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In order to detect shifts in community structure and function associated with global change, the natural background fluctuation in these traits must be known. In a 6 yr study we characterized the composition of young benthic communities at 7 sites along the 300 km coast of the Kiel and Lübeck bights in the German Baltic Sea and we quantified their interannual variability of taxonomic and functional composition. Along the salinity gradient from NW to SE, the relative abundance of primary producers decreased while that of heterotrophs increased. Along the same gradient, annual productivity tended to increase. Taxonomic and functional richness were higher in Kiel Bight as compared to Lübeck Bight. With increasing species richness functional group richness showed saturation indicating an increasing functional redundancy in species rich communities. While taxonomic fluctuations between years were substantial, functionality of the communities seem preserved in most cases. Environmental conditions potentially driving these fluctuations are winter temperatures and current regimes. We tentatively define a confidence range of natural variability in taxonomic and functional composition a departure from which might help identifying an ongoing regime shift driven by global change. In addition, we propose to use RELATE, a statistical procedure in the PRIMER (Plymouth Routines in Multivariate Ecological Research) package to distinguish directional shifts in time ("signal") from natural temporal fluctuations ("noise").

CO2 emissions are leading to an acidification of the oceans. Predicting marine community vulnerability towards acidification is difficult, as adaptation processes cannot be accounted for in most experimental studies. Naturally CO2 enriched sites thus can serve as valuable proxies for future changes in community structure. Here we describe a natural analogue site in the Western Baltic Sea. Seawater pCO2 in Kiel Fjord is elevated for large parts of the year due to upwelling of CO2 rich waters. Peak pCO2 values of >230 Pa (>2300 μatm) and pHNBS values of pCO2 values are ~70 Pa (~700 μatm). In contrast to previously described naturally CO2 enriched sites that have suggested a progressive displacement of calcifying auto- and heterotrophic species, the macrobenthic community in Kiel Fjord is dominated by calcifying invertebrates. We show that blue mussels from Kiel Fjord can maintain control rates of somatic and shell growth at a pCO2 of 142 Pa (1400 μatm, pHNBS = 7.7). Juvenile mussel recruitment peaks during the summer months, when high water pCO2 values of ~100 Pa (~1000 μatm) prevail. Our findings indicate that calcifying keystone species may be able to cope with surface ocean pHNBS values projected for the end of this century when food supply is sufficient. However, owing to non-linear synergistic effects of future acidification and upwelling of corrosive water, peak seawater pCO2 in Kiel Fjord and many other productive estuarine habitats could increase to values >400 Pa (>4000 μatm). These changes will most likely affect calcification and recruitment, and increase external shell dissolution.

α-Aminoacetophenones are identified as promising building blocks for the synthesis of highly substituted dioxolanes. The presented strategy is founded on the build and release of molecular strain and achieves a formal transposition of a methyl group. During light irradiation, 3-phenylazetidinols are forged as reaction intermediates, which readily undergo ring opening upon the addition of electron-deficient ketones or boronic acids. Key to the successful development of this two-step process is the identification of a benzhydryl-protecting group, which orchestrates the photochemical Norrish–Yang cyclization and facilitates the subsequent ring opening.

Abstract Background Seeking and obtaining effective health care for Long COVID remains a challenge in the USA. Women have particularly been impacted, as they are both at higher risk of developing Long COVID and of facing gendered barriers to having symptoms acknowledged. Long COVID clinics, which provide multidisciplinary and coordinated care, have emerged as a potential solution. To date, however, there has been little examination of U.S. patient experiences with Long COVID clinics and how patients may or may not have come to access care at a Long COVID clinic. Methods We conducted semi-structured interviews with 30 U.S. women aged 18 or older who had experienced Long COVID symptoms for at least 3 months, who had not been hospitalized for acute COVID-19, and who had seen at least one medical provider about their symptoms. Participants were asked about experiences seeking medical care for Long COVID. Long COVID clinic-related responses were analyzed using qualitative framework analysis to identify key themes in experiences with Long COVID clinics. Results Of the 30 women, 43.3% (n = 13) had been seen at a Long COVID clinic or by a provider affiliated with a Long COVID clinic and 30.0% (n = 9) had explored or attempted to see a Long COVID clinic but had not been seen at time of interview. Participants expressed five key themes concerning their experiences with seeking care from Long COVID clinics: (1) Access to clinics remains an issue, (2) Clinics are not a one stop shop, (3) Not all clinic providers have sufficient Long COVID knowledge, (4) Clinics can offer validation and care, and (5) Treatment options are critical and urgent. Conclusions While the potential for Long COVID clinics is significant, findings indicate that ongoing barriers to care and challenges related to quality and coordination of care hamper that potential and contribute to distress among women seeking Long COVID care. Since Long COVID clinics are uniquely positioned and framed as being the place to go to manage complex symptoms, it is critical to patient wellbeing that they be properly resourced to provide a level of care that complies with emerging best practices.

Recently we found compelling evidence for a gravitational-wave background with Hellings and Downs (HD) correlations in our 15 yr data set. These correlations describe gravitational waves as predicted by general relativity, which has two transverse polarization modes. However, more general metric theories of gravity can have additional polarization modes, which produce different interpulsar correlations. In this work, we search the NANOGrav 15 yr data set for evidence of a gravitational-wave background with quadrupolar HD and scalar-transverse (ST) correlations. We find that HD correlations are the best fit to the data and no significant evidence in favor of ST correlations. While Bayes factors show strong evidence for a correlated signal, the data does not strongly prefer either correlation signature, with Bayes factors ∼2 when comparing HD to ST correlations, and ∼1 for HD plus ST correlations to HD correlations alone. However, when modeled alongside HD correlations, the amplitude and spectral index posteriors for ST correlations are uninformative, with the HD process accounting for the vast majority of the total signal. Using the optimal statistic, a frequentist technique that focuses on the pulsar-pair cross-correlations, we find median signal-to-noise ratios of 5.0 for HD and 4.6 for ST correlations when fit for separately, and median signal-to-noise ratios of 3.5 for HD and 3.0 for ST correlations when fit for simultaneously. While the signal-to-noise ratios for each of the correlations are comparable, the estimated amplitude and spectral index for HD are a significantly better fit to the total signal, in agreement with our Bayesian analysis.

A mutator is a variant in a population of organisms whose mutation rate is higher than the average mutation rate in the population. For genetic and population dynamics reasons, mutators are produced and survive with much greater frequency than anti-mutators (variants with a lower-than-average mutation rate). This strong asymmetry is a consequence of both fundamental genetics and natural selection; it can lead to a ratchet-like increase in the mutation rate. The rate at which mutators appear is, therefore, a parameter that should be of great interest to evolutionary biologists generally; for example, it can influence: (1) the survival duration of a species, especially asexual species (which are known to be short-lived), (2) the evolution of recombination, a process that can ameliorate the deleterious effects of mutator abundance, (3) the rate at which cancer appears, (4) the ability of pathogens to escape immune surveillance in their hosts, (5) the long-term fate of mitochondria, etc. In spite of its great relevance to basic and applied science, the rate of mutation to a mutator phenotype continues to be essentially unknown. The reasons for this gap in our knowledge are largely methodological; in general, a mutator phenotype cannot be observed directly, but must instead be inferred from the numbers of some neutral “marker” mutation that can be observed directly: different mutation-rate variants will produce this marker mutation at different rates. Here, we derive the expected distribution of the numbers of the marker mutants observed, accounting for the fact that some of the mutants will have been produced by a mutator phenotype that itself arose by mutation during the growth of the culture. These developments, together with previous enhancements of the Luria–Delbrück assay (by one of us, dubbed the “Jones protocol”), make possible a novel experimental protocol for estimating the rate of mutation to a mutator phenotype. Simulated experiments using biologically reasonable parameters that employ this protocol show that such experiments in the lab can give us fairly accurate estimates of the rate of mutation to a mutator phenotype. Although our ability to estimate mutation-to-mutator rates from simulated experiments is promising, we view this study as a proof-of-concept study and an important first step towards practical empirical estimation.

We present the results of a Bayesian search for gravitational wave (GW) memory in the NANOGrav 12.5 yr data set. We find no convincing evidence for any gravitational wave memory signals in this data set. We find a Bayes factor of 2.8 in favor of a model that includes a memory signal and common spatially uncorrelated red noise (CURN) compared to a model including only a CURN. However, further investigation shows that a disproportionate amount of support for the memory signal comes from three dubious pulsars. Using a more flexible red-noise model in these pulsars reduces the Bayes factor to 1.3. Having found no compelling evidence, we go on to place upper limits on the strain amplitude of GW memory events as a function of sky location and event epoch. These upper limits are computed using a signal model that assumes the existence of a common, spatially uncorrelated red noise in addition to a GW memory signal. The median strain upper limit as a function of sky position is approximately 3.3 × 10 ^−14 . We also find that there are some differences in the upper limits as a function of sky position centered around PSR J0613−0200. This suggests that this pulsar has some excess noise that can be confounded with GW memory. Finally, the upper limits as a function of burst epoch continue to improve at later epochs. This improvement is attributable to the continued growth of the pulsar timing array.

The Australian, Chinese, European, Indian, and North American pulsar timing array (PTA) collaborations recently reported, at varying levels, evidence for the presence of a nanohertz gravitational-wave background (GWB). Given that each PTA made different choices in modeling their data, we perform a comparison of the GWB and individual pulsar noise parameters across the results reported from the PTAs that constitute the International Pulsar Timing Array (IPTA). We show that despite making different modeling choices, there is no significant difference in the GWB parameters that are measured by the different PTAs, agreeing within 1 σ . The pulsar noise parameters are also consistent between different PTAs for the majority of the pulsars included in these analyses. We bridge the differences in modeling choices by adopting a standardized noise model for all pulsars and PTAs, finding that under this model there is a reduction in the tension in the pulsar noise parameters. As part of this reanalysis, we “extended” each PTA’s data set by adding extra pulsars that were not timed by that PTA. Under these extensions, we find better constraints on the GWB amplitude and a higher signal-to-noise ratio for the Hellings–Downs correlations. These extensions serve as a prelude to the benefits offered by a full combination of data across all pulsars in the IPTA, i.e., the IPTA’s Data Release 3, which will involve not just adding in additional pulsars but also including data from all three PTAs where any given pulsar is timed by more than a single PTA.

Pulsar timing arrays (PTAs) are designed to detect low-frequency gravitational waves (GWs). GWs induce achromatic signals in PTA data, meaning that the timing delays do not depend on radio frequency. However, pulse arrival times are also affected by radio-frequency-dependent “chromatic” noise from sources such as dispersion measure (DM) and scattering delay variations. Furthermore, the characterization of GW signals may be influenced by the choice of chromatic noise model for each pulsar. To better understand this effect, we assess if and how different chromatic noise models affect the achromatic noise properties in each pulsar. The models we compare include existing DM models used by the North American Nanohertz Observatory for Gravitational waves (NANOGrav) and noise models used for the European PTA Data Release 2 (EPTA DR2). We perform this comparison using a subsample of six pulsars from the NANOGrav 15 yr data set, selecting the same six pulsars as from the EPTA DR2 six-pulsar data set. We find that the choice of chromatic noise model noticeably affects the achromatic noise properties of several pulsars. This is most dramatic for PSR J1713+0747, where the amplitude of its achromatic red noise lowers from ${\mathrm{log}}_{10}{A}_{\mathrm{RN}}=-{14.1}_{-0.1}^{+0.1}$ to $-{14.7}_{-0.5}^{+0.3}$ , and the spectral index broadens from ${\gamma }_{\mathrm{RN}}={2.6}_{-0.4}^{+0.5}$ to ${\gamma }_{\mathrm{RN}}={3.5}_{-0.9}^{+1.2}$ . We also compare each pulsar's noise properties with those inferred from the EPTA DR2, using the same models. From the discrepancies, we identify potential areas where the noise models could be improved. These results highlight the potential for custom chromatic noise models to improve PTA sensitivity to GWs.

Analyses of pulsar timing data have provided evidence for a stochastic gravitational wave background in the nanohertz frequency band. The most plausible source of this background is the superposition of signals from millions of supermassive black hole binaries. The standard statistical techniques used to search for this background and assess its significance make several simplifying assumptions, namely (i) Gaussianity, (ii) isotropy, and most often, (iii) a power-law spectrum. However, a stochastic background from a finite collection of binaries does not exactly satisfy any of these assumptions. To understand the effect of these assumptions, we test standard analysis techniques on a large collection of realistic simulated data sets. The data-set length, observing schedule, and noise levels were chosen to emulate the NANOGrav 15 yr data set. Simulated signals from millions of binaries drawn from models based on the Illustris cosmological hydrodynamical simulation were added to the data. We find that the standard statistical methods perform remarkably well on these simulated data sets, even though their fundamental assumptions are not strictly met. They are able to achieve a confident detection of the background. However, even for a fixed set of astrophysical parameters, different realizations of the universe result in a large variance in the significance and recovered parameters of the background. We also find that the presence of loud individual binaries can bias the spectral recovery of the background if we do not account for them.

The cytosolic concentration of free calcium ions ([Ca2+]) is an important intracellular messenger in most cell types, and the spatial distribution of [Ca2+] is often critical. In a salivary gland acinar cell, a polarised epithelial cell, whose principal function is to transport water and thus secrete saliva, [Ca2+] controls the secretion of primary saliva, but increases in [Ca2+] are localised to the apical regions of the cell. Hence, any quantitative explanation of how [Ca2+] controls saliva secretion must take into careful account the spatial distribution of the various Ca2+ sources, Ca2+ sinks, and Ca2+-sensitive ion channels. Based on optical slices, we have previously constructed anatomically accurate three-dimensional models of seven salivary gland acinar cells, and thus shown that a model in which Ca2+ responses are confined to the apical regions of the cell is sufficient to provide a quantitative and predictive explanation of primary saliva secretion. However, reconstruction of such anatomically accurate cells is extremely time consuming and inefficient. Here, we present an alternative, mostly automated method of constructing three-dimensional cells that are approximately anatomically accurate and show that the new construction preserves the quantitative accuracy of the model.

Stem cells: protein not needed for stem cell activity in mammary gland A protein considered necessary for mammary stem cell activity turns out to be dispensable. What’s more, it’s not required for tumor development either. Geoffrey Wahl, Christy Trejo, and colleagues from the Salk Institute for Biological Studies in La Jolla, CA, USA, investigated whether the expression of a protein called Lgr5 denotes mammary stem cells and whether it’s truly needed for the cells to be capable of giving rise to two cell lineages—a subject of active debate among researchers. Wahl’s team showed that mouse fetal mammary stem cells expressing Lgr5 had this dual-lineage capacity; their counterparts in the adult mouse did not. Yet, even though Lgr5 expression marks a population of fetal mammary stem cells, the protein is not required for stem cell activity or for tumors to form in a mouse model of breast cancer.