Unawareness of Primary Aldosteronism as a Common Cause of Hypokalemia - Insights from the IPAHK+ Trial (Incidence of Primary Aldosteronism in Patients with Hypokalemia).

Hypokalemia plays an important role in the diagnosis and management of primary aldosteronism (PA). While the hypokalemic variant of the disease accounts for about one third of all cases, little is known about the incidence of PA in hypokalemic populations. The IPAHK+ study is an epidemiological, cross-sectional trial to provide evidence on the incidence of PA in hypokalemic patients from a university hospital outpatient population. Recruitment of outpatients with hypokalemia≤3 mmol/l is carried out on a continuous referral-basis through an automated data delivery system. Up to an interim data closure, 66 patients underwent the study protocol. The mean age of the participants was 52.9±1.5 years with an equal sex ratio of 1:1 women to men, a mean potassium value of 2.78±0.31 mmol/l [1.8;3.0] and a prevalence of arterial hypertension of 72.7%. PA was diagnosed in 46.6% of all participants, all of whom had a history of hypertension. Incidence of PA increased continuously with decreasing potassium levels with proportions of 26.7%, 50% and 57.1% in the subgroups of 3.0 mmol/l (n=15), 2.8-2.9 mmol/l (n=22) and≤2.7 mmol/l (n=21), respectively. Prior to testing, 59.1% of all patients presented at least with one plausible other cause of hypokalemia. The incidence of PA in the investigated outpatient population was more than 4 out of 10 and inversely correlated with baseline potassium levels. Moderate or severe hypokalemia, regardless of its cause, should therefore prompt evaluation for PA in hypertensive individuals. Normotensive hypokalemic PA was not observed in this cohort.

Genetic Analysis and Status of Brown Bear Sub-Populations in Three National Parks of Greece Functioning as Strongholds for the Species' Conservation.

In order to optimize the appropriate conservation actions for the brown bear (Ursus arctos L.) population in Greece, we estimated the census (Nc) and effective (Ne) population size as well as the genetic status of brown bear sub-populations in three National Parks (NP): Prespa (MBPNP), Pindos (PINDNP), and Rhodopi (RMNP). The Prespa and Pindos sub-populations are located in western Greece and the Rhodopi population is located in eastern Greece. We extracted DNA from 472 hair samples and amplified through PCR 10 microsatellite loci. In total, 257 of 472 samples (54.5%) were genotyped for 6-10 microsatellite loci. Genetic analysis revealed that the Ne was 35, 118, and 61 individuals in MBPNP, PINDNP, and RMNP, respectively, while high levels of inbreeding were found in Prespa and Rhodopi but not in Pindos. Moreover, analysis of genetic structure showed that the Pindos population is genetically distinct, whereas Prespa and Rhodopi show mutual overlaps. Finally, we found a notable gene flow from Prespa to Rhodopi (10.19%) and from Rhodopi to Prespa (14.96%). Therefore, targeted actions for the conservation of the bears that live in the abovementioned areas must be undertaken, in order to ensure the species' viability and to preserve the corridors that allow connectivity between the bear sub-populations in Greece.

Incidence of Primary Aldosteronism in Patients with Hypokalemia (IPAHK+): Study Design and Baseline Characteristics.

Hypokalemia plays a central role for case finding, course, treatment decision, and prognosis of patients with primary aldosteronism. However, to date there is a lack of high-level evidence about the incidence of primary aldosteronism in hypokalemic patients. The IPAHK+study is an epidemiological, cross-sectional, monocentric study to provide evidence on the incidence of PA in a hypokalemic population. The aim of the current analysis was to describe the baseline characteristics of the first 100 patients eligible for study inclusion. The recruitment of patients with hypokalemia (≤3 mmol/l) is carried out continuously on a referral-basis by the central laboratory of the University Hospital Zurich through an automated suitability testing and data delivery system. The careful evaluation of the first 100 reported patients was based on the available reporting system. Out of 28 140 screened patients, 222 (0.79%) were identified with a serum potassium value of≤3 mmol/l (mean 2.89±0.02 mmol/l). Mean potassium levels were slightly lower in non-hypertensive subjects compared to hypertensive subjects (mean difference 0.07 mmol/l, p=0.033), while no significant difference was found between the sexes and patients with and without the diagnosis of primary aldosteronism, atrial fibrillation, or the use of diuretics. The incidence of PA was 4% in the total population studied and 7.5% in the subgroup of hypertensive patients. In conclusion, the continuous enrollment of patients from the IPHAK+hypokalemia registry into the IPAHK+trial will provide evidence about the actual incidence of primary aldosteronism in a hypokalemic outpatient population.

Hidden neural networks for transmembrane protein topology prediction.

Hidden Markov Models (HMMs) are amongst the most successful methods for predicting protein features in biological sequence analysis. However, there are biological problems where the Markovian assumption is not sufficient since the sequence context can provide useful information for prediction purposes. Several extensions of HMMs have appeared in the literature in order to overcome their limitations. We apply here a hybrid method that combines HMMs and Neural Networks (NNs), termed Hidden Neural Networks (HNNs), for biological sequence analysis in a straightforward manner. In this framework, the traditional HMM probability parameters are replaced by NN outputs. As a case study, we focus on the topology prediction of for alpha-helical and beta-barrel membrane proteins. The HNNs show performance gains compared to standard HMMs and the respective predictors outperform the top-scoring methods in the field. The implementation of HNNs can be found in the package JUCHMME, downloadable from http://www.compgen.org/tools/juchmme, https://github.com/pbagos/juchmme. The updated PRED-TMBB2 and HMM-TM prediction servers can be accessed at www.compgen.org.