Miracle-dz/UniFAR-FTUs huggingface dataset:
Peptide mediated, enhanced toxicity of a bacterial pesticidal protein against southern green stink bug

The damage caused by stink bugs that feed on agricultural crops accounts for such significant losses that transgenic plant resistance to stink bugs would be highly desirable. As the level of toxicity of the Bacillus thuringiensis‐derived, ETX/Mtx2 pesticidal protein Mpp83Aa1 is insufficient for practical use against the southern green stink bug Nezara viridula, we employed two disparate approaches to isolate peptides NvBP1 and ABP5 that bind to specific proteins (alpha amylase and aminopeptidase N respectively) on the surface of the N. viridula gut. Incorporation of these peptides into Mpp83Aa1 provided artificial anchors resulting in increased gut binding, and enhanced toxicity. These peptide‐modified pesticidal proteins with increased toxicity provide a key advance for potential future use against N. viridula when delivered by transgenic plants to mitigate economic loss associated with this important pest.
Gray and White Matter Changes Associated with Psychophysical Functions Induced by Diabolo Training in Young Men

Learning a skill has been demonstrated to relate to neural plasticity in both animal and human brains. Performing diabolo consists of different tricks and may cause brain structural changes associated with psychophysical functions. Therefore, the purpose of this study was to investigate gray matter (GM) and white matter (WM) changes associated with psychophysical functions induced by diabolo training in healthy subjects. Fourteen healthy right-handed male subjects were enrolled to receive the diabolo training. Whole brain T1-weighted images and diffusion tensor imaging (DTI) data were acquired from all subjects on a 3.0 T magnetic resonance scanner before and after the training. Voxel-based morphometry (VBM), surface-based morphometry (SBM), and voxel-wise DTI analysis were carried out to detect the GM volume, cortical thickness, and WM diffusion changes using T1-weighted image and DTI data, respectively. In addition, two-arm coordination and mirror-drawing tests were performed to evaluate their psychophysical functions before and after 2, 4, 6 and 8 weeks of training. Analysis of variance was performed to understand whether the psychophysical functions changed over time after the training. The results showed that the psychophysical functions were significantly changed over time during the training. The VBM and SBM analyses revealed that the GM volume and cortical thickness were significantly increased in the brain areas associated with visual, motor, sensory, and spatial cognition functions. The voxel-wise DTI analysis further demonstrated that the mean diffusivity was significantly reduced in the genu of corpus callosum. Moreover, significant correlations were revealed between the increase rate of GM volume and the improvement rate of psychophysical functions in the left angular gyrus. The results suggest that the diabolo training may induce increased GM volume associated with improved psychophysical function in the brain region involved in spatial cognition and attention. Therefore, we conclude that the diabolo training may improve psychophysical function which might be reflected by the increased GM volume in the angular gyrus.
In silico design of a novel nucleotide antiviral agent by free energy perturbation

Nucleoside analogs are the backbone of antiviral therapies. Drugs from this class undergo processing by host or viral kinases to form the active nucleoside triphosphate species that selectively inhibits the viral polymerase. It is the central hypothesis that the nucleoside triphosphate analog must be a favorable substrate for the viral polymerase and the nucleoside precursor must be a satisfactory substrate for the host kinases to inhibit viral replication. Herein, free energy perturbation (FEP) was used to predict substrate affinity for both host and viral enzymes. Several uridine 5’‐monophosphate prodrug analogs known to inhibit hepatitis C virus (HCV) were utilized in this study to validate the use of FEP. Binding free energies to the host monophosphate kinase and viral RNA‐dependent RNA polymerase (RdRp) were calculated for methyl‐substituted uridine analogs. The 2’‐C‐methyl‐uridine and 4’‐C‐methyl‐uridine scaffolds delivered favorable substrate binding to the host kinase and HCV RdRp that were consistent with results from cellular antiviral activity in support of our new approach. In a prospective evaluation, FEP results suggest that 2’‐C‐dimethyl‐uridine scaffold delivered favorable monophosphate and triphosphate substrates for both host kinase and HCV RdRp, respectively. Novel 2’‐C‐dimethyl‐uridine monophosphate prodrug was synthesized and exhibited sub‐micromolar inhibition of HCV replication. Using this novel approach, we demonstrated for the first time that nucleoside analogs can be rationally designed that meet the multi‐target requirements for antiviral activity.
Posterior parietal cortex predicts upcoming movement in dynamic sensorimotor control

Significance Most studies in sensorimotor neurophysiology have utilized reactive movements to stationary goals pre-defined by sensory cues, but this approach is fundamentally incapable of determining whether the observed neural activity reflects current sensory stimuli or predicts future movements. In the present study, we recorded single-neuron activity from behaving monkeys engaged in a dynamic, flexible, stimulus-response contingency task that enabled us to distinguish activity co-varying with sensory inflow from that co-varying with motor outflow in the posterior parietal cortex.
A comparative study on the stability of the furfural molecule on the low index Ni, Pd and Pt surfaces

We present a comparative density functional theory investigation of the furfural (Ff) molecule on the low index Ni, Pd and Pt surfaces to understand its geometrical and electronic properties to gain mechanistic insights into the experimentally measured catalytic reactivities of these metal catalysts. We show that the number of metal d-states, which hybridize with the nearest C and O p-orbitals of the Ff molecule, can be used to explain the stability of the Ff molecule on these surfaces. We find that the hybridization between atoms with higher electronegativity and the metal d-states plays a crucial role in determining the stability of these systems. Furthermore, we also find electron transfer from metal to the Ff molecule on the Ni and Pd surfaces, with a reverse process occurring on the Pt surface.
Multi-disciplinary Modeling and Collaborative Simulation of Hydraulic Gauge Control System of Rolling Mill Based on ADAMS

The HGC system of 1676 mm tandem cold rolling mill from Bensteel cold rolling plant was studied, and the executing mechanism model of HGC system including hydraulic systems was built. Based on the theory of multi-domain modeling and collaborative simulation, the Simulink model of control system was integrated using the interface of ADAMS/Controls, and a function model of HGC system which was relatively complete was built. Compared with the deviation curve of the outlet thickness gained from the monitor-control system on-line, the roller gap curve of the model dovetailed nicely with the reality, which approved the accuracy of the model building and the rationality of the model simplify. Through the collaborative simulation, the adjustment means of PI controller parameters was gained under the positioning control, which tally closely with the values of PI controller parameters in the large cold rolling mill, approving the reliability of the HGC system model based on collaborative simulation.
A comparison of fecal sac removal rates of male and female Carolina Chickadees (Poecile carolinensis)

ABSTRACT Parent songbirds keep their nests clean by removing nestling waste in the form of fecal sacs. Removing fecal sacs is beneficial for the nestlings but energetically costly for the parents. The purpose of our research was to determine whether there was a difference in energy spent on fecal sac removal between male and female Carolina Chickadees (Poecile carolinensis). We collected data for this project at St. Anne Woods and Wetlands in Melbourne, Kentucky, where we made a total of 215 one-hour observations of 30 different nests. For each color-banded parent, we calculated both the number of fecal sac removals and the number of removals divided by the total number of nest visits per hour. Our results showed that males removed more fecal sacs per hour than females. However, this was only because they visited the nest more frequently, as the number of fecal sac removal visits per provisioning visit was the same between the sexes. This suggests that parental energy invested in fecal sac removal is closely tied to their investment in nestling provisioning visits.
Plant community responses to kudzu (Pueraria montana) invasion in a southern upland forest

Abstract. Kudzu (Pueraria montana (Lour.) Merr. var. lobata (Willd.)) has long been regarded as one of the most destructive invasive species in temperate forests. Despite this, little is known about the specific impacts of kudzu on native plant communities. In this study we compared plant communities of mixed pine-oak forest sites in Mississippi infested with kudzu to those in uninvaded sites,and asked if kudzu generally suppresses the plant community or has unequal effects on species differing in weediness, shade tolerance, or growth form. At each site we determined species richness; percentage of cover of understory species; density of large trees, saplings, and seedlings; and species composition of sample plots. Kudzu-invaded sites had lower species richness, less understory cover, and lower density of woody species than control sites. Species persisting in kudzu-invaded sites were a subset of species found in control sites, and persistence was unrelated to growth form, weediness, or shade tolerance. Both light limitation and nitrogen fixation by kudzu may be related to these results but further study will be required to evaluate their relative impact on kudzu-invaded communities.
SignDS-FL: Local Differentially Private Federated Learning with Sign-based Dimension Selection

Federated Learning (FL) [31] is a decentralized learning mechanism that has attracted increasing attention due to its achievements in computational efficiency and privacy preservation. However, recent research highlights that the original FL framework may still reveal sensitive information of clients’ local data from the exchanged local updates and the global model parameters. Local Differential Privacy (LDP), as a rigorous definition of privacy, has been applied to Federated Learning to provide formal privacy guarantees and prevent potential privacy leakage. However, previous LDP-FL solutions suffer from considerable utility loss with an increase of model dimensionality. Recent work [29] proposed a two-stage framework that mitigates the dimension-dependency problem by first selecting one “important” dimension for each local update and then perturbing the dimension value to construct the sparse privatized update. However, the framework may still suffer from utility loss because of the insufficient per-stage privacy budget and slow model convergence. In this article, we propose an improved framework, SignDS-FL, which shares the concept of dimension selection with Reference [29], but saves the privacy cost for the value perturbation stage by assigning random sign values to the selected dimensions. Besides using the single-dimension selection algorithms in Reference [29], we propose an Exponential Mechanism-based Multi-Dimension Selection algorithm that further improves model convergence and accuracy. We evaluate the framework on a number of real-world datasets with both simple logistic regression models and deep neural networks. For training logistic regression models on structured datasets, our framework yields only a \( \sim \) 1%–2% accuracy loss in comparison to a \( \sim \) 5%–15% decrease of accuracy for the baseline methods. For training deep neural networks on image datasets, the accuracy loss of our framework is less than \( 8\% \) and at best only \( 2\% \) . Extensive experimental results show that our framework significantly outperforms the previous LDP-FL solutions and enjoys an advanced utility-privacy balance.
A Novel Social Interaction Assistive Device for Arab Deaf People

Many deaf people worldwide face problems with integrating into society and interacting with people who do not understand sign language. This can lead to isolation and difficulty in expressing feelings. In this research, our primary goal is to help deaf people communicate, express their feelings, and socialize with others. Toward that end, 40 Arabic words that are commonly used in social interactions were used to build a dataset of hand movements used by deaf people to express these words. These movements were recorded using a Leap Motion Controller (LMC). The resulting dataset consists of 1,579 instances and 112 features, recorded with the help of five deaf persons. Feature reduction and oversampling techniques were applied to analyze the dataset. Machine learning algorithms were then used to build a model that is able to classify any given hand posture or gesture into one of those 40 words. This work compared the performance of nine classification algorithms: Random Forest, Decision Table, Classification via Regression, K-Nearest Neighbor (KNN), Simple Logistic, Input Mapped Classifier, Random Tree, J48, and Bayes network. Results show that the Random Forest model achieved the highest accuracy with over 90%, outperforming the other eight models. Subsequently, a usability study was conducted by 10 deaf people to test the effectiveness of the proposed assistive device. The results suggest that the proposed device is useful for facilitating social communication with deaf people. It also suggests that the device was preferred, when compared with other relevant devices.
Gray-Box Shilling Attack: An Adversarial Learning Approach

Recommender systems are essential components of many information services, which aim to find relevant items that match user preferences. Several studies have shown that shilling attacks can significantly weaken the robustness of recommender systems by injecting fake user profiles. Traditional shilling attacks focus on creating hand-engineered fake user profiles, but these profiles can be detected effortlessly by advanced detection methods. Adversarial learning, which has emerged in recent years, can be leveraged to generate powerful and intelligent attack models. To this end, in this article we explore potential risks of recommender systems and shed light on a gray-box shilling attack model based on generative adversarial networks, named GSA-GANs. Specifically, we aim to generate fake user profiles that can achieve two goals: unnoticeable and offensive. Toward these goals, there are several challenges that we need to address: (1) learning complex user behaviors from user-item rating data, and (2) adversely influencing the recommendation results without knowing the underlying recommendation algorithms. To tackle these challenges, two essential GAN modules are respectively designed to make generated fake profiles more similar to real ones and harmful to recommendation results. Experimental results on three public datasets demonstrate that the proposed GSA-GANs framework outperforms baseline models in attack effectiveness, transferability, and camouflage. In the end, we also provide several possible defensive strategies against GSA-GANs. The exploration and analysis in our work will contribute to the defense research of recommender systems.
Dynamic play between human N-α-acetyltransferase D and H4-mutant histones: Molecular dynamics study

N-terminal acetyltransferases (NATs) are overexpressed in various cancers. Specifically in lung cancer, human N-α-acetyltransferase D (hNatD) is upregulated and prevents the histone H4 N-terminal serine phosphorylation, leading to the Epithelial-to-mesenchymal transition (EMT) of cancer cells. hNatD facilitates histone H4 N-α-terminal serine acetylation and halts the CK2α-mediated serine phosphorylation. In the present study, we report the effects of four N-terminal mutant (S1C, R3C, G4D and G4S) histone H4 peptides on their bindings with hNatD by employing a molecular dynamics simulation. We also used graph theory-based analyses to understand residue correlation and communication in hNatD under the influence of WT and MT H4 peptides. Results show that S1C, R3C and G4S mutant peptides have significant stability at the catalytic site of hNatD. However, S1C, G4D and G4S peptides disrupt hNatD structure. Additionally, intramolecular hydrogen bond analysis reveals greater stability of hNatD in complex with R3C peptide. Further, intermolecular hydrogen bond analysis of acetyl-CoA with hNatD and its RMSD analysis in five complexes indicate that cofactor has greater stability in WT and R3C complexes. Our findings support previously reported experimental study on impacts of H4 mutations on its hNatD-mediated acetylation catalytic efficiency. The Betweenness centrality (BC) analysis further gives insight into the hNatD residue communication dynamics that can be exploited to target hNatD using existed or novel drug candidates therapeutically.
Comparable theta phase coding dynamics along the transverse axis of CA1

Topographical projection patterns from the entorhinal cortex to area CA1 of the hippocampus have led to a hypothesis that proximal CA1 (pCA1, closer to CA2) is spatially more selective than distal CA1 (dCA1, closer to the subiculum). While earlier studies have shown evidence supporting this hypothesis, we recently showed that this difference does not hold true under all experimental conditions. In a complex environment with distinct local texture cues on a circular track and global visual cues, pCA1 and dCA1 display comparable spatial selectivity. Correlated with the spatial selectivity differences, the earlier studies also showed differences in theta phase coding dynamics between pCA1 and dCA1 neurons. Here we show that there are no differences in theta phase coding dynamics between neurons in these two regions under the experimental conditions where pCA1 and dCA1 neurons are equally spatially selective. We also show that dCA1 local field potentials (LFPs) show higher power in theta range compared to pCA1 LFPs. These findings challenge the established notion of dCA1 being inherently less spatially selective and theta modulated than pCA1 and suggest that theta-mediated activation of the CA1 sub-networks to represent space is task-dependent.
Transcellular chaperone signaling is an intercellular stress-response distinct from the HSF-1 mediated HSR

Organismal proteostasis is maintained by intercellular signaling processes including cell nonautonomous stress responses such as transcellular chaperone signaling (TCS). When TCS is activated upon tissue-specific knockdown of hsp-90 in the C. elegans intestine, heat-inducible hsp-70 is induced in muscle cells at the permissive temperature resulting in increased heat stress resistance and lifespan extension. However, our understanding of the molecular mechanism and signaling factors mediating transcellular activation of hsp-70 expression from one tissue to another is still in its infancy. Here we conducted a combinatorial approach using transcriptome RNA-Seq profiling and a forward genetic mutagenesis screen to elucidate how stress-signaling from the intestine to the muscle is regulated. We find that the TCS-mediated “gut-to-muscle” induction of hsp-70 expression is suppressed by HSF-1 and instead relies on transcellular-X-cross-tissue (txt) genes. We identify a key role for the PDZ-domain guanylate cyclase txt-1 and the homeobox transcription factor ceh-58 as signaling hubs in the stress receiving muscle cells to initiate hsp-70 expression and facilitate TCS-mediated heat stress resistance and lifespan extension. Our results provide a new view on cell-nonautonomous regulation of “inter-tissue” stress responses in an organism that highlight a key role for the gut. Our data suggest that the HSF-1-mediated HSR is switched off upon TCS activation, in favor of an intercellular stress-signaling-route to safeguard survival.
A dataset of 5 million city trees: species clustering and climate effects in urban forests

Sustainable cities depend on urban forests. City trees improve our health, clean the air, store CO2, and cool local temperatures. Comparatively less is known about urban forests as ecosystems, particularly their spatial composition, nativity statuses, biodiversity, and tree health. Here, we assembled and standardized a new dataset of N=5,132,890 trees from 63 of the largest US cities with detailed information on location, health, nativity status, and species. We further designed new tools to analyze the ecosystem structure of urban forests, including spatial clustering and abundance of native trees, and validate these tools in comparison to past methods. We show that city trees are significantly clustered by species in 93% of cities, potentially increasing pest vulnerability (even in cities with biodiverse urban forests). Further, non-native species significantly homogenize urban forests across cities, while native trees comprise 0.44%-85.6% (median=45.6%) of city tree populations. Native trees are less frequent in drier cities, and indeed climate significantly shapes both nativity and biodiversity in urban forests. Parks are more biodiverse than urban settings. Compared to past work which focused primarily on canopy cover and species richness, we show the importance of analyzing spatial composition and nativity statuses in urban forests (and we created new datasets and tools to do so). This dataset could be analyzed in combination with citizen-science datasets on bird, insect, or plant biodiversity; social and demographic data; or data on the physical environment. Urban forests offer a rare opportunity to intentionally design biodiverse, heterogenous, rich ecosystems.
Patterns of retrieval-related cortico-striatal connectivity are stable across the adult lifespan

Memory retrieval effects in the striatum are well documented and robust across a number of experimental paradigms and stimulus materials. However, the functional significance of these effects, and whether they are moderated by age, remains unclear. In the present study, we used fMRI paired with an associative recognition task to examine retrieval effects in the striatum in a large sample of healthy young, middle aged, and older adults. We identified anatomically segregated patterns of enhanced striatal BOLD activity during recollection- and familiarity-based memory judgments. Successful recollection was associated with enhanced BOLD activity in bilateral putamen and nucleus accumbens. Familiarity effects were evident in the head of the caudate nucleus bilaterally. Crucially, none of these effects were reliably moderated by age. Using psychophysiological interaction analyses, we observed a monitoring-related increase in functional connectivity between the caudate and regions of the frontoparietal control network, and between the putamen and bilateral retrosplenial cortex and intraparietal sulcus. In all instances, monitoring-related increases in cortico-striatal connectivity were unmoderated by age. These results suggest that the striatum, and the caudate in particular, couples with the frontoparietal control network to support top-down retrieval monitoring operations, and that the integrity of these effects are preserved in advanced age.