Phosphorus addition enhances heterotrophic respiration but reduces root respiration in a subtropical plantation forest.

Soil respiration (Rs) is a major component of the global carbon (C) cycle and is influenced by the availability of nutrients such as phosphorus (P). However, the response of Rs to P addition in P-limited subtropical forest ecosystems and the underlying mechanisms remain poorly understood. To address this, we conducted a P addition experiment (50 kg P ha-1 yr-1) in a subtropical Chinese fir (Cunninghamia lanceolata) plantation forest. We separated Rs into heterotrophic respiration (Rh), root respiration (Rr), and mycorrhizal hyphal respiration (Rm), and quantified soil properties, microbial biomass (phospholipid fatty acid, PLFA), fungal community composition (ITS), and the activity of extracellular enzymes. Phosphorus addition significantly increased Rs and Rh, but decreased Rr and did not influence Rm. Further, P addition increased fungal, bacterial, and total PLFAs, and phenol oxidase activity. Conversely, P application decreased root biomass and did not alter the relative abundance of symbiotrophic fungi. Phosphorus enrichment therefore enhances soil C emissions by promoting organic matter decomposition by heterotrophic activity, rather than via increases in root or mycorrhizal respiration. This advances our mechanistic understanding of the relationship between fertility and soil respiration in subtropical forests, with implications for predicting soil C emissions under global change.

A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Chain of events analysis in diving accidents treated by the Royal Netherlands Navy 1966-2023.

Introduction: Diving injuries are influenced by a multitude of factors. Literature analysing the full chain of events in diving accidents influencing the occurrence of diving injuries is limited. A previously published 'chain of events analysis' (CEA) framework consists of five steps that may sequentially lead to a diving fatality. This study applied four of these steps to predominately non-lethal diving injuries and aims to determine the causes of diving injuries sustained by divers treated by the Diving Medical Centre of the Royal Netherlands Navy. Methods: This retrospective cohort study was performed on diving injuries treated by the Diving Medical Centre between 1966 and 2023. Baseline characteristics and information pertinent to all four steps of the reduced CEA model were extracted and recorded in a database. Results: A total of 288 cases met the inclusion criteria. In 111 cases, all four steps of the CEA model could be applied. Predisposing factors were identified in 261 (90%) cases, triggers in 142 (49%), disabling agents in 195 (68%), and 228 (79%) contained a (possible-) disabling condition. The sustained diving injury led to a fatality in seven cases (2%). The most frequent predisposing factor was health conditions (58%). Exertion (19%), primary diver errors (18%), and faulty equipment (17%) were the most frequently identified triggers. The ascent was the most frequent disabling agent (52%). Conclusions: The CEA framework was found to be a valuable tool in this analysis. Health factors present before diving were identified as the most frequent predisposing factors. Arterial gas emboli were the most lethal injury mechanism.

Monitoring SARS-CoV-2 genetic variability: A post-market surveillance workflow for combined bioinformatic and laboratory evaluation of commercial RT-PCR assay performance.

OBJECTIVE: The speed at which Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is mutating has made it necessary to frequently assess how these genomic changes impact the performance of diagnostic real-time polymerase chain reaction (RT-PCR) assays. Herein, we describe a generic three-step workflow to assess the effect of genomic mutations on inclusivity and sensitivity of RT-PCR assays. METHODS: Sequences collected from the Global Initiative on Sharing All Influenza Data (GISAID) were mapped to a SARS-CoV-2 reference genome to evaluate the position and prevalence of mismatches in the oligonucleotide-binding sites of the QIAstat-Dx, an RT-PCR panel designed to detect SARS-CoV-2. The frequency of mutations and their impact on melting temperature were assessed, and sequences flagged by risk-based criteria were examined in vitro. RESULTS: Out of 8,900,393 SARS-CoV-2 genome sequences analyzed, only 173 (0.0019%) genomes contained potentially critical mutations for the QIAstat-Dx; follow-up in-vitro testing confirmed no impact on the assays' performance. CONCLUSIONS: The current study demonstrates that SARS-CoV-2 genetic variants do not affect the performance of the QIAstat-Dx device. It is recommended that manufacturers incorporate this workflow into obligatory post-marketing surveillance activities, as this approach could potentially enhance genetic monitoring of their product.

New cyclophilin D inhibitor rescues mitochondrial and cognitive function in Alzheimer's disease.

Mitochondrial dysfunction is an early pathological feature of Alzheimer disease and plays a crucial role in the development and progression of Alzheimer's disease. Strategies to rescue mitochondrial function and cognition remain to be explored. Cyclophilin D (CypD), the peptidylprolyl isomerase F (PPIase), is a key component in opening the mitochondrial membrane permeability transition pore, leading to mitochondrial dysfunction and cell death. Blocking membrane permeability transition pore opening by inhibiting CypD activity is a promising therapeutic approach for Alzheimer's disease. However, there is currently no effective CypD inhibitor for Alzheimer's disease, with previous candidates demonstrating high toxicity, poor ability to cross the blood-brain barrier, compromised biocompatibility and low selectivity. Here, we report a new class of non-toxic and biocompatible CypD inhibitor, ebselen, using a conventional PPIase assay to screen a library of ∼2000 FDA-approved drugs with crystallographic analysis of the CypD-ebselen crystal structure (PDB code: 8EJX). More importantly, we assessed the effects of genetic and pharmacological blockade of CypD on Alzheimer's disease mitochondrial and glycolytic bioenergetics in Alzheimer's disease-derived mitochondrial cybrid cells, an ex vivo human sporadic Alzheimer's disease mitochondrial model, and on synaptic function, inflammatory response and learning and memory in Alzheimer's disease mouse models. Inhibition of CypD by ebselen protects against sporadic Alzheimer's disease- and amyloid-ß-induced mitochondrial and glycolytic perturbation, synaptic and cognitive dysfunction, together with suppressing neuroinflammation in the brain of Alzheimer's disease mouse models, which is linked to CypD-related membrane permeability transition pore formation. Thus, CypD inhibitors have the potential to slow the progression of neurodegenerative diseases, including Alzheimer's disease, by boosting mitochondrial bioenergetics and improving synaptic and cognitive function.

Disease activity 4.5 years after starting cladribine: experience in 264 patients with multiple sclerosis.

Background: Cladribine is an effective immunotherapy for people with multiple sclerosis (pwMS). Whilst most pwMS do not require re-treatment following standard dosing (two treatment courses), disease activity re-emerges in others. The characteristics of pwMS developing re-emerging disease activity remain incompletely understood. Objectives: To explore whether clinical and/or paraclinical baseline characteristics, including the degree of lymphocyte reduction, drug dose and lesions on magnetic resonance imaging (MRI) are associated with re-emerging disease activity. Design: Service evaluation in pwMS undergoing subcutaneous cladribine (SClad) treatment. Methods: Demographics, clinical, laboratory and MRI data of pwMS receiving two courses of SClad were extracted from health records. To assess associations of predictor variables with re-emerging disease activity, a series of Cox proportional hazards models was fitted (one for each predictor variable). Results: Of n = 264 pwMS 236 received two courses of SClad and were included in the analysis. Median follow-up was 4.5 years (3.9, 5.3) from the first, and 3.5 years (2.9, 4.3) from the last SClad administration. Re-emerging disease activity occurred in 57/236 pwMS (24%); 22/236 received further cladribine doses (SClad or cladribine tablets) at 36.7 months [median; interquartile range (IQR): 31.7, 42.1], and 22/236 other immunotherapies 18.9 months (13.0, 30.2) after their second course of SClad, respectively. Eligibility was based on MRI activity in 29, relapse in 5, both in 13, elevated cerebrospinal fluid neurofilament light chain level in 3, deterioration unrelated to relapse in 4 and other in 3. Only 36/57 of those eligible for additional immunotherapy had received a reduced dose of SClad for their second treatment course. Association was detected between re-emerging disease activity and (i) high baseline MRI activity and (ii) low second dose of SClad. Conclusion: Re-emerging disease activity was associated with baseline MRI activity and low dose second course of SClad.

Breakdown of the growth-mortality trade-off along a soil phosphorus gradient in a diverse tropical forest.

An ecological paradigm predicts that plant species adapted to low resource availability grow slower and live longer than those adapted to high resource availability when growing together. We tested this by using hierarchical Bayesian analysis to quantify variations in growth and mortality of ca 40 000 individual trees from greater than 400 species in response to limiting resources in the tropical forests of Panama. In contrast to theoretical expectations of the growth-mortality paradigm, we find that tropical tree species restricted to low-phosphorus soils simultaneously achieve faster growth rates and lower mortality rates than species restricted to high-phosphorus soils. This result demonstrates that adaptation to phosphorus limitation in diverse plant communities modifies the growth-mortality trade-off, with important implications for understanding long-term ecosystem dynamics.

Widespread frontoparietal fMRI activity is greatly affected by changes in criterion placement, not discriminability, during recognition memory and visual detection tests.

Widespread frontoparietal activity is consistently observed in recognition memory tests that compare studied ("target") versus unstudied ("nontarget") responses. However, there are conflicting accounts that ascribe various aspects of frontoparietal activity to mnemonic evidence versus decisional processes. According to Signal Detection Theory, recognition judgments require individuals to decide whether the memory strength of an item exceeds an evidence threshold-the decision criterion-for reporting previously studied items. Yet, most fMRI studies fail to manipulate both memory strength and decision criteria, making it difficult to appropriately identify frontoparietal activity associated with each process. In the current experiment, we manipulated both discriminability and decision criteria across recognition memory and visual detection tests during fMRI scanning to assess how frontoparietal activity is affected by each manipulation. Our findings revealed that maintaining a conservative versus liberal decision criterion drastically affects frontoparietal activity in target versus nontarget response contrasts for both recognition memory and visual detection tests. However, manipulations of discriminability showed virtually no differences in frontoparietal activity in target versus nontarget response or item contrasts. Comparing across task domains, we observed similar modulations of frontoparietal activity across criterion conditions, though the recognition memory task revealed larger activations in both magnitude and spatial extent in these contrasts. Nonetheless, there appears to be some domain specificity in frontoparietal activity associated with the maintenance of a conservative versus liberal criterion. We propose that widespread frontoparietal activity observed in target versus nontarget contrasts is largely attributable to response bias where increased activity may reflect inhibition of a prepotent response, which differs depending on whether a person maintains a conservative versus liberal decision criterion.

Disaster reconnaissance framework for sustainable post-disaster materials management.

A first foundational assessment is provided for disaster debris reconnaissance that includes identifying tools and techniques for reconnaissance activities, identifying challenges in field reconnaissance, and identifying and developing preliminary guidelines and standards based on advancements from a workshop held in 2022. In this workshop, reconnaissance activities were analyzed in twofold: in relation to post-disaster debris and waste materials and in relation to waste management infrastructure. A four-phase timeline was included to capture the full lifecycle of management activities ranging from collection to temporary storage to final management route: pre-disaster or pre-reconnaissance, post-disaster response (days/weeks), short-term recovery (weeks/months), and long-term recovery (months/years). For successful reconnaissance, objectives of field activities and data collection needs; data types and metrics; and measurement and determination methods need to be identified. A reconnaissance framework, represented using a 3x2x2x4 matrix, is proposed to incorporate data attributes (tools, challenges, guides), reconnaissance attributes (debris, infrastructure; factors, actions), and time attributes (pre-event, response, short-term, long-term). This framework supports field reconnaissance missions and protocols that are longitudinally based and focused on post-disaster waste material and infrastructure metrics that advance sustainable materials management practices. To properly frame and develop effective reconnaissance activities, actions for all data attributes (tools, challenges, guides) are proposed to integrate sustainability and resilience considerations. While existing metrics, tools, methods, standards, and protocols can be adapted for sustainable post-disaster materials management reconnaissance, development of new approaches are needed for addressing unique aspects of disaster debris management.

Predicting variable gene content in Escherichia coli using conserved genes.

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%-90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943-0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including "hypothetical proteins" was accurately predicted (F1 = 0.902 [0.898-0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876-0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data. IMPORTANCE Having the ability to predict the protein-encoding gene content of a genome is important for assessing genome quality, binning genomes from shotgun metagenomic assemblies, and assessing risk due to the presence of antimicrobial resistance and other virulence genes. In this study, we built a set of binary classifiers for predicting the presence or absence of variable genes occurring in 10%-90% of all publicly available E. coli genomes. Overall, the results show that a large portion of the E. coli variable gene content can be predicted with high accuracy, including genes with functions relating to horizontal gene transfer. This study offers a strategy for predicting gene content using limited input sequence data.

Assessing the Role of Systems Thinking for Stocker Cattle Operations.

Bovine respiratory disease (BRD) is recognized as a complex multifactorial disease often resulting in significant economic losses for the stocker industry through reduced health and performance of feeder calves. Conventional approaches to manage BRD in stocker production systems can be challenged with a restricted view of the system, most importantly the structure, which drives the behavior of the system and fails to anticipate unintended consequences. The translation and implementation of systems thinking into veterinary medicine can offer an alternative method to problem-solving. Fundamental to the success of the systems thinker is the conceptualization of the Iceberg Diagram intended to identify root causes of complex problems such as BRD. Furthermore, veterinary and animal health professionals are well-positioned to serve as facilitators to establish creative tension, the positive energy necessary to identify high-leverage strategies. The interrelationships and interconnected behaviors of complex stocker systems warrant an understanding of various archetypes. Archetypes provide the systems thinker with a decision-making tool to explore tactics in a nonlinear fashion for the purpose of recognizing short- and long-term outcomes. Developing literacy in the discipline of systems thinking will further equip professionals with the skillset necessary to address the multitude of challenges ingrained in complex stocker cattle systems.

Beef Production Health Systems: Perspectives of a Trained Systems Thinker.

Managing beef cattle health across a segmented production and marketing system can be thought of as a perplexing problem due to the counterintuitive responses of the system to existing management strategies. The process of thinking in systems to recognize and develop systems thinking archetypes is emphasized. The 2 cases discussed are brought together to explore deeper but often unrecognized structure that contributes to reinforcing problematic behavior, the structure of mental models. Training in systems thinking and system dynamics modeling equips the scientist to translate within and between scientific disciplines, a much-needed skill for addressing current and emerging beef production problems.

Enhancing Phytate Availability in Soils and Phytate-P Acquisition by Plants: A Review.

Phytate (myo-inositol hexakisphosphate salts) can constitute a large fraction of the organic P in soils. As a more recalcitrant form of soil organic P, up to 51 million metric tons of phytate accumulate in soils annually, corresponding to ∼65% of the P fertilizer application. However, the availability of phytate is limited due to its strong binding to soils via its highly-phosphorylated inositol structure, with sorption capacity being ∼4 times that of orthophosphate in soils. Phosphorus (P) is one of the most limiting macronutrients for agricultural productivity. Given that phosphate rock is a finite resource, coupled with the increasing difficulty in its extraction and geopolitical fragility in supply, it is anticipated that both economic and environmental costs of P fertilizer will greatly increase. Therefore, optimizing the use of soil phytate-P can potentially enhance the economic and environmental sustainability of agriculture production. To increase phytate-P availability in the rhizosphere, plants and microbes have developed strategies to improve phytate solubility and mineralization by secreting mobilizing agents including organic acids and hydrolyzing enzymes including various phytases. Though we have some understanding of phytate availability and phytase activity in soils, the limiting steps for phytate-P acquisition by plants proposed two decades ago remain elusive. Besides, the relative contribution of plant- and microbe-derived phytases, including those from mycorrhizas, in improving phytate-P utilization is poorly understood. Hence, it is important to understand the processes that influence phytate-P acquisition by plants, thereby developing effective molecular biotechnologies to enhance the dynamics of phytate in soil. However, from a practical view, phytate-P acquisition by plants competes with soil P fixation, so the ability of plants to access stable phytate must be evaluated from both a plant and soil perspective. Here, we summarize information on phytate availability in soils and phytate-P acquisition by plants. In addition, agronomic approaches and biotechnological strategies to improve soil phytate-P utilization by plants are discussed, and questions that need further investigation are raised. The information helps to better improve phytate-P utilization by plants, thereby reducing P resource inputs and pollution risks to the wider environment.

ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and challenges of confined and extensive precision livestock production.

Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confined operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability. However, advancements in technology have helped to overcome many of these challenges. Investment in precision technologies is growing within the livestock sector, requiring the need to assess opportunities and challenges associated with implementation to enhance livestock production systems. In this review, precision livestock farming and digital livestock farming are explained in the context of a logical and iterative five-step process to successfully integrate precision livestock measurement and management tools, emphasizing the need for precision system models (PSMs). This five-step process acts as a guide to realize anticipated benefits from precision technologies and avoid unintended consequences. Consequently, the synthesis of precision livestock and modeling examples and key case studies help highlight past challenges and current opportunities within confined and extensive systems. Successfully developing PSM requires appropriate model(s) selection that aligns with desired management goals and precision technology capabilities. Therefore, it is imperative to consider the entire system to ensure that precision technology integration achieves desired goals while remaining economically and managerially sustainable. Achieving long-term success using precision technology requires the next generation of animal scientists to obtain additional skills to keep up with the rapid pace of technology innovation. Building workforce capacity and synergistic relationships between research, industry, and managers will be critical. As the process of precision technology adoption continues in more challenging and harsh, extensive systems, it is likely that confined operations will benefit from required advances in precision technology and PSMs, ultimately strengthening the benefits from precision technology to achieve short- and long-term goals.

Interest and investment in precision technologies are growing within the livestock sector. Though these technologies offer many promises of increased efficiency and reduced inputs, there is a need to assess the opportunities and challenges associated with precision technology implementation in livestock production systems. In this review, precision livestock measurement and management tools are explained in the context of a logical and iterative five-step process that highlights the need for systems computer modeling to realize anticipated benefits from these technologies and avoid unintended consequences. This review includes key case studies to highlight past challenges and current opportunities within operations that house animals in a central area or building with sufficient infrastructure (confined livestock production systems) and other operation settings that utilize large grasslands that contain far less infrastructure (extensive livestock production systems). The key to precision livestock management success is training the next generation of animal scientists in computer modeling, precision technologies, computer programming, and data science while still being grounded in traditional animal science principles.

Novel phytase PvPHY1 from the As-hyperaccumulator Pteris vittata enhances P uptake and phytate hydrolysis, and inhibits As translocation in Plant.

Developing P-efficient plants helps improve P uptake from soils with low-available P and reduce environmental damage by P runoff. Here, we investigated a novel root-specific phytase PvPHY1 from As-hyperaccumulator Pteris vittata, which can efficiently utilize phytate, a recalcitrant organic phosphorus in soil. Unlike other plants, expression of PvPHY1 in P. vittata was greater in the roots than the fronds. A pure phytase with considerable activity was obtained via prokaryotic expression. Expressing PvPHY1 in tobacco (PvPHY1-Ex) enhanced its growth (2.8 to 3.5-3.9 g per plant) and increased its P accumulation by 10-50% under low- and adequate-P conditions. Further, PvPHY1-Ex tobacco showed 25-32% lower intracellular phytate and 30-56% higher inorganic P in the roots, likely due to phytase-mediated hydrolysis of phytate. Decrease of phytate levels up-regulated phosphate transporter genes (NbPht1;1, NbPht1;2 and NbPht1;6), leading to greater P and As uptake. However, As translocation to the shoots was low, probably due to competition from increased inorganic P via phytate hydrolysis. As such, PvPHY1 facilitated P uptake from soils and phytate hydrolysis in plants, thereby promoting tobacco growth. Overall, PvPHY1 from P. vittata helps better understand the novel phytase to increase soil P utilization efficiency, thereby reducing P fertilizer requirements for crop production.

Factors contributing to CSF NfL reduction over time in those starting treatment for multiple sclerosis: An observational study.

BACKGROUND: In multiple sclerosis (MS) neurofilament light chain (NfL) is a marker of neuronal damage secondary to inflammation and neurodegeneration. NfL levels drop after commencement of disease-modifying treatment, especially the highly active ones. However, the factors that influence this drop are unknown. OBJECTIVE: To examine the patient and treatment-related factors that influence CSF NfL before and after starting treatment. METHODS: Eligible patients across two centres with two CSF NfL measurements, clinical and MRI data were included as part of an observational cohort study. RESULTS: Data were available in 61 patients, of which 40 were untreated at the first CSF sampling (T1) and treated at the second (T2; mean T1-T2: 19 months). CSF NfL reduction correlated with age (beta = 1.24 95%CI(1.07,1.43); R2 = 0.17; p = 0.005), Expanded Disability Status Scale (EDSS) (beta = 1.12 95%CI(1.00,1.25); R2 = 0.21; p = 0.05) and the type of MS (beta = 0.63 95%CI(0.43, 0.92); R2 = 0.12; p = 0.018; reference=relapsing MS). The treatment effect on a baseline NfL of 702 pg/mL was 451 pg/ml 95%CI(374,509) in a 30-year-old versus 228 pg/ml 95%CI(63,350) in a 60-year-old. There was no association in CSF NfL reduction with BMI, disease duration or sex. In cladribine- and alemtuzumab-treated patients, the CSF NfL T2/T1 ratio did not correlate with lymphocyte depletion rate at 23 weeks. CONCLUSIONS: In this observational study, we found that factors reflecting early disease stage, including a younger age, lower disability and relapsing MS were associated with treatment response in CSF NfL. Other factors were not found to be related, including lymphopaenia in highly-active treatments.

Evaluation of remote assessments for multiple sclerosis in an in-home setting.

BACKGROUND: There is an urgent clinical need for reliable remote monitoring methods in Multiple Sclerosis (MS). We evaluated the use of remotely patient-recorded timed 25-foot walk (rT25FW) and nine-hole peg test (r9HPT). METHODS: Seventy-one people with MS completed a previously-validated online EDSS (webEDSS) and r9HPT, and 108 completed the webEDSS and rT25FW. RESULTS: There was a mild-moderate positive correlation between webEDSS and rT25FW, and no significant correlation between webEDSS and r9HPT. Distributions of rT25FW and r9HPT times were positively skewed. CONCLUSIONS: Our results provide pilot evidence that remote monitoring of MS is potentially valid but requires refinement before wide-scale implementation. With a median EDSS of 4.5 and EDSS range of 0 - 8.0, at least some patients with ambulatory difficulty are able to complete the assessments.

Nitrogen deposition accelerates soil carbon sequestration in tropical forests.

Terrestrial ecosystem carbon (C) sequestration plays an important role in ameliorating global climate change. While tropical forests exert a disproportionately large influence on global C cycling, there remains an open question on changes in below-ground soil C stocks with global increases in nitrogen (N) deposition, because N supply often does not constrain the growth of tropical forests. We quantified soil C sequestration through more than a decade of continuous N addition experiment in an N-rich primary tropical forest. Results showed that long-term N additions increased soil C stocks by 7 to 21%, mainly arising from decreased C output fluxes and physical protection mechanisms without changes in the chemical composition of organic matter. A meta-analysis further verified that soil C sequestration induced by excess N inputs is a general phenomenon in tropical forests. Notably, soil N sequestration can keep pace with soil C, based on consistent C/N ratios under N additions. These findings provide empirical evidence that below-ground C sequestration can be stimulated in mature tropical forests under excess N deposition, which has important implications for predicting future terrestrial sinks for both elevated anthropogenic CO2 and N deposition. We further developed a conceptual model hypothesis depicting how soil C sequestration happens under chronic N deposition in N-limited and N-rich ecosystems, suggesting a direction to incorporate N deposition and N cycling into terrestrial C cycle models to improve the predictability on C sink strength as enhanced N deposition spreads from temperate into tropical systems.

Extinction at the end-Cretaceous and the origin of modern Neotropical rainforests.

The end-Cretaceous event was catastrophic for terrestrial communities worldwide, yet its long-lasting effect on tropical forests remains largely unknown. We quantified plant extinction and ecological change in tropical forests resulting from the end-Cretaceous event using fossil pollen (>50,000 occurrences) and leaves (>6000 specimens) from localities in Colombia. Late Cretaceous (Maastrichtian) rainforests were characterized by an open canopy and diverse plant-insect interactions. Plant diversity declined by 45% at the Cretaceous-Paleogene boundary and did not recover for ~6 million years. Paleocene forests resembled modern Neotropical rainforests, with a closed canopy and multistratal structure dominated by angiosperms. The end-Cretaceous event triggered a long interval of low plant diversity in the Neotropics and the evolutionary assembly of today's most diverse terrestrial ecosystem.

Seasonal upwelling reduces herbivore control of tropical rocky intertidal algal communities.

Communities are shaped by a variety of ecological and environmental processes, each acting at different spatial scales. Seminal research on rocky shores highlighted the effects of consumers as local determinants of primary productivity and community assembly. However, it is now clear that the species interactions shaping communities at local scales are themselves regulated by large-scale oceanographic processes that generate regional variation in resource availability. Upwelling events deliver nutrient-rich water to coastal ecosystems, influencing primary productivity and algae-herbivore interactions. Despite the potential for upwelling to alter top-down control by herbivores, we know relatively little about the coupling between oceanographic processes and herbivory on tropical rocky shores, where herbivore effects on producers are considered to be strong and nutrient levels are considered to be limiting. By replicating seasonal molluscan herbivore exclusion experiments across three regions exposed to varying intensity of seasonal upwelling, separated by hundreds of kilometers along Panama's Pacific coast, we examine large-scale environmental determinants of consumer effects and community structure on tropical rocky shores. At sites experiencing seasonal upwelling, grazers strongly limited macroalgal cover when upwelling was absent, leading to dominance by crustose algae. As nutrients increased and surface water cooled during upwelling events, increases in primary productivity temporarily weakened herbivory, allowing foliose, turf and filamentous algae to replace crusts. Meanwhile, grazer effects were persistently strong at sites without seasonal upwelling. Our results confirm that herbivores are key determinants of tropical algal cover, and that the mollusk grazing guild can control initial stages of macroalgal succession. However, our focus on regional oceanographic conditions revealed that bottom-up processes regulate top-down control on tropical shorelines. This study expands on the extensive body of work highlighting the influence of upwelling on local ecological processes by demonstrating that nutrient subsidies delivered by upwelling events can weaken herbivory in tropical rocky shores.