Audiovisual gamma stimulation enhances hippocampal neurogenesis and neural circuit plasticity in aging mice.

Gamma oscillations are disrupted in various neurological disorders, including Alzheimer's disease (AD). In AD mouse models, non-invasive audiovisual stimulation (AuViS) at 40 Hz enhances gamma oscillations, clears amyloid-beta, and improves cognition. We investigated mechanisms of circuit remodeling underlying these restorative effects by leveraging the sensitivity of hippocampal neurogenesis to activity in middle-aged wild-type mice.

Impact of size and fragmentation of the anteroinferior glenoid rim on clinical and functional outcomes of non-operatively treated Bony Bankart lesions in middle-aged population.

Introduction: The optimal treatment approach for Bony Bankart remains a subject of considerable debate among shoulder surgeons. Existing literature highlights low recurrence rates and high patient satisfaction with nonoperative treatment, particularly in the middle-aged population. This study aimed to evaluate the recurrence rate of dislocation, as well as the clinical and functional outcomes in middle-aged individuals treated nonoperatively following an acute bony Bankart fracture.

Influence of Front-End Electronics on Metrological Performance of QCM Systems.

Quartz Crystal Microbalances (QCMs) are versatile sensors employed in various fields, from environmental monitoring to biomedical applications, owing mainly to their very high sensitivity. However, the assessment of their metrological performance, including the impact of conditioning circuits, digital processing algorithms, and working conditions, is a complex and novel area of study. The purpose of this work is to investigate and understand the measurement errors associated with different QCM measurement techniques, specifically focusing on the influence of conditioning electronic circuits.

A Low Complexity Rolling Bearing Diagnosis Technique Based on Machine Learning and Smart Preprocessing.

In this work, we present a diagnosis system for rolling bearings that leverages simultaneous measurements of vibrations and machine rotation speed. Our approach combines the robustness of simple time domain methods for fault detection with the potential of machine learning techniques for fault location. This research is based on a neural network classifier, which exploits a simple and novel preprocessing algorithm specifically designed for minimizing the dependency of the classifier performance on the machine working conditions, on the bearing model and on the acquisition system set-up.

Unique potential of immature adult-born neurons for the remodeling of CA3 spatial maps.

Mammalian hippocampal circuits undergo extensive remodeling through adult neurogenesis. While this process has been widely studied, the specific contribution of adult-born granule cells (aGCs) to spatial operations in the hippocampus remains unknown. Here, we show that optogenetic activation of 4-week-old (young) aGCs in free-foraging mice produces a non-reversible reconfiguration of spatial maps in proximal CA3 while rarely evoking neural activity.

A Convolutional Neural Network for Electrical Fault Recognition in Active Magnetic Bearing Systems.

Active magnetic bearings are complex mechatronic systems that consist of mechanical, electrical, and software parts, unlike classical rolling bearings. Given the complexity of this type of system, fault detection is a critical process. This paper presents a new and easy way to detect faults based on the use of a fault dictionary and machine learning.

Supra-orbital whiskers act as wind-sensing antennae in rats.

We know little about mammalian anemotaxis or wind sensing. Recently, however, Hartmann and colleagues showed whisker-based anemotaxis in rats. To investigate how whiskers sense airflow, we first tracked whisker tips in anesthetized rats under low (0.

A Distributed IoT Air Quality Measurement System for High-Risk Workplace Safety Enhancement.

The safety of an operator working in a hazardous environment is a recurring topic in the technical literature of recent years, especially for high-risk environments such as oil and gas plants, refineries, gas depots, or chemical industries. One of the highest risk factors is constituted by the presence of gaseous substances such as toxic compounds such as carbon monoxide and nitric oxides, particulate matter or indoors, in closed spaces, low oxygen concentration atmospheres, and high concentrations of CO that can represent a risk for human health. In this context, there exist many monitoring systems for lots of specific applications where gas detection is required.

Characterization of the Response of Magnetron Sputtered InO Sensors to NO.

The response of resistive InO sensing devices was investigated as a function of the NO concentration in different operative conditions. Sensing layers are 150 nm thick films manufactured by oxygen-free room temperature magnetron sputtering deposition. This technique allows for a facile and fast manufacturing process, at same time providing advantages in terms of gas sensing performances.

Highly Reliable Multicomponent MEMS Sensor for Predictive Maintenance Management of Rolling Bearings.

In the field of vibration monitoring and control, the use of low-cost multicomponent MEMS-based accelerometer sensors is nowadays increasingly widespread. Such sensors allow implementing lightweight monitoring systems with low management costs, low power consumption and a small size. However, for the monitoring systems to provide trustworthy and meaningful data, the high accuracy and reliability of sensors are essential requirements.

Performance Evaluation of an IoT Sensor Node for Health Monitoring of Artwork and Ancient Wooden Structures.

In this paper, an IoT sensor node, based on smart Bluetooth low energy (BLE), for the health monitoring of artworks and large wooden structures is presented. The measurements from sensors on board the node are collected in real-time and sent to a remote gateway. The sensor node allows for the monitoring of environmental parameters, in particular, temperature and humidity, with accurate and robust integrated sensors.

Strategies for the Accurate Measurement of the Resonance Frequency in QCM-D Systems via Low-Cost Digital Techniques.

In this paper, an FPGA (Field Programmable Gate Array)-based digital architecture for the measurement of quartz crystal microbalance (QCM) oscillating frequency of transient responses, i.e., in QCM-D (QCM and Dissipation) applications, is presented.

Spatial maps and oscillations in the healthy hippocampus of Octodon degus, a natural model of sporadic Alzheimer's disease.

The Octodon degus is a South American rodent that is receiving increased attention as a potential model of aging and sporadic late-onset Alzheimer's disease (AD). Impairments in spatial memory tasks in Octodon degus have been reported in relation to either advanced AD-like disease or hippocampal lesion, opening the way to investigate how the function of hippocampal networks affects behavior across AD stages. However, no characterization of hippocampal electrophysiology exists in this species.

Overview of Anti-SARS-CoV-2 Immune Response Six Months after BNT162b2 mRNA Vaccine.

Background: We have designed a prospective study aiming to monitor the immune response in 178 health care workers six months after BNT162b2 mRNA vaccination.

Methods: The humoral immune response of all subjects was evaluated by chemiluminescence (CMIA); in 60 serum samples, a live virus-based neutralization assay was also tested. Moreover, 6 months after vaccination, B- and T-cell subsets from 20 subjects were observed by FACS analysis after restimulation with the trimeric SARS-CoV-2 Spike protein as an antigen, thus mimicking reinfection in vitro.

Fear memory modulation by incentive down and up-shifts.

Research on retrieval-induced malleability of maladaptive emotional memories has been mostly focused on the effect of drugs and extinction (i.e. post-retrieval extinction).

Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization.

This paper aims to thoroughly investigate the potential of ion current measurements in the context of combustion process monitoring in gas turbines. The study is targeted at characterizing the dynamic behavior of a typical ion-current measurement system based on a spark-plug. Starting from the preliminary study published in a previous work, the authors propose a refined model of the electrode (spark plug), based on the Langmuir probe theory, that incorporates the physical surface effects and proposes an optimized design of the conditioning electronics, which exploits a low frequency AC square wave biasing of the electrodes and allows for compensating some relevant parasitic effects.

Modeling the Conductivity Response to NO Gas of Films Based on MWCNT Networks.

This work proposes a model describing the dynamic behavior of sensing films based on functionalized MWCNT networks in terms of conductivity when exposed to time-variable concentrations of NO and operating with variable working temperatures. To test the proposed model, disordered networks of MWCNTs functionalized with COOH and Au nanoparticles were exploited. The model is derived from theoretical descriptions of the electronic transport in the nanotube network, of the NO chemisorption reaction and of the interaction of these two phenomena.

An Adaptive Measurement System for the Simultaneous Evaluation of Frequency Shift and Series Resistance of QCM in Liquid.

In this paper, a novel measurement system based on Quartz Crystal Microbalances is presented. The proposed solution was conceived specifically to overcome the measurement problems related to Quartz Crystal Microbalance (QCM) applications in dielectric liquids where the Q-factor of the resonant system is severely reduced with respect to in-gas applications. The QCM is placed in a Meacham oscillator embedding an amplifier with adjustable gain, an automatic strategy for gain tuning allows for maintaining the oscillator frequency close to the series resonance frequency of the quartz, which is related in a simple way with the physical parameters of interest.

Evaluating the efficiency of enzyme accelerated CO capture: chemical kinetics modelling for interpreting measurement results.

In this paper, the efficiency of the carbonic anhydrase (CA) enzyme in accelerating the hydration of CO is evaluated using a measurement system which consists of a vessel in which a gaseous flow of mixtures of nitrogen and CO is bubbled into water or water solutions containing a known quantity of CA enzyme. The pH value of the solution and the CO concentration at the measurement system gas exhaust are continuously monitored. The measured CO level allows for assessing the quantity of CO, which, subtracted from the gaseous phase, is dissolved into the liquid phase and/or hydrated to bicarbonate.

Prevention of Periprosthetic Joint Infection (PJI): A Clinical Practice Protocol in High-Risk Patients.

Periprosthetic joint infection (PJI) represents 25% of failed total knee arthroplasties (TKA). The European Knee Associates (EKA) formed a transatlantic panel of experts to perform a literature review examining patient-related risk factors with the objective of producing perioperative recommendations in PJI high-risk patients. Multiple databases (Pubmed/MEDLINE, EMBASE, Scopus, Cochrane Library) and recommendations on TKA PJI prevention measures from the International Consensus Meetings on PJI from the AAOS and AAHKS were reviewed.

No2 Sensing with SWCNT Decorated by Nanoparticles in Temperature Pulsed Mode: Modeling and Characterization.

In this paper, NO sensing by means of single-wall carbon nanotubes (SWCNT) networks, decorated with nanoparticles of TiO and Au, is proposed. In particular, it is shown that the performance of these materials can be enhanced using pulsed temperature mode. This sensing strategy effectiveness is theoretically and experimentally assessed.

Highly Sensitive Detection of NO by Au and TiO Nanoparticles Decorated SWCNTs Sensors.

The aim of this work is to investigate the gas sensing performance of single wall carbon nanotubes (SWCNTs)-based conductive sensors operating at low-medium temperatures (<250 °C). The investigated sensing films consists of an SWCNT network obtained by drop-casting a SWCNT suspension. Starting from this base preparation, different sensing devices were obtained by decorating the SWCNT network with materials suitable for enhancing the sensitivity toward the target gas.