Miracle-dz/UniFAR-FTUs huggingface dataset:
Event-related potential and EEG oscillatory predictors of verbal memory in mild cognitive impairment

Abstract Reliable biomarkers of memory decline are critical for the early detection of Alzheimer’s disease. Previous work has found three EEG measures, namely the event-related brain potential P600, suppression of oscillatory activity in the alpha frequency range (∼10 Hz) and cross-frequency coupling between low theta/high delta and alpha/beta activity, each of which correlates strongly with verbal learning and memory abilities in healthy elderly and patients with mild cognitive impairment or prodromal Alzheimer’s disease. In the present study, we address the question of whether event-related or oscillatory measures, or a combination thereof, best predict the decline of verbal memory in mild cognitive impairment and Alzheimer’s disease. Single-trial correlation analyses show that despite a similarity in their time courses and sensitivities to word repetition, the P600 and the alpha suppression components are minimally correlated with each other on a trial-by-trial basis (generally |rs| < 0.10). This suggests that they are unlikely to stem from the same neural mechanism. Furthermore, event-related brain potentials constructed from bandpass filtered (delta, theta, alpha, beta or gamma bands) single-trial data indicate that only delta band activity (1–4 Hz) is strongly correlated (r = 0.94, P < 0.001) with the canonical P600 repetition effect; event-related potentials in higher frequency bands are not. Importantly, stepwise multiple regression analyses reveal that the three event-related brain potential/oscillatory measures are complementary in predicting California Verbal Learning Test scores (overall R2’s in 0.45–0.63 range). The present study highlights the importance of combining EEG event-related potential and oscillatory measures to better characterize the multiple mechanisms of memory failure in individuals with mild cognitive impairment or prodromal Alzheimer’s disease.
Differential Changes in Arteriolar Cerebral Blood Volume between Parkinson’s Disease Patients with Normal and Impaired Cognition and Mild Cognitive Impairment (MCI) Patients without Movement Disorder – An Exploratory Study

Cognitive impairment amongst Parkinson’s disease (PD) patients is highly prevalent and associated with an increased risk of dementia. There is growing evidence that altered cerebrovascular functions contribute to cognitive impairment. Few studies have compared cerebrovascular changes in PD patients with normal and impaired cognition and those with mild-cognitive-impairment (MCI) without movement disorder. Here, we investigated arteriolar-cerebral-blood-volume (CBVa), an index reflecting the homeostasis of the most actively regulated segment in the microvasculature, using advanced MRI in various brain regions in PD and MCI patients and matched controls. Our goal is to find brain regions with altered CBVa that are specific to PD with normal and impaired cognition, and MCI-without-movement-disorder, respectively. In PD patients with normal cognition (n=10), CBVa was significantly decreased in the substantia nigra, caudate and putamen when compared to controls. In PD patients with impaired cognition (n=6), CBVa showed a decreasing trend in the substantia nigra, caudate and putamen, but was significantly increased in the presupplementary motor area and intracalcarine gyrus compared to controls. In MCI-patients-without-movement-disorder (n=18), CBVa was significantly increased in the caudate, putamen, hippocampus and lingual gyrus compared to controls. These findings provide important information for efforts towards developing biomarkers for the evaluation of potential risk of PD dementia (PDD) in PD patients. The current study is limited in sample size and therefore is exploratory in nature. The data from this pilot study will serve as the basis for power analysis for subsequent studies to further investigate and validate the current findings.
Novel cholesterol‐dependent regulation of cardiac KATP subunit expression revealed using histone deacetylase inhibitors

We recently discovered that the histone deacetylase inhibitor, trichostatin A (TSA), increases expression of the sulfonylurea receptor 2 (SUR2; Abcc9) subunit of the ATP‐sensitive K+ (KATP) channel in HL‐1 cardiomyocytes. Interestingly, the increase in SUR2 was abolished with exogenous cholesterol, suggesting that cholesterol may regulate channel expression. In the present study, we tested the hypothesis that TSA increases SUR2 by depleting cholesterol and activating the sterol response element binding protein (SREBP) family of transcription factors. Treatment of HL‐1 cardiomyocytes with TSA (30 ng/ml) caused a time‐dependent increase in SUR2 mRNA expression that correlates with the time course of cholesterol depletion assessed by filipin staining. Consistent with the cholesterol‐dependent regulation of SREBP increasing SUR2 mRNA expression, we observe a significant increase in SREBP cleavage and translocation to the nucleus following TSA treatment that is inhibited by exogenous cholesterol. Further supporting the role of SREBP in mediating the effect of TSA on KATP subunit expression, SREBP1 significantly increased luciferase reporter gene expression driven by the upstream SUR2 promoter. Lastly, HL‐1 cardiomyocytes treated with the SREBP inhibitor PF429242 significantly suppresses the effect of TSA on SUR2 gene expression. These results demonstrate that SREBP is an important regulator of KATP channel expression and suggest a novel method by which hypercholesterolemia may exert negative effects on the cardiovascular system, namely, by suppressing expression of the KATP channel.
Biologically active compounds from marine organisms in the strategies for combating coronaviruses

Despite the progress made in immunization and drug development, so far there are no prophylactic vaccines and effective therapies for many viral infections, including infections caused by coronaviruses. In this regard, the search for new antiviral substances continues to be relevant, and the enormous potential of marine resources are a stimulus for the study of marine compounds with antiviral activity in experiments and clinical trials. The highly pathogenic human coronaviruses-severe acute respiratory syndrome-related coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) remain a serious threat to human health. In this review, the authors hope to bring the attention of researchers to the use of biologically active substances of marine origin as potential broad-spectrum antiviral agents targeting common cellular pathways and various stages of the life cycle of different viruses, including coronaviruses. The review has been compiled using references from major databases such as Web of Science, PubMed, Scopus, Elsevier, Springer and Google Scholar (up to June 2020) and keywords such as ‘coronaviruses’, ‘marine organisms’, ‘biologically active substances’, ‘antiviral drugs’, ‘SARS-CoV’, ‘MERS-CoV’, ‘SARS-CoV-2’, ‘3CLpro’, ‘TMPRSS2’, ‘ACE2’. After obtaining all reports from the databases, the papers were carefully analysed in order to find data related to the topic of this review (98 references). Biologically active substances of marine origin, such as flavonoids, phlorotannins, alkaloids, terpenoids, peptides, lectins, polysaccharides, lipids and others substances, can affect coronaviruses at the stages of penetration and entry of the viral particle into the cell, replication of the viral nucleic acid and release of the virion from the cell; they also can act on the host's cellular targets. These natural compounds could be a vital resource in the fight against coronaviruses.
Prostaglandin E2 serves a dual role in regulating the migration of dendritic cells

Dendritic cells (DCs) are the most potent antigen-presenting cells, and are indispensable in the immune system. Prostaglandin E2 (PGE2) has been demonstrated to modulate the migration of DCs, but with inconsistent results. The present study, based on our previous research, used murine bone marrow-derived DCs to elucidate the potential regulatory mechanism of PGE2 on the migration of DCs. The results indicated that PGE2 served a dual role in regulating the migration of DCs in a dose-dependent manner. High concentrations of PGE2 inhibited cell migration, whereas low concentrations exhibited the opposite effect. Flow cytometry revealed that the expression of CC chemokine receptor type 7 on the DC surface was increased following treatment with low concentrations of PGE2 and slightly decreased by high concentrations of PGE2. The effect of PGE2 was indicated to be exerted via reorganizing the F-actin cytoskeleton using confocal micros-copy. Moreover, the regulatory effect of PGE2 on the migration of DCs was validated in vivo. Subsequent gene expression profile analyses using RNA-sequencing technology indicated that PGE2 induced alterations in the expression of multiple downstream genes and signaling pathway molecules associated with cell migration and the cytoskeleton. These findings may provide an improved understanding on the mechanism of DC migration under both pathological and physiological conditions. Moreover, the biological implications of these findings may provide a novel perspective of the immunological surveillance in the progression of different types of diseases.
Digitalization within the MME study program – teaching and assessment of communicative and interprofessional skills in the Heidelberg module via video conference together with a virtual OSCE course

Background: Due to the corona pandemic, we conducted the Heidelberg module of the Master of Medical Education (MME) study program, which focuses on teaching and assessment of communicative and interpofessional skills, digitally for the first time. Method: We outsourced the teaching to a pre-module phase in the weeks upfront. During the module week, the lecturers picked up again and deepened the topics and the participants created, revised and simulated a virtual OSCE course. Results/Conclusion: Evaluation and reflection of the module showed that the digital implementation including an OSCE examination can be an appropriate alternative to a classroom-based training. However, important elements of the MME program that provide networking possibilities and personal exchange can only be replicated in the digital environment to a limited extent. In the future, sensibly applied digital components can be used to enrich the study program.
Cytokinin isopentenyladenine and its glucoside isopentenyladenine‐9G delay leaf senescence through activation of cytokinin‐associated genes

Abstract Cytokinins (CKs) are well‐known as a class of phytohormones capable of delaying senescence in detached leaves. However, CKs are often treated as a monolithic group of compounds even though dozens of CK species are present in plants with varied degrees of reported biological activity. One specific type of CK, isopentenyladenine base (iP), has been demonstrated as having roles in delaying leaf senescence, inhibition of root growth, and promoting shoot regeneration. However, its N‐glucosides isopentenyladenine‐7‐ and ‐9‐glucoside (iP7G, iP9G) have remained understudied and thought of as inactive cytokinins for several decades, despite their relatively high concentrations in plants such as the model species Arabidopsis thaliana. Here we show that iP and one of its glucosides, iP9G, are capable of delaying senescence in leaves, though the glucosides having little to no activity in other bioassays. Additionally, we performed the first transcriptomic study of iP‐delayed cotyledon senescence which shows that iP is capable of upregulating photosynthetic genes and downregulating catabolic genes in detached cotyledons. Transcriptomic analysis also shows iP9G has limited effects on gene expression, but that the few affected genes are CK‐related and are similar to those seen from iP effects during senescence as seen for the type‐A response regulator ARR6. These findings suggest that iP9G functions as an active CK during senescence.
Atorvastatin potentiates the chemosensitivity of human liver cancer cells to cisplatin via downregulating YAP1

Atorvastatin is a competitive inhibitor of β-hydroxy β-methylglutaryl-CoA reductase, which is involved in anticancer effects in numerous types of cancer, including in human liver cancer. However, its functions and underlying mechanisms of chemosensitivity in liver cancer remain to be elucidated. The present study investigated the effect of atorvastatin on cisplatin chemosensitivity and its molecular mechanisms, with a focus on the Yes1-associated transcriptional regulator (YAP1) protein. The present study demonstrated that atorvastatin significantly potentiated chemosensitivity to cisplatin in the liver cancer HepG2 and Huh-7 cell lines. Furthermore, cell survival and apoptosis in liver cancer cell lines were analyzed using MTT assay and flow cytometry, respectively. Atorvastatin suppressed HepG2 and Huh-7 cell viability in a dose-dependent manner, similar to cisplatin and paclitaxel. Subtoxic levels of atorvastatin significantly increased cisplatin-induced apoptosis in Huh-7 cells. Atorvastatin-promoted chemosensitivity was predominantly mediated by caspase 3, caspase 9 and poly-(ADP ribose)-polymerase activation, and YAP1 downregulation. Finally, YAP1 overexpression significantly reversed the susceptibility of Huh-7 cells to cisplatin. Overall, the results of the present study suggested the underlying mechanisms of atorvastatin chemosensitivity in inducing liver cancer cell apoptosis via downregulating YAP1 and implicated the potential application of atorvastatin-potentiated chemosensitivity in liver cancer therapy.
Organizing Single-Walled Carbon Nanotubes on Gold Using a Wet Chemical Self-Assembling Technique

We provide a wet chemical approach for organizing randomly tangled single-walled carbon nanotubes (SWCNTs) on gold surfaces. The as-grown nanotubes were first chemically cut into short pipes and thiol-derivatized at the open ends. The ordered assembly of SWCNTs was made by their spontaneous chemical adsorption to gold via Au−S bonds. Tapping mode atomic force microscopy (AFM) images clearly show that the nanotubes have been organized on gold, forming a self-assembled monolayer structure with a perpendicular orientation. The adsorption kinetics of the nanotubes was very slow in comparison to conventional alkanethiols. The adsorption rate varied inversely with tube length. The nanotubes tend to form bundles as the adsorption propagates, following a “nucleation adsorption mechanism”. This work demonstrates that “giant” carbon nanotubes can be assembled on Au surfaces using wet chemistry similar to that exploited for “small” organic self-assembling species. We believe that assembled nanotube arrays will provi.
Characterization of the indacene S0/S1 conical intersection: an MMVB and CASSCF study

A conical intersection between the S0 and S1 states of s-indacene has been located with the molecular mechanics with valence bond (MMVB) and complete active space SCF (CASSCF) methods. In both cases the intersection minimum is close in energy and geometry to the overall minimum on the S1 surface, and can be reached directly along the coordinate which leads from the Franck—Condon geometry to the minimum on S1. The existence of such an accessible S1/S0 surface crossing leading to efficient non-radiative decay can explain the short S1 excited state lifetime and lack of fluorescence for s-indacene. Based on a comparison with X-ray structures for a derivative of s-indacene, we argue that the CASSCF ordering of S0 and S1 states is the correct one, whereas MMVB inverts the two states. However, because the energy differences involved are a few kcal mol-1, a definitive prediction will probably require a multi-reference correlated level of theory with gradient optimization.
A Critical Compilation of Atomic Transition Probabilities for Neutral and Singly Ionized Iron

We have carried out a new, expanded tabulation of the atomic transition probabilities for allowed and forbidden lines of Fe I and Fe II, based on the critical evaluation of all available literature sources. The compiled data are taken mainly from recent experimental and theoretical results that became available after the publication of our first compilation in 1988. The data are arranged in multiplet format and are ordered according to increasing excitation energies.
A practical mode system for recursive definitions

In call-by-value languages, some mutually-recursive definitions can be safely evaluated to build recursive functions or cyclic data structures, but some definitions (let rec x = x + 1) contain vicious circles and their evaluation fails at runtime. We propose a new static analysis to check the absence of such runtime failures. We present a set of declarative inference rules, prove its soundness with respect to the reference source-level semantics of Nordlander, Carlsson, and Gill [2008], and show that it can be directed into an algorithmic backwards analysis check in a surprisingly simple way. Our implementation of this new check replaced the existing check used by the OCaml programming language, a fragile syntactic criterion which let several subtle bugs slip through as the language kept evolving. We document some issues that arise when advanced features of a real-world functional language (exceptions in first-class modules, GADTs, etc.) interact with safety checking for recursive definitions.
The TALP-UPC System Description for WMT20 News Translation Task: Multilingual Adaptation for Low Resource MT

In this article, we describe the TALP-UPC participation in the WMT20 news translation shared task for Tamil-English. Given the low amount of parallel training data, we resort to adapt the task to a multilingual system to benefit from the positive transfer from high resource languages. We use iterative backtranslation to fine-tune the system and benefit from the monolingual data available. In order to measure the effectivity of such methods, we compare our results to a bilingual baseline system.
Attention Transformer Model for Translation of Similar Languages

This paper illustrates our approach to the shared task on similar language translation in the fifth conference on machine translation (WMT-20). Our motivation comes from the latest state of the art neural machine translation in which Transformers and Recurrent Attention models are effectively used. A typical sequence-sequence architecture consists of an encoder and a decoder Recurrent Neural Network (RNN). The encoder recursively processes a source sequence and reduces it into a fixed-length vector (context), and the decoder generates a target sequence, token by token, conditioned on the same context. In contrast, the advantage of transformers is to reduce the training time by offering a higher degree of parallelism at the cost of freedom for sequential order. With the introduction of Recurrent Attention, it allows the decoder to focus effectively on order of the source sequence at different decoding steps. In our approach, we have combined the recurrence based layered encoder-decoder model with the Transformer model. Our Attention Transformer model enjoys the benefits of both Recurrent Attention and Transformer to quickly learn the most probable sequence for decoding in the target language. The architecture is especially suited for similar languages (languages coming from the same family). We have submitted our system for both Indo-Aryan Language forward (Hindi to Marathi) and reverse (Marathi to Hindi) pair. Our system trains on the parallel corpus of the training dataset provided by the organizers and achieved an average BLEU point of 3.68 with 97.64 TER score for the Hindi-Marathi, along with 9.02 BLEU point and 88.6 TER score for Marathi-Hindi testing set.
Naver Labs Europe’s Participation in the Robustness, Chat, and Biomedical Tasks at WMT 2020

This paper describes Naver Labs Europe’s participation in the Robustness, Chat, and Biomedical Translation tasks at WMT 2020. We propose a bidirectional German-English model that is multi-domain, robust to noise, and which can translate entire documents (or bilingual dialogues) at once. We use the same ensemble of such models as our primary submission to all three tasks and achieve competitive results. We also experiment with language model pre-training techniques and evaluate their impact on robustness to noise and out-of-domain translation. For German, Spanish, Italian, and French to English translation in the Biomedical Task, we also submit our recently released multilingual Covid19NMT model.
Pretrained Language Models and Backtranslation for English-Basque Biomedical Neural Machine Translation

This paper describes the machine translation systems proposed by the University of Technology Sydney Natural Language Processing (UTS_NLP) team for the WMT20 English-Basque biomedical translation tasks. Due to the limited parallel corpora available, we have proposed to train a BERT-fused NMT model that leverages the use of pretrained language models. Furthermore, we have augmented the training corpus by backtranslating monolingual data. Our experiments show that NMT models in low-resource scenarios can benefit from combining these two training techniques, with improvements of up to 6.16 BLEU percentual points in the case of biomedical abstract translations.
TMUOU Submission for WMT20 Quality Estimation Shared Task

We introduce the TMUOU submission for the WMT20 Quality Estimation Shared Task 1: Sentence-Level Direct Assessment. Our system is an ensemble model of four regression models based on XLM-RoBERTa with language tags. We ranked 4th in Pearson and 2nd in MAE and RMSE on a multilingual track.
IST-Unbabel Participation in the WMT20 Quality Estimation Shared Task

We present the joint contribution of IST and Unbabel to the WMT 2020 Shared Task on Quality Estimation. Our team participated on all tracks (Direct Assessment, Post-Editing Effort, Document-Level), encompassing a total of 14 submissions. Our submitted systems were developed by extending the OpenKiwi framework to a transformer-based predictor-estimator architecture, and to cope with glass-box, uncertainty-based features coming from neural machine translation systems.
Multilingual Neural Machine Translation: Case-study for Catalan, Spanish and Portuguese Romance Languages

In this paper, we describe the TALP-UPC participation in the WMT Similar Language Translation task between Catalan, Spanish, and Portuguese, all of them, Romance languages. We made use of different techniques to improve the translation between these languages. The multilingual shared encoder/decoder has been used for all of them. Additionally, we applied back-translation to take advantage of the monolingual data. Finally, we have applied fine-tuning to improve the in-domain data. Each of these techniques brings improvements over the previous one. In the official evaluation, our system was ranked 1st in the Portuguese-to-Spanish direction, 2nd in the opposite direction, and 3rd in the Catalan-Spanish pair.
An Introduction to Fire Dynamics

Acknowledgements Foreword List of Symbols Fire Science and Combustion Heat Transfer and Aerodynamics Limits of Flammability and Premixed Flames Diffusion Flames and Fire Flumes Steady Burning of Liquid and Solid Fuels Ignition: The Initiation of Flaming Combustion Spread of Flame Spontaneous Ignition within Solids and Smouldering Combustion The Pre-flashover Compartment Fire The Post-flashover Compartment Fire The Production and Movement of Smoke References Appendix: Problems.