Dopamine is one of the significant neurotransmitters and its monitoring in biological fluids is a critical issue in healthcare and modern biomedical technology. Here, we have developed a dopamine biosensor based on surface plasmon resonance (SPR). For this purpose, the carboxymethyl dextran SPR chip was used as a surface to immobilize laccase as a bioaffinity recognition element. Data analysis exhibited that the acidic pH value is the optimal condition for dopamine interaction. Calculated kinetic affinity (KD) (48,545 nM), obtained from a molecular docking study, showed strong association of dopamine with the active site of laccase. The biosensor exhibited a linearity from 0.01 to 189 μg/ml and a lower detection limit of 0.1 ng/ml (signal-to-noise ratio (S/N) = 3) that is significantly higher than the most direct dopamine detecting sensors reported so far. Experiments for specificity in the presence of compounds that can co-exist with dopamine detection such as ascorbic acid, urea and L-dopa showed no significant interference. The current dopamine biosensor with high sensitivity and specificity, represent a novel detection tool that offers a label-free, simple procedure and cost effective monitoring system.

BACKGROUND: Immune cells and cytokines have been linked to viremia dynamic and immune status during HIV infection. They may serve as useful biomarkers in the monitoring of people living with HIV-1 (PLHIV-1). The present work was aimed to assess whether cytokines and immune cell profiles may help in the therapeutic follow-up of PLHIV-1.
METHODS: Forty PLHIV-1 in treatment success (PLHIV-1s) and fifty PLHIV-1 in treatment failure (PLHIV-1f) followed at the University Hospital of Abomey-Calavi/Sô-Ava in Benin were enrolled. Twenty healthy persons were also recruited as control group. Circulating cytokines and immune cells were quantified respectively by ELISA and flow cytometry.
RESULTS: PLHIV-1 exhibited low proportions of CD4 + T cells, NK, NKT, granulocytes, classical and non-classical monocytes, and high proportions of CD8 + T cells, particularly in the PLHIV-1f group, compared to control subjects. Eosinophils, neutrophils and B cell frequencies did not change between the study groups. Circulating IFN-γ decreased whereas IL-4 significantly increased in PLHIV-1s compared to PLHIV-1f and control subjects even though the HIV infection in PLHIV-1s downregulated the high Th1 phenotype observed in control subjects. However, Th1/Th2 ratio remained biased to a Th1 phenotype in PLHIV-1f, suggesting that high viral load may have maintained a potential pro-inflammatory status in these patients. Data on inflammatory cytokines showed that IL-6 and TNF-α concentrations were significantly higher in PLHIV-1s and PLHIV-1f groups than in control subjects. Significant high levels of IL-5 and IL-7 were observed in PLHIV-1f compared to controls whereas PLHIV-1s presented only a high level of IL-5. No change was observed in IL-13 levels between the study groups.
CONCLUSIONS: Our study shows that, in addition to CD4/CD8 T cell ratio, NK and NKT cells along with IL-6, TNF-α, IL-5 and IL-7 cytokines could serve as valuable immunological biomarkers in the therapeutic monitoring of PLHIV-1 although a larger number of patients would be necessary to confirm these results.

BACKGROUND: Cystine-depleting therapy in nephropathic cystinosis is currently monitored via the white blood cell cystine assay, although its application and usefulness are limited by practical and technical issues. Therefore, alternative biomarkers that are widely available, more economical and less technically demanding, while reliably reflecting long-term adherence to cysteamine treatment, are desirable. Recently, we proposed chitotriosidase enzyme activity as a potential novel biomarker for the therapeutic monitoring of cysteamine treatment in cystinosis. In this study, we aimed to validate our previous findings and to confirm the value of chitotriosidase in the management of cystinosis therapy.
METHODS: A retrospective study was conducted on 12 patients treated at the National Institutes of Health Clinical Center and followed up for at least 2 years. Plasma chitotriosidase enzyme activity was correlated with corresponding clinical and biochemical data.
RESULTS: Plasma chitotriosidase enzyme activity significantly correlated with WBC cystine levels, cysteamine total daily dosage and a Composite compliance score. Moreover, plasma chitotriosidase was a significant independent predictor for WBC cystine levels, and cut-off values were established in both non-kidney transplanted and kidney transplanted cystinosis patients to distinguish patients with a good versus poor compliance with cysteamine treatment. Our observations are consistent with those of our previous study and validate our findings.
CONCLUSIONS: Chitotriosidase enzyme activity is a valid potential alternative biomarker for monitoring cysteamine treatment in nephropathic cystinosis patients.
CONCLUSIONS: Chitotriosidase enzyme activity is a valid potential alternative biomarker for monitoring cysteamine treatment in nephropathic cystinosis patients.

This study presents an in-depth analysis of mitochondrial enzyme activities in Friedreich\'s ataxia (FA) patients, focusing on the Electron Transport Chain complexes I, II, and IV, the Krebs Cycle enzyme Citrate Synthase, and Coenzyme Q10 levels. It examines a cohort of 34 FA patients, comparing their mitochondrial enzyme activities and clinical parameters, including disease duration and cardiac markers, with those of 17 healthy controls. The findings reveal marked reductions in complexes II and, specifically, IV, highlighting mitochondrial impairment in FA. Additionally, elevated Neurofilament Light Chain levels and cardiomarkers were observed in FA patients. This research enhances our understanding of FA pathophysiology and suggests potential biomarkers for monitoring disease progression. The study underscores the need for further clinical trials to validate these findings, emphasizing the critical role of mitochondrial dysfunction in FA assessment and treatment.

Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) has demonstrated remarkable therapeutic effects in ALK-positive non-small cell lung cancer (NSCLC) patients. Identifying prognostic biomarkers can enhance the clinical efficacy of relapsed or refractory patients.
We profiled 737 plasma proteins from 159 pre-treatment and on-treatment plasma samples of 63 ALK-positive NSCLC patients using data-independent acquisition-mass spectrometry (DIA-MS). The consensus clustering algorithm was used to identify subtypes with distinct biological features. A plasma-based prognostic model was constructed using the LASSO-Cox method. We performed the Mfuzz analysis to classify the patterns of longitudinal changes in plasma proteins during treatment. 52 baseline plasma samples from another independent ALK-TKI treatment cohort were collected to validate the potential prognostic markers using ELISA.
We identified three subtypes of ALK-positive NSCLC with distinct biological features and clinical efficacy. Patients in subgroup 1 exhibited activated humoral immunity and inflammatory responses, increased expression of positive acute-phase response proteins, and the worst prognosis. Then we constructed and verified a prognostic model that predicts the efficacy of ALK-TKI therapy using the expression levels of five plasma proteins (SERPINA4, ATRN, APOA4, TF, and MYOC) at baseline. Next, we explored the longitudinal changes in plasma protein expression during treatment and identified four distinct change patterns (Clusters 1-4). The longitudinal changes of acute-phase proteins during treatment can reflect the treatment status and tumor progression of patients. Finally, we validated the prognostic efficacy of baseline plasma CRP, SAA1, AHSG, SERPINA4, and TF in another independent NSCLC cohort undergoing ALK-TKI treatment.
This study contributes to the search for prognostic and drug-resistance biomarkers in plasma samples for ALK-TKI therapy and provides new insights into the mechanism of drug resistance and the selection of follow-up treatment.

BACKGROUND: 18F-FDG-PET/CT is recommended to improve the diagnosis of prosthetic valve infective endocarditis (PVIE) and is a major criterion in the ESC-2015 classification. However, there is little evidence for its usefulness in the follow-up of medically treated PVIE patients.
METHODS: A monocentric retrospective analysis of patients hospitalized for PVIE between January 2013 and December 2019 who were not treated with surgery and who had at least two 18F-FDG-PET/CT examinations during their medical management.
RESULTS: Among 170 patients with PVIE, 117 were treated with antibiotic therapy but no surgery. Of these, 36 (31%) had at least two 18F-FDG-PET/CT examinations. At initial imaging, 28 patients had heterogeneous FDG uptake on their prosthetic valve and eight on their associated aortic graft. Hypermetabolism of spleen and bone marrow (HSBM) was observed in 18 and 19 patients, respectively. At the first follow-up 18F-FDG-PET/CT, 21 (58%) patients still had heterogeneous uptake, indicating persistent active endocarditis. HSBM was still present at the last follow-up imaging in four of the six patients with recurrent PVIE.
CONCLUSIONS: 18F-FDG-PET/CT monitoring of medically treated patients with PVIE provides valuable additional information and prospective multicentric study should be conducted to assess its usefulness.

Therapeutic monitoring of drugs, particularly those with multiple metabolites, can be time-consuming and labor-intensive due to the need for different analytical methods depending on the specific metabolite or matrix of interest. In this study, we employed a heart-cutting 2D-LC separation method based on the coupling of reversed-phase and mixed-mode mechanisms to determine Favipiravir and surrogates of five main metabolites. This approach was applied to serum, plasma, urine, and human peripheral blood mononuclear cells. The method underwent validation to ensure its reliability. The findings highlight the potential of 2D-LC as a practical and efficient approach for therapeutic drug monitoring.

BACKGROUND: Challenges remain in determining the most effective treatment strategies and identifying patients who would benefit from adjuvant or neoadjuvant therapy in renal cell carcinoma. The objective of this review is to provide a comprehensive overview of biomarkers in metastatic renal cell carcinoma (mRCC) and their utility in prediction of treatment response, prognosis, and therapeutic monitoring in patients receiving systemic therapy for metastatic disease.
METHODS: A systematic literature search was conducted using the PubMed database for relevant studies published between January 2017 and December 2022. The search focused on biomarkers associated with mRCC and their relationship to immune checkpoint inhibitors, targeted therapy, and VEGF inhibitors in the adjuvant, neoadjuvant, and metastatic settings.
RESULTS: The review identified various biomarkers with predictive, prognostic, and therapeutic monitoring potential in mRCC. The review also discussed the challenges associated with anti-angiogenic and immune-checkpoint monotherapy trials and highlighted the need for personalized therapy based on molecular signatures.
CONCLUSIONS: This comprehensive review provides valuable insights into the landscape of biomarkers in mRCC and their potential applications in prediction of treatment response, prognosis, and therapeutic monitoring. The findings underscore the importance of incorporating biomarker assessment into clinical practice to guide treatment decisions and improve patient outcomes in mRCC.

Accurate detection and monitoring of therapeutic drug levels are vital for effective patient care and treatment management. Aptamers, composed of single-stranded DNA or RNA molecules, are integral components of biosensors designed for both qualitative and quantitative detection of biological samples. Aptasensors play crucial roles in target identification, validation, detection of drug-target interactions and screening potential of drug candidates. This review focuses on the pivotal role of aptasensors in early disease detection, particularly in identifying biomarkers associated with various diseases such as cancer, infectious diseases and cardiovascular disorders. Aptasensors have demonstrated exceptional potential in enhancing disease diagnostics and monitoring therapeutic drug levels. Aptamer-based biosensors represent a transformative technology in the field of healthcare, enabling precise diagnostics, drug monitoring and disease detection.