The enduring world forest carbon sink.

The uptake of carbon dioxide (CO2) by terrestrial ecosystems is critical for moderating climate change1. To provide a ground-based long-term assessment of the contribution of forests to terrestrial CO2 uptake, we synthesized in situ forest data from boreal, temperate and tropical biomes spanning three decades. We found that the carbon sink in global forests was steady, at 3.6 ± 0.4 Pg C yr-1 in the 1990s and 2000s, and 3.5 ± 0.4 Pg C yr-1 in the 2010s. Despite this global stability, our analysis revealed some major biome-level changes. Carbon sinks have increased in temperate (+30 ± 5%) and tropical regrowth (+29 ± 8%) forests owing to increases in forest area, but they decreased in boreal (-36 ± 6%) and tropical intact (-31 ± 7%) forests, as a result of intensified disturbances and losses in intact forest area, respectively. Mass-balance studies indicate that the global land carbon sink has increased2, implying an increase in the non-forest-land carbon sink. The global forest sink is equivalent to almost half of fossil-fuel emissions (7.8 ± 0.4 Pg C yr-1 in 1990-2019). However, two-thirds of the benefit from the sink has been negated by tropical deforestation (2.2 ± 0.5 Pg C yr-1 in 1990-2019). Although the global forest sink has endured undiminished for three decades, despite regional variations, it could be weakened by ageing forests, continuing deforestation and further intensification of disturbance regimes1. To protect the carbon sink, land management policies are needed to limit deforestation, promote forest restoration and improve timber-harvesting practices1,3.

Consistent patterns of common species across tropical tree communities.

Trees structure the Earth's most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1-6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth's 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world's most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.

Hydroclimatic vulnerability of peat carbon in the central Congo Basin.

The forested swamps of the central Congo Basin store approximately 30 billion metric tonnes of carbon in peat1,2. Little is known about the vulnerability of these carbon stocks. Here we investigate this vulnerability using peat cores from a large interfluvial basin in the Republic of the Congo and palaeoenvironmental methods. We find that peat accumulation began at least at 17,500 calibrated years before present (cal. yr BP; taken as AD 1950). Our data show that the peat that accumulated between around 7,500 to around 2,000 cal. yr BP is much more decomposed compared with older and younger peat. Hydrogen isotopes of plant waxes indicate a drying trend, starting at approximately 5,000 cal. yr BP and culminating at approximately 2,000 cal. yr BP, coeval with a decline in dominant swamp forest taxa. The data imply that the drying climate probably resulted in a regional drop in the water table, which triggered peat decomposition, including the loss of peat carbon accumulated prior to the onset of the drier conditions. After approximately 2,000 cal. yr BP, our data show that the drying trend ceased, hydrologic conditions stabilized and peat accumulation resumed. This reversible accumulation-loss-accumulation pattern is consistent with other peat cores across the region, indicating that the carbon stocks of the central Congo peatlands may lie close to a climatically driven drought threshold. Further research should quantify the combination of peatland threshold behaviour and droughts driven by anthropogenic carbon emissions that may trigger this positive carbon cycle feedback in the Earth system.

High aboveground carbon stock of African tropical montane forests.

Tropical forests store 40-50 per cent of terrestrial vegetation carbon1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests2. Owing to climatic and soil changes with increasing elevation3, AGC stocks are lower in tropical montane forests compared with lowland forests2. Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane2,5,6 and lowland7 forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa8. We find that the low stem density and high abundance of large trees of African lowland forests4 is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse9,10 and carbon-rich ecosystems.

Fluorescent Probes for Disease Diagnosis.

The identification and detection of disease-related biomarkers is essential for early clinical diagnosis, evaluating disease progression, and for the development of therapeutics. Possessing the advantages of high sensitivity and selectivity, fluorescent probes have become effective tools for monitoring disease-related active molecules at the cellular level and in vivo. In this review, we describe current fluorescent probes designed for the detection and quantification of key bioactive molecules associated with common diseases, such as organ damage, inflammation, cancers, cardiovascular diseases, and brain disorders. We emphasize the strategies behind the design of fluorescent probes capable of disease biomarker detection and diagnosis and cover some aspects of combined diagnostic/therapeutic strategies based on regulating disease-related molecules. This review concludes with a discussion of the challenges and outlook for fluorescent probes, highlighting future avenues of research that should enable these probes to achieve accurate detection and identification of disease-related biomarkers for biomedical research and clinical applications.

Asynchronous carbon sink saturation in African and Amazonian tropical forests.

Structurally intact tropical forests sequestered about half of the global terrestrial carbon uptake over the 1990s and early 2000s, removing about 15 per cent of anthropogenic carbon dioxide emissions1-3. Climate-driven vegetation models typically predict that this tropical forest 'carbon sink' will continue for decades4,5. Here we assess trends in the carbon sink using 244 structurally intact African tropical forests spanning 11 countries, compare them with 321 published plots from Amazonia and investigate the underlying drivers of the trends. The carbon sink in live aboveground biomass in intact African tropical forests has been stable for the three decades to 2015, at 0.66 tonnes of carbon per hectare per year (95 per cent confidence interval 0.53-0.79), in contrast to the long-term decline in Amazonian forests6. Therefore the carbon sink responses of Earth's two largest expanses of tropical forest have diverged. The difference is largely driven by carbon losses from tree mortality, with no detectable multi-decadal trend in Africa and a long-term increase in Amazonia. Both continents show increasing tree growth, consistent with the expected net effect of rising atmospheric carbon dioxide and air temperature7-9. Despite the past stability of the African carbon sink, our most intensively monitored plots suggest a post-2010 increase in carbon losses, delayed compared to Amazonia, indicating asynchronous carbon sink saturation on the two continents. A statistical model including carbon dioxide, temperature, drought and forest dynamics accounts for the observed trends and indicates a long-term future decline in the African sink, whereas the Amazonian sink continues to weaken rapidly. Overall, the uptake of carbon into Earth's intact tropical forests peaked in the 1990s. Given that the global terrestrial carbon sink is increasing in size, independent observations indicating greater recent carbon uptake into the Northern Hemisphere landmass10 reinforce our conclusion that the intact tropical forest carbon sink has already peaked. This saturation and ongoing decline of the tropical forest carbon sink has consequences for policies intended to stabilize Earth's climate.

Visual hallucinations in Parkinson's disease: spotlight on central cholinergic dysfunction.

Visual hallucinations are a common non-motor feature of Parkinson's disease and have been associated with accelerated cognitive decline, increased mortality and early institutionalisation. Despite their prevalence and negative impact on patient outcomes, the repertoire of treatments aimed at addressing this troubling symptom is limited. Over the last two decades, significant contributions have been made in uncovering the pathological and functional mechanisms of visual hallucinations, bringing us closer to the development of a comprehensive neurobiological framework. Convergent evidence now suggests that degeneration within the central cholinergic system may play a significant role in the genesis and progression of visual hallucinations. Here, we outline how cholinergic dysfunction may serve as a potential unifying neurobiological substrate underlying the multifactorial and dynamic nature of visual hallucinations. Drawing upon previous theoretical models, we explore the impact that alterations in cholinergic neurotransmission has on the core cognitive processes pertinent to abnormal perceptual experiences. We conclude by highlighting that a deeper understanding of cholinergic neurobiology and individual pathophysiology may help to improve established and emerging treatment strategies for the management of visual hallucinations and psychotic symptoms in Parkinson's disease.

Abnormal higher-order network interactions in Parkinson's disease visual hallucinations.

Visual hallucinations in Parkinson's disease can be viewed from a systems-level perspective, whereby dysfunctional communication between brain networks responsible for perception predisposes a person to hallucinate. To this end, abnormal functional interactions between higher-order and primary sensory networks have been implicated in the pathophysiology of visual hallucinations in Parkinson's disease, however the precise signatures remain to be determined. Dimensionality reduction techniques offer a novel means for simplifying the interpretation of multidimensional brain imaging data, identifying hierarchical patterns in the data that are driven by both within- and between-functional network changes. Here, we applied two complementary non-linear dimensionality reduction techniques-diffusion-map embedding and t-distributed stochastic neighbour embedding (t-SNE)-to resting state functional MRI data, in order to characterize the altered functional hierarchy associated with susceptibility to visual hallucinations. Our study involved 77 people with Parkinson's disease (31 with hallucinations; 46 without hallucinations) and 19 age-matched healthy control subjects. In patients with visual hallucinations, we found compression of the unimodal-heteromodal gradient consistent with increased functional integration between sensory and higher order networks. This was mirrored in a traditional functional connectivity analysis, which showed increased connectivity between the visual and default mode networks in the hallucinating group. Together, these results suggest a route by which higher-order regions may have excessive influence over earlier sensory processes, as proposed by theoretical models of hallucinations across disorders. By contrast, the t-SNE analysis identified distinct alterations in prefrontal regions, suggesting an additional layer of complexity in the functional brain network abnormalities implicated in hallucinations, which was not apparent in traditional functional connectivity analyses. Together, the results confirm abnormal brain organization associated with the hallucinating phenotype in Parkinson's disease and highlight the utility of applying convergent dimensionality reduction techniques to investigate complex clinical symptoms. In addition, the patterns we describe in Parkinson's disease converge with those seen in other conditions, suggesting that reduced hierarchical differentiation across sensory-perceptual systems may be a common transdiagnostic vulnerability in neuropsychiatric disorders with perceptual disturbances.

Fluorescent small molecule donors.

Small molecule donors (SMDs) play subtle roles in the signaling mechanism and disease treatments. While many excellent SMDs have been developed, dosage control, targeted delivery, spatiotemporal feedback, as well as the efficiency evaluation of small molecules are still key challenges. Accordingly, fluorescent small molecule donors (FSMDs) have emerged to meet these challenges. FSMDs enable controllable release and non-invasive real-time monitoring, providing significant advantages for drug development and clinical diagnosis. Integration of FSMDs with chemotherapeutic, photodynamic or photothermal properties can take full advantage of each mode to enhance therapeutic efficacy. Given the remarkable properties and the thriving development of FSMDs, we believe a review is needed to summarize the design, triggering strategies and tracking mechanisms of FSMDs. With this review, we compiled FSMDs for most small molecules (nitric oxide, carbon monoxide, hydrogen sulfide, sulfur dioxide, reactive oxygen species and formaldehyde), and discuss recent progress concerning their molecular design, structural classification, mechanisms of generation, triggered release, structure-activity relationships, and the fluorescence response mechanism. Firstly, from the large number of fluorescent small molecular donors available, we have organized the common structures for producing different types of small molecules, providing a general strategy for the development of FSMDs. Secondly, we have classified FSMDs in terms of the respective donor types and fluorophore structures. Thirdly, we discuss the mechanisms and factors associated with the controlled release of small molecules and the regulation of the fluorescence responses, from which universal guidelines for optical properties and structure rearrangement were established, mainly involving light-controlled, enzyme-activated, reactive oxygen species-triggered, biothiol-triggered, single-electron reduction, click chemistry, and other triggering mechanisms. Fourthly, representative applications of FSMDs for trackable release, and evaluation monitoring, as well as for visible in vivo treatment are outlined, to illustrate the potential of FSMDs in drug screening and precision medicine. Finally, we discuss the opportunities and remaining challenges for the development of FSMDs for practical and clinical applications, which we anticipate will stimulate the attention of researchers in the diverse fields of chemistry, pharmacology, chemical biology and clinical chemistry. With this review, we hope to impart new understanding thereby enabling the rapid development of the next generation of FSMDs.

Predicting neurodegeneration from sleep related biofluid changes.

Sleep-wake disturbances are common in neurodegenerative diseases and may occur years before the clinical diagnosis, potentially either representing an early stage of the disease itself or acting as a pathophysiological driver. Therefore, discovering biomarkers that identify individuals with sleep-wake disturbances who are at risk of developing neurodegenerative diseases will allow early diagnosis and intervention. Given the association between sleep and neurodegeneration, the most frequently analyzed fluid biomarkers in people with sleep-wake disturbances to date include those directly associated with neurodegeneration itself, such as neurofilament light chain, phosphorylated tau, amyloid-beta and alpha-synuclein. Abnormalities in these biomarkers in patients with sleep-wake disturbances are considered as evidence of an underlying neurodegenerative process. Levels of hormonal sleep-related biomarkers such as melatonin, cortisol and orexin are often abnormal in patients with clinical neurodegenerative diseases, but their relationships with the more standard neurodegenerative biomarkers remain unclear. Similarly, it is unclear whether other chronobiological/circadian biomarkers, such as disrupted clock gene expression, are causal factors or a consequence of neurodegeneration. Current data would suggest that a combination of fluid biomarkers may identify sleep-wake disturbances that are most predictive for the risk of developing neurodegenerative disease with more optimal sensitivity and specificity.

Understanding REM Sleep Behavior Disorder through Functional MRI: A Systematic Review.

Neuroimaging studies in rapid eye movement sleep behavior disorder (RBD) can inform fundamental questions about the pathogenesis of Parkinson's disease (PD). Across modalities, functional magnetic resonance imaging (fMRI) may be better suited to identify changes between neural networks in the earliest stages of Lewy body diseases when structural changes may be subtle or absent. This review synthesizes the findings from all fMRI studies of RBD to gain further insight into the pathophysiology and progression of Lewy body diseases. A total of 32 studies were identified using a systematic review conducted according to PRISMA guidelines between January 2000 to February 2024 for original fMRI studies in patients with either isolated RBD (iRBD) or RBD secondary to PD. Common functional alterations were detectable in iRBD patients compared with healthy controls across brainstem nuclei, basal ganglia, frontal and occipital lobes, and whole brain network measures. Patients with established PD and RBD demonstrated decreased functional connectivity across the whole brain and brainstem nuclei, but increased functional connectivity in the cerebellum and frontal lobe compared with those PD patients without RBD. Finally, longitudinal changes in resting state functional connectivity were found to track with disease progression. Currently, fMRI studies in RBD have demonstrated early signatures of neurodegeneration across both motor and non-motor pathways. Although more work is needed, such findings have the potential to inform our understanding of disease, help to distinguish between prodromal PD and prodromal dementia with Lewy bodies, and support the development of fMRI-based outcome measures of phenoconversion and progression in future disease modifying trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Development of Redox-Active Lyotropic Lipid Cubic Phases for Biosensing Platforms.

Enzyme-based electrochemical biosensors play an important role in point-of-care diagnostics for personalized medicine. For such devices, lipid cubic phases (LCP) represent an attractive method to immobilize enzymes onto conductive surfaces with no need for chemical linking. However, research has been held back by the lack of effective strategies to stably co-immobilize enzymes with a redox shuttle that enhances the electrical connection between the enzyme redox center and the electrode. In this study, we show that a monoolein (MO) LCP system doped with an amphiphilic redox mediator (ferrocenylmethyl)dodecyldimethylammonium bromide (Fc12) can be used for enzyme immobilization to generate an effective biosensing platform. Small-angle X-ray scattering (SAXS) showed that MO LCP can incorporate Fc12 while maintaining the Pn3m symmetry morphology. Cyclic voltammograms of Fc12/MO showed quasi-reversible behavior, which implied that Fc12 was able to freely diffuse in the lipid membrane of LCP with a diffusion coefficient of 1.9 ± 0.2 × 10-8 cm2 s-1 at room temperature. Glucose oxidase (GOx) was then chosen as a model enzyme and incorporated into 0.2%Fc12/MO to evaluate the activity of the platform. GOx hosted in 0.2%Fc12/MO followed Michaelis-Menten kinetics toward glucose with a KM and Imax of 8.9 ± 0.5 mM and 1.4 ± 0.2 µA, respectively, and a linearity range of 2-17 mM glucose. Our results therefore demonstrate that GOx immobilized onto 0.2% Fc12/MO is a suitable platform for the electrochemical detection of glucose.

Mitochondrial function-associated genes underlie cortical atrophy in prodromal synucleinopathies.

Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49-87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41-88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks.

Progression of clinical markers in prodromal Parkinson's disease and dementia with Lewy bodies: a multicentre study.

The neurodegenerative synucleinopathies, including Parkinson's disease and dementia with Lewy bodies, are characterized by a typically lengthy prodromal period of progressive subclinical motor and non-motor manifestations. Among these, idiopathic REM sleep behaviour disorder is a powerful early predictor of eventual phenoconversion, and therefore represents a critical opportunity to intervene with neuroprotective therapy. To inform the design of randomized trials, it is essential to study the natural progression of clinical markers during the prodromal stages of disease in order to establish optimal clinical end points. In this study, we combined prospective follow-up data from 28 centres of the International REM Sleep Behavior Disorder Study Group representing 12 countries. Polysomnogram-confirmed REM sleep behaviour disorder subjects were assessed for prodromal Parkinson's disease using the Movement Disorder Society criteria and underwent periodic structured sleep, motor, cognitive, autonomic and olfactory testing. We used linear mixed-effect modelling to estimate annual rates of clinical marker progression stratified by disease subtype, including prodromal Parkinson's disease and prodromal dementia with Lewy bodies. In addition, we calculated sample size requirements to demonstrate slowing of progression under different anticipated treatment effects. Overall, 1160 subjects were followed over an average of 3.3 ± 2.2 years. Among clinical variables assessed continuously, motor variables tended to progress faster and required the lowest sample sizes, ranging from 151 to 560 per group (at 50% drug efficacy and 2-year follow-up). By contrast, cognitive, olfactory and autonomic variables showed modest progression with higher variability, resulting in high sample sizes. The most efficient design was a time-to-event analysis using combined milestones of motor and cognitive decline, estimating 117 per group at 50% drug efficacy and 2-year trial duration. Finally, while phenoconverters showed overall greater progression than non-converters in motor, olfactory, cognitive and certain autonomic markers, the only robust difference in progression between Parkinson's disease and dementia with Lewy bodies phenoconverters was in cognitive testing. This large multicentre study demonstrates the evolution of motor and non-motor manifestations in prodromal synucleinopathy. These findings provide optimized clinical end points and sample size estimates to inform future neuroprotective trials.

Unusual Regio- and Chemoselectivity in Oxidation of Pyrroles and Indoles Enabled by a Thianthrenium Salt Intermediate.

A dearomative oxidation of pyrroles to Δ3-pyrrol-2-ones is described, which employs a sulfoxide as oxidant, in conjunction with a carboxylic acid anhydride and a Brønsted acid additive. 3-substituted pyrroles undergo regioselective oxidation to give the product isomer in which oxygen has been introduced at the more hindered position. Regioselectivity is rationalized by a proposed mechanism that proceeds by initial thianthrenium introduction at the less-hindered pyrrole α-position, followed by distal attack of an oxygen nucleophile and subsequent elimination of thianthrene. The same reaction conditions are also able to effect a chemoselective oxidation of indoles to indolin-3-ones and additionally of indolin-3-ones to 2-hydroxyindolin-3-ones. Here again, the regio- and chemoselectivities are rationalized through the intermediacy of a thianthrenium salt.

Photochemical Fingerprinting Is a Sensitive Probe for the Detection of Synthetic Cannabinoid Receptor Agonists; toward Robust Point-of-Care Detection.

With synthetic cannabinoid receptor agonist (SCRA) use still prevalent across Europe and structurally advanced generations emerging, it is imperative that drug detection methods advance in parallel. SCRAs are a chemically diverse and evolving group, which makes rapid detection challenging. We have previously shown that fluorescence spectral fingerprinting (FSF) has the potential to provide rapid assessment of SCRA presence directly from street material with minimal processing and in saliva. Enhancing the sensitivity and discriminatory ability of this approach has high potential to accelerate the delivery of a point-of-care technology that can be used confidently by a range of stakeholders, from medical to prison staff. We demonstrate that a range of structurally distinct SCRAs are photochemically active and give rise to distinct FSFs after irradiation. To explore this in detail, we have synthesized a model series of compounds which mimic specific structural features of AM-694. Our data show that FSFs are sensitive to chemically conservative changes, with evidence that this relates to shifts in the electronic structure and cross-conjugation. Crucially, we find that the photochemical degradation rate is sensitive to individual structures and gives rise to a specific major product, the mechanism and identification of which we elucidate through density-functional theory (DFT) and time-dependent DFT. We test the potential of our hybrid "photochemical fingerprinting" approach to discriminate SCRAs by demonstrating SCRA detection from a simulated smoking apparatus in saliva. Our study shows the potential of tracking photochemical reactivity via FSFs for enhanced discrimination of SCRAs, with successful integration into a portable device.

Motor cortical excitability and pre-supplementary motor area neurochemistry in healthy adults with substantia nigra hyperechogenicity.

Substantia nigra (SN) hyperechogenicity, viewed with transcranial ultrasound, is a risk marker for Parkinson's disease. We hypothesized that SN hyperechogenicity in healthy adults aged 50-70 years is associated with reduced short-interval intracortical inhibition in primary motor cortex, and that the reduced intracortical inhibition is associated with neurochemical markers of activity in the pre-supplementary motor area (pre-SMA). Short-interval intracortical inhibition and intracortical facilitation in primary motor cortex was assessed with paired-pulse transcranial magnetic stimulation in 23 healthy adults with normal (n = 14; 61 ± 7 yrs) or abnormally enlarged (hyperechogenic; n = 9; 60 ± 6 yrs) area of SN echogenicity. Thirteen of these participants (7 SN- and 6 SN+) also underwent brain magnetic resonance spectroscopy to investigate pre-SMA neurochemistry. There was no relationship between area of SN echogenicity and short-interval intracortical inhibition in the ipsilateral primary motor cortex. There was a significant positive relationship, however, between area of echogenicity in the right SN and the magnitude of intracortical facilitation in the right (ipsilateral) primary motor cortex (p = .005; multivariate regression), evidenced by the amplitude of the conditioned motor evoked potential (MEP) at the 10-12 ms interstimulus interval. This relationship was not present on the left side. Pre-SMA glutamate did not predict primary motor cortex inhibition or facilitation. The results suggest that SN hyperechogenicity in healthy older adults may be associated with changes in excitability of motor cortical circuitry. The results advance understanding of brain changes in healthy older adults at risk of Parkinson's disease.

Toward a forest biomass reference measurement system for remote sensing applications.

Forests contribute to climate change mitigation through carbon storage and uptake, but the extent to which this carbon pool varies in space and time is still poorly known. Several Earth Observation missions have been specifically designed to address this issue, for example, NASA's GEDI, NASA-ISRO's NISAR and ESA's BIOMASS. Yet, all these missions' products require independent and consistent validation. A permanent, global, in situ, site-based forest biomass reference measurement system relying on ground data of the highest possible quality is therefore needed. Here, we have assembled a list of almost 200 high-quality sites through an in-depth review of the literature and expert knowledge. In this study, we explore how representative these sites are in terms of their coverage of environmental conditions, geographical space and biomass-related forest structure, compared to those experienced by forests worldwide. This work also aims at identifying which sites are the most representative, and where to invest to improve the representativeness of the proposed system. We show that the environmental coverage of the system does not seem to improve after at least the 175 most representative sites are included, but geographical and structural coverages continue to improve as more sites are added. We highlight the areas of poor environmental, geographical, or structural coverage, including, but not limited to, Canada, the western half of the USA, Mexico, Patagonia, Angola, Zambia, eastern Russia, and tropical and subtropical highlands (e.g. in Colombia, the Himalayas, Borneo, Papua). For the proposed system to succeed, we stress that (1) data must be collected and processed applying the same standards across all countries and continents; (2) system establishment and management must be inclusive and equitable, with careful consideration of working conditions; and (3) training and site partner involvement in downstream activities should be mandatory.

Simulating carbon accumulation and loss in the central Congo peatlands.

Peatlands of the central Congo Basin have accumulated carbon over millennia. They currently store some 29 billion tonnes of carbon in peat. However, our understanding of the controls on peat carbon accumulation and loss and the vulnerability of this stored carbon to climate change is in its infancy. Here we present a new model of tropical peatland development, DigiBog_Congo, that we use to simulate peat carbon accumulation and loss in a rain-fed interfluvial peatland that began forming ~20,000 calendar years Before Present (cal. yr BP, where 'present' is 1950 CE). Overall, the simulated age-depth curve is in good agreement with palaeoenvironmental reconstructions derived from a peat core at the same location as our model simulation. We find two key controls on long-term peat accumulation: water at the peat surface (surface wetness) and the very slow anoxic decay of recalcitrant material. Our main simulation shows that between the Late Glacial and early Holocene there were several multidecadal periods where net peat and carbon gain alternated with net loss. Later, a climatic dry phase beginning ~5200 cal. yr BP caused the peatland to become a long-term carbon source from ~3975 to 900 cal. yr BP. Peat as old as ~7000 cal. yr BP was decomposed before the peatland's surface became wetter again, suggesting that changes in rainfall alone were sufficient to cause a catastrophic loss of peat carbon lasting thousands of years. During this time, 6.4 m of the column of peat was lost, resulting in 57% of the simulated carbon stock being released. Our study provides an approach to understanding the future impact of climate change and potential land-use change on this vulnerable store of carbon.