The loss of skeletal muscle function with age, known as sarcopenia, significantly reduces independence and quality of life and can have significant metabolic consequences. Although exercise is effective in treating sarcopenia it is not always a viable option clinically, and currently, there are no pharmacological therapeutic interventions for sarcopenia. Here, we show that chronic treatment with pan-adiponectin receptor agonist AdipoRon improved muscle function in male mice by a mechanism linked to skeletal muscle metabolism and tissue remodeling. In aged mice, 6 weeks of AdipoRon treatment improved skeletal muscle functional measures in vivo and ex vivo. Improvements were linked to changes in fiber type, including an enrichment of oxidative fibers, and an increase in mitochondrial activity. In young mice, 6 weeks of AdipoRon treatment improved contractile force and activated the energy-sensing kinase AMPK and the mitochondrial regulator PGC-1a . In cultured cells, the AdipoRon induced stimulation of AMPK and PGC-1a was associated with increased mitochondrial membrane potential, reorganization of mitochondrial architecture, increased respiration, and increased ATP production. Furthermore, the ability of AdipoRon to stimulate AMPK and PGC1a was conserved in nonhuman primate cultured cells. These data show that AdipoRon is an effective agent for the prevention of sarcopenia in mice and indicate that its effects translate to primates, suggesting it may also be a suitable therapeutic for sarcopenia in clinical application. Sarcopenia is the generalized and progressive decline in skeletal muscle mass that is accompanied by reduced muscle strength and reduced physical performance . Loss ofSkeletal muscle composition is matched to function such that the muscles required for posture are not equivalent to those engaged in physical activity. Contractile content includes individual muscle fibers with differing force and endurance properties and differing metabolic fuel preference. Skeletal muscle also includes non-contractile components, including satellite cells and stromal-derived stem cells, vascular tissues, adipose, and extracellular matrix. With increasing age, muscle fibers undergo atrophy, and the levels of fibrosis and intra-muscular fat increase within and around the fiber bundles . SarcopeAdipor1 and Adipor2 receptors, with a poorly defined contribution from the T-cadherin receptor  or vehicle (PBS) were administered intravenously to 25-month-old C57BL/6J male mice three times per week for 6 weeks. AdipoRon treatment resulted in a decline in body weight in aged animals, which did not reach statistical significance . Body coThe therapeutic potential of AdipoRon was evaluated via in vivo and ex vivo functional measures. Baseline measures for rotarod did not differ between the groups; however, after 6 weeks of treatment, the AdipoRon treated animals tended to spend more time on the rotarod (p=0.08) suggesting a trend toward improved muscle function and agility . Ex vivopredominantly glycolytic muscle (Type IIb and Type IIx muscle fibers). Immunohistological detection of myosin isoforms in gastrocnemius muscle cross-section  were not altered by AdipoRon treatment. The Ppargc1 gene produces several isoforms including PGC-1a1 and PGC-1a4 from the canonical promoter and variants PGC-1a2, and PGC-1a3 from an alternate promoter  or vehicle (PBS) three times per week for 6 weeks by tail vein injections beginning at 2 months of age in male B6C3F1 hybrid mice. Chronic AdipoRon treatment did not alter body weight  fasting promoter . AdipoRoTo determine whether AdipoRon mediated changes in muscle function were coincident with changes in muscle composition, tissue sections from young mice were subject to immunodetection of myosin heavy chain isoforms. No changes in fiber cross-sectional area were identified, presumably because young mice are in peak physical condition . HistochPpargc1a expression were significantly higher in soleus than gastrocnemius muscle . Endogenous levels of s muscle , which is muscle . Interespargc1a3 . The posle types .Ppargc1a in gastrocnemius but not soleus muscle  were increased in response to acute AdipoRon treatment in gastrocnemius but not in soleus muscle  was investigated in muscles from young male B6C3F1 hybrid mice (6 weeks old) collected 90 min postinjection. AdipoRon treatment increased the gene expression of s muscle . Exercisificance . No chans muscle . Exercis Adipor2 . Within  Adipor2 . AdipoRoAdiponectin receptor stimulation by AdipoRon has been linked to activation of AMPK and PPARa  pathways in muscle and liver, including increased PGC-1a transcription and activation of expression of its gene targets . StudiesAdipor1 and Adipor2 are expressed in diverse cell types, including murine NIH-3T3, differentiated mouse myoblast C2C12 cells, and nonhuman primate peripheral blood mononuclear cells (PBMCs), although there is cell type specificity in levels and relative ratios of the two adiponectin receptors  were significantly increased at 10 µm and at 50 µm, indicating that PGC-1a activation at the lower dose of AdipoRon may occur at the posttranscriptional level. On day 7, differentiated C2C12 myotubes AdipoRon significantly induced phosphorylation of AMPK at Thr172  but not in predominantly oxidative soleus muscle. Skeletal muscle is known for its heterogeneous population of muscle fibers, each with distinct structural, biochemical, and metabolic properties. Studies in humans and nonhuman primates have previously demonstrated that there is a selective decrease in fiber size and mitochondrial activity of Type II fibers with aging   . CR is aion (CR) , which iAlthough these findings are promising, there are important caveats. The first is that the data shown here were generated in male mice only. Sex dimorphism is increasingly a focus in aging studies and across biomedical research . Our ongTwo cohorts of mice were used. Six-week-old male B6C3F1 hybrid mice were obtained from Jackson Laboratories  and 24-month-old male C57BL/6J mice from the NIA aged mouse colony. The animals were housed under controlled pathogen-free conditions. The animals were fed ad-libitum Purina LabChow 5001 diet with free access to water and placed on a 12-h light/dark cycle. AdipoRon (10 mg)  was reconstituted with 500 µl of DMSO (stock) and stored at –20°C. For the acute experiment, the animals were given either a single intravenous dose of AdipoRon @1.2 mg/kg BW in PBS (n=5) or an equivalent volume of DMSO in PBS  in a total volume of 100 µl. EDL and soleus muscle groups were harvested after 90 min. For the chronic experiments in young B6C3F1 mice (n=12) and old C57BL/6J mice (n=20), the animals in each age group were divided into two groups and received either AdipoRon @1.2 mg/kg BW in PBS or an equivalent volume of DMSO in PBS via tail vein injections three times per week  for 6 weeks. Body weight and food intake measurements were recorded once a week. Body composition was measured at the beginning and at the end of the treatment period using EchoMRI Body Composition Analyzer . Rotarod balance measures were performed on a Columbus Instruments Rotamax system. During the test, the instrument speed increased from 5 to 60 rpm over a 3-min interval. Animals were trained on the instrument 1 day prior to the test and were allowed three attempts during test. Time on the rotarod and the speed when the mice falls are recorded. At the end of the treatment period, animals were sacrificed. EDL, soleus, and gastrocnemius muscle specimens were mounted in OCT oriented to present fiber cross-section for tissue sectioning or snap-frozen in liquid nitrogen and stored at –80°C. All animal protocols were approved by the Institutional Animal Care and Use Committee at the William S. Middleton Memorial Veterans Hospital.Overnight fasting blood samples were collected for measures of glucose (OneTouch Ultra Blue glucometer), and insulin levels ). HOMA-IR (homeostasis model assessment of insulin resistance) index was calculated as [fasting serum glucose×fasting serum insulin/22.5].Metabolic parameters and activity were measured ) in mice acclimated to housing in the chamber for approximately 24 hr, followed by 24 hr continuous data collection period.2, 5% CO2) Tyrode’s solution at room temperature . Isolated muscles were attached to a contractile apparatus capable of measuring force (Aurora Scientific) and were electrically stimulated using parallel platinum electrodes. Maximal twitch force and tetanic force were determined by adjusting the length of the muscle until maximal twitch force is reached, defining the optimal length. A 15-min period of rest allowed muscle to equilibrate to the new environment. Fatigability was defined as the decline in tetanic force following 10 min of continuous stimulation. Muscles were tetanically stimulated at 100 Hz for 500 ms every 5 se at a voltage that generates the maximal force. Following 10 min of fatiguing stimulation, a 20-min recovery period was allowed, where there was no stimulation in an oxygenated Tyrode’s perfusion. After the recovery period, muscle was electrically stimulated again to quantify the amount of recovery force. A recovery force higher relative to fatiguing force was taken as an indication that the decline in force during fatiguing stimulation is reversible. The amount of fatigue and recovery force was represented as a percentage of the initial force (before fatiguing stimulation). Following these measurements, fatigued muscles were weighed, quick-frozen in liquid nitrogen, and stored at –80°C.EDL and soleus hindlimb muscles were dissected and perfused with oxygenated  were separated on Mini-Protean TGX precast protein gels  and transferred to a PVDF membrane using a Trans-Blot semi-dry transfer system . The membranes were blocked using 5% BSA in TBST for phospho-antibodies or 5% non-fat milk for other antibodies for 1 hr at RT. The following primary antibodies were used overnight: pAMPK Thr172 , AMPK , GAPDH , PGC1a , and Beta-Actin , washed in TBST, and incubated with the respective HRP-conjugated secondary antibodies  for 1 hr at RT. Proteins were detected  and digital images acquired (GE ImageQuant Gel Doc Imaging system). Densitometric analysis was carried out using Fiji software.∆∆Ct method . cDNA was synthesized from 1 µg of RNA (High-Capacity cDNA Reverse Transcription Kit [Applied Biosystems]). Real-time PCR reactions were carried out using iTaq Universal SYBR Green dye mix (Bio-Rad) with 10 ng cDNA per reaction. The treatment effect was analyzed by 2t method  and presary info  Table 1.Serial OCT mounted cryostat sections (10 µm in thickness) were cut at –14°C ). Freshly cut sections were stained for cytochrome c oxidase activity and digital images were captured the same day as described previously . BrieflyFiber types  were quantified in gastrocnemius muscle. Sections were air-dried for 30 min and then rehydrated with PBS for 5 min. Sections were then blocked with 0.5% BSA 0.5% Triton X-100 in PBS for 30 min at RT, then incubated with a cocktail of primary antibodies purchased from Developmental Studies Hybridoma Bank : BA-D5  specific for MyHC-I, SC-71  specific for MyHC-IIa and BF-F3  specific for MyHC-IIb for 1 hr at RT. After three washes with PBS (5 min each), the sections were incubated with secondary antibody cocktail (Invitrogen) to selectively bind to each primary antibody: goat anti-mouse IgG1 conjugated with Alexa Fluor488 ; goat anti-mouse IgG2b conjugated with Alexa Fluor350 ; goat anti-mouse IgM conjugated with Alexa Fluor594  for 1 hr in the dark at RT. After three washes with PBS (5 min each) and a brief rinse in water, the sections were mounted in 85% glycerol in PBS for imaging. Type IIa fibers will appear green, IIb as red, I as blue, and the fibers that are not stained by these antibodies will appear black and are classified as Type IIx.Digital images were captured using a 20× objective in a Leica DM4000B microscope equipped with Retiga 4000R digital camera . Background correction was conducted for all images using an unstained adjacent area of the slide. Images were converted to 8-bit format and inverted. Fiber type was classified based on immunostaining for myosin isoform and individual fibers were outlined using a freehand tool and the cross-sectional area. Stain intensity of the cytochrome c oxidase and succinate dehydrogenase was quantified using ImageJ/Fiji software. Using a custom-generated algorithm, the blue stained areas for collagen were separated and highlighted from the rest of the image and % stained area was quantified (MIPAR software). Mitochondrial analysis was performed on cells in ImageJ by applying image deconvolution, background subtraction, adaptive binarization, and segmentation algorithms, followed by particle analysis and morphology analysis with the ImageJ plugin MiNA  to quantNIH-3T3 fibroblasts were purchased  and cultured in DMEM supplemented with 10% bovine serum and 1% penicillin/streptomycin. The cells were treated with vehicle (DMSO in media) or AdipoRon (10 or 50 µM in media) for 10 (AMPK phosphorylation) or 60 min . After treatment, the cells were washed once with PBS and then lysed in TRIzol or RIPA buffer depending on the experiment. C2C12 cells were purchased  and grown in 10% bovine serum and 1% penicillin/streptomycin. Differentiation was initiated after 2–3 days growth by exposure to differentiation media: Serum-free DMEM supplemented with 2% equine serum, 1% penicillin/streptomycin, and 172 nM insulin. Myoblasts were fed differentiation media every 24 hr for 5–7 days until myotube morphology was reached. All cell lines were authenticated by STR profiling and cleared of mycoplasma contamination.4 overnight and treated with AdipoRon (50 µm) for 2 or 4 hr. Cells were then incubated for 30 min in 100 nM TMRE dye in media and, after equilibrating for 10 min, plates were read at 530 nm excitation/580 nm emission, parallel treatment with 10 µM uncoupler FCCP  accounted for mitochondrial oxidative phosphorylation. Data shown as fluorescent ratio of given treatment over uncoupled control. For oxygen consumption assays, cells were trypsinized and equal numbers (4×105) were resuspended in respiration buffer and loaded on to the PreSens Oxoplates . Appropriate ambient and anoxic controls were included in the same plate.Cells were treated with vehicle or AdipoRon (50 µM) for 2 or 4 hr. For TMRE fluorescence, cells were seeded at 5×10Relative ATP levels were quantified ATPLite assay ) in cells cultured as above and treated with vehicle or AdipoRon (50 µM) for the prescribed times.NIH-3T3 cell proliferation was quantified according to the CyQUANT Cell Proliferation Assay Kit  at four cell densities 1600–6700 cells/well. In brief, cells were seeded in microplate wells in growth medium at desired densities along with serial dilutions of cells for determination of a cell number standard curve. Cells were incubated for 24 hr after which culture medium was removed, and the number of cells quantified according to the manufacturer’s instructions.6) were cultured in 10 cm plates in DMEM supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin. Cells were treated with vehicle (DMSO in media) or AdipoRon (10 or 50 µM in media) for 5 (AMPK phosphorylation) or 60 min . PBMCs were collected by centrifugation and the cell pellet was washed and lysed in TRIzol or RIPA buffer.Blood was collected from primates at the Wisconsin National Primate Research Center (WNPRC) with the approval of the Institutional Animal Care and Use Committee of the Office of the Vice Chancellor for Research and Graduate Education of the University of Wisconsin, Madison. PBMCs were isolated from 6 ml of blood using SepMate-50 tubes . Isolated primate PBMC’s  involved in lipid and mitochondrial metabolism regulation to mitigate age-related muscle loss in mice. public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Carlos Isales as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: John C Newman (Reviewer #1).Thank you for submitting your article "Adiponectin receptor agonist AdipoRon improves skeletal muscle function in aged mice" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1) Use an additional, more reliable potentiometric dye (e.g. TMRE) instead to validate the JC-1 findings2) Justify the different time points or present time-course experiments for the cell culture results, possibly in a more relevant cell model. The use of 3T3 and PBMC instead of more relevant cell models3) Better description of the sample size, especially for endpoint measurements.Describe in more details the sample sizes for each cohort4) Re-evaluate the claims of improved muscle function and increased lipid metabolism.Optional – do the results hold true in the opposite sex, though I can understand if budgetary constraints prevent the authors for repeating the assays in female mice.Reviewer #1 (Recommendations for the authors):1) Overall this work provides a strong justification for continuing studies of AdipoRon in larger rodent experiments and in non-human primates, and provides excellent biomarker candidates for those. The underpowered mouse cohorts, though, leads to a lack of whole-animal muscle functional data. "Improved skeletal muscle function" and the like, used throughout, could be read to imply an improvement in relevant behavioral outcomes  which are not present here. Muscle mass does not increase in the aged mice either. This is the key issue to be careful with in the presentation of the findings.2) What were the final numbers in the aged cohorts? Methods states starting with 20 mice total, and Figure 1 legend says ending with 7-10 control and 6-8 AdipoRon. Did some mice die or were otherwise excluded? Were more of these in the AdipoRon group? One way or another, it is important to account for missing data and any signals of safety issues.3) I appreciate the prominent mentions of the limitations of a male-only study, although an even better approach would be to validate some of the findings in a female cohort! Given the pilot-sized experiments this seems not entirely unreasonable.4) As in the public review, why use different strains for young and old mice? I assume a practical reason  which is understandable enough but the limitations of cross-comparing different strains at different ages should be explicitly stated.5) As in the public review, why use NIH3T3 for in vitro pathway studies instead of a more muscle-like cell line or primary cell type? Similarly for using primate PBMCs. I didn't see confirmation that these cell types express adiponectin receptors, or other downstream components, and how similar the molecular responses are expected to be to muscle. Is there literature about PMBCs responding to adiponectin physiologically in vivo?6) The densitometry for Pgc1a in Figure 1I does not obviously correspond to the Pgc1a band intensity, and if normalized to Ponceau (which is not stated) the Ponceau difference between groups doesn't obviously account for a 2x difference in Pgc1a/Ponceau. This is worth a double-check.7) It is not always obvious what the reference condition is for presentation of "relative mRNA" and "mRNA Fold change" panels – one expects normalization to a comparison group mean set to 1.0 for each panel, but for most that comparison group is not clear.8) The in vitro acute treatments included varying treatment times, which were not always specifically described for each experiment in the legend or methods.9) The text states that food consumption was the same between groups in the aged mouse cohort, but these data do not appear to be shown. If food consumption is the same, activity is the same, and energy expenditure is the same, what explains the fat mass weight loss in the AdipoRon-treated group? Given the changes observed in fat metabolism and the loss of fat mass in old mice, why was no difference observed in RER?10) Why are the phenotype data that were collected different between the young and aged chronic treatment cohorts ? E.g. no body composition measurements, insulin, HOMA-IR, metabolic cages in young mice.11) A brief explanation of mTOR inhibition by AMPK activation (cell proliferation) could be included in the discussion of this study to further explain sarcopenia and other age-related muscle loss.12) The explanation of the glucoregulatory function in aged mice by AdipoRon could be accompanied by the catabolic pathways triggered by AMPK activation.13) The first two-thirds of the section titled "nonhuman primate cultured cells" continues to describe experiments in NIH3T3, which is confusing. The first sentence of the Figure 6 legend causes the same confusion, although the panel descriptions are clear which is which.14) In general, I appreciate the careful language used to describe suggestive but not statistically significant results.15) How was AdipoRon obtained? Was it donated by the company? Were there any considerations provided by the company for the study?Reviewer #2 (Recommendations for the authors):With the exception of the JC-1 assays, the study appears well done, with sufficient rigor in terms of numbers of animals used per group etc. However, in addition to the well known problems with the JC-1 dye being used to measure mitochondrial membrane potential, there a couple of minor quirks, which can easily be corrected.1) On page 4, references are made to Benton and Ruas as showing PGC-1a over expression protecting against muscle aging in mice. Neither of these papers show this. Benton et al. has no aging data. Ruas also has no aging data, and is in rats, not mice. Cite the correct references, and remove these.2) Rename the EchoMRI to "body composition measures". This is super confusing to those who don't know this instrument (it is neither "echo" nor "MRI").3) On page 5 there is reference to EDL and soleus being glycolytic and oxidative. As the authors point out repeatedly later on, these muscle are mixed fibre types, albeit heavily glycolytic or oxidative. I think there should be consistency on this point.Regarding JC-1, this results should be removed altogether for measuring mitochondrial membrane potential. Its problems have been documented extensively, and I'm not sure why investigators still use it. Its well known to be non specific to plasma membrane potential in addition to mitochondria, and has multiple problems with regards to specificity. The authors should revise their manuscript substantially on this point. Use of this assay spoils an otherwise good paper.Reviewer #3 (Recommendations for the authors):Page 6: "Expression levels of both receptors were numerically lower in AdipoRon treated mice. In soleus muscle, AdipoR1 expression was not altered with age  and AdipoRon increased expression, although neither change reached significance. AdipoR2 levels declined with age in soleus of control mice, but not in mice treated with AdipoRon."The two sentences seem to be at odds with one another. The first sentence is also not consistent with the data in figure S2.Page 9: JC-1 measurement of mitochondrial membrane potential can give artifacts, especially when fluorescence is measured via a plate reader and not visualized via microscopy or flow cytometry. I would encourage the authors to validate their results with TMRE or TMRM staining.Page 9: Why the different time points for measurements of cell proliferation, markers of mitochondrial function, and ATP levels (24 vs 48h vs 12h) ?Page 11: :The inference is a shift toward fatty acid fuel utilization, aligning with prior reports of lipid remodeling outcomes reported in renal endothelial cells"I don't know whether this inference is warranted without RER measurements or at least evidence of activation of fitty acid oxidation. Indeed, the in vivo indirect calorimetry failed to show a shift towards lipid catabolism, which is at odds with this statement.Page 12: Could you provide a justification for using only male animals and using two different strains between old and young animals?Page 13: Please include clone or catalog number for all antibodies used. Essential revisions:1) Use an additional, more reliable potentiometric dye (e.g. TMRE) instead to validate the JC-1 findingsWe have repeated the experiments on mitochondrial membrane potential using the TMRE dye as suggested. The outcome of increased membrane potential in response to AdipoRon treatment first detected using JC-1 is now validated with the new approach using TMRE and the data are shown in the revised Figure 5. We have also validated this outcome in an additional cell type (differentiated C2C12) now shown in the revised Figure 6.2) Justify the different time points or present time-course experiments for the cell culture results, possibly in a more relevant cell model. The use of 3T3 and PBMC instead of more relevant cell modelsWe have conducted parallel experiments in differentiated C2C12 myotubes and confirm that AdipoRon activates expression of PGC-1a and its targets in addition to increasing membrane potential as measured by TMRE. We have revised text to justify the selection of time points for the various measured parameters.3) Better description of the sample size, especially for endpoint measurements.Describe in more details the sample sizes for each cohortWe apologize that this was not clearer before, we have revised the manuscript accordingly.4) Re-evaluate the claims of improved muscle function and increased lipid metabolism.We have toned down the language here, and throughout make a clear distinction between statements referring to the data shown and those that are inference or speculation on our part.Optional – do the results hold true in the opposite sex, though I can understand if budgetary constraints prevent the authors for repeating the assays in female mice.We have just completed a follow up study using oral delivery of AdipoRon for a longer duration (4 months) in males and females and can confirm that AdipoRon treatment is associated with improvements in indices of systemic metabolism in males and females. In this study AdipoRon is associated with significant protection against age-related functional loss in males, although the study is not yet complete and we expect longitudinal analysis will yield greater insight than a cross-sectional approach. We are currently assessing the tissue, cellular, and molecular effects of aging and of AdipoRon in both males and females.Reviewer #1 (Recommendations for the authors):1) Overall this work provides a strong justification for continuing studies of AdipoRon in larger rodent experiments and in non-human primates, and provides excellent biomarker candidates for those. The underpowered mouse cohorts, though, leads to a lack of whole-animal muscle functional data. "Improved skeletal muscle function" and the like, used throughout, could be read to imply an improvement in relevant behavioral outcomes  which are not present here. Muscle mass does not increase in the aged mice either. This is the key issue to be careful with in the presentation of the findings.We agree with the reviewer on this point. In revising the manuscript, we have been careful to distinguish between statements of fact that those that are more interpretive or speculative. We recognize the limited set of parameters measured here, and as this reviewer will appreciate it is tricky with mice to get estimates of muscle mass in vivo – most investigations just report “lean mass” which is not muscle of course but everything that is not fat. As mentioned in our response above we have been conducting a follow-up study in mice that will allow for a more detailed investigation of the tissue, cellular, and molecular signatures of aging and of the response to AdipoRon.2) What were the final numbers in the aged cohorts? Methods states starting with 20 mice total, and Figure 1 legend says ending with 7-10 control and 6-8 AdipoRon. Did some mice die or were otherwise excluded? Were more of these in the AdipoRon group? One way or another, it is important to account for missing data and any signals of safety issues.We agree. In the revised figures we now specify the numbers of animals/observations contributing to the data reported. We lost 2 of the AdipoRon mice but given the advanced age of the cohort this was not unexpected. We were limited to the 20 starting mice and a loss of 2 (10%) in the period from 25 to 27 months of age (the study period) is aligned with the mortality expectation for this line for which 50% mortality is around 30 months of age.3) I appreciate the prominent mentions of the limitations of a male-only study, although an even better approach would be to validate some of the findings in a female cohort! Given the pilot-sized experiments this seems not entirely unreasonable.As mentioned above we have undertaken a follow up study and are analyzing the tissues now. The study described in this manuscript was exploratory and at the time we could only work with what was to hand. The follow up study is more comprehensive but we are eager to share our results now as we see terrific promise in the use of adiponectin receptor stimulation as a means to counter skeletal muscle aging. Our hope is that this paper will draw others to investigate metabolism as a target for delaying aging in skeletal muscle and hopefully in a shared effort we can move the field forward.4) As in the public review, why use different strains for young and old mice? I assume a practical reason  which is understandable enough but the limitations of cross-comparing different strains at different ages should be explicitly stated.We realize the importance of genetics and highlight this limitation in the revised manuscript. We would add that our follow up study in C3B6F1 hybrid mice reproduces the outcomes described here. In those mice there was very little impact of AdipoRon in young mice that were fit and healthy (6 months of age), modest differences in metabolic and functional outcomes late middle age (22 months) and significant differences at advanced age (28 months).5) As in the public review, why use NIH3T3 for in vitro pathway studies instead of a more muscle-like cell line or primary cell type? Similarly for using primate PBMCs. I didn't see confirmation that these cell types express adiponectin receptors, or other downstream components, and how similar the molecular responses are expected to be to muscle. Is there literature about PMBCs responding to adiponectin physiologically in vivo?We have conducted analysis of AdipoR1 and AdipoR2 expression in each of the cultured cell models , and these data are now shown in Figure 6. We do expect there to be cell type specificity in the outcome of AMPK/PGC-1a axis activation as this is a primary mode of action for adiponectin receptor stimulation; however, we suspect that there will be differences by cell type as far as the cellular consequence. Of relevance here, we expect differences by muscle group in the molecular consequence of AMPK/PGC-1a activation depending on fiber type distribution. Other skeletal muscle tissue resident cell types may also contribute. We know that age can impact tissue composition , and recognize the potential for differences in the responsiveness of various effectors both upstream and downstream in the signaling pathway. We should be able to make some headway in defining these differences in our ongoing follow up study.6) The densitometry for Pgc1a in Figure 1I does not obviously correspond to the Pgc1a band intensity, and if normalized to Ponceau (which is not stated) the Ponceau difference between groups doesn't obviously account for a 2x difference in Pgc1a/Ponceau. This is worth a double-check.We apologize for this error, there was a mistake in the quantification that I didn’t catch and I am relieved that you spotted this so we could fix it. We now show that the enrichment of PGC-1a protein is ~1.5 fold and state that the relative density based on normalization to ponceau, now shown in revised . As might be expected we do have some variability among individuals but this is a common feature in aging studies, in fact we believe that increased variance is a trait of aging and are pursuing this idea in our primate studies.7) It is not always obvious what the reference condition is for presentation of "relative mRNA" and "mRNA Fold change" panels – one expects normalization to a comparison group mean set to 1.0 for each panel, but for most that comparison group is not clear.We apologize for not being clear in our description. Briefly, there were two main ways in which the data were presented. The first, labeled “relative expression” shows the data as δ-CT against 18S, for this allows for comparison of expression among transcripts detected in the same specimen and is applied only for primer sets of equivalent efficiency. The second, labeled “fold change” normalizes the controls to 1 to emphasize the impact of AdipoRon. We now include this description in the methods and clarify in the text which comparisons are being made.8) The in vitro acute treatments included varying treatment times, which were not always specifically described for each experiment in the legend or methods.We apologize for the oversight, these details are now provided.9) The text states that food consumption was the same between groups in the aged mouse cohort, but these data do not appear to be shown. If food consumption is the same, activity is the same, and energy expenditure is the same, what explains the fat mass weight loss in the AdipoRon-treated group? Given the changes observed in fat metabolism and the loss of fat mass in old mice, why was no difference observed in RER?The reviewer raises important issues, a few explanations come to mind. Although we did not see differences in 12hour averages for EE or RER or activity, on closer inspection looking at 15-minute increments we do see changes indicative of differences between control and AdipoRon treated animals, but at specific time intervals only. These data are now shown in revised Figure 1. The magnitude of difference is modest; however, having the animals in the cages to acclimatize 24 hours before the start of measures means that they are at least a day out from the last injection with AdipoRon. In addition, the mice had continuous access to food such that circadian rhythm is quite blunted. In our experience, meal fed animals show much clearer profiles of fed and fasted but that was not the case with ad libitum feeding regimen used here. In hindsight it might have been worth conducting additional measures directly following injection and that is something we can consider doing in a separate group of mice. We would add confidentially that in our follow up study the trends reported here are reproduced, both males and females show changes in their RER and EE patterns, being quicker to adapt to feeding and to resolve post feeding.10) Why are the phenotype data that were collected different between the young and aged chronic treatment cohorts ? E.g. no body composition measurements, insulin, HOMA-IR, metabolic cages in young mice.Substantive changes in young animals were not expected, mice of 6 months of age were lean and fit. In our follow up study, we confirm body and HOMA-IR effects in old C3B6F1 hybrid mice. We now provide insulin data from the young mice on AdipoRon showing that insulin levels are not altered, based on the fact that the body weight did not differ we would argue a change in body fat is unlikely.11) A brief explanation of mTOR inhibition by AMPK activation (cell proliferation) could be included in the discussion of this study to further explain sarcopenia and other age-related muscle loss.Thank you for this great suggestion. We have added this to the discussion.12) The explanation of the glucoregulatory function in aged mice by AdipoRon could be accompanied by the catabolic pathways triggered by AMPK activation.This is also a great suggestion, we have added it to the discussion.13) The first two-thirds of the section titled "nonhuman primate cultured cells" continues to describe experiments in NIH3T3, which is confusing. The first sentence of the Figure 6 legend causes the same confusion, although the panel descriptions are clear which is which.Good point. We have rewritten this section addressing this concern and adding the new data on the differentiated C2C12 as shown in revised Figure 6.14) In general, I appreciate the careful language used to describe suggestive but not statistically significant results.Thanks, as mentioned above aging is accompanied by increase in variance for a host of measured parameters. We favor discussing all outcomes that we believe are biologically meaningful while being careful to note whether or not there was statistical significance in differences reported.15) How was AdipoRon obtained? Was it donated by the company? Were there any considerations provided by the company for the study?AdipoRon was obtained at considerable cost. As indicated in our declaration of no conflict, we did not receive favor or inducements of any kind from the manufacturer or any other party.Reviewer #2 (Recommendations for the authors):With the exception of the JC-1 assays, the study appears well done, with sufficient rigor in terms of numbers of animals used per group etc. However, in addition to the well known problems with the JC-1 dye being used to measure mitochondrial membrane potential, there a couple of minor quirks, which can easily be corrected.We have replaced the JC-1 assay with the TMRE as recommended. Although the outcome is similar, TMRE confirms the ability of AdipoRon to impact mitochondrial membrane potential, we are eager to make sure we are using the right tool for the job by eliminating the possibility that our signature is compromised by changes in extra-mitochondrial membranes. Thank you for bringing this to our attention.1) On page 4, references are made to Benton and Ruas as showing PGC-1a over expression protecting against muscle aging in mice. Neither of these papers show this. Benton et al. has no aging data. Ruas also has no aging data, and is in rats, not mice. Cite the correct references, and remove these.We have removed the incorrect references and replaced them with the correct ones.2) Rename the EchoMRI to "body composition measures". This is super confusing to those who don't know this instrument (it is neither "echo" nor "MRI").Thanks for pointing this out, we have made the suggested correction to our manuscript.3) On page 5 there is reference to EDL and soleus being glycolytic and oxidative. As the authors point out repeatedly later on, these muscle are mixed fibre types, albeit heavily glycolytic or oxidative. I think there should be consistency on this point.The reviewer is spot on here and we apologize for not being clearer about this in our initial submission. We have revised the manuscript to make sure we are consistent in our description of the fiber type and metabolic setting of the different muscle groups.Reviewer #3 (Recommendations for the authors):Page 6: "Expression levels of both receptors were numerically lower in AdipoRon treated mice. In soleus muscle, AdipoR1 expression was not altered with age  and AdipoRon increased expression, although neither change reached significance. AdipoR2 levels declined with age in soleus of control mice, but not in mice treated with AdipoRon."The two sentences seem to be at odds with one another. The first sentence is also not consistent with the data in figure S2.We are grateful to the reviewer for picking up on this clumsy wording. The first part is about gastrocnemius and the second refers to soleus. We have revised the text accordingly.Page 9: JC-1 measurement of mitochondrial membrane potential can give artifacts, especially when fluorescence is measured via a plate reader and not visualized via microscopy or flow cytometry. I would encourage the authors to validate their results with TMRE or TMRM staining.Thanks, we have replaced the JC-1 with TMRE as requested, please see our responses to reviewers 1 and 2 above.Page 9: Why the different time points for measurements of cell proliferation, markers of mitochondrial function, and ATP levels (24 vs 48h vs 12h) ?The timing of the experiments was matched to the outcomes being measured. For the immediate responses, cell signaling through AMPK and PGC-1a directed gene expression, we measured within 90 mintues based on time course experiments. The activation of AMPK is transient, as is the activation of gene expression. For physiological responses, membrane potential and respiration, we measured hours after exposure and show data from 2 and 4 hours. For ATP production we include data that we had left out initially. At 2 and 4 hours ATP production is lower but then corrects and is elevated relative to untreated cells at 12 hours. We have no explanation for the biphasic response which is why we had left it out of the initial submission. For proliferation we were guided by the doubling time of the cells, and for the and mitochondrial remodeling we were guided by a time course showing gradual changes that become significant at 24 hours and persist to 48 hours. We have included some of this detail in the revised manuscript and hope we have struck the correct balance with just enough information without getting lost in the detail.Page 11: :The inference is a shift toward fatty acid fuel utilization, aligning with prior reports of lipid remodeling outcomes reported in renal endothelial cells" I don't know whether this inference is warranted without RER measurements or at least evidence of activation of fitty acid oxidation. Indeed, the in vivo indirect calorimetry failed to show a shift towards lipid catabolism, which is at odds with this statement.We have rephrased this sentence to separate out what is known and reported previously in the literature from speculation on our part. The reviewer is correct that the definitive test would be done using ex vivo tissues to demonstrate preference for lipid fuel. We are pursuing this avenue now but in the meantime have made changes in the revised manuscript.Page 12: Could you provide a justification for using only male animals and using two different strains between old and young animals?At the time these experiments were conducted we were limited by what was available. We expanded our thoughts on these limitations in the discussion. Please also see the responses to reviewers 1 and 2 above.Page 13: Please include clone or catalog number for all antibodies used.Thank you for pointing out this oversight, this information is now provided.


Predicting upper limb capacity recovery is important to set treatment goals, select therapies and plan discharge. We introduce a prediction model of the patient-specific profile of upper limb capacity recovery up to 6 months poststroke by incorporating all serially assessed clinical information from patients.Model input was recovery profile of 450 patients with a first-ever ischaemic hemispheric stroke measured using the Action Research Arm Test (ARAT). Subjects received at least three assessment sessions, starting within the first week until 6 months poststroke. We developed mixed-effects models that are able to deal with one or multiple measurements per subject, measured at non-fixed time points. The prediction accuracy of the different models was established by a fivefold cross-validation procedure.A model with only ARAT time course, finger extension and shoulder abduction performed as good as models with more covariates. For the final model, cross-validation prediction errors at 6 months poststroke decreased as the number of measurements per subject increased, from a median error of 8.4 points on the ARAT (Q1–Q3:1.7–28.1) when one measurement early poststroke was used, to 2.3 (Q1–Q3:1–7.2) for seven measurements. An online version of the recovery model was developed that can be linked to data acquisition environments.Our innovative dynamic model can predict real-time, patient-specific upper limb capacity recovery profiles up to 6 months poststroke. The model can use all available serially assessed data in a flexible way, creating a prediction at any desired moment poststroke, stand-alone or linked with an electronic health record system. Predicting poststroke motor recovery is important to set realistic and feasible treatment goals, select effective therapies and determine adequate discharge policy and long-term management.Until today, a large number of prediction models for poststroke upper limb motor recovery have been developed  scores. Subsequently, we investigated how this dynamic model can take time-dependent clinical improvement of patients into account as soon as new information is available. After comparing several model alternatives, we cross-validated the accuracy of the predictions and developed an online patient-specific model in which the predicted outcome can be used at stroke units and throughout the care chain for predicting the recovery profile of upper limb capacity.We combined data on upper extremity capacity recovery in first-ever ischaemic anterior circulation stroke patients from four early poststroke prospective cohort studies with repeated measurements in time: the EXPLICIT,All datasets contain repeated measurements of the ARAT scores after the stroke. Patients in the 4D-EEG and EXPLORE cohorts were recruited within 3 weeks poststroke. Patients in the 4D-EEG study and the EXPLORE study were measured in the first week poststroke and after 5, 12 and 26 weeks. In the EXPLICIT study, patients were measured 1, 2, 3, 5, 12 and 26 weeks poststroke and in the EPOS study in the first 3 days, at day 5 and 9 and after 6 months. All studies included adult patients with a monoparesis or hemiparesis within the first 72 hours after stroke onset, without disabling medical history and with no severe deficits in communication, memory, or understanding that impede proper measurement performance.Patients received standard rehabilitation treatment according to the Dutch rehabilitation guidelines, which are in agreement with current international rehabilitation guidelines.In line with recent international recommendations,We included the following potential demographic and clinical covariates variables during the model development: age, gender, affected bodyside, dominant side, Bamford scale ,As time-dependent variables, we included the Fugl Meyer Upper Extremity (FM-UE) motor score (range 0–66).For model fitting, we included all patients with at least three repeated measurements from which the first and last measurements were at least 12 weeks apart. We excluded patients for the model fitting who showed an FM-EU decrease beyond the upper limit of the clinically important difference for the FM-UE (7.25) in the first 6 months.As a first step in the model fitting, we compared mixed-effects models with different time structures to investigate whether a nonlinear time, compared with a linear time structure, was more appropriate to capture the mean recovery profile of the ARAT (fixed effects) and the subject-specific ARAT evolutions (random effects). For the models with nonlinear time structures, we used natural cubic splines with a different number of knots. The knots were placed at the quartile points in the case of 1, 2 and 3 knots and placed manually in the case of 6 knots.Subsequently, we developed models with different fixed effect structures, starting from the most complex model with all covariates mentioned above see also . More spWe selected the optimal model from the above-mentioned models by comparing the prediction accuracy of the models. To express model accuracy, we calculated the absolute error between the predicted and the observed (true) ARAT measurement and presented the distribution of the errors using box-plots with the median, the IQR, the lower whisker presented as Q1 - 1.5 * IQR and the upper whisker presented as Q3 +1.5 * IQR. Values outside the range . The packages nlme (V.3.1.144) and JMbayes (V.0.8.85) were used. In particular, we used the function lme from the package nlme to fit the models and the function IndvPred_lme from the package JMbayes to obtain the dynamic predictions.For all analyses, R (V.3.6.1) software was used , so that recorded data from individual patients can be used to display the predicted outcome without further data entry or analysis. Finally, we published the source code of the prediction models web-based, allowing other centres to develop similar real-time prediction tools , as a model of how more computationally complex prediction models can be coupled to electronic health record data or other types of online healthcare data collection systems.Online access to a real-time tool to predicting upper extremity recovery for an individual patient can be found at In the current study, we introduce an innovative mixed-effects model able to predict the patient-specific time course of upper limb recovery, including the associated limits of uncertainty within the first 6 months poststroke. We found that a model with only ARAT time course, FE and SA performed as good as models with more covariates for predicting the ARAT over time. In this final model, cross-validation prediction errors at 6 months poststroke decreased as the number of measurements per subject increased, from a median error of 8.4 points on the ARAT when one measurement early poststroke was used, to 2.3 for seven measurements. Linking this model with an electronic health record system at stroke units and rehabilitation wards will allow clinicians to obtain and visualise real time a patient’s recovery profile early poststroke.In contrast to prognosis based on regression models, a major strength of current dynamic prediction modelling is that individual patient-specific neurological and functional recovery profiles are taken into account. By making the model accessible online and potentially connected to electronic health record systems, professionals can obtain predictions without needing to perform complex computations. At any given moment in time, such as in individual patient consultation or multidisciplinary team meetings, an individual prediction of the recovery profile of the ARAT may be generated, taking into account all available data points.https://emcbiostatistics.shinyapps.io/DynamicPredictionARATapp/We found that a model with only time-depended improvements in SA and FE predicted recovery as accurately as more complex models that included covariates such as age, gender, the Bamford classification, the NIHSS or the full FM-UE score, which is in line with the SAFE model.Since the implementation of prediction models in clinical care depends on the ease of use, an important benefit of the present algorithm is that it can be an integral part of existing electronic health record systems at stroke units, allowing direct access to the model input variables. Since the current study also shows that serial measurements in time after discharge from stroke units have an important added value in the accuracy of individual predictions, preferably, patient-specific prediction modelling should be part of electronic health record systems that span the entire chain of care of stroke services. The current prognostic study further emphasises the need for consensus on using clinically validated assessments including neuroimaging within stroke services.A strength of our innovative statistical approach is that it is possible to predict a patient-specific recovery profile of the upper paretic limb using only simple demographic and relatively easy to measure clinical information from electronic health record systems at stroke units. After cross-validation, we showed that the accuracy of prediction improved by retesting patients serially in time. This finding further emphasises the need for building regional stroke services in which clinicians working in the chain of settings use the same core set of clinical outcomes poststroke as recently recommended in an international consensus meeting.The current study predicts the 6-month outcome on the ARAT scale based on a population of first-ever, ischaemic hemispheric strokes measured from 2005 onwards in the Netherlands. The predicted time course shown is irrespective of differences in type and intensity of rehabilitation therapies applied, which were applied according to the Dutch Stroke guidelines.A limitation of our study is that we were restricted to clinical time-dependent variables alone, such as synergism, strength, voluntary shoulder and FE. With that, our clinical model has room for improvement, especially in those patients with low baseline motor scores who may or may not show neurological recovery. This is in line with previous studies indicating less accurate outcome prediction in patients with low FM-UE scores <18 points) within the first week poststroke. points wA strength of our model is that we predict the exact ARAT score as well as prediction uncertainty. For clinical purposes, this level of detail may not always be needed and classifications of the ARAT scores in four different levels have been proposed


A live-cell analysis platform measures growth rate and phenotypic properties of up to 100,000 clones per experiment. Single-cell analysis tools have made substantial advances in characterizing genomic heterogeneity; however, tools for measuring phenotypic heterogeneity have lagged due to the increased difficulty of handling live biology. Here, we report a single-cell phenotyping tool capable of measuring image-based clonal properties at scales approaching 100,000 clones per experiment. These advances are achieved by exploiting a previously unidentified flow regime in ladder microfluidic networks that, under appropriate conditions, yield a mathematically perfect cell trap. Machine learning and computer vision tools are used to control the imaging hardware and analyze the cellular phenotypic parameters within these images. Using this platform, we quantified the responses of tens of thousands of single cell–derived acute myeloid leukemia (AML) clones to targeted therapy, identifying rare resistance and morphological phenotypes at frequencies down to 0.05%. This approach can be extended to higher-level cellular architectures such as cell pairs and organoids and on-chip live-cell fluorescence assays. In recent years, advances in sequencing technology have enabled deep, clonally resolved views into the genomic and transcriptional heterogeneity that exists within cellular populations  and representing the fluid flow along the paths connecting the nodes as equivalent resistors. The flow profiles in the resistor network can be solved by standard matrix solvers in many cases analytically.For example, the trapping geometry used in the Fluidigm C1 instrument, and also studied by others , is higher than the resistance through the serpentine bypass section, RS (the opposite ladder rail). Another way to view the different flow states is that the pressure at the exit of one trap can be higher (or lower) than the pressure at the entrance of the next adjacent trap. If the pressure is higher (lower), then the flow in the short bypass will point toward (away from) the entrance of the adjacent trap, as depicted by the red (blue) arrows in In this work, we investigate the third class of weir traps that have a hexagonal arrangement, which leads to more uniform flow profiles across each trap, which we expected to improve performance in long-duration cell cultures. These flow architectures can be arranged in one-dimensional (1D) ladder or 2D mesh resistor networks, and they are unique in that they support two flow regimes depending on the ratio of the resistance in the bypass relative to that of the trap. The transition between the two flow states is achieved by tuning the fluidic resistances in the rails of the ladder  at the microfluidic outlet. The remaining cells are then rinsed from the device by washing the inlet several times and then flowing clean filtered media through the chip for another minute, leading to a trapping distribution similar to that shown in To load the cells onto the chip, a cell suspension at a concentration of 10Once the traps are filled, the cells are transferred into the apartments by applying a subsecond elevated pressure pulse, which squeezes the cells through the constrictions into the adjacent apartments. These mechanical perturbations are benign and have been successfully used in various drug and gene delivery applications  the number of traps that end up capturing a single cell  and (ii) the number of cells needed to completely fill all of the traps, which is related to how the cells are distributed in each of the parallel channels during the loading process. Both of these parameters need to be optimized to effectively make use of limited cell samples. Because this design is very efficient at capturing cells, the 6016 traps in the device are consistently filled when ~10,000 cells are introduced to the inlet. Because of the combination of fabrication defects, presence of debris in the cell culture media, and incompletely dissociated cell suspensions, the trap occupancy for MOLM-13 cells was found, on average, to yield ~80% single cells, ~10% empty apartments, and ~10% apartments having more than one cell .This platform has the ability to organize other types of cellular architectures for myriad potential cellular analysis applications by tuning the device geometry and/or serially repeating the trap and transfer process. The ability to form heterogeneous cell pairs , for exaThis device can be modified to form reproducible cell groupings in a single shot by opening up the front trap, as shown in The chips are fabricated by deep reactive ion etching (DRIE) of silicon wafers, then anodically bonding the wafers to glass lids, followed by dicing the wafers into individual chips, and finally assembling the chips into a custom-machined microfluidic chip holder . This fabrication approach can be readily accomplished in a standard university cleanroom and allowed us to fabricate features as small as 2 μm. The microfluidic architecture was designed such that cells were able to squeeze through the front traps having 3- to 6-μm constrictions; however, cells were retained by the parallel frit structure at the back of the apartments that had smaller 2-μm constrictions. This geometry allowed fluid to pass through the apartments while retaining the cells inside the apartments over many days, enabling the study of clonal growth patterns and variability in morphological features.To achieve steady perfusion of media into the chips while inside the incubator, we connect 10-ml syringes to the inlet and outlet, which serve as media reservoirs. We fill the inlet syringe with media while the outlet syringe is connected to a vacuum line. In this way, we ensure that the media reservoir at the inlet has unimpeded gas exchange with the ambient conditions inside the incubator. We maintain good cell viability by using weak vacuum pressures in the range of −20 to −50 mbar to continuously flow media through the device. For this specific chip, an optimal flow rate of ~5 ml per day is sufficient to remove metabolic waste products and provide fresh nutrients. However, the exact flow rates need to be tuned for other microfluidic geometries, cell types, and other experimental parameters.The simplicity of this microfluidic design allows resealable connections to be made easily between the chip and the external pressure controllers, which enables many on-chip experiments to be conducted in parallel (fig. S1A). Each day, the chip is disconnected from the pumping system to perform imaging on a standard fully automated microscope (fig. S1B). To rapidly acquire high-resolution images of each apartment in the chip, we developed imaging algorithms that use microscope image quality focus classifiers  as well as a phycoerythrin (PE)–conjugated antibody against CD45, a marker expressed on all hematopoietic cells . Paired FLT3, a gene mutated in ~30% of acute myeloid leukemia (AML) patients and associated with poor prognosis  or 0.5 or 1.5 nM of the FLT3 inhibitor quizartinib (AC220). MOLM-13 cells harbor the internal tandem duplication (ITD) in-frame insertion in During long-term culture, the flow through the chip needs to be fast enough so that the metabolic waste products from upstream apartments do not substantially affect the downstream apartments. The vacuum pressure required to achieve an optimal flow rate was found to be in the range of −30 to −70 mbar, depending on the total number of cells in the chip. When exposed to a vacuum pressure of −50 mbar, the heatmaps in 2, with the middle quartiles ranging from 128 to 144 μm2, whereas at 0.5 nM quizartinib the mean cell areas were reduced to a median of 126 μm2 and with the middle quartiles ranging from 119 to 133 μm2. However, we did not observe similar trends in the relationship between cell shape (eccentricity versus growth rate) as shown in fig. S2. These relationships are further exemplified in fig. S3, which shows a parallel coordinate plot linking the individual cell trajectories to the size dependence. The similarity of the growth trajectories across different cohorts was also classified with t-SNE (t-distributed stochastic neighbor embedding) plots in fig. S4.We also observed a consistent, positive correlation between cell area and growth rates across the different drug conditions, likely reflecting FLT3 ITD’s established control over cell size and proliferation regulators like the mechanistic target of rapamycin (mTOR) and extracellular signal–regulated kinase (ERK) pathways, respectively . The photoresist mask is then stripped and cleaned in piranha solution (3:1 H2SO4 to H2O2 at 200°C). Next, a 15-μm-thick layer of AZ 9260 photoresist is spun onto the backside of the wafer at 500 rpm for 5 s and 1800 rpm for 60 s, baked at 110°C for 60 s, exposed to 4000 mJ/cm2, and developed for 300 s in AZ 400K 1:4 developer. This layer is used to create through-silicon vias to establish the inlets and outlets and dice the chips. The photoresist is then stripped and thoroughly cleaned as described previously. Last, we anodically bond borosilicate glass to the silicon microchannels at 300°C for 3 hours. In total, each wafer yields 12 devices (chips), which have dimensions of 30 mm × 25 mm.Microfluidic chips are fabricated on 6-inch wafers using DRIE to form the channel walls, as previously described . The chip holders were also anodized  to ensure that they would last inside the high humidity environment of a cell culture incubator for long durations. The chip holders were placed onto a custom stage adapter and mounted on an ASI-RAMM microscope , which contains an automated focus drive, an objective changer, and a filter changer. Fluid was introduced to the chip with an Elvesys pressure controller  that applied vacuum pressure at the outlet.Custom-made chip holders were machined in Aluminum , comprising a bottom holder and a top-viewing window. The bottom piece contained 2 environment. Cells were passaged in T25 flasks and centrifuged for 5 min at 350 relative centrifugal force before subculturing to maintain a density range of 2.0 × 106 to 3.0 × 106 cells per milliliter. A new thaw of cells was used every 8 weeks to minimize genetic drift. Counting and viability with 0.4% trypan blue were determined with a Countess II instrument (Thermo Fisher Scientific). Quizartinib (AC220) was obtained from Selleck Chemicals LLC.MOLM-13 AML cells —this provided a lethal radiation dose to any nonspecifically adhered cells and prevented the chips from being invaded with cells at later time points. Last, the cells were squeezed through the constrictions by applying a brief (~1-s) pressure pulse in the range of 300 to 800 mbar to the outlet, similar to previously reported techniques  was added to ~50 μl of media at the microfluidic inlet port and flowed onto the chip using negative pressure (−100 mbar) applied at the microfluidic outlet. Constant flow was maintained for 10 to 15 min to stain cell nuclei, followed by rinsing with media. Similarly, 5 μl of PE-conjugated anti-CD45  was flowed in, incubated, and rinsed before imaging. Multichannel images were collected in brightfield and using standard 4′,6-diamidino-2-phenylindole (DAPI) and Texas Red filter sets.Chips were loaded with MOLM-13 cells and cultured in 0.2 μm–filtered R10 media at 37°C and 5% COWe developed custom python codes to rapidly analyze the images and extract cellular phenotypic properties in a computationally efficient manner. Our cell extraction algorithms make use of the Mask R-CNN image segmentation model , given an image containing multiple apartments . Images of individual apartments were then extracted using these markers. Because the raw microscope images often have slight rotations, the relative positions of the identified markers in adjacent apartments were used to infer an overall rotation of the images to be inverted before further decomposing the individual apartment images. The apartment images were then registered against a template image to remove small translations. The digit identifiers for each apartment, with no rotations or translations, were extracted on the basis of fixed offsets from the marker position. Fixed offsets are determined relative to several chip landmarks and need to be updated whenever the chip form factor is altered. Identification of individual cell objects is performed on the basis of the entire apartment image, but segmented results are filtered to the apartment and trap areas, again using fixed offsets from the marker, as a way to prohibit erroneous classification of debris within microfluidic channels.Training for the cell segmentation model included 814 annotated images, and the Mask R-CNN model trained was initialized to a weight set resulting from pretraining over the COCO  = p02tλ, where λ is the cell division rate and t is the time measured in days. This simple exponential model ignored any hysteretic effects and therefore should be considered as an approximation of a given clone that maintains positive continuous growth throughout the experiment. The calculated growth rates are likely to be a lower bound, because the image segmentation models begin to miss cells in apartments that are very crowded, as shown in P values shown in The data presented in


BackgroundA telephone triage consultation, as part of the two-week wait head and neck cancer referral pathway, was implemented nationally in March 2020. This was in response to the COVID-19 pandemic to stream cancer referrals to minimize unnecessary interactions and appointments with health services. The aim of this study is to assess patient satisfaction with this novel telephone triage system in the setting of a district general hospital.MethodsA custom designed patient satisfaction questionnaire covering different facets of the patient experience was used. These questions were adapted from several internally validated questionnaires. A retrospective telephone survey was conducted by interviewers for all continuous new head and neck cancer referrals over two 4-week periods in 2020. Questionnaire responses to the initial modality of consult (either telephone triage or face to face) were collected, and data were analysed both qualitatively and quantitatively.ResultsSeventy-five responses were received, with 51 patients providing feedback on an initial telephone triage consultation. Patients rated the telephone triage consultation to be between satisfied and very satisfied across most domains, with an overall score of 4.29 out of 5. Accessibility and efficiency of the telephone triage were the domains with the least satisfaction. Fifty-five percent of patients would be happy to receive a similar telephone triage consultation beyond the pandemic. Qualitative analysis showed praise for the safety and convenience of the telephone triage consultation during the pandemic but highlighted a general preference for a face-to-face consultation and dissatisfaction regarding a lack of physical examination.ConclusionsOverall, patients are satisfied with the telephone triage consultation employed in the pandemic, with high satisfaction rates for multiple aspects of care. However, there were concerns regarding the accessibility and inefficiency associated with a lack of/delayed physical examination and inability to adequately address the fear and anxiety associated with the referral. A mixed response is obtained on whether the telephone triage system should stay for the long run. The COVID-19 virus outbreak was declared a pandemic on 11th March 2020 by the World Health Organisation (WHO) . It is tAs such, a head and neck cancer telephone triage pathway was developed by ENT UK and implemented in March 2020 using the evidence-based, structured head and neck cancer risk calculator (HaNC-RC)-V.2 . It woulPatient satisfaction stems from patient experience and, as best explained by the NHS published "The Patient Experience Book," is what the process of receiving care feels like for the patient, their family and carers . This isThe aim of this study is to assess multiple dimensions of patient satisfaction with the telephone triage consultation via a custom patient satisfaction questionnaire and appreciate underlying themes for satisfaction or dissatisfaction. Current planned studies explore the technical aspects of the telephone triage system including the efficacy of the existing risk calculators . Our stuData collectionAll continuous new two-week wait (2WW) head and neck cancer referrals to Torbay Hospital since the inception of the telephone triage system from March 2020 to April 2020, as well as the month of August 2020, were included in the study. Two study periods are necessary to allow comparison between patients who had the telephone triage consultation at the peak of the pandemic versus those who had the traditional face-to-face consultations which resumed towards the end of the first wave. Following study approval, the patient list was obtained from the local hospital information team. Three authors  phoned patients with a suggested script to introduce the study before asking the 13 questions from the questionnaire. These questions were directed at the initial modality of consult, either via telephone triage (TT group) or a face-to-face consultation (F2F group). Participation was entirely voluntary. Responses were documented in a shared secure, confidential electronic database.The protocol of this study and all questions used in the questionnaire have been approved by the Clinical Psychology team, as well as the Clinical Audit and Effectiveness Group of Torbay Hospital. Ethics approval was not required for this service evaluation project.AnalysisQuantitative data were analysed using Prism . All responses on the Likert scale were converted to a numerical scale from 1 (strongly disagree) to 5 (strongly agree). Patient satisfaction was also quantitatively inferred from this scale . Descriptive statistics were computed  for patient demographics  as well as questionnaire answers. Unpaired T-test analysis was used to compare the mean values of each question answered by the TT and F2F groups. A two-tailed p-value of <0.05 was considered to be significant with 95% confidence intervals.Qualitatively, open-ended questionnaire responses are inductively and thematically analysed. Key phrases are coded and then grouped into overarching themes , which aSelection and rationale of questions usedThe overall questionnaire was formulated from five different internally validated instruments including the Telemedicine Satisfaction Questionnaire (TSQ) , Visit-SThe authors felt that it was important to include an amalgamation of questions from the various established questionnaires and modify these to fit our unique context. This is so that multiple domains of patient satisfaction can be targeted while questions remain relevant. In fact, it is encouraged for such surveys to be specific and applicable in the evaluation of a service in question, using other questions/instruments if necessary -18. In aThe list of questions asked is presented in Table Seventy-five responses were collated out of 131 patients contacted (57.3% response rate). In total, there were a total of 27 males and 48 females, with an age range from 21 to 91 (mean: 58.7). Of which, 51 patients were in the TT group, while 24 were in the F2F group. Demographics for each group are presented in Table Quantitative assessmentFor Q1-11, patient satisfaction was between satisfied and very satisfied (4-5) for all domains for both the TT and F2F groups, except for Q3  and Q10 (effectiveness of consult for the TT group), in which patients were between neutral and satisfied (3-4) about. Comparatively, there is a significant difference in the above questions between the two groups (p<0.05), favouring the F2F group. These results are presented in Table Qualitative assessmentThematic analysis produced four main themes. These are presented in Table Patients are generally satisfied with the telephone triage consultation implemented for the 2WW head and neck cancer referral process during the pandemic. A range of patient satisfaction aspects was rated highly, including being understood over the phone (Q1), duration of the consult (Q7), receiving adequate information (Q8) and feeling involved in their own care (Q9). Comparatively, these results are not significantly different from those who went for an initial face-to-face consultation.In terms of accessibility to health services (Q3), a telephone consultation shines by increasing accessibility for those geographically isolated or housebound and provides convenience for those who have commitments at work or at home . In our A significant finding of our study was that patients were satisfied with the relational aspects (Q4-6) of their care during the telephone consultation with the clinician, despite existing studies showing that the lack of visual cues and weaker rapport building, including social speech compared to their face to face counterparts, may have implications for the effective development of long-term relationships . While cAs for the effectiveness of the telephone triage (Q10), patients in our study perceived this to be between neutral and satisfied, which is significantly lower than the reported satisfaction for the patients in the F2F group (mean of 3.63 versus 4.75 out of 5). From our qualitative analysis, some of this dissatisfaction are intrinsic to the triage process, for example, patients expecting a physical examination or being told to return for a further appointment, while another source of dissatisfaction may be related to the outcome of the consult, a few patients felt that it was ineffective in addressing their needs. On the extreme end, one patient in our study reported having to seek a second opinion from a private specialist as she was anxious about the outcome of not being seen. A key theme in our analysis is that this consult also serves to provide reassurance for patients. Two-week wait appointments can be anxiety inducing, and one study found that 77.2% of patients were anxious to varying degrees about their referral to a tertiary head and neck cancer unit .While it can be acknowledged that some patients are not necessarily reassured even in a face-to-face setting, nonverbal communication is essential alongside verbal messages to influence patients’ perception of a conversation and trust in the clinician . NonverbOther surgical specialties have reported much higher rates of patient satisfaction with the implementation of remote consultations during a similar time period, to the extent that 83% of patients attending a British general maxillofacial clinic  and 93% The main limitation of this study is its design which compares patient satisfaction of a triage telephone consultation with a full initial face-to-face appointment. While this may not be a like for like comparison, the authors felt that an initial face-to-face appointment would provide the best yardstick for evaluating the new telephone triage consultation, to uncover themes behind the pros and cons of each modality, rather than evaluating the telephone triage consultation in isolation. With a 57.3% response rate, this study is also vulnerable to nonresponse bias, which could reduce the external validity of our custom patient satisfaction questionnaire. Finally, there is an element of recall bias, as participants were phoned four to six months after their initial consultation. In this context, some participants may have had further appointments with our service and may not accurately provide feedback on their initial experience.Moving forwards, further studies can explore the effects of age and cancer diagnosis on patient satisfaction. Patient focus groups can also gather better qualitative data which may produce themes outwith the scope of a single broad open-ended question. Ultimately, on whether this telephone triage consultation should stay beyond the pandemic, patient satisfaction is only one component of this decision, and further studies including those exploring the efficacy of the risk calculator used, hospital resource allocation and clinician satisfaction with the process would also be instrumental in contributing to the overall decision.Overall, patient satisfaction for the initial telephone triage is positive, with satisfaction rates maintained for multiple aspects of care, and is comparable to that of a face-to-face consultation. When employed in a pandemic, this study supports the use of the telephone triage system from the patient’s perspective. However, some of its main advantages, for example, increased accessibility, are not as pronounced as expected, and there is a degree of perceived inefficacy of the telephone triage process particularly with the lack of physical examination. Some patients also felt that such a telephone consult increased their fear and anxiety over a possible cancer diagnosis. Beyond the pandemic, patient satisfaction response is mixed on whether the telephone triage system should stay for the foreseeable future.