Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure-Activity Relationships and Docking Studies of Hydroxychavicol and Its Analogs as Xanthine Oxidase Inhibitors.

Hydroxychavicol (HC), which is obtained from the leaves of Piper betle LINN. (Piperaceae), inhibits xanthine oxidase (XO) with an IC50 value of 16.7 µM, making it more potent than the clinically used allopurinol (IC50=30.7 µM). Herein, a structure-activity relationship analysis of the polar part analogs of HC was conducted and an inhibitor was discovered with a potency 13 times that of HC. Kinetic studies have revealed that HC and its active analog inhibit XO in an uncompetitive manner. The binding structure prediction of these inhibitor molecules to the XO complex with xanthine suggested that both compounds (HC and its analog) could simultaneously form hydrogen bonds with xanthine and XO.
Eigenvalue Bounds for the Signless p-Laplacian

We consider the signless $p$-Laplacian of a graph, a generalisation of the usual signless Laplacian (the case $p=2$). We show a Perron-Frobenius property and basic inequalites for the largest eigenvalue and provide upper and lower bounds for the smallest eigenvalue in terms of a parameter related to the bipartiteness. The latter result generalises bounds by Desai and Rao and, interestingly, in the limit $p\to 1$ upper and lower bounds coincide.
Of POOR ON SOME EQUIVALENT CONFIGURATIONS OF SYSTOLIC ARRAYS

In this paper we consider the problem of modeling and equalization of a nonlinear satellite channel. The channel is assumed to be bandlimited and exhibits both amplitude and phase nonlinearities. A discrete time satellite link is modeled under both uplink and downlink white Gaussian noise. Under conditions of practical interest, a simple and computationally ffficieni design technique for the minimum mean square error linear equalizer is presented. The bit error probability and some numerical results for a BPSK system demonstrate that the proposed equalization technique outperforms standard linear receiver structures.
Genetic Loci Associated with Alzheimer’s Disease and Cerebrospinal Fluid Biomarkers in a Finnish Case-Control Cohort

Objectives To understand the relation between risk genes for Alzheimer’s disease (AD) and their influence on biomarkers for AD, we examined the association of AD in the Finnish cohort with single nucleotide polymorphisms (SNPs) from top AlzGene loci, genome-wide association studies (GWAS), and candidate gene studies; and tested the correlation between these SNPs and AD markers Aβ1–42, total tau (t-tau), and phosphorylated tau (p-tau) in cerebrospinal fluid (CSF). Methods We tested 25 SNPs for genetic association with clinical AD in our cohort comprised of 890 AD patients and 701-age matched healthy controls using logistic regression. For the correlational study with biomarkers, we tested 36 SNPs in a subset of 222 AD patients with available CSF using mixed models. Statistical analyses were adjusted for age, gender and APOE status. False discovery rate for multiple testing was applied. All participants were from academic hospital and research institutions in Finland. Results APOE-ε4, CLU rs11136000, and MS4A4A rs2304933 correlated with significantly decreased Aβ1–42 (corrected p<0.05). At an uncorrected p<0.05, PPP3R1 rs1868402 and MAPT rs2435211 were related with increased t-tau; while SORL1 rs73595277 and MAPT rs16940758, with increased p-tau. Only TOMM40 rs2075650 showed association with clinical AD after adjusting for APOE-ε4 (p = 0.007), but not after multiple test correction (p>0.05). Conclusions We provide evidence that APOE-ε4, CLU and MS4A4A, which have been identified in GWAS to be associated with AD, also significantly reduced CSF Aβ1–42 in AD. None of the other AlzGene and GWAS loci showed significant effects on CSF tau. The effects of other SNPs on CSF biomarkers and clinical AD diagnosis did not reach statistical significance. Our findings suggest that APOE-ε4, CLU and MS4A4A influence both AD risk and CSF Aβ1–42.
Convolutional Neural Networks For Automated Edema Segmentation in Patients With Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is a common type of stroke with high morbidity and mortality rate. Edema often forms around ICH. Because edema increases the chance of poor outcome, edema quantification is needed for finding the optimal ICH treatment. CNN has been proven to be a reliable method in medical image segmentation. In this study, we introduce CNN to develop an automated method for edema and ICH quantification. We found that our CNN is a promising quantification method for edema.
Development of National Norm for Multidimensional Sub-health Questionnaire of Adolescents(MSQA)

Objective To describe the distribution characteristics of physical and psychological sub-health,and to develop the national norm for adolescents.Methods The sample of 22 325 students were chosen from middle school and high school in city and countryside,they were from 9 cities in 9 provinces.The multidimensional sub-health questionnaire of adolescents was used for self-rating,and calculated the values of P85,P90,and P95 related to physical and psychological domains and six dimensions.Results There was no significant gender difference in incidence of physical,psychological and total sub-health,but there was significant difference in grade,just that high school was higher than middle school and university.The high school had the highest P85 incidence of physical,psychological and total and six dimensions of adolescents,and then were the middle school and university.Conclusion Proposed P85 as the demarcation value for adolescents' physical,psychological and total sub-health of different grades,it can be used as epidemiology criterion for sub-health study of adolescents in China.
Exergaming: Interactive balance training in healthy community-dwelling older adults

Exergaming is a term used for videogame exercise. The aim of this study was to examine the training effect of an exergame that relies on the movements of a dynamic balance board. Nine healthy elderly subjects participated in a six-week intervention in which they played balance games three times a week. before, after and during the intervention phase balance was assessed with the figure-of-eight test, the berg balance Scale (BBS), and the tandem and one-leg stance, both performed with eyes open and closed. Intervention effects were examined using multilevel modeling statistics. predomi- nantly, the dynamic balance performance, measured by the figure-of-eight and the BBS, improved (p
HEALTH Metaphor in Political and Economic Discourse: a Cross-Linguistic Analysis

The present paper sets out to examine the conceptua l metaphor of HEALTH through its linguistic realisation in English and Lithuanian political and economic discourse. The investigation relies on th e cognitive theory of metaphor and applies its main theoretical principles alongside with the frequency count and cross- linguistic comparison. The results have revealed th at HEALTH metaphors are twice as frequent in English; however, both languages are equally prone to conceptualise political and economic difficulties in term s of health problems. Of the seven types of HEALTH metaphors, the most numerously represented is the PROBLEM IS AILMENT / MALFUNCTION metaphor. The same major tendencies of metaphorical reasoning have been preserved in both languages. The lexical realisation, however , remains in some types of metaphors very culture-s pecific. Overall, the results have demonstrated that the soc io-economic discourse is conceptualised in accordan ce with the universal embodiment/ anthropocentric parameter of the cognitive linguistic theory of metaphor and has preserved some culture-specific features .
On the Power Law Property of Latency-Reducing Relays

Application relays can be used to reduce latency for real-time media communication. In this paper, we utilize the triangle inequality violations (TIV) in delay space to model the relays and analyze their properties in several data sets. We find that both the demand and utility for relays approximate the power law distribution, which inspires us to deduce guidelines to further improve the efficiency of relay discovery and selection algorithms.
Evaluating Classiﬁers

In a real-world application of supervised learning, we have a training set of examples with labels, and a test set of examples with unknown labels. The whole point is to make predictions for the test examples. However, in research or experimentation we want to measure the performance achieved by a learning algorithm. To do this we use a test set consisting of examples with known labels. We train the classifier on the training set, apply it to the test set, and then measure performance by comparing the predicted labels with the true labels (which were not available to the training algorithm). Sometimes we have a training set and a test set given already. Other times, we just have one database of labeled training examples. In this case, we have to divide the database ourselves into separate training and test subsets. A common rule of thumb is to use 70% of the database for training and 30% for testing. Dividing the database into training and test subsets is usually done randomly, in order to guarantee that both subsets are random samples from the same distribution. It can be reasonable to do stratified sampling, which means to ensure that each class is present in the exact same proportion in the training and test subsets. It is absolutely vital to measure the performance of a classifier on an independent test set. Every training algorithm looks for patterns in the training data, i.e. correlations between the features and the class. Some of the patterns discovered may be spurious, i.e. they are valid in the training data due to randomness in how the training data was selected from the population, but they are not valid, or not as strong, in the whole population. A classifier that relies on these spurious patterns will have higher accuracy on the training examples than it will on the whole population. Only accuracy measured on an independent test set is a fair estimate of accuracy on the whole population. The phenomenon of relying on
Dynamics of nutrient utilization, heat production, and body composition in broiler breeder hens during egg production

Abstract Changes in heat production (HP) and body composition (BC) in modern broiler breeders can provide means to understand nutrient utilization. Twelve Cobb 500 breeders were evaluated 10 times from 26 to 59 wk of age. The same wired caged breeders were moved to respiratory chambers connected to an indirect calorimetry to obtain oxygen consumption (VO2) and carbon dioxide production (VCO2), HP, and respiratory exchange ratio (RER). The same hens were evaluated for BC using a dual X‐ray absorptiometry (DEXA). Data were analyzed during light (16 h) and dark (8 h) period using a mixed model to evaluate calorimetry parameters, a factorial design 2 × 10 for normalized calorimetry parameters, and Complete Randomized Design (CRD)—one way ANOVA for BC. Means were separated by Tukey‐Honest Significant difference (HSD). HP increased with age (d) in 0.152 kcal/d, VO2 and VCO2 were 0.031 and 0.024 L/d per each increase in age (d), respectively. In the light period, hens consumed +17.4 L/d VO2 and produced +18.9 L/d VCO2 (P < 0.01). HP during the dark period was 84 kcal/kg0.75 and during the light period was 115 kcal/kg0.75. RER decreased with age until 43 wk and remained the same until 59 wk suggesting more fat and/or protein being oxidized at later periods of production. Lean body mass ranged from 642 to 783 g/kg during the whole study reaching the lowest at 37 and 50 wk and the highest at 26 to 33 wk (P < 0.01). Body fat ranged from 168 to 261 g/kg with the lowest at 26 to 33 wk and the highest at 50 wk of age (P < 0.01). Broiler breeder females may be catabolizing fat energy reserves from 50 wk onwards when the egg production is reduced, and HP increased at 54 and 59 wk (P < 0.01) due to higher energy required for maintenance of a higher lean mass structure. Broiler breeders change nutrient fuel use during egg production. Indirect calorimetry and DEXA can be used to pursue further feed strategies to maximize egg production and maintain a healthy breeder.
Open Problem: Adversarial Multiarmed Bandits with Limited Advice

Adversarial multiarmed bandits with expert advice is one of the fundamental problems in studying the exploration-exploitation trade-o. It is known that if we observe the advice of all experts on every round we can achieve O(√KTlnN) regret, where K is the number of arms, T is the number of game rounds, and N is the number of experts. It is also known that if we observe the advice of just one expert on every round, we can achieve regret of order O(√NT). Our open problem is what can be achieved by asking M experts on every round, where 1 < M < N.
Antibody Reactivity of Synthetic Peptides Belonging to Proteins Encoded by Genes Located in Mycobacterium tuberculosis-Specific Genomic Regions of Differences

The comparisons of mycobacterial genomes have identified several Mycobacterium tuberculosis-specific genomic regions that are absent in other mycobacteria and are known as regions of differences. Due to M. tuberculosis-specificity, the peptides encoded by these regions could be useful in the specific diagnosis of tuberculosis. To explore this possibility, overlapping synthetic peptides corresponding to 39 proteins predicted to be encoded by genes present in regions of differences were tested for antibody-reactivity with sera from tuberculosis patients and healthy subjects. The results identified four immunodominant peptides corresponding to four different proteins, with three of the peptides showing significantly stronger antibody reactivity and rate of positivity with sera from tuberculosis patients than healthy subjects. The fourth peptide was recognized equally well by the sera of tuberculosis patients as well as healthy subjects. Predication of antibody epitopes by bioinformatics analyses using ABCpred server predicted multiple linear epitopes in each peptide. Furthermore, peptide sequence analysis for sequence identity using BLAST suggested M. tuberculosis-specificity for the three peptides that had preferential reactivity with sera from tuberculosis patients, but the peptide with equal reactivity with sera of TB patients and healthy subjects showed significant identity with sequences present in nobtuberculous mycobacteria. The three identified M. tuberculosisspecific immunodominant peptides may be useful in the serological diagnosis of tuberculosis. Keywords—Genomic regions of differences, Mycobacterium tuberculosis, peptides, serodiagnosis.
The impact of an in-class sensory activity schedule on task performance of children with autism and intellectual disability: A pilot study

Introduction There is limited evidence to support use of sensory interventions by teachers in the classroom. The purpose of this pilot study is to determine the effectiveness of sensory activity schedule intervention in supporting participation and increasing classroom task performance in students with autism. Method A non-concurrent, AB single system research design across multiple baselines was used with four students with autism who attended an autism-specific school. Students demonstrated atypical sensory processing, which negatively affected their school performance. Repeated baseline and intervention data were collected by school staff using video recording during classroom tasks. Tasks performed were designated by the child’s teacher. Stage one of the Perceive, Recall, Plan, Perform System of Task Analysis was used as a repeated measure of student performance. Ratings were carried out by independent raters who were blinded to the condition of performance. Results Results revealed three out of four students achieved significant improvements in classroom task performance following the use of sensory activity schedule intervention developed in consultation with an occupational therapist as measured by the task analysis. Conclusion This study provides emerging evidence for the use of sensory activity schedule intervention in the classroom for students with autism.
Heart rate variability testing: could it change spending for rheumatoid arthritis patients in the United States? An exploratory economic analysis

Abstract Background: Autonomic nervous system (ANS) testing with heart rate variability (HRV) has been shown in early research to predict 52-week outcomes in rheumatoid arthritis (RA). HRV testing could be combined with putative ANS biologic pathways to improve treatment response for RA patients. This study explored potential costs and health outcomes of introducing HRV testing into RA treatment, without and with ANS optimization. Methods: A decision tree exploratory economic model compared HRV testing to standard care in moderate-to-severe biologic-eligible patients over a 10-year time horizon. HRV data was derived from an observational study of RA patients (n = 33). Patients were stratified into treatment groups based on HRV test scores indicating “low probability of response” and “moderate to high probability of response”. This study explored adding ANS optimization based on HRV score followed by clinically-appropriate treatment. Costs and quality-adjusted life-years (QALYs) for the US population were estimated. Results: HRV testing in biologic-eligible patients decreased non-effective biologic use, reducing US healthcare costs by $34.6 billion over 10 years with QALYs unchanged. When combined with ANS optimization in biologic-eligible patients, HRV testing could increase costs by $3.6 billion over 10 years but save over 350,000 QALYs. Among all RA patients, HRV testing with ANS optimization could save over $8 billion and over 100,000 QALYs over 10 years, depending on the positive predictive value (PPV) of the HRV test. Conclusions: The potential economic impact of introducing HRV testing and ANS optimization into RA treatment appears substantial and cost-effective based on the exploratory analysis. Additional rigorous studies are warranted in larger patient samples to better inform decision-making.
Predictors of perceived stigmatization in patients with psoriasis

The physical appearance of psoriasis can be cosmetically disfiguring, resulting in a substantial social burden for patients. An important aspect of this burden is the experience of stigmatization. While stigmatization is known to be disabling and stressful for patients, little is known about its correlates, and effective interventions are lacking.
Efficient gene transfer in C.elegans: extrachromosomal maintenance and integration of transforming sequences.

We describe a dominant behavioral marker, rol‐6(su‐1006), and an efficient microinjection procedure which facilitate the recovery of Caenorhabditis elegans transformants. We use these tools to study the mechanism of C.elegans DNA transformation. By injecting mixtures of genetically marked DNA molecules, we show that large extrachromosomal arrays assemble directly from the injected molecules and that homologous recombination drives array assembly. Appropriately placed double‐strand breaks stimulated homologous recombination during array formation. Our data indicate that the size of the assembled transgenic structures determines whether or not they will be maintained extrachromosomally or lost. We show that low copy number extrachromosomal transformation can be achieved by adjusting the relative concentration of DNA molecules in the injection mixture. Integration of the injected DNA, though relatively rare, was reproducibly achieved when single‐stranded oligonucleotide was co‐injected with the double‐stranded DNA.
Improving the Drought Tolerance in Barley by Osmopriming and Biopriming

Determination of physiological and biochemical changes induced by drought stress can be helpful for induction of stress tolerance in plants. This 2-years study was conducted to determine the potential of different seed priming techniques in improving tolerance of barley against drought stress at different levels. Seeds of two barley genotypes (Haider-93 and Frontier-87) were primed with aerated water (hydropriming), and solutions of CaCl2 (1.5%; osmopriming) or Enterobacter sp. strain FD17 (biopriming) for 12 h keeping seed to solution ratio of 1:5 (w/v) while non-primed (dry) seeds were taken as control. Primed and non-primed seeds were sown in soil-filled earthen pots. After uniformity of seedling establishment, soil moisture was maintained at 80 (well-watered), 60 (moderate drought) and 40% (severe drought) of water holding capacity. Drought stress decreased plant growth, yield, chlorophyll contents, water relations and grain nutrient contents, while increased osmolytes accumulation and lipid peroxidation in both genotypes. Seed priming, biopriming in particular, improved leaf area, grain yield, chlorophyll contents, accumulation of phenolics, proline, glycine betaine, total soluble proteins, relative water contents, water, osmotic and pressure potentials, cell membrane stability, and grain Zn, Mn and B contents, while decreased malondialdehyde contents in both genotypes under drought stress. Improvement in yield and related traits by seed priming under drought stress was in the order biopriming>osmopriming>hydropriming. However, seed priming induced tolerance was more prominent under moderate drought than severe drought stress. Performance of genotype Haider-93 was quite better than Frontier-87. In conclusion, seed priming induced increase in osmolytes accumulation enhanced drought tolerance in barley by improving water relations and decreasing lipid peroxidation. Thus, seed priming, mainly biopriming with Enterobacter sp. strain FD17, could be utilized to improve barley performance under drought stress. © 2018 Friends Science Publishers
Identification of a potential fibromyalgia diagnosis using random forest modeling applied to electronic medical records

Background Diagnosis of fibromyalgia (FM), a chronic musculoskeletal condition characterized by widespread pain and a constellation of symptoms, remains challenging and is often delayed. Methods Random forest modeling of electronic medical records was used to identify variables that may facilitate earlier FM identification and diagnosis. Subjects aged ≥18 years with two or more listings of the International Classification of Diseases, Ninth Revision, (ICD-9) code for FM (ICD-9 729.1) ≥30 days apart during the 2012 calendar year were defined as cases among subjects associated with an integrated delivery network and who had one or more health care provider encounter in the Humedica database in calendar years 2011 and 2012. Controls were without the FM ICD-9 codes. Seventy-two demographic, clinical, and health care resource utilization variables were entered into a random forest model with downsampling to account for cohort imbalances (<1% subjects had FM). Importance of the top ten variables was ranked based on normalization to 100% for the variable with the largest loss in predicting performance by its omission from the model. Since random forest is a complex prediction method, a set of simple rules was derived to help understand what factors drive individual predictions. Results The ten variables identified by the model were: number of visits where laboratory/non-imaging diagnostic tests were ordered; number of outpatient visits excluding office visits; age; number of office visits; number of opioid prescriptions; number of medications prescribed; number of pain medications excluding opioids; number of medications administered/ordered; number of emergency room visits; and number of musculoskeletal conditions. A receiver operating characteristic curve confirmed the model’s predictive accuracy using an independent test set (area under the curve, 0.810). To enhance interpretability, nine rules were developed that could be used with good predictive probability of an FM diagnosis and to identify no-FM subjects. Conclusion Random forest modeling may help to quantify the predictive probability of an FM diagnosis. Rules can be developed to simplify interpretability. Further validation of these models may facilitate earlier diagnosis and enhance management.