Hybridogenesis is a hemiclonal reproductive strategy in diploid and triploid hybrids. Our study model is a frog
P. esculentus
(diploid RL and triploids RLL and RRL), a natural hybrid between
P. ...lessonae
(LL) and
P. ridibundus
(RR). Hybridogenesis relies on elimination of one genome (L or R) from gonocytes (G) in tadpole gonads during prespermatogenesis, but not from spermatogonial stem cells (SSCs) in adults. Here we provide the first comprehensive study of testis morphology combined with chromosome composition in the full spectrum of spermatogenic cells. Using genomic
in situ
hybridization (GISH) and FISH we determined genomes in metaphase plates and interphase nuclei in Gs and SSCs. We traced genomic composition of SSCs, spermatocytes and spermatozoa in individual adult males that were crossed with females of the parental species and gave progeny. Degenerating gonocytes (24%–39%) and SSCs (18%–20%) led to partial sterility of juvenile and adult gonads. We conclude that elimination and endoreplication not properly completed during prespermatogenesis may be halted when gonocytes become dormant in juveniles. After resumption of mitotic divisions by SSCs in adults, these 20% of cells with successful genome elimination and endoreplication continue spermatogenesis, while in about 80% spermatogenesis is deficient. Majority of abnormal cells are eliminated by cell death, however some of them give rise to aneuploid spermatocytes and spermatozoa which shows that hybridogenesis is a wasteful process.
Abstract
Hybrid taxa from the genus Pelophylax can propagate themselves in a modified way of sexual reproduction called hybridogenesis ensuring the formation of clonal gametes containing the genome ...of only one parental (host) species. Pelophylax grafi from South-Western Europe is a hybrid composed of P. ridibundus and P. perezi genomes and it lives with a host species P. perezi (P-G system). Yet it is unknown, whether non-Mendelian inheritance is fully maintained in such populations. In this study, we characterize P. perezi and P. grafi somatic karyotypes by using comparative genomic hybridization, genomic in situ hybridization, fluorescent in situ hybridization, and actinomycin D-DAPI. Here, we show the homeology of P. perezi and P. grafi somatic karyotypes to other Pelophylax taxa with 2n = 26 and equal contribution of ridibundus and perezi chromosomes in P. grafi which supports F1 hybrid genome constitution as well as a hemiclonal genome inheritance. We show that ridibundus chromosomes have larger regions of interstitial (TTAGGG)n repeats flanking the nucleolus organizing region on chromosome no. 10 and a high quantity of AT pairs in the centromeric regions. In P. perezi, we found species-specific sequences in metaphase chromosomes and marker structures in lampbrush chromosomes. Pericentromeric RrS1 repeat sequence was present in perezi and ridibundus chromosomes, but the blocks were stronger in ridibundus. Various cytogenetic techniques applied to the P-G system provide genome discrimination between ridibundus and perezi chromosomal sets. They could be used in studies of germ-line cells to explain patterns of clonal gametogenesis in P. grafi and broaden the knowledge about reproductive strategies in hybrid animals.
In this retrospective study we analyzed over 300 patients with diagnosed retinoblastoma treated in the Department of Ophthalmology and Ocular Oncology in Kraków in 1967-2011. Nine families (parents ...and offspring) with diagnosed familial retinoblastoma present in at least two generations were analyzed. A review of the age of onset, diagnosis and recurrence rate of tumors as well as the long-term results of applied therapy and advantages of prophylactic ophthalmic screening in children at high risk of familial retinoblastoma was performed. The results of our observations showed that in offspring the tumors were diagnosed earlier, and the therapy outcomes were better as compared to the group of Parents. We conclude that these observations were associated with performed genetic screening, early prophylactic ophthalmic examination of children born in families with diagnosed retinoblastoma and chemoreduction treatment.
The article presents a novel application of the most up-to-date computational approach, i.e., artificial intelligence, to the problem of the compression of closed-cell aluminium. The objective of the ...research was to investigate whether the phenomenon can be described by neural networks and to determine the details of the network architecture so that the assumed criteria of accuracy, ability to prognose and repeatability would be complied. The methodology consisted of the following stages: experimental compression of foam specimens, choice of machine learning parameters, implementation of an algorithm for building different structures of artificial neural networks (ANNs), a two-step verification of the quality of built models and finally the choice of the most appropriate ones. The studied ANNs were two-layer feedforward networks with varying neuron numbers in the hidden layer. The following measures of evaluation were assumed: mean square error (
), sum of absolute errors (
) and mean absolute relative error (
). Obtained results show that networks trained with the assumed learning parameters which had 4 to 11 neurons in the hidden layer were appropriate for modelling and prognosing the compression of closed-cell aluminium in the assumed domains; however, they fulfilled accuracy and repeatability conditions differently. The network with six neurons in the hidden layer provided the best accuracy of prognosis at MARE≤2.7% but little robustness. On the other hand, the structure with a complexity of 11 neurons gave a similar high-quality of prognosis at MARE≤3.0% but with a much better robustness indication (80%). The results also allowed the determination of the minimum threshold of the accuracy of prognosis: MARE≥1.66%. In conclusion, the research shows that the phenomenon of the compression of aluminium foam is able to be described by neural networks within the frames of made assumptions and allowed for the determination of detailed specifications of structure and learning parameters for building models with good-quality accuracy and robustness.
The task of controlling a wheeled mobile robot is an important element of navigation algorithms. The control algorithm manages the robot’s movement in accordance with the path determined by the ...planner module, where the accuracy of mapping the given route is very important. Most often, mobile robots are battery-powered, which makes minimizing energy consumption and shortening travel time an important issue. For this reason, in this work, the mobile robot control algorithm was tested in terms of energy consumption, travel time and path mapping accuracy. During the research, a criterion was developed, thanks to which it was possible to select the optimal parameters of the pure pursuit algorithm that controls the movement of the tested robot. The research was carried out in the Laboratory of Intelligent Mobile Robots using the QBot2e mobile robot operating on the basis of differential drive kinematics. As a result of the research, optimal values of the control parameters were obtained, minimizing the travel time, energy consumption and mapping error of the given paths.
Introducing integrated, automatic control to buildings operating with the environmental quality management (EQM) system, we found that existing energy models are not suitable for use in integrated ...control systems as they poorly represent the real time, interacting, and transient effects that occur under field conditions. We needed another high-precision estimator for energy efficiency and indoor environment and to this end we examined artificial neural networks (ANNs). This paper presents a road map for design and evaluation of ANN-based estimators of the given performance aspect in a complex interacting environment. It demonstrates that in creating a precise representation of a mathematical relationship one must evaluate the stability and fitness under randomly changing initial conditions. It also shows that ANN systems designed in this manner may have a high precision in characterizing the response of the building exposed to the variable outdoor climatic conditions. The absolute value of the relative errors ( M a x A R E ) being less than 1.4% for each stage of the ANN development proves that our objective of monitoring and EQM characterization can be reached.
Skin Microbiome in Prurigo Nodularis Tutka, Klaudia; Żychowska, Magdalena; Żaczek, Anna ...
International journal of molecular sciences,
04/2023, Letnik:
24, Številka:
8
Journal Article
Recenzirano
Odprti dostop
Prurigo nodularis (PN) is a chronic condition characterized by the presence of nodular lesions accompanied by intense pruritus. The disease has been linked to several infectious factors, but data on ...the direct presence of microorganisms in the lesions of PN are scarce. The aim of this study was to evaluate the diversity and composition of the bacterial microbiome in PN lesions by targeting the region V3-V4 of 16S rRNA. Skin swabs were obtained from active nodules in 24 patients with PN, inflammatory patches of 14 patients with atopic dermatitis (AD) and corresponding skin areas of 9 healthy volunteers (HV). After DNA extraction, the V3-V4 region of the bacterial 16S rRNA gene was amplified. Sequencing was performed using the Illumina platform on the MiSeq instrument. Operational taxonomic units (OTU) were identified. The identification of taxa was carried out using the Silva v.138 database. There was no statistically significant difference in the alpha-diversity (intra-sample diversity) between the PN, AD and HV groups. The beta-diversity (inter-sample diversity) showed statistically significant differences between the three groups on a global level and in paired analyses.
was significantly more abundant in samples from PN and AD patients than in controls. The difference was maintained across all taxonomic levels. The PN microbiome is highly similar to that of AD. It remains unclear whether the disturbed composition of the microbiome and the domination of
in PN lesions may be the trigger factor of pruritus and lead to the development of cutaneous changes or is a secondary phenomenon. Our preliminary results support the theory that the composition of the skin microbiome in PN is altered and justify further research on the role of the microbiome in this debilitating condition.
The knowledge on strength properties of porous metals in compression is essential in tailored application design, as well as in elaboration of general material models. In this article, the authors ...propose specification details of the ANN architecture for adequate modelling of the phenomenon of compressive behaviour of open-cell aluminum. In the presented research, an algorithm was used to build different structures of artificial neural networks (ANNs), which approximated stress-strain relations of an aluminum sponge subjected to compression. Next, the quality of the built approximations was appraised. The mean absolute relative error (MARE), coefficient of determination between outputs and targets R2, root mean square error (RMSE), and mean square error (MSE) were assumed as criterial measures for the assessment of the fitting quality. The studied neural networks (NNs) were two-layer feedforward networks with different numbers of neurons in the hidden layer. A set of experimental stress-strain data from quasistatic uniaxial compression tests of open-cell aluminum of various apparent densities was used as data for training of neural networks. Analysis was performed in two modes: in the first one, all samples were taken for training, and in the second case, one sample was left out during training in order to play the role of external data for testing the trained network later. The taken out samples were maximum and minimum density samples (for extrapolation) and one random from within the density interval. The results showed that good approximation on the engineering level MARE<5% was reached for teaching networks with ≥7 neurons in the hidden layer for the first studied case and with ≥8 neurons for the second. Calculations on external data proved that 8 neurons are enough to actually obtain MARE<10%. Moreover, it was shown that the quality of approximation can be significantly improved to MARE≈7% (tested on external data) if the initial region of the stress-strain relation is modelled by an additional network.
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