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Karin Holmfeldt et al. sequence metagenomes and metatranscriptomes of viruses in deep groundwaters down to 448 m below the surface. The results reveal ecological dynamics of viruses including slow motion ‘boom and burst’ cycles and a ‘kill the winner’ model potentially driven by viral predation.

Objective: Unusual clinical course Background: Anal squamous cell carcinoma (SCC) is a rare cancer commonly treated with the Nigro protocol, which combines chemotherapy and radiation. Patients who received radiation therapy prior to modern advances, such as computer-based tumor targeting, volumetric planning, and intensity-modulated radiation therapy, experience more acute and chronic adverse effects. Though exceedingly rare, radiation necrosis is of particular concern, as it can result in significant morbidity and mortality, including complex pelvic fistula formation and predisposition to potentially life-threatening necrotizing soft-tissue infections. Case Report: Here, we present a case of a 66-year-old woman with a prior history of anal SCC stage T3N×M0 who was treated with the Nigro protocol. Her treatment course was complicated by radiation proctitis, necessitating fecal diversion and ureteral strictures, requiring frequent stent exchanges. She presented 18 years after her cancer treatment, with widespread necrosis of her pelvic organs and surrounding soft tissue, resulting in formation of a large pelvic "cloaca", with a superimposed necrotizing soft-tissue infection. She was successfully treated by expedited resuscitation, septic source control, using multiple extensive debridements, and complete urinary diversion, utilizing a multidisciplinary team. Conclusions: This case highlights the importance of monitoring patients for signs of radiation toxicity, particularly in patients who received radiation prior to the latest technological advancements, as they are at increased risk of developing severe, late adverse effects decades after treatment. When these complications are recognized, early and aggressive intervention is required to spare the patient significant morbidity and mortality. [ABSTRACT FROM AUTHOR]

The more insects there are, the more food there is for insectivores and the higher the likelihood for insect-associated ecosystem services. Yet, we lack insights into the drivers of insect biomass over space and seasons, for both tropical and temperate zones. We used 245 Malaise traps, managed by 191 volunteers and park guards, to characterize year-round flying insect biomass in a temperate (Sweden) and a tropical (Madagascar) country. Surprisingly, we found that local insect biomass was similar across zones. In Sweden, local insect biomass increased with accumulated heat and varied across habitats, while biomass in Madagascar was unrelated to the environmental predictors measured. Drivers behind seasonality partly converged: In both countries, the seasonality of insect biomass differed between warmer and colder sites, and wetter and drier sites. In Sweden, short-term deviations from expected season-specific biomass were explained by week-to-week fluctuations in accumulated heat, rainfall and soil moisture, whereas in Madagascar, weeks with higher soil moisture had higher insect biomass. Overall, our study identifies key drivers of the seasonal distribution of flying insect biomass in a temperate and a tropical climate. This knowledge is key to understanding the spatial and seasonal availability of insects—as well as predicting future scenarios of insect biomass change. [ABSTRACT FROM AUTHOR]

Abstract Background Knee osteoarthritis (OA) is a highly prevalent musculoskeletal condition causing pain, physical disability, and reduced quality of life. Exercise and patient education are non-pharmacological interventions for knee OA unanimously recommended as first-line treatments based on extensive research evidence. However, none of the numerous randomised controlled trials of exercise and education for knee OA has used adequate sham/placebo comparison groups because the ‘active’ ingredients are unknown. Designing and executing an adequate and ‘blindable placebo’ version of an exercise and education intervention is impossible. Therefore, using an open-label study design, this trial compares the efficacy of a widely used ‘state-of-art’ exercise and education intervention (Good Life with osteoarthritis in Denmark; GLAD) with presumably inert intra-articular saline injections on improvement in knee pain in patients with knee OA. Methods In this open-label randomised trial, we will include 200 patients with radiographically verified OA of the knee and randomly allocate them to one of two interventions: (i) 8 weeks of exercise and education (GLAD) or (ii) Intra-articular injections of 5 ml isotonic saline every second week for a total of 4 injections. Outcomes are taken at baseline, after 8 weeks of treatment (week 9; primary endpoint) and after an additional 4 weeks of follow-up (week 12). The primary outcome is change from baseline in the Knee Injury and Osteoarthritis Outcome Score questionnaire (KOOS) pain subscale score. Secondary outcomes include the Physical function in Activities of Daily Living, Symptoms, and Knee-related Quality of Life subscales of the KOOS, the patients’ global assessment of disease impact, physical performance tests, and presence of knee joint swelling. Discussion This current trial compares a presumably active treatment (GLAD) with a presumably inert treatment (IA saline injections). Both study interventions have well-established and anticipated similar effects on knee OA symptoms, but the underlying mechanisms are unknown. The interpretation of the results of this trial will likely be difficult and controversial but will contribute to a better understanding of the bias introduced in the effect estimation of classically unblindable exercise and education interventions for knee OA. Trial registration www.ClinicalTrials.gov NCT03843931 . Prospectively registered on 18 February 2019.

ObjectivesPeriodontitis and rheumatoid arthritis (RA) are two widespread chronic inflammatory diseases with a previously suggested association. The objective of the current study was to compare the oral microbial composition and host´s inflammatory mediator profile of saliva samples obtained from subjects with periodontitis, with and without RA, as well as to predict biomarkers, of bacterial pathogens and/or inflammatory mediators, for classification of samples associated with periodontitis and RA.MethodsSalivary samples were obtained from 53 patients with periodontitis and RA and 48 non-RA with chronic periodontitis. The microbial composition was identified using 16S rRNA gene sequencing and compared across periodontitis patients with and without RA. Levels of inflammatory mediators were determined using a multiplex bead assay, compared between the groups and correlated to the microbial profile. The achieved data was analysed using PCoA, DESeq2 and two machine learning algorithms, OPLS-DA and sPLS-DA.ResultsDifferential abundance DESeq2 analyses showed that the four most highly enriched (log2 FC >20) amplicon sequence variants (ASVs) in the non-RA periodontitis group included Alloprevotella sp., Prevotella sp., Haemophilus sp., and Actinomyces sp. whereas Granulicatella sp., Veillonella sp., Megasphaera sp., and Fusobacterium nucleatum were the most highly enriched ASVs (log2 FC >20) in the RA group. OPLS-DA with log2 FC analyses demonstrated that the top ASVs with the highest importance included Vampirovibrio sp. having a positive correlation with non-RA group, and seven ASVs belonging to Sphingomonas insulae, Sphingobium sp., Novosphingobium aromaticivorans, Delftia acidovorans, Aquabacterium spp. and Sphingomonas echinoides with a positive correlation with RA group. Among the detected inflammatory mediators in saliva samples, TWEAK/TNFSF12, IL-35, IFN-α2, pentraxin-3, gp130/sIL6Rb, sIL-6Ra, IL-19 and sTNF-R1 were found to be significantly increased in patients with periodontitis and RA compared to non-RA group with periodontitis. Moreover, correlations between ASVs and inflammatory mediators using sPLS-DA analysis revealed that TWEAK/TNFSF12, pentraxin-3 and IL-19 were positively correlated with the ASVs Sphingobium sp., Acidovorax delafieldii, Novosphingobium sp., and Aquabacterium sp.ConclusionOur results suggest that the combination of microbes and host inflammatory mediators could be more efficient to be used as a predictable biomarker associated with periodontitis and RA, as compared to microbes and inflammatory mediators alone.

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra.

Group A Streptococcus (GAS; Streptococcus pyogenes) is a nearly ubiquitous human pathogen responsible for a significant global disease burden. No vaccine exists, so antibiotics are essential for effective treatment. Despite a lower incidence of antimicrobial resistance than many pathogens, GAS is still a top 10 cause of death due to infections worldwide. The morbidity and mortality are primarily a consequence of the immune sequelae and invasive infections that are difficult to treat with antibiotics. GAS has remained susceptible to penicillin and other β-lactams, despite their widespread use for 80 years. However, the failure of treatment for invasive infections with penicillin has been consistently reported since the introduction of antibiotics, and strains with reduced susceptibility to β-lactams have emerged. Furthermore, isolates responsible for outbreaks of severe infections are increasingly resistant to other antibiotics of choice, such as clindamycin and macrolides. This review focuses on the challenges in the treatment of GAS infection, the mechanisms that contribute to antibiotic failure, and adjunctive therapeutics. Further understanding of these processes will be necessary for improving the treatment of high-risk GAS infections and surveillance for non-susceptible or resistant isolates. These insights will also help guide treatments against other leading pathogens for which conventional antibiotic strategies are increasingly failing.

Sex hormones are known to interact with the immune system on multiple levels but information on the types of sex hormone receptors (SHR) and their expression levels in immune cells is scarce. Estrogen, testosterone and progesterone are all considered to interact with the immune system through their respective cell receptors (ERα and ERβ including the splice variant ERβ2, AR and PGR). In this study expression levels of SHR genes in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4+ and CD8+ T-cells, CD56+ NK-cells, CD14+ monocytes and CD19+ B-cells) were analyzed using standard manual qPCR or a qPCR array (TLDA). Nine healthy individuals including men (n = 2), premenopausal (Pre-MP, n = 5) and postmenopausal (post-MP, n = 2) women were sampled for PBMCs which were separated to cell subsets using FACS. Ten Pre-MP women were longitudinally sampled for total PBMCs at different phases of the menstrual cycle. We found that ERα was most abundant and, unexpectedly, that ERβ2 was the dominant ERβ variant in several FACS sorted cell subsets. In total PBMCs, SHR (ERα, ERβ1, ERβ2, and AR) expression did not fluctuate according to the phase of the menstrual cycle and PGR was not expressed. However, several immune response genes (GATA3, IFNG, IL1B, LTA, NFKB1, PDCD1, STAT3, STAT5A, TBX21, TGFB1, TNFA) were more expressed during the ovulatory and mid-luteal phases. Sex hormone levels did not correlate significantly with gene expression of SHR or immune response genes, but sex hormone-binding globulin (SHBG), a steroid hormone transporting protein, was positively correlated to expression of ERβ1 gene. This study provides new insights in the distribution of ERs in immune cells. Furthermore, expression patterns of several immune response genes differ significantly between phases of the menstrual cycle, supporting a role for sex hormones in the immune response.

Bacteria are ubiquitous and live in complex microbial communities. Due to differences in physiological properties and niche preferences among community members, microbial communities respond in specific ways to environmental drivers, potentially resulting in distinct microbial fingerprints for a given environmental state. As proof of the principle, our goal was to assess the opportunities and limitations of machine learning to detect microbial fingerprints indicating the presence of the munition compound 2,4,6-trinitrotoluene (TNT) in southwestern Baltic Sea sediments. Over 40 environmental variables including grain size distribution, elemental composition, and concentration of munition compounds (mostly at pmol⋅g–1 levels) from 150 sediments collected at the near-to-shore munition dumpsite Kolberger Heide by the German city of Kiel were combined with 16S rRNA gene amplicon sequencing libraries. Prediction was achieved using Random Forests (RFs); the robustness of predictions was validated using Artificial Neural Networks (ANN). To facilitate machine learning with microbiome data we developed the R package phyloseq2ML. Using the most classification-relevant 25 bacterial genera exclusively, potentially representing a TNT-indicative fingerprint, TNT was predicted correctly with up to 81.5% balanced accuracy. False positive classifications indicated that this approach also has the potential to identify samples where the original TNT contamination was no longer detectable. The fact that TNT presence was not among the main drivers of the microbial community composition demonstrates the sensitivity of the approach. Moreover, environmental variables resulted in poorer prediction rates than using microbial fingerprints. Our results suggest that microbial communities can predict even minor influencing factors in complex environments, demonstrating the potential of this approach for the discovery of contamination events over an integrated period of time. Proven for a distinct environment future studies should assess the ability of this approach for environmental monitoring in general.

Group A Streptococcus is an obligate human pathogen that is a major cause of infectious morbidity and mortality. It has a natural tropism for the oropharynx and skin, where it causes infections with excessive inflammation due to its expression of proinflammatory toxins and other virulence factors. Inflammation directly contributes to the severity of invasive infections, toxic shock syndrome, and the induction of severe post-infection autoimmune disease caused by autoreactive antibodies. This review discusses what is known about how the virulence factors of Group A Streptococcus induce inflammation and how this inflammation can promote disease. Understanding of streptococcal pathogenesis and the role of hyper-immune activation during infection may provide new therapeutic targets to treat the often-fatal outcome of severe disease.

The Sloan Digital Sky Survey (SDSS) has been in operation since 2000 April. This paper presents the Tenth Public Data Release (DR10) from its current incarnation, SDSS-III. This data release includes the first spectroscopic data from the Apache Point Observatory Galaxy Evolution Experiment (APOGEE), along with spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS) taken through 2012 July. The APOGEE instrument is a near-infrared R 22,500 300 fiber spectrograph covering 1.514-1.696 μm. The APOGEE survey is studying the chemical abundances and radial velocities of roughly 100,000 red giant star candidates in the bulge, bar, disk, and halo of the Milky Way. DR10 includes 178,397 spectra of 57,454 stars, each typically observed three or more times, from APOGEE. Derived quantities from these spectra (radial velocities, effective temperatures, surface gravities, and metallicities) are also included. DR10 also roughly doubles the number of BOSS spectra over those included in the Ninth Data Release. DR10 includes a total of 1,507,954 BOSS spectra comprising 927,844 galaxy spectra, 182,009 quasar spectra, and 159,327 stellar spectra selected over 6373.2 deg2. © 2014. The American Astronomical Society. All rights reserved..

To inhibit bacterial transmission and infection, health care facilities use bactericidal metal coatings to prevent colonization of surfaces and implanted devices. In these environments, antibiotics are commonly used, but their effect on metal resistance is unclear.