Miracle-dz/UniFAR-FTUs huggingface dataset:
TrnH-psbA sequence analyses of asparagus cochinchinensis from different geographical origin in China

This template explains and demonstrates how to prepare your camera-ready paper for The trnH-psbA sequences of 13 Asparagus cochinchinensis populations from 6 provinces of China were studied. The results showed that length of trnH-psbA change and the mutation of GC content were small. The length of trnH-psbA sequences were from 619 bp to 632 bp, and the GC content was about 36%. The total variation rates of 13 populations were from 2.21% to 3.47%, when the missing sites were considered as variation sites. A. cochinchinensis from different sources had 10 information sites in trnH-psbA sequence, accounting for 1.58% of the total sequence. The information sites were located in the sites 8, 9, 120, 457, 458, 486, 487, 491, 492, and 593, respectively. Clustering analysis showed that the Qianxi and Hengshan populations clustered together; Dushan, Yuqing, and Guangzhou populations were grouped; Nanning and Xinning populations formed another cluster. trnH-psbA sequences could identify different A. cochinchinensis populations. Clustering of different A. cochinchinensis populations related primarily to latitude and had little relationship with longitude.
Interaction of Bacterial Phenazines with Colistimethate in Bronchial Epithelial Cells

ABSTRACT Multidrug-resistant bacterial infections are being increasingly treated in clinics with polymyxins, a class of antibiotics associated with adverse effects on the kidney, nervous system, or airways of a significant proportion of human and animal patients. Although many of the resistant pathogens display enhanced virulence, the hazard of cytotoxic interactions between polymyxin antibiotics and bacterial virulence factors (VFs) has not been assessed, to date. We report here the testing of paired combinations of four Pseudomonas aeruginosa VF phenazine toxins, pyocyanin (PYO), 1-hydroxyphenazine (1-HP), phenazine-1-carboxylic acid (PCA), and phenazine-1-carboxamide (PCN), and two commonly prescribed polymyxin drugs, colistin-colistimethate sodium (CMS) and polymyxin B, in three human airway cell lines, BEAS-2B, HBE-1, and CFT-1. Cytotoxicities of individual antibiotics, individual toxins, and their combinations were evaluated by the simultaneous measurement of mitochondrial metabolic, total transcriptional/translational, and Nrf2 stress response regulator activities in treated cells. Two phenazines, PYO and 1-HP, were cytotoxic at clinically relevant concentrations (100 to 150 μM) and prompted a significant increase in oxidative stress-induced transcriptional activity in surviving cells. The polymyxin antibiotics arrested cell proliferation at clinically achievable (<1 mM) concentrations as well, with CMS displaying surprisingly high cytotoxicity (50% effective dose [ED50] = 180 μM) in BEAS-2B cells. The dose-response curves were probed by a median-effect analysis, which established a synergistically enhanced cytotoxicity of the PYO-CMS combination in all three airway cell lines; a particularly strong effect on BEAS-2B cells was observed, with a combination index (CI) of 0.27 at the ED50. PCA, PCN, and 1-HP potentiated CMS cytotoxicity to a smaller extent. The cytotoxicity of CMS could be reduced with 10 mM N-acetyl-cysteine. Iron chelators, while ineffective against the polymyxins, could rescue all three bronchial epithelial cell lines treated with lethal PYO or CMS-PYO doses. These findings suggest that further evaluations of CMS safety are needed, along with a search for means to moderate potentially cytotoxic interactions.
Two-Dimensional PCA with F-Norm Minimization

Two-dimensional principle component analysis (2DPCA) has been widely used for face image representation and recognition. But it is sensitive to the presence of outliers. To alleviate this problem, we propose a novel robust 2DPCA, namely 2DPCA with F-norm minimization (F-2DPCA), which is intuitive and directly derived from 2DPCA. In F-2DPCA, distance in spatial dimensions (attribute dimensions) is measured in F-norm, while the summation over different data points uses 1-norm. Thus it is robust to outliers and rotational invariant as well. To solve F-2DPCA, we propose a fast iterative algorithm, which has a closed-form solution in each iteration, and prove its convergence. Experimental results on face image databases illustrate its effectiveness and advantages.
Comparison of a Rat Primary Cell-Based Blood-Brain Barrier Model With Epithelial and Brain Endothelial Cell Lines: Gene Expression and Drug Transport

Cell culture-based blood-brain barrier (BBB) models are useful tools for screening of CNS drug candidates. Cell sources for BBB models include primary brain endothelial cells or immortalized brain endothelial cell lines. Despite their well-known differences, epithelial cell lines are also used as surrogate models for testing neuropharmaceuticals. The aim of the present study was to compare the expression of selected BBB related genes including tight junction proteins, solute carriers (SLC), ABC transporters, metabolic enzymes and to describe the paracellular properties of nine different culture models. To establish a primary BBB model rat brain capillary endothelial cells were co-cultured with rat pericytes and astrocytes (EPA). As other BBB and surrogate models four brain endothelial cells lines, rat GP8 and RBE4 cells, and human hCMEC/D3 cells with or without lithium treatment (D3 and D3L), and four epithelial cell lines, native human intestinal Caco-2 and high P-glycoprotein expressing vinblastine-selected VB-Caco-2 cells, native MDCK and MDR1 transfected MDCK canine kidney cells were used. To test transporter functionality, the permeability of 12 molecules, glucopyranose, valproate, baclofen, gabapentin, probenecid, salicylate, rosuvastatin, pravastatin, atorvastatin, tacrine, donepezil, was also measured in the EPA and epithelial models. Among the junctional protein genes, the expression level of occludin was high in all models except the GP8 and RBE4 cells, and each model expressed a unique claudin pattern. Major BBB efflux (P-glycoprotein or ABCB1) and influx transporters (GLUT-1, LAT-1) were present in all models at mRNA levels. The transcript of BCRP (ABCG2) was not expressed in MDCK, GP8 and RBE4 cells. The absence of gene expression of important BBB efflux and influx transporters BCRP, MRP6, -9, MCT6, -8, PHT2, OATPs in one or both types of epithelial models suggests that Caco-2 or MDCK models are not suitable to test drug candidates which are substrates of these transporters. Brain endothelial cell lines GP8, RBE4, D3 and D3L did not form a restrictive paracellular barrier necessary for screening small molecular weight pharmacons. Therefore, among the tested culture models, the primary cell-based EPA model is suitable for the functional analysis of the BBB.
Learning Environmental Calibration Actions for Policy Self-Evolution

Reinforcement learning in physical world is often expensive. Simulators are commonly employed to train policies. Due to the simulation error, trained-in-simulator policies are hard to be directly deployed in physical world. Therefore, how to efficiently reuse these policies to the real environment is a key issue. To address this issue, this paper presents a policy self-evolution process: in the target environment, the agent firstly executes a few calibration actions to perceive the environment, and then reuses the previous policies according to the observation of the environment. In this way, the mission of policy learning in the target environment is reduced to the task of environment identification through executing the calibration actions, which needs much less samples than learning a policy from scratch. We propose the POSEC (POlicy Self-Evolution by Calibration) approach, which learns the most informative calibration actions for policy self-evolution. Taking three robotic arm controlling tasks as the test beds, we show that the proposed method can learn a fine policy for a new arm with only a few (e.g. five) samples of the target environment.
The effects of probiotics supplementation on metabolic health in pregnant women: An evidence based meta-analysis

The prevalence of maternal obesity and gestational diabetes mellitus (GDM) is increasing rapidly. Probiotics supplementation have been shown to improve metabolic health in humans. In our study, we aimed to evaluate the effects of probiotics supplementation on metabolic health and pregnancy complications in pregnant women. The literature search, data extraction and quality assessment were performed, and data were synthesized in accordance with standardized guidelines. Ten randomized clinical trials with eligible data were included in our meta-analysis. For pregnant women with GDM, we found negative correlations between probiotics supplementation and fasting serum insulin (OR -2.94, 95%CI [-5.69, -0.20], p = 0.04) and homoeostasis model assessment for insulin resistance (HOMA-IR) (OR -0.65, 95%CI [-1.18, -0.11], p = 0.02). There were no significant correlations between probiotics supplementation and lipid levels in women with GDM, including total cholesterol (OR -2.72, 95%CI [-17.18, 11.74], P = 0.71), high density lipoprotein cholesterol (HDL-c) (OR -0.29, 95%CI [-3.60, 3.03], P = 0.87), low density lipoprotein cholesterol (LDL-c) (OR -0.38, 95%CI [-18.54, 17.79], P = 0.97), or triglycerides (OR -12.83, 95%CI [-36.63, 10.97], P = 0.29). For healthy pregnant women, probiotics supplementation were negatively associated with fasting serum insulin (OR -3.76, 95%CI [-4.29, -3.23], P < 0.00001) and HOMA-IR (OR -0.57, 95%CI [-1.08, -0.06], p = 0.03). However, no significant correlations were observed between probiotics supplementation and fasting plasma glucose (FPG) (OR -2.02, 95%CI [-5.56, 1.52], p = 0.26). Thus, our study revealed that probiotics supplementation during pregnancy have beneficial effects on glucose metabolism, rather than lipid metabolism among pregnant women.
What are the causes of a suboptimal FFR after coronary stent deployment? Insights from a consecutive series using OCT imaging.

AIMS Fractional flow reserve (FFR) can be used to detect a suboptimal result after percutaneous coronary intervention (PCI). A lower post-procedure FFR (<0.90) has been shown to be associated with adverse clinical outcomes at follow-up. This pilot study aimed to understand the mechanisms resulting in a suboptimal FFR and whether optical coherence tomography (OCT)-guided optimisation could improve final FFR. METHODS AND RESULTS Thirty-five patients undergoing complex PCI were prospectively enrolled. After stenting and post-dilatation, OCT and pressure wire were performed. An FFR threshold <0.90 after PCI was defined as suboptimal and mandated further PCI optimisation. A satisfactory post-PCI FFR (predefined as ≥0.90) was achieved immediately after conventional PCI in 14 patients (40%) and in this group no further treatment was performed. Minor abnormalities (stent malapposition of 200-500 µm) were observed with OCT in three of these patients. Suboptimal functional results after conventional stenting (predefined as an FFR <0.90) were found in 21 patients (60%). In thirteen out of these 21 patients (61.9%), OCT demonstrated a suboptimal stent result. Subsequent OCT-guided optimisation was performed resulting in a higher final FFR (increase from 0.80±0.02 to 0.88±0.01; p=0.008). CONCLUSIONS Despite a satisfactory angiographic result, a suboptimal functional result is evident in a substantial proportion of patients undergoing complex PCI. Implementation of an OCT-guided PCI optimisation protocol may reveal potentially treatable causes, allowing optimisation of the post-PCI functional result.
An Elevated Dietary Cysteine to Methionine Ratio Does Not Impact on Dietary Methionine Efficiency and the Derived Optimal Methionine to Lysine Ratio in Diets for Meat Type Chicken

Optimal dietary methionine (Met) to lysine (Lys) ratio in presence of elevated dietary cysteine (Cys) levels was derived for meat type growing chicken. Twelve averaged weighed Ross 308 birds (each 50% of male and female per dietary treatment) were utilized in N balance trials. During starter (d10 - 20) and grower period (d25 - 35) five dietary treatments were used. Diets based on uniform mixtures of maize, wheat, soybean meal, potato protein and fish meal were supplemented with crystalline amino acids (AA). In diets 1 - 3, the dietary Cys to Met ratio was set as 85, 95 and 105 to 100, respectively. Diet 4, at a Cys to Met ratio of 105 to 100, was additionally supplemented with betaine (BET) as methyl group donor. Diets 1 - 4 were limiting in Met, diet 5 without L-Lys·HCl addition was limiting in Lys. Individual N-balance data per treatment were utilized for assessing protein quality and efficiency of dietary Met (Diets 1 - 4) or Lys (Diet 5) based on “Goettingen approach”. Elevated dietary Cys supply and supplemented BET failed to improve both dietary protein quality and Met efficiency. The established optimal Met to Lys ratio was on average 34 to 100 for growing chicken during starter and grower period, respectively.
Learning with Non-Convex Truncated Losses by SGD

Learning with a {\it convex loss} function has been a dominating paradigm for many years. It remains an interesting question how non-convex loss functions help improve the generalization of learning with broad applicability. In this paper, we study a family of objective functions formed by truncating traditional loss functions, which is applicable to both shallow learning and deep learning. Truncating loss functions has potential to be less vulnerable and more robust to large noise in observations that could be adversarial. More importantly, it is a generic technique without assuming the knowledge of noise distribution. To justify non-convex learning with truncated losses, we establish excess risk bounds of empirical risk minimization based on truncated losses for heavy-tailed output, and statistical error of an approximate stationary point found by stochastic gradient descent (SGD) method. Our experiments for shallow and deep learning for regression with outliers, corrupted data and heavy-tailed noise further justify the proposed method.
Calculation of the Surface Tension of Ordinary Organic and Ionic Liquids by Means of a Generally Applicable Computer Algorithm Based on the Group-Additivity Method

The calculation of the surface tension of ordinary organic and ionic liquids, based on a computer algorithm applying a refined group-additivity method, is presented. The refinement consists of the complete breakdown of the molecules into their constituting atoms, further distinguishing them by their immediate neighbour atoms and bond constitution. The evaluation of the atom-groups’ contributions was carried out by means of a fast Gauss-Seidel fitting method, founded upon the experimental data of 1893 compounds from literature. The result has been tested for plausibility using a 10-fold cross-validation (cv) procedure. The direct calculation and the cv test proved the applicability of the present method by the close similarity and excellent goodness of fit R2 and Q2 of 0.9039 and 0.8823, respectively. The respective standard deviations are ±1.99 and ±2.16 dyn/cm. Some correlation peculiarities have been observed in a series of ordinary and ionic liquids with homologous alkyl chains, as well as with di- and trihydroxy-groups-containing liquids, which have been discussed in detail, exhibiting the limit of the present method.
NeuralREG: An end-to-end approach to referring expression generation

Traditionally, Referring Expression Generation (REG) models first decide on the form and then on the content of references to discourse entities in text, typically relying on features such as salience and grammatical function. In this paper, we present a new approach (NeuralREG), relying on deep neural networks, which makes decisions about form and content in one go without explicit feature extraction. Using a delexicalized version of the WebNLG corpus, we show that the neural model substantially improves over two strong baselines.
Effect of season and breed on physiological and blood parameters in buffaloes

In this Research Communication we describe the effect of temperature and humidity index (THI) on various physiological traits, the plasma heat shock protein 70 (HSP70), heat shock protein 90 (HSP90) and cortisol levels and other blood parameters in crossbred buffalo (Nili-Ravi × Murrah) and Mediterranean buffalo to compare their tolerance to heat stress. As expected, crossbred buffalo had a significantly higher rectal temperature (RT), body surface temperature (BT), respiratory rate (RR), HSP70 and HSP90 levels in summer compared to spring and winter. RT and BT were also significantly higher in spring compared to winter. A significant correlation existed between THI and RT (r = 0·81) and RR (r = 0·84). Importantly, in summer the crossbred buffalo had a significantly lower RT, BT and RR and higher HSP70, HSP90 and cortisol levels than the Mediterranean buffalo. In conclusion, higher THI was associated with significant increase in RT, RR, BT, HSP70, HSP90 and cortisol levels, and the crossbred buffalo were more heat tolerant than Mediterranean buffalo.
Intention of Older Women to Consume 100% Watermelon Juice for Vascular Health: An Application of Theory of Planned Behavior

Abstract To strengthen randomized controlled trials (RCT) evaluating the efficacy of 100% watermelon juice on vascular function of older women, theory-driven behavioral analysis as well as comparative sensory analysis of the intervention and placebo were conducted. The Theory of Planned Behavior was adopted to assess psychosocial determinants of intention to consume watermelon juice. Sensory attributes were assessed utilizing hedonic scales. Analysis included Structural Equation Modeling with maximum likelihood. The measurement model provided a good fit (x2 = 70.22, df = 38; RMSEA = 0.07, CFI = 0.98; NFI = 0.95). Attitude (γ = 0.36), subjective norm (γ = 0.43), and perceived behavioral control (γ = 0.21,) were significant predictors (p < 0.001) of intention. Participants identified no significant differences in sensorial attributes between beverages, thereby minimizing sensory bias and discrimination. Similar approaches may help other RCT investigating novel foods and bioactive compounds bridge gaps between efficacy and effectiveness.
Developmental and molecular responses of buffalo (Bubalus bubalis) cumulus–oocyte complex matured in vitro under heat shock conditions

Summary To investigate the effects of physiologically relevant heat shock during oocyte maturation, buffalo cumulus–oocyte complexes (COCs) were cultured at 38.5°C (control) or were exposed to 39.5°C (T1) or 40.5°C (T2) for the first 6 h of in vitro maturation (IVM), followed by 38.5°C through the next 18 h/IVM and early embryonic development up to the blastocyst stage. Gene expression analysis was performed on selected target genes (HSF-1, HSF-2, HSP-70, HSP-90, BAX, p53, SOD1, COX1, MAPK14) in denuded oocytes and their isolated cumulus cells resulting from control COCs as well as from COCs exposed to a temperature of 39.5°C (T1). The results indicated that heat shock significantly (P < 0.01) decreased the maturation rate in T1 and T2 cells compared with the control. After in vitro fertilization (IVF), cleavage rate was lower (P < 0.01) for oocytes exposed to heat stress, and the percentage of oocytes arrested at the 2- or 4-cell stage was higher (P < 0.01) than that of the control. The percentage of oocytes that developed to the 8-cell, 16-cell or blastocyst stage was lower (P < 0.01) in both T1 and T2 groups compared with the control group. mRNA expression levels for the studied genes were decreased (P < 0.05) in treated oocytes (T1) except for HSP-90 and HSF-1, which were increased. In cumulus cells isolated from COCs (T1), the expression for the target genes was upregulated except for BAX, which was downregulated. The results of this study demonstrated that exposure of buffalo oocytes to elevated temperatures for 6 h severely compromised their developmental competence and gene expression.
Luteolin ameliorates rat myocardial ischaemia–reperfusion injury through activation of peroxiredoxin II

Antioxidants provide a promising therapeutic effect for the cardiovascular disease. Luteolin, a polyphenolic bioflavonoid, is known to confer cardioprotection, although the underlying mechanisms, especially the role of luteolin on the antioxidant enzymes, such as the peroxiredoxin family, remain unknown.
Masking: A New Perspective of Noisy Supervision

It is important to learn various types of classifiers given training data with noisy labels. Noisy labels, in the most popular noise model hitherto, are corrupted from ground-truth labels by an unknown noise transition matrix. Thus, by estimating this matrix, classifiers can escape from overfitting those noisy labels. However, such estimation is practically difficult, due to either the indirect nature of two-step approaches, or not big enough data to afford end-to-end approaches. In this paper, we propose a human-assisted approach called Masking that conveys human cognition of invalid class transitions and naturally speculates the structure of the noise transition matrix. To this end, we derive a structure-aware probabilistic model incorporating a structure prior, and solve the challenges from structure extraction and structure alignment. Thanks to Masking, we only estimate unmasked noise transition probabilities and the burden of estimation is tremendously reduced. We conduct extensive experiments on CIFAR-10 and CIFAR-100 with three noise structures as well as the industrial-level Clothing1M with agnostic noise structure, and the results show that Masking can improve the robustness of classifiers significantly.
Efficient Online Portfolio with Logarithmic Regret

We study the decades-old problem of online portfolio management and propose the first algorithm with logarithmic regret that is not based on Cover's Universal Portfolio algorithm and admits much faster implementation. Specifically Universal Portfolio enjoys optimal regret $\mathcal{O}(N\ln T)$ for $N$ financial instruments over $T$ rounds, but requires log-concave sampling and has a large polynomial running time. Our algorithm, on the other hand, ensures a slightly larger but still logarithmic regret of $\mathcal{O}(N^2(\ln T)^4)$, and is based on the well-studied Online Mirror Descent framework with a novel regularizer that can be implemented via standard optimization methods in time $\mathcal{O}(TN^{2.5})$ per round. The regret of all other existing works is either polynomial in $T$ or has a potentially unbounded factor such as the inverse of the smallest price relative.