A Microarray Immunoassay for Serum Thyrotropin and Thyroglobulin Using Antibodies Immobilized on Track-Etched Membranes

Serum thyroglobulin (Tg) and thyroid stimulating hormone (TSH) measurements have evolved as important analytes for monitoring the prognosis of patients with differentiated thyroid cancer, post-thyroidectomy. Individual analyte immunoassay is the current practice in clinical pathology, but the simultaneous assay for all relevant analytes for a given disease, can reduce assay costs, improve patient compliance and give the clinician more information for an unequivocal diagnosis. Microarray immunoassay (MI) can achieve this goal and, hence, we have developed and validated a immuno-radiometric MI for quantitation of serum TSH and Tg by using highly micro-porous polycarbonate (PC) track-etched membranes (TEM) to immobilize the monoclonal anti-TSH and polyclonal anti-Tg antibodies in ~1 mm diameter spots. Non-competitive immunoassays were performed using mixture of ¹²⁵I labeled monoclonal anti-TSH and anti-Tg antibodies. Phosphorimager was used to quantify the bound radioactivity. TSH and Tg were detected with detection limit of 0.07 µIU/ml and 0.13 ng/ml respectively, which is lower than the clinically required cut-off level. The assay showed: acceptable intra-assay precision within 20 % and recovery in the range of 76–111.2 %. MI compared well with the established immunoradiometric assay (IRMA) with r = 0.98, p < 0.01 (n = 41). No cross-reactivity was seen between the immobilized antibodies. Although two hormones are addressed in this report, MI using PC TEM and isotopic/non-isotopic tracers has the potential for highly automated multiplexed analysis.     

Hyperbaric oxygen therapy improves the effect of keloid surgery and radiotherapy by reducing the recurrence rate

Objective

Keloids are exuberant cutaneous scars that form due to abnormal growth of fibrous tissue following an injury. The primary aim of this study was to assess the efficacy and mechanism of hyperbaric oxygen therapy (HBOT) to reduce the keloid recurrence rate after surgical excision and radiotherapy.

Methods

(1) A total of 240 patients were randomly divided into two groups. Patients in the HBOT group (O group) received HBOT after surgical excision and radiotherapy. Patients in the other group were treated with only surgical excision and radiotherapy (K group). (2) Scar tissue from recurrent patients was collected after a second operation. Hematoxylin and eosin (H&E) staining was used to observe keloid morphology. Certain inflammatory factors (interleukin-6 (IL-6), hypoxia-inducible factor-1α (HIF-1α), tumor necrosis factor-α (TNF-α), nuclear factor κB (NF-κB), and vascular endothelial growth factor (VEGF)) were measured using immunohistochemical staining.

Results

(1) The recurrence rate of the O group (5.97%) was significantly lower than that of the K group (14.15%), P<0.05. Moreover, patients in the O group reported greater satisfaction than those in the K group (P<0.05). (2) Compared with the recurrent scar tissue of the K group, the expression levels of the inflammatory factors were lower in the recurrent scar tissue of the O group.

Conclusions

Adjunctive HBOT effectively reduces the keloid recurrence rate after surgical excision and radiotherapy by improving the oxygen level of the tissue and alleviating the inflammatory process.

     

Application of the Levenshtein Distance Metric for the Construction of Longitudinal Data Files

The analysis of longitudinal data in education is becoming more prevalent given the nature of testing systems constructed for No Child Left Behind Act (NCLB). However, constructing the longitudinal data files remains a significant challenge. Students move into new schools, but in many cases the unique identifiers (ID) that should remain constant for each student change. As a result, different students frequently share the same ID, and merging records for an ID that is erroneously assigned to different students clearly becomes problematic. In small data sets, quality assurance of the merge can proceed through human reviews of the data to ensure all merged records are properly joined. However, in data sets with hundreds of thousands of cases, quality assurance via human review is impossible. While the record linkage literature has many applications in other disciplines, the educational measurement literature lacks details of formal protocols that can be used for quality assurance procedures for longitudinal data files. This article presents an empirical quality assurance procedure that may be used to verify the integrity of the merges performed for longitudinal analysis. We also discuss possible extensions that would permit merges to occur even when unique identifiers are not available.