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Boreal fire regimes are intensifying because of climate change, and the northern parts of boreal forests are underlain by permafrost. Boreal fires combust vegetation and organic soils, which insulate permafrost, and as such deepen the seasonally thawed active layer and can lead to further carbon emissions to the atmosphere. Current understanding of the environmental drivers of post-fire thaw depth is limited but of critical importance. In addition, mapping thaw depth over fire scars may enable a better understanding of the spatial variability in post-fire responses of permafrost soils. We assessed the environmental drivers of post-fire thaw depth using field data from a fire scar in a larch-dominated forest in the continuous permafrost zone in eastern Siberia. Particularly, summer thaw depth was deeper in burned (mean=127.3 cm, standard deviation (SD) = 27.7 cm) than in unburned (98.1 cm, SD=26.9 cm) landscapes 1 year after the fire, yet the effect of fire was modulated by landscape and vegetation characteristics. We found deeper thaw in well-drained upland, in open and mature larch forest often intermixed with Scots pine, and in high-severity burns. The environmental drivers basal area, vegetation density, and burn depth explained 73.3 % of the measured thaw depth variability at the study sites. In addition, we evaluated the relationships between field-measured thaw depth and several remote sensing proxies. Albedo, the differenced normalized burn ratio (dNBR), and the pre-fire normalized difference vegetation index (NDVI) derived from Landsat 8 imagery together explained 66.3 % of the variability in field-measured thaw depth. Moreover, land surface temperature (LST) displayed particularly strong correlations with post-fire thaw depth (r=0.65, p). Based on these remote sensing proxies and multiple linear regression analysis, we estimated thaw depth over the entire fire scar. Our study reveals some of the governing processes of post-fire thaw depth development and shows the capability of Landsat imagery to estimate post-fire thaw depth at a landscape scale.

The Arctic region has undergone warming at a rate more than 3 times higher than the global average. This warming has led to the degradation of near-surface permafrost, resulting in decreased ground stability. This instability not only poses a primary hazard to Arctic infrastructure and human-impacted areas but can also lead to secondary ecological hazards from infrastructure failure associated with hazardous materials. This development underscores the need for a comprehensive inventory of critical infrastructure and human-impacted areas. The inventory should be linked to environmental data to assess their susceptibility to permafrost degradation as well as the ecological consequences that may arise from infrastructure failure. Here, we provide such an inventory for Alaska, a vast state covering approximately 1.7 × 106 km2, with a population of over 733 000 people and a history of industrial development on permafrost. Our Synthesized Inventory of CRitical Infrastructure and HUman-Impacted Areas in AlaSka (SIRIUS) integrates data from (i) the Sentinel-1/2-derived Arctic Coastal Human Impact dataset (SACHI); (ii) OpenStreetMap (OSM); (iii) the pan-Arctic Catchment Database (ARCADE); (iv) a dataset of permafrost extent, probability and mean annual ground temperatures; and (v) the Contaminated Sites Database and reports to create a unified new dataset of critical infrastructure and human-impacted areas as well as permafrost and watershed information for Alaska. The integration process included harmonizing spatial references, extents and geometries across all the datasets as well as incorporating a uniform usage type classification scheme for the infrastructure data. Additionally, we employed text-mining techniques to generate complementary geospatial data from textual reports on contaminated sites, including details on contaminants, cleanup duration and the affected media. The combination of SACHI and OSM enhanced the detail of the usage type classification for infrastructure from 5 to 13 categories, allowing the identification of elements critical to Arctic communities beyond industrial sites. Further, the new inventory integrates the high spatial detail of OSM with the unbiased infrastructure detection capability of SACHI, accurately representing 94 % of the polygonal infrastructure and 78 % of the linear infrastructure, respectively. The SIRIUS dataset is presented as a GeoPackage, enabling spatial analysis and queries of its components, either as a function of or in combination with one another. The dataset is available on Zenodo at https://doi.org/10.5281/zenodo.8311243 (Kaiser et al., 2023).

Tropical reefs encompass tremendous biodiversity yet are imperiled by increasing natural and anthropogenic disturbances worldwide. Meiobenthic biota on coral reefs, for example, ostracods, may experience substantial diversity loss and compositional changes even before being examined. In this study, we investigated the reefal ostracod assemblages from the highly diverse and productive ecosystem in the Zanzibar Archipelago (Pemba, Zanzibar, and Mafia islands), Tanzania, to understand how their diversity and faunal structure vary in response to water depth, benthic community type, and human impacts. We characterized four distinct ostracod faunas associated with different benthic habitats, which were deep fore reefs, shallow fringing reefs, degraded fringing reefs, and algae-covered intertidal flats. We identified typical ostracod associations, i.e., Bairdiidae versus Loxoconchidae–Xestoleberididae, that showed affinities towards hard corals or algae on the reef platforms, respectively. The highest diversity was found on shallow fringing reefs where coral-affined and algae-affined taxa exhibited maximum overlap of their distributional ranges, while the sand flats, mangrove, and marginal reefs within the intertidal zone had much lower diversity with a high dominance of euryhaline taxa. Along the western coast of Zanzibar Island, coastal development likely resulted in a unique faunal composition and comparatively low diversity of ostracod assemblages among those in reefal habitats, in conjunction with overall reef ecosystem degradation. This study represents the first large-scale assessment of shallow-marine ostracods in the Zanzibar Archipelago. It lays a solid foundation for future research into the ecological significance of ostracods on coral reefs.

Abstract Landscape drying associated with permafrost thaw is expected to enhance microbial methane oxidation in arctic soils. Here we show that ice-rich, Yedoma permafrost deposits, comprising a disproportionately large fraction of pan-arctic soil carbon, present an alternate trajectory. Field and laboratory observations indicate that talik (perennially thawed soils in permafrost) development in unsaturated Yedoma uplands leads to unexpectedly large methane emissions (35–78 mg m−2 d−1 summer, 150–180 mg m−2 d−1 winter). Upland Yedoma talik emissions were nearly three times higher annually than northern-wetland emissions on an areal basis. Approximately 70% emissions occurred in winter, when surface-soil freezing abated methanotrophy, enhancing methane escape from the talik. Remote sensing and numerical modeling indicate the potential for widespread upland talik formation across the pan-arctic Yedoma domain during the 21st and 22nd centuries. Contrary to current climate model predictions, these findings imply a positive and much larger permafrost-methane-climate feedback for upland Yedoma.

Abstract Background Cognitive assessment is a required component of the Medicare Annual Wellness Visit (AWV). In this prospective study, we evaluated acceptability and usefulness of a patient-reported outcome measure (the PROMIS® Cognitive Function Screener, or PRO-CS) to screen for cognitive impairment during the AWV. We compared two versions of the PRO-CS: Abilities and Concerns. Methods We developed PRO-CS Abilities and PRO-CS Concerns using items from the PROMIS Cognitive Function item banks. We partnered with a large health system in Pennsylvania to implement an electronic health record (EHR)-integrated version of the 4-item PRO-CS into their AWV workflow. PRO-CS Abilities was implemented in June 2022 and then replaced with PRO-CS Concerns in October 2022. We used EHR data to evaluate scores on Abilities versus Concerns and their association with patient characteristics. We gathered feedback from providers on experiences with the PRO-CS and conducted cognitive interviews with patients to evaluate their preferences for Abilities versus Concerns. Results Between June 2022 and January 2023, 3,088 patients completed PRO-CS Abilities and 2,614 patients completed PRO-CS Concerns. Mean T-scores for Abilities (54.8) were slightly higher (indicating better cognition) than for Concerns (52.6). 10% of scores on Abilities and 13% of scores on Concerns indicated concern for cognitive impairment (T-score

Understanding the future evolution of permafrost requires a better understanding of its climatological past. This requires permafrost models to efficiently simulate the thermal dynamics of permafrost over the past centuries to millennia, taking into account highly uncertain soil and snow properties. In this study, we present a computationally efficient numerical permafrost model which satisfactorily reproduces the current ground temperatures and active layer thicknesses of permafrost in the Arctic and their trends over recent centuries. The performed simulations provide insights into the evolution of permafrost since the 18th century and show that permafrost on the North American continent is subject to early degradation, while permafrost on the Eurasian continent is relatively stable over the investigated 300-year period. Permafrost warming since industrialization has occurred primarily in three “hotspot” regions in northeastern Canada, northern Alaska, and, to a lesser extent, western Siberia. We find that the extent of areas with a high probability (p3 m>0.9) of near-surface permafrost (i.e., 3 m of permafrost within the upper 10 m of the subsurface) has declined substantially since the early 19th century, with loss accelerating during the last 50 years. Our simulations further indicate that short-term climate cooling due to large volcanic eruptions in the Northern Hemisphere in some cases favors permafrost aggradation within the uppermost 10 m of the ground, but the effect only lasts for a relatively short period of a few decades. Despite some limitations, e.g., with respect to the representation of vegetation, the presented model shows great potential for further investigation of the climatological past of permafrost, especially in conjunction with paleoclimate modeling.

Climate change modifies the water and energy fluxes between the atmosphere and the surface in mountainous regions such as the Qinghai–Tibet Plateau (QTP), which has shown substantial hydrological changes over the last decades, including rapid lake level variations. The ground across the QTP hosts either permafrost or is seasonally frozen, and, in this environment, the ground thermal regime influences liquid water availability, evaporation and runoff. Consequently, climate-induced changes in the ground thermal regime may contribute to variations in lake levels, but the validity of this hypothesis has yet to be established. This study focuses on the cryo-hydrology of the catchment of Lake Paiku (southern Tibet) for the 1980–2019 period. We process ERA5 data with downscaling and clustering tools (TopoSCALE, TopoSUB) to account for the spatial variability of the climate in our forcing data (Fiddes and Gruber, 2012, 2014). We use a distributed setup of the CryoGrid community model (version 1.0) to quantify thermo-hydrological changes in the ground during this period. Forcing data and simulation outputs are validated with data from a weather station, surface temperature loggers and observations of lake level variations. Our lake budget reconstruction shows that the main water input to the lake is direct precipitation (310 mm yr−1), followed by glacier runoff (280 mm yr−1) and land runoff (180 mm yr−1). However, altogether these components do not offset evaporation (860 mm yr−1). Our results show that both seasonal frozen ground and permafrost have warmed (0.17 ∘C per decade 2 m deep), increasing the availability of liquid water in the ground and the duration of seasonal thaw. Correlations with annual values suggest that both phenomena promote evaporation and runoff. Yet, ground warming drives a strong increase in subsurface runoff so that the runoff/(evaporation + runoff) ratio increases over time. This increase likely contributed to stabilizing the lake level decrease after 2010. Summer evaporation is an important energy sink, and we find active-layer deepening only where evaporation is limited. The presence of permafrost is found to promote evaporation at the expense of runoff, consistently with recent studies suggesting that a shallow active layer maintains higher water contents close to the surface. However, this relationship seems to be climate dependent, and we show that a colder and wetter climate produces the opposite effect. Although the present study was performed at the catchment scale, we suggest that this ambivalent influence of permafrost may help to understand the contrasting lake level variations observed between the south and north of the QTP, opening new perspectives for future investigations.

The ground ice content in cold environments influences the permafrost thermal regime and the thaw trajectories in a warming climate, especially for soils containing excess ice. Despite their importance, the amount and distribution of ground ice are often unknown due to lacking field observations. Hence, modeling the thawing of ice-rich permafrost soils and associated thermokarst is challenging as ground ice content has to be prescribed in the model setup. In this study, we present a model scheme, capable of simulating segregated ice formation during a model spinup together with associated ground heave. It provides the option to add a constant sedimentation rate throughout the simulation. Besides ice segregation, it can represent thaw consolidation processes and ground subsidence under a warming climate. The computation is based on soil mechanical processes, soil hydrology by the Richards equation and soil freezing characteristics. The code is implemented in the CryoGrid community model (version 1.0), a modular land surface model for simulations of the ground thermal regime. The simulation of ice segregation and thaw consolidation with the new model scheme allows us to analyze the evolution of ground ice content in both space and time. To do so, we use climate data from two contrasting permafrost sites to run the simulations. Several influencing factors are identified, which control the formation and thaw of segregated ice. (i) Model results show that high temperature gradients in the soil as well as moist conditions support the formation of segregated ice. (ii) We find that ice segregation increases in fine-grained soils and that especially organic-rich sediments enhance the process. (iii) Applying external loads suppresses ice segregation and speeds up thaw consolidation. (iv) Sedimentation leads to a rise of the ground surface and the formation of an ice-enriched layer whose thickness increases with sedimentation time. We conclude that the new model scheme is a step forward to improve the description of ground ice distributions in permafrost models and can contribute towards the understanding of ice segregation and thaw consolidation in permafrost environments under changing climatic conditions.

Abstract Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Long-term measurements of permafrost temperatures do not provide a complete picture of the Arctic subsurface thermal regime. Regions with warmer permafrost often show little to no long-term change in ground temperature due to the uptake and release of latent heat during freezing and thawing. Thus, regions where the least warming is observed may also be the most vulnerable to permafrost degradation. Since direct measurements of ice and liquid water contents in the permafrost layer are not widely available, thermal modeling of the subsurface plays a crucial role in understanding how permafrost responds to changes in the local energy balance. In this work, we first analyze trends in observed air and permafrost temperatures at four sites within the continuous permafrost zone, where we find substantial variation in the apparent relationship between long-term changes in permafrost temperatures (0.02–0.16 K yr−1) and air temperature (0.09–0.11 K yr−1). We then apply recently developed Bayesian inversion methods to link observed changes in borehole temperatures to unobserved changes in latent heat and active layer thickness using a transient model of heat conduction with phase change. Our results suggest that the degree to which recent warming trends correlate with permafrost thaw depends strongly on both soil freezing characteristics and historical climatology. At the warmest site, a 9 m borehole near Ny-Ålesund, Svalbard, modeled active layer thickness increases by an average of 13 ± 1 cm K−1 rise in mean annual ground temperature. In stark contrast, modeled rates of thaw at one of the colder sites, a borehole on Samoylov Island in the Lena River delta, appear far less sensitive to temperature change, with a negligible effect of 1 ± 1 cm K−1. Although our study is limited to just four sites, the results urge caution in the interpretation and comparison of warming trends in Arctic boreholes, indicating significant uncertainty in their implications for the current and future thermal state of permafrost.

The Arctic is warming at an above-average rate, and small, shallow waterbodies such as ponds are vulnerable to this warming due to their low thermal inertia compared to larger lakes. While ponds are a relevant landscape-scale source of methane under the current climate, the response of pond methane emissions to warming is uncertain. We employ a new, process-based model for methane emissions from ponds (MeEP) to investigate the methane emission response of polygonal-tundra ponds in northeastern Siberia to warming. MeEP is the first dedicated model of pond methane emissions which differentiates between the three main pond types of the polygonal-tundra, ice-wedge, polygonal-center, and merged polygonal ponds and resolves the three main pathways of methane emissions – diffusion, ebullition, and plant-mediated transport. We perform idealized warming experiments, with increases in the mean annual temperature of 2.5, 5, and 7.5 ∘C on top of a historical simulation. The simulations reveal an approximately linear increase in emissions from ponds of 1.33 g CH4 yr−1 ∘C−1 m−2 in this temperature range. Under annual temperatures 5 ∘C above present temperatures, pond methane emissions are more than 3 times higher than now. Most of this emission increase is due to the additional substrate provided by the increased net productivity of the vascular plants. Furthermore, plant-mediated transport is the dominating pathway of methane emissions in all simulations. We conclude that vascular plants as a substrate source and efficient methane pathway should be included in future pan-Arctic assessments of pond methane emissions.

Abstract Subsea permafrost carbon pools below the Arctic shelf seas are a major unknown in the global carbon cycle. We combine a numerical model of sedimentation and permafrost evolution with simplified carbon turnover to estimate accumulation and microbial decomposition of organic matter on the pan-Arctic shelf over the past four glacial cycles. We find that Arctic shelf permafrost is a globally important long-term carbon sink storing 2822 (1518–4982) Pg OC, double the amount stored in lowland permafrost. Although currently thawing, prior microbial decomposition and organic matter aging limit decomposition rates to less than 48 Tg OC/yr (25–85) constraining emissions due to thaw and suggesting that the large permafrost shelf carbon pool is largely insensitive to thaw. We identify an urgent need to reduce uncertainty in rates of microbial decomposition of organic matter in cold and saline subaquatic environments. Large emissions of methane more likely derive from older and deeper sources than from organic matter in thawing permafrost.

Heat storage within the Earth system is a fundamental metric for understanding climate change. The current energy imbalance at the top of the atmosphere causes changes in energy storage within the ocean, the atmosphere, the cryosphere, and the continental landmasses. After the ocean, heat storage in land is the second largest term of the Earth heat inventory, affecting physical processes relevant to society and ecosystems, such as the stability of the soil carbon pool. Here, we present an update of the continental heat storage, combining for the first time the heat in the land subsurface, inland water bodies, and permafrost thawing. The continental landmasses stored 23.8 ± 2.0 × 1021 J during the period 1960–2020, but the distribution of heat among the three components is not homogeneous. The sensible diffusion of heat through the ground accounts for ∼90 % of the continental heat storage, with inland water bodies and permafrost degradation (i.e. latent heat) accounting for ∼0.7 % and ∼9 % of the continental heat, respectively. Although the inland water bodies and permafrost soils store less heat than the solid ground, we argue that their associated climate phenomena justify their monitoring and inclusion in the Earth heat inventory.

The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice–water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2, and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Different model components, characterized by their process representations and parameterizations, are realized as classes (i.e., objects) in CryoGrid. Standardized communication protocols between these classes ensure that they can be stacked vertically. For example, the CryoGrid community model features several classes with different complexity for the seasonal snow cover, which can be flexibly combined with a range of classes representing subsurface materials, each with their own set of process representations (e.g., soil with and without water balance, glacier ice). We present the CryoGrid architecture as well as the model physics and defining equations for the different model classes, focusing on one-dimensional model configurations which can also interact with external heat and water reservoirs. We illustrate the wide variety of simulation capabilities for a site on Svalbard, with point-scale permafrost simulations using, e.g., different soil freezing characteristics, drainage regimes, and snow representations, as well as simulations for glacier mass balance and a shallow water body. The CryoGrid community model is not intended as a static model framework but aims to provide developers with a flexible platform for efficient model development. In this study, we document both basic and advanced model functionalities to provide a baseline for the future development of novel cryosphere models.

The Earth climate system is out of energy balance, and heat has accumulated continuously over the past decades, warming the ocean, the land, the cryosphere, and the atmosphere. According to the Sixth Assessment Report by Working Group I of the Intergovernmental Panel on Climate Change, this planetary warming over multiple decades is human-driven and results in unprecedented and committed changes to the Earth system, with adverse impacts for ecosystems and human systems. The Earth heat inventory provides a measure of the Earth energy imbalance (EEI) and allows for quantifying how much heat has accumulated in the Earth system, as well as where the heat is stored. Here we show that the Earth system has continued to accumulate heat, with 381±61 ZJ accumulated from 1971 to 2020. This is equivalent to a heating rate (i.e., the EEI) of 0.48±0.1 W m−2. The majority, about 89 %, of this heat is stored in the ocean, followed by about 6 % on land, 1 % in the atmosphere, and about 4 % available for melting the cryosphere. Over the most recent period (2006–2020), the EEI amounts to 0.76±0.2 W m−2. The Earth energy imbalance is the most fundamental global climate indicator that the scientific community and the public can use as the measure of how well the world is doing in the task of bringing anthropogenic climate change under control. Moreover, this indicator is highly complementary to other established ones like global mean surface temperature as it represents a robust measure of the rate of climate change and its future commitment. We call for an implementation of the Earth energy imbalance into the Paris Agreement's Global Stocktake based on best available science. The Earth heat inventory in this study, updated from von Schuckmann et al. (2020), is underpinned by worldwide multidisciplinary collaboration and demonstrates the critical importance of concerted international efforts for climate change monitoring and community-based recommendations and we also call for urgently needed actions for enabling continuity, archiving, rescuing, and calibrating efforts to assure improved and long-term monitoring capacity of the global climate observing system. The data for the Earth heat inventory are publicly available, and more details are provided in Table 4.

Arctic river deltas define the interface between the terrestrial Arctic and the Arctic Ocean. They are the site of sediment, nutrient, and soil organic carbon discharge to the Arctic Ocean. Arctic deltas are unique globally because they are underlain by permafrost and acted on by river and sea ice, and many are surrounded by a broad shallow ramp. Such ramps may buffer the delta from waves, but as the climate warms and permafrost thaws, the evolution of Arctic deltas will likely take a different course, with implications for both the local scale and the wider Arctic Ocean. One important way to understand and predict the evolution of Arctic deltas is through numerical models. Here we present ArcDelRCM.jl, an improved reduced-complexity model (RCM) of arctic delta evolution based on the DeltaRCM-Arctic model (Lauzon et al., 2019), which we have reconstructed in Julia language using published information. Unlike previous models, ArcDelRCM.jl is able to replicate the ramp around the delta. We have found that the delayed breakup of the so-called “bottom-fast ice” (i.e. ice that is in direct contact with the bed of the channel or the sea, also known as “bed-fast ice”) on and around the deltas is ultimately responsible for the appearance of the ramp feature in our models. However, changes made to the modelling of permafrost erosion and the protective effects of bottom-fast ice are also important contributors. Graph analyses of the delta network performed on ensemble runs show that deltas produced by ArcDelRCM.jl have more interconnected channels and contain less abandoned subnetworks. This may suggest a more even feeding of sediments to all sections of the delta shoreline, supporting ramp growth. Moreover, we showed that the morphodynamic processes during the summer months remain active enough to contribute significant sediment input to the growth and evolution of Arctic deltas and thus should not be neglected in simulations gauging the multi-year evolution of delta features. Finally, we tested a strong climate-warming scenario on the simulated deltas of ArcDelRCM.jl, with temperature, discharge, and ice conditions consistent with RCP7–8.5. We found that the ramp features degrade on the timescale of centuries and effectively disappear in under 1 millennium. Ocean processes, which are not included in these models, may further shorten the timescale. With the degradation of the ramps, any dissipative effects on wave energy they offered would also decrease. This could expose the sub-aerial parts of the deltas to increased coastal erosion, thus impacting permafrost degradation, nutrients, and carbon releases.

Background. A portion of the Functional Assessment of Cancer Therapy-Lung (FACT-L) instrument contributed to a previously published utility index, the FACT Lung Utility Index or FACT-LUI. Six FACT items representing lung cancer quality of life covered fatigue, pain, dyspnea, cough, anxiety, and depression. Two FACT items had been previously combined by the index authors into one for nausea and/or appetite loss, resulting in 7 final domains. Methods. The objective was to perform measurement invariance testing within a confirmatory factor analysis (CFA) framework to support the feasibility of using the FACT-LUI for non–preference-based psychometric applications. The original index patients comprised group 1, and similar FACT patient data ( n = 249) from another published study comprised group 2. One 2-factor model and two 1-factor CFA models were evaluated to assess measurement invariance across groups, using varying degrees of item parceling and a small number of residual covariances, all justified by the literature. Results. The 1-factor models were most optimal. A 1-factor model with 1 pair of items parceled showed invariance to the partial scalar level using usual fit criteria across groups, requiring 2 unconstrained intercepts. A 1-factor model with 3 pairs of justified parcels showed full configural, metric, and scalar invariance across groups. Conclusions. The FACT-LUI items fit a partially to fully invariant 1-factor model, suggesting feasibility for non–preference-based applications. Implications. Results suggest useful incorporation of the FACT-LUI into clinical trials with no substantial increased respondent burden, allowing preference-based and other psychometric applications from the same index items. Highlights This work suggests that in addition to being originally designed for use as a utility index, the 7 FACT-LUI items together also fit simple CFA and measurement invariance models. This less expected result indicates that these items as a group are also potentially useful in non–preference-based applications. Clinical trials can make for challenging decisions concerning which patient-reported outcome measures to include without being burdensome. However, the literature suggests a need for improved reporting of quality of life in lung cancer in particular as well as cancer in general. Inclusion of more disease-specific items such as the FACT-LUI may allow for information gathering of both preference-based and non–preference-based data with less demand on patients, similar to what has been done with some generic instruments.

Pancreatic cancer remains a formidable challenge due to limited treatment options and its aggressive nature. In recent years, the naturally occurring anticancer compound juglone has emerged as a potential therapeutic candidate, showing promising results in inhibiting tumor growth and inducing cancer cell apoptosis. However, concerns over its toxicity have hampered juglone’s clinical application. To address this issue, we have explored the use of polymeric micelles as a delivery system for juglone in pancreatic cancer treatment. These micelles, formulated using Poloxamer 407 and D-α-Tocopherol polyethylene glycol 1000 succinate, offer an innovative solution to enhance juglone’s therapeutic potential while minimizing toxicity. In-vitro studies have demonstrated that micelle-formulated juglone (JM) effectively decreases proliferation and migration and increases apoptosis in pancreatic cancer cell lines. Importantly, in-vivo, JM exhibited no toxicity, allowing for increased dosing frequency compared to free drug administration. In mice, JM significantly reduced tumor growth in subcutaneous xenograft and orthotopic pancreatic cancer models. Beyond its direct antitumor effects, JM treatment also influenced the tumor microenvironment. In immunocompetent mice, JM increased immune cell infiltration and decreased stromal deposition and activation markers, suggesting an immunomodulatory role. To understand JM’s mechanism of action, we conducted RNA sequencing and subsequent differential expression analysis on tumors that were treated with JM. The administration of JM treatment reduced the expression levels of the oncogenic protein MYC, thereby emphasizing its potential as a focused, therapeutic intervention. In conclusion, the polymeric micelles-mediated delivery of juglone holds excellent promise in pancreatic cancer therapy. This approach offers improved drug delivery, reduced toxicity, and enhanced therapeutic efficacy.

Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost–vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen–evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics.

The study of phase formation in the U-Te-O systems with mono and divalent cations under high-temperature high-pressure (HT/HP) conditions has resulted in four new inorganic compounds: K2 [(UO2) (Te2O7)], Mg [(UO2) (TeO3)2], Sr [(UO2) (TeO3)2] and Sr [(UO2) (TeO5)]. Tellurium occurs as TeIV, TeV, and TeVI in these phases which demonstrate the high chemical flexibility of the system. Uranium VI) adopts a variety of coordinations, namely, UO6 in K2 [(UO2) (Te2O7), UO7 in Mg [(UO2) (TeO3)2] and Sr [(UO2) (TeO3)2], and UO8 in Sr [(UO2) (TeO5)]. The structure of K2 [(UO2) (Te2O7)] is featured with one dimensional (1D) [Te2O7]4- chains along the c-axis. The Te2O7 chains are further linked by UO6 polyhedra, forming the 3D [(UO2) (Te2O7)]2- anionic frameworks. In Mg [(UO2) (TeO3)2], TeO4 disphenoids share common corners with each other resulting in infinite 1D chains of [(TeO3)2]4- propagating along the a-axis. These chains link the uranyl bipyramids by edge sharing along two edges of the disphenoids, resulting in the 2D layered structure of [(UO2) (Te2O6)]2-. The structure of Sr [(UO2) (TeO3)2] is based on 1D chains of [(UO2) (TeO3)2]∞2− propagating into the c-axis. These chains are formed by edge-sharing uranyl bipyramids which are additionally fused together by two TeO4 disphenoids, which also share two edges. The 3D framework structure of Sr [(UO2) (TeO5)] is composed of 1D [TeO5]4− chains sharing edges with UO7 bipyramids. Three tunnels based on 6-Membered rings (MRs) are propagating along [001] [010] and [100] directions. The HT/HP synthetic conditions for the preparation of single crystalline samples and their structural aspects are discussed in this work.

At the early days of organ transplantation before the diagnosis of brain death came in use only organs of non-heart-beating persons - who were the first donors after cardiac death (DCD) - could be taken for organ transplantation beside the living donors.Organs from the first brain-dead donor were transplanted in 1963 in Belgium, five years later the famous Harvard Committee criteria were published. Following that in the Western world DCD was not used for organ transplantation, just in exceptional cases for several decades.However, organ scarceness lead the way back to the idea of DCD. The original Maastricht classification discerns uncontrolled and controlled DCD in 4 categories from dead upon arrival through unsuccessful resuscitation attempt and awaiting cardiac death to cardiac arrest of a brain-dead person.The time between the cessation of the of the circulation and the perfusion of the organ with the specific storage fluid is crucial for the possible use of the organs as transplants.The recent studies explore the possibilities of the reconditioning of the organs to allow more and more of them to use for transplantation. The applicability is mostly needed in DCD cases. It is still open whether cold or warm perfusion, static or machine perfusion in continuous or pulsatile form would be the best for which organ.Despite the evidence of the usefulness of this donor category, DCD is still not used universally. For example in Europe only one-third of the countries use DCD, the main reason is the underdevelopment of the infrastructural criteria in some of the countries, and the unsolved ethical and organizational challenges in others.

In this study we assessed the utility of self-reported cognitive function using two PROMIS ® Cognitive Function (PROMIS-CF) items in an observational clinical sample of patients aged 65 and older ( n = 16,249) at a large health system. We evaluated the association of PROMIS-CF scores with clinical characteristics and Montreal Cognitive Assessment (MoCA) scores, and we used logistic regression to examine predictors of 1-year decline in PROMIS-CF scores among patients with available data. PROMIS-CF scores were associated with clinical characteristics as hypothesized, with lower (more impaired) scores for patients with cognitive impairment (CI) diagnoses, multiple comorbidities, and those taking cognitive enhancing or interfering medications. PROMIS-CF scores were also positively associated with MoCA scores. Predictors of 1-year decline in PROMIS-CF scores included CI diagnoses, use of cognitive enhancing medications, higher depression scores, and lower social role function. Our findings suggest potential utility of PROMIS-CF items in a brief patient-administered screening tool for CI.

Detection of micropollutants (MPs) in wastewater effluents using traditional toxicity tests or chemical analysis with discrete samples is challenging due to concentration dynamics. This study evaluates a continuous monitoring approach for detecting MPs in wastewater effluents using a combination of biological early warning systems (BEWS). Three BEWS with Chlorella vulgaris , Daphnia magna , and Gammarus pulex were operated in parallel in a full-scale municipal wastewater treatment plant. Concentrations of MPs were monitored by simultaneous online chemical analysis using high performance liquid chromatography-high resolution mass spectrometry (MS2Field). Over 5 weeks, behavioral changes observed in the BEWS occasionally exceeded acute toxicity thresholds, triggering alarms. These changes were related to MPs identified by the MS2Field, to abiotic factors, or to operational parameters of the BEWS. For one toxic event, behavioral responses were linked to a pesticide, not authorized in Switzerland, at concentrations close to literature EC 50 values. Verification tests confirmed that the pesticide in the effluent was the most likely cause for the organism response. The study demonstrates the potential of BEWS as a stand-alone technique for detecting contamination peaks in wastewater, and identifies key limitations and critical factors that need to be addressed to optimize the use of BEWS in wastewater monitoring.

Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Introduction: Mechanical heart valve (MHV) replacement requires long-life anticoagulation due to the risk of Prosthetic Valve Dysfunction (PVD) and cardioembolism., Methods: We report data from a prospective observational study conducted on MHV patients in the Khartoum Salam Centre for Cardiac Surgery built by 'Emergency,' an Italian Non-Governmental Organization, to evaluate the occurrence of PVD and associated risk factors., Results: We prospectively followed 3647 patients, and 38 patients (rate 1.04 × 100 pt-years) had PVD during follow-up. The time in therapeutic range (TTR) among patients without PVD was 53 % (IQR 37-67), and it was 43 % (IQR 19-58) among patients with PVD (p = 0.04). Twenty-three over 38 patients (60.5 %) were symptomatic, 18 (47.4 %) had obstructive valvular stenosis, 24 patients (63.2 %) had INR <2.0 at diagnosis, and 21 patients (55.3 %) had been off warfarin for a long time: 3 patients for 1 week, 1 patient for 2 weeks, and 17 patients for >4 weeks (6 patients were off warfarin from 3 to 12 months). Ten were uncompliant to treatment, and 8 were pregnant women. Ten patients (26.3 %) with PVD had had a previous episode of PVD, and 14 patients (36.8 %) had 2 or more associated risk factors. Only in 6 cases were no associate risk factors found., Conclusions: Among MHV patients on warfarin treatment with a sub-optimal quality of anticoagulation, the rate of PVD is 1.04 % pt-years, and the most frequent associated risk factor for PVD occurrence is warfarin withdrawal lasting more than one week., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Objective: Studies suggest that men who undergo assisted reproductive technologies (ART) may have a higher risk of cardiovascular disease; however, limited data on this matter is available. This observational pilot study aimed to investigate the overall vascular health of fathers with history of intracytoplasmic sperm injection (ICSI) compared to fathers whose partners conceived spontaneously., Methods: Diet quality, physical activity, sedentary behavior as well as overall vascular function including the assessment of pulse wave analysis, intima-media thickness (cIMT), arterial stiffness of the common carotid artery (CCA) and blood lipids, were evaluated., Results: A total of 34 fathers with history of ICSI and 29 controls (48.49 [46.32 - 57.09] years vs. 47.19 [40.62 - 55.18] years, p  = 0.061) were included. After adjusting for age, no significantly increased cardiovascular risk was detected regarding vascular function., Conclusions: The results suggest an unaltered cardiovascular risk profile in fathers with history of ICSI. In the future, prospective multicenter studies are required to validate these preliminary results.

Organizations, researchers, and software increasingly use automatic speech recognition (ASR) to transcribe speech to text. However, ASR can be less accurate for (i.e., biased against) certain demographic subgroups. This is concerning, given that the machine-learning (ML) models used to automatically score video interviews use ASR transcriptions of interviewee responses as inputs. To address these concerns, we investigate the extent of ASR bias and its effects in automatically scored interviews. Specifically, we compare the accuracy of ASR transcription for English as a second language (ESL) versus non-ESL interviewees, people of color (and Black interviewees separately) versus White interviewees, and male versus female interviewees. Then, we test whether ASR bias causes bias in ML model scores-both in terms of differential convergent correlations (i.e., subgroup differences in correlations between observed and ML scores) and differential means (i.e., shifts in subgroup differences from observed to ML scores). To do so, we apply one human and four ASR transcription methods to two samples of mock video interviews ( N s = 1,014 and 414), and then we train and test models using these different transcripts to score multiple constructs. We observed significant bias in the commercial ASR services across nearly all comparisons, with the magnitude of bias differing across the ASR services. However, the transcription bias did not translate into meaningful measurement bias for the ML interview scores-whether in terms of differential convergent correlations or means. We discuss what these results mean for the nature of bias, fairness, and validity of ML models for scoring verbal open-ended responses. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

We present a new, to the best of our knowledge, method to simulate diffraction images accounting for both coherent and incoherent effects, based on the Wigner distribution function of the exit wave. This permits the simulation of wave and particle effects simultaneously and simulates images photon by photon. It is motivated by artifacts observed in x ray phase-contrast images after phase retrieval, present as noise in the low spatial frequency range, which can make analysis of such images challenging. Classical simulations have so far not been able to reproduce these artifacts. We hypothesize that these artifacts are due to incoherent scatter present in the images, hence the interest in developing a simulator that permits the simulation of both diffraction and incoherent scattering. Here, we give a first demonstration of the method by simulating the Gaussian double-slit experiment. We demonstrate the capability of combining diffraction and incoherent scattering, as well as simulating images for any propagation distance.

An increasing number of children are conceived by assisted reproductive technologies (ART). Several studies indicated vascular alterations in ART children. However, limited data is available within the adult ART population. Therefore, this study investigated the overall vascular health of young ART adults in comparison to spontaneously conceived peers. In total, 16 ART subjects and 22 spontaneously conceived peers (22.06 ± 2.21 years vs. 22.00 ± 2.14 years, p = 0.194) were enrolled for the assessment of endothelial function, brachial blood pressure, central blood pressure, pulse wave velocity, carotid intima-media thickness, and blood lipids. No significant differences in vascular function were detected between the in vitro fertilization subgroup (n = 9), the intracytoplasmic sperm injection subgroup (n = 7) and spontaneously conceived peers. This pilot study suggests an unimpaired vascular function in young ART adults. In the future, multi-centric studies with a greater sample size are required to confirm the results of the current study and enable precise cardiovascular risk stratification of the adult ART population., (© 2022. The Author(s).)

Landscape drying associated with permafrost thaw is expected to enhance microbial methane oxidation in arctic soils. Here we show that ice-rich, Yedoma permafrost deposits, comprising a disproportionately large fraction of pan-arctic soil carbon, present an alternate trajectory. Field and laboratory observations indicate that talik (perennially thawed soils in permafrost) development in unsaturated Yedoma uplands leads to unexpectedly large methane emissions (35-78 mg m -2  d -1 summer, 150-180 mg m -2  d -1 winter). Upland Yedoma talik emissions were nearly three times higher annually than northern-wetland emissions on an areal basis. Approximately 70% emissions occurred in winter, when surface-soil freezing abated methanotrophy, enhancing methane escape from the talik. Remote sensing and numerical modeling indicate the potential for widespread upland talik formation across the pan-arctic Yedoma domain during the 21 st and 22 nd centuries. Contrary to current climate model predictions, these findings imply a positive and much larger permafrost-methane-climate feedback for upland Yedoma., (© 2024. The Author(s).)