Miracle-dz/UniFAR-FTUs huggingface dataset:
Low expression of microRNA-328 can predict sepsis and alleviate sepsis-induced cardiac dysfunction and inflammatory response

Sepsis often leads to cardiac dysfunction and inflammation. This study investigated the clinical value of microRNA-328 (miR-328) in sepsis and its role in cardiac dysfunction and inflammation caused by sepsis. The expression level of miR-328 in the serum of the subjects was detected by qRT-PCR. Receiver operating characteristic (ROC) curve measured the diagnostic value of miR-328 in sepsis. Rat sepsis model was established to detect left ventricular systolic pressure (LVSP), left ventricular end-diastolic pressure (LVEDP), and maximal rate of increase/decrease of left ventricular pressure (±dp/dtmax). Myocardial injury markers serum cardiac troponin I (cTnI), myocardial kinase isoenzyme (CK-MB), and inflammatory factors were detected by enzyme-linked immunosorbent assay (ELISA). miR-328 expression was assessed in serum of sepsis patients and in rat models of sepsis. The AUC of ROC curve was 0.926, sensitivity 87.60%, and specificity 86.36%. Compared with the sham group, LVSP and +dp/dtmax were decreased in the rat model of sepsis. LVEDP, -dp/dtmax, cTnI, CK-MB, tumor necrosis factor-α, interleukin (IL)-6, and IL-1β were upregulated in the rat model of sepsis. The low expression of miR-328 reversed these indicators. miR-328 is a diagnostic marker for patients with sepsis, and decreasing the expression level of miR-328 can ameliorate cardiac dysfunction and cardiac inflammation in sepsis.
Association of Protein and Genetic Biomarkers With Response to Lumbar Epidural Steroid Injections in Subjects With Axial Low Back Pain

Objective The purpose of this observational study was to examine the association of protein and genetic biomarkers with pain and pain-related disability in individuals with axial low back pain undergoing epidural steroid injections. Design Forty-eight adults with axial low back pain undergoing an epidural steroid injection were recruited from an academic medical center. Blood samples were assayed at baseline and follow-up for plasma proteins and functional single-nucleotide polymorphisms associated with pain. Data regarding pain and function were collected at baseline and follow-up. The characteristics of responders (defined as 50% improvement in pain score) and nonresponders were compared, and the association between response and baseline biomarkers was examined. Results Thirty-five percent of subjects were responders to injection. Responders had lower baseline plasma levels of chondroitin sulfate 846 and higher neuropeptide Y and serotonin levels than nonresponders, and baseline neuropeptide Y level correlated with change in disability levels. In addition, subjects with the variant allele for the catechol-O-methyltransferase single-nucleotide polymorphism demonstrated increased odds of responding to the injection. Conclusions These data identify candidates who may have utility for patient selection for spinal procedures and provide support for exploration in prospective studies to assess and validate their predictive ability.
Oxygen sensing; a stunningly elegant molecular machinery highjacked in cancer

Abstract Oxygen is of fundamental importance for most living organisms, and the maintenance of oxygen homeostasis is a key physiological challenge for all large animals. Oxygen deprivation, hypoxia, is a critical component of many human diseases including cancer, heart disease, stroke, vascular disease, and anaemia. The discovery of oxygen sensing provides fundamental knowledge of a stunningly elegant molecular machinery; it also promises development of new therapeutics for serious diseases such as cancer. As a result of their impressive contributions to our understanding of the mechanisms by which cells sense oxygen and signal in hypoxia, Gregg Semenza, Peter Ratcliffe, and William Kaelin were awarded the Nobel Prize in 2019.
A Generate-and-Rank Framework with Semantic Type Regularization for Biomedical Concept Normalization

Concept normalization, the task of linking textual mentions of concepts to concepts in an ontology, is challenging because ontologies are large. In most cases, annotated datasets cover only a small sample of the concepts, yet concept normalizers are expected to predict all concepts in the ontology. In this paper, we propose an architecture consisting of a candidate generator and a list-wise ranker based on BERT. The ranker considers pairings of concept mentions and candidate concepts, allowing it to make predictions for any concept, not just those seen during training. We further enhance this list-wise approach with a semantic type regularizer that allows the model to incorporate semantic type information from the ontology during training. Our proposed concept normalization framework achieves state-of-the-art performance on multiple datasets.
Meta-Reinforced Multi-Domain State Generator for Dialogue Systems

A Dialogue State Tracker (DST) is a core component of a modular task-oriented dialogue system. Tremendous progress has been made in recent years. However, the major challenges remain. The state-of-the-art accuracy for DST is below 50% for a multi-domain dialogue task. A learnable DST for any new domain requires a large amount of labeled in-domain data and training from scratch. In this paper, we propose a Meta-Reinforced Multi-Domain State Generator (MERET). Our first contribution is to improve the DST accuracy. We enhance a neural model based DST generator with a reward manager, which is built on policy gradient reinforcement learning (RL) to fine-tune the generator. With this change, we are able to improve the joint accuracy of DST from 48.79% to 50.91% on the MultiWOZ corpus. Second, we explore to train a DST meta-learning model with a few domains as source domains and a new domain as target domain. We apply the model-agnostic meta-learning algorithm (MAML) to DST and the obtained meta-learning model is used for new domain adaptation. Our experimental results show this solution is able to outperform the traditional training approach with extremely less training data in target domain.
A Relaxed Matching Procedure for Unsupervised BLI

Recently unsupervised Bilingual Lexicon Induction(BLI) without any parallel corpus has attracted much research interest. One of the crucial parts in methods for the BLI task is the matching procedure. Previous works impose a too strong constraint on the matching and lead to many counterintuitive translation pairings. Thus We propose a relaxed matching procedure to find a more precise matching between two languages. We also find that aligning source and target language embedding space bidirectionally will bring significant improvement. We follow the previous iterative framework to conduct experiments. Results on standard benchmark demonstrate the effectiveness of our proposed method, which substantially outperforms previous unsupervised methods.
Hypernymy Detection for Low-Resource Languages via Meta Learning

Hypernymy detection, a.k. a, lexical entailment, is a fundamental sub-task of many natural language understanding tasks. Previous explorations mostly focus on monolingual hypernymy detection on high-resource languages, e.g., English, but few investigate the low-resource scenarios. This paper addresses the problem of low-resource hypernymy detection by combining high-resource languages. We extensively compare three joint training paradigms and for the first time propose applying meta learning to relieve the low-resource issue. Experiments demonstrate the superiority of our method among the three settings, which substantially improves the performance of extremely low-resource languages by preventing over-fitting on small datasets.
Learning Efficient Dialogue Policy from Demonstrations through Shaping

Training a task-oriented dialogue agent with reinforcement learning is prohibitively expensive since it requires a large volume of interactions with users. Human demonstrations can be used to accelerate learning progress. However, how to effectively leverage demonstrations to learn dialogue policy remains less explored. In this paper, we present Sˆ2Agent that efficiently learns dialogue policy from demonstrations through policy shaping and reward shaping. We use an imitation model to distill knowledge from demonstrations, based on which policy shaping estimates feedback on how the agent should act in policy space. Reward shaping is then incorporated to bonus state-actions similar to demonstrations explicitly in value space encouraging better exploration. The effectiveness of the proposed Sˆ2Agentt is demonstrated in three dialogue domains and a challenging domain adaptation task with both user simulator evaluation and human evaluation.
Study of genes of the phytopathogenic fungus Verticillium longisporum involved in the colonization of xylem vessels of its host Brassica napus

Verticillium longisporum is a devastating soil - borne fungal pathogen of the rapeseed (Brassica napus). It colonizes the xylem vessels of the host plants but the nutritional status of the fungus and response to the plant defense mechanisms in the xylem vessel is largely unexplored.The gene for chorismate synthase of V. longisporum, Vlaro2 - 1 was isolated from the cDNA library of V. longisporum by performing a yeast complementation assay in &Delta aro2. Chorismate synthase is involved in the biosynthesis of the aromatic amino acids. As Vlaro2 - 1 complemented the bifunctional aro2 in yeast, it implied that the fungal enzyme is also bifunctional which means that apart from its catalytic activity it also possess an intrinsic NADPH : FMN oxidoreductase activity. It was determined that Vlaro2 - 1 has an isogene, Vlaro2 - 2 with identical sequence supporting a &lsquo near diploid &rsquo genome of V. longis porum. The deduced VlARO2 protein sequence of both isogenes is identical to the corresponding protein in V. dahliae. A novel knock - down method was established successfully in V. longisporum using RNA - mediated gene silencing to silence both isogenes of chorismate synthase which demonstrated that the gene silencing mechanism by RNAi works in the genus Verticillium. The Vlaro2 silenced mutant showed normal growth on minimal medium but marked growth retardation in the presence of 5 - methyl - DL - tryptophan, an inhibitor of the tryptophan biosynthesis as compared to the wild type. In a pathogenicity assay in Brassica napus, the propagation and virulence of the Vlaro2 silenced mutant was significantly reduced.The effect of the xylem sap of the host, Brassica napus on the protein expression of the pathogen, V. longisporum was further studied using a proteomic approach. The 2 - Dimensional Electrophoresis ( 2 - DE ) was conducted to identify the differentially expressed proteins of V.longisporum in the presence of the xylem sap. Fourteen proteins were observed to be differentially expressed in the 2 - DE analysis, of which six were upregulated and eight downregulated. For identification, MS / MS was employed and ten proteins were identified confidently. On functional analysis, it was observed that all the upregulated proteins may be involved in stress response. One of the upregulated proteins, catalase - peroxidase of V . longisporum, VlCPEA, was further characterized. V. longisporum has two isogenes, VlcpeA - 1 and VlcpeA - 2, which further supports its &lsquo near diploid &rsquo status. The catalase - peroxidase might play a role in protecting the fungus from the oxidative stress generated by the host plant.The development of a knock - down method for efficient gene silencing and the first characterization of two gene pairs presumably necessary for prototrophy or oxidative stress response are prerequisites for the further analysis of this fungus - plant interaction.
Machine-Learned Association of Next-Generation Sequencing-Derived Variants in Thermosensitive Ion Channels Genes with Human Thermal Pain Sensitivity Phenotypes

Genetic association studies have shown their usefulness in assessing the role of ion channels in human thermal pain perception. We used machine learning to construct a complex phenotype from pain thresholds to thermal stimuli and associate it with the genetic information derived from the next-generation sequencing (NGS) of 15 ion channel genes which are involved in thermal perception, including ASIC1, ASIC2, ASIC3, ASIC4, TRPA1, TRPC1, TRPM2, TRPM3, TRPM4, TRPM5, TRPM8, TRPV1, TRPV2, TRPV3, and TRPV4. Phenotypic information was complete in 82 subjects and NGS genotypes were available in 67 subjects. A network of artificial neurons, implemented as emergent self-organizing maps, discovered two clusters characterized by high or low pain thresholds for heat and cold pain. A total of 1071 variants were discovered in the 15 ion channel genes. After feature selection, 80 genetic variants were retained for an association analysis based on machine learning. The measured performance of machine learning-mediated phenotype assignment based on this genetic information resulted in an area under the receiver operating characteristic curve of 77.2%, justifying a phenotype classification based on the genetic information. A further item categorization finally resulted in 38 genetic variants that contributed most to the phenotype assignment. Most of them (10) belonged to the TRPV3 gene, followed by TRPM3 (6). Therefore, the analysis successfully identified the particular importance of TRPV3 and TRPM3 for an average pain phenotype defined by the sensitivity to moderate thermal stimuli.
Risk Factors and Management of Osteoporosis Post-Transplant

Bone and mineral disorders are common after organ transplantation. Osteoporosis post transplantation is associated with increased morbidity and mortality. Pathogenesis of bone disorders in this particular sub set of the population is complicated by multiple co-existing factors like preexisting bone disease, Vitamin D deficiency and parathyroid dysfunction. Risk factors include post-transplant immobilization, steroid usage, diabetes mellitus, low body mass index, older age, female sex, smoking, alcohol consumption and a sedentary lifestyle. Immunosuppressive medications post-transplant have a negative impact on outcomes, and further aggravate osteoporotic risk. Management is complex and challenging due to the sub-optimal sensitivity and specificity of non-invasive diagnostic tests, and the underutilization of bone biopsy. In this review, we summarize the prevalence, pathophysiology, diagnostic tests and management of osteoporosis in solid organ and hematopoietic stem cell transplant recipients.
Perceptions of physicians and nurses concerning advanced care planning for patients with heart failure in Japan.

BACKGROUND The importance of advance care planning (ACP) has been recognized in the palliative care of patients with heart failure. It is necessary for dissemination of ACP to characterize the perceptions of physicians and nurses towards ACP and to promote mutual understanding. The aim of this study is to investigate the perceptions of physicians and nurses concerning ACP for patients with heart failure. METHODS We conducted a self-administered questionnaire survey with physicians and nurses who belonged to the 427 certified institutions for implantable cardioverter defibrillator (ICD) and/or cardiac resynchronization therapy (CRT) in Japan. The self-administered questionnaire was originally designed based on the guidelines on palliative care or ACP and previous studies on the barriers of ACP. We asked the participants the recognition about condition/timing to implement ACP, Content of care to be implemented in ACP, and barriers against implementing ACP. A Mann-Whitney U test was performed and r value was calculated an effect size (ES) in order to evaluate the characteristic perceptions among physicians and nurses. RESULTS Valid responses were obtained from 163 physicians (38.2%) and 208 nurses (48.7%). Regarding the condition/timing, nurses tended to recognize that ACP should be implemented from earlier clinical stages than physicians. Regarding the contents of ACP, both physicians and nurses placed emphasis in assessing the patient's perception of disease progression. The biggest difference was found in the item "Ask patient about what has been important in life so far"; 78.6% of physicians but 94.2% of nurses chose "it must/should be implemented" (Cohen's r=0.31). Regarding the barriers, both physicians and nurses recognized the difficulty in prognosis prediction. The biggest differences were found in the items "Medical staff does not know how to implement ACP for patients and their families" (45.6% of physicians and 70.4% of nurses chose "strongly agree/agree", r=0.27), and "There is disagreement regarding care goals among team members of different professions" (18.5% in physicians and 43.3% in nurses, r=0.27). CONCLUSIONS It is suggested that discussions and further studies are necessary concerning the condition/ timing of implementing ACP from early stages, specific manuals/protocols and recommendation on rolesharing within a multidisciplinary team.
Defining the Landscape of the PARKIN- and PINK1-Dependent Ubiquitin-Modified Proteome in Response to Mitochondrial Dysfunction

Defining the landscape of the PARKINand PINK1-dependent ubiquitin-modified proteome in response to mitochondrial dysfunction Parkinson’s disease (PD) is a progressive neurological disorder resulting from loss of dopaminergic neurons of the substantia nigra, in part due to mitochondrial dysfunction. The E3 ubiquitin ligase, PARKIN, and mitochondrial kinase, PINK1, found mutated in familial early onset recessive forms of PD play central roles in mitochondrial homeostasis, thus maintaining control of a diversity of cellular processes, including energy metabolism, calcium buffering, and cell death. Together, PARKIN and PINK1 control mitochondrial homeostasis via a signaling cascade in which depolarization-induced PINK1 stabilization and activation on the mitochondrial outer membrane (MOM) promotes recruitment of PARKIN. Consequently, the outer mitochondrial membrane is extensively decorated with ubiquitin, ultimately resulting in removal of the damaged organelles via mitophagy, the selective autophagic removal of mitochondria. While PARKIN has been demonstrated to ubiquitylate Porin, Mitofusin, and Miro proteins on the MOM, the full repertoire of PARKIN substrates – the PARKIN-dependent ubiquitylome – remains poorly defined. Here, large-scale quantitative diGlycine (diGly) capture proteomics was used to identify PARKIN-dependent ubiquitylation on lysine residues in proteins modified upon mitochondrial depolarization. Hundreds of ubiquitylation sites in dozens of proteins were identified, with strong enrichment for MOM proteins, indicating that PARKIN activity has the capacity to dramatically alter the ubiquitylation status of the mitochondrial proteome. Complementary interaction proteomics identified physical association of PARKIN with a cohort of MOM ubiquitylation targets, autophagy receptors, and the proteasome, interactions which were completely dependent upon mitochondrial damage and drastically reduced upon mutation
Predicting the Focus of Negation: Model and Error Analysis

The focus of a negation is the set of tokens intended to be negated, and a key component for revealing affirmative alternatives to negated utterances. In this paper, we experiment with neural networks to predict the focus of negation. Our main novelty is leveraging a scope detector to introduce the scope of negation as an additional input to the network. Experimental results show that doing so obtains the best results to date. Additionally, we perform a detailed error analysis providing insights into the main error categories, and analyze errors depending on whether the model takes into account scope and context information.
Antimicrobial efficacy of Althaea officinalis Linn. seed extracts and essential oil against respiratory tract pathogens

In present study, Althaea officinalis seed extracts and essential oil were screened for antimicrobial activity against five bacteria and one fungi responsible for dominant, lethal or opportunistic infection of respiratory regions. The maximum inhibition was noted by essential oil against Streptococcus pyogenes (21.3±0.28 mm) and Haemophilus influenzae (19.0±0.50 mm) at 200 mg/ml. The minimum inhibitory concentration values for methanol extract was 3.12- 12.5 mg/ml. The antifungal activity noted highest with 41.28% by essential oil and 36.27% inhibition by aqueous extract represented by dosage-response curve.
Towards an integrated sheep parasite decision support system. Part I. Sheep Blowfly Strike

An outline is provided of a proposed integrated Decision Support System (DSS) for arthropod sheep parasites (initially). The DSS would include multiple parasite species. The first component will describe the likely timing of emergence of blowflies in spring around Australia, and the effects on blow fly populations and incidence of fly strike of multiple protective products. It will address a number of performance criteria including population suppression, profitability, and sustainability as affected by resistance and effects on non-target species, and complementarities of management actions. The DSS will enable a holistic assessment of options to optimise returns on parasite control and increase the sustainability of sheep production in Australia by minimising risks from resistance and chemical residues in sheep products. Examples are given to illustrate the use of the DYMEX modelling package, which has formed the basis of the Australian IPM Modelling network. This network provides a mechanism for facilitating national approaches to Australia’s pest and disease problems, and is recommended as a vehicle for a collaborative effort to develop and apply the proposed Decision Support System.
Quality and validity of large animal experiments in stroke: A systematic review

An important factor for successful translational stroke research is study quality. Low-quality studies are at risk of biased results and effect overestimation, as has been intensely discussed for small animal stroke research. However, little is known about the methodological rigor and quality in large animal stroke models, which are becoming more frequently used in the field. Based on research in two databases, this systematic review surveys and analyses the methodological quality in large animal stroke research. Quality analysis was based on the Stroke Therapy Academic Industry Roundtable and the Animals in Research: Reporting In Vivo Experiments guidelines. Our analysis revealed that large animal models are utilized with similar shortcomings as small animal models. Moreover, translational benefits of large animal models may be limited due to lacking implementation of important quality criteria such as randomization, allocation concealment, and blinded assessment of outcome. On the other hand, an increase of study quality over time and a positive correlation between study quality and journal impact factor were identified. Based on the obtained findings, we derive recommendations for optimal study planning, conducting, and data analysis/reporting when using large animal stroke models to fully benefit from the translational advantages offered by these models.