Search

Cases of iatrogenic cerebral amyloid angiopathy (CAA) have been increasingly reported recently, particularly those associated with neurosurgery. Preclinical studies have shown taxifolin to be promising for treating CAA. We describe a young 42-year-old man with a history of childhood traumatic brain injury that required a craniotomy for hematoma evacuation. He later presented with recurrent lobar intracerebral hemorrhage (ICH) decades later, which was histologically confirmed to be CAA. Serial 11C-Pittsburgh compound B positron emission tomography (11C-PiB-PET) imaging showed a 24% decrease in global standardized uptake value ratio (SUVR) at 10 months after taxifolin use. During this period, the patient experienced clinical improvement with improved consciousness and reduced recurrent ICH frequency, which may be partly attributable to the potential amyloid-β (Aβ) clearing the effect of taxifolin. However, this effect seemed to have diminished at 15 months, CAA should be considered in young patients presenting with recurrent lobar ICH with a history of childhood neurosurgery, and serial 11C-PiB-PET scans warrant further validation as a strategy for monitoring treatment response in CAA for candidate Aβ-clearing therapeutic agents such as taxifolin.

Abstract The neurobiological effects of mind–body exercise on brain activation, functional neural connections and structural changes in the brain remain elusive. This systematic review and coordinate-based meta-analysis investigated the changes in resting-state and task-based brain activation, as well as structural brain changes before and after mind–body exercise compared to waitlist or active controls based on published structural or functional magnetic resonance imaging randomized controlled trials or cross-sectional studies. Electronic database search and manual search in relevant publications yielded 34 empirical studies with low-to-moderate risk of bias (assessed by Cochrane risk-of-bias tool for randomized trials or Joanna Briggs Institute’s critical appraisal checklist for analytical cross-sectional studies) that fulfilled the inclusion criteria, with 26 studies included in the narrative synthesis and 8 studies included in the meta-analysis. Coordinate-based meta-analysis showed that, while mind–body exercise enhanced the activation of the left anterior cingulate cortex within the default mode network (DMN), it induced more deactivation in the left supramarginal gyrus within the ventral attention network (uncorrected ps

Abstract Background This paper examines the factors that led to the collapse of hemp grown for cannabidiol (CBD) in Arizona, the United States of America (USA), and particularly in Yuma County, which is a well-established agricultural area in the state. Methods This research uses a combination of mapping analysis along with a survey of hemp farmers to assess the reasons why the hemp industry collapsed as well as to foster solutions to these problems. Results In 2019, 5430 acres were sown with hemp seed in Arizona with 3890 acres inspected by the state to determine if they could be harvested. By 2021, there were only 156 acres planted, and only 128 of those acres were inspected by the state for compliance. (Crop mortality accounts for the difference between acres sown and acres inspected.) Conclusions A lack of knowledge about the hemp life cycle greatly contributed to the failure of high CBD hemp crops in Arizona. Other problems included noncompliance with tetrahydrocannabinol limits, poor sources for seeds and inconsistent genetics of the hemp varieties sold to farmers, and diseases that hemp plants were susceptible to such as Pythium crown and root rot and beet curly top virus. Addressing these factors will go far in making hemp a profitable and widespread crop in Arizona. Additionally, hemp grown for other traditional uses (e.g., fiber or seed oil) as well as new applications (e.g., microgreens, hempcrete, and phytoremediation) offers other pathways for successful hemp agriculture in this state.

Medicinal and recreational uses of Cannabis sativa, commonly known as cannabis or hemp, has increased following its legalization in certain regions of the world. Cannabis and hemp plants interact with a community of microbes (i.e., the phytobiome), which can influence various aspects of the host plant. The fungal composition of the C. sativa phytobiome (i.e., mycobiome) currently consists of over 100 species of fungi, which includes phytopathogens, epiphytes, and endophytes, This mycobiome has often been understudied in research aimed at evaluating the safety of cannabis products for humans. Medical research has historically focused instead on substance use and medicinal uses of the plant. Because several components of the mycobiome are reported to produce toxic secondary metabolites (i.e., mycotoxins) that can potentially affect the health of humans and animals and initiate opportunistic infections in immunocompromised patients, there is a need to determine the potential health risks that these contaminants could pose for consumers. This review discusses the mycobiome of cannabis and hemp flowers with a focus on plant-infecting and toxigenic fungi that are most commonly found and are of potential concern (e.g., Aspergillus, Penicillium, Fusarium, and Mucor spp.). We review current regulations for molds and mycotoxins worldwide and review assessment methods including culture-based assays, liquid chromatography, immuno-based technologies, and emerging technologies for these contaminants. We also discuss approaches to reduce fungal contaminants on cannabis and hemp and identify future research needs for contaminant detection, data dissemination, and management approaches. These approaches are designed to yield safer products for all consumers.

Measurement(s) wildfire Technology Type(s) NIMS/ICS Reporting Sample Characteristic - Environment wildfire Sample Characteristic - Location United States

Measurement(s) Fire event occurrence • growth rate • size Technology Type(s) Satellite fire detections Sample Characteristic - Environment fire Sample Characteristic - Location global

Metallic contaminants pose a significant challenge to the viability of directly recycling Li-ion batteries. To date, few strategies exist to selectively remove metallic impurities from mixtures of shredded end-of-life material (black mass; BM) without concurrently damaging the structure and electrochemical performance of the target active material. We herein present tailored methods to selectively ionize two major contaminants—Al and Cu—while retaining a representative cathode (LiNi0.33Mn0.33Co0.33O2; NMC-111) intact. This BM purification process is conducted at moderate temperatures in a KOH-based solution matrix. We rationally evaluate approaches to increase both the kinetic corrosion rate and the thermodynamic solubility of Al0 and Cu0, and evaluate the impact of these treatment conditions on the structure, chemistry, and electrochemical performance of NMC. Specifically, we explore the impacts of chloride-based salts, a strong chelating agent, elevated temperature, and sonication on the rate and extent of contaminant corrosion, while concurrently evaluating the effects on NMC. The reported BM purification process is then demonstrated on samples of “simulated BM” containing a practically relevant 1 wt% concentration of Al or Cu. Increasing the kinetic energy of the purifying solution matrix through elevated temperature and sonication accelerates the corrosion of metallic Al and Cu, such that ∼100% corrosion of 75 μm Al and Cu particles is achieved within 2.5 hr. Further, we determine that effective mass transport of ionized species critically impacts the efficacy of Cu corrosion, and that saturated Cl– hinders rather than accelerates Cu corrosion by increasing solution viscosity and introducing competitive pathways for Cu surface passivation. The purification conditions do not induce bulk structural damage to NMC, and electrochemical capacity is maintained in half-cell format. Testing in full cells suggests that a limited quantity of residual surface species are present after treatment, which initially disrupt electrochemical behavior at the graphite anode but are subsequently consumed. Process demonstration on simulated BM suggests that contaminated samples—which prior to treatment show catastrophic electrochemical performance—can be recovered to pristine electrochemical capacity. The reported BM purification method offers a compelling and commercially viable solution to address contamination, particularly in the “fine” fraction of BM where contaminant sizes are on the same order of magnitude as NMC and where traditional separation approaches are unfeasible. Thus, this optimized BM purification technique offers a pathway towards viable direct recycling of BM feedstocks that would otherwise be unusable.

Purpose: Women with lobular carcinoma in-situ (LCIS) have an increased risk for developing breast cancer (BC) compared with the general population. However, little is known about the clinical implication of diagnosing LCIS concurrently with an invasive breast cancer. We aimed to define the rate of LCIS diagnosed concurrently with an invasive breast cancer and investigate the risk of contralateral breast cancer (CBC) during survivorship care. Materials and methods: A single center retrospective review over 6 years identified women with stage I-III BC who underwent lumpectomy or unilateral mastectomy. Patients with or without concurrent LCIS were compared using Chi-squared analyses to assess for differences in clinicopathologic factors and risk of future CBC (including invasive and in-situ disease). Results: Of 1808 patients, 16.6% (n = 301) had LCIS concurrent with their index breast cancer. Patients with LCIS had a higher rate of subsequent CBC development than those without LCIS (3.3% versus 1.0%, P = .004). The risk ratio for patients with LCIS developing subsequent CBC compared with those without LCIS was 3.3 (95% confidence interval [CI]: 1.5-7.3). Conclusions: Patients with LCIS diagnosed concurrently with their index breast cancer at surgery are at higher risk for subsequent CBC than those without LCIS. The evidence from this study suggest that it may be appropriate for women with LCIS diagnosed alongside an index breast cancer to consider on-going high-risk screening during survivorship care.

Neurological hazard assessment of industrial and pesticidal chemicals demands a substantial amount of time and resources. Caenorhabditis elegans is an established model organism in developmental biology and neuroscience. It presents an ideal test system with relatively fewer neurons (302 in hermaphrodites) versus higher-order species, a transparent body, short lifespan, making it easier to perform neurotoxic assessment in a time and cost-effective manner. Yet, no regulatory testing guidelines have been developed for C. elegans in the field of developmental and adult neurotoxicity. Here, we describe a set of morphological and behavioral assessment protocols to examine neurotoxicity in C. elegans with relevance to cholinergic and dopaminergic systems. We discuss the homology of human genes and associated proteins in these two signaling pathways and evaluate the morphological and behavioral endpoints of C. elegans in the context of published adverse outcome pathways of neurodegenerative diseases. We conclude that C. elegans neurotoxicity testing will not only be instrumental to eliminating mammalian testing in neurological hazard assessment but also lead to new knowledge and mechanistic validation in the adverse outcome pathway framework.

Abstract Biological invasions threaten global biodiversity and natural resources. Anticipating future invasions is central to strategies for combating the spread of invasive species. Ecological niche models are thus increasingly used to predict potential distribution of invasive species. In this study, we compare ecological niches of Rhododendron ponticum in its native (Iberian Peninsula) and invasive (Britain) ranges. Here, we test the conservation of ecological niche between invasive and native populations of R. ponticum using principal component analysis, niche dynamics analysis, and MaxEnt‐based reciprocal niche modeling. We show that niche overlap between native and invasive populations is very low, leading us to the conclusion that the two niches are not equivalent and are dissimilar. We conclude that R. ponticum occupies novel environmental conditions in Britain. However, the evidence of niche shift presented in this study should be treated with caution because of nonanalogue climatic conditions between native and invasive ranges and a small population size in the native range. We then frame our results in the context of contradicting genetic evidence on possible hybridization of this invasive species in Britain. We argue that the existing contradictory studies on whether hybridization caused niche shift in R. ponticum are not sufficient to prove or disprove this hypothesis. However, we present a series of theoretical arguments which indicate that hybridization is a likely cause of the observed niche expansion of R. ponticum in Britain.

Abstract The extensive lava piles of Iceland contain a unique record of geomagnetic field variations spanning the past ~ 16 Ma. Since the 1950s, palaeomagnetic data have been obtained from over 9400 Icelandic lavas. We have compiled all palaeomagnetic data currently available and developed a publicly accessible database (http://www.icepmag.org). The data within the database are primarily palaeodirections, with a relatively smaller number of palaeointensity data (8936 entries contain direction only, 218 intensity only, and 337 both direction and intensity). In addition, the database contains a wide range of metadata, including geochronological information, site details, and laboratory methods. The search interface of the database allows users to search for data using a range of customisable filters (e.g. by publication, geological age, location, laboratory method, palaeomagnetic statistics) and to quickly visualise and download the matching search results. The data within the database have significant potential for understanding long-term palaeomagnetic field variations at high latitude, the behaviour of excursions and reversals, and geological mapping on Iceland.

Tears of the rotator cuff tendons can occur that do not allow anatomic footprint restoration yet may not be large enough to require a superior capsular reconstruction technique. Typically, these intermediate-sized tears are addressed with a medialized repair or partial repair technique. A partially repaired rotator cuff tendon, however, can lead to a high retear rate, as the repaired tendon is required to serve as both a dynamic tendon and a static ligamentous stabilizer. One potential static support, as a nearby autologous graft donor, is the proximal long head biceps tendon. The purpose of this Technical Note is to describe a surgical technique for an anterior cable reconstruction using the proximal biceps tendon for large rotator cuff defects.

Amoeboid cell types are fundamental to animal biology and broadly distributed across animal diversity, but their evolutionary origin is unclear. The closest living relatives of animals, the choanoflagellates, display a polarized cell architecture (with an apical flagellum encircled by microvilli) that resembles that of epithelial cells and suggests homology, but this architecture differs strikingly from the deformable phenotype of animal amoeboid cells, which instead evoke more distantly related eukaryotes, such as diverse amoebae. Here, we show that choanoflagellates subjected to confinement become amoeboid by retracting their flagella and activating myosin-based motility. This switch allows escape from confinement and is conserved across choanoflagellate diversity. The conservation of the amoeboid cell phenotype across animals and choanoflagellates, together with the conserved role of myosin, is consistent with homology of amoeboid motility in both lineages. We hypothesize that the differentiation between animal epithelial and crawling cells might have evolved from a stress-induced switch between flagellate and amoeboid forms in their single-celled ancestors.

There is an increase in the use of photogrammetric point clouds for tree attribute mensuration. Stem diameter and circumference can be estimated from point clouds using stem disks of varying thicknesses along the bole. However, there is a dearth of information on the effect of the thickness of point cloud-based stem disks on the accuracy of diameter and circumference estimations. In this study, we outlined a GIS-based procedure for analysing Structure from Motion-derived photogrammetric point clouds with a view to providing an optimal disk thickness for accurate circumference estimates. Geo-referenced point clouds were created from photographs of 30 trees belonging to five savanna species. For each tree, 20 horizontal stem disks, with increasing thicknesses of 1 to 20 mm were made at breast height using the open source QGIS software. The resulting cross-sections were manually delineated and digitised. The difference between reference (manually measured) and point cloud-based circumferences at breast height was expressed as mean absolute percent error (MAPE) and compared across tree species, size and disk thickness. We found significant effects of species identity, tree size and disk thickness on MAPE. A stem disk of 7 mm in thickness provided consistently lower MAPE values (< 6%). This suggests that the accuracy of tree stem circumference estimations from photogrammetric point clouds depends on stem disk thickness.

Ibodi Monkey Forest (IMF) is one of the least studied forest reserves in Nigeria. This forest is being increasingly subjected to anthropic actions. There is dearth of information on the Carbon sequestration potential of this forest. We investigated the distribution patterns of Carbon pools and overall sequestration potentials in different physiognomies in Ibodi Monkey Forest. We identified three physiognomies in IMF based on levels of anthropogenic interferences as follows: Regrowth Forest (RF), Cocoa Plantation (CP), and Tree Fallow (TF). Four plots (25 × 25 m2) were randomly selected within each physiognomy. Soil Organic Carbon (SOC) was estimated from a total of 48 soil samples collected across the three physiognomies at four depths (0–15, 15–30, 30–45, and 45–60 cm). Carbon stock in Understory Pool (UP) and Standing Litter Pool (SLP) were estimated from samples clipped at 2 cm, and standing litter which were randomly taken at 5 location within 0.5 m x 0.5 m quadrat. Diameter at Breast Height and tree height of all trees within each plot were measured. Basic wood density was determined from wood cores collected at heights 1 m and 1.4 m aboveground level from each species. Aboveground Carbon (AGC), Below Ground Carbon (BGC) were estimated using pantropical allometric equation incorporating wood density, DBH and H. Carbon Sequestration Potential (CSP) was estimated from SOC, UP, SLP, AGC and BGC, and compared across physiognomies. Total SOC up to 60 cm was 332.60 tha−1, with RF (144.34 tha−1), CP (94.37 tha−1) and TF (94.40 tha−1). Total UP was 0.02 tCha−1, in the order TF>CP>RF (0.008 tCha−1>0.007 tCha−1>0.004 tCha−1, respectively).Total SLP was 0.13 tCha−1. The trend followed RF>CP>TF (0.08 tCha−1>0.04 tCha−1>0.01 tCha−1, respectively).Total AGC stock was 57.52tCha−1. The trend followed RF>CP>TF (37.35 tCha−1>19.53 tCha−1>0.64 tCha−1 respectively). Total BGC was 13.80 tCha−1, in the order RF>CP>TF (8.96 tCha−1>4.69 tCha−1>0.15 tCha−1 respectively). The total CSP in IMF was 1481.59 tCO2eha−1. The AGC and BGC pool had CSP of 162.00 tCO2eha−1 and 50.61 tCO2eha−1 respectively and SOC pool had1219.53 tCO2eha−1 SLP had 0.48 tCO2eha−1with UP with the least figure of 0.07 tCO2eha−1. These results suggests IMF has an appreciable Carbon sequestration potential. However, the potential is being threatened by increased anthropogenic effect at the fringes of the forest.

Human skin is composed of the cell-rich epidermis, the extracellular matrix (ECM) rich dermis, and the hypodermis. Within the dermis, a dense network of ECM proteins provides structural support to the skin and regulates a wide variety of signaling pathways which govern cell proliferation and other critical processes. Both intrinsic aging, which occurs steadily over time, and extrinsic aging (photoaging), which occurs as a result of external insults such as solar radiation, cause alterations to the dermal ECM. In this study, we utilized both quantitative and global proteomics, alongside single harmonic generation (SHG) and two-photon autofluorescence (TPAF) imaging, to assess changes in dermal composition during intrinsic and extrinsic aging. We find that both intrinsic and extrinsic aging result in significant decreases in ECM-supporting proteoglycans and structural ECM integrity, evidenced by decreasing collagen abundance and increasing fibril fragmentation. Intrinsic aging also produces changes distinct from those produced by photoaging, including reductions in elastic fiber and crosslinking enzyme abundance. In contrast, photoaging is primarily defined by increases in elastic fiber-associated protein and pro-inflammatory proteases. Changes associated with photoaging are evident even in young (mid 20s) sun-exposed forearm skin, indicating that proteomic evidence of photoaging is present decades prior to clinical signs of photoaging. GO term enrichment revealed that both intrinsic aging and photoaging share common features of chronic inflammation. The proteomic data has been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD015982.

Low first-cycle Coulombic efficiency is especially poor for silicon (Si)-based anodes due to the high surface area of the Si-active material and extensive electrolyte decomposition during the initial cycles forming the solid electrolyte interphase (SEI). Therefore, developing successful prelithiation methods will greatly benefit the development of lithium-ion batteries (LiBs) utilizing Si anodes. In pursuit of this goal, in this study, lithium oxide (Li2O) was added to a LiNi0.6Mn0.2Co0.2O2 (NMC622) cathode using a scalable ball-milling approach to compensate for the initial Li loss at the anode. Different milling conditions were tested to evaluate the impact of particle morphology on the additive performance. In addition, Co3O4, a well-known oxygen evolution reaction catalyst, was introduced to facilitate the activation of Li2O. The Li2O + Co3O4 additives successfully delivered an additional capacity of 1116 mAh/gLi2O when charged up to 4.3 V in half cells and 1035 mAh/gLi2O when charged up to 4.1 V in full cells using Si anodes.

Nuclear magnetic resonance (NMR) spectroscopy is an important analytical technique in synthetic organic chemistry, but its integration into high-throughput experimentation workflows has been limited by the necessity of manually analyzing the NMR spectra of new chemical entities. Current efforts to automate the analysis of NMR spectra rely on comparisons to databases of reported spectra for known compounds and, therefore, are incompatible with the exploration of new chemical space. By reframing the NMR spectrum of a reaction mixture as a joint probability distribution, we have used Hamiltonian Monte Carlo Markov Chain and density functional theory to fit the predicted NMR spectra to those of crude reaction mixtures. This approach enables the deconvolution and analysis of the spectra of mixtures of compounds without relying on reported spectra. The utility of our approach to analyze crude reaction mixtures is demonstrated with the experimental spectra of reactions that generate a mixture of isomers, such as Wittig olefination and C-H functionalization reactions. The correct identification of compounds in a reaction mixture and their relative concentrations is achieved with a mean absolute error as low as 1%.

Background How habitat fragmentation affects the relationship between local richness and the variation in community composition across space is important to both ecology and conservation biology, but this effect remains poorly understood. Methods Here, we present an empirical study to address this topic in a fragmented landscape, the Thousand Island Lake (TIL), an artificial land-bridge island system with more than 1,000 islands, which provides an “experimental” fragmented landscape with a homogeneous matrix and similar successional history. We measured species composition and plant functional type (PFT) on 29 islands, and tested the effects of island area and isolation on the relationship between α- and β-diversity. General Linear Models were applied to test the impact of habitat fragmentation. In addition, variation partitioning was used to decouple α-diversity dependent and α-diversity independent spatial turnover in β-diversity of the plant community and across different PFTs. Results We found habitat fragmentation influences β-diversity of plants primarily by modifying local α-diversity, not spatial turnover in the TIL system. We also found area-dependent environmental filtering and differential plant responses across functional types were the most likely underlying driving mechanisms. Discussion These results highlight the importance of hierarchical linkages between components of biodiversity across scales in fragmented landscapes, and have practical conservation implications.

Data-based global paleomagnetic field models provide a more complete view of geomagnetic excursions than individual records. They allow the temporal and spatial field evolution to be mapped globally, and facilitate investigation of dipole and non-dipole field components. We have developed a suite of spherical harmonic (SH) field models that span 50–30 ka and include the Laschamp (~41 ka) and Mono Lake (~33 ka) excursions. Paleomagnetic field models depend heavily on the data used in their construction. Variations in paleomagnetic sediment records from the same region are in some cases inconsistent. To test the influence of data selection and reliance on age models, we have built a series of SH models based upon different data sets. A number of excursion characteristics are robust in all models, despite some differences in energy distribution among SH coefficients. Quantities, such as field morphology at the core-mantle boundary (CMB) or individual SH degree power variations should be interpreted with caution. All models suggest that the excursion process during the Laschamp is mainly governed by axial dipole decay and recovery, without a significant influence from the equatorial dipole or non-dipole fields. The axial dipole component reduces to almost zero, but does not reverse. This results in excursional field behavior seen globally, but non-uniformly at Earth's surface. The Mono Lake excursion may be a series of excursions occurring between 36 and 30 ka rather than a single excursion. In contrast to the Laschamp, these excursions appear driven by smaller decreases in axial dipole field strength during a time when the axial dipole power at the CMB is similar to the power in the non-dipole field. We suggest three phases for the 50 to 30 ka period: (1) a broadly stable phase dominated by the axial dipole (50–43 ka); (2) the Laschamp excursion, with the underlying excursion process lasting ~5 ka (43–38 ka) and the surface field expression lasting ~2 ka (42–40 ka); (3) a weak phase during which axial dipole and non-dipole power at the CMB are comparable, leading to more than one excursion between 36 and 30 ka.

Activation barriers of elementary reactions are essential to predict molecular reaction mechanisms and kinetics. However, computing these energy barriers by identifying transition states with electronic structure methods (e.g., density functional theory) can be time-consuming and computationally expensive. In this work, we introduce CoeffNet, an equivariant graph neural network that predicts activation barriers using coefficients of any frontier molecular orbital (such as the highest occupied molecular orbital) of reactant and product complexes as graph node features. We show that using coefficients as features offer several advantages, such as chemical interpretability and physical constraints on the network's behaviour and numerical range. Model outputs are either activation barriers or coefficients of the chosen molecular orbital of the transition state; the latter quantity allows us to interpret the results of the neural network through chemical intuition. We test CoeffNet on a dataset of SN2 reactions as a proof-of-concept and show that the activation barriers are predicted with a mean absolute error of less than 0.025 eV. The highest occupied molecular orbital of the transition state is visualized and the distribution of the orbital densities of the transition states is described for a few prototype SN2 reactions.

Harnessing the fire data revolution, i.e., the abundance of information from satellites, government records, social media, and human health sources, now requires complex and challenging data integration approaches. Defining fire events is key to that effort. In order to understand the spatial and temporal characteristics of fire, or the classic fire regime concept, we need to critically define fire events from remote sensing data. Events, fundamentally a geographic concept with delineated spatial and temporal boundaries around a specific phenomenon that is homogenous in some property, are key to understanding fire regimes and more importantly how they are changing. Here, we describe Fire Events Delineation (FIRED), an event-delineation algorithm, that has been used to derive fire events (N = 51,871) from the MODIS MCD64 burned area product for the coterminous US (CONUS) from January 2001 to May 2019. The optimized spatial and temporal parameters to cluster burned area pixels into events were an 11-day window and a 5-pixel (2315 m) distance, when optimized against 13,741 wildfire perimeters in the CONUS from the Monitoring Trends in Burn Severity record. The linear relationship between the size of individual FIRED and Monitoring Trends in Burn Severity (MTBS) events for the CONUS was strong (R2 = 0.92 for all events). Importantly, this algorithm is open-source and flexible, allowing the end user to modify the spatio-temporal threshold or even the underlying algorithm approach as they see fit. We expect the optimized criteria to vary across regions, based on regional distributions of fire event size and rate of spread. We describe the derived metrics provided in a new national database and how they can be used to better understand US fire regimes. The open, flexible FIRED algorithm could be utilized to derive events in any satellite product. We hope that this open science effort will help catalyze a community-driven, data-integration effort (termed OneFire) to build a more complete picture of fire.

Background and Objectives: The recent use of Structure-from-Motion with Multi-View Stereo photogrammetry (SfM-MVS) in forestry has underscored its robustness in tree mensuration. This study evaluated the differences in tree metrics resulting from various related SfM-MVS photogrammetric image acquisition scenarios. Materials and Methods: Scaled tri-dimensional models of 30 savanna trees belonging to five species were built from photographs acquired in a factorial design with shooting distance (d = 1, 2, 3, 4 and 5 m away from tree) and angular shift (α = 15°, 30°, 45° and 60°; nested in d). Tree stem circumference at 1.3 m and bole volume were estimated using models resulting from each of the 20 scenarios/tree. Mean absolute percent error (MAPE) was computed for both metrics in order to compare the performance of each scenario in relation to reference data collected using a measuring tape. Results: An assessment of the effect of species identity (s), shooting distance and angular shift showed that photographic point cloud density was dependent on α and s, and optimal for 15° and 30°. MAPEs calculated on stem circumferences and volumes significantly differed with d and α, respectively. There was a significant interaction between α and s for both circumference and volume MAPEs, which varied widely (1.6 ± 0.4%−20.8 ± 23.7% and 2.0 ± 0.6%−36.5 ± 48.7% respectively), and were consistently lower for smaller values of d and α. Conclusion: The accuracy of photogrammetric estimation of individual tree attributes depended on image-capture approach. Acquiring images 2 m away and with 30° intervals around trees produced reliable estimates of stem circumference and bole volume. Research Highlights: This study indicates that the accuracy of photogrammetric estimations of individual tree attributes is species-dependent. Camera positions in relation to the subject substantially influence the level of uncertainty in measurements.

Mexican sunflower, Tithonia diversifolia (Asteraceae), is an invasive tropical plant species native to Central America. It has spread in more than 70 countries across Asia, Africa and Australia. In Africa, this species is known to disturb native crops and plant communities, but its negative impacts remain underestimated. Moreover, its potential invasion risk has not been investigated so far. A fundamental aspect in the identification and prediction of habitats susceptible to biological invasions lies in the ability of an organism to conserve or change its ecological niche as part of the invasion process. Here, we compared the realised climatic niche of T. diversifolia between its Central American and African ranges. In addition, reciprocal distribution models were calibrated on its native and invaded ranges. Models were combined and projected to current and future climatic conditions in Africa to estimate the potential distribution of this species. Niche overlap given by Schoner's D index was low (0.23), equivalency and similarity tests suggested that the climatic niche of T. diversifolia is not similar in both ranges. However the low expansion (U = 0.09) and very high stability (S = 0.92) indices support climatic niche conservatism for this species in Africa, although it has not filled its entire niche so far. Our combined reciprocal models highlight highly suitable areas for this species in humid regions throughout East, Central and West Africa, then in some parts of South Africa and Madagascar. Future projections indicated that the distribution of climatically suitable habitats will likely remain stable.

N-nitrosodimethylamine (NDMA) is a disinfection by-product (DBP) that has been classified as a probable human carcinogen in multiple risk assessments. NDMA presence in drinking water is widespread and dependent on source water, disinfectant type, precursors, and water treatment strategies. The objectives of this study were to investigate NDMA formation potential in a modeled monochloramine water treatment plant (WTP) fed by seasonally and spatially varying source water; and to optimize DBP precursor removal by combining conventional and additional treatment techniques. After NDMA analysis, it was found that NDMA formation was significantly dependent on source water type and monochloramine contact time (CT); e.g., at 24 h CT, Cork Brook produced 12.2 ng/L NDMA and Bailey Brook produced 4.2 ng/L NDMA, compared with 72 h CT, Cork Brook produced 4.1 ng/L NDMA and Bailey Brook produced 3.4 ng/L NDMA. No correlations were found between traditional DBP precursors such as total organic carbon and total nitrogen, and the formation of NDMA. The laboratory bench-top treatment system was highly effective at removing traditional DBP precursors, highlighting the need for WTPs to alter their current treatment methods to best accommodate the complex system of DBP control.

Duplication of the vas deferens is a rare anomaly, defined as the presence of two distinct vasa deferentia within one spermatic cord, with only 28 cases reported worldwide since 1959. We report the case of a 63-year-old man with a duplicate vas deferens, presenting with abdominal pain from bowel obstruction secondary to incarcerated inguinal hernia. Spermatic cord dissection during hernioplasty revealed duplication of the vas deferens within the right spermatic cord. Doppler ultrasonography confirmed absence of waveforms in both vasa deferentia with arterial signal in the accompanying vessel. The hernia was repaired without complication. This report emphasizes recognition of duplicate vas deferens in avoiding iatrogenic injury and optimizing surgical outcome.

The nuclear magnetic resonance (NMR) chemical shift tensor is a highly sensitive probe of the electronic structure of an atom and furthermore its local structure. Recently, machine learning has been applied to NMR in the prediction of isotropic chemical shifts from a structure. Current machine learning models, however, often ignore the full chemical shift tensor for the easier-to-predict isotropic chemical shift, effectively ignoring a multitude of structural information available in the NMR chemical shift tensor. Here we use an equivariant graph neural network (GNN) to predict full 29Si chemical shift tensors in silicate materials. The equivariant GNN model predicts full tensors to a mean absolute error of 1.05 ppm and is able to accurately determine the magnitude, anisotropy, and tensor orientation in a diverse set of silicon oxide local structures. When compared with other models, the equivariant GNN model outperforms the state-of-the-art machine learning models by 53%. The equivariant GNN model also outperforms historic analytical models by 57% for isotropic chemical shift and 91% for anisotropy. The software is available as a simple-to-use open-source repository, allowing similar models to be created and trained with ease.

The construction of three-dimensional (3D) microvascular networks with defined structures remains challenging. Emerging bioprinting strategies provide a means of patterning endothelial cells (ECs) into the geometry of 3D microvascular networks, but the microenvironmental cues necessary to promote their self-organization into cohesive and perfusable microvessels are not well known. To this end, we reconstituted microvessel formation in vitro by patterning thin lines of closely packed ECs fully embedded within a 3D extracellular matrix (ECM) and observed how different microenvironmental parameters influenced EC behaviors and their self-organization into microvessels. We found that the inclusion of fibrillar matrices, such as collagen I, into the ECM positively influenced cell condensation into extended geometries such as cords. We also identified the presence of a high-molecular-weight protein(s) in fetal bovine serum that negatively influenced EC condensation. This component destabilized cord structure by promoting cell protrusions and destabilizing cell-cell adhesions. Endothelial cords cultured in the presence of fibrillar collagen and in the absence of this protein activity were able to polarize, lumenize, incorporate mural cells, and support fluid flow. These optimized conditions allowed for the construction of branched and perfusable microvascular networks directly from patterned cells in as little as 3 days. These findings reveal important design principles for future microvascular engineering efforts based on bioprinting and micropatterning techniques. Impact statement Bioprinting is a potential strategy to achieve microvascularization in engineered tissues. However, the controlled self-organization of patterned endothelial cells into perfusable microvasculature remains challenging. We used DNA Programmed Assembly of Cells to create cell-dense, capillary-sized cords of endothelial cells with complete control over their structure. We optimized the matrix and media conditions to promote self-organization and maturation of these endothelial cords into stable and perfusable microvascular networks.

Neurodegeneration has been correlated with mitochondrial DNA (mtDNA) damage and exposure to environmental toxins, but causation is unclear. We investigated the ability of several known environmental genotoxins and neurotoxins to cause mtDNA damage, mtDNA depletion, and neurodegeneration in Caenorhabditis elegans. We found that paraquat, cadmium chloride and aflatoxin B1 caused more mitochondrial than nuclear DNA damage, and paraquat and aflatoxin B1 also caused dopaminergic neurodegeneration. 6-hydroxydopamine (6-OHDA) caused similar levels of mitochondrial and nuclear DNA damage. To further test whether the neurodegeneration could be attributed to the observed mtDNA damage, C. elegans were exposed to repeated low-dose ultraviolet C radiation (UVC) that resulted in persistent mtDNA damage; this exposure also resulted in dopaminergic neurodegeneration. Damage to GABAergic neurons and pharyngeal muscle cells was not detected. We also found that fasting at the first larval stage was protective in dopaminergic neurons against 6-OHDA-induced neurodegeneration. Finally, we found that dopaminergic neurons in C. elegans are capable of regeneration after laser surgery. Our findings are consistent with a causal role for mitochondrial DNA damage in neurodegeneration, but also support non mtDNA-mediated mechanisms.

Li-ion batteries will lose both capacity and power over time due to calendar aging caused by slow parasitic processes that consume Li+ ions. Studying and mitigating these processes is traditionally an equally slow venture, which is especially taxing for the validation of new active materials and electrolyte additives. Here, we evaluate whether potentiostatic holds can be used to accelerate the diagnosis of Li+ loss during calendar aging. The technique is based on the idea that, under the right conditions, the current measured as the cell voltage is held constant can be correlated with the instantaneous rate of side reactions. Thus, in principle, these measurements could capture the rate of capacity fade in real time. In practice, we show that this method is incapable of quantitatively forecasting calendar aging trends. Instead, our study demonstrates that potentiostatic holds can be applied for initial qualitative screening of systems that exhibit promising long-term stability, which can be useful to shrink the parameter space for calendar aging studies. By facilitating the identification of improved formulations, this approach can help accelerate innovation in the battery industry.

The nuclear shielding anisotropy, ζ, is a useful nuclear magnetic resonance (NMR) shielding tensor parameter in describing the extent of electron cloud distortion about an atom. Despite the advantages afforded by NMR in structural characterization, the relationship between ζ and local structure of an atom in high-symmetry environments, such as Si-Q4sites, is poorly understood. Here, we use a data-driven approach combining random forest feature ranking and the Sure Independence Screening and Sparsifying Operator (SISSO) approach to derive a simple and accurate geometric descriptor for ζ with a root-mean-squared prediction error of 6.77 ppm and anR2of 0.761. We then apply this descriptor to describe the local geometric distortion of zeolites Sigma-2 and silica-ZSM-5 whose chemical shift anisotropy tensor has been reported. We envision that this geometric descriptor will allow for structural description and refinement in previously difficult-to-describe materials.

Amoeboid cell types are fundamental to animal biology and broadly distributed across animal diversity, but their evolutionary origin is unclear. The closest living relatives of animals, the choanoflagellates, display a polarized cell architecture (with an apical flagellum encircled by microvilli) that resembles that of epithelial cells and suggests homology, but this architecture differs strikingly from the deformable phenotype of animal amoeboid cells, which instead evoke more distantly related eukaryotes, such as diverse amoebae. Here, we show that choanoflagellates subjected to confinement become amoeboid by retracting their flagella and activating myosin-based motility. This switch allows escape from confinement and is conserved across choanoflagellate diversity. The conservation of the amoeboid cell phenotype across animals and choanoflagellates, together with the conserved role of myosin, is consistent with homology of amoeboid motility in both lineages. We hypothesize that the differentiation between animal epithelial and crawling cells might have evolved from a stress-induced switch between flagellate and amoeboid forms in their single-celled ancestors.