Water-clear cell adenoma of the parathyroid gland is a rare neoplasm that consists of cells with abundant clear-pink cytoplasm. There have only been 19 cases reported in the English literature. Here we report a case of water-clear cell adenoma of the mediastinal parathyroid gland. A 70-year-old male patient presented to the hospital with back pain and a mediastinal mass 6 cm in size was detected. After excision and microscopic evaluation, uniform, large clear cells with fine cytoplasmic vacuolization, without nuclear atypia, and arranged in solid and acinar patterns were revealed. The cells formed nests that were separated by fine fibrovascular septae and stained positively with anti-parathyroid hormone. To the best of our knowledge, this has not been previously reported in this location. In the differential diagnosis of clear cell lesions of the mediastinum, water-clear cell parathyroid adenoma should be considered.
A 21-year-old male having a history of 4 years of working at a denim factory as a sandblaster was diagnosed with pulmonary silicosis and he was also an active smoker. Productive cough, dyspnea on effort, night sweats, and weight loss in a short period of time were his complaints. Chronic occupational exposure to tiny particles of silicon dioxide can stimulate parenchymal inflammation, collagen synthesis and, ultimately pulmonary fibrosis called silicosis. A typical history of exposure and chest X-ray is usually enough for diagnosis. No effective treatment exists except supportive care. Although chest X-ray of the patient revealed bilateral disseminated micronodular densities, a peripherally diffuse prominent FDG [(F-18)-2-fluoro-2-deoxy-D-glucose] uptake in both lungs and faint FDG uptake in mediastinal lymph nodes demonstrating active inflammation regions were noted on PET (Positron Emission Tomography) scan. This case was presented to show the active disease discriminated by FDG PET from chronic changes detected by radiological studies. FDG PET can provide additional information to CT regarding the diagnosis of acute silicosis and the rare accelerated silicosis.
Using a machine-learning model, we examined drivers of antibiotic prescribing for antibiotic-inappropriate acute respiratory illnesses in a large US claims data set. Antibiotics were prescribed in 11% of the 42 million visits in our sample. The model identified outpatient setting type, patient age mix, and state as top drivers of prescribing.
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