Developing an ultra-performance liquid chromatography-tandem mass spectrometry for detecting aldosterone in human plasma.

BACKGROUND: Accurately measuring plasma aldosterone concentration is difficult but meaningful for primary aldosteronism (PA) diagnosis. METHODS: In this study, we developed an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for plasma aldosterone detection, evaluated its performance according to guidelines issued by CLSI, including detection limit, linearity, precision, and compared it with chemiluminescence immunoassay. Then, a reference range of plasma aldosterone in young people was established by using this method. RESULTS: The lower limit of quantitation (LOQ) was 10 pg/ml. The mean recovery rates of analyte added to serum were 100.07-102.05% in different concentrations. The linearity range was 20-2000 pg/ml. Inter-assay CVs were 2.20-3.97% at aldosterone concentrations of 65.66-854.75 pg/ml. The regression equation of UPLC-MS/MS (x) and chemiluminescence immunoassay (y) was y = 1.002x + 65.854 (r = 0.9456, n = 237). The reference range of plasma aldosterone detected by UPLC-MS/MS was 11.30-363.82 pg/ml in young people in South China, and there was no statistically significant difference in plasma aldosterone concentration between two genders. CONCLUSION: In conclusion, UPLC-MS/MS can rapidly and accurately detect plasma aldosterone and is appropriate for clinical application.

Matrine enhances the efficacy of adriamycin chemotherapy in osteosarcoma cells by the STAT3 pathway.

Matrine and adriamycin have been extensively considered to be effective in anticancer therapies. However, the role of matrine in the antitumor activity of adriamycin against human osteosarcoma (OS) remains elusive. The aim of this study was to investigate the effect of matrine in OS chemotherapy of adriamycin. In the study, we found that matrine promoted the inhibitory effect of adriamycin against OS cell proliferation and growth. Wound healing and transwell assays showed that the inhibitory effect of adriamycin against migration and invasion of OS cells was significantly enhanced by matrine. For the underlying mechanism investigation, we showed that adriamycin reduced the protein level of PCNA, MMP-9, phosphorylated STAT3, and survivin, which was further intensified by the application of matrine. These results show that matrine could promote the therapeutic efficacy of adriamycin against human OS.

Online prediction model for primary aldosteronism in patients with hypertension in Chinese population: A two-center retrospective study.

Background: The prevalence of primary aldosteronism (PA) varies from 5% to 20% in patients with hypertension but is largely underdiagnosed. Expanding screening for PA to all patients with hypertension to improve diagnostic efficiency is needed. A novel and portable prediction tool that can expand screening for PA is highly desirable. Methods: Clinical characteristics and laboratory data of 1,314 patients with hypertension were collected for modeling and randomly divided into a training cohort (919 of 1,314, 70%) and an internal validation cohort (395 of 1,314, 30%). Additionally, an external dataset (n = 285) was used for model validation. Machine learning algorithms were applied to develop a discriminant model. Sensitivity, specificity, and accuracy were used to evaluate the performance of the model. Results: Seven independent risk factors for predicting PA were identified, including age, sex, hypokalemia, serum sodium, serum sodium-to-potassium ratio, anion gap, and alkaline urine. The prediction model showed sufficient predictive accuracy, with area under the curve (AUC) values of 0.839 (95% CI: 0.81-0.87), 0.814 (95% CI: 0.77-0.86), and 0.839 (95% CI: 0.79-0.89) in the training set, internal validation, and external validation set, respectively. The calibration curves exhibited good agreement between the predictive risk of the model and the actual risk. An online prediction model was developed to make the model more portable to use. Conclusion: The online prediction model we constructed using conventional clinical characteristics and laboratory tests is portable and reliable. This allowed it to be widely used not only in the hospital but also in community health service centers and may help to improve the diagnostic efficiency of PA.

An online alpha-thalassemia carrier discrimination model based on random forest and red blood cell parameters for low HbA2 cases.

BACKGROUND: Since screening of α-thalassemia carriers by low HbA2 has a low positive predictive value (PPV), the PPV was as low as 40.97% in our laboratory, other more effective screening methods need to be devised. This study aimed at developing a machine learning model by using red blood cell parameters to identify α-thalassemia carriers from low HbA2 patients. METHODS: Laboratory data of 1213 patients with low HbA2 used for modeling was randomly divided into the training set (849 of 1213, 70%) and the internal validation set (364 of 1213, 30%). In addition, an external data set (n = 399) was used for model validation. Fourteen machine learning methods were applied to construct a discriminant model. Performance was evaluated with accuracy, sensitivity, specificity, etc. and compared with 7 previously published discriminant function formulae. RESULTS: The optimal model was based on random forest with 5 clinical features. The PPV of the model was more than twice the PPV of HbA2, and the model had a high negative predictive value (NPV) at the same time. Compared with seven formulae in screening of α-thalassemia carriers, the model had a better accuracy (0.915), specificity (0.967), NPV (0.901), PPV (0.942) and area under the receiver operating characteristic curve (AUC, 0.948) in the independent test set. CONCLUSION: Use of a random forest-based model enables rapid discrimination of α-thalassemia carriers from low HbA2 cases.

Prenatal Genetic Counseling in a Chinese Pregnant Woman With Rare Thalassemia: A Case Report.

Background: Prenatal genetic counseling can be difficult, especially when it is related to fetuses with a rare thalassemia. An intronic variant located far from obvious regulatory sequences in the HBB gene could be very difficult to evaluate as it may affect the mRNA processing or cause ß-thalassemia (ß-thal). In the present study, a Chinese pregnant woman with HbJ-Bangkok and a very rare change in the second intron of the HBB gene [IVS-II-806(G>C), NM_000518.4, HBB: c.316-45G>C] in combination with α+-thalassemia was reported, which can assist in prenatal genetic counseling. Case Report: A 26-year-old pregnant woman presented at the obstetric clinic for a routine pregnancy check at 12 weeks of gestation. Red blood counts and high-performance liquid chromatography (HPLC) were consistent with clinical manifestations of anemia. Multiplex gap-polymerase chain (gap-PCR) displayed rightward deletion (-α3.7/αα). Direct DNA sequencing of the δ-globin gene showed no mutation. Sanger sequencing of the ß-globin gene showed a previously undescribed condition of double heterozygosity for HbJ-Bangkok and a very rare change in the second intron of the HBB gene [IVS-II-806(G>C), NM_000518.4, HBB: c.316-45G>C] that has not been previously reported in the HbVar database. Thus, a rare combination of α+-thal and a compound heterozygosity of HbJ-Bangkok and [IVS-II-806(G>C)] with α+-thal (-α3.7/αα) was finally diagnosed. Prenatal genetic counseling was made based on the genotype and phenotype analyses. Conclusion: This study enlarges the mutation spectrum of ß-globin gene and emphasizes DNA analysis in resolving unusual patterns in Hb analysis and the importance of sharing the observed rare undefined mutations and the possible interactions with known molecular defects, which can assist in prenatal genetic counseling.

High Efficiency and Problems of Chemiluminescence Assay-Detected Aldosterone-To-Renin Ratio in Practical Primary Aldosteronism Screening.

Primary aldosteronism is a main cause of secondary hypertension which can be effectively treated. The screening test for primary aldosteronism is benefit for minimizing damage to the patient. In the previous retrospective study, we obtained the optimal cutoff value of aldosterone-to-renin ratio detected by chemiluminescence assay, a newly developing method, and prompted its high efficiency in primary aldosteronism screening in upright position. In this study, we want to evaluate its efficiency in practical work. We used this ratio to continuously screen 238 patients, and 58 patients were finally diagnosed with primary aldosteronism. We found it had 86.13% accuracy rate in the upright position compared with the final clinical diagnosis. False negative and positive rates were 13.79% and 13.89%. Diagnostic sensitivity and specificity were 86.21% and 86.11%, which are slightly different from results in our previous study. False negative rate can be improved by combining the aldosterone-to-renin ratio with aldosterone concentration. We also found impaired glucose tolerance may be a reason for high false positive rate. Besides, chemiluminescence assay may be interfered in aldosterone detection. Although it has some shortcomings, chemiluminescence assay-detected aldosterone-to-renin ratio is a highly effective index for screening primary aldosteronism in practice.

High efficiency of the aldosterone-to-renin ratio in precisely detecting primary aldosteronism.

The aldosterone-to-renin ratio (ARR) is extensively used for primary aldosteronism detection. Chemiluminescence immune assay (CLIA) is newly applied in aldosterone and renin detection for calculating the aldosterone-to-renin ratio. The performance of new ARR in aldosteronism detection is poorly evaluated. We aim to estimate the diagnostic value of this new aldosterone-to-renin ratio by highly standardized and clinically based protocol. Four hundred and forty-two patients were enrolled in our retrospective study. They went to the first affiliated hospital of Sun Yat-sen University with difficult-to-control hypertension. Primary aldosteronism diagnosis was based on clinical criteria, including a saline infusion test and other necessary inspections. ARR was calculated from plasma aldosterone and renin measured by CLIA. The cutoff value was determined and the diagnostic value was evaluated. The cutoff value of ARR for primary aldosteronism diagnosis was 28.3, with a sensitivity of 87.6%, specificity of 100%, negative-predictive value of 96.4%, and positive-predictive value of 100%. Then, we found that Age was weakly correlated with ARR. The cutoff values of ARR for primary aldosteronism diagnosis in 26-45-, 46-65-, and 66-85-year-old patients were, respectively, 29.45, 27.95, and 28.4, with sensitivities of 87.5%, 87.7%, and 87.5%, specificities of 100% for all, negative-predictive values of 97.7%, 94.3%, and 96.3%, and positive-predictive values of 100% for all. ARR generated by CLIA is a good diagnostic test for primary aldosteronism without making a false-positive diagnosis. Although ARR is correlated with age, ARR cutoff values for different ages are not more efficient than that for total sample in primary aldosteronism diagnosis.

High serum uric acid concentration predicts poor survival in patients with breast cancer.

BACKGROUND: Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. METHODS: A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. RESULTS: Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). CONCLUSIONS: High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients.