Self-reported bruxism in patients with post-traumatic stress disorder.

OBJECTIVE: The present study aimed to investigate the association between self-reported awake/sleep bruxism, and orofacial pain with post-traumatic stress disorder (PTSD). METHODS: A case-control study with a convenience sample was designed. Participants were recruited from a university-based Trauma Ambulatory. The diagnosis of PTSD was established through a clinical interview and the Structured Clinical Interview (SCID-I/P). Thirty-eight PTSD patients and 38 controls completed the Research Diagnostic Criteria for Temporomandibular Disorders Axis-II to categorize awake/sleep bruxism and orofacial pain. Following this, we performed a short clinical examination of the temporomandibular joint and extraoral muscles. RESULTS: Adjusted logistic regression analysis showed that awake bruxism was associated with PTSD (OR = 3.38, 95% CI = 1.01-11.27, p = 0.047). Sleep bruxism was not associated with any covariate included in the model. In a Poisson regression model, PTSD (IRR = 3.01, 95% CI = 1.38-6.55, p = 0.005) and the muscle pain/discomfort (IRR = 5.12, 95% CI = 2.80-9.36, p < 0.001) were significant predictors for current orofacial pain. CONCLUSIONS: PTSD was associated with self-reported awake bruxism and low-intensity orofacial pain. These conditions were frequent outcomes in patients previously exposed to traumatic events. CLINICAL RELEVANCE: We suggest including a two-question screening for bruxism in psychiatry/psychology interviews to improve under-identification and to prevent harmful consequences at the orofacial level.

Traumatic memory retrieval followed by electroconvulsive therapy as a treatment for posttraumatic stress disorder: A pilot study.

Delivering electroconvulsive therapy (ECT) during the reconsolidation of traumatic memories may enhance the treatment efficacy in posttraumatic stress disorder (PTSD). To test this, 14 patients with severe and refractory PTSD were randomly allocated to receive ECT sessions either after retrieving the traumatic (n=8) or a neutral (n=6) memory. We found that delivering ECT after retrieving the traumatic memory enhanced the improvement of PTSD symptoms and the reduction of subjective reactivity to the traumatic memory. Reduction in anxiety and mood symptoms and physiological reactivity to the traumatic memory were observed in the sample as a whole regardless of memory retrieval.

Improvement of individual learning with mentoring programs for first-year undergraduate students.

Introduction: This study presents a brief analysis of Spanish universities that promote mentoring programs with students. These mentoring programs are divided into different categories depending on the persons (faculty or students) involved in the process and their characteristics (for novice, senior, or international students). The case of the Universidad Francisco de Vitoria is presented, where first-year students from all undergraduate degrees are involved in an annual course where the core part is related to formal mentoring activities. Methods: This study analyzes undergraduate degree students' outcomes and results from 10 different degrees for a period of 4 academic years (from 2016-2017 to 2019-2020). This first analysis corresponds to students' activities and marks awarded on the assessment of the assigned mentoring tasks related to the competencies of critical thinking, proactivity, personal knowledge (with the objective of acceptance and improvement), and the ability to ask transcendental questions. Then, a reliable and valid survey, conducted every year to all senior students, was used to get feedback from students. Results: After a quantitative and qualitative analysis of students' results, it was noticed that they become more confident in their studies when they engage in mentoring-based courses and sessions, and this benefits their lives. All this information led to the improvement of the mentoring process.

Network QoS Impact on Spatial Perception through Sensory Substitution in Navigation Systems for Blind and Visually Impaired People.

A navigation system for individuals suffering from blindness or visual impairment provides information useful to reach a destination. Although there are different approaches, traditional designs are evolving into distributed systems with low-cost, front-end devices. These devices act as a medium between the user and the environment, encoding the information gathered on the surroundings according to theories on human perceptual and cognitive processes. Ultimately, they are rooted in sensorimotor coupling. The present work searches for temporal constraints due to such human-machine interfaces, which in turn constitute a key design factor for networked solutions. To that end, three tests were conveyed to a group of 25 participants under different delay conditions between motor actions and triggered stimuli. The results show a trade-off between spatial information acquisition and delay degradation, and a learning curve even under impaired sensorimotor coupling.

Wireless EEG: A survey of systems and studies.

The popular brain monitoring method of electroencephalography (EEG) has seen a surge in commercial attention in recent years, focusing mostly on hardware miniaturization. This has led to a varied landscape of portable EEG devices with wireless capability, allowing them to be used by relatively unconstrained users in real-life conditions outside of the laboratory. The wide availability and relative affordability of these devices provide a low entry threshold for newcomers to the field of EEG research. The large device variety and the at times opaque communication from their manufacturers, however, can make it difficult to obtain an overview of this hardware landscape. Similarly, given the breadth of existing (wireless) EEG knowledge and research, it can be challenging to get started with novel ideas. Therefore, this paper first provides a list of 48 wireless EEG devices along with a number of important-sometimes difficult-to-obtain-features and characteristics to enable their side-by-side comparison, along with a brief introduction to each of these aspects and how they may influence one's decision. Secondly, we have surveyed previous literature and focused on 110 high-impact journal publications making use of wireless EEG, which we categorized by application and analyzed for device used, number of channels, sample size, and participant mobility. Together, these provide a basis for informed decision making with respect to hardware and experimental precedents when considering new, wireless EEG devices and research. At the same time, this paper provides background material and commentary about pitfalls and caveats regarding this increasingly accessible line of research.

Analysis of Simple Algorithms for Motion Detection in Wearable Devices.

Brain Computer Interfaces are used to obtain relevant information from the electroencephalogram (EEG) with a concrete objective. The evoked potentials related to movement are much demanded nowadays, in particular the ones associated to imagery movement. The objective of this work is to develop simple algorithms to imagery motion detection that can be included in a non-invasive wearable that everybody can use in a comfortable way for new services and applications. A wearable implies low resources, which is the most important requirement that the algorithms have. A public database with 105 subjects doing an upper-limb imagery movement is used. We have developed two algorithms (FBA and BLA) based on three characteristics of the signal (correlation, wavelet energy per segment and wavelet energy per electrode). They are tested for different number of electrodes and frequency bands. The best performance is found for 6 electrodes. The beta band is not the only band who achieves good performances. In fact, in this study the range between 25 Hz - 30 Hz has obtained the best performance using 6 electrodes. The conclusions show that these simple algorithms not fit well with the wearable requirements. However, it shows the need of adaptive algorithms to bypass the differences between subjects. Also, it affirms that more electrodes not lead to a better information, as well as, less electrodes not lead to a worse information. The same goes for frequency, where not only the beta band have the information required that fits our needs.

VES: A Mixed-Reality Development Platform of Navigation Systems for Blind and Visually Impaired.

Herein, we describe the Virtually Enhanced Senses (VES) system, a novel and highly configurable wireless sensor-actuator network conceived as a development and test-bench platform of navigation systems adapted for blind and visually impaired people. It allows to immerse its users into "walkable" purely virtual or mixed environments with simulated sensors and validate navigation system designs prior to prototype development. The haptic, acoustic, and proprioceptive feedback supports state-of-art sensory substitution devices (SSD). In this regard, three SSD were integrated in VES as examples, including the well-known "The vOICe". Additionally, the data throughput, latency and packet loss of the wireless communication can be controlled to observe its impact in the provided spatial knowledge and resulting mobility and orientation performance. Finally, the system has been validated by testing a combination of two previous visual-acoustic and visual-haptic sensory substitution schemas with 23 normal-sighted subjects. The recorded data includes the output of a "gaze-tracking" utility adapted for SSD.

Methods for Lowering the Power Consumption of OS-Based Adaptive Deep Brain Stimulation Controllers.

The identification of a new generation of adaptive strategies for deep brain stimulation (DBS) will require the development of mixed hardware-software systems for testing and implementing such controllers clinically. Towards this aim, introducing an operating system (OS) that provides high-level features (multitasking, hardware abstraction, and dynamic operation) as the core element of adaptive deep brain stimulation (aDBS) controllers could expand the capabilities and development speed of new control strategies. However, such software frameworks also introduce substantial power consumption overhead that could render this solution unfeasible for implantable devices. To address this, in this work four techniques to reduce this overhead are proposed and evaluated: a tick-less idle operation mode, reduced and dynamic sampling, buffered read mode, and duty cycling. A dual threshold adaptive deep brain stimulation algorithm for suppressing pathological oscillatory neural activity was implemented along with the proposed energy saving techniques on an energy-efficient OS, YetiOS, running on a STM32L476RE microcontroller. The system was then tested using an emulation environment coupled to a mean field model of the parkinsonian basal ganglia to simulate local field potential (LFPs) which acted as a biomarker for the controller. The OS-based controller alone introduced a power consumption overhead of 10.03 mW for a sampling rate of 1 kHz. This was reduced to 12 µW by applying the proposed tick-less idle mode, dynamic sampling, buffered read and duty cycling techniques. The OS-based controller using the proposed methods can facilitate rapid and flexible testing and implementation of new control methods. Furthermore, the approach has the potential to become a central element in future implantable devices to enable energy-efficient implementation of a wide range of control algorithms across different neurological conditions and hardware platforms.

Adaptive Body Area Networks Using Kinematics and Biosignals.

The increasing penetration of wearable and implantable devices necessitates energy-efficient and robust ways of connecting them to each other and to the cloud. However, the wireless channel around the human body poses unique challenges such as a high and variable path-loss caused by frequent changes in the relative node positions as well as the surrounding environment. An adaptive wireless body area network (WBAN) scheme is presented that reconfigures the network by learning from body kinematics and biosignals. It has very low overhead since these signals are already captured by the WBAN sensor nodes to support their basic functionality. Periodic channel fluctuations in activities like walking can be exploited by reusing accelerometer data and scheduling packet transmissions at optimal times. Network states can be predicted based on changes in observed biosignals to reconfigure the network parameters in real time. A realistic body channel emulator that evaluates the path-loss for everyday human activities was developed to assess the efficacy of the proposed techniques. Simulation results show up to 41% improvement in packet delivery ratio (PDR) and up to 27% reduction in power consumption by intelligent scheduling at lower transmission power levels. Moreover, experimental results on a custom test-bed demonstrate an average PDR increase of 20% and 18% when using our adaptive EMG- and heart-rate-based transmission power control methods, respectively. The channel emulator and simulation code is made publicly available at https://github.com/a-moin/wban-pathloss.

A randomized clinical trial to assess the efficacy of trial-based cognitive therapy compared to prolonged exposure for post-traumatic stress disorder: preliminary findings.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a prevalent mental health condition that is often associated with psychiatric comorbidities and changes in quality of life. Prolonged exposure therapy (PE) is considered the gold standard psychological treatment for PTSD, but treatment resistance and relapse rates are high. Trial-based cognitive therapy (TBCT) is an effective treatment for depression and social anxiety disorder, and its structure seems particularly promising for PTSD. Therefore, we evaluated the efficacy of TBCT compared to PE in patients with PTSD. METHODS: Ninety-five patients (77.6% females) who met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision, criteria for PTSD were randomly assigned to receive either TBCT (n = 44) or PE (n = 51). Patients were evaluated before and after treatment, and at follow-up 3 months after treatment. The primary outcome was improvement in PTSD symptoms as assessed by the Davidson Trauma Scale (DTS). Secondary outcomes were depression, anxiety, and dysfunctional attitudes assessed by the Beck Depression/Anxiety Inventories and Dysfunctional Attitudes Scale, as well as the dropout rate. RESULTS: A significant reduction in DTS scores was observed in both arms, but no significant difference between treatments. Regarding the secondary outcomes, we found significant differences in depressive symptoms in favor of TBCT, and the dropout rate was lower in the TBCT group than the PE group. CONCLUSION: Our preliminary results suggest that TBCT may be an effective alternative for treating PTSD. Further research is needed to better understand its role and the mechanisms of change in the treatment of this disorder.

Targeting the reconsolidation of traumatic memories with a brief 2-session imaginal exposure intervention in post-traumatic stress disorder.

BACKGROUND: Evidence suggests that extinction during memory reconsolidation diminishes the return of defensive responses. In order to translate these effects to the clinical setting, we tested whether retrieving a traumatic memory and delivering a brief two-sessions imaginal exposure intervention during its reconsolidation would produce stronger decreases in reactivity to these memories than standard imaginal exposure method. METHODS: Participants with Post-Traumatic Stress Disorder (PTSD) had either their traumatic (n = 21) or a neutral (n = 21) memory retrieved 1 h before an imaginal exposure session for two consecutive days. One day before and one day after, participants were exposed to script-driven imagery of their traumatic event, during which skin conductance responses were measured and, immediately after, subjective responses were assessed by means of Visual Analogue Scales. RESULTS: Traumatic retrieval improved the physiological, but not the subjective effects of imaginal exposure intervention on over-reactivity to traumatic memories. CONCLUSIONS: Our results suggest that delivering extinction-based treatments over the reconsolidation of traumatic memories may enhance its effects. These results suggest that this is a promising path toward the development of new therapeutic techniques.

Análise da produção científica brasileira sobre hanseníase identificada na base de dados web of science / Analysis of brazilian scientific production on leprosy identified on the web of science database

Este estudo analisou a bibliografia relacionada à hanseníase no Brasil, representada pela publicação de artigos científicos indexados na base de dados científica Web of Science, de 2000 a 2019. Por meio de análise bibliométrica, procurou-se delinear um panorama das produções científicas acerca do tema, identificando os autores, a evolução histórica do número de produções, as áreas de pesquisa que mais publicam, os tipos de artigos publicados e quais as agências financiadoras envolvidas nas publicações relacionadas ao tema. O corpus documental contou com 376 artigos completos, que demonstraram uma intensificação na produção de estudos sobre a hanseníase nos últimos anos, especialmente na área de Medicina Tropical, com predomínio de financiamento por agências brasileiras, e cuja maior fonte de publicações é uma revista científica internacional, dedicada ao estudo de doenças tropicais negligenciadas. Conclui-se que o interesse no estudo do tema se eleva com o passar dos anos, mas dentre as temáticas evidenciadas pela análise empreendida, as políticas públicas para controle e eliminação da doença, foram incipientes. Revela ainda a necessidade de maior aporte científico sobre a temática estimuladas por órgãos governamentais e que amplie as produções científicas por instituições de ensino e pesquisa, que possam alavancar reflexões direcionadas à implementação de diretrizes políticas efetivas para o controle e eliminação da doença.

This study analyzed the literature related to leprosy in Brazil, represented by the publication of scientific papers indexed in the Web of Science scientific database from 2000 to 2019. Through bibliometric analysis, the authors sought to delineate an overview of scientific productions on the topic, identifying the authors, the historical evolution of the number of productions, the areas of research that had most publications, the types of articles published and which funding agencies are involved in publications related to the topic. The documentary corpus consisted of 376 complete articles, which demonstrated an intensification in the production of studies on leprosy in recent years, especially in the area of Tropical Medicine, with a predominance of funding from Brazilian agencies, and whose largest source of publications is an international scientific journal dedicated to the study of neglected tropical diseases. It can be concluded that the interest in the study of the topic has increased over the years, but among the topics evidenced by the analysis undertaken, public policies for the control and elimination of the disease were incipient. It also reveals the need for greater scientific input on the topic stimulated by both government agencies and educational and research institutions, which can leverage reflections aimed at the implementation of effective political guidelines for the control and elimination of the disease.

MIGOU: A Low-Power Experimental Platform with Programmable Logic Resources and Software-Defined Radio Capabilities.

The increase in the number of mobile and Internet of Things (IoT) devices, along with the demands of new applications and services, represents an important challenge in terms of spectral coexistence. As a result, these devices are now expected to make an efficient and dynamic use of the spectrum, and to provide processed information instead of simple raw sensor measurements. These communication and processing requirements have direct implications on the architecture of the systems. In this work, we present MIGOU, a wireless experimental platform that has been designed to address these challenges from the perspective of resource-constrained devices, such as wireless sensor nodes or IoT end-devices. At the radio level, the platform can operate both as a software-defined radio and as a traditional highly integrated radio transceiver, which demands less node resources. For the processing tasks, it relies on a system-on-a-chip that integrates an ARM Cortex-M3 processor, and a flash-based FPGA fabric, where high-speed processing tasks can be offloaded. The power consumption of the platform has been measured in the different modes of operation. In addition, these hardware features and power measurements have been compared with those of other representative platforms. The results obtained confirm that a state-of-the-art tradeoff between hardware flexibility and energy efficiency has been achieved. These characteristics will allow for the development of appropriate solutions to current end-devices' challenges and to test them in real scenarios.

Experimental Evaluation of an RSSI-Based Localization Algorithm on IoT End-Devices.

In recent years, wireless sensor networks (WSNs) have experienced a significant growth as a fundamental part of the Internet of Things (IoT). WSNs nodes constitute part of the end-devices present in the IoT, and in many cases location data of these devices is expected by IoT applications. For this reason, many localization algorithms for WSNs have been developed in the last years, although in most cases the results provided are obtained from simulations that do not consider the resource constraints of the end-devices. Therefore, in this work we present an experimental evaluation of a received signal strength indicator (RSSI)-based localization algorithm implemented on IoT end-devices, comparing its results with those obtained from simulations. We have implemented the fuzzy ring-overlapping range-free (FRORF) algorithm with some modifications to make its operation feasible on resource-constrained devices. Multiple tests have been carried out to obtain the localization accuracy data in three different scenarios, showing the difference between simulation and real results. While the overall behaviour is similar in simulations and in real tests, important differences can be observed attending to quantitative accuracy results. In addition, the execution time of the algorithm running in the nodes has been evaluated. It ranges from less than 10 ms to more than 300 ms depending on the fuzzification level, which demonstrates the importance of evaluating localization algorithms in real nodes to prevent the introduction of large overheads that may not be affordable by resource-constrained nodes.

A Methodology for Choosing Time Synchronization Strategies for Wireless IoT Networks.

The wireless Internet of Things (IoT) family grows without interruption. Every day more applications and wireless devices are available to interconnect and help solve multiple problems in areas such as health, critical infrastructure, industry, etc. Many of the tasks to be performed by the IoT network require time synchronization for their correct operation, either to use the spectrum more efficiently, to add data from different sensors, or to carry out coordinated communications. Each of these applications has different requirements regarding time synchronization. This means that the decision of which strategy to follow to synchronize an IoT end device becomes a task that requires important prior analysis and usually, if developers are experts in the topic, ends with the implementation of an ad hoc solution. In this article, we present a methodology to choose an adequate time-synchronization strategy for any wireless IoT application. We also present a tool that executes the methodology, guiding the IoT application developer through some input forms. This combination of methodology and tool abstracts developers from the complexities of time-synchronization strategies, allowing them to choose the correct strategy regardless of their level of knowledge in wireless IoT time synchronization. As a result, the methodology offers a set of time-synchronization strategies that are adjusted to the needs of developers and applications.

Navigation Systems for the Blind and Visually Impaired: Past Work, Challenges, and Open Problems.

Over the last decades, the development of navigation devices capable of guiding the blind through indoor and/or outdoor scenarios has remained a challenge. In this context, this paper's objective is to provide an updated, holistic view of this research, in order to enable developers to exploit the different aspects of its multidisciplinary nature. To that end, previous solutions will be briefly described and analyzed from a historical perspective, from the first "Electronic Travel Aids" and early research on sensory substitution or indoor/outdoor positioning, to recent systems based on artificial vision. Thereafter, user-centered design fundamentals are addressed, including the main points of criticism of previous approaches. Finally, several technological achievements are highlighted as they could underpin future feasible designs. In line with this, smartphones and wearables with built-in cameras will then be indicated as potentially feasible options with which to support state-of-art computer vision solutions, thus allowing for both the positioning and monitoring of the user's surrounding area. These functionalities could then be further boosted by means of remote resources, leading to cloud computing schemas or even remote sensing via urban infrastructure.

Process Management in IoT Operating Systems: Cross-Influence between Processing and Communication Tasks in End-Devices.

The emergence and spread of Internet of Things (IoT) technologies along with the edge computing paradigm has led to an increase in the computational load on sensor end-devices. These devices are now expected to provide high-level information instead of just raw sensor measurements. Therefore, the processing tasks must share the processor time with the communication tasks, and both of them may have strict timing constraints. In this work, we present an empirical study, from the edge computing perspective, of the process management carried out by an IoT Operating System (OS), showing the cross-influence between the processing and communication tasks in end-devices. We have conducted multiple tests in two real scenarios with a specific OS and a set of wireless protocols. In these tests, we have varied the processing and communication tasks timing parameters, as well as their assigned priority levels. The results obtained from these tests demonstrate that there is a close relationship between the characteristics of the processing tasks and the communication performance, especially when the processing computational load is high. In addition, these results also show that the computational load is not the only factor responsible for the communication performance degradation, as the relationship between the processing tasks and the communication protocols timing parameters also plays a role. These conclusions should be taken into account for future OSs and protocol developments.

Edge and Fog Computing Platform for Data Fusion of Complex Heterogeneous Sensors.

The explosion of the Internet of Things has dramatically increased the data load on networks that cannot indefinitely increment their capacity to support these new services. Edge computing is a viable approach to fuse and process data on sensor platforms so that information can be created locally. However, the integration of complex heterogeneous sensors producing a great amount of diverse data opens new challenges to be faced. Rather than generating usable data straight away, complex sensors demand prior calculations to supply meaningful information. In addition, the integration of complex sensors in real applications requires a coordinated development from hardware and software teams that need a common framework to reduce development times. In this work, we present an edge and fog computing platform capable of providing seamless integration of complex sensors, with the implementation of an efficient data fusion strategy. It uses a symbiotic hardware/software design approach based on a novel messaging system running on a modular hardware platform. We have applied this platform to integrate Bluetooth vehicle identifiers and radar counters in a specific mobility use case, which exhibits an effective end-to-end integration using the proposed solution.

Impact of depression and/or anxiety on the presentation of cardiovascular events in a cohort with metabolic syndrome. StreX project: Five years of follow-up.

OBJECTIVES: To determine the role of anxiety and depression on the incidence of cardiovascular events (CVE) in a Catalonian population with metabolic syndrome (MetS) over a five-year follow-up according to the number/type of MetS criteria. METHODS: Prospective study to determine the incidence of CVE according to the presence of anxiety and depression disorders among individuals with different combinations of clinical traits of the MetS. SETTING: Primary Care, Catalonia (Spain). SUBJECTS: 35-75 years old fulfilling MetS criteria without CVE at the initiation of follow-up (2009). We studied 16 MetS phenotypes [NCEP-ATPIII criteria] based on the presence of depression/anxiety. The primary endpoint was the incidence of CVE at five years. RESULTS: We analyzed 401,743 people with MetS (17.2% of the population); 8.7% had depression, 16.0% anxiety and 3.8% both. 14.5% consumed antidepressants and 20.8% tranquilizers. At the 5-year follow-up, the incidence of CVE was 5.5%, being 6.4% in men and 4.4% in women. On comparing individuals with and without depression the incidence of CVE was 6.7% vs. 5.3%, respectively (p<0.01), being 5.5% in both groups in relation to anxiety. CONCLUSION: Depression and anxiety play a role in the poor prognosis of patients with MetS. In Catalonia, the two predominant MetS phenotypes do not include obesity as a criterion.

Impact of post-traumatic stress disorder on oral health.

BACKGROUND: The stress experienced as an intense and traumatic event can increase the odds of orofacial pain, affect the biomechanics of masticatory system and compromise the periodontal health. This study was conducted to investigate the impact of post-traumatic stress disorder (PTSD) on oral health. METHODS: A case-control study with a convenience sample was designed. Probing pocket depth (PPD), clinical attachment level (CAL), bleeding on probing, and plaque were recorded at 6 sites per tooth. A visual analog scale (VAS) was used to evaluate the pain after probing. The Research Diagnostic Criteria for Temporomandibular Disorders Axis II (RDC/TMD Axis II) and Structured Clinical Interview (DSM-IV) were also applied. The final sample comprised 38 PTSD patients and 38 controls. RESULTS: Patients with PTSD had a higher degree of chronic pain, more depression and nonspecific physical symptoms (including and excluding pain) compared with the control group (Fisher exact test p < 0.001, and Chi-squared test, p < 0.001, < 0.001, < 0.001, respectively). Patients with PTSD also had more pain after periodontal probing compared with controls (Mann-Whitney, p = 0.037). The prevalence of sites with CAL or PPD ≥ 4, ≥ 5, ≥ 6 were not different between the groups. Age was associated with moderate periodontitis (multivariable logistic regression model, OR = 3.33, 95% CI = 1.03-10.75, p = 0.04). LIMITATION: The severity of PTSD precluded an ample sample size. CONCLUSIONS: Patients with PTSD presented a worse RDC/TMD Axis II profile, more pain after periodontal probing, and no difference related to periodontal clinical parameters. More studies are needed to confirm these findings.