Miracle-dz/UniFAR-FTUs huggingface dataset:
Costunolide prevents renal ischemia-reperfusion injury in rats by reducing autophagy, apoptosis, inflammation, and DNA damage

Objective(s): Renal ischemia-reperfusion (I/R) is a vital health condition leading to acute kidney injury. Costunolide (COST) is an actively used molecule clinically for its anti-inflammatory, antioxidant, and immunomodulatory properties. In the present study, we searched for the possible protective effects of COST against renal ischemia/reperfusion (I/R) injury in rats. Materials and Methods: We established a renal I/R rat model. We divided forty rats into four groups: group I (sham), group II (I/R), group III (I/R+COST 5 mg/kg), and group IV (I/R+COST 10 mg/kg). We collected blood, kidney, and lung samples for analysis. Results: COST administration performed anti-oxidant and anti-inflammatory activity by reducing oxidant parameters and proinflammatory cytokine levels. COST alleviated DNA damage through declining 8-hydroxydeoxyguanosine (8-OHdG) levels. In addition, COST diminished tubular damage and inflammation by reducing kidney injury molecule-1 (KIM-1) production. COST administration also ameliorated apoptosis and autophagy by decreasing caspase-3 and microtubule-associated protein light chain 3B (MAPLC3, LC3B) expression. Conclusion: COST demonstrated protective effects against renal I/R-induced injury.
Recent progress in the intranasal PLGA-based drug delivery for neurodegenerative diseases treatment

One of the most challenging problems of the current treatments of neurodegenerative diseases is related to the permeation and access of most therapeutic agents to the central nervous system (CNS), prevented by the blood-brain barrier (BBB). Recently, intranasal (IN) delivery has opened new prospects because it directly delivers drugs for neurological diseases into the brain via the olfactory route. Recently, PLGA-based nanocarriers have attracted a lot of interest for IN delivery of drugs. This review gathered clear and concise statements of the recent progress of the various developed PLGA-based nanocarriers for IN drug delivery in brain diseases including Alzheimer’s, Parkinson’s, brain tumors, ischemia, epilepsy, depression, and schizophrenia. Subsequently, future perspectives and challenges of PLGA-based IN administration are discussed briefly.
Roles of the interaction with children and families in mediating the association between digital health literacy and well-being of early childhood teachers in Portugal: A cross-sectional study

Aim To analyze the associations between early childhood education (ECE) teachers´ digital health literacy (DHL) and well-being, and to determine whether the ECE teachers´ interaction with children and family mediated these associations. Methods A total of 853 early childhood teachers, predominantly women (99.4%) participated in this cross-sectional study. The participants had a mean age of 39.9 years (standard deviation SD = 8.2). Data was collected through an online survey. DHL was assessed using five subscales adapted to the new coronavirus context, and the professionals´ well-being was measured using the WHO-5 well-being scale. Binary logistic regression and mediation analysis were used to analyze the data. Results ECE teachers’ DHL in dimensions of “information searching” and “determining relevance” had both direct and indirect effect on their well-being. Specifically, higher DHL in these dimensions was associated with better well-being. The dimension “evaluating reliability” had an indirect positive effect on well-being by promoting interaction with children. Conclusion These findings suggest that improving ECE teachers´ DHL could have a positive effect on their well-being and their interactions with children. Therefore, it is recommended to develop health promotion practices aimed at enhancing DHL among ECE teachers. Additionally, integrating DHL contents and competencies more prominently into the qualification, further education and training of ECE teachers may help equip them with the necessary skills to access and apply health information effectively. This, in turn, can enhance interactions with children and contribute to their overall well-being.
Violence in fishing, hunting, and gathering societies of the Atacama Desert coast: A long-term perspective (10,000 BP—AD 1450)

In this study, we examine the long-term trajectory of violence in societies that inhabited the coast of the Atacama Desert in northern Chile using three lines of evidence: bioarchaeology, geoarchaeology and socio-cultural contexts (rock art, weapons, and settlement patterns). These millennia-old populations adopted a way of life, which they maintained for 10,000 years, based on fishing, hunting, and maritime gathering, complementing this with terrestrial resources. We analyzed 288 adult individuals to search for traumas resulting from interpersonal violence and used strontium isotopes 87Sr/86Sr as a proxy to evaluate whether individuals that showed traces of violence were members of local or non-local groups. Moreover, we evaluated settlement patterns, rock art, and weapons. The results show that the violence was invariant during the 10,000 years in which these groups lived without contact with the western world. During the Formative Period (1000 BC-AD 500), however, the type of violence changed, with a substantial increase in lethality. Finally, during the Late Intermediate Period (AD 1000–1450), violence and lethality remained similar to that of the Formative Period. The chemical signal of Sr shows a low frequency of individuals who were coastal outsiders, suggesting that violence occurred between local groups. Moreover, the presence of weapons and rock art depicting scenes of combat supports the notion that these groups engaged in violence. By contrast, the settlement pattern shows no defensive features. We consider that the absence of centralized political systems could have been a causal factor in explaining violence, together with the fact that these populations were organized in small-scale grouping. Another factor may have been competition for the same resources in the extreme environments of the Atacama Desert. Finally, from the Formative Period onward, we cannot rule out a certain level of conflict between fishers and their close neighbors, the horticulturalists.
Development of a yeast cell factory for production of aromatic secondary metabolites

Aromatic amino acids are precursors of numerous plant secondary metabolites with diverse biological functions. Many of these secondary metabolites are already being used as active pharmaceutical or nutraceutical ingredients, and there are numerous exploratory studies of other compounds with promising applications. p-Coumaric acid is derived from aromatic amino acids and, besides being a valuable chemical building block, it serves as precursor for biosynthesis of many secondary metabolites, such as polyphenols, flavonoids, and some polyketides. Here we developed a p-coumaric acid-overproducing Saccharomyces cerevisiae platform strain. First, we reduced by-product formation by knocking out phenylpyruvate decarboxylase ARO10 and pyruvate decarboxylase PDC5. Second, different versions of feedback-resistant DAHP synthase and chorismate mutase were overexpressed. Finally, we identified shikimate kinase as another important fluxcontrolling step in the aromatic amino acid pathway by overexpressing enzymes from Escherichia coli, homologous to the pentafunctional enzyme Aro1p and to the bifunctional chorismate synthase-flavin reductase Aro2p. The highest titer of p-coumaric acid of 1.9370. 26 g L 1 was obtained, when overexpressing tyrosine ammonia-lyase TAL from Flavobacterium johnsoniaeu, DAHP synthase ARO4, chorismate mutase ARO7 and E. coli shikimate kinase II (aroL) in Δpdc5Δaro10 strain background. To our knowledge this is the highest reported titer of an aromatic compound produced by yeast. The developed S. cerevisiae strain represents an attractive platform host for production of pcoumaric-acid derived secondary metabolites, such as flavonoids, polyphenols, and polyketides. & 2015 International Metabolic Engineering Society Published by Elsevier Inc. On behalf of International Metabolic Engineering Society. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Engineering Yeast Hexokinase 2 for Improved Tolerance Toward Xylose-Induced Inactivation

Hexokinase 2 (Hxk2p) from Saccharomyces cerevisiae is a bi-functional enzyme being both a catalyst and an important regulator in the glucose repression signal. In the presence of xylose Hxk2p is irreversibly inactivated through an autophosphorylation mechanism, affecting all functions. Consequently, the regulation of genes involved in sugar transport and fermentative metabolism is impaired. The aim of the study was to obtain new Hxk2p-variants, immune to the autophosphorylation, which potentially can restore the repressive capability closer to its nominal level. In this study we constructed the first condensed, rationally designed combinatorial library targeting the active-site in Hxk2p. We combined protein engineering and genetic engineering for efficient screening and identified a variant with Phe159 changed to tyrosine. This variant had 64% higher catalytic activity in the presence of xylose compared to the wild-type and is expected to be a key component for increasing the productivity of recombinant xylose-fermenting strains for bioethanol production from lignocellulosic feedstocks.
230Th/U and 14C dating of mollusc shells from the coasts of the Caspian, Barents, White and Black Seas

We dated Holocene and Late Pleistocene mollusc shells collected from coastal sediments of the Caspian, Barents, White and Black Seas by means of both a modified 230Th/U method and the radiocarbon method. Essence of the modification is the removal of the surface (about 1/3 of the weight) of the mollusc shells by nitric acid as it may contain adsorbed detrital 232Th and 230Th. The 230Th/U dates of the inner part of the shells do not require detrital correction with the 232Th activity and well agree with the corresponding reservoir-corrected and calibrated 14C ages of mollusc shells with ages between 1300 and 13,500 BP. We tested the modified 230Th/U method on thick-walled and well-preserved mollusc shells from the transgression sediments of the Barentz, White and Black Seas derived during the Mikulino Interglacial (MIS 5e) and the Early Valday Glaciation (MIS 5c). The 230Th/U ages of the inner part of the shells from the Boreal (Eem) transgression sediments of the Barentz and White Seas ranged from 86 to 114 ka and those from the Karangat (Eem) transgression in the Black Sea (Maly Kut and Eltigen sections) from 95 to 115 ka. The new 230Th/U dates of the shells from the section Eltigen ranged from 100 to 125 ka.
Vulnerability to climate change of United States marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean

Climate change and climate variability are affecting marine mammal species and these impacts are projected to continue in the coming decades. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species using currently available information. We conducted a trait-based climate vulnerability assessment using expert elicitation for 108 marine mammal stocks and stock groups in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. Our approach combined the exposure (projected change in environmental conditions) and sensitivity (ability to tolerate and adapt to changing conditions) of marine mammal stocks to estimate vulnerability to climate change, and categorize stocks with a vulnerability index. The climate vulnerability score was very high for 44% (n = 47) of these stocks, high for 29% (n = 31), moderate for 20% (n = 22), and low for 7% (n = 8). The majority of stocks (n = 78; 72%) scored very high exposure, whereas 24% (n = 26) scored high, and 4% (n = 4) scored moderate. The sensitivity score was very high for 33% (n = 36) of these stocks, high for 18% (n = 19), moderate for 34% (n = 37), and low for 15% (n = 16). Vulnerability results were summarized for stocks in five taxonomic groups: pinnipeds (n = 4; 25% high, 75% moderate), mysticetes (n = 7; 29% very high, 57% high, 14% moderate), ziphiids (n = 8; 13% very high, 50% high, 38% moderate), delphinids (n = 84; 52% very high, 23% high, 15% moderate, 10% low), and other odontocetes (n = 5; 60% high, 40% moderate). Factors including temperature, ocean pH, and dissolved oxygen were the primary drivers of high climate exposure, with effects mediated through prey and habitat parameters. We quantified sources of uncertainty by bootstrapping vulnerability scores, conducting leave-one-out analyses of individual attributes and individual scorers, and through scoring data quality for each attribute. These results provide information for researchers, managers, and the public on marine mammal responses to climate change to enhance the development of more effective marine mammal management, restoration, and conservation activities that address current and future environmental variation and biological responses due to climate change.
Expert-Enhanced Machine Learning for Cardiac Arrhythmia Classi(cid:28)cation

We propose a new method for the classi(cid:28)cation task of distinguishing atrial (cid:28)brillation (AFib) from regular atrial tachycardias including atrial (cid:29)utter (AFlu) on the basis of a surface electrocardiogram (ECG). Although recently many approaches for an automatic classi(cid:28)cation of cardiac arrhythmia were proposed, to our knowledge none of them can distinguish between these two. We discuss reasons why deep learning might not yield satisfactory results for this task. We generate new and clinically interpretable features using mathematical optimization for subsequent use within a machine learning (ML) model. These features are generated from the same input data and by solving an additional regression problem with complicated combinatorial substructures. The resulting model can thus also be seen as a completely novel ML model that incorporates expert knowledge on the pathophysiology of AFlu. Our approach achieved an unprecedented accuracy of 82.84% and an excellent area under the ROC curve of 0 . 9 . One additional advantage of our approach is the inherent interpretability of the classi(cid:28)cation results. Our features give insight into a possibly occurring multi-level atrioventricular
Hepatoprotective and antifibrotic effects of trans-chalcone against bile duct ligation-induced liver fibrosis in rats

Objective(s): Several lines of research have shown that hepatic fibrosis is one of the leading causes of death worldwide. Trans-chalcone is a flavonoid precursor with anti-oxidant and anti-inflammatory effects. The present study was conducted to examine the antifibrotic properties of trans-chalcone on bile duct ligation (BDL)-induced liver cholestasis in rats. Materials and Methods: Following the BDL operation, trans-chalcone at doses of 12, 24, and 50 mg/kg was administered orally once a day for 45 consecutive days. Serum levels of liver indices, including alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total and direct bilirubin, and lipid profile in addition to blood urea nitrogen (BUN) and creatinine, were measured. Additionally, catalase (CAT) and superoxide dismutase (SOD) activities were assessed in liver homogenates. Histopathological evaluations were performed using Masson trichrome (MT) and hematoxylin and eosin (H&E) staining. Results: The elevated levels of liver enzymes, total and direct bilirubin, BUN, creatinine, cholesterol, triglyceride, and low-density lipoprotein (LDL) induced by BDL were significantly reduced following trans-chalcone administration; while serum level of high-density lipoprotein (HDL) increased. Besides, treatment with trans-chalcone elevated the activities of CAT and SOD in the liver tissues of the animals with BDL surgery. According to MT and H&E staining, BDL-induced histopathological changes, including infiltration of inflammatory cells, hepatocyte necrosis, ductal hyperplasia, and collagen deposition were ameliorated using trans-chalcone administration. Conclusion: It can be concluded from the present study that trans-chalcone, possibly by its anti-oxidant and anti-inflammatory properties, may exert hepatoprotective and antifibrotic effects in BDL-induced liver fibrosis.
Towards Effective Disambiguation for Machine Translation with Large Language Models

Resolving semantic ambiguity has long been recognised as a central challenge in the field of Machine Translation. Recent work on benchmarking translation performance on ambiguous sentences has exposed the limitations of conventional Neural Machine Translation (NMT) systems, which fail to handle many such cases. Large language models (LLMs) have emerged as a promising alternative, demonstrating comparable performance to traditional NMT models while introducing new paradigms for controlling the target outputs. In this paper, we study the capabilities of LLMs to translate “ambiguous sentences” - i.e. those containing highly polysemous words and/or rare word senses. We also propose two ways to improve their disambiguation capabilities, through a) in-context learning and b) fine-tuning on carefully curated ambiguous datasets. Experiments show that our methods can match or outperform state-of-the-art systems such as DeepL and NLLB in four out of five language directions. Our research provides valuable insights into effectively adapting LLMs to become better disambiguators during Machine Translation. We release our curated disambiguation corpora and resources at https://data.statmt. org/ambiguous-europarl.
Generalize Synchronization Mechanism: Specification, Properties, Limits

Shared resources synchronization is a well studied problem, in both shared memory environment or distributed memory environment. Many synchronization mechanisms are proposed, with their own way to reach certain consistency level. This thesis further found that there is no perfect synchronization mechanism. Each of them has its properties at different level. For example, to enforce strong consistency, writers may loose writing freedom or it would take more time to coordinate. This thesis proposes a framework to generalize all synchronization mechanism in a formal way for better reasoning on properties, from the perspective of multi-writer to single-writer convergence. Therefore, limitations prevent a synchronization mechanism from achieving every property at its optimal level. CAP and ROLL were proposed in previous works to explain such. CAP theorem states that it can only achieve two of Consistency, Availability and Partition tolerance properties. ROLL Theorem uses a framework to model leaderless SMR protocol and states quorum size and fault tolerance are trading off. The thesis covers five properties in a more understandable way to analyze trade-offs and explore new mechanisms.
Infinitesimal deformations of opers in positive characteristic and the de Rham cohomology of symmetric products

The Eichler-Shimura isomorphism describes a certain cohomology group with coefficients in a space of polynomials by using holomorphic modular/cusp forms. It determines a canonical decomposition of the corresponding de Rham cohomology group associated to a specific oper on a Riemann surface. One purpose of the present paper is to establish its analogue for opers in positive characteristic. We first discuss some basic properties on the (parabolic) de Rham cohomology groups and deformation spaces of $G$-opers (where $G$ is a semisimple algebraic group of adjoint type) in a general formulation. In particular, it is shown that the deformation space of a $G$-oper induced from an $\mathrm{SL}_2$-oper decomposes into a direct sum of the (parabolic) de Rham cohomology groups of its symmetric products. As a consequence, we obtain an Eichler-Shimura-type decomposition for dormant opers on general pointed stable curves by considering a transversal intersection of related spaces in the de Rham moduli space.
Enabling Quartile-based Estimated-Mean Gradient Aggregation As Baseline for Federated Image Classifications

Federated Learning (FL) has revolutionized how we train deep neural networks by enabling decentralized collaboration while safeguarding sensitive data and improving model performance. However, FL faces two crucial challenges: the diverse nature of data held by individual clients and the vulnerability of the FL system to security breaches. This paper introduces an innovative solution named Estimated Mean Aggregation (EMA) that not only addresses these challenges but also provides a fundamental reference point as a $\mathsf{baseline}$ for advanced aggregation techniques in FL systems. EMA's significance lies in its dual role: enhancing model security by effectively handling malicious outliers through trimmed means and uncovering data heterogeneity to ensure that trained models are adaptable across various client datasets. Through a wealth of experiments, EMA consistently demonstrates high accuracy and area under the curve (AUC) compared to alternative methods, establishing itself as a robust baseline for evaluating the effectiveness and security of FL aggregation methods. EMA's contributions thus offer a crucial step forward in advancing the efficiency, security, and versatility of decentralized deep learning in the context of FL.
A Multiscale Autoencoder (MSAE) Framework for End-to-End Neural Network Speech Enhancement

Neural network approaches to single-channel speech enhancement have received much recent attention. In particular, mask-based architectures have achieved significant performance improvements over conventional methods. This paper proposes a multiscale autoencoder (MSAE) for mask-based end-to-end neural network speech enhancement. The MSAE performs spectral decomposition of an input waveform within separate band-limited branches, each operating with a different rate and scale, to extract a sequence of multiscale embeddings. The proposed framework features intuitive parameterization of the autoencoder, including a flexible spectral band design based on the Constant-Q transform. Additionally, the MSAE is constructed entirely of differentiable operators, allowing it to be implemented within an end-to-end neural network, and be discriminatively trained. The MSAE draws motivation both from recent multiscale network topologies and from traditional multiresolution transforms in speech processing. Experimental results show the MSAE to provide clear performance benefits relative to conventional single-branch autoencoders. Additionally, the proposed framework is shown to outperform a variety of state-of-the-art enhancement systems, both in terms of objective speech quality metrics and automatic speech recognition accuracy.
Phase-ordering kinetics of the asymmetric Coulomb glass model.

We present results for phase-ordering kinetics in the Coulomb glass (CG) model, which describes electrons on a lattice with unscreened Coulombic repulsion. The filling factor is denoted by K∈[0,1]. For a square lattice with K=0.5 (symmetric CG), the ground state is a checkerboard with alternating electrons and holes. In this paper, we focus on the asymmetric CG where K≲0.5, i.e., the ground state is checkerboard-like with excess holes distributed uniformly. There is no explicit quenched disorder in our system, though the Coulombic interaction gives rise to frustration. We find that the evolution morphology is in the same dynamical universality class as the ordering ferromagnet. Further, the domain growth law is slightly slower than the Lifshitz-Cahn-Allen law, L(t)∼t^{1/2}, i.e., the growth exponent is underestimated. We speculate that this could be a signature of logarithmic growth in the asymptotic regime.