bioinformatics challenges associated with immune cell sequencing and clone detection by designing a novel web tool, CloneRetriever (CR), which uses machine-learning principles to generate clone classification schemes that are customizable, and can be applied to large datasets. CR has 2 applications-a "validation" mode to derive a clonality classifier, and a "live" mode to screen for clones by applying a validated and/or customized classifier. In this study, CR-generated multiple classifiers using 2 datasets comprising 106 annotated patient samples. A custom classifier was then applied to 36 unannotated samples.ResultsThe optimal classifier for clonality required clonal dominance ≥4.5× above background, read representation ≥8% of all reads, and technical replicate agreement. Depending on the dataset and analysis step, the optimal algorithm yielded sensitivities of 81%-90%, specificities of 97%-100%, areas under the curve of 91%-94%, positive predictive values of 92-100%, and negative predictive values of 88%-98%. Customization of the algorithms yielded 95%-100% concordance with gold-standard clonality determination, including rescue of indeterminate samples. Application to a set of unknowns showed concordance rates of 83%-96%.ConclusionsCR is an out-of-the-box ready and user-friendly software designed to identify clonal rearrangements in large NGS datasets for the diagnosis of lymphoid malignancies.

Background25-Hydroxyvitamin D [25(OH)D] may be a poor marker of vitamin D status as it reflects differences in vitamin D binding protein (VDBP) between individuals. The vitamin D metabolite ratio [VMR, ratio of 24,25(OH)2D3 to 25(OH)D3] is a marker of vitamin D status that has been hypothesized to be independent of variability in VDBP. This hypothesis has not been directly evaluated.MethodsWe measured 25(OH)D3, 24,25(OH)2D3, 1,25(OH)2D3, and VDBP in 377 community-dwelling older adults that participated in the Health Aging and Body Composition Study. 24,25(OH)2D3 and 25(OH)D3 were used to calculate the VMR. We used linear regression to assess the relationship between VDBP with the VMR, 24,25(OH)2D3, 25(OH)D3, and 1,25(OH)2D3.ResultsParticipants had mean age 75 ± 3 years, 52% were female, 40% were black, and 24% had chronic kidney disease. VDBP concentrations were associated with sex, serum albumin, and VDBP phenotype in multivariable models. In fully adjusted models, each 1% higher VDBP was associated with a 0.92%[95% CI(0.37,1.49%)], 0.76% (0.39, 1.13%), and 0.57% (0.29, 0.85%), higher 24,25(OH)2D3, 25(OH)D3, and 1,25(OH)2D3. The VMR was independent of VDBP concentration, [0.16%(-0.11, 0.44) higher VMR per 1% higher VDBP, P = .25].ConclusionsThe VMR was independent of VDBP concentration, whereas VDBP was strongly directly associated with the individual vitamin D metabolite concentrations. Prior studies evaluating only 25(OH)D3 may have been confounded by absence of data on VDBP status. The VMR may serve as an important biomarker of vitamin D status and clinical outcomes that can be utilized in populations with a large spectrum of VDBP concentrations.

BackgroundIt is unknown whether a positive serology result correlates with protective immunity against SARS-CoV-2. There are also concerns regarding the low positive predictive value of SARS-CoV-2 serology tests, especially when testing populations with low disease prevalence.MethodsA neutralization assay was validated in a set of PCR-confirmed positive specimens and in a negative cohort. In addition, 9530 specimens were screened using the Diazyme SARS-CoV-2 IgG serology assay and all positive results (N = 164 individuals) were reanalyzed using the neutralization assay, the Roche total immunoglobin assay, and the Abbott IgG assay. The relationship between the magnitude of a positive SARS-CoV-2 serology result and neutralizing activity was determined. Neutralizing antibody titers (50% inhibitory dilution, ID50) were also longitudinally monitored in patients confirmed to have SARS-CoV-2 by PCR.ResultsThe SARS-CoV-2 neutralization assay had a positive percentage agreement (PPA) of 96.6% with a SARS-CoV-2 PCR test and a negative percentage agreement (NPA) of 98.0% across 100 negative control individuals. ID50 neutralization titers positively correlated with all 3 clinical serology platforms. Longitudinal monitoring of hospitalized PCR-confirmed patients with COVID-19 demonstrated they made high neutralization titers against SARS-CoV-2. PPA between the Diazyme IgG assay alone and the neutralization assay was 50.6%, while combining the Diazyme IgG assay with either the Roche or Abbott platforms increased the PPA to 79.2 and 78.4%, respectively.ConclusionsThese 3 clinical serology assays positively correlate with SARS-CoV-2 neutralization activity observed in patients with COVID-19. All patients confirmed SARS-CoV-2 positive by PCR develop neutralizing antibodies.

BACKGROUND:Clinical LC-MS/MS assays traditionally require that samples be run in batches with calibration curves in each batch. This approach is inefficient and presents a barrier to random access analysis. We developed an alternative approach called multipoint internal calibration (MPIC) that eliminated the need for batch-mode analysis. METHODS:The new approach used 4 variants of 13C-labeled methotrexate (0.026-10.3 µM) as an internal calibration curve within each sample. One site carried out a comprehensive validation, which included an evaluation of interferences and matrix effects, lower limit of quantification (LLOQ), and 20-day precision. Three sites evaluated assay precision and linearity. MPIC was also compared with traditional LC-MS/MS and an immunoassay. RESULTS:Recovery of spiked analyte was 93%-102%. The LLOQ was validated to be 0.017 µM. Total variability, determined in a 20-day experiment, was 11.5%CV. In a 5-day variability study performed at each site, total imprecision was 3.4 to 16.8%CV. Linearity was validated throughout the calibrator range (r2 > 0.995, slopes = 0.996-1.01). In comparing 40 samples run in each laboratory, the median interlaboratory imprecision was 6.55%CV. MPIC quantification was comparable to both traditional LC-MS/MS and immunoassay (r2 = 0.96-0.98, slopes = 1.04-1.06). Bland-Altman analysis of all comparisons showed biases rarely exceeding 20% when MTX concentrations were >0.4 µM. CONCLUSION:The MPIC method for serum methotrexate quantification was validated in a multisite proof-of-concept study and represents a big step toward random-access LC-MS/MS analysis, which could change the paradigm of mass spectrometry in the clinical laboratory.

BackgroundBiomarkers are needed for noninvasive early detection of gastric cancer (GC). We investigated salivary extracellular RNA (exRNA) biomarkers as potential clinical evaluation tools for GC.MethodsUnstimulated whole saliva samples were prospectively collected from 294 individuals (163 GC and 131 non-GC patients) who underwent endoscopic evaluation at the Samsung Medical Center in Korea. Salivary transcriptomes of 63 GC and 31 non-GC patients were profiled, and mRNA biomarker candidates were verified with reverse transcription quantitative real-time PCR (RT-qPCR). In parallel, microRNA (miRNA) biomarkers were profiled and verified with saliva samples from 10 GC and 10 non-GC patients. Candidate biomarkers were validated with RT-qPCR in an independent cohort of 100/100 saliva samples from GC and non-GC patients. Validated individual markers were configured into a best performance panel.ResultsWe identified 30 mRNA and 15 miRNA candidates whose expression pattern associated with the presence of GC. Among them, 12 mRNA and 6 miRNA candidates were verified with the discovery cohort by RT-qPCR and further validated with the independent cohort (n = 200). The configured biomarker panel consisted of 3 mRNAs (SPINK7, PPL, and SEMA4B) and 2 miRNAs (MIR140-5p and MIR301a), which were all significantly down-regulated in the GC group, and yielded an area under the ROC curve (AUC) of 0.81 (95% CI, 0.72-0.89). When combined with demographic factors, the AUC of the biomarker panel reached 0.87 (95% CI, 0.80-0.93).ConclusionsWe have discovered and validated a panel of salivary exRNA biomarkers with credible clinical performance for the detection of GC. Our study demonstrates the potential utility of salivary exRNA biomarkers in screening and risk assessment for GC.

BackgroundIt was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential.MethodsWe compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated.ResultsThe miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%).ConclusionsOur results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies.

BackgroundAssociations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined.MethodsWe performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies.ResultsHigher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00-0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14-0.25) serving/day higher dairy intake (P = 3.15 × 10-12) and 0.12 (95% CI, 0.06-0.17) kg/m2 higher BMI (P = 2.11 × 10-5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27-0.92; P = 3.0 × 10-4).ConclusionsThe present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.

BACKGROUND:A fundamental precept of the carbohydrate-insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight. METHODS:Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI. RESULTS:Higher genetically determined insulin-30 was strongly associated with higher BMI (β = 0.098, P = 2.2 × 10-21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30. CONCLUSIONS:Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate-insulin model of obesity.

BackgroundCharacterization of circulating tumor cells (CTCs) has been used to provide prognostic, predictive, and pharmacodynamic information in many different cancers. However, the clinical significance of CTCs and circulating tumor microemboli (CTM) in patients with pancreatic ductal adenocarcinoma (PDAC) has yet to be determined.MethodsIn this prospective study, CTCs and CTM were enumerated in the peripheral blood of 63 patients with PDAC before treatment using anti-EpCAM (epithelial cell adhesion molecule)-conjugated supported lipid bilayer-coated microfluidic chips. Associations of CTCs and CTM with patients' clinical factors and prognosis were determined.ResultsCTCs were abundant [mean (SD), 70.2 (107.6)] and present in 81% (51 of 63) of patients with PDAC. CTM were present in 81% (51 of 63) of patients with mean (SD) 29.7 (1101.4). CTM was an independent prognostic factor of overall survival (OS) and progression free survival (PFS). Patients were stratified into unfavorable and favorable CTM groups on the basis of CTM more or less than 30 per 2 mL blood, respectively. Patients with baseline unfavorable CTM, compared with patients with favorable CTM, had shorter PFS (2.7 vs 12.1 months; P < 0.0001) and OS (6.4 vs 19.8 months; P < 0.0001). Differences persisted if we stratified patients into early and advanced diseases. The number of CTM before treatment was an independent predictor of PFS and OS after adjustment for clinically significant factors.ConclusionsThe number of CTM, instead of CTCs, before treatment is an independent predictor of PFS and OS in patients with PDAC.

BackgroundHistorically the success of mass spectrometry in the clinical laboratory has focused on drugs of abuse confirmations, newborn screening, and steroid analysis. Clinical applications of mass spectrometry continue to expand, and mass spectrometry is now being used in almost all areas of laboratory medicine.ContentA brief background of the evolution of mass spectrometry in the clinical laboratory is provided with a discussion of future applications. Prominent examples of mass spectrometry are covered to illustrate how it has improved the practice of medicine and enabled physicians to provide better patient care. With increasing economic pressures and decreasing laboratory test reimbursement, mass spectrometry testing has been shown to provide cost-effective solutions. In addition to pointing out the numerous benefits, the challenges of implementing mass spectrometry in the clinical laboratory are also covered.SummaryMass spectrometry continues to play a prominent role in the field of laboratory medicine. The advancement of this technology along with the development of new applications will only accelerate the incorporation of mass spectrometry into more areas of medicine.

BackgroundLaboratory diagnosis of erythropoietic protoporphyria (EPP) requires a marked increase in total erythrocyte protoporphyrin (300-5000 μg/dL erythrocytes, reference interval

Background24,25-Dihydroxyvitamin D [24,25(OH)2D] is a metabolite of 25-hydroxyvitamin D (25D). Blacks frequently have low total 25D without manifestations of vitamin D deficiency, suggesting that total serum 25D may incorrectly reflect vitamin D status in different racial groups. The ratio of serum 24,25(OH)2D to 25D [vitamin D metabolite ratio (VMR)] represents a new candidate biomarker for vitamin D status.MethodsWe measured 24,25(OH)2D3 and 25D3 by mass spectrometry in a random community cohort of black (n = 212) and white (n = 164) Americans to evaluate VMR as a marker for vitamin D status. We measured parathyroid hormone concentrations by immunoassay to compare VMR and 25D3 against a physiological indicator of vitamin D deficiency.ResultsSerum 24,25(OH)2D3 strongly correlated with 25D3 in both black and white study participants (r = 0.90, P < 0.001 and r = 0.86, P < 0.001 respectively). Blacks had lower mean 25D3 than whites [17.0 (7.8) vs 27.5 (11.3) ng/mL; 42.4 (19.5) vs 68.6 (28.2) nmol/L, P < 0.001] and lower mean 24,25(OH)2D3 [2.1 (1.3) vs 3.6 (2.0) ng/mL; 5.1 (3.1) vs 8.7 (4.8) nmol/L, P < 0.001]. In contrast to total 25D3 concentrations, mean VMR values were similar in blacks and whites [11.9 (4.0) vs 12.5 (3.4), P = 0.16, respectively] and were negatively correlated with parathyroid hormone concentrations in both races (rs = -0.26, P < 0.001, and rs = -0.25, P < 0.001, respectively).ConclusionsOur results provide further evidence that measurement of total 25D for assessment of vitamin D status in patients of African descent deserves reevaluation and suggest that alternative measures such as VMR should be considered.

BackgroundExtracellular RNAs (exRNAs) in human body fluids are emerging as effective biomarkers for detection of diseases. Saliva, as the most accessible and noninvasive body fluid, has been shown to harbor exRNA biomarkers for several human diseases. However, the entire spectrum of exRNA from saliva has not been fully characterized.MethodsUsing high-throughput RNA sequencing (RNA-Seq), we conducted an in-depth bioinformatic analysis of noncoding RNAs (ncRNAs) in human cell-free saliva (CFS) from healthy individuals, with a focus on microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and circular RNAs (circRNAs).ResultsOur data demonstrated robust reproducibility of miRNA and piRNA profiles across individuals. Furthermore, individual variability of these salivary RNA species was highly similar to those in other body fluids or cellular samples, despite the direct exposure of saliva to environmental impacts. By comparative analysis of >90 RNA-Seq data sets of different origins, we observed that piRNAs were surprisingly abundant in CFS compared with other body fluid or intracellular samples, with expression levels in CFS comparable to those found in embryonic stem cells and skin cells. Conversely, miRNA expression profiles in CFS were highly similar to those in serum and cerebrospinal fluid. Using a customized bioinformatics method, we identified >400 circRNAs in CFS. These data represent the first global characterization and experimental validation of circRNAs in any type of extracellular body fluid.ConclusionsOur study provides a comprehensive landscape of ncRNA species in human saliva that will facilitate further biomarker discoveries and lay a foundation for future studies related to ncRNAs in human saliva.

BackgroundHigh-resolution mass spectrometry (HRMS) has the potential to supplement other drug screening platforms used in toxicology laboratories. HRMS offers high analytical specificity, which can be further enhanced by incorporating a fragment ion for each analyte. The ability to obtain precursor ions and fragment ions using elevated collision energies (MS(E)) can help improve the specificity of HRMS methods.MethodsWe developed a broad-spectrum screening method on an ultraperformance liquid chromatography TOF mass spectrometer (UPLC-TOF-MS) using the MS(E) mode. A diverse set of patient samples were subjected to a simple dilute, hydrolyze, and shoot protocol and analyzed in a blind manner. Data were processed with 3 sets of criteria with increasing stringency, and the results were compared with the reference laboratory results.ResultsA combination of retention time match (±0.2 min), a protonated analyte, and fragment ion mass accuracy of ±5 ppm produced zero false-positive results. Using these criteria, we confirmed 92% (253/275) of true positives. The positive confirmation rate increased to 98% (270/275) when the requirement for a fragment ion was dropped, but also produced 53 false positives. A total of 136 additional positive drug findings not identified by the reference methods were identified with the UPLC-TOF-MS.ConclusionsMS(E) provides a unique way to incorporate fragment ion information without the need of precursor ion selection. A primary limitation of requiring a fragment ion for positive identification was that certain drug classes required high-energy collisions, which formed many fragment ions of low abundance that were not readily detected.

BackgroundCirculating cell-free DNA (ccf-DNA) is becoming an important biomarker for cancer diagnostics and therapy monitoring. The isolation of ccf-DNA from plasma as a "liquid biopsy" may begin to replace more invasive tissue biopsies for the detection and analysis of cancer-related mutations. Conventional methods for the isolation of ccf-DNA from plasma are costly, time-consuming, and complex, preventing the use of ccf-DNA biomarkers for point-of-care diagnostics and limiting other biomedical research applications.MethodsWe used an AC electrokinetic device to rapidly isolate ccf-DNA from 25 μL unprocessed blood. ccf-DNA from 15 chronic lymphocytic leukemia (CLL) patients and 3 healthy individuals was separated into dielectrophoretic (DEP) high-field regions, after which other blood components were removed by a fluidic wash. Concentrated ccf-DNA was detected by fluorescence and eluted for quantification, PCR, and DNA sequencing. The complete process, blood to PCR, required

BackgroundEndothelial lipase (EL) regulates the metabolism of HDL cholesterol (HDL-C). However, the role of EL in regulating plasma HDL-C concentrations and EL's potential involvement in atherosclerosis in humans has not been fully investigated due to the lack of reliable assays for EL mass. We developed an ELISA system for serum EL mass.MethodsHuman recombinant EL proteins, purified from cultured media of human EL-transfected Chinese hamster ovary cells, were used as antigen and calibrator. Two specific monoclonal antibodies were generated in mice against recombinant EL protein for a sandwich ELISA. We measured EL mass in human serum using EL recombinant protein as a calibration standard.ResultsThe EL antibodies did not cross-react with lipoprotein lipase and hepatic triglyceride lipase. The detection limit of the ELISA was 20 pg/mL, which is approximately 10 times lower than that of previous ELISA systems. Recovery of spiked EL in serum was 90%-105%. Assay linearity was intact with a >4-fold dilution of serum. Intra- and interassay CVs were

BackgroundOf the 3 circulating multimeric forms of adiponectin, the high-molecular-weight (HMW) form, as measured by size-exclusion and/or immunoblotting techniques, is a better index of insulin sensitivity for monitoring health and disease than is total adiponectin. We aimed to develop a simple ELISA to measure HMW adiponectin.MethodsWe pretreated serum or plasma samples with digestion solution containing proteinase K (Millipore, ESDS). HMW (Millipore, EZHMWA-64K) and total adiponectin (Millipore, EZHADP-61K) concentrations were measured in treated and untreated samples, respectively, from 108 individuals and from 20 morbidly obese patients before and at 1, 3, 6, and 12 months after gastric-bypass surgery.ResultsThe ELISA has a dynamic range of 3-200 microg/L and a detection limit of 0.8 microg/L. Intraassay and interassay CVs were

Adipose tissue secretes leptin, which interacts with receptors in the hypothalamus. In rodent models of obesity, leptin increases metabolism and decreases food intake, which helps to maintain normal body composition. Accurate and precise methods to quantitate circulating leptin concentrations are needed for physiological studies. We developed an RIA to measure leptin in rat plasma, serum, or adipocyte culture fluids. The working range of the assay, defined by the detection limit and the highest calibrator, was 0.5-50 micrograms/L. Recovery of 1.6-11.6 micrograms/L leptin added to serum was 92-103%. The rat leptin RIA correlated well with a previously developed mouse RIA when rat plasma was assayed with both methods (r = 0.94), but the mouse leptin assay underestimated rat leptin in plasma. Within- and between-run CVs were 2.4% to 5.7%. Plasma leptin concentrations correlated directly with percentage of body fat, and correlation improved when the results were separated by gender (r = 0.796, P < 0.001 for males; r = 0.710, P < 0.001 for females). Leptin concentrations were generally higher in male rats than in females; plasma leptin increased 0.60 microgram/L for each percentage of increase in body fat for males but only 0.22 microgram/L for females. We conclude that rat serum/plasma leptin concentrations are accurately and precisely measured with this new RIA.

We used quartz optical fibers and laser excitation in developing single-fiber fluoroprobes, to be used to measure molecular fluorescence in minute volumes of body fluids. We illustrate and discuss the analytical capabilities of these fluoroprobes. Limits of detection for the anti-tumor drug doxorubicin are about 10(-7) mol/L, by either conventional fluorescence or sequentially excited fluoroscence modes of detection. We also report the results of preliminary in vivo measurements of doxorubicin in the interstitial fluids of human tumors, heterotransplanted in immune-deficient laboratory mice.