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Kiwifruit decline syndrome (KiDS) has affected kiwifruit orchards for more than ten years in the Mediterranean area, severely compromising productivity and causing extensive uprooting. The affected plants go through an irreversible and fast wilting process. The problem has not been solved yet, and a single cause has not been identified. In this work, we carried out a survey on ten five-year-old healthy kiwifruit cv. Hayward plants cultivated in an area strongly affected by KiDS and characterised by a rising temperature and vapor pressure deficit (VPD). Five plants were located in a KiDS-affected orchard. Our goal was to assess the hydraulic conductance of asymptomatic plants in a KiDS-affected area where rising climate change stress is underway. Our hypothesis was that a rising temperature and VPD could impair xylem functionality, leading the plants to develop strategies of tolerance, such as vessel narrowing, or stress symptoms, such as cavitation or implosion, inducing a higher risk of KiDS onset. Hydraulic conductance was investigated using a physiological and morphological approach to detect trunk sap flow, trunk growth and daily diameter variations, leaf gas exchanges and temperature, stem water potential, and the root xylem vessel diameter and vulnerability to cavitation. A strong xylem vessel narrowing was observed in all plants, with the highest frequency in the 30–45 µm diameter class, which is an indicator of long-term adaptation to a rising VPD. In some plants, cavitation and implosion were also observed, which are indicative of a short-term stress response; this behaviour was detected in the plants in the KiDS-affected orchard, where a high leaf temperature (>39 °C), low stomatal conductance (2O m−2 s−1) and transpiration (2O m−2 s−1), low stem water potential (−2), low trunk sap flow and high daily stem diameter variation confirmed the water stress status. The concurrence of climate stress and agronomic management in predisposing conditions favourable to KiDS onset are discussed, evidencing the role of soil preparation, propagation material and previous crop.

Neurological disorders such as stroke, Parkinson’s disease (PD), and severe traumatic brain injury (sTBI) are leading global causes of disability and mortality. This study aimed to assess the ability to walk of patients with sTBI, stroke, and PD, identifying the differences in dynamic postural stability, symmetry, and smoothness during various dynamic motor tasks. Sixty people with neurological disorders and 20 healthy participants were recruited. Inertial measurement unit (IMU) sensors were employed to measure spatiotemporal parameters and gait quality indices during different motor tasks. The Mini-BESTest, Berg Balance Scale, and Dynamic Gait Index Scoring were also used to evaluate balance and gait. People with stroke exhibited the most compromised biomechanical patterns, with lower walking speed, increased stride duration, and decreased stride frequency. They also showed higher upper body instability and greater variability in gait stability indices, as well as less gait symmetry and smoothness. PD and sTBI patients displayed significantly different temporal parameters and differences in stability parameters only at the pelvis level and in the smoothness index during both linear and curved paths. This study provides a biomechanical characterization of dynamic stability, symmetry, and smoothness in people with stroke, sTBI, and PD using an IMU-based ecological assessment.

BACKGROUND:Low back pain is one of the leading causes of disability worldwide. Exercise therapy is widely recommended to treat persistent non-specific low back pain. While evidence suggests exercise is, on average, moderately effective, there remains uncertainty about which individuals might benefit the most from exercise. METHODS:In parallel with a Cochrane review update, we requested individual participant data (IPD) from high-quality randomised clinical trials of adults with our two primary outcomes of interest, pain and functional limitations, and calculated global recovery. We compiled a master data set including baseline participant characteristics, exercise and comparison characteristics, and outcomes at short-term, moderate-term and long-term follow-up. We conducted descriptive analyses and one-stage IPD meta-analysis using multilevel mixed-effects regression of the overall treatment effect and prespecified potential treatment effect modifiers. RESULTS:We received IPD for 27 trials (3514 participants). For studies included in this analysis, compared with no treatment/usual care, exercise therapy on average reduced pain (mean effect/100 (95% CI) -10.7 (-14.1 to -7.4)), a result compatible with a clinically important 20% smallest worthwhile effect. Exercise therapy reduced functional limitations with a clinically important 23% improvement (mean effect/100 (95% CI) -10.2 (-13.2 to -7.3)) at short-term follow-up. Not having heavy physical demands at work and medication use for low back pain were potential treatment effect modifiers-these were associated with superior exercise outcomes relative to non-exercise comparisons. Lower body mass index was also associated with better outcomes in exercise compared with no treatment/usual care. This study was limited by inconsistent availability and measurement of participant characteristics. CONCLUSIONS:This study provides potentially useful information to help treat patients and design future studies of exercise interventions that are better matched to specific subgroups. PROTOCOL PUBLICATION: https://doi.org/10.1186/2046-4053-1-64.

Abstract Cell migration is a pivotal biological process, whose dysregulation is found in many diseases including inflammation and cancer. Advances in microscopy technologies allow now to study cell migration in vitro, within engineered microenvironments that resemble in vivo conditions. However, to capture an entire 3D migration chamber for extended periods of time and with high temporal resolution, images are generally acquired with low resolution, which poses a challenge for data analysis. Indeed, cell detection and tracking are hampered due to the large pixel size (i.e., cell diameter down to 2 pixels), the possible low signal-to-noise ratio, and distortions in the cell shape due to changes in the z-axis position. Although fluorescent staining can be used to facilitate cell detection, it may alter cell behavior and it may suffer from fluorescence loss over time (photobleaching). Here we describe a protocol that employs an established deep learning method (U-NET), to specifically convert transmitted light (TL) signal from unlabeled cells imaged with low resolution to a fluorescent-like signal (class 1 probability). We demonstrate its application to study cancer cell migration, obtaining a significant improvement in tracking accuracy, while not suffering from photobleaching. This is reflected in the possibility of tracking cells for three-fold longer periods of time. To facilitate the application of the protocol we provide WID-U, an open-source plugin for FIJI and Imaris imaging software, the training dataset used in this paper, and the code to train the network for custom experimental settings.

Background and aimAdvances in computing technology enabled researchers and clinicians to exploit technological devices for cognitive training and rehabilitation interventions. This expert review aims to describe the available software and device used for cognitive training or rehabilitation interventions of patients with neurological disorders.MethodsA scoping review was carried out to analyze commercial devices/software for computerized cognitive training (CCT) in terms of feasibility and efficacy in both clinical and home settings. Several cognitive domains responding to the different patients’ needs are covered.ResultsThis review showed that cognitive training for patients with neurological diseases is largely covered by several devices that are widely used and validated in the hospital setting but with few translations to remote/home applications. It has been demonstrated that technology and software-based devices are potential and valuable tools to administer remotely cognitive rehabilitation with accessible costs.ConclusionAccording to our results, CCT entails the possibility to continue cognitive training also in different settings, such as home, which is a significant breakthrough for the improvement of community care. Other possible areas of use should be the increase in the amount of cognitive therapy in the free time during the hospital stay.

About one-third of stroke survivors present unilateral spatial neglect (USN) that negatively impacts the rehabilitation outcome. We reported the study protocol and usability results of an eye-tracking (ET) biofeedback immersive virtual reality (iVR) protocol. Healthy controls and stroke patients with and without USN underwent a single session of the three iVR tasks. The system usability scale (SUS), adverse events (AEs), and ET data were collected and analyzed via parametric analysis. Twelve healthy controls (six young adults and six older adults) and seven patients with a diagnosis of single ischemic stroke (four without USN and three with confirmed diagnosis of USN) completed the usability investigation. SUS results showed good acceptability of the system for healthy controls and stroke patients without USN. ET results showed a lower performance for patients with USN concerning healthy controls and stroke patients without USN, in particular in the exploration of the left visual field. The results showed that the proposed iVR-ET biofeedback protocol is a safe and well-tolerated technique in patients with USN. The real-time feedback can induce a performance response supporting its investigation such as a treatment approach.

Cyanobacteria are among the oldest organisms colonizing Earth. Their great biodiversity and ability to biosynthesize secondary metabolites through a variety of routes makes them attractive resources for biotechnological applications and drug discovery. In this pioneer study, four filamentous cyanobacteria (Cephalothrix lacustris LEGE 15493, Leptolyngbya boryana LEGE 15486, Nodosilinea nodulosa LEGE 06104 and Leptothoe sp. LEGE 11479) were explored for their anti-inflammatory potential in cell and cell-free in vitro bioassays, involving different inflammatory mediators and enzymes. Extracts of different polarities were sequentially prepared and chemically characterized for their content of phycobiliproteins (PBPs) and carotenoids. HPLC-PDA analysis of the acetone extracts revealed β-carotene to be the dominant carotenoid (18.4–44.3 mg/g) and zeaxanthin as the dominant xanthophyll (52.7–192.9 mg/g), with Leptothoe sp. LEGE 11479 and Nodosilinea nodulosa LEGE 06104, respectively, being the richest strains. The PBP profile was in accordance with the color presented by the aqueous extracts, with Leptolyngbya boryana LEGE 15486 being the richest in phycocyanin (204.5 μg/mg) and Leptothoe sp. LEGE 11479 the richest in phycoerythrin (78.5 μg/mg). Aqueous extracts were more effective in superoxide anion radical scavenging, while acetone ones were more effective in scavenging nitric oxide radical (●NO) and in inhibiting lipoxygenase. Acetone extracts also reduced ●NO production in lipopolysaccharide-stimulated RAW 264.7 macrophages, with the mechanistic study suggesting a downregulation of the inducible nitric oxide synthase expression. Nodosilinea nodulosa LEGE 06104 and Leptothoe sp. LEGE 11479 acetone extracts presented the lowest IC50 values for the mentioned assays, pointing them out as promising resources for the development of new multi-target anti-inflammatory therapies.

We uncover the connection between the Fitness-Complexity algorithm, developed in the economic complexity field, and the Sinkhorn–Knopp algorithm, widely used in diverse domains ranging from computer science and mathematics to economics. Despite minor formal differences between the two methods, both converge to the same fixed-point solution up to normalization. The discovered connection allows us to derive a rigorous interpretation of the Fitness and the Complexity metrics as the potentials of a suitable energy function. Under this interpretation, high-energy products are unfeasible for low-fitness countries, which explains why the algorithm is effective at displaying nested patterns in bipartite networks. We also show that the proposed interpretation reveals the scale invariance of the Fitness-Complexity algorithm, which has practical implications for the algorithm’s implementation in different datasets. Further, analysis of empirical trade data under the new perspective reveals three categories of countries that might benefit from different development strategies.

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