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Abstract Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ( $$n = 36$$ n = 36 ) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was $$2.1\% \pm 2\%$$ 2.1 % ± 2 % compared to $$1.1\% \pm 1\%$$ 1.1 % ± 1 % ( $$p = 0.002$$ p = 0.002 ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or $$1.4\% \pm 1\%$$ 1.4 % ± 1 % ( $$p = 0.01$$ p = 0.01 ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( $$p = 0.05$$ p = 0.05 ) and PKD2 mutation ( $$p = 0.04$$ p = 0.04 ) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate.

Background:. Enhanced recovery after surgery (ERAS) protocols have demonstrated success in reducing hospital stay and opioid consumption, but are less well studied in patients undergoing tissue expander-based breast reconstruction (TEBR). This study evaluates the effectiveness of an ERAS postoperative protocol for TEBR at a high-volume center. Methods:. All patients undergoing immediate tissue expander reconstruction after the introduction of ERAS were prospectively included from April 2019 to June 2023. An equivalent number of similar patients were retrospectively reviewed before this date as the non-ERAS control. Data included demographics, operative details, postoperative length of stay, inpatient and discharge narcotic quantities, inpatient pain assessments, postoperative radiation, and complications within 90 days. Results:. There were 201 patients in each cohort with statistically similar demographics. Patients in the ERAS cohort were more likely to undergo prepectoral reconstruction (83.1% versus 4.5%, P < 0.001), be discharged by day 1 (96.5% versus 70.2%, P < 0.001) and consume lower inpatient milligram morphine equivalent (MME) median (79.8 versus 151.8, P < 0.001). Seroma rates (17.4% versus 3.5%, P < 0.001) and hematoma incidence (4.5% versus 0%, P = 0.004) were higher in the ERAS cohort. Adjusting for implant location, ERAS was associated with a 60.7 MME reduction (β=-60.7, P < 0.001) and a shorter inpatient duration by 0.4 days (β =-0.4, P < 0.001). Additionally, prepectoral reconstruction significantly decreased MME (β=-30.9, P = 0.015) and was the sole predictor of seroma development (odds ratio = 5.2, P = 0.009). Conclusions:. ERAS protocols significantly reduce opioid use and hospital stay after TEBR.

Modern and fossil pollen data are widely used in paleoenvironmental research to characterize past environmental changes in a given location. However, their discrete and discontinuous nature can limit the inferences that can be made from them. Deriving continuous spatial maps of the pollen presence from point-based datasets would enable more robust regional characterization of such past changes. To address this problem, we propose a comprehensive collection of European pollen presence maps including 194 pollen taxa derived from the interpolation of pollen data from the Eurasian Modern Pollen Database (EMPD v2) restricted to the Euro-Mediterranean Basin. To do so, we developed an automatic Kriging-based interpolation workflow to select an optimal geostatistical model describing the spatial variability for each taxon. The output of the interpolation model consists of a series of multivariate predictive maps of Europe at 25 km scale, showing the occurrence probability of pollen taxa, the predicted presence based on diverse probability thresholds, and the interpolation uncertainty for each taxon. Combined visual inspections of the maps and systematic cross-validation tests demonstrated that the ensemble of predictions is reliable even in data-scarce regions, with a relatively low uncertainty, and robust to complex and non-stationary pollen distributions. The maps, freely distributed as GeoTIFF files (https://doi.org/10.5281/zenodo.10015695, Oriani et al., 2023), are proposed as a ready-to-use tool for spatial paleoenvironmental characterization. Since the interpolation model only uses the coordinates of the observation to spatialize the data, the model can also be employed with fossil pollen records (or other presence/absence indicators), thus enabling the spatial characterization of past changes, and possibly their subsequent use for quantitative paleoclimate reconstructions.

Objective Diagnostic testing is an important tool to combat the COVID-19 pandemic, yet access to and uptake of testing vary widely 3 years into the pandemic. The WHO recommends the use of COVID-19 self-testing as an option to help expand testing access. We aimed to calculate the cost of providing COVID-19 self-testing across countries and distribution modalities.Design We estimated economic costs from the provider perspective to calculate the total cost and the cost per self-test kit distributed for three scenarios that differed by costing period (pilot, annual), the number of tests distributed (actual, planned, scaled assuming an epidemic peak) and self-test kit costs (pilot purchase price, 50% reduction).Setting We used data collected between August and December 2022 in Brazil, Georgia, Malaysia, Ethiopia and the Philippines from pilot implementation studies designed to provide COVID-19 self-tests in a variety of settings—namely, workplace and healthcare facilities.Results Across all five countries, 173 000 kits were distributed during pilot implementation with the cost/test distributed ranging from $2.44 to $12.78. The cost/self-test kit distributed was lowest in the scenario that assumed implementation over a longer period (year), with higher test demand (peak) and a test kit price reduction of 50% ($1.04–3.07). Across all countries and scenarios, test procurement occupied the greatest proportion of costs: 58–87% for countries with off-site self-testing (outside the workplace, for example, home) and 15–50% for countries with on-site self-testing (at the workplace). Staffing was the next key cost driver, particularly for distribution modalities that had on-site self-testing (29–35%) versus off-site self-testing (7–27%).Conclusions Our results indicate that it is likely to cost between $2.44 and $12.78 per test to distribute COVID-19 self-tests across common settings in five heterogeneous countries. Cost-effectiveness analyses using these results will allow policymakers to make informed decisions on optimally scaling up COVID-19 self-test distribution programmes across diverse settings and evolving needs.

A mismatch between model- and proxy-based Holocene climate change, known as the “Holocene conundrum”, may partially originate from the poor spatial coverage of climate reconstructions in, for example, Asia, limiting the number of grid cells for model–data comparisons. Here we investigate hemispheric, latitudinal, and regional mean time series and time-slice anomaly maps of pollen-based reconstructions of mean annual temperature, mean July temperature, and annual precipitation from 1908 records in the Northern Hemisphere extratropics. Temperature trends show strong latitudinal patterns and differ between (sub-)continents. While the circum-Atlantic regions in Europe and eastern North America show a pronounced Middle Holocene temperature maximum, western North America shows only weak changes, and Asia mostly shows a continuous Holocene temperature increase. Likewise, precipitation trends show certain regional peculiarities such as the pronounced Middle Holocene precipitation maximum between 40 and 50∘ N in Asia and Holocene increasing trends in Europe and western North America, which can all be linked with Holocene changes in the regional circulation pattern responding to temperature change. Given a background of strong regional heterogeneity, we conclude that the calculation of global or hemispheric means, which initiated the Holocene conundrum debate, should focus more on understanding the spatiotemporal patterns and their regional drivers.

Total kidney volume measured on MRI is an important biomarker for assessing the progression of autosomal dominant polycystic kidney disease and response to treatment. However, we have noticed that there can be substantial differences in the kidney volume measurements obtained from the various pulse sequences commonly included in an MRI exam. Here we examine kidney volume measurement variability among five commonly acquired MRI pulse sequences in abdominal MRI exams in 105 patients with ADPKD. Right and left kidney volumes were independently measured by three expert observers using model-assisted segmentation for axial T2, coronal T2, axial single-shot fast spin echo (SSFP), coronal SSFP, and axial 3D T1 images obtained on a single MRI from ADPKD patients. Outlier measurements were analyzed for data acquisition errors. Most of the outlier values (88%) were due to breathing during scanning causing slice misregistration with gaps or duplication of imaging slices (n = 35), slice misregistration from using multiple breath holds during acquisition (n = 25), composing of two overlapping acquisitions (n = 17), or kidneys not entirely within the field of view (n = 4). After excluding outlier measurements, the coefficient of variation among the five measurements decreased from 4.6% pre to 3.2%. Compared to the average of all sequences without errors, TKV measured on axial and coronal T2 weighted imaging were 1.2% and 1.8% greater, axial SSFP was 0.4% greater, coronal SSFP was 1.7% lower and axial T1 was 1.5% lower than the mean, indicating intrinsic measurement biases related to the different MRI contrast mechanisms. In conclusion, MRI data acquisition errors are common but can be identified using outlier analysis and excluded to improve organ volume measurement consistency. Bias toward larger volume measurements on T2 sequences and smaller volumes on axial T1 sequences can also be mitigated by averaging data from all error-free sequences acquired.

Here we describe LegacyClimate 1.0, a dataset of the reconstruction of the mean July temperature (TJuly), mean annual temperature (Tann), and annual precipitation (Pann) from 2594 fossil pollen records from the Northern Hemisphere, spanning the entire Holocene, with some records reaching back to the Last Glacial Period. Two reconstruction methods, the modern analog technique (MAT) and weighted averaging partial least squares regression (WA-PLS), reveal similar results regarding spatial and temporal patterns. To reduce the impact of precipitation on temperature reconstruction, and vice versa, we also provide reconstructions using tailored modern pollen data, limiting the range of the corresponding other climate variables. We assess the reliability of the reconstructions, using information from the spatial distributions of the root mean squared error in the prediction and reconstruction significance tests. The dataset is beneficial for synthesis studies of proxy-based reconstructions and to evaluate the output of climate models and thus help to improve the models themselves. We provide our compilation of reconstructed TJuly, Tann, and Pann as open-access datasets at PANGAEA (https://doi.org/10.1594/PANGAEA.930512; Herzschuh et al., 2023a). The R code for the reconstructions is provided at Zenodo (https://doi.org/10.5281/zenodo.7887565; Herzschuh et al., 2023b), including the harmonized open-access modern and fossil datasets used for the reconstructions, so that customized reconstructions can be easily established.

Objectives To determine the most epidemiologically effective and cost-effective school-based SARS-CoV-2 antigen-detection rapid diagnostic test (Ag-RDT) self-testing strategies among teachers and students.Design Mathematical modelling and economic evaluation.Setting and participants Simulated school and community populations were parameterised to Brazil, Georgia and Zambia, with SARS-CoV-2 self-testing strategies targeted to teachers and students in primary and secondary schools under varying epidemic conditions.Interventions SARS-CoV-2 Ag-RDT self-testing strategies for only teachers or teachers and students—only symptomatically or symptomatically and asymptomatically at 5%, 10%, 40% or 100% of schools at varying frequencies.Outcome measures Outcomes were assessed in terms of total infections and symptomatic days among teachers and students, as well as total infections and deaths within the community under the intervention compared with baseline. The incremental cost-effectiveness ratios (ICERs) were calculated for infections prevented among teachers and students.Results With respect to both the reduction in infections and total cost, symptomatic testing of all teachers and students appears to be the most cost-effective strategy. Symptomatic testing can prevent up to 69·3%, 64·5% and 75·5% of school infections in Brazil, Georgia and Zambia, respectively, depending on the epidemic conditions, with additional reductions in community infections. ICERs for symptomatic testing range from US$2 to US$19 per additional school infection averted as compared with symptomatic testing of teachers alone.Conclusions Symptomatic testing of teachers and students has the potential to cost-effectively reduce a substantial number of school and community infections.

Places of worship serve as a venue for both mass and routine gathering around the world, and therefore are associated with risk of large-scale SARS-CoV-2 transmission. However, such routine gatherings also offer an opportunity to distribute self-tests to members of the community to potentially help mitigate transmission and reduce broader community spread of SARS-CoV-2. Over the past four years, self-testing strategies have been an impactful tool for countries' response to the COVID-19 pandemic, especially early on to mitigate the spread when vaccination and treatment options were limited. We used an agent-based mathematical model to estimate the impact of various strategies of symptomatic and asymptomatic self-testing for a fixed percentage of weekly routine gatherings at places of worship on community transmission of SARS-CoV-2 in Brazil, Georgia, and Zambia. Testing strategies assessed included weekly and bi-weekly self-testing across varying levels of vaccine effectiveness, vaccine coverage, and reproductive numbers to simulate developing stages of the COVID-19 pandemic. Self-testing symptomatic people attending routine gatherings can cost-effectively reduce the spread of SARS-CoV-2 within places of worship and the community, resulting in incremental cost-effectiveness ratios of $69-$303 USD. This trend is especially true in contexts where population level attendance at such gatherings is high, demonstrating that a distribution approach is more impactful when a greater proportion of the population is reached. Asymptomatic self-testing of attendees at 100% of places of worship in a country results in the greatest percent of infections averted and is consistently cost-effective but remains costly. Budgetary needs for asymptomatic testing are expensive and likely unaffordable for lower-middle income countries (520-1550x greater than that of symptomatic testing alone), promoting that strategies to strengthen symptomatic testing should remain a higher priority.

Introduction: Post-traumatic osteoarthritis (PTOA) develops following traumatic articular insult. One model system used to study the progression and treatment of PTOA is the destabilization of the medial meniscus (DMM) as first described by Glasson et al performed in mini-pigs. Miniature pigs are less available, more expensive, and have synovial fluid sampling limitations, limiting the availability of osteoarthritis biomarkers compared to domestic pigs. Objectives: The following technical note details stepwise procedures and animal welfare strategies for the use of Yorkshire pigs as a large animal PTOA model. Methods: The following technical note details stepwise procedures to perform peroperative saphenous nerve block, DMM, and subsequent postoperative management in Yorkshire pigs as a large animal PTOA model. Results: At 4 weeks post-operatively, all pigs develop mild-moderate PTOA based on postmortem joint dissections. Conclusions: This technical note provides further details on the arthrotomy approach to destabilize the medial meniscus of domestic pigs as a model of PTOA.

Comparing temporal and spatial vegetation changes between reconstructions or between reconstructions and model simulations requires carefully selecting an appropriate evaluation metric. A common way of comparing reconstructed and simulated vegetation changes involves measuring the agreement between pollen- or model-derived unary vegetation estimates, such as the biome or plant functional type (PFT) with the highest affinity scores. While this approach based on summarising the vegetation signal into unary vegetation estimates performs well in general, it overlooks the details of the underlying vegetation structure. However, this underlying data structure can influence conclusions since minor variations in pollen percentages modify which biome or PFT has the highest affinity score (i.e. modify the unary vegetation estimate). To overcome this limitation, we propose using the Earth mover's distance (EMD) to quantify the mismatch between vegetation distributions such as biome or PFT affinity scores. The EMD circumvents the issue of summarising the data into unary biome or PFT estimates by considering the entire range of biome or PFT affinity scores to calculate a distance between the compared entities. In addition, each type of mismatch can be given a specific weight to account for case-specific ecological distances or, said differently, to account for the fact that reconstructing a temperate forest instead of a boreal forest is ecologically more coherent than reconstructing a temperate forest instead of a desert. We also introduce two EMD-based statistical tests that determine (1) if the similarity of two samples is significantly better than a random association given a particular context and (2) if the pairing between two datasets is better than might be expected by chance. To illustrate the potential and the advantages of the EMD as well as the tests in vegetation comparison studies, we reproduce different case studies based on previously published simulated and reconstructed biome changes for Europe and capitalise on the advantages of the EMD to refine the interpretations of past vegetation changes by highlighting that flickering unary estimates, which give an impression of high vegetation instability, can correspond to gradual vegetation changes with low EMD values between contiguous samples (case study 1). We also reproduce data–model comparisons for five specific time slices to identify those that are statistically more robust than a random agreement while accounting for the underlying vegetation structure of each pollen sample (case study 2). The EMD and the statistical tests are included in the paleotools R package (https://github.com/mchevalier2/paleotools, last access: 3 May 2023).

Abdominal imaging of autosomal dominant polycystic kidney disease (ADPKD) has historically focused on detecting complications such as cyst rupture, cyst infection, obstructing renal calculi, and pyelonephritis; discriminating complex cysts from renal cell carcinoma; and identifying sources of abdominal pain. Many imaging features of ADPKD are incompletely evaluated or not deemed to be clinically significant, and because of this, treatment options are limited. However, total kidney volume (TKV) measurement has become important for assessing the risk of disease progression (i.e., Mayo Imaging Classification) and predicting tolvaptan treatment’s efficacy. Deep learning for segmenting the kidneys has improved these measurements’ speed, accuracy, and reproducibility. Deep learning models can also segment other organs and tissues, extracting additional biomarkers to characterize the extent to which extrarenal manifestations complicate ADPKD. In this concept paper, we demonstrate how deep learning may be applied to measure the TKV and how it can be extended to measure additional features of this disease.

Organ volume measurements are a key metric for managing ADPKD (the most common inherited renal disease). However, measuring organ volumes is tedious and involves manually contouring organ outlines on multiple cross-sectional MRI or CT images. The automation of kidney contouring using deep learning has been proposed, as it has small errors compared to manual contouring. Here, a deployed open-source deep learning ADPKD kidney segmentation pipeline is extended to also measure liver and spleen volumes, which are also important. This 2D U-net deep learning approach was developed with radiologist labeled T2-weighted images from 215 ADPKD subjects (70% training = 151, 30% validation = 64). Additional ADPKD subjects were utilized for prospective (n = 30) and external (n = 30) validations for a total of 275 subjects. Image cropping previously optimized for kidneys was included in training but removed for the validation and inference to accommodate the liver which is closer to the image border. An effective algorithm was developed to adjudicate overlap voxels that are labeled as more than one organ. Left kidney, right kidney, liver and spleen labels had average errors of 3%, 7%, 3%, and 1%, respectively, on external validation and 5%, 6%, 5%, and 1% on prospective validation. Dice scores also showed that the deep learning model was close to the radiologist contouring, measuring 0.98, 0.96, 0.97 and 0.96 on external validation and 0.96, 0.96, 0.96 and 0.95 on prospective validation for left kidney, right kidney, liver and spleen, respectively. The time required for manual correction of deep learning segmentation errors was only 19:17 min compared to 33:04 min for manual segmentations, a 42% time saving (p = 0.004). Standard deviation of model assisted segmentations was reduced to 7, 5, 11, 5 mL for right kidney, left kidney, liver and spleen respectively from 14, 10, 55 and 14 mL for manual segmentations. Thus, deep learning reduces the radiologist time required to perform multiorgan segmentations in ADPKD and reduces measurement variability.

Statistical climate reconstruction techniques are fundamental tools to study past climate variability from fossil proxy data. In particular, the methods based on probability density functions (or PDFs) can be used in various environments and with different climate proxies because they rely on elementary calibration data (i.e. modern geolocalised presence data). However, the difficulty of accessing and curating these calibration data and the complexity of interpreting probabilistic results have often limited their use in palaeoclimatological studies. Here, I introduce a new R package (crestr) to apply the PDF-based method CREST (Climate REconstruction SofTware) on diverse palaeoecological datasets and address these problems. crestr includes a globally curated calibration dataset for six common climate proxies (i.e. plants, beetles, chironomids, rodents, foraminifera, and dinoflagellate cysts) associated with an extensive range of climate variables (20 terrestrial and 19 marine variables) that enables its use in most terrestrial and marine environments. Private data collections can also be used instead of, or in combination with, the provided calibration dataset. The package includes a suite of graphical diagnostic tools to represent the data at each step of the reconstruction process and provide insights into the effect of the different modelling assumptions and external factors that underlie a reconstruction. With this R package, the CREST method can now be used in a scriptable environment and thus be more easily integrated with existing workflows. It is hoped that crestr will be used to produce the much-needed quantified climate reconstructions from the many regions where they are currently lacking, despite the availability of suitable fossil records. To support this development, the use of the package is illustrated with a step-by-step replication of a 790 000-year-long mean annual temperature reconstruction based on a pollen record from southeastern Africa.

We report the first multi-differential measurements of strange hadrons of K−, ϕ and Ξ− yields as well as the ratios of ϕ/K− and ϕ/Ξ− in Au+Au collisions at sNN=3 GeV with the STAR experiment fixed target configuration at RHIC. The ϕ mesons and Ξ− hyperons are measured through hadronic decay channels, ϕ→K+K− and Ξ−→Λπ−. Collision centrality and rapidity dependence of the transverse momentum spectra for these strange hadrons are presented. The 4π yields and ratios are compared to thermal model and hadronic transport model predictions. At this collision energy, thermal model with grand canonical ensemble (GCE) under-predicts the ϕ/K− and ϕ/Ξ− ratios while the result of canonical ensemble (CE) calculations reproduce ϕ/K−, with the correlation length rc∼2.7 fm, and ϕ/Ξ−, rc∼4.2 fm, for the 0-10% central collisions. Hadronic transport models including high mass resonance decays could also describe the ratios. While thermal calculations with GCE work well for strangeness production in high energy collisions, the change to CE at 3 GeV implies a rather different medium property at high baryon density.

The Eurasian (née European) Modern Pollen Database (EMPD) was established in 2013 to provide a public database of high-quality modern pollen surface samples to help support studies of past climate, land cover, and land use using fossil pollen. The EMPD is part of, and complementary to, the European Pollen Database (EPD) which contains data on fossil pollen found in Late Quaternary sedimentary archives throughout the Eurasian region. The EPD is in turn part of the rapidly growing Neotoma database, which is now the primary home for global palaeoecological data. This paper describes version 2 of the EMPD in which the number of samples held in the database has been increased by 60 % from 4826 to 8134. Much of the improvement in data coverage has come from northern Asia, and the database has consequently been renamed the Eurasian Modern Pollen Database to reflect this geographical enlargement. The EMPD can be viewed online using a dedicated map-based viewer at https://empd2.github.io and downloaded in a variety of file formats at https://doi.pangaea.de/10.1594/PANGAEA.909130 (Chevalier et al., 2019).

Abstract We report on the measurement of the Central Exclusive Production of charged particle pairs h + h − (h = π, K, p) with the STAR detector at RHIC in proton-proton collisions at s $$ \sqrt{s} $$ = 200 GeV. The charged particle pairs produced in the reaction pp → p′ + h + h − + p′ are reconstructed from the tracks in the central detector and identified using the specific energy loss and the time of flight method, while the forward-scattered protons are measured in the Roman Pot system. Exclusivity of the event is guaranteed by requiring the transverse momentum balance of all four final-state particles. Differential cross sections are measured as functions of observables related to the central hadronic final state and to the forward-scattered protons. They are measured in a fiducial region corresponding to the acceptance of the STAR detector and determined by the central particles’ transverse momenta and pseudorapidities as well as by the forward-scattered protons’ momenta. This fiducial region roughly corresponds to the square of the four-momentum transfers at the proton vertices in the range 0.04 GeV2 < −t 1 , −t 2 < 0.2 GeV2, invariant masses of the charged particle pairs up to a few GeV and pseudorapidities of the centrally-produced hadrons in the range |η| < 0.7. The measured cross sections are compared to phenomenological predictions based on the Double Pomeron Exchange (DPE) model. Structures observed in the mass spectra of π + π − and K + K − pairs are consistent with the DPE model, while angular distributions of pions suggest a dominant spin-0 contribution to π + π − production. For π + π − production, the fiducial cross section is extrapolated to the Lorentz-invariant region, which allows decomposition of the invariant mass spectrum into continuum and resonant contributions. The extrapolated cross section is well described by the continuum production and at least three resonances, the f 0(980), f 2(1270) and f 0(1500), with a possible small contribution from the f 0(1370). Fits to the extrapolated differential cross section as a function of t 1 and t 2 enable extraction of the exponential slope parameters in several bins of the invariant mass of π + π − pairs. These parameters are sensitive to the size of the interaction region.

We report on the measurements of directed flow v1 and elliptic flow v2 for hadrons (π±, K±, KS0, p, ϕ, Λ and Ξ−) from Au+Au collisions at sNN=3GeV and v2 for (π±, K±, p and p‾) at 27 and 54.4GeV with the STAR experiment. While at the two higher energy midcentral collisions the number-of-constituent-quark (NCQ) scaling holds, at 3GeV the v2 at midrapidity is negative for all hadrons and the NCQ scaling is absent. In addition, the v1 slopes at midrapidity for almost all observed hadrons are found to be positive, implying dominant repulsive baryonic interactions. The features of negative v2 and positive v1 slope at 3GeV can be reproduced with a baryonic mean-field in transport model calculations. These results imply that the medium in such collisions is likely characterized by baryonic interactions.

Measurement by the STAR experiment at RHIC of the cold nuclear matter (CNM) effects experienced by inclusive J/ψ at mid-rapidity in 0-100% p+Au collisions at sNN = 200 GeV is presented. Such effects are quantified utilizing the nuclear modification factor, RpAu, obtained by taking a ratio of J/ψ yield in p+Au collisions to that in p+p collisions scaled by the number of binary nucleon-nucleon collisions. The differential J/ψ yield in both p+p and p+Au collisions is measured through the dimuon decay channel, taking advantage of the trigger capability provided by the Muon Telescope Detector in the RHIC 2015 run. Consequently, the J/ψ RpAu is derived within the transverse momentum (pT) range of 0 to 10 GeV/c. A suppression of approximately 30% is observed for pT

Countries around the world have implemented restrictions on mobility, especially cross-border travel to reduce or prevent SARS-CoV-2 community transmission. Rapid antigen testing (Ag-RDT), with on-site administration and rapid turnaround time may provide a valuable screening measure to ease cross-border travel while minimizing risk of local transmission. To maximize impact, we developed an optimal Ag-RDT screening algorithm for cross-border entry. Using a previously developed mathematical model, we determined the daily number of imported COVID-19 cases that would generate no more than a relative 1% increase in cases over one month for different effective reproductive numbers (Rt) and COVID-19 prevalence within the recipient country. We then developed an algorithm-for differing levels of Rt, arrivals per day, mode of travel, and SARS-CoV-2 prevalence amongst travelers-to determine the minimum proportion of people that would need Ag-RDT testing at border crossings to ensure no greater than the relative 1% community spread increase. When daily international arrivals and/or COVID-19 prevalence amongst arrivals increases, the proportion of arrivals required to test using Ag-RDT increases. At very high numbers of international arrivals/COVID-19 prevalence, Ag-RDT testing is not sufficient to prevent increased community spread, especially when recipient country prevalence and Rt are low. In these cases, Ag-RDT screening would need to be supplemented with other measures to prevent an increase in community transmission. An efficient Ag-RDT algorithm for SARS-CoV-2 testing depends strongly on the epidemic status within the recipient country, volume of travel, proportion of land and air arrivals, test sensitivity, and COVID-19 prevalence among travelers.

The dynamics of HIV-1 DNA sequences early after HIV-1 transmission remains poorly characterized. Here, the authors perform a longitudinal evaluation of HIV-1 DNA sequences in subtype C-infected individuals during acute infection, providing a landscape of the nature and evolution of the very early viral genome.

In this letter, measurements of the shared momentum fraction (zg) and the groomed jet radius (Rg), as defined in the SoftDrop algorithm, are reported in p+p collisions at s=200 GeV collected by the STAR experiment. These substructure observables are differentially measured for jets of varying resolution parameters from R=0.2−0.6 in the transverse momentum range 15

Flow harmonics (vn) of the Fourier expansion for the azimuthal distributions of hadrons are commonly employed to quantify the azimuthal anisotropy of particle production relative to the collision symmetry planes. While lower order Fourier coefficients (v2 and v3) are more directly related to the corresponding eccentricities of the initial state, the higher-order flow harmonics (vn>3) can be induced by a mode-coupled response to the lower-order anisotropies, in addition to a linear response to the same-order anisotropies. These higher-order flow harmonics and their linear and mode-coupled contributions can be used to more precisely constrain the initial conditions and the transport properties of the medium in theoretical models. The multiparticle azimuthal cumulant method is used to measure the linear and mode-coupled contributions in the higher-order anisotropic flow, the mode-coupled response coefficients, and the correlations of the event plane angles for charged particles as functions of centrality and transverse momentum in Au+Au collisions at nucleon-nucleon center-of-mass energy sNN= 200 GeV. The results are compared to similar LHC measurements as well as to several viscous hydrodynamic calculations with varying initial conditions.

We report results on the total and elastic cross sections in proton-proton collisions at s=200 GeV obtained with the Roman Pot setup of the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The elastic differential cross section was measured in the squared four-momentum transfer range 0.045≤−t≤0.135 GeV2. The value of the exponential slope parameter B of the elastic differential cross section dσ/dt∼e−Bt in the measured −t range was found to be B=14.32±0.09(stat.)−0.28+0.13(syst.) GeV−2. The total cross section σtot, obtained from extrapolation of the dσ/dt to the optical point at −t=0, is σtot=54.67±0.21(stat.)−1.38+1.28(syst.) mb. We also present the values of the elastic cross section σel=10.85±0.03(stat.)−0.41+0.49(syst.) mb, the elastic cross section integrated within the STAR t-range σeldet=4.05±0.01(stat.)−0.17+0.18(syst.) mb, and the inelastic cross section σinel=43.82±0.21(stat.)−1.44+1.37(syst.) mb. The results are compared with the world data.

Introduction: IgA nephropathy is the most common glomerulonephritis in the world. We conducted a pilot trial (NCT01103778) to test the effect of bortezomib in patients with IgA nephropathy and significant proteinuria. Methods: We treated 8 consecutive subjects from July 2011 until March 2016 with 4 doses of bortezomib. All subjects had biopsy-proven IgA nephropathy and proteinuria of greater than 1 g per day. They were given 4 doses of bortezomib i.v. at 1.3 mg/m2 of body surface area per dose. Changes in proteinuria and renal function were followed for 1 year after enrollment. The primary endpoint was full remission defined as proteinuria of less than 300 mg per day. Results: All 8 subjects received and tolerated 4 doses of bortezomib over a 2-week period during enrollment. The median baseline daily proteinuria was 2.46 g (interquartile range: 2.29–3.16 g). At 1-year follow-up, 3 subjects (38%) had achieved the primary endpoint. The 3 subjects who had complete remission had Oxford classification T scores of 0 before enrollment. Of the remaining 5 subjects, 1 was lost to follow-up within 1 month of enrollment and 4 (50%) did not have any response or had progression of disease. Conclusion: Proteasome inhibition by bortezomib may reduce significant proteinuria in select cases of IgA nephropathy. Subjects who responded to bortezomib had Oxford classification T score of 0 and normal renal function. Keywords: bortezomib, IgA nephropathy, proteinuria

Monoacylglycerol lipase (MGL) is a ubiquitously expressed enzyme that catalyzes the hydrolysis of monoacylglycerols (MGs) to yield FFAs and glycerol. MGL contributes to energy homeostasis through the mobilization of fat stores and also via the degradation of the endocannabinoid 2-arachidonoyl glycerol. To further examine the role of MG metabolism in energy homeostasis, MGL−/− mice were fed either a 10% (kilocalories) low-fat diet (LFD) or a 45% (kilocalories) high-fat diet (HFD) for 12 weeks. Profound increases of MG species in the MGL−/− mice compared with WT control mice were found. Weight gain over the 12 weeks was blunted in both diet groups. MGL−/− mice were leaner than WT mice at both baseline and after 12 weeks of LFD feeding. Circulating lipids were decreased in HFD-fed MGL−/− mice, as were the levels of several plasma peptides involved in glucose homeostasis and energy balance. Interestingly, MGL−/− mice had markedly reduced intestinal TG secretion following an oral fat challenge, suggesting delayed lipid absorption. Overall, the results indicate that global MGL deletion leads to systemic changes that produce a leaner phenotype and an improved serum metabolic profile.

INTRODUCTION:Pharmacist-patient communication during medication counselling has been successfully investigated using Communication Accommodation Theory (CAT). Communication researchers in other healthcare professions have utilised Discursis software as an adjunct to their manual qualitative analysis processes. Discursis provides a visual, chronological representation of communication exchanges and identifies patterns of interactant engagement. AIM:The aim of this study was to describe how Discursis software was used to enhance previously conducted qualitative analysis of pharmacist-patient interactions (by visualising pharmacist-patient speech patterns, episodes of engagement, and identifying CAT strategies employed by pharmacists within these episodes). METHODS:Visual plots from 48 transcribed audio recordings of pharmacist-patient exchanges were generated by Discursis. Representative plots were selected to show moderate-high and low- level speaker engagement. Details of engagement were investigated for pharmacist application of CAT strategies (approximation, interpretability, discourse management, emotional expression, and interpersonal control). RESULTS:Discursis plots allowed for identification of distinct patterns occurring within pharmacist-patient exchanges. Moderate-high pharmacist-patient engagement was characterised by multiple off-diagonal squares while alternating single coloured squares depicted low engagement. Engagement episodes were associated with multiple CAT strategies such as discourse management (open-ended questions). Patterns reflecting pharmacist or patient speaker dominance were dependant on clinical setting. DISCUSSION AND CONCLUSIONS:Discursis analysis of pharmacist-patient interactions, a novel application of the technology in health communication, was found to be an effective visualisation tool to pin-point episodes for CAT analysis. Discursis has numerous practical and theoretical applications for future health communication research and training. Researchers can use the software to support qualitative analysis where large data sets can be quickly reviewed to identify key areas for concentrated analysis. Because Discursis plots are easily generated from audio recorded transcripts, they are conducive as teaching tools for both students and practitioners to assess and develop their communication skills.

Several methods currently exist to quantitatively reconstruct palaeoclimatic variables from fossil botanical data. Of these, probability density function (PDF)-based methods have proven valuable as they can be applied to a wide range of plant assemblages. Most commonly applied to fossil pollen data, their performance, however, can be limited by the taxonomic resolution of the pollen data, as many species may belong to a given pollen type. Consequently, the climate information associated with different species cannot always be precisely identified, resulting in less-accurate reconstructions. This can become particularly problematic in regions of high biodiversity. In this paper, we propose a novel PDF-based method that takes into account the different climatic requirements of each species constituting the broader pollen type. PDFs are fitted in two successive steps, with parametric PDFs fitted first for each species and then a combination of those individual species PDFs into a broader single PDF to represent the pollen type as a unit. A climate value for the pollen assemblage is estimated from the likelihood function obtained after the multiplication of the pollen-type PDFs, with each being weighted according to its pollen percentage. To test its performance, we have applied the method to southern Africa as a regional case study and reconstructed a suite of climatic variables (e.g. winter and summer temperature and precipitation, mean annual aridity, rainfall seasonality). The reconstructions are shown to be accurate for both temperature and precipitation. Predictable exceptions were areas that experience conditions at the extremes of the regional climatic spectra. Importantly, the accuracy of the reconstructed values is independent of the vegetation type where the method is applied or the number of species used. The method used in this study is publicly available in a software package entitled CREST (Climate REconstruction SofTware) and will provide the opportunity to reconstruct quantitative estimates of climatic variables even in areas with high geographical and botanical diversity.

Secondary causes of minimal change disease (MCD) account for a minority of cases compared to its primary or idiopathic form and provide ground for consideration of common mechanisms of pathogenesis. In this paper we report a case of a 27-year-old Latina woman, a renal transplant recipient with systemic lupus erythematosus (SLE), who developed nephrotic range proteinuria 6 months after transplantation. The patient had recurrent acute renal failure and multiple biopsies were consistent with MCD. However, she lacked any other features of the typical nephrotic syndrome. An angiogram revealed a right external iliac vein stenosis in the region of renal vein anastomosis, which when restored resulted in normalization of creatinine and relief from proteinuria. We report a rare case of MCD developing secondary to iliac vein stenosis in a renal transplant recipient with SLE. Additionally we suggest that, in the event of biopsy-proven MCD presenting as an atypical nephrotic syndrome, alternative or secondary, potentially reversible, causes should be considered and explored.