Differential response of Oryza sativa L. and Phragmites australis L. plants in trace elements contaminated soils under flooded and unflooded conditions.

Drastic changes in the water regime of trace elements (TEs) contaminated soils under semiarid conditions, from completely dry to flooding situations, may alter the solubility of the contaminants and, therefore, their potential mobility and availability to plants. Certain macrophyte species have shown a promising suitability for their use in the phytoremediation of TEs contaminated soils under fluctuating flooded-unflooded conditions, as a consequence of their high resistance and tolerance to contamination. Similarly, different water conditions occur during rice (Oryza sativa) cultivation, a species often used as a model plant for TEs toxicity studies. The aim of this work was to study the tolerance and oxidative response to TEs of common reed (Phragmites australis) and rice grown in contaminated mining soils, when exposed to different water saturation conditions. Both species (common reed and rice) were cultivated in three different contaminated soils from the Sierra Minera of La Unión-Cartagena (SE-Spain) under contrasting water saturation conditions (flooded and unflooded) in a pot experiment. Soil EC and elevated metal (mainly Cd and Zn) soluble concentrations conditioned the survival of the plants. Whereas, As accumulation in the aerial part of both species influenced the most oxidative stress homeostasis. Common reed showed to be a good candidate for its use in the phytostabilization of TEs contaminated soils under both flooded and unflooded conditions.

Chlorophyll content estimation in an open-canopy conifer forest with Sentinel-2A and hyperspectral imagery in the context of forest decline.

With the advent of Sentinel-2, it is now possible to generate large-scale chlorophyll content maps with unprecedented spatial and temporal resolution, suitable for monitoring ecological processes such as vegetative stress and/or decline. However methodological gaps exist for adapting this technology to heterogeneous natural vegetation and for transferring it among vegetation species or plan functional types. In this study, we investigated the use of Sentinel-2A imagery for estimating needle chlorophyll (Ca+b) in a sparse pine forest undergoing significant needle loss and tree mortality. Sentinel-2A scenes were acquired under two extreme viewing geometries (June vs. December 2016) coincident with the acquisition of high-spatial resolution hyperspectral imagery, and field measurements of needle chlorophyll content and crown leaf area index. Using the high-resolution hyperspectral scenes acquired over 61 validation sites we found the CI chlorophyll index R750/R710 and Macc index (which uses spectral bands centered at 680 nm, 710 nm and 780 nm) had the strongest relationship with needle chlorophyll content from individual tree crowns (r2 = 0.61 and r2 = 0.59, respectively; p < 0.001), while TCARI and TCARI/OSAVI, originally designed for uniform agricultural canopies, did not perform as well (r2 = 0.21 and r2 = 0.01, respectively). Using lower-resolution Sentinel-2A data validated against hyperspectral estimates and ground truth needle chlorophyll content, the red-edge index CI and the Sentinel-specific chlorophyll indices CI-Gitelson, NDRE1 and NDRE2 had the highest accuracy (with r2 values >0.7 for June and >0.4 for December; p < 0.001). The retrieval of needle chlorophyll content from the entire Sentinel-2A bandset using the radiative transfer model INFORM yielded r2 = 0.71 (RMSE = 8.1 µg/cm2) for June, r2 = 0.42 (RMSE = 12.2 µg/cm2) for December, and r2 = 0.6 (RMSE = 10.5 µg/cm2) as overall performance using the June and December datasets together. This study demonstrates the retrieval of leaf Ca+b with Sentinel-2A imagery by red-edge indices and by an inversion method based on a hybrid canopy reflectance model that accounts for tree density, background and shadow components common in sparse forest canopies.

Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery.

The operational monitoring of forest decline requires the development of remote sensing methods that are sensitive to the spatiotemporal variations of pigment degradation and canopy defoliation. In this context, the red-edge spectral region (RESR) was proposed in the past due to its combined sensitivity to chlorophyll content and leaf area variation. In this study, the temporal dimension of the RESR was evaluated as a function of forest decline using a radiative transfer method with the PROSPECT and 3D FLIGHT models. These models were used to generate synthetic pine stands simulating decline and recovery processes over time and explore the temporal rate of change of the red-edge chlorophyll index (CI) as compared to the trajectories obtained for the structure-related Normalized Difference Vegetation Index (NDVI). The temporal trend method proposed here consisted of using synthetic spectra to calculate the theoretical boundaries of the subspace for healthy and declining pine trees in the temporal domain, defined by CItime=n/CItime=n+1 vs. NDVItime=n/NDVItime=n+1. Within these boundaries, trees undergoing decline and recovery processes showed different trajectories through this subspace. The method was then validated using three high-resolution airborne hyperspectral images acquired at 40 cm resolution and 260 spectral bands of 6.5 nm full-width half-maximum (FWHM) over a forest with widespread tree decline, along with field-based monitoring of chlorosis and defoliation (i.e., 'decline' status) in 663 trees between the years 2015 and 2016. The temporal rate of change of chlorophyll vs. structural indices, based on reflectance spectra extracted from the hyperspectral images, was different for trees undergoing decline, and aligned towards the decline baseline established using the radiative transfer models. By contrast, healthy trees over time aligned towards the theoretically obtained healthy baseline. The applicability of this temporal trend method to the red-edge bands of the MultiSpectral Imager (MSI) instrument on board Sentinel-2a for operational forest status monitoring was also explored by comparing the temporal rate of change of the Sentinel-2-derived CI over areas with declining and healthy trees. Results demonstrated that the Sentinel-2a red-edge region was sensitive to the temporal dimension of forest condition, as the relationships obtained for pixels in healthy condition deviated from those of pixels undergoing decline.

Proline accumulation and antioxidant response are crucial for citrus tolerance to UV-B light-induced stress.

Plants face a wide range of biotic and abiotic stress conditions, which are further intensified by climate change. Among these stressors, increased irradiation in terms of intensity and wavelength range can lead to detrimental effects, such as chlorophyll degradation, destruction of the PSII reaction center, generation of ROS, alterations to plant metabolism, and even plant death. Here, we investigated the responses of two citrus genotypes, Citrus macrophylla (CM), and Troyer citrange (TC) to UV-B light-induced stress, by growing plants of both genotypes under control and UV-B stress conditions for 5 days to evaluate their tolerance mechanisms. TC seedlings had higher sensitivity to UV-B light than CM seedlings, as they showed more damage and increased levels of oxidative harm (indicated by the accumulation of MDA). In contrast, CM seedlings exhibited specific adaptive mechanisms, including accumulation of higher levels of proline under stressful conditions, and enhanced antioxidant capacity, as evidenced by increased ascorbate peroxidase activity and upregulation of the CsAPX2 gene. Phytohormone accumulation patterns were similar in both genotypes, with a decrease in ABA content in response to UV-B light. Furthermore, expression of genes involved in light perception and response was specifically affected in the tolerant CM seedlings, which exhibited higher expression of CsHYH/CsHY5 and CsRUP1-2 genes. These findings underscore the importance of the antioxidant system in citrus plants subjected to UV-B light-induced stress and suggest that CsHYH/CsHY5 and CsRUP1-2 could be considered genes associated with tolerance to such challenging conditions.

Synthesis of the BCDE molecular fragment of azadiradione mediated by titanocene(III).

A practical, short, and diastereoselective synthesis of the azadiradione BCDE fragment from a readily available starting material is described. The key step was the titanocene(III)-promoted tandem cyclization of unsaturated epoxy nitrile.

A systematic review of the application of machine-learning algorithms in multiple sclerosis.

INTRODUCTION: The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years. OBJECTIVE: We present a systematic review of the application of ML algorithms in MS. MATERIALS AND METHODS: We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected. CONCLUSIONS: After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

Response of Phragmites australis to increasing As(V) concentrations: Accumulation and speciation of As, and plant oxidative stress.

The use of macrophytes has been proposed recently as a suitable option for the phytostabilization or rhizofiltration of soils or waters contaminated by trace elements. As one of the most representative species of this type of plant, common reed (Phragmites australis (Cav.) Trin. ex Steud.) has shown tolerance to high concentrations of potentially hazardous elements, as is the case of arsenic. However, a deeper knowledge of how these plants deal with this toxicity, including their oxidative response, is needed for the optimum utilization of this species in phytoremediation procedures. In fact, little is known about how common reed plants react to As toxicity or the tolerance limits and accumulation potential of this species. In this work, common reed plants were exposed to a range of As(V) mass concentrations (0.5-10 mg L-1) in a hydroponic experiment, and the performance of the plants (growth, photosynthetic pigments, and oxidative stress related parameters) was evaluated and related to the major As species present in the different parts of the plants. The plants did not show any apparent symptom of toxicity and no significant effects were found for any of the different plant parameters analyzed. Arsenic was mostly accumulated as As(III) in the roots of the plants, and almost no translocation to the aerial part of the plants was observed for any of the As species analyzed. Common reed has shown a high capacity for As accumulation in its roots with no signs of toxicity, despite small nutrient imbalances. Thus, it can be considered to be a good candidate for use in the rhizofiltration and phytostabilization of As contaminated waters and soils, respectively.

Effects of ascorbic acid addition on the oxidative stress response of Oryza sativa L. plants to As(V) exposure.

Accumulation of noxious elements in the edible part of crops and its impact on food safety is of increasing concern. Rice is one of the major staple food crops worldwide, including arsenic (As)-polluted areas, in which dietary As exposure is becoming a widespread health threat. Plant chemical priming has been shown to be an effective strategy to enhance tolerance to environmental stresses, including metal(loid) exposure. The priming effect of ascorbic acid (AsA) was assessed in rice seedlings exposed to As(V) in a hydroponics experiment. AsA treatment (co-addition to the growing media concomitantly (t0) or 24 h in advance (t24)) prevented an excessive accumulation of As in the roots (that decreased âˆ¼ 60%) and stimulated the activities of photosynthetic and antioxidant attributes (∼1.2-fold) in the aerial part of the plants. The increase in proline levels in both shoots (∼2.1-fold) and roots (∼2.4-fold) was found to be the most sensitive stress parameter, and was able to reflect the AsA-induced reduction of As toxic effects (concentrations back to Control levels, both simultaneously added or added as a pretreatment) in the aerial part of the plants. However, the phytotoxic effects related to As exposure were not fully prevented by priming with AsA, and further research is needed to find alternative priming approaches.

A systematic review of the application of machine-learning algorithms in multiple sclerosis. / Revisión sistemática de la aplicación de algoritmos de «machine learning¼ en la esclerosis múltiple.

INTRODUCTION: The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years. OBJECTIVE: We present a systematic review of the application of ML algorithms in MS. MATERIALS AND METHODS: We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected. CONCLUSIONS: After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

Divergent abiotic spectral pathways unravel pathogen stress signals across species.

Plant pathogens pose increasing threats to global food security, causing yield losses that exceed 30% in food-deficit regions. Xylella fastidiosa (Xf) represents the major transboundary plant pest and one of the world's most damaging pathogens in terms of socioeconomic impact. Spectral screening methods are critical to detect non-visual symptoms of early infection and prevent spread. However, the subtle pathogen-induced physiological alterations that are spectrally detectable are entangled with the dynamics of abiotic stresses. Here, using airborne spectroscopy and thermal scanning of areas covering more than one million trees of different species, infections and water stress levels, we reveal the existence of divergent pathogen- and host-specific spectral pathways that can disentangle biotic-induced symptoms. We demonstrate that uncoupling this biotic-abiotic spectral dynamics diminishes the uncertainty in the Xf detection to below 6% across different hosts. Assessing these deviating pathways against another harmful vascular pathogen that produces analogous symptoms, Verticillium dahliae, the divergent routes remained pathogen- and host-specific, revealing detection accuracies exceeding 92% across pathosystems. These urgently needed hyperspectral methods advance early detection of devastating pathogens to reduce the billions in crop losses worldwide.

Implications of the use of As-rich groundwater for agricultural purposes and the effects of soil amendments on as solubility.

An agricultural site in Segovia province (Spain) contains high levels of arsenic (As) of geological origin in its groundwater, which is used intensively for irrigation. Crops, irrigation waters, and soils were analyzed to evaluate the occurrence of As in this area and its potential impact on the food chain. High As mobility was found in the agricultural soils, related to the application of As in the irrigation waters (14.8-280 µg As L(-1)) and the general alkaline and sandy character of these soils, which imposes a low capacity for As sorption and therefore enhances plant uptake. The use of amendments can also affect the solubility of As in these soils. Evidence for this was evaluated based on a study of the effect of organic (compost) and inorganic (iron oxides-rich rolling mill scale and phosphate fertilizer) amendments. Arsenic solubility in soil and plant uptake were high, but not significantly affected by organic matter or phosphate addition, while As immobilization was associated with addition of iron oxides with the rolling mill scale, although this did not result in a decrease of As uptake by the tested plants.

Major As species, lipid peroxidation and protein carbonylation in rice plants exposed to increasing As(V) concentrations.

Arsenic (As) uptake by plants is mainly carried out as arsenate (As(V)), whose chemical analogy with phosphate is largely responsible for its elevated toxicity. Arsenate is known to stimulate reactive oxygen species (ROS) formation in plants that provoke oxidative stress. This manuscript reports the results of a hydroponics study using rice (Oryza sativa L.) seedlings as a test plant, where the effects of increasing arsenate concentrations (0-10 mg L-1) on both lipid and protein oxidation, as well as As accumulation and speciation in plant roots and shoots were examined. Plant yield was negatively affected by increasing As concentration. Accumulation in plant roots was higher than in shoots at low arsenate doses (0.5-2.5 mg L-1), while root to shoot transport was drastically enhanced at the highest doses (5 and 10 mg L-1). Moreover, As(V) was the dominating species in the shoots and As(III) in the roots. Rice leaves in the 10 mg As L-1 treatment showed the highest lipid peroxidation damage (malondialdehyde concentration), whilst protein oxidation was not remarkably influenced by As dose. Lipid peroxidation seems to be therefore conditioned by As accumulation in rice plants, particularly by the presence of high As(V) concentrations in the aerial part of the plants as a consequence of unregulated translocation from roots to shoots above a threshold concentration (1.25-2.5 mg L-1) in the growing media. These results provide relevant information regarding As(V) toxic concentrations for rice plants, highlight the importance of major As species analysis in plant tissues regarding As toxicity and contribute to better understand plants response to elevated As concentrations in the growing media.

SASBDB: Towards an automatically curated and validated repository for biological scattering data.

Small-angle scattering (SAS) of X-rays and neutrons is a fundamental tool to study the nanostructural properties, and in particular, biological macromolecules in solution. In structural biology, SAS recently transformed from a specialization into a general technique leading to a dramatic increase in the number of publications reporting structural models. The growing amount of data recorded and published has led to an urgent need for a global SAS repository that includes both primary data and models. In response to this, a small-angle scattering biological data bank (SASBDB) was designed in 2014 and is available for public access at www.sasbdb.org. SASBDB is a comprehensive, free and searchable repository of SAS experimental data and models deposited together with the relevant experimental conditions, sample details and instrument characteristics. SASBDB is rapidly growing, and presently has over 1,000 entries containing more than 1,600 models. We describe here the overall organization and procedures of SASBDB paying most attention to user-relevant information during submission. Perspectives of further developments, in particular, with OneDep system of the Protein Data Bank, and also widening of SASBDB including new types of data/models are discussed.

Altered phase and nonphase EEG activity expose impaired maintenance of a spatial-object attentional focus in multiple sclerosis patients.

Some of the anatomical and functional basis of cognitive impairment in multiple sclerosis (MS) currently remains unknown. In particular, there is scarce knowledge about modulations in induced EEG (nonphase activity) for diverse frequency bands related to attentional deficits in this pathology. The present study analyzes phase and nonphase alpha and gamma modulations in 26 remitting-relapsing multiple sclerosis patients during their participation in the attention network test compared with twenty-six healthy controls (HCs) matched in sociodemographic variables. Behavioral results showed that the MS group exhibited general slowing, suggesting impairment in alerting and orienting networks, as has been previously described in other studies. Time-frequency analysis of EEG revealed that the gamma band was related to the spatial translation of the attentional focus, and the alpha band seemed to be related to the expectancy mechanisms and cognitive processing of the target. Moreover, phase and nonphase modulations differed in their psychophysiological roles and were affected differently in the MS and HC groups. In summary, nonphase modulations can unveil hidden cognitive mechanisms for phase analysis and complete our knowledge of the neural basis of cognitive impairment in multiple sclerosis pathology.

Combination of soil organic and inorganic amendments helps plants overcome trace element induced oxidative stress and allows phytostabilisation.

Trace element (TE)-contaminated soils require the improvement of their physico-chemical properties in order to allow their restoration through phytostabilization technologies. This study aimed to determine the usefulness of oxidative stress related parameters to validate the suitability of two different combinations of organic (solid fraction of pig slurry) and inorganic (paper mill sludge or a commercial red mud derivative) amendments for the phytostabilization of an acidic (4.2) TE-contaminated mine soil from SE Spain. Two wild species (Silybum marianum and Piptatherum miliaceum) were greenhouse cultivated and the development of the plants, their ionome, and oxidative stress related parameters were determined. Both amendment combinations increased significantly soil pH (to 5-6) and soil/pore water total organic C and total N concentrations, allowing an adequate plant growth and development (plants did not grow in untreated soils). The combination of amendments significantly reduced metal availability and showed to be effective (specially the one including the red mud derivative) in limiting shoot TE concentrations, which were all within common ranges (exclusion based tolerance of these species). Both protein carbonylation and lipid peroxidation were significantly higher in S. marianum plants from phytostabilized soils than in those from non-contaminated soils, which confirms the oxidative stress these plants suffer despite their satisfactory growth in the treated soils. P. miliaceum plants showed no differences between phytostabilized and non-contaminated soils. Therefore, the combination of amendments and TE-tolerant autochthonous species would be a suitable option for the phytostabilisation of soils contaminated by mining activities, reducing TE solubility and allowing an adequate plant growth.

Severe obstructive sleep apnoea exacerbates the microvascular impairment in very mild hypertensives.

BACKGROUND: Different studies have shown that obstructive sleep apnoea syndrome (OSAS), frequently associated with hypertension, represents a harmful and independent risk for cardiovascular diseases. The aim of our study was to ascertain whether the occurrence of OSAS could worsen microcirculatory impairment in very mild hypertensives. MATERIALS AND METHODS: One hundred untreated very mild hypertensives underwent polysomnography and subdivided into 32 non-OSAS, 33 mild OSAS and 35 severe OSAS patients on standardized criteria. They underwent routine blood chemistry, ambulatory blood pressure monitoring and anthropometric analysis. Skin capillary density (n mm(-2)) of forearm (FAC) and periungueal (PUC) fields was obtained through videocapillaroscopy. By a venous congestion manoeuvre, PUC was maximized (CVC) and secondary capillary recruitment (GAIN) was calculated. These measurements served as indices of structural and functional capillary rarefaction, respectively. RESULTS: Severe OSAS hypertensives showed reduced FAC (P < 0.001) and PUC (P < 0.001) as compared to those with mild OSAS and non-OSAS, but a greater CVC (P < 0.01) and GAIN (P < 0.001). Multiple regression analysis showed that PUC was inversely related to total sleep time with oxyhaemoglobin saturation at < 90% (TST90) (P < 0.001) and FAC to the apnoea-hypopnoea index (AHI) (P < 0.001) and to the sleep propensity (P < 0.01). CVC was positively associated to AHI (P < 0.001) and GAIN to TST90 (P < 0.05). CONCLUSIONS: The findings suggest that OSAS, by means of reduced basal and functional capillarity rarefaction, might pose an additional risk of impaired peripheral perfusion in very mild hypertensives. A microcirculation study therefore should be a part of the clinical approach in patients at high cerebro-cardiovascular risk such as hypertensives and patients with OSAS.

Changes in metal speciation and pH in olive processing waste and sulphur-treated contaminated soil.

Degradation of organic matter from olive mill waste and changes in the heavy metal fractionation of a metal-contaminated calcareous soil were studied in a laboratory experiment, in which the olive mill waste was mixed with the soil and then incubated under aerobic conditions. The soil was calcareous (15% CaCO(3)) with high Zn and Pb concentrations (2058 and 2947 mg kg(-1), respectively). The organic amendment was applied at a rate equivalent to 20 g kg(-1) soil, and unamended soil was run as a control. To discern if changes in metal solubility were due to the acidic character of the waste, elemental sulphur was applied to soil as a non-organic acidifying material. The S(0) rates used were 3.14, 4.71 and 6.28 g kg(-1). The mineralisation of total organic-C (TOC) from the waste reached 14.8% of the original TOC concentration after 56 days of incubation. The CO(2)-C produced from S(0)-treated soils showed the carbonate destruction by the H(2)SO(4) formed through S(0) oxidation. The organic waste increased EDTA-extractable Zn and Pb concentrations and CaCl(2)-extractable Mn levels in soil after two days of incubation. The changes in metal availability with time indicated that the oxidation of phenols from the waste reduced Mn (IV) oxides, releasing Zn and Pb associated with this mineral phase. Organic waste addition did not decrease soil pH; the acidifying effect of S(0) did not change metal fractionation in the soil.

Revisión sistemática de la aplicación de algoritmos de «machine learning» en la esclerosis múltiple / A systematic review of the application of machine-learning algorithms in multiple sclerosis

Introducción: La aplicación de la inteligencia artificial y en particular de algoritmos de aprendizaje automático o «machine learning» (ML) constituye un desafío y al mismo tiempo una gran oportunidad en diversas disciplinas científicas, técnicas y clínicas. Las aplicaciones específicas en el estudio de la esclerosis múltiple (EM) no han sido una excepción mostrando un creciente interés en los últimos años. Objetivo: Realizar una revisión sistemática de la aplicación de algoritmos de ML en la EM. Material y métodos: Empleando el motor de búsqueda de libre acceso PubMed que accede a la base de datos MEDLINE, se seleccionaron aquellos estudios que incluyeran simultáneamente los dos siguientes conceptos de búsqueda: «machine learning» y «multiple sclerosis». Se rechazaron aquellos estudios que fueran revisiones, estuvieran en otro idioma que no fuera el castellano o el inglés, y aquellos trabajos que tuvieran un carácter técnico y no fueran aplicados para la EM. Se seleccionaron como válidos 76 artículos y fueron rechazados 38. Conclusiones: Tras la revisión de los estudios seleccionados, se pudo observar que la aplicación del ML en la EM se concentró en cuatro categorías: 1) clasificación de subtipos de pacientes dentro de la enfermedad; 2) diagnóstico del paciente frente a controles sanos u otras enfermedades; 3) predicción de la evolución o de la respuesta a intervenciones terapéuticas y por último 4) otros enfoques. Los resultados hallados hasta la fecha muestran que los diferentes algoritmos de ML pueden ser un gran apoyo para el profesional sanitario tanto en la clínica como en la investigación de la EM.(AU)

Introduction: The applications of artificial intelligence, and in particular automatic learning or “machine learning” (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years. Objective: We present a systematic review of the application of ML algorithms in MS. Materials and methods: We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords “machine learning” and “multiple sclerosis.” We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected. Conclusions: After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.(AU)

Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations.

Plant pathogens cause significant losses to agricultural yields and increasingly threaten food security1, ecosystem integrity and societies in general2-5. Xylella fastidiosa is one of the most dangerous plant bacteria worldwide, causing several diseases with profound impacts on agriculture and the environment6. Primarily occurring in the Americas, its recent discovery in Asia and Europe demonstrates that X. fastidiosa's geographic range has broadened considerably, positioning it as a reemerging global threat that has caused socioeconomic and cultural damage7,8. X. fastidiosa can infect more than 350 plant species worldwide9, and early detection is critical for its eradication8. In this article, we show that changes in plant functional traits retrieved from airborne imaging spectroscopy and thermography can reveal X. fastidiosa infection in olive trees before symptoms are visible. We obtained accuracies of disease detection, confirmed by quantitative polymerase chain reaction, exceeding 80% when high-resolution fluorescence quantified by three-dimensional simulations and thermal stress indicators were coupled with photosynthetic traits sensitive to rapid pigment dynamics and degradation. Moreover, we found that the visually asymptomatic trees originally scored as affected by spectral plant-trait alterations, developed X. fastidiosa symptoms at almost double the rate of the asymptomatic trees classified as not affected by remote sensing. We demonstrate that spectral plant-trait alterations caused by X. fastidiosa infection are detectable previsually at the landscape scale, a critical requirement to help eradicate some of the most devastating plant diseases worldwide.