Search

Plants display a range of temporal patterns of inter-annual reproduction, from relatively constant seed production to mast seeding, the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long-lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community-level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long-Term Ecological Research (LTER) or long-term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community-level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent-scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license.

The introduction of localized electronic states into a metal can alter its physical properties, for example enabling exotic metal physics including heavy fermion and strange metal behaviour. A common source of localized states in such systems are partially filled 4f and 5f shells because of the inherently compact nature of those orbitals. The interaction of electrons in these orbitals with the conduction sea is well described by the Kondo framework. However, there have also been observations of Kondo-like behaviour in 3d transition metal oxides and in 4d- and 5d-containing van der Waals heterostructures. This calls for a broader consideration of the physical requirements for Kondo systems. Here we show transport and thermodynamic hallmarks of heavy fermion and strange metal behaviour that arise in the kagome metal Ni3In, wherein the source of localized states is destructive interference-induced band flattening of partially filled Ni 3d states. With magnetic field and pressure tuning, we also find evidence that the system is proximate to quantum criticality, extending the analogy to f-electron Kondo lattices. These observations highlight the role of hopping frustration in metallic systems as a potential source for strong correlations. Additionally, this suggests a lattice-driven approach to realizing correlated metals with non-trivial band topology.

The COVID-19 pandemic brought diagnostics into the spotlight in an unprecedented way not only for case management but also for population health, surveillance, and monitoring. The industry saw notable levels of investment and accelerated research which sparked a wave of innovation. Simple non-invasive sampling methods such as nasal swabs have become widely used in settings ranging from tertiary hospitals to the community. Self-testing has also been adopted as standard practice using not only conventional lateral flow tests but novel and affordable point-of-care molecular diagnostics. The use of new technologies, including artificial intelligence-based diagnostics, have rapidly expanded in the clinical setting. The capacity for next-generation sequencing and acceptance of digital health has significantly increased. However, 4 years after the pandemic started, the market for SARS-CoV-2 tests is saturated, and developers may benefit from leveraging their innovations for other diseases; tuberculosis (TB) is a worthwhile portfolio expansion for diagnostics developers given the extremely high disease burden, supportive environment from not-for-profit initiatives and governments, and the urgent need to overcome the long-standing dearth of innovation in the TB diagnostics field. In exchange, the current challenges in TB detection may be resolved by adopting enhanced swab-based molecular methods, instrument-based, higher sensitivity antigen detection technologies, and/or artificial intelligence-based digital health technologies developed for COVID-19. The aim of this article is to review how such innovative approaches for COVID-19 diagnosis can be applied to TB to have a comparable impact.

This article covers liquid chromatography (LC) columns and accessories commercially released after Pittcon 2023 through the 2024 conference. As in the past, LCGC International sent out a survey in late 2023 and early 2024 asking vendors to supply information on products launched over the course of the year. Note that new products for gas chromatography (GC), LC instrumentation and software, and sample preparation are covered elsewhere. Information for this article is obtained over the course of many months, and thus, it is possible that some information could have been missed or misinterpreted. The reader is encouraged to check with specific vendor sites for additional product releases, as well as more detailed information on product usage and attributes. Links to vendor sites are provided where applicable., THE VENDORS THAT responded to the survey and their new liquid chromatography (LC) products are listed in Table I. This year, the new products are classified by the mode of [...]

The Brazilian Amazon has been a focus of land development with large swaths of forests converted to agriculture. Forest degradation by selective logging and fires has accompanied the agricultural frontier and has resulted in significant impacts on Amazonian ecosystems. Changes in forest structure resulting from forest disturbances have large impacts on the surface energy balance, including on land surface temperature (LST) and evapotranspiration (ET). This study's objective is to assess the effects of forest disturbances on water fluxes and forest structure in a transitional forest site in the Southern Amazon. We used ET and LST products from MODIS and Landsat 8 and GEDI-derived forest structure data to address our research questions. We found that disturbances induced seasonal water stress, more pronounced in croplands/pastures than in forests (differences up to 20% in the dry season), and more pronounced in second-growth and recently burned areas than in logged and intact forests (differences up to 12% in the dry season). Moreover, ET and LST were negatively related, with more consistent relationships across disturbance classes in the dry season (R2: 0.41–0.87) than in the wet season (R2: 0.18–0.49). Forest and cropland or pasture classes showed contrasting relationships in the dry season. Finally, we found that forest structure exhibited stronger relationships with ET and LST in the most disturbed forests (R2: 0.01–0.43) than in the least disturbed forests (R2

OBJECTIVE: To compare the efficacies of remote symptom-based diagnosis of malaria, rapid diagnostic tests and microscopy in an area of low endemicity in the Philippines. METHODS: In Trial I, 350 symptomatic patients were tested within their villages using malaria Plasmodium falciparum (Pf)/Plasmodium vivax (Pv) immunochromatographic tests (ICT tests) and blood films stored and read under local conditions. The slides were later restained and read. In Trial II, unsupervised volunteer barangay health workers prepared ICT tests and slides after brief training. These slides were read at rural health units. Twenty-seven barangay health workers and 72 community members were later questioned about the three diagnostic strategies. FINDINGS: A history of fever alone was sensitive (95.4%) but poorly specific (16.5%) for predicting parasitaemia. The inclusion of other symptoms reduced the sensitivity to below 85%, while specificity remained low. The axillary temperature was poorly predictive. ICT tests achieved high sensitivity (97.9%) but many cases indicated as positive by ICT tests were negative by microscopy. Further analysis of these cases in Trial I indicated that ICT tests were detecting low-level parasitaemias missed by microscopy, and that local microscopy had poor accuracy. ICT tests were well accepted and accurately performed by barangay health workers. CONCLUSION: These tests meet a strong desire in the community for blood-based diagnosis and may increase the compliance and treatment-seeking behaviour of patients.

Introduction Beginning in the 1980s, a series of foreign movies appeared that focused on cooking and eating-Tampopo (1985), Babette's Feast (1987), Like Water for Chocolate (1992), Eat Drink Man Woman [...]

Abstract Diagnostic testing for malaria has for many years been eschewed, lest it be an obstacle to the delivery of rapid, life-saving treatment. The approach of treating malaria without confirmatory testing has been reinforced by the availability of inexpensive treatment with few side effects, by the great difficulty of establishing quality-assured microscopy in rural and resource-poor settings, and by the preeminence of malaria as a cause of important fever in endemic regions. Within the last decade, all three of these factors have changed. More expensive artemisinin combination therapy (ACT) has been widely introduced, simple immunochromatographic tests for malaria have been developed that can be used as an alternative to microscopy by village health workers, and recognition of the health cost of mismanaging non-malarial fever is growing. In most of the world a small fraction of fever is due to malaria, and reflex treatment with ACT does not make medical or economic sense. Global malaria control efforts have been energized by the availability of new sources of funding, and by the rapid reduction in malaria prevalence in a number of settings where bed nets, indoor residual spraying with insecticides, and ACT have been systematically deployed. This momentum has been captured by a new call for malaria elimination. Without wide implementation of accurate and discriminating diagnostic testing, and reporting of results, most fever will be inappropriately managed, millions of doses of ACT will be wasted, and malaria control programmes will be blindfolded to the impact of their efforts.

A universal approach to characterizing sport-related physical activity (PA) types in sport settings does not yet exist. Young adults (n = 30), 19-33 years, engaged in a 15-min activity session, performing warm-ups, 3-on-3 soccer, and 3-on-3 basketball. Videos were recorded and manually coded as criterion PA types (walking, running, jumping, rapid lateral movements). Participants wore an accelerometer on their right hip. Multiple machine learning models were developed and compared for predicting PA type. Most models underestimated time spent completing the activities performed least commonly. Point estimates for percent agreement, sensitivity, specificity, F-scores, and kappa were similar across models, with Hidden Markov Models (HMMs) being best at classifying rare events. Models detected activity type during sport-related movements with modest accuracy (kappas [less than or equal to] 0.40). Given the better performance of HMMs, incorporating the temporal nature of sport-related activities is important for improving sport-related PA classification.

Context: As youth sport participation grows, athletic trainers (ATs) continue to be important health care providers in managing growth-related injuries. Objective: To examine secondary school ATs' reported knowledge on diagnosing and treating growth-related injuries and reported confidence for determining growth status and to report methods secondary school ATs use to determine patient growth status. Design: Cross-sectional. Setting: An online questionnaire was distributed to secondary school ATs in the United States. Data collection occurred in the summer of 2021 over a 6-week period. Patients or Other Participants: A total of 430 secondary school ATs (highest degree earned: master's degree 5 66%). Main Outcome Measures: The questionnaire contained secondary school ATs' confidence in determining if an athlete was going through a growth spurt, level of knowledge on diagnosing and treating growth-related injuries, methods secondary school ATs use to determine growth status in their athletes, and demographics. Results: Most secondary school ATs believed that growth spurts affected sport-related injury risk (88%); however, only 37% of secondary school ATs were "fairly" or "completely" confident in their ability to determine if an athlete was going through a growth spurt. For those 37% of secondary school ATs, 89% of them used history or observation over time, but no formal method, for determining growth status of their patients. Patient self-assessed Tanner stages (32%) and clinical evaluation of Tanner stages (28%) were the next most used methods for assessing growth. Conclusions: In accord with Domain I of athletic training, secondary school ATs could benefit from improved knowledge on how to measure and manage growth in their patient population. To aid education in this area, future researchers should focus on assessing barriers secondary school ATs face in implementing methods for measuring growth and exploring secondary school ATs' knowledge levels on risk management programs for youth athletes going through growth spurts.

Tropical forest degradation (e.g., anthropogenic disturbances such as selective logging and fires) alters forest structure and function and influences the forest's carbon sink. In this study, we explored structure-function relationships across a variety of degradation levels in the southern Brazilian Amazon by 1) investigating how forest structural properties vary as a function of degradation history using airborne lidar data; 2) assessing the effects of degradation on solar-induced chlorophyll fluorescence (SIF) seasonality using TROPOMI data; and 3) quantifying the contribution of structural variables to SIF using multiple regression models with stepwise selection of lidar metrics. Forest degradation history was obtained through Landsat time-series classification. We found that fire, logging, and time since disturbance were major determinants of forest structure, and that forests affected by fires experienced larger variability in leaf area index (LAI), canopy height and vertical structure relative to logged and intact forests. Moreover, only recently burned forests showed significantly depressed SIF during the dry season compared to intact forests. Canopy height and the vertical distribution of foliage were the best predictors of SIF. Unexpectedly, we found that wet-season SIF was higher in active regenerating forests (~ 4 years after fires or logging) compared with intact forests, despite lower LAI. Our findings help to elucidate the mechanisms of carbon accumulation in anthropogenically disturbed tropical forests and indicate that they can capture large amounts of carbon while recovering.

The 51st International Symposium on High Performance Liquid Phase Separations and Related Techniques, or HPLC 2023, was held in Duesseldorf, Germany, and it was chaired by Michael Lammerhofer (Tubingen) and [...]