mockrobiota: a Public Resource for Microbiome Bioinformatics Benchmarking.

Mock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at http://caporaso-lab.github.io/mockrobiota/. The materials contained in mockrobiota include data set and sample metadata, expected composition data (taxonomy or gene annotations or reference sequences for mock community members), and links to raw data (e.g., raw sequence data) for each mock community data set. mockrobiota does not supply physical sample materials directly, but the data set metadata included for each mock community indicate whether physical sample materials are available. At the time of this writing, mockrobiota contains 11 mock community data sets with known species compositions, including bacterial, archaeal, and eukaryotic mock communities, analyzed by high-throughput marker gene sequencing. IMPORTANCE The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community

A perfusion-capable microfluidic bioreactor for assessing microbial heterologous protein production

We present an integrated microfluidic bioreactor for fully continuous perfusion cultivation of suspended microbial cell cultures. This system allowed continuous and stable heterologous protein expression by sustaining the cultivation of Pichia pastoris over 11 days. This technical capability also allowed testing the impact of perfusion conditions on protein expression. This advance should enable small-scale models for process optimization in continuous biomanufacturing.United States. Defense Advanced Research Projects Agency (N66001-13-C-4025)National Cancer Institute (U.S.) (P30-CA14051)United States. National Institutes of Health (2T32GM008334-26

Exosomal αvβ6 integrin is required for monocyte M2 polarization in prostate cancer

Therapeutic approaches aimed at curing prostate cancer are only partially successful given the occurrence of highly metastatic resistant phenotypes that frequently develop in response to therapies. Recently, we have described αvβ6, a surface receptor of the integrin family as a novel therapeutic target for prostate cancer; this epithelial-specific molecule is an ideal target since, unlike other integrins, it is found in different types of cancer but not in normal tissues. We describe a novel αvβ6-mediated signaling pathway that has profound effects on the microenvironment. We show that αvβ6 is transferred from cancer cells to monocytes, including β6-null monocytes, by exosomes and that monocytes from prostate cancer patients, but not from healthy volunteers, express αvβ6. Cancer cell exosomes, purified via density gradients, promote M2 polarization, whereas αvβ6 down-regulation in exosomes inhibits M2 polarization in recipient monocytes. Also, as evaluated by our proteomic analysis, αvβ6 down-regulation causes a significant increase in donor cancer cells, and their exosomes, of two molecules that have a tumor suppressive role, STAT1 and MX1/2. Finally, using the Ptenpc−/− prostate cancer mouse model, which carries a prostate epithelial-specific Pten deletion, we demonstrate that αvβ6 inhibition in vivo causes up-regulation of STAT1 in cancer cells. Our results provide evidence of a novel mechanism that regulates M2 polarization and prostate cancer progression through transfer of αvβ6 from cancer cells to monocytes through exosomes

Molecular Gas in the z=1.2 Ultraluminous Merger GOODS J123634.53+621241.3

We report the detection of CO(2-1) emission from the z=1.2 ultraluminous infrared galaxy (ULIRG) GOODS J123634.53+621241.3 (also known as the sub-millimeter galaxy GN26). These observations represent the first discovery of high-redshift CO emission using the new Combined Array for Research in Millimeter-Wave Astronomy (CARMA). Of all high-redshift (z>1) galaxies within the GOODS-North field, this source has the largest far-infrared (FIR) flux observed in the Spitzer 70um and 160um bands. The CO redshift confirms the optical identification of the source, and the bright CO(2-1) line suggests the presence of a large molecular gas reservoir of about 7x10^10 M(sun). The infrared-to-CO luminosity ratio of L(IR)/L'(CO) = 80+/-30 L(sun) (K Km/s pc^2)^-1 is slightly smaller than the average ratio found in local ULIRGs and high-redshift sub-millimeter galaxies. The short star-formation time scale of about 70 Myr is consistent with a starburst associated with the merger event and is much shorter than the time scales for spiral galaxies and estimates made for high-redshift galaxies selected on the basis of their B-z and z-K colors.Comment: Accepted for publication in ApJ Letter

Eight principles of integrated pest management

The use of pesticides made it possible to increase yields, simplify cropping systems, and forego more complicated crop protection strategies. Over-reliance on chemical control, however, is associated with contamination of ecosystems and undesirable health effects. The future of crop production is now also threatened by emergence of pest resistance and declining availability of active substances. There is therefore a need to design cropping systems less dependent on synthetic pesticides. Consequently, the European Union requires the application of eight principles (P) of Integrated Pest Management that fit within sustainable farm management. Here, we propose to farmers, advisors, and researchers a dynamic and flexible approach that accounts for the diversity of farming situations and the complexities of agroecosystems and that can improve the resilience of cropping systems and our capacity to adapt crop protection to local realities. For each principle (P), we suggest that (P1) the design of inherently robust cropping systems using a combination of agronomic levers is key to prevention. (P2) Local availability of monitoring, warning, and forecasting systems is a reality to contend with. (P3) The decision-making process can integrate cropping system factors to develop longer-term strategies. (P4) The combination of non-chemical methods that may be individually less efficient than pesticides can generate valuable synergies. (P5) Development of new biological agents and products and the use of existing databases offer options for the selection of products minimizing impact on health, the environment, and biological regulation of pests. (P6) Reduced pesticide use can be effectively combined with other tactics. (P7) Addressing the root causes of pesticide resistance is the best way to find sustainable crop protection solutions. And (P8) integration of multi-season effects and trade-offs in evaluation criteria will help develop sustainable solutions. (Résumé d'auteur

The learning curve associated with the introduction of the subcutaneous implantable defibrillator

Aims: The subcutaneous implantable cardioverter defibrillator (S-ICD) was introduced to overcome complications related to transvenous leads. Adoption of the S-ICD requires implanters to learn a new implantation technique. The aim of this study was to assess the learning curve for S-ICD implanters with respect to implant-related complications, procedure time, and inappropriate shocks (IASs). Methods and results: In a pooled cohort from two clinical S-ICD databases, the IDE Trial and the EFFORTLESS Registry, complications, IASs at 180 days follow-up and implant procedure duration were assessed. Patients were grouped in quartiles based on experience of the implanter and Kaplan-Meier estimates of complication and IAS rates were calculated. A total of 882 patients implanted in 61 centres by 107 implanters with a median of 4 implants (IQR 1,8) were analysed. There were a total of 59 patients with complications and 48 patients with IAS. The complication rate decreased significantly from 9.8% in Quartile 1 (least experience) to 5.4% in Quartile 4 (most experience) (P = 0.02) and non-significantly for IAS from 7.9 to 4.8% (P = 0.10). Multivariable analysis demonstrated a hazard ratio of 0.78 (P = 0.045) for complications and 1.01 (P = 0.958) for IAS. Dual-zone programming increased with experience of the individual implanter (P 13 implants). Conclusion: There is a short and significant learning curve associated with physicians adopting the S-ICD. Performance stab

Effect of Tumor-Treating Fields Plus Maintenance Temozolomide vs Maintenance Temozolomide Alone on Survival in Patients With Glioblastoma: A Randomized Clinical Trial.

Tumor-treating fields (TTFields) is an antimitotic treatment modality that interferes with glioblastoma cell division and organelle assembly by delivering low-intensity alternating electric fields to the tumor. To investigate whether TTFields improves progression-free and overall survival of patients with glioblastoma, a fatal disease that commonly recurs at the initial tumor site or in the central nervous system. In this randomized, open-label trial, 695 patients with glioblastoma whose tumor was resected or biopsied and had completed concomitant radiochemotherapy (median time from diagnosis to randomization, 3.8 months) were enrolled at 83 centers (July 2009-2014) and followed up through December 2016. A preliminary report from this trial was published in 2015; this report describes the final analysis. Patients were randomized 2:1 to TTFields plus maintenance temozolomide chemotherapy (n = 466) or temozolomide alone (n = 229). The TTFields, consisting of low-intensity, 200 kHz frequency, alternating electric fields, was delivered (≥ 18 hours/d) via 4 transducer arrays on the shaved scalp and connected to a portable device. Temozolomide was administered to both groups (150-200 mg/m2) for 5 days per 28-day cycle (6-12 cycles). Progression-free survival (tested at α = .046). The secondary end point was overall survival (tested hierarchically at α = .048). Analyses were performed for the intent-to-treat population. Adverse events were compared by group. Of the 695 randomized patients (median age, 56 years; IQR, 48-63; 473 men [68%]), 637 (92%) completed the trial. Median progression-free survival from randomization was 6.7 months in the TTFields-temozolomide group and 4.0 months in the temozolomide-alone group (HR, 0.63; 95% CI, 0.52-0.76; P < .001). Median overall survival was 20.9 months in the TTFields-temozolomide group vs 16.0 months in the temozolomide-alone group (HR, 0.63; 95% CI, 0.53-0.76; P < .001). Systemic adverse event frequency was 48% in the TTFields-temozolomide group and 44% in the temozolomide-alone group. Mild to moderate skin toxicity underneath the transducer arrays occurred in 52% of patients who received TTFields-temozolomide vs no patients who received temozolomide alone. In the final analysis of this randomized clinical trial of patients with glioblastoma who had received standard radiochemotherapy, the addition of TTFields to maintenance temozolomide chemotherapy vs maintenance temozolomide alone, resulted in statistically significant improvement in progression-free survival and overall survival. These results are consistent with the previous interim analysis. clinicaltrials.gov Identifier: NCT00916409

Stir to Pour: Efficient Calibration of Liquid Properties for Pouring Actions

Humans use simple probing actions to develop intuition about the physical behaviour of common objects. Such intuition is particularly useful for adaptive estimation of favourable manipulation strategies of those objects in novel contexts. For example, observing the effect of tilt on a transparent bottle containing an unknown liquid provides clues on how the liquid might be poured. It is desirable to equip general-purpose robotic systems with this capability because it is inevitable that they will encounter novel objects and scenarios. In this paper, we teach a robot to use a simple, specified probing strategy – stirring with a stick – to reduce spillage while pouring unknown liquids. In the probing step, we continuously observe the effects of a real robot stirring a liquid, while simultaneously tuning the parameters to a model (simulator) until the two outputs are in agreement. We obtain optimal simulation parameters, characterising the unknown liquid, via a Bayesian Optimiser that minimises the discrepancy between real and simulated outcomes. Then, we optimise the pouring policy conditioning on the optimal simulation parameters determined via stirring. We show that using stirring as a probing strategy results in reduced spillage for three qualitatively different liquids when executed on a UR10 Robot, compared to probing via pouring. Finally, we provide quantitative insights into the reason for stirring being a suitable calibration task for pouring – a step towards automatic discovery of probing strategies