bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-world﻿ artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia
Authors: Scheetz Jane , Koca Dilara , McGuinness Myra , Holloway Edith , Tan Zachary , Zhu Zhuoting , O’Day Rod , Sandhu Sukhpal , MacIsaac Richard J. , Gilfillan Chris , Turner Angus , Keel Stuart , He Mingguang 
Published: August 2021

AbstractThis study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinopathy (DR) screening model in real-world Australian healthcare settings. The study consisted of two components: (1) DR screening of patients using an AI-assisted system and (2) in-depth interviews with health professionals involved in implementing screening. Participants with type 1 or type 2 diabetes mellitus attending two endocrinology outpatient and three Aboriginal Medical Services clinics between March 2018 and May 2019 were invited to a prospective observational study. A single 45-degree (macula centred), non-stereoscopic, colour retinal image was taken of each eye from participants and were instantly screened for referable DR using a custom offline automated AI system. A total of 236 participants, including 174 from endocrinology and 62 from Aboriginal Medical Services clinics, provided informed consent and 203 (86.0%) were included in the analysis. A total of 33 consenting participants (14%) were excluded from the primary analysis due to ungradable or missing images from small pupils (n = 21, 63.6%), cataract (n = 7, 21.2%), poor fixation (n = 2, 6.1%), technical issues (n = 2, 6.1%), and corneal scarring (n = 1, 3%). The area under the curve, sensitivity, and specificity of the AI system for referable DR were 0.92, 96.9% and 87.7%, respectively. There were 51 disagreements between the reference standard and index test diagnoses, including 29 which were manually graded as ungradable, 21 false positives, and one false negative. A total of 28 participants (11.9%) were referred for follow-up based on new ocular findings, among whom, 15 (53.6%) were able to be contacted and 9 (60%) adhered to referral. Of 207 participants who completed a satisfaction questionnaire, 93.7% specified they were either satisfied or extremely satisfied, and 93.2% specified they would be likely or extremely likely to use this service again. Clinical staff involved in screening most frequently noted that the AI system was easy to use, and the real-time diagnostic report was useful. Our study indicates that AI-assisted DR screening model is accurate and well-accepted by patients and clinicians in endocrinology and indigenous healthcare settings. Future deployments of AI-assisted screening models would require consideration of downstream referral pathways.
Mesenchymal stromal cells in the bone marrow niche consist of multi-populations with distinct transcriptional and epigenetic properties
Authors: Kanazawa Sanshiro , Okada Hiroyuki , Hojo Hironori , Ohba Shinsuke , Iwata Junichi , Komura Makoto , Hikita Atsuhiko , Hoshi Kazuto 
Published: August 2021

AbstractAlthough multiple studies have investigated the mesenchymal stem and progenitor cells (MSCs) that give rise to mature bone marrow, high heterogeneity in their morphologies and properties causes difficulties in molecular separation of their distinct populations. In this study, by taking advantage of the resolution of the single cell transcriptome, we analyzed Sca-1 and PDGFR-α fraction in the mouse bone marrow tissue. The single cell transcriptome enabled us to further classify the population into seven populations according to their gene expression profiles. We then separately obtained the seven populations based on candidate marker genes, and specified their gene expression properties and epigenetic landscape by ATAC-seq. Our findings will enable to elucidate the stem cell niche signal in the bone marrow microenvironment, reconstitute bone marrow in vitro, and shed light on the potentially important role of identified subpopulation in various clinical applications to the treatment of bone- and bone marrow-related diseases.
Fine-scale structures as spots of increased fish concentration in the open ocean
Authors: Baudena Alberto , Ser-Giacomi Enrico , D’Onofrio Donatella , Capet Xavier , Cotté Cedric , Cherel Yves , D’Ovidio Francesco 
Published: August 2021

AbstractOceanic frontal zones have been shown to deeply influence the distribution of primary producers and, at the other extreme of the trophic web, top predators. However, the relationship between these structures and intermediate trophic levels is much more obscure. In this paper we address this knowledge gap by comparing acoustic measurements of mesopelagic fish concentrations to satellite-derived fine-scale Lagrangian Coherent Structures in the Indian sector of the Southern Ocean. First, we demonstrate that higher fish concentrations occur more frequently in correspondence with strong Lagrangian Coherent Structures. Secondly, we illustrate that, while increased fish densities are more likely to be observed over these structures, the presence of a fine-scale feature does not imply a concomitant fish accumulation, as other factors affect fish distribution. Thirdly, we show that, when only chlorophyll-rich waters are considered, front intensity modulates significantly more the local fish concentration. Finally, we discuss a model representing fish movement along Lagrangian features, specifically built for mid-trophic levels. Its results, obtained with realistic parameters, are qualitatively consistent with the observations and the spatio-temporal scales analysed. Overall, these findings may help to integrate intermediate trophic levels in trophic models, which can ultimately support management and conservation policies.
HIV-1 molecular diversity in Brazil unveiled by 10 years of sampling by the national genotyping network
Authors: Gräf Tiago , Bello Gonzalo , Andrade Paula , Arantes Ighor , Pereira João Marcos , da Silva Alexandre Bonfim Pinheiro , Veiga Rafael V. , Mariani Diana , Boullosa Lídia Theodoro , Arruda Mônica B. , Fernandez José Carlos Couto , Dennis Ann M. , Rasmussen David A. , Tanuri Amilcar 
Published: August 2021

AbstractHIV-1 has diversified into several subtypes and recombinant forms that are heterogeneously spread around the world. Understanding the distribution of viral variants and their temporal dynamics can help to design vaccines and monitor changes in viral transmission patterns. Brazil has one of the largest HIV-1 epidemics in the western-world and the molecular features of the virus circulating in the country are still not completely known. Over 50,000 partial HIV-1 genomes sampled between 2008 and 2017 by the Brazilian genotyping network (RENAGENO) were analyzed. Sequences were filtered by quality, duplicate sequences per patient were removed and subtyping was performed with online tools and molecular phylogeny. Association between patients’ demographic data and subtypes were performed by calculating the relative risk in a multinomial analysis and trends in subtype prevalence were tested by Pearson correlation. HIV-1B was found to be the most prevalent subtype throughout the country except in the south, where HIV-1C prevails. An increasing trend in the proportion of HIV-1C and F1 was observed in several regions of the country, while HIV-1B tended to decrease. Men and highly educated individuals were more frequently infected by HIV-1B and non-B variants were more prevalent among women with lower education. Our results suggest that socio-demographic factors partially segregate HIV-1 diversity in Brazil while shaping viral transmission networks. Historical events could explain a preferential circulation of HIV-1B among men who have sex with men (MSM) and non-B variants among heterosexual individuals. In view of an increasing male/female ratio of AIDS cases in Brazil in the last 10–15 years, the decrease of HIV-1B prevalence is surprising and suggests a greater penetrance of non-B subtypes in MSM transmission chains.
Agonist dependency of the second phase access of β-arrestin 2 to the heteromeric µ-V1b receptor
Authors: Ngamlertwong Nuttawadee , Tsuchiya Hiroyoshi , Mochimaru Yuta , Azuma Morio , Kuchimaru Takahiro , Koshimizu Taka-aki 
Published: August 2021

AbstractDuring the development of analgesic tolerance to morphine, the V1b vasopressin receptor has been proposed to bind to β-arrestin 2 and the µ-opioid receptor to enable their interaction. However, direct evidence of such a high-order complex is lacking. Using bioluminescent resonance energy transfer between a split Nanoluciferase and the Venus fluorescent protein, the NanoBit-NanoBRET system, we found that β-arrestin 2 closely located near the heteromer µ-V1b receptor in the absence of an agonist and moved closer to the receptor carboxyl-termini upon agonist stimulation. An additive effect of the two agonists for opioid and vasopressin receptors was detected on the NanoBRET between the µ-V1b heteromer and β-arrestin 2. To increase the agonist response of NanoBRET, the ratio of the donor luminophore to the acceptor fluorophore was decreased to the detection limit of luminescence. In the first phase of access, β-arrestin 2 was likely to bind to the unstimulated V1b receptor in both its phosphorylated and unphosphorylated forms. In contrast, the second-phase access of β-arrestin 2 was agonist dependent, indicating a possible pharmacological intervention strategy. Therefore, our efficient method should be useful for evaluating chemicals that directly target the vasopressin binding site in the µ-V1b heteromer to reduce the second-phase access of β-arrestin 2 and thereby to alleviate tolerance to morphine analgesia.
Development of novel artificial intelligence systems to predict facial morphology after orthognathic surgery and orthodontic treatment in Japanese patients
Authors: Tanikawa Chihiro , Yamashiro Takashi 
Published: August 2021

AbstractFrom a socio-psychological standpoint, improving the morphology of the facial soft-tissues is regarded as an important therapeutic goal in modern orthodontic treatment. Currently, many of the algorithms used in commercially available software programs that are said to provide the function of performing profile prediction are based on the false assumption that the amount of movement of hard-tissue and soft-tissue has a proportional relationship. The specification of the proportionality constant value depends on the operator, and there is little evidence to support the validity of the prediction result. Thus, the present study attempted to develop artificial intelligence (AI) systems that predict the three-dimensional (3-D) facial morphology after orthognathic surgery and orthodontic treatment based on the results of previous treatment. This was a retrospective study in a secondary adult care setting. A total of 137 patients who underwent orthognathic surgery (n = 72) and orthodontic treatment with four premolar extraction (n = 65) were enrolled. Lateral cephalograms and 3-D facial images were obtained before and after treatment. We have developed two AI systems to predict facial morphology after orthognathic surgery (System S) and orthodontic treatment (System E) using landmark-based geometric morphometric methods together with deep learning methods; where cephalometric changes during treatment and the coordinate values of the faces before treatment were employed as predictive variables. Eleven-fold cross-validation showed that the average system errors were 0.94 mm and 0.69 mm for systems S and E, respectively. The total success rates, when success was defined by a system error of < 1 mm, were 54% and 98% for systems S and E, respectively. The total success rates when success was defined by a system error of < 2 mm were both 100%. AI systems to predict facial morphology after treatment were therefore confirmed to be clinically acceptable.
Circulating skeletal muscle related microRNAs profile in Piedmontese cattle during different age
Authors: Tewari Rupal S. , Ala Ugo , Accornero Paolo , Baratta Mario , Miretti Silvia 
Published: August 2021

AbstractPiedmontese cattle is known for double-muscle phenotype. MicroRNAs (miRNAs) play important role as regulators in skeletal muscle physiological processes, and we hypothesize that plasma miRNAs expression profiles could be affected by skeletal muscle growth status related to age. Plasma samples of cattle were collected during four different ages from first week of life until the time of commercial end of the fattening period before slaughter. Small-RNA sequencing data analysis revealed the presence of 40% of muscle-related miRNAs among the top 25 highly expressed miRNAs and, 19 miRNAs showed differential expression too. Using qRT-PCR, we validated in a larger bovine population, miRNAs involved in skeletal muscle physiology pathways. Comparing new-born with the other age groups, miR-10b, miR-126-5p, miR-143 and miR-146b were significantly up-regulated, whereas miR-21-5p, miR-221, miR-223 and miR-30b-5p were significantly down-regulated. High expression levels of miR-23a in all the groups were found. Myostatin, a negative regulator of skeletal muscle hypertrophy, was predicted as the target gene for miR-23a and miR-126-5p and we demonstrated their direct binding. Correlation analysis revealed association between miRNAs expression profiles and animals’ weights along the age. Circulating miRNAs could be promising for future studies on their biomarker potentialities to beef cattle selection.
Feeding sites promoting wildlife-related tourism might highly expose the endangered Yunnan snub-nosed monkey (Rhinopithecus bieti) to parasite transmission
Authors: Afonso Eve , Fu Rong , Dupaix Amaël , Goydadin Anne-Claude , Yu ZhongHua , Callou Cécile , Villette Petra , Giraudoux Patrick , Li Li 
Published: August 2021

AbstractAn increasing number of studies have found that the implementation of feeding sites for wildlife-related tourism can affect animal health, behaviour and reproduction. Feeding sites can favour high densities, home range overlap, greater sedentary behaviour and increased interspecific contacts, all of which might promote parasite transmission. In the Yunnan snub-nosed monkey (Rhinopithecus bieti), human interventions via provisioning monkeys at specific feeding sites have led to the sub-structuring of a group into genetically differentiated sub-groups. The fed subgroup is located near human hamlets and interacts with domesticated animals. Using high-throughput sequencing, we investigated Entamoeba species diversity in a local host assemblage strongly influenced by provisioning for wildlife-related tourism. We identified 13 Entamoeba species or lineages in faeces of Yunnan snub-nosed monkeys, humans and domesticated animals (including pigs, cattle, and domestic chicken). In Yunnan snub-nosed monkeys, Entamoeba prevalence and OTU richness were higher in the fed than in the wild subgroup. Entamoeba polecki was found in monkeys, pigs and humans, suggesting that this parasite might circulates between the wild and domestic components of this local social–ecological system. The highest proportion of faeces positive for Entamoeba in monkeys geographically coincided with the presence of livestock and humans. These elements suggest that feeding sites might indirectly play a role on parasite transmission in the Yunnan snub-nosed monkey. The implementation of such sites should carefully consider the risk of creating hotspots of disease transmission, which should be prevented by maintaining a buffer zone between monkeys and livestock/humans. Regular screenings for pathogens in fed subgroup are necessary to monitor transmission risk in order to balance the economic development of human communities dependent on wildlife-related tourism, and the conservation of the endangered Yunnan snub-nosed monkey.
Element-specific contributions to improved magnetic heating of theranostic CoFe2O4 nanoparticles decorated with Pd
Authors: Shams S. Fatemeh , Schmitz Detlef , Smekhova Alevtina , Ghazanfari Mohammad Reza , Giesen Margret , Weschke Eugen , Chen Kai , Luo Chen , Radu Florin , Schmitz-Antoniak Carolin 
Published: August 2021

AbstractDecoration with Pd clusters increases the magnetic heating ability of cobalt ferrite (CFO) nanoparticles by a factor of two. The origin of this previous finding is unraveled by element-specific X-ray absorption spectroscopy (XAS) and magnetic circular dichroism (XMCD) combined with atomic multiplet simulations and density functional theory (DFT) calculations. While the comparison of XAS spectra with atomic multiplet simulations show that the inversion degree is not affected by Pd decoration and, thus, can be excluded as a reason for the improved heating performance, XMCD reveals two interrelated responsible sources: significantly larger Fe and Co magnetic moments verify an increased total magnetization which enhances the magnetic heating ability. This is accompanied by a remarkable change in the field-dependent magnetization particularly for Co ions which exhibit an increased low-field susceptibility and a reduced spin canting behavior in higher magnetic fields. Using DFT calculations, these findings are explained by reduced superexchange between ions on octahedral lattice sites via oxygen in close vicinity of Pd, which reinforces the dominating antiparallel superexchange interaction between ions on octahedral and tetrahedral lattice sites and thus reduces spin canting. The influence of the delocalized nature of Pd 4d electrons on the neighboring ions is discussed and the conclusions are illustrated with spin density isosurfaces of the involved ions. The presented results pave the way to design nanohybrids with tailored electronic structure and magnetic properties.
Discriminating chaotic and stochastic time series using permutation entropy and artificial neural networks
Authors: Boaretto B. R. R. , Budzinski R. C. , Rossi K. L. , Prado T. L. , Lopes S. R. , Masoller C. 
Published: August 2021

AbstractExtracting relevant properties of empirical signals generated by nonlinear, stochastic, and high-dimensional systems is a challenge of complex systems research. Open questions are how to differentiate chaotic signals from stochastic ones, and how to quantify nonlinear and/or high-order temporal correlations. Here we propose a new technique to reliably address both problems. Our approach follows two steps: first, we train an artificial neural network (ANN) with flicker (colored) noise to predict the value of the parameter, $$\alpha$$
α
, that determines the strength of the correlation of the noise. To predict $$\alpha$$
α
the ANN input features are a set of probabilities that are extracted from the time series by using symbolic ordinal analysis. Then, we input to the trained ANN the probabilities extracted from the time series of interest, and analyze the ANN output. We find that the $$\alpha$$
α
value returned by the ANN is informative of the temporal correlations present in the time series. To distinguish between stochastic and chaotic signals, we exploit the fact that the difference between the permutation entropy (PE) of a given time series and the PE of flicker noise with the same $$\alpha$$
α
parameter is small when the time series is stochastic, but it is large when the time series is chaotic. We validate our technique by analysing synthetic and empirical time series whose nature is well established. We also demonstrate the robustness of our approach with respect to the length of the time series and to the level of noise. We expect that our algorithm, which is freely available, will be very useful to the community.
Structural insight into host plasma membrane association and assembly of HIV-1 matrix protein
Authors: Ciftci Halilibrahim , Tateishi Hiroshi , Koiwai Kotaro , Koga Ryoko , Anraku Kensaku , Monde Kazuaki , Dağ Çağdaş , Destan Ebru , Yuksel Busra , Ayan Esra , Yildirim Gunseli , Yigin Merve , Ertem F. Betul , Shafiei Alaleh , Guven Omur , Besler Sabri O. , Sierra Raymond G. , Yoon Chun Hong , Su Zhen , Liang Mengling , Acar Burcin , Haliloglu Turkan , Otsuka Masami , Yumoto Fumiaki , Fujita Mikako , Senda Toshiya , DeMirci Hasan 
Published: August 2021

AbstractOligomerization of Pr55Gag is a critical step of the late stage of the HIV life cycle. It has been known that the binding of IP6, an abundant endogenous cyclitol molecule at the MA domain, has been linked to the oligomerization of Pr55Gag. However, the exact binding site of IP6 on MA remains unknown and the structural details of this interaction are missing. Here, we present three high-resolution crystal structures of the MA domain in complex with IP6 molecules to reveal its binding mode. Additionally, extensive Differential Scanning Fluorimetry analysis combined with cryo- and ambient-temperature X-ray crystallography and GNM-based transfer entropy calculations identify the key residues that participate in IP6 binding. Our data provide novel insights about the multilayered HIV-1 virion assembly process that involves the interplay of IP6 with PIP2, a phosphoinositide essential for the binding of Pr55Gag to membrane. IP6 and PIP2 have neighboring alternate binding sites within the same highly basic region (residues 18–33). This indicates that IP6 and PIP2 bindings are not mutually exclusive and may play a key role in coordinating virion particles’ membrane localization. Based on our three different IP6-MA complex crystal structures, we propose a new model that involves IP6 coordination of the oligomerization of outer MA and inner CA domain’s 2D layers during assembly and budding.
Local clustering via approximate heat kernel PageRank with subgraph sampling
Authors: Lu Zhenqi , Wahlström Johan , Nehorai Arye 
Published: August 2021

AbstractGraph clustering, a fundamental technique in network science for understanding structures in complex systems, presents inherent problems. Though studied extensively in the literature, graph clustering in large systems remains particularly challenging because massive graphs incur a prohibitively large computational load. The heat kernel PageRank provides a quantitative ranking of nodes, and a local cluster can be efficiently found by performing a sweep over the heat kernel PageRank vector. But computing an exact heat kernel PageRank vector may be expensive, and approximate algorithms are often used instead. Most approximate algorithms compute the heat kernel PageRank vector on the whole graph, and thus are dependent on global structures. In this paper, we present an algorithm for approximating the heat kernel PageRank on a local subgraph. Moreover, we show that the number of computations required by the proposed algorithm is sublinear in terms of the expected size of the local cluster of interest, and that it provides a good approximation of the heat kernel PageRank, with approximation errors bounded by a probabilistic guarantee. Numerical experiments verify that the local clustering algorithm using our approximate heat kernel PageRank achieves state-of-the-art performance.