Miracle-dz/UniFAR-FTUs huggingface dataset:
Developmental differences in genome replication program and origin activation

Abstract To ensure error-free duplication of all (epi)genetic information once per cell cycle, DNA replication follows a cell type and developmental stage specific spatio-temporal program. Here, we analyze the spatio-temporal DNA replication progression in (un)differentiated mouse embryonic stem (mES) cells. Whereas telomeres replicate throughout S-phase, we observe mid S-phase replication of (peri)centromeric heterochromatin in mES cells, which switches to late S-phase replication upon differentiation. This replication timing reversal correlates with and depends on an increase in condensation and a decrease in acetylation of chromatin. We further find synchronous duplication of the Y chromosome, marking the end of S-phase, irrespectively of the pluripotency state. Using a combination of single-molecule and super-resolution microscopy, we measure molecular properties of the mES cell replicon, the number of replication foci active in parallel and their spatial clustering. We conclude that each replication nanofocus in mES cells corresponds to an individual replicon, with up to one quarter representing unidirectional forks. Furthermore, with molecular combing and genome-wide origin mapping analyses, we find that mES cells activate twice as many origins spaced at half the distance than somatic cells. Altogether, our results highlight fundamental developmental differences on progression of genome replication and origin activation in pluripotent cells.
Legged locomotion in resistive terrains

The utility, efficiency, and reliability of legged robots has increased dramatically in recent years. Limbed robots are now capable of locomotion across a variety of terrains, however, achieving both rapid and efficient operation when ground conditions are complex or deformable is still challenging. Resistive terrains such as streams, snow, mud, littoral regions, and tall grass are an important class or set of complex and difficult terrain which are commonly found in the desired operating environments of legged robots. This work presents a reduced-order, dynamic model designed to capture the effect of these environments on the legs of a robot while running. This model, and an experimental platform, are used to evaluate the efficacy of a pair of strategies for adapting running to the inevitable slowing that occurs in resistive terrains. Simulation and experimental results show that intelligent retraction of the foot during flight has a more beneficial effect on the maximum achievable velocity and cost of transport of the runner than a ‘punting gait’ for a range of fluid depths. However, this performance gap became much smaller in deep fluids suggesting that fluid depth may drive transition from a foot retraction gait to a punting gait.
A review of P.D.E. models in image processing and image analysis

The years 1985-2000 have seen the emergence of several nonlinear P.D. E. models in image restoration and image analysis. Before that date, the heat equation and the reverse heat equation had been considered as relevant, one as a model of image smoothing compatible with Shannon conditions, and one as a restoration model proposed by Gabor. We try in this review to organize the P.D. E. models according to their genealogy from the initial heat equation and according to their very diverse use : some are useful for image denoising, some for image deblurring, some for invariant smoothing in view of shape recognition. Some permit to define easily active contours (snakes), some may be used for a nonlinear interpolation of sparse images. We show many experiments illustrating these different applicative aspects.
Multi-Walled Carbon Nanotubes Can Promote Brassica napus L. and Arabidopsis thaliana L. Root Hair Development through Nitric Oxide and Ethylene Pathways

Here, we report that multi-walled carbon nanotubes (MWCNTs) can promote plant root hair growth in the species analyzed in this study; however, low and excessive concentrations of MWCNTs had no significant effect or even an inhibiting influence. Further results show that MWCNTs can enter rapeseed root cells. Meanwhile, nitrate reductase (NR)-dependent nitric oxide (NO) and ethylene syntheses, as well as root hair formation, were significantly stimulated by MWCNTs. Transcription of root hair growth-related genes were also modulated. The above responses were sensitive to the removal of endogenous NO or ethylene with a scavenger of NO or NO/ethylene synthesis inhibitors. Pharmacological and molecular evidence suggested that ethylene might act downstream of NR-dependent NO in MWCNTs-induced root hair morphogenesis. Genetic evidence in Arabidopsis further revealed that MWCNTs-triggered root hair growth was abolished in ethylene-insensitive mutants ein2-5 and ein3-1, and NR mutant nia1/2, but not in noa1 mutant. Further data placed NO synthesis linearly before ethylene production in root hair development triggered by MWCNTs. The above findings thus provide some insights into the molecular mechanism underlying MWCNTs control of root hair morphogenesis.
Syringic Acid Alleviates Cesium-Induced Growth Defect in Arabidopsis

Syringic acid, a phenolic compound, serves a variety of beneficial functions in cells. Syringic acid increases in plants in response to cesium, and exogenous application of syringic acid resulted in a significant attenuation of cesium-induced growth defects in Arabidopsis. In addition, cesium or syringic acid application to plants also resulted in increased lignin deposition in interfascicular fibers. To better understand the role of lignin and syringic acid in attenuating cesium-induced growth defects, two mutants for Arabidopsis REDUCED EPIDERMAL FLUORESCENE 4 (REF4) and fourteen laccase mutants, some of which have lower levels of lignin, were evaluated for their response to cesium. These mutants responded differently to cesium stress, compared to control plants, and the application of syringic acid alleviated cesium-induced growth defects in the laccase mutants but not in the ref4 mutants. These findings imply that lignin plays a role in cesium signaling but the attenuation of cesium stress defects by syringic acid is mediated by regulatory components of lignin biosynthesis and not lignin biosynthesis itself. In contrast, syringic acid did not alleviate any low potassium-induced growth defects. Collectively, our findings provide the first established link between lignin and cesium stress via syringic acid in plants.
Variation in model performance by data cleanliness and classification methods in the prediction of 30-day ICU mortality, a US nationwide retrospective cohort and simulation study

Objective There has been a proliferation of approaches to statistical methods and missing data imputation as electronic health records become more plentiful; however, the relative performance on real-world problems is unclear. Materials and methods Using 355 823 intensive care unit (ICU) hospitalisations at over 100 hospitals in the nationwide Veterans Health Administration system (2014–2017), we systematically varied three approaches: how we extracted and cleaned physiologic variables; how we handled missing data (using mean value imputation, random forest, extremely randomised trees (extra-trees regression), ridge regression, normal value imputation and case-wise deletion) and how we computed risk (using logistic regression, random forest and neural networks). We applied these approaches in a 70% development sample and tested the results in an independent 30% testing sample. Area under the receiver operating characteristic curve (AUROC) was used to quantify model discrimination. Results In 355 823 ICU stays, there were 34 867 deaths (9.8%) within 30 days of admission. The highest AUROCs obtained for each primary classification method were very similar: 0.83 (95% CI 0.83 to 0.83) to 0.85 (95% CI 0.84 to 0.85). Likewise, there was relatively little variation within classification method by the missing value imputation method used—except when casewise deletion was applied for missing data. Conclusion Variation in discrimination was seen as a function of data cleanliness, with logistic regression suffering the most loss of discrimination in the least clean data. Losses in discrimination were not present in random forest and neural networks even in naively extracted data. Data from a large nationwide health system revealed interactions between missing data imputation techniques, data cleanliness and classification methods for predicting 30-day mortality.
Interaction of transcription factor AP‐2 gamma with proto‐oncogene PELP1 promotes tumorigenesis by enhancing RET signaling

A significant proportion of estrogen receptor‐positive (ER+) breast cancer (BC) initially responds to endocrine therapy but eventually evolves into therapy‐resistant BC. Transcription factor AP‐2 gamma (TFAP2C) is a known regulator of ER activity, and high expression of TFAP2C is associated with a decreased response to endocrine therapies. PELP1 is a nuclear receptor coregulator, commonly overexpressed in BC, and its levels are correlated with poorer survival. In this study, we identified PELP1 as a novel interacting protein of TFAP2C. RNA‐seq analysis of PELP1 knockdown BC cells followed by transcription factor motif prediction pointed to TFAP2C being enriched in PELP1‐regulated genes. Gene set enrichment analysis (GSEA) revealed that the TFAP2C‐PELP1 axis induced a subset of common genes. Reporter gene assays confirmed PELP1 functions as a coactivator of TFAP2C. Mechanistic studies showed that PELP1‐mediated changes in histone methylation contributed to increased expression of the TFAP2C target gene RET. Furthermore, the TFAP2C‐PELP1 axis promoted the activation of the RET signaling pathway, which contributed to downstream activation of AKT and ERK pathways in ER+ BC cells. Concomitantly, knockdown of PELP1 attenuated these effects mediated by TFAP2C. Overexpression of TFAP2C contributed to increased cell proliferation and therapy resistance in ER+ BC models, while knockdown of PELP1 mitigated these effects. Utilizing ZR75‐TFAP2C xenografts with or without PELP1 knockdown, we provided genetic evidence that endogenous PELP1 is essential for TFAP2C‐driven BC progression in vivo. Collectively, our studies demonstrated that PELP1 plays a critical role in TFAP2C transcriptional and tumorigenic functions in BC and blocking the PELP1‐TFAP2C axis could have utility for treating therapy resistance.
Functional Properties and Sustainability Improvement of Sourdough Bread by Lactic Acid Bacteria

Preventing food spoilage without the addition of chemical food additives, while increasing functional properties of wheat-based bakery products, is an increasing demand by the consumers and a challenge for the food industry. Within this study, lactic acid bacteria (LAB) isolated from sourdough were screened in vitro for the ability to utilize the typical wheat carbohydrates, for their antimicrobial and functional properties. The dual culture overlay assay revealed varying levels of inhibition against the examined fungi, with Lactiplantibacillus plantarum S4.2 and Lentilactobacillus parabuchneri S2.9 exhibiting the highest suppression against the indicator strains Fusarium graminearum MUCL43764, Aspergillus fumigatus, A. flavus MUCL11945, A. brasiliensis DSM1988, and Penicillium roqueforti DSM1079. Furthermore, the antifungal activity was shown to be attributed mainly to the activity of acids produced by LAB. The antibacillus activity was evaluated by the spot-on-the-lawn method revealing a high inhibition potential of the majority of LAB isolated from sourdough against Bacillus cereus DSM31, B. licheniformis DSM13, B. subtilis LMG7135, and B. subtilis S15.20. Furthermore, evaluating the presence of the glutamate decarboxylase gen in LAB isolates by means of PCR showed a strain dependency of a potential GABA production. Finally, due to improved functional activities, LAB isolated from sourdoughs exhibit promising characteristics for the application as natural preservatives in wheat-based bakery products.
Angiopoietin-2 Combined with Radiochemotherapy Impedes Glioblastoma Recurrence by Acting in an Autocrine and Paracrine Manner: A Preclinical Study

Simple Summary Glioblastoma (GB) is a highly aggressive brain tumor characterized by poor prognosis and high rate of recurrence in response to conventional treatments consisting of tumor resection and radiochemotherapy (RCT). The reasons for this therapeutic failure are mainly due to the complexity of GB biology and its environment. GB progression is highly dependent on its vascularization and inflammatory status. Besides, evidence showed that RCT also induces vascular change and inflammation. In GB patients, Angiopoietin-2 (Ang2), biomarker of poor prognosis is a crucial angiogenic factor also involved in inflammation. Our aim was to clarify the role of Ang2 in RCT-induced changes in the GB environment. To this end, we generated Ang2-overexpressing GL261 cells and characterized tumor progression, as well as inflammation and vascularization, in response to RCT. We showed that Ang2 delays tumor recurrence and makes a lasting improvement in animal survival when combined with conventional RCT. Abstract (1) We wanted to assess the impact of Ang2 in RCT-induced changes in the environment of glioblastoma. (2) The effect of Ang2 overexpression in tumor cells was studied in the GL261 syngeneic immunocompetent model of GB in response to fractionated RCT. (3) We showed that RCT combined with Ang2 led to tumor clearance for the GL261-Ang2 group by acting on the tumor cells as well as on both vascular and immune compartments. (4) In vitro, Ang2 overexpression in GL261 cells exposed to RCT promoted senescence and induced robust genomic instability, leading to mitotic death. (5) Coculture experiments of GL261-Ang2 cells with RAW 264.7 cells resulted in a significant increase in macrophage migration, which was abrogated by the addition of soluble Tie2 receptor. (6) Together, these preclinical results showed that, combined with RCT, Ang2 acted in an autocrine manner by increasing GB cell senescence and in a paracrine manner by acting on the innate immune system while modulating the vascular tumor compartment. On this preclinical model, we found that an ectopic expression of Ang2 combined with RCT impedes tumor recurrence.
Improvements of Disability Outcomes in CAPABLE Older Adults Differ by Financial Strain Status

The Community Aging in Place–Advancing Better Living for Elders (CAPABLE) program reduces disability in low-income older adults. In this study, we used CAPABLE baseline and 5-month data to examine whether its effects in reducing activities of daily living (ADLs) and instrumental ADLs (IADLs) difficulties differed by participants’ financial strain status. At baseline, participants with financial strain were more likely to report higher scores on depression (p < .001), have low energy (p < .001), and usually feel tired (p = .004) compared with participants without financial strain, but did not differ in ADL/IADL scores. Participants with financial strain benefited from the program in reducing ADL (relative risk [RR]: 0.61, 95% confidence interval [CI]: 0.43, 0.86) and IADL disabilities (RR: 0.69, 95% CI: 0.54, 0.87), compared with those with financial strain receiving attention control. Individuals with financial strain benefited more from a home-based intervention on measures of disability than those without financial strain. Interventions that improve disability may be beneficial for financially strained older adults.
The LENT index predicts 30 day outcomes following hospitalization for heart failure

The LE index (Length of hospitalization plus number of Emergent visits ≤6 months) predicts 30 day all‐cause readmission or death following hospitalization for heart failure (HF). We combined N‐terminal pro‐B type natriuretic peptide (NT‐proBNP) levels with the LE index to derive and validate the LENT index for risk prediction at the point of care on the day of hospital discharge.
Emergence of radial orientation selectivity: Effect of cell density changes and eccentricity in a layered network

We establish a simple mechanism by which radially oriented simple cells can emerge in the primary visual cortex. In 1986, R. Linsker. proposed a means by which radially symmetric, spatial opponent cells can evolve, driven entirely by noise, from structure in the initial synaptic connectivity distribution. We provide an analytical derivation of Linsker's results, and further show that radial eigenfunctions can be expressed as a weighted sum of degenerate Cartesian eigenfunctions, and vice-versa. These results are extended to allow for radially dependent cell density, from which we show that, despite a circularly symmetric synaptic connectivity distribution, radially biased orientation selectivity emerges in the third layer when cell density in the first layer, or equivalently, synaptic radius, changes with eccentricity; i.e., distance to the center of the lamina. This provides a potential mechanism for the emergence of radial orientation in the primary visual cortex before eye opening and the onset of structured visual input after birth.
Design, Implementation, and Empirical Validation of an IoT Smart Irrigation System for Fog Computing Applications Based on LoRa and LoRaWAN Sensor Nodes †

Climate change is driving new solutions to manage water more efficiently. Such solutions involve the development of smart irrigation systems where Internet of Things (IoT) nodes are deployed throughout large areas. In addition, in the mentioned areas, wireless communications can be difficult due to the presence of obstacles and metallic objects that block electromagnetic wave propagation totally or partially. This article details the development of a smart irrigation system able to cover large urban areas thanks to the use of Low-Power Wide-Area Network (LPWAN) sensor nodes based on LoRa and LoRaWAN. IoT nodes collect soil temperature/moisture and air temperature data, and control water supply autonomously, either by making use of fog computing gateways or by relying on remote commands sent from a cloud. Since the selection of IoT node and gateway locations is essential to have good connectivity and to reduce energy consumption, this article uses an in-house 3D-ray launching radio-planning tool to determine the best locations in real scenarios. Specifically, this paper provides details on the modeling of a university campus, which includes elements like buildings, roads, green areas, or vehicles. In such a scenario, simulations and empirical measurements were performed for two different testbeds: a LoRaWAN testbed that operates at 868 MHz and a testbed based on LoRa with 433 MHz transceivers. All the measurements agree with the simulation results, showing the impact of shadowing effects and material features (e.g., permittivity, conductivity) in the electromagnetic propagation of near-ground and underground LoRaWAN communications. Higher RF power levels are observed for 433 MHz due to the higher transmitted power level and the lower radio propagation losses, and even in the worst gateway location, the received power level is higher than the sensitivity threshold (−148 dBm). Regarding water consumption, the provided estimations indicate that the proposed smart irrigation system is able to reduce roughly 23% of the amount of used water just by considering weather forecasts. The obtained results provide useful guidelines for future smart irrigation developers and show the radio planning tool accuracy, which allows for optimizing the sensor network topology and the overall performance of the network in terms of coverage, cost, and energy consumption.
Dual function of GTPBP6 in biogenesis and recycling of human mitochondrial ribosomes

Abstract Translation and ribosome biogenesis in mitochondria require auxiliary factors that ensure rapid and accurate synthesis of mitochondrial proteins. Defects in translation are associated with oxidative phosphorylation deficiency and cause severe human diseases, but the exact roles of mitochondrial translation-associated factors are not known. Here we identify the functions of GTPBP6, a homolog of the bacterial ribosome-recycling factor HflX, in human mitochondria. Similarly to HflX, GTPBP6 facilitates the dissociation of ribosomes in vitro and in vivo. In contrast to HflX, GTPBP6 is also required for the assembly of mitochondrial ribosomes. GTPBP6 ablation leads to accumulation of late assembly intermediate(s) of the large ribosomal subunit containing ribosome biogenesis factors MTERF4, NSUN4, MALSU1 and the GTPases GTPBP5, GTPBP7 and GTPBP10. Our data show that GTPBP6 has a dual function acting in ribosome recycling and biogenesis. These findings contribute to our understanding of large ribosomal subunit assembly as well as ribosome recycling pathway in mitochondria.
Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize

Fast and stable fluid simulations are an essential prerequisite for applications ranging from computer-generated imagery to computer-aided design in research and development. However, solving the partial differential equations of incompressible fluids is a challenging task and traditional numerical approximation schemes come at high computational costs. Recent deep learning based approaches promise vast speed-ups but do not generalize to new fluid domains, require fluid simulation data for training, or rely on complex pipelines that outsource major parts of the fluid simulation to traditional methods. In this work, we propose a novel physics-constrained training approach that generalizes to new fluid domains, requires no fluid simulation data, and allows convolutional neural networks to map a fluid state from time-point t to a subsequent state at time t + dt in a single forward pass. This simplifies the pipeline to train and evaluate neural fluid models. After training, the framework yields models that are capable of fast fluid simulations and can handle various fluid phenomena including the Magnus effect and Karman vortex streets. We present an interactive real-time demo to show the speed and generalization capabilities of our trained models. Moreover, the trained neural networks are efficient differentiable fluid solvers as they offer a differentiable update step to advance the fluid simulation in time. We exploit this fact in a proof-of-concept optimal control experiment. Our models significantly outperform a recent differentiable fluid solver in terms of computational speed and accuracy.
A Skellam regression model for quantifying positional value in soccer

Abstract Soccer is undeniably the most popular sport world-wide and everyone from general managers and coaching staff to fans and media are interested in evaluating players’ performance. Metrics applied successfully in other sports, such as the (adjusted) +/− that allows for division of credit among a basketball team’s players, exhibit several challenges when applied to soccer due to severe co-linearities. Recently, a number of player evaluation metrics have been developed utilizing optical tracking data, but they are based on proprietary data. In this work, our objective is to develop an open framework that can estimate the expected contribution of a soccer player to his team’s winning chances using publicly available data. In particular, using data from (i) approximately 20,000 games from 11 European leagues over eight seasons, and, (ii) player ratings from the FIFA video game, we estimate through a Skellam regression model the importance of every line (attackers, midfielders, defenders and goalkeeping) in winning a soccer game. We consequently translate the model to expected league points added above a replacement player (eLPAR). This model can further be used as a guide for allocating a team’s salary budget to players based on their expected contributions on the pitch. We showcase similar applications using annual salary data from the English Premier League and identify evidence that in our dataset the market appears to under-value defensive line players relative to goalkeepers.