Immunosensors for quantifying cyclooxygenase 2 pain biomarkers

Objective clinical pain analysis using serum cyclooxygenase-2 and inducible nitric oxide synthase in American patients

BACKGROUND

Pain is a multidimensional condition of multiple origins. Determining both intensity and underlying cause are critical for effective management. Utilization of painkillers does not follow any guidelines relying on biomarkers, which effectively eliminates objective treatment. The aim of this study was to evaluate the use of serum cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) as pain biomarkers. This work could significantly advance the diagnosis and treatment of pain.

METHODS

We assessed the potential utility of serum COX-2 and iNOS as objective measures of pain in a sample of American patients. Pain was scaled between level 0-5 in accordance with the level reported by the patients. Blood samples were collected from 102 patients in the emergency room. Sandwich ELISA was used to determine the COX-2 and iNOS levels in the blood serum while statistical analysis was performed using Pearson product-moment correlation coefficients, Regression and Receiver Operating Characteristics (ROC) analyses. The biomarker results were also compared with self-reports of pain by the patients using conventional pain ratings and patients were asked to report the cause of the pain. Pain levels were clustered into four groups as 0 [self-reported 0], 1 [self-reported as 1], 2 [self-reported as 2 and 3] and 3 [self-reported as 4 and 5]. Co-expression of COX-2 and iNOS could significantly alter pain development and its sensitization. Therefore, iNOS dependent COX-2 levels were employed as categorized level.

RESULTS

Self-reported pain levels did not show a correlation with the serum level of COX-2 and iNOS. The lack of correlation is attributed to multiple reasons including patients' intake of painkillers prior to participation, painkiller intake habit, chronic diseases, and subjectivity of self-reported pain. Increased serum COX-2 levels were reported in relation to the subtypes of these health issues. Further, 83% of the patients who reported pain also showed the presence of COX-2 in serum, while only 53% of the patients showed the presence of iNOS in serum. Moderate relation was found between the clustered pain level and categorized COX-2 and iNOS- levels.

CONCLUSIONS

The findings support the requirement of further studies to use COX-2 and iNOS as prognostic biomarkers for objective quantification of pain at the clinical level.

Selective Sensing and Imaging of Penicillium italicum Spores and Hyphae Using Carbohydrate-Lectin Interactions

The blue-green mold Penicillium italicum is among the most problematic post-harvest plant infections limiting the integrity of citrus and many other crops during storage and transportation, but there is no sensor for its on-site or field detection. We hereby, for the first time, report the development of novel biomolecular sensor for assessing the presence of P. italicum spores and hyphae using carbohydrate-lectin recognitions. Two approaches were developed: (i) lateral tests using standalone poly(amic) acid (PAA) membranes and glass surfaces and (ii) quantitative tests on 96-well polystyrene plates and paper electrodes. In both cases, the surfaces were functionalized with novel derivatized sugar based ligands while staining was performed with gold nanoparticles. Both approaches provided strong signals for 10⁴ spores/mL of P. italicum isolated from experimentally infected lemons as the lowest-reliable concentration. The 96-well plate-based gave the most sensitive detection with a 4 × 10² spores/mL limit of detection, a linear dynamic range between 2.9 × 10³ and 6.02 × 10⁴ spores/mL ( R² = 0.9939) and standard deviation of less than 5% for five replicate measurements. The selectivity of the ligands was tested against Trichaptum biforme, Glomerulla cingulata ( Colletotrichum gloeosporioides), and Aspergillus nidulans fungi species. The highest selectivity was obtained using the sugar-based gold-nanoparticles toward both the spores and the hyphae of P. italicum. The advanced specificity was provided by the utilized sugar ligands employed in the synthesis of gold nanoparticles and was independent from size and shapes of the AuNPs. Accuracy of the sensor response showed dramatic dependence on the sample preparation. In the case of 5-10 min centrifugation at 600 rpm, the spores can be isolated free from hyphae and conidiophore, for which spiked recovery was up to 95% (std ±4). In contrast, for gravity-based precipitation of hyphae, the spiked recovery was 88% (std 11).

Screening and Biosensor-Based Approaches for Lung Cancer Detection

Early diagnosis of lung cancer helps to reduce the cancer death rate significantly. Over the years, investigators worldwide have extensively investigated many screening modalities for lung cancer detection, including computerized tomography, chest X-ray, positron emission tomography, sputum cytology, magnetic resonance imaging and biopsy. However, these techniques are not suitable for patients with other pathologies. Developing a rapid and sensitive technique for early diagnosis of lung cancer is urgently needed. Biosensor-based techniques have been recently recommended as a rapid and cost-effective tool for early diagnosis of lung tumor markers. This paper reviews the recent development in screening and biosensor-based techniques for early lung cancer detection.

Early lung cancer diagnosis by biosensors

Lung cancer causes an extreme threat to human health, and the mortality rate due to lung cancer has not decreased during the last decade. Prognosis or early diagnosis could help reduce the mortality rate. If microRNA and tumor-associated antigens (TAAs), as well as the corresponding autoantibodies, can be detected prior to clinical diagnosis, such high sensitivity of biosensors makes the early diagnosis and prognosis of cancer realizable. This review provides an overview of tumor-associated biomarker identifying methods and the biosensor technology available today. Laboratorial researches utilizing biosensors for early lung cancer diagnosis will be highlighted.