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The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

Context: The rice-wheat (RW) system, spanning 13.5 million hectares in South Asia, is crucial for food security and livelihoods. However, intensive conventional tillage-based practices have harmed soil and environmental health, decreased productivity trends and increased greenhouse gas emissions. Objective: This study aims to develop resilient, climate-smart cropping systems within the RW system, focusing on soil and crop productivity, economic viability, and reduced greenhouse gas (GHG) emissions. Methods: Over eight years, the study evaluated diverse parameters compared to farmer practices (FP) in seven scenarios (Sc), including one representing FP (Sc1) and six based on conservation agriculture (CA) principles. The study assessed system crop productivity, economic returns, soil quality (organic carbon; OC, nitrogen; N, phosphorus; P, potassium; K contents, bulk density; BD, soil aggregation, infiltration rates, microbial counts, and earthworm density), and GHG emissions. Results: CA-based scenarios (Sc2 to Sc7) showed improved soil quality, lower bulk density, enhanced soil aggregation, and increased infiltration rates compared to Sc1. In the 0–15 cm layer, surface soil organic carbon (OC) and C stock were 63.7 % and 49.6 % higher, respectively, in CA-based scenarios. Additionally, available N, P and K contents in the surface layer increased by 10.2 %, 28.6 %, and 21.8 % under CA-based scenarios. Adoption of CA in intensified maize-based scenarios (Sc4 and Sc5) led to the increased system and economic yields, higher soil quality index (SQI), reduced GHG emissions and increased C stock compared to Sc1. Implications: The study highlights that Conservation Agriculture (CA) practices and diversified crop rotations can address issues like falling crop productivity, reduced economic returns, soil degradation, and increasing environmental impacts in northwestern India's traditional rice-wheat system. However, widespread adoption requires government policies, including C credit payments and guaranteed markets with supportive pricing.

Transformative change is needed to align common small‐scale ecological restoration approaches with expectations to restore millions of hectares of degraded lands globally. Currently, most restoration projects target small areas using costly manual methods that cannot be scaled up to meet global commitments. We propose that a judicious integration of agricultural practices into ecological restoration offers an opportunity to address this issue. This transformative process relies on three sequential and interconnected steps: (1) ensure that sufficient land is truly available for restoration; (2) compensate for the loss of agricultural production, income, or land value to encourage landholders to opt for restoration; and (3) develop scalable, affordable, and effective methods for restoring native ecosystems across the pledged hundreds of millions of hectares to deliver benefits to both nature and people. Large‐scale terrestrial restoration will require incorporating agronomic practices into the restoration toolbox to go beyond vague, ambitious promises and wishful thinking.

Applied nucleation and other spatially patterned restoration methods are promising approaches for scaling up projects to meet ambitious international restoration commitments in an ecologically and economically sound manner. Much of the corresponding literature to date, however, has centered around theoretical discussions and small‐scale studies that are largely divorced from constraints faced by restoration practitioners. We briefly review recent academic literature about applied nucleation and other spatially patterned restoration methods and discuss practical challenges to their implementation. We offer several recommendations to move spatially patterned restoration from an academic conversation to scalable application, including: (1) comparing different planting designs and natural regeneration within the same system at an appropriate scale; (2) monitoring ecological outcomes throughout the restored area over sufficient time to evaluate recovery; (3) quantifying costs and documenting other logistical constraints to implementation; and (4) exploring methods for using unplanted areas to provide benefits to landholders until planted vegetation establishes.

Aim: Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species?. Location: Global. Time period: 1990–2017. Major taxa studied: Trees. Methods: We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results: Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation. Main conclusions: By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.

Machine learning has been found to be ubiquitously useful across many industries, presenting an opportunity to improve radiation detection performance using data-driven algorithms. Improved detector resolution can aid in the detection, identification, and quantification of radionuclides. In this work, a novel, data-driven, unsupervised learning approach is developed to improve detector spectral characteristics by learning, and subsequently rejecting, poorly performing regions of the pixelated detector. Feature engineering is used to fit individual characteristic photo peaks to a Doniach lineshape with a linear background model. Then, principal component analysis is used to learn a lower-dimension latent space representation of each photo peak where the pixels are clustered, and subsequently ranked, based on the cluster mean distance to an optimal point. Pixels within the worst cluster(s) are rejected to improve the full-width at half-maximum (FWHM) by 10% to 15% (relative to the bulk detector) at 50% net efficiency when applied to training data obtained from measurements of a 100 μCi 154Eu source using a H3D M400i pixelated cadmium zinc telluride detector. These results compare well with, but do not outperform, a greedy algorithm that accumulates pixels in order of FWHM from lowest to highest used as a benchmark. In the future, this approach can be extended to include the detector energy and angular response. Finally, the model is applied to newly seen natural and enriched uranium spectra relevant for nuclear safeguards applications.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

Gitishree Das,1 Han-Seung Shin,2 Kyung-Jik Lim,2 Jayanta Kumar Patra1 1Research Institute of Integrative Life Sciences, Dongguk University-Seoul, Goyangsi, Republic of Korea; 2Department of Food Science & Biotechnology, Dongguk University-Seoul, Goyangsi, Republic of KoreaCorrespondence: Jayanta Kumar Patra, Research Institute of Integrative Life Sciences, Dongguk University-Seoul, Goyangsi, 10326, Republic of Korea, Email jkpatra@dongguk.eduBackground: Bio-based synthesis of metallic nanoparticles has garnered much attention in recent times owing to their non-toxic, environmentally friendly, and cost-effective nature.Methods: In this study, gold nanoparticles (S4-GoNPs) were synthesized by a simple and environmentally friendly technique using an aqueous extract of jamun leaves (JLE) as an effective capping, stabilizer, and reducing agent. JLE was screened for the presence of phytochemicals followed by synthesis, characterization, and evaluation of their antibacterial, antidiabetic, antioxidant, and photocatalytic degradation potentials using standard established procedures.Results: The phytochemical profile of JLE was found to be rich in flavonoids, tannins, terpenoid phenols, anthraquinones, and cardiac glycosides. Its GC-MS analysis revealed the presence of compounds majorly of them as the (1R)-2,6,6-Trimethylbicyclo[3.1.1]hept-2-ene (5.141%), 2(10)-pinene (4.119%), α-cyclopene (5.274%) α,α-muurolene (7.525%), naphthalene, 1,2,3,4,4a,5,6,8a-octahydro-7-methyl-4-methylene-1-(1-methylethyl)-(1.alpha.,4a.beta.,8a.alpha) (8.470%), delta-cadinene (23.246), α-guajene (3.451%), and gamma-muurolene (4.379%). The visual morphology and UV–Vis spectral surface plasmon resonance at 538 nm confirmed the successful synthesis of S4-GoNPs. The average particle size was determined as 120.5 nm with Pdi = 0.152, and − 27.6 mV zeta potential. Using the Scherrer equation, the average crystallite size was calculated as 35.69 nm. S4-GoNPs displayed significant antidiabetic properties, with 40.67% of α-amylase and 91.33% of α-glucosidase inhibition activity. It also exhibited promising antioxidant potential in terms of the DPPH (91.56%) ABTS (76.59%) scavenging. It displayed 31.04% tyrosinase inhibition at 0.1 mg/mL. Moreover, it also demonstrated encouraging antibacterial effects with zones of inhibition ranging from 11.02 – 14.12 mm as compared to 10.55– 16.24 mm by the reference streptomycin (at 0.01 mg/disc). In addition, S4-GoNPs also showed potential for the photocatalytic degradation of the industrial dye, methylene blue.Conclusion: In conclusion, these results suggest the promising applicability of green-synthesized S4-GoNPs in various sectors, including the biomedical, cosmetic, food, and environmental waste management industries.Keywords: gold nanoparticles, antidiabetic, antioxidant, antibacterial, tyrosinase inhibition

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

The nuclear dependence of the inclusive inelastic electron scattering cross section (the EMC effect) has been measured for the first time in B10 and B11. Previous measurements of the EMC effect in A≤12 nuclei showed an unexpected nuclear dependence; B10 and B11 were measured to explore the EMC effect in this region in more detail. Results are presented for Be9, B10, B11, and C12 at an incident beam energy of 10.6 GeV. The EMC effect in the boron isotopes was found to be similar to that for Be9 and C12, yielding almost no nuclear dependence in the EMC effect in the range A=4-12. This represents important new data supporting the hypothesis that the EMC effect depends primarily on the local nuclear environment due to the cluster structure of these nuclei.

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions.

Reactor neutrino experiments play a crucial role in advancing our knowledge of neutrinos. In this Letter, the evolution of the flux and spectrum as a function of the reactor isotopic content is reported in terms of the inverse-beta-decay yield at Daya Bay with 1958 days of data and improved systematic uncertainties. These measurements are compared with two signature model predictions: the Huber-Mueller model based on the conversion method and the SM2018 model based on the summation method. The measured average flux and spectrum, as well as the flux evolution with the ^{239}Pu isotopic fraction, are inconsistent with the predictions of the Huber-Mueller model. In contrast, the SM2018 model is shown to agree with the average flux and its evolution but fails to describe the energy spectrum. Altering the predicted inverse-beta-decay spectrum from ^{239}Pu fission does not improve the agreement with the measurement for either model. The models can be brought into better agreement with the measurements if either the predicted spectrum due to ^{235}U fission is changed or the predicted ^{235}U, ^{238}U, ^{239}Pu, and ^{241}Pu spectra are changed in equal measure.

We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3}  eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3}  eV^{2} for the inverted mass ordering.

Wang Q, Li WN, Otkur W, Cui Y, Chen HS. J Inflamm Res. 2024:17:5543—5553. The authors have advised the affiliation list on page 5543 is incorrect. The correct author list and affiliations are as follows. Qi Wang1,2,*, Wen-Na Li3,*, Wuxiyar Otkur4, Yu Cui2, Hui-Sheng Chen1,2 1Graduate School, Dalian Medical University, Dalian, People’s Republic of China; 2Department of Neurology, General Hospital of Northern Theater Command, Shenyang, 110016, People’s Republic of China; 3Department of Neurology, Tangshan Central Hospital, Tangshan, People’s Republic of China; 4School of Life Science and Biopharmaceutics, Shenyang Pharmaceutical University, Shenyang, 110016, People’s Republic of China *These authors contributed equally to this work The authors apologize for the error.

The Simple Standard for Ontological Mappings (SSSOM) was first published in December 2021 (v. 0.9). After a number of revisions prompted by community feedback, we have published version 0.15.0 in July 2023. Here we report on the progress made since August 2022, in particular changes to tooling, data model and summary of ongoing standardisation efforts.

Accumulating evidence suggests amyloid and tau-related neurodegeneration may play a role in development of late-onset epilepsy of unknown etiology (LOEU). In this article, we review recent evidence that epilepsy may be an initial manifestation of an amyloidopathy or tauopathy that precedes development of Alzheimer's disease (AD). Patients with LOEU demonstrate an increased risk of cognitive decline, and patients with AD have increased prevalence of preceding epilepsy. Moreover, investigations of LOEU that use CSF biomarkers and imaging techniques have identified preclinical neurodegeneration with evidence of amyloid and tau deposition. Overall, findings to date suggest a relationship between acquired, non-lesional late-onset epilepsy and amyloid and tau-related neurodegeneration, which supports that preclinical or prodromal AD is a distinct etiology of late-onset epilepsy. We propose criteria for assessing elevated risk of developing dementia in patients with late-onset epilepsy utilizing clinical features, available imaging techniques, and biomarker measurements. Further research is needed to validate these criteria and assess optimal treatment strategies for patients with probable epileptic preclinical AD and epileptic prodromal AD.

Leptomeningeal disease (LMD) is a devastating complication of metastatic breast cancer (MBC). In this non-therapeutic study, we enrolled 12 patients with MBC and known or suspected LMD who were undergoing a lumbar puncture as part of clinical care and collected extra cerebrospinal fluid (CSF) and a paired blood sample from each patient at a single time point. Of the 12 patients, 7 patients are confirmed to have LMD based on positive cytology and/or convincing MRI imaging (LMDpos), and 5 patients are deemed not to have LMD based on similar criteria (LMDneg). Using high-dimensional, multiplexed flow cytometry, we profile and compare the CSF and peripheral blood mononuclear cell (PBMCs) immune populations between patients with LMD and those without. Patients with LMD observe a lower overall frequency of CD45+ cells (29.51% vs. 51.12%, p

Background and aimGemcitabine remains the cornerstone of pancreatic cancer treatment, despite exhibiting a modest effect on patient survival due to the development of drug resistance. Nuvastatic™ polymolecular botanical drug Orthosiphon stamineus (O. stamineus) is a folklore Asian herbal medicine that is used for the treatment of a variety of ailments. However, little is known about the mechanism of actions of the Nuvastatic™ polymolecular botanical drug of O. stamineus as a complementary therapy in resistant pancreatic cancer. It is postulated that the proprietary O. stamineus extract formulation (ID: C5EOSEW5050ESA) in Nuvastatic™ may sensitise resistant pancreatic cancer cells to gemcitabine. This study was conducted to assess the cytotoxic activity and synergistic effects of C5EOSEW5050ESA in gemcitabine-resistant pancreatic cancer cells.Experimental procedureThe effects of C5EOSEW5050ESA treatment on cell viability, multidrug-resistant genes, epithelial-mesenchymal transition, cellular senescence, cell death, and Notch signalling pathway were evaluated in gemcitabine-resistant Panc-1 cells.Results and conclusionC5EOSEW5050ESA sensitised gemcitabine resistant cells towards C5EOSEW5050ESA-gemcitabine combination treatment by reducing the expression of multidrug-resistant genes and epithelial-mesenchymal transition markers in gemcitabine-resistant cells compared to the control group, possibly through the inhibition of Notch signalling. This study provides valuable insight into using C5EOSEW5050ESA as a potential complementary treatment for resistant pancreatic cancer.

Abstract: The central motivation to restore ecosystems at a planetary scale has been to reverse degradation and provide multiple environmental benefits, but key global players like governments may be more interested in social outcomes from undertaking restoration, such as job creation. Assessing the job opportunities stemming from ongoing restoration programmes can leverage additional investments for their implementation and support their long‐term maintenance. Here, we aimed to understand and quantify current and potential ecosystem restoration jobs in Brazil, based on a widely distributed online survey performed in 2020 and led by the main restoration networks in the country. We explored the structure, job distribution and outputs of the national restoration supply chain. At the beginning of 2020, 4713 temporary and 3510 permanent jobs were created, nearly 60% of which were generated by organizations specialized in restoration, mainly from the non‐profit (48%) and private (37%) sectors. Restoration jobs were concentrated in organizations working in one (58%) or two (28%) biomes, and the vast majority were in the Atlantic Forest (85%). Similarly, most restoration jobs were concentrated in the southeast region (61%), with one‐third in the state of São Paulo. This geographical distribution was more strongly associated with the states' GDP than with the legal deficit of native vegetation area. Nearly 20% of the restoration jobs were terminated during the COVID‐19 pandemic in 2020. We estimate that restoration activities can generate 0.42 jobs per hectare undergoing restoration, which could potentially create 1.0–2.5 million direct jobs through the implementation of Brazil's target of restoring 12 million hectares. We conclude by reinforcing the value of ecosystem restoration in promoting economic development and job creation, which can be crucial to promote countries' effective engagement in the UN Decade on Ecosystem Restoration. We also highlight the critical role of grassroots organizations to maximize restoration opportunities for socioeconomic development during the post‐pandemic economic recovery. Read the free Plain Language Summary for this article on the Journal blog.

PurposeEvidence supports the role of prescribed exercise for cancer survivors, yet few are advised to exercise by a healthcare practitioner (HCP). We sought to investigate the gap between HCPs' knowledge and practice from an international perspective.MethodsAn online questionnaire was administered to HCPs working in cancer care between February 2020 and February 2021. The questionnaire assessed knowledge, beliefs, and practices regarding exercise counselling and referral of cancer survivors to exercise programs.ResultsThe questionnaire was completed by 375 participants classified as medical practitioners (42%), nurses (28%), exercise specialists (14%), and non-exercise allied health practitioners (16%). Between 35 and 50% of participants self-reported poor knowledge of when, how, and which cancer survivors to refer to exercise programs or professionals, and how to counsel based on exercise guidelines. Commonly reported barriers to exercise counselling were safety concerns, time constraints, cancer survivors being told to rest by friends and family, and not knowing how to screen people for suitability to exercise (40-48%). Multivariable logistic regression models including age, gender, practitioner group, leisure-time physical activity, and recall of guidelines found significant effects for providing specific exercise advice (χ2(7) = 117.31, p

All-solid-state batteries have recently gained considerable attention due to their potential improvements in safety, energy density, and cycle-life compared to conventional liquid electrolyte batteries. Sodium all-solid-state batteries also offer the potential to eliminate costly materials containing lithium, nickel, and cobalt, making them ideal for emerging grid energy storage applications. However, significant work is required to understand the persisting limitations and long-term cyclability of Na all-solid-state-based batteries. In this work, we demonstrate the importance of careful solid electrolyte selection for use against an alloy anode in Na all-solid-state batteries. Three emerging solid electrolyte material classes were chosen for this study: the chloride Na2.25Y0.25Zr0.75Cl6, sulfide Na3PS4, and borohydride Na2(B10H10)0.5(B12H12)0.5. Focused ion beam scanning electron microscopy (FIB-SEM) imaging, X-ray photoelectron spectroscopy (XPS), and electrochemical impedance spectroscopy (EIS) were utilized to characterize the evolution of the anode-electrolyte interface upon electrochemical cycling. The obtained results revealed that the interface stability is determined by both the intrinsic electrochemical stability of the solid electrolyte and the passivating properties of the formed interfacial products. With appropriate material selection for stability at the respective anode and cathode interfaces, stable cycling performance can be achieved for Na all-solid-state batteries.

ContextSARS-CoV-2 infects cells via the angiotensin converting enzyme 2 (ACE2) receptor, whose downstream effects "counterbalance" the classical renin angiotensin aldosterone system (RAAS).ObjectiveWe aimed to determine to what extent circulating RAAS biomarker levels differ in persons with and without COVID-19 throughout the disease course.MethodsWe measured classical (renin, aldosterone, aldosterone/renin ratio [ARR], Ang2, ACE activity) and nonclassical (ACE2, Ang1,7) RAAS biomarkers in hospitalized COVID-19 patients vs SARS-CoV-2 negative controls. We compared biomarker levels in cases with contemporaneous samples from control patients with upper respiratory symptoms and a negative SARS-CoV-2 PCR test. To assess RAAS biomarker changes during the course of COVID-19 hospitalization, we studied cases at 2 different times points ∼ 12 days apart. We employed age- and sex-adjusted generalized linear models and paired/unpaired t tests.ResultsMean age was 51 years for both cases (31% women) and controls (50% women). ARR was higher in the first sample among hospitalized COVID-19 patients vs controls (P = 0.02). ACE activity was lower among cases at their first sample vs controls (P =

Extensive evidence shows that regional (gamma) diversity is often lower across restored landscapes than in reference landscapes, in part due to common restoration practices that favor widespread species through selection of easily-grown species with high survival and propagation practices that reduce genetic diversity. We discuss approaches to counteract biotic homogenization, such as reintroducing species that are adapted to localized habitat conditions and are unlikely to colonize naturally; periodically reintroducing propagules from remnant populations to increase genetic diversity; and reintroducing higher trophic level fauna to restore interaction networks and processes that promote habitat heterogeneity. Several policy changes would also increase regional diversity; these include regional coordination amongst restoration groups, financial incentives to organizations producing conservation-valued species, and experimental designations for rare species introductions.

IntroductionThe antibody-drug conjugate trastuzumab deruxtecan (T-DXd) targets human epidermal growth factor receptor 2 (HER2) and has been evaluated in patients with HER2-positive unresectable/metastatic breast cancer in the phase II DESTINY-Breast01 trial (NCT03248492; DS8201-A-U201) and the randomized phase III DESTINY-Breast03 trial (NCT03529110; DS8201-A-U302). Approximately 20 additional studies are ongoing in breast cancer, including HER2-low breast cancer, and other solid tumor types within the DESTINY trial program. T-DXd has demonstrated a generally manageable safety profile, with low-grade hematologic and gastrointestinal adverse events (AEs) among the most common; interstitial lung disease (ILD)/pneumonitis has been observed in patients receiving T-DXd and can be severe. This review discusses the management of common AEs and AEs of special interest in patients with HER2-positive unresectable/metastatic breast cancer, including nausea and vomiting, neutropenia, infusion-related reactions, alopecia, fatigue, ILD/pneumonitis, and left ventricular dysfunction.MethodsExpert opinions, institutional protocols, and strategies to help optimize AE management and maximize the potential benefits of T-DXd in patients with breast cancer from five oncologists treating patients with T-DXd in North America and Europe are discussed.ResultsProphylaxis for nausea and vomiting and proactive management of ILD/pneumonitis are especially important in treating patients with T-DXd. Management strategies for other T-DXd-related AEs of interest (e.g. neutropenia, infusion-related reactions, alopecia, fatigue, and left ventricular dysfunction) are also discussed.ConclusionsThis review provides context for understanding the usage, monitoring, and management practices of other health care providers and institutions with experience using T-DXd to help with safe and effective management of T-DXd-related AEs, particularly since the duration of T-DXd treatment may be quite long. Proper management of T-DXd-related AEs will allow optimal exposure and benefit from T-DXd and will help avoid premature discontinuation or improper dose reductions.

Context. One of the long-term goals of exoplanet science is the atmospheric characterization of dozens of small exoplanets in order to understand their diversity and search for habitable worlds and potential biosignatures. Achieving this goal requires a space mission of sufficient scale that can spatially separate the signals from exoplanets and their host stars and thus directly scrutinize the exoplanets and their atmospheres.Aims. We seek to quantify the exoplanet detection performance of a space-based mid-infrared (MIR) nulling interferometer that measures the thermal emission of exoplanets. We study the impact of various parameters and compare the performance with that of large single-aperture mission concepts that detect exoplanets in reflected light.Methods. We have developed an instrument simulator that considers all major astrophysical noise sources and coupled it with Monte Carlo simulations of a synthetic exoplanet population around main-sequence stars within 20 pc of the Sun. This allows us to quantify the number (and types) of exoplanets that our mission concept could detect. Considering single visits only, we discuss two different scenarios for distributing 2.5 yr of an initial search phase among the stellar targets. Different apertures sizes and wavelength ranges are investigated.Results. An interferometer consisting of four 2 m apertures working in the 4–18.5 μ.m wavelength range with a total instrument throughput of 5% could detect up to ≈550 exoplanets with radii between 0.5 and 6 R⊕ with an integrated S/N ≥ 7. At least ≈160 of the detected exoplanets have radii ≤1.5 R⊕. Depending on the observing scenario, ≈25–45 rocky exoplanets (objects with radii between 0.5 and 1.5 R⊕) orbiting within the empirical habitable zone (eHZ) of their host stars are among the detections. With four 3.5 m apertures, the total number of detections can increase to up to ≈770, including ≈60–80 rocky eHZ planets. With four times 1 m apertures, the maximum detection yield is ≈315 exoplanets, including ≤20 rocky eHZ planets. The vast majority of small, temperate exoplanets are detected around M dwarfs. The impact of changing the wavelength range to 3–20 μm or 6–17 μm on the detection yield is negligible.Conclusions. A large space-based MIR nulling interferometer will be able to directly detect hundreds of small, nearby exoplanets, tens of which would be habitable world candidates. This shows that such a mission can compete with large single-aperture reflected light missions. Further increasing the number of habitable world candidates, in particular around solar-type stars, appears possible via the implementation of a multi-visit strategy during the search phase. The high median S/N of most of the detected planets will allow for first estimates of their radii and effective temperatures and will help prioritize the targets for a second mission phase to obtain high-S/N thermal emission spectra, leveraging the superior diagnostic power of the MIR regime compared to shorter wavelengths.

This Letter reports the first measurement of high-energy reactor antineutrinos at Daya Bay, with nearly 9000 inverse beta decay candidates in the prompt energy region of 8-12 MeV observed over 1958 days of data collection. A multivariate analysis is used to separate 2500 signal events from background statistically. The hypothesis of no reactor antineutrinos with neutrino energy above 10 MeV is rejected with a significance of 6.2 standard deviations. A 29% antineutrino flux deficit in the prompt energy region of 8-11 MeV is observed compared to a recent model prediction. We provide the unfolded antineutrino spectrum above 7 MeV as a data-based reference for other experiments. This result provides the first direct observation of the production of antineutrinos from several high-Q_{β} isotopes in commercial reactors.

Background Rabies is 100% preventable by administering early and complete post exposure prophylaxis (PEP). Animal bite victims must have the knowledge and attitude necessary to seek appropriate medical care at the earliest to receive the required PEP. Objectives The present study sought to ascertain the health-seeking behavior of animal bite victims, their knowledge and attitude regarding rabies prophylaxis, the PEP they received, and their level of compliance with the full course of anti-rabies vaccination. Methods The study included animal bite cases that presented to the anti-rabies clinic and matched the eligibility criteria. All the required details were recorded using an internally validated structured questionnaire. All participants were followed up for six months to ensure their health conditions and compliance with the vaccination schedule. Results Out of 1058 respondents, 57.9% were adults, with 46.6% belonging to middle socioeconomic class. 91.1% of them were informed biting animals as dogs. Before arriving at the anti-rabies clinic, 93.3% of the study subjects washed their wounds, and 62.4% visited to another health facility. Rabies knowledge was inadequate among the study participants, only 54.8% being mindful about the disease and its prevention. The compliance with the full course of antirabies vaccination was found to be 77.9%. All subjects were healthy, confirming that PEP is safe and effective. Conclusion Regular social and behavioral change communication (SBCC) needs to be implemented with regard to health-seeking behavior.

Genome sequencing is a powerful tool for identifying SARS-CoV-2 variant lineages; however, there can be limitations due to sequence dropout when used to identify specific key mutations. Recently, ThermoFisher Scientific has developed genotyping assays to help bridge the gap between testing capacity and sequencing capability to generate real-time genotyping results based on specific variants. Over a 6-week period during the months of April and May 2021, we set out to assess the ThermoFisher TaqMan mutation panel genotyping assay, initially for three mutations of concern and then for an additional two mutations of concern, against SARS-CoV-2-positive clinical samples and the corresponding COVID-19 Genomics UK Consortium (COG-UK) sequencing data. We demonstrate that genotyping is a powerful in-depth technique for identifying specific mutations, is an excellent complement to genome sequencing, and has real clinical health value potential, allowing laboratories to report and take action on variants of concern much more quickly.