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Abstract Earthquake swarms may be driven by fluids, through hydraulic injections or natural fluid circulation, but also by slow and aseismic slip transients. Understanding the driving factors for these prolific sequences and how they can potentially develop into larger ruptures remains a challenge. A notable and almost ubiquitous feature of swarms is their hypocenters migration, which occurrence is closely related to the processes driving the observed seismicity, in a similar way as seismicity accompanies slow-slip events at subduction zones. Here, we analyze global data on migrating sequences, and identify scaling laws for migration velocity, moment and duration measured on natural and injection-induced swarms, foreshock sequences, and slow slip events. We highlight two different behaviors among these sequences: one linked to slow slips, with elevated migration velocities and moments, and the other related to fluid-induced processes, featuring lower velocities and moments. These results provide metrics for distinguishing between the drivers of earthquake swarms, fluid or slow-slip related, and prompt a reevaluation of scaling laws of fault slip transients, especially for swarms.

Abstract Background In recent years, significant efforts have been directed towards the research and development of disease-modifying therapies for dementia. These drugs focus on prodromal (mild cognitive impairment, MCI) and/or early stages of Alzheimer’s disease (AD). Literature evidence indicates that a considerable proportion of individuals with MCI do not progress to dementia. Identifying individuals at higher risk of developing dementia is essential for appropriate management, including the prescription of new disease-modifying therapies expected to become available in clinical practice in the near future. Methods The ongoing INTERCEPTOR study is a multicenter, longitudinal, interventional, non-therapeutic cohort study designed to enroll 500 individuals with MCI aged 50–85 years. The primary aim is to identify a biomarker or a set of biomarkers able to accurately predict the conversion from MCI to AD dementia within 3 years of follow-up. The biomarkers investigated in this study are neuropsychological tests (mini-mental state examination (MMSE) and delayed free recall), brain glucose metabolism ([18F]FDG-PET), MRI volumetry of the hippocampus, EEG brain connectivity, cerebrospinal fluid (CSF) markers (p-tau, t-tau, Aβ1-42, Aβ1-42/1–40 ratio, Aβ1-42/p-Tau ratio) and APOE genotype. The baseline visit includes a full cognitive and neuropsychological evaluation, as well as the collection of clinical and socio-demographic information. Prognostic models will be developed using Cox regression, incorporating individual characteristics and biomarkers through stepwise selection. Model performance will be evaluated in terms of discrimination and calibration and subjected to internal validation using the bootstrapping procedure. The final model will be visually represented as a nomogram. Discussion This paper contains a detailed description of the statistical analysis plan to ensure the reproducibility and transparency of the analysis. The prognostic model developed in this study aims to identify the population with MCI at higher risk of developing AD dementia, potentially eligible for drug prescriptions. The nomogram could provide a valuable tool for clinicians for risk stratification and early treatment decisions. Trial registration ClinicalTrials.gov NCT03834402. Registered on February 8, 2019

Abstract Cadmium is a highly toxic metal, and its presence can have adverse effects on both human health and aquatic ecosystems. The efficient removal of cadmium from wastewater is therefore of crucial importance, but traditional methods have proved to be inadequate. Thus, technologies for the treatment of wastewater containing cadmium, including adsorption, have been developed. The aim of this study was the preparation of a polymeric material by the grafting reaction of κ-carrageenan and its use as an adsorbent for cadmium removal. This was performed to study the removal capacity of cadmium ions in synthetic solutions, as well as the effects of pH and ions on adsorption capacity, adsorption kinetics, isotherms, and reusability. Additionally, the disinfectant potential of the solution was evaluated for the inactivation of total coliforms and E. coli in river water. The best adsorption capacity was 75.52 ± 1.325 mg g−1, with the kinetics described by the pseudo-second order model. Maximum adsorption capacity (127.6 ± 1.833 mg g−1) and RL (0.0113) were determined using the Langmuir model, the Freundlich model was the one that best fits the experimental data and indicated cooperative adsorption, and the Dubinin-Radushkevich isotherm was used to obtain the adsorption energy and identify that it is physical. The presence of ions K+, Na+, Mg2+, and Ca2+ in a concentration of 0.5% decreased the adsorption capacity, and that at pH 2.0, the adsorption capacity was drastically reduced. The study indicates that the polymer has potential as an adsorbent for removing cadmium from aqueous solutions and exhibits self-disinfecting properties.

ObjectiveThe aim of the study was to characterize drug prescription patterns in elderly patients hospitalized in acute wards as a function of cognitive status and staff training.MethodsWe recorded clinical parameters reflecting health status and drug prescriptions at admission, during hospital stay, and at discharge before and after a short staff training on the needs of aged cognitively impaired patients. Participants aged 65 and older had a Mini-Mental State Examination (MMSE) score ≥16. The number of prescriptions, sedative and anticholinergic load, and drug–drug interactions were evaluated. Of the 116 older patients analyzed, 59 patients were cognitively impaired, and 57 were cognitively normal with an MMSE value > 24. Fifty-nine patients (28 CN, 31 CI) were assisted by the hospital health staff after training.ResultsParticipants presented a widespread polypharmacy. Cognitively impaired patients received more prescriptions, more inappropriate prescriptions, had a greater sedative load, and were exposed to more interactions. Staff training had no effect on the prescription pattern.ConclusionThe results suggest that hospitalized cognitively impaired patients are overprescribed psychotropic drugs and have an excessive sedative and anticholinergic load. Interventions designed to improve dementia care practices in health staff that are not also designed to manage drug polypharmacy do not modify prescription patterns.

Genomic Selection (GS) in tree breeding optimizes genetic gains by leveraging genomic data to enable early selection of seedlings without phenotypic data reducing breeding cycle and increasing selection intensity. Traditional assessments of the potential of GS in forest trees have typically focused on model performance using cross-validation within the same generation but evaluating effectively realized predictive ability (RPA) across generations is crucial. This study estimated RPAs for volume growth (VOL), wood density (WD), and pulp yield (PY) across four generations breeding of Eucalyptus grandis. The training set spanned three generations, including 34,461 trees with three-year growth data, 6,014 trees with wood quality trait data, and 1,918 trees with 12,695 SNPs (single nucleotide polymorphisms) data. Employing single-step genomic BLUP, we compared the genomic predictions of breeding values (GEBVs) for 1,153 fourth-generation full-sib seedlings in the greenhouse with their later-collected phenotypic estimated breeding values (EBVs) at age three years. RPAs were estimated using three GS targets (individual trees, trees within families, and families), two selection criteria (single- and multiple-trait), and training populations of either all 1,918 genotyped trees or the 67 direct ancestors of the selection candidates. RPAs were higher for wood quality traits (0.33 to 0.59) compared to VOL (0.14 to 0.19) and improved for wood traits (0.42 to 0.75) but not for VOL when trained only with direct ancestors, highlighting the challenges in accurately predicting growth traits. GS was more effective at excluding bottom-ranked candidates than selecting top-ranked ones. The between-family GS approach outperformed individual-tree selection for VOL (0.11 to 0.16) and PY (0.72 to 0.75), but not for WD (0.43 vs. 0.42). Furthermore, higher levels of relatedness and lower genotype by environment (G × E) interaction between training and testing populations enhanced RPAs for VOL (0.39). In summary, despite limited effectiveness in ranking top VOL individuals, GS effectively identified low-performing individuals and families. These multi-generational findings underscore GS’s potential in tree breeding, stressing the importance of considering relatedness and G × E interaction for optimal performance.

IntroductionWe aim to provide guidance on outcomes and measures for use in patients with Alzheimer's clinical syndrome.MethodsA consensus group of 20 voting members nominated by 10 professional societies, and a non-voting chair, used a Delphi approach and modified GRADE criteria.ResultsConsensus was reached on priority outcomes (n = 66), measures (n = 49) and statements (n = 37) across nine domains. A number of outcomes and measurement instruments were ranked for: Cognitive abilities; Functional abilities/dependency; Behavioural and neuropsychiatric symptoms; Patient quality of life (QoL); Caregiver QoL; Healthcare and treatment-related outcomes; Medical investigations; Disease-related life events; and Global outcomes.DiscussionThis work provides indications on the domains and ideal pertinent measurement instruments that clinicians may wish to use to follow patients with cognitive impairment. More work is needed to develop instruments that are more feasible in the context of the constraints of clinical routine.

Abstract Background Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes. Methods We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients. Results Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440–21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR. Conclusions We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.

Abstract Currently food fraud and authenticity of products composition are topics of great concern; ingredients quantification could allow to identify small amounts of contaminats or voluntary addition of improper components. Many molecular methods are available for species identification in foodstuffs but, for a better application, they should not be affected by the interference of other ingredients. The main purpose of this work was to verify the Real Time PCR and the Digital PCR (dPCR) quantification performances on baby food samples, specifically selected for their high miscibility to limit variability; chicken was selected as target to verify the performance of quantification of methods after having spiked the same quantity in different baby foods. The other aims were: (1) to verify a constant genome copies ratio existence between mammalian and avian species (2) to verify the dPCR performance, set up on housekeeping, to quantify mammalian and avian species in commercial products. Digital PCR showed fewer differences respect to Real Time PCR, at the same 15% w/w chicken spiking level. Despite the constant difference between mammalian and avian genome copies, in samples with the same spiking weight, the confidence intervals increasing towards the extreme values, made impossible to use genome copies ratio as a sort of correction factor between species. Finally, the dPCR system using the myostatin housekeeping gene to determine the chicken content seemed reliable to verify the labelling compliance in meat-based commercial products.

Abstract Background The identification and staging of Alzheimer’s Disease (AD) represent a challenge, especially in the prodromal stage of Mild Cognitive Impairment (MCI), when cognitive changes can be subtle. Worldwide efforts were dedicated to select and harmonize available neuropsychological instruments. In Italy, the Italian Network of Neuroscience and Neuro-Rehabilitation has promoted the adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB), collecting normative data from 433 healthy controls (HC). Here, we aimed to explore the ability of I-UDSNB to differentiate between a) MCI and HC, b) AD and HC, c) MCI and AD. Methods One hundred thirty-seven patients (65 MCI, 72 AD) diagnosed after clinical-neuropsychological assessment, and 137 HC were included. We compared the I-UDSNB scores between a) MCI and HC, b) AD and HC, c) MCI and AD, with t-tests. To identify the test(s) most capable of differentiating between groups, significant scores were entered in binary logistic and in stepwise regressions, and then in Receiver Operating Characteristic curve analyses. Results Two episodic memory tests (Craft Story and Five Words test) differentiated MCI from HC subjects; Five Words test, Semantic Fluency (vegetables), and TMT-part B differentiated AD from, respectively, HC and MCI. Conclusions Our findings indicate that the I-UDSNB is a suitable tool for the harmonized and concise assessment of patients with cognitive decline, showing high sensitivity and specificity for the diagnosis of MCI and AD.

A high-resolution soot particle aerosol mass spectrometer (SP-AMS) was used to selectively measure refractory black carbon (rBC) and its associated coating material using both the ensemble size-resolved mass spectral mode and the event trigger single particle (ETSP) mode in Houston, Texas, in summer 2022. This study was conducted as part of the Department of Energy Atmospheric Radiation Measurement (ARM) program's TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign. The study revealed an average (±1σ) rBC concentration of 103 ± 176 ng m−3. Additionally, the coatings on the BC particles were primarily composed of organics (59 %; 219 ± 260 ng m−3) and sulfate (26 %; 94 ± 55 ng m−3). Positive matrix factorization (PMF) analysis of the ensemble mass spectra of BC-containing particles resolved four distinct types of soot aerosol, including an oxidized organic aerosol (OOABC,PMF) factor associated with processed primary organic aerosol, an inorganic sulfate factor (SO4,BC,PMF), an oxidized rBC factor (O-BCPMF), and a mixed mineral dust–biomass burning aerosol factor with significant contribution from potassium (K-BBBC,PMF). Additionally, K-means clustering analysis of the single-particle mass spectra identified eight different clusters, including soot particles enriched in hydrocarbon-like organic aerosol (HOABC,ETSP), sulfate (SO4,BC,ETSP), two types of rBC, OOA (OOABC,ETSP), chloride (ClBC,ETSP), and nitrate (NO3,BC,ETSP). The single-particle measurements demonstrate substantial variation in BC coating thickness with coating-to-rBC mass ratios ranging from 0.1 to 100. The mixing state index (χ), which denotes the degree of homogeneity of the soot aerosol, varied from 4 % to 94 % with a median of 40 %, indicating that the aerosol population lies in between internal and external mixing but has large temporal and source type variability. In addition, a significant fraction of BC-containing particles, a majority enriched with oxidized organics and sulfate, exhibit sufficiently high κ values and diameters conducive to activation as cloud nuclei under atmospherically relevant supersaturation conditions. This finding bears significance in comprehending the aging processes of rBC-containing particles and their activation into cloud droplets. Our analysis highlights the complex nature of soot aerosol and underscores the need to comprehend its variability across different environments for accurate assessment of climate change.

During the first operational phase (OP 1.1) of Wendelstein 7-X (W7-X) electron cyclotron resonance heating (ECRH) was the exclusive heating method and provided plasma start-up, wall conditioning, heating and current drive. Six gyrotrons were commissioned for OP1.1 and used in parallel for plasma operation with a power of up to 4.3 MW. During standard X2-heating the spatially localized power deposition with high power density allowed controlling the radial profiles of the electron temperature and the rotational transform. Even though W7-X was not fully equipped with first wall tiles and operated with a graphite limiter instead of a divertor, electron densities of n e > 3·1019 m-3 could be achieved at electron temperatures of several keV and ion temperatures above 2 keV. These plasma parameters allowed the first demonstration of a multipath O2-heating scenario, which is envisaged for safe operation near the X-cutoff-density of 1.2·1020 m-3 after full commissioning of the ECRH system in the next operation phase OP1.2.

Benjamin was perhaps Kafka’s most congenial critic, and he was among the first to understand the scope and value of the challenge posed by his entire literary oeuvre. In one of his notes, written in the 1930s, Benjamin placed Baudelaire and Kafka side by side, pointing to the former as a key figure in the literature of the xix century and the latter as that of the xxcentury. The article seeks to show how the main themes of Benjamin’s thought find the ground for elaboration and unraveling in the confrontation with Kafka’s work, opening up a perspective that interweaves the force of criticism with the sometimes visionary view of the most current aesthetic tensions.

The development of reduced models provide efficient methods that can be used to perform short term experimental data analysis or narrow down the parametric range of more sophisticated numerical approaches. Reduced models are derived by simplifying the physics description with the goal of retaining only the essential ingredients required to reproduce the phenomena under study. This is the role of the gyro-fluid code FAR3d, dedicated to analyze the linear and nonlinear stability of Alfvén Eigenmodes (AE), Energetic Particle Modes (EPM) and magnetic-hydrodynamic modes as pressure gradient driven mode (PGDM) and current driven modes (CDM) in nuclear fusion devices. Such analysis is valuable for improving the plasma heating efficiency and confinement; this can enhance the overall device performance. The present review is dedicated to a description of the most important contributions of the FAR3d code in the field of energetic particles (EP) and AE/EPM stability. FAR3d is used to model and characterize the AE/EPM activity measured in fusion devices as LHD, JET, DIII-D, EAST, TJ-II and Heliotron J. In addition, the computational efficiency of FAR3d facilitates performing massive parametric studies leading to the identification of optimization trends with respect to the AE/EPM stability. This can aid in identifying operational regimes where AE/EPM activity is avoided or minimized. This technique is applied to the analysis of optimized configurations with respect to the thermal plasma parameters, magnetic field configuration, external actuators and the effect of multiple EP populations. In addition, the AE/EPM saturation phase is analyzed, taking into account both steady-state phases and bursting activity observed in LHD and DIII-D devices. The nonlinear calculations provide: the induced EP transport, the generation of zonal structures as well as the energy transfer towards the thermal plasma and between different toroidal/helical families. Finally, FAR3d is used to forecast the AE/EPM stability in operational scenarios of future devices as ITER, CFETR, JT60SA and CFQS as well as possible approaches to optimization with respect to variations in the most important plasma parameters.

IntroductionCardiovascular disease (CVD) is responsible for over 30% of mortality worldwide. CVD arises from the complex influence of molecular, clinical, social, and environmental factors. Despite the growing number of autosomal genetic variants contributing to CVD, the cause of most CVDs is still unclear. Mitochondria are crucial in the pathophysiology, development and progression of CVDs; the impact of mitochondrial DNA (mtDNA) variants and mitochondrial haplogroups in the context of CVD has recently been highlighted.AimsWe investigated the role of genetic variants in both mtDNA and nuclear-encoded mitochondrial genes (NEMG) in CVD, including coronary artery disease (CAD), hypertension, and serum lipids in the UK Biobank, with sub-group analysis for diabetes.MethodsWe investigated 371,542 variants in 2,527 NEMG, along with 192 variants in 32 mitochondrial genes in 381,994 participants of the UK Biobank, stratifying by presence of diabetes.ResultsMitochondrial variants showed associations with CVD, hypertension, and serum lipids. Mitochondrial haplogroup J was associated with CAD and serum lipids, whereas mitochondrial haplogroups T and U were associated with CVD. Among NEMG, variants within Nitric Oxide Synthase 3 (NOS3) showed associations with CVD, CAD, hypertension, as well as diastolic and systolic blood pressure. We also identified Translocase Of Outer Mitochondrial Membrane 40 (TOMM40) variants associated with CAD; Solute carrier family 22 member 2 (SLC22A2) variants associated with CAD and CVD; and HLA-DQA1 variants associated with hypertension. Variants within these three genes were also associated with serum lipids.ConclusionOur study demonstrates the relevance of mitochondrial related variants in the context of CVD. We have linked mitochondrial haplogroup U to CVD, confirmed association of mitochondrial haplogroups J and T with CVD and proposed new markers of hypertension and serum lipids in the context of diabetes. We have also evidenced connections between the etiological pathways underlying CVDs, blood pressure and serum lipids, placing NOS3, SLC22A2, TOMM40 and HLA-DQA1 genes as common nexuses.