Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of a Culturally Responsive Professional Development Program in Assistive Technology for Latinx Teachers

Very few studies have examined how to culturally and linguistically (CL) adapt professional development (PD) programs in assistive technology (AT) for Latinx teachers serving young children with disabilities. The purposes of this article are (a) to present an iterative design of a CL-adapted PD program, (b) to examine the impact of this program on teachers’ use of AT practices to support young children with disabilities in early childhood classrooms, and (c) to evaluate the usefulness of program adaptations through the lens of bilingual Latinx practitioners. The Ecological Validity Model (EVM) was used as a framework for both the development and assessment of the program’s CL adaptations. Quantitative results indicated significant changes in teachers’ AT use pre- to post-intervention, while qualitative findings revealed the program’s alignment with the language, persons, metaphors, and context dimensions of the EVM. In addition, three themes provided rich descriptions of the program’s responsiveness to practitioners and classrooms. This study supports the CL adaptation of AT interventions as an equitable practice, supporting young children across a range of disabilities, cultures, and contexts while empowering the diverse practitioners who serve them.
Accuracy comparison of different space intersection models based on generalized stereopair

According to the concept of Generalized Stereopair,this paper constructed the generalized stereopair from the different-source high resolution remotely sensed imagery covering the same regions,and investigated several space intersection mathematics models based on RFM.Based on the available remotely sensed imagery,this paper separately calculated the ground 3D coordinates using these space intersection models,and compared the computing accuracies of these models,then analyzed and discussed the accuracy factors of them.Finally,it validated that the accuracy of generalized stereopair space intersection models could absolutely satisfy the requirement of mapping production from remotely sensed imagery.
Comprehensive characterization of the neurogenic and neuroprotective action of a novel TrkB agonist using mouse and human stem cell models of Alzheimer’s Disease

Neural stem cell (NSC) proliferation and differentiation in the mammalian brain decreases to minimal levels postnatally. Nevertheless, neurogenic niches persist in the adult cortex and hippocampus in rodents, primates and humans, with adult NSC differentiation sharing key regulatory mechanisms with development. Adult neurogenesis impairments have been linked to Alzheimer’s Disease (AD) pathology. Addressing these impairments is a promising new avenue for therapeutic intervention based on neurogenesis. However, this possibility has been hindered by technical difficulties of using in-vivo models to conduct screens, including working with scarce NSCs in the adult brain and differences between human and mouse models or ethical limitations. In our study, we use a combination of mouse and human stem cell models to circumvent these issues and perform comprehensive characterization of a novel neurogenic compound using in vitro screening. Our work focuses on the brain-derived neurotrophic factor (BDNF) pathway, a pivotal neurotrophin in the regulation of neuronal growth and differentiation via its receptor tyrosine receptor kinase B (TrkB). We describe the design, chemical synthesis and biological characterization of ENT-A011, a steroidal dehydroepiandrosterone (DHEA) derivative and BDNF mimetic with neuroprotective and neurogenic actions. The compound is able to increase proliferation of mouse primary adult hippocampal NSCs and embryonic cortical NSCs, in the absence of EGF/FGF, while reducing Amyloid-β (Aβ) induced cell death, acting specifically through TrkB activation. The compound is also able to increase astrocytic gene markers involved in NSC maintenance, protect hippocampal neurons from Αβ toxicity and prevent synapse loss after Aβ treatment. To provide a translational link to human cells, we also used neural progenitor cells (NPCs) differentiated from three human induced pluripotent stem cell lines from healthy and AD donors. Our findings suggest that ENT-A011 successfully induces proliferation and prevents cell death after Aβ toxicity of human NPCs. Additionally, using RNAseq profiling, we demonstrate that the compound acts through a core gene network shared with BDNF. Our work characterizes a novel synthetic BDNF mimetic with potential neurogenic and neuroprotective actions in Alzheimer’s disease via stem cell-based screening, demonstrating the promise of stem cell systems for short-listing competitive candidates for further testing.
Digital Manufacturing of Functional Ready-to-Use Microfluidic Systems

Digital manufacturing (DM) strives for the seamless manufacture of a functional device from a digital file. DM holds great potential for microfluidics, but requirements for embedded conduits and high resolution beyond the capability of common manufacturing equipment, and microfluidic systems’ dependence on peripherals (e.g. connections, power supply, computer), have limited its adoption. Microfluidic capillaric circuits (CCs) are structurally-encoded, self-contained microfluidic systems that operate and self-fill thanks to precisely tailored hydrophilicity. CCs were heretofore hydrophilized in a plasma chamber, but which only produces transient hydrophilicity, lacks reproducibility, and limits CC design to open surface channels sealed with a tape. Here we introduce the additive DM of monolithic, fully functional and intrinsically hydrophilic CCs. CCs were 3D printed with commonly available light engine-based 3D printers using polyethylene(glycol)diacrylate-based ink co-polymerized with hydrophilic acrylic acid crosslinkers and optimized for hydrophilicity and printability. A new, robust capillary valve design and embedded conduits with circular cross-sections that prevent bubble trapping are presented, and complex interwoven circuit architectures created, and their use illustrated with an immunoassay. Finally, the need for external paper capillary pumps is eliminated by directly embedding the capillary pump in the chip as a porous gyroid structure, realizing fully functional, monolithic CCs. Thence, a computer-aided design file can be made into a CC by commonly available 3D printers in less than 30 minutes enabling low-cost, distributed, DM of fully functional ready-to-use microfluidic systems.
Nitrogen starvation causes lipid remodeling in Rhodotorula toruloides

The oleaginous yeast Rhodotorula toruloides is a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited by R. toruloides under nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers. Here, we present a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Through an integrative lens of transcriptomic and lipidomic analysis, we identify that R. toruloides undergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals. Highlights The oleaginous yeast R. toruloides displays enhanced lipid accumulation during nitrogen starvation. A multi-omic investigation of the lipid accumulation phenotype was carried out. Lipid remodeling was observed during the accumulation phase, wherein carbon was transferred from phospholipids to storage lipids. Multi-omic analysis suggested that selective regulation within lipid biosynthesis controls for the specific increase of storage lipids.
Simultaneous enhancement of multiple functional properties using evolution-informed protein design

Designing optimized proteins is important for a range of practical applications. Protein design is a rapidly developing field that would benefit from approaches that enable many changes in the amino acid primary sequence, rather than a small number of mutations, while maintaining structure and enhancing function. Homologous protein sequences contain extensive information about various protein properties and activities that have emerged over billions of years of evolution. Evolutionary models of sequence co-variation, derived from a set of homologous sequences, have proven effective in a range of applications including structure determination and mutation effect prediction. In this work we apply one of these models (EVcouplings) to computationally design highly divergent variants of the model protein TEM-1 β-lactamase, and characterize these designs experimentally using multiple biochemical and biophysical assays. Nearly all designed variants were functional, including one with 84 mutations from the nearest natural homolog. Surprisingly, all functional designs had large increases in thermostability and most had a broadening of available substrates. These property enhancements occurred while maintaining a nearly identical structure to the wild type enzyme. Collectively, this work demonstrates that evolutionary models of sequence co-variation (1) are able to capture complex epistatic interactions that successfully guide large sequence departures from natural contexts, and (2) can be applied to generate functional diversity useful for many applications in protein design.
High-Dimensional Behavior of Some Multivariate Two-Sample Tests

It is a difficult problem to test the equality of distribution of two independent p-dimensional (p>1) samples (of sizes m and n, say) in a nonparametric framework. It is not only because we need deal with issues such as tractability of the null distribution of test-statistics but also the fact that the latter are rarely distribution-free. Several notable nonparametric tests for comparing multivariate distributions are the multivariate runs test of Friedman and Rafsky (1979), the nearest-neighbour test of Henze (1988) and the inter-point distance-based test of Baringhaus and Franz (BF) (2004). Biswas and Ghosh (BG) (2014) recently have shown that in a high dimension, low sample-size (HDLSS) scenario, i.e. where p goes to infinity but m, n are small or fixed, all the tests mentioned do not perform well. However, the BG-test is shown to be consistent in the case of HDLSS. In this work, we study the asymptotic behaviours of BF and BG tests when m, n and p go to infinity and min(m, n) = o(p). Our results reveal when these tests are expected to work well and when they are not. Results are illustrated by simulated data.
Alpha-180 spin-echo based line-scanning method for high resolution laminar-specific fMRI

Laminar-specific functional magnetic resonance imaging (fMRI) has been widely used to study circuit-specific neuronal activity by mapping spatiotemporal fMRI response patterns across cortical layers. Hemodynamic responses reflect indirect neuronal activity given limit of spatial and temporal resolution. Previous gradient-echo based line-scanning fMRI (GELINE) method was proposed with high temporal (50 ms) and spatial (50 µm) resolution to better characterize the fMRI onset time across cortical layers by employing 2 saturation RF pulses. However, the imperfect RF saturation performance led to poor boundary definition of the reduced region of interest (ROI) and aliasing problems outside of the ROI. Here, we propose α (alpha)-180 spin-echo-based line-scanning fMRI (SELINE) method to resolve this issue by employing a refocusing 180° RF pulse perpendicular to the excitation slice. In contrast to GELINE signals peaked at the superficial layer, we detected varied peaks of laminar-specific BOLD signals across deeper cortical layers with the SELINE method, indicating the well-defined exclusion of the large drain-vein effect with the spin-echo sequence. Furthermore, we applied the SELINE method with 200 ms TR to sample the fast hemodynamic changes across cortical layers with a less draining vein effect. In summary, this SELINE method provides a novel acquisition scheme to identify microvascular-sensitive laminar-specific BOLD responses across cortical depth.
Gene networks reveal stem-cell state convergence during preneoplasia and progression to malignancy in multistage skin carcinogenesis

Adult mammalian stem cells play critical roles in normal tissue homeostasis, as well as in tumor development, by contributing to cell heterogeneity, plasticity, and development of drug resistance. The relationship between different types of normal and cancer stem cells is highly controversial and poorly understood. Here, we carried out gene expression network analysis of normal and tumor samples from genetically heterogeneous mice to create network metagenes for visualization of stem-cell networks, rather than individual stem-cell markers, at the single-cell level during multistage carcinogenesis. We combined this approach with lineage tracing and single-cell RNASeq of stem cells and their progeny, identifying a previously unrecognized hierarchy in which Lgr6+ stem cells from tumors generate progeny that express a range of other stem-cell markers including Sox2, Pitx1, Foxa1, Klf5, and Cd44. Our data identify a convergence of multiple stem-cell and tumor-suppressor pathways in benign tumor cells expressing markers of lineage plasticity and oxidative stress. This same single-cell population expresses network metagenes corresponding to markers of cancer drug resistance in human tumors of the skin, lung and prostate. Treatment of mouse squamous carcinomas in vivo with the chemotherapeutic cis-platin resulted in elevated expression of the genes that mark this cell population. Our data have allowed us to create a simplified model of multistage carcinogenesis that identifies distinct stem-cell states at different stages of tumor progression, thereby identifying networks involved in lineage plasticity, drug resistance, and immune surveillance, providing a rich source of potential targets for cancer therapy. One-Sentence Summary Genes act in networks to drive cancer, and we identify these groups of genes from bulk-tissue and trace them at single-cell resolution.
High-resolution molecular atlas of a lung tumor in 3D

Cells live and interact in three-dimensional (3D) cellular neighborhoods. However, histology and spatial omics methods mostly focus on 2D tissue sections. Here we present a 3D spatial atlas of a routine clinical sample, an aggressive human lung carcinoma, by combining in situ quantification of 960 cancer-related genes across ∼340,000 cells with measurements of tissue-mechanical components. 3D cellular neighborhoods subdivided the tumor microenvironment into tumor, stromal, and immune multicellular niches. Interestingly, pseudotime analysis suggested that pro-invasive epithelial-to-mesenchymal transition (EMT), detected in stroma-infiltrating tumor cells, already occurred in one region at the tumor surface. There, myofibroblasts and macrophages specifically co-localized with pre-invasive tumor cells and their multicellular molecular signature identified patients with shorter survival. Moreover, cytotoxic T-cells did not infiltrate this niche but colocalized with inhibitory dendritic and regulatory T cells. Importantly, systematic scoring of cell-cell interactions in 3D neighborhoods highlighted niche-specific signaling networks accompanying tumor invasion and immune escape. Compared to 2D, 3D neighborhoods improved the characterization of immune niches by identifying dendritic niches, capturing the 3D extension of T-cell niches and boosting the quantification of niche-specific cell-cell interactions, including druggable immune checkpoints. We believe that 3D communication analyses can improve the design of clinical studies investigating personalized, combination immuno-oncology therapies.
Systematic characterization of a non-transgenic Aβ1–42 amyloidosis model: synaptic plasticity and memory deficits in female and male mice

Background One of the neuropathological hallmarks of Alzheimer’s disease (AD) is amyloid-β (Aβ) accumulation in the hippocampus that causes its dysfunction. This disruption includes excitatory/inhibitory imbalance, synaptic plasticity and oscillatory activity impairments, and memory deficits. Although AD prevalence is higher in women than men, the possible sex difference is scarcely explored and information from amyloidosis transgenic mice models is contradictory. Thus, given the lack of data of the early amyloidosis stages in females, the aim of this study was to systematically characterize the effect of an intracerebroventricular (icv.) injection of Aβ1–42 on hippocampal-dependent memory, and on associated activity-dependent synaptic plasticity in the hippocampal CA1–CA3 synapse, in both male and female mice. Methods To do so, we evaluated long term potentiation (LTP) with ex vivo electrophysiological recordings and spatial (working, short- and long-term) and exploratory habituation memory using Barnes maze or open field habituation tasks respectively. Results We found that Aβ1–42 administration impairs all forms of memory evaluated, regardless the sex, in a long-lasting manner (up to 17 days post-injection). Furthermore, LTP was inhibited at a postsynaptic level, both in males and females, and a long-term depression (LTD) was induced for the same prolonged period, which could underly memory deficits. Conclusions In conclusion, our results provide further evidence of the shifting of LTP/LTD threshold due to a single icv. Aβ1-42 injection, which underly cognitive deficits in early stages of AD. These long-lasting cognitive and functional alterations in males and females validate this model for the study of early amyloidosis in both sexes, thus offering a solid alternative to the inconsistence of amyloidosis transgenic mice models.
Pseudorabies virus hijacks DDX3X, initiating an addictive “mad itch” and immune suppression, to facilitate viral spread

Infections with defined Herpesviruses, such as Pseudorabies virus (PRV) and Varicella zoster virus (VZV) can cause neuropathic itch, referred to as “mad itch” in multiple species. The underlying mechanisms involved in neuropathic “mad itch” are poorly understood. Here, we show that PRV infections hijack the RNA helicase DDX3X in sensory neurons to facilitate anterograde transport of the virus along axons. PRV induces re-localization of DDX3X from the cell body to the axons which ultimately leads to death of the infected sensory neurons. Inducible genetic ablation of Ddx3x in sensory neurons results in neuronal death and “mad itch” in mice. This neuropathic “mad itch” is propagated through activation of the opioid system making the animals “addicted to itch”. Moreover, we show that PRV co-opts and diverts T cell development in the thymus via a sensory neuron-IL-6-hypothalamus-corticosterone stress pathway. Our data reveal how PRV, through regulation of DDX3X in sensory neurons, travels along axons and triggers neuropathic itch and immune deviations to initiate pathophysiological programs which facilitate its spread to enhance infectivity.
STUSC: selection tests under size change

Summary Natural selection leaves signatures in genetic diversity. A challenge in detecting these signatures is that demographic history can shape genetic variation in ways similar to selection, making their effects difficult to disentangle. STUSC takes a simulation based approach to the problem. It performs five widely used tests for natural selection, Tajima’s D, Fu and Li’s F and F*, and Fu and Li’s D and D*, which ordinarily require the assumption of constant population size, under any size history. It also provides methods for generating their statistical distributions, allowing their responses to demography to be studied and past results to be evaluated. Availability and implementation STUSC is written in Java, and is freely available at the author’s website, woodinglab.org/stusc Contact swooding@ucmerced.edu
Dopamine signaling regulates predator-driven changes in Caenorhabditis elegans’ egg laying behavior

Prey respond to predators by altering their behavior to optimize their own fitness and survival. Specifically, prey are known to avoid predator-occupied territories to reduce their risk of harm or injury to themselves and their progeny. We probe the interactions between Caenorhabditis elegans and its naturally cohabiting predator Pristionchus uniformis to reveal the pathways driving changes in prey behavior. While C. elegans prefers to lay its eggs on a bacteria food lawn, the presence of a predator inside a lawn induces C. elegans to lays more eggs away from that lawn. We confirm that this change in egg laying is in response to bites from predators, rather than to predatory secretions. Moreover, predator-exposed prey continue to lay their eggs away from the dense lawn even after the predator is removed, indicating a form of learning. Next, we find that mutants in dopamine synthesis significantly reduce egg laying behavior off the lawn in both predator-free and predator-inhabited lawns, which we can rescue by transgenic complementation or supplementation with exogenous dopamine. Moreover, we find that dopamine is likely released from multiple dopaminergic neurons and requires combinations of both D1-(DOP-1), and D2-like (DOP-2 and DOP-3) dopamine receptors to alter predator-induced egg laying behavior, whereas other combinations modify baseline levels of egg laying behavior. Together, we show that dopamine signaling can alter both predator-free and predator-induced foraging strategies, implying a role for this pathway in defensive behaviors.