Public health use and lessons learned from a statewide SARS-CoV-2 wastewater monitoring program (MiNET).

The global SARS-CoV-2 monitoring effort has been extensive, resulting in many states and countries establishing wastewater-based epidemiology programs to address the spread of the virus during the pandemic. Challenges for programs include concurrently optimizing methods, training new laboratories, and implementing successful surveillance programs that can rapidly translate results for public health, and policy making. Surveillance in Michigan early in the pandemic in 2020 highlights the importance of quality-controlled data and explores correlations with wastewater and clinical case data aggregated at the state level.

Understanding the efficacy of wastewater surveillance for SARS-CoV-2 in two diverse communities.

During the COVID-19 pandemic, wastewater-based surveillance has been shown to be a useful tool for monitoring the spread of disease in communities and the emergence of new viral variants of concern. As the pandemic enters its fourth year and clinical testing has declined, wastewater offers a consistent non-intrusive way to monitor community health in the long term. This study sought to understand how accurately wastewater monitoring represented the actual burden of disease between communities.

Waist-What? Can a single sensor positioned at the waist detect parameters of gait at a speed and distance reflective of older adults' activity?

One of the problems facing an ageing population is functional decline associated with reduced levels of physical activity (PA). Traditionally researcher or clinician input is necessary to capture parameters of gait or PA. Enabling older adults to monitor their activity independently could raise their awareness of their activitiy levels, promote self-care and potentially mitigate the risks associated with ageing.

Prediction of low pulse oxygen saturation in COVID-19 using remote monitoring post hospital discharge.

Background: Monitoring systems have been developed during the COVID-19 pandemic enabling clinicians to remotely monitor physiological measures including pulse oxygen saturation (SpO), heart rate (HR), and breathlessness in patients after discharge from hospital. These data may be leveraged to understand how symptoms vary over time in COVID-19 patients. There is also potential to use remote monitoring systems to predict clinical deterioration allowing early identification of patients in need of intervention.

Generalizability of deep learning models for predicting outdoor irregular walking surfaces.

Observations from laboratory-based gait analysis are difficult to extrapolate to real-world environments where gait behavior is modulated in response to complex environmental conditions and surface profiles. Inertial measurement units (IMUs) permit real-world gait analysis; however, automatic detection of surfaces encountered remains largely unexplored. The aims of this study are to quantify for machine learning models the effect of (1) random and subject-wise data splitting and (2) sensor location and count on surface classification performance.

Connecting microbial, nutrient, physiochemical, and land use variables for the evaluation of water quality within mixed use watersheds.

As non-point sources of pollution begin to overtake point sources in watersheds, source identification and complicating variables such as rainfall are growing in importance. Microbial source tracking (MST) allows for identification of fecal contamination sources in watersheds; when combined with data on land use and co-occuring variables (e.g.

EntropyHub: An open-source toolkit for entropic time series analysis.

An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data. Entropy, as it relates to information theory and dynamical systems theory, can be estimated in many ways, with newly developed methods being continuously introduced in the scientific literature. Despite the growing interest in entropic time series and image analysis, there is a shortage of validated, open-source software tools that enable researchers to apply these methods.

Methods Evaluation for Rapid Concentration and Quantification of SARS-CoV-2 in Raw Wastewater Using Droplet Digital and Quantitative RT-PCR.

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging public health tool to understand the spread of Coronavirus Disease 2019 (COVID-19) in communities. The performance of different virus concentration methods and PCR methods needs to be evaluated to ascertain their suitability for use in the detection of SARS-CoV-2 in wastewater. We evaluated ultrafiltration and polyethylene glycol (PEG) precipitation methods to concentrate SARS-CoV-2 from sewage in wastewater treatment plants and upstream in the wastewater network (e.

A comparison of E. coli concentration estimates quantified by the EPA and a Michigan laboratory network using EPA Draft Method C.

We evaluated data from 10 laboratories that analyzed water samples from 82 recreational water sites across the state of Michigan between 2016 and 2018. Water sample replicates were analyzed by experienced U.S.

Quantitative clinical assessment of motor function during and following LSVT-BIG® therapy.

Background: LSVT-BIG® is an intensively delivered, amplitude-oriented exercise therapy reported to improve mobility in individuals with Parkinson's disease (PD). However, questions remain surrounding the efficacy of LSVT-BIG® when compared with similar exercise therapies. Instrumented clinical tests using body-worn sensors can provide a means to objectively monitor patient progression with therapy by quantifying features of motor function, yet research exploring the feasibility of this approach has been limited to date.

The Influence of Force Level and Motor Unit Coherence on Nonlinear Surface EMG Features Examined Using Model Simulation.

Nonlinear features extracted from surface EMG signals have been previously used to infer information on coherent or synchronous activity in the underlying motor unit discharges. However, it has not yet been assessed how these features are affected by the density of the surface EMG signal, and whether changes in the level of muscle activation can influence the effective detection of correlated motor unit firing. To examine this, a motoneuron pool model receiving a beta-band modulated cortical input was used to generate correlated motor unit firing trains.

Application of the Teagar-Kaiser energy operator and wavelet transform for detection of finger tapping contact and release times using accelerometery.

The Teager-Kaiser energy operator (TKEO), when applied to a signal gives an estimation of the instantaneous energy of that signal. It, therefore, accentuates both frequency and amplitude changes in a signal. To date, it has been primarily used in communications systems and most popularly in electromyographic signal analysis to detect bursts of muscle activity, however, it has the potential to be used in a number of applications including accelerometer and movement data.

Optical Coherence Tomography Angiography Findings in a Case of Cosmetic Laser Induced Retinal Injury.

We report the first known case of iris and retinal injury using optical coherence tomography angiography (OCTA) images following cosmetic laser injury. A 23-year-old female developed left iris and retinal injury post inadvertent firing of a 755 nm Alexandrite cosmetic laser. The patient had no significant past medical history and the injury resulted from inappropriate eye protection during laser use.

Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force.

Motor unit firing times are weakly coupled across a range of frequencies during voluntary contractions. Coherent activity within the beta-band (15-35 Hz) has been linked to oscillatory cortical processes, providing evidence of functional connectivity between the motoneuron pool and motor cortex. The aim of this study was to investigate whether beta-band motor unit coherence is altered with increasing abduction force in the first dorsal interosseous muscle.

Gait Event Detection From Accelerometry Using the Teager-Kaiser Energy Operator.

Objective: A novel method based on the application of the Teager-Kaiser Energy Operator is presented to estimate instances of initial contact (IC) and final contact (FC) from accelerometry during gait. The performance of the proposed method was evaluated against four existing gait event detection (GED) methods under three walking conditions designed to capture the variance of gait in real-world environments.

Methods: A symmetric discrete approximation of the Teager-Kaiser energy operator was used to capture simultaneous amplitude and frequency modulations of the shank acceleration signal at IC and FC during flat treadmill walking, inclined treadmill walking, and flat indoor walking.

Increased EMG intermuscular coherence and reduced signal complexity in Parkinson's disease.

Objectives: To investigate differences in surface electromyography (EMG) features in individuals with idiopathic Parkinson's disease (PD) and aged-matched controls.

Methods: Surface EMG was recorded during isometric leg extension in PD patients prior to, and after undergoing a locomotor training programme, and in aged-matched controls. Differences in EMG structure were quantified using determinism (%DET), sample entropy (SampEn) and intermuscular coherence.

Regional Variations of Bovine and Porcine Fecal Pollution as a Function of Landscape, Nutrient, and Hydrological Factors.

The effects of manure application in agriculture on surface water quality has become a local to global problem because of the adverse consequences on public health and food security. This study evaluated (i) the spatial distribution of bovine (cow) and porcine (pig) genetic fecal markers, (ii) how hydrologic factors influenced these genetic markers, and (iii) their variations as a function of land use, nutrients, and other physiochemical factors. We collected 189 samples from 63 watersheds in Michigan's Lower Peninsula during baseflow, spring melt, and summer rain conditions.

Cytotoxic oplopane sesquiterpenoids from Arnoglossum atriplicifolium.

Pale Indian plantain (Arnoglossum atriplicifolium (L.) H. Rob.

Ammonia-oxidizing bacteria and archaea in sediments of the Gulf of Mexico.

The diversity (richness and community composition) of ammonia-oxidizing archaea (AOA) and bacteria (AOB) within sediments of the Gulf of Mexico was examined. Using polymerase chain reaction primers designed to specifically target the archaeal ammonia monooxygenase-subunit (amoA) gene and bacterial amoA gene, we found AOA and AOB to be present in all three sampling sites. Archaeal amoA libraries were dominated by a few widely distributed Nitrosopumilus-like sequence types, whereas AOB diversity showed significant variation in both richness and community composition.

Linking bacterial diversity and geochemistry of uranium-contaminated groundwater.

To understand the link between bacterial diversity and geochemistry in uranium-contaminated groundwater, microbial communities were assessed based on clone libraries of 16S rDNA genes from the USDOE Oak Ridge Field Research Centre (FRC) site. Four groundwater wells (GW835, GW836, FW113-47 and FW215-49) with a wide range of pH (3 to 7), nitrate (44 to 23,400 mg L(-1)), uranium (0.73 to 60.

Injuries and deformities in fish: their potential impacts upon aquacultural production and welfare.

Fish can be the recipients of numerous injuries that are potentially deleterious to aquacultural production performance and welfare. This review will employ a systematic approach that classifies injuries in relation to specific anatomical areas of the fish and will evaluate the effects of injury upon production and welfare. The selected areas include the (1) mouth, (2) eye, (3) epidermis and (4) fins.