New morphometrical data of Lake Ladoga

Depth distribution in Lake Ladoga reflects the geological structure of the lake basin. Bottom relief determines the distribution of bottom sediments, benthic organisms, horizontal temperature distribution and other characteristics and effects general current pattern in different seasons of the year. In this paper new values of mean depth, volume and area of Lake Ladoga and its parts are presented, and also the length and fractal dimension of the shoreline are determined. Based on the analysis of relative volume curves, the integrity of morphogenesis of the northern and the southern parts of Lake Ladoga despite their quite different bottom topography was established.     

Hemodynamic monitoring by intracardiac impedance measured by cardiac resynchronization defibrillators: Evaluation in a controlled clinical setting (BIO.Detect HF II study)

BackgroundIn patients with cardiac resynchronization therapy defibrillators (CRT-Ds), intracardiac impedance measured by dedicated CRT-D software may be used to monitor hemodynamic changes. We investigated the relationship of hemodynamic parameters assessed by intracardiac impedance and by echocardiography in a controlled clinical setting.MethodsThe study enrolled 68 patients (mean age, 66 ± 9 years; 74% males) at 12 investigational sites. The patients had an indication for CRT-D implantation, New York Heart Association class II/III symptoms, left ventricular ejection fraction 15%–35%, and a QRS duration ≥150 ms. Two months after a CRT-D implantation, hemodynamic changes were provoked by overdrive pacing. Intracardiac impedance was recorded at rest and at four pacing rates ranging from 10 to 40 beats/min above the resting rate. In parallel, echocardiography measurements were performed. We hypothesized that a mean intra-individual correlation coefficient (r_mean) between stroke impedance (difference between end-systolic and end-diastolic intracardiac impedance) measured by CRT-D and the aortic velocity time integral (i.e., stroke volume) determined by echocardiography would be significantly larger than 0.65.ResultsThe hypothesis was evaluated in 40 patients with complete data sets. The r_mean was 0.797, with a lower confidence interval bound of 0.709. The study hypothesis was met (p = 0.007). A stepwise reduction of stroke impedance and stroke volume was observed with increasing heart rate.ConclusionsIntracardiac impedance measured by implanted CRT-Ds correlated well with the aortic velocity time integral (stroke volume) determined by echocardiography. The impedance measurements bear potential and are readily available technically, not requiring implantation of additional material beyond standard CRT-D system.     

Role of blood oxygenation saturation in ovarian cancer diagnosis using multi-spectral photoacoustic tomography

In photoacoustic tomography (PAT), a tunable laser typically illuminates the tissue at multiple wavelengths, and the received photoacoustic waves are used to form functional images of relative total haemoglobin (rHbT) and blood oxygenation saturation (%sO₂). Due to measurement errors, the estimation of these parameters can be challenging, especially in clinical studies. In this study, we use a multi-pixel method to smooth the measurements before calculating rHbT and %sO₂. We first perform phantom studies using blood tubes of calibrated %sO₂ to evaluate the accuracy of our %sO₂ estimation. We conclude by presenting diagnostic results from PAT of 33 patients with 51 ovarian masses imaged by our co-registered PAT and ultrasound system. The ovarian masses were divided into malignant and benign/normal groups. Functional maps of rHbT and %sO₂ and their histograms as well as spectral features were calculated using the PAT data from all ovaries in these two groups. Support vector machine models were trained on different combinations of the significant features. The area under ROC (AUC) of 0.93 (0.95%CI: 0.90-0.96) on the testing data set was achieved by combining mean %sO₂, a spectral feature, and the score of the study radiologist.     

High-security photoacoustic identity recognition by capturing hierarchical vascular structure of finger

Currently, most biometric methods mainly use single features, making them easily forged and cracked. In this study, a novel triple-layers biometric recognition method, based on photoacoustic microscopy, is proposed to improve the security of biometric identity recognition. Using the photoacoustic (PA) dermoscope, three-dimensional absorption-structure information of the fingers was obtained. Then, by combining U-Net, Gabor filtering, wavelet analysis and morphological transform, a lightweight algorithm called photoacoustic depth feature recognition algorithm (PADFR) was developed to automatically realize stratification (the fingerprint, blood vessel fingerprint and venous vascular), extracting feature points and identity recognition. The experimental results show that PADFR can automatically recognize the PA hierarchical features with an average accuracy equal to 92.99%. The proposed method is expected to be widely used in biometric identification system due to its high security.     

Predicting protein oxidation sites with feature selection and analysis approach

Protein oxidation is a ubiquitous post-translational modification that plays important roles in various physiological and pathological processes. Owing to the fact that protein oxidation can also take place as an experimental artifact or caused by oxygen in the air during the process of sample collection and analysis, and that it is both time-consuming and expensive to determine the protein oxidation sites purely by biochemical experiments, it would be of great benefit to develop in silico methods for rapidly and effectively identifying protein oxidation sites. In this study, we developed a computational method to address this problem. Our method was based on the nearest neighbor algorithm in which, however, the maximum relevance minimum redundancy and incremental feature selection approaches were incorporated. From the initial 735 features, 16 features were selected as the optimal feature set. Of such 16 optimized features, 10 features were associated with the position-specific scoring matrix conservation scores, three with the amino acid factors, one with the propensity of conservation of residues on protein surface, one with the side chain count of carbon atom deviation from mean, and one with the solvent accessibility. It was observed that our prediction model achieved an overall success rate of 75.82%, indicating that it is quite encouraging and promising for practical applications. Also, the 16 optimal features obtained through this study may provide useful clues and insights for in-depth understanding the action mechanism of protein oxidation.     

Phylogeny,extinction and conservation: embracing uncertainties in a time of urgency

Evolutionary studies have played a fundamental role in our understanding of life, but until recently, they had only a relatively modest involvement in addressing conservation issues. The main goal of the present discussion meeting issue is to offer a platform to present the available methods allowing the integration of phylogenetic and extinction risk data in conservation planning. Here, we identify the main knowledge gaps in biodiversity science, which include incomplete sampling, reconstruction biases in phylogenetic analyses, partly known species distribution ranges, and the difficulty in producing conservation assessments for all known species, not to mention that much of the effective biological diversity remains to be discovered. Given the impact that human activities have on biodiversity and the urgency with which we need to address these issues, imperfect assumptions need to be sanctioned and surrogates used in the race to salvage as much as possible of our natural and evolutionary heritage. We discuss some aspects of the uncertainties found in biodiversity science, such as the ideal surrogates for biodiversity, the gaps in our knowledge and the numerous available phylogenetic diversity-based methods. We also introduce a series of cases studies that demonstrate how evolutionary biology can effectively contribute to biodiversity conservation science.