Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of the Novel Oncogenic Role of SAAL1 and Its Therapeutic Potential in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer deaths worldwide, affecting over 700,000 people per year. The treatment effect in advanced HCC is still disappointing and prognosis of advanced HCC remains poor. Hence, to find more effective therapeutic targets to improve the treatment outcome of HCC is of urgent need. In this study, we reported the novel oncogenic function of SAAL1 (serum amyloid A-like 1) in HCC, which previously is considered as an inflammation-related gene. We found that SAAL1 was significantly upregulated in HCC tumor tissues when compared to the adjacent normal tissues and high expression of SAAL1 correlated with shorter overall survival in The Cancer Genome Atlas (TCGA) HCC database. Functionally, we showed that the depletion of SAAL1 significantly reduced cell proliferation, 3D colony formation, and migration/invasion abilities of HCC cancer cells. Furthermore, suppression of SAAL1 impaired the HGF/Met-driven Akt/mTOR phosphorylation cascade and increased the chemosensitivity of HCC cells to sorafenib and foretinib treatment. Our data indicated that SAAL1 plays an important role in HCC via mediating oncogenic HGF/Met-driven Akt/mTOR signaling and could serve as an independent prognostic marker, as well as a promising therapeutic target for HCC patients.
The 21-Gene Recurrence Score Assay and Prediction of Chemotherapy Benefit: A Propensity Score-Matched Analysis of the SEER Database

Background: To evaluate the performance of the 21-gene recurrence score (RS) assay in predicting chemotherapy benefit in the Surveillance, Epidemiology, and End Results population, we aimed to assess breast cancer-specific mortality (BCSM) by chemotherapy use within each of the RS categories. Methods: Data on breast cancer (BC) cases diagnosed between 2004 and 2015 with available RS results were released. Our analysis included patients with hormone receptor-positive, node-negative early-stage BC (n = 89,402), and three RS groups were defined; RS < 11, low; RS 11–25, intermediate; RS > 25, high. A propensity score matched-analysis was performed to assess and compare BCSM. Results: Chemotherapy was significantly associated with a reduced risk of BC death among patients in the high RS group (hazard ratio = 0.782; 95% CI, 0.618–0.990; p = 0.041). However, in the low and intermediate RS groups, there were no significant differences in BCSM between patients who received chemotherapy and those who did not. Among those with RS 11–25, chemotherapy benefit varied with tumor size (p = 0.001). Conclusions: Our findings provide real-world evidence that the 21-gene RS assay is predictive of chemotherapy benefit among patients in clinical practice. More refined risk estimates would be needed for patients with an intermediate RS.
Automated identification of live moths (Macrolepidoptera) using digital automated identification System (DAISY)

Abstract Two hundred and thirty‐seven species of Macrolepidoptera were light trapped at Treborth Botanical Garden, Gwynedd, UK. Live adults were digitally imaged using a simple, inexpensive method suitable for field use, then released. Inconsistent lighting, variation in resting posture and inclusion of worn individuals produced image sets high in intraspecific variation. Thirty‐five common species were selected to provide training images for the Digital Automated Identification SYstem (DAISY). Twenty individuals per species were pre‐processed to standardize size and posture and to enhance features. The right forewing of each was highlighted manually and the pattern rendered polar and greyscale for DAISY analysis. Despite poor quality of some images, 83% of unknown species were identified correctly. The best species had 100% correct identification and the worst 35%. The most poorly identified images were those of moths that had lost scales or been unevenly illuminated. The precision with which the forewing was highlighted affected performance. When highlighted carefully, Laothoe populi was identified correctly twice as successfully as when the same image was highlighted poorly. Size of the training set was also important. Sets of 5, 10, 15 and 20 training images, plotted against performance produced a curve of diminishing returns. Colourimages and inclusion of size should improve accuracy.
Redox currents associated with ion mobility in stems of plants

In vivo investigations of bioelectric currents associated with growth, tissue nietabolism, and water responses in the stems of trees and herbaceous plants are described. This experimentation is based on a new technique which allows the continuoils monitoring of variations in bioelectric currents related to intertissue redox conditions. Exploratory studies indicate relationships between variations in the redox current and turgor conditions in plants. A correlation between the bioelectric current and the difference in oxidation potentials between the plant and ground electrodes is discussed. In field studies, the current was monitored in different species of trees over a 1-year interval. Similarities in current variations occurred in similar species of trees and were examined in relation to temperature, rainfall, and phenological factors. The current level, examined in trees as a function of radial depth, disclosed the maximum output in the cambium layer. In a study of diurnal variations, a temporal shift in a current maximum was noted along the tree bole.
Soil phosphorus as a control of productivity and openness in temperate interglacial forest ecosystems

Aim Observations of long chronosequences in forest ecosystems show that, after some millennia of build‐up, biomass declines in relation to the slow depletion of soil phosphorus. Plants that dominate during this period of soil impoverishment have specialized strategies for P acquisition, including ectomycorrhiza or root clusters. We use quantitative, pollen‐based reconstructions of regional vegetation in four Quaternary warm stages (Holocene, Eemian, Holsteinian, Harreskovian) to test whether inferred forest cover and productivity changes are consistent with long‐term modification of soil nutrient pools.
Genetic background modifies vulnerability to glaucoma-related phenotypes in Lmx1b mutant mice

ABSTRACT Variants in the LIM homeobox transcription factor 1-beta (LMX1B) gene predispose individuals to elevated intraocular pressure (IOP), a key risk factor for glaucoma. However, the effect of LMX1B mutations varies widely between individuals. To better understand the mechanisms underlying LMX1B-related phenotypes and individual differences, we backcrossed the Lmx1bV265D (also known as Lmx1bIcst) allele onto the C57BL/6J (B6), 129/Sj (129), C3A/BLiA-Pde6b+/J (C3H) and DBA/2J-Gpnmb+ (D2-G) mouse strain backgrounds. Strain background had a significant effect on the onset and severity of ocular phenotypes in Lmx1bV265D/+ mutant mice. Mice of the B6 background were the most susceptible to developing abnormal IOP distribution, severe anterior segment developmental anomalies (including malformed eccentric pupils, iridocorneal strands and corneal abnormalities) and glaucomatous nerve damage. By contrast, Lmx1bV265D mice of the 129 background were the most resistant to developing anterior segment abnormalities, had less severe IOP elevation than B6 mutants at young ages and showed no detectable nerve damage. To identify genetic modifiers of susceptibility to Lmx1bV265D-induced glaucoma-associated phenotypes, we performed a mapping cross between mice of the B6 (susceptible) and 129 (resistant) backgrounds. We identified a modifier locus on Chromosome 18, with the 129 allele(s) substantially lessening severity of ocular phenotypes, as confirmed by congenic analysis. By demonstrating a clear effect of genetic background in modulating Lmx1b-induced phenotypes, providing a panel of strains with different phenotypic severities and identifying a modifier locus, this study lays a foundation for better understanding the roles of LMX1B in glaucoma with the goal of developing new treatments. Summary: We observed that Lmx1b mutant mice of different strain backgrounds vary in onset and severity of glaucoma-related phenotypes and identified a modifier locus on Chr 18. These results could increase understanding of the mechanisms underlying glaucoma.
Intraprostatic Ethanol Injection in the Treatment of Lower Urinary Tract Symptoms Associated with Benign Prostatic Hyperplasia: A Safer and Less Invasive Alternative?

Gold standard surgical therapies for Benign Prostatic Hyperplasia (BPH) are invasive and associated with complications and long-term side effects. The need for the development of safer and less invasive alternatives has been recognized and, as a result, significant progress has been made in recent years in the development of minimally invasive treatment options for male lower urinary symptoms associated with BPH. Intraprostatic injection has been evaluated as a potential minimally invasive treatment for BPH. Four agents have been tested during the past two decades. Absolute Anhydrous Ethanol (EtOH) has been tested most extensively in both preclinical and clinical studies, however, a randomized controlled trial has not been published to date and EtOH use as a BPH treatment has been abandoned by many due to rare, but serious complications involving extraprostatic tissue damage caused by EtOH. This review summarizes preclinical and clinical studies published to date and presents outcomes of research aimed at improving the safety and efficacy of intraprostatic EtOH injection.
Glucose-6-phosphate dehydrogenase deficiency and stroke outcomes

Objective To assess the risk of glucose-6-phosphate dehydrogenase (G6PD) on stroke prognosis, we compared outcomes between patients with stroke with and without G6PD deficiency. Methods The study recruited 1,251 patients with acute ischemic stroke. Patients were individually categorized into G6PD-deficiency and non-G6PD-deficiency groups according to G6PD activity upon admission. The primary endpoint was poor outcome at 3 months defined by a modified Rankin Scale (mRS) score ≥2 (including disability and death). Secondary outcomes included the overall mRS score at 3 months and in-hospital death and all death within 3 months. Logistic regression and Cox models, adjusted for potential confounders, were fitted to estimate the association of G6PD deficiency with the outcomes. Results Among 1,251 patients, 150 (12.0%) were G6PD-deficient. Patients with G6PD deficiency had higher proportions of large-artery atherosclerosis (odds ratio [OR] 1.53, 95% confidence interval [CI] 1.09–2.17) and stroke history (OR 1.93, 95% CI 1.26–2.90) compared to the non-G6PD-deficient group. The 2 groups differed significantly in the overall mRS score distribution (adjusted common OR 1.57, 95% CI 1.14–2.17). Patients with G6PD deficiency had higher rates of poor outcome at 3 months (adjusted OR 1.73, 95% CI 1.08–2.76; adjusted absolute risk increase 13.0%, 95% CI 2.4%–23.6%). The hazard ratio of in-hospital death for patients with G6PD-deficiency was 1.46 (95% CI 1.37–1.84). Conclusions G6PD deficiency is associated with the risk of poor outcome at 3 months after ischemic stroke and may increase the risk of in-hospital death. These findings suggest the rationality of G6PD screening in patients with stroke.
Tsunami Resilience of Pile-Supported Wharves: A First Principles Approach

New Zealand’s is a Pacific Island nation which experiences impacts from a wide variety of natural hazards including tsunami. While large-scale, destructive tsunami have not recently been generated in the vicinity of New Zealand, there is a history of large local and distant source tsunami occurring and resulting in significant runup heights along various coastlines. Although tsunami have the potential to penetrate inland, the first and most severe damage will occur in coastal cities and communities. Among that infrastructure that is most exposed to damage from tsunami is ports. Given the criticality of ports to the economic and social wellbeing of New Zealand, this research sought to assess potential tsunami impacts on existing New Zealand port infrastructure via a first-principles approach consisting of three steps. First, tsunami propagation models were developed for each of New Zealand’s 13 major ports. Second, tsunami loading characteristics were derived from a variety of design standards and experimental modelling. Finally, structural wharf models were developed to represent New Zealand infrastructure and tested against the tsunami loads to calculate predictive damage states. The results of this work included both detailed tsunami hazard information for the respective ports and the generalised damage states that could be linked back to specific ports.
Antiresonant Hollow-Core Fiber-Based Dual Gas Sensor for Detection of Methane and Carbon Dioxide in the Near- and Mid-Infrared Regions

In this work, we present for the first time a laser-based dual gas sensor utilizing a silica-based Antiresonant Hollow-Core Fiber (ARHCF) operating in the Near- and Mid-Infrared spectral region. A 1-m-long fiber with an 84-µm diameter air-core was implemented as a low-volume absorption cell in a sensor configuration utilizing the simple and well-known Wavelength Modulation Spectroscopy (WMS) method. The fiber was filled with a mixture of methane (CH4) and carbon dioxide (CO2), and a simultaneous detection of both gases was demonstrated targeting their transitions at 3.334 µm and 1.574 µm, respectively. Due to excellent guidance properties of the fiber and low background noise, the proposed sensor reached a detection limit down to 24 parts-per-billion by volume for CH4 and 144 parts-per-million by volume for CO2. The obtained results confirm the suitability of ARHCF for efficient use in gas sensing applications for over a broad spectral range. Thanks to the demonstrated low loss, such fibers with lengths of over one meter can be used for increasing the laser-gas molecules interaction path, substituting bulk optics-based multipass cells, while delivering required flexibility, compactness, reliability and enhancement in the sensor’s sensitivity.
GENOTOXIN-INDUCED ACETYLATION OF THE WERNER SYNDROME PROTEIN (WRN) AND EFFECT ON ITS DNA METABOLIC FUNCTION

OF DISSERTATION Enerlyn Meliza Lozada Santiago The Graduate School University of Kentucky 2011 GENOTOXIN-INDUCED ACETYLATION OF THE WERNER SYNDROME PROTEIN (WRN) AND EFFECT ON ITS DNA METABOLIC FUNCTION ABSTRACT OF DISSERTATIONOF DISSERTATION A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the College of Medicine at the University of Kentucky
A cross-sectional study on the rate of non-adherence to anti-seizure medications and factors associated with non-adherence among patients with epilepsy

Background Non-adherence to anti-seizure medication (ASM) therapy is an important contributing factor to the higher mortality rate and treatment failure of epilepsy. This study aimed to determine the rate and factors associated with non-adherence to ASM therapy through the WHO five dimensions of medication adherence framework. Methods We conducted a cross-sectional study at an outpatient Neurology Clinic of a tertiary government hospital in Malaysia. Between March and July 2019, we identified 217 patients with a confirmed diagnosis of epilepsy, receiving oral ASM therapy and able to administer their medications. We performed a semi-structured interview to gather information on sociodemographic background, clinical and medication history, and perceptions on healthcare services. Adherence to ASM therapy was evaluated using the Medication Compliance Questionnaire (MCQ). Patient’s illness perception was assessed by the Brief Illness Perception Questionnaire (B-IPQ). Results 208 patients participated in this study. The median age of the study participants was 35 years (IQR 26–44). 58.2% were females and majority, 55.8%, were from the Malay ethnic group. Based on the MCQ scoring, 89 patients (42.8%) were non-adherent. Multiple logistic regression demonstrated that being employed or students (adjusted odds ratio [aOR] 2.26, 95%CI: 1.19–4.29 p = 0.012) and having an average or below average perceived access to pharmacy services (aOR 2.94, 95%CI: 1.38–6.24, p = 0.005) were significant contributors to non-adherence. Conclusion Being employed or students and having an average or below average perceived access to pharmacy services were associated with ASM non-adherence Efforts to improve ASM adherence should adopt a comprehensive approach considering the success of adherence is contingent on the interrelationship of multiple dimensions.
The Streptomyces violaceusniger Cluster Is Heterogeneous in DNA Relatedness among Strains: Emendation of the Descriptions of S. violaceusniger and Streptomyces hygroscopicus

The taxonomic status of strains belonging to the Streptomyces violaceusniger phenotypic cluster, including eight S. violaceusniger strains, three Streptomyces hygroscopicus strains, and the type strains of Streptomyces sparsogenes and Streptomyces melanosporofaciens, was evaluated by using DNA relatedness data. The S. violaceusniger strains were separated into seven different DNA homology groups, including four single-member clusters, at a level of DNA relatedness of >70%. S. hygroscopicus NRRL 2387T (T = type strain) clustered with the type strain of Streptomyces endus and several S. violaceusniger strains. The other strains of S. hygroscopicus, S. sparsogenes, and S. melanosporofaciens formed single-member homology groups.
Learning to Discretely Compose Reasoning Module Networks for Video Captioning

Generating natural language descriptions for videos, i.e., video captioning, essentially requires step-by-step reasoning along the generation process. For example, to generate the sentence “a man is shooting a basketball”, we need to first locate and describe the subject “man”, next reason out the man is “shooting”, then describe the object “basketball” of shooting. However, existing visual reasoning methods designed for visual question answering are not appropriate to video captioning, for it requires more complex visual reasoning on videos over both space and time, and dynamic module composition along the generation process. In this paper, we propose a novel visual reasoning approach for video captioning, named Reasoning Module Networks (RMN), to equip the existing encoder-decoder framework with the above reasoning capacity. Specifically, our RMN employs 1) three sophisticated spatio-temporal reasoning modules, and 2) a dynamic and discrete module selector trained by a linguistic loss with a Gumbel approximation. Extensive experiments on MSVD and MSR-VTT datasets demonstrate the proposed RMN outperforms the state-of-the-art methods while providing an explicit and explainable generation process. Our code is available at https://github.com/tgc1997/RMN.
Aggregating Crowd Wisdom with Side Information via a Clustering-based Label-aware Autoencoder

Aggregating crowd wisdom infers true labels for objects, from multiple noisy labels provided by various sources. Besides labels from sources, side information such as object features is also introduced to achieve higher inference accuracy. Usually, the learning-from-crowds framework is adopted. However, the framework considers each object in isolation and does not make full use of object features to overcome label noise. In this paper, we propose a clustering-based label-aware autoencoder (CLA) to alleviate label noise. CLA utilizes clusters to gather objects with similar features and exploits clustering to infer true labels, by constructing a novel deep generative process to simultaneously generate object features and source labels from clusters. For model inference, CLA extends the framework of variational autoencoders and utilizes maximizing a posteriori (MAP) estimation, which prevents the model from overfitting and trivial solutions. Experiments on real-world tasks demonstrate the significant improvement of CLA compared with the state-of-the-art aggregation algorithms.
Learning Sensitivity of RCPSP by Analyzing the Search Process

Solving the problem is an important part of optimization. An equally important part is the analysis of the solution where several questions can arise. For a scheduling problem, is it possible to obtain a better solution by increasing the capacity of a resource? What happens to the objective value if we start a speciﬁc task earlier? Answering such questions is important to provide explanations and increase the acceptability of a solution. A lot of research has been done on sensitivity analysis, but few techniques can be applied to constraint programming. We present a new method for sensitivity analysis applied to constraint programming. It collects information, during the search, about the propagation of the CUMULATIVE constraint, the ﬁltering of the variables, and the solution returned by the solver. Using machine learning algorithms, we predict if increasing/decreasing the capacity of the cumulative resource allows a better solution. We also predict the impact on the objective value of forcing a task to ﬁnish earlier. We experimentally validate our method with the RCPSP problem.
Bridging the Gap between Training and Inference for Neural Machine Translation (Extended Abstract)

Neural Machine Translation (NMT) generates target words sequentially in the way of predicting the next word conditioned on the context words. At training time, it predicts with the ground truth words as context while at inference it has to generate the entire sequence from scratch. This discrepancy of the fed context leads to error accumulation among the translation. Furthermore, word-level training requires strict matching between the generated sequence and the ground truth sequence which leads to overcorrection over different but reasonable translations. In this paper, we address these issues by sampling context words not only from the ground truth sequence but also from the predicted sequence during training. Experimental results on NIST Chinese->English and WMT2014 English->German translation tasks demonstrate that our method can achieve significant improvements on multiple data sets compared to strong baselines.
The Plasmin System Is Induced by and Degrades Amyloid-β Aggregates

Amyloid-β (Aβ) appears critical to Alzheimer's disease. To clarify possible mechanisms of Aβ action, we have quantified Aβ-induced gene expression in vitro by using Aβ-treated primary cortical neuronal cultures and in vivo by using mice transgenic for the Aβ precursor (AβP). Here, we report that aggregated, but not nonaggregated, Aβ increases the level of the mRNAs encoding tissue plasminogen activator (tPA) and urokinase-type plasminogen activator (uPA). Moreover, tPA and uPA were also upregulated in aged AβP overexpressing mice. Because others have reported that Aβ aggregates can substitute for fibrin aggregates in activating tPA post-translationally, the result of tPAinduction by Aβ would be cleavage of plasminogen to the active protease plasmin. To gain insights into the possible actions of plasmin, we evaluated the hypotheses that tPA and plasmin may mediate Aβ in vitro toxicity or, alternatively, that plasmin activation may lead to Aβ degradation. In evaluating these conflicting hypotheses, we found that purified plasmin degrades Aβ with physiologically relevant efficiency, i.e., ∼1/10th the rate of plasmin on fibrin. Mass spectral analyses show that plasmin cleaves Aβ at multiple sites. Electron microscopy confirms indirect assays suggesting that plasmin degrades Aβ fibrils. Moreover, exogenously added plasmin blocks Aβ neurotoxicity. In summation, we interpret these results as consistent with the possibility that the plasmin pathway is induced by aggregated Aβ, which can lead to Aβ degradation and inhibition of Aβ actions.