Miracle-dz/UniFAR-FTUs huggingface dataset:
Complementary and alternative therapies in the palliative setting

Complementary and alternative medicine (CAM) encompasses a wide range of medication, herbal, dietary and physical therapies that are not usually considered within the realm of conventional therapeutics. Approximately two thirds of the Australian population use CAMs and only around half of this number will discuss their use of these products with their doctor. Clinical use is commonly seen in patients with life‐limiting illness, often because they experience a high burden of symptoms. However, it is also the case that many of these therapies do not have demonstrated efficacy, particularly for the often broad list of conditions and symptoms for which they are chosen to be used. Further, depending on whether they are sold as medications, sold as food supplements or imported illegally and distributed via nonstandard therapeutic channels, several products have had reports of toxicity, severe adverse effects, batch irregularities and drug interactions with other therapies. This awareness, together with lack of standardisation of products and lack of interchangeability between brands has made prescribers unwilling to put patients at risk of harm by supporting their use. In this article, we cover general pharmacological principles around use of a small selection of chemicals used in a medical setting to enable some guidance for use.
So ManyFolds, So Little Time: Efficient Protein Structure Prediction With pLMs and MSAs

In recent years, machine learning approaches for de novo protein structure prediction have made significant progress, culminating in AlphaFold which approaches experimental accuracies in certain settings and heralds the possibility of rapid in silico protein modelling and design. However, such applications can be challenging in practice due to the significant compute required for training and inference of such models, and their strong reliance on the evolutionary information contained in multiple sequence alignments (MSAs), which may not be available for certain targets of interest. Here, we first present a streamlined AlphaFold architecture and training pipeline that still provides good performance with significantly reduced computational burden. Aligned with recent approaches such as OmegaFold and ESMFold, our model is initially trained to predict structure from sequences alone by leveraging embeddings from the pretrained ESM-2 protein language model (pLM). We then compare this approach to an equivalent model trained on MSA-profile information only, and find that the latter still provides a performance boost – suggesting that even state-of-the-art pLMs cannot yet easily replace the evolutionary information of homologous sequences. Finally, we train a model that can make predictions from either the combination, or only one, of pLM and MSA inputs. Ultimately, we obtain accuracies in any of these three input modes similar to models trained uniquely in that setting, whilst also demonstrating that these modalities are complimentary, each regularly outperforming the other.
Elucidating a locus coeruleus-hippocampal dopamine pathway for operant reinforcement

Animals can learn to repeat behaviors to earn desired rewards, a process commonly known as reinforcement learning. While previous work has implicated the ascending dopaminergic projections to the basal ganglia in reinforcement learning, little is known about the role of the hippocampus. Here we report that a specific population of hippocampal neurons and their dopaminergic innervation contribute to operant self-stimulation. These neurons are located in the dentate gyrus, receive dopaminergic projections from the locus coeruleus, and express D1 dopamine receptors. Activation of D1+ dentate neurons is sufficient for self-stimulation: mice will press a lever to earn optogenetic activation of these neurons. A similar effect is also observed with selective activation of the locus coeruleus projections to the dentate gyrus, and blocked by D1 receptor antagonism. Calcium imaging of D1+ dentate neurons revealed significant activity at the time of action selection, but not during passive reward delivery. These results reveal the role of dopaminergic innervation of the hippocampus in supporting operant reinforcement.
Borrelia burgdorferi DnaA and the Nucleoid-Associated Protein EbfC Coordinate Expression of the dnaX-ebfC Operon

The dual life cycle of Borrelia burgdorferi, the causative agent of Lyme disease, is characterized by periods of rapid and slowed replication. The expression patterns of many of the spirochete’s virulence factors are impacted by these changes in replication rates. ABSTRACT Borrelia burgdorferi, the spirochete agent of Lyme disease, has evolved within a consistent infectious cycle between tick and vertebrate hosts. The transmission of the pathogen from tick to vertebrate is characterized by rapid replication and a change in the outer surface protein profile. EbfC, a highly conserved nucleoid-associated protein, binds throughout the borrelial genome, affecting expression of many genes, including the Erp outer surface proteins. In B. burgdorferi, like many other bacterial species, ebfC is cotranscribed with dnaX, an essential component of the DNA polymerase III holoenzyme, which facilitates chromosomal replication. The expression of the dnaX-ebfC operon is tied to the spirochete’s replication rate, but the underlying mechanism for this connection was unknown. In this work, we provide evidence that the expression of dnaX-ebfC is controlled by direct interactions of DnaA, the chromosomal replication initiator, and EbfC at the unusually long dnaX-ebfC 5′ untranslated region (UTR). Both proteins bind to the 5′ UTR DNA, with EbfC also binding to the RNA. The DNA binding of DnaA to this region was similarly impacted by ATP and ADP. In vitro studies characterized DnaA as an activator of dnaX-ebfC and EbfC as an antiactivator. We further found evidence that DnaA may regulate other genes essential for replication. IMPORTANCE The dual life cycle of Borrelia burgdorferi, the causative agent of Lyme disease, is characterized by periods of rapid and slowed replication. The expression patterns of many of the spirochete’s virulence factors are impacted by these changes in replication rates. The connection between replication and virulence can be understood at the dnaX-ebfC operon. DnaX is an essential component of the DNA polymerase III holoenzyme, which replicates the chromosome. EbfC is a nucleoid-associated protein that regulates the infection-associated outer surface Erp proteins, as well as other transcripts. The expression of dnaX-ebfC is tied to replication rate, which we demonstrate is mediated by DnaA, the master chromosomal initiator protein and transcription factor, and EbfC.
Chromosome-length genome assemblies of cactophilic Drosophila illuminate links between structural and sequence evolution

A thorough understanding of adaptation and speciation requires model organisms with both a history of ecological and phenotypic study as well as a robust set of genomic resources. For decades, the cactophilic Drosophila species of the southwestern US and northern Mexico have fit this profile, serving as a crucial model system for understanding ecological adaptation, particularly in xeric environments, as well as the evolution of reproductive incompatibilities and speciation. Here, we take a major step towards gaining a complete molecular description of this system by assembling and annotating seven chromosome-length de novo genomes across the three species D. mojavensis, D. arizonae, and D. navojoa. Using this data, we present the most accurate reconstruction of the phylogenetic history of this clade to date. We further demonstrate a relationship between structural evolution and coding evolution both within and between species in this clade, and use this relationship to generate novel hypotheses for adaptation genes. All of our data are presented in a new public database (cactusflybase.arizona.edu), providing one of the most in-depth resources for the analysis of inter- and intraspecific evolutionary genomic data.
Tactile perception of auditory roughness

Auditory roughness resulting of fast temporal beatings is often studied by summing two pure tones with close frequencies. Interestingly, the tactile counterpart of auditory roughness can be provided through touch with vibrotactile actuators. However, whether auditory roughness could also be perceived through touch, and whether they exhibit similar characteristics is unclear. Here, auditory roughness perception and its tactile counterpart were evaluated using similar two pure tones stimuli. Results revealed similar roughness curves in both modalities suggesting similar sensory processing. This study attests of the relevance of such a paradigm for investing auditory and tactile roughness in a multisensory fashion.
Tracking the online construction of linguistic meaning through negation

Combining words and composing meanings is at the basis of human language. However, how the brain constructs meaning online is not well understood. We develop an approach to address this puzzle that exploits the ubiquitous operation of negation. Although negation has been extensively debated among philosophers, psychologists, logicians, and linguists, the cognitive mechanisms supporting this elementary function remain largely unknown. Here, we track the compositional effects of negation (“not”) on scalar adjectives (e.g., “good”) in parametrically designed behavioral and magnetoencephalography (MEG) experiments. The behavioral data show that participants first interpret negated adjectives as affirmative and then modify their interpretation towards the opposite meaning. Decoding analyses of neural activity further reveal that negation does not invert the representation of adjectives but rather weakens their representation, as soon as lexical-semantic representations are encoded in the brain. This suppression mechanism is supported by desynchronization of beta-band activity elicited in sensory-motor areas during the processing of the adjective.
Metagenomic Analyses Reveal the Influence of Depth Layers on Marine Biodiversity on Tropical and Subtropical Regions

The emergence of open ocean global-scale studies provided important information about the genomics of oceanic microbial communities. Metagenomic analyses shed light on the structure of marine habitats, unraveling the biodiversity of different water masses. Many biological and environmental factors can contribute to marine organism composition, such as depth. However, much remains unknown about microbial communities’ taxonomic and functional features in different water layer depths. Here, we performed a metagenomic analysis of 76 publicly available samples from the Tara Ocean Project, distributed in 8 collection stations located in tropical or subtropical regions, and sampled from three layers of depth (surface water layer—SRF, deep chlorophyll maximum layer—DCM, and mesopelagic zone—MES). The SRF and DCM depth layers are similar in abundance and diversity, while the MES layer presents greater diversity than the other layers. Diversity clustering analysis shows differences regarding the taxonomic content of samples. At the domain level, bacteria prevail in most samples, and the MES layer presents the highest proportion of archaea among all samples. Taken together, our results indicate that the depth layer influences microbial sample composition and diversity.
Hill-type computational models of muscle-tendon actuators: a systematic review

Backed by a century of research and development, Hill-type muscle-tendon models are extensively used for countless applications. Lacking recent reviews, the field of Hill-type modelling is however dense and hard-to-explore, with detrimental consequences on knowledge transmission, inter-study consistency, and innovation. Here we present the first systematic review of the field of Hill-type muscle-tendon modelling. It aims to clarify the literature by detailing its contents and proposing updated terminology and definitions, and discussing the state-of-the-art by identifying the latest advances, current gaps, and potential improvements in modelling muscle properties. To achieve this aim, fifty-five criteria-abiding studies were extracted using a systematic search and their Hill-type models assessed according to a completeness evaluation, which identified the modelled muscle-tendon properties, and a modelling evaluation, which considered the level of validation and reusability of the model, and attention given to its modelling strategy and calibration. It is concluded that most models (1) do not significantly advance the dated gold standards in muscle modelling and do not build upon more recent advances, (2) overlook the importance of parameter identification and tuning, (3) are not strongly validated, and (4) are not reusable in other studies. Besides providing a convenient tool supported by extensive supplementary material for understanding the literature, the results of this review open a discussion on the necessity for global recommendations in Hill-type modelling and more frequent reviews to optimize inter-study consistency, knowledge transmission and model reusability.
Loss of N-terminal acetyltransferase A activity induces thermally unstable ribosomal proteins and increases their turnover in Saccharomyces cerevisiae

Protein N-terminal (Nt) acetylation is one of the most abundant modifications in eukaryotes, covering ∼50-80 % of the proteome, depending on species. Cells with defective Nt-acetylation display a wide array of phenotypes such as impaired growth, mating defects and increased stress sensitivity. However, the pleiotropic nature of these effects has hampered our understanding of the functional impact of protein Nt-acetylation. The main enzyme responsible for Nt-acetylation throughout the eukaryotic kingdom is the N-terminal acetyltransferase NatA. Here we employed a multi-dimensional proteomics approach to analyze Saccharomyces cerevisiae lacking NatA activity, which caused global proteome remodeling. Pulsed-SILAC experiments revealed that NatA-deficient strains consistently increased degradation of ribosomal proteins compared to wild type. Explaining this phenomenon, thermal proteome profiling uncovered decreased thermostability of ribosomes in NatA-knockouts. Our data are in agreement with a role for Nt-acetylation in promoting stability for parts of the proteome by enhancing the avidity of protein-protein interactions and folding. Teaser A multidimensional proteomics approach reveals the effect of N-terminal acetylation on Saccharomyces cerevisiae cytosolic ribosomal proteins.
Widespread coding of navigational variables in prefrontal cortex

To navigate, we must represent information about our place in the environment. Traditional research highlights the role of the hippocampal complex in this process. Spurred by recent research highlighting the widespread cortical encoding of cognitive and motor variables previously thought to have localized function, we hypothesized that navigational variables would be likewise encoded widely, especially in the prefrontal cortex, which is often associated with control of volitional behavior. We recorded neural activity from six prefrontal structures while macaques performed a foraging task in an open enclosure. In all six regions, we found strong encoding of allocentric position, head direction, egocentric boundary distance, and linear and angular velocity. These encodings were not accounted for by distance or time to reward. Strength of coding of all variables increase along a ventral-to-dorsal gradient. Together these results argue that encoding of navigational variables is not localized to the hippocampal complex and support the hypothesis that navigation is continuous with other forms of flexible cognition in the service of action.
Spherically symmetric scalar field collapse in any dimension

We describe a formalism and numerical approach for studying spherically symmetric scalar field collapse for an arbitrary spacetime dimension d and cosmological constant $\ensuremath{\Lambda}. $ The prescription uses a double null formalism, and is based on field redefinitions first used to simplify the field equations in generic two-dimensional dilaton gravity. The formalism is used to construct a code in which d and \ensuremath{\Lambda} are input parameters. We reproduce known results in $d=4$ and $d=6$ with $\ensuremath{\Lambda}=0,$ and we present new results for $d=5$ with a zero and negative \ensuremath{\Lambda}.
The formation of disc galaxies in a ΛCDM universe

We study the formation of disc galaxies in a fully cosmological framework using adaptive mesh refinement simulations. We perform an extensive parameter study of the main subgrid processes that control how gas is converted into stars and the coupled effect of supernovae feedback. We argue that previous attempts to form disc galaxies have been unsuccessful because of the universal adoption of strong feedback combined with high star formation efficiencies. Unless extreme amounts of energy are injected into the interstellar medium during supernovae events, these star formation parameters result in bulge-dominated S0/Sa galaxies as star formation is too efficient at z~ 3. We show that a low efficiency of star formation more closely models the subparsec physical processes, especially at high redshift. We highlight the successful formation of extended disc galaxies with scalelengths rd= 4-5 kpc, flat rotation curves and bulge-to-disc ratios of B/D ~ 1/4. Not only do we resolve the formation of a Milky Way-like spiral galaxy, we also observe the secular evolution of the disc as it forms a pseudo-bulge. The disc properties agree well with observations and are compatible with the photometric and baryonic Tully-Fisher relations, the ΣSFR-Σgas (Kennicutt-Schmidt) relation and the observed angular momentum content of spiral galaxies. We conclude that the underlying small-scale star formation physics plays a greater role than previously considered in simulations of galaxy formation. (Less)
Matrix Completion Recommendation Algorithm Based on Attention Mechanism

Matrix completion, as a method of recommendation system, can well represent the user's rating relationship with the item. The traditional matrix completion algorithms rely on a lot of edge information and the model is too complex, and in a real recommendation system, there is usually not enough edge information available, which can lead to a very large recommendation error. Therefore, this paper proposes a matrix completion recommendation model based on attention mechanism without using edge information. The model only uses user-rating matrix, trains the matrix completion model through multi-layer graph convolution neural network, beyond this, uses graph attention mechanism to give different weights to different nodes, which can make full use of the information of import nodes. Experiments on public datasets have shown that our method is superior to the traditional algorithms related to matrix completion.
Generating text from structured data

In this thesis we examine ways of conditionally generating documentscale natural language text given structured input data. Specifically we train Deep Neural Network models on recently introduced RotoWire dataset containing statistical data about basketball matches paired with descriptive summaries. First, we analyse the dataset and propose several preprocessing methods (i.e. Byte Pair Encoding). Next, we train a baseline model based on the EncoderDecoder architecture on the preprocessed dataset. We discuss several problems of the baseline and explore advanced Deep Neural Network architectures that aim to solve them (Copy Attention, Content Selection, Content Planning). We hypothesize that our models are not able to learn the structure of the input data and we propose a method reducing its complexity. Our best model trained on the simplified data manages to outperform the baseline by more than 5 BLEU points.
TEXNOLOGIYASI TIZIMIDA FARMATSEVTIKA TARMOQLARINING IKKILAMCHI RESURSLARIDAN FOYDALANISH THE USE OF SECONDARY RESOURCES OF PHARMACEUTICAL PRODUCTION IN THE SYSTEM OF WASTELESS TECHNOLOGY OF RAW MATERIALS

in comparison with THM -13.4 %. The wastes can be a raw material for obtaining various aromatic and phenolic compounds for the food, pharmaceutical and perfumery industries. The high content of pentosans in AHM and THM wastes (28.7 - 27.3%) allows their use as a raw material for obtaining such valuable goods as hemicellulose, xylose, xylite, as well as furfural and MB. MB AB showed the highest phosphatase activity - 650.5 mg p-nitrophenol kg -1 MB hour -1 . It was found, that the production of phosphatase enzyme by phosphate-solubilizing microorganisms is influenced by both the chemical composition of the substrate and the type of microorganism strain. The purpose of this work is to study the chemical composition of the herb meal of Aconitum septentrionale (AHM) and Thermopsis alterniflora (THM) as a secondary raw material for hemicellulose and xylose as well as microbiological biofertilizer (MB). The object of our study were wastes of AHM and THM, after extraction of pharmaceutical substances with 80% ethanol solution, as well as MB obtained by fermentation of organic waste hydrolysis of meal with phosphate-solubilizing microorganisms Bacillus subtilis BS-26 and Trichoderma harzianum F-888. At the same time four types of MB differing in types of substrate and microbial strain were obtained:
Quote Attribution and Character Networks in Novels

This thesis focuses on extracting information from literary works using tools for language analysis. Our goal is to automatically extract a conversational network of the characters in a novel. We divide the work into three subproblems and solve them separately: Character Extraction, Quote Attribution and Network Creation. The result is an end-to-end tool that gets a text of a novel in English and outputs a visual representation of the character network. Our work is based on existing literature. It presents new ideas and compares the accuracy of various methods for each subproblem.
Loyola eCommons Loyola eCommons Young Tableaux, Multisegments, and PBW Bases Young Tableaux, Multisegments, and PBW Bases

The crystals for ﬁnite dimensional representations of sl n +1 can be realized using Young tableaux. The inﬁnity crystal on the other hand is naturally realized using multisegments, and there is a simple description of each embedding B ( λ ) (cid:44) → B ( ∞ ) in terms of these realizations. The inﬁnity crystal is also parameterized by Lusztig’s PBW basis with respect to any reduced expression for w 0 . We give an explicit description of the unique crystal isomorphism from PBW bases to multisegments in the case where w 0 = s 1 s 2 s 3 · · · s n s 1 · · · s 1 s 2 s 1 , thus obtaining simple formulas for the actions of all crystal operators on this PBW basis. Our proofs use the fact that the twists of the crystal operators by Kashiwara’s involution also have simple descriptions in terms of multisegments, and a characterization of B ( ∞ ) due to Kashiwara and Saito. These results are to varying extents known to experts, but we do not think there is a self-contained exposition of this material in the literature, and our proof of the relationship between multisegments and PBW bases seems to be new.