Automated Security Assessment Framework for Wearable BLE-enabled Health Monitoring Devices

The growth of IoT technology, increasing prevalence of embedded devices, and advancements in biomedical technology have led to the emergence of numerous wearable health monitoring devices (WHMDs) in clinical settings and in the community. The majority of these devices are Bluetooth Low Energy (BLE) enabled. Though the advantages offered by BLE-enabled WHMDs in tracking, diagnosing, and intervening with patients are substantial, the risk of cyberattacks on these devices is likely to increase with device complexity and new communication protocols. Furthermore, vendors face risk and financial tradeoffs between speed to market and ensuring device security in all situations. Previous research has explored the security and privacy of such devices by manually testing popular BLE-enabled WHMDs in the market and generally discussed categories of possible attacks, while mostly focused on IP devices. In this work, we propose a new semi-automated framework that can be used to identify and discover both known and unknown vulnerabilities in WHMDs. To demonstrate its implementation, we validate it with a number of commercially available BLE-enabled enabled wearable devices. Our results show that the devices are vulnerable to a number of attacks, including eavesdropping, data manipulation, and denial of service attacks. The proposed framework could therefore be used to evaluate potential devices before adoption into a secure network or, ideally, during the design and implementation of new devices.

Rhythm and Music-Based Interventions in Motor Rehabilitation: Current Evidence and Future Perspectives

Research in basic and clinical neuroscience of music conducted over the past decades has begun to uncover music’s high potential as a tool for rehabilitation. Advances in our understanding of how music engages parallel brain networks underpinning sensory and motor processes, arousal, reward, and affective regulation, have laid a sound neuroscientific foundation for the development of theory-driven music interventions that have been systematically tested in clinical settings. Of particular significance in the context of motor rehabilitation is the notion that musical rhythms can entrain movement patterns in patients with movement-related disorders, serving as a continuous time reference that can help regulate movement timing and pace. To date, a significant number of clinical and experimental studies have tested the application of rhythm- and music-based interventions to improve motor functions following central nervous injury and/or degeneration. The goal of this review is to appraise the current state of knowledge on the effectiveness of music and rhythm to modulate movement spatiotemporal patterns and restore motor function. By organizing and providing a critical appraisal of a large body of research, we hope to provide a revised framework for future research on the effectiveness of rhythm- and music-based interventions to restore and (re)train motor function.

Microfluidic Approaches and Methods Enabling Extracellular Vesicle Isolation for Cancer Diagnostics

Advances in cancer research over the past half-century have clearly determined the molecular origins of the disease. Central to the use of molecular signatures for continued progress, including rapid, reliable, and early diagnosis is the use of biomarkers. Specifically, extracellular vesicles as biomarker cargo holders have generated significant interest. However, the isolation, purification, and subsequent analysis of these extracellular vesicles remain a challenge. Technological advances driven by microfluidics-enabled devices have made the challenges for isolation of extracellular vesicles an emerging area of research with significant possibilities for use in clinical settings enabling point-of-care diagnostics for cancer. In this article, we present a tutorial review of the existing microfluidic technologies for cancer diagnostics with a focus on extracellular vesicle isolation methods.

Shared decision-making and the lessons learned about decision regret in cancer patients

The commentary presents reflections on the literature on post-treatment cancer patient regret. Even though a lot of effort has been made to increase patient satisfaction by engaging them in medical decisions, patient regret remains present in clinical settings. In our commentary, we identify three main aspects of shared decision-making that previously have been shown to predict patient regret. Based on these findings, we provide recommendations for physicians involved in the shared decision-making process. In addition, we make methodological suggestions for future research in the field.

Comparison of delirium detection tools in acute care

Background Delirium is a frequent psychopathological syndrome in geriatric patients. It is sometimes the only symptom of acute illness and bears a high risk for complications. Therefore, feasible assessments are needed for delirium detection. Objective and methods Rapid review of available delirium assessments based on a current Medline search and cross-reference check with a special focus on those implemented in acute care hospital settings. Results A total of 75 delirium detection tools were identified. Many focused on inattention as well as acute onset and/or fluctuating course of cognitive changes as key features for delirium. A range of assessments are based on the confusion assessment method (CAM) that has been adapted for various clinical settings. The need for a collateral history, time resources and staff training are major challenges in delirium assessment. Latest tests address these through a two-step approach, such as the ultrabrief (UB) CAM or by optional assessment of temporal aspects of cognitive changes (4 As test, 4AT). Most delirium screening assessments are validated for patient interviews, some are suitable for monitoring delirium symptoms over time or diagnosing delirium based on collateral history only. Conclusion Besides the CAM the 4AT has become well-established in acute care because of its good psychometric properties and practicability. There are several other instruments extending and improving the possibilities of delirium detection in different clinical settings.

An Individualized Algorithm to Predict Mortality in COVID-19 Pneumonia: a Machine Learning Based Study

IntroductionIdentifying SARS-CoV-2 patients at higher risk of mortality is crucial in the management of a pandemic. Artificial intelligence techniques allow to analyze big amount of data to find hidden patterns. We aimed to develop and validate a mortality score at admission for COVID-19 based on high-level machine learning.Material and methodsWe conducted a retrospective cohort study on hospitalized adults COVID-19 patients between March and December 2020. The primary outcome was in-hospital mortality. A machine learning approach on vital parameters, laboratory values, and demographic features was applied to develop different models. Then, a feature importance analysis was performed to reduce the number of variables included in the model, to develop a risk score with good overall performance, that was finally evaluated in terms of discrimination and calibration capabilities. All results underwent cross-validation.Results1,135 consecutive patients (median age 70 years, 64% males) were enrolled, 48 patients were excluded, the cohort was randomly divided in training (760) and test (327). During hospitalization, 251 (22%) patients died. After feature selection, the best performing classifier was random forest (AUC 0.88±0.03). Based on the relative importance of each variable, a pragmatic score was developed, showing good performances (AUC 0.85, ±0.025), and three levels were defined that correlated well with in-hospital mortality.ConclusionsMachine learning techniques were applied in order to develop an accurate in-hospital mortality risk score for COVID-19 based on ten variables. The application of the proposed score has utility in clinical settings to guide the management and prognostication of COVID-19 patients.

[18F]DCFPyL PET/CT for Imaging of Prostate Cancer

Prostate-specific membrane antigen (PSMA)-directed positron emission tomography (PET) has gained increasing interest for imaging of men affected by prostate cancer (PC). In recent years, 68Ga-labeled PSMA compounds have been widely utilized, although there is a trend towards increased utilization of 18F-labeled agents. Among others, [18F]DCFPyL (piflufolastat F 18, PYLARIFY) has been tested in multiple major trials, such as OSPREY and CONDOR, which provided robust evidence on the clinical utility of this compound for staging, restaging, and change in management. Recent explorative prospective trials have also utilized [18F]DCFPyL PET/CT for response assessment, e.g., in patients under abiraterone or enzalutamide, rendering this 18F-labeled PSMA radiotracer as an attractive biomarker for image-guided strategies in men with PC. After recent approval by the U.S. Food and Drug Administration, one may expect more widespread use, not only in the U.S., but also in Europe in the long term. In the present review, we will provide an overview of the current clinical utility of [18F]DCFPyL in various clinical settings for men with PC.

Application of 3D printing and its various technologies in dentistry

Many applications for these technologies have been reported in multiple fields, including dentistry, within the last three decades. It can be used in periodontology, endodontics, orthodontics, oral implantology, maxillofacial and oral surgery, and prosthodontics. In the present literature review, we have discussed the different clinical applications of various 3D printing technologies in dentistry. Evidence indicates that 3D printing approaches are usually associated with favorable outcomes based on the continuous development and production of novel approaches, enabling clinicians to develop complex equipment in different clinical and surgical aspects. Developing work models to facilitate diagnostic and surgical settings is the commonest application of these modalities in dentistry. Besides, they can also be used to manufacture various implantable devices. Accordingly, they significantly help enhance the treatment process, reducing costs and less invasive procedures with favorable outcomes. Finally, 3D printing technologies can design complex devices in a facilitated and more accurate way than conventional methods. Therefore, 3D printing should be encouraged in clinical settings for its various advantages over conventional maneuvers.

The Pulmonary Artery Catheter in the Perioperative Setting: Should It Still Be Used?

The pulmonary artery catheter (PAC) was introduced into clinical practice in the 1970s and was initially used to monitor patients with acute myocardial infarctions. The indications for using the PAC quickly expanded to critically ill patients in the intensive care unit as well as in the perioperative setting in patients undergoing major cardiac and noncardiac surgery. The utilization of the PAC is surrounded by multiple controversies, with literature claiming its benefits in the perioperative setting, and other publications showing no benefit. The right interpretation of the hemodynamic parameters measured by the PAC and its clinical implications are of the utmost essence in order to guide a specific therapy. Even though clinical trials have not shown a reduction in mortality with the use of the PAC, it still remains a valuable tool in a wide variety of clinical settings. In general, the right selection of the patient population (high-risk patients with or without hemodynamic instability undergoing high-risk procedures) as well as the right clinical setting (centers with experience and expertise) are essential in order for the patient to benefit most from PAC use.

Genomic and Phenotypic Characterization of Experimentally Selected Resistant Leishmania donovani Reveals a Role for Dynamin-1-Like Protein in the Mechanism of Resistance to a Novel Antileishmanial Compound

Humans and their pathogens are continuously locked in a molecular arms race during which the eventual emergence of pathogen drug resistance (DR) seems inevitable. For neglected tropical diseases (NTDs), DR is generally studied retrospectively once it has already been established in clinical settings.