Masks thermal degradation as an alternative of waste valorization on the COVID-19 pandemic: A kinetic study.

The COVID-19 pandemic generated a new dynamic around waste management. Personal protective equipment such as masks, gloves, and face shields were essential to prevent the spread of the disease. However, despite the increase in waste, no technical alternatives were foreseen for the recovery of these wastes, which are made up of materials that can be valued for energy recovery. It is essential to design processes such as waste to energy to promote the circular economy. Therefore, techniques such as pyrolysis and thermal oxidative decomposition of waste materials need to be studied and scaled up, for which kinetic models and thermodynamic parameters are required to allow the design of this reaction equipment. This work develops kinetic models of the thermal degradation process by pyrolysis as an alternative for energy recovery of used masks generated by the COVID-19 pandemic. The wasted masks were isolated for 72 h for virus inactivation and characterized by FTIR-ATR spectroscopy, elemental analysis, and determinate the higher calorific value (HCV). The composition of the wasted masks included polypropylene, polyethylene terephthalate, nylon, and spandex, with higher calorific values than traditional fuels. For this reason, they are susceptible to value as an energetic material. Thermal degradation was performed by thermogravimetric analysis at different heating rates in N2 atmosphere. The gases produced were characterized by gas chromatography and mass spectrometry. The kinetic model was based on the mass loss of the masks on the thermal degradation, then calculated activation energies, reaction orders, pre-exponential factors, and thermodynamic parameters. Kinetics models such as Coats and Redfern, Horowitz and Metzger, Kissinger-Akahira-Sunose were studied to find the best-fit models between the experimental and calculated data. The kinetic and thermodynamic parameters of the thermal degradation processes demonstrated the feasibility and high potential of recovery of these residues with conversions higher than 89.26% and obtaining long-chain branched hydrocarbons, cyclic hydrocarbons, and CO2 as products.

Relevance of Fluorodopa PET Scan in Dopamine Responsive Dystonia and Juvenile Parkinsonism: A Systematic Review.

BACKGROUND: Dopamine Responsive Dystonia (DRD) and Juvenile Parkinsonism (JP) are two diseases commonly presenting with parkinsonian symptoms in young patients. Current clinical guidelines offer a diagnostic approach based on molecular analysis. However, developing countries have limitations in terms of accessibility to these tests. We aimed to assess the utility of imaging equipment, usually more available worldwide, to help diagnose and improve patients' quality of life with these diseases. METHODS: We performed a systematic literature review in English using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) and meta-analysis of observational studies in epidemiology (MOOSE) protocols. We only used human clinical trials about dopamine responsive dystonia and juvenile parkinsonism patients in which a fluorodopa (FD) positron emission tomography (PET) scan was performed to identify its use in these diseases. RESULTS: We included six studies that fulfilled our criteria. We found a clear pattern of decreased uptake in the putamen and caudate nucleus in JP cases. At the same time, the results in DRD were comparable to normal subjects, with only a slightly decreased marker uptake in the previously mentioned regions by the FD PET scan. CONCLUSIONS: We found a distinctive pattern for each of these diseases. Identifying these findings with FD PET scans can shorten the delay in making a definitive diagnosis when genetic testing is unavailable, a common scenario in developing countries.

Alignment Between Heart Rate Variability From Fitness Trackers and Perceived Stress: Perspectives From a Large-Scale In Situ Longitudinal Study of Information Workers.

BACKGROUND: Stress can have adverse effects on health and well-being. Informed by laboratory findings that heart rate variability (HRV) decreases in response to an induced stress response, recent efforts to monitor perceived stress in the wild have focused on HRV measured using wearable devices. However, it is not clear that the well-established association between perceived stress and HRV replicates in naturalistic settings without explicit stress inductions and research-grade sensors. OBJECTIVE: This study aims to quantify the strength of the associations between HRV and perceived daily stress using wearable devices in real-world settings. METHODS: In the main study, 657 participants wore a fitness tracker and completed 14,695 ecological momentary assessments (EMAs) assessing perceived stress, anxiety, positive affect, and negative affect across 8 weeks. In the follow-up study, approximately a year later, 49.8% (327/657) of the same participants wore the same fitness tracker and completed 1373 EMAs assessing perceived stress at the most stressful time of the day over a 1-week period. We used mixed-effects generalized linear models to predict EMA responses from HRV features calculated over varying time windows from 5 minutes to 24 hours. RESULTS: Across all time windows, the models explained an average of 1% (SD 0.5%; marginal R2) of the variance. Models using HRV features computed from an 8 AM to 6 PM time window (namely work hours) outperformed other time windows using HRV features calculated closer to the survey response time but still explained a small amount (2.2%) of the variance. HRV features that were associated with perceived stress were the low frequency to high frequency ratio, very low frequency power, triangular index, and SD of the averages of normal-to-normal intervals. In addition, we found that although HRV was also predictive of other related measures, namely, anxiety, negative affect, and positive affect, it was a significant predictor of stress after controlling for these other constructs. In the follow-up study, calculating HRV when participants reported their most stressful time of the day was less predictive and provided a worse fit (R2=0.022) than the work hours time window (R2=0.032). CONCLUSIONS: A significant but small relationship between perceived stress and HRV was found. Thus, although HRV is associated with perceived stress in laboratory settings, the strength of that association diminishes in real-life settings. HRV might be more reflective of perceived stress in the presence of specific and isolated stressors and research-grade sensing. Relying on wearable-derived HRV alone might not be sufficient to detect stress in naturalistic settings and should not be considered a proxy for perceived stress but rather a component of a complex phenomenon.

Adjuvant Treatment for Protocadherin 19 (PCDH19) Syndrome.

Protocadherin 19 (PCDH19) syndrome is inherited as an X-linked pattern and affects mainly females. This syndrome is caused by a mutation in the PCDH19 gene encoding for the protocadherin protein. It is characterized by refractory seizures during febrile episodes with neuropsychiatric manifestations. There is no consensus on the treatment of PCDH19. We conducted a literature review to investigate the main drugs used for this syndrome, and to evaluate the best possible course of adjuvant treatment for these patients. We used an advanced PubMed search strategy with the following inclusion criteria: a) full-text papers, b) English Language, and c) studies conducted in humans. Exclusion criteria: a) literature reviews, b) systematic reviews, and c) metanalysis. We gathered 26 observational papers to conduct this literature review on clobazam and bromide which have been shown to reduce seizures by 50%. Corticosteroids improved neurological symptoms during the episodes in a few patients. Nevertheless, they recurred after a few months. Preliminary results of ganaxolone, which is still under study, demonstrated a reduction of 60% in seizure episodes. A ketogenic diet has been studied to treat several refractory epilepsies, including PCDH19; it has promising results as effective adjuvant therapy in the resolution of status epilepticus, suggesting it could be used as part of the treatment in early childhood. Stiripentol was given as adjuvant therapy in a patient with PCDH19 epilepsy resulting in the most extended period of seizure-free episodes, but more studies must be performed to assess its efficacy.

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study.

BACKGROUND: Studies that use ecological momentary assessments (EMAs) or wearable sensors to track numerous attributes, such as physical activity, sleep, and heart rate, can benefit from reductions in missing data. Maximizing compliance is one method of reducing missing data to increase the return on the heavy investment of time and money into large-scale studies. OBJECTIVE: This paper aims to identify the extent to which compliance can be prospectively predicted from individual attributes and initial compliance. METHODS: We instrumented 757 information workers with fitness trackers for 1 year and conducted EMAs in the first 56 days of study participation as part of an observational study. Their compliance with the EMA and fitness tracker wearing protocols was analyzed. Overall, 31 individual characteristics (eg, demographics and personalities) and behavioral variables (eg, early compliance and study portal use) were considered, and 14 variables were selected to create beta regression models for predicting compliance with EMAs 56 days out and wearable compliance 1 year out. We surveyed study participation and correlated the results with compliance. RESULTS: Our modeling indicates that 16% and 25% of the variance in EMA compliance and wearable compliance, respectively, could be explained through a survey of demographics and personality in a held-out sample. The likelihood of higher EMA and wearable compliance was associated with being older (EMA: odds ratio [OR] 1.02, 95% CI 1.00-1.03; wearable: OR 1.02, 95% CI 1.01-1.04), speaking English as a first language (EMA: OR 1.38, 95% CI 1.05-1.80; wearable: OR 1.39, 95% CI 1.05-1.85), having had a wearable before joining the study (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.50, 95% CI 1.23-1.83), and exhibiting conscientiousness (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.34, 95% CI 1.14-1.58). Compliance was negatively associated with exhibiting extraversion (EMA: OR 0.74, 95% CI 0.64-0.85; wearable: OR 0.67, 95% CI 0.57-0.78) and having a supervisory role (EMA: OR 0.65, 95% CI 0.54-0.79; wearable: OR 0.66, 95% CI 0.54-0.81). Furthermore, higher wearable compliance was negatively associated with agreeableness (OR 0.68, 95% CI 0.56-0.83) and neuroticism (OR 0.85, 95% CI 0.73-0.98). Compliance in the second week of the study could help explain more variance; 62% and 66% of the variance in EMA compliance and wearable compliance, respectively, was explained. Finally, compliance correlated with participants' self-reflection on the ease of participation, usefulness of our compliance portal, timely resolution of issues, and compensation adequacy, suggesting that these are avenues for improving compliance. CONCLUSIONS: We recommend conducting an initial 2-week pilot to measure trait-like compliance and identify participants at risk of long-term noncompliance, performing oversampling based on participants' individual characteristics to avoid introducing bias in the sample when excluding data based on noncompliance, using an issue tracking portal, and providing special care in troubleshooting to help participants maintain compliance.

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea.

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea. We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py. Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing.

Previous studies of seasonal effects on sleep have yielded unclear results, likely due to methodological differences and limitations in data size and/or quality. We measured the sleep habits of 216 individuals across the U.S. over four seasons for slightly over a year using objective, continuous, and unobtrusive measures of sleep and local weather. In addition, we controlled for demographics and trait-like constructs previously identified to correlate with sleep behavior. We investigated seasonal and weather effects of sleep duration, bedtime, and wake time. We found several small but statistically significant effects of seasonal and weather effects on sleep patterns. We observe the strongest seasonal effects for wake time and sleep duration, especially during the spring season: wake times are earlier, and sleep duration decreases (compared to the reference season winter). Sleep duration also modestly decreases when day lengths get longer (between the winter and summer solstice). Bedtimes and wake times tend to be slightly later as outdoor temperature increases.

INDISIM-Denitrification, an individual-based model for study the denitrification process.

Denitrification is one of the key processes of the global nitrogen (N) cycle driven by bacteria. It has been widely known for more than 100 years as a process by which the biogeochemical N-cycle is balanced. To study this process, we develop an individual-based model called INDISIM-Denitrification. The model embeds a thermodynamic model for bacterial yield prediction inside the individual-based model INDISIM and is designed to simulate in aerobic and anaerobic conditions the cell growth kinetics of denitrifying bacteria. INDISIM-Denitrification simulates a bioreactor that contains a culture medium with succinate as a carbon source, ammonium as nitrogen source and various electron acceptors. To implement INDISIM-Denitrification, the individual-based model INDISIM was used to give sub-models for nutrient uptake, stirring and reproduction cycle. Using a thermodynamic approach, the denitrification pathway, cellular maintenance and individual mass degradation were modeled using microbial metabolic reactions. These equations are the basis of the sub-models for metabolic maintenance, individual mass synthesis and reducing internal cytotoxic products. The model was implemented in the open-access platform NetLogo. INDISIM-Denitrification is validated using a set of experimental data of two denitrifying bacteria in two different experimental conditions. This provides an interactive tool to study the denitrification process carried out by any denitrifying bacterium since INDISIM-Denitrification allows changes in the microbial empirical formula and in the energy-transfer-efficiency used to represent the metabolic pathways involved in the denitrification process. The simulator can be obtained from the authors on request.

Social network structure is predictive of health and wellness.

Social networks influence health-related behavior, such as obesity and smoking. While researchers have studied social networks as a driver for diffusion of influences and behavior, it is less understood how the structure or topology of the network, in itself, impacts an individual's health behavior and wellness state. In this paper, we investigate whether the structure or topology of a social network offers additional insight and predictability on an individual's health and wellness. We develop a method called the Network-Driven health predictor (NetCARE) that leverages features representative of social network structure. Using a large longitudinal data set of students enrolled in the NetHealth study at the University of Notre Dame, we show that the NetCARE method improves the overall prediction performance over the baseline models-that use demographics and physical attributes-by 38%, 65%, 55%, and 54% for the wellness states-stress, happiness, positive attitude, and self-assessed health-considered in this paper.

Consumer acceptance and sensory drivers of liking for high plant protein snacks.

BACKGROUND: Consumers are being encouraged to increase the proportion of plant protein in their diet to tend to a sustainable food system. Solutions could include developing a food rich in plant protein. However, these new products have an interest only if they are in accordance with expectation and the liking of consumers. In this context, extruded snack balls were developed to explore the sensory drivers of liking and barriers to consumption of formulated products with a high level of plant proteins. Eight different products varying in the type of cereal flour (rice or wheat) and pea flour content (from 60% to 90%) were developed following a factorial design. Eighty omnivore and 72 flexitarian consumers were recruited to evaluate the liking of these products. In addition, their sensory properties were described by a trained panel according to a profile method. RESULTS: The cereal type had globally more influence on liking than the percentage of pea. However, liking was inversely correlated with pea flour content, regardless of the cereal type. The main drivers of liking are texture criteria (in particular crispy and puffy), whereas flavor perception (pea, green) constitutes a barrier to acceptance. Interestingly, very few differences of liking were observed depending on the diet of consumers even though the attitudes of flexitarian'towards such type of products differed from those of omnivores. We identified three clusters of consumers based on their preferences. Pea flavor acceptance or rejection could explain these clusters. Although most consumers rejected pea flavor, approximately 40% of the participants preferred the products with highest pea content. CONCLUSION: The results of the present study will help provide guidance for innovative plant food design and formulation. © 2019 Society of Chemical Industry.

INDISIM-Paracoccus, an individual-based and thermodynamic model for a denitrifying bacterium.

We have developed an individual-based model for denitrifying bacteria. The model, called INDISIM-Paracoccus, embeds a thermodynamic model for bacterial yield prediction inside the individual-based model INDISIM, and is designed to simulate the bacterial cell population behavior and the product dynamics within the culture. The INDISIM-Paracoccus model assumes a culture medium containing succinate as a carbon source, ammonium as a nitrogen source and various electron acceptors such as oxygen, nitrate, nitrite, nitric oxide and nitrous oxide to simulate in continuous or batch culture the different nutrient-dependent cell growth kinetics of the bacterium Paracoccus denitrificans. The individuals in the model represent microbes and the individual-based model INDISIM gives the behavior-rules that they use for their nutrient uptake and reproduction cycle. Three previously described metabolic pathways for P. denitrificans were selected and translated into balanced chemical equations using a thermodynamic model. These stoichiometric reactions are an intracellular model for the individual behavior-rules for metabolic maintenance and biomass synthesis and result in the release of different nitrogen oxides to the medium. The model was implemented using the NetLogo platform and it provides an interactive tool to investigate the different steps of denitrification carried out by a denitrifying bacterium. The simulator can be obtained from the authors on request.

Modified carbon paste electrodes for flow injection amperometric determination of isocitrate dehydrogenase activity in serum.

A carbon paste electrode modified with the adsorbed products of the electrochemical oxidation of adenosine triphosphate is described. The electrode was applied to the amperometric electrocatalytic detection of the reduced form of both nicotinamide adenine dinucleotide and nicotinamide adenine dinucleotide phosphate. The catalytic oxidation current shows a linear dependence on the concentration of the reduced form of nicotinamide adenine dinucleotide up to 1x10(-4)M, with a detection limit of 5x10(-9)M. Modified carbon paste electrodes were coated with an electrogenerated film of nonconducting poly(o-phenylenediamine) to obtain a stable amperometric response for at least 150h. In addition to static measurements, determination of both reduced cofactors was carried out in a flow injection analysis system with a thin-layer amperometric detection cell. The electrocatalytic monitoring of reduced nicotinamide adenine dinucleotide phosphate was applied to flow injection measurement of isocitrate dehydrogenase activity in serum. The results were in good agreement with those for the standard spectrophotometric test kit. The proposed method consumed less time and reagents and provided better precision than the standard method.