Miracle-dz/UniFAR-FTUs huggingface dataset:
Reluctance Network for Analysing Induction Machines

This thesis presents the components, the construction rules and the equations of the reluctance network used in the analysis of an electrical machine. It defines the equations to form the components of a single-phase electric equivalent circuit from the results of a reluctance network. As part of the study, a computer program has been developed to solve a two-dimensional reluctance network. As a result, the flux and current distributions are calculated for a cage induction motor. The rotor construction with a single-cage and double-cage winding is studied. From the analysis results, a single-phase equivalent circuit is defined to calculate the locked-rotor current of the motor in the steady-state period after the inrush current, at the moment when the rotor starts to rotate. The target in the study is to develop a single-phase equivalent circuit for a starting motor with the effects of iron saturation and eddy-current losses included. The leakage-flux paths of the core in the rotor have their own reactances and iron-loss resistances in the single-phase equivalent circuit. The cumulative influence of the main and leakage fluxes on the magnetic saturation of the machine cross-section is taken into account by using a reluctance model covering the whole cross-sectional area of the machine. The components for the equivalent circuit are defined from the energy distribution over a period in steady-state condition. In the analysis program, damping caused by leakage reactance of the end-windings in the stator and rotor is excluded from the model equations. Only the resistances of the windings are included to limit the supply current. © All rights reserved. No part of the publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the author.
Modeling the role of the thalamus in resting-state functional connectivity: Nature or structure

The thalamus is a central brain structure that serves as a relay station for sensory inputs from the periphery to the cortex and regulates cortical arousal. Traditionally, it has been regarded as a passive relay that transmits information between brain regions. However, recent studies have suggested that the thalamus may also play a role in shaping functional connectivity (FC) in a task-based context. Based on this idea, we hypothesized that due to its centrality in the network and its involvement in cortical activation, the thalamus may also contribute to resting-state FC, a key neurological biomarker widely used to characterize brain function in health and disease. To investigate this hypothesis, we constructed ten in-silico brain network models based on neuroimaging data (MEG, MRI, and dwMRI), and simulated them including and excluding the thalamus. and raising the noise into thalamus to represent the afferences related to the reticular activating system (RAS) and the relay of peripheral sensory inputs. We simulated brain activity and compared the resulting FC to their empirical MEG counterparts to evaluate model’s performance. Results showed that a parceled version of the thalamus with higher noise, able to drive damped cortical oscillators, enhanced the match to empirical FC. However, with an already active self-oscillatory cortex, no impact on the dynamics was observed when introducing the thalamus. We also demonstrated that the enhanced performance was not related to the structural connectivity of the thalamus, but to its higher noisy inputs. Additionally, we highlighted the relevance of a balanced signal-to-noise ratio in thalamus to allow it to propagate its own dynamics. In conclusion, our study sheds light on the role of the thalamus in shaping brain dynamics and FC in resting-state and allowed us to discuss the general role of criticality in the brain at the mesoscale level. Author summary Synchrony between brain regions is an essential aspect of coordinated brain function and serves as a biomarker of health and disease. The thalamus, due to its centrality and widespread connectivity with the cortex, is a crucial structure that may contribute to this synchrony by allowing distant brain regions to work together. In this study, we used computational models to investigate the thalamus’s role in generating brain synchrony at rest. Our findings suggest that the structural connectivity of the thalamus is not its primary contribution to brain synchrony. Instead, we found that the thalamus plays a critical role in driving cortical activity, and when it is not driving this activity, its impact on brain synchrony is null. Our study provides valuable insights into the thalamocortical network’s role in shaping brain dynamics and FC in resting state, laying the groundwork for further research in this area.
Temporal landscape and translational regulation of A-to-I editing in mouse retina development

The significance of A-to-I RNA editing in neurological development is widely recognized, however, its influence on retina development remains to be thoroughly understood. In this study, we aimed to characterize the temporal landscape of A-to-I editing in mouse retina development using total RNA-seq and Ribosome profiling, with a specific emphasis on its effect on gene translation. Our findings revealed that the editing underwent plastic changes and distinct editing contents facilitated stage-specific functions. Further analysis showed a dynamic interplay between A-to-I editing and alternative splicing, with A-to-I editing having a significant impact on splicing efficiency and increasing the quantity of splicing events. A-to-I editing held the potential of enhancing the translatome’s diversity, but this came at the expense of reduced translational efficiency. When coupled with splicing, it could produce a coordinated regulatory effect on translatome dynamics. Overall, our study presents a temporally resolved atlas of A-to-I editing, connecting its dynamic changes with the regulatory impact on splicing and translation.
Fear-conditioning to unpredictable threats reveals sex differences in rat fear-potentiated startle (FPS)

Fear-potentiated startle (FPS) has been widely used to study fear processing in humans and rodents. Human studies have shown higher startle amplitudes and exaggerated fear reactivity to unpredictable vs. predictable threats in individuals suffering from post-traumatic stress disorder (PTSD). Although human FPS studies often use both sexes, a surprisingly limited number of rodent FPS studies use females. Here we investigate the effects of signal-threat contingency, signal-threat order and threat predictability on FPS in both sexes. We use a classic fear-conditioning protocol (100% contingency of cue and shock pairings, with forward conditioning such that the cue co-terminates with the shock) and compare it to modified fear-conditioning protocols (70% contingency; backward conditioning; or cue and shock unpaired). Although there are no sex differences in the startle amplitudes when corrected for body weight, females demonstrate higher shock reactivity during fear-conditioning. Both sexes demonstrate comparable levels of cued, non-cued, and contextual fear in the classic FPS but females show reduced fear discrimination vs. males. Fear-conditioning with 70% contingency or backward order (cue co-starts with shock) induces similar levels of cued, non-cued, and contextual fear in both sexes but they differ in contextual fear extinction. Lastly, a prominent sex difference is uncovered following unpredictable fear-conditioning protocol (cue and shock un-paired), with females showing significantly higher startle overall during the FPS recall, regardless of trial type, and higher contextual fear than males. This striking sex difference in processing unpredictable threats in rodent FPS might help to understand the mechanisms underlying higher incidence of PTSD in women. Highlights Male and female rats have comparable startle amplitudes when corrected for body weight Female rats show higher foot-shock reactivity than males during fear-conditioning Female rats show reduced fear discrimination vs. males in the classic FPS Reversed signal-threat order increases contextual fear in both sexes Exposure to unpredictable threats increases startle in general and contextual fear only in females
Deep convolutional and conditional neural networks for large-scale genomic data generation

Applications of generative models for genomic data have gained significant momentum in the past few years, with scopes ranging from data characterization to generation of genomic segments and functional sequences. In our previous study, we demonstrated that generative adversarial networks (GANs) and restricted Boltzmann machines (RBMs) can be used to create novel high-quality artificial genomes (AGs) which can preserve the complex characteristics of real genomes such as population structure, linkage disequilibrium and selection signals. However, a major drawback of these models is scalability, since the large feature space of genome-wide data increases computational complexity vastly. To address this issue, we implemented a novel convolutional Wasserstein GAN (WGAN) model along with a novel conditional RBM (CRBM) framework for generating AGs with high SNP number. These networks implicitly learn the varying landscape of haplotypic structure in order to capture complex correlation patterns along the genome and generate a wide diversity of plausible haplotypes. We performed comparative analyses to assess both the quality of these generated haplotypes and the amount of possible privacy leakage from the training data. As the importance of genetic privacy becomes more prevalent, the need for effective privacy protection measures for genomic data increases. We used generative neural networks to create large artificial genome segments which possess many characteristics of real genomes without substantial privacy leakage from the training dataset. In the near future with further improvements in haplotype quality and privacy preservation, large-scale artificial genome databases can be assembled to provide easily accessible surrogates of real databases, allowing researchers to conduct studies with diverse genomic data within a safe ethical framework in terms of donor privacy. Author summary Generative modelling has recently become a prominent research field in genomics, with applications ranging from functional sequence design to characterization of population structure. We previously used generative neural networks to create artificial genome segments which possess many characteristics of real genomes but these segments were short in size due to computational requirements. In this work, we present novel generative models for generating artificial genomes with larger sequence size. We test the generated artificial genomes with multiple summary statistics to assess the haplotype quality, overfitting and privacy leakage from the training dataset. Our findings suggest that although there is still room for improvement both in terms of genome quality and privacy preservation, convolutional architectures and conditional generation can be utilised for generating good quality, large-scale genomic data. In the near future with additional improvements, large-scale artificial genomes can be used for assembling surrogate biobanks as alternatives to real biobanks with access restrictions, increasing data accessibility to researchers around the globe.
Molecular Characterization of Fischerella uthpalarensis, the first subsection V cyanobiont from a tropical Azolla species containing dual nitrogenases

There have been theories presented on Azolla cyanobionts, known for voracious nitrogen fixation, vertical transmission of cyanobiont and helping transform a greenhouse planet to an icehouse one ~49 Mya. One such theory encapsulates the existence of two cyanobionts, named Major and Minor. We show here the identity of a possible minor cyanobiont of Azolla named Fischerella uthpalarensis. A likely cyanobiont with straight or curved filaments that were truly branched was isolated. Seven gene fragments, namely 16s rDNA (Forward and Reverse), RNA Polymerase, ITS1 region (Forward and Reverse), nifD and GroEL genes were utilized to identify the isolated cyanobiont. The best match based on BLASTn search tool was found in the RNA Polymerase beta subunit (rpoC) gene fragment, that showed 99.54% identity with 55% coverage to Fischerella muscicola. Phylogenetic inferences with the rpoC genetic locus and the GroEL protein sequence suggest a likely Fischerella genus identity. Furthermore, VnfDG and VnfN fragments too were amplified using PCR and sequenced to demonstrate that this cyanobiont has alternate nitrogenase genes, on top of the molybdenum counterpart, providing an advantage in lifestyle. We encountered a higher level of genomic-level synonymous substitutions, which was not reflected in protein sequences, namely VnfDG and VnfN gene products, which may be due to codon heterogeneity. We also propose for F. uthpalarensis atypicality in codon usage due to the likely acquisition of the V-nitrogenase operon from a presumed recent horizontal gene transfer (HGT) event. The cyanobiont from this study showcases a higher preference for AT over GC at the VnfDG composite locus again hinting at a symbiotic lifestyle.
Postbuckling of nano rods/tubes based on nonlocal beam theory

This paper is concerned with the postbuckling problem of cantilevered nano rods/tubes under an end concentrated load. Eringen's nonlocal beam theory is used to account for the small length scale effect. The governing equation is derived from statical and geometrical considerations and Eringen's nonlocal constitutive relation. The nonlinear differential equation is solved using the shooting method for the postbuckling load and the buckled shape. By comparing with the classical postbuckling solutions, the sensitivity of the small length scale effect on the buckling load and buckled shape may be observed. It is found that the small length scale effect decreases the postbuckling load and increases the deflection of the rod.
Analysis of histone antibody specificity directly in sequencing data using siQ-ChIP

We previously developed sans spike-in quantitative chromatin immunoprecipitation sequencing (siQ-ChIP), a technique that introduces an absolute quantitative scale to ChIP-seq data without reliance on spike-in normalization approaches. The physical model of siQ-ChIP predicted that the IP step of ChIP would produce a classical binding isotherm when antibody or epitope was titrated. Here, we define experimental conditions in which this titration is observable for antibodies that recognize modified states of histone proteins. We show that minimally sequenced points along an isotherm can reveal differential binding specificities that are associated with on- and off-target epitope interactions. This work demonstrates that the interpretation of histone post-translational modification distribution from ChIP-seq data has a dependence on antibody concentration. Collectively, these studies introduce a simplified and reproducible experimental method to generate quantitative ChIP-seq data without spike-in normalization and demonstrate that histone antibody specificity can be analyzed directly in ChIP-seq experiments.
Comparative Genomics of Firmicutes reveals probable adaptations for xylose fermentation in Thermoanaerobacterium saccharolyticum

Second-generation (2G) ethanol is one potential biofuel that could be used to achieve the goal of reducing greenhouse gas emissions. Many challenges still need to be overcome for the feasibility of this technology, most of them related to consumption of xylose, a pentose sugar not easily metabolized by industrial microorganisms. Thus, exploring genes, pathways and other organisms that can ferment xylose is a strategy implemented to solve industrial bottlenecks. Thermoanaerobacterium saccharolyticum (T. sac) is an organism from the firmicutes phylum, capable of naturally fermenting compounds of industrial interest, such as xylan and xylose. Understanding evolutionary adaptations may help not only to solidify this bacterium as a potential substitute to the yeast Saccharomyces cerevisiae in industry, but also bring novel genes and information that can be used for yeast, enhance its fermenting capabilities, and increase production of current bio-platforms. This study presents a deep evolutionary study of members of the firmicutes clade, focusing on adaptations that may be related to overall fermentation metabolism, especially for xylose fermentation. One highlight is the finding of positive selection on a xylose binding protein of the xylFGH operon, close to the annotated sugar binding site, with this protein already being found to be expressed in xylose fermenting conditions in a previous study. Results from this study can serve as basis for searching for candidate genes to use in industrial strains or to improve T. sac as a new microbial cell factory, which may help to solve current problems found in the biofuels industry.
Top-down, auditory pallial regulation of the social behavior network

Social encounters rely on sensory cues that carry nuanced information to guide social decision-making. While high-level features of social signals are processed in the telencephalic pallium, nuclei controlling social behaviors, called the social behavior network (SBN), reside mainly in the diencephalon. Although it is well known how mammalian olfactory pallium interfaces with the SBN, there is little information for how pallial processing of other sensory modalities can modulate SBN circuits. This is surprising given the importance of complex vocalizations, for example, for social behavior in many vertebrate taxa such as humans and birds. Using gregarious and highly vocal songbirds, female Zebra finches, we asked to what extent auditory pallial circuits provide consequential input to the SBN as it processes social sensory cues. We transiently inactivated auditory pallium of female Zebra finches during song playback and examined song-induced activation in SBN nuclei. Auditory pallial inactivation impaired responses to song specifically within the lateral ventromedial nucleus of the hypothalamus (VMHl), providing the first evidence in vertebrates of a connection between auditory pallium and the SBN. This same treatment elevated feeding behavior, which also correlated with VMHl activation. This suggests that signals from auditory pallium to VMHl can tune the balance between social attention and feeding drive. A descending influence of sensory pallium on hypothalamic circuits could therefore provide a functional connection for the integration of social stimuli with internal state to influence social decision-making. Significance Sensory cues such as vocalizations contain important social information. These social signals can be substantially nuanced, containing information about vocalizer identity, prior experience, valence, and emotional state. Processing these features of vocalizations necessitates processing the fast, complex sound streams in song or speech, which depends on circuits in pallial cortex. But whether and how this information is then transferred to social circuits in limbic and hypothalamic regions remains a mystery. Here, we identify a top-down influence of the songbird auditory pallium on one specific node of the social behavior network within the hypothalamus. Descending functional connections such as these may be critical for the wide range of vertebrate species that rely on intricate sensory communication signals to guide social decision-making.
Caudal Fgfr1 disruption produces localised spinal mis-patterning and a terminal myelocystocele-like phenotype in mice

Closed spinal dysraphisms are poorly understood neurodevelopmental malformations commonly classed as neural tube defects. Several, including terminal myelocystocele, selectively affect the distal lumbosacral spine. We previously identified a neural tube closure-initiating point, Closure 5, involved in forming the distal spine of mice. Here we document equivalent morphology of the caudal-most end of the closing posterior neuropore (PNP) in mice and humans, suggesting Closure 5 is conserved in humans. It forms in a region of active fibroblast growth factor (FGF) signalling and pharmacological blockade of FGF receptors (Fgfr) impairs Closure 5 formation in cultured mouse embryos. Conditional genetic deletion of Fgfr1 in caudal embryonic tissues with Cdx2Cre similarly impairs Closure 5 formation and leads to morphologically abnormal PNPs, which nonetheless achieve delayed closure although delayed. After PNP closure, a localised region of the distal neural tube of Fgfr1-disrupted embryos re-opens into a trumpet-like flared central canal between the presumptive hindlimbs, progressing to form a distal fluid-filled sac overlying ventrally flattened spinal cord. This phenotype resembles terminal myelocystocele. Histological analysis of spinal progenitor domains reveals regional and progressive loss of ventral spinal cord progenitor domains preceding cystic dilation of the central canal. Initially, the Shh and FoxA2-positive ventral domains are lost, resulting in Olig2-labelling of the ventral-most neural tube. The Olig2-domain is also subsequently lost, eventually producing a neural tube entirely positive for the dorsal marker Pax3. Thus, a terminal myelocystocele-like phenotype can arise after completion of neural tube closure due to localised spinal mis-patterning caused by disruption of Fgfr1 signalling.
Structural basis for differential p19 targeting by IL-23 biologics

Background IL-23 is central to the pathogenesis of psoriasis, and is structurally comprised of p19 and p40 subunits. “Targeted” IL-23 inhibitors risankizumab, tildrakizumab, and guselkumab differ mechanistically from ustekinumab because they bind p19, whereas ustekinumab binds p40; however, a knowledge gap exists regarding the structural composition of their epitopes and how these molecular properties relate to their clinical efficacy. Objectives To characterize and differentiate the structural epitopes of the IL-23 inhibitors risankizumab, guselkumab, tildrakinumab, and ustekinumab, and correlate their molecular characteristics with clinical response in plaque psoriasis therapy. Methods We utilized epitope data derived from hydrogen-deuterium exchange studies for risankizumab, tildrakizumab, and guselkumab, and crystallographic data for ustekinumab to map drug epitope locations, hydrophobicity, and surface charge onto the IL-23 molecular surface (Protein Data Bank ID Code 3D87) using UCSF Chimera. PDBePISA was used to calculate solvent accessible surface area (SASA). Epitope composition was determined by classifying residues as acidic, basic, polar, or hydrophobic and calculating their contribution to epitope SASA. Linear regression and analysis of variance was performed. Results All the p19-specific inhibitor epitopes differ in location and size, with risankizumab and guselkumab having large epitope surface areas (SA), and tildrakizumab and ustekinumab having smaller SA. The tildrakizumab epitope was mostly hydrophobic (56%), while guselkumab, risankizumab, and ustekinumab epitopes displayed >50% non-hydrophobic residues. Risankizumab and ustekinumab exhibited acidic surface charges, while tildrakizumab and guselkumab were net neutral. Each inhibitor binds an epitope with a unique size and composition, and with mostly distinct locations except for a 10-residue overlap region that lies outside of the IL-23 receptor epitope. We observed a strong correlation between epitope SA and PASI-90 rates (R2 = 0.9969, p = 0.0016), as well as between epitope SA and KD (R2 = 0.9772, p = 0.0115). In contrast, we found that total epitope hydrophobicity, polarity, and charge content do not correlate with clinical efficacy. Conclusions Structural analysis of IL-23 inhibitor epitopes reveals strong association between epitope SA and early drug efficacy in plaque psoriasis therapy, exemplifying how molecular data can explain clinical observations, inform future innovation, and help clinicians in specific drug selection for patients.