Miracle-dz/UniFAR-FTUs huggingface dataset:
Endotaxis: A neuromorphic algorithm for mapping, goal-learning, navigation, and patrolling

An animal entering a new environment typically faces three challenges: explore the space for resources, memorize their locations, and navigate towards those targets as needed. Experimental work on exploration, mapping, and navigation has mostly focused on simple environments – such as an open arena [68], a pond [42], or a desert [44] – and much has been learned about neural signals in diverse brain areas under these conditions [12, 54]. However, many natural environments are highly structured, such as a system of burrows, or of intersecting paths through the underbrush. Similarly, for many cognitive tasks, a sequence of simple actions can give rise to complex solutions. Here we propose an algorithm that learns the structure of a complex environment, discovers useful targets during exploration, and navigates back to those targets by the shortest path. It makes use of a behavioral module common to all motile animals, namely the ability to follow an odor to its source [4]. We show how the brain can learn to generate internal “virtual odors” that guide the animal to any location of interest. This endotaxis algorithm can be implemented with a simple 3-layer neural circuit using only biologically realistic structures and learning rules. Several neural components of this scheme are found in brains from insects to humans. Nature may have evolved a general mechanism for search and navigation on the ancient backbone of chemotaxis.
Identiﬁcation of Bacteriophages Using Deep Representation Model with Pre-training

Bacteriophages/Phages are viruses that infect and replicate within bacteria and archaea. Antibiotic resistance is one of the biggest threats to global health. The therapeutic use of bacteriophages provides another potential solu-tion for solving antibiotic resistance. To develop phage therapies, the identiﬁcation of phages from metagenome sequences is the fundamental step. Currently, several methods have been developed for identifying phages. These methods can be categorized into two types: database-based methods and alignment-free methods. The database-based approach, such as VIBRANT, utilizes existing databases and compares sequence similarity between candidates and those in the databases. The alignment-free method, such as Seeker and DeepVirFinder, uses deep learning models to directly predict phages based on nucleotide sequences. Both approaches have their advantages and disadvantages. In this work, we propose using a deep representation learning model with pre-training to integrate the database-based and non-alignment-based methods (we call it INHERIT). The pre-training is used as an alternative way for acquiring knowledge representations from existing databases, while the BERT-style deep learning framework retains the advantage of alignment-free methods. We compared the proposed method with VIBRANT and Seeker on a third-party benchmark dataset. Our experiments show that INHERIT achieves better performance than the database-based approach and the alignment-free method, with the best F1-score of 0.9868. Meanwhile, we demonstrated that using pre-trained models helps to improve the non-alignment deep learning model further.
DcPAR1 is Required for Development and Carotenoid Synthesis in the Dark-Grown Carrot Taproot

Light stimulates carotenoid synthesis in plants during photomorphogenesis through the expression of PHYTOENE SYNTHASE (PSY), a key gene in carotenoid biosynthesis. The orange Daucus carota (carrot) synthesizes and accumulates high amounts of carotenoids in the taproot that grows underground. Contrary to other organs, light impairs carrot taproot development and represses the expression of carotenogenic genes such as DcPSY1 and DcPSY2 reducing carotenoid accumulation. By means of an RNA-seq, in previous analysis we observed that carrot PHYTOCHROME RAPIDLY REGULATED 1 (DcPAR1) is more expressed in the underground grown taproot respect to those grown in light. PAR1 is a transcriptional cofactor with a negative role in the shade avoidance syndrome regulation in Arabidopsis thaliana through the dimerization with PHYTOCHROME INTERACTING FACTORs (PIFs), allowing a moderate synthesis of carotenoids. Here we show that overexpressing AtPAR1 in carrot produces an increment of carotenoids in taproots grown underground as well as higher DcPSY1 expression. The high identity of AtPAR1 and DcPAR1 let us to suggest a functional role of DcPAR1 that was verified through the in vivo binding to AtPIF7 and the overexpression in Arabidopsis, where it increments AtPSY expression and carotenoid accumulation together with a photomorphogenic phenotype. Finally, DcPAR1 antisense carrot lines presented a dramatic decrease in carotenoids levels and in the relative expression of key carotenogenic genes as well as impairment in taproot development. These results let us to propose that DcPAR1 is a key factor for secondary root development, plastid differentiation and carotenoid synthesis in carrot taproot grown underground. One-sentence summary DcPAR1 is a key factor for secondary root development, plastid differentiation and carotenoid synthesis in carrot taproot grown underground.
Antibacterial and Antibiofouling Properties of Light Triggered Fluorescent Hydrophobic Carbon Quantum Dots Langmuir–Blodgett Thin Films

Inimitable properties of carbon quantum dots as well as a cheap production contribute to their possible application in biomedicine especially as antibacterial and antibiofouling coatings. Fluorescent hydrophobic carbon quantum dots are synthesized by bottom-up condensation method and used for deposition of uniform and homogeneous Langmuir–Blodgett thin films on different substrates. It is found that this kind of quantum dots generates singlet oxygen under blue light irradiation. Antibacterial and antibiofouling testing on four different bacteria strains (Escherichia coli, Staphylococcus aureus, Bacillus cereus, and Pseudomonas aeruginosa) reveals enhanced antibacterial and antibiofouling activity of hydrophobic carbon dots thin films under blue light irradiation. Moreover, hydrophobic quantum dots show noncytotoxic effect on mouse fibroblast cell line. These properties enable potential usage of hydrophobic carbon quantum dots thin films as excellent antibacterial and antibiofouling coatings for different .
Maturyoshka: a maturase inside a maturase, and other peculiarities of the novel chloroplast genomes of marine euglenophytes

Organellar genomes often carry group II introns, which occasionally encode proteins called maturases that are important for splicing. The number of introns varies substantially among various organellar genomes, and bursts of introns have been observed in multiple eukaryotic lineages, including euglenophytes, with more than 100 introns in their plastid genomes. To examine the evolutionary diversity and history of maturases, an essential gene family among euglenophytes, we searched for their homologs in newly sequenced and published plastid genomes representing all major euglenophytes’ lineages. We found that maturase content in plastid genomes has a patchy distribution, with a maximum of eight of them present in Eutreptiella eupharyngea. The most basal lineages of euglenophytes, Eutreptiales, share the highest number of maturases, but the lowest number of introns. We also identified a peculiar convoluted structure of a gene located in an intron, in a gene within an intron, within yet another gene, present in some Eutreptiales. Further investigation of functional domains of identified maturases shown that most of them lost at least one of the functional domains, which implies that the patchy maturase distribution is due to frequent inactivation and eventual loss over time. Finally, we identified the diversified evolutionary origin of analysed maturases, which were acquired along with the green algal plastid or horizontally transferred. These findings indicate that euglenophytes’ plastid maturases have experienced a surprisingly dynamic history due to gains from diversified donors, their retention, and loss.
Control of subunit stoichiometry in single-chain MspA nanopores

Transmembrane protein channels enable fast and highly sensitive electrical detection of single molecules. Nanopore sequencing of DNA was achieved using an engineered Mycobacterium smegmatis porin A (MspA) in combination with a motor enzyme. Due to its favorable channel geometry, the octameric MspA pore exhibits the highest current level as compared to other pore proteins. To date, MspA is the only protein nanopore with a published record of DNA sequencing. While widely used in commercial devices, nanopore sequencing of DNA suffers from significant base-calling errors due to stochastic events of the complex DNA-motor-pore combination and the contribution of up to five nucleotides to the signal at each position. Asymmetric mutations within subunits of the channel protein offer an enormous potential to improve nucleotide resolution and sequencing accuracy. However, random subunit assembly does not allow control of the channel composition of MspA and other oligomeric protein pores. In this study, we showed that it is feasible to convert octameric MspA into a single-chain pore by connecting eight subunits using peptide linkers. We constructed single-chain MspA trimers, pentamers, hexamers and heptamers to demonstrate that it is feasible to alter the subunit stoichiometry and the MspA pore diameter. All single-chain MspA proteins formed functional channels in lipid bilayer experiments. Importantly, we demonstrated that single-chain MspA discriminated all four nucleotides identical to MspA produced from monomers. Thus, single-chain MspA constitutes a new milestone in its development and adaptation as a biosensor for DNA sequencing and many other applications. STATEMENT OF SIGNFICANCE Nanopore sequencing of DNA is a fast and cheap technology that uniquely delivers multi-kilobase reads. It is currently used world-wide in many applications such as genome sequencing, epigenetics, and surveillance of viral and bacterial pathogens and has started to revolutionize human lives in medicine, agriculture and environmental studies. However, the high base-calling error rates prevent nanopore DNA sequencing from reaching its full potential. In this study, we converted octameric MspA into a single-chain pore enabling asymmetric mutations to fine-tune the pore geometry and chemistry and address the shortcomings of nanopores. Thus, single-chain MspA constitutes a new milestone in its development and adaptation as a biosensor for DNA sequencing and many other applications.
Dissection of function and recognition mechanism of M. tuberculosis ESX-1 secreted virulence factor EspC

Mycobacterium tuberculosis uses the ESAT-6 system-1/type VII (ESX-1) system for secretion of virulence proteins into the host cell, however the mechanism of virulence proteins secretion, molecular components and regulation of ESX-1 system are only partly understood. In the current study, we have analyzed the biological function and recognition mechanism between ESX-1 virulence EspC and EccA1 ATPase proteins. The EspC enters into A549 human lung carcinoma cells and exhibited cytotoxicity, as observed in MTT Assay. To understand the recognition mechanism between EspC and EccA1 ATPase, the EspC and EccA1 mutants were generated based on EspC~EccA1 interactions, as observed in molecular modeling. Binding analysis shows that EspC export arm interacts specifically to the β-hairpin insertion motif of the TPR domain of EccA1 ATPase. Mutations in these epitopes lead to significant decrease/or abolish the binding between EspC and EccA1 ATPase. Our study provides insight into biological function and recognition mechanism between EspC and EccA1 ATPase, which can be used as target to prevent EspC secretion/ or in general virulence factor secretion by mycobacterial ESX-1 system.
Coding sequence-independent homology search identifies highly divergent homopteran putative effector gene family

Many genomes contain rapidly evolving and highly divergent genes whose homology to genes of known function often cannot be determined from sequence similarity alone. However, coding sequence-independent features of genes, such as intron-exon boundaries, often evolve more slowly than coding sequences and can provide complementary evidence for homology. We found that a linear logistic regression classifier using only structural features of rapidly evolving bicycle aphid effector genes identified many putative bicycle homologs in aphids, phylloxerids, and scale insects, whereas sequence similarity search methods yielded few homologs in most aphids and no homologs in phylloxerids and scale insects. Subsequent examination of sequence features and intron locations supported homology assignments. Differential expression studies of newly-identified bicycle homologs, together with prior proteomic studies, support the hypothesis that BICYCLE proteins act as plant effector proteins in many aphid species and perhaps also in phylloxerids and scale insects.
Estimating Rényi's α-Cross-Entropies in a Matrix-Based Way

Conventional information-theoretic quantities assume access to probability distributions. Estimating such distributions is not trivial. Here, we consider function-based formulations of cross entropy that sidesteps this a priori estimation requirement. We propose three measures of R\'enyi's $\alpha$-cross-entropies in the setting of reproducing-kernel Hilbert spaces. Each measure has its appeals. We prove that we can estimate these measures in an unbiased, non-parametric, and minimax-optimal way. We do this via sample-constructed Gram matrices. This yields matrix-based estimators of R\'enyi's $\alpha$-cross-entropies. These estimators satisfy all of the axioms that R\'enyi established for divergences. Our cross-entropies can thus be used for assessing distributional differences. They are also appropriate for handling high-dimensional distributions, since the convergence rate of our estimator is independent of the sample dimensionality. Python code for implementing these measures can be found at https://github.com/isledge/MBRCE
Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat (Triticum aestivum L.)

Stripe rust is one of the most destructive diseases of wheat (Triticum aestivum L.), caused by Puccinia striiformis f. sp. tritici (Pst), and responsible for significant yield losses worldwide. Single-nucleotide polymorphism (SNP) diagnostic markers were used to identify new sources of resistance at adult plant stage to wheat stripe rust (YR) in 141 CIMMYT advanced bread wheat lines over 3 years in replicated trials at Borlaug Institute for South Asia (BISA), Ludhiana. We performed a genome-wide association study and genomic prediction to aid the genetic gain by accumulating disease resistance alleles. The responses to YR in 141 advanced wheat breeding lines at adult plant stage were used to generate G × E (genotype × environment)-dependent rust scores for prediction and genome-wide association study (GWAS), eliminating variation due to climate and disease pressure changes. The lowest mean prediction accuracies were 0.59 for genomic best linear unbiased prediction (GBLUP) and ridge-regression BLUP (RRBLUP), while the highest mean was 0.63 for extended GBLUP (EGBLUP) and random forest (RF), using 14,563 SNPs and the G × E rust score results. RF and EGBLUP predicted higher accuracies (∼3%) than did GBLUP and RRBLUP. Promising genomic prediction demonstrates the viability and efficacy of improving quantitative rust tolerance. The resistance to YR in these lines was attributed to eight quantitative trait loci (QTLs) using the FarmCPU algorithm. Four (Q.Yr.bisa-2A.1, Q.Yr.bisa-2D, Q.Yr.bisa-5B.2, and Q.Yr.bisa-7A) of eight QTLs linked to the diagnostic markers were mapped at unique loci (previously unidentified for Pst resistance) and possibly new loci. The statistical evidence of effectiveness and distribution of the new diagnostic markers for the resistance loci would help to develop new stripe rust resistance sources. These diagnostic markers along with previously established markers would be used to create novel DNA biosensor-based microarrays for rapid detection of the resistance loci on large panels upon functional validation of the candidate genes identified in the present study to aid in rapid genetic gain in the future breeding programs.
Crosstalk Between Abnormal TSHR Signaling Activation and PTEN/PI3K in the Dedifferentiation of Thyroid Cancer Cells

Iodide uptake and the metabolism of thyroid cells are regulated by thyrotropin (TSH)-TSH receptor (TSHR) signaling. Thus, it is necessary to elevate serum TSH levels by T4 withdraw or rTSH administration to facilitate radioiodide (131I) therapy for differentiated thyroid cancer (DTC). However, non-iodide-avid metastases of DTC which is dedifferentiated do not respond to stimulation by high levels of TSH, suggesting abnormal TSH-TSHR signal transduction in cancer cells. In addition, PI3K/AKT/mTOR signaling activation has been shown to be associated with the dedifferentiated phenotype of thyroid cancer, but the mechanism remains elusive. Therefore, in this study, we aimed to explore the role of abnormal TSH-TSHR signaling activation in regulating iodide uptake and cell mobility in thyroid cancer and its relationship with PI3K/AKT/mTOR signaling. We found that in thyroid cancer cells, TSH binds TSHR coupled to the Gα12/13 protein and then activates RhoA through interacting with leukemia associated RhoA guanine exchange factor (LARG). This results in a promigration tumorigenic phenotype independent of canonical TSHR-GαS signaling that regulates the expression of molecules involved in iodine uptake and metabolism. We observed that signaling pathways downstream of Gα12/13 signaling were increased, while that of Gαs signaling was decreased in thyroid cancer cells undergoing dedifferentiation compared to control cells following stimulation with different levels of TSH. PI3K/AKT/mTOR signaling activation enhanced Gα12/13 signaling through increasing LARG levels but also inhibited the expression of molecules downstream of Gαs signaling, including thyroid-specific molecules, and iodide uptake. In summary, our results demonstrate the noncanonical activation of TSH-TSHR signaling and its role in increasing the cell mobility and dedifferentiation of thyroid cancer through crosstalk with PI3K/AKT/mTOR signaling.
Functional Brain Imaging During Extra-Ocular Light Stimulation in Anophthalmic and Sighted Participants: No Evidence for Extra-Ocular Photosensitive Receptors

Light plays a critical role in regulating physiology and behavior, including both visual and non-visual responses. In mammals, loss of both eyes abolishes all of these responses, demonstrating that the photoreceptors involved are exclusively ocular. By contrast, many non-mammalian species possess extra-ocular photoreceptors located in the pineal complex and deep brain. Whilst there have been suggestions of extra-ocular photoreception in mammals, including man, evidence for these photoreceptors is limited. One approach to objectively determine the presence of such receptors is to measure brain responses to light using functional magnetic resonance imaging (fMRI). Moreover, by using participants who are clinically anophthalmic (congenital and acquired), it is possible to investigate potential light detection in the absence of the retina. Here we scanned participants with anophthalmia and sighted participants in 4 different conditions; the first 3 conditions had a bright light source applied to the following locations: behind the right ear (“ear”), just below the nasal bridge and between the eyes (“head”), and at the right popliteal fossa (“knee”). In the fourth and final scan, the light source was switched off so that there was no light stimulus. All participants were scanned in a completely dark room. No consistent brain activity was detected during any of the light conditions in either sighted controls or anophthalmic participants. Thus, we do not provide any evidence for the presence of extraocular photoreceptors modulating human brain activity, despite recent evidence for gene transcription that may occur as a result of these photoreceptors.
Rewards of Compassion: Dispositional Compassion Predicts Lower Job Strain and Effort-Reward Imbalance Over a 11-Year Follow-Up

Dispositional compassion has been shown to predict higher well-being and to be associated with lower perceived stress and higher social support. Thus, compassion may be a potential individual factor protecting from job strain. The current study examines (i) whether dispositional compassion predicts job strain and effort-reward imbalance (ERI) or does the predictive relationship run from job strain and ERI to dispositional compassion and (ii) the effect of dispositional compassion on the developmental trajectory of job strain and ERI over a 11-year follow-up. We used data from the Young Finns study (n=723) between 2001 and 2012. The direction of the predictive relationships was analyzed with cross-lagged panel models. Compassion’s effect on the trajectories of job strain, ERI, and their components was examined with multilevel models. First, the cross-lagged panel models demonstrated there was no evidence for the predictive pathways between compassion and job strain or its components. However, the predictive pathways from high dispositional compassion to low ERI and high rewards had better fit to the data than the predictive pathways in the opposite direction. In addition, multilevel models showed that high compassion predicted various job characteristics from early adulthood to middle age (lower job strain and higher job control as well as lower ERI and higher reward). Compassion did not predict job demand/effort. The findings were obtained independently of age, gender, and socioeconomic factors in childhood and adulthood. These findings indicate that compassion may be beneficial in work context. Further, compassion might be useful in the management or prevention of some aspects of strain. Our study provides new insight about the role of compassion in work life.