Miracle-dz/UniFAR-FTUs huggingface dataset:
ERG3-Encoding Sterol C5,6-DESATURASE in Candida albicans Is Required for Virulence in an Enterically Infected Invasive Candidiasis Mouse Model

Gastrointestinal colonization by Candida species is considered the main source of candidemia. The ERG3 gene in Candida albicans encodes a sterol C5,6-desaturase, which is essential for ergosterol biosynthesis. Although ERG3 inactivation shows reduced virulence in mouse models of disseminated candidiasis, the role of ERG3 in intestinal infections is unknown. Here, we infected mice with the C. albicans strains CAE3DU3 and CAF2-1, containing mutant and wild-type ERG3, respectively, and studied gut infection and colonization by these strains. We found that the CAE3DU3 strain showed reduced colonization, pathogenesis, damage to gut mucosa, and chemokine production in the mouse model of invasive candidiasis. Additionally, mice inoculated with CAE3DU3 showed lower mortality than mice inoculated with CAF2-1 (p < 0.0001). Chemokines were less induced in the gut inoculated with CAE3DU3 than in the gut inoculated with CAF2-1. Histopathologically, although the wild-type gene was associated with a higher pathogenicity and invasion of the gut mucosa and liver tissues causing remarkable tissue necrosis, the erg3/erg3 mutant was associated with a higher accumulation of cells and lower damage to surrounding tissues than wild-type ERG3. These results establish that the ergosterol biosynthetic pathway may be associated with C. albicans gut colonization and subsequent dissemination.
Therapeutic Targeting of Non-oncogene Dependencies in High-risk Neuroblastoma

Purpose: Neuroblastoma is a pediatric malignancy of the sympathetic nervous system with diverse clinical behaviors. Genomic amplification of MYCN oncogene has been shown to drive neuroblastoma pathogenesis and correlate with aggressive disease, but the survival rates for those high-risk tumors carrying no MYCN amplification remain equally dismal. The paucity of mutations and molecular heterogeneity has hindered the development of targeted therapies for most advanced neuroblastomas. We use an alternative method to identify potential drugs that target nononcogene dependencies in high-risk neuroblastoma. Experimental Design: By using a gene expression–based integrative approach, we identified prognostic signatures and potentially effective single agents and drug combinations for high-risk neuroblastoma. Results: Among these predictions, we validated in vitro efficacies of some investigational and marketed drugs, of which niclosamide, an anthelmintic drug approved by the FDA, was further investigated in vivo. We also quantified the proteomic changes during niclosamide treatment to pinpoint nucleoside diphosphate kinase 3 (NME3) downregulation as a potential mechanism for its antitumor activity. Conclusions: Our results establish a gene expression–based strategy to interrogate cancer biology and inform drug discovery and repositioning for high-risk neuroblastoma.
Pantoprazole Affecting Docetaxel Resistance Pathways via Autophagy (PANDORA): Phase II Trial of High Dose Pantoprazole (Autophagy Inhibitor) with Docetaxel in Metastatic Castration-Resistant Prostate Cancer (mCRPC).

BACKGROUND Enhancing the effectiveness of docetaxel for men with metastatic castration-resistant prostate cancer (mCRPC) is an unmet clinical need. Preclinical studies demonstrated that high-dose pantoprazole can prevent or delay resistance to docetaxel via the inhibition of autophagy in several solid tumor xenografts. MATERIALS AND METHODS Men with chemotherapy-naive mCRPC with a prostate-specific antigen (PSA) >10 ng/mL were eligible for enrolment. Men received intravenous pantoprazole (240 mg) prior to docetaxel (75 mg/m2) every 21 days, with continuous prednisone 5 mg twice daily. Primary endpoint was a confirmed ≥50% decline of PSA. The trial used a Simon's two-stage design. RESULTS Between November 2012 and March 2015, 21 men with a median age of 70 years (range, 58-81) were treated (median, 6 cycles; range, 2-11). Men had received prior systemic therapies (median, 1; range, 0-3), and 14 had received abiraterone and/or enzalutamide. PSA response rate was 52% (11/21), which did not meet the prespecified criterion (≥13/21 responders) to proceed to stage 2 of the study. At interim analysis with a median follow-up of 17 months, 18 (86%) men were deceased (15 castration-resistant prostate cancer, 2 unknown, 1 radiation complication). Of the men with RECIST measurable disease, the radiographic partial response rate was 31% (4/13). The estimated median overall survival was 15.7 months (95% confidence interval [CI], 9.3-19.6) and median PFS was 5.3 months (95% CI, 2.6-12.9). There were no toxic deaths, and all adverse events were attributed to docetaxel. CONCLUSION The combination of docetaxel and pantoprazole was tolerable, but the resultant clinical activity was not sufficient to meet the ambitious predefined target to warrant further testing. IMPLICATIONS FOR PRACTICE To date, no docetaxel combination regimen has reported superior efficacy over docetaxel alone in men with metastatic castration-resistant prostate cancer (mCRPC). The PANDORA trial has demonstrated that the combination of high dose pantoprazole with docetaxel is tolerable, but the clinical activity was not sufficient to warrant further testing. The chemotherapy standard of care for men with mCRPC remains docetaxel with prednisone. Future studies of autophagy inhibitors will need to measure autophagy inhibition accurately and determine the degree of autophagy inhibition required to produce a meaningful clinical response.
Comparision of Preoperative Mri Findings with Intraoperative Findings in Patient of Fistula in ANO

MRI has become the method of choice for evaluating perianal fistulae due to its ability to display theanatomy of the sphincter muscles orthogonally, with good contrast resolution. In this article we compareMRI findings to intraoperative findings in patients of Fistula in Ano. This study is based on a retrospectiveanalysis of 35 patients with a clinical diagnosis of perianal fistula
Immune checkpoint inhibitors use and effects on prognosis of COVID-19 infection: a systematic review and meta-analysis

Aim: We aimed to quantify the effects of immune checkpoint inhibitors (ICIs) on the prognosis of COVID-19. Materials & methods: A meta-analysis was conducted and the hospitalization, severe disease and mortality rates were assessed. Thirteen studies comprising of 4614 cancer patients with COVID-19 were included. Results: When compared with cancer patients without prior ICI exposure, patients with prior ICI treatment exhibited a higher rate of hospitalization (odds ratio [OR] 2.0, 95% CI 1.19–3.38, p = 0.01). However, the OR of severe disease and mortality in ICI exposed cases was similar to non-ICI exposed patients (OR 1.55, 95% CI 0.69–3.51, p = 0.29; OR 1.12, 95% CI 0.85–1.48, p = 0.42, respectively). Conclusion: It is uncertain whether prior exposure to ICIs increases the risk of severe disease and death, however the observed OR suggest a higher rate of hospitalization.
Impact of oil prices, the U.S interest rates on Turkey’s real estate market. New evidence from combined co-integration and bootstrap ARDL tests

The research aims to provide new empirical evidence by testing the impact of the external shocks namely: oil prices and the U.S interest rate on Turkey’s real estate market by using three techniques of co-integration tests namely: the newly developed bootstrap autoregressive distributed lag (ARDL) testing approach as proposed by (McNown et al. 2018), the new approach involving the Bayer-Hanck (2013) combined co-integration test, Hatemi-J (2008) co-integration testing approach. The ARDL model is utilized to explore the relationship between the variables. The findings show that the oil prices have a positive impact on Turkey’s real estate market, the results confirm that there is a significant impact of oil prices on Turkey’s real estate market through the domestic interest rate. Furthermore, the results demonstrated that there is a significant spillover influence of the U.S. interest rates on Turkey’s real estate market through oil prices and domestic interest rates. This study suggests that the following factors led to increasing the sensitivity and volatility of the Turkish real estate market to oil prices and the U.S. interest rate fluctuations: the presence of economic interdependence between the USA and Turkey, and the majority of the external debts and the reserve currency in Turkey are composed in the USD, and Turkey’s oil imports hit record high in last years. Finally, this article suggests that policymakers in Turkey should pay close attention to the effects of external shocks namely the oil prices and U.S. interest rates on Turkish markets to maintain economic and financial stability.
Spanish language teachers’ pedagogical beliefs in Chinese universities

Understanding teachers’ beliefs is critical to improving educational practice. There is a significant need for research on foreign language teachers’ pedagogical beliefs, as these can exert an influence on students’ learning outcomes. This study draws on Kember’s (1997) theorization of teaching beliefs to explore the beliefs of Spanish language teachers regarding their pedagogy in Chinese universities. Twenty teachers from the Spanish departments in eight Chinese universities were recruited as participants, and a Q-methodology analysis with supplementary interview data identified three types of pedagogical beliefs: “integrated capacity-building”, “ELE learning outcome-focused”, and “social interaction-focused”. The findings suggest that ELE teachers in China no longer subscribe to the traditional teaching methodology which places themselves at the class center, and have instead progressed along a continuum from teacher-centeredness to student-centeredness. With a novel focus on Spanish teachers’ beliefs in Chinese universities, this study provides insights into the teaching of languages other than English (LOTEs) in China, and helps to expand the methodological repertoire in the field of linguistic research.
Serendipity—A Machine-Learning Application for Mining Serendipitous Drug Usage From Social Media

Serendipitous drug usage refers to the unexpected relief of comorbid diseases or symptoms when taking medication for a different known indication. Historically, serendipity has contributed significantly to identifying many new drug indications. If patient-reported serendipitous drug usage in social media could be computationally identified, it could help generate and validate drug-repositioning hypotheses. We investigated deep neural network models for mining serendipitous drug usage from social media. We used the word2vec algorithm to construct word-embedding features from drug reviews posted in a WebMD patient forum. We adapted and redesigned the convolutional neural network, long short-term memory network, and convolutional long short-term memory network by adding contextual information extracted from drug-review posts, information-filtering tools, medical ontology, and medical knowledge. We trained, tuned, and evaluated our models with a gold-standard dataset of 15714 sentences (447 [2.8%] describing serendipitous drug usage). Additionally, we compared our deep neural networks to support vector machine, random forest, and AdaBoost.M1 algorithms. Context information helped to reduce the false-positive rate of deep neural network models. If we used an extremely imbalanced dataset with limited instances of serendipitous drug usage, deep neural network models did not outperform other machine-learning models with n-gram and context features. However, deep neural network models could more effectively use word embedding in feature construction, an advantage that makes them worthy of further investigation. Finally, we implemented natural-language processing and machine-learning methods in a web-based application to help scientists and software developers mine social media for serendipitous drug usage.
Communicative Competence for Individuals who require Augmentative and Alternative Communication: A New Definition for a New Era of Communication?

Abstract In 1989, Light defined communicative competence for individuals with complex communication needs who require augmentative and alternative communication (AAC) as a dynamic interpersonal construct based on functionality of communication; adequacy of communication; and sufficiency of knowledge, judgment, and skills. Specifically, Light argued that, in order to demonstrate communicative competence, individuals who required AAC had to develop and integrate knowledge, judgment, and skills in four interrelated domains: linguistic, operational, social, and strategic. In 2003, Light expanded this definition and argued that the attainment of communicative competence is influenced by not just linguistic, operational, social, and strategic competencies but also a variety of psychosocial factors (e.g., motivation, attitude, confidence, resilience) as well as barriers and supports in the environment. In the 25 years since this definition of communicative competence for individuals who use AAC was originally proposed, there have been significant changes in the AAC field. In this paper, we review the preliminary definition of communicative competence, consider the changes in the field, and then revisit the proposed definition to determine if it is still relevant and valid for this new era of communication.
Deep-CRM: A New Deep Learning Approach for Capacitance Resistive Models

Summary Classical reservoir engineering studies require building geological models and solving complex fluid flow transport equations that require high-quality data, numerous computational resources, time and workflows. For large and mature fields data-driven models can be used to get faster answer and to perform production analysis more efficiently. Capacitance Resistive Models (CRM) are a class of methods based on material balance that can be used to estimate production wells liquid rates as a function of injected water and Bottom Hole Pressure (BHP) variations. CRM methods quantify the connectivity between producers and injectors using only dynamic data. An important drawback of CRM is that they can suffer from parameter identification problems. Moreover, the analytical solution can be only obtained in specific conditions: linear variations of BHP and fixed injection rate between two consecutive time steps. In this work we present a new approach combining CRM material balance equations with neural networks in order to obtain more robust and reliable estimation of the CRM parameters (i.e. well connectivity, productivity indices and time constants). This proposal is also interesting since it is not based on any assumption on BHP and injection rates. To this end, we use a recent approach called Physics Informed Neural Networks (PINNs). In this approach neural networks are trained on observed data with additional physics constraints traduced in appropriate loss functions. The parameters of this physical equation are evaluated at the same time as the neural network weights. The introduction of PINNs in our approach raised after testing classical machine learning (ML) models (SVMs, Random Forests …) and deep learning models (MLP, LSTM, RNNs…). Indeed, such models can perform well in some specific cases but usually struggle to produce robust results (i.e. forecasting) in the long term. Unfortunately, such systems do not natively integrate physics constraints. Our aim is to impose physic constraints in neural networks. Thus, we may obtain more stable and reliable results. On the same time, we should be able to account for more behaviors that are not explained by simplified physic equations such as material balance. We performed a full comparison between our approach using PINNs, other standard ML and DL approaches and a given framework of CRMs on two data-sets: a simple but realistic model build using a commercial reservoir simulator, and a real data set. We show that our approach gives more robust results (in terms of MSE) while not suffering from parameter identification issue.
Biochemical evaluation of newly composed tercumin capsules

In the present study, bitter dry beans of lupine seeds (Lupinus termis L.) cultivar Giza-1, and powder of turmeric rhizomes, (Curcuma longa L.,), and grains of yellow corn (Zea mays L.) cultivar Giza-368 were used to prepare three tercumin capsules. Chemical composition and elementary analysis of all capsules and their sources were done. The tercumin capsules composed from three portions, the first one, is fine powdered lupine seeds (FPLS), the second portion is turmeric powdered (TP) and the third one is the grain husks of yellow corn (GHYC). Generally, these data ` that the three chosen crops studied here are good, complementary and inexpensive sources for composed capsules. While the crude protein (6.69 -34.15 %) and lipids (3.82-11.07%) and TSS (21.16-25.32%). From obtained, results turmeric rhizomes contain the highest content of lutein, zeaxanthin, β-cryptoxanthin and β-carotene followed by bitter lupines Giza-1, and husks of yellow corn grain. Lupine seeds, turmeric rhizomes andyellow corn grains contain large quantities of carotenoid pigments, which can be used as dietary supplements or as safe food additives. Results of carotenoid levels in three tercumin capsules show that lutein, zeaxanthin, β-cryptoxanthin and β-carotene content in tercumin capsule-2 are higher than those determined in tercumin capsule-3 and tercumin capsule-1. TPCs in both tercumin capsules and their sources tercumin capsules ranged from 2.18 to 29.48 mg/100g. TPCs in the yellow corn grains are higher than those found in the bitter lupine seeds Giza-1 (2.185 mg/100g) and turmeric rhizomes. TPCs concentrations in thetercumin capsules-3 are higher than those found in the tercumin capsules-1 and tercumin capsules-2. The levels of TPCs in the tercumin capsules-1, capsules-2 and capsules-3 are 20.1, 25.63 and 29.480 mg/100g respectively. Total flavonoid contents in tercumin capsules and their sources were assayed and the results indicate that turmeric powdered contained the highest level 4.97 mg/100 g CE followed by grain husks of yellow corn (GHYC) and the lowest level (1.396) was found in the powder of lupine seed Giza-1.The results also showed that tercumin capsule-3 contain the highest concentration (5.142) of TFs followed by tercumin capsule-1and tercumin capsule-2 contain the lowest concentration. These results showed that total alkaloids in turmeric rhizomes (1.82%) are higher than those determined in yellow corn grains (1.203%). The levels of TAs in turmeric rhizomes are always higher than those determined in yellow corn grains.
LOTE (Languages Other than English) learners’ investment in learning languages

This study draws on the model of language learning investment to explore China’s LOTE (Languages Other than English) students’ learning motivation. Data collected through in-depth interviews with 35 university students were analyzed in an inductive way. The findings show that: (1) the participants invested in learning LOTEs because they had enough affordances (resources applicable to LOTE learning) and/or perceived target language-related benefits (economic, cultural or social ones) from LOTE learning, even though most of our participants were initially involuntary applicants; (2) students were reluctant to invest in learning their target language(s) and merely strove to fulfil their program(s) when they were lacking affordances, perceiving few benefits, or even devalued by the in-context ideologies. These findings provide important implications for LOTE educators to motivate their students, and for policy makers to improve China’s LOTE education.
Modelling the role of dual specificity phosphatases in Herceptin resistant breast cancer cell lines

Background Breast cancer remains the most lethal type of cancer for women. A significant proportion of breast cancer cases are characterised by overexpression of the human epidermal growth factor receptor 2 protein (HER2). These cancers are commonly treated by Herceptin (Trastuzumab), but resistance to drug treatment frequently develops in tumour cells. Dual-specificity phosphatases (DUSPs) are thought to play a role in the mechanism of resistance, since some of them were reported to be overexpressed in tumours resistant to Herceptin. Results We used a systems biology approach to investigate how DUSP overexpression could favour cell proliferation and to predict how this mechanism could be reversed by targeted inhibition of selected DUSPs. We measured the expression of 20 DUSP genes in two breast cancer cell lines following long-term (6 months) exposure to Herceptin, after confirming that these cells had become resistant to the drug. We constructed several Boolean models including specific substrates of each DUSP, and showed that our models correctly account for resistance when overexpressed DUSPs were kept activated. We then simulated inhibition of both individual and combinations of DUSPs, and determined conditions under which the resistance could be reversed. Conclusions These results show how a combination of experimental analysis and modelling help to understand cell survival mechanisms in breast cancer tumours, and crucially enable us to generate testable predictions potentially leading to new treatments of resistant tumours.
C1q/TNF‐related protein‐9 promotes macrophage polarization and improves cardiac dysfunction after myocardial infarction

The timely regulation of inflammatory M1 macrophage polarization toward regenerative M2 macrophages suggests the possibility of immunotherapy after myocardial infarction (MI). C1q/TNF‐related protein‐9 (CTRP9) has anti‐inflammatory effects and can ameliorate heart function in mice after long‐term myocardial infarction. The role of CTRP9 in macrophage polarization remains completely unclear. This study determined whether CTRP9 can preserve post‐MI early cardiac function through the regulation of macrophage polarization. In the present study, an adenovirus‐delivered CTRP9 supplement promoted macrophage polarization at Day 3 post MI and improved cardiac function at Day 7 post MI. Pretreatment with gCTRP9 promoted the M1 to M2 polarization transition and attenuated inflammation after lipopolysaccharide + interferon‐γ stimulation; the effects were partly abrogated by the adenosine monophosphate kinase (AMPK) inhibitor compound C and were obviously reinforced by pyrrolidine dithiocarbamate, a nuclear factor‐κB (NF‐κB) inhibitor. Meanwhile, CTPR9 markedly reduced the expression of toll‐like receptor 4 (TLR4), myeloid differentiation factor 88 (MyD88), and NF‐κB p65 phosphorylation by promoting AMPK phosphorylation in vivo and in vitro. Moreover, the competitive binding of gCTRP9 and LPS to the myeloid differentiation protein 2 (MD2)/TLR4 complex was associated with direct binding to MD2, thereby inhibiting the downstream signaling molecule MyD88. Taken together, we demonstrated that CTRP9 improved post‐MI early cardiac function, at least in part, by modulating M1/M2 macrophage polarization, largely via the TLR4/MD2/MyD88 and AMPK‐NF‐κB pathways.
Effect of a Lower Limb Restless Period on Expression of Mir-1 and Mir-206 Neural Muscle Genes in Endurance Training Rats

* Corresponding Author: Mohammad Reza Kordi, PhD. Address: Department of Sports Physiology, Faculty of Physical Education and Sport Sciences, University of Tehran, Tehran, Iran. Tel: +98 (912) 3300076 E-mail: mrkordi@ut.ac. ir 1. Department of Sports Physiology, Faculty of Physical Education and Sport Sciences, Kish Campus, University of Tehran, Kish, Iran. 2. Department of Sports Physiology, Faculty of Physical Education and Sport Sciences, University of Tehran, Tehran, Iran. 3. Department of Sport Physiology, Faculty of Physical Education and Sports Sciences, Kharazmi University, Tehran, Iran. Mahboubeh Sheikhan1 , *Mohammad Reza Kordi2 , Hamid Rajabi3