Miracle-dz/UniFAR-FTUs huggingface dataset:
Fracture Analysis of FRP-Plated Notched Concrete Beams Subjected to Three-Point Bending

AbstractThree-point bending tests of fiber-reinforced polymer (FRP) plated notched concrete beams have great potential to become a standard test method for evaluating the shear bond performance of FRP-to-concrete interfaces. This paper presents an analytical approach to predict the full-range response of FRP-plated notched concrete beams. The focus of the analysis is to simulate the interactions between Mode II debonding of the FRP-to-concrete interface and Mode I fracture at the crack tip of the concrete beam. In analyzing the FRP-to-concrete interface, the slip is selected as the unknown function to derive a second-order ordinary differential equation, and the analytical relationship between the pull force of the FRP laminate and the interfacial slip at its loaded end is formulated. Crack propagation in concrete is modeled using the weight function method. The stress intensity factors induced by various external loads and internal forces are all given in an analytical manner. Finally, a global equation .
LRRK2 and Parkinson's disease: from genetics to targeted therapy

LRRK2 variants are implicated in both familial and sporadic PD. LRRK2‐PD has a generally benign clinical presentation and variable pathology, with inconsistent presence of Lewy bodies and marked Alzheimer's disease pathology. The mechanisms underlying LRRK2‐PD are still unclear, but inflammation, vesicle trafficking, lysosomal homeostasis, and ciliogenesis have been suggested, among others. As novel therapies targeting LRRK2 are under development, understanding the role and function of LRRK2 in PD is becoming increasingly important. Here, we outline the epidemiological, pathophysiological, and clinical features of LRRK2‐PD, and discuss the arising therapeutic approaches targeting LRRK2 and possible future directions for research.
Cell biology of protein–lipid conjugation

Protein–lipid conjugation is a widespread modification involved in many biological processes. Various lipids, including fatty acids, isoprenoids, sterols, glycosylphosphatidylinositol, sphingolipids, and phospholipids, are covalently linked with proteins. These modifications direct proteins to intracellular membranes through the hydrophobic nature of lipids. Some of these membrane-binding processes are reversible through delipidation or by reducing the affinity to membranes. Many signaling molecules undergo lipid modification, and their membrane binding is important for proper signal transduction. The conjugation of proteins to lipids also influences the dynamics and function of organellar membranes. Dysregulation of lipidation has been associated with diseases such as neurodegenerative diseases. In this review, we first provide an overview of diverse forms of protein–lipid conjugation and then summarize the catalytic mechanisms, regulation, and roles of these modifications.
Transcriptomic Profile of Penicillium digitatum Reveals Novel Aspects of the Mode of Action of the Antifungal Protein AfpB

Fungal infections threaten human health worldwide and have a negative impact on food security, damaging crop production and causing animal diseases. At present, only a few classes of fungicides are available due to the complexity of targeting fungi without affecting plant, animal, or human hosts. ABSTRACT Antifungal proteins (AFPs) from filamentous fungi are promising biomolecules to control fungal pathogens. Understanding their biological role and mode of action is essential for their future application. AfpB from the citrus fruit pathogen Penicillium digitatum is highly active against fungal phytopathogens, including its native fungus. Our previous data showed that AfpB acts through a multitargeted three-stage process: interaction with the outer mannosylated cell wall, energy-dependent cell internalization, and intracellular actions that result in cell death. Here, we extend these findings by characterizing the functional role of AfpB and its interaction with P. digitatum through transcriptomic studies. For this, we compared the transcriptomic response of AfpB-treated P. digitatum wild type, a ΔafpB mutant, and an AfpB-overproducing strain. Transcriptomic data suggest a multifaceted role for AfpB. Data from the ΔafpB mutant suggested that the afpB gene contributes to the overall homeostasis of the cell. Additionally, these data showed that AfpB represses toxin-encoding genes, and they suggest a link to apoptotic processes. Gene expression and knockout mutants confirmed that genes coding for acetolactate synthase (ALS) and acetolactate decarboxylase (ALD), which belong to the acetoin biosynthetic pathway, contribute to the inhibitory activity of AfpB. Moreover, a gene encoding a previously uncharacterized extracellular tandem repeat peptide (TRP) protein showed high induction in the presence of AfpB, whereas its TRP monomer enhanced AfpB activity. Overall, our study offers a rich source of information to further advance in the characterization of the multifaceted mode of action of AFPs. IMPORTANCE Fungal infections threaten human health worldwide and have a negative impact on food security, damaging crop production and causing animal diseases. At present, only a few classes of fungicides are available due to the complexity of targeting fungi without affecting plant, animal, or human hosts. Moreover, the intensive use of fungicides in agriculture has led to the development of resistance. Therefore, there is an urgent need to develop antifungal biomolecules with new modes of action to fight human-, animal-, and plant-pathogenic fungi. Fungal antifungal proteins (AFPs) offer great potential as new biofungicides to control deleterious fungi. However, current knowledge about their killing mechanism is still limited, which hampers their potential applicability. AfpB from P. digitatum is a promising molecule with potent and specific fungicidal activity. This study further characterizes its mode of action, opening avenues for the development of new antifungals.
Remote phosphor LED modules for general illumination: toward 200 lm/W general lighting LED light sources

Phosphor converted white LEDs are becoming more and more attractive for general lighting applications because of the steadily increasing luminous efficacy numbers reported by LED-suppliers. Despite these high numbers, a further significant improvement step can be made when a low-to-medium brightness (<500 kCd/m2) source is acceptable. The wall plug efficiency of a blue LED is generally better than that of a conventional white LED made from the same die. To take full advantage of this, we have developed medium-brightness LED-modules (~150 kCd/m2) for general lighting in which the phosphor is applied remote from the blue LEDs. By direct comparison with modules in which conventional high power white LEDs with almost identical dies are applied, we have shown that on system level the remote phosphor modules can have up to 50% better efficacy. Using a downlight module as a carrier, we have shown that in the relevant color temperature range of 2700 to 4000K a high CRI (>80) can be obtained in combination with a high luminous efficacy, while the optical efficiency of the module can be over 85%. A module efficacy of over 100 lm/W at 4000K with CRI 80 seems to be within reach, with a long-term expectation of over 180 lm/W. The remote phosphor LED modules deliver well homogenized white light with a Lambertian radiation profile. They are ideal for general illumination, as they combine glare reduction with high system efficacy and enable high optical efficiencies of the luminaries. The RP modules enable forward compatibility by well defined interfaces and optical properties that are decoupled from the actual performance, form factor and number of LEDs in the module. The Philips Fortimo downlight system is based on this remote phosphor concept, featuring forward compatibility and a total system efficacy (including driver) of over 60 lm/W under operating conditions using currently available Luxeon Rebel emitters.
Variation in salivary cortisol responses in yearling Thoroughbred racehorses during their first year of training

Thoroughbred horses are bred for competitive racing and undergo intense training regimes. The maintenance of physical soundness and desirable behavioural characteristics are critical to the longevity of a racing career. Horses intended for Flat racing generally enter training as yearlings and undergo introductory training prior to exercise conditioning for racing. This period requires rapid adjustment to a novel environment. As a prey animal, a horse’s ‘fight-or-flight’ response is highly adapted, in which a well-understood component of this response, the hypothalamic-pituitary-axis, is activated in response to a stress stimulus, releasing cortisol. In the Thoroughbred, a significant difference in salivary cortisol concentrations between pre- and post-first time ridden (i.e., first backing) by a jockey have previously been identified. Here, to test the hypothesis that salivary cortisol concentrations may be used to objectively detect individual variations in the acute physiological stress response we investigate individual variation in cortisol response to training milestones. Saliva samples were collected from a cohort of n = 96 yearling Flat racehorses, at the same training yard, across three timepoints at rest: before entering the training yard (n = 66), within three days of entry to the training yard (n = 67) and following 2–3 weeks in the training yard (n = 50). Salivary cortisol concentration was measured using an ELISA. There was no significant difference in cortisol concentration (ANOVA, P > 0.05) across the samples collected at timepoints at rest. Samples were also collected before and 30 minutes after exposure to three novel training events: first time long-reined (n = 6), first time backed by a jockey (n = 34), and first time ridden on the gallops (n = 10). Mean salivary cortisol concentration after all three novel training events was significantly higher than prior to the training event (Paired t-test, P <0.005). The ranges of post-event salivary cortisol concentration across all timepoints suggest individual variation in the measured stress response, reflecting individual differences in stress response to the early training environment. This measure may be used as an objective assessment of the stress response of Thoroughbred racehorses during training.
Mapping and identification of molecular markers for the Pc96 gene conferring resistance to crown rust in oat

Oat crown rust caused by Puccinia coronata f. sp. avenae P. Syd. & Syd (Pca) is a major constraint to oat (Avena sativa L.) production in many parts of the globe. The objectives of this study were to locate Pc96 on the oat consensus map and to develop SNP markers linked to Pc96 for use in marker-assisted selection. SNP loci linked to the crown rust resistance gene Pc96 were identified by linkage analysis and PACE assays were developed for marker-assisted selection in breeding programs. Pc96 is a race-specific crown rust resistance gene originating from cultivated oat that has been deployed in North American oat breeding programs. Pc96 was mapped in a recombinant inbred line population (n = 122) developed from a cross between the oat crown rust differential known to carry Pc96 and the differential line carrying Pc54. A single resistance locus was identified on chromosome 7D between 48.3 and 91.2 cM. The resistance locus and linked SNPs were validated in two additional biparental populations, Ajay × Pc96 (F2:3, n = 139) and Pc96 × Kasztan (F2:3, n = 168). Based on all populations, the most probable location of the oat crown rust resistance gene Pc96 on the oat consensus map was on chromosome 7D approximately at 87.3 cM. In the Ajay × Pc96 population, a second unlinked resistance gene was contributed by the Pc96 differential line, which mapped to chromosome 6C at 75.5 cM. A haplotype of nine linked SNPs predicted the absence of Pc96 in a diverse group of 144 oat germplasm. SNPs that are closely linked to the Pc96 gene may be beneficial as PCR-based molecular markers in marker-assisted selection.
A Multivariate Bayesian Scan Statistic

OBJECTIVE This paper develops a new method for multivariate spatial cluster detection, the “multivariate Bayesian scan statistic” (MBSS). MBSS combines information from multiple data streams in a Bayesian framework, enabling faster and more accurate outbreak detection. BACKGROUND The Bayesian spatial scan statistic [1] is an extension of Kulldorff’s spatial scan statistic [2] that combines observations and prior knowledge in a principled Bayesian framework. We have demonstrated that the Bayesian method has several advantages over the standard frequentist approach, including higher detection power, faster computation, and easier visualization and calibration. Here we generalize the Bayesian spatial scan to multivariate data, enabling us to combine our priors with observations of multiple data streams and to characterize outbreaks by modeling and differentiating between multiple potential causes. METHODS In the MBSS framework, we are given a set of outbreak types O = {Ok} and a set of data streams D = {Dm}. The outbreak types may be either specific illnesses (influenza, anthrax, etc.) or non-specific syndromes. The data streams may include sources such as emergency department (ED) visits, with each stream representing a different chief complaint type, and over-the-counter (OTC) drug sales, with each stream representing a different product group. We are also given a set of spatial regions S to search, where each S contains some subset of the spatial locations si. Finally, we are given the count ci,m for each spatial location si at each time step t for each data stream Dm. Our goal is to compute the posterior probability Pr(H1(S, Ok) | D) that each outbreak type Ok has affected each spatial region S, as well as the probability Pr(H0 | D) that no outbreak has occurred.
Household energy technology projects in voluntary carbon markets: storylines of co-benefits

This paper analyses how co-benefits have been conceptualized in household energy technology carbon offset projects. Offset projects, where emissions in one place are compensated through reducing emissions elsewhere, are justified on the basis of providing local development co-benefits in addition to the global emissions reduction. I focus on the voluntary carbon market, where the price of emissions reductions is more sensitive to the perceptions of produced co-benefits. I focus specifically on three types of household energy technologies that have been popular in the voluntary carbon markets: improved cookstoves, biogas digesters and ceramic water purifiers. The co-benefits of the technologies are conceptualized through three different storylines: achieving health benefits, challenging carbon credit ownership and creating sustainable local markets. While the first and last storylines have been dominant, they also contain a tension over supporting local production of the technologies versus importing more efficient technologies. The storyline of carbon credit ownership is more marginal. How the co-benefits of household energy technologies are conceptualized carries material implications through influencing what type of projects are successful in the voluntary carbon
L‐lactate production in engineered Saccharomyces cerevisiae using a multistage multiobjective automated design framework

The design of alternative biodegradable polymers has the potential of severely reducing the environmental impact, cost and production time currently associated with the petrochemical industry. In fact, growing demand for renewable feedstock has recently brought to the fore synthetic biology and metabolic engineering. These two interdependent research areas focus on the study of microbial conversion of organic acids, with the aim of replacing their petrochemical‐derived equivalents with more sustainable and efficient processes. The particular case of Lactic acid (LA) production has been the subject of extensive research because of its role as an essential component for developing an eco‐friendly biodegradable plastic—widely used in industrial biotechnological applications. Because of its resistance to acidic environments, among the many LA‐producing microbes, Saccharomyces cerevisiae has been the main focus of research into related biocatalysts. In this study, we present an extensive in silico investigation of S. cerevisiae cell metabolism (modeled with Flux Balance Analysis) with the overall aim of maximizing its LA production yield. We focus on the yeast 8.3 steady‐state metabolic model and analyze it under the impact of different engineering strategies including: gene knock‐in, gene knock‐out, gene regulation and medium optimization; as well as a comparison between results in aerobic and anaerobic conditions. We designed ad‐hoc constrained multiobjective evolutionary algorithms to automate the engineering process and developed a specific postprocessing methodology to analyze the genetic manipulation results obtained. The in silico results reported in this paper empirically show that our method is able to automatically select a small number of promising genetic and metabolic manipulations, deriving competitive strains that promise to impact microorganisms design in the production of sustainable chemicals.
Health-related quality of life of women with breast cancer being treated with hormone therapy: A scoping review

Objective To map the evidence available in the literature on the health-related quality of life of women with breast cancer using hormone therapy. Data sources This review followed the Joanna Briggs Institute methodological recommendations and Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews reporting guidelines. Searches were performed in nine databases using descriptors, synonyms and keywords; grey literature was also included. The review protocol was registered with the Open Science Framework under doi: http://doi.org/10.17605/OSF.IO/347FM. Inclusion criteria were established according to the Population, Concept, and Context strategy. The selection of studies was performed by two independent reviewers with the aid of RAYYAN software and disagreements were resolved by a third reviewer. The main information from the included articles was grouped into textual categories and presented by means of a narrative synthesis. Data Summary A total of 5419 records were identified, of which 42 studies fully met the eligibility criteria. Most were multicenter studies (42.9%) and randomized controlled trials (62%). Most studies addressed anastrozole (39.5%), letrozole (34.2%), and tamoxifen (26.3%), which were studied alone or in combination. The most widely used health-related quality-of-life assessment tool was the EORTC-QLQ-C30. The concomitant use of hormone therapy and cyclin-dependent kinase inhibitors 4 and 6 showed improvement in health-related quality of life. Conclusion In recent years there has been an increase in studies focused on health-related quality of life, and the evidence pointed to relevant information on health-related quality of life and the use of endocrine therapy, tamoxifen in combination with aromatase inhibitors, as well as aromatase inhibitor alone and the use of cyclin-dependent kinase 4 and 6.
Degradation of Perfluorooctanoic Acid on Aluminum Oxide Surfaces: New Mechanisms from Ab Initio Molecular Dynamics Simulations

Perfluorooctanoic acid (PFOA) is a part of a large group of anthropogenic, persistent, and bioaccumulative contaminants known as per- and polyfluoroalkyl substances (PFAS) that can be harmful to human health. In this work, we present the first ab initio molecular dynamics (AIMD) study of temperature-dependent degradation dynamics of PFOA on (100) and (110) surfaces of γ-Al2O3. Our results show that PFOA degradation does not occur on the pristine (100) surface, even when carried out at high temperatures. However, introducing an oxygen vacancy on the (100) surface facilitates an ultrafast (<100 fs) defluorination of C–F bonds in PFOA. We also examined degradation dynamics on the (110) surface and found that PFOA interacts strongly with Al(III) centers on the surface of γ-Al2O3, resulting in a stepwise breaking of C–F, C–C, and C–COO bonds. Most importantly, at the end of the degradation process, strong Al–F bonds are formed on the mineralized γ-Al2O3 surface, which prevents further dissociation of fluorine into the surrounding environment. Taken together, our AIMD simulations provide critical reaction mechanisms at a quantum level of detail and highlight the importance of temperature effects, defects, and surface facets for PFOA degradation on reactive surfaces, which have not been systematically explored or analyzed.
Nitrogen use strategy drives interspecific differences in plant photosynthetic CO2 acclimation

Rising atmospheric CO2 concentration triggers an emergent phenomenon called plant photosynthetic acclimation to elevated CO2 (PAC). PAC is often characterized by a reduction in leaf photosynthetic capacity (Asat), which varies dramatically along the continuum of plant phylogeny. However, it remains unclear whether the mechanisms responsible for PAC are also different across plant phylogeny, especially between gymnosperms and angiosperms. Here, by compiling a dataset of 73 species, we found that although leaf Asat increased significantly from gymnosperms to angiosperms, there was no phylogenetic signal in the PAC magnitude along the phylogenetic continuum. Physio‐morphologically, leaf nitrogen concentration (Nm), photosynthetic nitrogen‐use efficiency (PNUE), and leaf mass per area (LMA) dominated PAC for 36, 29, and 8 species, respectively. However, there was no apparent difference in PAC mechanisms across major evolutionary clades, with 75% of gymnosperms and 92% of angiosperms regulated by the combination of Nm and PNUE. There was a trade‐off between Nm and PNUE in driving PAC across species, and PNUE dominated the long‐term changes and inter‐specific differences in Asat under elevated CO2. These findings indicate that nitrogen‐use strategy drives the acclimation of leaf photosynthetic capacity to elevated CO2 across terrestrial plant species.
Use of genetic correlations to examine selection bias

Observational studies are rarely representative of their target population, because there are known and unknown factors that affect an individual's choice to participate (known as the selection mechanism). Selection can cause bias in a given analysis, if the outcome is related to selection (conditional on the other variables in the model). However, the selection mechanism usually cannot be detected from the observed data if we have no data on the non-selected sample - for example, when the selected sample is participants in a research study. Here, we develop methods to examine the selection mechanism by comparing correlations among variables in the selected sample to those expected under no selection. We examine the use of four hypothesis tests to identify induced associations between genetic variants in the selected sample. We evaluate these approaches with Monte Carlo simulations. Finally, these approaches are demonstrated with an applied example, using data from UK Biobank (UKBB), with alcohol intake as exposure to test the presence of selection bias. The proposed tests have identified selection due to alcohol intake into UKBB, and the subsample of individuals with weekly alcohol intake. Analyses in UKBB with alcohol consumption as exposure or outcome may be biased by this selection.