Miracle-dz/UniFAR-FTUs huggingface dataset:
Antitumor activity of an inhibitor of miR-34a in liver cancer with β-catenin-mutations miR-34a oncogenicity in β-catenin-mutated liver cancer

Objective: Hepatocellular carcinoma (HCC) is the most prevalent primary tumor of the liver. About a third of these tumors presents activating mutations of the β-catenin gene. The molecular pathogenesis of HCC has been elucidated, but mortality remains high and new therapeutic approaches, including treatments based on microRNAs, are required. We aimed to identify candidate microRNAs, regulated by β-catenin, potentially involved in liver tumorigenesis. Design: We used a mouse model, in which β-catenin signaling was overactivated exclusively in the liver, by the tamoxifen-inducible and Cre-Lox-mediated inactivation of the Apc gene. This model develops tumors with properties similar to human HCC. Results: We found that miR-34a was regulated by β-catenin, and significantly induced by the overactivation of β-catenin signaling in mouse tumors and in HCC patients. An inhibitor of miR-34a (LNA-34a) exerted anti-proliferative activity in primary cultures of hepatocyte. This inhibition of proliferation was associated with a decrease in cyclin D1 levels, orchestrated principally by HNF-4α, a target of miR-34a considered to act as a tumor suppressor in the liver. In vivo, LNA-34a approximately halved progression rates for tumors displaying β-catenin activation together with an activation of caspases 2 and 3. Conclusion: This work demonstrates the key oncogenic role of miR-34a in liver tumors with β-catenin gene mutations. We suggest that patients diagnosed with HCC with β-catenin mutations could be treated with an inhibitor of miR-34a. The potential value of this strategy lies in the modulation of the tumor suppressor HNF-4α, which targets cyclin D1, and the induction of a pro-apoptotic program.
GENETIC AND EPIGENETIC REGULATION OF OVULE DEVELOPMENT AND PLANT REPRODUCTION IN A. THALIANA

The developmental programme of the pistil is under the control of both auxin and cytokinin. Crosstalk between these factors converges on regulation of the auxin carrier PIN-FORMED 1 (PIN1). Here, we show that in the triple transcription factor mutant cytokinin response factor 2 (crf2) crf3 crf6 both pistil length and ovule number were reduced. PIN1 expression was also lower in the triple mutant and the phenotypes could not be rescued by exogenous cytokinin application. pin1 complementation studies using genomic PIN1 constructs showed that the pistil phenotypes were only rescued when the PCRE1 domain, to which CRFs bind, was present. Without this domain, pin mutants resemble the crf2 crf3 crf6 triple mutant, indicating the pivotal role of CRFs in auxin-cytokinin crosstalk.
Urban-Scale NO2 Prediction with Sensors Aboard Bicycles: A Comparison of Statistical Methods Using Synthetic Observations

Mobile devices for city-scale air quality monitoring is receiving increasing attention due to the advent of low-cost and miniaturized sensors. Mobility and crowdsensing have emerged as a new means to investigate the ambient air quality in urban areas. However, the design of the network (e.g., number of sensors per unit area) and the scientific interpretation of collected data with an ad hoc method are still challenging. In this paper, we focus on the use of a fleet of private bicycles to monitor NO2 concentrations in the city of Marseille, France. The study is based on synthetic observations generated by means of a regional air quality simulation system at a spatial resolution of 25 m × 25 m and simulated bike trips that are randomly generated in the city. The bike trips correspond to a maximum of 4500 bike commuters and are generated using a web-based navigation service. Simulated bike tracks are validated using available statistics on bike counts. Each bike track is associated with the along-track corresponding NO2 concentrations collected from the air quality simulations and physical features on the ground collected from Open Street Map. Spatialization of the information collected aboard the bikes is tested by using three different algorithms: kriging, land-use regression (LUR) and neural network (NN). LUR and NN show that the fleet can be limited to below 100 bikes while the performance of kriging is steadily increasing with the number of bikes. Increasing the sample distance above 200 m also impairs the citywide prediction of simulated NO2 concentrations.
Structural and functional assessment of multi-stressed lowland waters

Water bodies in densely populated lowland areas are commonly affected by pollution from agricultural activities and wastewater treatment plant (WWTP) discharges, yet the selection of appropriate water quality assessment methods for these water bodies is under debate. Therefore, we aimed to 1) compare the ability of structural and functional metrics to detect adverse effects of anthropogenic stress on aquatic ecosystems and 2) assess the ability of trait-based metrics to diagnose the potential causes of the observed adverse effects in water quality assessment. Specifically, we compared the responses of several structural (both taxonomic and trait-based) and functional (i.e., based on ecological processes) metrics across a series of stressors in 20 lowland water bodies affected to varying degrees by agricultural activities and WWTP discharges. The measured stressors included nutrients, dissolved oxygen saturation, water temperature, and proxies for pesticides, pharmaceuticals, and personal care products. Taxa evenness and the trait-based SPEcies At Risk organic (SPEARorganic) and pesticide (SPEARpesticide) metrics were negatively correlated with the proxy for organic toxicants. Microbial decomposition and invertebrate consumption showed opposite and more complex relationships with the stressors. These findings suggest that functional metrics may detect patterns of anthropogenic stress that are not evident from structural metrics alone. In terms of diagnostic value, our results indicated that both SPEAR metrics may be used to diagnose the combined presence of organic toxicants from agricultural activities and WWTP discharges, although the SPEAR approach may need to be combined with other methods. We conclude that structural (both taxonomic and trait-based) and functional metrics may provide complementary information that, when integrated, allows for more thorough water quality assessment strategies.
Joint modelling of longitudinal and survival data in the presence of competing risks with applications to prostate cancer data

This research is motivated from the data from a large Selenium and Vitamin E Cancer Prevention Trial (SELECT). The prostate specific antigens (PSAs) were collected longitudinally, and the survival endpoint was the time to low-grade cancer or the time to high-grade cancer (competing risks). In this article, the goal is to model the longitudinal PSA data and the time-to-prostate cancer (PC) due to low- or high-grade. We consider the low-grade and high-grade as two competing causes of developing PC. A joint model for simultaneously analysing longitudinal and time-to-event data in the presence of multiple causes of failure (or competing risk) is proposed within the Bayesian framework. The proposed model allows for handling the missing causes of failure in the SELECT data and implementing an efficient Markov chain Monte Carlo sampling algorithm to sample from the posterior distribution via a novel reparameterization technique. Bayesian criteria, Δ DIC Surv , and Δ WAIC Surv , are introduced to quantify the gain in fit in the survival sub-model due to the inclusion of longitudinal data. A simulation study is conducted to examine the empirical performance of the posterior estimates as well as Δ DIC Surv and Δ WAIC Surv and a detailed analysis of the SELECT data is also carried out to further demonstrate the proposed methodology.
Joint seismic and electromagnetic inversion for reservoir mapping using a deep learning aided feature-oriented approach

As more and more types of geophysical measurements informing about different characteristics of subsurface formations are available, effectively synergizing the information from these measurements becomes critical to enhance deep reservoir characterization, determine interwell fluid distribution and ultimately maximize oil recovery. In this study, we develop a feature-based model calibration workflow by combining the power of ensemble methods in data integration and deep learning techniques in feature segmentation. The performance of the developed workflow is demonstrated with a synthetic channelized reservoir model, in which crosswell seismic and electromagnetic (EM) data are jointly inverted.
Accuracy of Digital Image Analysis (DIA) of Borderline Human Epidermal Growth Factor Receptor (HER2) Immunohistochemistry in Invasive Ductal Carcinoma

Background: Digital image analysis (DIA), used to extract information from pathology slides, provides better precision and no limitation regarding different interpretations by observers. Objectives: The present study aimed at evaluating the accuracy of DIA in the interpretation of borderline (2+) human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) slides of invasive ductal carcinoma of the breast. Methods: Sixty pathology samples with invasive ductal carcinoma of the breast were extracted based on HER2 (2+) and their fluorescence in situ hybridization (FISH), and chromogenic in situ hybridization (CISH) responses (as reference standard). The slides were digitized and, then, two pathologists examined the slides and documented diagnosis. DIA was performed by a free web application. Results: Totally, 307 digital images with 298 megabytes volume were extracted. The accuracy, sensitivity, and specificity values of DIA were 86 %, 46.1 %, and 97.8 %, respectively, with 8 false-negative cases. There was moderate agreement between the pathologist 1 (kappa = 0.42) and pathologist 2 (kappa = 0.41) with DIA. Conclusions: DIA had good accuracy and could be used for the interpretation of borderline HER2 IHC method in invasive ductal carcinoma.
Time-lapse CSEM: how important is survey repeatability?

An important concern for time-lapse studies using the controlled-source electromagnetic (CSEM) method is repeatability of acquisition parameters for the base and monitoring surveys. We consider a challenging case when variations in source and receiver positions, conductivity of seawater, etc. will lead to differences in the recorded EM fields that exceed EM response due to production-induced changes in the reservoir resistivity. We show that even in that case, 4-D response can often be clearly resolved if the base and monitor EM data sets are inverted to produce 3-D resistivity distributions. More precisely, for a synthetic model of the Snøhvit gas field, changes in the inverted resistivity maps caused by such non-repeatability will be at least 10 times smaller than the time-lapse differences in the reservoir resistivity. By contrast, measurement errors and poor knowledge of background resistivity may reduce the resolution of 4-D CSEM to a much stronger degree. Analysis of field CSEM data from the Wisting oil field supports our conclusion about strongly relaxed repeatability requirements when 4-D effects are established by examining inverted resistivity volumes rather than by looking at raw EM data.
Kurgan Tunnug 1—New Data on the Earliest Horizon of Scythian Material Culture

ABSTRACT Questions surrounding the emergence of highly mobile nomadic pastoralism and the origins of the associated Scythian material culture have a long history in Eurasian steppe archaeology, but advances in knowledge have been hindered by a lack of data. Here we present new findings on the Early Iron Age royal burial mound Tunnug 1 in Tuva. While the site belongs to the same cultural tradition as Arzhan 1, the conceptual roots of the funerary ritual architecture can be traced to precursors in the Mongun Taiga culture and the Mongolian deer stone khirigsuur complex. The clay architecture uncovered at Tunnug 1 does not find any regional comparisons and possibly hints towards a western Central Asian contribution to the formation of the earliest Scythian horizon. Our research demonstrates the value of a multi-disciplinary approach to documenting monumental earthen architecture, including technical approaches (satellite imagery, aerial photographs, 3D models, digital elevation models, geophysics, and radiocarbon dating) with an analysis of construction material and associated finds.
Enhancing Short-Term Plasticity by Inserting a Thin TiO2 Layer in WOx-Based Resistive Switching Memory

In this work, we emulate biological synaptic properties such as long-term plasticity (LTP) and short-term plasticity (STP) in an artificial synaptic device with a TiN/TiO2/WOx/Pt structure. The graded WOx layer with oxygen vacancies is confirmed via X-ray photoelectron spectroscopy (XPS) analysis. The control TiN/WOx/Pt device shows filamentary switching with abrupt set and gradual reset processes in DC sweep mode. The TiN/WOx/Pt device is vulnerable to set stuck because of negative set behavior, as verified by both DC sweep and pulse modes. The TiN/WOx/Pt device has good retention and can mimic long-term memory (LTM), including potentiation and depression, given repeated pulses. On the other hand, TiN/TiO2/WOx/Pt devices show non-filamentary type switching that is suitable for fine conductance modulation. Potentiation and depression are demonstrated in the TiN/TiO2 (2 nm)/WOx/Pt device with moderate conductance decay by application of identical repeated pulses. Short-term memory (STM) is demonstrated by varying the interval time of pulse inputs for the TiN/TiO2 (6 nm)/WOx/Pt device with a quick decay in conductance.
Seasonal Variation in the Behavior of Sea Turtles at a Brazilian Foraging Area

Abstract This study was conducted in São Sebastião Channel, along the Southern Brazil Platform, and describes the occurrence of 3 species of sea turtles in the area, their main behavioral patterns, and the anthropogenic-related threats. Green turtles (Chelonia mydas) showed a preference for a site covered by Halodule spp. seagrass and hawksbill turtles (Eretmochelys imbricata) showed a preference for a sheltered bay with little wave action and the presence of rocks covered with Palythoa caribaeorum. These sites exhibited different characteristics due to the presence of ocean currents and variable habitat types in the Channel. This study enabled the description of the São Sebastião Channel as a foraging and resting area for sea turtles. We also suggest changing the category of the local marine protected area to enable better protection of turtles.
Rapid restoration of belowground structure and fauna of a seagrass habitat

Seagrass meadows are habitat for an abundance and diversity of animal life, and their continuing global loss has focused effort on their restoration. This restoration not only aims to re‐establish the structure of the seagrass, but also to restore its function, particularly as habitat. The success of seagrass restoration is typically measured by the recovery of aboveground structure, but this ignores the important role of the belowground component of seagrass ecosystems, which may not recover at the same rate, and is equally important for faunal communities. We quantify infaunal communities (abundance, richness, and composition) within expanding plots of restored seagrass, and relate their change to the recovery of belowground seagrass biomass and sediment properties. We found that infaunal abundance and composition converged on that found in natural seagrass within 2 years, while the overall infaunal richness was not affected by habitat. The carbon content of surface sediments also recovered within 2 years, although recovery of belowground biomass and sediment grain size took 4 to 6 years. These results suggest that the structure of recovering seagrass habitats may not need to attain that of natural meadows before they support infauna that is comparable to natural communities. This pace and effectiveness of recovery provides some optimism for future seagrass restoration.
Antimicrobial efficacy of curcumin nanoparticles against Listeria monocytogenes is mediated by surface charge

Curcumin, a hydrophobic phenolic compound isolated from tumeric (Curcuma longa), has gained a great attention due to its health benefits and antimicrobial effects. In this study, curcumin nanoparticles (CNPs) were formulated via acusto-plastic deformation technique, with three differently surface-charged surfactants-sodium dodecylsulfate, Tween 20 and cetrimonium bromide (CTAB). The fabricated CNPs were evaluated for their antimicrobial activity against Listeria monocytogenes, one of the most severe foodborne pathogens. Our results demonstrated that the CNPs formulated with positively charged surfactant (CTAB) exhibited the highest antimicrobial activity against L. monocytogenes, indicating that there is a strong relationship between surface charge and antimicrobial activity of curcumin. The enhanced antimicrobial action of CNPs-CTAB was concluded to be due to the increased cell-antimicrobial interaction, which resulted from the opposing electrical charges between CNPs-CTAB and L. monocytogenes cells, as well as increased antimicrobial penetration endowed by the small size. Practical applications In this study, we showed that surface charge as well as the small size of curcumin nanoparticles play a key role in enhancing cell-antimicrobial interaction and antimicrobial efficacy. The fabricated CNP-CTAB showed the best antimicrobial activity against Listeria monocytogenes. A size reduction to nano-scale is a recently developed strategy used to improve drug/food delivery and matching the public demand for effective and safe antimicrobial formulations for control of foodborne pathogens.
Driver Model Validation through Interaction with Varying Levels of Haptic Guidance

Driver modeling is essential in the development of haptic guidance systems. A new cybernetic driver model designed to account for the cooperation between the driver and haptic guidance systems has recently been proposed. This paper aims to validate this model in situations of interaction with different levels of haptic guidance on a driving simulator. Two experiments have been performed for this purpose. The first experiment consisted of implementing the driver model in the driving simulator and evaluating its lateral control performance when interacting with a haptic guidance system. The results reveal that the model can be adapted to different sharing levels by adjusting only the gain of an internal model of the steering wheel compliance. The second experiment consisted of estimating the evolution of the gain of this internal model using the unscented Kalman filter. The results reveal consistency between the evolution of the identified parameter and the level of sharing of the haptic guidance system. The driver model represents the process of human driver adaptation to variations in the level of sharing in haptic guidance systems.
Mechanistic Insights Into Molecular Proxies Through Comparison of Subannually Resolved Sedimentary Records With Instrumental Water Column Data in the Santa Barbara Basin, Southern California

Lipid biomarkers archived in marine sediments include widely applied proxies to reconstruct sea surface temperature (SST). Two prominent groups of SST sensitive biomarkers are long‐chain alkenones from haptophyte algae and glycerol dibiphytanyl glycerol tetraethers (GDGTs) from planktonic Thaumarchaeota. The corresponding proxies, U37K' and TEX86, respectively, are strongly correlated with mean annual SST. However, culture experiments suggest that other factors such as nutrients could also influence the proxy signals. We created monthly resolved records of molecular SST proxies via mass spectrometry imaging at 200‐μm resolution in varved sediments from Santa Barbara Basin deposited between 1984 and 2009. Direct comparison to coeval water column data determined at seasonal resolution allows new mechanistic insights into environmental parameters influencing proxy signal formation. The U37K' responds sensitively to SST variations, while also being influenced by seasonal variations in nutrient concentrations. Surface water nitrate concentrations above or below ~2 μmol/L are associated with U37K' values that overestimate or underestimate actual SST, respectively. Distributions of the two major GDGTs, expressed as the Crenarchaeol‐Caldarchaeol‐Tetraether index (CCaT), are highly similar to those of the minor cycloalkylated compounds GDGT‐1 to GDGT‐3, presented as the corresponding ring index. The CCaT is correlated with subsurface chemical properties, which are controlled by interannual variations in upwelling intensity linked to dynamics of the California Current System. This relationship is attributed to the impact of nutrients on thaumarchaeal growth rates and GDGT cyclization. The coupling of CCaT to SST was weak but enhanced for temperatures averaged across the upper 100 m of the water column.
Fabric defect fetection via weighted low-rank decomposition and Laplacian regularization

Low-rank decomposition models have potential for fabric defect detection, where a feature matrix is decomposed into a low-rank matrix that corresponding to repeated texture structure and a sparse matrix that represent defective regions. Two limitations, however, still exist. First, previous work might fail to detect some large homogeneous defective block. Second, when the background and defective regions are relatively coherent or the texture of fabric image is complex, it is difficult to use previous methods to separate them. To deal with these problems, a new weighted low-rank decomposition model with Laplace regularization (WLRL) is proposed in this paper: (1) a weighted low-rank decomposition model that can decompose the original image into background and defective regions, and (2) a Laplace regularization that can enlarge the distance between the background and the defective regions. The performance of the proposed method WLRL is evaluated on the box- and star-patterned fabric databases, and superior results are shown compared with state-of-the-art methods, that is, 98.70% ACC (accuracy) and 72.83% TPR (true positive rate) for box-patterned fabrics, 99.09% ACC (accuracy) and 83.63% TPR (true positive rate) for star-patterned fabrics.
Blueberry Cultivar Identification Using Random Amplified Polymorphic DNA and Sequence-characterized Amplified Region Markers

Blueberry cultivars have traditionally been identiﬁed based on the evaluation of sets of morphological characters; however, distinguishing closely related cultivars remains difﬁcult. In the present study, we developed DNA markers for the genetic ﬁngerprinting of 45 blueberry cultivars, including 31 cultivars introduced from the United States Department of Agriculture. We obtained 210 random ampliﬁed of polymorphic DNA (RAPD) markers using 43 different primers. The number of polymorphic bands ranged from three (OPG-10 and OPQ-04) to eight (OPR-16), with an average of ﬁve. A cluster analysis performed with the unweighted pair group method using arithmetic averages produced genetic similarity values among the blueberry cultivars ranging from 0.53 to 0.85, with an average similarity of 0.68. A dendrogram clustered the 45 blueberry cultivars into two main clusters, with a similarity value of 0.65. Cluster I consisted of four rabbiteye cultivars (Pink Lemonade, Alapaha, Titan, and Vernon) and the Ashworth northern highbush cultivar. Cluster II consisted of 31 northern highbush cultivars, eight southern highbush blueberry cultivars, and North- land half-highbush blueberry cultivar. Fifty ﬁve RAPD fragments selected were sequenced to develop sequence-characterized ampliﬁed region (SCAR) markers, result- ing in the successful conversion of 16 of 55 fragments into SCAR markers. An ampliﬁed polymorphic band has the same size as the RAPD fragment or smaller according to the primer combinations in the 16 SCAR markers. Among these markers, a combination of