Miracle-dz/UniFAR-FTUs huggingface dataset:
A mechanistic model of primer synthesis from catalytic structures of DNA polymerase α–primase

The mechanism by which polymerase α–primase (polα–primase) synthesizes chimeric RNA-DNA primers of defined length and composition, necessary for replication fidelity and genome stability, is unknown. Here, we report cryo-EM structures of polα–primase in complex with primed templates representing various stages of DNA synthesis. Our data show how interaction of the primase regulatory subunit with the primer 5′-end facilitates handoff of the primer to polα and increases polα processivity, thereby regulating both RNA and DNA composition. The structures detail how flexibility within the heterotetramer enables synthesis across two active sites and provide evidence that termination of DNA synthesis is facilitated by reduction of polα and primase affinities for the varied conformations along the chimeric primer/template duplex. Together, these findings elucidate a critical catalytic step in replication initiation and provide a comprehensive model for primer synthesis by polα–primase.
ADAM17 targeting by human cytomegalovirus remodels the cell surface proteome to simultaneously regulate multiple immune pathways

Significance Human cytomegalovirus (HCMV) is an important pathogen, being the commonest infectious cause of brain damage to infants and the primary reason for hospital readmissions in transplant recipients. Even though HCMV induces the strongest immune responses by any human pathogen, it evades host defenses and persists for life. This study describes an immunoregulatory strategy through which HCMV modulates multiple immune pathways simultaneously, by targeting a single host protein. HCMV UL148 and UL148D impair the maturation of the sheddase, A Disintegrin And Metalloproteinase 17, profoundly altering surface expression of numerous immunoregulatory proteins. Our findings may be relevant for future viral therapies and understanding the impact of HCMV in developmental biology.
CLN3 deficiency leads to neurological and metabolic perturbations during early development

Juvenile Neuronal Ceroid Lipofuscinosis (or Batten disease) is an autosomal recessive, rare neurodegenerative disorder that affects mainly children above the age of 5 years and is most commonly caused by mutations in the highly conserved CLN3 gene. Here, we generated cln3 morphants and stable mutant lines in zebrafish. Although neither morphant nor mutant cln3 larvae showed any obvious developmental or morphological defects, behavioral phenotyping of the mutant larvae revealed higher basal activity, hyposensitivity to abrupt light changes and hypersensitivity to pro-convulsive drugs. Importantly, in-depth metabolomics and lipidomics analyses revealed significant accumulation of several glycerophosphodiesters (GPDs) and a global decrease of bis(monoacylglycero)phosphate (BMP) species, two classes of molecules previously proposed as potential biomarkers for CLN3 disease based on independent studies in other organisms. We could also demonstrate GPD accumulation in human-induced pluripotent stem cell-derived cerebral organoids carrying a pathogenic variant for CLN3. Our models revealed that GPDs accumulate at very early stages of life in the absence of functional CLN3 and highlight glycerophosphoinositol and BMP as promising biomarker candidates for pre-symptomatic CLN3 disease.
Enveloped viruses pseudotyped with mammalian myogenic cell fusogens target skeletal muscle for gene delivery

Entry of enveloped viruses into cells is mediated by fusogenic proteins that form a complex between membranes to drive rearrangements needed for fusion. Skeletal muscle development also requires membrane fusion events between progenitor cells to form multinucleated myofibers. Myomaker and Myomerger are muscle-specific cell fusogens, but do not structurally or functionally resemble classical viral fusogens. We asked if the muscle fusogens could functionally substitute for viral fusogens, despite their structural distinctiveness, and fuse viruses to cells. We report that engineering of Myomaker and Myomerger on the membrane of enveloped viruses leads to specific transduction of skeletal muscle. We also demonstrate that locally and systemically injected virions pseudotyped with the muscle fusogens can deliver micro-Dystrophin (μDys) to skeletal muscle of a mouse model of Duchenne muscular dystrophy. Through harnessing the intrinsic properties of myogenic membranes, we establish a platform for delivery of therapeutic material to skeletal muscle.
Cancer mutations rewire the RNA methylation specificity of METTL3-METTL14

Chemical modification of RNAs is important for post-transcriptional gene regulation. The METTL3-METTL14 complex generates most N6-methyladenosine (m6A) modifications in mRNAs, and dysregulated methyltransferase expression has been linked to numerous cancers. Here we show that changes in m6A modification location can impact oncogenesis. A gain-of-function missense mutation found in cancer patients, METTL14R298P, promotes malignant cell growth in culture and in transgenic mice. The mutant methyltransferase preferentially modifies noncanonical sites containing a GGAU motif and transforms gene expression without increasing global m6A levels in mRNAs. The altered substrate specificity is intrinsic to METTL3-METTL14, helping us to propose a structural model for how the METTL3-METTL14 complex selects the cognate RNA sequences for modification. Together, our work highlights that sequence-specific m6A deposition is important for proper function of the modification and that noncanonical methylation events can impact aberrant gene expression and oncogenesis.
Aedes aegypti gut transcriptomes respond differently to microbiome transplants from field-caught or laboratory-reared mosquitoes

The mosquito microbiome is critical for host development and plays a major role in many aspects of mosquito biology. While the microbiome is commonly dominated by a small number of genera, there is considerable variation in composition among mosquito species, life stages, and geography. How the host controls and is affected by this variation is unclear. Using microbiome transplant experiments, we asked whether there were differences in transcriptional responses when mosquitoes of different species were used as microbiome donors. We used microbiomes from four different donor species spanning the phylogenetic breadth of the Culicidae, collected either from the laboratory or field. We found that when recipients received a microbiome from a donor reared in the laboratory, the response was remarkably similar regardless of donor species. However, when the donor had been collected from the field, far more genes were differentially expressed. We also found that while the transplant procedure did have some effect on the host transcriptome, this is likely to have had a limited effect on mosquito fitness. Overall, our results highlight the possibility that variation in mosquito microbiome communities are associated with variability in host-microbiome interactions and further demonstrate the utility of the microbiome transplantation technique.
Ingestion of Bacillus cereus spores dampens the immune response to favor bacterial persistence

Spores are considered as dormant entities highly resistant to extreme conditions. Among them, Bacillus cereus spores are commonly associated with foodborne outbreaks. Nevertheless, the pathological processes associated with spore ingestion and germination remain poorly understood. Here, we show that while ingestion of vegetative bacteria leads to their elimination from the midgut and small intestines of Drosophila and mice, respectively, a single ingestion of spores leads to the persistence of bacteria for at least 10 days. Using Drosophila genetics, we demonstrate that spores escape the innate immune response of the anterior midgut. Once in the posterior midgut, spores germinate, and the vegetative cells dampen the immune signaling through the induction of amidases which are negative regulators of the immune response. This study provides evidence for how B. cereus spores hijack the intestinal immune defenses allowing the localized birth of vegetative bacteria responsible for the digestive symptoms associated with foodborne illness outbreaks.
Towards a Framework for Continuous Ontology Engineering

Ontologies are recognized as a successful approach to solve semantic and knowledge-related problems. However, even providing many benefits, ontologies have still not reached broad use in industry. Often, the benefits are undermined by the time and resources needed to develop the ontologies and by the difficulties to maintain and evolve existing ontologies. Moreover, traditional ontology engineering methods may fail to deal with industry needs and requirements changes. To overcome these issues, we can look at Software Engineering, where a recent field of study, Continuous Software Engineering (CSE), aims at delivering valuable software through agility, continuity, integration, and alignment to business. Although some ontology engineering approaches have been based on agile principles, the continuous nature of ontology engineering activities has still not been considered. In this paper, we introduce Continuous Ontology Engineering and propose COntE, a framework containing a set of processes connected by data and information flows to be performed in an integrated, continuous and iterative way. We also raise some research questions and make some discussions about them.
“Getting lost in stars and glitter”: black girls’ multimodal literacies as portals to new suns

ABSRACT Using Octavia Butler’s prophetic writing, specifically, passages from her Parable series, as a conceptual lens, this article will explore the ways one Black girl uses multimodal literacies to imagine new worlds that center and celebrate her Black girlhood. An exploration of her multimodal literacies shows how she simultaneously confronts reality, what exists under this earthly sun, and, in turn, also imagines and shares a new world, under a new sun, built for and by Black girls. This article builds on data collected from a practitioner research study of writing collaborative for girls of Color and applies feminist of Color analyses to create a narrative portrait that explores Black girl literacies as portals to new suns.
Survey on Plagiarism Challenges

This paper describes the current state of plagiarism detection and the challenges that arise in modern society and are caused by plagiarism. There are several significant aspects that were highlighted: technological aspects caused by recent developments of modern NLP tools, social aspects caused by the ongoing COVID-19 pandemic, development of new content similarity detection methods, etc. All of them add new aspects to plagiarism challenges.
Uso de Ontologias no Suporte a Aplicação de Machine Learning: Um Caso no Domínio de Evasão Escolar

With technological advances in the area of Artificial Intelligence, studies and applications combining machine learning and ontologies are increasingly present. In this convergence, ontologies enable a better understanding of the domain and the data, which is essential for providing semantic integration of different data sources and for favoring a proper application of ML techniques. This combination allows creating solutions that generate ML models able for dealing with different data sources. This paper presents a case in the field of school dropout, demonstrating how this combination allows the development of technological resources for predicting school dropout that can be applied to different educational institutions.
An Improved Online Reduction from PAC Learning to Mistake-Bounded Learning

A basic result in learning theory is that mistake-bounded learnability implies PAC learnability. It was shown in [Lit89] that, if a problem can be learned with M mistakes, it can be ( ε, δ )-PAC-learned from O ( 1 ε ( M +log 1 δ )) samples. However, this reduction needs to store either O ( 1 ε log 1 δ ) samples or O ( M ) hypotheses. A different reduction, in [KLPV87], only needs to store O (1) samples and hypotheses but was only shown to work with O ( 1 ε ( M · log Mδ )) samples. We give a refined analysis of the KLPV reduction, showing that it only uses O ( Mε ) samples with probability 1 − M − O (1) . This gives the optimal sample complexity with only O (1) space overhead, for δ > M − O (1) .
Investigation of Artificial Intelligence Methods in the Short-Term and Middle-Term Forecasting in Financial Sphere

In this paper the problems of short-and middle-term forecasting at the financial sphere are considered. For this problem intelligent forecasting methods: LSTM and hybrid deep learning networks based on GMDH are suggested. The optimal parameters of LSTM and hybrid networks were found. Optimal structures of hybrid networks were constructed for short-term and middle-term forecasting. The experimental investigations of LSTM and hybrid DL networks were carried out and their accuracy was compared. The fields of preferable application of LSTM and hybrid DL networks in forecasting problems in finance are determined.
Modeling the Optimal Grocery Store Trading Area using Machine Learning Methods

Over the past few years, the COVID-19 pandemic has significantly transformed consumer behavior, which has undoubtedly affected a large number of industries. Food retail was among the sectors where the effect was significant and led to the transformation of the approach to customer interaction. A large part of consumers began to use online delivery services more, and key players were able to provide delivery of products with their own delivery services or third-party on-demand courier service companies. Undoubtedly, in addition to operational changes in retailers' business model, this also affected their investment activities. Some key players began to reduce their trading floor areas to increase financial efficiency and look for options to work in a convenience store format. In our research, we offer an approach for making the right investment decisions when opening a new store to balance financial metrics and customer satisfaction indicators, which is a key sales driver for the segment of customers who substitute delivery service for brick-and-mortar store visits. Using Machine Learning methods, we solve the task of scenario modeling of revenue and operational efficiency metrics for different areas of the store's trading floor, which allows us to identify the optimal choice for the retailer. Using traffic metrics during peak operation hours, we determine the minimal density of the trading area that will not lead to a decrease in the activity of guests inside the store. Such an approach allows us to evaluate the best format of the store, forecast the object's revenue, and recommend investment project parameters.
X-ray morphologies of Abell clusters

Results are presented for X-ray measurements made with the Einstein Observatory's IPC for a sample of 49 Abell clusters, which were used to determine quantitative measures of two morphological parameters of these clusters, the orientation and ellipticity. Consideration is given to the techniques used for estimating and removing background noise in the images and for determining the variation of these parameters with the flux level of a cluster. It was found that most clusters are clearly flattened; for 20 of these clusters, the orientation was unambiguously determined. A catalog of cluster properties is presented. 17 refs.
Guided Epistemic Expansion in a Science Classroom

: In this paper, we study students’ epistemic engagement in a learning environment that uses Emergent Systems Microworlds (ESMs). ESMs are agent-based computational models that are designed as constructionist microworlds. We use Engeström’s theory of expansive learning for analyzing how agent-based restructurations and constructionist design features of a learning environment facilitate the epistemic expansion of an activity system in a science classroom. We analyze three design features of an ESM-based learning environment that created generative contradictions, which allowed students to devise epistemically expansive ways using the same features to address those contradictions. We discuss how these features facilitated student learning as the students used the ESM as a computational experimental system to test and establish evidence-based claims and collectively shape epistemic practices. This work provides an approach for designing learning environments that foreground students’ epistemic engagement in shaping science practices to learn about disciplinary ideas.
IMPACT OF ENVIRONMENTAL FACTORS ON AIR POLLUTION RELATED TO A RESPIRATORY DISEASES USING STATISTICAL MODELS

Air pollution is a serious environmental problem with various health threatening outcomes. Hospital admission data were collected from 120 randomly selected respiratory diseases during May 2020 to April 2021 in Southern districts Tamil Nadu were taken into account of this research work. Statistical analyses were performed using generalized linear models, generalized additive models, parameter driven model and transitional regression model. This study investigates the hospitalization of respiratory diseases and air pollution levels in Southern district of Tamil Nadu.
Effects of oregano essential oil and capsicum extract supplementation on slaughter characteristics, meat quality, and fatty acid composition of lambs

The aim of this study was to evaluate the effect of oregano essential oil (OEO) and capsicum oleoresin extract (CAO) supplementation on lamb slaughter characteristics, meat quality, and fatty acid composition. In the study, 18 male and 18 female lambs were divided into three equal groups for a 56- day feeding period. The first group was fed the control diet, while the other groups were fed a control diet containing either 300 mg OEO/kg or 300 mg CAO/kg of diet. Feeding OEO or CAO had no effect on the slaughter and carcass quality of the fattening lambs. However, when compared to the female lambs, the male lambs were found to have higher slaughter weights, hot and cold carcass weights, and dressing percentage, while having lower back fat thickness. In addition, OEO substantially increased the intramuscular fat. Dry matter, protein, pH24, meat colour (L*, a*, and b*), drip loss, and cooking loss were not affected by dietary treatment or sex. The addition of OEO or CAO to the diets did not change the meat lipid oxidation or sensory quality characteristics at different storage times. However, meat from the female lambs was found to have thiobarbituric acid reactive substances (TBARS) values lower than that of the meat from the male lambs after 2 d and 4 d of storage. However, the female lamb meat was more preferred in terms of flavour and general acceptance. The ΣMUFA, ΣPUFA, ΣUFA, Σn-6, Σn-3, and Σn-6/Σn-3 contents of the lamb meat were not affected by the dietary treatment. As a result, the inclusion of 300 mg of oregano essential oil/kg of DM in lamb diets is considered appropriate because of its significant contributions to the fat composition of lamb meat.
Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions

Large language models have abilities in creating high-volume human-like texts and can be used to generate persuasive misinformation. However, the risks remain under-explored. To address the gap, this work first examined characteristics of AI-generated misinformation (AI-misinfo) compared with human creations, and then evaluated the applicability of existing solutions. We compiled human-created COVID-19 misinformation and abstracted it into narrative prompts for a language model to output AI-misinfo. We found significant linguistic differences within human-AI pairs, and patterns of AI-misinfo in enhancing details, communicating uncertainties, drawing conclusions, and simulating personal tones. While existing models remained capable of classifying AI-misinfo, a significant performance drop compared to human-misinfo was observed. Results suggested that existing information assessment guidelines had questionable applicability, as AI-misinfo tended to meet criteria in evidence credibility, source transparency, and limitation acknowledgment. We discuss implications for practitioners, researchers, and journalists, as AI can create new challenges to the societal problem of misinformation.
OBSERVATION OF NON-RAYLEIGH SCATTERING IN THE SPECTRUM OF THE DAY SKY IN THE REGION 0.56 TO 2.2 MICRONS

Abstract Spectral records of the day skylight from 0.56 to 2. 2µ were obtained at 5415- and 2200-ft stations for the morning sun along the solar almucantar with a lead-sulfide cell and glass-prism spectrometer. Scattering intensities in the spectral region 1.0 to 2. 2µ appear unusually large up to 30 deg from the sun. Comparison of the recorded scattered intensity with direct solar radiation shows the trend from the high infrared scatter toward Rayleigh scattering. A similar result is obtained by examining the records of Adel. Examination of the scattering function for selected wavelengths shows the loss of visibie light in the forward direction and predominance of infrared. Comparison with Hulburt's curve for the total visible region shows similarity only from 90 to 180 deg from the sun. The slope of the scattering function at small angles for different wavelengths is used as an approximate method for obtaining particle size. Values of roughly 0. 5µ for the visible region and 3. 5µ for the infrared region ha.
Influence of compression-expansion effect on oscillating-flow heat transfer in a finned heat exchanger

Compression and expansion of a working gas due to the pressure oscillation of an oscillating flow can lead to a temperature variation of the working gas, which will affect the heat transfer in the oscillating flow. This study focuses on the impact of the compression-expansion effect, indicated by the pressure ratio, on the heat transfer in a finned heat exchanger under practical operating conditions of the ambient-temperature heat exchangers in Stirling-type pulse tube refrigerators. The experimental results summarized as the Nusselt number are presented for analysis. An increase in the pressure ratio can result in a marked rise in the Nusselt number, which indicates that the compression-expansion effect should be considered in characterizing the heat transfer of the oscillating flow, especially in the cases with a higher Valensi number and a lower maximum Reynolds number.
Malignant tumor and atherosclerotic plaque diagnosis using laser-induced fluorescence

A review of tissue diagnostics using laser-induced fluorescence is given with illustrations chosen from work performed by the authors' group. Two major topics are considered: the demarcation of malignant tumors from normal surrounding tissue and the identification of atherosclerotic regions in arteries. Specific fluorescence from injected agents and tissue natural autofluorescence are discussed. Steady-state and time-resolved fluorescence can be utilized. Original data showing immunity to blood interference in artery monitoring are presented. Imaging techniques for diseased tissue real-time visualization are discussed and illustrated. >