A Use of Tritium-Labeled Peat Fulvic Acids and Polyphenolic Derivatives for Designing Pharmacokinetic Experiments on Mice

Natural products (e.g., polyphenols) have been used as biologically active compounds for centuries. Still, the mechanisms of biological activity of these multicomponent systems are poorly understood due to a lack of appropriate experimental techniques. The method of tritium thermal bombardment allows for non-selective labeling and tracking of all components of complex natural systems. In this study, we applied it to label two well-characterized polyphenolic compounds, peat fulvic acid (FA-Vi18) and oxidized lignin derivative (BP-Cx-1), of predominantly hydrophilic and hydrophobic character, respectively. The identity of the labeled samples was confirmed using size exclusion chromatography. Using ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT ICR MS), key differences in the molecular composition of BP-Cx-1 and FA-Vi18 were revealed. The labeled samples ([3H]-FA-Vi18 (10 mg/kg) and [3H]-BP-Cx-1 (100 mg/kg)) were administered to female BALB/c mice intravenously (i.v.) and orally. The label distribution was assessed in blood, liver, kidneys, brain, spleen, thymus, ovaries, and heart using liquid scintillation counting. Tritium label was found in all organs studied at different concentrations. For the fulvic acid sample, the largest accumulation was observed in the kidney (Cmax 28.5 mg/kg and 5.6 mg/kg, respectively) for both routes. The organs of preferential accumulation of the lignin derivative were the liver (Cmax accounted for 396.7 and 16.13 mg/kg for i.v. and p.o. routes, respectively) and kidney (Cmax accounted for 343.3 and 17.73 mg/kg for i.v. and p.o. routes, respectively). Our results demonstrate that using the tritium labeling technique enabled successful pharmacokinetic studies on polyphenolic drugs with very different molecular compositions. It proved to be efficient for tissue distribution studies. It was also shown that the dosage of the polyphenolic drug might be lower than 10 mg/kg due to the sensitivity of the 3H detection technique.

Age Label Distribution Learning Based on Unsupervised Comparisons of Faces

Although label distribution learning has made significant progress in the field of face age estimation, unsupervised learning has not been widely adopted and is still an important and challenging task. In this work, we propose an unsupervised contrastive label distribution learning method (UCLD) for facial age estimation. This method is helpful to extract semantic and meaningful information of raw faces with preserving high-order correlation between adjacent ages. Similar to the processing method of wireless sensor network, we designed the ConAge network with the contrast learning method. As a result, our model maximizes the similarity of positive samples by data enhancement and simultaneously pushes the clusters of negative samples apart. Compared to state-of-the-art methods, we achieve compelling results on the widely used benchmark, i.e., MORPH.

Multireader Evaluation of Radiologist Performance for COVID-19 Detection on Emergency Department Chest Radiographs

Background Chest radiographs (CXR) are frequently used as a screening tool for patients with suspected COVID-19 infection pending reverse transcriptase polymerase chain reaction (RT-PCR) results, despite recommendations against this. We evaluated radiologist performance for COVID 19 diagnosis on CXR at the time of patient presentation in the Emergency Department (ED). Materials and Methods We extracted RT PCR results, clinical history, and CXRs of all patients from a single institution between March and June 2020. 984 RT PCR positive and 1043 RT-PCR negative radiographs were reviewed by 10 emergency radiologists from 4 academic centers. 100 cases were read by all radiologists and 1927 cases by 2 radiologists. Each radiologist chose the single best label per case: Normal, COVID 19, Other Infectious, Other Noninfectious, Non diagnostic, and Endotracheal Tube. Cases labeled with endotracheal tube or non-diagnostic were excluded. Remaining cases were analyzed for label distribution, clinical history, and inter-reader agreement. Results 1727 radiographs (732 RT PCR positive, 995 RT PCR negative) were included from 1,594 patients (51.2% male, 48.8% female, age 59 +/- 19 years). For 89 cases read by all readers, there was poor agreement for RT PCR positive (Fleiss Score 0.36) and negative (Fleiss Score 0.46) exams. Agreement between two readers on 1,638 cases was 54.2% (373/688) for RT-PCR positive cases and 71.4% (679/950) for negative cases. Agreement was highest for RT PCR negative cases labeled as Normal (50.4%, n= 479). Reader performance did not improve with clinical history or time between CXR and RT-PCR result. Conclusion At the time of presentation to the emergency department, emergency radiologist performance is non-specific for diagnosing COVID 19.