Aldosterone- and cortisol-coproducing adrenal adenoma (A/CPA) cases have been observed in patients with primary aldosteronism (PA). This study investigated the incidence, clinical characteristics, and molecular biological features of patients with A/CPAs. We retrospectively identified 22 A/CPA patients from 555 PA patients who visited the Chinese People's Liberation Army General Hospital between 2004 and 2015. Analysis of clinical parameters revealed that patients with A/CPAs had larger tumors than those with pure APAs (P < 0.05). Moreover, they had higher proportions of cardiovascular complications, glucose intolerance/diabetes, and osteopenia/osteoporosis compared to the pure APA patients (P < 0.001). In the molecular biological findings, quantitative real-time PCR analysis revealed similar CYP11B1 and CYP17A1 mRNA expressions in resected A/CPA specimens and in pure APA specimens. Western blot and immunochemical analyses showed CYP11B1, CYP11B2, and CYP17A1 expressions in both A/CPAs and pure APAs. Seventeen cases with KCNJ5 mutations were detected among the 22 A/CPA DNA samples, but no PRKACA or other causative mutations were observed. Each patient improved following adrenalectomy. In conclusion, A/CPAs were not rare among PA patients. These patients associated with high incidences of cardiovascular events and metabolic disorders. Screening for excess cortisol secretion is necessary for PA patients.

Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic, which has reached 28 million cases worldwide in 1 year. The serological detection of antibodies against the virus will play a pivotal role in complementing molecular tests to improve diagnostic accuracy, contact tracing, vaccine efficacy testing, and seroprevalence surveillance. Here, we aimed first to evaluate a lateral flow assay's ability to identify specific IgM and IgG antibodies against SARS-CoV-2 and second, to report the seroprevalence estimates of these antibodies among health care workers and healthy volunteer blood donors in Panama. We recruited study participants between April 30th and July 7th, 2020. For the test validation and performance evaluation, we analyzed serum samples from participants with clinical symptoms and confirmed positive RT-PCR for SARS-CoV-2, and a set of pre-pandemic serum samples. We used two by two table analysis to determine the test positive and negative percentage agreement as well as the Kappa agreement value with a 95% confidence interval. Then, we used the lateral flow assay to determine seroprevalence among serum samples from COVID-19 patients, potentially exposed health care workers, and healthy volunteer donors. Our results show this assay reached a positive percent agreement of 97.2% (95% CI 84.2–100.0%) for detecting both IgM and IgG. The assay showed a Kappa of 0.898 (95%CI 0.811–0.985) and 0.918 (95% CI 0.839–0.997) for IgM and IgG, respectively. The evaluation of serum samples from hospitalized COVID-19 patients indicates a correlation between test sensitivity and the number of days since symptom onset; the highest positive percent agreement [87% (95% CI 67.0–96.3%)] was observed at ≥15 days post-symptom onset (PSO). We found an overall antibody seroprevalence of 11.6% (95% CI 8.5–15.8%) among both health care workers and healthy blood donors. Our findings suggest this lateral flow assay could contribute significantly to implementing seroprevalence testing in locations with active community transmission of SARS-CoV-2.

BackgroundType 2 diabetes mellitus (T2DM), an epidemic disease around world, has recently been identified as a risk factor for osteoporosis-associated fracture. However, there is no consensus on the best method of assessing fracture risk in patients with T2DM. The aim of this study was to evaluate the usefulness of the Osteoporosis Self-Assessment Tool for Asians (OSTA) and the Singh Index (SI) in hip fracture risk assessment in patients with T2DM.MethodsWe enrolled 261 postmenopausal women with T2DM: 87 had hip fracture resulting from low-energy trauma and 174 age-matched controls had no fracture (two controls per fracture case). Bone mineral density (BMD) was measured with dual-energy X-ray absorptiometry in the lumbar spine and hip region. The SI was obtained from standard antero-posterior radiographs of the pelvis. The OSTA was calculated with a formula based on weight and age. Data were analyzed with descriptive statistics and tests of difference. Receiver operating characteristic analysis was used to determine optimum cutoff values, sensitivity, and specificity of screening methods. Discriminative abilities of different screening tools were compared with the area under the curve (AUC).ResultsThere were significant differences in BMD at all sites (lumbar spine, femoral neck, trochanter, and total hip) and in SI between the fracture and non-fracture groups (P < 0.05). There was no significant difference in OSTA between the groups (P > 0.05). The area under the curve was 0.747 (95% CI: 0.680–0.813) for lumbar spine BMD, 0.699 (95% CI: 0.633–0.764) for total hip BMD, 0.659 (95% CI: 0.589–0.729) for femoral neck BMD, 0.631 (95% CI: 0.557–0.704) for trochanter BMD, 0.534 (95% CI: 0.459–0.610) for OSTA, 0.636 (95% CI: 0.564–0.709) for SI, and 0.795 (95% CI: 0.734–0.857) for OSTA plus SI. The AUC for combined OSTA plus SI was significantly superior to other parameters besides BMD of the lumbar spine.ConclusionsThe combination of OSTA plus SI could be a clinical alternative tool for screening of hip fracture risk in large diabetic populations. These tests are inexpensive and simple to perform and could be especially useful in areas where BMD measurement is not accessible.

Background. Disorders of autophagic processes have been reported to affect the survival outcome of clear cell renal cell carcinoma (ccRCC) patients. The purpose of our study was to identify and validate the candidate prognostic long noncoding RNA signature of autophagy. Methods. Transcriptome profiles were obtained from The Cancer Genome Atlas. The autophagy gene list was obtained from the Human Autophagy Database. Based on coexpression analysis, we obtained a list of autophagy-related lncRNAs (ARlncRNAs). GO enrichment analysis and KEGG pathway analysis were conducted to explore the functional annotation of these ARlncRNAs. Univariate and multivariate Cox regression analyses were conducted to elucidate the correlation between overall survival and the expression level of each ARlncRNAs. We then established a prognostic signature that was a linear combination of the regression coefficients from the multivariate Cox regression model ( β ) multiplied by the expression levels of the respective ARlncRNAs in the training cohort. The predictive performance was tested in the validation cohort. Additionally, the independence of the risk signature was assessed, and the relationship between the risk signature and conventional clinicopathological features was explored. Results. Seven autophagy-related lncRNAs with prognostic value (SNHG3, SNHG17, MELTF-AS1, HOTAIRM1, EPB41L4A-DT, AP003352.1, and AC145423.2) were identified and integrated into a risk signature, dividing patients into low-risk and high-risk groups. The risk signature was independent of conventional clinical characteristics as a prognostic indicator of ccRCC (HR, 1.074, 95% confidence interval: 1.036-1.113, p < 0.001 ) and was valuable in the prediction of ccRCC progression. Conclusion. Our risk signature has potential prognostic value in ccRCC, and these ARlncRNAs may play a significant role in ccRCC tumor biology.