Bilobed Gallbladder: A Rare Anatomical Variation Discovered During Laparoscopic Cholecystectomy.

A bilobed gallbladder is a rare congenital anomaly with two lobes sharing a single cystic duct, typically diagnosed preoperatively and rarely identified intraoperatively. Only a small number of cases have been documented in medical literature with limited information on associated conditions. A 22-year-old male patient, with a past medical history of cholelithiasis and no prior surgical history, presented with acute right upper quadrant pain and was diagnosed with acute cholecystitis.

A Surgical Conundrum: Addressing a Large Nasal Defect Following Mohs Micrographic Surgery.

Managing large nasal defects following Mohs surgery presents complex reconstructive challenges due to the nose's prominent and visible nature. These cases require a careful balance of preserving structural integrity, optimizing cosmetic outcomes, and maintaining vascular health. In situations where primary closure is impractical due to defect size and location, innovative techniques like the double rhomboid transposition flap offer versatile solutions, addressing both aesthetic concerns and functional requirements.

Beyond the surface: unveiling gaps in medical education through eyes of diverse learners.

Inadequate education regarding disease manifestations in diverse skin colors hinders diagnosis and exacerbates health disparities. All levels of medical trainees report low confidence in accurately identifying disease in skin of color (SOC). To help further elucidate these concerns, our research aims to assess medical student confidence in recognizing cutaneous diseases in SOC and their viewpoints regarding SOC education within their institution.

Psychosomatic response to acute emotional stress in healthy students.

The multidimensionality of the stress response has shown the complexity of this phenomenon and therefore the impossibility of finding a unique biomarker among the physiological variables related to stress. An experimental study was designed and performed to guarantee the correct synchronous and concurrent measure of psychometric tests, biochemical variables and physiological features related to acute emotional stress. The population studied corresponds to a group of 120 university students between 20 and 30 years of age, with healthy habits and without a diagnosis of chronic or psychiatric illnesses.

Machine-Learning Based Monitoring of Cognitive Workload in Rescue Missions With Drones.

In search and rescue missions, drone operations are challenging and cognitively demanding. High levels of cognitive workload can affect rescuers' performance, leading to failure with catastrophic outcomes. To face this problem, we propose a machine learning algorithm for real-time cognitive workload monitoring to understand if a search and rescue operator has to be replaced or if more resources are required.

ReBeatICG: Real-time Low-Complexity Beat-to-beat Impedance Cardiogram Delineation Algorithm.

This work presents ReBeatICG, a real-time, low-complexity beat-to-beat impedance cardiography (ICG) delineation algorithm that allows hemodynamic parameters monitoring. The proposed procedure relies only on the ICG signal compared to most algorithms found in the literature that rely on synchronous electrocardiogram signal (ECG) recordings. ReBeatICG was designed with implementation on an ultra-low-power microcontroller (MCU) in mind.

ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signals.

Continuous and multimodal stress detection has been performed recently through wearable devices and machine learning algorithms. However, a well-known and important challenge of working on physiological signals recorded by conventional monitoring devices is missing data due to sensors insufficient contact and interference by other equipment. This challenge becomes more problematic when the user/patient is mentally or physically active or stressed because of more frequent conscious or subconscious movements.

Importance of Timely Treatment Initiation in Infantile-Onset Pompe Disease, a Single-Centre Experience.

Classic infantile Pompe disease (IPD) is a rare lysosomal storage disorder characterized by severe hypertrophic cardiomyopathy and profound muscle weakness. Without treatment, death occurs within the first 2 years of life. Although enzyme replacement therapy (ERT) with alglucosidase alfa has improved survival, treatment outcome is not good in many cases and is largely dependent on age at initiation.

MBioTracker: Multimodal Self-Aware Bio-Monitoring Wearable System for Online Workload Detection.

Cognitive workload affects operators' performance principally in high-risk or time-demanding situations and when multitasking is required. An online cognitive workload monitoring system can provide valuable inputs to decision-making instances, such as the operator's state of mind and resulting performance. Therefore, it can allow potential adaptive support to the operator.

Urine Phenylacetylglutamine Determination in Patients with Hyperphenylalaninemia.

Phenylketonuria (PKU), an autosomal-recessive inborn error of phenylalanine (Phe) metabolism is the most prevalent disorder of amino acid metabolism. Currently, clinical follow-up relies on frequent monitoring of Phe levels in blood. We hypothesize that the urine level of phenylacetylglutamine (PAG), a phenyl-group marker, could be used as a non-invasive biomarker.

Real-Time EEG-Based Cognitive Workload Monitoring on Wearable Devices.

Objective: Cognitive workload monitoring (CWM) can enhance human-machine interaction by supporting task execution assistance considering the operator's cognitive state. Therefore, we propose a machine learning design methodology and a data processing strategy to enable CWM on resource-constrained wearable devices.

Methods: Our CWM solution is built upon edge computing on a simple wearable system, with only four peripheral channels of electroencephalography (EEG).

Real-Time Cognitive Workload Monitoring Based on Machine Learning Using Physiological Signals in Rescue Missions.

High levels of cognitive workload decreases human's performance and leads to failures with catastrophic outcomes in risky missions. Today, reliable cognitive workload detection presents a common major challenge, since the workload is not directly observable. However, cognitive workload affects several physiological signals that can be measured non-invasively.

REWARD: Design, Optimization, and Evaluation of a Real-Time Relative-Energy Wearable R-Peak Detection Algorithm.

Wearable devices are an unobtrusive, cost-effective means of continuous ambulatory monitoring of chronic cardiovascular diseases. However, on these resource-constrained systems, electrocardiogram (ECG) processing algorithms must consume minimal power and memory, yet robustly provide accurate physiological information. This work presents REWARD, the Relative-Energy-based WeArable R-Peak Detection algorithm, which is a novel ECG R-peak detection mechanism based on a nonlinear filtering method called Relative-Energy (Rel-En).

Multi-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices.

Monitoring stress and, in general, emotions has attracted a lot of attention over the past few decades. Stress monitoring has many applications, including high-risk missions and surgical procedures as well as mental/emotional health monitoring. In this paper, we evaluate the possibility of stress and emotion monitoring using off-the-shelf wearable sensors.

Production and Detection of an Axion Dark Matter Echo.

Electromagnetic radiation with angular frequency equal to half the axion mass stimulates the decay of cold dark matter axions and produces an echo, i.e., faint electromagnetic radiation traveling in the opposite direction.

Measuring acute stress response through physiological signals: towards a quantitative assessment of stress.

Social and medical problems associated with stress are increasing globally and seriously affect mental health and well-being. However, an effective stress-level monitoring method is still not available. This paper presents a quantitative method for monitoring acute stress levels in healthy young people using biomarkers from physiological signals that can be unobtrusively monitored.

Evaluation of chronic stress indicators in geriatric and oncologic caregivers: a cross-sectional study.

Caregiving induces chronic stress with physical and psychological impact on informal caregivers health. Therefore, subjective and objective indicators are needed for the early diagnosis of pathologic stress to prevent the risk of developing stress-related diseases in caregivers. Our aim was to assess the self-perceived stress, that is, how and how much the stressor affects the individual, through endocrine, metabolic, and immunologic biomarkers levels in geriatric and oncologic informal caregivers.

An approach to an acute emotional stress reference scale.

Introduction: The clinical diagnosis aims to identify the degree of affectation of the psycho-physical state of the patient as a guide to therapeutic intervention. In stress, the lack of a measurement tool based on a reference makes it difficult to quantitatively assess this degree of affectation.

Aim: To define and perform a primary assessment of a standard reference in order to measure acute emotional stress from the markers identified as indicators of the degree.

Inclusion of Respiratory Frequency Information in Heart Rate Variability Analysis for Stress Assessment.

Respiratory rate and heart rate variability (HRV) are studied as stress markers in a database of young healthy volunteers subjected to acute emotional stress, induced by a modification of the Trier Social Stress Test. First, instantaneous frequency domain HRV parameters are computed using time-frequency analysis in the classical bands. Then, the respiratory rate is estimated and this information is included in HRV analysis in two ways: 1) redefining the high-frequency (HF) band to be centered at respiratory frequency; 2) excluding from the analysis those instants where respiratory frequency falls within the low-frequency (LF) band.

Towards an objective measurement of emotional stress: Preliminary analysis based on heart rate variability.

This paper presents a study performed in 25 young healthy subjects measuring the evolution of heart rate variability (HRV) indices during emotional stress. Acute emotional stress was generated with a modified version of Trier Social Stress Test (TSST). The TSST comprises several tasks which include a memory test, anticipation of stress, public exposition, and an arithmetic task.