Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical Fiber-Assisted Printing: A Platform Technology for Straightforward Photopolymer Resins Patterning and Freeform 3D Printing

Light-based 3D printing techniques represent powerful tools, enabling the precise fabrication of intricate objects with high resolution and control. An innovative addition to this set of printing techniques is Optical Fiber-Assisted Printing (OFAP) introduced in this manuscript. OFAP is a platform utilizing a LED-coupled optical fiber (LOF) which selectively crosslinks photopolymer resins. It allows on-the-fly change of parameters like light intensity and LOF velocity during fabrication, facilitating the creation of structures with progressive features and multi-material constructs layer-by-layer. An optimized formulation based on allyl-modified gelatin (gelAGE) with food dyes as photoabsorbers is introduced. Additionally, a novel gelatin-based biomaterial, alkyne-modified gelatin (gelGPE), featuring alkyne moieties, demonstrates near-visible light absorption thus fitting OFAP needs, paving the way for multifunctional hydrogels through thiol-yne click chemistry. Besides 2D patterning, OFAP is transferred to embedded 3D printing within a resin bath demonstrating the proof-of-concept as novel printing technology with potential applications in tissue engineering and biomimetic scaffold fabrication, offering rapid and precise freeform printing capabilities.
Modular Phoneme Processing in Human Superior Temporal Gyrus

Modular organization is fundamental to cortical processing, but its presence is human association cortex is unknown. We characterized phoneme processing with 128-1024 channel micro-arrays at 50-200μm pitch on superior temporal gyrus of 7 patients. High gamma responses were highly correlated within ∼1.7mm diameter modules, sharply delineated from adjacent modules with distinct time-courses and phoneme-selectivity. We suggest that receptive language cortex may be organized in discrete processing modules.
IN-DEPTH MAPPING OF DNA-PKcs SIGNALING UNCOVERS CONSERVED FEATURES OF ITS KINASE SPECIFICITY

DNA-PKcs is a DNA damage sensor kinase with established roles in DNA double-strand break repair via non-homologous end joining. Recent studies have revealed additional roles of DNA-PKcs in the regulation of transcription, translation and DNA replication. However, the substrates through which DNA-PKcs regulates these processes remain largely undefined. Here we utilized quantitative phosphoproteomics to generate a high coverage map of DNA-PKcs signaling in response to ionizing radiation and mapped its interplay with the ATM kinase. Beyond the detection of the canonical S/T-Q phosphorylation motif, we uncovered a non-canonical mode of DNA-PKcs signaling targeting S/T-ψ-D/E motifs. Cross-species analysis in mouse pre-B and human HCT116 cell lines revealed splicing factors and transcriptional regulators phosphorylated at this novel motif, several of which contain SAP domains. These findings expand the list of DNA-PKcs and ATM substrates and establish a novel preferential phosphorylation motif for DNA-PKcs that connects it to proteins involved in nucleotide processes and interactions.
Signatures of adaptation at key insecticide resistance loci in Anopheles gambiae in Southern Ghana revealed by low-coverage WGS

Resistance to insecticides and adaptation to a diverse range of environments present challenges to Anopheles gambiae s.l. mosquito control efforts in sub-Saharan Africa. Whole-genome-sequencing is often employed for identifying the genomic basis underlying adaptation in Anopheles, but remains expensive for large-scale surveys. Low-coverage whole-genome-sequencing (lcWGS) can identify regions of the genome involved in adaptation at a lower cost, but is currently untested in Anopheles mosquitoes. Here, we use lcWGS to investigate population genetic structure and identify signatures of local adaptation in Anopheles mosquitoes across southern Ghana. In contrast to previous analyses, we find no structuring by ecoregion, with Anopheles coluzzii and Anopheles gambiae populations largely displaying the hallmarks of large, unstructured populations. However, we find signatures of selection at insecticide resistance (IR) loci that appear ubiquitous across ecoregions in An. coluzzii, and strongest in forest ecoregions in An. gambiae. In the IR gene Cyp9k1, we find species-specific alleles under selection, suggesting interspecific variation in the precise mechanism of resistance conferred by Cyp9k1. Our study highlights resistance candidate genes in this region, and validates lcWGS, potentially to very low coverage levels, for population genomics and exploratory surveys for adaptation in Anopheles taxa.
Single cell RNA-sequencing of Ewing sarcoma tumors demonstrates transcriptional heterogeneity and clonal evolution

Ewing sarcoma is the second most common bone cancer in children, accounting for 2% of pediatric cancer diagnoses. Patients who present with metastatic disease at the time of diagnosis have a dismal prognosis, compared to the >70% 5-year survival of those with localized disease. Here, we utilized single cell RNA-sequencing to characterize the transcriptional landscape of primary Ewing sarcoma tumors and surrounding tumor microenvironment (TME). Copy-number analysis identified subclonal evolution within patients even prior to treatment. Primary tumor samples demonstrate a heterogenous transcriptional landscape with several conserved gene expression programs, including those composed of genes related to proliferation and EWS targets. We also were able to identify the composition of the TME and molecularly dissect the transcriptional profile of circulating tumor cells in peripheral blood at the time of diagnosis.
Injury Severity is a Key Contributor to Coagulation Dysregulation and Fibrinogen Consumption

Background Traumatic injury is a leading cause of death for those under the age of 45, with 40% occurring due to hemorrhage. Severe tissue injury and hypoperfusion lead to marked changes in coagulation, thereby preventing formation of a stable blood clot and increasing hemorrhage associated mortality. Objectives We aimed to quantify changes in clot formation and mechanics occurring after traumatic injury and the relationship to coagulation kinetics, and fibrinolysis. Methods Plasma was isolated from injured patients upon arrival to the emergency department. Coagulation kinetics and mechanics of healthy donors and patient plasma were compared with rheological, turbidimetric and thrombin generation assays. ELISA’s were performed to determine tissue plasminogen activator (tPA) and D-dimer concentration, as fibrinolytic markers. Results Sixty-three patients were included in the study. The median injury severity score (ISS) was 17, median age was 37.5 years old, and mortality rate was 30%. Rheological, turbidimetric and thrombin generation assays indicated that trauma patients on average, and especially deceased patients, exhibited reduced clot stiffness, increased fibrinolysis and reduced thrombin generation compared to healthy donors. Fibrinogen concentration, clot stiffness, D-dimer and tPA all demonstrated significant direct correlation to increasing ISS. Machine learning algorithms identified and highlighted the importance of clinical factors on determining patient outcomes. Conclusions Viscoelastic and biochemical assays indicate significant contributors and predictors of mortality for improved patient treatment and therapeutic target detection. ESSENTIALS Traumatic injury may lead to alterations in a patient’s ability to form stable blood clots A study was performed to assess how trauma severity affects coagulation kinetics Key alterations were observed in trauma patients, who exhibit weaker and slower forming clots Paired with machine learning methods, the results indicate key aspects contributing to mortality
Spaceflight alters host-gut microbiota interactions

The rodent habitat on the International Space Station has provided crucial insights into the impact of spaceflight on mammals, including observation of symptoms characteristic of liver disease, insulin resistance, osteopenia and myopathy. Although these physiological responses can involve the microbiome when observed on Earth, changes in host-microbiota interactions during spaceflight are still being elucidated. Here, NASA GeneLab multiomic data from the Rodent Research 6 mission are used to determine changes to gut microbiota and murine host colon and liver gene expression after 29 and 56-days of spaceflight. Using hybrid amplicon and whole metagenome sequencing analysis, significant spaceflight-associated alterations to 42 microbiome species were identified. These included relative reductions of bacteria associated with bile acid and butyrate metabolism, such as Extibacter muris and Dysosmobacter welbionis. Functional prediction suggested over-representation of fatty acid and bile acid metabolism, extracellular matrix interactions, and antibiotic resistance genes within the gut microbiome, while host intestinal and hepatic gene expression described corresponding changes to host bile acid and energy metabolism, and immune suppression from spaceflight. Taken together, these changes imply that interactions at the host-gut microbiome interface contribute to spaceflight pathology and highlight how these interactions might critically influence human health and the feasibility of long-duration spaceflight.
Energy Optimization Induces Predictive-coding Properties in a Multicompartment Spiking Neural Network Model

Predictive coding is a prominent theoretical framework for understanding the hierarchical sensory processing in the brain, yet how it could be implemented in networks of cortical neurons is still unclear. While most existing works have taken a hand-wiring approach to creating microcircuits that match experimental results, recent work in applying an optimisation approach to rate-based artificial neural networks revealed that cortical connectivity might result from self-organisation given some fundamental computational principle, such as energy efficiency. As no corresponding approach has studied this in more plausible networks of spiking neurons, we here investigate whether predictive coding properties in a multi-compartment spiking neural network can emerge from energy optimisation. We find that a model trained with an energy objective in addition to a task-relevant objective is able to reconstruct internal representations given top-down expectation signals alone. Additionally, neurons in the energy-optimised model also show differential responses to expected versus unexpected stimuli, qualitatively similar to experimental evidence for predictive coding. These findings indicate that predictive-coding-like behaviour might be an emergent property of energy optimisation, providing a new perspective on how predictive coding could be achieved in the cortex.
Pharmacological manipulations of the dorsomedial and dorsolateral striatum during fear extinction have opposing effects on fear renewal

Systemic manipulations that enhance dopamine (DA) transmission around the time of fear extinction can strengthen fear extinction and reduce conditioned fear relapse. Prior studies investigating the brain regions where DA augments fear extinction focus on targets of mesolimbic and mesocortical DA systems originating in the ventral tegmental area, given the role of these DA neurons in prediction error. The dorsal striatum (DS), a primary target of the nigrostriatal DA system originating in the substantia nigra (SN), is implicated in behaviors beyond its canonical role in movement, such as reward and punishment, goal-directed action, and stimulus-response associations, but whether DS DA contributes to fear extinction is unknown. We have observed that chemogenetic stimulation of SN DA neurons during fear extinction prevents the return of fear in contexts different from the extinction context, a form of relapse called renewal. This effect of SN DA stimulation is mimicked by a DA D1 receptor (D1R) agonist injected into the DS, thus implicating DS DA in fear extinction. Different DS subregions subserve unique functions of the DS, but it is unclear where in the DS D1R agonist acts during fear extinction to reduce renewal. Furthermore, although fear extinction increases neural activity in DS subregions, whether neural activity in DS subregions is causally involved in fear extinction is unknown. To explore the role of DS subregions in fear extinction, adult, male Long-Evans rats received microinjections of either the D1R agonist SKF38393 or a cocktail consisting of GABAA/GABAB receptor agonists muscimol/baclofen selectively into either dorsomedial (DMS) or dorsolateral (DLS) DS subregions immediately prior to fear extinction, and extinction retention and renewal were subsequently assessed drug-free. While increasing D1R signaling in the DMS during fear extinction did not impact fear extinction retention or renewal, DMS inactivation reduced later renewal. In contrast, DLS inactivation had no effect on fear extinction retention or renewal but increasing D1R signaling in the DLS during extinction reduced fear renewal. These data suggest that DMS and DLS activity during fear extinction can have opposing effects on later fear renewal, with the DMS promoting renewal and the DLS opposing renewal. Mechanisms through which the DS could influence the contextual gating of fear extinction are discussed. Highlights Dorsolateral striatum D1 receptor signaling during fear extinction reduces renewal Neural activity in the dorsomedial striatum during fear extinction permits renewal Dorsal striatum subregions have opposing roles in contextual gating of fear extinction Graphical Abstract
Cell-autonomous and non-cell-autonomous effects of arginase-II on cardiac aging

Aging is a predominant risk factor for heart disease. Aging heart reveals low-grade chronic inflammation, cell apoptosis, cardiac fibrosis, and increased vulnerability to ischemic injury. The underlying molecular mechanisms responsible for the cardiac aging phenotype and its susceptibility to injury are far from being fully understood. Although previous literature reports a role of the mitochondrial enzyme arginase-II (Arg-II) in development of heart failure, contradictory results are reported and no systematic analysis of cellular expression and localization of Arg-II in the heart has been performed. Whether and how Arg-II participates in cardiac aging are still unknown. In this study, we demonstrate, to our surprise, that Arg-II is not expressed in cardiomyocytes from aged mice and human patients, but upregulated in non-myocytes of the aging heart, including macrophages, fibroblasts, endothelial cells. Mice with genetic deficiency of arg-ii (arg-ii-/-) are protected from age-associated cardiac inflammation, myocyte apoptosis, interstitial and perivascular fibrosis, endothelial-mesenchymal transition (EndMT), and susceptibility to ischemic injury. Further experiments show that Arg-II mediates IL-1β release from macrophages of old mice, contributing to the above-described cardiac aging phenotype. In addition, Arg-II enhances mitochondrial reactive oxygen species (mtROS) and activates cardiac fibroblasts that is inhibited by inhibition of mtROS. Thus, our study demonstrates a non-cell-autonomous effect of Arg-II on cardiomyocytes, fibroblasts, and endothelial cells mediated by IL-1β from aging macrophages as well as a cell-autonomous effect of Arg-II through mtROS in fibroblasts contributing to cardiac aging phenotype.
Efficacy of auxin-inducible protein degradation in C. elegans tissues using different auxins and TIR1-expressing strains

The auxin-inducible degradation system has emerged as a powerful tool to deplete proteins of interest in cells and tissues of various model organisms, including C. elegans 2–5. Here, we present a detailed protocol to perform AID-driven spatiotemporal depletion of specific proteins in C. elegans tissues. First, we introduced the AID degron and a fluorescent reporter at two conserved proteins: (a) the transcription factor CFI-1 (human ARID3), which is expressed in the nucleus of multiple C. elegans neurons and head muscle cells 6,7, and (b) the broadly expressed translation initiation factor Y47D3A.21 (human DENR) that localizes in the cytoplasm. Second, we provide a step-by-step guide on how to generate C. elegans strains suitable for AID-mediated protein (CFI-1 and DENR) depletion. Third, we find that the degree of CFI-1 and DENR depletion in C. elegans tissues is comparable upon treatment with either natural auxin (indole-3-acetic acid (IAA) or a water-soluble synthetic auxin analog (K-NAA). Last, we compare the degree of AID-mediated CFI-1 depletion in C. elegans neurons when the transport inhibitor response 1 (TIR1), component of the SCF ubiquitin ligase complex, is provided in neurons or all somatic cells. Altogether, this protocol provides side-by-side comparisons of different auxins and TIR1-expressing lines. Such comparisons may benefit future studies of AID-mediated protein depletion in C. elegans. Graphical abstract Image provided as pdf (together with Figures). Highlights Efficient protein depletion in C. elegans tissues upon treatment with either natural or synthetic auxins. Pansomatic TIR1 expression leads to efficient depletion of CFI-1 and DENR. Panneuronal TIR1 expression leads to neuron-specific, yet variable CFI-1 depletion. The AID system is compatible with fluorescence microscopy, Western blotting and behavioral assays.
Quantum Machine Learning: from NISQ to Fault Tolerance

Quantum machine learning, which involves running machine learning algorithms on quantum devices, has garnered significant attention in both academic and business circles. In this paper, we offer a comprehensive and unbiased review of the various concepts that have emerged in the field of quantum machine learning. This includes techniques used in Noisy Intermediate-Scale Quantum (NISQ) technologies and approaches for algorithms compatible with fault-tolerant quantum computing hardware. Our review covers fundamental concepts, algorithms, and the statistical learning theory pertinent to quantum machine learning.
A Replication of a Prosocial Reasoning Intervention for Juveniles

Aim/Background: A replication of a prior validation study was conducted using a workbook and relationship-based intervention which targeted prosocial reasoning in juveniles who sexually offended. Material/Methods: The study sample consisted of 14 males, all in residential treatment for sexual offenses. The average age was 16.4. The ethnic breakdown was Hispanic 36%, Black 29%, White 29%, and Other 7%. Three counselor rating scales were used to assess outcomes. A pre/post test design was used. The intervention required training in the method for counselors and was completed in 10 individual sessions. Results: A multivariate analysis found statistically significant pre to post test changes on all three counselor rating scales in a prosocial direction. Conclusions: This study was a replication of a prior validation study, and consistent with the hypothesis that the workbook-and relationship-based intervention was related to positive changes in prosocial behaviors. However, replication of the results using more rigorous methodologies to rule out rival hypotheses is necessary.
sta-Associations between serum health biomarker concentrations and reproductive performance, accounting for milk yield, in pasture-based Holstein cows in southeastern Australia

In this single cohort study, we investigated associations between the concentrations of a suite of serum biomarkers measured in the first 30 d of lactation and subsequent reproductive performance measured as mating start date to conception intervals, in pasture-based Holstein cows. A secondary objective was to examine associations between biomarker concentrations and 305-d milk yield to assess whether any positive associations between biomarker concentration and reproductive performance were explained by reduced milk production. The data used had been collected as part of an ongoing project from 2017 to 2020 to compile a data set from a large population of lactating dairy cows. Biomarkers measured were those associated with energy balance (β-hydroxybutyrate [BHB] and nonesterified fatty acids [NEFA]), protein nutritional status (urea and albumin), immune status (globulin, albumin to globulin ratio and haptoglobin), and macromineral status (calcium and magnesium). Associations between biomarker concentrations and mating start date to conception interval were investigated using Cox proportional hazard models, using between 634 and 1,121 lactations (varying by biomarker) from 632 to 1,103 cows and 11 to 17 mating periods from 10 to 13 herds. Based on hazard ratio (HR) estimates and associated 95% confidence intervals (CI), hazard of conception on any particular day of the herds’ mating periods was positively associated with the concentrations of albumin (HR = 1.09; 95% CI: 1.05–1.12), albumin to globulin ratio (HR = 2.82; 95% CI: 1.66–4.79), calcium (HR = 2.01; 95% CI: 1.18– 3.43), and magnesium (HR = 2.17; 95% CI: 1.01–4.66), and negatively associated with globulin concentration (HR = 0.98; 95% CI: 0.97 to 1.00). There was also some evidence that NEFA concentration was negatively associated (HR = 0.76; 95% CI: 0
Full one-loop radiative corrections to e + e − → H + H − in the Inert Higgs Doublet Model

We compute the full one-loop radiative corrections for charged Higgs pair production e + e − → H + H − in the Inert Higgs Doublet Model. The on-shell renormalization scheme have been used. We include the full electroweak contributions as well as the QED corrections (soft and hard). We use FeynArts/FormCalc/LoopTools to compute the one-loop virtual corrections while the real emission is evaluated by using Feynman Diagram Calculation. The resummed cross section is introduced to cure the Coulomb singularity which occurs in the QED corrections. We have analyzed the parameter space of the Inert Higgs Doublet Model after taking into account theoretical constraints, the collider experimental bounds and dark matter search bounds as well. The resummed cross section is introduced to cure the Coulomb singularity which occurs in the QED corrections. It is found that the weak interaction dominates the radiative corrections, and its size is determined by the triple Higgs coupling λ h 0 H + H − , which is further connected to the mass of the charged Higgs boson. For √ s = 250 GeV and √ s = 500 GeV, the weak corrections are around − 6% ∼ − 5% and − 10% ∼ − 3%, respectively. While for √ s = 1000 GeV, the weak corrections can reach − 15% ∼ +25%. The new feature is that the weak corrections can be positive near the threshold when charged Higgs boson is larger than 470 GeV. Six benchmarks for future collider searches have been proposed.