Miracle-dz/UniFAR-FTUs huggingface dataset:
Hyperphosphorylation of Tau Associates With Changes in Its Function Beyond Microtubule Stability

Tau is a neuronal microtubule associated protein whose main biological functions are to promote microtubule self-assembly by tubulin and to stabilize those already formed. Tau also plays an important role as an axonal microtubule protein. Tau is an amazing protein that plays a key role in cognitive processes, however, deposits of abnormal forms of tau are associated with several neurodegenerative diseases, including Alzheimer disease (AD), the most prevalent, and Chronic Traumatic Encephalopathy (CTE) and Traumatic Brain Injury (TBI), the most recently associated to abnormal tau. Tau post-translational modifications (PTMs) are responsible for its gain of toxic function. Alonso et al. (1996) were the first to show that the pathological tau isolated from AD brains has prion-like properties and can transfer its toxic function to the normal molecule. Furthermore, we reported that the pathological changes are associated with tau phosphorylation at Ser199 and 262 and Thr212 and 231. This pathological version of tau induces subcellular mislocalization in cultured cells and neurons, and translocates into the nucleus or accumulated in the perinuclear region of cells. We have generated a transgenic mouse model that expresses pathological human tau (PH-Tau) in neurons at two different concentrations (4% and 14% of the total endogenous tau). In this model, PH-Tau causes cognitive decline by at least two different mechanisms: one that involves the cytoskeleton with axonal disruption (at high concentration), and another in which the apparent neuronal morphology is not grossly affected, but the synaptic terminals are altered (at lower concentration). We will discuss the putative involvement of tau in proteostasis under these conditions. Understanding tau’s biological activity on and off the microtubules will help shed light to the mechanism of neurodegeneration and of normal neuronal function.
Correction of the Lower Face and Neck

Abstract Rejuvenation of the lower face and neck strives to reverse signs of aging while optimizing the patient's natural anatomy. Common features of an aesthetically pleasing lower face include a well-defined and appropriately balanced mandible and an acute cervicomental angle. Correction of the aging lower face and neck is accomplished through multiple surgical interventions, performed either alone or in combination. Determination of appropriate procedures is based on individual anatomic pathology. Intimate knowledge of facial anatomy and the complexity of the aging process is paramount to achieve a natural and aesthetic result. Thorough patient evaluation and counseling should precede any intervention. Specifically, the surgeon should be cognizant of the patient's skeletal structure, soft tissue distribution, muscular anatomy, and skin quality. Appropriate postoperative care and management of complications are vital to success.
Conception et évaluation d'interfaces de navigation dans les environnements sonores 3D

Nous nous posons ici la question de l’ergonomie d’un dispositif audio 3D, donc de sa mise en œuvre et de son usage. Avant d’entrer dans les details de la conception d’une interface Humain-Machine, nous avons voulu tester prealablement les capacites des indices de la localisation auditive a representer l’espace lui-meme. L’experience a pris la forme d’un jeu de navigation en vue subjective dans une ville virtuelle simplifiee ou le joueur devait s’orienter en mettant a profit les informations sonores qui lui etaient fournies. Nous avons pu decrire assez precisement differents comportements de localisation dynamique, qui expliquent en partie pourquoi un rendu binaural des effets de spatialisation offrent de meilleures performances qu’un rendu stereophonique. D’autre part, nous avons definit l’architecture d’une interface sonore dite « zoomable ». Elle s’articule autour d’une abstraction analytique, composee de deux noeuds audio, dont la semantique est emprunte a la norme MPEG-4 : les DirectiveSounds, sons monophoniques spatialises individuellement et les Surroundingsounds, sons multi-canaux, capturant la configuration spatiale d’une scene sonore grâce a un certain encodage (panning d’amplitude). Une fois developpe un premier prototype de l’interface, nous avons realise une derniere experience tentant d’evaluer la degradation percue lorsque l’on substituait un ensemble de DirectiveSound par un unique SurroundingSound. Les resultats indiquent que les SurroundingSound ne constituent une amelioration significative par rapport a une stereophonie upmixee, que lorsque le nombre de sources qui constituent la scene est suffisamment important.
Deeply learning molecular structure-property relationships using attention- and gate-augmented graph convolutional network

Molecular structure-property relationships are key to molecular engineering for materials and drug discovery. The rise of deep learning offers a new viable solution to elucidate the structure-property relationships directly from chemical data. Here we show that the performance of graph convolutional networks (GCNs) for the prediction of molecular properties can be improved by incorporating attention and gate mechanisms. The attention mechanism enables a GCN to identify atoms in different environments. The gated skip-connection further improves the GCN by updating feature maps at an appropriate rate. We demonstrate that the resulting attention- and gate-augmented GCN could extract better structural features related to a target molecular property such as solubility, polarity, synthetic accessibility and photovoltaic efficiency compared to the vanilla GCN. More interestingly, it identified two distinct parts of molecules as essential structural features for high photovoltaic efficiency, and each of them coincided with the areas of donor and acceptor orbitals for charge-transfer excitations, respectively. As a result, the new model could accurately predict molecular properties and place molecules with similar properties close to each other in a well-trained latent space, which is critical for successful molecular engineering.
MiRNA-155 regulates lymphangiogenesis in natural killer/T-cell lymphoma by targeting BRG1

ABSTRACT Background: miR-155 was up-regulated in natural killer/T-cell lymphoma (NKTCL), an aggressive malignancy, and correlated with disease progression. However, minimal is known on biological activities and underlying mechanisms of miR-155 in NKTCL. In this study, we examined BRG1, a potential target of miR-155, and focused on the miR-155/BRG1 signaling in regulating lymphangiogenesis of NKTCL. Methods: The expression of miR-155, BRG1, VEGFC, and VEGFD was compared between two NKTCL cell lines and normal NK cells. The critical role of miR-155 and STAT3 was assessed using miR-155 inhibitor and STAT3 inhibitor S31-201, respectively. Two biological phenotypes, apoptosis and pro-lymphangiogenesis, were examined in vitro by flow cytometry and lymphatic tube formation, respectively, and in vivo using an NKTCL xenograft model. Results: The miR-155 level negatively correlated with BRG1, but positively with VEGFC in normal NK as well as two NKTCL cell lines. Targeting miR-155 in NKTCL cells significantly boosted BRG1 expression and decreased the activated STAT3 or VEGFC level, leading to enhanced apoptosis and reduced lymphangiogenesis. STAT3 acted downstream of BRG1 and essentially regulated miR-155-mediated up-regulation of VEGFC and pro-lymphangiogenesis. In vivo, targeting miR-155 inhibited primary xenograft growth as well as tumor-associated lymphangiogenesis. Conclusions: By inhibiting BRG1 expression, miR-155 activated STAT3/VEGFC signaling and promoted lymphangiogenesis. In addition, miR-155 also controlled the viability of NKTCL cells. Therefore, targeting miR-155 provides a novel therapy for NKTCL.
Building a language evolution tree based on word vector combination model

In this paper, we try to explore the evolution of language through case calculations. First, we chose the novels of eleven British writers from 1400 to 2005 and found the corresponding works; Then, we use the natural language processing tool to construct the corresponding eleven corpora, and calculate the respective word vectors of 100 high-frequency words in eleven corpora; Next, for each corpus, we concatenate the 100 word vectors from beginning to end into one; Finally, we use the similarity comparison and hierarchical clustering method to generate the relationship tree between the combined eleven word vectors. This tree represents the relationship between eleven corpora. We found that in the tree generated by clustering, the distance between the corpus and the year corresponding to the corpus are basically the same. This means that we have discovered a specific language evolution tree. To verify the stability and versatility of this method, we add three other themes: Dickens's eight works, the 19th century poets' works, and art criticism of recent 60 years. For these four themes, we tested different parameters such as the time span of the corpus, the time interval between the corpora, the dimension of the word vector, and the number of high-frequency public words. The results show that this is fairly stable and versatile.
Sparse natural gesture spotting in free living to monitor drinking with wrist-worn inertial sensors

We present a spotting network composed of Gaussian Mixture Hidden Markov Models (GMM-HMMs) to detect sparse natural gestures in free living. The key technical features of our approach are (1) a method to mine non-gesture patterns that deals with the arbitrary data (Null Class), and (2) an optimisation based on multipopulation genetic programming to approximate spotting network's parameters across target and non-target models. We evaluate our GMM-HMMs spotting network in a novel free living dataset, including totally 35 days of annotated inertial sensor's recordings from seven participants. Drinking was chosen as target gesture. Our method reached an average F1-score of over 74% and clearly outperformed an HMM-based threshold model approach. The results suggest that our spotting network approach is viable for sparse natural pattern spotting.
Decentralized Multi-Antenna Coded Caching with Cyclic Exchanges

This paper considers a single cell multi-antenna base station delivering content to multiple cache enabled single-antenna users. Coding strategies are developed that allow for decentralized placement in the wireless setting. Three different cases namely, max-min multicasting, linear combinations in the complex field, and linear combinations in the finite field, are considered and closed-form rate expressions are provided that hold with high probability. For the case of max-min fair multicasting delivery, we propose a new coding scheme that is capable of working with only two-user broadcasts. A cyclic-exchange protocol for efficient content delivery is proposed and shown to perform almost as well as the original multi-user broadcast scheme.
Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition

The emergence of the digital world has greatly increased the number of accounts and passwords that users must remember. It has also increased the need for secure access to personal information in the cloud. Biometrics is one approach to person recognition, which can be used in identification as well as authentication. Among the various modalities that have been developed, electroencephalography (EEG)-based biometrics features unparalleled universality, distinctiveness and collectability, while minimizing the risk of circumvention. However, commercializing EEG-based person recognition poses a number of challenges. This article reviews the various systems proposed over the past few years with a focus on the shortcomings that have prevented wide-scale implementation, including issues pertaining to temporal stability, psychological and physiological changes, protocol design, equipment and performance evaluation. We also examine several directions for the further development of usable EEG-based recognition systems as well as the niche markets to which they could be applied. It is expected that rapid advancements in EEG instrumentation, on-device processing and machine learning techniques will lead to the emergence of commercialized person recognition systems in the near future.
A 32-year-old man with hypoxemia and bilateral upper-lobe predominant ground-glass infiltrates on chest imaging

Abstract Diffuse alveolar hemorrhage (DAH) is a rare, but potentially fatal, complication of antiphospholipid syndrome, and may present with acute and fulminant symptoms. We report a case of DAH presenting as sudden onset dyspnea in a gentleman with known antiphospholipid syndrome. Chest computed tomography angiography with pulmonary embolism protocol showed right lower lobe segmental filling defects, upper-lobe predominant diffuse ground-glass opacities, and centrilobular nodules bilaterally. The presence of DAH can be confirmed by bronchoalveolar lavage with serial aliquots, but this procedure typically does not elucidate the specific etiology for the hemorrhage. The treatment for patients with severe disease typically consists of a combination of immunosuppressive medications in the form of high-dose intravenous glucocorticoids plus rituximab, cyclophosphamide or mycophenolate; and/or plasma exchange. This case both provides an example of high-quality diagnostic imaging of diffuse alveolar hemorrhage as well as demonstrates the clinical and image-based improvement after treatment.
Large-Scale Circuitry Interactions Upon Earthquake Experiences Revealed by Recurrent Neural Networks

Brain dynamics has recently received increasing interest due to its significant importance in basic and clinical neurosciences. However, due to inherent difficulties in both data acquisition and data analysis methods, studies on large-scale brain dynamics of mouse with local field potential (LFP) recording are very rare. In this paper, we did a series of works on modeling large-scale mouse brain dynamic activities responding to fearful earthquake. Based on LFP recording data from 13 brain regions that are closely related to fear learning and memory and the effective Bayesian connectivity change point model, we divided the response time series into four stages: “Before,” “Earthquake,” “Recovery,” and “After. ” We first reported the changes in power and theta–gamma coupling during stage transitions. Then, a recurrent neural network model was designed to model the functional dynamics in these thirteen brain regions and six frequency bands in response to the fear stimulus. Interestingly, our results showed that the functional brain connectivities in theta and gamma bands exhibited distinct response processes: in theta band, there is a separated–united–separated alternation in whole-brain connectivity and a low-high-low change in connectivity strength; however, gamma bands have a united–separated–united transition and a high-low-high alternation in connectivity pattern and strength. In general, our results offer a novel perspective in studying functional brain dynamics under fearful stimulus and reveal its relationship to the brain’s structural connectivity substrates.
Construction of the Pentacyclic Core and Formal Total Synthesis of (rac)‐Renieramycin T

Abstract Invited for this month's cover picture is the group of Professor Naoki Saito at the Graduate School of Pharmaceutical Sciences, Meiji Pharmaceutical University (Japan). They achieved the first total synthesis of renieramycin T in 2016, and they have been following an alternative route to supply a large amount of it in order to promote research of the next stage, such as structure–activity relationship studies. This paper reports a formal total synthesis in 21 steps from a known piperazine‐2,5‐dione derivative. The key step of this synthesis is the modified Pictet–Spengler cyclization of a primary amine with an oxomalonic acid ester derivative followed by decarboxylation, and stereo‐controlled protonation at C‐1 position of the enol intermediate from the less‐hindered face. Read the full text of their Full Paper at https://doi.org/10.1002/open.201800112.
Automated Person Detection in Dynamic Scenes to Assist People with Vision Impairments: An Initial Investigation

We propose a computer vision system that can automatically detect people in dynamic real-world scenes, enabling people with vision impairments to have more awareness of, and interactions with, other people in their surroundings. As an initial step, we investigate the feasibility of four camera systems that vary in their placement, field-of-view, and image distortion for: (i) capturing people generally; and (ii) detecting people via a specific person-pose estimator. Based on our findings, we discuss future opportunities and challenges for detecting people in dynamic scenes, and for communicating that information to visually impaired users.
Neutrino Mass Ordering from Oscillations and Beyond: 2018 Status and Future Prospects

The ordering of the neutrino masses is a crucial input for a deep understanding of flavor physics, and its determination may provide the key to establish the relationship among the lepton masses and mixings and their analogous properties in the quark sector. The extraction of the neutrino mass ordering is a data-driven field expected to evolve very rapidly in the next decade. In this review, we both analyze the present status and describe the physics of subsequent prospects. Firstly, the different current available tools to measure the neutrino mass ordering are described. Namely, reactor, long-baseline (accelerator and atmospheric) neutrino beams, laboratory searches for beta and neutrinoless double beta decays and observations of the cosmic background radiation and the large scale structure of the universe are carefully reviewed. Secondly, the results from an up-to-date comprehensive global fit are reported: the Bayesian analysis to the 2018 publicly available oscillation and cosmological data sets provides strong evidence for the normal neutrino mass ordering versus the inverted scenario, with a significance of 3.5 standard deviations. This preference for the normal neutrino mass ordering is mostly due to neutrino oscillation measurements. Finally, we shall also emphasize the future perspectives for unveiling the neutrino mass ordering. In this regard, apart from describing the expectations from the aforementioned probes, we also focus on those arising from alternative and novel methods, as 21 cm cosmology, core-collapse supernova neutrinos and the direct detection of relic neutrinos.
Increased risk profile in the treatment of patients with symptomatic degenerative aortic valve stenosis over the last 10 years

Introduction Currently, Cardiology Centres are overfilled with patients with degenerative aortic valve stenosis (DAS), usually eldery, with severe concommittant comorbidities, who are referred for further decisions and possible intervention. Aim To evaluate changes in the risk profile of patients with severe DAS admitted to the cardiology department a decade ago compared with patients currently being admitted. Material and methods We retrospectively evaluated all patients admitted with confirmed severe DAS, hospitalized during 2005–2006 (group I: 140 patients) and in 2016 (group II: 152 patients), admitted for aortic valve intervention. A standard transthoracic echocardiogram, cardiovascular symptom and risk factor distribution, perioperative risk with the logistic EuroSCORE II and STS mortality scores were obtained. Results Patients in group II were significantly older (p < 0.001), had more cardiovascular risk factors, and more often presented with atrial fibrillation (27% vs. 11.4%, p = 0.001), renal impairment (34.9% vs. 22.8%; p = 0.024), severe lung disease (17.1% vs. 2.1%, p < 0.001), and extracardiac arteriopathy (40.1% vs. 17.8%, p < 0.001). The aortic valve area (AVA) (p = 0.356), mean-transvalvular pressure gradient (p = 0.215), and left ventricular ejection fraction (p = 0.768) were similar in both groups. However, the prevalence of pulmonary hypertension, severe mitral regurgitation, and low-flow, low-gradient DAS were 3.1-, 8.4- and 1.84-fold more frequent in group II than group I. The percentages of subjects with EuroSCORE II and STS scores ≥ 4% in 2005–2006 were 7.1% and 6.4%, as compared to 27% and 26.3% in 2016 (both p < 0.001). 22% of patients in 2016, as compared to 31% in 2005/2006, were considered ineligible for DAS intervention. Conclusions In just a decade, the risk profile of patients admitted with DAS has increased hugely, mainly due to older age, accumulation of comorbidities and more advanced disease at presentation. Although transcatheter aortic valve intervention has expanded the indications for intervention in high-risk patients, the number of patients disqualified from interventional treatment remains high.
Long-term safety and efficacy of weekly subcutaneous tocilizumab monotherapy in patients with rheumatoid arthritis who had an inadequate response to subcutaneous tocilizumab every other week: Results from the open-label extension of the SHINOBI study

Abstract Objective: To evaluate the long-term safety and efficacy of subcutaneous tocilizumab (TCZ-SC) monotherapy administered weekly (qw) in patients with rheumatoid arthritis who had an inadequate response to TCZ-SC every other week (q2w). Methods: Patients who completed 12 weeks of double-blind treatment with either TCZ-SC q2w monotherapy or TCZ-SC qw monotherapy were switched to or continued to receive open-label treatment with TCZ-SC qw monotherapy for 40 weeks. Safety and efficacy were assessed. Subgroup analyses of Disease Activity Score based on 28 joints using erythrocyte sedimentation rate (DAS28-ESR) were performed at 12 weeks. Results: The incidence of adverse events was 464.4/100 patient-years (PY). The incidence of infection was 121.3/100 PY. The safety profile of TCZ-SC qw monotherapy was consistent with that of prior studies of TCZ. No additional safety concerns were observed. Improvement from baseline in DAS28-ESR was maintained at week 52 in patients who continued TCZ-SC qw and improved in patients who switched from TCZ-SC q2w to qw. At week 12, the efficacy of TCZ-SC qw monotherapy was greater than that of TCZ-SC q2w monotherapy irrespective of weight and BMI subgroups. Conclusion: The long-term weekly dosing of TCZ-SC monotherapy was well tolerated and efficacy was maintained over 52 weeks.