Long-Term Bone Mineral Density Changes in Kidney Transplant Recipients Treated with Denosumab: A Retrospective Study with Nonequivalent Control Group.

Data on the effectiveness of denosumab on osteoporosis after kidney transplantation are limited. We investigated the long-term bone mineral density (BMD) changes in kidney transplant recipients (KTRs) treated with denosumab compared to untreated KTRs. We enrolled KTRs treated with denosumab 60 mg/6 months for 4 years. An untreated group of sex and age-matched KTRs with a 1:1 ratio was included. The primary outcome was BMD changes assessed by Dual-energy X-ray Absorptiometry over 4 years. Data on serum creatinine, alkaline phosphatase (ALP), parathyroid hormone, and 25-hydroxyvitamin D were collected. All patients received oral cholecalciferol and calcium supplementation. 23 denosumab-treated KTRs were enrolled, and 23 untreated KTRs. The median time from transplant to the start of denosumab was 4 years (range 0:24). The denosumab group showed a significant increase from baseline in BMD at the lumbar spine (LS) (9.0 ± 10.7%, p < 0.001), and total hip (TH) (3.8 ± 7.9%, p = 0.041). The untreated group showed a significant decrease at all sites (- 3.0 ± 7%, p = 0.041 at the LS; - 6.3 ± 9.2%, p = 0.003 at the TH; - 6.7 ± 9.3%, p = 0.003 at the FN). The between-group differences in percent BMD changes were statistically significant at all sites. Similar results were found for the respective Z-scores. The ALP serum levels significantly decreased from baseline only in the denosumab group, with a significant between-group difference (p = 0.032). No significant differences in serum creatinine, hypocalcaemic events or acute graft rejection rates were observed. Four years of denosumab therapy were associated with increased BMD in KTRs, while untreated KTRs showed significant BMD losses at all sites.

Radiofrequency echographic multi-spectrometry and DXA for the evaluation of bone mineral density in a peritoneal dialysis setting.

BACKGROUND: The aim of this real-life cross-sectional explorative study was to compare radiofrequency echographic multi-spectrometry (REMS) with dual-energy X-rays absorptiometry (DXA) in the BMD assessment of patients receiving peritoneal dialysis (PD). Furthermore, we investigated the relationship between lumbar aortic calcifications (AOCs) and the DXA lumbar measurements. METHODS: Consecutive patients referring to the PD clinic of our hospital were included. Lumbar spine and femur scans were acquired with both techniques (including lumbar laterolateral DXA scans). The risk assessment of two fracture risk algorithms (FRAX® and DeFRA®) were compared. Cohen's k coefficients were used to assess the inter-technique agreement in the classification of patients as osteoporotic. Lumbar AOCs were estimated semi-quantitatively on laterolateral DXA scans. RESULTS: 41 patients were enrolled. No significant differences were documented between the BMD T-scores measured through DXA or REMS at the femur. At the lumbar spine, the DXA anteroposterior mean T-score (- 0.49 ± 1.98) was significantly higher than both the laterolateral DXA (- 1.66 ± 0.99) and the REMS (- 2.00 ± 1.94) measurements (p < 0.01 vs both). No significant differences were found between the DXA and REMS fracture risk estimates with both algorithms. The inter-technique Cohen's k coefficient (for the worst T-score, any site) was 0.421, p < 0.001. The discrepancy between the DXA laterolateral and anteroposterior lumbar T-score was positively associated with the AOCs extent and severity (r = 0.402, p < 0.01). CONCLUSIONS: Our data showed a promising agreement, in a real-life PD setting, between DXA and REMS BMD assessment and in the consequent fracture risk estimation and confirm the AOCs interference on the diagnostic accuracy of lumbar DXA.

Unraveling intrinsic correlation effects with angle-resolved photoemission spectroscopy.

Interaction effects can change materials properties in intriguing ways, and they have, in general, a huge impact on electronic spectra. In particular, satellites in photoemission spectra are pure many-body effects, and their study is of increasing interest in both experiment and theory. However, the intrinsic spectral function is only a part of a measured spectrum, and it is notoriously difficult to extract this information, even for simple metals. Our joint experimental and theoretical study of the prototypical simple metal aluminum demonstrates how intrinsic satellite spectra can be extracted from measured data using angular resolution in photoemission. A nondispersing satellite is detected and explained by electron-electron interactions and the thermal motion of the atoms. Additional nondispersing intensity comes from the inelastic scattering of the outgoing photoelectron. The ideal intrinsic spectral function, instead, has satellites that disperse both in energy and in shape. Theory and the information extracted from experiment describe these features with very good agreement.

"When did you see it?" The effect of emotional valence on temporal source memory in aging.

Previous studies consistently showed age-related differences in temporal judgment and temporal memory. Importantly, emotional valence plays a crucial role in older adults' information processing. In this study, we examined the effects of emotions at the intersection between time and memory, analysing age-related differences in a temporal source memory task. Twenty-five younger adults (age range 18-35), 25 old adults (age range 65-74), and 25 old-old adults (age range 75-84) saw a series of emotional pictures in three sessions separated by a one-day rest period. In the fourth session, participants were asked to indicate in which session (1, 2, or 3) they saw each picture. Results showed that old-old adults tended to collocate negative pictures distant in time, while positive stimuli were remembered as more recent than real, compared to neutral pictures. To a lower extent, people over 65 showed the same pattern of results. In contrast, emotional valence did not affect younger adults' temporal positioning of stimuli. Current findings fit well with the Socio-Emotional Selectivity Theory's assumptions and extended the literature on the positivity effect to temporal source memory.

UAV-Based Hyperspectral Monitoring Using Push-Broom and Snapshot Sensors: A Multisite Assessment for Precision Viticulture Applications.

Hyperspectral aerial imagery is becoming increasingly available due to both technology evolution and a somewhat affordable price tag. However, selecting a proper UAV + hyperspectral sensor combo to use in specific contexts is still challenging and lacks proper documental support. While selecting an UAV is more straightforward as it mostly relates with sensor compatibility, autonomy, reliability and cost, a hyperspectral sensor has much more to be considered. This note provides an assessment of two hyperspectral sensors (push-broom and snapshot) regarding practicality and suitability, within a precision viticulture context. The aim is to provide researchers, agronomists, winegrowers and UAV pilots with dependable data collection protocols and methods, enabling them to achieve faster processing techniques and helping to integrate multiple data sources. Furthermore, both the benefits and drawbacks of using each technology within a precision viticulture context are also highlighted. Hyperspectral sensors, UAVs, flight operations, and the processing methodology for each imaging type' datasets are presented through a qualitative and quantitative analysis. For this purpose, four vineyards in two countries were selected as case studies. This supports the extrapolation of both advantages and issues related with the two types of hyperspectral sensors used, in different contexts. Sensors' performance was compared through the evaluation of field operations complexity, processing time and qualitative accuracy of the results, namely the quality of the generated hyperspectral mosaics. The results shown an overall excellent geometrical quality, with no distortions or overlapping faults for both technologies, using the proposed mosaicking process and reconstruction. By resorting to the multi-site assessment, the qualitative and quantitative exchange of information throughout the UAV hyperspectral community is facilitated. In addition, all the major benefits and drawbacks of each hyperspectral sensor regarding its operation and data features are identified. Lastly, the operational complexity in the context of precision agriculture is also presented.

Gas exchange, vine performance and modulation of secondary metabolism in Vitis vinifera L. cv Barbera following long-term nitrogen deficit.

MAIN CONCLUSION: A reprogramming of secondary metabolism to acclimate to nitrogen deficiency was seen in grapevine eliciting an accumulation of strigolactones and jasmonate. This response links with photosynthetic compensation and enhanced ripening. In addition to the metabolism directly related to nitrogen assimilation, long-term nitrogen depletion may affect plant secondary metabolism, in turn affecting grapevine performance. In this work, the effect of nitrogen deficit was investigated in V. vinifera cv. Barbera potted vines following three years of deprivation, using a combination of morpho-physiological assessments and mass spectrometry-based untargeted metabolomics. Plants grown under nitrogen limitation showed reduced growth and even more curtailed yields, lowered SPAD values, and a quite preserved leaf gas exchange, compared to plants grown under non-limiting nitrogen availability. Ripening was decidedly accelerated, and berry composition improved in terms of higher sugar and phenolic contents under nitrogen-limiting conditions. Metabolomics showed the broad involvement of secondary metabolism in acclimation to nitrogen deficiency, including a distinctive modulation of the phytohormone profile. Several nitrogen-containing metabolites were down accumulated under nitrogen-limiting conditions, including alkaloids, glucosinolates, hypoxanthine, and inosine. On the other hand, phenylpropanoids showed an accumulation trend. Concerning the recruitment of hormones, nitrogen deprivation elicited an accumulation of strigolactones and jasmonate. Noteworthy, both strigolactones and jasmonates have been previously related to increased photosynthetic efficiency under abiotic stress. Furthermore, the severe reduction of lateral shoot development we recorded in N-deprived vines is consistent with the accumulation of strigolactones. Overall, our results suggest that nitrogen deprivation induced a rather broad metabolic reprogramming, mainly including secondary metabolism and hormones profile, reflected in the modulation of photosynthetic performance, canopy growth, and possibly fruit quality.

Strategies to build functionals of the density, or functionals of Green's functions: what can we learn?

The many-body problem cannot in general be solved exactly, and one of the most prominent approximations is to build perturbation expansions. A huge variety of expansions are possible, which differ by the quantity to be expanded, the expansion variable, the starting point, and ideas of how to re-sum or terminate the series. Although much has been discussed and much has been done, some choices were made for historical reasons, in particular, limited computation or storage capacities. The present work aims to examine the justification for different choices made in different contexts, by comparing the components of functionals based on Green's functions on the one side, and on the charge density on the other side. Of particular interest will be the question of how to build an optimal starting point for the approximation of non-local quantities, making use of near- or far-sightedness, and daring to consider models beyond the homogeneous electron gas. This will include the use of connector approximations. We will also discuss why it is a good idea to build functionals of the density.

Design of auxiliary systems for spectroscopy.

The Kohn-Sham system is the prototypical example of an auxiliary system that targets, in principle exactly, an observable like the electronic density without the need to calculate the complicated many-body wavefunction. Although the Kohn-Sham system does not describe excited-state properties directly, it also represents a very successful strategy guideline for many spectroscopy applications. Here we propose a generalization of the Kohn-Sham idea. In many situations one is interested only in limited answers to specific questions, whereas in state-of-the-art approaches a lot of information is generally calculated that is not needed for the interpretation of experimental spectra. For example, when the target is a spectrum S(ω) like the optical absorption of a solid, within time-dependent density-functional theory (TDDFT) one calculates the whole response function χ(r,r',ω). Analogously, within many-body perturbation theory (MBPT) one calculates the whole one-particle Green's function G(r,r',ω), while only the total spectral function A(ω) is needed for angle-integrated photoemission spectra. In this contribution, we advocate the possibility of designing auxiliary systems with effective potentials or kernels that target only the specific spectral properties of interest and are simpler than the self-energy of MBPT or the exchange-correlation kernel of TDDFT. In particular, we discuss the fundamentals and prototypical applications of simplified effective kernels for optical absorption and spectral potentials for photoemission, and we discuss how to express these potentials or kernels as functionals of the density.

Insights into one-body density matrices using deep learning.

The one-body reduced density matrix (1-RDM) of a many-body system at zero temperature gives direct access to many observables, such as the charge density, kinetic energy and occupation numbers. It would be desirable to express it as a simple functional of the density or of other local observables, but to date satisfactory approximations have not yet been found. Deep learning is the state of the art approach to performing high dimensional regressions and classification tasks, and is becoming widely used in the condensed matter community to develop increasingly accurate density functionals. Autoencoders are deep learning models that perform efficient dimensionality reduction, allowing the distillation of data to the fundamental features needed to represent it. By training autoencoders on a large data-set of 1-RDMs from exactly solvable real-space model systems, and performing principal component analysis, the machine learns to what extent the data can be compressed and hence how it is constrained. We gain insight into these machine learned constraints and employ them to inform approximations to the 1-RDM as a functional of the charge density. We exploit known physical properties of the 1-RDM in the simplest possible cases to perform feature engineering, where we inform the structure of the models from known mathematical relations, allowing us to integrate existing understanding into the machine learning methods. By comparing various deep learning approaches we gain insight into what physical features of the density matrix are most amenable to machine learning, utilising both known and learned characteristics.

Metabolic and transcriptional changes associated with the use of Ascophyllum nodosum extracts as tools to improve the quality of wine grapes (Vitis vinifera cv. Sangiovese) and their tolerance to biotic stress.

BACKGROUND: Recent studies report that Ascophyllum nodosum extracts, once applied on the canopy of different crops, deliver positive effects, increasing yield, inducing tolerance to biotic stress, and improving the quality of products. However, the mechanisms of action are still unclear. In this research, vines subjected to multiple foliar applications of an A. nodosum extract (ANE) at label doses were compared with untreated vines (NTV) in accordance with a comparative approach. The investigation coupled a field experiment with a second trial conducted under semi-controlled conditions, to clarify the mechanisms of action involved. RESULTS: The biostimulant did not affect soluble solids or the acidity of grapes; instead, it improved their anthocyanin and phenolic concentrations and the respective profiles. At the time of harvest, anthocyanin, and phenolic concentration were increased by 10.4% and 14.5%, respectively, when compared to the NTV. These effects correlated with a specific modulation of genes involved in the flavonoid metabolic pathways. Moreover, grapes from ANE vines witnessed a significant reduction in the spreading of gray mold when they were either assessed in field conditions or in vitro, compared to the grapes of NTV vines. This was related to a significant upregulation of the defense-related genes of the plant. CONCLUSIONS: Overall, the results showed that A. nodosum extracts can be valuable tools in viticulture considering the emergence of challenging environmental conditions; hence, the regulation of specific metabolic pathways is the mechanism of action that leads to an increased tolerance of biotic stress and of changes in the content of grape metabolites. © 2019 Society of Chemical Industry.

Nonlocal and Nonadiabatic Effects in the Charge-Density Response of Solids: A Time-Dependent Density-Functional Approach.

The charge-density response of extended materials is usually dominated by the collective oscillation of electrons, the plasmons. Beyond this feature, however, intriguing many-body effects are observed. They cannot be described by one of the most widely used approaches for the calculation of dielectric functions, which is time-dependent density functional theory (TDDFT) in the adiabatic local density approximation (ALDA). Here, we propose an approximation to the TDDFT exchange-correlation kernel which is nonadiabatic and nonlocal. It is extracted from correlated calculations in the homogeneous electron gas, where we have tabulated it for a wide range of wave vectors and frequencies. A simple mean density approximation allows one to use it in inhomogeneous materials where the density varies on a scale of 1.6 r_{s} or faster. This kernel contains effects that are completely absent in the ALDA; in particular, it correctly describes the double plasmon in the dynamic structure factor of sodium, and it shows the characteristic low-energy peak that appears in systems with low electronic density. It also leads to an overall quantitative improvement of spectra.

Distinct transcriptome responses to water limitation in isohydric and anisohydric grapevine cultivars.

BACKGROUND: Grapevine (Vitis vinifera L.) is an economically important crop with a wide geographical distribution, reflecting its ability to grow successfully in a range of climates. However, many vineyards are located in regions with seasonal drought, and these are often predicted to be global climate change hotspots. Climate change affects the entire physiology of grapevine, with strong effects on yield, wine quality and typicity, making it difficult to produce berries of optimal enological quality and consistent stability over the forthcoming decades. RESULTS: Here we investigated the reactions of two grapevine cultivars to water stress, the isohydric variety Montepulciano and the anisohydric variety Sangiovese, by examining physiological and molecular perturbations in the leaf and berry. A multidisciplinary approach was used to characterize the distinct stomatal behavior of the two cultivars and its impact on leaf and berry gene expression. Positive associations were found among the photosynthetic, physiological and transcriptional modifications, and candidate genes encoding master regulators of the water stress response were identified using an integrated approach based on the analysis of topological co-expression network properties. In particular, the genome-wide transcriptional study indicated that the isohydric behavior relies upon the following responses: i) faster transcriptome response after stress imposition; ii) faster abscisic acid-related gene modulation; iii) more rapid expression of heat shock protein (HSP) genes and iv) reversion of gene-expression profile at rewatering. Conversely, that reactive oxygen species (ROS)-scavenging enzymes, molecular chaperones and abiotic stress-related genes were induced earlier and more strongly in the anisohydric cultivar. CONCLUSIONS: Overall, the present work found original evidence of a molecular basis for the proposed classification between isohydric and anisohydric grapevine genotypes.

Exciton Band Structure in Two-Dimensional Materials.

Low-dimensional materials differ from their bulk counterparts in many respects. In particular, the screening of the Coulomb interaction is strongly reduced, which can have important consequences such as the significant increase of exciton binding energies. In bulk materials the binding energy is used as an indicator in optical spectra to distinguish different kinds of excitons, but this is not possible in low-dimensional materials, where the binding energy is large and comparable in size for excitons of very different localization. Here we demonstrate that the exciton band structure, which can be accessed experimentally, instead provides a powerful way to identify the exciton character. By comparing the ab initio solution of the many-body Bethe-Salpeter equation for graphane and single-layer hexagonal boron nitride, we draw a general picture of the exciton dispersion in two-dimensional materials, highlighting the different role played by the exchange electron-hole interaction and by the electronic band structure. Our interpretation is substantiated by a prediction for phosphorene.

MECS-VINE®: A New Proximal Sensor for Segmented Mapping of Vigor and Yield Parameters on Vineyard Rows.

Ground-based proximal sensing of vineyard features is gaining interest due to its ability to serve in even quite small plots with the advantage of being conducted concurrently with normal vineyard practices (i.e., spraying, pruning or soil tilling) with no dependence upon weather conditions, external services or law-imposed limitations. The purpose of the present work was to test performance of the new terrestrial multi-sensor MECS-VINE® in terms of reliability and degree of correlation with several canopy growth and yield parameters in the grapevine. MECS-VINE®, once conveniently positioned in front of the tractor, can provide simultaneous assessment of growth features and microclimate of specific canopy sections of the two adjacent row sides. MECS-VINE® integrates a series of microclimate sensors (air relative humidity, air and surface temperature) with two (left and right) matrix-based optical RGB imaging sensors and a related algorithm, termed Canoyct). MECS-VINE® was run five times along the season in a mature cv. Barbera vineyard and a Canopy Index (CI, pure number varying from 0 to 1000), calculated through its built-in algorithm, validated vs. canopy structure parameters (i.e., leaf layer number, fractions of canopy gaps and interior leaves) derived from point quadrat analysis. Results showed that CI was highly correlated vs. any canopy parameter at any date, although the closest relationships were found for CI vs. fraction of canopy gaps (R² = 0.97) and leaf layer number (R² = 0.97) for data pooled over 24 test vines. While correlations against canopy light interception and total lateral leaf area were still unsatisfactory, a good correlation was found vs. cluster and berry weight (R² = 0.76 and 0.71, respectively) suggesting a good potential also for yield estimates. Besides the quite satisfactory calibration provided, main improvements of MECS-VINE® usage versus other current equipment are: (i) MECS-VINE® delivers a segmented evaluation of the canopy up to 15 different sectors, therefore allowing to differentiate canopy structure and density at specific and crucial canopy segments (i.e., basal part where clusters are located) and (ii) the sensor is optimized to work at any time of the day with any weather condition without the need of any supplemental lighting system.

Effects of low-energy excitations on spectral properties at higher binding energy: the metal-insulator transition of VO(2).

The effects of electron interaction on spectral properties can be understood in terms of coupling between excitations. In transition-metal oxides, the spectral function close to the Fermi level and low-energy excitations between d states have attracted particular attention. In this work we focus on photoemission spectra of vanadium dioxide over a wide (10 eV) range of binding energies. We show that there are clear signatures of the metal-insulator transition over the whole range due to a cross coupling of the delocalized s and p states with low-energy excitations between the localized d states. This coupling can be understood by advanced calculations based on many-body perturbation theory in the GW approximation. We also advocate the fact that tuning the photon energy up to the hard-x-ray range can help to distinguish fingerprints of correlation from pure band-structure effects.

Dynamical effects in electron spectroscopy.

One of the big challenges of theoretical condensed-matter physics is the description, understanding, and prediction of the effects of the Coulomb interaction on materials properties. In electronic spectra, the Coulomb interaction causes a renormalization of energies and change of spectral weight. Most importantly, it can lead to new structures, often called satellites. These can be linked to the coupling of excitations, also termed dynamical effects. State-of-the-art methods in the framework of many-body perturbation theory, in particular, the widely used GW approximation, often fail to describe satellite spectra. Instead, approaches based on a picture of electron-boson coupling such as the cumulant expansion are promising for the description of plasmon satellites. In this work, we give a unified derivation of the GW approximation and the cumulant expansion for the one-body Green's function. Using the example of bulk sodium, we compare the resulting spectral functions both in the valence and in the core region, and we discuss the dispersion of quasi-particles and satellites. We show that self-consistency is crucial to obtain meaningful results, in particular, at large binding energies. Very good agreement with experiment is obtained when the intrinsic spectral function is corrected for extrinsic and interference effects. Finally, we sketch how one can approach the problem in the case of the two-body Green's function, and we discuss the cancellation of various dynamical effects that occur in that case.

Quasiparticle self-consistent GW method for the spectral properties of complex materials.

The GW approximation to the formally exact many-body perturbation theory has been applied successfully to materials for several decades. Since the practical calculations are extremely cumbersome, the GW self-energy is most commonly evaluated using a first-order perturbative approach: This is the so-called G 0 W 0 scheme. However, the G 0 W 0 approximation depends heavily on the mean-field theory that is employed as a basis for the perturbation theory. Recently, a procedure to reach a kind of self-consistency within the GW framework has been proposed. The quasiparticle self-consistent GW (QSGW) approximation retains some positive aspects of a self-consistent approach, but circumvents the intricacies of the complete GW theory, which is inconveniently based on a non-Hermitian and dynamical self-energy. This new scheme allows one to surmount most of the flaws of the usual G 0 W 0 at a moderate calculation cost and at a reasonable implementation burden. In particular, the issues of small band gap semiconductors, of large band gap insulators, and of some transition metal oxides are then cured. The QSGW method broadens the range of materials for which the spectral properties can be predicted with confidence.

Instantaneous band gap collapse in photoexcited monoclinic VO2 due to photocarrier doping.

Using femtosecond time-resolved photoelectron spectroscopy we demonstrate that photoexcitation transforms monoclinic VO2 quasi-instantaneously into a metal. Thereby, we exclude an 80 fs structural bottleneck for the photoinduced electronic phase transition of VO2. First-principles many-body perturbation theory calculations reveal a high sensitivity of the VO2 band gap to variations of the dynamically screened Coulomb interaction, supporting a fully electronically driven isostructural insulator-to-metal transition. We thus conclude that the ultrafast band structure renormalization is caused by photoexcitation of carriers from localized V 3d valence states, strongly changing the screening before significant hot-carrier relaxation or ionic motion has occurred.

Risk of fracture in women with glucocorticoid requiring diseases is independent from glucocorticoid use: An analysis on a nation-wide database.

OBJECTIVE: Glucocorticoid-induced osteoporosis (GIOP) is a common cause of secondary osteoporosis. However, glucocorticoid requiring diseases pose a risk themselves for fracture. The aim of the present study was to determine the risk of fracture associated with variety of glucocorticoid requiring diseases independently from glucocorticoid use and other risk factors for osteoporosis. METHODS: We conducted a retrospective cross-sectional analysis of a nation-wide cohort (DeFRACalc79 database). We used multivariable regression analysis adjusting for several risk factors for fracture and glucocorticoid intake to estimate the independent role of glucocorticoid requiring illnesses on fracture risk. RESULTS: We found that patients with rheumatoid arthritis, connective tissue diseases, chronic obstructive pulmonary disease (COPD) and neurological diseases were at greater risk of vertebral or hip fracture (crude ORs 1.31, 1.20, 1.92 and 2.97 respectively). After adjusting for potential confounders COPD and neurological diseases remained significantly associated with an increased risk of vertebral or hip fractures (aORs 1.33, 95 % CI 1.18-1.49 and 2.43, 95 % CI 2.17-2.74). Rheumatoid arthritis, COPD, IBD and neurological diseases also significantly increased the risk of non-vertebral, non-hip fractures (aORs 1.23, 1.42, 1.52 and 1.94 respectively). CONCLUSION: Some glucocorticoid requiring diseases were independently associated with an increased risk of fractures. COPD and neurological diseases with both vertebral and non-vertebral fracture risk while RA and IBD were independently associated only with non-vertebral, non-hip fractures.