[Texture analysis of 3D models for the prediction of the grade of clear cell renal cell carcinoma of the kidney (pilot study)].

AIM: To evaluate the possibilities of textural analysis of 3D models in differentiating the degree of nuclear dysplasia of the clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS: The specimens after surgical treatment of 190 patients with ccRCC were analyzed. In all cases, nephron-sparing surgery (NSS) was performed through laparoscopic access. The clinical characteristics were evaluated, including age, gender, tumor localization (side, surface and segments), absolute tumor volume, Charlson comorbidity index, body mass index, nephrometry scores (RENAL, PADOVA, C-index). Patients were divided into 2 groups. In group 1, there were 119 patients with the ccRCC of Grade 1 or 2, while group 2 consisted of 71 patients with ccRCC of Grade 3 and 4. All patients underwent 3D virtual planning of procedure using the 3D modeling program "Amira". At the first stage, two experienced radiologists performed manual segmentation of 3D models of kidney parenchyma tumors. At the second stage, the tumor shape was analyzed with a mathematical calculation of three indicators and more than 300 textural features of statistics of types 1-2 were extracted. Further, an intellectual analysis was carried out. For the evaluation of tumor grade according to Furman system, the classification problem was solved using the machine learning algorithm Stochastic Gradient Descent and cross-validation k=5. RESULTS: The accuracy of classification for the two groups of Grade 1 or 2 and Grade 3 or 4 on the F1 metric was 72.2. To build the model, the following parameters were selected: the absolute tumor volume, the Charlson comorbidity index, "Energy", the first quartile and the second decile of the pixel intensity distribution. CONCLUSION: The texture analysis of 3D models for the prediction of Fuhrman grade in ccRCC demonstrated satisfactory quality for two groups of Grade 1 or 2 and Grade 3 or 4 nuclear dysplasia.

[Forensic medical characteristics of the prevalence of sudden death from cardiovascular diseases in the constituent entities of the Russian Federation]. / Sudebno-meditsinskaya kharakteristika rasprostranennosti vnezapnoi smerti ot serdechno-sosudistykh zabolevanii v sub"ektakh Rossiiskoi Federatsii.

The purpose of the study is to study the prevalence and frequency of sudden death (SD) from cardiovascular diseases (CVD) in the structure of non-violent death, taking into account the socio-economic development of the constituent entities of the Russian Federation. We analyzed the frequency of this indicator, compared it with the data of the Federal State Statistics Service, and determined the overall dynamics. We conducted a non-parametric analysis of the initial data, carried out clustering and visualization based on the following parameters of the initial sample: «CVD mortality in the structure of non-violent death¼, «morbidity¼ and «per capita income level¼. Correlation dependences of the level of mortality from CVD according to the form 42 on the indicated indicators of the socio-economic condition of the subject were determined. Identified subjects of the Russian Federation with an increase in mortality from CVD; established the dependence of the level of VS on CVD and a number of medical and economic indicators.

[Use of intelligent analysis in urology].

The main methods of intellectual analysis (IA) used in modern medicine are described in the review. The main areas for IA application in the healthcare are diagnostics, treatment, prognosis of the course and efficiency of treatment in various diseases. The IA is based on mathematical methods and algorithms. The basic concepts of IA along with examples of its use in urological practice are presented in the review.

[Analysis of the learning curve in laparoscopic partial nephrectomy in patients with localized renal parenchymal lesions depending on the nephrometric score].

AIM: to analyze the learning curve of surgeons while performing laparoscopic partial nephrectomy in patients with localized renal parenchymal lesions by calculating the MIC (negative surgical margin, ischemia, and complications) index depending on tumor complexity according to the R.E.N.A.L. and PADUA nephrometric scores. MATERIALS AND METHODS: the retrospective study included the results of laparoscopic partial nephrectomies in 320 patients with localized renal parenchymal lesions. The procedures were carried out by four surgeons from the Institute of Urology and Human Reproductive Health of FGAOU VO I.M. Sechenov First Moscow State Medical University, Moscow, Russia (EC-1; ESH-4; EB-7; ME-13) from January 2014 to June 2019. At baseline, all operators had experience of performing at least 30 laparoscopic interventions. In addition to the standard preoperative examination, a 3D virtual planning was carried out using the Amira 3D modeling program. In all cases, the nephrometric assessment of complexity was performed according to the R.E.N.A.L. and PADUA scores. The learning curve was assessed based on the results of operations based on the MIC index. All surgical interventions were divided into eras. In the era, 40 consecutive procedures for each operator were evaluated. Acquired skills were assessed over two eras. RESULTS: The average age of patients, of which 191 (59.7%) were men, was 54.4+/-11.37 years. The average body mass index was 28.55+/-3.85 kg/m2, the absolute volume of kidney lesions was 26.72+/-43.72 cm3, the average Charlson comorbidity index was 1.46+/-1.29, the average R.E.N.A.L. and PADUA scores were 6.38+/-1.75 and 7.92+/-1.51, respectively, the average duration of procedure was 150.36+/-50.18 min, the average blood loss was 227.94+/-280.22 ml, the average time thermal ischemia was 13.28+/-7.82 min. Postoperative complications were seen in 36 (11.2%) cases, of which grade III and more according to Clavien-Dindo developed in 8 patients (2.5%). A positive surgical margin was found in 4 (1.2%) patients. The overall MIC index was achieved in 243 (75.9%) cases; in era 1 it was seen in 71.9% cases in comparison with 80% in era 2. With the 1st degree of complexity (152 (47.5%) patients), MIC was achieved in 80.9% of cases, compared to 76.6% and 56.8% in patients with 2nd degree of complexity (n=124, 38.8%) and 3rd degree of complexity (n=44, 13.8%), respectively. Rate of MIC achievement in eras 1 and 2 for different surgeons were as following: 65% and 72.5%, 75 and 80%, 87.5 and 85% and 60 and 82.5%, for operator 1, 4, 7 and 13, respectively. Age, tumor complexity, R.E.N.A.L. score and PADUA score were the most significant parameters for determining MIC, identified on the basis of the criterion of equality of group means of discrete analysis. CONCLUSION: In all surgeons, the MIC index increased with the accumulation of experience in performing laparoscopic partial nephrectomy, but was lower with an increased degree of complexity of procedures. The minimum number of laparoscopic partial nephrectomies required to achieve an MIC more or equal 70% should be at least 40.

Modelling transport and mean age of dense core vesicles in large axonal arbours.

A model simulating the transport of dense core vesicles (DCVs) in type II axonal terminals of Drosophila motoneurons has been developed. The morphology of type II terminals is characterized by the large number of en passant boutons. The lack of both scaled-up DCV transport and scaled-down DCV capture in boutons results in a less efficient supply of DCVs to distal boutons. Furthermore, the large number of boutons that DCVs pass as they move anterogradely until they reach the most distal bouton may lead to the capture of a majority of DCVs before they turn around in the most distal bouton to move in the retrograde direction. This may lead to a reduced retrograde flux of DCVs and a lack of DCV circulation in type II terminals. The developed model simulates DCV concentrations in boutons, DCV fluxes between the boutons, age density distributions of DCVs and the mean age of DCVs in various boutons. Unlike published experimental observations, our model predicts DCV circulation in type II terminals after these terminals are filled to saturation. This disagreement is likely because experimentally observed terminals were not at steady state, but rather were accumulating DCVs for later release. Our estimates show that the number of DCVs in the transiting state is much smaller than that in the resident state. DCVs travelling in the axon, rather than DCVs transiting in the terminal, may provide a reserve of DCVs for replenishing boutons after a release. The techniques for modelling transport of DCVs developed in our paper can be used to model the transport of other organelles in axons.

A Numerical Study of Sensitivity Coefficients for a Model of Amyloid Precursor Protein and Tubulin-Associated Unit Protein Transport and Agglomeration in Neurons at the Onset of Alzheimer's Disease.

Modeling of intracellular processes occurring during the development of Alzheimer's disease (AD) can be instrumental in understanding the disease and can potentially contribute to finding treatments for the disease. The model of intracellular processes in AD, which we previously developed, contains a large number of parameters. To distinguish between more important and less important parameters, we performed a local sensitivity analysis of this model around the values of parameters that give the best fit with published experimental results. We show that the influence of model parameters on the total concentrations of amyloid precursor protein (APP) and tubulin-associated unit (tau) protein in the axon is reciprocal to the influence of the same parameters on the average velocities of the same proteins during their transport in the axon. The results of our analysis also suggest that in the beginning of AD the aggregation of amyloid-ß and misfolded tau protein have little effect on transport of APP and tau in the axon, which suggests that early damage in AD may be reversible.

How the formation of amyloid plaques and neurofibrillary tangles may be related: a mathematical modelling study.

We develop a mathematical model that enables us to investigate possible mechanisms by which two primary markers of Alzheimer's disease (AD), extracellular amyloid plaques and intracellular tangles, may be related. Our model investigates the possibility that the decay of anterograde axonal transport of amyloid precursor protein (APP), caused by toxic tau aggregates, leads to decreased APP transport towards the synapse and APP accumulation in the soma. The developed model thus couples three processes: (i) slow axonal transport of tau, (ii) tau misfolding and agglomeration, which we simulated by using the Finke-Watzky model and (iii) fast axonal transport of APP. Because the timescale for tau agglomeration is much larger than that for tau transport, we suggest using the quasi-steady-state approximation for formulating and solving the governing equations for these three processes. Our results suggest that misfolded tau most likely accumulates in the beginning of the axon. The analysis of APP transport suggests that APP will also likely accumulate in the beginning of the axon, causing an increased APP concentration in this region, which could be interpreted as a 'traffic jam'. The APP flux towards the synapse is significantly reduced by tau misfolding, but not due to the APP traffic jam, which can be viewed as a symptom, but rather due to the reduced affinity of kinesin-1 motors to APP-transporting vesicles.

Simulating the effect of formation of amyloid plaques on aggregation of tau protein.

In this paper, we develop a mathematical model that enables the investigation of the production and intracellular transport of amyloid precursor protein (APP) and tau protein in a neuron. We also investigate the aggregation of APP fragments into amyloid-ß (Aß) as well as tau aggregation into tau oligomers and neurofibrillary tangles. Using the developed model, we investigate how Aß aggregation can influence tau transport and aggregation in both the soma and the axon. We couple the Aß and tau agglomeration processes by assuming that the value of the kinetic constant that describes the autocatalytic growth (self-replication) reaction step of tau aggregation is proportional to the Aß concentration. The model predicts that APP and tau are distributed differently in the axon. While APP has a uniform distribution along the axon, tau's concentration first decreases and then increases towards the synapse. Aß is uniformly produced along the axon while misfolded tau protein is mostly produced in the proximal axon. The number of Aß and tau polymers originating from the axon is much smaller than the number of Aß and tau polymers originating from the soma. The rate of production of misfolded tau polymers depends on how strongly their production is facilitated by Aß.

Simulating Reversibility of Dense Core Vesicles Capture in En Passant Boutons: Using Mathematical Modeling to Understand the Fate of Dense Core Vesicles in En Passant Boutons.

The goal of this paper is to use mathematical modeling to investigate the fate of dense core vesicles (DCVs) captured in en passant boutons located in nerve terminals. One possibility is that all DCVs captured in boutons are destroyed, another possibility is that captured DCVs can escape and reenter the pool of transiting DCVs that move through the boutons, and a third possibility is that some DCVs are destroyed in boutons, while some reenter the transiting pool. We developed a model by applying the conservation of DCVs in various compartments composing the terminal, to predict different scenarios that emerge from the above assumptions about the fate of DCVs captured in boutons. We simulated DCV transport in type Ib and type III terminals. The simulations demonstrate that, if no DCV destruction in boutons is assumed and all captured DCVs reenter the transiting pool, the DCV fluxes evolve to a uniform circulation in a type Ib terminal at steady-state and the DCV flux remains constant from bouton to bouton. Because at steady-state the amount of captured DCVs is equal to the amount of DCVs that reenter the transiting pool, no decay of DCV fluxes occurs. In a type III terminal at steady-state, the anterograde DCV fluxes decay from bouton to bouton, while retrograde fluxes increase. This is explained by a larger capture efficiency of anterogradely moving DCVs than of retrogradely moving DCVs in type III boutons, while the captured DCVs that reenter the transiting pool are assumed to be equally split between anterogradely and retrogradely moving components. At steady-state, the physiologically reasonable assumption of no DCV destruction in boutons results in the same number of DCVs entering and leaving a nerve terminal. Because published experimental results indicate no DCV circulation in type III terminals, modeling results suggest that DCV transport in these type III terminals may not be at steady-state. To better understand the kinetics of DCV capture and release, future experiments in type III terminals at different times after DCV release (molting) may be proposed.

Simulating tubulin-associated unit transport in an axon: using bootstrapping for estimating confidence intervals of best-fit parameter values obtained from indirect experimental data.

In this paper, we first develop a model of axonal transport of tubulin-associated unit (tau) protein. We determine the minimum number of parameters necessary to reproduce published experimental results, reducing the number of parameters from 18 in the full model to eight in the simplified model. We then address the following questions: Is it possible to estimate parameter values for this model using the very limited amount of published experimental data? Furthermore, is it possible to estimate confidence intervals for the determined parameters? The idea that is explored in this paper is based on using bootstrapping. Model parameters were estimated by minimizing the objective function that simulates the discrepancy between the model predictions and experimental data. Residuals were then identified by calculating the differences between the experimental data and model predictions. New, surrogate 'experimental' data were generated by randomly resampling residuals. By finding sets of best-fit parameters for a large number of surrogate data the histograms for the model parameters were produced. These histograms were then used to estimate confidence intervals for the model parameters, by using the percentile bootstrap. Once the model was calibrated, we applied it to analysing some features of tau transport that are not accessible to current experimental techniques.

Utilization of the bootstrap method for determining confidence intervals of parameters for a model of MAP1B protein transport in axons.

This paper develops a model of axonal transport of MAP1B protein. The problem of determining parameter values for the proposed model utilizing limited available experimental data is addressed. We used a global minimum search algorithm to find parameter values that minimize the discrepancy between model predictions and published experimental results. By analyzing the best fit parameter values it was established that some processes can be dropped from the model without losing accuracy, thus a simplified version of the model was formulated. In particular, our analysis suggests that reversals in MAP1B transport are infrequent and can be neglected. The detachment of anterogradely-biased MAP1B from microtubules (MTs) and the attachment of retrogradely-biased MAP1B to MTs can also be neglected. An analytical solution for the simplified model was obtained. Confidence intervals for the determined parameters were found by bootstrapping model residuals. The resultant analysis heavily constrained the values of some parameters while showing that some could vary without significantly impacting model error. For example, our analysis suggests that, above a certain threshold value, the kinetic constant determining the rate of MAP1B transition from the retrograde pausing state to the off-track state has little impact on model error. On the contrary, the kinetic constant describing MAP1B transition from a pausing to a running state has great impact on model error.

What mechanisms of tau protein transport could be responsible for the inverted tau concentration gradient in degenerating axons?

In tauopathies, such as Alzheimer's disease (AD), microtubule (MT)-associated protein tau detaches from MTs and aggregates, eventually forming insoluble neurofibrillary tangles. In a healthy axon, the tau concentration increases toward the axon terminal, but in a degenerating axon, the tau concentration gradient is inverted and the highest tau concentration is in the soma. In this article, we developed a mathematical model of tau transport in axons. We calibrated and tested the model by using published distributions of tau concentration and tau average velocity in a healthy axon. According to published research, the inverted tau concentration gradient may be one of the reasons leading to AD. We therefore used the model to investigate what modifications in tau transport can lead to the inverted tau concentration gradient. We investigated whether tau detachment from MTs due to tau hyperphosphorylation can cause the inverted tau concentration gradient. We found that the assumption that most tau molecules are detached from MTs does not consistently predict the inverted tau concentration gradient; the predicted tau distribution becomes more uniform if the axon length is increased. We then hypothesized that in degenerating axons some tau remains bound to MTs and participates in the component 'a' of slow axonal transport but that the rate of tau reversals from anterograde to retrograde motion increases. We demonstrated that this hypothesis results in a tau distribution where the tau concentration has its maximum value at the axon hillock and its minimum value at the axon terminal, in agreement with what is observed in AD. Our results thus suggest that defects in active transport of tau may be a contributing factor to the onset of neural degeneration.

What can trigger the onset of Parkinson's disease - A modeling study based on a compartmental model of α-synuclein transport and aggregation in neurons.

The aim of this paper is to develop a minimal model describing events leading to the onset of Parkinson's disease (PD). The model accounts for α-synuclein (α-syn) production in the soma, transport toward the synapse, misfolding, and aggregation. The production and aggregation of polymeric α-syn is simulated using a minimalistic 2-step Finke-Watzky model. We utilized the developed model to analyze what changes in a healthy neuron are likely to lead to the onset of α-syn aggregation. We checked the effects of interruption of α-syn transport toward the synapse, entry of misfolded (infectious) α-syn into the somatic and synaptic compartments, increasing the rate of α-syn synthesis in the soma, and failure of α-syn degradation machinery. Our model suggests that failure of α-syn degradation machinery is probably the most likely cause for the onset of α-syn aggregation leading to PD.

Mathematical models of α-synuclein transport in axons.

To investigate possible effects of diffusion on α-synuclein (α-syn) transport in axons, we developed two models of α-syn transport, one that assumes that α-syn is transported only by active transport, as part of multiprotein complexes, and a second that assumes an interplay between motor-driven and diffusion-driven α-syn transport. By comparing predictions of the two models, we were able to investigate how diffusion could influence axonal transport of α-syn. The predictions obtained could be useful for future experimental work aimed at elucidating the mechanisms of axonal transport of α-syn. We also attempted to simulate possible defects in α-syn transport early in Parkinson's disease (PD). We assumed that in healthy axons α-syn localizes in the axon terminal while in diseased axons α-syn does not localize in the terminal (this was simulated by postulating a zero α-syn flux into the terminal). We found that our model of a diseased axon predicts the build-up of α-syn close to the axon terminal. This build-up could cause α-syn accumulation in Lewy bodies and the subsequent axonal death pattern observed in PD ('dying back' of axons).

Can numerical modeling help understand the fate of tau protein in the axon terminal?

In this paper, we used mathematical modeling to investigate the fate of tau protein in the axon terminal. We developed a comprehensive model of tau transport that accounts for transport of cytosolic tau by diffusion, diffusion transport of microtubule (MT)-bound tau along the MT lattice, active motor-driven transport of MT-bound tau via slow axonal transport mechanism, and degradation of tau in the axon due to tau's finite half-life. We investigated the effect of different assumptions concerning the fate of tau in the terminal on steady-state transport of tau in the axon. In particular, we studied two possible scenarios: (i) tau is destroyed in the terminal and (ii) there is no tau destruction in the terminal, and to avoid tau accumulation we postulated zero flux of tau at the terminal. We found that the tau concentration and percentage of MT-bound tau are not very sensitive to the assumption concerning the fate of tau in the terminal, but the tau's flux and average velocity of tau transport are very sensitive to this assumption. This suggests that measuring the velocity of tau transport and comparing it with the results of mathematical modeling for different assumptions concerning tau's fate in the terminal can provide information concerning what happens to tau in the terminal.

Can an increase in neuropeptide production in the soma lead to DCV circulation in axon terminals with type III en passant boutons?

Neuropeptides are synthesized in the neuron soma; they are packaged in dense core vesicles (DCVs) which undergo axonal transport toward nerve terminals. Published experimental results suggest that in terminals with type Ib boutons DCVs circulate in the terminal, undergoing repeated anterograde and retrograde transport, while in type III terminals DCVs do not circulate in the terminal. In this paper we developed a mathematical model that allowed us to investigate the effects of an increased rate of DCV production in the soma. We demonstrated that our model reproduces some important experimental results, in particular those concerning DCV circulation in type Ib and type III terminals. Our model makes testable predictions. Probably the most important prediction concerns the effect of an increased DCV production rate in the soma, which we anticipate leads to increased DCV circulation in type Ib boutons and to the appearance of DCV circulation in type III boutons. Other predictions concern various stages of development of DCV circulation in the terminals after they were depleted of DCVs due to neuropeptide release.

Can a death signal half-life be used to sense the distance to a lesion site in axons?

Neuron response to injury depends on the distance to the lesion site, which means that neurons are capable of sensing this distance. Several mechanisms explaining how neurons can do this have been proposed and it is possible that neurons use a combination of several mechanisms to make such measurements. In this paper we investigate the feasibility of the simplest mechanism, which is based on the hypothesis that death signals, produced at the lesion site, propagate toward the neuron soma. The signals are propelled by dynein motors. If signals have a finite half-life, they decay as they propagate. By measuring the concentration of death signals arriving to the soma, neurons should thus be able to determine the distance to the injury site. We develop and solve a transport equation based on the above model. We investigate how a death signal distribution depends on the dynein velocity distribution. We evaluate the efficiency of such a mechanism by investigating the sensitivity of death signal concentration at the soma to the distance to the injury site. By using the hypothesis that system performance is optimized by evolution, we evaluate death signal half-lives that would maximize this sensitivity.

Modeling neuropeptide transport in various types of nerve terminals containing en passant boutons.

We developed a mathematical model for simulating neuropeptide transport inside dense core vesicles (DCVs) in axon terminals containing en passant boutons. The motivation for this research is a recent experimental study by Levitan and colleagues (Bulgari et al., 2014) which described DCV transport in nerve terminals of type Ib and type III as well as in nerve terminals of type Ib with the transcription factor DIMM. The goal of our modeling is validating the proposition put forward by Levitan and colleagues that the dramatic difference in DCV number in type Ib and type III terminals can be explained by the difference in DCV capture in type Ib and type III boutons rather than by differences in DCV anterograde transport and half-life of resident DCVs. The developed model provides a tool for studying the dynamics of DCV transport in various types of nerve terminals. The model is also an important step in gaining a better mechanistic understanding of transport processes in axons and identifying directions for the development of new models in this area.

Modelling organelle transport after traumatic axonal injury.

This paper is motivated by recent experimental research (Tang-Schomer et al. 2012) on the formation of periodic varicosities in axons after traumatic brain injury (TBI). TBI leads to the formation of undulated distortions in the axons due to their dynamic deformation. These distortions result in the breakage of some microtubules (MTs) near the peaks of undulations. The breakage is followed by catastrophic MT depolymerisation around the broken ends. Although after relaxation axons regain their straight geometry, the structure of the axon after TBI is characterised by the presence of periodic regions where the density of MTs has been decreased due to depolymerisation. We modelled organelle transport in an axon segment with such a damaged MT structure and investigated how this structure affects the distributions of organelle concentrations and fluxes. The modelling results suggest that organelles accumulate at the boundaries of the region where the density of MTs has been decreased by depolymerisation. According to the model, the presence of such damaged regions decreases the organelle flux by only about 12%. This provides evidence that axon degradation after TBI may be caused by organelle accumulation rather than by starvation due to insufficient organelle flux.

A coupled model of fast axonal transport of organelles and slow axonal transport of tau protein.

We have developed a model that accounts for the effect of a non-uniform distribution of tau protein along the axon length on fast axonal transport of intracellular organelles. The tau distribution is simulated by using a slow axonal transport model; the numerically predicted tau distributions along the axon length were validated by comparing them with experimentally measured tau distributions reported in the literature. We then developed a fast axonal transport model for organelles that accounts for the reduction of kinesin attachment rate to microtubules by tau. We investigated organelle transport for two situations: (1) a uniform tau distribution and (2) a non-uniform tau distribution predicted by the slow axonal transport model. We found that non-uniform tau distributions observed in healthy axons (an increase in tau concentration towards the axon tip) result in a significant enhancement of organelle transport towards the synapse compared with the uniform tau distribution with the same average amount of tau. This suggests that tau may play the role of being an enhancer of organelle transport.