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The distribution of tumor-infiltrating lymphocytes (TILs) within the tumor microenvironment provides strong prognostic value, which is increasingly important with the arrival of new immunotherapy modalities. Both visual and image analysis-based assays are developed to assess the immune contexture of the tumors. We propose an automated method based on grid subsampling of microscopy image analysis data to extract the tumor-stroma interface zone (IZ) of controlled width. The IZ is a ranking of tissue areas by their distance to the tumor edge, which is determined by a set of explicit rules. TIL density profiles across the IZ are used to compute a set of novel immunogradient indicators that reflect TIL gradient towards the tumor. We applied this method on CD8 immunohistochemistry images of surgically excised hormone receptor-positive breast and colorectal cancers to predict overall patient survival. In both cohorts, the immunogradient indicators enabled strong and independent prognostic stratification, outperforming clinical and pathologic variables. Patients with breast cancer with low immunogradient levels had a prominent decrease in survival probability 5 years after surgery. Our study provides proof of concept that data-driven, automated, operator-independent IZ sampling enables spatial immune response measurement in the tumor-host interaction frontline for prediction of disease outcomes.

Uncontrolled proliferation is a hallmark of cancer and can be assessed by labelling breast tissue using immunohistochemistry for Ki67, a protein associated with cell proliferation. Accurate measurement of Ki67-positive tumour nuclei is of critical importance, but requires annotation of the tumour regions by a pathologist. This manual annotation process is highly subjective, time-consuming and subject to inter- and intra-annotator experience. To address this challenge, we have developed Proliferation Tumour Marker Network (PTM-NET), a deep learning model that objectively annotates the tumour regions in Ki67-labelled breast cancer digital pathology images using a convolution neural network. Our custom designed deep learning model was trained on 45 immunohistochemical Ki67-labelled whole slide images to classify tumour and non-tumour regions and was validated on 45 whole slide images from two different sources that were stained using different protocols. Our results show a Dice coefficient of 0.74, positive predictive value of 70% and negative predictive value of 88.3% against the manual ground truth annotation for the combined dataset. There were minimal differences between the images from different sources and the model was further tested in oestrogen receptor and progesterone receptor-labelled images. Finally, using an extension of the model, we could identify possible hotspot regions of high proliferation within the tumour. In the future, this approach could be useful in identifying tumour regions in biopsy samples and tissue microarray images.

Introduction: Many theories have been proposed to explain pathogenesis of COPD; however, remains unclear why the majority of smokers (~80%) do not develop COPD, or only develop a mild disease. To explore if COPD has an autoimmune component, the role of T regulatory lymphocytes (Tregs) in the lung tissue of COPD patients is of crucial importance. Material and methods: Bronchial tissue biopsy samples were prospectively collected from 64 patients (39 COPD and 25 controls—15 smokers and 10 non-smokers). The patients with COPD were subdivided into mild/moderate (GOLD stage I−II) and severe/very severe (GOLD stage III−IV) groups. Digital image analysis was performed to estimate densities of CD4+ CD25+ cell infiltrates in double immunohistochemistry slides of the biopsy samples. Blood samples were collected from 42 patients (23 COPD and 19 controls) and tested for CD3+ CD4+ CD25+ bright lymphocytes by flow cytometry. Results: The number of intraepithelial CD4+ CD25+ lymphocytes mm-2 epithelium was significantly lower in the severe/very severe COPD (GOLD III–IV) group as well as in the control non-smokers (NS) group (p < 0,0001). Likewise, the absolute number of Treg (CD3+ CD4+ CD25+ bright) cells in the peripheral blood samples was significantly different between the four groups (p = 0.032). The lowest quantity of Treg cells was detected in the severe/very severe COPD and healthy non-smokers groups. Conclusions: Our findings suggest that severe COPD is associated with lower levels of Tregs in the blood and bronchial mucosa, while higher Tregs levels in the smokers without COPD indicate potential protective effect of Tregs against developing COPD.

The Mie theory was the very first description of light interaction with a particle and it was extended for describing the interaction with highly focused beams. The polarization properties of highly focused electromagnetic beams strongly influence the size and shape of the focal spot of the beams [1]. The optical response of the nanoparticle is strongly dependent both on the particle location in the focal plane and on the polarization state of the beam, and it differs notably from that of the classical Mie theory [2]. An accurate analytical description of highly focused linearly, radially and azimuthally polarized light beams can be obtained via an extension of the so-called complex source beam (CSB) model [3]. Furthermore, the CSB model can be also employed for an accurate and unified vectorial description of highly focused vortex beams of various polarizations that are rigorous solutions of Maxwell's equations [4].

Supplemental material, Supplementary_data for Osteochondral Repair and Electromechanical Evaluation of Custom 3D Scaffold Microstructured by Direct Laser Writing Lithography by Justinas Maciulaitis, Milda Miskiniene, Sima Rekštytė, Maksim Bratchikov, Adas Darinskas, Agne Simbelyte, Gintaras Daunoras, Aida Laurinaviciene, Arvydas Laurinavicius, Rimtautas Gudas, Mangirdas Malinauskas and Romaldas Maciulaitis in CARTILAGE

Although treatment of colorectal cancer with 5-florouracil and oxaliplatin is widely used, it is frequently followed by a relapse. Therefore, there is an urgent need for profound understanding of chemotherapy resistance mechanisms as well as the profiling of predictive markers for individualized treatment. In this study, we identified the changes in 14 miRNAs in 5-fluouracil and 40 miRNAs in oxaliplatin-resistant cell lines by miRNA sequencing. The decrease in miR-224-5p expression in the 5-fluorouracil-resistant cells correlated with drug insensitivity due to its overexpression-induced drug-dependent apoptosis. On the other hand, the miR-23b/27b/24-1 cluster was overexpressed in oxaliplatin-resistant cells. The knockout of miR-23b led to the partial restoration of oxaliplatin susceptibility, showing the essential role of miR-23b in the development of drug resistance by this cluster. Proteomic analysis identified target genes of miR-23b and showed that endothelial–mesenchymal transition (EMT) was implicated in oxaliplatin insensibility. Data revealed that EMT markers, such as vimentin and SNAI2, were expressed moderately higher in the oxaliplatin-resistant cells and their expression increased further in the less drug-resistant cells, which had miR-23b knockout. This establishes that the balance of EMT contributes to the drug resistance, showing the importance of the miR-23b-mediated fine-tuning of EMT in oxaliplatin-resistant cancer cells.

BACKGROUND AND AIMS Immunohistochemistry (IHC) is an essential component of biomarker research in cancer. Automated biomarker quantification is hampered by the failure of computational algorithms to discriminate 'negative' tumour cells from 'negative' stromal cells. We sought to develop an algorithm for segmentation of tumour epithelium in colorectal cancer (CRC), irrespective of the biomarker expression in the cells. METHODS AND RESULTS We developed tumour parcellation and quantification (TuPaQ) to segment tumour epithelium and parcellate sections into 'epithelium' and 'non-epithelium'. TuPaQ comprises image pre-processing, extraction of regions of interest (ROIs) and quantification of tumour epithelium (total area occupied by epithelium and number of nuclei in the occupied area). A total of 286 TMA cores from CRC were manually annotated and analysed using the commercial halo software to provide ground truth. The performance of TuPaQ was evaluated against the ground truth using a variety of metrics. The image size of each core was 7000 × 7000 pixels and each core was analysed in a matter of seconds. Pixel × pixel analysis showed a sensitivity of 84% and specificity of 95% in detecting epithelium. The mean tumour area obtained by TuPaQ was very close to the area quantified after manual annotation (r = 0.956, P < 0.001). Moreover, quantification of tumour nuclei by TuPaQ correlated very strongly with that of halo (r = 0.891, P < 0.001). CONCLUSION TuPaQ is a very rapid and accurate method of separating the epithelial and stromal compartments of colorectal tumours. This will allow more accurate and objective analysis of immunohistochemistry.

The complex direct contact condensation phenomenon is investigated in horizontal flow channels both experimentally and numerically with special emphasis on its implications on safety assessment studies. Under certain conditions direct contact condensation can act as the driving force for the water hammer phenomenon with potentially local devastating results, thus posing a threat to the integrity of the affected NPP components. New experimental results of in-depth analysis of the direct contact condensation phenomena obtained in Kaunas at the Lithuanian Energy Institute will be presented. The German system code ATHLET employing for the calculation of the heat transfer coefficient a mechanistic model accounting for two different eddy length scales, combined with the interfacial area transport equation will be assessed against condensation induced water hammer experimental data from the integral thermal-hydraulic experimental facility PMK-2, located at the KFKI Atomic Energy Research Institute in Budapest Hungary.

We describe two types of enzyme-containing filters. The first type consists of a semi-permeable membrane with immobilized enzyme covered with inert membrane, permeable for the substrate and badly permeable for the product. The second filter type is a semi-permeable enzyme containing a membrane where substrate is pumping through the membrane. The first type is described by a system of two reaction–diffusion equations. The diffusion is described by Fick’s law, and the reaction is described by the Michaelis–Menten term. We obtain mathematical expression of the effectiveness of the bio-catalytic active filters to generate flux of the product and parameter describing permeability of the bio-catalytic filter for substrate. An inert membrane leads to the increase of the product flow through the bio-catalytic membrane about three times and possesses the optimal thickness of the later. Decreasing permeability of inert membrane for product decreases the product flow back, and increases product flow forward about six times. The second-type filter is described by a system of two reaction–diffusion–convection equations. The included convection term is a principal innovation of the research. The convection term increases the transport of the substrate and restricts the flux of the product in the back direction. The convection term increases both rate of the product generation and the capacity to consume the substrate more than 12 times.

Proliferative activity, assessed by Ki67 immunohistochemistry (IHC), is an established prognostic and predictive biomarker of breast cancer (BC). However, it remains under-utilized due to lack of standardized robust measurement methodologies and significant intratumor heterogeneity of expression. A recently proposed methodology for IHC biomarker assessment in whole slide images (WSI), based on systematic subsampling of tissue information extracted by digital image analysis (DIA) into hexagonal tiling arrays, enables computation of a comprehensive set of Ki67 indicators, including intratumor variability. In this study, the tiling methodology was applied to assess Ki67 expression in WSI of 152 surgically removed Ki67-stained (on full-face sections) BC specimens and to test which, if any, Ki67 indicators can predict overall survival (OS). Visual Ki67 IHC estimates and conventional clinico-pathologic parameters were also included in the study. Analysis revealed linearly independent intrinsic factors of the Ki67 IHC variance: proliferation (level of expression), disordered texture (entropy), tumor size and Nottingham Prognostic Index, bimodality, and correlation. All visual and DIA-generated indicators of the level of Ki67 expression provided significant cutoff values as single predictors of OS. However, only bimodality indicators (Ashman's D, in particular) were independent predictors of OS in the context of hormone receptor and HER2 status. From this, we conclude that spatial heterogeneity of proliferative tumor activity, measured by DIA of Ki67 IHC expression and analyzed by the hexagonal tiling approach, can serve as an independent prognostic indicator of OS in BC patients that outperforms the prognostic power of the level of proliferative activity.

Immunohistochemistry (IHC) is widely used in contemporary pathology as a diagnostic and, increasingly, as a prognostic and predictive tool. The main value of the method today comes from a sensitive and specific detection of a protein of interest in the context of tissue architecture and cell populations. One of the major limitations of conventional IHC is related to the fact that the results are usually obtained by visual qualitative or semiquantitative evaluation. While this is sufficient for diagnostic purposes, measurement of prognostic and predictive biomarkers requires better accuracy and reproducibility. Also, objective evaluation of the spatial heterogeneity of biomarker expression as well as the development of combined/integrated biomarkers are in great demand. On the other end of the scale, the rapid development of tissue proteomics accounting for 2D spatial aspects has led to a disruptive concept of next-generation IHC, promising high multiplexing and broad dynamic range quantitative/spatial data on tissue protein expression. This ‘evolutionary gap' between conventional and next-generation IHC can be filled by comprehensive IHC based on digital technologies (empowered by quantification and spatial and multiparametric analytics) and integrated into the pathology workflow and information systems. In this paper, we share our perspectives on a comprehensive IHC road map as a multistep development process.

Background and aim: Immunoglobulin A nephropathy (IgAN) is the most frequent glomerular disease worldwide and one of the main causes of chronic kidney disease. We aimed to investigate clinicopathological correlations in IgAN patients by gender. Materials and methods: The study was based on a retrospective analysis of renal biopsy data and clinical manifestations of the disease. Consecutive 73 biopsy-proven IgAN cases of male (62%) and female (38%) patients were investigated. Renal biopsies were reviewed using the new Oxford classification assessing the MEST (mesangial hypercellularity, endocapillary hypercellularity, segmental sclerosis/adhesion, tubular atrophy/interstitial fibrosis) score. The most powerful IgAN prognostic risk factors, morphological (segmental glomerulosclerosis and tubular atrophy/interstitial fibrosis) as well as clinical (proteinuria and hypertension) were taken into account in the correlation analysis. The mean rate of renal function decline was expressed as a slope of eGFR during the follow-up (FU) dividing delta GFR with the FU years. Results: The mean age of the patients was 33.7 years (range, 16–76). Follow-up data were available for 64 patients with the mean follow-up of 4.1 years. The mean proteinuria at biopsy was 0.79 g/24 h. The mean arterial pressure (MAP) was 94.5 ± 16.7 mmHg and 7% of the patients were hypertensive. The initial mean estimated glomerular filtration rate (eGFR) was 94.9 ± 30.7 mL/min, at the end of the follow-up it was 86.2 ± 27.1 mL/min. The mean rate of renal function decline was −3.4 ± 11.9 mL/min/1.73 m2 per year in males (P &lt, 0.05) and −0.7 ± 5.3 mL/min/1.73 m2 per year in females. The Spearman correlation analysis confirmed a higher MEST score in the whole cohort and in males correlated with disease progression. In patients with proteinuria below 1.0 g/24 h, disease progression was faster in males. Conclusions: According to the correlation analysis of the main prognostic risk factors, affecting the progression of IgAN, we can conclude that IgA nephropathy in males progresses more rapidly compared to females.

Background: The nuclear proliferation biomarker Ki67 has multiple potential roles in breast cancer, including prognosis-based decisions, but unacceptable between-laboratory variability has limited its clinical value. The International Ki67 Working Group (IKWG) has undertaken a systematic program to determine whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories. Technological advances and broader availability of devices for automated assessment of stained slides raise the possibility that these machines may improve on reproducibility of traditional pathologist-based visual Ki67 assessment. Aims: To characterize reproducibility of automated machine-measured Ki67 expression using slides previously analyzed in the IKWG phase 3 study that evaluated reproducibility of visual Ki67 assessment. Methods: Two sets of 30 previously stained slides containing core-cut biopsy sections of breast tumors were circulated to 14 laboratories for scanning and automated assessment of Ki67 expression. Sites were instructed to return average and maximum percentage of tumor cells positive for Ki67 for each slide, where maximum is designed to reflect “hot spot” analysis. Two laboratories returned scores from 2 operators; not all laboratories reported values for maximum Ki67 scores. Different operators were treated as distinct laboratories in analyses. Sixteen and 10 score sets were available for average and maximum Ki67 analyses, respectively, encompassing 7 unique scanner and 10 software platforms. Pre-specified analyses included evaluation of reproducibility across all laboratories as well as within a subgroup limited to those using Aperio scanners. The primary reproducibility metric was intraclass correlation coefficient between laboratories (ICC), regardless of device platform or software. Results: Geometric means across 30 cases for 16 operators ranged from 11.06% to 38.11% with overall mean 16.75% (95% CI:14.45-19.42) for average scores. Geometric means for 10 operators ranged from 16.44% to 68.73% with overall mean 25.16% (95% CI: 18.71-33.84) for maximum scores. ICC for automated average scores across 16 operators was 0.83 (95% CI: 0.73-0.91) and ICC for maximum scores across 10 operators was 0.63 (95% CI: 0.44-0.80) although one outlier lab dramatically affected results. For the laboratories using the Aperio platform (8 score sets), ICC for automated average scores was 0.89 (95% CI; 0.81-0.96). These results are similar to ICC of 0.87 (95%CI; 0.81-0.93) reported using these same slides in the Phase 3 visual assessment reproducibility study in which observers counted 500 cells per slide (Leung et al, NPJBrCancer, in press). Conclusions: Between-laboratory reproducibility for automated machine assessment of average Ki67 is similar to that for pathologist-based visual assessment of Ki67. However, the observed ICC was markedly numerically lower for the maximum score method compared to the average method, suggesting that the maximum score may not be useful as a reproducible measure of proliferation. Automated average scoring methods show promise for standardization of Ki67 scoring, supporting future studies to clinically validate Ki67. Citation Format: Rimm DL, McShane LM, Leung SCY, Bai Y, Bane AL, Bartlett JMS, Bayani J, Chang MC, Dean M, Denkert C, Enwere E, Galderisi C, Gholap A, Hugh JC, Jadhav A, Kornaga E, Laurinavicius A, Levenson R, Lima J, Miller K, Pantanowitz L, Piper T, Ruan J, Srinivasan M, Virk S, Wu Y, Yang H, Hayes DF, Nielsen TO, Dowsett M. An international multicenter study to evaluate reproducibility of automated scoring methods for assessment of Ki67 in breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-03-01.

Background & Aim Acute kidney injury (AKI) is a life-threatening postoperative complication, affecting 10-30% of treated patients and characterized by the damage to the proximal tubular cells, thereby markedly impairing renal function.1,2,3 15% of patients develop chronic kidney disease (CKD) and fibrosis, eventually managed by hemodialysis and kidney transplantation.4 Mesenchymal stem cells have been shown to possess anti-inflammatory and immunomodulatory properties and be able to aid in tissue repair.5 A link between AKI and CKD has been established and the optimal treatment approach to reduce the high unmet medical need and an economical burden is still being researched.6 Placenta-derived mesenchymal stem cells (PSCs) may be a viable approach to treat AKI and prevent subsequent CKD development. Methods, Results & Conclusion M.: PSCs have been isolated using GMP grade materials, cultivated for three weeks and characterized by yield, viability, flow cytometry and potency in vitro. Wistar rats (8-12 wk) underwent preclinical ischemia-reperfusion injury (IRI). Two experimental groups received treatment. Experimental group (Index) received 3 × 105 of PSCs in the corticomedullar region of each kidney. Control group (Control) received PBS vehicle solution. Survival analysis was carried out till day 7. Urine and blood serum samples were collected on day 0, 3 and 7 and analysed for urine volume/24hrs., protein, creatinine, urea, Na+ and K+. Histological kidney analysis on days 3 and 7 for evaluation of tubular necrosis. R. PSCs had a consistent yield, viability, MSCs markers expression and suppressed proliferation of T cells. Survival rate improved – 100% (Index) vs. 75% (Control). Serum urea and K+ was reduced in index group on day 7 (p Serum creatinine was 1.9 and 1.6 times lower in index group on days 3 and 7, respectively. Na+ was similarly lower after 7 days after PSCs injection. Extensive acute tubular necrosis (ATN) with broad coagulative tubular epithelial necrosis was evident after 3 days in the Control group. Variable extent of ATN without significant coagulative necrosis was observed after 3 and 7 days of Index group. C. Placental derived stem cells have the potential to prevent initial kidney fibrosis cascade through ameliorating initial kidney damage and improving kidney function. A superior 100% survival rate of treated animal group exhibits the potential of characterised PSCs to be used in a larger scale preclinical tumorigenicity and toxicity studies and subsequent clinical first-in-human studies.

Objective We sought to investigate the impact of self-reported fasting duration times on the lipid profile results and its impact on the cardiovascular risk stratification and metabolic syndrome diagnosis. Subjects and methods We analyzed data from all consecutive individuals evaluated in a comprehensive health examination at the Hospital Israelita Albert Einstein from January to December 2015. We divided these patients in three groups, according to the fasting duration recalled (< 8h, 8-12h and > 12h). We calculated the global cardiovascular risk and diagnosed metabolic syndrome according to the current criteria and estimated their change according to fasting duration. Results A total of 12,196 (42.3 ± 9.2 years-old, 30.2% females) patients were evaluated. The distribution of cardiovascular risk was not different among groups defined by fasting duration in both men and women (p = 0.547 for women and p = 0.329 for men). Similarly, the prevalence of metabolic syndrome was not influenced by the fasting duration (p = 0.431 for women and p = 0.166 for men). Conclusion Self-reported fasting duration had no significant impact on the lipid profile results, including triglyceride levels. Consequently, no changes on the cardiovascular risk stratification using the Framingham risk score nor changes on the prevalence of metabolic syndrome were noted.

Glomerulus classification and detection in kidney tissue segments are key processes in nephropathology used for the correct diagnosis of the diseases. In this paper, we deal with the challenge of automating Glomerulus classification and detection from digitized kidney slide segments using a deep learning framework. The proposed method applies Convolutional Neural Networks (CNNs) between two classes: Glomerulus and Non-Glomerulus, to detect the image segments belonging to Glomerulus regions. We configure the CNN with the public pre-trained AlexNet model and adapt it to our system by learning from Glomerulus and Non-Glomerulus regions extracted from training slides. Once the model is trained, labeling is performed by applying the CNN classification to the image blocks under analysis. The results of the method indicate that this technique is suitable for correct Glomerulus detection in Whole Slide Images (WSI), showing robustness while reducing false positive and false negative detections.

Guidelines have recommended statin initiation based on the absolute cardiovascular risk. We tested the hypothesis that a strategy based on the predicted cardiovascular benefit, compared with the risk-based approach, modifies statin eligibility and the estimated benefit in a population in primary cardiovascular prevention. The study included 16,008 subjects (48 ± 6 years, 73% men) with low-density lipoprotein cholesterol levels of 70 to 190 mg/dl, not on lipid-lowering drugs, who underwent a routine health screening in a single center. For the risk-based strategy, criterion for statin eligibility was defined as a 10-year atherosclerotic cardiovascular disease (ASCVD) risk of ≥7.5%. In the benefit-based strategy, subjects were considered for statin according to the predicted absolute cardiovascular risk reduction, so that the number of statin candidates would be the same as in the risk-based strategy. The benefit-based strategy would replace 11% of statin candidates allocated in the risk-based approach with younger, lower risk subjects with higher low-density lipoprotein cholesterol. Using the benefit-based strategy, 13% of subjects with 5.0% to 7.5% ASCVD risk would shift from a statin-ineligible to a statin-eligible status, whereas 24% of those with 7.5% to10.0% ASCVD risk would become statin ineligible. These effects would transfer the benefit from higher to lower risk subjects. In the entire population, no clinically meaningful change in the benefit would be expected. In conclusion, switching from a risk-based strategy to a benefit-based approach, while keeping the same rate of statin use in the population, is expected to promote substantial changes in statin eligibility in subjects at intermediate cardiovascular risk, modifying the subpopulation to be benefited by the treatment.

Digital image analysis (DIA) enables higher accuracy, reproducibility, and capacity to enumerate cell populations by immunohistochemistry; however, the most unique benefits may be obtained by evaluating the spatial distribution and intra-tissue variance of markers. The proliferative activity of breast cancer tissue, estimated by the Ki67 labeling index (Ki67 LI), is a prognostic and predictive biomarker requiring robust measurement methodologies. We performed DIA on whole-slide images (WSI) of 302 surgically removed Ki67-stained breast cancer specimens; the tumour classifier algorithm was used to automatically detect tumour tissue but was not trained to distinguish between invasive and non-invasive carcinoma cells. The WSI DIA-generated data were subsampled by hexagonal tiling (HexT). Distribution and texture parameters were compared to conventional WSI DIA and pathology report data. Factor analysis of the data set, including total numbers of tumor cells, the Ki67 LI and Ki67 distribution, and texture indicators, extracted 4 factors, identified as entropy, proliferation, bimodality, and cellularity. The factor scores were further utilized in cluster analysis, outlining subcategories of heterogeneous tumors with predominant entropy, bimodality, or both at different levels of proliferative activity. The methodology also allowed the visualization of Ki67 LI heterogeneity in tumors and the automated detection and quantitative evaluation of Ki67 hotspots, based on the upper quintile of the HexT data, conceptualized as the "Pareto hotspot". We conclude that systematic subsampling of DIA-generated data into HexT enables comprehensive Ki67 LI analysis that reflects aspects of intra-tumor heterogeneity and may serve as a methodology to improve digital immunohistochemistry in general.

Our aim was to evaluate the incidence of biopsy-proven kidney diseases in Lithuania and to compare their changes in three different time intervals. All Lithuanian kidney biopsies were performed in the National Center of Pathology, enabling analysis at the national level. The native kidney biopsy data were reviewed, and incidence of renal disorders and patient demographics were compared during three time intervals: 1994–1999, 2000–2006, and 2007–2012. A total of 5,368 kidney biopsies were performed, including 3,640 native kidney and 1,728 kidney transplant biopsies; 59.5 % (2,165) of the native kidney biopsies were classified as primary glomerulopathies. The most common entity was IgA nephropathy (737; 34.0 %), followed by focal segmental glomerulosclerosis (285; 13.2 %) and membranoproliferative glomerulonephritis (256; 11.8 %). Prominent decrease in incidence of membranoproliferative glomerulonephritis (16.8 to 8.7 % from the first to third time interval) and increase in (mainly, pauci-immune) crescentic glomerulonephritis (6.2 to 15.3 %) were noted over the study period. In a subgroup of 427 pediatric native kidney biopsies, IgAN accounted for 24.9 % of biopsies. The incidence of MCNS increased dramatically from the first to third time interval (6.3 to 25.4 %), while the number of MPGN increased in the second time interval (from 7.2 to 8.9 %) but decreased in the third one (to 4.4 %). Decrease in relative incidence of membranoproliferative glomerulonephritis, most likely, reflects improvement in socioeconomic conditions, while relative increase in crescentic glomerulonephritis is interpreted as improved diagnostics of the disease.

A set of 10 quinoidal compounds synthesized enzymatically using laccase from Coriolopsis byrsina GRB13 have been examined as redox mediators applicable for bioelectrocatalytic systems using two types of pyrroloquinoline quinone-dependent alcohol dehydrogenases – periplasmic (s-PQQ-ADH) and membrane-bound (m-PQQ-ADH). The efficiency of the biosensors have been evaluated for both types of enzymes and varied in range from 2 × 10−7 A for Phenazine-2,3-diamine to 26 × 10−7 A for 2-(3-Nitroanilino)-1,4-benzoquinone. Experimental data correlated with the molecular properties of mediators using results of ab initio quantum chemical calculations. The oxidation potential of mediators as well as the maximum current (Imax) of biosensors correlated with the calculated energy of the lowest unoccupied molecular orbital (ELUMO) of mediators. In the case of Imax, this result indicates the rate-limiting character of enzymatic mediator reduction in the overall process of biosensor response. The proposed approach demonstrates that the advance determination of molecular properties of potential mediators by ab initio quantum chemical calculations might be a useful instrument in the development process of the redox enzymes based biosensors.