Dietary, socioeconomic, and maize handling practices associated with aflatoxin and fumonisin exposure among women tortilla makers in 5 departments in Guatemala.

Previous research has demonstrated human exposure to mycotoxins among Guatemalans, with high levels of mycotoxins being found in blood and urine samples as well as in maize for human consumption. Mishandling of crops such as maize during pre- and post-harvest has been associated with mycotoxin contamination. The overarching goal of this study was to identify risk factors for aflatoxin and fumonisin exposure in Guatemala. A cross-sectional survey of 141 women tortilla makers was conducted in the departments of Guatemala, Sololá, Suchitepéquez, Izabal, and Zacapa in February 2022. Maize and tortilla samples were collected and analyzed for aflatoxin B1 (AFB1) and fumonisin B1, B2, and B3 contamination (FB1, FB2, FB3). Urine samples were collected and analyzed for urinary FB1 (uFB1) contamination. A questionnaire was administered to collect data on sociodemographic characteristics, dietary intake of maize-based foods the week prior to the study, and maize handling practices. Descriptive statistics were used to describe common maize handling practices. A univariable analysis was conducted to identify predictors of low/high AFB1, total fumonisins, and uFB1. Multivariable logistic regression was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). During tortilla processing, a reduction in the AFB1 and total fumonisin levels was observed. The presence of AFB1 in maize was associated with department and mean total fumonisin level in maize (OR: 1.705, 95% CI: 1.113-2.613). The department where the tortilleria was located was significantly associated with the presence of fumonisins in tortillas. Increased consumption of Tortrix was significantly associated with the presence of FB1 in urine (OR: 1.652, 95% CI: 1.072-2.546). Results of this study can be used in the development and implementation of supply chain management practices that mitigate mycotoxin production, reduce food waste and economic loss, and promote food security.

Identifying and characterising sources of variability in digital outcome measures in Parkinson's disease.

Smartphones and wearables are widely recognised as the foundation for novel Digital Health Technologies (DHTs) for the clinical assessment of Parkinson's disease. Yet, only limited progress has been made towards their regulatory acceptability as effective drug development tools. A key barrier in achieving this goal relates to the influence of a wide range of sources of variability (SoVs) introduced by measurement processes incorporating DHTs, on their ability to detect relevant changes to PD. This paper introduces a conceptual framework to assist clinical research teams investigating a specific Concept of Interest within a particular Context of Use, to identify, characterise, and when possible, mitigate the influence of SoVs. We illustrate how this conceptual framework can be applied in practice through specific examples, including two data-driven case studies.

Dietary and socioeconomic risk factors for fumonisin exposure among women of reproductive age in 18 municipalities in Guatemala from 2013 to 2014.

Fumonisin exposure is common in populations where maize is a dietary staple, such as in Guatemala, and has been associated with negative health outcomes including neural tube defects. The objective of this study was to estimate fumonisin B1 (FB1) exposure among Guatemalan reproductive-age women and develop a better understanding of the dietary and sociodemographic risk factors for exposure. A cross-sectional study in 18 municipalities in Guatemala was conducted. Midwives and study nurses enrolled consenting women and collected individual and household demographic and socioeconomic data. A food frequency questionnaire was administered to estimate quantity and types of food products consumed. A urine sample was collected and urinary fumonisin B1 (uFB1) concentration was measured. A univariable analysis was conducted to identify predictors of low/high uFB1. Multivariable logistic regression was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). In total, 775 women had analyzable urine samples. Higher uFB1 levels were associated with speaking Mayan (OR = 2.33, 95% CI:1.44-3.77), less than high school education (OR = 1.61, 95% CI:1.12-2.30), increasing dietary proportion of maize-based foods (OR = 1.02, 95% CI:1.01-1.03), and consumption of tostadas (fried tortillas) (OR = 1.11, 95% CI:1.02-1.22). Lower uFB1 levels were associated with consumption of highly processed maize-based foods (OR = 0.93, 95% CI:0.87-0.99). Tortillas were the most frequently consumed maize-based food among study participants and significantly associated with high uFB1 exposure in the univariable but not multivariable analysis. Consumption of >4,750 grams/week of maize-based foods, >5,184 g/week of locally produced maize-based foods, and >110 servings/week of tortillas were also significantly associated with high uFB1 exposure in univariable analysis. Populations with low socioeconomic status/education levels and high consumption of maize-based foods had higher fumonisin exposure. Interventions aimed at reducing the risk of exposure to mycotoxins through maize in Guatemala, including the increased consumption of non-maize-based foods, should be further explored.

A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the Remote Early Detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: It is currently thought that most-but not all-individuals infected with SARS-CoV-2 develop symptoms, but the infectious period starts on average 2 days before the first overt symptoms appear. It is estimated that pre- and asymptomatic individuals are responsible for more than half of all transmissions. By detecting infected individuals before they have overt symptoms, wearable devices could potentially and significantly reduce the proportion of transmissions by pre-symptomatic individuals. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests [to determine if there are antibodies against the SARS-CoV-2 in the blood] or SARS-CoV-2 infection tests such as polymerase chain reaction [PCR] or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the following two algorithms to detect first time SARS-CoV-2 infection including early or asymptomatic infection: • The algorithm using Ava bracelet data when coupled with self-reported Daily Symptom Diary data (Wearable + Symptom Data Algo; experimental condition) • The algorithm using self-reported Daily Symptom Diary data alone (Symptom Only Algo; control condition) In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. TRIAL DESIGN: The trial is a randomized, single-blinded, two-period, two-sequence crossover trial. The study will start with an initial learning phase (maximum of 3 months), followed by period 1 (3 months) and period 2 (3 months). Subjects entering the study at the end of the recruitment period may directly start with period 1 and will not be part of the learning phase. Each subject will undergo the experimental condition (the Wearable + Symptom Data Algo) in either period 1 or period 2 and the control condition (Symptom Only Algo) in the other period. The order will be randomly assigned, resulting in subjects being allocated 1:1 to either sequence 1 (experimental condition first) or sequence 2 (control condition first). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. PARTICIPANTS: The trial will be conducted in the Netherlands. A target of 20,000 subjects will be enrolled. Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. This results in approximately 6500 normal-risk individuals and 3500 high-risk individuals per sequence. Subjects will be recruited from previously studied cohorts as well as via public campaigns and social media. All data for this study will be collected remotely through the Ava COVID-RED app, the Ava bracelet, surveys in the COVID-RED web portal and self-sampling serology and PCR kits. More information on the study can be found in www.covid-red.eu . During recruitment, subjects will be invited to visit the COVID-RED web portal. After successfully completing the enrolment questionnaire, meeting eligibility criteria and indicating interest in joining the study, subjects will receive the subject information sheet and informed consent form. Subjects can enrol in COVID-RED if they comply with the following inclusion and exclusion criteria: Inclusion criteria: • Resident of the Netherlands • At least 18 years old • Informed consent provided (electronic) • Willing to adhere to the study procedures described in the protocol • Must have a smartphone that runs at least Android 8.0 or iOS 13.0 operating systems and is active for the duration of the study (in the case of a change of mobile number, the study team should be notified) • Be able to read, understand and write Dutch Exclusion criteria: • Previous positive SARS-CoV-2 test result (confirmed either through PCR/antigen or antibody tests; self-reported) • Current suspected (e.g. waiting for test result) COVID-19 infection or symptoms of a COVID-19 infection (self-reported) • Participating in any other COVID-19 clinical drug, vaccine or medical device trial (self-reported) • Electronic implanted device (such as a pacemaker; self-reported) • Pregnant at the time of informed consent (self-reported) • Suffering from cholinergic urticaria (per the Ava bracelet's user manual; self-reported) • Staff involved in the management or conduct of this study INTERVENTION AND COMPARATOR: All subjects will be instructed to complete the Daily Symptom Diary in the Ava COVID-RED app daily, wear their Ava bracelet each night and synchronize it with the app each day for the entire period of study participation. Provided with wearable sensor and/or self-reported symptom data within the last 24 h, the Ava COVID-RED app's underlying algorithms will provide subjects with a real-time indicator of their overall health and well-being. Subjects will see one of three messages, notifying them that no seeming deviations in symptoms and/or physiological parameters have been detected; some changes in symptoms and/or physiological parameters have been detected and they should self-isolate; or alerting them that deviations in their symptoms and/or physiological parameters could be suggestive of a potential COVID-19 infection and to seek additional testing. We will assess the intraperson performance of the algorithms in the experimental condition (Wearable + Symptom Data Algo) and control conditions (Symptom Only Algo). Note that both algorithms will also instruct to seek testing when any SARS-CoV-2 symptoms are reported in line with those defined by the Dutch national institute for public health and the environment 'Rijksinstituut voor Volksgezondheid en Milieu' (RIVM) guidelines. MAIN OUTCOMES: The trial will evaluate the use and performance of the Ava COVID-RED app and Ava bracelet, which uses sensors to measure breathing rate, pulse rate, skin temperature and heart rate variability for the purpose of early and asymptomatic detection and monitoring of SARS-CoV-2 in general and high-risk populations. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests, PCR tests and/or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for each of the following two algorithms to detect first-time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava bracelet data when coupled with the self-reported Daily Symptom Diary data and the algorithm using self-reported Daily Symptom Diary data alone. In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. The protocol contains an additional twenty secondary and exploratory objectives which address, among others, infection incidence rates, health resource utilization, symptoms reported by SARS-CoV-2-infected participants and the rate of breakthrough and asymptomatic SARS-CoV-2 infections among individuals vaccinated against COVID-19. PCR or antigen testing will occur when the subject receives a notification from the algorithm to seek additional testing. Subjects will be advised to get tested via the national testing programme and report the testing result in the Ava COVID-RED app and a survey. If they cannot obtain a test via the national testing programme, they will receive a nasal swab self-sampling kit at home, and the sample will be tested by PCR in a trial-affiliated laboratory. In addition, all subjects will be asked to take a capillary blood sample at home at baseline (between month 0 and 3.5 months after the start of subject recruitment), at the end of the learning phase (month 3; note that this sampling moment is skipped if a subject entered the study at the end of the recruitment period), period 1 (month 6) and period 2 (month 9). These samples will be used for SARS-CoV-2-specific antibody testing in a trial-affiliated laboratory, differentiating between antibodies resulting from a natural infection and antibodies resulting from COVID-19 vaccination (as vaccination will gradually be rolled out during the trial period). Baseline samples will only be analysed if the sample collected at the end of the learning phase is positive, or if the subject entered the study at the end of the recruitment period, and samples collected at the end of period 1 will only be analysed if the sample collected at the end of period 2 is positive. When subjects obtain a positive PCR/antigen or serology test result during the study, they will continue to be in the study but will be moved into a so-called COVID-positive mode in the Ava COVID-RED app. This means that they will no longer receive recommendations from the algorithms but can still contribute and track symptom and bracelet data. The primary analysis of the main objective will be executed using the data collected in period 2 (months 6 through 9). Within this period, serology tests (before and after period 2) and PCR/antigen tests (taken based on recommendations by the algorithms) will be used to determine if a subject was infected with SARS-CoV-2 or not. Within this same time period, it will be determined if the algorithms gave any recommendations for testing. The agreement between these quantities will be used to evaluate the performance of the algorithms and how these compare between the study conditions. RANDOMIZATION: All eligible subjects will be randomized using a stratified block randomization approach with an allocation ratio of 1:1 to one of two sequences (experimental condition followed by control condition or control condition followed by experimental condition). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence, resulting in approximately equal numbers of high-risk and normal-risk individuals between the sequences. BLINDING (MASKING): In this study, subjects will be blinded to the study condition and randomization sequence. Relevant study staff and the device manufacturer will be aware of the assigned sequence. The subject will wear the Ava bracelet and complete the Daily Symptom Diary in the Ava COVID-RED app for the full duration of the study, and they will not know if the feedback they receive about their potential infection status will only be based on the data they entered in the Daily Symptom Diary within the Ava COVID-RED app or based on both the data from the Daily Symptom Diary and the Ava bracelet. NUMBERS TO BE RANDOMIZED (SAMPLE SIZE): A total of 20,000 subjects will be recruited and randomized 1:1 to either sequence 1 (experimental condition followed by control condition) or sequence 2 (control condition followed by experimental condition), taking into account their risk level. This results in approximately 6500 normal-risk and 3500 high-risk individuals per sequence. TRIAL STATUS: Protocol version: 3.0, dated May 3, 2021. Start of recruitment: February 19, 2021. End of recruitment: June 3, 2021. End of follow-up (estimated): November 2021 TRIAL REGISTRATION: The Netherlands Trial Register on the 18th of February, 2021 with number NL9320 ( https://www.trialregister.nl/trial/9320 ) FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this letter serves as a summary of the key elements of the full protocol.

A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the remote early detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: It is currently thought that most-but not all-individuals infected with SARS-CoV-2 develop symptoms, but that the infectious period starts on average two days before the first overt symptoms appear. It is estimated that pre- and asymptomatic individuals are responsible for more than half of all transmissions. By detecting infected individuals before they have overt symptoms, wearable devices could potentially and significantly reduce the proportion of transmissions by pre-symptomatic individuals. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests [to determine if there are antibodies against the SARS-CoV-2 in the blood] or SARS-CoV-2 infection tests such as polymerase chain reaction [PCR] or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the following two algorithms to detect first time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava bracelet data when coupled with self-reported Daily Symptom Diary data (Wearable + Symptom Data Algo; experimental condition) the algorithm using self-reported Daily Symptom Diary data alone (Symptom Only Algo; control condition) In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. TRIAL DESIGN: The trial is a randomized, single-blinded, two-period, two-sequence crossover trial. All subjects will participate in an initial Learning Phase (varying from 2 weeks to 3 months depending on enrolment date), followed by two contiguous 3-month test phases, Period 1 and Period 2. Each subject will undergo the experimental condition (the Wearable + Symptom Data Algo) in one of these periods and the control condition (Symptom Only Algo) in the other period. The order will be randomly assigned, resulting in subjects being allocated 1:1 to either Sequence 1 (experimental condition first) or Sequence 2 (control condition first). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. PARTICIPANTS: The trial will be conducted in the Netherlands. A target of 20,000 subjects will be enrolled. Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. This results in approximately 6,500 normal-risk individuals and 3,500 high-risk individuals per sequence. Subjects will be recruited from previously studied cohorts as well as via public campaigns and social media. All data for this study will be collected remotely through the Ava COVID-RED app, the Ava bracelet, surveys in the COVID-RED web portal, and self-sampling serology and PCR kits. During recruitment, subjects will be invited to visit the COVID-RED web portal ( www.covid-red.eu ). After successfully completing the enrolment questionnaire, meeting eligibility criteria and indicating interest in joining the study, subjects will receive the subject information sheet and informed consent form. Subjects can enrol in COVID-RED if they comply with the following inclusion and exclusion criteria. INCLUSION CRITERIA: Resident of the Netherlands At least 18 years old Informed consent provided (electronic) Willing to adhere to the study procedures described in the protocol Must have a smartphone that runs at least Android 8.0 or iOS 13.0 operating systems and is active for the duration of the study (in the case of a change of mobile number, study team should be notified) Be able to read, understand and write Dutch Exclusion criteria: Previous positive SARS-CoV-2 test result (confirmed either through PCR/antigen or antibody tests; self-reported) Previously received a vaccine developed specifically for COVID-19 or in possession of an appointment for vaccination in the near future (self-reported) Current suspected (e.g., waiting for test result) COVID-19 infection or symptoms of a COVID-19 infection (self-reported) Participating in any other COVID-19 clinical drug, vaccine, or medical device trial (self-reported) Electronic implanted device (such as a pacemaker; self-reported) Pregnant at time of informed consent (self-reported) Suffering from cholinergic urticaria (per the Ava bracelet's User Manual; self-reported) Staff involved in the management or conduct of this study INTERVENTION AND COMPARATOR: All subjects will be instructed to complete the Daily Symptom Diary in the Ava COVID-RED app daily, wear their Ava bracelet each night and synchronise it with the app each day for the entire period of study participation. Provided with wearable sensor and/or self-reported symptom data within the last 24 hours, the Ava COVID-RED app's underlying algorithms will provide subjects with a real-time indicator of their overall health and well-being. Subjects will see one of three messages, notifying them that: no seeming deviations in symptoms and/or physiological parameters have been detected; some changes in symptoms and/or physiological parameters have been detected and they should self-isolate; or alerting them that deviations in their symptoms and/or physiological parameters could be suggestive of a potential COVID-19 infection and to seek additional testing. We will assess intraperson performance of the algorithms in the experimental condition (Wearable + Symptom Data Algo) and control conditions (Symptom Only Algo). MAIN OUTCOMES: The trial will evaluate the use and performance of the Ava COVID-RED app and Ava bracelet, which uses sensors to measure breathing rate, pulse rate, skin temperature, and heart rate variability for the purpose of early and asymptomatic detection and monitoring of SARS-CoV-2 in general and high-risk populations. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests, PCR tests and/or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for each of the following two algorithms to detect first-time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava Bracelet data when coupled with the self-reported Daily Symptom Diary data, and the algorithm using self-reported Daily Symptom Diary data alone. In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. The protocol contains an additional seventeen secondary outcomes which address infection incidence rates, health resource utilization, symptoms reported by SARS-CoV-2 infected participants, and the rate of breakthrough and asymptomatic SARS-CoV-2 infections among individuals vaccinated against COVID-19. PCR or antigen testing will occur when the subject receives a notification from the algorithm to seek additional testing. Subjects will be advised to get tested via the national testing programme, and report the testing result in the Ava COVID-RED app and a survey. If they cannot obtain a test via the national testing programme, they will receive a nasal swab self-sampling kit at home, and the sample will be tested by PCR in a trial-affiliated laboratory. In addition, all subjects will be asked to take a capillary blood sample at home at baseline (Month 0), and at the end of the Learning Phase (Month 3), Period 1 (Month 6) and Period 2 (Month 9). These samples will be used for SARS-CoV-2-specific antibody testing in a trial-affiliated laboratory, differentiating between antibodies resulting from a natural infection and antibodies resulting from COVID-19 vaccination (as vaccination will gradually be rolled out during the trial period). Baseline samples will only be analysed if the sample collected at the end of the Learning Phase is positive, and samples collected at the end of Period 1 will only be analysed if the sample collected at the end of Period 2 is positive. When subjects obtain a positive PCR/antigen or serology test result during the study, they will continue to be in the study but will be moved into a so-called "COVID-positive" mode in the Ava COVID-RED app. This means that they will no longer receive recommendations from the algorithms but can still contribute and track symptom and bracelet data. The primary analysis of the main objective will be executed using data collected in Period 2 (Month 6 through 9). Within this period, serology tests (before and after Period 2) and PCR/antigen tests (taken based on recommendations by the algorithms) will be used to determine if a subject was infected with SARS-CoV-2 or not. Within this same time period, it will be determined if the algorithms gave any recommendations for testing. The agreement between these quantities will be used to evaluate the performance of the algorithms and how these compare between the study conditions. RANDOMISATION: All eligible subjects will be randomized using a stratified block randomization approach with an allocation ratio of 1:1 to one of two sequences (experimental condition followed by control condition or control condition followed by experimental condition). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence, resulting in equal numbers of high-risk and normal-risk individuals between the sequences. BLINDING (MASKING): In this study, subjects will be blinded as to study condition and randomization sequence. Relevant study staff and the device manufacturer will be aware of the assigned sequence. The subject will wear the Ava bracelet and complete the Daily Symptom Diary in the Ava COVID-RED app for the full duration of the study, and they will not know if the feedback they receive about their potential infection status will only be based on data they entered in the Daily Symptom Diary within the Ava COVID-RED app or based on both the data from the Daily Symptom Diary and the Ava bracelet. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): 20,000 subjects will be recruited and randomized 1:1 to either Sequence 1 (experimental condition followed by control condition) or Sequence 2 (control condition followed by experimental condition), taking into account their risk level. This results in approximately 6,500 normal-risk and 3,500 high-risk individuals per sequence. TRIAL STATUS: Protocol version: 1.2, dated January 22nd, 2021 Start of recruitment: February 22nd, 2021 End of recruitment (estimated): April 2021 End of follow-up (estimated): December 2021 TRIAL REGISTRATION: The trial has been registered at the Netherlands Trial Register on the 18th of February, 2021 with number NL9320 ( https://www.trialregister.nl/trial/9320 ) FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint.

To support the successful adoption of digital measures into internal decision making and evidence generation for medical product development, we present a unified lexicon to aid communication throughout this process, and highlight key concepts including the critical role of participant engagement in development of digital measures. We detail the steps of bringing a successful proof of concept to scale, focusing on key decisions in the development of a new digital measure: asking the right question, optimized approaches to evaluating new measures, and whether and how to pursue qualification or acceptance. Building on the V3 framework for establishing verification and analytical and clinical validation, we discuss strategic and practical considerations for collecting this evidence, illustrated with concrete examples of trailblazing digital measures in the field.

Food Safety Challenges in Refugee Camps: What Do We Know?

ABSTRACT: Refugee camps provide basic necessities such as food, water, shelter, and medical treatment for displaced persons. Unsanitary conditions in refugee camps due to overcrowding, poor sanitation systems, lack of clean water, and minimal ways to cook and store food can lead to an increased risk of foodborne illness. This article reviews the limited literature on the epidemiology of foodborne illness in refugee camps, effective risk mitigation strategies, and opportunities for future research. Eleven relevant articles were identified, suggesting that research in this area is limited. Identified research focused on three pathogens-Vibrio cholerae, Salmonella, and hepatitis E virus-that can cause serious diseases such as cholera, salmonellosis, typhoid fever, and hepatitis E. Storage and handling of clean water for personal hygiene and food preparation were critical components for ensuring food safety. Knowledge pertaining to best practices for hygiene and food preparation also were identified as important. Gaps in current research include determination of the prevalence of pathogens in food sold in refugee camps and development of culturally relevant food safety supply chain quality management systems. More research that focuses on burden and attribution of foodborne illness and food safety interventions in refugee camps is necessary.

Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs).

Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science.

Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease. This poses a major challenge for the development of new therapies and is compounded by the considerable heterogeneity in clinical manifestations across patients and the fluctuating nature of many signs and symptoms of PD. Digital health technologies (DHT), such as smartphone applications, wearable sensors, and digital diaries, have the potential to address many of these gaps by enabling the objective, remote, and frequent measurement of PD signs and symptoms in natural living environments. The current climate of the COVID-19 pandemic creates a heightened sense of urgency for effective implementation of such strategies. In order for these technologies to be adopted in drug development studies, a regulatory-aligned consensus on best practices in implementing appropriate technologies, including the collection, processing, and interpretation of digital sensor data, is required. A growing number of collaborative initiatives are being launched to identify effective ways to advance the use of DHT in PD clinical trials. The Critical Path for Parkinson's Consortium of the Critical Path Institute is highlighted as a case example where stakeholders collectively engaged regulatory agencies on the effective use of DHT in PD clinical trials. Global regulatory agencies, including the US Food and Drug Administration and the European Medicines Agency, are encouraging the efficiencies of data-driven engagements through multistakeholder consortia. To this end, we review how the advancement of DHT can be most effectively achieved by aligning knowledge, expertise, and data sharing in ways that maximize efficiencies.

Enabling Stroke Rehabilitation in Home and Community Settings: A Wearable Sensor-Based Approach for Upper-Limb Motor Training.

High-dosage motor practice can significantly contribute to achieving functional recovery after a stroke. Performing rehabilitation exercises at home and using, or attempting to use, the stroke-affected upper limb during Activities of Daily Living (ADL) are effective ways to achieve high-dosage motor practice in stroke survivors. This paper presents a novel technological approach that enables 1) detecting goal-directed upper limb movements during the performance of ADL, so that timely feedback can be provided to encourage the use of the affected limb, and 2) assessing the quality of motor performance during in-home rehabilitation exercises so that appropriate feedback can be generated to promote high-quality exercise. The results herein presented show that it is possible to detect 1) goal-directed movements during the performance of ADL with a [Formula: see text]-statistic of 87.0% and 2) poorly performed movements in selected rehabilitation exercises with an [Formula: see text]-score of 84.3%, thus enabling the generation of appropriate feedback. In a survey to gather preliminary data concerning the clinical adequacy of the proposed approach, 91.7% of occupational therapists demonstrated willingness to use it in their practice, and 88.2% of stroke survivors indicated that they would use it if recommended by their therapist.

Telehealth monitor to measure physical activity and pressure relief maneuver performance in wheelchair users.

This study demonstrated the feasibility of a device for monitoring pressure relief maneuvers and physical activity for wheelchair users. The device counts the number of wheel pushes based on wheelchair acceleration and measures pressure relief maneuvers using a seat sensor consisting of three force sensing resistors (FSRs). To establish the feasibility of the seat sensor for the detection of pressure relief maneuvers, 10 wheelchair users and 10 non-disabled controls completed a series of wheelchair depression raises, forward trunk leans, and lateral trunk leans. The seat sensor was placed underneath the user's seat cushion. To establish the feasibility of wheel push counting, 10 full-time wheelchair users navigated a flat 50-m outdoor track and a 100-m outdoor obstacle course during self-propulsion (e.g., wheel pushes) and during assisted-propulsion (e.g., no wheel pushes). Of the 240 performed pressure relief, 225 were properly classified by the seat sensor (accuracy: 94%, sensitivity: 96%, specificity: 80%). Sensitivity was highest for depression raises (98%) and lowest for front lean maneuvers (80%). The wheelchair activity monitor measured 2,112 pushes during the self-propulsion trials compared to 2,162 pushes measured with the instrumented push-rim (97.7%). During assisted-propulsion trials, there were 477 incorrectly identified pushes (8.0 per trial).

Wearable Sensors in Huntington Disease: A Pilot Study.

BACKGROUND: The Unified Huntington's Disease Rating Scale (UHDRS) is the principal means of assessing motor impairment in Huntington disease but is subjective and generally limited to in-clinic assessments. OBJECTIVE: To evaluate the feasibility and ability of wearable sensors to measure motor impairment in individuals with Huntington disease in the clinic and at home. METHODS: Participants with Huntington disease and controls were asked to wear five accelerometer-based sensors attached to the chest and each limb for standardized, in-clinic assessments and for one day at home. A second chest sensor was worn for six additional days at home. Gait measures were compared between controls, participants with Huntington disease, and participants with Huntington disease grouped by UHDRS total motor score using Cohen's d values. RESULTS: Fifteen individuals with Huntington disease and five controls completed the study. Sensor data were successfully captured from 18 of the 20 participants at home. In the clinic, the standard deviation of step time (time between consecutive steps) was increased in Huntington disease (p < 0.0001; Cohen's d = 2.61) compared to controls. At home with additional observations, significant differences were observed in seven additional gait measures. The gait of individuals with higher total motor scores (50 or more) differed significantly from those with lower total motor scores (below 50) on multiple measures at home. CONCLUSIONS: In this pilot study, the use of wearable sensors in clinic and at home was feasible and demonstrated gait differences between controls, participants with Huntington disease, and participants with Huntington disease grouped by motor impairment.

Modification of Knee Flexion Angle Has Patient-Specific Effects on Anterior Cruciate Ligament Injury Risk Factors During Jump Landing.

BACKGROUND: The incidence of anterior cruciate ligament (ACL) injuries may be decreased through the use of intervention programs that focus on increasing the knee flexion angle during jump landing, which decreases strain on the ACL. PURPOSE: To investigate whether intervention training designed to change the knee flexion angle during landing causes secondary changes in other known measures associated with the risk of ACL injuries and to examine the time points when these secondary measures change. STUDY DESIGN: Controlled laboratory study. METHODS: A total of 39 healthy recreational athletes performed a volleyball block jump task in an instrumented gait laboratory. The participants first completed the jumps without any modification to their normal landing technique. They were then given oral instruction to land softly and to increase their knee flexion angle during landing. Lower body kinematics and kinetics were measured before and after the modification using an optoelectronic motion capture system. RESULTS: The knee flexion angle after the modification significantly increased from 11.2° to 15.2° at initial contact and from 67.8° to 100.7° at maximum flexion, and the time between initial contact and maximum flexion increased from 177.4 to 399.4 milliseconds. The flexion modification produced a substantial reduction in vertical ground-reaction force (243.1 to 187.8 %BW) with a concomitant reduction in the maximum flexion moment. Interestingly, the flexion modification only affected the abduction angle and abduction moment for the group of participants that landed in an initial adducted position before the modification and had no significant effect on the group that landed in an abducted position. CONCLUSION: Increasing the knee flexion angle during jump landing may be an effective intervention to improve knee biomechanical risk factors associated with an ACL injury. However, the fact that the flexion modification only influenced critical risk factors (the abduction angle and abduction moment) in participants who initially landed in an adducted position suggests that the selection of interventions to prevent ACL injuries should account for patient-specific characteristics. CLINICAL RELEVANCE: The study helps elucidate how increasing the knee flexion angle affects lower body biomechanics and provided evidence for the need to introduce patient-specific strategies for preventing ACL injuries.

Electrothermal Vaporization Sample Introduction for Spaceflight Water Quality Monitoring via Gas Chromatography-Differential Mobility Spectrometry.

In the history of manned spaceflight, environmental monitoring has relied heavily on archival sampling. However, with the construction of the International Space Station (ISS) and the subsequent extension in mission duration up to one year, an enhanced, real-time method for environmental monitoring is necessary. The station air is currently monitored for trace volatile organic compounds (VOCs) using gas chromatography-differential mobility spectrometry (GC-DMS) via the Air Quality Monitor (AQM), while water is analyzed to measure total organic carbon and biocide concentrations using the Total Organic Carbon Analyzer (TOCA) and the Colorimetric Water Quality Monitoring Kit (CWQMK), respectively. As mission scenarios extend beyond low Earth orbit, a convergence in analytical instrumentation to analyze both air and water samples is highly desirable. Since the AQM currently provides quantitative, compound-specific information for air samples and many of the targets in air are also common to water, this platform is a logical starting point for developing a multimatrix monitor. Here, we report on the interfacing of an electrothermal vaporization (ETV) sample introduction unit with a ground-based AQM for monitoring target analytes in water. The results show that each of the compounds tested from water have similar GC-DMS parameters as the compounds tested in air. Moreover, the ETV enabled AQM detection of dimethlsilanediol (DMSD), a compound whose analysis had proven challenging using other sample introduction methods. Analysis of authentic ISS water samples using the ETV-AQM showed that DMSD could be successfully quantified, while the concentrations obtained for the other compounds also agreed well with laboratory results.

Optimization of the anterior cruciate ligament injury prevention paradigm: novel feedback techniques to enhance motor learning and reduce injury risk.

SYNOPSIS: Primary anterior cruciate ligament (ACL) injury prevention programs effectively reduce ACL injury risk in the short term. Despite these programs, ACL injury incidence is still high, making it imperative to continue to improve current prevention strategies. A potential limitation of current ACL injury prevention training may be a deficit in the transfer of conscious, optimal movement strategies rehearsed during training sessions to automatic movements required for athletic activities and unanticipated events on the field. Instructional strategies with an internal focus of attention have traditionally been utilized, but may not be optimal for the acquisition of the control of complex motor skills required for sports. Conversely, external-focus instructional strategies may enhance skill acquisition more efficiently and increase the transfer of improved motor skills to sports activities. The current article will present insights gained from the motor-learning domain that may enhance neuromuscular training programs via improved skill development and increased retention and transfer to sports activities, which may reduce ACL injury incidence in the long term.

Synthesis of a quantum nanocrystal-gold nanoshell complex for near-infrared generated fluorescence and photothermal decay of luminescence.

Multifunction nanoparticle complexes have previously been developed to aid physicians in both diagnosis and treatment of cancerous tissue. Here, we designed a nanoparticle complex structure that consists of a plasmonically active hollow gold nanoshell core surrounded by photoluminescent quantum nanocrystals (QNs) in the form of PbS encapsulated by a silica layer. There are three main design variables including HGN synthesis and optical tuning, formation of the silica layer on the hollow gold nanoshell surface, and fabrication and photoluminescence tuning of PbS quantum nanocrystals. The hollow gold nanoshells were deliberately designed to function in the optical regimes that maximize tissue transmissivity (800 nm) and minimize tissue absorption (1100 nm). Secondly, several chemical ligands were tested such as (3-mercaptopropyl)trimethoxysilane and mercaptoundecanoic acid for controlled growth of the silica layer. Last, PbS QNs were synthesized and optimized with various capping agents, where the nanocrystals excited at the same wavelength were used to activate the photothermal properties of the hollow gold nanoshells. Upon irradiation of the complex with a lower power 800 nm laser, the nanocrystals luminesce at 1100 nm. At ablative temperatures the intrinsic luminescent properties of the QNs are altered and the luminescent output is significantly reduced (>70%). While this paper focuses on synthesis and optimization of the QN-HGN complex, in the future we believe that this novel particle complex design may have the potential to serve as a triple theranostic agent, which will aid satellite tumor localization, photothermal treatment, and ablative confirmation.

Encapsulated Fe3O4 /Ag complexed cores in hollow gold nanoshells for enhanced theranostic magnetic resonance imaging and photothermal therapy.

Designed and fabrication of a novel magnetic hollow gold nanoshell complexes that incorporates iron oxide nanoparticles in the hollow interior. The combined effect of the smaller IONPs improved the overall magnetic properties of the design and MRI contrast capability. The overall complex could be synthesized in the range of 60-80 nm in diameter while still having a plasmonic peak in the near infrared region.

An Adaptive Home-Use Robotic Rehabilitation System for the Upper Body.

Robotic rehabilitation systems have been developed to treat musculoskeletal conditions, but limited availability prevents most patients from using them. The objective of this paper was to create a home-use robotic rehabilitation system. Data were obtained in real time from a Microsoft [Formula: see text] and a wireless surface electromyograph system. Results from the [Formula: see text] sensor were compared to a standard motion capture system. A subject completed visual follow exercise tasks in a 3-D visual environment. Data from two training exercises were used to generate a neural network, which was then used to simulate the subject's individual performance. The subjects completed both the exercise task output from the neural network (custom), and the unmodified task (standard). In addition, a wearable arm robot prototype was built. Basic system identification was completed, and a control algorithm for the robot based on pressure control was designed and tested. The subjects had greater root-mean-square error for position and velocity variables during the custom exercise tasks. These results suggest that the custom task was difficult to complete, possibly because the neural network was unconstrained. Finally, the robot prototype was able to mimic changes in a subject's elbow angle in real time, demonstrating the feasibility of the robotic rehabilitation system.

Electro-thermal vaporization direct analysis in real time-mass spectrometry for water contaminant analysis during space missions.

The development of a direct analysis in real time-mass spectrometry (DART-MS) method and first prototype vaporizer for the detection of low molecular weight (∼30-100 Da) contaminants representative of those detected in water samples from the International Space Station is reported. A temperature-programmable, electro-thermal vaporizer (ETV) was designed, constructed, and evaluated as a sampling interface for DART-MS. The ETV facilitates analysis of water samples with minimum user intervention while maximizing analytical sensitivity and sample throughput. The integrated DART-ETV-MS methodology was evaluated in both positive and negative ion modes to (1) determine experimental conditions suitable for coupling DART with ETV as a sample inlet and ionization platform for time-of-flight MS, (2) to identify analyte response ions, (3) to determine the detection limit and dynamic range for target analyte measurement, and (4) to determine the reproducibility of measurements made with the method when using manual sample introduction into the vaporizer. Nitrogen was used as the DART working gas, and the target analytes chosen for the study were ethyl acetate, acetone, acetaldehyde, ethanol, ethylene glycol, dimethylsilanediol, formaldehyde, isopropanol, methanol, methylethyl ketone, methylsulfone, propylene glycol, and trimethylsilanol.

Pathogenesis of West Nile virus lineage 1 and 2 in experimentally infected large falcons.

West Nile virus (WNV) is a zoonotic flavivirus that is transmitted by blood-suckling mosquitoes with birds serving as the primary vertebrate reservoir hosts (enzootic cycle). Some bird species like ravens, raptors and jays are highly susceptible and develop deadly encephalitis while others are infected subclinically only. Birds of prey are highly susceptible and show substantial mortality rates following infection. To investigate the WNV pathogenesis in falcons we inoculated twelve large falcons, 6 birds per group, subcutaneously with viruses belonging to two different lineages (lineage 1 strain NY 99 and lineage 2 strain Austria). Three different infection doses were utilized: low (approx. 500 TCID50), intermediate (approx. 4 log10 TCID50) and high (approx. 6 log10 TCID50). Clinical signs were monitored during the course of the experiments lasting 14 and 21 days. All falcons developed viremia for two weeks and shed virus for almost the same period of time. Using quantitative real-time RT-PCR WNV was detected in blood, in cloacal and oropharyngeal swabs and following euthanasia and necropsy of the animals in a variety of neuronal and extraneuronal organs. Antibodies to WNV were first time detected by ELISA and neutralization assay after 6 days post infection (dpi). Pathological findings consistently included splenomegaly, non-suppurative myocarditis, meningoencephalitis and vasculitis. By immunohistochemistry WNV-antigens were demonstrated intralesionally. These results impressively illustrate the devastating and possibly deadly effects of WNV infection in falcons, independent of the genetic lineage and dose of the challenge virus used. Due to the relatively high virus load and long duration of viremia falcons may also be considered competent WNV amplifying hosts, and thus may play a role in the transmission cycle of this zoonotic virus.