Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of short-term fasting on in vivo rumen microbiota and in vitro rumen fermentation characteristics

Objective Fasting may lead to changes in the microbiota and activity in the rumen. In the present study, the effects of fasting on rumen microbiota and the impact of fasting on in vitro rumen fermentation were evaluated using molecular culture-independent methods. Methods Three ruminally cannulated Holstein steers were fed rice straw and concentrates. The ruminal fluids were obtained from the same steers 2 h after the morning feeding (control) and 24 h after fasting (fasting). The ruminal fluid was filtrated through four layers of muslin, collected for a culture-independent microbial analysis, and used to determine the in vitro rumen fermentation characteristics. Total DNA was extracted from both control and fasting ruminal fluids. The rumen microbiota was assessed using denaturing gradient gel electrophoresis (DGGE) and quantitative polymerase chain reaction. Microbial activity was evaluated in control and fasting steers at various intervals using in vitro batch culture with rice straw and concentrate at a ratio of 60:40. Results Fasting for 24 h slightly affected the microbiota structure in the rumen as determined by DGGE. Additionally, several microorganisms, including Anaerovibrio lipolytica, Eubacterium ruminantium, Prevotella albensis, Prevotella ruminicola, and Ruminobacter amylophilus, decreased in number after fasting. In addition, using the ruminal fluid as the inoculum after 24 h of fasting, the fermentation characteristics differed from those obtained using non-fasted ruminal fluid. Compared with the control, the fasting showed higher total gas production, ammonia, and microbial protein production (p<0.05). No significant differences, however, was observed in pH and dry matter digestibility. Conclusion When in vitro techniques are used to evaluate feed, the use of the ruminal fluid from fasted animals should be used with caution.
Transient Phase Locking of the Spin-Transfer Nanooscillator

In this work, the spectral analysis of signals with the use of spin-transfer nano-oscillator in the external phase locking regime is investigated. This work is motivated by the spintronics, spin-transfer nanooscillators (STNO), neuromorphic computing. A mathematical model of the spectral analyzer based on the STNO is considered. Using methods of oscillation theory we analytically found its main performance characteristics, which are compared with similar, obtained numerically. The results found in this paper can be used in the experimental study of spectrum analyzers based on the STNO and various spintronic devices.
Molecular strain typing of the yaws pathogen, Treponema pallidum subspecies pertenue

Yaws is a neglected tropical disease caused by the bacterium Treponema pallidum subspecies pertenue. The disease primarily affects children under 15 years of age living in low socioeconomic conditions in tropical areas. As a result of a renewed focus on the disease owing to a recent eradication effort initiated by the World Health Organization, we have evaluated a typing method, adapted from and based on the enhanced Centers for Disease Control and Prevention typing method for T. pallidum subsp. pallidum, for possible use in epidemiological studies. Thirty DNA samples from yaws cases in Vanuatu and Ghana, 11 DNA samples extracted from laboratory strains, and 3 published genomic sequences were fully typed by PCR/RFLP analysis of the tpr E, G, and J genes and by determining the number of 60-bp repeats within the arp gene. Subtyping was performed by sequencing a homonucleotide “G” tandem repeat immediately upstream of the rpsA gene and an 84-bp region of tp0548. A total of 22 complete strain types were identified; two strain types in clinical samples from Vanuatu (5q11/ak and 5q12/ak), nine strain types in clinical samples from Ghana (3q12/ah, 4r12/ah, 4q10/j, 4q11/ah, 4q12/ah, 4q12/v, 4q13/ah, 6q10/aj, and 9q10/ai), and twelve strain types in laboratory strains and published genomes (2q11/ae, 3r12/ad, 4q11/ad, 4q12/ad, 4q12/ag, 4q12/v, 5r12/ad, 6r12/x, 6q11/af, 10q9/r, 10q12/r, and 12r12/w). The tpr RFLP patterns and arp repeat sizes were subsequently verified by sequencing analysis of the respective PCR amplicons. This study demonstrates that the typing method for subsp. pallidum can be applied to subsp. pertenue strains and should prove useful for molecular epidemiological studies on yaws.
An investigation the main internal brand crisis antecedents

To enrich literature of brand crisis causes regards internal perspective, this paper investigates internal brand shortage as crisis antecedents provoking brand fire consequently. Phenomenological approach is adopted using in-depth interviews, key-note seminar and validating by case studies analysis, internal brand crises antecedents were explored based on insights taken from experts in marketing and branding industry. Drafting from the phenomenological research, there are six problems leading to crisis found as follows: lack of human-centred strategy, lack of crisis prevention, lack of market understanding, lack of leadership and management skill, lack of innovation, and lack of quality assurance. These internal antecedents which accumulate to both performance-related and value-related brand crisis. This paper can have explicit implications for marketer, branders and managers, understanding these drivers and its occurrence, business managers are able to scan and analyses crisis situation faster to form timely response to crisis.
Insights into the Human Virome Using CRISPR Spacers from Microbiomes

Due to recent advances in next-generation sequencing over the past decade, our understanding of the human microbiome and its relationship to health and disease has increased dramatically. Yet, our insights into the human virome, and its interplay with important microbes that impact human health, is relatively limited. Prokaryotic and eukaryotic viruses are present throughout the human body, comprising a large and diverse population which influences several niches and impacts our health at various body sites. The presence of prokaryotic viruses like phages, has been documented at many different body sites, with the human gut being the richest ecological niche. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and associated proteins constitute the adaptive immune system of bacteria, which prevents attack by invasive nucleic acid. CRISPR-Cas systems function by uptake and integration of foreign genetic element sequences into the CRISPR array, which constitutes a genomic archive of iterative vaccination events. Consequently, CRISPR spacers can be investigated to reconstruct interplay between viruses and bacteria, and metagenomic sequencing data can be exploited to provide insights into host-phage interactions within a niche. Here, we show how the CRISPR spacer content of commensal and pathogenic bacteria can be used to determine the evidence of their phage exposure. This framework opens new opportunities for investigating host-virus dynamics in metagenomic data, and highlights the need to dedicate more efforts for virome sampling and sequencing.
Mental health, psychotropic medication use, and menstrual cycle characteristics

Purpose To examine the influence of depressive symptoms, perceived stress, and psychotropic medication use on prospectively assessed menstrual cycle regularity and length. Participants and methods Data were obtained from Pregnancy Study Online, a prospective cohort study of pregnancy planners from North America. At baseline, women reported information on demographics, anthropometrics, lifestyle, and medical history, including their use of psychotropic medications. They also completed the Major Depression Inventory and the Perceived Stress Scale. Every 8 weeks for up to 12 months or until conception, women completed follow-up questionnaires to assess changes in psychotropic medication use, perceived stress, and menstrual cycle characteristics (ie, cycle regularity and length). Women who completed at least one follow-up questionnaire from 2013 to 2018 (n=3,346) were included in the primary analyses. A total of 5,439 women were included in secondary analyses utilizing baseline data only. Primary analyses estimated prevalence ratios (PR) and 95% CIs using log-binomial regression models. Results Women with severe depressive symptoms at baseline, regardless of psychotropic medication use, had an 80% greater prevalence of irregular cycles during follow-up than women with no or low depressive symptoms (PR =1.80, 95% CI =1.48–2.19). Perceived stress was also associated with the prevalence of irregular cycles during follow-up (PR =1.33, 95% CI =1.14–1.55). Psychotropic medication use was not appreciably associated with menstrual characteristics after controlling for history of diagnosed depression and/or anxiety. Depressive symptoms, perceived stress, and psychotropic medication use showed little association with menstrual cycle length. Conclusion Higher levels of depressive symptoms and perceived stress were associated with irregular menstrual cycles, but not appreciably associated with menstrual cycle length. Use of psychotropic medications was not meaningfully associated with cycle regularity or length.
Ensemble of Convolutional Neural Networks for Automatic Grading of Diabetic Retinopathy and Macular Edema

In this manuscript, we automate the procedure of grading of diabetic retinopathy and macular edema from fundus images using an ensemble of convolutional neural networks. The availability of limited amount of labeled data to perform supervised learning was circumvented by using transfer learning approach. The models in the ensemble were pre-trained on a large dataset comprising natural images and were later fine-tuned with the limited data for the task of choice. For an image, the ensemble of classifiers generate multiple predictions, and a max-voting based approach was utilized to attain the final grade of the anomaly in the image. For the task of grading DR, on the test data (n=56), the ensemble achieved an accuracy of 83.9\%, while for the task for grading macular edema the network achieved an accuracy of 95.45% (n=44).
Immunomodulation by Processed Animal Feed: The Role of Maillard Reaction Products and Advanced Glycation End-Products (AGEs)

The immune system provides host protection to infection with pathogenic organisms, while at the same time providing tolerance upon exposure to harmless antigens. Thus, an impaired immune function is associated with increased susceptibility to infections with increased disease severity and thereby necessitating the therapeutic use of antibiotics. Livestock performance and feed efficiency, in addition to their health status, are dependent on the microbial load of their gut, the barrier function of the intestinal epithelium and the activity of the mucosal immune system, all of which can be modulated by dietary components. The majority of feeds that are consumed in pets and livestock have been processed. Processing promotes a non-enzymatic reaction between proteins and sugars called Maillard reaction (MR). Maillard reaction products (MRPs) and advanced Maillard reaction products (AGEs) determine taste, smell, and color of many food products therefore the MR is highly relevant for the feed industry. MRPs interact with different types of immune receptors, including the receptor for advanced glycation end products (RAGE) and immunomodulatory potential of feed proteins can be modified by Maillard reaction. This MR has become an important concern since MRPs/AGEs have been shown to contribute to increasing prevalence of diet-related chronic inflammatory states in the gut with negative health consequences and performance. The immunomodulatory effects of dietary MRPs and AGEs in livestock and pet animals are far less well-described, but widely considered to be similar to the relevant concepts and mechanisms obtained in the human field. This review will highlight immunological mechanisms underlying initiation of the innate and adaptive immune responses by MRPs/AGEs present in animal feeds, which are currently not completely understood. Bridging this knowledge gap, and taking advantage of progress in the human field, will significantly improve nutritional quality of feed and increase the prevention of diet-mediated inflammation in animals.
Hierarchical HotNet: identifying hierarchies of altered subnetworks

Motivation The analysis of high‐dimensional ‘omics data is often informed by the use of biological interaction networks. For example, protein‐protein interaction networks have been used to analyze gene expression data, to prioritize germline variants, and to identify somatic driver mutations in cancer. In these and other applications, the underlying computational problem is to identify altered subnetworks containing genes that are both highly altered in an ‘omics dataset and are topologically close (e.g. connected) on an interaction network. Results We introduce Hierarchical HotNet, an algorithm that finds a hierarchy of altered subnetworks. Hierarchical HotNet assesses the statistical significance of the resulting subnetworks over a range of biological scales and explicitly controls for ascertainment bias in the network. We evaluate the performance of Hierarchical HotNet and several other algorithms that identify altered subnetworks on the problem of predicting cancer genes and significantly mutated subnetworks. On somatic mutation data from The Cancer Genome Atlas, Hierarchical HotNet outperforms other methods and identifies significantly mutated subnetworks containing both well‐known cancer genes and candidate cancer genes that are rarely mutated in the cohort. Hierarchical HotNet is a robust algorithm for identifying altered subnetworks across different ‘omics datasets. Availability and implementation http://github.com/raphael‐group/hierarchical‐hotnet. Supplementary information Supplementary material are available at Bioinformatics online.
Reduced Cancer Survival Among Adults With HIV and AIDS-Defining Illnesses Despite No Difference in Cancer Stage at Diagnosis

Background: It is not known whether immune dysfunction is associated with increased risk of death after cancer diagnosis in persons with HIV (PWH). AIDS-defining illness (ADI) can signal significant immunosuppression. Our objective was to determine differences in cancer stage and mortality rates in PWH with and without history of ADI. Methods: PWH with anal, oropharynx, cervical, lung cancers, or Hodgkin lymphoma diagnoses from January 2000 to December 2009 in the North American AIDS Cohort Collaboration on Research and Design were included. Results: Among 81,865 PWH, 814 had diagnoses included in the study; 341 (39%) had a history of ADI at time of cancer diagnosis. For each cancer type, stage at diagnosis did not differ by ADI (P > 0.05). Mortality and survival estimates for cervical cancer were limited by n = 5 diagnoses. Adjusted mortality rate ratios showed a 30%–70% increase in mortality among those with ADI for all cancer diagnoses, although only lung cancer was statistically significant. Survival after lung cancer diagnosis was poorer in PWH with ADI vs. without (P = 0.0001); the probability of survival was also poorer in those with ADI at, or before other cancers although not statistically significant. Conclusions: PWH with a history of ADI at lung cancer diagnosis had higher mortality and poorer survival after diagnosis compared to those without. Although not statistically significant, the findings of increased mortality and decreased survival among those with ADI (vs. without) were consistent for all other cancers, suggesting the need for further investigations into the role of HIV-related immune suppression and cancer outcomes.
Bayesian Semi-supervised Learning with Graph Gaussian Processes

We propose a data-efficient Gaussian process-based Bayesian approach to the semi-supervised learning problem on graphs. The proposed model shows extremely competitive performance when compared to the state-of-the-art graph neural networks on semi-supervised learning benchmark experiments, and outperforms the neural networks in active learning experiments where labels are scarce. Furthermore, the model does not require a validation data set for early stopping to control over-fitting. Our model can be viewed as an instance of empirical distribution regression weighted locally by network connectivity. We further motivate the intuitive construction of the model with a Bayesian linear model interpretation where the node features are filtered by an operator related to the graph Laplacian. The method can be easily implemented by adapting off-the-shelf scalable variational inference algorithms for Gaussian processes.
Impact of Social Interaction on the Capacity of Hybrid Wireless Networks

In this paper, we jointly consider the optimal max-<inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>-hops routing policy and social features for the throughput capacity of a hybrid wireless network, which is different from the existing works that ignored the network traffic model. For the social feature, each node’s social group is determined by a probability related to the distance from the source node. To embody the features of social behavior, we propose a traffic model within a social group. Under the max-<inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>-hops routing policy in the hybrid wireless network, we analyze the effects of physical distance, clustering property, and a number of base station on throughput capacity. We also study the influence of different social group sizes on the throughput capacity. Our results demonstrate that: 1) the optimal <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> is not only related to social group size, but also the selection of destination nodes; 2) when the social contact factors <inline-formula> <tex-math notation="LaTeX">$\alpha$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\beta$ </tex-math></inline-formula> increase, the throughput capacity trends to be independent of the number of base station and routing parameter <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>. Particularly, our results show that the wireless network is scalable with the number of node, if the social contact factor is large enough; and 3) the results demonstrate that the base station and social interaction improve the throughput capacity of hybrid wireless networks.
Investigating the generalizability of EEG-based cognitive load estimation across visualizations

We examine if EEG-based cognitive load (CL) estimation is generalizable across the character, spatial pattern, bar graph and pie chart-based visualizations for the n-back task. CL is estimated via two recent approaches: (a) Deep convolutional neural network [2], and (b) Proximal support vector machines [15]. Experiments reveal that CL estimation suffers across visualizations calling for for effective machine learning techniques to benchmark visual interface usability for a given analytic task.
Arbitrarily Varying Remote Sources

We study a lossy source coding problem for an arbitrarily varying remote source (AVRS) which was proposed in a prior work. An AVRS transmits symbols, each generated in an independent and identically distributed manner, which are sought to be estimated at the decoder. These symbols are remotely generated, and the encoder and decoder observe noise corrupted versions received through a two-output noisy channel. This channel is an arbitrarily varying channel controlled by a jamming adversary. We assume that the adversary knows the coding scheme as well as the source data non-causally, and hence, can employ malicious jamming strategies correlated to them. Our interest lies in studying the rate distortion function for codes with a stochastic encoder, i.e, when the encoder can privately randomize while the decoder is deterministic. We provide upper and lower bounds on this rate distortion function.
How the Eyes Add Fractions: Adult Eye Movement Patterns During Fraction Addition Problems

Recent studies have tracked eye movements to assess the cognitive processes involved in fraction comparison. This study advances that work by assessing eye movements during the more complex task of fraction addition. Adults mentally solved fraction addition problems that were presented on a computer screen. The study included four types of problems. The two fractions in each problem had either like denominators (e.g., 3/7 + 2/7), or unlike denominators exhibiting one of the following relationships: one denominator was a multiple of the other denominator (e.g., 2/3 + 1/9), both denominators were prime numbers (e.g., 2/7 + 3/5), or both denominators had a common divisor larger than one (e.g., 5/6 + 3/8). Self-reports, accuracy, and response times confirmed that participants adapted their strategy use according to problem type. We analysed the number of eye fixations on each fraction component, as well as the number of saccades (rapid eye movements) between fixations on components. We found that participants predominantly processed the fraction components separately rather than processing the overall fraction magnitudes. Alternating between the two denominators appeared to be the dominant process, although in problems with common denominators alternating between numerators was dominant. Participants rarely used diagonal saccades in any of the problems, which would indicate cross-multiplication. Our findings suggest that adults adapt their cognitive processes of fraction addition according to problem type. We discuss the implications of our findings for numerical cognition and mathematics education, as well as the limitations of our current understanding of eye movement patterns.
Effects of trans-endocardial delivery of bone marrow-derived CD133+ cells on angina and quality of life in patients with refractory angina: A sub-analysis of the REGENT-VSEL trial.

BACKGROUND The REGENT-VSEL trial demonstrated a neutral effect of transendocardial injection of autologous bone marrow (BM)-derived CD133+ in regard to myocardial ischemia. The current sub-analysis of the REGENT VSEL trial aims to assess the effect stem cell therapy has on quality of life (QoL) in patients with refractory angina. METHODS Thirty-one patients (63.0 ± 6.4 years, 70% male) with recurrent CCS II-IV angina, despite optimal medical therapy, enrolled in the REGENT-VSEL single center, randomized, double-blinded, and placebo-controlled trial. Of the 31 patients, 16 individuals were randomly assigned to the active stem cell group and 15 individuals were randomly assigned to the placebo group on a 1:1 basis. The inducibility of ischemia, (≥ one myocardial segment) was confirmed for each patient using Tc-99m SPECT. QoL was measured using the Seattle Angina Questionnaire. Each patient completed the questionnaire prior to treatment and at the time of their outpatient follow-up visits at 1, 4, 6, and 12 months after cell/placebo treatment. RESULTS The main finding of the REGENT-VSEL trial sub-analysis was that transendocardial injection of autologous BM-derived CD133+ stem cells in patients with chronic refractory angina did not show significant improvement in QoL in comparison to the control group. Moreover, there was no significant difference between cell therapy and placebo in a number of patients showing improvement of at least 1 Canadian Cardiovascular Society class during the follow-up period. CONCLUSIONS Intra-myocardial delivery of autologous CD133+ stem cells is safe and feasible but does not show a significant improvement in the QoL or angina pectoris symptoms in patients with chronic myocardial ischemia.