Plant extracellular self-DNA inhibits growth and induces immunity via the jasmonate signaling pathway.

Plants have evolved sophisticated mechanisms to detect various forms of danger. Damage-associated molecular patterns (DAMPs) are endogenous danger molecules that are released from damaged cells and activate the innate immunity. Recent evidence suggests that plant extracellular self-DNA (esDNA) can serve as a DAMP molecule. However, the mechanisms by which esDNA functions are largely unknown. In this study, we confirmed that esDNA inhibits root growth and triggers reactive oxygen species (ROS) production in a concentration- and species-specific manner in Arabidopsis (Arabidopsis thaliana) and tomato (Solanum lycopersicum L.). Furthermore, by combining RNA sequencing, hormone measurement, and genetic analysis, we found that esDNA-mediated growth inhibition and ROS production are achieved through the jasmonic acid (JA) signaling pathway. Specifically, esDNA induces JA production and the expression of JA-responsive genes. The esDNA-mediated growth inhibition, ROS production, and gene expression are impaired in the JA-related mutants. Finally, we found that the JA signaling pathway is required for the esDNA-elicited resistance against the pathogens Botrytis cinerea and Pseudomonas syringae pv. tomato DC3000. This finding highlights the importance of JA signaling in esDNA-mediated biological effects, thereby providing insight into how esDNA functions as a DAMP.

Self-DNA in Caenorhabditis elegans Affects the Production of Specific Metabolites: Evidence from LC-MS and Chemometric Studies.

The worm Caenorhabditis elegans, with its short lifecycle and well-known genetic and metabolic pathways, stands as an exemplary model organism for biological research. Its simplicity and genetic tractability make it an ideal system for investigating the effects of different conditions on its metabolism. The chemical analysis of this nematode was performed to identify specific metabolites produced by the worms when fed with either self- or nonself-DNA. A standard diet with OP50 feeding was used as a control. Different development stages were sampled, and their chemical composition was assessed by liquid chromatography-mass spectrometry combined with chemometrics, including both principal component analysis and orthogonal partial least squares discriminant analysis tools. The obtained data demonstrated that self-DNA-treated larvae, when arrested in their cycle, showed significant decreases in dynorphin, an appetite regulator of the nematode, and in N-formyl glycine, a known longevity promoter in C. elegans. Moreover, a substantial decrease was also recorded in the self-DNA-fed adults for the FMRF amide neuropeptide, an embryogenesis regulator, and for a dopamine derivative modulating nematode locomotion. In conclusion, this study allowed for the identification of key metabolites affected by the self-DNA diet, providing interesting hints on the main molecular pathways involved in its biological inhibitory effects.

PhenoCaB: a new phenological model based on carbon balance in boreal conifers.

Traditional phenological models use chilling and thermal forcing (temperature sum or degree-days) to predict budbreak. Because of the heightening impact of climate and other related biotic or abiotic stressors, a model with greater biological support is needed to better predict budbreak. Here, we present an original mechanistic model based on the physiological processes taking place before and during budbreak of conifers. As a general principle, we assume that phenology is driven by the carbon status of the plant, which is closely related to environmental variables and the annual cycle of dormancy-activity. The carbon balance of a branch was modelled from autumn to winter with cold acclimation and dormancy and from winter to spring when deacclimation and growth resumption occur. After being calibrated in a field experiment, the model was validated across a large area (> 34 000 km2 ), covering multiple conifers stands in Québec (Canada) and across heated plots for the SPRUCE experiment in Minnesota (USA). The model accurately predicted the observed dates of budbreak in both Québec (±3.98 d) and Minnesota (±7.98 d). The site-independent calibration provides interesting insights on the physiological mechanisms underlying the dynamics of dormancy break and the resumption of vegetative growth in spring.

Field evidence for litter and self-DNA inhibitory effects on Alnus glutinosa roots.

Litter decomposition releases nutrients beneficial to plants but also induces phytotoxicity. Phytotoxicity can result from either labile allelopathic compounds or species specific and caused by conspecific DNA. Aquatic plants in flowing water generally do not suffer phytotoxicity because litter is regularly removed. In stagnant water or in litter packs an impact on root functionality can occur. So far, studies on water plant roots have been carried out in laboratory and never in field conditions. The effect of conspecific vs heterospecific litter and purified DNA were assessed on aquatic roots of the riparian woody species Alnus glutinosa L. using a novel method, using closed and open plastic tubes fixed to single roots in the field with closed tubes analogous to stagnant water. Four fresh and four decomposed litter types were used and analysed on extractable C, cellulose, lignin, N content and using 13 C-CPMAS NMR spectroscopy. Inhibitory effects were observed with fresh litter in closed systems, with a positive correlation with extractable C and negative with lignin and lignin : N ratio. Alnus self-DNA, but not heterologous one, caused acute toxic effects in the closed system. Our results demonstrate the first field-based evidence for self-DNA inhibition as causal factor of negative feedback between plants and substrate.

Assessment of the Mechanical Support Characteristics of a Light and Wearable Robotic Exoskeleton Prototype Applied to Upper Limb Rehabilitation.

Robotic exoskeletons are active devices that assist or counteract the movements of the body limbs in a variety of tasks, including in industrial environments or rehabilitation processes. With the introduction of textile and soft materials in these devices, the effective motion transmission, mechanical support of the limbs, and resistance to physical disturbances are some of the most desirable structural features. This paper proposes an evaluation protocol and assesses the mechanical support properties of a servo-controlled robotic exoskeleton prototype for rehabilitation in upper limbs. Since this prototype was built from soft materials, it is necessary to evaluate the mechanical behavior in the areas that support the arm. Some of the rehabilitation-supporting movements such as elbow flexion and extension, as well as increased muscle tone (spasticity), are emulated. Measurements are taken using the reference supplied to the system's control stage and then compared with an external high-precision optical tracking system. As a result, it is evidenced that the use of soft materials provides satisfactory outcomes in the motion transfer and support to the limb. In addition, this study lays the groundwork for a future assessment of the prototype in a controlled laboratory environment using human test subjects.

Contrasting effects of Rhizophagus irregularis versus bacterial and fungal seed endophytes on Trifolium repens plant-soil feedback.

Interactions between plants and soil affect plant-plant interactions and community composition by modifying soils conditions in plant-soil feedback, where associated microbes have the most crucial role. Both arbuscular mycorrhizal fungi (AMF) and microbial seed endophytes have been demonstrated to influence, directly or indirectly, biotic or abiotic soil properties, thus affecting subsequent plant growth, and community structure. However, little is known about how plant endophyte communities, individually or in interaction with AMF, affect plant-soil feedback processes. Here, we investigated, through a manipulative experiment, the behavior of endophyte-free and endophyte-associated Trifolium repens plants grown in soils previously conditioned by conspecific endophyte-free and endophyte-associated plants, inoculated or not by Rhizophagus intraradices. Furthermore, we identified microbial endophytes directly from the inner tissues of seeds by high-throughput sequencing, to compare seed fungal and bacterial endophyte composition. Results demonstrated that the outcome of simultaneous occurrence of seed endophytes and AMF on plant behavior depended on matching the endophytic status, i.e., either the presence or absence of seed microbial endophytes, of the conditioning and response phase. Seed fungal endophytes generated strong conspecific negative feedback, while seed bacterial endophytes proved to shift the feedback from negative to positive. Moreover, the simultaneous occurrence of both seed endophytes with AMF could either generate or expand negative plant-soil feedback effects. Our results show that seed and root symbionts can play a significant role on setting conspecific plant-soil feedback.

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review.

In recent years, various studies have demonstrated the potential of electroencephalographic (EEG) signals for the development of brain-computer interfaces (BCIs) in the rehabilitation of human limbs. This article is a systematic review of the state of the art and opportunities in the development of BCIs for the rehabilitation of upper and lower limbs of the human body. The systematic review was conducted in databases considering using EEG signals, interface proposals to rehabilitate upper/lower limbs using motor intention or movement assistance and utilizing virtual environments in feedback. Studies that did not specify which processing system was used were excluded. Analyses of the design processing or reviews were excluded as well. It was identified that 11 corresponded to applications to rehabilitate upper limbs, six to lower limbs, and one to both. Likewise, six combined visual/auditory feedback, two haptic/visual, and two visual/auditory/haptic. In addition, four had fully immersive virtual reality (VR), three semi-immersive VR, and 11 non-immersive VR. In summary, the studies have demonstrated that using EEG signals, and user feedback offer benefits including cost, effectiveness, better training, user motivation and there is a need to continue developing interfaces that are accessible to users, and that integrate feedback techniques.

Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review.

Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.

Integration and Testing of a High-Torque Servo-Driven Joint and Its Electronic Controller with Application in a Prototype Upper Limb Exoskeleton.

Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented in various electronic devices to improve the performance and usability of these devices, which is desirable in any application. This paper proposes the integration and testing of a high-torque, servo-driven joint and its electronic controller, exposing its use in a robotic exoskeleton prototype as a case study. Following a brief background review, the development and implementation of the proposal are presented, allowing the control of the servo-driven joint in terms of torque, rotational velocity, and position through a straightforward, closed-loop control architecture. Additionally, the stability and performance of the servo-driven joint were assessed with and without load. In conclusion and based on the obtained results, the servo-driven joint and its control system demonstrate consistent performance under the proposed test protocol (max values: angular velocity 97 °/s, torque 33 Nm, positioning RMSE 1.46°), enabling this approach for use in various applications related to robotic exoskeletons, including human performance enhancement, rehabilitation, or support for daily living activities.

Design, Development, and Testing of an Intelligent Wearable Robotic Exoskeleton Prototype for Upper Limb Rehabilitation.

Neuromotor rehabilitation and recovery of upper limb functions are essential to improve the life quality of patients who have suffered injuries or have pathological sequels, where it is desirable to enhance the development of activities of daily living (ADLs). Modern approaches such as robotic-assisted rehabilitation provide decisive factors for effective motor recovery, such as objective assessment of the progress of the patient and the potential for the implementation of personalized training plans. This paper focuses on the design, development, and preliminary testing of a wearable robotic exoskeleton prototype with autonomous Artificial Intelligence-based control, processing, and safety algorithms that are fully embedded in the device. The proposed exoskeleton is a 1-DoF system that allows flexion-extension at the elbow joint, where the chosen materials render it compact. Different operation modes are supported by a hierarchical control strategy, allowing operation in autonomous mode, remote control mode, or in a leader-follower mode. Laboratory tests validate the proper operation of the integrated technologies, highlighting a low latency and reasonable accuracy. The experimental result shows that the device can be suitable for use in providing support for diagnostic and rehabilitation processes of neuromotor functions, although optimizations and rigorous clinical validation are required beforehand.

Quantitative Analysis of Performance Recovery in Semi-Professional Football Players after the COVID-19 Forced Rest Period.

This study proposes the instrumental analysis of the physiological and biomechanical adaptation of football players to a fatigue protocol during the month immediately after the COVID-19 lockdown, to get insights into fitness recovery. Eight male semi-professional football players took part in the study and filled a questionnaire about their activity during the lockdown. At the resumption of activities, the mean heart rate and covered distances during fatiguing exercises, the normalized variations of mean and maximum exerted power in the Wingate test and the Bosco test outcomes (i.e., maximum height, mean exerted power, relative strength index, leg stiffness, contact time, and flight time) were measured for one month. Questionnaires confirmed a light-intensity self-administered physical activity. A significant effect of fatigue (Wilcoxon signed-rank test p < 0.05) on measured variables was confirmed for the four weeks. The analysis of the normalized variations of the aforementioned parameters allowed the distinguishing of two behaviors: downfall in the first two weeks, and recovery in the last two weeks. Instrumental results suggest a physiological and ballistic (i.e., Bosco test outcomes) recovery after four weeks. As concerns the explosive skills, the observational data are insufficient to show complete recovery.

Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemical Parameters.

The coronavirus disease 2019 (COVID-19) pandemic has affected hundreds of millions of individuals and caused millions of deaths worldwide. Predicting the clinical course of the disease is of pivotal importance to manage patients. Several studies have found hematochemical alterations in COVID-19 patients, such as inflammatory markers. We retrospectively analyzed the anamnestic data and laboratory parameters of 303 patients diagnosed with COVID-19 who were admitted to the Polyclinic Hospital of Bari during the first phase of the COVID-19 global pandemic. After the pre-processing phase, we performed a survival analysis with Kaplan-Meier curves and Cox Regression, with the aim to discover the most unfavorable predictors. The target outcomes were mortality or admission to the intensive care unit (ICU). Different machine learning models were also compared to realize a robust classifier relying on a low number of strongly significant factors to estimate the risk of death or admission to ICU. From the survival analysis, it emerged that the most significant laboratory parameters for both outcomes was C-reactive protein min; HR=17.963 (95% CI 6.548-49.277, p < 0.001) for death, HR=1.789 (95% CI 1.000-3.200, p = 0.050) for admission to ICU. The second most important parameter was Erythrocytes max; HR=1.765 (95% CI 1.141-2.729, p < 0.05) for death, HR=1.481 (95% CI 0.895-2.452, p = 0.127) for admission to ICU. The best model for predicting the risk of death was the decision tree, which resulted in ROC-AUC of 89.66%, whereas the best model for predicting the admission to ICU was support vector machine, which had ROC-AUC of 95.07%. The hematochemical predictors identified in this study can be utilized as a strong prognostic signature to characterize the severity of the disease in COVID-19 patients.

One ring to rule them all: an ecosystem engineer fungus fosters plant and microbial diversity in a Mediterranean grassland.

Species coexistence in grasslands is regulated by several environmental factors and interactions with the soil microbial community. Here, the development of the Basidiomycetes fungus Agaricus arvensis, forming fairy rings, in a species-rich Mediterranean grassland, is described. Effects of the mycelial front on plants, fungi and bacteria were assessed by vegetation survey and next generation sequencing approaches. Our results showed a fungal-dependent shift in the community structure operated by a wave-like spread of fairy rings that decreased plant, fungal and bacterial diversity, indicating a detrimental effect of fairy rings on most species. The fairy rings induced successional processes in plants that enhanced the replacement of a community dominated by perennial plants with short-living and fast-growing plant species. In parallel, fungal and bacterial communities showed evident differences in species composition with several taxa associated within distinct sampling zone across the fairy rings. Notably, bacteria belonging to the Burkholderia genus and fungi of the genus Trichoderma increased in response to the advancing mycelium of A. arvensis. The profound changes in community composition and the overall increase in taxa diversity at ecosystemic scale suggest that fairy ring-forming fungi may act as ecosystem engineer species in Mediterranean grasslands.

Gait rehabilitation in persons with spinal cord injury using innovative technologies: an observational study.

STUDY DESIGN: Prospective, quasi-experimental study, pre- and post-design, single arm study. OBJECTIVES: Investigate whether persons affected by SCI can safely experience walking function using Robotic Exoskeletons and Functional Electrical Stimulation (FES). SETTING: Inpatient METHODS: 52 persons with SCI were recruited (36 completed the protocol) and assigned to one of two groups based on their Lower Limb Motor Scores (LEMS): Group A: LEMS ≥ 10 and Group B: LEMS < 10. Participants in Group A (n = 19) underwent 20 sessions of Robot-Assisted Gait Training (RAGT) on a treadmill followed by 20 sessions of FES during Overground Gait (FES-OG). Participants in Group B (n = 17) received 20 sessions of FES-cycling followed by 20 sessions of overground RAGT. The main outcome measures were: WISCI-II, 10MWT, 6MWT, TUG and SCIM-II. RESULTS: 36 persons completed the study with no complications; only 4 of the 16 dropped out because of mild complications during the RAGT. Participants in Group A exhibited significant improvements in WISCI-II, 10MWT, 6MWT and TUG (p < 0.05), while those in Group B did not significantly improve their gait function but their walking velocity and resistance with the assistance of the robotic exoskeleton increased. SCIM-II scores increased followed therapy only in Group A. CONCLUSIONS: Persons affected by SCI can safely experience their walking function with RAGT and FES therapy; only few mild complications were observed. Our data provides initial evidence of the potential value of these technologies, especially in persons with SCI having LEMS > 10.

AgriLogger: A New Wireless Sensor for Monitoring Agrometeorological Data in Areas Lacking Communication Networks.

The use of wireless technologies in the field of agriculture, or so-called smart or precision agriculture, is considered as one of the main efforts applied nowadays to multiply the food production on earth. However, wireless sensor network (WSN) technology is still at its early development stage and its application in agriculture and food industry is still rare due to the lack of farmers' awareness and outreach about the matter. This paper presents a new agro-sensor named AgriLogger with an aim to collect, store for long periods and transmit agrometeorological data represented by temperature and relative humidity in remote areas hard to reach and not served by telecommunication networks. The sensor exhibits long battery life, in the order of 10 years, thanks to low consumption technologies and to hardware sleep/wake up approach. It can be remotely placed on preselected sites through a customized drone. This latter, equipped with a dedicated payload, can then return on the sites where sensors have been placed, and, while hovering, wakes up the single devices and uploads their collected data through local wireless network. Field tests have demonstrated that the sensor, after being placed manually in two different positions, inside and outside a vineyard canopy, is able to collect and store successfully agrometeorological data like temperature and relative humidity. Moreover, the use of a drone potentially allows the collection of data from remote areas and, therefore, is able to provide a periodical monitoring of agro-ecological conditions.

Effect of verticalization with Erigo® in the acute rehabilitation of severe acquired brain injury.

The recovery of the orthostatism after a severe acquired brain injury (sABI) is an essential objective to pursue in order to avoid the occurrence of secondary complications resulting from prolonged immobilization to which the patient is subjected during the acute phase. This randomized controlled trial aims to evaluate the effect of verticalization with the lower limb robot-assisted training system Erigo® versus conventional neurorehabilitation in 44 adult subjects affected by sequelae of sABI in the acute rehabilitation phase, related to cardiorespiratory signs and measures of impairment and activity. At the end of the study (20 treatment sessions, 5 sessions per week), in both groups of patients, there were no dropouts nor adverse events. In subject verticalized with Erigo®, there were no episodes of (pre)syncope from orthostatic hypotension nor postural orthostatic tachycardia and cardiorespiratory signs remained stable; moreover, there were no increase in muscle tone nor reduction in range of motion at lower limbs. Results obtained show improved outcomes on the whole and in a similar way in both groups; however, the improvement in scores of the National Institutes of Health Stroke Scale, the Tinetti scale, and the Functional Independence Measure from the enrollment to the end of the treatment cycle being equal, the evaluation performed at the 10th session allows to establish that the improvement appears earlier in the intervention group and later in the control group. The more rapid recovery of impairments and some activities in subjects treated with Erigo® could allow a "time-saver" to devote to the rehabilitation of sensory-motor functions which are more complex and subordinated to the preliminary reacquisition of elementary postures and motor strategies.

Comparing chemistry and bioactivity of burned vs. decomposed plant litter: different pathways but same result?

Litter burning and biological decomposition are oxidative processes co-occurring in many terrestrial ecosystems, producing organic matter with different chemical properties and differently affecting plant growth and soil microbial activity. We tested the chemical convergence hypothesis, i.e., materials with different initial chemistry converge toward a common profile, with similar biological effects, as the oxidative process advances, for burning and decomposition. We compared the molecular composition, assessed by 13 C NMR, of seven plant litter types either fresh, decomposed for 30, 90, 180 d in a microcosms incubation experiment, or heated at 100°C, 200°C, 300°C, 400°C, 500°C for 30 minutes. We used litter water extracts (5% dry weight) as treatments in bioassays on plant (Lepidium sativum) and fungal (Aspergillus niger) growth, and a washed quartz sand amended with litter (0.5% dw) to assess heterotrophic respiration by flux chamber (i.e., [µg of CO2 released]·[g added litter]-1 ·d-1 ). We observed different molecular variations for materials either burning (i.e., a sharp increase of aromatic C and a decrease of other fractions above 200°C) or decomposing (i.e., early increase of alkyl, methoxyl, and N-alkyl C and decrease of O-alkyl and di-O-alkyl C fractions). Soil respiration and fungal growth decreased with litter age and heating severity, down to 20% relative to fresh litter. Plants were inhibited on fresh litter (on average 13% of the control), but recovered on aged (180 d) and heated (30 min at 500°C) materials, up to 126% and 63% of the control, respectively. Correlation between the intensity of 13 C NMR signals in litter spectra and bioassay results showed that O-alkyl, methoxyl, and aromatic C fractions are crucial to understand organic matter effects, with plant response negatively affected by labile C but positively associated to lignification and pyrogenic C. The pattern of association of soil respiration and fungal growth to these C fractions was essentially opposite to that observed for plant root growth. Our findings suggest a functional convergence of decomposed and burned organic substrates, emerging from the balance between the bioavailability of labile C sources and the presence of recalcitrant and pyrogenic compounds, oppositely affecting different trophic levels.

Effects of Hydraulic Soil Properties on Vegetation Pattern Formation in Sloping Landscapes.

Current models of vegetation pattern formation rely on a system of weakly nonlinear reaction-diffusion equations that are coupled by their source terms. While these equations, which are used to describe a spatiotemporal planar evolution of biomass and soil water, qualitatively capture the emergence of various types of vegetation patterns in arid environments, they are phenomenological and have a limited predictive power. We ameliorate these limitations by deriving the vertically averaged Richards' equation to describe flow (as opposed to "diffusion") of water in partially saturated soils. This establishes conditions under which this nonlinear equation reduces to its weakly nonlinear reaction-diffusion counterpart used in the previous models, thus relating their unphysical parameters (e.g., diffusion coefficient) to the measurable soil properties (e.g., hydraulic conductivity) used to parameterize the Richards equation. Our model is valid for both flat and sloping landscapes and can handle arbitrary topography and boundary conditions. The result is a model that relates the environmental conditions (e.g., precipitation rate, runoff and soil properties) to formation of multiple patterns observed in nature (such as stripes, labyrinth and spots).

On the assessment of coordination between upper extremities: towards a common language between rehabilitation engineers, clinicians and neuroscientists.

Well-developed coordination of the upper extremities is critical for function in everyday life. Interlimb coordination is an intuitive, yet subjective concept that refers to spatio-temporal relationships between kinematic, kinetic and physiological variables of two or more limbs executing a motor task with a common goal. While both the clinical and neuroscience communities agree on the relevance of assessing and quantifying interlimb coordination, rehabilitation engineers struggle to translate the knowledge and needs of clinicians and neuroscientists into technological devices for the impaired. The use of ambiguous definitions in the scientific literature, and lack of common agreement on what should be measured, present large barriers to advancements in this area. Here, we present the different definitions and approaches to assess and quantify interlimb coordination in the clinic, in motor control studies, and by state-of-the-art robotic devices. We then propose a taxonomy of interlimb activities and give recommendations for future neuroscience-based robotic- and sensor-based assessments of upper limb function that are applicable to the everyday clinical practice. We believe this is the first step towards our long-term goal of unifying different fields and help the generation of more consistent and effective tools for neurorehabilitation.

Inhibitory and toxic effects of extracellular self-DNA in litter: a mechanism for negative plant-soil feedbacks?

Plant-soil negative feedback (NF) is recognized as an important factor affecting plant communities. The objectives of this work were to assess the effects of litter phytotoxicity and autotoxicity on root proliferation, and to test the hypothesis that DNA is a driver of litter autotoxicity and plant-soil NF. The inhibitory effect of decomposed litter was studied in different bioassays. Litter biochemical changes were evaluated with nuclear magnetic resonance (NMR) spectroscopy. DNA accumulation in litter and soil was measured and DNA toxicity was assessed in laboratory experiments. Undecomposed litter caused nonspecific inhibition of root growth, while autotoxicity was produced by aged litter. The addition of activated carbon (AC) removed phytotoxicity, but was ineffective against autotoxicity. Phytotoxicity was related to known labile allelopathic compounds. Restricted (13) C NMR signals related to nucleic acids were the only ones negatively correlated with root growth on conspecific substrates. DNA accumulation was observed in both litter decomposition and soil history experiments. Extracted total DNA showed evident species-specific toxicity. Results indicate a general occurrence of litter autotoxicity related to the exposure to fragmented self-DNA. The evidence also suggests the involvement of accumulated extracellular DNA in plant-soil NF. Further studies are needed to further investigate this unexpected function of extracellular DNA at the ecosystem level and related cellular and molecular mechanisms.