Miracle-dz/UniFAR-FTUs huggingface dataset:
The proteome of agroinfiltrated Nicotiana benthamiana is shaped by extensive protein processing

Processing by proteases irreversibly regulates the fate of plant proteins and hampers the production of recombinant protein in plants, yet only few processing events have been described in agroinfiltrated Nicotiana benthamiana, which has emerged as a favorite transient protein expression platform in plant science and molecular pharming. Here, we used in-gel digests and mass spectrometry to monitor the migration and topography of 5,040 plant proteins of agroinfiltrated N. benthamiana within a protein gel. By plotting the peptides over the gel slices, we generated peptographs that reveal where which part of each protein was detected within the protein gel. These data uncovered that 60% of the detected proteins have proteoforms that migrate at lower than predicted molecular weights, implicating extensive proteolytic processing. For instance, this analysis confirms the proteolytic removal and degradation of autoinhibitory prodomains of most but not all proteases, and revealed differential processing within pectinemethylesterase and lipase families. This analysis also uncovered intricate processing of glycosidases and uncovered that ectodomain shedding might be common for a diverse range of receptor-like kinases. Transient expression of double-tagged candidate proteins confirmed various processing events in vivo. This extensive proteomic dataset can be investigated further and demonstrates that most plant proteins are proteolytically processed and implicates an extensive proteolytic machinery shaping the proteome of agroinfiltrated N. benthamiana.
Differential activation states of direct pathway striatal output neurons associated with the development of L-DOPA-induced dyskinesia

L-DOPA-induced dyskinesia (LID) is a debilitating motor side effect arising from chronic dopamine replacement therapy with L-DOPA for the treatment of Parkinson disease (PD). The emergence of LID is linked to heightened sensitivity of striatal dopaminergic signaling and driven by abnormal fluctuations in synaptic dopamine levels following each administration of L-DOPA. This maladaptive plasticity narrows the therapeutic window for L-DOPA treatment, even as the progressive worsening of PD symptoms demands escalating doses. The heterogeneous composition of the striatum, including diverse subpopulations of medium spiny output neurons (MSNs), interneurons, and supporting cells, has complicated the precise identification of the cell(s) underlying LID development and persistence. To elucidate the cellular and molecular mechanisms of LID, we used single nucleus RNA-sequencing (snRNA-seq) to establish a comprehensive striatal transcriptional profile during the development and maintenance of LID in an animal model. Hemiparkinsonian mice were treated with vehicle or L-DOPA for progressive durations (1, 5, or 10 d) and nuclei from the striata were processed for snRNA-seq. Our analysis found that a limited population of dopamine D1 receptor-expressing MSNs (D1-MSNs), arising from both the patch and matrix compartments, formed three subclusters in response to L-DOPA treatment that expressed cellular markers of activation. These activated D1-MSN subpopulations display many of the transcriptional changes previously associated with LID; however, the prevalence and transcriptional behavior of activated D1-MSNs was differentially influenced by the extent of L-DOPA experience. The differentially expressed genes found in these D1-MSNs indicated that acute L-DOPA induced upregulation of multiple plasticity-related transcription factors and regulators of MAPK signaling, while repeated L-DOPA exposure induced numerous genes associated with synaptic remodeling, learning and memory, and transforming growth factor-ß (TGFß) signaling. Notably, repeated L-DOPA led to a sensitization in the expression of Inhba, a member of the activin/TGFß superfamily, in activated D1-MSNs. We tested pharmacological inhibition of its receptor, ALK4, and found that it impaired LID development. Collectively, these data suggest that distinct subsets of D1-MSNs become differentially responsive to L-DOPA due to the aberrant induction of the molecular mechanisms necessary for neuronal entrainment, similar to those processes underlying hippocampal learning and memory formation. Our data further suggests that activin/TGFß signaling may play an essential role in LID development in this subpopulation of D1-MSNs.
Deep Reinforcement Learning Enables Better Bias Control in Benchmark for Virtual Screening

Virtual screening (VS) has been incorporated into the paradigm of modern drug discovery. This field is now undergoing a new wave of revolution driven by artificial intelligence and more specifically, machine learning (ML). In terms of those out-of-the- box datasets for model training or benchmarking, their data volume and applicability domain are limited. They are suffering from the biases constantly reported in the ML application. To address these issues, we present a novel benchmark named MUBDsyn. The utilization of synthetic decoys (i.e., presumed inactives) is the main feature of MUBDsyn, where deep reinforcement learning was leveraged for bias control during decoy generation. Then, we carried out extensive validations on this new benchmark. First, we confirmed that MUBDsyn was superior to the classical benchmarks in control of domain bias, artificial enrichment bias and analogue bias. Moreover, we found that the assessment of ML models based on MUBDsyn was less biased as revealed by the analysis of asymmetric validation embedding bias. In addition, MUBDsyn showed better setting of benchmarking challenge for deep learning models compared with NRLiSt- BDB. Overall, we have proven that MUBDsyn is the close-to-ideal benchmark for VS. The computational tool is publicly available for the easy extension of MUBDsyn.
Disturbance-generated competitive coexistence

Explaining how competing species coexist remains a challenge in ecology. A major hypothesis is that disturbance opens up the opportunity for types with different “life history” strategies to coexist, allowing types better at getting to and using recently disturbed patches to coexist with better competitor types. A simple model introduced several decades ago demonstrated this, but its focus on patch dynamics (i.e. the dynamics of the number of patches a species occupies) gives limited insight into how coexistence-enabling variation arises from within-patch demographic strategies. Here we present, and demonstrate how to analyze, a partial differential equation model that captures the emergence of larger-scale competitive dynamics from within-patch population dynamics of species competing for patches subject to disturbance. We analyze key cases of the model framework, with competition acting in turn on each aspect of within-patch demography included in the model: reproduction, offspring-survival, and adult-survival. Insights arising from these analyses include: 1) variation between species on a simple reproduction-adult-survival trade-off can enable disturbance-generated coexistence, 2) variation along trade-offs with species’ robustness-to-competition can also generate coexistence 3) disturbance-generated coexistence may or may not involve classical “successional dynamics” within patches, and 4) coexistence is easier to generate at intermediate disturbance rates. Our work here provides new tools for more complete development of the theory of disturbance-generated coexistence.
Predicting Attentional Focus: Heartbeat-Evoked Responses and Brain Dynamics During Interoceptive and Exteroceptive Information Processing

Attention shapes our consciousness content and perception by increasing the probability of becoming aware and, or, better encode a selection of the incoming inner or outer sensory world. We designed a task to engage interoceptive and exteroceptive attention by orienting healthy participants to their heartbeats or auditory stimuli and investigated whether brain dynamics (Kolmogorov complexity – KC, permutation entropy – PE, weighted symbolic mutual information – wSMI, power spectrum density – PSD) and the heartbeat-evoked potential (HEP) distinguished interoceptive from exteroceptive covert attention. Exteroceptive attention yielded an overall flattening of the PSD, whereas during interoceptive attention there was a decrease in complexity, an increase in frontal connectivity and oscillations in the theta range, and a modulation of the HEP. Subject-level classifiers based on HEP features classified the attentional state of 17/20 participants. KC, PE, and wSMI showed comparable accuracy in classifying exteroceptive-interoceptive attention and exhibited a synergic behavior with the HEP features. PSD features demonstrated exceptional performance (20/20). Command-following was assessed in 5 brain-injured patients with a modified version of the task. An Unresponsive Wakefulness Syndrome/Vegetative State patient and a locked-in syndrome patient demonstrated a willful modulation of the HEP and the patient-level classifiers suggest that patients were complying with task instructions. Our findings show that directing attention to bodily rhythms or external stimuli elicits distinct neural responses that can be employed to track covert attention at the individual level. Importantly, the brain markers studied in this work provide multiple layers to explore information processing in disorders of conscious patients. Significance statement We show that directing attention to bodily rhythms or external stimuli induces specific neural responses, allowing for individual-level tracking of covert attention in healthy participants. The time-locked and dynamical brain markers identified as relevant to distinguish between interoceptive-exteroceptive attention were further assessed in a small cohort of brain-injured patients as an EEG proxy of command-following. We show for the first time the willful modulation of the HEP in an UWS/VS patient and a locked-in syndrome patient, along with significant classification accuracies when combining the explored features. Importantly, the brain markers studied in this work provide multiple layers to explore information processing in disorders of conscious patients, and expand the framework of heart-brain interactions employed for diagnostic purposes.
From Noise to Knowledge: Probabilistic Diffusion-Based Neural Inference of Gene Regulatory Networks

Understanding gene regulatory networks (GRNs) is crucial for elucidating cellular mechanisms and advancing therapeutic interventions. Original methods for GRN inference from bulk expression data often struggled with the high dimensionality and inherent noise in the data. The prevalence of dropout events and background noise inherent in single-cell RNA sequencing have only increased network-inference challenges. Here we introduce RegDiffusion, a novel neural network structure inspired by Denoising Diffusion Probabilistic Models but focusing on the regulatory effects among feature variables. Unlike other GRN methods for single-cell RNA sequencing data, RegDiffusion introduces Gaussian noise to the input data following a diffusion schedule. It is subsequently trained to predict the added noise using a neural network with a parameterized adjacency matrix. We show that using this process, GRNs can be learned effectively with a surprisingly simple model architecture. In our benchmark experiments, RegDiffusion shows superior performance compared to several baseline methods in multiple datasets. We also demonstrate that RegDiffusion can infer biologically-meaningful regulatory networks from real-world single-cell data sets with over 10,000 genes in under 5 minutes. This work not only introduces a fresh perspective on GRN inference but also highlights the promising capacity of diffusion-based models in the area of single-cell analysis. The RegDiffusion software package and experiment data are available at https://github.com/TuftsBCB/RegDiffusion.
Challenges in the Biotechnological Implementation of Oral RNA Interference as an Antiviral Strategy in Aedes aegypti

Mosquitoes, particularly Aedes aegypti, are critical vectors for globally significant pathogenic viruses. This study examines the limitations of oral RNA interference (RNAi) as a strategy to disrupt viral transmission by Ae. aegypti. We hypothesized that double-stranded RNA (dsRNA) targeting the Zika virus (ZIKV) or chikungunya virus (CHIKV) genomes produced by engineered bacterial symbionts could trigger an antiviral response. Mosquitoes mono-colonized with Escherichia coli producing dsZIK or dsCHIK did not display reduced viral titers following exposure to virus-contaminated bloodmeals and failed to generate dsZIK- or dsCHIK-derived small interfering RNAs. To address potential limitations of bacterial dsRNA release, we explored dsRNA inoculation via feeding and injection. While viral replication was impeded in mosquitoes injected with dsZIK or dsCHIK, no antiviral effect was observed in dsRNA-fed mosquitoes. These findings highlight complexities of implementing oral RNAi as an antiviral strategy in Ae. aegypti and warrant further exploration of local and systemic RNAi mechanisms.
Human neural stem cells restore spatial memory in a transgenic Alzheimer’s disease mouse model by an immunomodulating mechanism

Introduction Stem cells are a promising therapeutic in Alzheimer’s disease (AD) given the complex pathophysiologic pathways involved. However, the therapeutic mechanisms of stem cells remain unclear. Here, we used spatial transcriptomics to elucidate therapeutic mechanisms of human neural stem cells (hNSCs) in an animal model of AD. Methods hNSCs were transplanted into the fimbria fornix of the hippocampus using the 5XFAD mouse model. Spatial memory was assessed by Morris water maze. Amyloid plaque burden was quantified. Spatial transcriptomics was performed and differentially expressed genes (DEGs) identified both globally and within the hippocampus. Subsequent pathway enrichment and ligand-receptor network analysis was performed. Results hNSC transplantation restored learning curves of 5XFAD mice. However, there were no changes in amyloid plaque burden. Spatial transcriptomics showed 1,061 DEGs normalized in hippocampal subregions. Plaque induced genes in microglia, along with populations of stage 1 and stage 2 disease associated microglia (DAM), were normalized upon hNSC transplantation. Pathologic signaling between hippocampus and DAM was also restored. Discussion hNSCs normalized many dysregulated genes, although this was not mediated by a change in amyloid plaque levels. Rather, hNSCs appear to exert beneficial effects in part by modulating microglia-mediated neuroinflammation and signaling in AD.
Nitrate isotope anomalies reflect N2 fixation in the Azores Front region (subtropical NE Atlantic)

[1] The subtropical northeast Atlantic has previously been identified as a marine environment with an apparent imbalance between low nitrate supply to the surface and concurrent high export production. To better constrain the sources and fluxes of mixed layer nitrate and to assess the potential role of N2 fixation in providing new nitrogen (N), we investigated the depth distribution of nitrate δ15N and δ18O at six stations across the Azores Front in the NE Atlantic. In addition, we measured the δ15N of dissolved organic N (DON) in surface waters and of sinking particulate N collected in sediment traps at 2000 m depth between 2003 and 2005 at Station KIEL276. The nitrate isotope profiles at the majority of the hydrographic stations displayed a decrease in the δ15N from depth toward low-nitrate surface waters, concomitant with an increase in δ18O. Given that nitrate uptake by phytoplankton leads to a proportional increase in nitrate δ15N and δ18O, the observed surface water nitrate isotope anomalies (Δ(15;18) up to −6‰) indicate that nitrate assimilation is not the sole process controlling the isotopic composition of nitrate in the photic zone and implicate a significant addition of newly fixed N that is remineralized in surface and subsurface waters. Both the concentration of DON and its δ15N in surface water were spatially invariant, showing mean values of 4.7 ± 0.5 μmol L−1 and 2.6 ± 0.4‰ (n = 35), respectively, supporting the conjecture of a mostly recalcitrant DON pool. The weighted biannual mean δ15N of sinking particulate N (1.8 ± 0.8‰, n = 33) was low with respect to thermocline nitrate. The anomalous dual nitrate isotope signatures together with the low δ15N of export production and elevated nitrate-to-phosphate ratios in surface and subsurface waters strongly suggest that N2 fixation represents a substantive source of N in this part of the subtropical northeast Atlantic. Simple isotope mass balance suggests that, locally, N2 fixation supplies between 56 and 259 mmol N m−2 a−1 for phytoplankton growth in the photic zone, accounting for up to ∼40% of the estimated export production.
Who takes care of the kids and when? Sex differences in avian parental care

Parental care in birds consists of many elaborate forms, including nest building, incubation, and offspring provision, but we still do not know how much each parent contributes to the different forms. Furthermore, the variations, relationships, and potential drivers of sex differentiation in providing care across different care stages remain largely unknown. Here, we surveyed species in birds and uncovered remarkable differences in the sex role patterns across different care forms. This result implied that parental care should not be treated as a unitary trait but as a composite of integrated features with great variations. Further analyses revealed moderate correlations of the sex roles between care forms, indicating the existence of shared intrinsic drivers. We tested the effects of sexual selection, certainty of paternity, predation risk, and offspring’s life history traits in driving sex role variations. Results showed that species with strong sexual selection on males or uncertainty of paternity tend to have female-biased care.
Auto-Classification of Parkinson’s Disease with Different Motor Subtypes Using Arterial Spin Labelling MRI Based on Machine Learning

The purpose of this study was to automatically classify different motor subtypes of Parkinson’s disease (PD) on arterial spin labelling magnetic resonance imaging (ASL-MRI) data using support vector machine (SVM). This study included 38 subjects: 21 PD patients and 17 normal controls (NCs). Based on the Unified Parkinson’s Disease Rating Scale (UPDRS) subscores, patients were divided into the tremor-dominant (TD) subtype and the postural instability gait difficulty (PIGD) subtype. The subjects were in a resting state during the acquisition of ASL-MRI data. The automated anatomical atlas 3 (AAL3) template was registered to obtain an ASL image of the same size and shape. We obtained the voxel values of 170 brain regions by considering the location coordinates of these regions and then normalized the data. The length of the feature vector depended on the number of voxel values in each brain region. Three binary classification models were utilized for classifying subjects’ data, and we applied SVM to classify voxels in the brain regions. The left subgenual anterior cingulate cortex (ACC_sub_L) was clearly distinguished in both NCs and PD patients using SVM, and we obtained satisfactory diagnostic rates (accuracy = 92.31%, specificity = 96.97%, sensitivity = 84.21%, and AUCmax = 0.9585). For the right supramarginal gyrus (SupraMarginal_R), SVM distinguished the TD group from the other groups with satisfactory diagnostic rates (accuracy = 84.21%, sensitivity = 63.64%, specificity = 92.59%, and AUCmax = 0.9192). For the right intralaminar of thalamus (Thal_IL_R), SVM distinguished the PIGD group from the other groups with satisfactory diagnostic rates (accuracy = 89.47%, sensitivity = 70.00%, specificity = 6.43%, and AUCmax = 0.9464). These results are consistent with the changes in blood perfusion related to PD subtypes. In addition, the sensitive brain regions of the TD group and PIGD group involve the brain regions where the cerebellothalamocortical (CTC) and the striatal thalamocortical (STC) loops are located. Therefore, it is suggested that the blood perfusion patterns of the two loops may be different. These characteristic brain regions could become potential imaging markers of cerebral blood flow to distinguish TD from PIGD. Meanwhile, our findings provide an imaging basis for personalised treatment, thereby optimising clinical diagnostic and treatment approaches.
Estimation of Genetic Diversity between and within Biparental Clones and Full-Sib Families of the Chinese Pine Using SSR Markers

Quantifying the genetic diversity present in plant populations is crucial for the success of selection of elite plants and breeding programs. The population structure and partition of genetic variance within and between plant populations allows inferences about the distribution and extent of variation available in plant breeding populations. The Chinese pine (Pinus tabuliformis Carriere) is a native species that is ecologically and economically important to Northern China. Studying the genetic variation and partition of P. tabuliformis will be invaluable for its efficient utilization. In this study, we selected 21 pairs of SSR primers to estimate the genetic diversity of 35 clones from four populations and 216 progenies from 22 full-sib families of P. tabuliformis. Our results showed that P. tabuliformis was a typical outcrossing plant (FIS = −0.053/−0.165) containing moderately high genetic diversity (He = 0.542/0.605) both for the clone populations and the progenies produced by the clone crosses via controlled pollination. The genetic differentiation between the clones (FST = 0.076) was lower than that between the full-sib progenies (FST = 0.155). Such diverse FST may be promoted by different gene flows (Nm = 3.881/1.546) due to distinct pollination patterns. The clustering methods showed a lack of significant division of the clone populations, with a similar genetic admixture found for each of the clones. However, two groups were found between the full-sib families with genetic admixture between them. The analysis of molecular variance (AMOVA) showed that the most plentiful genetic variability exists between the cloned individuals (98%) as well as within the full-sib progenies (89%). Such distribution of genetic variation suggests rich internal variance and thus it is feasible to select the elite plants within each population or family. These results provide genetic materials and theoretical guidance for the selection and breeding of the Chinese pine.