Search Results (8)

Mosquitoes (Diptera: Culicidae) exhibit vertical stratification patterns in forest environments, a fundamental ecological aspect for understanding niche occupation patterns, host-seeking behavior, and consequently arbovirus transmission mechanisms. Despite the relevance of this topic, available studies mostly focus on genera such as Aedes, Haemagogus, and Sabethes which are traditionally associated with arbovirus transmission. There are still important gaps regarding stratification and seasonality in the Mansoniini tribe, whose biology and epidemiological role remain underexplored, especially in highly biodiverse ecosystems such as the Atlantic Forest. This study evaluated the influence of seasonality and vertical stratification on the mosquito community, with a detailed focus on the Mansoniini tribe, in an Atlantic Forest fragment in Brazil, between May 2023 and December 2024. Captures were performed monthly using CDC light traps positioned at 1.5 m and 10 m heights, and specimens were morphologically identified. A total of 880 mosquitoes from nine genera and 24 species were captured, of which 91 (10.3%) belonged to the Mansoniini tribe. The most abundant species were Coquillettidia fasciolata and Mansonia titillans, recorded in both strata. Our results indicate no marked vertical segregation for the studied mosquito community in this specific location, but a strong influence of seasonality, particularly for the Mansoniini tribe, reinforcing the role of meteorological data on the population structure of these species. These site-specific findings offer a foundational ecological portrait and a robust methodological template for a neglected taxon. They generate critical, testable hypotheses about niche partitioning in fragmented forests and underscore the necessity for broader spatial replication to disentangle the relative influence of seasonal versus vertical drivers in similar ecosystems. Full article

To model the response of neural networks to electromagnetic radiation in real-world environments, this study proposes a memristive dual-wing fractional-order Hopfield neural network (MDW-FOMHNN) model, utilizing a fractional-order memristor to simulate neuronal responses to electromagnetic radiation, thereby achieving complex chaotic dynamics. Analysis reveals that within specific ranges of the coupling strength, the MDW-FOMHNN lacks equilibrium points and exhibits hidden chaotic attractors. Numerical solutions are obtained using the Adomian Decomposition Method (ADM), and the system’s chaotic behavior is confirmed through Lyapunov exponent spectra, bifurcation diagrams, phase portraits, and time series. The study further demonstrates that the coupling strength and fractional order significantly modulate attractor morphologies, revealing diverse attractor structures and their coexistence. The complexity of the MDW-FOMHNN output sequence is quantified using spectral entropy, highlighting the system’s potential for applications in cryptography and related fields. Based on the polynomial form derived from ADM, a field programmable gate array (FPGA) implementation scheme is developed, and the expected chaotic attractors are successfully generated on an oscilloscope, thereby validating the consistency between theoretical analysis and numerical simulations. Finally, to link theory with practice, a simple and efficient MDW-FOMHNN-based encryption/decryption scheme is presented. Full article

Human pluripotent stem cells have the potential for unlimited proliferation and controlled differentiation into various somatic cells, making them a unique tool for regenerative and personalized medicine. Determining the best clone selection is a challenging problem in this field and requires new sensing instruments and methods able to automatically assess the state of a growing colony (‘phenotype’) and make decisions about its destiny. One possible solution for such label-free, non-invasive assessment is to make phase-contrast images and/or videos of growing stem cell colonies, process the morphological parameters (‘morphological portrait’, or signal), link this information to the colony phenotype, and initiate an automated protocol for the colony selection. As a step in implementing this strategy, we used machine learning methods to find an effective model for classifying the human pluripotent stem cell colonies of three lines according to their morphological phenotype (‘good’ or ‘bad’), using morphological parameters from the previously published data as predictors. We found that the model using cellular morphological parameters as predictors and artificial neural networks as the classification method produced the best average accuracy of phenotype prediction (67%). When morphological parameters of colonies were used as predictors, logistic regression was the most effective classification method (75% average accuracy). Combining the morphological parameters of cells and colonies resulted in the most effective model, with a 99% average accuracy of phenotype prediction. Random forest was the most efficient classification method for the combined data. We applied feature selection methods and showed that different morphological parameters were important for phenotype recognition via either cellular or colonial parameters. Our results indicate a necessity for retaining both cellular and colonial morphological information for predicting the phenotype and provide an optimal choice for the machine learning method. The classification models reported in this study could be used as a basis for developing and/or improving automated solutions to control the quality of human pluripotent stem cells for medical purposes. Full article

Coarse-grained molecular dynamics simulations that incorporate explicit water-mediated hydrophilic/hydrophobic interactions are employed to track spatiotemporal evolution of diblock copolymer aggregation in initially homogeneous solutions. A phase portrait of the observed morphologies and their quantitative geometric features such as aggregation numbers, packing parameters, and radial distribution functions of solvent/monomers are presented. Energetic and entropic measures relevant to self-assembly such as specific solvent accessible surface area (SASA) and probability distribution functions (pdfs) of segmental stretch of copolymer chains are analyzed. The simulations qualitatively capture experimentally observed morphological diversity in diblock copolymer solutions. Topologically simpler structures predicted include spherical micelles, vesicles (polymersomes), lamellae (bilayers), linear wormlike micelles, and tori. More complex morphologies observed for larger chain lengths and nearly symmetric copolymer compositions include branched wormlike micelles with Y-shaped junctions and cylindrical micelle networks. For larger concentrations, vesicle strands, held together by hydrogen bonds, and “giant” composite aggregates that consist of lamellar, mixed hydrophobic/hydrophilic regions and percolating water cores are predicted. All structures are dynamic and exhibit diffuse domain boundaries. Morphology transitions across topologically simpler structures can be rationalized based on specific SASA measurements. PDFs of segmental stretch within vesicular assemblies appear to follow a log-normal distribution conducive for maximizing configuration entropy. Full article

The ability of human pluripotent stem cells for unlimited proliferation and self-renewal promotes their application in the fields of regenerative medicine. The morphological assessment of growing colonies and cells, as a non-invasive method, allows the best clones for further clinical applications to be safely selected. For this purpose, we analyzed seven morphological parameters of both colonies and cells extracted from the phase-contrast images of human embryonic stem cell line H9, control human induced pluripotent stem cell (hiPSC) line AD3, and hiPSC line HPCASRi002-A (CaSR) in various passages during their growth for 120 h. The morphological phenotype of each colony was classified using a visual analysis and associated with its potential for pluripotency and clonality maintenance, thus defining the colony phenotype as the control parameter. Using the analysis of variance for the morphological parameters of each line, we showed that selected parameters carried information about different cell lines and different phenotypes within each line. We demonstrated that a model of classification of colonies and cells by phenotype, built on the selected parameters as predictors, recognized the phenotype with an accuracy of 70–75%. In addition, we performed a qRT-PCR analysis of eleven pluripotency markers genes. By analyzing the variance of their expression in samples from different lines and with different phenotypes, we identified group-specific sets of genes that could be used as the most informative ones for the separation of the best clones. Our results indicated the fundamental possibility of constructing a morphological portrait of a colony informative for the automatic identification of the phenotype and for linking this portrait to the expression of pluripotency markers. Full article

Today, domestic cats are important human companion animals for their appearance and favorable personalities. During the history of their domestication, the morphological and genetic portraits of domestic cats changed significantly from their wild ancestors, and the gut microbial communities of different breeds of cats also apparently differ. In the current study, the gut microbiota of Ragdoll cats and Felinae cats were analyzed and compared. Our data indicated that the diversity and richness of the gut microbiota in the Felinae cats were much higher than in the Ragdoll cats. The taxonomic analyses revealed that the most predominant phyla of the feline gut microbiota were Firmicutes, Bacteroidota, Fusobacteriota, Proteobacteria, Actinobacteriota, Campilobacterota, and others, while the most predominant genera were Anaerococcus, Fusobacterium, Bacteroides, Escherichia-Shigella, Finegoldia, Porphyromonas, Collinsella, Lactobacillus, Ruminococcus_gnavus_group, Prevotella, and others. Different microbial communities between the Ragdoll group and the Felinae group were observed, and the compared results demonstrated that the relative abundances of beneficial microbes (such as Lactobacillus, Enterococcus, Streptococcus, Blautia, Roseburia, and so on) in the Ragdoll group were much higher than in the Felinae group. The co-occurrence network revealed that the number of nodes and links in the Felinae group was significantly higher than the Ragdoll group, which meant that the network of the Felinae group was larger and more complex than that of the Ragdoll group. PICRUSt function analyses indicated that the differences in microbial genes might influence the energy metabolism and immune functions of the host. In all, our data demonstrated that the richness and diversity of beneficial microbes in the Ragdoll group were much higher than the Felinae group. Therefore, it is possible to isolate and identify more candidate probiotics in the gut microbiota of growing Ragdoll cats. Full article

Fayum mummy portraits, painted around 2000 years ago, represent a fascinating fusion of Egyptian and Graeco-Roman funerary and artistic traditions. Examination of these artworks may provide insight into the Roman Empire’s trade and economic and social structure during one of its most crucial yet still hazy times of transition. The lack of proper archaeological documentation of the numerous excavated portraits currently prevents their chronological dating, be it absolute or relative. So far, their production period has been defined essentially on the basis of the relevant differences in their pictorial style. Our study introduces the use of Accelerator Mass Spectrometry (AMS) to assess the age of a fragment of an encaustic painting belonging to the corpus of the Fayum portraits. The unexpected age resulting from ¹⁴C analysis suggests the need to reconsider previous assumptions regarding the period of production of the Fayum corpus. Furthermore, our multi-analytical, non-invasive approach yields further details regarding the fragment’s pictorial technique and constituting materials, based on spectral and morphological analysis and cross-sectional examination. Full article

The study of congenital virus infections in humans requires suitable ex vivo platforms for the species-specific events during embryonal development. A prominent example for these infections is rubella virus (RV) which most commonly leads to defects in ear, heart, and eye development. We applied teratogenic RV to human induced pluripotent stem cells (iPSCs) followed by differentiation into cells of the three embryonic lineages (ecto-, meso-, and endoderm) as a cell culture model for blastocyst- and gastrulation-like stages. In the presence of RV, lineage-specific differentiation markers were expressed, indicating that lineage identity was maintained. However, portrait analysis of the transcriptomic expression signatures of all samples revealed that mock- and RV-infected endodermal cells were less related to each other than their ecto- and mesodermal counterparts. Markers for definitive endoderm were increased during RV infection. Profound alterations of the epigenetic landscape including the expression level of components of the chromatin remodeling complexes and an induction of type III interferons were found, especially after endodermal differentiation of RV-infected iPSCs. Moreover, the eye field transcription factors RAX and SIX3 and components of the gene set vasculogenesis were identified as dysregulated transcripts. Although iPSC morphology was maintained, the formation of embryoid bodies as three-dimensional cell aggregates and as such cellular adhesion capacity was impaired during RV infection. The correlation of the molecular alterations induced by RV during differentiation of iPSCs with the clinical signs of congenital rubella syndrome suggests mechanisms of viral impairment of human development. Full article