Establishing In-House Cutoffs of CSF Alzheimer’s Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort

Background: Clinical diagnosis of Alzheimer’s disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. Methods: We quantified CSF Aβ1-42, Aβ1-40, t-Tau, and p181Tau with standard INNOTEST^® ELISA and Lumipulse G^® chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer’s disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for Aβ1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and Aβ1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and Aβ1-42/Aβ1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). Results: Cutoff values of Aβ1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1-40 and 0.96 for p181TAU. Passing–Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1-40. Bland–Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the Aβ1-42/Aβ1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan–Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815⁻²⁷). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. Conclusions: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects.     

Postischemic Neuroprotection of Aminoethoxydiphenyl Borate Associates Shortening of Peri-Infarct Depolarizations

Brain stroke is a highly prevalent pathology and a main cause of disability among older adults. If not promptly treated with recanalization therapies, primary and secondary mechanisms of injury contribute to an increase in the lesion, enhancing neurological deficits. Targeting excitotoxicity and oxidative stress are very promising approaches, but only a few compounds have reached the clinic with relatively good positive outcomes. The exploration of novel targets might overcome the lack of clinical translation of previous efficient preclinical neuroprotective treatments. In this study, we examined the neuroprotective properties of 2-aminoethoxydiphenyl borate (2-APB), a molecule that interferes with intracellular calcium dynamics by the antagonization of several channels and receptors. In a permanent model of cerebral ischemia, we showed that 2-APB reduces the extent of the damage and preserves the functionality of the cortical territory, as evaluated by somatosensory evoked potentials (SSEPs). While in this permanent ischemia model, the neuroprotective effect exerted by the antioxidant scavenger cholesteronitrone F2 was associated with a reduction in reactive oxygen species (ROS) and better neuronal survival in the penumbra, 2-APB did not modify the inflammatory response or decrease the content of ROS and was mostly associated with a shortening of peri-infarct depolarizations, which translated into better cerebral blood perfusion in the penumbra. Our study highlights the potential of 2-APB to target spreading depolarization events and their associated inverse hemodynamic changes, which mainly contribute to extension of the area of lesion in cerebrovascular pathologies.     

miR-218-5p/RUNX2 Axis Positively Regulates Proliferation and Is Associated with Poor Prognosis in Cervical Cancer

The overexpression of miR-218-5p in cervical cancer (CC) cell lines decreases migration, invasion and proliferation. The objective was to identify target genes of miR-218-5p and the signaling pathways and cellular processes that they regulate. The relationship between the expression of miR-218-5p and RUNX2 and overall survival in CC as well as the effect of the exogenous overexpression of miR-218-5p on the level of RUNX2 were analyzed. The target gene prediction of miR-218-5p was performed in TargetScan, miRTarBase and miRDB. Predicted target genes were subjected to gene ontology (GO) and pathway enrichment analysis using the Kyoto Encyclopaedia of Genes and Genomes (KEGG). The miR-218-5p mimetic was transfected into C-33A and CaSki cells, and the miR-218-5p and RUNX2 levels were determined by RT–qPCR. Of the 118 predicted targets for miR-218-5p, 86 are involved in protein binding, and 10, including RUNX2, are involved in the upregulation of proliferation. Low miR-218-5p expression and a high level of RUNX2 are related to poor prognosis in CC. miR-218-5p overexpression is related to decreased RUNX2 expression in C-33A and CaSki cells. miR-218-5p may regulate RUNX2, and both molecules may be prognostic markers in CC.     

Design of high stroke electrostatic micropumps: a charge control approach with ring electrodes

A novel design strategy to avoid pull-in occurrence in electrostatic micro electro mechanical systems is proposed. It combines charge control with ring electrodes, on a circular geometry. This idea is introduced here for the design of efficient and reliable high stroke electrostatic diaphragm micropumps, while it has a broad potential applicability. A minimal lumped one degree-of-freedom model is derived and used to introduce and demonstrate the proposed approach for a circular plate geometry. Finite element models are subsequently adopted for a more detailed device modelling. As expected, charge control exhibits a stabilizing effect with respect to voltage drive, but not sufficient to achieve a full-range stability for the considered geometry. When the electrode area is properly defined, stability range can be extended up to gap closure in the central part of the membrane. In this configuration, the increase in voltage required for full-range device drive would be relevant, while in charge control the penalty is considerably lower. Finally, loading conditions and geometrical parameters for an optimized actuation are suggested.     

Inclusion dynamics hybrid automata

Hybrid systems are dynamical systems with the ability to describe mixed discrete-continuous evolution of a wide range of systems. Consequently, at first glance, hybrid systems appear powerful but recalcitrant, neither yielding to analysis and reasoning through a purely continuous-time modeling as with systems of differential equations, nor open to inferential processes commonly used for discrete state-transition systems such as finite state automata. A convenient and popular model, called hybrid automata, was introduced to model them and has spurred much interest on its tractability as a tool for inference and model checking in a general setting. Intuitively, a hybrid automaton is simply a “finite-state” automaton with each state augmented by continuous variables, which evolve according to a set of well-defined continuous laws, each specified separately for each state. This article investigates both the notion of hybrid automaton and the model checking problem over such a structure. In particular, it relates first-order theories and analysis results on multivalued maps and reduces the bounded reachability problem for hybrid automata whose continuous laws are expressed by inclusions (x′f(x,t)) to a decidability problem for first-order formulæ over the reals. Furthermore, the paper introduces a class of hybrid automata for which the reachability problem can be decided and shows that the problem of deciding whether a hybrid automaton belongs to this class can be again decided using first-order formulæ over the reals. Despite the fact that the bisimulation quotient for this class of hybrid automata can be infinite, we show that our techniques permit effective model checking for a nontrivial fragment of CTL.     

TMEM106B Acts as a Modifier of Cognitive and Motor Functions in Amyotrophic Lateral Sclerosis

The transmembrane protein 106B (TMEM106B) gene is a susceptibility factor and disease modifier of frontotemporal dementia, but few studies have investigated its role in amyotrophic lateral sclerosis. The aim of this work was to assess the impact of the TMEM106B rs1990622 (A–major risk allele; G–minor allele) on phenotypic variability of 865 patients with amyotrophic lateral sclerosis. Demographic and clinical features were compared according to genotypes by additive, dominant, and recessive genetic models. Bulbar onset was overrepresented among carriers of the AA risk genotype, together with enhanced upper motor neuron involvement and poorer functional status in patients harboring at least one major risk allele (A). In a subset of 195 patients, we found that the homozygotes for the minor allele (GG) showed lower scores at the Edinburgh Cognitive and Behavioral Amyotrophic Lateral Sclerosis Screen, indicating a more severe cognitive impairment, mainly involving the amyotrophic lateral sclerosis-specific cognitive functions and memory. Moreover, lower motor neuron burden predominated among patients with at least one minor allele (G). Overall, we found that TMEM106B is a disease modifier of amyotrophic lateral sclerosis, whose phenotypic effects encompass both sites of onset and functional status (major risk allele), motor functions (both major risk and minor alleles), and cognition (minor allele).     

A realistic framework to a greener supply chain for electric vehicles

The quantity of electric vehicles in the transport sector has steadily risen over the last 10 years. Most developed countries and China have laid out ambitious plans for electric vehicles penetration. However, there are several challenges that must be addressed on the supply‐chain side of the problem for a successful transition toward an alternative and less environmentally harmful transport system. This study proposes a methodology for the optimal plan and decision making of primary energy sources, electricity generation, electricity distribution to vehicles' charging stations, carbon capture and sequestration, and electric vehicles' charging stations network to satisfy the electricity demand of the overall economy including electric vehicles at a regional/countrywide level under operation and green constraints. The optimization problem was modeled as a mixed integer program in general algebraic modeling system (GAMS). The formulation was employed to propose the upcoming electricity supply chain for electric vehicles in the most populous German state (North Rhine‐Westphalia) in 2025. The optimization show that fossil‐based power still controls the generation in 2025, while carbon capture and sequestration along with higher renewable penetration help meeting the state's greenhouse gases (GHG) emission target. The charging stations network expansion consists of 12 820 charging points mainly alternating current (AC) chargers (22‐kW capacity).     

Impact of packaging properties on the physical-chemical-microbiological-sensory characteristics of Ricotta cheese during storage

Ricotta is a highly perishable cheese of which shelf-life is strongly influenced by the properties of packages in which it is stored. Four plastic packages currently in use in Italy (IT), Romania (RO), Slovenia (SLO), and Spain (SP) are characterized in term of structure, barrier, and antimicrobial properties, and their efficiency in the ricotta storage at 4°C is assessed. Differential scanning calorimetry and Fourier-transform infrared spectroscopy analysis indicate that the IT and SP packages are made of low-density polyethylene and the RO and SLO packages consist of polyethylene and polyamide 6. Permeability to the water vapour and oxygen transmission rate vary as follows: IT>SLO > RO > SP and SP > IT>RO > SLO, respectively. The SP package expressed the highest antimicrobial inhibition whilst the IT package the lowest. The maximum amounts of volatile compounds in cheese were reached after 3 days in the IT and SP packages and after 6 days in the SLO and RO packages. The score 2.8 for cheese overall acceptability was exceeded after 7 days in the IT, RO, and SP packages and 6 days in the SLO package. Barrier properties of packages significantly influence the shelf-life of ricotta. Low barrier properties resulted in high level of oxygen and water vapours inside the headspace of packages ultimately favour the microbial development. The simultaneous compliance of microbiological safety level and overall acceptability score gives ricotta a shelf-life of 3 days in the IT, RO, and SP packages and 1 day in the SLO package.