Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent advances in diffusion neuroimaging: applications in the developing preterm brain

Measures obtained from diffusion-weighted imaging provide objective indices of white matter development and injury in the developing preterm brain. To date, diffusion tensor imaging (DTI) has been used widely, highlighting differences in fractional anisotropy (FA) and mean diffusivity (MD) between preterm infants at term and healthy term controls; altered white matter development associated with a number of perinatal risk factors; and correlations between FA values in the white matter in the neonatal period and subsequent neurodevelopmental outcome. Recent developments, including neurite orientation dispersion and density imaging (NODDI) and fixel-based analysis (FBA), enable white matter microstructure to be assessed in detail. Constrained spherical deconvolution (CSD) enables multiple fibre populations in an imaging voxel to be resolved and allows delineation of fibres that traverse regions of fibre-crossings, such as the arcuate fasciculus and cerebellar–cortical pathways. This review summarises DTI findings in the preterm brain and discusses initial findings in this population using CSD, NODDI, and FBA.
Analysing the Focus of a Hierarchical Attention Network: the Importance of Enjambments When Classifying Post-modern Poetry

After overcoming the traditional metrics, modern and postmodern poetry developed a large variety of ‘free verse prosodies’ that falls along a spectrum from a more ﬂuent to a more disﬂuent and choppy style. We present a method, grounded in philological analysis and theories on cognitive (dis)ﬂuency, to analyze this ‘free verse spectrum’ into six classes of poetic styles as well as to differentiate three types of poems with enjambments. We use a model for automatic prosodic analysis of spoken free verse poetry which uses deep hierarchical attention networks to integrate the source text and audio and predict the assigned class. We then analyze and ﬁne-tune the model with a particular focus on enjambments and in two ways: we drill down on classiﬁcation performance by analyzing whether the model focuses on similar traits of poems as humans would, speciﬁcally, whether it internally builds a notion of enjambment. We ﬁnd that our model is similarly good as humans in ﬁnding enjambments; however, when we employ the model for classifying enjambment-dominated poem types, it does not pay particular attention to those lines. Adding enjambment labels to the training only marginally improves performance, indicating that all other lines are similarly informative for the model.
Prevalence and Genetic Diversity of Grabloviruses in Free-Living Vitis spp.

The distribution and diversity of grapevine red blotch virus (GRBV) and wild Vitis virus 1 (WVV1) (genus Grablovirus; family Geminiviridae) were determined in free-living Vitis spp. in northern California and New York from 2013 to 2017. Grabloviruses were detected by polymerase chain reaction in 28% (57 of 203) of samples from California but in none of the 163 samples from New York. The incidence of GRBV in free-living vines was significantly higher in samples from California counties with high compared with low grape production (χ2 = 83.09; P < 0.001), and in samples near (<5 km) to compared with far (>5 km) from vineyards (χ2 = 57.58; P < 0.001). These results suggested a directional spread of GRBV inoculum predominantly from vineyards to free-living Vitis spp. WVV1 incidence was also significantly higher in areas with higher grape production acreage (χ2 = 16.02; P < 0.001). However, in contrast to GRBV, no differential distribution of WVV1 incidence was observed with regard to distance from vineyards (χ2 = 0.88; P = 0.3513). Two distinct phylogenetic clades were identified for both GRBV and WVV1 isolates from free-living Vitis spp. , although the nucleotide sequence variability of the genomic diversity fragment was higher for WWV1 (94.3 to 99.8% sequence identity within clade 1 isolates and 90.1 to 100% within clade 2 isolates) than GRBV (98.3% between clade 1 isolates and 96.9 to 100% within clade 2 isolates). Additionally, evidence for intraspecific recombination events was found in WVV1 isolates and confirmed in GRBV isolates. The prevalence of grabloviruses in California free-living vines highlights the need for vigilance regarding potential grablovirus inoculum sources in order to protect new vineyard plantings and foundation stock vineyards in California.
The Molecular Basis for Specificity at the Level of the Protein Kinase a Catalytic Subunit

Assembly of multi enzyme complexes at subcellular localizations by anchoring- and scaffolding proteins represents a pivotal mechanism for achieving spatiotemporal regulation of cellular signaling after hormone receptor targeting [for review, see (1)]. In the 3′ 5′-cyclic adenosine monophosphate (cAMP) dependent protein kinase (PKA) signaling pathway it is generally accepted that specificity is secured at several levels. This includes at the first level stimulation of receptors coupled to heterotrimeric G proteins which through stimulation of adenylyl cyclase (AC) forms the second messenger cAMP. Cyclic AMP has several receptors including PKA. PKA is a tetrameric holoenzyme consisting of a regulatory (R) subunit dimer and two catalytic (C) subunits. The R subunit is the receptor for cAMP and compartmentalizes cAMP signals through binding to cell and tissue-specifically expressed A kinase anchoring proteins (AKAPs). The current dogma tells that in the presence of cAMP, PKA dissociates into an R subunit dimer and two C subunits which are free to phosphorylate relevant substrates in the cytosol and nucleus. The release of the C subunit has raised the question how specificity of the cAMP and PKA signaling pathway is maintained when the C subunit no longer is attached to the R subunit-AKAP complex. An increasing body of evidence points toward a regulatory role of the cAMP and PKA signaling pathway by targeting the C subunits to various C subunit binding proteins in the cytosol and nucleus. Moreover, recent identification of isoform specific amino acid sequences, motifs and three dimensional structures have together provided new insight into how PKA at the level of the C subunit may act in a highly isoform-specific fashion. Here we discuss recent understanding of specificity of the cAMP and PKA signaling pathway based on C subunit subcellular targeting as well as evolution of the C subunit structure that may contribute to the dynamic regulation of C subunit activity.
Diet Supplemented with Chia Flour did not Modified the Inflammatory Process and Tumor Development in Wistar Rats Inoculated with Walker 256 Cells

Abstract Chia seed (Salvia hispanica L.) contains high amounts of n-3 α-linolenic acid (ALA) and has been associated with many health benefits. The aim of the present study was to evaluate the AIN-93 diet supplemented by chia flour on cancer-cachexia development and tissues inflammatory response. Wistar rats at 30 days old were treated with control diet or diet supplemented with chia flour for eight weeks. After this period, half of the animals in each diet group were inoculated with Walker 256 tumor cells. On the 14th day after tumor inoculation, the animals were euthanized and white adipose tissue depots, liver, gastrocnemius muscle, and tumor were removed. The tumor weight was higher and IL-10 content was lower in chia flour group. The tumor bearing did not modify the cytokines content in gastrocnemius muscle, retroperitoneal and epididymal adipose tissue, however, it decreased IL-1β and TNF-α content in liver, and IL6R and IL-10R protein content in mesenteric adipose tissue. In conclusion, our results demonstrated that supplementation with chia flour did not prevent the tumor bearing effects in Walker 256 model.
Vitamin D: Effect on Haematopoiesis and Immune System and Clinical Applications

Vitamin D is a steroid-like hormone which acts by binding to vitamin D receptor (VDR). It plays a main role in the calcium homeostasis and metabolism. In addition, vitamin D display other important effects called “non-classical actions. ” Among them, vitamin D regulates immune cells function and hematopoietic cells differentiation and proliferation. Based on these effects, it is currently being evaluated for the treatment of hematologic malignancies. In addition, vitamin D levels have been correlated with patients’ outcome after allogeneic stem cell transplantation, where it might regulate immune response and, accordingly, might influence the risk of graft-versus-host disease. Here, we present recent advances regarding its clinical applications both in the treatment of hematologic malignancies and in the transplant setting.
The effect of liraglutide on the proliferation, migration, and osteogenic differentiation of human periodontal ligament cells

OBJECTIVE Liraglutide (LIRA) is a novel antidiabetic therapy that may have anti-inflammatory and bone protective effects. Thus, we studied the potential therapeutic effect of LIRA on periodontitis by assessing the effects of LIRA on the proliferation, migration, inflammation, and osteogenic differentiation of human periodontal ligament cells (hPDLCs) after LPS stimulation. MATERIAL AND METHODS The expression of glucagon like-peptide 1 receptor (GLP-1R) was measured using qRT-PCR. HPDLCs proliferation after LIRA were analyzed using MTT assays. Cell migration was quantified using a wound-healing assay. The expression of inflammatory (IL-6 and TNF-α) was measured by qRT-PCR and ELISA in hPDLCs. The effect of LIRA on the mineralization potential of hPDLCs was assessed by alizarin red S staining. Furthermore, the expression of Runx2 and ALP was measured by qRT-PCR and Western blot in hPDLCs. RESULTS GLP-1R mRNA was present on hPDLCs, and LIRA increased the expression of GLP-1R mRNA. When cultured with 25, 50, 75, 100 and 125 nM LIRA for 24 h, hPDLCs proliferation was enhanced in a dose-dependent manner (P < 0.05), and 100 nM was optimal. LIRA promoted hPDLCs migration in a time-dependent manner. LPS significantly increased the expression of IL-6 and TNF-α (P < 0.01), decreased the formation of mineralization nodes (P < 0.01), and inhibited the expression of ALP and Runx2 (P < 0.05). LIRA treatment blocked the expression of IL-6 and TNF-α (P < 0.01), increased the formation of mineralization nodes (P < 0.01), and enhanced the expression of ALP and Runx2 (P < 0.05). CONCLUSION LIRA can enhance the proliferation, migration, and osteogenic differentiation of hPDLCs and inhibit the inflammatory response. Thus, LIRA may have potential therapeutic use as an adjuvant treatment for human periodontitis, and this effect is independent of hypoglycemic activity.
Recognizing Overlapped Speech in Meetings: A Multichannel Separation Approach Using Neural Networks

The goal of this work is to develop a meeting transcription system that can recognize speech even when utterances of different speakers are overlapped. While speech overlaps have been regarded as a major obstacle in accurately transcribing meetings, a traditional beamformer with a single output has been exclusively used because previously proposed speech separation techniques have critical constraints for application to real meetings. This paper proposes a new signal processing module, called an unmixing transducer, and describes its implementation using a windowed BLSTM. The unmixing transducer has a fixed number, say J, of output channels, where J may be different from the number of meeting attendees, and transforms an input multi-channel acoustic signal into J time-synchronous audio streams. Each utterance in the meeting is separated and emitted from one of the output channels. Then, each output signal can be simply fed to a speech recognition back-end for segmentation and transcription. Our meeting transcription system using the unmixing transducer outperforms a system based on a state-of-the-art neural mask-based beamformer by 10.8%. Significant improvements are observed in overlapped segments. To the best of our knowledge, this is the first report that applies overlapped speech recognition to unconstrained real meeting audio.
Phoneme-to-Articulatory Mapping Using Bidirectional Gated RNN

Deriving articulatory dynamics from the acoustic speech signal has been addressed in several speech production studies. In this paper, we investigate whether it is possible to predict articulatory dynamics from phonetic information without having the acoustic speech signal. The input data may be considered as not sufficiently rich acoustically, as probably there is no explicit coarticulation information but we expect that the phonetic sequence provides compact yet rich knowledge. Motivated by the recent success of deep learning techniques used in the acoustic-to-articulatory inversion, we have experimented around the bidirectional gated recurrent neural network archi-tectures. We trained these models with an EMA corpus, and have obtained good performances similar to the state-of-the-art articulatory inversion from LSF features, but using only the phoneme labels and durations.
A Signal Adaptive Diffusion Filter for Video Coding Using Directional Total Variation

In this paper we combine state of the art video compression with inpainting methods. We introduce a new signal adaptive method to filter the predictions of a hybrid video codec using a constrained optimization approach. The filter is embedded into the framework of HEVC. The efficiency of the HEVC video codec is improved by up to −6.14% Bj Ø ntegaard delta (BD) rate for All Intra.
Enhanced Ctu-Level Inter Prediction with Deep Frame Rate Up-Conversion for High Efficiency Video Coding

Inter prediction serves as the foundation of prediction based hybrid video coding framework. The state-of-the-art video coding standards employ the reconstructed frames as the references, and the motion vectors which convey the relative position shift between the current block and the prediction block are explicitly signalled in the bitstream. In this paper, we propose a high efficient inter prediction scheme by introducing a new methodology based on virtual reference frame, which is effectively generated with the deep neural network such that the motion data does not need to be explicitly signalled. In particular, the high quality virtual reference frame is generated with the deep learning based frame rate up-conversion (FRUC) algorithm from two reconstructed bi-prediction frames. Subsequently, a novel CTU level coding mode termed as direct virtual reference frame (DVRF) mode, is proposed to adaptively compensate for the current to-be-coded block in the sense of rate-distortion optimization (RDO). The proposed scheme is integrated into the HM-16.6 software, and experimental results demonstrate significant superiority of the proposed method, which provides more than 3% coding gains on average for HEVC test sequences.
Monocular Semantic Occupancy Grid Mapping With Convolutional Variational Encoder–Decoder Networks

In this letter, we research and evaluate end-to-end learning of monocular semantic-metric occupancy grid mapping from weak binocular ground truth. The network learns to predict four classes, as well as a camera to bird's eye view mapping. At the core, it utilizes a variational encoder–decoder network that encodes the front-view visual information of the driving scene and subsequently decodes it into a two-dimensional top-view Cartesian coordinate system. The evaluations on Cityscapes show that the end-to-end learning of semantic-metric occupancy grids outperforms the deterministic mapping approach with flat-plane assumption by more than 12% mean intersection-over-union. Furthermore, we show that the variational sampling with a relatively small embedding vector brings robustness against vehicle dynamic perturbations, and generalizability for unseen KITTI data. Our network achieves real-time inference rates of approx. 35 Hz for an input image with a resolution of 256 × 512 pixels and an output map with 64 × 64 occupancy grid cells using a Titan V GPU.
The Cerebrospinal Fluid Inflammatory Response to Preterm Birth

Background: Preterm birth is the leading risk factor for perinatal white matter injury, which can lead to motor and neuropsychiatric impairment across the life course. There is an unmet clinical need for therapeutics. White matter injury is associated with an altered inflammatory response in the brain, primarily led by microglia, and subsequent hypomyelination. However, microglia can release both damaging and trophic factors in response to injury, and a comprehensive assessment of these factors in the preterm central nervous system (CNS) has not been carried out. Method: A custom antibody array was used to assess relative levels of 50 inflammation- and myelination-associated proteins in the cerebrospinal fluid (CSF) of preterm infants in comparison to term controls. Results: Fifteen proteins differed between the groups: BDNF, BTC, C5a, FasL, Follistatin, IL-1β, IL-2, IL-4, IL-9, IL-17A, MIP-1α, MMP8, SPP1, TGFβ, and TNFβ (p < 0.05). To investigate the temporal regulation of these proteins after injury, we mined a gene expression dataset of microglia isolated from a mouse model of developmental white matter injury. Microglia in the experimental model showed dynamic temporal expression of genes encoding these proteins, with an initial and sustained pro-inflammatory response followed by a delayed anti-inflammatory response, and a continuous expression of genes predicted to inhibit healthy myelination. Conclusion: Preterm CSF shows a distinct neuroinflammatory profile compared to term controls, suggestive of a complex neural environment with concurrent damaging and reparative signals. We propose that limitation of pro-inflammatory responses, which occur early after perinatal insult, may prevent expression of myelination-suppressive genes and support healthy white matter development.
A Neural Model to Predict Parameters for a Generalized Command Response Model of Intonation

The Generalised Command Response (GCR) model is a time-local model of intonation that has been shown to lend itself to (cross-language) transfer of emphasis. In order to generalise the model to longer prosodic sequences, we show that it can be driven by a recurrent neural network emulating a spiking neural network. We show that a loss function for error backpropagation can be formulated analogously to that of the Spike Pattern Association Neuron (SPAN) method for spiking networks. The resulting system is able to generate prosody comparable to a state-of-the-art deep neural network implementation, but poten-tially retaining the transfer capabilities of the GCR model.
Trends in sweetened beverages consumption among adults in the Brazilian capitals, 2007–2016

Abstract Objective To analyse trends in sweetened beverages consumption among adults in Brazil between 2007 and 2016. Design A time-series analysis, with data from the Surveillance System of Risk and Protection Factors for Chronic Diseases by Telephone Survey (VIGITEL). The prevalence of regular consumption (≥5 d/week), the average daily consumption (millilitres) and the prevalence of non-consumption of these beverages were analysed. The temporal variations of the indicators were calculated by linear regression. The analyses were performed for the complete set of the evaluated population and stratified by sociodemographic characteristics. Setting Brazilian capitals and Federal District. Subjects Brazilian adults aged ≥18 years (n 519 641). Results There was a reduction in both regular and average daily consumption of sugar- and artificially sweetened beverages (−1·28 percentage points (pp)/year, P=0·001 and −9·63 ml/year, P=0·001, respectively). The same result regarding regular consumption was found when only sugar-sweetened beverages were analysed (−1·11 pp/year, P=0·011). Similar trends were identified in the stratified analyses, with a greater magnitude of reduction among males, young adults, those with higher schooling and residents of more developed regions. Coincidentally, there was an increase in the prevalence of adults who did not consume sweetened beverages (1·54 pp/year, P=0·005). Conclusions The consumption of sweetened beverages decreased during the period. However, a significant portion of the population still referred a daily consumption of these beverages.
Keyword Based Speaker Localization: Localizing a Target Speaker in a Multi-speaker Environment

Speaker localization is a hard task, especially in adverse environmental conditions involving reverberation and noise. In this work we introduce the new task of localizing the speaker who uttered a given keyword, e.g., the wake-up word of a distant-microphone voice command system, in the presence of overlapping speech. We employ a convolutional neural network based localization system and investigate multiple identifiers as additional inputs to the system in order to characterize this speaker. We conduct experiments using ground truth identifiers which are obtained assuming the availability of clean speech and also in realistic conditions where the identifiers are computed from the corrupted speech. We find that the identifier consisting of the ground truth time-frequency mask corresponding to the target speaker provides the best localization performance and we propose methods to estimate such a mask in adverse reverberant and noisy conditions using the considered keyword.
CLINICAL CHARACTERIZATION OF STARGARDT DISEASE PATIENTS WITH THE p.N1868I ABCA4 MUTATION.

PURPOSE To investigate the Stargardt disease phenotype associated with an unusually common and "extremely hypomorphic" ABCA4 variant, p.N1868I. METHODS The charts of 27 patients with p.N1868I on one allele and a severe/deleterious mutation on the other allele were reviewed. Subjective age of onset, best-corrected visual acuity, and stage of disease were recorded for all 27 patients, 18 of whom had multiple visits. When available, fundus photography, spectral domain optical coherence tomography, fundus autofluorescence, full-field electroretinograms, Goldmann visual fields, and fluorescein angiography were included. Five families with multiple affected members were analyzed. RESULTS The median age at symptom onset was 41.5 years, and 3 p.N1868I patients had not developed visual symptoms as of the most recent eye examination. Median best-corrected visual acuity in the better-seeing eye at baseline was 20/25, and the median duration from symptom onset to legal blindness was 25 years. The five families described in this study demonstrated clinically significant intrafamilial variability, and affected family members who did not share the p.N1868I variant had relatively more severe phenotypes. CONCLUSION This study demonstrates the consistency of foveal sparing, the variation in age at onset, the intrafamilial variability, and the prognosis with regard to visual acuity in p.N1868I-associated Stargardt disease.