(1) Background: Continuous monitoring of tacrolimus (TAC), mycophenolic acid (MPA), and creatinine (Cre) after renal transplantation is vitally important. In this study, we developed a new method based on volumetric absorptive microsampling (VAMS) combined with Ultra Performance Liquid Chromatography–Tandem Mass Spectrometry (UPLC-MS/MS) to simultaneously quantify three analytes including TAC, MPA, and Cre in whole blood. (2) Methods: The VAMS-based UPLC-MS/MS assay used a shared extraction and a single injection to simultaneously quantify the included TAC, MPA, and Cre. Development and validation were carried out following the Food and Drug Administration and European Medicines Agency guidelines for the validation of bioanalytical methods. Moreover, clinical validation for the three analytes was performed in both dried blood spot (DBS) and VAMS. Furthermore, a willingness survey was conducted using the system usability scale (SUS) for renal transplant recipients. (3) Results: The assay was successfully validated for all analytes. No interference, carryover, or matrix effects were observed, and extraction recoveries and process efficiencies were >90.00%. Analysis was unaffected by hematocrit (0.20~0.60, L/L) and anticoagulants (EDTA-2K). Dried VAMS samples were stable for 7 days at ambient temperature and stable for at least 1 month at −20 °C. During clinical validation, the measured TAC, corrected MPA, and Cre concentrations of VAMS samples met the analytical standards (95.00%, 88.57%, and 92.50%). When more stringent clinical acceptance criteria were set, the results obtained by VAMS (90.00%, 71.43%, and 85.00%) better than DBS (77.50%, 62.86%, and 70.00%). Compared with DBS, the survey found that renal transplant recipients are more inclined to use VAMS. (4) Conclusions: A robust extraction and UPLC-MS/MS analysis method in VAMS tips was developed and fully validated for the simultaneous quantification of TAC, MPA, and Cre concentrations. This method provides analytical support for the one-sample remote monitoring of both immunosuppressive drug concentrations and renal function in allo-renal recipients. Based on the good consistency between this method and the routine detection of venous blood samples and higher patient satisfaction than DBS, we believe that VAMS sampling can be a better alternative to venous whole-blood sampling.

Background: Clinically diagnosed pulmonary tuberculosis (PTB) patients lack Mycobacterium tuberculosis (MTB) microbiologic evidence, and misdiagnosis or delayed diagnosis often occurs as a consequence. We investigated the potential of lncRNAs and corresponding predictive models to diagnose these patients. Methods: We enrolled 1372 subjects, including clinically diagnosed PTB patients, non-TB disease controls and healthy controls, in three cohorts (Screening, Selection and Validation). Candidate lncRNAs differentially expressed in blood samples of the PTB and healthy control groups were identified by microarray and qRT-PCR in the Screening Cohort. Logistic regression models were developed using lncRNAs and/or electronic health records (EHRs) from clinically diagnosed PTB patients and non-TB disease controls in the Selection Cohort. These models were evaluated by AUC and decision curve analysis, and the optimal model was presented as a Web-based nomogram, which was evaluated in the Validation Cohort. The biological function of lncRNAs was interrogated using ELISA, lactate dehydrogenase release analysis and flow cytometry. Results: Three differentially expressed lncRNAs ( ENST00000497872, n333737, n335265 ) were identified. The optimal model (i.e., nomogram) incorporated these three lncRNAs and six EHR variables (age, hemoglobin, weight loss, low-grade fever, CT calcification and TB-IGRA). The nomogram showed an AUC of 0.89, sensitivity of 0.86 and specificity of 0.82 in the Validation Cohort, which demonstrated better discrimination and clinical net benefit than the EHR model. ENST00000497872 may regulate inflammatory cytokine production, cell death and apoptosis during MTB infection. Conclusion: LncRNAs and the user-friendly nomogram could facilitate the early identification of PTB cases among suspected patients with negative MTB microbiologic evidence. Key Messages: What is the key question?: Does integrating immune-related lncRNA signatures and electronic health records (EHRs) promote the early identification of PTB patients who are symptomatic but lack microbiologic evidence of Mycobacterium tuberculosis (MTB)? What is the bottom line?: We found three long non-coding RNAs (lncRNAs), i.e., ENST00000497872 , n 333737 and n335265 , were potential diagnostic biomarkers for clinically diagnosed PTB patients; and we further developed and validated a novel nomogram incorporating these three lncRNAs and six electronic health records (EHRs), which were readily obtainable even in a resource-constrained setting and achieved a c-statistic of 0.89, sensitivity of 0.86 and specificity of 0.82 in a separate validation cohort. Why read on?: This study focuses on the challenge of accurately diagnosing PTB patients with negative MTB microbiological evidence and serves as the first proof-of-concept that integrating lncRNA signatures and EHR data could be a more promising diagnostic approach for clinically diagnosed PTB patients. SUMMARY: This study developed and validated a novel nomogram that incorporated three lncRNAs and six EHR fields could be a useful predictive tool in identifying PTB patients who lack MTB microbiologic evidence.