31 Matching Annotations
  1. May 2019
    1. 54Primer NameGenome Co-ordinatesSequence (5’-3’)Brk_RE_FchrX:7200547-7200702AAACCTCTGTGTTCGTCTGGCBrk_RE_RTCCGTAGAAACCGCGCAACBrk_RC_FchrX:7200789-7200926CCGATGTGGAAGGGGTATGGBrk_RC_RGGCTCTGCCAGTTGCTCATAC15_RE_Fchr3R:17325974-17326067GCCAAAATGTCCAGCCACGAC15_RE_RTGACATCCGCGAGTCCGAC15_RC_Fchr3R:17325763-17325861CCGTAGACCGTAATCCGTGAAC15_RC_RCCGCGAAGCACACACTAATCTable 2.4. | Primer sequences to determine DpnII digestion efficiency. Digestion efficiency was calculated using the following formula (Hagège et al., 2007):Digestion Efficiency %= 100-1002CtRE-CtRCDigested-CtRE-CtRCUndigestedSequencing Library Preparation:Prior to preparation of sequencing libraries, 5-6μg 3C libraries were sonicated using a S220 Focussed Ultrasonicator (Covaris) aiming for a peak size of 200bp. Libraries were sonicated with the following settings: Duty Cycle: 10%, Intensity: 5, Cycles per burst: 200 and Mode set as Frequency Sweeping with 6 cycles each of 60s. Following sonication, samples underwent clean-up using AMPure XP SPRI beads (Beckmann Coulter), with sonication quality assessed using a TapeStation 2200 (Agilent). Sequencing libraries were prepared using the NEBNext DNA Prep Reagent set and the NEBNext Multiplex Oligos for Illumina (NEB), following the manufacturers instructions with the following modifications. Firstly, AMPure bead clean up steps were performed x1.8 volume to avoid skewing for larger fragments. Secondly, library PCR amplification was performed using Herculase II Fusion DNA Polymerase kit (Agilent) to a total of 50μl using: 1x Herculase II Buffer, 250μM dNTPs, 0.5μM of both the NEB Universal and NEB Index Primer, and Units Herculase II Polymerase. Libraries were assessed after adaptor ligation and post indexing PCR on a TapeStation 2200 (Agilent)
    2. until 2-4h AEL. Collected embryos were dechorionated in cold 50% Bleach (Sodium Hydrochlorate) for 3mins and rinsed thoroughly in cold dH20 and cold Triton-NaCl (previously described). The subsequent steps for both cross-linking and nuclei isolation were based on a ChIP protocol for Drosophilaembryos (Sandmann et al., 2006).Covalent Cross-linking: Collected embryos were blotted dry then rinsed in 100% isopropanol, to remove the excess water. Covalent cross-linking was performed using 2% methanol-free formaldehyde (ThermoFisher Scientific) for 20mins with 50% Heptane and Cross-linking Buffer (1mM EDTA, 0.5mM EGTA, 50mM HEPES pH 8.0, 100mM NaCl) and quenched using 125mM Glycine in 1x PBS, 0.1% Triton X-100 for 1min. Embryos were subsequently washed in 1x PBS, 0.1% Triton X-100, flash frozen andthen stored at -80°C. Replicates were obtained through collections of two independent sets of cages.Isolating Nuclei: 1.2 ml of embryos were resuspended in cold 1x PBS with 0.1% Triton X-100 and dounced 5 times in 4ml aliquots in a 7ml Wheaton Dounce Homogenizer. The homogenate was centrifuged at 400g for 1min at 4°C and transferred to a new tube and centrifuged at 1100g for 10mins at 4°C. The cell pellet was resuspended in 5ml of cold cell lysis buffer (85mM KCl, 0.5% (v/v) IGEPAL CA-630, 5mM HEPES pH 8.0, 1mM PMSF and 1x Protease and Phosphatase inhibitors (Roche)) and dounced 20 times. Nuclei were pelleted by centrifugation at 2000g for 4min at 4°C. 3C Library Preparation: Preparation of Capture-C libraries were performed according to the Next-Generation (NG) Capture-C Protocol (Davies et al., 2015). Briefly, nuclei were resuspended to a total volume of 650μl and digested overnight at 37°C whilst agitating at 1400rpm on an Eppendorf Thermomixer. Digestion was performed using 1500 Units DpnII (NEB High Concentration 50,000 U/ml), 1x NEBuffer DpnII, 0.25% SDS and 1.65% Triton X-100, including a non-digested control. Digested 3C libraries were ligated using 240 Units T4 DNA HC Ligase (ThermoFisher Scientific) and 1x Ligation Buffer overnight at 16°C whilst agitating. Following ligation, all 3C libraries including controls were de-crosslinked overnight at 65°C with 3 Units Proteinase K (ThermoFisher Scientific). Ligated 3C libraries were digested with 15μg/μl RNAse (Roche) and DNA subsequently extracted with phenol-chloroform followed by ethanol precipitation. Digestion efficiency: Digestion efficiency was determined using primers pairs designed against DpnII digestion sites and genomic controls at two independent regions comparing the digested and undigested controls for both replicates. Efficiency was determined through qPCR on a StepOnePlus Real-Time PCR System (ThermoFisher Scientific) using the SYBR Select Master Mix (ThermoFisher Scientific) as per the manufacturers instructions. Primers used to determine restriction efficiency are shown in Table 2.4
    3. Embryo Collection: Embryo collections were carried out as described above with the following modifications. Prior to collections, plates from the first 2hrs were discarded to prevent inclusion of older embryonic stages. After pre-clearing, collections were carried out as above with ageing
    4. Capture-C
    5. smiFISH: The smiFISH protocol was performed as described by Tsanov et al., 2016with modifications for use in the Drosophila embryo. Briefly, a minimum of 50μl of embryos were transferred to Glass V-vials (Wheaton) and transitioned from 100% Methanol to PBT in 50% increments, followed by several 10min PBT washes. Subsequently, embryos were washed at 37°C in stellaris wash buffer(1x SSC (150 mM NaCl and Sodium Citrate at pH 7.0), 10% deionised formamide) pre-warmed to 37°C. Hybridisation was performed using 4uM of labelled probes mixtures, as described above, incubated in stellaris hybridisation buffer (1x SSC, 100mg dextran sulphate, 10% deionised formamide) for a minimum of 14 hours at 37°C. Following hybridisation excess probes are removed with washes in stellaris wash buffer, pre-warmed to 37°C and subsequently washed with PBT. During the pen-ultimate PBT wash DNA and the nuclear membrane were stained using 1:1000 of DAPI (5mg/ml) and 1:1000 of wheat germ agglutinin (WGA) conjugated to Alexa 555 (5mg/ml, ThermoFisher Scientific), respectively. Embryos were subsequently mounted with ProLong Gold AntiFade (ThermoScientific).Alkaline Phosphatase Immunostaining: For immunostaining, a minimum of 50μl of embryos were gradually transferred from methanol to PBT and washed in PBT for 30mins with repeated changes of PBT. Embryos were blocked for 2hrs in 10% BSA in PBT and subsequently washed in PBT. Following this, embryos were incubated with monoclonal mouse anti-Hindsight-IgG1 (1:20, DSHB) primary in 1% BSA in PBT overnight at 4°C. To remove excess antibody, embryos were washed for 2hrs in 1% BSA in PBT. Next, polyclonal goat anti-mouse-IgG (H+L) AP Conjugate (1:500, Promega) was added in 0.1% BSA in PBT and incubated for 2hrs at room temperature. This was followed by washes with PBT and staining solution (defined above). Following staining, washing and mounting was performed as above. Image Acquisition: Images from alkaline phosphatase staining were acquired on a Leica DMR. Fluorescent images were acquired using a Leica TCS SP5 AOBS inverted confocal. Whole embryos were viewed using a20x 0.70 HXC PL APO Lambda Blue Immersion objective and embryo sections viewed with a 63x 1.40 HCX PL APO Lambda Blue Oil objective, with a maximum of 3x confocal zoom. Additional confocal settings were as follows: pinhole diameter of 1 airy unit, 400Hz unidirectional scan speedwith all images collected at 1024 x 1024. Images were collected sequentially usingPMTdetectors with the following mirror detection settings:DAPI (420-470nm), Alexa 488 (490-525nm), Alexa 555 (570-620nm) and Alexa 647 (650-780nm). The respective fluorophores were detected using the blue diode (20%) and the following laser lines: 488nm (50%), 555nm (50%) and 633nm (40%). When acquiring 3D optical stacks the confocal software was used to determine the optimal number of Z sections based on a Z section depth of 1μm at 20x and 0.3μm at 63x. Only themaximumintensity projections of these 3D stacks are shown in the results
    6. fluorescently conjugated secondary antibodies, also at a ratio of 1:400. Secondaries used included: donkey anti-mouse-IgG-Alexa 488, donkey anti-sheep-IgG-Alexa 555 and donkey anti-rabbit-IgG-Alexa 647 (all from ThermoFisher Scientific). Following incubation, excess secondaries were removed with PBT washes over 2hrs, including a 40 min incubation with 1:1000 wash with DAPI (5mg/ml, ThermoFisher Scientific). Finally embryos were resuspended in ProLong Gold AntiFade (ThermoScientific) and mounted. smiFISH Probe Design: CustomsmiFISH probes were designed using the Biosearch Technologies Stellaris RNA FISH Probe Designer ver 4.2 (Biosearch Technologies, Inc., Petaluma, CA), (available online at www.biosearchtech.com/stellarisdesigner(last accessed: 18/05/2017)) against the Drosophila genome. Probes were designed with the following parameters; masking level of >=3, oligo length between 18bp to 22bp, a minimum of 2bp spacing between probes with a minimum of 24 probes per gene. Sequences complementary to the Y and Z flaps based onTsanov et al., 2016were added to the 5’ end of the probes. 250pmoles of labelled flap sequences were hybridised to 200pmoles of smiFISH probes in 1x NEB Buffer 3 (NEB) and incubated in a thermocycler at a final concentration of 4uM in the following conditions: 85°C for 3min, 65°C for 3min and 25°C for 5min.Details of target regions, number of probes and flap sequence are shown below in Table 2.2with details of fluorescent-labelled flap sequences shown in Table 2.3. Individual probe sequences for Ance, peb and ush are available in the following supplementary tables: Table S1.1, Table S1.2 and Table S1.3, respectively. ProbeProbe TargetTarget Region(s)FlapNumber of ProbesAnceExon 1;Intron 1;Exon 2chr2L:13905733-13906413;chr2L:13906591-13907163;chr2L:13907608-13907958Y48PebIntron 1;Intron 2chrX:4512107-4513998;chrX:4514915-4515168Z48UshIntron 3;Intron 4chr2L:524083-525382;chr2L:525516-535905Z48Table 2.2. | smiFISH target probes target regions, including: flap sequence and total number of probes per regionsFlapSequenceFluorophore (nm)YAATGCATGTCGACGAGGTCCGAGTGTAAAlexa 488ZCTTATAGGGCATGGATGCTAGAAGCTGGAlexa 647Table 2.3. | Fluorescently labelled Flap sequences complementary to probes flaps, including fluorophore for smiFISH
    7. GenePrimer DirectionSequence (5’-3’)Intronic or ExonicAnceForwardAAACAAGTCATTCGCTTTAGGGCIntronicReverseCGCATTTTCGGATGACTCTGGKek1ForwardGCAGATTCGCACGGATGAACIntronicReverseTTTGCGTGGCAAAATGTGCTNetForwardATTCACCCAATTCCAACGACExonicReverseGTGGCAATGGACGGTACGGATupForwardCGGGAAAAGCAGCCTTGGATIntronicReverseTAGCTACAGCGAGTGCGAAATable 2.1. | Primer sequences for FISH.Alkaline Phosphatase RNA In-situ Hybridisation: For in situ hybridisations, a minimum of 50μl of embryos were washed with 100% ethanol, transitioned to 100% methanol, and then to PBT (1x PBS, 0.1% Tween-80). Embryos were then transferred to hybridisation buffer (previously described) and incubated at 55°C for 1hr, followed by overnight incubation in 0.5-2μl of the RNA probe in 50μl of hybridisation buffer. Sequential washes were then performed with hybridisation buffer and PBT, after which the embryos were incubated overnight at 4°C with anti-Digoxigenin-AP Fab fragments (1:250, Roche), pre-absorbed prior use against fixed embryos, in 500μl PBT. Excess primary antibody was removed with sequential several PBT washes, followed by two 5min washes in staining buffer (100mM NaCl, 50mM MgCl2, 100mM Tris pH 9.5, 0.1% Tween 80). The antibody bound RNA probe was visualised using 0.27mg Nitro-Blue tetrazolium and 0.14mg 5-Bromo-4-Chloro-3-indolyphosphate in 400ul. Staining was stopped by washing with PBT, followed by repeated washes with 100% ethanol over 1hr. Lastly embryos are briefly treated with 100% xylenes prior being mounted in Permount mounting medium (bioPLUS).Fluorescent RNA In-situ Hybridisation: For FISH, a minimum of 50μl of embryos were transferred from 100% methanol to 100% ethanol, as above. Embryos were washed for 1hr in 90% xylenes with 10% ethanol, followed by ethanol washes until complete removal of xylenes. Subsequently, embryos were washed with methanol and underwent post-fixation for 25mins using PBT with 5% formaldehyde. Following this embryos were pre-hybridised using hybridisation buffer (previously described) for 1hr at 55°C. Hybridisation was performed in 100ul of hybridisation buffer overnight at 55°C with 2μl of denatured RNA probe. Excess probes were removed through washes with hybridisation buffer and PBT. Prior to addition of primary antibodies, embryos were blocked for 30mins in 1x Blocking Reagent in PBT (Western Blocking Reagent, Roche). For detection of labelled RNA probes, the following primary antibodies were used: mouse monoclonal anti-Biotin-IgG (1:400, Roche), sheep polyclonal anti-DIG-IgG (1:400, Roche), rabbit polyclonal anti-DNP-IgG (1:400, ThermoFisher Scientific). Primary detection was performed overnight at 4°C in 400μl of 1x Blocking Buffer in PBT. Following incubation, excess primaries were removed with PBT washes and embryo re-blocked with 1x Blocking Reagent for 30mins. Subsequently, embryos were incubated for 1hr 30mins at room temperatur
    8. Embryo Collection: Embryos were collected at 25°C on apple juice agar plates from cages withapproximately 5ml of well-fed young flies. Collections were performed every 2hrs with plates aged at 18°C or 25°C After Egg Laying (AEL), as appropriate, resulting in a pool of embryos between 2-4hrs (Stage 5 to 9), unless otherwise stated.After ageing, collected embryos were washed with 1x NaCl/Triton X (68nM NaCl, 0.03% (w/v) Triton X-100) and loosened from plates with a brush. Embryos were subsequently dechorionated in 50% bleach for 2min and thoroughly washed, alternating between dH20 and 1x NaCl/Triton X. For RNA In-situ hybridisations, embryos were fixed with 4.625% formaldehyde for 20mins with 50% heptane and Fixing Buffer (0.5x PBS, 25mM EGTA pH 8.0). Following fixation, embryos are devitellinised using methanol, transferred to 100% ethanol and stored at -20°C. For Immunostaining, overnight plates with a maximum 12hrs of ageing were collected and dechorionated as above. Fixing was performed for 12mins with 1.85% formaldehyde, 50% heptane, and Buffer B (4.5mM KPO4, 6.75mM NaCl, 20.25mM MgCl2, 4.5mM NaP). Embryos were devitellinised as previously described, but stored in 100% methanol at 4°C.RNA Probe Synthesis: RNA probes for RNA in-situ hybridisation were synthesized using gene specific primers, flanked by the T3 and T7 promoters to transcribe sense or anti-sense probes respectively, except for the AncecDNA probes. All probes were designed against approximately 1kb of the target RNA unless otherwise constrained by sequence or target limits. All primers used to generate RNA probes are described in Table 2.1, including intronic or exonic position of probes. Anti-sense probes for Ancewere derived from Ance cDNA cloned between T3 and T7 promoters within pBluescript KS plasmid. Template is produced through PCR of the plasmid template using primers against the T3 and T7 promoters. Approximately 1ug of DNA template was used to generate labelled anti-sense RNA in a transcription reaction. Probes were either labelled with Biotin, Digoxigenin (DIG) or Dinitrophenol (DNP) labelled UTP in a mix with other nucleotides. The transcription reaction was carried out for 2 hrs at 37°Cusing, 1x transcription buffer (0.06M MgCl2, 0.1M NaCl, 0.02M Spermidine-HCl, 0.4M Tris pH 7.5), 10 Units RNAse inhibitor (Roche), 20 Units T3/T7 polymerase (Roche), 1x nucleotide mix (10mM ATP, 10mM GTP, 10mM CTP, 6mM UTP and 4mM Biotin, DIG or DNP labelled UTP (Roche)) and dH2O. The probes were then hydrolysed in 1x carbonate buffer (60mM Na2CO3, 40mM NaHCO3, pH 10.2) and incubated for 5mins at 65°C. Following hydrolysis, the reaction was stopped by the addition of 40μl dH2O, 50μl STOP solution (0.2M NaAc, pH6.0) for 5min and precipitated overnight at -20°C with 2μg of tRNA in 0.1M LiCl, and 100% ethanol. The sample was then centrifuged for 20mins at 13,000g and the pellet resuspended in 150ul of hybridisationbuffer (50% formamide, 750mM NaCl, 75mM sodium citrate, 100μg/ml ssDNA, 50μg/ml heparin, 0.1% Tween-80).
    9. Expression analysis of Drosophila Embryos
    10. Percentage lethality was calculated as:100×((number of non-CyO/ number CyO)×100)
    11. Flies were maintained at 18°C or 25°C as appropriate. Through out this thesis, flies defined as wild-type were yellow white of the genotype: y67c23w118. BEAF32 null lines BEAF32AB-KO/CyOGFP, kindly provided by Craig Hart, University of Illinois (Roy et al., 2007a). Homozygous BEAF32AB-KOlines were obtained by selection against the CyOGFPmarker at the 3rdinstar larvae stage, using a Leica M165 FC with a GFP filter. Lethality of the BEAF32AB-KOallele was assessed against the dppHr27hypersensitive allele (genotype: dppHr27,cn1,bw1/CyO P{dpp-P23}). For this embryos were collected from the following crosses as set up by Catherine Sutcliffe:BEAF32AB-KO/+ ×dppHr27,cn1,bw1/CyO P{dpp-P23}and+/+ ×dppHr27,cn1,bw1/CyO P{dpp-P23}
    12. Fly Stocks and Crosses
  2. Oct 2017
    1. We tested this –1/6 power-law dependence by measuring the lapping frequency for eight species of felines, from videos

      The authors wanted to test the relation they found between the mass and the lapping frequency.

      So in this experiments they calculated the lapping frequencies among different species of feline using videos available on the internet.

    2. To test the proposition that the column dynamics are set by a competition between inertia and gravity, we compared the height of the disk (Z) at pinch-off, ZP, with that predicted from our scaling analysis.

      To measure the impact of the inertia to gravity ratio, the authors compared the disk's height at pinch-off time observed in the experiments, with the one predicted with a simplified model.

    3. Experiments were therefore conducted over a range of Fr and H/R values (16), for a fixed lapping height, H = 3 cm, determined from observations (Fig. 2B).

      The authors repeated the experiment, changing the values of Fr, which is the ratio of the forces of inertia (upward pull) to gravity (downward pull), and the aspect ratio (the height of the water column divided by the radius of the disk).

    4. To help understand the mechanism of lapping, we performed physical experiments in which a glass disk of radius R (representing the tongue’s tip), initially placed on a water surface, was pulled vertically upward (Fig. 3).

      This experiment simulated the movement of the tongue while lapping. The authors used a glass disk to model the overall shape of the tongue and a piston to simulate its movement . This way, they accturately simulated a real cat tongue. This strategy enables to change easily the model in order to understand the relative importance of each of them and find the optimum model.

    5. We used high-speed imaging to capture the motion of both the tongue and liquid during lapping [Fig. 1 and movie S1 (16)].

      The use of high-speed imaging (500 frames/second in this experiment) enables the researcher's to collect accurate images about the position of the cat's tongue and the volume of the water column for many different time steps.

    6. Here, we report on the lapping mechanism of the domestic cat (Felis catus).

      The authors used cameras to record the tongue's motion of the cat when lapping water. The images showed water adheres to the dorsal side of the tongue. The authors then tried to reproduce this mechanism of adhesion by lifting a disk placed on the surface of water.

    1. Torque was applied to one ankle using a versatile exoskeleton emulator system (30) (Fig. 2, C and D, and figs. S2 and S3) with precise low-level torque control (31). The emulator, inspired in part by other laboratory-based testbeds (32–34), allows a wide range of assistive behaviors to be applied in rapid succession, without the need to design or build new hardware

      The methods the authors used required changes in the torque. So, instead of building different exoskeletons with different torque values, they decided to use an emulator, a device that will provide the same assistance and results as the exoskeleton, but with easily adjustable peak torque and timing of peak torque. This made it easier to test different generations with different torque values.

    2. The double-reversal validation test prevented confounding influences from measurement noise during optimization and trial order during validation (26). Participants were not exposed to any of the validation conditions during optimization, because optimized assistance was the weighted average of the best control laws from the final generation (26). The primary outcome was the energy cost of walking, defined as gross metabolic rate during walking minus the rate measured while standing still

      The double reversal test refers to the use of the 'zero torque' and 'static' models, compared to the adaptable one. This comparison is used to eliminate the author's possible bias when assuming his design and adjustments may influence positively his results. Therefore the authors use it to prove their hypothesis. For the static model, different configurations were tested while for the adaptable model, since it is based on an evolutionary framework, only the last generation is taken into account for the comparison.

    3. This parameterization also implicitly allowed adjustment of features such as the timing and amount of positive joint work, which may be important to energy economy (29). Some torque patterns were not possible with this parameterization, such as those with multiple peaks. More complex patterns, defined by additional parameters, might allow better approximations of global optima at the cost of lengthier optimization periods.

      Since the assistance (assistive ankle torque) depends on 4 parameters, these can be adjusted to allow different possible configurations. Adjusting the timing and positive joint work gave the authors better results, reducing the energy the user inputs in the exoskeleton to achieve movement. If more parameters could be controlled, more efficient configurations could be achieved, but the time to evaluate all of them will be lengthier.

    4. and the shape and size of the distribution are chosen to increase the likelihood of further improvement in subsequent generations. This optimization strategy is relatively tolerant of both measurement noise and human adaptation, because neither objective function values nor their derivatives are used directly, and each generation is evaluated independently

      Using the CAM-ES method, they adapt the control laws for optimization. First they run an algorithm to adjust the pattern of assistance that uses a set of control laws for a determined time, they gather the information for a determined period of time, make random changes and adaptions with CAM-ES and start over. Unlike other type of experiments, this one is designed to make up for common situations that cause errors, such as sudden abnormal values or human adaption to the machine (which reduces the energy input).

    5. We tested our method by optimizing the pattern of assistive torque applied by an exoskeleton worn on one ankle during walking. We applied assistance at one ankle to allow comparisons to a prior study that used the same hardware

      The authors decided to apply their method in an exoskeleton in only one ankle because the same equipment was used in another study in only one ankle. So they tried to replicate the same conditions so that any differences will be a result of their pattern of assistive torque. Therefore, they could see if their method (pattern of assistive torque) could get better results than the authors of reference #17.

  3. Sep 2017
    1. We performed a test of convergence with a subset of participants in the main study (n = 8) by continuing the optimization for an additional four generations

      To demonstrate that the number of generations chosen in the original test was optimal, they continued the experiment to see if the results continued to improve or varied in a significant way. The initial test was done with 11 participants. From this group, 8 were chosen to continue with the adjustments using the same algorithm and methodology to adjust the control laws.

    2. We optimized assistance for 11 participants (subjects 1 to 11; table S1) as they walked on a treadmill at a normal speed (1.25 m s−1). After optimization, we performed validation tests comparing optimized assistance with a fully passive “zero-torque” mode and with a “static” assistance condition. Static assistance approximated the best hand-tuned torque pattern for this device, which had previously resulted in a 6% reduction in energy cost compared to zero torque (17).

      Two systems were used as a comparison for the adaptable model. The first was the 'zero torque' in which the device did not exert any force to assist the person walking. The second was the device with a static assisting force, that did not change or adapt with time.

    3. forming one generation, a covariance matrix adaptation evolution strategy (CMA-ES) (28) is used to calculate the next generation of control laws to be tested

      After applying the formulas and algorithms (control laws) that regulate the changes in the assistance the exoskeleton gives the user, all the results are taken into account to improve the efficiency of the control laws. The method they use is CAM-ES, which imitates biological evolution. In a broad sense, it tends to keep the control laws that are more efficient and it randomly changes or adjusts those which don't produce the expected results of energy consumption by the user.

    4. Steady-state metabolic energy cost is estimated for each control law by fitting a first-order dynamical model to 2 min of transient metabolic data (fig. S1)

      Using the frequency and volume of respiration, CO2 production and oxygen consumption, the authors formulated a model (with first order differential equations) that estimates the metabolic rate.

    5. defined by a control law, while metabolic rate is measured

      The control laws are formulas that can be used to calculate and correct for the difference within the expected results and the actual results obtained. In this case, the difference between the expected energy consumption (metabolic rate) and the results obtained are considered in the control law that determines the changes in the pattern in which the device will assist the user.

    6. By using indirect calorimetry to measure metabolic rates, the authors were able to adjust the torque provided by the device while users were walking, running, and carrying a load

      The authors used gas exchange rate of oxygen and CO2 of the users breathing (indirect calorimetry) to measure how much energy was used when walking with their device, the ankle exoskeleton. The authors adjusted the device to reduce this energy input from the users for three activities: walking, running and carrying a load.

    1. Dimensional analysis reveals that two dimensionless parameters control lapping

      In order to find parameters that characterise the lapping, the authors used the fact that dimension units (m, s , kg,...) are identical in both side of an equation (example, if A and B are in meter (m), A/B is dimensionless, A*B is in meter square (m^2)). So, in this case, the two parameters are dimensionless.

  4. Mar 2017