Sparse tree-based clustering of microbiome data to characterize microbiome heterogeneity in pancreatic cancer

There is a keen interest in characterizing variation in the microbiome across cancer patients, given increasing evidence of its important role in determining treatment outcomes. Here our goal is to discover subgroups of patients with similar microbiome profiles. We propose a novel unsupervised clustering approach in the Bayesian framework that innovates over existing model-based clustering approaches, such as the Dirichlet multinomial mixture model, in three key respects: we incorporate feature selection, learn the appropriate number of clusters from the data, and integrate information on the tree structure relating the observed features. We compare the performance of our proposed method to existing methods on simulated data designed to mimic real microbiome data. We then illustrate results obtained for our motivating data set, a clinical study aimed at characterizing the tumor microbiome of pancreatic cancer patients

Recombinant expression and functional analysis of proteases from Streptococcus pneumoniae, Bacillus anthracis, and Yersinia pestis

<p>Abstract</p> <p>Background</p> <p>Uncharacterized proteases naturally expressed by bacterial pathogens represents important topic in infectious disease research, because these enzymes may have critical roles in pathogenicity and cell physiology. It has been observed that cloning, expression and purification of proteases often fail due to their catalytic functions which, in turn, cause toxicity in the <it>E. coli </it>heterologous host.</p> <p>Results</p> <p>In order to address this problem systematically, a modified pipeline of our high-throughput protein expression and purification platform was developed. This included the use of a specific <it>E. coli </it>strain, BL21(DE3) pLysS to tightly control the expression of recombinant proteins and various expression vectors encoding fusion proteins to enhance recombinant protein solubility. Proteases fused to large fusion protein domains, maltosebinding protein (MBP), SP-MBP which contains signal peptide at the N-terminus of MBP, disulfide oxidoreductase (DsbA) and Glutathione S-transferase (GST) improved expression and solubility of proteases. Overall, 86.1% of selected protease genes including hypothetical proteins were expressed and purified using a combination of five different expression vectors. To detect novel proteolytic activities, zymography and fluorescence-based assays were performed and the protease activities of more than 46% of purified proteases and 40% of hypothetical proteins that were predicted to be proteases were confirmed.</p> <p>Conclusions</p> <p>Multiple expression vectors, employing distinct fusion tags in a high throughput pipeline increased overall success rates in expression, solubility and purification of proteases. The combinatorial functional analysis of the purified proteases using fluorescence assays and zymography confirmed their function.</p

An Overview of the Rotational Behavior of Metal--Poor Stars

The present paper describes the behavior of the rotational velocity in metal--poor stars ([Fe/H]<-0.5 dex) in different evolutionary stages, based on Vsini values from the literature. Our sample is comprised of stars in the field and some Galactic globular clusters, including stars on the main sequence, the red giant branch (RGB), and the horizontal branch (HB). The metal--poor stars are, mainly, slow rotators, and their Vsini distribution along the HR diagram is quite homogeneous. Nevertheless, a few moderate to high values of Vsini are found in stars located on the main sequence and on the HB. We show that the overall distribution of Vsini values is basically independent of metallicity for the stars in our sample. In particular, the fast-rotating main sequence stars in our sample present similar rotation rates as their metal-rich counterparts, suggesting that some of them may actually be fairly young, in spite of their low metallicity, or else that at least some of them would be better classified as blue straggler stars. We do not find significant evidence of evolution in Vsini values as a function of position on the RGB; in particular, we do not confirm previous suggestions that stars close to the RGB tip rotate faster than their less evolved counterparts. While the presence of fast rotators among moderately cool blue HB stars has been suggested to be due to angular momentum transport from a stellar core that has retained significant angular momentum during its prior evolution, we find that any such transport mechanisms must likely operate very fast as the star arrives on the zero-age HB (ZAHB), since we do not find a link between evolution off the ZAHB and Vsini values. We present an extensive tabulation of all quantities discussed in this paper, including rotation velocities, temperatures, gravitieComment: 22 pages, 10 figure

A catalog of rotational and radial velocities for evolved stars. IV. Metal-poor stars

The present paper describes the first results of an observational program intended to refine and extend the existing vsini measurements of metal-poor stars, with anemphasis on field evolved stars. The survey was carried out with the FEROS and CORALIE spectrometers. For the vsini measurements, obtained from spectral synthesis, we estimate an uncertainty of about 2.0 km/s. Precise rotational velocities vsini are presented for a large sample of 100 metal-poor stars, most of them evolving off the main-sequence. For the large majority of the stars composing the present sample, rotational velocities have been measured for the first time.Comment: 5 pages, 1 Postscript figures, accepted for publication in the A&

A review of metabolomic profiling in rheumatoid arthritis : bringing new insights in disease pathogenesis, treatment and comorbidities

Metabolomic analysis provides a wealth of information that can be predictive of distinctive phenotypes of pathogenic processes and has been applied to better understand disease development. Rheumatoid arthritis (RA) is an autoimmune disease with the establishment of chronic synovial inflammation that affects joints and peripheral tissues such as skeletal muscle and bone. There is a lack of useful disease biomarkers to track disease activity, drug response and follow-up in RA. In this review, we describe potential metabolic biomarkers that might be helpful in the study of RA pathogenesis, drug response and risk of comorbidities. TMAO (choline and trimethylamine oxide) and TCA (tricarboxylic acid) cycle products have been suggested to modulate metabolic profiles during the early stages of RA and are present systemically, which is a relevant characteristic for biomarkers. Moreover, the analysis of lipids such as cholesterol, FFAs and PUFAs may provide important information before disease onset to predict disease activity and treatment response. Regarding therapeutics, TNF inhibitors may increase the levels of tryptophan, valine, lysine, creatinine and alanine, whereas JAK/STAT inhibitors may modulate exclusively fatty acids. These observations indicate that different disease modifying antirheumatic drugs have specific metabolic profiles and can reveal differences between responders and non-responders. In terms of comorbidities, physical impairment represented by higher fatigue scores and muscle wasting has been associated with an increase in urea cycle, FFAs, tocopherols and BCAAs. In conclusion, synovial fluid, blood and urine samples from RA patients seem to provide critical information about the metabolic profile related to drug response, disease activity and comorbidities

The effects of resistance training with blood flow restriction on muscle strength, muscle hypertrophy and functionality in patients with osteoarthritis and rheumatoid arthritis : a systematic review with meta-analysis

Introduction Rheumatoid arthritis(RA) and osteoarthritis(OA) patients showed systemic manifestations that may lead to a reduction in muscle strength, muscle mass and, consequently, to a reduction in functionality. On the other hand, moderate intensity resistance training(MIRT) and high intensity resistance training(HIRT) are able to improve muscle strength and muscle mass in RA and OA without affecting the disease course. However, due to the articular manifestations caused by these diseases, these patients may present intolerance to MIRT or HIRT. Thus, the low intensity resistance training combined with blood flow restriction (LIRTBFR) may be a new training strategy for these populations. Objective To perform a systematic review with meta-analysis to verify the effects of LIRTBFR on muscle strength, muscle mass and functionality in RA and OA patients. Materials and methods A systematic review with meta-analysis of randomized clinical trials(RCTs), published in English, between 1957–2021, was conducted using MEDLINE(PubMed), Embase and Cochrane Library. The methodological quality was assessed using Physiotherapy Evidence Database scale. The risk of bias was assessed using RoB2.0. Mean difference(MD) or standardized mean difference(SMD) and 95% confidence intervals(CI) were pooled using a random- effects model. A P<0.05 was considered statistically significant. Results Five RCTs were included. We found no significant differences in the effects between LIRTBFR, MIRT and HIRT on muscle strength, which was assessed by tests of quadriceps strength(SMD = -0.01[-0.57, 0.54], P = 0.96; I2 = 58%) and functionality measured by tests with patterns similar to walking(SMD = -0.04[-0.39, 0.31], P = 0.82; I2 = 0%). Compared to HIRT, muscle mass gain after LIRTBFR was reported to be similar. When comparing LIRTBFR with low intensity resistance training without blood flow restriction(LIRT), the effect LIRTBFR was reported to be higher on muscle strength, which was evaluated by the knee extension test. Conclusion LIRTBFR appears to be a promising strategy for gains in muscle strength, muscle mass and functionality in a predominant sample of RA and OA women