Acoustofluidic Virus Isolation via Bessel Beam Excitation Separation Technology.

The isolation of viruses from complex biological samples is essential for creating sensitive bioassays that assess the efficacy and safety of viral therapeutics and vaccines, which have played a critical role during the COVID-19 pandemic. However, existing methods of viral isolation are time-consuming and labor-intensive due to the multiple processing steps required, resulting in low yields. Here, we introduce the rapid, efficient, and high-resolution acoustofluidic isolation of viruses from complex biological samples via Bessel beam excitation separation technology (BEST). BEST isolates viruses by utilizing the nondiffractive and self-healing properties of 2D, in-plane acoustic Bessel beams to continuously separate cell-free viruses from biofluids, with high throughput and high viral RNA yield. By tuning the acoustic parameters, the cutoff size of isolated viruses can be easily adjusted to perform dynamic, size-selective virus isolation while simultaneously trapping larger particles and separating smaller particles and contaminants from the sample, achieving high-precision isolation of the target virus. BEST was used to isolate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from human saliva samples and Moloney Murine Leukemia Virus from cell culture media, demonstrating its potential use in both practical diagnostic applications and fundamental virology research. With high separation resolution, high yield, and high purity, BEST is a powerful tool for rapidly and efficiently isolating viruses. It has the potential to play an important role in the development of next-generation viral diagnostics, therapeutics, and vaccines.

Saliva, Plasma, and Multifluid Metabolomic Signatures of Periodontal Disease, Type 2 Diabetes Progression, and Markers of Glycemia and Dyslipidemia Among Puerto Rican Adults With Overweight and Obesity.

BACKGROUND: Evidence from cohort studies indicates a bidirectional relationship between periodontal disease and type 2 diabetes (T2D), but the underlying mechanisms remain unknown. In this study, we aimed to (1) identify saliva, plasma, and multifluid metabolomic signatures associated with periodontal disease and (2) determine if these signatures predict T2D progression and cardiometabolic biomarkers at year 3. METHODS AND RESULTS: We included participants from the SOALS (San Juan Overweight Adult Longitudinal Study) (n=911). Metabolites from saliva (k=635) and plasma (k=1051) were quantified using liquid chromatography-mass spectrometry. We applied elastic net regression with 10-fold cross-validation to identify baseline metabolomic signatures of periodontal disease. Multivariable Cox proportional hazards regression and linear regression were used to evaluate the association with T2D progression and biomarker concentrations. Metabolomic profiles included highly weighted metabolites related to lysine and pyrimidine metabolism. Periodontal disease or its 3 metabolomic signatures were not associated with T2D progression in 3 years. Prospectively, 1-SD increments in the multifluid and saliva metabolomic signatures were associated with higher low-density lipoprotein (multifluid: 12.9±5.70, P=0.02; saliva: 13.3±5.11, P=0.009). A 1-SD increment in the plasma metabolomic signature was also associated with Homeostatic Model Assessment for Insulin Resistance (2.67±1.14, P=0.02) and triglyceride (0.52±0.18, P=0.002). CONCLUSIONS: Although metabolomic signatures of periodontal disease could not predict T2D progression, they were associated with low-density lipoprotein, triglyceride, and Homeostatic Model Assessment for Insulin Resistance levels at year 3.

The Association between Retinal Thickness Fluctuations and Visual Outcomes under Anti-Vascular Endothelial Growth Factor Therapy: A Systematic Review and Meta-Analysis.

INTRODUCTION: The objective of this study was to examine the association between retinal thickness (RT) fluctuations and best corrected visual acuity (BCVA) in eyes with neovascular AMD, macular edema secondary to RVO, and DME treated with anti-VEGF therapy. METHODS: A systematic search of Ovid MEDLINE, EMBASE, and the Cochrane Library was performed from January 2006 to March 2024. Studies comparing visual or anatomic outcomes of patients treated with anti-VEGF therapy, stratified by magnitudes of RT fluctuation, were included. ROBINS-I and Cochrane RoB 2 tools were used to assess risk of bias, and certainty of evidence was evaluated with GRADE criteria. Meta-analysis was performed with a random-effects model. Primary outcomes were final BCVA and change in BCVA relative to baseline. RESULTS: 15,725 articles were screened; 15 studies were identified in the systematic review and 5 studies were included in the meta-analysis. Final ETDRS VA was significantly worse in eyes with the highest level of RT fluctuation (weighted mean difference [WMD] = 7.86 letters; 95% CI, 4.97, 10.74; p < 0.00001; I2 = 81%; 3,136 eyes). RT at last observation was significantly greater in eyes with high RT fluctuations (WMD = -27.35 µm; 95% CI, -0.04, 54.75; p = 0.05; I2 = 88%; 962 eyes). CONCLUSIONS: Final visual outcome is associated with magnitude of RT fluctuation over the course of therapy. It is unclear whether minimizing RT fluctuations would help optimize visual outcomes in patients treated with anti-VEGF therapy. These findings are limited by a small set of studies, risk of bias, and considerable heterogeneity.

Single-stranded pre-methylated 5mC adapters uncover the methylation profile of plasma ultrashort Single-stranded cell-free DNA.

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed genes of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults.

AIMS/HYPOTHESIS: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites. METHODS: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors. RESULTS: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures. CONCLUSIONS/INTERPRETATION: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

Seronegative patients with primary Sjögren's syndrome and non-pSS sicca test positive for anti-SSA/Ro52 and -Ro60 in saliva.

OBJECTIVES: Testing for anti-SSA/Ro antibodies in serum is essential in the diagnostic work-up for primary Sjögren's syndrome (pSS). In this study, we aimed to validate our previous assay for detection of salivary anti-SSA/Ro52, and to develop assays for detection of salivary anti-SSA/Ro60 and for detection of anti-Ro52 and -Ro60 in plasma using the electric field-induced release and measurement (EFIRM) platform. METHODS: Whole saliva samples from two independent Danish cohorts (DN1 and DN2) including 49 patients with pSS, 73 patients with sicca symptoms, but not fulfilling the classification criteria for pSS (non-pSS sicca), and 51 healthy controls (HC), as well as plasma samples from the DN1 cohort were analyzed using EFIRM to detect anti-SSA/Ro52 and -Ro60. RESULTS: In the DN1 cohort, 100 % in the pSS group and 16 % in the non-pSS sicca group were serum anti-SSA/Ro positive by ELISA. EFIRM detected anti-SSA (Ro52 and/or -Ro60) in plasma and saliva in 100 % and 96 % patients with pSS, and 16 % and 29 % with non-pSS sicca. In the DN2 cohort, 80 % patients with pSS and 26 % with non-pSS sicca were serum anti-SSA/Ro positive. Salivary anti-SSA discriminated patients with pSS from HC and non-pSS sicca with an AUC range of 0.74-0.96 in the DN1 and DN2 cohorts. EFIRM discriminated pSS from non-pSS sicca with an AUC of 0.98 in plasma. CONCLUSION: Our findings suggest that salivary anti-SSA/Ro antibodies are potential discriminatory biomarkers for pSS, which may also identify seronegative patients, addressing the unmet clinical need of early detection and stratification of pSS.

Distinctive profile of monomeric and polymeric anti-SSA/Ro52 immunoglobulin A1 isoforms in saliva of patients with primary Sjögren's syndrome and Sicca.

OBJECTIVE: Primary Sjögren's syndrome (pSS) is the second most common chronic autoimmune connective tissue disease. Autoantibodies, immunoglobulin (IgG) anti-SSA/Ro, in serum is a key diagnostic feature of pSS. Since pSS is a disease of the salivary gland, we investigated anti-SSA/Ro52 in saliva. METHODS: Using a novel electrochemical detection platform, Electric Field-Induced Release and Measurement, we measured IgG/M/A, IgG, IgA, IgA isotypes (IgA1 and IgA2) and IgA1 subclasses (polymeric and monomeric IgA1) to anti-SSA/Ro52 in saliva supernatant of 34 pSS, 35 dry eyes and dry mouth (patients with Sicca) and 41 health controls. RESULTS: Saliva IgG/M/A, IgG, IgA, IgA isotypes and IgA1 subclasses to anti-SSA/Ro52 differed significantly between pSS, non-pSS Sicca and healthy subjects. Elevated monomeric IgA1 was observed in patients with non-pSS Sicca while elevated polymeric IgA1 (pIgA1) was observed in patients with pSS. Salivary polymeric but not monomeric IgA1 (mIgA1) isoform correlated with focus score (r2=0.467, p=0.001) CONCLUSIONS: Salivary anti-Ro52 polymeric IgA1 isoform is associated with glandular inflammation in pSS, while salivary monomeric IgA1 is associated with Sicca. Whether IgA1 isotope switching plays a role in the progression of the Sicca to pSS warrants further investigation.

A review on the impact of single-stranded library preparation on plasma cell-free diversity for cancer detection.

In clinical oncology, cell-free DNA (cfDNA) has shown immense potential in its ability to noninvasively detect cancer at various stages and monitor the progression of therapy. Despite the rapid improvements in cfDNA liquid biopsy approaches, achieving the required sensitivity to detect rare tumor-derived cfDNA still remains a challenge. For next-generation sequencing, the perceived presentation of cfDNA is strongly linked to the extraction and library preparation protocols. Conventional double-stranded DNA library preparation (dsDNA-LP) focuses on assessing ~167bp double-stranded mononucleosomal (mncfDNA) and its other oligonucleosomal cell-free DNA counterparts in plasma. However, dsDNA-LP methods fail to include short, single-stranded, or nicked DNA in the final library preparation, biasing the representation of the actual cfDNA populations in plasma. The emergence of single-stranded library preparation (ssDNA-LP) strategies over the past decade has now allowed these other populations of cfDNA to be studied from plasma. With the use of ssDNA-LP, single-stranded, nicked, and ultrashort cfDNA can be comprehensively assessed for its molecular characteristics and clinical potential. In this review, we overview the current literature on applications of ssDNA-LP on plasma cfDNA from a potential cancer liquid biopsy perspective. To this end, we discuss the molecular principles of single-stranded DNA adapter ligation, how library preparation contributes to the understanding of native cfDNA characteristics, and the potential for ssDNA-LP to improve the sensitivity of circulating tumor DNA detection. Additionally, we review the current literature on the newly reported species of plasma ultrashort single-stranded cell-free DNA plasma, which appear biologically distinct from mncfDNA. We conclude with a discussion of future perspectives of ssDNA-LP for liquid biopsy endeavors.

Multi-faceted attributes of salivary cell-free DNA as liquid biopsy biomarkers for gastric cancer detection.

BACKGROUND: Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. METHODS: In this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. RESULTS: Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). CONCLUSION: These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases.

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring.

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

Distinct Features of Plasma Ultrashort Single-Stranded Cell-Free DNA as Biomarkers for Lung Cancer Detection.

BACKGROUND: Using broad range cell-free DNA sequencing (BRcfDNA-Seq), a nontargeted next-generation sequencing (NGS) methodology, we previously identified a novel class of approximately 50 nt ultrashort single-stranded cell-free DNA (uscfDNA) in plasma that is distinctly different from 167 bp mononucleosomal cell-free DNA (mncfDNA). We hypothesize that uscfDNA possesses characteristics that are useful for disease detection. METHODS: Using BRcfDNA-Seq, we examined both cfDNA populations in the plasma of 18 noncancer controls and 14 patients with late-stage nonsmall cell lung carcinoma (NSCLC). In comparison to mncfDNA, we assessed whether functional element (FE) peaks, fragmentomics, end-motifs, and G-Quadruplex (G-Quad) signatures could be useful features of uscfDNA for NSCLC determination. RESULTS: In noncancer participants, compared to mncfDNA, uscfDNA fragments showed a 45.2-fold increased tendency to form FE peaks (enriched in promoter, intronic, and exonic regions), demonstrated a distinct end-motif-frequency profile, and presented with a 4.9-fold increase in G-Quad signatures. Within NSCLC participants, only the uscfDNA population had discoverable FE peak candidates. Additionally, uscfDNA showcased different end-motif-frequency candidates distinct from mncfDNA. Although both cfDNA populations showed increased fragmentation in NSCLC, the G-Quad signatures were more discriminatory in uscfDNA. Compilation of cfDNA features using principal component analysis revealed that the first 5 principal components of both cfDNA subtypes had a cumulative explained variance of >80%. CONCLUSIONS: These observations indicate that the distinct biological processes of uscfDNA and that FE peaks, fragmentomics, end-motifs, and G-Quad signatures are uscfDNA features with promising biomarker potential. These findings further justify its exploration as a distinct class of biomarker to augment pre-existing liquid biopsy approaches.

Extrinsic and intrinsic preanalytical variables affecting liquid biopsy in cancer.

Liquid biopsy, through isolation and analysis of disease-specific analytes, has evolved as a promising tool for safe and minimally invasive diagnosis and monitoring of tumors. It also has tremendous utility as a companion diagnostic allowing detection of biomarkers in a range of cancers (lung, breast, colon, ovarian, brain). However, clinical implementation and validation remains a challenge. Among other stages of development, preanalytical variables are critical in influencing the downstream cellular and molecular analysis of different analytes. Although considerable progress has been made to address these challenges, a comprehensive assessment of the impact on diagnostic parameters and consensus on standardized and optimized protocols is still lacking. Here, we summarize and critically evaluate key variables in the preanalytical stage, including study population selection, choice of biofluid, sample handling and collection, processing, and storage. There is an unmet need to develop and implement comprehensive preanalytical guidelines on the optimal practices and methodologies.

Immunoassay Detects Salivary Anti-SSA/Ro-52 Autoantibodies in Seronegative Patients with Primary Sjögren's Syndrome.

The diagnostic work-up for Sjögren's syndrome is challenging and complex, including testing for serum autoantibodies to SSA/Ro and a labial salivary gland biopsy. Furthermore, the diagnosis is often delayed. In this study, we tested the hypothesis that anti-SSA/Ro autoantibodies are detectable in the saliva of patients with primary Sjögren's syndrome (pSS) because the disease affects the salivary glands, and these autoantibodies display greater discriminatory performance in saliva than in serum. SSA/Ro-52 Ags were used to develop what is, to our knowledge, a novel quantitative electrochemical-based immunoassay: the electric field-induced release and measurement (EFIRM) platform. The clinical utility was determined by measuring salivary anti-SSA/Ro-52 autoantibodies in patients with pSS and sicca (n = 34), patients without pSS with sicca (n = 35), and healthy subjects (n = 41). The statistical analysis of discrimination included the area under the receiver operating characteristic curve. Salivary anti-SSA/Ro-52 autoantibodies were measured in 94% (32 of 34) of patients with pSS with 85% (29 of 34) seropositivity. Four of the five seronegative patients with pSS had EFIRM-measurable anti-SSA/Ro-52 autoantibodies in saliva. Additionally, 60% (21 of 35) of the seronegative patients without pSS who had sicca had EFIRM-detectable SSA/Ro-52 autoantibodies in saliva, indicating the onset of autoimmune disease. Two of the 41 healthy control subjects had EFIRM-detectable SSA/Ro-52 autoantibodies in their saliva. Salivary SSA/Ro-52 autoantibodies significantly discriminated patients with pSS or patients with the initial stage of autoimmune disease from healthy subjects with an area under the receiver operating characteristic curve of 0.91. Our findings suggest that the proposed saliva SSA/Ro-52 immunoassay improves early and accurate diagnosis of seronegative patients with pSS and patients with early-onset autoimmune disease.

Multi-Faceted Attributes of Salivary Cell-free DNA as Liquid Biopsy Biomarkers for Gastric Cancer Detection.

Background: Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. Methods: In this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. Results: Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). Conclusion: These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases.

Saliva diagnostics: Salivaomics, saliva exosomics, and saliva liquid biopsy.

BACKGROUND: Each day, humans produce approximately 0.5 through 1.5 liters of saliva, a biofluid that is rich in biological omic constituents. Our lack of understanding how omic biomarkers migrate from diseased tissue to the saliva has impeded the clinical translation of saliva testing. Although such biomarkers must be conveyed via the vascular and lymphatic systems to the salivary glands, the molecular mechanisms that underlie this transport remain unclear. Although COVID-19 highlighted the need for rapid and reliable testing for infectious diseases, it represents only one of the many health conditions that potentially can be diagnosed using a saliva sample. TYPES OF STUDIES REVIEWED: The authors discuss salivaomics, saliva exosomics, and the mechanisms on which saliva diagnostics are based and introduce a novel electrochemical sensing technology that may be exploited for saliva liquid biopsy. RESULTS: The utility of saliva for screening for lung cancer is under investigation. Saliva testing may be used to stratify patients, monitor treatment response, and detect disease recurrence. The authors also highlight the landscapes of saliva-based SARS-CoV-2 testing and ultrashort cell-free DNA and outline how these fields are likely to evolve in the near future. PRACTICAL IMPLICATIONS: Breakthroughs in the study of saliva research, therefore, will facilitate clinical deployment of saliva-based testing.

Single-Droplet Microsensor for Ultra-Short Circulating EFGR Mutation Detection in Lung Cancer Based on Multiplex EFIRM Liquid Biopsy.

Liquid biopsy is a rapidly emerging field that involves the minimal/non-invasive assessment of signature somatic mutations through the analysis of circulating tumor DNA (ctDNA) shed by tumor cells in bodily fluids. Broadly speaking, the unmet need in liquid biopsy lung cancer detection is the lack of a multiplex platform that can detect a mutation panel of lung cancer genes using a minimum amount of sample, especially for ultra-short ctDNA (usctDNA). Here, we developed a non-PCR and non-NGS-based single-droplet-based multiplexing microsensor technology, "Electric-Field-Induced Released and Measurement (EFIRM) Liquid Biopsy" (m-eLB), for lung cancer-associated usctDNA. The m-eLB provides a multiplexable assessment of usctDNA within a single droplet of biofluid in only one well of micro-electrodes, as each electrode is coated with different probes for the ctDNA. This m-eLB prototype demonstrates accuracy for three tyrosine-kinase-inhibitor-related EGFR target sequences in synthetic nucleotides. The accuracy of the multiplexing assay has an area under the curve (AUC) of 0.98 for L858R, 0.94 for Ex19 deletion, and 0.93 for T790M. In combination, the 3 EGFR assay has an AUC of 0.97 for the multiplexing assay.

The effects of analytics capability and sensing capability on operations performance: the moderating role of data-driven culture.

Studies indicate that organizational capability is a key factor in operational performance, and that both sensing and analytics capabilities have a significant influence on operational performance. This study develops a framework to examine the impact of organizational capability on operational performance, with a specific focus on the implementation of sensing and analytics capabilities. We combine strategic fit theory, the dynamic capability view, and the resource-based view to examine how micro, small, and medium enterprises (MSMEs) strategically integrate a data-driven culture (DDC) with their organizational capabilities to enhance operational performance. We carry out empirical research to investigate whether a DDC moderates the influence of organizational capability on operational performance. Structural equation modeling of survey data from 149 MSMEs reveals that both sensing and analytics capabilities have a positive impact on operational performance. The results also suggest that a DDC positively moderates the influence of organizational capability on operational performance. We discuss the theoretical and managerial implications of our findings, the limitations of the study, and opportunities for further research.