The center cannot hold: A Bayesian chronology for the collapse of Tiwanaku.

The timing of Tiwanaku's collapse remains contested. Here we present a generational-scale chronology of Tiwanaku using Bayesian models of 102 radiocarbon dates, including 45 unpublished dates. This chronology tracks four community practices: residing short- vs. long-term, constructing monuments, discarding decorated ceramics, and leaving human burials. Tiwanaku was founded around AD 100 and around AD 600, it became the region's principal destination for migrants. It grew into one of the Andes' first cities and became famous for its decorated ceramics, carved monoliths, and large monuments. Our Bayesian models show that monument building ended ~AD 720 (the median of the ending boundary). Around ~AD 910, burials in tombs ceased as violent deaths began, which we document for the first time in this paper. Ritualized murders are limited to the century leading up to ~AD 1020. Our clearest proxy for social networks breaking down is a precise estimate for the end of permanent residence, ~AD 1010 (970-1050, 95%). This major inflection point was followed by visitors who used the same ceramics until ~AD 1040. Temporary camps lasted until roughly ~AD 1050. These four events suggest a rapid, city-wide collapse at ~AD 1010-1050, lasting just ~20 years (0-70 years, 95%). These results suggest a cascading breakdown of community practices and social networks that were physically anchored at Tiwanaku, though visitors continued to leave informal burials for centuries. This generation-scale chronology suggests that collapse 1) took place well before reduced precipitation, hence this was not a drought-induced societal change and 2) a few resilient communities sustained some traditions at other sites, hence the chronology for the site of Tiwanaku cannot be transposed to all sites with similar material culture

Functional Genomics Unique to Week 20 Post Wounding in the Deep Cone/Fat Dome of the Duroc/Yorkshire Porcine Model of Fibroproliferative Scarring

Background: Hypertrophic scar was first described over 100 years ago; PubMed has more than 1,000 references on the topic. Nevertheless prevention and treatment remains poor, because 1) there has been no validated animal model; 2) human scar tissue, which is impossible to obtain in a controlled manner, has been the only source for study; 3) tissues typically have been homogenized, mixing cell populations; and 4) gene-by-gene studies are incomplete.Methodology/Principal Findings: We have assembled a system that overcomes these barriers and permits the study of genome-wide gene expression in microanatomical locations, in shallow and deep partial-thickness wounds, and pigmented and non-pigmented skin, using the Duroc( pigmented fibroproliferative)/Yorkshire( non-pigmented non-fibroproliferative) porcine model. We used this system to obtain the differential transcriptome at 1, 2, 3, 12 and 20 weeks post wounding. It is not clear when fibroproliferation begins, but it is fully developed in humans and the Duroc breed at 20 weeks. Therefore we obtained the derivative functional genomics unique to 20 weeks post wounding. We also obtained long-term, forty-six week follow-up with the model.Conclusions/Significance: 1) the scars are still thick at forty-six weeks post wounding further validating the model. 2) the differential transcriptome provides new insights into the fibroproliferative process as several genes thought fundamental to fibroproliferation are absent and others differentially expressed are newly implicated. 3) the findings in the derivative functional genomics support old concepts, which further validates the model, and suggests new avenues for reductionist exploration. in the future, these findings will be searched for directed networks likely involved in cutaneous fibroproliferation. These clues may lead to a better understanding of the systems biology of cutaneous fibroproliferation, and ultimately prevention and treatment of hypertrophic scarring.The National Institute on Disability and Rehabilitation ResearchThe National Institutes of HealthThe Washington State Council of Fire Fighters Burn FoundationThe Northwest Burn FoundationUniv Washington, Dept Surg, Div Plast Surg, Seattle, WA 98195 USAIowa State Univ, Dept Anim Sci, Ames, IA USAUniv Washington, Dept Biostat, Seattle, WA 98195 USAMahidol Univ, Ramathibodi Hosp, Dept Surg, Bangkok 10700, ThailandUniv Washington, Dept Environm & Occupat Hlth Sci, Seattle, WA 98195 USAUniversidade Federal de São Paulo, Div Plast Surg, Dept Surg, São Paulo, BrazilUniversidade Federal de São Paulo, Div Plast Surg, Dept Surg, São Paulo, BrazilThe National Institute on Disability and Rehabilitation Research: H133G050022The National Institutes of Health: 1R21GM074673The National Institutes of Health: 5U54GM062119-09Web of Scienc

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

The Arctic Coastal Dynamics database. A new classification scheme and statistics on arctic permafrost coastlines

Arctic permafrost coasts are sensitive to changing climate. The lengthening open water season and the increasing open water area are likely to induce greater erosion and threaten community and industry infrastructure as well as dramatically change nutrient pathways in the near-shore zone. The shallow, mediterranean Arctic Ocean is likely to be strongly affected by changes in currently poorly observed arctic coastal dynamics. We present a geomorphological classification scheme for the arctic coast, with 101,447 km of coastline in 1,315 segments. The average rate of erosion for the arctic coast is 0.5 m year(-1) with high local and regional variability. Highest rates are observed in the Laptev, East Siberian, and Beaufort Seas. Strong spatial variability in associated database bluff height, ground carbon and ice content, and coastline movement highlights the need to estimate the relative importance of shifting coastal fluxes to the Arctic Ocean at multiple spatial scales