Phylogenetic conservation of soil bacterial responses to simulated global changes.

Soil bacterial communities are altered by anthropogenic drivers such as climate change-related warming and fertilization. However, we lack a predictive understanding of how bacterial communities respond to such global changes. Here, we tested whether phylogenetic information might be more predictive of the response of bacterial taxa to some forms of global change than others. We analysed the composition of soil bacterial communities from perturbation experiments that simulated warming, drought, elevated CO2 concentration and phosphorus (P) addition. Bacterial responses were phylogenetically conserved to all perturbations. The phylogenetic depth of these responses varied minimally among the types of perturbations and was similar when merging data across locations, implying that the context of particular locations did not affect the phylogenetic pattern of response. We further identified taxonomic groups that responded consistently to each type of perturbation. These patterns revealed that, at the level of family and above, most groups responded consistently to only one or two types of perturbations, suggesting that traits with different patterns of phylogenetic conservation underlie the responses to different perturbations. We conclude that a phylogenetic approach may be useful in predicting how soil bacterial communities respond to a variety of global changes. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'

Ionization of oriented targets by intense circularly polarized laser pulses: Imprints of orbital angular nodes in the 2D momentum distribution

We solve the three-dimensional time-dependent Schr\"{o}dinger equation for a few-cycle circularly polarized femtosecond laser pulse interacting with an oriented target exemplified by an Argon atom, initially in a $3\text{p}_{x}$ or $3\text{p}_{y}$ state. The photoelectron momentum distributions show distinct signatures of the orbital structure of the initial state as well as the carrier-envelope phase of the applied pulse. Our \textit{ab initio} results are compared with results obtained using the length-gauge strong-field approximation, which allows for a clear interpretation of the results in terms of classical physics. Furthermore, we show that ionization by a circularly polarized pulse completely maps out the angular nodal structure of the initial state, thus providing a potential tool for studying orbital symmetry in individual systems or during chemical reactions

Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change

We acknowledge funding from the US DOE Genomic Science Program, BER, Office of Science project DE-SC0016410. We thank Bin Wang for discussion and inputs on trait-based modelling.Peer reviewedPublisher PD

Cellulolytic potential under environmental changes in microbial communities from grassland litter

In many ecosystems, global changes are likely to profoundly affect microorganisms. In Southern California, changes in precipitation and nitrogen deposition may influence the composition and functional potential of microbial communities and their resulting ability to degrade plant material. To test whether such environmental changes impact the distribution of functional groups involved in leaf litter degradation, we determined how the genomic diversity of microbial communities in a semi-arid grassland ecosystem changed under reduced precipitation or increased N deposition. We monitored communities seasonally over a period of 2 years to place environmental change responses into the context of natural variation. Fungal and bacterial communities displayed strong seasonal patterns, Fungi being mostly detected during the dry season whereas Bacteria were common during wet periods. Most putative cellulose degraders were associated with 33 bacterial genera and predicted to constitute 18% of the microbial community. Precipitation reduction reduced bacterial abundance and cellulolytic potential whereas nitrogen addition did not affect the cellulolytic potential of the microbial community. Finally, we detected a strong correlation between the frequencies of genera of putative cellulose degraders and cellulase genes. Thus, microbial taxonomic composition was predictive of cellulolytic potential. This work provides a framework for how environmental changes affect microorganisms responsible for plant litter deconstruction

The Pharmacopsychometric Triangle to Illustrate the Effectiveness of T-PEMF Concomitant with Antidepressants in Treatment Resistant Patients: A Double-Blind, Randomised, Sham-Controlled Trial Revisited with Focus on the Patient-Reported Outcomes

Background. Our T-PEMF trial has been revisited with focus on the pharmacopsychometric triangle in which effect size is used when comparing wanted versus unwanted clinical effects and quality of life as outcomes. In this analysis, we have especially focused on the self-reported HAM-D6. Methods. The antidepressive medication which the patients were resistant to was kept unchanged during the five weeks of active versus sham T-PEMF. Results. In total 21, patients received active T-PEMF, and 19 patients received sham T-PEMF. The effect size was 1.02 and 0.90, respectively, on HAM-D6 and HAM-D6-S. Concerning side effects, the active T-PEMF reduced the baseline score on concentration problems with an effect size of 0.44 while inducing more autonomic symptoms than sham T-PEMF with an effect size of −0.41. The advantage of active over sham T-PEMF obtained an effect size of 0.48. Conclusion. Active T-PEMF was found superior to sham T-PEMF within the pharmacopsychometric triangle with a clinically significant effect size level above 0.40

Ionization of 1D and 3D oriented asymmetric top molecules by intense circularly polarized femtosecond laser pulses

We present a combined experimental and theoretical study on strong-field ionization of a three-dimensionally oriented asymmetric top molecule, benzonitrile (C$_7$H$_5$N), by circularly polarized, nonresonant femtosecond laser pulses. Prior to the interaction with the strong field, the molecules are quantum-state selected using a deflector, and 3-dimensionally (3D) aligned and oriented adiabatically using an elliptically polarized laser pulse in combination with a static electric field. A characteristic splitting in the molecular frame photoelectron momentum distribution reveals the position of the nodal planes of the molecular orbitals from which ionization occurs. The experimental results are supported by a theoretical tunneling model that includes and quantifies the splitting in the momentum distribution. The focus of the present article is to understand strong-field ionization from 3D-oriented asymmetric top molecules, in particular the suppression of electron emission in nodal planes of molecular orbitals. In the preceding article [Dimitrovski et al., Phys. Rev. A 83, 023405 (2011)] the focus is to understand the strong-field ionization of one-dimensionally-oriented polar molecules, in particular asymmetries in the emission direction of the photoelectrons.Comment: 12 pages, 9 figure

Combination of MALDI-TOf mass spectrometry and machine learning for rapid antimicrobial resistance screening: the CASE of Campylobacter spp

While MALDI-TOF mass spectrometry (MS) is widely considered as the reference method for the rapid and inexpensive identification of microorganisms in routine laboratories, less attention has been addressed to its ability for detection of antimicrobial resistance (AMR). Recently, some studies assessed its potential application together with machine learning for the detection of AMR in clinical pathogens. The scope of this study was to investigate MALDI-TOF MS protein mass spectra combined with a prediction approach as an AMR screening tool for relevant foodborne pathogens, such as Campylobacter coli and Campylobacter jejuni. A One-Health panel of 224 C. jejuni and 116 C. coli strains was phenotypically tested for seven antimicrobial resistances, i.e., ciprofloxacin, erythromycin, tetracycline, gentamycin, kanamycin, streptomycin, and ampicillin, independently, and were submitted, after an on- and off-plate protein extraction, to MALDI Biotyper analysis, which yielded one average spectra per isolate and type of extraction. Overall, high performance was observed for classifiers detecting susceptible as well as ciprofloxacin- and tetracycline-resistant isolates. A maximum sensitivity and a precision of 92.3 and 81.2%, respectively, were reached. No significant prediction performance differences were observed between on- and off-plate types of protein extractions. Finally, three putative AMR biomarkers for fluoroquinolones, tetracyclines, and aminoglycosides were identified during the current study. Combination of MALDI-TOF MS and machine learning could be an efficient and inexpensive tool to swiftly screen certain AMR in foodborne pathogens, which may enable a rapid initiation of a precise, targeted antibiotic treatment