Drosophila melanogaster is a powerful model to study small-scale, temporally-transient social behavior. However, longer-term analysis of large groups of flies is hampered by the lack of effective and reliable tools. We built a new imaging arena and improved the existing tracking algorithm to reliably follow a large number of flies simultaneously. Next, based on the automatic classification of touch and graph-based social network analysis, we designed an algorithm to quantify changes in the social network in response to prior social isolation. We observed that isolation significantly and swiftly enhanced individual and local social network parameters depicting near-neighbor relationships. We explored the genome-wide molecular correlates of these behavioral changes and found that whereas behavior changed throughout the six days of isolation, gene expression alterations occurred largely on day one. These changes occurred mostly in metabolic genes, and we verified the metabolic changes by showing an increase of lipid content in isolated flies. In summary, we describe a highly reliable tracking and analysis pipeline for large groups of flies that we use to unravel the behavioral, molecular and physiological impact of isolation on social network dynamics in Drosophila.Isolation profoundly influences social behavior in all animals. In humans, isolation has serious effects on health.  Social isolation severely affects the behavior and physiology of social animals, including humans. The fruit fly is a powerful model for studying the mechanisms of development, health and disease and is also used to study social behaviors such as mating and aggression. However, these studies are limited to examining few individuals for shorts amounts of time, due to the lack of effective computational tools for the analysis of large groups over prolonged time. To overcome this hurdle, we built a new behavioral arena and developed new software that accurately tracks many flies simultaneously over long time periods. The arena is cheap and easy to build and the software works with low resolution videos. Using these improved tools, we studied social isolation in groups of male flies. We found that isolation caused flies to form stronger interactions with neighboring flies in their social network. These behavioral changes were preceded by transient changes in the expression of metabolism genes and eventually resulted in isolated flies accumulating fat, as has been previously observed in studies in mice and humans. Our study opens the door for the use of fruit flies in future studies of social isolation. Caenorhabditis elegans, Drosophila melanogaster (fruit flies) and other animals, to the most complex social behaviors of primates including human beings [et al [Social interactions range from simple touch contacts as seen in n beings –4. Socian beings –10. In hn beings . Furthern beings ,13. For s [et al  profiledTo unravel the complex mechanisms of social behaviors, which occur in groups, tools are essential to analyze all interacting individuals at the same time. Whilst most studies still focus on dyadic interactions to limit the complexity of analysis –17, thesDrosophila melanogaster is a very powerful genetic and neuroscience model that can to a certain extent readily be used to study social behavior and its underlying mechanisms. In order to study social behaviors in the fly, for example the effects of isolation on behavior and metabolism, a few key challenges remained open and needed to be addressed. These include appropriate experimental setups, reliability and accuracy of tracking, behavioral classification and detailed social network analysis. Presently, few of these are readily available with the required level of accuracy that we needed for our study on the effects of isolation on social behavior.While there has been enormous progress in the study of pairs of flies in dyadic interactions , tools aet al [The next key issue in the analysis of social behaviors is the classification of various types of behaviors. Manual scoring is observer-dependent and can be arduous when multiple flies are involved . Schneidet al  proposedet al , in whicet al [Drosophila at the group level by generating unweighted dynamic networks. Based on binary social network parameters, they concluded that social isolation had no effect on the networks. On the other hand, Simon et al [Schneider et al  were theon et al  used a sAlthough a social interaction network can be useful to quantify social behaviors, it has its limitations when comparing different conditions, such as different biological repeats of an experiment. In that case, the intuition is to average the parameters of the social networks obtained from the individual repeats, which is only valid for a homogenous network structure . This isIn summary, in this paper we describe an effective and reliable pipeline to image and analyze large groups of walking male flies. The pipeline consists of 1) an efficient and relatively low-cost acquisition setup, 2) an improved tracking algorithm  based on a graph-theoretical framework, 3) a machine learning method for the classification of social interactions, and 4) a novel algorithm for computing an average social network to analyze the social structure. We apply this pipeline to study behavioral changes due to isolation and correlate these with changes in genome-wide gene expression. Our results show strong and specific effects of isolation on social network dynamics, metabolic gene expression and animal physiology.Data acquisition was performed using Flyworld, a closed computer vision setup, consisting of a specifically designed arena  and a hiTo demonstrate the improvement Flytracker provides compared to previously available methods, we used Ctrax to reanalyze our videos, and found that it detected wrong numbers of flies in 60–70% of the frames , varyingTo validate Flytracker, we established ground-truth. For this, we manually tracked all flies, and found only three identity swaps in one 50-fly 1-hour video and zero errors in two randomly chosen 16-fly 1-hour videos S2 Fig).The average weighted directional networks of control experiments and experiments under social isolation conditions were compared quantitatively. For this, we calculated three types of parameters: individual fly parameters such as the Weighted Degree (describing the tendency of a fly to interact), local interaction parameters such as the Clustering Coefficient (describing the strength of interactions between neighboring flies) and global interaction parameters such as the Global Efficiency . The key parameters for our analysis were the Weighted Degree, Weighted Total Interactions (describing the tendency of flies to interact in the whole group), Clustering Coefficient, Global Efficiency, Assortativity (describing the tendency of interactions between similarly active flies), Betweenness Centrality (describing the importance of a fly as connection “hub” to other flies) and Transitivity . For a detailed description of all the parameters please refer to the methods section. Besides these network parameters, the Total Walking Distance is calculated directly from the tracks as a measure for the locomotor activity.In order to test our social network analysis pipeline and to study the effect of isolation on the social network structure, we performed isolation experiments. In a first set of experiments, we tested the effect of 6-day isolation on the social network. From ten repeats of the experiment, each time with a different control and isolation group, we constructed the average networks of the control and isolated groups and analyzed their network parameters .A strong effect of 6-day social isolation was that the flies displayed an enhanced locomotor activity, demonstrated by a significant increase in Total Walking Distance . HoweverTo address the observation that isolation enlarges the number of interactions without a major change in the global structure of the social network, we examined local network parameters. No significant difference between control and isolated flies was found in the Betweenness Centrality. Therefore, no evidence was found for an enhanced activity of specific “hub” flies . In contAs stated above, the activity at the whole-group level was not affected by isolation, since along with the Weighted Total Interaction, the other global network parameters did not differ significantly between the control and isolated flies. This was the case for Global Efficiency, Density, Assortativity and Transitivity, respectively .In summary, we found that 6 days of isolation caused an increase in the locomotor activity and frequency of interactions at the local level without changing the global structure of the social network.The isolation period of 6 days may be longer than required to cause changes in social behavior. Conversely, behavioral changes may have occurred and then disappeared again within the 6-day period. To determine the minimum number of days of isolation required to result in social behavioral changes, we repeated the isolation experiments for periods of 1, 2, 3, 4 and 5 days of isolation using the same methodology. Isolated flies walked significantly more than flies in control groups starting from day 2 of the experiment onwards see . The walThe network data indicated that individual and local social parameter changes after social isolation are early-occurring and long-lasting. Next, we investigated if these behavioral changes were accompanied by alterations in gene expression . To thisOur differential expression analysis showed that the vast majority of changes in gene expression occurred after 1 day of isolation and that the changes were very transient . A few cAltogether, our data so far suggest that already after only a single day of isolation flies alter their physiology and behavior to promote social interactions with neighboring flies. One of the individual fly parameters that changes early and persistently is walking distance. We therefore asked how this individual fly parameter might relate with local network-level parameters affected by isolation such as Weighted Degree and Clustering Coefficient and how this might evolve over isolation time. To this end, we calculated the correlation coefficient between walking distance and local interaction parameters on days 1, 2 and 6. We find that after 1 day of isolation there is a strong correlation between walking distance and local interaction parameters in isolated flies but not in controls. These correlations emerge in controls on day 2 and persist in both groups on day 6 . This suFinally, to gain insight into the physiological processes affected by isolation-induced that might trigger early changes in behavior, we analyzed the isolation-induced gene expression alterations. The DAVID Bioinformatics Resources 6.8 (Beta) ,36 was uMyofilin, coding a core protein in the thick filaments of muscle [Pif1B, a Janus Kinase and microtubule-interacting protein coding gene [Mf was alternatively spliced on both the first two days. After 3 days of isolation, a gene encoding a nucleic acid regulating protein, namely the Purine-nucleoside Phosphorylase Related protein, CG16758 [squid (sqd) [desaturase 1 (desat1) gene, whose product is involved in fatty acid synthesis [Next, we investigated if isolation affects gene expression by changing isoform balance through alternative splicing. To this end, alternative splicing events in our RNA-seq data  were prof muscle , and Pifing gene , were af CG16758 , and theid (sqd)  gene encynthesis ,43 and pynthesis  was affein vivo by measuring the weight and lipid content of isolated flies compared to controls. The wet weight, dry weight, and lipid weight of 16 flies of each group were measured (mean ± SD) than that of control flies   . Furtheran ± SD) .Drosophila. Importantly, this pipeline uses easily available hardware to record long videos of interacting flies. The use of a graph-theoretic structure for the tracking algorithm allows to detect a constant number of flies in each frame, thus it is highly reliable and accurate and no further steps are required to correct for broken tracks. We confirmed this by the manual tracking of 2 randomly chosen videos. The supervised machine learning approach that we used for classification is generic and allows to extend the study of mere “touch” interactions to other types of interactions such as “sniff” or “chase”. Therefore, this platform is well suited for an accurate large-scale, long-term assessment of social behavior in flies. In theory, this approach is transferrable to any other species. Additionally, the interfaces between different components of the pipeline are compatible with other established methods, so that other researchers can adapt their experiments to our pipeline with minimum effort.In this paper, we describe the establishment of a novel framework for the accurate tracking of multiple flies, their behavior classification and a method to study social network dynamics. We use this framework to study the effects of isolation on social network dynamics and performed the first genome-wide gene expression analysis to correlate transcriptomic and behavioral changes upon social isolation in male In this study, we implement for the first time the use of an average network for social touch interactions for a large group of male flies. Previously,  work useHaving developed these tools, we applied them to study the consequences of isolation on social network dynamics. The results showed that social isolation affects the interactions between isolated flies by increased locomotion activity and local social interactions, with minimal effects on the global pattern of social interactions.Drosophila compared to that of control group, both in the gross weight  and normalized lipid content. It is tantalizing to speculate that a transient alteration in the metabolic state of flies upon social isolation plays a potentially causal role in long term behavioral changes, but this needs to be studied in much greater depth in the future.Social isolation in humans is a risk factor for, and may contribute to, poorer overall cognitive performance and executive function, increased negativity and depressive cognition . There aDrosophila melanogaster were raised on standard cornmeal/agar medium in large vials at room temperature (22 °C) and a 12h light/dark cycle. 9-day old flies were taken out of their vials and put onto a petri dish after cold anesthetization. Male flies were collected under a stereo microscope. Groups of 16 male flies were sorted and introduced into a new small vial. All flies were kept in new vials for one day before treatment.Canton-S wild-type After one day, the flies were transferred to new small vials either individually or grouped depending on the treatment. For the isolation group, 16 flies were transferred to 16 new small vials and kept in the small vial for 1–6 days, depending on the length of isolation. For the control groups, all 16 flies were transferred to one small vial and kept for 1–6 days, depending on the length of treatment in the experimental group. In total for each repeat of the experiment, there were 6 groups of isolated flies and 6 groups of control flies. All experiments were repeated 10 times.We constructed Flyworld  to record multiple flies in a walking arena  under diMovies were recorded at 30 fps using a high-speed infrared Genie HM640 camera . The recording chamber was designed to enforce the movements of flies in a two dimensional plane . In ordehttps://github.com/flytracker/flytracker). Flytracker’s reliability in tracking multiple flies is based on one particular assumption that shapes the algorithm: the number of flies remains constant throughout the video. Since the field of view of the camera in Flyworld covers the whole walking arena, this assumption is automatically met. As in Ctrax [The Flytracker is developed mainly using MATLAB  is labeled with a black box for easy tracking. Positions of the particular fly, 30 frames before and after the current frame are displayed in black dots to help the observer to predict possible losses of identity. All flies were labeled with their fly ID number. During each validation cycle, an observer followed the particular fly throughout the whole 1-hour video to check if there is a loss or swap of identities. After completion of one cycle, the observer choses another particular fly (Fly 2) and so on to repeat the above procedure until all flies have been analyzed. The same procedure was applied to validate two 16-fly 1-hour videos.Once all flies are tracked, social interactions between the flies can be detected. Flies can exhibit different types of interaction . Given the low spatial resolution of Flyworld, detailed fly body kinematics are not visible, which limits our search to simple types of interactions. In this work, we focused on one particular touch event, in which one fly (the interactor fly) approaches another fly (the interacted fly) by a head-to-tail contact. A touch interaction was then defined as a situation where a touch event lasts for at least 0.5 seconds, while a gap of at least 0.5 seconds was required to separate two distinct touch interactions.et al [Single frame touch events were determined by a supervised learning method, using Support Vector Machines . For thA training data set was built by manually annotating touch events. The training data set contained 1000 frames of touch events and an equal number of no-touch events. Testing data sets were built by manually annotating 3 different fly-pairs exhibiting the two events. Each testing data set contains 1000 events, to be classified into one of the two behavioral classes. The result of the classifier was validated with the ground–truth of the testing data set. A separate comparison was also made with a second expert’s annotation on the same video and on the same set of flies.Once all frames are classified either as a touch event or as a no-touch event, the touch interactions are determined based on the 0.5 second rule. All fly trajectories are then subdivided into intervals in which the fly either exhibits a touch interaction or not.After video annotation and classification, the results are represented by a weighted adjacency matrix, which is a square matrix, with each element denoting a particular fly pair. The value of the element (weight) represents the number of touch interactions between the particular fly pair. From the adjacency matrix, a social network is constructed, as a directed weighted graph, by representing flies by nodes and their specific touch interactions by edges. An illustrative example adjacency matrix and its corresponding social network is shown in The network is directed in order to identify the principal interactor fly and the interacted fly: the edge starts from the node of the principal interactor fly and points to the node of the interacted fly. In the networks, the flies are labeled with numbers (from 1 to 16) in ascending order of out-going activity (number of touch interactions as an interactor fly) so that all flies with similar network ranking across different networks are placed into similar positions.et al [Each social network was quantified by nine well established network parameters, as previously defined by Wey. T et al . Each adIndividual parameters:1In-Degree, Out-Degree, Degree. These degree-related individual parameters are directional parameters. The Out-Degree is the number of edges that leave a node, while the In-Degree is the number of edges that reach a node. In the sample social network, fly X1 interacts with flies X2, X3, X4, X5, and X6, leading to an Out-Degree of 5. Fly X1 receives interactions from flies X2, X3, and X5, so its In-Degree is 3. The Degree is the sum of the In-Degree and Out-Degree.2Weighted In-Degree, Out-Degree, and Degree. When accounting for the weights of the edges , weighted values for the degrees are obtained.Local parameters:3et.al [Clustering Coefficient: This parameter indicates how interactive the neighbors of a node are. A node with high clustering coefficient has a high number of connected neighbors that are also connected to each other. The Clustering Coefficient for a weighted directed network is defined by Fagiolo. G. et.al  and is cet.al .4Betweenness Centrality : BetweenGlobal parameters:5Assortativity: This parameter indicates the preference of nodes in a network to connect to other nodes that have similar degree . In an a6Global Efficiency: This parameter is the network average of the inverse path lengths between any two nodes . For soc7Transitivity : This pa8Density: This parameter measures the proportion of direct connections to the total number of possible connections . A dense9Weighted Total Interaction: This parameter is the total number of weighted interactions between all nodes. If the weight is neglected, one obtains the Unweighted Total Interaction.1, …, Xk) is a sample of k graphs, then the standard method of calculating the mean graph, 1 and W2 represent 2 (m × m) networks, then both graphs are matched by minimizing the Frobenius norm ∥W1 –PW2PT∥, where P is the set of all (m × m) permutation matrices [X′i represents the matched network of the ith experiment.In order to represent several experimental repeats as a single network with the same features as the individual networks, a methodology is proposed to construct a single graph from a set of multiple graphs. If D =  interaction matrices each representing a social interaction network. Output: an average network of the set of k originals networks.1 and set the mean matrix M = W1Step 1: Choose one interaction matrix WStep 2: For i = 2 to ki and compute permutation matrix R which minimizes the Frobenius norm ∥M − R WiRT∥. Reorder the nodes of Wi by setting Choose interaction matrix WUpdate the mean matrix, Step 3: EndIsolated or control flies were collected on the day of experiment. Isolation or grouped housing lasted for six days. Three repeats of each experiment were performed, with 16 flies in each group. Flies were collected 2–4 hours after the light cycle starts. Cold anesthesia was used to immobile the flies and to transfer them into RNA free tubes with beads. Following the TRIzol (Invitrogen) protocol . In shorDrosophila melanogaster reference genome dm3 using STAR2.3.1t with default parameters [Drosophila melanogaster annotation BDPG5 to calculate the numbers of reads per gene. The counts of all samples were tabulated. Then this table was fed to DESeq [Raw sequence reads from the FASTQ files of 24 samples were mapped against the rameters . Only thto DESeq  for normto DESeq –64. The to DESeq  was usedDrosophila melanogaster annotation BDPG5 to calculate the number of reads on the splicing junctions. The junction counts were then processed to extract the splicing events. The counts for each event was tabulated and the differential splicing of each event between control and isolated groups for all four time points  was tested using the Dirichlet multinomial model as previously described [To identify the differentially alternatively spliced events, the reads were count against the gene models generated from the Ensembl escribed . The Benescribed  was usedThe dry weights of adult flies were measured with a Mettler-Toledo XS105 precision balance in groups of 16 from isolated or grouped housed flies  test was used for post-hoc multiple comparison in experiments where flies were isolated for different days. Fisher’s exact test was used for GO enrichment analysis. D’Agostino & Pearson normality test was used for normality test of lipid/dry-weight analysis. Paired t-test was used for comparison between control and isolation groups in lipid weight experiment.S1 Fig1, C21 are duplicated nodes. After solving the assignment problem, a minimum weighted graph is obtained where the nodes P1 and P2 are connected to C1 while P3 and P4 are connected to C2. Each of the 2 connected components thus contains 2 individual flies.The nodes P1,.., P4 represent the individual flies in the previous frame while C1 and C2 represent the candidate connected components containing multiple interacting flies. C1(TIF)Click here for additional data file.S2 FigOn the left are the different networks constructed from 10 biological repeats of an experiment under the same conditions. Each network was constructed from its corresponding adjacency matrix, normalized to the maximum number of interactions within that matrix. On the right is the average network, reconstructed based on the graph matching method.(TIF)Click here for additional data file.S3 FigThe individual network parameters In-Degree, Out-Degree and Degree all show significant differences with p<0.0001. (D) No significant difference between isolated and control groups was observed for the local parameter Betweenness Centrality, demonstrating that pivot flies do not significantly gain in importance. Significant differences between control and isolation groups were observed for the weighted individual parameters Weighted In-/Out-Degrees (G-H). The global parameters Density and Transitivity show no significant differences. All plots use 2.5th to 97.5th percentiles as whiskers and 25th to 75th percentiles as box, with the median value in the middle of the box (n = 10).(TIF)Click here for additional data file.S4 FigDifferent parameters show changes over time and differences between control (blue) and isolated (red) groups. Significance is noted with asterisks, the number of which represent the negative orders of magnitude of p value. Data are shown in median with interquartile ranges (n = 10 on each day in both groups).(TIF)Click here for additional data file.S5 Fig2 of fold changes versus log10 of gene counts on days 2 and 3. (C) GO analysis shows up-regulated genes on day 2 are mainly related to iron ion binding. (D) GO analysis shows down-regulated genes on day 2 are mainly clustered into carboxylase and amino metabolic processes. (E-H) Wet, dry, ether and lipid weight changes between control and isolation groups in male and female groups. . All p values are less than 0.05 in paired t-test. Scatter plots of log(TIF)Click here for additional data file.S6 Fig(A) The matrix consists of the number of interactions between any two flies. For example, row 1 column 2 indicates 2 interactions from fly X1 to fly X2, which is shown in (B) as an arrow from X1 to X2, whose thickness is proportional to the number of interactions.(TIF)Click here for additional data file.S7 FigEach filled circle represents the correlation coefficient with p value less than 0.01. The size and color of the circle are proportional to the correlation coefficients and blue colors indicate positive correlations while red colors indicate negative correlations. On Day 1 the total walking distance showed positive correlations to all individual parameters and clustering coefficient in isolation group compared to control group. For the remaining days, the correlation map is similar between control and isolation groups.(TIF)Click here for additional data file.S1 VideoEach fly is labelled blue while trajectories are labelled with different colours. The video is a 15 minute clip of a 1-hour tracking video.(MP4)Click here for additional data file.S2 VideoEach fly is labelled with a number and a distinct colour for its trajectory (+/- 0.5 s). The video is a 30 second clip of a 1-hour tracking video.(MP4)Click here for additional data file.S3 VideoEach fly is labelled with a distinct colour for its trajectory (from 0.5s before current position). The video is an 8 second clip of a 1-hour tracking video.(MP4)Click here for additional data file.S4 VideoThe colored shapes represent different flies that Ctrax detects. This clip started from when the errors become severe. The errors include losing identity (no color contour covers the fly), swapping identity rapidly (change of colors), emerging new false identity, and false connection (odd connection line), etc. Using the Fixerror tool provided along with Ctrax has already fixed some errors in the beginning of the original video although the errors still occur as shown in this clip.(MOV)Click here for additional data file.S5 VideoTwo female and eight male flies with clipped wings walking on the platform surrounded by water to prevent them walking outside of the platform. All flies were labeled with detected identity.(MP4)Click here for additional data file.S6 VideoEach time, the observer focuses on one single fly . All flies were labeled with their corresponding identity numbers to help the observer to check if there are missing or swapped identities.(MP4)Click here for additional data file.S7 VideoAn interactor approaches the rear part of the interacted and the interaction is considered valid only when two flies maintain relative positions for more than 15 frames (~0.5 s).(MP4)Click here for additional data file.S1 TableNote. PATH1&2 A path includes the alternative exons and the flanking exons from one of the two isoforms of the event. The two paths of an event describe the two alternatively used isoforms of the splicing event. Event Types: A5SS: Alternative 5’ splicing sites; AFE: Alternative first exons; ES: Exon skipping, MC: Multi-comparison, there are more than 2 paths in comparison.(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S1 FileIn the zip file, there are 3D model designs of key parts of Flyworld used in this experiment in folder “Flyworld” and designs of Buridan’s Paradigm for testing Flytracker in the folder “Buridan setup”. All 3D designs are made using SolidWorks which can be viewed and measured using the free software “eDrawings”.(ZIP)Click here for additional data file.


NEEDSinALS.com).This is an observational study on well-being and end-of-life preferences in patients with amyotrophic lateral sclerosis (ALS) in the locked-in state (LIS) in a Polish sample within the EU Joint Programme–Neurodegenerative Disease Research study NEEDSinALS  were interviewed on well-being  as a measure of psychosocial adaptation, coping mechanisms, and preferences towards life-sustaining treatments  and hastened death. Also, clinical data were recorded . Standardized questionnaires , ALS Depression Inventory–12 items [ADI-12], schedule of attitudes toward hastened death [SAHD], Motor Neuron Disease Coping Scale) were used, which were digitally transcribed; answers were provided via eye-tracking control. In addition, caregivers were asked to judge patients' well-being.The majority of patients had an ACSA score >0 and a SEIQoL score >50%  and ADI-12 <29 . Physical function did not reflect subjective well-being; even more, those with no residual physical function had a positive well-being. All patients would again choose the life-sustaining techniques they currently used and their wish for hastened death was low (SAHD <10). Caregivers significantly underestimated patient's well-being.Some patients with ALS in LIS maintain a high sense of well-being despite severe physical restrictions. They are content with their life-sustaining treatments and have a strong will to live, which both may be underestimated by their families and public opinion. LIS may also occur in amyotrophic lateral sclerosis (ALS), which is pathologically characterized by progressive loss of efferent control leading to tetraplegia, anarthria, muscle wasting, respiratory insufficiency, and death within 2 years on average. Patients may survive longer only if therapeutic devices such as noninvasive ventilation (NIV)2 or invasive ventilation and percutaneous endoscopic gastrostomy (PEG) are provided.3 As most patients in LIS live at home with greatly reduced contact with the outside world, little is known about their thoughts, feelings, and wishes in this condition. For healthy people, LIS may seem among the most threatening conditions, and quality of life (QoL) is generally considered low and depression highly prevalent.4 Patients are discouraged to choose life-prolonging treatments such as invasive ventilation as the usage “appears [to be] associated with a lesser quality of life […and a] fear of a locked-in state.” 5 On the contrary, previous studies have suggested that loss of physical function is not necessarily associated with low well-being6 despite the usage of invasive ventilation.7 Shortly after diagnosis, well-being may decline in some patients because of a reactive episode following the diagnosis.9 If patients readjust their expectations according to the test, operate, test, exit (TOTE) model10 and allow for successful coping in the sense of response shift (changing attitudes on what is important in life), reframing , and reappraisal (looking at things from a different perspective), psychosocial adaptation may occur in the sense of satisfactory QoL and low depression rate11 compared to the general healthy population4 and despite the use of invasive techniques to support life.7 This may not be specific to ALS but may be a general capacity to adjust to adverse circumstances.12 Little is known about patients with ALS’ satisfaction with life-sustaining treatments or their wish to end life in the context of their well-being and coping strategies. Previous research has provided evidence that patients in LIS may have a strong will to live,13 but quality is limited by the fact that most studies so far used simple blink Morse code to communicate with the patients or focused primarily on well-being. We present a unique explorative approach of communication with patients in LIS via eye-tracking control to learn not only about their well-being,11 but also about their therapeutic decision-making and end-of-life preferences in a state of complete physical restriction .The locked-in state (LIS) is a rare phenomenon, which may occur in various diseases and is characterized by complete immobility and loss of verbal communication abilities (anarthria) while being fully conscious (deefferentiation).14 with classical LIS with severe physical restriction but  complete loss of purposeful volitional motor control for communication  and walking. Exclusion criteria were an overt cognitive impairment certified by a trained neuropsychologist (M.L. and O.H.) or clinically defined frontotemporal dementia according to Rascovsky criteria.16In this exploratory cross-sectional study, 103 caregivers of patients in the LIS were contacted by email by Dignitas Dolentium, the Polish patient organization. Caregivers of 25 patients responded  and 19  were interviewed between December 2016 and January 2017 ; 1 patieU < 1.31 with p > 0.05).All patients had used NIV to start with, but at the time of the study, most patients (17/19) used invasive ventilation via tracheostomy and PEG. Two patients had declined to use invasive ventilation and continued to use NIV via facial mask. In total, 12 patients (71%) received invasive ventilation in an emergency situation, including 7 with no prior information on the measures, 5 with a prior positive attitude. Those five patients with a prior positive attitude towards invasive ventilation underwent a planned tracheostomy. In Poland, there are no legal means to discontinue invasive ventilation. There was no clinical difference between those who had planned invasive ventilation/PEG and those who did not with regard to time since onset/diagnosis, ALS Functional Rating Scale - revised version (ALSFRS-R), age, or years of education  and Warsaw (KB/138/2013). All participants provided written (for patients via eye-tracking) informed consent.Patients provided their answers either via eye-tracking control on a visual keyboard or via blink responses or via both. Questionnaires were presented on a portable screen (tablet PC) and in addition, the interviewer asked the question. Therefore, the patients had both verbal and auditory input. For those 12 patients who used the eye-tracker system, a virtual keyboard was presented on a tablet screen. This tablet was placed about 30 cm in front of the patient and a mobile telescope arm (possible rotation 360°) was used for fixation of the tablet so patients could either sit or lie in bed. Patients fixated targets consecutively (letters or numbers) with their eyes and thus “typed” their answers letter by letter. Gaze was tracked by a standard eye-tracking device with infrared light  placed below the laptop screen or by an individual device owned by the patient . Respons.Questions and choices for answers were visually and verbally presented by the interviewer and 9 patients indicated their choices via eye-tracking, 6 via eye-blink, 3 patients used a combination of both, and 1 patient had residual verbal communication skills (but was completely tetraplegic). The interview lasted between 3 and 4 hours with breaks in-between to allow the patient some rest ad libitumOn a daily basis, only 1 patient used eye-tracking technique for communication; all other patients had no access and used blinking with the eyes to indicate responses to others (blink Morse code). One patient had previously used the Tobii eye-tracking system and one patient a sensor system by foot control, but no techniques were used at the time of the study.17 Progression was determined as total loss on the ALSFRS-R divided by the time since diagnosis in months (48 − current ALSFRS-R/months since diagnosis). None of the patients presented with severe cognitive or behavioural deficits certified by the trained psychologists O.H. and M.L. Minor cognitive deficits can be assumed to not interfere with well-being or medical decision-making.18To reduce patient load, clinical data were provided by caregivers where possible. Physical function was measured with the ALS Functional Rating Scale–revised version (ALSFRS-R) with a range of 0–48 where 0 defines no movement abilities of the extremities and complete anarthria.19 where the patient is asked to judge his or her global quality of life in relation to the worst  and best (+5) experience in one's own life (≥0 indicates positive QoL). Furthermore, subjective QoL was determined with the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting (SEIQoL-DW),20 where patients determine their 5 most relevant fields of QoL, the share of each field for the subjective QoL, and the overall satisfaction with this field. A SEIQoL index score can be determined .Measures of psychosocial adaptation were determined with standardized questionnaires. Patients were asked to evaluate their QoL and affective state (depressiveness) as measures of emotional and psychological adjustment to the condition. Global QoL was determined using the Anamnestic Comparative Self-Assessment (ACSA),21 which addresses the patient's affective state. Response options are fully agree (1) to fully disagree (4), adding up to scores 12–48, where scores >28 are indicative of clinically relevant depression.Depressiveness was determined with the ALS Depression Inventory–12 items (ADI-12),22 with a score ≥10 indicating a clinically significant wish.Patients indicated wish for hastened death with the schedule for attitudes towards hastened death with binary options (correct/wrong) to respond to 20 statements on wish for hastened death ,23In addition, patients indicated satisfaction with therapeutic techniques and machines they used for support of breathing (noninvasive and invasive ventilation) and nutrition (PEG) in a semi-structured interview based on previous questionnaires.24 Responses were provided on a Likert scale from never (1) to always (6).Patients' coping was determined with the Motor Neuron Disease Coping Scale, encompassing 22 items that can be subsumed under 6 subscales of support, positive action, independence, avoidance, information seeking, and positive thinking.For caregiver's evaluation of patient's well-being, ACSA and ADI-12 were used with the request to judge the patient's QoL and depressiveness from the caregiver's perspective with the instruction “What do you think would be the patient's response?”U test was used. All analyses were performed using IBM SPSS  version 21.0, 2-sided, and the significance level was set at p < 0.05. Due to the explorative nature of the study, no correction for multiple comparisons was applied.Data were analyzed for normal distribution a priori using the Kolmogorov-Smirnov test and statistics were selected accordingly. Spearman ρ correlation analyses were used to determine correlation coefficients between clinical data  and well-being . In order to detect group differences between patients with ALS and caregiver responses and between those with planned compared to unplanned therapeutic measures, Mann-Whitney Any anonymized data not published within the article will be shared by request from the corresponding author.Patients reported a median global QoL in the ACSA of 1 (Q = −2 to 3); 8 patients reported scores below 0 and the majority of 11 patients reported scores between 1 and +5. Median subjective QoL measured with the SEIQoL was 66 (Q = 58–88), with 17 patients reporting scores between 53 and 98; 2 patients reported a SEIQoL score below 50. Depressiveness measured with the ADI-12 showed a median score of 25 (Q = 22–30); 27% presented no signs of depressiveness, 47% presented with a dysthymic affective state, and 26% presented with clinically relevant depression.r < 0.03), progression , or physical function loss . Even more, those 5 patients (26%) patients with no residual physical function (ALSFRS-R = 0) reported positive QoL and no clinically significant depression . Tentatively, there was no association of QoL  or depression (ADI-12) with time since diagnosis , but no other association of coping strategies and clinical measures was found .Regarding coping strategies, information-seeking increased with time since diagnosis only . There were only 2 patients on NIV who had decided against invasive techniques of invasive ventilation and PEG . Five ofPatients presented with a median wish for hastened death of 4.5 (Q = 2 to 7.25); 2 patients had a clinically relevant wish for hastened death .U < 4.55 with p > 0.05).There was no difference in outcome measures between those who had planned invasive ventilation/PEG and those who did not with regard to depressiveness, QoL, coping strategies, or wish for hastened death  and underestimated QoL, but this difference was not significant .Caregivers significantly overestimated depressiveness 23 despite this devastating condition and dependence on (invasive) therapeutic devices, which supports previous results.12 In many studies, physical function is regarded as a measure of QoL, which is of course low in patients who are unable to walk, communicate, or undertake any activities. From the perspective of a healthy person, LIS is often among the most threatening scenarios one can imagine and prolongation of life is discouraged due to “fear of a locked-in state.”5 Our results indicate, however, that the human being is more than just physical function, and that subjective (hedonic) QoL can be preserved despite physical limitations. Accordingly, the most physically restricted patients in LIS from our study showed a great sense of well-being. As supported by social studies, despite objectively negative factors, these patients found their way to adapt to the condition (“well-being paradox”).25 This was even true for patients in LIS in Poland with much lower socioeconomic support than in many other Western countries, where patients with ALS have been shown to have even higher well-being compared to Polish patients.23 High religiosity in Poland might be suspected to facilitate and explain the reported positive well-being26 and strong will to prolong life. But the contrary has been shown in Polish patients with ALS compared to other European countries with a comparably low QoL and a general preference to decline life-prolonging treatments despite high religiosity.23Due to an overall lack of verbal or written communication, little is known about the psychological state,27 and requires some preconditions in ALS: it takes time  and strong social support28  so the patients in LIS presented here may represent a biased sample. Still, low physical function is not necessarily associated with low well-being, as outlined in previous work.12 Also, internal resources need to be accessible, which may explain more than 60% of the well-being variance in ALS.28 Often, patients with good psychosocial adaptation are also the ones who are well-informed, as shown in the current study: the longer the disease duration, the more information seeking.From previous research, we know that similar psychosocial adaptation may also happen in other fatal disorders 29; even more, the patients in the current study would volitionally choose them if there was a second choice. Accordingly, these most invasive techniques are the only way to secure life and thus they are cherished by the patients.2 In the currently studied group, patients presented with both a high preference for therapeutic devices and a low wish for hastened death, indicating a strong will to live, similar to previous studies of patients with ALS in less advanced stages of the disease.8 This might come as a surprise to healthy people, who are rarely confronted with these circumstances. Healthy people without experience with ALS are unable to correctly anticipate this fact8 and only experienced health care providers in the field of ALS and palliative care are able to correctly anticipate the emotional state30 and the disability paradox25 of a patient in LIS. Even the caregivers (mostly spouses) in the current study were unable to correctly anticipate the well-being of their loved ones and were unable to imagine that for the patient the condition was acceptable. We know from previous work that caregivers are physically, mentally, and financially heavily burdened by the circumstances of the disease31 and caregivers rather extrapolate from their own feelings so the worse their own mood, the worse they expect the patient's mood to be.4 Instead, many patients with ALS are “strong fighters” with a positive attitude despite their desperate physical condition.Patients in the current study were satisfied with the life-prolonging treatment they used, especially the invasive techniques of invasive ventilation and PEG, although most of them did not prefer these measures in the first place. This supports previous findings that once decisions for these means are taken, patients rarely change their preferences28 This capacity to adapt has been reported by other patients in LIS with different etiology and strong social support.12 This prerequisite is also a limitation of the current study: the patients interviewed for this study were those who had supportive families (who answered our invitation indicating the patients' willingness to participate). So the presented data might be true for patients who are interested in communicating their messages to the outside world or who have active and supportive families. None of this might be true for nonresponders. Furthermore, these patients had survived longer than all fast progressors, with mean survival time of 2 years or less.4 Thus, the presented conclusions are not valid for every patient with ALS. We lack information on the percentage of those who preserve well-being in LIS compared to those who do not. Yet, there is a subgroup of individuals with good preconditions who find their way to emotionally cope with the disease although it was not their primary choice to continue life with invasive techniques. Therefore, it is not true that only those occasional patients who initially favor invasive life-sustaining treatments are those who learn to live their life with invasive techniques. The reported 19 patients represent about 18% of all patients in LIS registered in the patient organization in Poland who have received invasive ventilation (12 in an emergency situation) with no means to discontinue and no other medical circumstances leading to death. The conclusion that a life in LIS is a life in misery in general as many healthy people anticipate7 is not necessarily true, as these tentative data from a highly selected sample show. We are unaware of psychosocial adaptation of the nonresponders within this study, so the presented data might not represent them. Longitudinal studies with patients on incident mechanical ventilation are needed to further analyze psychosocial adaptation in LIS in general. Finally, making decisions in ALS is not simply a matter of accepting invasive measures or not, and the presented data are unable to fully describe the highly complex situation of living with ALS. Yet the reported data from a Polish sample are representative for patients in LIS in many European countries with respect to coverage of costs  and a general right to take life-sustaining measures such as invasive ventilation and PEG.32Patients in LIS may find a way to readjust their expectations and emotionally adapt to the situation although a majority received invasive life-sustaining treatments in an emergency situation without any means to discontinue.Overall, there are subgroups of patients who end up in a LIS and who develop a positive mental attitude despite the devastating physical condition. Therapeutic devices that significantly extend life are favored by these patients and the wish for hastened death is low.


Activity monitoring is necessary to investigate sedentary behavior after a stroke. Consumer wearable devices are an attractive alternative to research-grade technology, but measurement properties have not been established.The purpose of this study was to determine the accuracy of 2 wrist-worn fitness trackers: Fitbit Charge HR (FBT) and Garmin Vivosmart (GAR).t or Wilcoxon signed rank tests (one- and two-sided). Subgroup analyses were conducted.Adults attending in- or outpatient therapy for stroke (n=37) wore FBT and GAR each on 2 separate days, in addition to an X6 accelerometer and Actigraph chest strap monitor. Step counts and heart rate data were extracted, and the agreement between devices was determined using Pearson or Spearman correlation and paired P<.001, respectively) but were significantly lower (P<.01). For individuals using a rollator, there was no significant correlation between step counts from the X6 accelerometer and either FBT  or GAR . Heart rate from Actigraph, FBT, and GAR demonstrated responsiveness to changes in activity. Both FBT and GAR positively correlated with Actigraph for average heart rate  and time in target zone ; these measures were not significantly different, but nonequivalence was found.Step counts from FBT and GAR positively correlated with the X6 accelerometer (ρ=.78 and ρ=.65, FBT and GAR had moderate to strong correlation with best available reference measures of walking activity in individuals with subacute stroke. Accuracy appears to be lower among rollator users and varies according to heart rhythm. Consumer wearables may be a viable option for large-scale studies of physical activity. Physical activity and exercise are recommended for stroke survivors because of the wide range of benefits that support recovery ,2. In adAs an outcome measure for research trials, for example, testing the effectiveness of exercise training, self-report measures are frequently used to collect information on free-living physical activity but are prone to inaccuracy  from recall bias ,17. As sHistorically, accelerometer-based activity monitors developed for research settings have been expensive and relatively difficult to use. For example, the Accelerometry for Bilateral Lower Extremities system, which accurately measures walking activity after stroke, requires trained personnel and a custom algorithm that operates on proprietary software to process the data . The comAccelerometers can be reliable and valid for activity monitoring in persons with stroke , whereasThis study was approved by the institutional research ethics board. Sample size target was 40 to represent the range of physical function typical of the subacute stroke population. Between June 2016 and March 2017, 37 adults attending in- or outpatient therapy for stroke at the Toronto Rehabilitation Institute provided written informed consent following an invitation to participate. Individuals were excluded if they were unable to walk without physical assistance from another person or if they were unable to understand written or spoken English. Participant characteristics are presented in Participants wore 4 devices for 5.5-10 hours consecutively: (1) Actigraph chest strap heart rate monitor worn under clothing; (2) wGT3X+ sensor ; (3) Model X6-2mini (“X6”) accelerometer ; and (4) consumer wearable device on the wrist of the less-affected arm: FBT  and GAR , which were worn on 2 separate days within 1 week. The wGT3X+ sensor is also capable of accelerometry but was only used in this study to store the Actigraph heart rate data. Although body location differs between devices, the placements are consistent with previous validation methods and regular functionality such that results are applicable to use in “real-life.”Study personnel visited inpatients on the stroke unit in the morning  to don the devices and then retrieved them at the end of the workday (~4 pm). Outpatient participants were met during the day and sent home wearing the devices, along with instructions to remove them before bed and to return them at their next visit or therapy session. A piece of Fabrifoam was used to affix the wGT3X+ sensor and X6 accelerometer to the ankle of the less-affected leg. Participants were instructed to go about normal daily activities and not remove the devices unless required , or unless they became a burden. Upon retrieval or return, participants completed a feasibility questionnaire asking about their experience and thoughts on the device . Part A Within 2 days of activity monitoring, the following tests were conducted for each participant during a short data collection session or as part of routine clinical care (data then extracted from patient chart): the National Institutes of Health-Stroke Scale (NIH-SS) , Berg BaMaximum heart rate was determined in 1 of the following 3 ways: cardiopulmonary exercise test as part of routine care ; estimation using published formulas  . FBT andHeart rate data, transmitted from the Actigraph chest strap monitor to the wGT3X+ sensor via Bluetooth, were transferred to a computer, initially processed in 60-second epochs using the ActiLife software version 6 , and exported to a text file. We noted that a number of Actigraph data points were physiologically improbable (<45 beats per minute); these were removed before further processing. To allow for comparison of heart rate measurement, we created time-aligned Actigraph and FBT/GAR data series. Actigraph heart rate data were averaged over 5-min epochs to compare with FBT values, which were manually transcribed into a spreadsheet from the Web application due to manufacturer’s restrictions in accessing raw data. GAR heart rate time series data were downloaded from the Web application as TCX files in 60-second epochs and converted into text files.Because a large amount of heart rate data were missing, we first examined responsiveness of Actigraph, FBT, and GAR measures to changes in activity. Step counts from the X6 accelerometer were tallied over 5-min (for FBT) and 1-min (for GAR) epochs and aligned with the heart rate data. Heart rate, as recorded by each device, was averaged over all periods of rest (epochs with zero steps recorded) and at 3 intensities of walking activity: 50-79%, 80-99%, and ≥100% of comfortable cadence . We then determined agreement between the Actigraph and FBT/GAR heart rate data. If epochs were missing for one device, the corresponding data were deleted for the other device. From these modified time series, average heart rate and time within a target zone (55-80% of maximum heart rate) were calculated for each device.t tests. Pearson or Spearman correlation and paired t tests or Wilcoxon signed rank tests, respectively, were used to compare average heart rate and time within the target heart rate zone from the Actigraph with those from the FBT and GAR. Analyses of heart rate data were conducted for the group as a whole and separately for those with and without diagnosis of arrhythmia ; only those participants with at least 60 min of valid heart rate data for both devices were included. For one-sided tests of equivalence, ±5% of the mean or median reference value was chosen as the upper/lower boundary limit; however, a clinically acceptable level of uncertainty is not clear from previous research. All statistical analyses were conducted in SAS version 9.2 , and alpha was .05.Step counts from FBT and GAR were compared with the X6 accelerometer using Spearman correlation (ρ) and Wilcoxon signed rank tests. Both step count analyses were conducted for the whole group and separately by usual gait aid. To test the responsiveness of the devices to changes in physical activity, average heart rate at each intensity was compared with resting heart rate using paired Bland-Altman plots were used to visualize interdevice agreement. The difference between the FBT or GAR data and the reference measurements for each participant were plotted against the average of the 2 values. The mean or median difference and its 95% CI or interquartile range were represented by lines on each graph.Out of all the participants, 5 chose not to complete the second day of the study; therefore, analysis of step count data was limited to 36 participants for FBT and 33 for GAR. Furthermore, 2 participants declined to wear the Actigraph chest strap, and there were less than 60 min of valid heart rate data on both devices for 4 (when wearing FBT) and 9 participants (when wearing GAR); therefore, comparison of Actigraph and wrist-device heart rate data was limited to 30 (for FBT) and 22 (for GAR) participants. Potential reasons for missing data are discussed below.Results of the step count analyses are presented in P<.001) and a moderate positive correlation between the X6 accelerometer and GAR . However, the FBT  and GAR  significantly undercounted steps compared with the X6 accelerometer. According to the equivalence tests, the median step count differences were not significantly less than the respective upper boundary limits (PU=.99).For step count measurement of all participants combined, there was a strong positive correlation between the X6 accelerometer and FBT  and no significant difference in step counts between devices in both the no gait aid  and single-point cane  groups. However, nonequivalence from undercounting was revealed by one-tailed tests . Conversely, for the rollator group, there was no significant correlation between X6 accelerometer and FBT step counts , and the FBT significantly undercounted steps compared with the X6 accelerometer . There was a moderate positive correlation  and no significant difference in step counts between the X6 accelerometer and GAR  for participants not using a gait aid, but measurements were not equivalent (PL=.77). Although there was a strong positive correlation between step counts from the X6 accelerometer and GAR in the single-point cane group , the GAR significantly undercounted steps for these individuals . In the rollator group, there was no significant correlation between X6 accelerometer and GAR step counts , and the GAR significantly undercounted steps compared with the X6 accelerometer .For the gait aid subanalyses, there were strong positive correlations between X6 accelerometer and FBT step counts , 95.3% (95% CI 93.3-97.2), and 75.1% (95% CI 63.8-86.5) of the time worn during monitoring, respectively. Data indicating responsiveness of heart rate to changes in activity are presented in P values≤.017). When Actigraph heart rate data were averaged over 5-min epochs, there was a trend toward higher heart rate with increasing activity, but the lack of significance for walking at 80-99% and greater than or equal to 100% of self-paced cadence was likely due to a large amount of missing data and consequent low sample size . GAR showed a significant increase in heart rate at 50-79% (P=.006) and 80-99% (P=.02) but not greater than or equal to 100% of self-paced cadence (P=.27), compared with rest.Both Actigraph (for 1-min epochs) and FBT showed significant increases in heart rate when participants walked at greater than or equal to 50% of their self-paced cadence compared with rest  as well as between GAR and Actigraph ; however, nonequivalence was revealed by one-tailed tests . There was a significant positive correlation of Actigraph with GAR  and FBT  for time in target zone. Time in target zone was not significantly different between FBT and Actigraph  or between GAR and Actigraph , but measurements were not equivalent .Results of the comparison in heart rate data between devices are presented in r=.64, P<.001) and time in target zone  improved slightly. Conversely, there were no significant correlations between Actigraph and FBT for average heart rate  or time in target zone  among participants with atrial fibrillation. Average heart rate and time in target zone were not significantly different between FBT and Actigraph for participants without arrhythmia or those with atrial fibrillation . According to the equivalence tests, none of the interdevice differences were significantly less than the upper or lower boundary limits . When participants without arrhythmia were analyzed separately, the correlation between Actigraph and FBT for average heart rate  and those with atrial fibrillation . Average heart rate and time in target zone were not significantly different between GAR and Actigraph for participants without arrhythmia or those with atrial fibrillation , yet there was no equivalence of measurements .The positive correlations between Actigraph and GAR for average heart rate and time in zone remained high for both those without arrhythmia . In terms of comfort, 94% (31/33) and 97% (32/33) of participants found FBT and GAR, respectively, to be somewhat or very comfortable, whereas 89% (33/37) and 91% (31/34) said the same for the X6 accelerometer and heart rate monitor, respectively. Overall, 7 individuals reported problems wearing the devices. Issues included general discomfort, trouble with doffing, and wrist strap feeling too tight. When asked about the level of confidence in their ability to don and doff independently, the average response, based on a visual analog scale from 0  to 10 (extremely confident), was 8.8 for all devices except for the chest strap (7.7). A large majority of participants said they would be likely or very likely to participate in a study that involved wearing the FBT , GAR , X6 accelerometer , or heart rate monitor  every day for 1 week. Some concerns included sleeping with the device and remembering to put it on.The main finding of this study is that FBT and GAR had a moderate to strong correlation with the best available reference devices for measuring walking activity in terms of step count and heart rate among individuals with subacute stroke. Accuracy varied widely according to mobility status and based on whether or not heart rhythm was normal. The consumer devices were well accepted by participants.In patients not using a gait aid, steps counted by the fitness trackers were not different from that of the X6 accelerometer; however, GAR was inaccurate (23.1% error) compared with FBT (10.3% error), and equivalence was not demonstrated. Neither device appears suitable for rollator users due to significant undercounting, and despite strong correlation of FBT with the X6 accelerometer for single-point cane users, accuracy was low (>10% error). Most studies on consumer wearables have been conducted with healthy adults, but, consistent with our results, overall validity of step counts with a tendency toward underestimation has been found . A diffeAlthough the high accuracy of chest strap monitors is well established, comparison of heart rate data was complicated by the low reliability of the Actigraph acquisition system. This may have been due to Bluetooth transmission problems, drying of electrode areas over time, or chest strap placement issues such as slippage through the day. Therefore, the positive correlations of the Actigraph with FBT and GAR could be over- or underestimated, and power to detect a difference in average heart rate or time in target zone was reduced. Considering data availability and responsiveness, FBT appeared superior, but heart rate measured by GAR was also sensitive to changes in walking intensity . In general, intensity of physical activity appeared to be relatively low according to total time in target zone and the sample size of higher cadence levels, although data may not have been available when participants walked quickly, which could account for the relatively high error associated with this parameter. For individuals with atrial fibrillation, FBT had lower agreement with the Actigraph (10.7% average heart rate error) than did GAR; however, it is not clear to which device the inaccuracy for this clinical subgroup can be attributed as no criterion standard was performed for comparison (see below). Some wearable heart rate monitors based on photopletysmography  have been evaluated with evidence of variable accuracy -38. In 2It may have been possible to minimize the large amount of missing data by performing the study in a laboratory with constant supervision of the participants, but, aside from being more resource-efficient, our design benefits from ecological validity. Devices were compared from different but typical and realistic body positions. The portability of the technology tested allowed for monitoring to take place under free-living conditions over many hours such that a range of activity levels could theoretically be captured. This precluded the use of “gold standard” measures such as electrocardiography and visual step counts to establish criterion validity. Clinically relevant variables were evaluated, and subanalyses revealed differences between groups to more precisely guide the interpretation of results. Although manual entry of some data was necessary for the purpose of this study, the commercially intended functions of consumer wearables provide information in a user-friendly format that could easily be applied in clinical or research settings.Overall, the strength of correlations and measures of accuracy suggest that FBT is valid for step-counting in individuals who do not use a gait aid, whereas both devices are suitable for group analyses that tolerate greater measurement variability. The tendency to underestimate steps and general lack of equivalence with reference standards should be considered. FBT was reliable, responsive, and accurate for recording nonarrhythmic heart rate. Assessing validity in participants with atrial fibrillation was limited by low sample sizes. These results, along with the generally positive feedback from the feasibility questionnaire, imply that fitness trackers may be a viable alternative to “research grade” activity monitors for large clinical trials. As more commercial models and algorithms are developed, consumer wearables should continue to be investigated for accuracy. The selection of a device for research or health care purposes will ultimately depend on the context, including patient population and primary outcome.


As prostate cancer (PCa) screening decisions often occur in outpatient primary care, a brief tool to help the PCa screening conversation in busy clinic settings is needed.A previously created 9-item tool to aid PCa screening discussions was tested in five diverse primary care clinics. Fifteen providers were recruited to use the tool for 4 weeks, and the tool was revised based upon feedback. The providers then used the tool with a convenience sample of patients during routine clinic visits. Pre- and post-visit surveys were administered to assess patients’ knowledge of the option to be screened for PCa and of specific factors to consider in the decision. McNemar’s and Stuart–Maxwell tests were used to compare pre-and post-survey responses.p = 0.018) from the pre- to post-survey, that there are factors in the personal or family history that may affect PCa risk from 34 to 47% (p = 0.012), and that their opinions about possible side effects of treatment for PCa should be considered in the decision from 47 to 61% (p = 0.009).14 of 15 providers completed feedback surveys and had positive responses to the tool. All 15 providers then tested the tool on 95 men aged 40–69 at the five clinics with 2–10 patients each. The proportion of patients who strongly agreed that they had the option to choose to screen for PCa increased from 57 to 72% (A brief conversation tool for the PCa screening discussion was well received in busy primary-care settings and improved patients’ knowledge about the screening decision. The current US Preventive Services Task Force (USPSTF) Prostate Cancer (PCa) Screening Recommendations for men aged 55–69 suggest individualized decision-making for the PCa screening decision after a discussion with a clinician of benefits, harms, and consideration of a patient’s values and preferences . For youEach item on the PCa conversation tool is scored from 0 to 3  with higher scores suggesting PCa screening may be beneficial. We tested the tool in three steps in five diverse urban and suburban primary care clinics. First, 15 primary care providers were recruited using an electronic mail announcement about the study to agree to use the tool for 4 weeks from June to July 2017 with up to 10 patients each. At the end of the 4 weeks, to assess provider experience with the tool, the validated Perceived Usefulness 6-item) and Perceived Ease of Use (6-item) scales (-item andp = 0.018) from the pre- to post-survey, that there are factors in the personal or family history that may affect risk for PCa from 34 to 47% (p = 0.012), and that their opinions about possible side effects of treatment for PCa should be considered in the decision from 47 to 61% (p = 0.009). When selecting from a list, the three most important factors in the PCa screening decision, the most frequent responses were age (65%), family history of PCa (42%), and concern about developing PCa (36%). Concern about sex life and leakage of urine were among the three most important factors for 10 and 18% of patients, respectively  that the current USPSTF recommends for individualized decision-making for PCa screening. However, we believe our findings across these age groups remain relevant to practicing clinicians.We demonstrated the usefulness of a brief PCa conversation tool in primary care settings to improve PCa screening conversations and to identify the need for further shared decision-making around the PCa screening decision. Future work will focus on the implementation of the PCa tool in additional settings and on the outcome of the screening decision after use of the tool.This protocol was approved by the Institutional Review Board at Cleveland Clinic. All patient participants gave verbal consent to participation in the study after discussion of the Institutional Review Board—approved study information sheet.AM-H designed the protocol, supervised the data collection and analysis, and drafted and revised the final manuscript. GH, EK, J-SJ, JB, XJ, and MK contributed to protocol development. GH administered the patient surveys and created the databases for the study information. NG administered the patient surveys. XJ performed the data analysis. AS reviewed the data and manuscript and made substantial contributed to revisions. All authors reviewed the final draft of the manuscript for important intellectual content.MK reports research funding from Novo Nordisk, Otsuka, Celgene, and Merck. He is a consultant for Novartis. AM-H, XJ, and JB report receiving research funding from Novo Nordisk and Merck. The remaining coauthors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Pseudomonas sp. NICB 9816-4. The oxygen sensors were used to measure the oxygen consumption rate of several variants during the conversion of styrene to 1-phenylethanediol. The oxygen consumption rate allowed the distinguishing of endogenous respiration of the cell host from the oxygen consumed in the reaction. Furthermore, it was possible to identify the higher activity and different reaction rate of two variants, relative to the wild-type NDO. The meander microchannel with integrated oxygen sensors can therefore be used as a simple and fast screening platform for the selection of dioxygenase mutants, in terms of their ability to convert styrene, and potentially in terms of substrate specificity.Selective oxidative functionalization of molecules is a highly relevant and often demanding reaction in organic chemistry. The use of biocatalysts allows the stereo- and regioselective introduction of oxygen molecules in organic compounds at milder conditions and avoids the use of complex group-protection schemes and toxic compounds usually applied in conventional organic chemistry. The identification of enzymes with the adequate properties for the target reaction and/or substrate requires better and faster screening strategies. In this manuscript, a microchannel with integrated oxygen sensors was applied to the screening of wild-type and site-directed mutated variants of naphthalene dioxygenase (NDO) from  The use of biocatalysts in industry is increasingly relevant, enabling the production of (new) compounds, some through the conversion of non-natural substrates . BiocataEscherichia coli, Pseudomonas sp., Trichoderma reesei) [Nowadays, around 60% of the industrial biocatalysis is performed using whole cell catalysts . Whole c reesei) ,5. In wh reesei) . This reBiocatalyst screening, especially for new processes or products or when involving non-natural substrates, is a complex task, involving different levels of screening . CharactMethods for biocatalyst screening and variant selection require proper design in order to maintain the association between the phenotype observed and the genotype measured . The scrThe majority of traditional screening approaches are performed in vitro, thus requiring extraction of the sample from the reaction mixture, or to stop the reaction to perform the quantification of the reaction components. On the other hand, in vivo screening (when the biotransformation/bioconversion is monitored in the microorganisms) broadens the number of parameters that can be screened and accelerates biocatalyst development and selection. However, in vivo screening strategies present some limitations associated with the host’s transformation efficiency and growth rate, but also the expression of the target enzyme, limitations in substrate uptake and intracellular background . Most assays tend to be specific  to adeq8 screened variants per day [Faster screening methods often involve the formation or consumption of a colorimetric, luminescent or fluorescent compound, which intensity is related with the substrate’s affinity or turnover rate . SpectroAnother screening method using reporters allows for an indirect measure of the characteristic target, not by the product or substrate of the bioconversion, but by the genetic reporter that encodes that phenotype. This approach is regarded as reaction independent, and the reporter may be colorimetric, fluorescent, bioluminescent or result in conditional survival, cell motility, acidification, or cell display. The activity of the measured reporter is connected to the activity of the target enzyme by interference at either the transcription , translation  or post-translational modification level , or even enzyme degradation or solubility  to the enzyme variant, and thus only soluble GFP variants are positively selected). Reporter-based screening using natural transcriptional regulators are usually extremely selective for the target product, having no false positives, but still requires a case-based choice of reporter and approach . A summary of the commonly used screening technologies is presented in 5 variants can be analyzed [Screening in agar plates usually occurs by formation or disappearance of color on the agar surrounding the incubated colonies or by color appearance on the colonies themselves due to bioconversion, providing a straightforward identification of positive colonies. Differences between activity or catalytic rates are, however, not easily achieved with this type of screening and usually up to 10analyzed . Couplinanalyzed . Metagen4 variants [Microtiter plates are the most frequently used screening devices, due to high-throughput and compatibility with a wide range of analytical techniques, from colorimetric approaches to GC, NMR or MS. Microtiter plates are, however, usually limited to libraries of up to 10variants  can be uvariants . This mevariants ) to tranvariants . Samorskvariants . Codexisvariants . Escherichia coli (E. coli). The best variants were selected with laser-induced fluorescence in a second device with a dielectrophoretic sorter and broken to isolate their plasmid content and use it for the next evolution cycle. Droplets generated this way, where the target compound can be optically read, can also be screened using FACS. The whole cycle of variants’ screening developed by Kintses et al. (2012) was performed in two days with the analysis of 107 droplets every 3 h [9 variants can be screened [Microfluidic approaches for the screening of biocatalysts have emerged recently. Microfluidics, due to the ease of flow manipulation and sensor integration, can potentially enable faster measurement and/or the monitoring of a higher number of parameters ,25,26. Fvery 3 h . This tescreened  or Strobscreened , for exascreened .Due to the ubiquitous presence of oxygen and its importance in bioprocesses, screening of biocatalysts in terms of oxygen utilization and/or influence is highly relevant. Of the different enzymes  that use oxygen as the electron acceptor during the reaction, the screening of oxygenase variants or mutants is specially complicated. This stems from the fact that the generated products do not cause a change in pH, color or fluorescence, and distinction between regioisomers is often the main objective of the screening program. Also, since most oxygenase substrates and products present poor water solubility, biotransformations are mostly performed in two-liquid phase systems. Furthermore, it is usually applied in whole cell systems and strains that express oxygenases require oxygen not only for the bioconversion but also for endogenous respiration, and so during the biotransformation the oxygen pressure needs to be maintained in order to allow the oxidation reaction to compete with respiration . Among oScreening of dioxygenases is thus usually achieved with more time-consuming and sensitive analytical methods, some of them mentioned above, such as GC or liquid-chromatography (LC) often coupled with MS, or even NMR . These aMeasurement of the initial oxygen consumption rate in the presence of substrate excess has also been used for characterization of oxygenases, namely dioxygenases ,36,37. AE. coli. The E. coli cells were used as resting cells, since the use of whole cell biocatalysts as resting cells, besides separating growth phase from catalysis, can moreover decrease the competition of cellular reactions such as oxidative phosphorylation with co-factor regeneration [Microfluidic systems can enable a good control of diffusion and gradient generation, due to the predominance of laminar flow and mostly diffusion-limited mass and heat transfer achievable at the micro-scale , thus prneration . Styreneneration ,45 and tIn this way, the main goal of this work was to test, as proof-of-concept, whether such a microfluidic system with integrated luminescent oxygen sensors can be used to accelerate the screening of dioxygenase variants, by identifying the earliest reaction time point where a difference in reaction rate can be observed. These reactions are usually performed for 20 h and the mutants evaluated by quantifying product concentration at the end of the reaction by GC ,44. By mE. coli JM109/DE3_pDTG141 was obtained by Julia Halder and Prof. Bernhard Hauer , Universität Stuttgart, Stuttgart, Germany) from Prof. Dr. Rebecca Parales  [All solvents , buffer components  and chemicals  were obtained from Sigma-Aldrich and Fluka , Carl Roth GmbH  and Alfa Aesar . CA, USA) .The general protocol followed to obtain the variants/mutants is described in Gally et al. (2015)  and furtE. coli JM109 (DE3) cells previously made competent using rubidium chloride, were thawed on ice for 5 min. Then, 1 µL of plasmid DNA for naphthalene dioxygenase  or one of the tested mutants was added to the cells and mixed gently by flicking the base of the eppendorf tube and shortly centrifuging. Cell transformation was performed by heat shock by placing the cells in a water bath at 42 °C for 90 s, followed by 2 min on ice. The heat shock treatment was followed by addition of 500 µL of LB medium to the cells and incubation for 1 h at 37 °C and 600 rpm. The competent cells were then plated on selective agar plates containing ampicillin (100 µg/mL) and incubated overnight at 37 °C. To generate the induced cells, one colony from the agar plates was used to inoculate a 2 L shaking flask with 500 mL of TB medium and 500 µL of ampicillin. The flask was incubated at 37 °C and 180 rpm until an optical density (OD600nm) of 0.8–1 was obtained. The cells were then induced with 0.1 mM of isopropyl β-d-1-thiogalactopyranoside (IPTG) dissolved in water and incubated at 25 °C for 16 to 18 h. Indole  and resuspended in 0.1 M potassium phosphate buffer (pH 7.2) containing 20 mM glucose.To produce induced biomass, . Indole c was addg and 4 °C. The cells were then spread uniformly in a petri dish and placed inside a freezer at −80 °C for up to 2 h. After freezing the cells were placed inside a freeze drier and freeze-dried overnight under vacuum conditions.To obtain freeze-dried cells, the harvested cells were resuspended in 0.9% sodium chloride (NaCl) solution and centrifuged for 15 min at 4000× cww/mL and 0.05 gcww/mL (cell wet weight) of the freshly prepared resting cells, or 66 mgcdw/mL and 33 mgcdw/mL (cell dry weight) of the freeze-dried resting cells, in 1 mL of 0.1 M phosphate buffer (pH 7.2) with 20 mM glucose. The cells for the oxygen measurements were also dissolved in 1 mL of 0.1 M phosphate buffer (pH 7.2) with 20 mM glucose, but at lower concentrations (0.005 gcww/mL to 0.05 gcww/mL). Glucose was added for in situ co-factor regeneration. Immediately, before starting the reaction, styrene (from a stock solution of 100 mM styrene in pure ethanol) was added to the solution to have 1, 1.5 or 2 mM styrene present for the reaction. The reaction was performed in 4 mL vials with a plastic cap (GC and oxygen measurements) or with a plastic cap with a rubber seal (oxygen measurements) in a tabletop orbital MRH11 Heating ThermoMixer  at 30 °C and 400 rpm (with 3 mm shaking diameter). The rotation chosen to perform the bioconversion was optimized by previously measuring oxygen concentration with reaction time using an oxygen sensor integrated in a syringe tip  connected to a FireStingO2 Optical Oxygen Meter . The rotation which allowed the reaction to be performed with a constant supply of oxygen was the selected one. Two reaction vials were used per residence time, one for GC validation and one for oxygen measurement.The cells for the reaction for gas chromatography (GC) validation were prepared by dissolving 0.1 gThe samples for GC analysis were prepared by centrifuging the cells and extracting the supernatant two times with 500 µL of methyl tert-butyl ether (MTBE). The reaction mixture was analyzed at different reaction times by measuring product (1-phenylethanediol) a concentThe used microfluidic channel is a glass and silicon chip developed and batch-produced by iX-factory  in Dortmund, Germany, and has been previously described in Ehgartner et al. (2016) . The micThe setup used for the measurement of the oxygen consumption rate in the cell samples is presented in ® XLP 6000 syringe pumps  with 250 µL syringes controlled with LabVIEW . The two syringes were connected to the meander microchannel by polytetrafluoroethylene (PTFE) 1.5875 mm (OD) × 1mm (ID) tubing (S 1810-12) , using Flangeless polypropylene (PP) fingertight 1.5875 mm (ID) fittings (XP-201) and flangeless ferrules (P200X) .The setup presented includes two Cavrov/v) in deionized water followed by solely deionized water. Deionized water was first pulled through the outlet and then the cleaning solutions were pushed through the channel’s second inlet. All the experiments presented in this work were obtained with the meander microfluidic channel placed in an upright position , and it was unknown the number of monitoring (residence time) points that would be required to perform the screening, it was deemed best to perform the reaction in a separate vial and only perform the measurement inside the microchannel. As such, per residence time point, 250 µL of the reaction mixture were sampled from the reaction vial and introduced inside the microchannel at the same flowrate. During the uptake, the oxygen concentration inside the channel was measured. The oxygen consumption rate values were determined from the slope of oxygen concentration during the sampling (oxygen concentration divided by measurement time). The variability of the oxygen measurement was quantified during the reaction with empty-vector cells and is presented through the error bars in Figures 6a, 7a, 8a and 9. In Figures 6b, 7b and 8b the error bars represent the reproducibility of the performed GC measurements.The oxygen consumption rate in the presence of substrate (1 mM of styrene) of empty-vector and wild-type (wt) cells was measured for the selected reaction times: 1, 3, 5, 15 and 30 min, as can be observed in To evaluate the microreactor’s performance in screening dioxygenase variants, the oxygen consumption rate in the presence of styrene (2 mM) of two NDO-variant containing cells (V260A and H295A) was measured in the meander microfluidic channel. Measurements of product concentration at the different reaction times was also performed in the GC.To test the device’s ability to distinguish reaction rate at different substrate concentrations, the oxygen consumption rate and product concentration of wt cells at two different styrene concentrations (1 mM and 1.5 mM) were also measured for the different residence times. No significant difference was observed in terms of oxygen consumption rate, which could be either due to the small difference in substrate concentration or possibly due to mass-transfer limitation of the substrate though the cell wall. The amount of product obtained was also similar for the two styrene concentrations tested, as can be observed in The influence of cell preparation on cell behavior was assessed by measuring the endogenous respiration of freshly prepared empty-vector cells and freeze-dried empty-vector cells in the presence of 2 mM styrene. As shown in E. coli cells have dimensions (<2 µm in length) smaller than the microchannels in the meander chip used, and so no significant obstruction of the channels was expected for the relatively diluted solutions used in the experimental work. Another concern involved the cell endogenous respiration rate, which in case of high respiration rates could rapidly consume the oxygen inside the reactor and thus prevent the measurement of the oxygen consumption due to the bioconversion. To address both issues, the cell density was optimized. This was achieved by introducing in the microreactor at a fixed flowrate different dilutions of the wild-type (wt) NDO containing resting cells without substrate present. The resting cells used were E. coli JM109 (DE3) cells which were transformed with a pDTG141 plasmid for NDO. The cell dilution considered optimal (0.01 gcww/mL) was the one which allowed a good distinction between slow and fast reaction rates, as shown in the The application of the meander channel with integrated oxygen sensors to the measurement of reactions involving whole cells encompassed several challenges. One of the main concerns was the possible clogging of the microchannels due to formation of cell clusters and its effect on fluid flow. Ideally, the meander microchannel with integrated oxygen sensors would function as an online monitoring system, where the inlet tube connected to the syringe pump would be submerged in the reaction volume, thus allowing sampling from the reaction mixture at given reaction times. This approach, however, was not followed in this study due to several difficulties that could arise from such setup. One of these issues is regarding the high volatility of the substrate (styrene), which could lead to a decrease in the concentration over time, since to sample the reaction mixture, the vial would not be completely sealed. The use of an adequate membrane or a septum could avoid this issue. The other concern relates to the fact that the reaction could be faster than expected and the initial reaction rate missed due to the time taken for sample uptake into the syringe and then introduction in the microreactor.To avoid these possible issues, a different sampling strategy was applied. The reaction was performed in two identical vials per residence time placed at the same conditions in the tabletop thermomixer. One of the vials was used for measuring the oxygen consumption rate and the other for product quantification in the GC. This enabled a direct correlation between the oxygen measurements and product concentration at the chosen reaction times. Furthermore, by performing the reaction this way, loss of substrate due to its volatility was minimized since the vial was only opened immediately before measurement. To address the possibility of a fast initial reaction rate, sampling uptake was performed through the outlet, instead of pushing the sample through the inlet see . ThroughThe chosen sampling strategy allowed measurement of a difference in the oxygen consumption rate between empty and wt cells, as can be observed in It is interesting to observe that 74% of the substrate is converted in the first minute of the reaction. The product concentrations obtained were equivalent to previous lab-scale assays where the reaction had run for 20 h with only end-point GC quantification . After 1The oxygen consumption rate of the two NDO-variant containing cells (V260A and H295A) was also measured in the meander microchannel. As can be observed in The other variant (H295A) presented an oxygen consumption rate closer to the wt cells, meaning that the oxygen consumption rate during the bioconversion is very similar to the endogenous respiration for this variant  . The comE. coli JM109/DE3 are half or lower than the one obtained for NDO from Pseudomonas sp. NCIB 9816-4. The lower oxygen consumption rate could be related to the already discussed diffusion limitations due to the cell membrane. It should, however, be taken into account that the data presented in this work indicates that the oxygen consumption rates measured for the NDO from E. coli JM109/DE3 are diffusion limited and so a linear relationship between oxygen concentration rate and substrate concentration does not occur.A direct comparison between the values retrieved from the literature and the ones measured in this study is difficult to perform since different enzymes, substrates, substrate concentrations and oxygen measurement techniques were used. There are one or two orders of magnitude of difference in the oxygen uptake between the different catalysts, but it is interesting to notice that the highest uptake rate was obtained for the natural substrate of the enzyme . When comparing biocatalyst performance for the same substrate (styrene), it should be noted that the measurement with whole cells was performed at a substrate concentration that is 10-fold higher relative to the corresponding substrate literature value. If a linear relationship between oxygen concentration rate and substrate concentration is considered, then the rate values obtained for the NDO from It is also worth mentioning the degree of variability in the data presented here, especially in oxygen consumption rate results which was not possible to quantify appropriately throughout the duration of the experiments. Data variability is most likely related to differences in the preparations of the cell solutions due to small variations in the amount of weighed cells, and thus the number of cells present. However, the variability in oxygen data obtained can also be inherent to the measurement itself, as also described by Jouanneau et al. (2006) with the observed discrepancies in the enzyme activities obtained when the oxygen assay was applied (polarographic assay using Clark-type oxygen sensors) .The presented microfluidic system cannot compete in terms of throughput with most of the screening systems discussed in the introduction. However, it can provide a different type of input (oxygen consumption rate and maybe other oxidative properties) than the above discussed screening platforms. In terms of throughput, the presented system can perform a single measurement every 10 min (including sample uptake and channel cleaning). This means that in a continuous operation, it could perform 47 single measurements in an 8 h working day and 129 single measurements in a 22 h working day . Considering the same reactions performed for this work (around 50 min for each one to be completed), per day we could perform 9 entire reactions in an 8 h working day or 26 entire reactions in a 22 h working day. Thus, to perform measurements every minute of a certain reaction vial, 10 microreactors of this type would have to work in parallel, and such a system is easily achieved with microfluidic units. Furthermore, by working in solution and not in droplet, such a system enables a direct measurement  from the reaction vial using a simpler microfluidic arrangement, if a more air-tight setup is assembled. This setup could be achieved by using stainless steel or a less permeable polymer as the tubing material, as well as more appropriate sealed reaction vial caps. The system can also be connected to one of the droplet-based systems discussed in the introduction to achieve a more comprehensive characterization of the mutants during screening.Moreover, two different screening approaches can be achieved with this platform: variant comparison or substrate comparison. The first approach, which was the one demonstrated in this study, compares the oxygen consumption of different variants relative to the same substrate. A higher rate indicates either higher variant activity or higher substrate specificity for the target substrate. In the second approach, the same cell type can be tested with different substrates. As mentioned, different rates would correlate with differences in specificity and activity. Furthermore, in this case, endogenous cell respiration of the cell without the target enzyme, or of the mutant at different substrate concentrations could further indicate possible toxicity concerns from the substrates being screened.It is also relevant to mention that the bioconversion at the reaction conditions and cell densities used has a relatively high conversion rate , which greatly contributed to the measurable oxygen consumption difference between the biotransformation and cell respiration. Since higher cell densities might lead to obstruction issues, there is a limitation on the use of this platform in terms of reaction rate to fast reactions only, which generate oxygen consumption rates higher than the host’s respiration rate. This limitation can be observed in E. coli cells used and distinguish respiration rate from oxygen consumption due to styrene oxidation by wild-type NDO. Additionally, the two tested NDO variants showed different oxygen consumption rates from the ones obtained with the wild-type. Variant V260A presented a higher oxygen consumption rate in the first 3 min of the reaction, corresponding to a faster styrene conversion (90% after 1 min). On the other hand, variant H295A showed a similar oxygen consumption rate compared to the wild-type NDO, which was equally maintained throughout the monitoring time (30 min), unlike the wild-type NDO, whose consumption rate decreased close to endogenous respiration levels after 15 min. H295A variant, generated however a smaller conversion rate with a steady increase during the reaction time, indicating a slower reaction rate than the other variants tested. Furthermore, this variant (H295A) allowed highlighting of a potential limitation in terms of reaction rates measurable by the microfluidic platform, identifying the reaction rate below which the microfluidic platform is unable to distinguish oxygen consumption due to the biotransformation from the endogenous respiration. The oxygen consumption rates measured with the meander channel with integrated oxygen sensors appear to be concordant with the values found in the literature.The presented results have demonstrated the potential of the meander microchannel with integrated oxygen sensors to function as a biocatalyst screening platform for oxygen-dependent whole cell biocatalysts. It was possible to measure the endogenous respiration rate of the The presented platform shows a considerable potential as a screening platform for mutants involved in oxidative reactions, especially enzymes with high reaction rates and fast bioconversions. The platform can achieve a throughput (129 single measurements or 26 reactions per day) comparable with the current approach, which can be further improved by adding more microfluidic systems in parallel and automating sampling. The current throughput of the platform is similar to the one obtained with the GC, where 129 reactions could be measured within 21.5 h, without time required for reaction preparation (which would imply a further 6 h).In the future, towards achieving a full characterization of the presented microfluidic system as a screening platform, it would be interesting to perform experiments with additional variants to detect relevant patterns or tendencies observable by using only the oxygen sensors. It would also be interesting to check whether phenomena such as product overoxidation beyond the desired product , substra