Stable and precise control of humidity is imperative for a wide variety of experiments. However, commercially available humidistats (devices that maintain a constant humidity) are often prohibitively expensive. Here, we present a simple yet effective humidistat for laboratory-scale applications that can be easily and affordably (<€250) constructed based on an Arduino Uno as microcontroller, a set of proportional miniature solenoid valves, a gas washing bottle, and a humidity sensor. The microcontroller implements a PID controller that regulates the ratio of a dry and humid airflow. The design and implementation of the device, including a custom driver circuit for the solenoids, are described in detail, and the firmware is freely available online. Finally, we demonstrate its proper operation and performance through step response and long-term stability tests, which shows settling times of approx. 30 s and an attainable relative humidity range of 10–95%The online version supplementary material available at 10.1140/epje/s10189-021-00062-5. In contrast to a thermostat, however, humidity is less easily adjusted; instead of heating the chamber by controlling a heat exchanger or Joule heating element, humid and dry air must be mixed in proper proportions and led into the chamber.Careful control of the humidity in a sample chamber is necessary for numerous experiments ranging from controlling molecular charge transport  to desigRelative humidity is a dimensionless number representing the ratio of the partial pressure of water vapour with respect to its saturation pressure:absolute humidity refers to the mass of water in a volume or mass of air. When not further specified, ‘humidity’ usually refers to relative humidity.Different inexpensive techniques have been developed to adjust the relative humidity. A commonly employed method is based on thermodynamic equilibria of water vapour with various salt solutions –5. This Another technique that is commonly utilised is local heating of a water bath in an enclosed chamber , 7. The Major advantages of electro-pneumatic devices are that no collection of chemicals is required, the relative humidity can be freely specified over a broad continuous range, equilibration is fast, and changing to a different value of humidity is as easy as pressing a button on the controller interface. However, the equipment is naturally more complex. Commercial solutions exist, but are often prohibitively expensive and/or not versatile enough because they are tailored specifically to a particular set-up, as noted by others –14.proportional solenoid valves controlled by a PWMBoulogne  describementclass2pt{minimThe principle of the humidistat presented in this work is based on mixing a humid (saturated water vapour) and a dry airflow in a chamber. By varying the ratio of the two flows, the full humidity range can be reached. Figure process variable (PV) to a user-specified setpoint (SP). The controller then seeks to close the error between the PV and SP by adjusting the control variable (CV), which acts as an input to the plant through the final control element (FCE), e.g. a valve. [PID  control is a common closed-loop control scheme. Its principle is to compare the measured quantity of interest called the a valve. u(t) is the control variable, and e(t) is the error. x is a bound variable within the integral. In practice, this continuous PID equation is discretised and the integral and derivative are approximated by finite difference methods.Three terms contribute to the CV: the proportional term, which is given by the error between the PV and SP; the integral term, which is given by the integral of the error over time; and finally the derivative term, which is given by the derivative (rate of change) of the error with respect to time. The CV is the sum of each of the three terms multiplied with a gain. This can be expressed by the following equation:In this case, the PV is the humidity, as measured using a sensor in the chamber. The user enters the desired SP on the controller interface, and the CV affects the control voltages presented to the solenoid drivers. The two valves are operated counter to each other: one of the valve’s control voltages is reversed. This way, the total flowrate is constant .Microcontroller: Arduino UnoHumidity sensor: DHT22Proportional miniature solenoid valves (2x): SMC PVQ31Solenoid drivers: Custom-builtHumidifier: Gas washing bottlesAn exhaustive bill of materials can be found in sect. 1 of the SI.The hardware implementation of the design outlined above consists of the following main components Fig. :MicroconFor the microcontroller, an Arduino Uno Rev3 is used. The Arduino Uno is one of the most popular boards from the Arduino line of inexpensive open-source microcontroller boards. The Uno is powered by an 8-bit ATmega328P MicroController Unit (MCU) and featuring sufficient flash memory, RAM, and input/output pins for this purpose.For the user interface, a Keyestudio LCD1602 Expansion Shield is used. This is an expansion board (or ‘shield’) that combines a We use a AM2302  for sensing the humidity. This is an simple, small, and inexpensive module that combines a polymer capacitance humidity sensor with a temperature sensor. The manufacturer specifies a 0.1% resolution, and a typical accuracy of 2%, diverging at the two extrema to 5% . IndepenThe specified sampling rate is only p. Smith  found thProportional solenoid valves are solenoid valves that provide analog control over the flowrate by allowing the valve to be partially opened, in contrast to ordinary  solenoid valves that are either fully open or fully closed.For regulating the flow of humid and dry air, two solenoid valves are used. Solenoid valves employ a solenoid that electromagnetically actuates the plunger of a valve. By using two proportional solenoid valves , the ratio of dry to humid airflow can be continuously varied, while the total flowrate can be kept constant.We use two PVQ30-series miniature proportional solenoid valves from SMC. These valves are normally closed direct-acting valves with a hysteresis of less than 10%. We selected the PVQ31-6G-16 model, which has an orifice diameter of olenoid. The solenoid valves cannot be powered by the Arduino directly, because the Arduino cannot supply the voltage and current required. Therefore, a simple electronic circuit is designed and built that drives the solenoid according to a control signal from the Arduino.The solenoids can be driven by a simple variable direct current, but in practice, PWM is more commonly used. This has multiple reasons: first of all, the Arduino Uno used does not have any true DC output capability, so an external DAC  would be required. Second, to some degree driving a solenoid valve by PWM or a smoothed PWM current is beneficial for reducing hysteresis in the valve because the ripple in the current helps to overcome the stiction (static friction) that lies at the basis of this hysteresis.The flowrate through a solenoid valve is controlled by the current flowing through the solenoid. The SMC PVQ31-6G-16 solenoid valve used requires ull flow . For driWater vapour for humid air is generated by passing air through gas washing bottles (DURAN laboratory bottle with Drechsel-type head with filter disc). Two bottles are connected in series to ensure sufficient water vapour saturation at higher flowrates.A controller class which ‘wraps’ a class implementing a PID loopUser interface using the buttons and LCDCommunication over serial (USB) with a Python script for real-time monitoring and loggingTemperature monitoring The PID class is heavily inspired by the Arduino PID library by Beauregard [The firmware for the MCU was written in C++ with the Arduino Core and the PlatformIO build system for AVR-GCC. It consists of classes with the following tasks:auregard .The humidistat can be used in fully standalone manner with the integrated buttons and displayed as a user interface. When monitoring and/or recording of the parameters  is desired, it is possible to connect to a PC over USB. A Python script for this purpose is included.The source is available online under a free license .Fig. 4ReThe humidistat was subjected to testing with a chamber Fig.  designedThe control scheme employed requires tuning of the proportional, integral, and derivative gains for proper operation. In this case, this is complicated by the nonlinearities exhibited by the plant. First of all, the flowrate through a solenoid valve is not exactly linear with the coil current. In our set-up, where two solenoid valves are operated counter to each other and the two flows are combined, this also means that the total flowrate does not add up to a perfectly constant value. This has implications for the dynamics of the system: for instance, the system’s response time is for a large part composed of the residence time of air in the chamber which is dependent on the flowrate. The solenoid valves also exhibit quite severe hysteresis arising from plunger stiction , 22. ThiIn addition to the three PID gains, two additional parameters are subject to adjustment: the interval (timestep) of the control loop and the minimum duty cycle. For the former, lower is usually better because it reduces dead time and improves stability, but it is limited by the temporal resolution of the sensor; if the timestep of the control loop is shorter than the temporal resolution of the sensor, the controller only ‘sees’ sporadic (large) changes in the PV which leads to undesirable behaviour. We use an interval of pressure . Hence, Despite the challenges in PID tuning resulting from imperfect actuators, reasonably satisfactory manual tunings were achieved Table .Table 1TCorresponding responses to step changes are shown in Fig. ng times . This isSettling times depend on the setpoint step size, but are at most on the order of The humidistat is able to achieve humidity values ranging from 10 to 95% at room temperature. The limiting factors for the extrema are the dryness of the feed air, efficacy of the humidifier, and air-tightness of the chamber. As we use a dry laboratory nitrogen supply as feed, this is not a limiting factor for the minimum humidity. However, in case that the air feed is not fully dry, this obviously imposes a limit on the lowest humidity achievable. When very low humidities are still desired, a desiccator can be added to ensure adequate dryness.Furthermore, we found that the chamber has to be adequately sealed in order to achieve extreme humidity values. When the chamber . The device was tested with a small chamber with a volume of Some improvements to this design are conceivable. An effective technique to improve performance and stability of the controller is to utilise cascaded PID control, where the humidity controller does not directly actuate the valves, but instead a cascade of control loops is set up, where the outer loop which controls the humidity regulates the setpoints of the inner loops. The inner loops control the flow through each valve using mass flow sensors. This essentially constitutes a mass flow controller. The benefits of such a control scheme stem from the fact that the inner flow control loop is much faster: its PV (the flowrate) can respond much more rapidly than the outer PV (the humidity in the chamber), yielding better dynamic performance. However, this would add some complexity and considerable cost.Another option that does not require more costly hardware is to employ a more sophisticated control scheme. Techniques exist for correcting for actuator imperfections such as valve stiction by augmenting the PID scheme with a stiction model-based compensator . AlthougA less-radical improvement would be to modify the voltage divider/RC-filter stage in the solenoid driver to not only scale the maximum voltage, but also shift the lowest voltage so it corresponds to the deadband in the solenoid valves, permitting usage of the full PWM range and thereby increasing CV resolution. This simple modification to the solenoid driver circuit would reduce the CV quantisation error, which leads to further reduction in the slight steady-state PV oscillations shown in sect. 4 of the SI.It is possible to reduce the number of components required by swapping the set of 2-port solenoid valves for a single 3-port  solenoid valve, simplifying the design. An additional benefit of this choice is that the nonlinear response is less problematic, because the total flowrate is always a linear combination of the two inlets. However, we were unable to source suitable 3-port proportional solenoid valves.Some improvement to accuracy and precision may be attainable by upgrading to a more accurate sensor, like the slightly more expensive Sensirion SHT71. This sensor offers tighter specifications and better reliability . It is aFinally, the Supplementary material 1 (pdf 1356 KB)Below is the link to the electronic supplementary material.


Here, an integrated experimental-theoretical approach is used to resolve the key electronic interactions in outer-sphere electron transfer (OS-ET), a cornerstone elementary electrochemical reaction, at graphene as-grown on a copper electrode. Using scanning electrochemical cell microscopy, and co-located structural microscopy, the classical hexaamineruthenium (III/II) couple shows the ET kinetics trend: monolayer > bilayer > multilayer graphene. This trend is rationalized quantitatively through the development of rate theory, using the Schmickler-Newns-Anderson model Hamiltonian for ET, with the explicit incorporation of electrostatic interactions in the double layer, and parameterized using constant potential density functional theory calculations. The ET mechanism is predominantly adiabatic; the addition of subsequent graphene layers increases the contact potential, producing an increase in the effective barrier to ET at the electrode/electrolyte interface. This combined experimental and theoretical study reveals the nature of electron transfer at graphene as grown on copper. The authors find that outer-sphere electron transfer occurs adiabatically with slower kinetics for multi- than for monolayer graphene. This situation prevails even for the simplest (textbook) case of outer-sphere electron-transfer (OS-ET), where the redox couple is typically at a distance of at least a solvent layer from the electrode surface2. Depending on the degree of electronic coupling between the redox couple and electrode, OS-ET is classified as adiabatic or non-adiabatic, and identifying the degree to which OS-ET lies towards either limit is of considerable fundamental interest3. Studies of OS-ET at electrode surfaces modified with self-assembled monolayers5 or a thin insulating oxide layer6, which separate the redox couple from the conductive electrode surface, naturally push OS-ET towards the non-adiabatic limit, as confirmed by experiment and theory in the past9. However, the degree of electronic coupling for OS-ET at more commonly used bare electrodes has been much more difficult to study with both theory or experiment. As a consequence, we lack convincing microscopic pictures for OS-ET2, the most elementary electrochemical redox reaction.Electrochemistry offers a unique possibility to modify both the thermodynamics and kinetics of redox reactions by changing the electrode potential. Much of our present theoretical understanding of electrochemical kinetics is based on rather rudimentary treatments and model Hamiltonians which describe the kinetics in terms of simple but physically and conceptually well-defined parameters. Extracting atomic-level insight from these models remains challenging, as the parameters are often treated merely as fitting parameters or obtained from first principles for simplified systems which cannot be addressed experimentally11. In contrast, in the non-adiabatic limit, the rate is proportional to the density of electronic states (DOS) near the Fermi level (moderated by the electronic coupling efficiency)14. As a consequence, experimental tests of adiabatic versus non-adiabatic theory have been made with different electrode materials, as a means of examining the DOS-dependence of ET kinetics18. An independence of ET rate constant on electrode material is considered to indicate an adiabatic reaction, whereas an electrode-material dependent rate constant, is argued to mean the reaction is non-adiabatic. Yet, reported DOS effects on ET kinetics are usually weak, with non-adiabacity deduced from rate constant ratios on different types of metal electrodes of <2 or <1.318. A general experimental issue for all such measurements is that OS-ET reactions are typically fast and close to the diffusion-limit of the experimental techniques employed18, making kinetic assignments difficult.In the adiabatic limit, the pre-exponential factor is independent of the electron tunneling probability between the electrode and the redox couple, and the OS-ET rate is predicted to become independent of the electrode material, provided the electronic interaction between the redox couple and electrode is sufficiently strong20. The necessity to account for the solvent, interface electrostatics, and the potential that is applied to the electrode, have made it difficult for theory and atomistic modeling to be reconciled with electrochemical experiments in the past, hindering atomic-level insight on OS-ET1. This situation has only very recently started to change due to advances in electronic structure theory21.It is increasingly recognized that true understanding of complex electrochemical reactions at the atomic level can only be reached by combining detailed experiments, theory, and simulations28 provide an interesting testbed for ET theory, as electrochemical activity can be modulated and controlled via the electronic interaction of the metal back contact/2D material33. This is especially the case for metal-supported graphene, a configuration with growing applications in electrocatalysis24, and for corrosion protection of metal surfaces by graphene35. Although many earlier electrochemical studies of graphene, both exfoliated and grown by chemical vapor deposition (CVD), considered material transferred to a Si/SiO2 surface44, the study of graphene as-grown on Cu not only provides a back contact for electrochemistry28, but negates the need for polymeric transfer to a substrate, which may significantly contaminate the graphene surface and the resulting electrochemistry45.Metal-supported 2D electrode materials47 on a contiguous monolayer (ML) of graphene/Cu. These different distinct structural motifs can be targeted directly with scanning electrochemical cell microscopy (SECCM), a technique that provides spatially-resolved measurements at different locations on an electrode surface54, while the response of unwanted pinholes can be detected55 and eliminated from the analysis. SECCM delivers reasonably high mass transport rates56, so that fast ET kinetics can be measured. The further use of co-located Raman microscopy and field emission scanning electron microscopy (FE-SEM) allow unambiguous characterization of the sites of the electrochemical measurements in a correlative multi-microscopy approach57. The Cu substrate surface crystallography upon which the graphene sits, can also be mapped with electron backscatter diffraction (EBSD) to determine any influence on the electrochemical response63.As-grown graphene on Cu presents small islands of bilayer (BL) and multilayer graphene3)6]3+/2+, a classic example of OS-ET68, which has been employed for studies of outer-sphere electrochemistry at graphene69, and does not adsorb on graphene at a detectable level70. SECCM multi-microscopy reveals that the ET kinetics is in the order ML>BL>multilayer graphene on copper. To explain this trend, we develop a theoretical model based on the Schmickler–Newns–Anderson (SNA) model Hamiltonian for ET accounting explicitly for the electrostatic interactions73 in the double layer. The SNA Hamiltonian is parametrized using constant potential density functional theory (DFT) and used to study the degree of (non-)adiabaticity of OS-ET from rate theory, allowing us to connect atomistic structure and potential-dependent properties with the OS-ET rate. Detailed analysis of data for ML and BL graphene indicates a predominantly adiabatic mechanism, where the addition of subsequent graphene layers increases the effective barrier, by partially screening the electrode potential. The methodology and combined experiment/theory/simulation analysis we outline should be generally applicable to many electrochemical processes particularly for metal-supported 2D materials.Herein, we address the question of adiabatic vs. non-adiabatic OS-ET to provide a new perspective on electronic control of electrochemistry at Cu-supported graphene. We consider the ET kinetics of 3+/2+ on graphene/copper electrodes. Experimental observations are analyzed by computing the SNA Hamiltonian parameters from constant potential DFT calculations of ML and BL graphene on Cu(111).To explicitly include key microscopic parameters in a single theoretical formulation, several extensions59 6]3+/2+ ET process at graphene/copper working electrodes of defined character, deduced from co-located correlative microscopy (vide infra) and the results are compared to the OS-ET model 6]3+/2+ and 50 mM KCl supporting electrolyte, with an AgCl-coated Ag wire in each channel to act as a quasi-reference counter electrode (QRCE)87. All potentials are quoted against this electrode, which had a stable potential88 of 56 mV vs. saturated calomel electrode (SCE). The advantage of the theta pipet probe is that the meniscus landing of the SECCM tip is sensed via the ion conductance current that flows across a bias between the 2 QRCEs and so the meniscus cell can be landed on any surface48. Moreover, the ion conductance current across the meniscus informs on the stability and reproducibility of meniscus contact from point to point89 (vide infra).Voltammetric SECCM59 Fig.  is emplodel Fig. . Dual chvide infra), starting from a potential of 0 V, with the potential swept linearly with time to −0.6 V, and then swept back to 0 V. These measurements can be presented as a potentiodynamic movie  scanned by a theta pipet (diameter ~700 nm) is considered first. A cyclic voltammogram (CV) was recorded at each position in the array  indicates high-quality graphene90. These data enabled the co-located potentiodynamic maps and movies to be correlated with the graphene character.Area 1 was characterized with FE-SEM  vs. Ag/AgCl QRCE (beginning of CV), (b) −0.33 V  and (c) −0.60 V (limiting current region). The white outline on each map demarks the boundary between ML and BL graphene, identified from the SEM image. At 0 V (a), most of the surface shows little electrochemical activity , but there are a few pixels with a significant positive current (marked with white rings), attributed to pinholes in the graphene layer that exposes the Cu foil to the electrolyte solution, resulting in anodic dissolution in the chloride medium at this potential. CVs at these pinholes were extracted and examined, as exemplified by the responses in Supplementary Fig. Current density maps taken from Supplementary Movie EWE = −0.33 V  vs. substrate working electrode potential, EWE, for the ML and BL regions are shown in Fig. 3)6]3+/2+ redox process is faster at ML than BL graphene on copper, as also evident from the distributions of the half-wave potential, E1/2  indicates that the measurements are reasonably consistent across the different graphene areas. These data were obtained with a pipet of diameter ~1 μm  > −0.378 ± 0.017 V  > −0.409 ± 0.025 V  graphene derived from a histogram of E1/2 values  numerical model , providing confidence in the kinetic assignment.Analysis of the 93, but is different with oxygen present due to oxygen intercalation between Cu(100) and graphene, forming a (√2 × 2√2)R45° superstructure, which does not occur for Cu(111). As a consequence, and because graphene preferentially aligns with the Cu(111) surface, we focused exclusively on this case for atomistic modeling (vide infra)93.While the ratio of ML to BL kinetic ratios in areas 1 and 2 is similar, there is a difference in the baseline ML kinetics in the 2 areas. EBSD measurements of the copper surface were performed on areas 1 and 2 to elucidate the underlying crystallography of the support . The complete computational details of our calculations are summarized in Supplementary Note We seek to understand the difference in OS-ET rates of ML and BL graphene on copper, and as a model system undertake DFT calculations of graphene layers adsorbed on a single-crystal Cu(111) surface see Fig. . In this96. In the case of graphene on copper, we find almost negligible DOS contribution of ML graphene at the Fermi level and only little contribution of the outer graphene layer in BL graphene, which likely is not strongly coupled to the metal. We therefore find it highly unlikely that a similar conclusion as for Ni can be reached in the case of copper and we prefer the conclusions that electrons are transferred from copper.When comparing the DOS of the copper electrode functionalized with ML and BL graphene, we find that, in both cases, the graphene states do not significantly contribute to the DOS at the Fermi level. This is true when exposed against vacuum , defined as97Whereas DFT calculations show that graphene adsorption does not dramatically change the electronic structure of the electrode at the Fermi level, adsorption of subsequent layers of graphene has a significant effect on the electrostatic potential drop above the electrode. As shown in Fig. To assess the ability of DFT to accurately predict the electrode potentials, we compare the computed and independently measured Volta (or contact) potential difference of a typical graphene on copper substrate, and the results are given in Fig. i.e. a bias voltage of −0.33 V vs. Ag/AgCl QRCE; the ML graphene electrode is more negatively charged than the BL electrode. As a consequence, the electrostatic potential of the electrode felt by the redox couple decays more gradually into the solvent for ML graphene than it does for BL graphene 6]3+/2+ is half-filled for both systems at the transition state and hence 3)6]3+/2+ is an outer-sphere redox couple, we can assume that the solvent rearrangement contributions to Eq.  the electrode results in the rate ratio of 7.5 (2.7) which shows that the predicted values for the adiabatic case are robust and close to the experimentally measured ratios regardless of uncertainties that may arise from the standard approximations inherent in our DFT treatment.Next, we combine the insight gained from constant potential DFT data with the electrochemical rate theory and the SNA model Hamiltonian to understand the nature of the ET and why the ET rate changes as a function of the number of graphene layers. The use of SNA and general electrochemical rate theory enables us to consider both adiabatic and non-adiabatic OS-ET kinetics, and to discriminate between these two mechanisms. In the strong molecule–metal coupling regime, the reaction is adiabatic and the difference in rates is exclusively due to the changes in the activation energy 98 which demonstrated that the potential of zero charge and crystal facet dependent work function played a decisive role in Co[NH3]63+ reduction on a range of Au single crystal electrodes in 50 mM KCl electrolyte solution. An opposite conclusion was reached by Iwasita et al. for strong electrolyte solutions (1 M KF) for a range of electrode materials15. We also note that electrostatic potential profile obtained with the Solvated Jellium Model (SJM) model is in good agreement with more refined modified Poisson-Boltzmann models101 which faithfully model the double-layer capacitance and electrostatic potential in 100 mM electrolytes until the surface charge density is above 0.04 e/Å2 (in our work the surface charge is below ~0.01 e/Å2). Another possible complication arises from the presence of Cl− in the electrolyte and possible ion-pairing, which can affect the ET kinetics. This can be addressed using the Fuoss model102 of ion-pairing, which was adopted by Brown and Sutin to address ion-paring effects in the exchange ET of Ru-complexes (incl. Ru[NH3]63+ 103). Within this semi-quantitative model, the ion-pair formation affects both the ET rate prefactor and the barrier. The former is constant for a given redox couple-electrolyte system affecting only absolute values and is cancelled when considering rate ratios as done herein. The formation of ion pairs modifies the reaction barrier through electrostatic interactions and within the SNA framework the absolute rate constants would change by a factor of 2 when going from 0 mM to 100 mM electrolyte. However, the contribution from ion pairs cancels out when computing the ratio of rates at ML and BL graphene and does not affect our analysis. Hence, our computational model is expected to accurately capture the electrostatic potential double-layer and model the experiments carried out in 50 mM KCl.The above analysis highlights the importance of the electrostatic potential in modulating adiabatic OS-ET within the double layer. This conclusion is supported by the studies of Hromadová and Fawcett3)6]3+/2+ and the metal differs by about 3 Å between ML and BL graphene104. If the ET had a significant non-adiabatic contribution, we would expect this to affect the kinetics and be reflected in the distance-dependent coupling constant, To determine the adiabaticity of the OS-ET, the prefactor was addressed next (see Supplementary Note 3)6]3+/2+, whereas the ET is still adiabatically conducted between the redox couple and the underlying Cu metal support. This conclusion could only be reached with the integration of the experimental design (where the effect of graphene on ET at the Cu electrode is assessed side-by-side at ML and BL motifs), microscopic SNA model Hamiltonian and rate theory, and  DFT simulations.As described in Supplementary Note 3)6]3+/2+ couple.Knowledge of how the structure and composition of an electrode affects the mechanism and kinetics of electrochemical reactions is of vital importance in the design of electrochemical devices with applications spanning energy storage, electrochemical sensors, electrocatalysis, and biochemical analysis. In this paper we outlined that even for the simple case of OS-ET, it has proven challenging to answer the basic question of adiabatic vs. non-adiabatic control in past work. Taking graphene as-grown on copper as a model 2D material/metal-supported electrode, we have shown that the combination of voltammetric SECCM, with complementary co-located microscopy techniques, microscopic theory, and DFT calculations, constitutes a powerful approach to determine mechanistic details that govern ET kinetics of the Cl3, purity 99.9%) were purchased from Sigma Aldrich. Fresh solutions comprising of 1 mM [Ru(NH3)6]Cl3 in 50 mM KCl electrolyte were prepared prior to each experiment. Silver-chloride coated silver (Ag/AgCl) wires were used as quasi-reference counter electrodes (QRCEs) for SECCM88. All potentials are reported against the QRCE in the solution defined ), referred to herein as Ag/AgCl. High quality n-type silicon/silicon dioxide substrates  were obtained from IDB Technologies Ltd. Copper foil was purchased from Alfa-Aesar .All aqueous solutions were prepared from ultrapure water . Potassium chloride  and hexaamineruthenium (III) chloride  hydrogen, followed by exposure to a gas mixture of 10 sccm hydrogen and 3 sccm methane (purity 99.95%) for a growth time of 25 min. After cooling under hydrogen to room temperature (over a period ca. 1 h), the graphene covered copper foil was removed from the furnace and stored. Before study, the rear (Cu) surface of the Cu/graphene sample was fixed to a gold (300 nm) layer evaporated on an Si/SiO2 wafer, using silver paint . The sample was then connected to a Cu wire, ready for electrochemical measurements.Graphene substrates were grown on polycrystalline copper foils as reported previously107. An important point to bear in mind for SECCM studies of graphene39, and also for other local electrochemical measurements30, is that because all of the different structural motifs are assessed on the same sample, they all have the same history. The [Ru(NH3)6]3+/2+ process displays fast kinetics  on carbon electrode materials even after extensive exposure to ambient atmosphere109, and so we can be confident in the ratio of ET kinetics measured at ML and BL graphene. Nonetheless, even if surface contamination were to provide some charge transfer resistance, it would have a similar effect on ML and BL domains and so the effect would be to make the ratio kML/kBL (slightly) larger, which does not affect the conclusions and analysis  using a Sutter P-2000 laser puller . The total inner diameters of pipets were in the range 600 nm–1 μm, determined accurately by scanning electron microscopy (SEM) using a Zeiss SUPRA 55FE-SEM. The outer walls of the pipets were rendered hydrophobic by silanization with dichlorodimethylsilane , by flowing argon through the pipet to protect the inside from silanization.110. The Warwick Electrochemical Scanned Probe Microscope platform used herein centered on a bespoke LabVIEW program controlling a National Instruments Field Programmable Gate Array (FPGA) card (model PCIe-7852R), to output voltage signals to synchronously control the Physik Instrument xyz piezoelectric positioning system and the SECCM electrochemical cell, and acquire the resulting data . Referring to Fig. V1 (200 mV) was applied between two Ag/AgCl QRCEs inserted into the tapered pipet filled with 1 mM [Ru(NH3)6]3+ as the chloride salt, in 50 mM KCl electrolyte, to generate an ion conductance current (iDC). The z-position of the pipet  was modulated sinusoidally  by a lock-in amplifier , generating an alternating current component in the ion conductance current at the same frequency (iAC). iAC is negligible when the pipet is in air, but has a measurable amplitude when the pipet is in meniscus contact with the surface110. A threshold (setpoint) value of iAC magnitude (6 pA) was set to position the meniscus on the sample. The effective potential of the sample (working electrode) with respect to the QRCEs (EWE) is −(V2 + V1/2), which could be changed via the value of V2 while maintaining the QRCE bias voltage, V156. The electrochemical current (density) flowing through the sample is denoted as iWE.The setup and instrumentation for SECCM has been reported in previous papers from our group59. The pipet was approached towards the surface at a speed of 0.3 μm s−1, and once the meniscus had contacted the surface, the pipet was held in that position for 0.1 s before a potential sweep (0.5 V s−1) was applied, from the starting potential of 0 V to –0.6 V and back to the starting potential to generate CVs for [Ru(NH3)6]3+ reduction. The pipet was then retracted a distance of 1.5 μm at a speed of 2 μm s−1 to break the meniscus contact with the working electrode surface and the pipet was moved to the next pixel with a hopping distance of 600 nm in the x-y plane at a rate of 1 μm s−1. This protocol was repeated at each pixel in the area of interest.SECCM was implemented in a voltammetric hopping modeThe potential waveform output from the FPGA had a resolution of 5 μV and electrochemical current-potential data were recorded every 3 mV. Potentiodynamic movies, containing 121 frames, were plotted every 10 mV. All data analyses were performed with Matlab .111. Maps of the DC ion conductance current (between the 2 QRCEs across the meniscus), obtained during SECCM measurements, reveal information on the meniscus stability and shape108. DC ion conductance current histograms obtained from SECCM scanning of area 1 at −0.1 V (foot of the CV) and −0.6 V (diffusion-limit region) are detailed in Supplementary Note vide infra)56.Current maps herein are presented as current density to allow comparison between tips of different sizes. Meniscus landing did not leave sufficiently clear footprints to allow SECCM electrode areas to be measured directly, and so to estimate the current density we used the tip size, which is a good approximation of the contact area for SECCM measurements on graphene, graphite, and metal and metal oxide surfacesFE-SEM. The morphology of the scanned area (particularly to identify graphene grains) was imaged on a Zeiss Supra 55-VP FE-SEM by using the in-lens secondary electron detector, operated at 10 kV.vide infra). The full width half-maximum (FWHM) values (2D) of ML and BL graphene for the 2 areas were analysed by choosing 60 pixels randomly in each graphene region and the corresponding histograms were plotted.Raman spectra of graphene were obtained with a Renishaw Invia micro-Raman spectrometer, using a diode-pumped solid-state laser (Renishaw RL523C50) with an excitation wavelength of 532 nm. Spectra were obtained at 100% power with an integration time of 10 s. The same parameters were used for Raman spectroscopy mapping of graphene/Cu samples, with a 50× lens and a step size of 1 μm. For imaging purposes, the peak intensities of the 2D peak and G peak were extracted for each pixel to provide the 2D/G ratio that was plotted as maps  imaging with a Nordlys F (Oxford Instruments) camera. Measurements were performed at an accelerating voltage of 20 kV, with a collection step of 0.4 μm, with the sample tilted at 70°. Data analysis was performed using Aztec 3.1 (Oxford Instruments).tight basis set definition112 and the GPAW code115 using the projector-augmented wave method116 . We modeled the graphene adsorption on a Cu(111) surface using a dispersion-inclusive Perdew-Burke-Ernzerhof (PBE) functional that correctly accounts for screening effects in the metal substrate (PBE + vdWsurf)95. Slab models for a clean Cu(111) surface, and for 1, 2, or 3 layers of graphene on Cu(111) were relaxed in vacuum and under electrochemical conditions using a fixed potential, grand-canonical DFT formalism99 using the solvated jellium approach118 and a continuum solvation model for water119. Density of states (DOS) and other properties were calculated for the different electrodes in vacuum, against a potential of zero charge, and at a fixed bias potential relevant to the experimental measurements. To ensure the choice of unit cell did not affect the results, quantities such as the DOS, contact potential and electrostatic potential decay were recalculated using a different unit cell to establish convergence. Further computational details can be found in Supplementary Notes Density functional theory (DFT) calculations were performed with the all-electron atomic-orbital code FHI-aims using the default Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2


Social communication via instant messaging (IM) and social networking (SN) apps makes up a large part of the time that smartphone users spend on their devices. Previous research has indicated that the excessive use of these apps is positively associated with problematic smartphone use behaviors. In particular, image-based SN apps, such as Instagram (Facebook Inc) and Snapchat (Snap Inc), have been shown to exert stronger detrimental effects than those exerted by traditional apps, such as Facebook (Facebook Inc) and Twitter (Twitter Inc).In this study, we investigated the correlation between individuals’ tendencies toward smartphone use disorder (SmUD) and objective measures of the frequency of smartphone usage. Additionally, we put to test the hypothesis that the pathway linking the frequency of actual smartphone usage to self-reported tendencies toward SmUD was mediated by the increased frequency of IM and SN app usage.We recruited a sample of 124 adult smartphone users  and collected objective information about the frequency of smartphone and SN app usage over 1 week. Participants also filled in a self-report measure for assessing the multiple components of tendencies toward SmUD. Bivariate associations were investigated by using Spearman correlation analyses. A parallel mediation analysis was conducted via multiple regression analysis.The frequency of smartphone usage, as well as the use of IM apps , Facebook, and image-based apps (Instagram and Snapchat), had significant positive associations with at least 1 component of SmUD, and the cyberspace-oriented relationships factor exhibited the strongest associations overall. We found support for an indirect effect that linked actual smartphone usage to SmUD tendencies via the frequency of the use of image-based SN apps.Our novel results shed light on the factors that promote SmUD tendencies and essentially indicate that image-based SN apps seem to be more strongly associated with problematic smartphone behaviors compared to IM apps and traditional SN apps, such as Facebook. Web-based social communication via instant messaging (IM) and social networking (SN) apps makes up a large part of the time that smartphone users spend on their devices, and this time exceeds the time that smartphone users spend on other activities, including being productive and gaming . Among tdisorder, which is used to describe behavioral addictions in the International Classification of Diseases, 11th edition  as well as those in previous literature related to this area of research [International Classification of Diseases, 11th edition. The criteria suggested are (1) scientific relevance for clinical relevance, (2) theoretical embedding within addiction frameworks, and (3) empirical evidence for the validity of mechanisms that underlie addictive behaviors. In terms of a potential social networks use disorder, these criteria are widely met, although the scientific evidence for clinical relevance and functional impairment are still less convincing compared to the evidence for other disorders resulting from addictive behaviors, such as gaming disorder [Previous findings have indicated that the excessive use of SN apps on smartphones is positively associated with problematic behaviors related to the use of devices in general -8. Theseresearch ,10, we cresearch , similarresearch ,13. Furtdisorder .It is noteworthy that although we distinguish between messaging and SN apps in this paper, SN can be seen as an umbrella term that also includes messenger apps . For ourTo build on these findings, in this study, we aimed to examine the existing associations between objective records of smartphone, IM platform, and SN platform activity and individual differences in self-reported SmUD. More specifically, we tested the following hypotheses:Hypothesis 1: Significant associations exist between self-reported tendencies toward SmUD and objective measures of the usage of the smartphone and IM and SN platforms.Hypothesis 2: The association between self-reported tendencies toward SmUD and overall smartphone usage is mediated by the frequency of IM and SN app usage .Based on the existing literature about theoretical considerations and previous empirical findings -8, we exObjective Smartphone Activity Data section), how data were recorded, who was granted access to their data, and where data were saved and analyzed. Participants were informed about their right to request the deletion of their data at any time during this study. All participants provided digital informed consent via the app prior to their participation in this study. In order to facilitate the installation process, participants were invited to the laboratory, where scientists guided the participants through the Insights app installation process. Therefore, no problems with the installation process were observed. The study was approved by the local ethics committee of Ulm University, Ulm, Germany. It should be noted that in this study’s data set, there was an overlap among other publications—there was 1 study that investigated links between call variables and personality [Our sample consisted of individuals who were recruited among students at a German university campus by using a convenience sampling strategy. The inclusion criteria for this study were legal age (18 years and over) and current ownership of a smartphone. Participants were recruited between March 2017 and August 2018 and consisted of 124 individuals with a mean age of 23.84 years  and a majority of female individuals . Participants gained university credits or monetary compensation for their participation. With regard to education level, of the 124 participants, 2 (1.6%) reported having finished secondary school, 10 (8.1%) reported holding a vocational baccalaureate diploma, 92 (74.2%) reported holding an A-level diploma, 3 (2.4%) reported holding a degree from a university of applied sciences, and 17 (13.7%) reported holding a university degree. Prior to their participation in this study, participants were provided with detailed information on the aim of this study, all variables that were tracked by the Insights app . Based on considerations about the potential incomparability of data that are collected during different time frames and the need to maximize our sample size for this study, we decided to limit our analyses to smartphone data that were collected during the first week (7 days) of smartphone data collection. Given this time frame, we retrieved the following information: the number of smartphone sessions that were started by the user unlocking the smartphone screen  and the number of sessions on IM apps , traditional SN apps , and image-based SN apps . Participants were coded as having 0 sessions on the app if they either had the app installed on their smartphones and did not use it or did not have the app installed on their smartphones. We followed such a strategy to conduct analyses on the complete sample and to take into account that not each app of interest was installed on each phone. The Insights app allowed for the tracking of both the screen unlock events and screen on events of Android smartphones; each event represented an indicator of users’ active use of their smartphone. However, while both screen unlock events and screen on events were triggered through users’ interaction with their smartphone’s hardware , screen on events could also be triggered by app notifications (depending on the smartphone settings). Due to this potential confounding factor, for the purpose of this paper, analyses were presented by using the screen unlock event variable. However, for full transparency, we presented and commented on the associations between screen on and screen unlock events and app session and SmUD variables in Based on the collected data, WhatsApp was the most used app during the investigated time frame , followed by Facebook , Messenger , Instagram , Snapchat , and Telegram . Of the 124 participants, 123 (99.2%) used IM apps and 67 (54%) used image-based SN apps. In turn, we found that no participants used the TikTok app; however, it should be noted that at the time data collection started for the present study, the TikTok app was called “musical.ly” , and wasWe administered a German version of the Smartphone Addiction Scale (SAS) , which cP was <.05.First, we computed descriptive statistics (the mean and SD of the number of app and smartphone sessions). Second, we calculated Spearman correlation values between the number of app and smartphone sessions and age and between the number of such sessions and indicators of tendencies toward SmUD . Mann-Whitney U tests were performed to evaluate the association between gender and smartphone and app session variables. In all inferential tests, results were considered significant when P<.05). Analyses were performed with SPSS 23 (IBM Corporation) by using the Process macro [Third, we performed a mediation analysis via multiple linear regression models for predicting the overall tendency toward SmUD. The diagrams for the examined models are shown in ss macro .P=.53), Messenger (P=.21), and Telegram (P=.72) sessions, had a significant negative correlation with age. We also analyzed correlations between the objectively recorded SN app, IM app, and smartphone session variables and the indicators of tendencies toward SmUD variables. The daily life disturbances score had positive correlations with the number of Instagram sessions, Snapchat sessions, image-based SN app sessions, IM app sessions, and overall smartphone sessions, but not with the number of Facebook and each specific IM app sessions. Positive anticipation, withdrawal, and the general tendency toward SmUD  had positive correlations with all of the app and smartphone session variables except for the number of Facebook and Telegram sessions. Cyberspace-oriented relationships had moderate positive correlations with all app and smartphone session variables except for the Telegram session variable. The overuse subscale scores positively correlated with the number of participants’ Snapchat, Instagram, image-based SN app, and Messenger sessions and the number of overall smartphone sessions. Finally, tolerance positively correlated with the number of participants’ Snapchat, Instagram, image-based SN app, and IM app sessions (tolerance did not show significant correlations with sessions on specific IM apps) and the number of overall smartphone sessions.The results of Mann-Whitney U  tests inWe also examined the total effect and mediation models for analyzing the association between the number of smartphone sessions and participants’ general tendency toward SmUD . The results of total and direct effects are shown in The examination of indirect effects  showed tThis study investigated the associations between individual differences in self-reported tendencies toward SmUD and a set of objectively measured smartphone activity frequency and IM and SN app usage indicators. First, we explored the hypothesis that objectively measured indicators of smartphone and app usage would have a significant association with self-reported tendencies toward SmUD. Our data support this hypothesis. From a purely quantitative standpoint, based on our findings, the association between actual smartphone usage (assessed via screen unlock events) and overall tendencies toward SmUD is moderate (ρ=0.38) and appears to be close to the upper limit of what has been reported in previous studies that used objective smartphone data ,25. FurtThe overall use of IM apps was positively related to all of the components of tendencies toward SmUD except for the overuse component. In turn, Facebook use was only associated with the cyberspace-oriented relationship component of SmUD. Moreover, among the different components of tendencies toward SmUD, the cyberspace-oriented relationship score had the strongest association with the usage of both IM and SN apps as well as overall smartphone usage. It should be noted that in our previous work in investigating SmUD among the users of different IM and SN platforms via self-report questionnaires, the highest associations were observed between SmUD and problematic Instagram and WhatsApp use, and the lowest (but still significant) associations were observed between SmUD and Snapchat and Facebook use .We also examined our second hypothesis and tested the potential role of the usage of IM and SN apps as a mediator of the link between smartphone usage  and self-reported tendencies toward SmUD. We go beyond previous studies by exploring the associations between smartphone and app usage variables and self-reported tendencies toward SmUD by using a parallel mediation model. Our findings supported the hypothesis that the association between the frequency of overall smartphone use and tendencies toward SmUD could be mediated by the frequency of the usage of apps that allow for web-based social communication . In particular, our analyses indicated the existence of an indirect effect that links smartphone use and tendencies toward SmUD via the image-based SN app session route . However, this indirect effect does not exist in the IM app session and traditional SN app session routes.Overall, combined with the findings that emerged from the correlation analysis, the results from the mediation analyses are in line with those of previous studies that suggest the importance of social motives for smartphone use as predictors of tendencies toward SmUD ,8 as welThis study has strengths. Since we used a validated instrument for the assessment of tendencies toward SmUD and smartphone activity data were obtained by the use of an objective assessment procedure , our results appear to be more reliable and valid than those reported by studies that relied solely on self-report measures of smartphone activity. The fact that our results were, in several ways, in line with those reported by previous studies further supports the validity of our findings. Future studies should also use measures for directly assessing individual differences in social networks use disorder and contrast their findings with those that we observed in our study .This study also has several limitations. First, analyses were performed on a relatively small convenience sample that consisted mostly of young adults aged equal or below 30 years old . Thus, our results cannot be generalized to the general population. The relatively small sample size may also have had a negative impact on statistical power; based on the posthoc computation, our sample size appears to be large enough to detect medium to large correlations and regression effects, but it was not large enough to detect small associations among the examined variables in a robust way. These limitations are common in psychological studies that are based on objective assessments of smartphone use . Still, This study provides novel results that shed light on the association between individuals’ use of popular SN and IM apps and tendencies toward SmUD. The results from nonzero correlations and regression analyses seem to suggest that the features implemented in image-based SN apps could be more strongly related to individual differences in tendencies toward SmUD compared to those available in IM apps and traditional SN apps, such as Facebook. Further, we also mention our previous work  in using


Since the clinical outcome of patients with sarcoidosis is still unpredictable, a good prognostic biomarker is necessary. Autotaxin (ATX) and phosphatidylserine-specific phospholipase A1 (PS-PLA1) function as main enzymes to produce lysophospholipids (LPLs), and these enzymes are attracting attention as useful biomarkers for several chronic inflammatory diseases. Here, we investigated the relationships between LPLs-producing enzymes and the disease activity of sarcoidosis. In total, 157 patients with sarcoidosis  were consecutively enrolled. Using plasma or urine specimens, we measured the values of LPLs-producing enzymes. Urine ATX (U-ATX) levels were significantly lower in the active state compared to those in the inactive state, while the plasma ATX (P-ATX) and PS-PLA1 levels showed no significant difference between these two states. Concerning the comparison with existing clinical biomarkers for sarcoidosis, U-ATX showed a weak negative correlation to ACE, P-ATX a weak positive correlation to both ACE and sIL-2R, and PS-PLA1 a weak positive one to sIL-2R. Notably, only the U-ATX levels inversely fluctuated depending on the status of disease activity whether OCS had been used or not. These findings suggest that U-ATX is likely to be a novel and useful molecule for assessing the disease activity of sarcoidosis. Because of the diversity in the pathogenesis of sarcoidosis, it is difficult to predict the clinical outcome of sarcoidosis, ranging from spontaneous remission to severe dysfunction of major organs5. Increased levels in several serum laboratory tests such as angiotensin converting enzyme (ACE), soluble interleukin-2 receptor (sIL-2R) and lysozyme were observed at the time of diagnosis. These molecules seem somewhat useful for monitoring the disease activity, but not enough to estimate the changes in severity or to predict the prognosis of sarcoidosis. Concerning the treatment for patients with severe sarcoidosis or severe dysfunction of major organs, oral corticosteroids (OCS) are commonly used as a first line therapy, but long-term use of OCS may cause many serious adverse effects including hyperglycemia, immunodeficiency, osteoporosis and so on. If we can find useful monitoring or prognostic biomarkers associated with the pathophysiology of sarcoidosis, it would be helpful not only for improving the management of patients with sarcoidosis, but also for developing novel treatment strategies.Sarcoidosis is a systemic granulomatous disorder of unknown etiology. The clinical features of sarcoidosis are quite different among regions, races and ethnicities and the outcomes of this disease also greatly differ9. Among these LPLs, LPA and LysoPS are produced extracellularly, whereas S1P is produced intracellularly and released extracellularly. Relatively high concentrations of LPLs are known to exist in body fluids such as blood  and function through specific G protein-coupled receptors expressed on the surfaces of target cells. Although assays of these lipids themselves are possible, the regulation of the metabolism of LPL mediators is complicated and it is not LPLs themselves but the enzymes catalyzing their production, that are encoded by the genomic DNA. Therefore, LPLs-producing enzymes such as autotaxin (ATX) or phosphatidylserine-specific phospholipase A1 (PS-PLA1) and even a carrier such as apolipoprotein M (ApoM) are more promising as alternate biomarkers for LPA, LysoPS and S1P, respectively12. ATX is a secreted lysophospholipase D catalyzing the extracellular hydrolyses of lysophosphatidylcholine to LPA and is considered to be responsible for the synthesis of the majority of extracellular LPA13. ATX/LPA signaling plays important roles in the pathophysiology of several chronic inflammatory diseases such as interstitial lung diseases, cancer, liver cirrhosis and atherosclerosis18. It has been reported that ATX can bind to lymphocytes, and LPA or ATX/LPC strongly enhances the trans-endothelial migration of integrin-arrested T cells across an endothelial monolayer and promotes lymphocytes to enter lymphoid organs from the blood20. In mouse models with rheumatoid arthritis, ATX proteins are expressed on synovial fibroblasts and its expression is markedly stimulated by TNF, which is one of the crucial mediators for granuloma formation21. PS-PLA1 is one of the enzymes that is responsible for LysoPS production. Unlike the ATX/LPA axis, the biological roles of PS-PLA1/LysoPS in the pathogenesis of those diseases have not been well studied. Recent studies suggest that the PS-PLA1/LysoPS axis is partially involved in the pathogenesis of cancer, acute coronary syndrome, and hyperthyroidism25. However, although it has been reported that the PS-PLA1/LysoPS axis inhibits mitogen-induced T-cell activation in vitro26, the association between the LPLs-producing enzymes/LPLs signaling and the disease activity of sarcoidosis remains to be elucidated.Eicosanoid mediators such as prostaglandins and leukotrienes have long been studied as first-generation bioactive lipids. On the other hand, lysophospholipids (LPLs), such as lysophosphatidic acid (LPA), sphingosine 1-phosphate (S1P), and lysophosphatidylserine (LysoPS), have emerged and been attracting attention to researchers as second-generation bioactive lipids in recent decades27.To investigate potential diagnostic of prognostic biomarkers for sarcoidosis, we collected over 150 plasma and urine samples from patient with active or inactive sarcoidosis and analyzed the relationships between LPLs-producing enzymes and the disease activity. Because the present study aims to find novel clinically useful biomarkers and apply them to the daily examination in a clinical setting, we focused on the values of ATX and PS-PLA1, both of which are present in body fluids and have been used as an alternative for the value of LPA and LysoPS, respectively28, we first analyzed the data among gender groups in addition to the whole subjects group. The clinical characteristics of subjects are summarized in Table 30. The disease activity was not significantly different between male and female groups.During the inclusion period, 53 out of 211 patients with sarcoidosis were excluded because of ongoing OCS therapy at the time of enrollment and 1 patient because of chronic hepatitis, and then 157 patients were finally enrolled in this study. Because the plasma- ATX (P-ATX) levels are known to differ between gendersThe subjects were classified into two groups according to their disease activity, that is, 80 patients in an active state and 77 in an inactive state Table . Subjectp = 0.28, PS-PLA1: 16.2 [13.5–18.8] for active state and 15.25 [12.4–17.7] ng/mL for inactive state, p = 0.13). On the other hand, subjects in an inactive state showed a significant increase in urine-ATX (U-ATX) (3.21 [1.34–6.15] for active state and 5.53 [3.41–8.57] p < 0.001)  and U-ATX  (Table p = 0.001)  , while male subjects did not (3.20 [1.52–4.57] for active state and 4.29 [1.96–5.94] p = 0.10)   and sIL-2R levels          and tended to decrease after disease progression, though the difference was not statistically significant (p = 0.11)  Fig. d,e.p < 0.0001), while the PS-PLA1 levels didn’t show any change , which was similar to the changes after OCS administration  showed an association with the U-ATX concentration33. In the present study, most subjects did not have severe glomerular injury and U-ATX showed a weak positive correlation with eGFR  or ongoing OCS and/or immunosuppressants therapy were excluded, because these agents may affect the disease activity and OCS is also known to reduce the synthesis of ATX34. Likewise, patients with chronic hepatitis were excluded, because the serum ATX level is known to be elevated in patients with hepatic fibrosis15. The disease activity of sarcoidosis was evaluated as active if (1) the patient was newly diagnosed with clinical symptoms such as cough, fever, fatigue and joint pain, (2) the asymptomatic patient had worsening organ involvement during the last 3–6 months follow-up or (3) the number of affected organs associated with sarcoidosis increased during the last 3–6 months follow-up. Inactive sarcoidosis was defined as subjects without clinical symptoms, worsening organ involvement or novel affected organs for at least 3 months. These activities were determined by two independent pulmonologists who were blinded to the measurement of the LPLs-producing enzymes. Patients’ characteristics and medical information including age, sex, smoking status, laboratory findings and radiological imaging data were obtained from the patients’ medical chart.All patients were diagnosed with sarcoidosis according to the American Thoracic Society (ATS)/European Respiratory Society (ERS)/ World Association of Sarcoidosis and Other Granulomatous Disorders (WASOG) statement on sarcoidosisThis was a single-center, cross-sectional survey that targeted sarcoidosis patients. The ethics committee of Tohoku University Graduate School of Medicine approved this study  and all participants provided informed written consent. In total, 157 outpatients with sarcoidosis in Tohoku University Hospital were consecutively enrolled in this study from October 1, 2014 to December 31, 2018. The study was carried out in accordance with the Declaration of Helsinki.43. Briefly, primary antibody coated with magnetic beads were placed in the reaction cup and alkaline phosphatase-labeled secondary antibody in assay buffer was added to the reaction cup. The ATX and PS-PLA1 assay reagent was prepared by a freeze-dry procedure of the reaction cap. All procedures, such as samples dispensation, incubation of reaction cap, washing and fluorometric detection, were automatically performed by an automated immunoassay analyzer (TOSOH AIA system). Because the ATX antigen levels in urine were lower than the lower limit of the standard ATX measurement, the U-ATX levels were measured using a slightly modified reagent containing a more sensitive anti-ATX monoclonal antibody as compared to the reagent used in the standard assay. The details and performances of the high-sensitive ATX measurement have been described by us previously33. On the other hand, the urinary PS-PLA1 levels were not measured because PS-PLA1 in the urine sample was not detectable in the preliminary data.Both plasma and urine samples were obtained from patients with sarcoidosis simultaneously and were immediately stored at −80 °C until use. The samples were collected twice or more from some patients whose disease activity had changed spontaneously or by OCS administration. The ATX and PS-PLA1 antigen levels were measured using specific 2-site enzyme immunoassay with TOSOH AIA system p < 0.05. All statistical analyses were performed using JMP Pro 14 software .Data of age, ACE, sIL-2R, KL-6 and pulmonary function were expressed as median and interquartile range . The clinical characteristics were compared using Mann–Whitney U-test or Fisher’s exact test. Using a Spearman’s rank test, univariate correlations analyses were assessed, and multivariate logistic regression analyses were performed to investigate the relationship between several biomarkers and LPLs-producing enzymes. Statistical significance was accepted as Supplementary Information.


It is well established that the health professional workforce is not adequately prepared to meet the demands of an aging older population. Caregivers are often the backbone supplemental workforce for seniors, providing daily care with assistance with activities of daily living, with little training. Part of the mission of the South Florida Geriatric Workforce Enhancement Program (SFGWEP) is to support and empower caregivers through community based training programs. Between January 1 2020 to January 31, 2021 SFGWEP provided education to more than 340 caregivers on topics related to opioid use, effective communication with individuals with dementia and other topics. Attendees responded to a short evaluation survey, which included three multiple-choice questions on if attending was a good use of their time, if they gained knowledge and if they plan to apply material, and two open-ended questions to identify opportunities for improvement in future trainings. Responses were overwhelmingly positive (>98% for multiple-choice questions.) There were also three open-ended questions that were analyzed using a modified thematic approach. The three questions covered what attendees learned, what they wanted to learn more about and suggestions for improvement. Analysis suggests that attendees plan to be more mindful about communication  and that they want more information on neurocognitive disorders and resent research, including psychological changes due to disease and medication side effects. In terms of improvement, attendees said the program should allow more time for questions and should use more engaging materials .


Blockers of angiotensin II type 1 receptor (AT1R) exert antidepressant-like effects by indirectly facilitating the activation of the angiotensin II type 2 receptor (AT2R), which leads to increased surface expression and transactivation of tropomyosin-related kinase B receptors (TRKB). Compound 21 (C21) is a non-peptide AT2R agonist that produces neuroprotective effects. However, the behavioral effects of C21 and its involvement with the brain-derived neurotrophic factor (BDNF)-TRKB system still need further investigation. The aim of the present study was to assess the effect of C21 on the activation of TRKB and its consequences on conditioned fear. The administration of C21 (0.1–10 μM/15 min) increased the surface levels of TRKB but was not sufficient to increase the levels of phosphorylated TRKB (pTRKB) in cultured cortical neurons from rat embryos. Consistent with increased TRKB surface expression, C21 (10 μM/15 min or 3 days) facilitated the effect of BDNF (0.1 ng/mL/15 min) on pTRKB in these cells. In contextual fear conditioning, the freezing time of C21-treated  wild-type mice was decreased compared to the vehicle-treated group, but no effect of C21 was observed in BDNF.het animals. We observed no effect of C21 in the elevated plus-maze test for anxiety. Taken together, our results indicate that C21 facilitated BDNF effect by increasing the levels of TRKB on the cell surface and reduced the freezing time of mice in a BDNF-dependent manner, but not through a general anxiolytic-like effect. The renin-angiotensin system (RAS) has been historically implicated in cardiovascular and peripheral fluid homeostasis. However, an increasing number of studies suggest that RAS also plays a role in the central nervous system (CNS). In fact, all RAS components are found within the CNS and function independently of the periphery ,2,3. BriThe majority of ANG2 actions are usually mediated by angiotensin II type 1 and type 2 receptors . Both receptors are constitutively expressed in brain areas such as the frontal cortex ,4, whichThere is evidence indicating that RAS can modulate the brain levels of both brain-derived neurotrophic factor (BDNF) and its receptor tropomyosin-related kinase B (TRKB). For instance, chronic treatment with telmisartan (AT1 antagonist) prevented retinal damage and a decrease in BDNF levels in an animal model of induced diabetes . AnotherRecently, the antidepressant-like effect of losartan, another AT1R antagonist, has been described to involve TRKB transactivation and increase on the cell surface, an effect likely linked to an indirect AT2R activation after AT1R blockade . HoweverThus, to extend our previous findings regarding the interaction between AT2R and TRKB , we invep < 0.0001]. All doses of C21  were different from the control group = 58.50, p = 0.0116]. While longer administration of C21 (3 days) increased pTRKB levels per se , the facilitation of the BDNF effect was still present , The two-way ANOVA indicated a significant interaction between C21 and BDNF administration at the levels of pTRKB . Then, we proceeded with two-way ANOVA for each trial individually, as seen in p = 0.706, p = 0.033, p = 0.856, p < 0.05; Hedges’ g = 2.989) but not in BDNF.het mice .The two-way ANOVA with repeated measures indicated a significant interaction between C21 treatment, genotype and trials even considering the total distance traveled as covariant on freezing time  sulfonylcarbamate}  and BDNF  were used. For in vitro experiments, C21 was dissolved in DMSO, and BDNF was dissolved in PBS; for in vivo experiments C21 was dissolved in sterile saline. Isoflurane  and treated with C21  and surface levels of TRKB was determined as previously described ,43. BrieFor assaying the phosphorylated TRKB (pTRKB), cortical neurons were cultured in 24-well plates  and treated with C21 (10 μM/15 min) and challenged with BDNF (0.1 ng/mL/15 min) at a concentration that is beyond the BDNF Ki for TRKB  but inefThe cells were washed with ice-cold PBS and lysis buffer , containing a cocktail of protease and phosphatase inhibitors  was added.2CO3 57.4 mM, NaHCO3 42.6 mM) ON at 4 °C. The plate was blocked with 2% BSA in PBS with 0.1% Tween (PBS-T) for 2 h at RT. Then, cell lysates were added to the plate and left ON at 4 °C. The plate was washed again with PBS-T, and biotinylated anti-phosphotyrosine secondary antibody  was added followed by ON incubation at 4 °C. Following another washing step, the plate was incubated with HRP-conjugated streptavidin  for 2 h at RT. The plate was washed with PBS-T and the chemiluminescent signal was detected by a plate reader  after addition of ECL (1:1). The signal from the samples, after blank subtraction, were normalized by the average of the control group (ctrl/ctrl) and expressed as percentage from control. The signal of pTRKB was determined by ELISA ,23,44. OWe used 34 mice  in the fear conditioning experiment. All treatment and behavioral experiments were conducted between 9:00–14:00 h. Littermates of wt or BDNF.het mice were divided into two groups, where they were given either vehicle or C21  by intranasal route . BrieflyAn independent cohort of wild-type mice (12 wt) was submitted to the elevated plus-maze. The animals were divided (n = 6/group) and received the same drug administration protocol as described above  under light anesthesia. Two hours after the last administration the animals were submitted to the acrylic-built elevated plus-maze composed of two open arms (30 × 5 cm with a 1 cm rim) and two enclosed arms  connected by a central platform (5 × 5 cm) and elevated 40 cm above the floor. The percentage of time and entries in the open arms and the number of entries in the enclosed arms and the total distance traveled were determined by the software  in the 5 min session.t test. The data from fear conditioning were analyzed by two-way ANOVA with repeated measures with treatment, genotype and trials as factors, and the total distance traveled in the first 2 min of the conditioning session as covariant; since an interaction was observed a two-way ANOVA was performed for each trial, followed by Fisher’s LSD post hoc tests. p < 0.05 was considered significant.The data from surface TRKB assay were analyzed using Kruskal-Wallis test, followed by Dunn’s post hoc test since homoscedasticity was not observed among the groups. The effect-size of the treatment was calculated by Hedges’ method . The datAlthough still modest, there is increasing interest about the brain effect of RAS-acting drugs. Indeed, AT1R-antagonists such as losartan have been shown to improve stimuli discrimination, which was followed by changes in amygdala activity, in healthy volunteers with high trait anxiety . Therefo


For people with physical disabilities, manual wheelchairs are essential enablers of mobility, participation in society, and a healthy lifestyle. Their most general design offers great flexibility and direct feedback, but has been described to be inefficient and demands good coordination of the upper extremities while critically influencing users’ actions. Multiple research groups have used Inertial Measurement Units (IMUs) to quantify physical activities in wheelchairs arguing that knowledge over behavioural patterns in manual wheelchair usage can guide technological development and improved designs. The present study investigates turning behaviour among fulltime wheelchair users, laying the foundation of the development of novel steering systems that allow directing kinetic energy by means other than braking. Three wearable sensors were installed on the wheelchairs of 14 individuals for tracking movement over an entire week. During detected “moving windows”, phases where the velocities of the two rear wheels differed by more than 0.05 m/s were considered as turns. Kinematic characteristics for both turns-on-the-spot as well as for moving turns were then derived from the previously reconstructed wheeled path. For the grand total of 334 km of recorded wheelchair movement, a turn was detected every 3.6 m, which equates to about 900 turns per day on average and shows that changing and adjusting direction is fundamental in wheelchair practice. For moving turns, a median turning radius of 1.09 m and a median turning angle of 39° were found. With a median of 89°, typical turning angles were considerably larger for turns-on-the-spot, which accounted for roughly a quarter of the recognised turns and often started from a standstill. These results suggest that a frequent pattern in daily wheelchair usage is to initiate movement with an orienting turn-on-the-spot, and cover distances with short, straightforward sections while adjusting direction in small and tight moving turns. As large bends often require simultaneous pushing and breaking, this is, perhaps, the result of users intuitively optimising energy efficiency, but more research is needed to understand how the design of the assistive devices implicitly directs users’ movement. According to the World Health Organisation, approximately 1% of the population with musculoskeletal impairments or disabilities, or worldwide more than 65 million people rely on a wheelchair for mobility . The samWheelchairs generally use four independent wheels and are push-rim controlled, meaning that hand-rims on the large rear wheels act as the interface for propelling and navigating the system: pushing forward on both sides simultaneously results in a forward motion, while braking on one side causes a turn to the respective direction. Although offering great flexibility and direct visual, proprioceptive and kinaesthetic feedback , such a This study aimed to lay the foundations for introducing novel interaction-principles in the design of manual wheelchairs based on the concept of steering systems that allow directing kinetic energy by means other than braking. Multiple groups have argued that knowledge of wheelchair usage in daily life is an invaluable resource to the design, engineering, and manufacture of new, possibly improved models . Here, tTowards improving rehabilitation process, different portable measurement systems have been proposed for tracking wheelchair user’s activity, for example by monitoring and promoting active sitting . Similarhow people negotiate spaces and move from one place to another.Interestingly, rotation behaviour is developing as an important parameter in neuropsychological studies, where the number of left/right turns are thought to be indicative of laterality or rotation biases . HoweverIndividuals who have relied on a manual wheelchair for mobility for a duration of at least 6 months before the measurements were included in this study. Participants were required to be at least 18 years old, active wheelchair users that are able to propel their wheelchairs independently. Exclusion criteria included suffering from an acute injury, such as a pressure ulcer or shoulder injury, as well as untreated mental illnesses such as depression. The study was approved by the ethics committee of ETH Zurich (EK 2020-N-04), and all participants provided written informed consent prior to the start of measurements.For this study, a set of three ZurichMOVE  sensors One sensor was rigidly mounted on the spokes of each wheel and one was fixed to the frame below the seat using custom-made, durable adaptors . Primariz-axis coincided with the rotation axis, zrot, of the wheelchair wheels. For the sensor on the frame, the time periods where the wheelchair was at rest  were used to align the z-axis of the sensor with the direction of the gravitational acceleration, zg . Before further calculations, the orientation of the sensors was corrected. For the sensors on the spokes, time periods with a straight-forward wheeling movement  with a duration longer than one second were identified in order to rotate the sensor’s coordinate systems such that the respective tion, zg . These rTo identify and describe turns and turning patterns, a two-step process was undertaken: firstly, only phases in which the wheelchair was moving were considered of interest, and secondly, a reconstructed movement path served as a basis to estimate turning radii and angles.Phases of wheelchair movement were identified, using the definition of moving windows by Popp and co-workers : The wheTo derive wheeled distances and directions, angular velocities of both wheels were multiplied with the wheel’s radius and then integrated. Knowing the wheelchair’s track width allowed the reconstruction of the wheeled path in a 2-dimensional space over time to provide a basis for identifying turns .To determine start- and end-points of a turn during the recognised moving windows, a distinction between moving straight-forward and turning was made. Segments in which the wheel velocities differed by less than 0.05 m/s were considered as straight. Turns were investigated in the remaining time periods.• The duration of a turn-on-the-spot was greater than 0.5 s.• The mean angular velocity of a turn-on-the-spot was greater than 20°/s.• The turning angle of a turn-on-the-spot is at least 45°.The signs of the wheel velocities enabled a differentiation between “moving turns” and “turns-on-the-spot”. The latter were characterised by one wheel moving forward while the other moved backwards, and were detected by opposite signs in the directional data. Assuming that no notable distance was covered for this type of turn, the turning radius was set to zero. All identified turns-on-the-spot were taken into account if all of the following conditions were met:• The duration of a moving turn was greater than 0.5 s.• The mean velocity during a moving turn was greater than 0.12 m/s.• The wheeled distance of a moving turn was greater than 20 cm.• The turning angle of a moving turn was at least 15°.Two consecutive turns-on-the-spot were merged if they were separated by less than 0.3 s. Moving turns were then analysed based on the previously reconstructed wheeled path. Here, turning radius was approximated for each segment using least squares fitting according to Pratt  Figure . Moving Consecutive moving turns were merged if they were separated by less than 0.3 s, or the wheeled distance in between was less than 20 cm. Furthermore, moving turns with a radius greater than 10 m were considered as straight-forward movements. All parameters were chosen based on repeated test measurements where known movement paths like rectangular trajectories, circles, figure-8s and straight lines with turns-on-the-spot at their ends where wheeled. This helped finding definitions that result in plausible distinctions between different types of movement .To verify circularity, the normalised root-mean-square error (NRMSE) of the turning radius was calculated for each moving turn. Turns with NRMSE <4% were classified as “regular turns”. Non–circular turns with NRMSE >4% were further analysed. Here, the first third and the last third of the moving turn were again approximated with the Pratt method in order to examine whether the turning radius was increasing or decreasing. If both new fitted circles had an NRMSE <4%, then the ratio of the two radii was calculated. Turns with a ratio smaller than 0.5 or higher than 2 were classified as “spiral turn” . All remg) from the sensor on the frame was used for calculation.Turns where the absolute velocity of the right wheel was greater than that of the left wheel were categorised as left turns, and the remaining as right turns. Moving turns were further classified as forward or backward turns based on the signs of the wheel velocities. For all moving turns, turning distance was calculated by integrating the center of mass velocity of the wheelchair. For regular turns, turning angles and radii were derived from the fitted circle. For turns-on-the-spot, the angular velocity in the direction of the axis of rotation . The majority of participants had a thoracic spinal cord injury, although one individual with tetraplegia, one with cerebral palsy, and one with knee disarticulation were also included. Additional descriptions of all participant characteristics are presented in The expected maximum measurement error was added to the individual sensor values in order to analyse the maximum offset of parameters of interest and assess their reliability. A comparison between the directly calculated results with artificially erroneous ones over the entire data collection yielded the error values given in The datasets contained a total of 31′410 moving windows. The mean number of daily moving windows was 331 ± 101. Daily moving time was 71 ± 24 min on average, whereby a mean daily distance of 3.10 ± 1.44 km was covered. A large proportion of moving windows were rather short, with a per person median duration averaging 7.0 ± 0.9 s and a median distance of 2.3 ± 0.6 m. Mean median velocity was 0.35 ± 0.05 m/s.Probing moving windows by duration, 64 ± 5% were found to be shorter than 10 s . During Consecutive moving windows were separated by a median time of 16 s, and a mean time of 151 s 78% were separated by less than 60 s, 57% by less than 20 s.A total of 19′673 turns-on-the-spot and 66′829 moving turns was detected in the collected data. Among the latter, 97.2% were classified as regular and 1.9% as spiral. The remaining 658 irregular turns (0.9%) were excluded from the analysis.No participant showed a clear preference with regards to turning direction, resulting in almost equal number of left and right turns in both moving turns and turns-on-the-spot. The majority of moving turns, 89.1 ± 4.3% were wheeled in forward direction.Overall, the median turning radius was found to be 1.09 ± 0.12 m, whereby 90% of the radii were smaller than 3.33 m . The medMedian mean velocity for moving turns was found to be 0.49 ± 0.09 m/s, while backward turns were slower than turns wheeled forward . DuratioTurning with a radius of 0.6–0.8 m was found to be most frequent . In thisDuring the week-long measurement period, participants wheeled a mean 897 ± 328 turns per day, whereby moving turns accounted for 77 ± 5% of all recognised turns .About 30% of all moving windows started with a turn-on-the-spot. 12% of all windows contained neither a moving turn nor a turn-on-the-spot. In the remaining 88%, a mean of 3.1 turns per moving window, composed of 2.4 moving turns and 0.7 turns-on-the-spot, were detected. During moving windows, a turn was wheeled every 4.9 s, with an interjacent mean distance of 3.6 m. More specifically, every 6.2 s a moving turn, and every 22.8 s a turn-on-the-spot was identified, with a mean distance interval of 4.6 m, and 17.0 m, respectively.A comparison between initial and final velocity of moving turns showed that during 63 ± 3%, velocity was lost during the turn . This asIn order to describe typical movement sequences, actions 1 s before and after each turn were assessed. For actions before moving turns, a straightforward movement was found to be the most common, accounting for 41% of the cases. The second most frequent action was another moving turn (25%), a standstill (19%), or turn-on-the-spot (15%). The majority of turns-on-the-spot started from rest (58%) or occurred immediately after a moving turn (29%). Activities including a turn-on-the-spot following a straightforward movement, or another turn-on-the-spot, appeared less frequently .After a moving turn, participants continued with a straightforward movement in about 47% of cases, wheeled a subsequent moving turn in 25%, and stopped directly afterwards in 20%. Another turn-on-the-spot was least frequent with 8%. More than half of all turns-on-the-spot were directly followed by a moving turn (55%), while the wheelchair was stopped in 25%, or superseded by a straightforward movement in about 19% of cases. Turns-on-the-spot following each other were found to be infrequent (<1%) .As enablers of mobility, participation and health, wheelchairs critically shape users’ actions - knowledge about which can, in turn, guide the design and customisation of future assistive technologies. Towards developing novel wheelchair-user-interfaces, this study characterises the turning behaviour of wheelchair users during normal functional activities of daily living. With about 900 turns per day or a turn every 3.6 m, changing and adjusting direction is fundamental in wheelchair usage. A median turning radius of 1.09 m and a median angle of 39° for moving turns suggest that this is typically achieved in sharp corners rather than large bends. Similarly, turns-on-the-spot account for about a quarter of recognised activities and are typically associated with high angles (in the range of 60°–120°), with a majority starting from a standstill. In summary, manoeuvring manual wheelchairs in daily life is best described as a concatenation of orienting turns-on-the-spot, short straight sections, and tight, corrective moving turns.Adding to a body of research on the study of daily activities using wearable sensors, wheelchairs of 14 active wheelchair users were instrumented with a set of 3 IMUs for measurement of an entire week. From these participants, a total of 2,302 h and 334 km of wheelchair movement distributed over 31′410 moving windows that contained 86′565 turns was analysed within this study. Error analysis substantiated that a valid method was chosen to describe the kinematics of turning wheelchairs in daily life. Maximum theoretical errors were small, 5% (NRMSE) or less for all analysed parameters, implying that the analysis results could only been marginally affected by possible inaccuracies in the measured IMU sensor data.The measured mean wheelchair velocity during moving windows, turns, and straightforward movements of 0.35 m/s, 0.57 m/s, and 0.48 m/s, respectively, are comparable with previous literature ranging from 0.2 to 0.8 m/s . The meaFor a general description of activity, Popp and others’ definition of moving windows was used  instead During the measurement periods, an average of 331 moving windows per day were detected. Echoing other authors’ findings , most ofOn average, a moving window contained about 3 turns, most of which were characterised by small turning radii in the range of up to twice the wheelchairs’ track widths as well as small turning angles of less than 90°. Instead of turning in large curves, wheelchair users seemed to prefer to move larger parts of a distance in a straightforward movement and adjust direction in short, tight turns or–in other words–it appears they favour a polygon over continuous circumscribing circles. Literature that helps explaining these findings is extremely limited. In 1990, Reid and co-workers  attempteAssuming that wheelchair users intuitively optimise energy consumption to at least some degree, both the overall high frequency of turns and the predominance of sharp moving turns with small angles appear to be reasonable consequences of the conventional wheelchair configuration that, at least during movement, requires users to break on one side in order to change direction. The large proportion of turns-on-the-spot further supports this argument, especially given frequent movement patterns: almost 60% of turns-on-the-spot started from standstill and about 25% ended a moving window. Roughly a third of moving windows directly started with a turn-on-the-spot. A typical technique of reaching a desired destination appears to be to first align the wheelchair’s orientation with a turn-on-the-spot, then start moving in the desired direction and later adjust the direction with short moving turns as needed. This explanation is further supported by the finding that moving turns often occur during movement or between straightforward segments.The relevance of these results is two-fold: firstly, they highlight the importance of good maneuverability of wheelchairs. The ability to change direction quickly and fluently seems to be essential. Secondly, the kinematics of manoeuvres in wheelchairs are testimony to the conventional wheelchair-user-interaction principle that offers great flexibility thanks to the usually small and light castor front wheels, but on the other hand, this arrangement is inefficient for the precise control of direction. The present study provides a unique insight into wheelchair users’ daily routines, gearing towards the development of novel, steering wheelchairs. Future wheelchair designs will need to offer effortless turning-on-the-spot, and allow small turning radii together with controlled and efficient turning at higher speeds.One limitation was that only 14 wheelchair users participated in this study. Even though some trends were found, inter-subject variability was relatively large. In addition, 85% of participants in this study had a spinal cord dysfunction. The observed results are likely to differ if more subjects with other walking disabilities were included. Next, long-term data collection in daily live can be influenced by many unknown factors such as sensors getting caught or subjects manipulating their position. Even though several measures to prevent sensor misalignment were taken, slight changes to the sensors positions relative to participants’ wheelchairs could have had a marginal influence on the study results. Equally, this study’s outcomes are the results of chosen methods. Especially the definitions of turns, turns-on-the-spot and straightforward movement clearly influenced the central findings. To avoid arbitrary choices, these central parameters were carefully developed in repeated test measurements. Furthermore, some participants reported that they predominantly stayed at home during the measurement period due to the outbreak of COVID-19 and could have moved further and more frequently under different circumstances. The overall distances travelled however still appeared comparable to or even exceeded those reported in previous studies. These limitations imply that a generalisation about overall wheelchair use is difficult, and further studies with a higher number of participants of greater diversity would be needed in order to obtain more conclusive results.This study aimed at describing manoeuvres of wheelchair users in general and did not consider any potentially stratifying factors such as the types of activities, users’ experience and skills or specific wheelchair models. Such comparisons could be the target of further studies. Similarly, the investigation should be repeated if wheelchairs with new steering concepts become available. Potential differences in movement patterns between different wheelchair technologies would highlight the extent to which assistive device mechanisms are able to influence and support users’ behaviour, and hopefully also decrease the risk of injuries and developing pain due to overuse.It is important to note that the methods developed in this study might also be useful in other fields. Therapists could use similar techniques to monitor patients’ activities in order to tailor treatments and training more specifically to each individual’s skills and abilities–especially as different turning techniques are among the most essential wheelchair skills . In courKnowledge about reoccurring patterns in manual wheelchair movement during everyday life can critically contribute to improvements in rehabilitation and related technologies. Analysis of moving windows, turn characteristics, and typical movement patterns in this study provide deeper insight into how wheelchairs are used. Our data suggest that initiating movements, stopping, covering short distances, and manoeuvring in small circles dominate the daily wheelchair usage. These movements are associated with a change in inertia and requires effort from the user. Future wheelchair mechanisms should reflect this by minimising such energy costs to improve efficiency, and develop more ergonomic, energy-efficient, and user-friendly wheelchairs. More research is needed to investigate if the turning behaviour directly depends on the wheelchair type used, or differs significantly between different activities, for example by differentiating indoor and outdoor use. If movement patterns differ considerably, future wheelchairs should offer adaptive mechanisms to switch to the appropriate environment.