Enhancing Laryngeal Spinocellular Carcinoma Image Security with DCT.

This work proposes a novel secret sharing scheme to enhance the security of Laryngeal Spinocellular Carcinoma or Laryngeal Squamous Cell Carcinoma (LSCC) images using the Discrete Cosine Transformation (DCT) as a cryptographic tool. The DCT-based secret sharing method divides LSCC images into shares, each containing DCT coefficients that represent the image's frequency components. The original image can only be reconstructed when a predefined number of shares are combined, ensuring confidentiality and preventing unauthorized access.

Employment and Social Security/Insurance among patients affected by mental disorders in Italy: A descriptive multi-center study.

Introduction: Many mental disorders especially chronic serious ones such as schizophrenia-spectrum disorders, are disabling syndromes and impact on patients' social and cognitive functioning, including work activity. Thus, affected patients may show a particular socio-economic vulnerability and need specific social security as well as rehabilitation interventions, including pensions or job-placements. In Italy, the Working Group named 'Employment and Social Security/Insurance in Mental Health (ESSIMH)' was founded in 2020 in order to collect research evidence on mental illness, employment, social security, and rehabilitation.

Reduced magnetic mismatch negativity: a shared deficit in psychosis and related risk.

Background: Abnormal auditory processing of deviant stimuli, as reflected by mismatch negativity (MMN), is often reported in schizophrenia (SCZ). At present, it is still under debate whether this dysfunctional response is specific to the full-blown SCZ diagnosis or rather a marker of psychosis in general. The present study tested MMN in patients with SCZ, bipolar disorder (BD), first episode of psychosis (FEP), and in people at clinical high risk for psychosis (CHR).

Closed-loop motor imagery EEG simulation for brain-computer interfaces.

In a brain-computer interface (BCI) system, the testing of decoding algorithms, tasks, and their parameters is critical for optimizing performance. However, conducting human experiments can be costly and time-consuming, especially when investigating broad sets of parameters. Attempts to utilize previously collected data in offline analysis lack a co-adaptive feedback loop between the system and the user present online, limiting the applicability of the conclusions obtained to real-world uses of BCI.

Benefits of deep learning classification of continuous noninvasive brain-computer interface control.

. Noninvasive brain-computer interfaces (BCIs) assist paralyzed patients by providing access to the world without requiring surgical intervention. Prior work has suggested that EEG motor imagery based BCI can benefit from increased decoding accuracy through the application of deep learning methods, such as convolutional neural networks (CNNs).

Spatial-temporal aspects of continuous EEG-based neurorobotic control.

The goal of this work is to identify the spatio-temporal facets of state-of-the-art electroencephalography (EEG)-based continuous neurorobotics that need to be addressed, prior to deployment in practical applications at home and in the clinic.Nine healthy human subjects participated in five sessions of one-dimensional (1D) horizontal (LR), 1D vertical (UD) and two-dimensional (2D) neural tracking from EEG. Users controlled a robotic arm and virtual cursor to continuously track a Gaussian random motion target using EEG sensorimotor rhythm modulation via motor imagery (MI) commands.

Unexpected ICU Admission Is Associated with Pulmonary Complications but Not Increased Mortality; Rescue Is Essential for Optimal Patient Outcome.

ICU beds are in demand in large regional referral hospitals; therefore, nonintubated polytrauma patients are often admitted to general care (GC) wards. We hypothesized that trauma patients with Injury Severity Score (ISS) greater than 15 and unexpected ICU admission (U-ICU) after initial admission to GC had increased morbidity and mortality. We also hypothesized that those requiring U-ICU could be predicted based on admission parameters.

Noninvasive neuroimaging enhances continuous neural tracking for robotic device control.

Brain-computer interfaces (BCIs) utilizing signals acquired with intracortical implants have achieved successful high-dimensional robotic device control useful for completing daily tasks. However, the substantial amount of medical and surgical expertise required to correctly implant and operate these systems significantly limits their use beyond a few clinical cases. A noninvasive counterpart requiring less intervention that can provide high-quality control would profoundly impact the integration of BCIs into the clinical and home setting.

Brain-Heart Interactions Underlying Traditional Tibetan Buddhist Meditation.

Despite accumulating evidence suggesting improvement in one's well-being as a result of meditation, little is known about if or how the brain and the periphery interact to produce these behavioral and mental changes. We hypothesize that meditation reflects changes in the neural representations of visceral activity, such as cardiac behavior, and investigated the integration of neural and visceral systems and the spontaneous whole brain spatiotemporal dynamics underlying traditional Tibetan Buddhist meditation. In a large cohort of long-term Tibetan Buddhist monk meditation practitioners, we found distinct transient modulations of the neural response to heartbeats in the default mode network (DMN), along with large-scale network reconfigurations in the gamma and theta bands of electroencephalography (EEG) activity induced by meditation.

Three-Dimensional Brain-Computer Interface Control Through Simultaneous Overt Spatial Attentional and Motor Imagery Tasks.

Objective: While noninvasive electroenceph-alography (EEG) based brain-computer interfacing (BCI) has been successfully demonstrated in two-dimensional (2-D) control tasks, little work has been published regarding its extension to practical three-dimensional (3-D) control.

Methods: In this study, we developed a new BCI approach for 3-D control by combining a novel form of endogenous visuospatial attentional modulation, defined as overt spatial attention (OSA), and motor imagery (MI).

Results: OSA modulation was shown to provide comparable control to conventional MI modulation in both 1-D and 2-D tasks.

Interdependence theory of tissue failure: bulk and boundary effects.

The mortality rate of many complex multicellular organisms increases with age, which suggests that net ageing damage is accumulative, despite remodelling processes. But how exactly do these little mishaps in the cellular level accumulate and spread to become a systemic catastrophe? To address this question we present experiments with synthetic tissues, an analytical model consistent with experiments, and a number of implications that follow the analytical model. Our theoretical framework describes how shape, curvature and density influences the propagation of failure in a tissue subjected to oxidative damage.

The influence of tissue antioxidant enzymes and inflammatory cascade in pathology of cystitis: An experimental rat model.

We evaluate the role of antioxidant enzyme status and inflammatory cascade in disease progression of cystitis in a rat model. The animals were injected with clinically isolated Uropathogenic Escherichia coli (UPEC) and study the effect of various antioxidant enzymes and inflammatory markers in disease pathology on the 0 day, 12 h and 7 day of infection. The antioxidant status of bladder tissue was decreased during the 7 day of infection.

Role of antioxidant defence, renal toxicity markers and inflammatory cascade in disease progression of acute pyelonephritis in experimental rat model.

Urinary tract infections are the most common bacterial infections affecting millions of people each year worldwide. The animal model provides an excellent and suitable system for studying cystitis and pyelonephritis caused by Escherichia coli and other uropathogens. Using this established model, we evaluate the role of antioxidant defence system, renal injury markers, and blood parameters in the diseases progression during Escherichia coli infection on 0 day, 12h and 7 day.