However, all show unique patterns after 1850 CE, particularly during the Great Acceleration (after 1950 CE). Recent Lflux increase could be related to higher erodibility by rainfall and run-off during the longer snow-free season in the Pyrenees. In all sites, higher TOCflux and geochemical  and biological (diatom assemblages) signatures since 1950 CE suggest an increase in algal productivity, likely favored by warmer temperatures and higher nutrient deposition. These recent, unprecedented Lflux and TOCflux increases, in spite of their diverse history and limnological properties of the lakes, demonstrate the regional impact of the Great Acceleration not only in the ecological dynamics of alpine lakes but also in the hydrological cycle in high altitude mountain watersheds.We have conducted a monitoring survey and paleolimnological study of a W-E transect of six high altitude lakes (1870–2630 m asl) in the western and central Pyrenees (Spain) to evaluate the regional response to current global change in high altitude Mediterranean mountains. The reconstructed Total Organic Carbon (TOC At a global scale, recent changes in mountain lake dynamics have been related to climate variability, direct human impact in the watersheds5 and increased global deposition rates of nutrients6, altering their structure, functioning and diversity7 and causing eutrophication and pollution9.Lakes are a central component of the carbon cycle and several paleolimnological studies have shown organic carbon burial rate increases during the last centuries, although the causes for regional variability, the specific involved processes, and likely future scenarios remain uncertain10 and the current Great Acceleration11 (GA). In particular, Mediterranean mountains face great environmental risks as temperature and precipitation regimes12 and human pressure13 have changed during the last century. A clear example of such trends are documented in the Pyrenees where, since 1959, the annual mean temperature has increased by more than 1.6 °C and summer temperature by more than 2.3 °C. The decrease in annual precipitation has been small  but winter rainfall events are now more frequent14 .The high altitude lakes in the Pyrenees provide an opportunity to investigate the role of climate change and human activities in carbon and sediment dynamics, as past climate variability23 and the history of human impacts are relatively well known24. Human activities had a restricted impact till the onset of ca.twelfth century deforestation phase25. The abandonment of traditional agropastoral activities has led to large socioeconomic changes since the mid twentieth century, and currently, lakes provide numerous services for new infrastructure development for energy resources, ski resorts and tourism26.To assess the recent rates of response and vulnerability of ecosystems and territories to rapid shifts of the Earth System they have to be evaluated in the context of the Anthropocene27, increased sediment dynamics28 and ecological changes in alpine lakes5. However, the absence of long-term series and high-resolution reconstructions along geographic transects have impeded the evaluation of the regional nature of these recent observations within the context of past periods of rapid change. To investigate the nature of recent changes in high altitude Pyrenean watersheds, we reconstruct past organic carbon and depositional dynamics in six high altitude (1870–2630 m asl) lakes along a West–East transect in the Pyrenees  to 1877 m asl (AC), with variable sizes  and depths . The watershed surface areas range between 3.4 km2 (CR) and 0.57 km2 (AC) and the geology includes mostly carbonate  or siliceous  formations. All lakes are of low productivity (ultra-oligotrophic to mesotrophic) and dimictic (a first overturn period after winter inverse stratification and a second overturn period after summer stratification) with different alkalinity (13.9 ppm in CR to 141.6 ppm in SA) and conductivity (14 µS cm−1 in CR to 209 µS cm−1 in SA)  Table . Histori210Pb, 137Cs, and 14C dates were obtained with Bayesian age-depth modeling33 . Fluxes calculated from the first cm of the sediment cores range from 132 to 219 g m−2 year−1 in lakes located in silicate watersheds , and they are larger in carbonate-dominated watersheds . Flux trends calculated from the sediment sequences directly reflect the age models, and consequently they have variable uncertainties and time-resolution during the last 1200 years. Lflux plots with the associated time uncertainty  but the values remained high during the last decades. In spite of the different nature of the depositional processes and the expected variability among all lakes, late twentieth century Lflux values were among the highest fluxes observed in all records.Lithogenic fluxes (Lflux) calculated from sediment traps are between 20 and188 g mcomp) including TOC, TIC, geochemical  and grain size (%sand) data  to 46 g m−2 year−1 (AC), and the values are similar to those calculated from core-top sediment samples (from 4.8 g m−2 year−1 in CR to 49 g m−2 year−1 in SA). Sediment traps have higher TOC content and lower C/N (5–15) and δ13COM (−33‰ to –25‰) values than surface and downcore sediment samples. The TOC content in the lake sediments ranges between 0.06 (MA) and 13% (AC). TOCflux and Lflux trends are similar, with generally lower TOCflux values prior to 1850 CE, and the most prominent changes associated to the LIA and the GA. TOCflux is high in early medieval times (SI) and during some phases of the LIA . The 1850 CE transition is marked by an increase in TOCflux in three lakes , a decrease in MA and SI and no changes in UR. However, values during the GA are the largest in all cases. The largest increase in TOCflux occurred in the 1970s in SA (from 14 to 66 g m−2 year−1) and even though it has decreased afterward, still remained high (> 40 g m−2 year−1). In SI, the largest change occurred around 1980 CE (from 4 to 12 g cm−2 year−1). In CR, after a small increase in TOCflux around 1850 CE, it also intensified during the GA (from 3.1 to 4.9 g m−2 year−1). MA is the only lake with similar values during the GA (4.5 to 6.5 g m−2 year–1) and the LIA (2 to 9 g m−2 year−1). The highest values in UR occurred after the damming in the 1940s (from 12 to 31 g m−2 year−1) and although later decreased, still remained at relatively high values  and chlorophyll. Our survey shows that soil and watershed vegetation have higher C/N values with high variability (12–70) and a relatively small δ13COM range (−30‰ to −25‰), while lake sediments and Particulate Organic Matter (POM) samples have the lowest C/N ratios  , except in carbonate-watershed lakes with no trend (MA) or increasing values (SA).The TOC35) Fig. . CR has 13COM values correspond to sediment traps (−33‰ to −25‰), lake sediments (−26‰ to −17‰) and POM (−30‰ to −25‰). Aquatic and terrestrial vegetation have similar δ13COM values, but aquatic samples have relatively lower C/N values than terrestrial, although the range is large (10–50). Soil samples have lower C/N values (12–23) than terrestrial and aquatic vegetation, but similar δ13COM signatures as sediment and vegetation samples. Sediments collected in the creeks feeding the lakes have relatively low C/N values (5–20) and more positive δ13COM (−26‰ to −17‰). A sample from a biofilm in CR buoy has the highest δ13COM value (−18‰). Most lake sediment samples—except SA—plot in the same δ13COM (−32‰ to −20‰) vs C/N (7–15) graph, but each lake has a distinctive distribution . Higher altitude lakes have relatively higher δ13COM (UR > MA > CR) than lower altitude sites. SA samples have the largest C/N (5 to 35) and δ13COM ranges distributed in two distinct populations with some of the highest δ13COM values (up to −7‰). Among the other sites, small, shallow SI has the largest δ13COM range (−32‰ to −26‰). MA and UR also have large C/N ranges and among the highest δ13COM ranges (−27‰ to −21‰). CR and SI have relatively more negative δ13COM values (−29‰ to −25‰). In spite of the δ13COM variability in each lake during the last 1200 years  but started earlier (around 1700 CE) with an increasing C/N till 1950 and decreasing afterwards. SI also has a large δ13COM decline (−6‰) associated with variable but decreasing C/N values. AC showed a −2‰ decrease with lower C/N values during the GA. Carbonate lakes showed a different behavior: SA had an increasing δ13COM (6‰) during the IR and a large decline with abrupt shifts (up to 20‰) during the GA. MA also showed increasing δ13COM (up to −4‰) between 1850 and 1950 and then decreasing during the GA with little changes in C/N. Some of the observed decline in δ13COM during the last two centuries could be due to the documented decreasing in δ13COM value for atmospheric CO2 from pre-industrial (−6.4‰) to recent times (−8.4‰ in 2014) (“Suess effect”)35. However, as the δ13COM range in our data set is larger  it is likely that other factors 37 have contributed to these recent patterns.The lowest δars Fig. A–C all tCyclotella spp., Discotella spp., Pantocsekiella spp. and planktonic Fragilaria spp.) , although diatoms were poorly preserved in MA. The CR, AC and SA diatom records show recent rapid changes in diatom assemblages. All three records started with benthic and thycoplanktonic taxa dominance, but all three lakes show an unprecedented recent increase in small planktonic diatoms (p.) Fig. .A–C. Biop.) Fig. .A–C. Botp.) Fig. .A–C.flux, TOCflux, C/N ratio and δ13COM time series, one based on GAMs 39  in our time series using statistical tools is hampered by the non-regular nature of the data and the relatively low number of elements. We applied two methodologies to the Lflux plots show main Lflux CPs in the nineteenth century  and in the twentieth century . The GAM analysis  using two sets of variables41): (1) TOCflux, CN, and δ13COM that were interpreted as indicators of organic matter accumulation and sources (PCAUorg) and (2) Lflux and PC1comp that represent sediment delivery to lakes (PCAUlit)  explained 52% and 49% of the variance. This means that for the same age assemblage, more than half of the variability in the data associated with sediment and organic matter input increases simultaneously. Figure AUorg and only 26% for PCAUlit. The PC1AUorg y PC1AUlit versus age plots show similar structure, with larger positive values around the end of the LIA (1850), 1950 and recent decades   the human presence in higher altitude areas was reduced25, and another peak in human population was reached after the mid nineteenth century. Rural exodus since the mid twentieth century again decreased human pressure in mid mountains28.The different timing and intensity of sediment input variability may reflect local responses of the watersheds and lakes to varied climate and human pressure in mountain environments during the last millennium44 and reconstructions of past cryospheric activity45 have shown that in the Pyrenees, periods with more precipitation—either as snow in winter or rainfall the rest of the year—and higher seasonality (rapid spring–summer snowmelt) are conducive to higher run-off, erosion and sediment delivery in the watersheds. On the other hand, during colder episodes lake bioproductivity is reduced46. The maximum extent of LIA glaciers in the Pyrenees occurred during the last decades of the seventeenth century (Maunder Minimum) minor re-advances between 1750 and 1800, and a significant expansion until 1830 47. In our records we have identified periods with higher Lflux and higher bioproductivity that we relate to dominantly wetter and warmer conditions respectively. Lflux time series show that greater sediment delivery did not occur during the coldest periods as the Maunder minimum (1620–1715 CE), but prior to 1570 CE and after 1715 CE . In MA and CR several moraines show active glaciers during the LIA, but the Equilibrium Line Altitudes (ELA) fluctuated at higher elevations, between 2620 and 2945 m asl and the glacier ice was never in contact with the lakes42.There are historical reports from eighteenth century Pyrenean explorers of a small ice accumulation reaching the NW margin of Marboré Lake that lasted till early twentieth century31 This smaller ice patch could have been responsible for the important increase in sediment input during the second phase of the LIA (1750- 1850 CE) in Marboré sequence.At higher altitude sites, sediment fluxes are mostly controlled by hydrological and cryospheric processes, as snowmelt is responsible for mobilization of sediment in the watershed and deposition in the lakes. Monitoring data in the Izas experimental watershedinimum 160–1715 CEflux during the last 1200 years occurred during the last century and particularly during the last decades. This is somehow unexpected as the watersheds have not been directly affected by large land use changes or direct human activities and changes in precipitation amount have been relatively small. Since the 1950s, agropastoralism pressure in the Pyrenees has been greatly reduced, and new socioeconomic activities (tourism) have become the main agents of landscape transformation46. In absence of direct changes in land cover, we propose that new precipitation regimes could be responsible for this trend. The data from the high altitude Izas experimental basin—including SI watershed—44 shows the paramount relevance of the short (two-month) snowmelt period as it is responsible for about 50% of the total annual runoff and 35–43% of the total solute and suspended sediment yield. Higher temperatures also increase the probability of larger runoff events in spring and more frequent rain events with higher erodibility impact than snow48. The reconstructions and instrumental temperature data for central Pyrenean area  suggest dominant algal sources in lake production, and variable contribution of terrestrial carbon. Periods with increased organic carbon accumulation may respond to higher input of watershed-derived organic matter (higher C/N) during periods of higher erosion and/or run-off and/or increased lake bioproductivity . The C/N records have a large variability, but during the GA, all those located in silicate—watersheds showed decreasing trends, indicative of increasing lake productivity. MA values have remained constant during the last centuries and SA is the only one with an increasing trend, likely related to mac rophyte development in the littoral areas. An increase in BioSi and chlorophyll and changes in diatom assemblages also occurred in CR, SA and AC during the last decades  and reached the most negative values during the last decades. The two lakes with carbonate-facies and dominant carbonate formations in the watersheds (MA and SA) show a distinctive large increasing δ13COM trend in recent times, which points to other sources of DIC in these lakes. In MA, more DIC from carbonate bedrock could reach the lake during warmer periods42. In SA, recent development of charophyte meadows has shifted the type of organic matter accumulation and contributed to higher δ13COM. The ice-cover period could be another factor as shorter ice cover decreases the accumulation of CO2 during winter in the water column, which also decreases CO2 exchange between the lake and the atmosphere leading to more positive δ13COM15.Organic accumulation in high altitude Pyrenean lakes is limited by the reduced vegetation and soil cover in their watersheds and by the low productivity, which strongly depends on seasonality (ice-free season)des Fig. A–C. As iues Fig. . ChangesAulacoseira spp. showed higher abundance prior to the mid twentieth century . Other CPs are associated with dam construction—MA and UR, 1920–1940—, a LIA phase in MA  and documented medieval deforestation in some low altitude lakes . As we discussed before, prior to the twentieth century, periods of higher sediment input in the high-altitude Pyrenean lakes would be related to wetter and/or higher seasonality climate phases during the LIA and increased human pressure (twelfth to thirteenth centuries and late 1800s–early 1900s)  Figs.  and 4.GAM analyses show the most important change in isotope signatures in the twentieth century in most lakes , except in AC that occurred at the end of the LIA and MA with no model adjustment. CumSum showed CPs in 1975 CE in CR, SI and SA and a little bit later (2000 CE) in MA. MA and AC have CPs at the end (1880) and the mid nineteenth century, respectively. GAM analyses showed an earlier CP for AC and CumSum for SI and CR  coinciding with CPs identified with other proxies. The analyses for the C/N record show more CPs prior to the twentieth century than for the other time series, but still most occurred in the mid to late twentieth century  and in the late nineteenth century (SA and SI). Some of the variability in CPs could be attributed to the age uncertainty associated with the Bayesian age models. Biological evidence suggests that the increase in organic carbon accumulation during the last decades has been driven by increased productivity Fig. .A–C.flux, and both techniques identified CPs. This supports an intensification of surface processes  in the watersheds. Similar trends have been described in other settings with reduced recent human disturbance in the watersheds , and they have been ascribed to higher dust deposition55. Dust could be a contributing factor in Pyrenean lakes as Saharan dust fluxes in the southern Pyrenees are the highest in the Iberian Peninsula56. In the case of the Pyrenean mountains, the documented trends of overall decrease in the duration of the snowpack, earlier snowmelt and the increasing frequency of winter rain events45 could be potentially responsible for increasing erodibility and runoff in alpine basins, conducive to higher sediment delivery to the lakes.During the last century, a common feature of the lake records is the rapid increase in LThe TOC fluxes during the last decades are the largest in the records Figs.  and 6 anAU) for the four variables used in this study  show similar patterns and the % of variance explained by each PC1 was between 54 and 80% . The structure of these PC1 versus age plots was similar to the general PC1AUorg y PC1AUlit and confirmed that the main changes occurred during the mid nineteenth century and mid twentieth century. For organic accumulation (PC1 TOCflux and PC1 δ13COM) the periods with the largest deviations occurred during the early and mid to late twentieth century and for sediment delivery (PC1 C/N and PC1 Lflux) during the mid nineteenth century (end of LIA) and late twentieth century, although variability was larger.The individual uncertain age PCA (PCvs siliceous) supports global processes in lake ecology as main factors explaining TOCflux and shifts in diatom assemblages during the GA . A similar recent rapid increase on the planktonic component in another Pyrenean lake (Redon) has been correlated with higher air temperatures at the end of summer and more stable stratification5. Similar increases in planktonic diatoms have been related to climate warming57, and increasing nutrient availability58. Studies in other lakes in the central Pyrenees showed an increase in atmospheric P and N deposition during the last decades59. Higher atmospheric CO2, temperatures, nitrogen and phosphorus deposition all increase primary productivity7. Both, longer and more stable summer stratification and the observed increase in lithogenic mobilization from lake catchment would change lake nutrients availability for phytoplankton growth23. The decrease in C/D ratio (Chrysophyte/Diatoms ratio) and the increase in BioSi observed in lake CR reinforce the idea of an increase in the lake trophic state. Other factors, as faster C burial favoring C preservation due to higher Lflux and incomplete organic matter decomposition near the sediment–water interface, may have amplified the effects of increased bioproductivity and resulted in overestimation of recent TOCflux,The similarities in sites located at higher (CR) and lower (AC) altitude and with different bedrock geology  and wetter phases of the LIA. Lakes at lower altitudes  show higher TOCIncreased sediment fluxes to the lakes during the last decades may be related to changes in seasonality, leading to longer ice-free periods and higher erodibility of rainfall versus snow precipitation. Increased organic accumulation is driven by higher algal productivity, primarily controlled by higher temperatures and longer ice-free and growing season, although higher atmospheric input of nutrients could also be a significant factor. The exponential increase in lithogenic and organic carbon fluxes in all lakes since the mid twentieth century is a unique feature in the last 1200 years.Lakes were surveyed for bathymetric maps, sediment traps were deployed and limnological parameters  were measured in mid Summer and early Autumn. Short sediment cores were retrieved with a gravity UWITEC corer, split, imaged and logged with a Geotek Multi-Sensor Core Logger (MSCL). Watersheds were sampled to characterize vegetation, soils and sediments (C/N and isotope composition) and the drainage network, geology, geomorphology and soils were mapped from available data and field surveys.60: (1) grain size; clays: 0.01–2.0 µm, silts: 2.0–63.0 µm and sands: > 63.0 µm61. (2) Main components as of organic matter, silicates and carbonates calculated from the elemental data of organic and inorganic carbon62: % Carbonates = (100.09 × TIC)/12.01; % Organic matter = % TOC × 1724 and % silicates = 100 − % Carbonates − % MO. (3) Sedimentological features such as color, lamination , and grain size. (4) Geochemical composition, based on XRF scanner and ICP.The definition of sedimentary facies has followed four main criteriaTOC fluxes were calculated as:Lithogenic Flux were calculated as:Total carbon (TC), total inorganic carbon (TIC) were analyzed at 1 cm resolution in the sediment cores and in watershed and sediment trap samples at the IPE-CSIC  using a LECO SC144 DR analyser. For TIC analysis, organic matter was previously removed at 460 °C in a muffle furnace for 300 min. The Total Organic Carbon (TOC) was calculated as the difference between TC and TIC.13COM in bulk organic matter were analyzed with a FlashEA 1112 (ThermoFinnigan) coupled with an interface ConfloII (ThermoFinnigan) to a mass spectrometer of isotopic ratios Deltaplus (ThermoFinnigan) at the University of A Coruña, Spain.The δ3 (1:1:3 de H2O:HCl:HNO3) in a UltraWAVE (Milestone) at 220 °C during 15 min.Quantitative chemical analyses were performed in the composite sequences at a lower resolution  with an ICP-OES 720-ES (Varian) at the Experimental Station El Zaidin—CSIC . Elements measured by ICP-OES were Al, As, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, S, Se, Si, Sr, Ti, V, Zn. Samples were digested with HCl and HNOSamples for grain size analyses were heated 24 h at 80 °C in 3% hydrogen peroxide to eliminate organic matter and were measured with a MasterSizer 2000 at the IPE-CSIC laboratories. Smear slides and thin sections were used to define sedimentary facies using an optical microscope.63 after carbonates and organic matter were removed by HCl 1 M and peroxide. Then, BioSi was leached with Na2CO3 2 M and solution separated from the remaining sediment by centrifugation and bicarbonate was neutralized with HCl. BioSi, as dissolved silicate, was measured by the molybdate blue colorimetric method using an AutoAnalyser Technicon II64 at the IIM-CSIC.Biogenic silica (BioSi) was measured every 4 cm using the wet-alkaline leaching technique65.Photosynthetic pigments in bulk sediment were analyzed at the University of Valencia, Spain, with three successive pigment extractions measured with a spectrophotometer Beckman DU 640; the chlorophyll and the pheophytin in the sediment were calculated according the equations described in2O2) and HCl (2 ml 1 M) and mounted in Naphrax on a microscope slide following the method described in66. A minimum of 300 diatoms valves were identified per slide, and simultaneously we counted chrysophyte cysts to calculate C/D ratio (Chrysophyte/Diatoms ratio) using a Zeiss Axio Imager A1 microscope  equipped with a 100× objective (Zeiss Plan-Apo 1.4 numeric aperture) and differential interference contrast optics at 1000 magnification. Diatoms concentration in sediment samples was estimated by adding a known number of microspheres66. Diatom identifications were based mainly on67 and taxonomic references therein, with the currently accepted diatom names following the Algabase database .Sediment samples for diatom analysis were processed using hydrogen peroxide  using gamma ray spectrometry and AMS 14C dating (Table 32 implemented in the geoChronR package v1.1.633.Age models were obtained combining ng Table . We usedcomp) including compositional , geochemical (elements measured in ICP) and grain-size data (% sand)  as an indicator of the lithogenic composition of the sediments. We used the geoChronR package v1.1.633 to implement two “age-uncertain PCA”41 that were applied to two groups of variables: (i) TOCflux, C/N and δ13COM and (ii) Lflux and PCAcomp. GeoChronR uses a binning procedure to achieve this across multiple ensembles33 and a probabilistic PCA (PPCA) approach using the pcaMethods package68. For the “diatom PCA”, we used a Principal Components Analysis (PCA) based on Hellinger transformation69 of diatoms counts (only diatoms with relative abundance higher than 1% and with at least two occurrences across the entire record) to extract the main components of variability in CR and AC. The PCA was performed using the R package Vegan (2.5-7)70.We calculated a “Compositional PCA'' (PCnd) Fig. .A–C and 40 was applied to the time series of δ13COM, C/N, LFlux and TOCflux. A CumSum is the sequential sum of the successive elements of a variable after removing from each temporal observation the mean of the time series and plotting the cumulative sum of residuals. A positive slope of the CumSum indicates an above-average tendency in the data and a negative slope represents a below-average tendency, meanwhile changes in the slope of the cumulative sum curve from positive to negative or vice versa indicate phases for which the mean of the data is higher or lower than the mean of the original time series40. Not all the identified Change Points (CPs)  of deviations of the mean38 based on the use of GAMs 39  method proposed bySupplementary Information.


Background: Only a few studies have explored experiences ofmeaningful activity and associations with psychosocial wellbeing duringCOVID-19. None reflect a Canadian context or focus on persons living in poverty.Purpose: To identify experiences and associations betweenmeaningful activity and psychosocial wellbeing for persons living in povertyduring the first year of COVID-19. Method: We delivered aquantitative survey at three time points during the first year of the pandemicsupplemented by qualitative interviews at Time(T) 1 and 1 year later at T3.Findings: One hundred and eight participants completed T1surveys, and 27 participated in qualitative interviews. Several statisticallysignificant correlations between indices of meaningful activity engagement andpsychosocial wellbeing were identified across T1–T3. Meaningful activitydecreased from T1–T3 , with a significant decline from T2–T3 . In T1 qualitative interviews, participantsindicated that physical distancing exacerbated exclusion from meaningfulactivities early in the pandemic. At T3 (1 year later), they described howclassist and ableist physical distancing policies layered additional burdens ondaily life. Implications: Meaningful activity engagement andpsychosocial wellbeing are closely associated and need to be accounted for inthe development of pandemic policies that affect persons living in low income.Occupational therapists have a key role in pandemic recovery. Physical distancing policies implemented during the COVID-19 pandemic have beenessential for controlling viral spread; however, an unintended side effect of thesepolicies is that they have imposed restrictions on meaningful activity and areassociated with decreases in psychosocial wellbeing .Prior tIntersectionality theory emerged from feminist thought, and posits thatindividuals are afforded opportunities and societal privilege through the sociallocations that they occupy . Social The COVID-19 pandemic has exposed pre-existing inequities for persons who live inlow income . Occupat“Meaningful activities” represent what a person “does” with theirtime that is meaningful to them personally, professionally, and socially  1 survey to potential participants. The survey link wasshared by email with a range of advocacy groups, social housing organizations,and health and social care organizations in Ontario, Canada who agreed to sharethe survey with potential participants. We also shared a link to our survey onTwitter and Facebook. We recruited participants in one province only as physicaldistancing policies were provincially mandated in Canada and varied across thecountry. Recruiting in one province ensured that participants in our researchwould be exposed to a similar public health policy environment throughout ourstudy. As our team was primarily situated within the province of Ontario, wechose this province given our familiarity and embeddedness within the policyenvironment during data collection.Inclusion and exclusion criteria: We included participants who were (1) over the age of 18; (2) wereliving in low income according to the 2019 LIM criteria established byStatistics Canada ; and (3) lived in the Province of Ontario.Using Qualtrics, we delivered three surveys beginning 2 months following thefirst pandemic lockdown in the Province of Ontario in 2020 . Only participants whocompleted surveys at T1 were contacted to participate in T2–T3 surveys. Atthe end of the first and third surveys, we asked participants if they wouldbe willing to be contacted to participate in qualitative interviews.Participants in this subsample were purposively selected to obtain a diversesample based on age, gender, race, income source, and health history. Surveyrespondents were provided with a $10 gift card or e-transfer for each surveycompleted across the 1-year data collection period.After completion of T1 surveys, a member of our research team contactedparticipants using the email address provided in the survey. Aftercompletion of an informed consent procedure, we conducted interviews withparticipants via Zoom or telephone depending upon participant preference.After completion of the T3 survey, participants who had been engaged inqualitative interviews at T1 were approached again to participate in asecond qualitative interview. Participants were provided with a $30 giftcard or e-transfer for participating in each qualitative interview. SeeSurveys began with screening questions to determine eligibilityincluding a question that asked participants about their age, and householdincome and composition. To ensure that only participants living on lowincomes participated in our study, we designed our survey so that itexcluded participants who reported incomes above the LIM based on the numberof individuals living in their household so that we would only includeparticipants meeting the low-income threshold identified by Qualitative interviews were semistructured and focused on experiences ofphysical distancing and how they influenced participants’ daily lives,including meaningful activity. The first interview (following T1) focused onexperiences of physical distancing policies, and how these influenced dailylife and the wellbeing of participants. The second interview (following T3)included the same questions but focused on how physical distancinginfluenced daily life including meaningful activity over the previous yearsee . AsamplUsing SPSS (v. 28), we calculated descriptive statistics for all variables.Demographic characteristics were calculated for the full participant sampleat T1. These were calculated again for participants at T2 and T3 to describethe sample composition across all three time points. We conducted one-wayanalysis of variances (ANOVAs) and Chi-square tests to identify anysignificant differences in demographic characteristics across T1–T3 groupsto understand whether attrition could be attributed to demographic factors.We used Fisher's exact tests when the expected cell counts were less than 5.Summary scores were generated for each standardized measure using processesdescribed by the test authors. As our data were ordinal and not normallydistributed, we opted to use nonparametric statistics.p < .05.To identify associations between indices of meaningful activity engagement and psychosocial wellbeing ,we conducted Spearman correlations for data collected from T1 to T3. Tocompare any differences across these time points, we also conducted Friedmantests. To gain insight into any significant differences, we conductedpost-hoc Mann–Whitney U tests. To minimize type 1 error, we used aBonferroni correction to account for multiple Mann–Whitney U tests byadjusting our minimum significance level to .017 instead of the standard .05typically used in social and health sciences research  by dividT1 and T3 transcripts were separated and uploaded to Dedoose, a qualitativedata management program, to facilitate analysis . T1 and T3 transcripts were analyzed separately toenable our team to describe distinct experiences across two time points.Transcripts were coded abductively, informed by intersectionality theory byseveral members of our research team . Usingthematic analysis  at T3 than atT1 (6.5%) and T2 (6.1%). There were also some significant differences in theproportion of participants who were employed at T1 (20.4%) versus T2 (13.6%) andT3 (15.6%). A smaller proportion of participants relied on workers’ compensationbenefits  at baseline(11.1%) versus T2 (18.1%) and T3 (18.8%), and a greater proportion relied onemployment insurance  at T3 (9.4%) versus T1 (6.5%) and T2 (6.5%). There wereno other demographic differences in participants across T1–T3. A completesummary of the demographic characteristics of participants at T1–T3 is providedin In terms of residential and family characteristics, a greater proportion ofparticipants at T1 reported living in a rural community  than atT2  and T3 . A complete summary of the residential andfamily characteristics of participants at T1–T3 is provided in p < .01 significancelevel. One exception to this was that higher EMAS and lower MSBS scores weresignificantly associated with decreased UCLA-LS scores at T1; however, theopposite association was observed at T2 and T3. Further, indices ofmeaningful activity engagement  were onlysignificantly correlated with alcohol use (AUDIT-10) at T2. Drug use(DAST-10) was not significantly correlated with indices of meaningfulactivity engagement across T1–T3, which was likely due to the low levels ofdrug use reported by participants in the sample overall. See Across T1–T3, there were medium to large correlations between indices ofmeaningful activity engagement  and indices ofpsychosocial wellbeing . Of note,higher EMAS scores and lower levels of boredom (MSBS-8) were significantlycorrelated with better psychosocial wellbeing overall across all three timepoints with the majority at the Complete data from T1 to T3 were available for 47 to 50 participants of thefull sample for all standardized measures. This is presented as a rangebecause while 50 individuals participated across T1–T3, not all participantscompleted standardized measures in full. Because Friedman tests aresensitive to missing data and require data from all time points, onlyparticipants for whom complete data was available were included in ouranalyses. Friedman tests conducted to identify differences in indices ofmeaningful activity engagement  and psychosocialwellbeing revealed significant differences across T1–T3. Descriptive statistics andthe results of Friedman tests, post-hoc tests, and effect sizes aresummarized in 2  = 9.110, p < .05].Inspection of the median values showed a small decrease in EMAS scoresfrom T1  and T2 to T3 . Post-hoc tests confirmthat EMAS scores decreased significantly from T2 to T3  and from T1 to T3  both with medium effect sizes . IMRS-5 (productivity time) scores decreasedsignificantly across time points . Median values, however, remained thesame across T1 to T3 .Post-hoc tests revealed a decrease from T2 to T3, but this decrease wasnonsignificant at p < .017 level . MSBS-8 (boredom) increased from T1 toT3; however, this increase was not statistically significant.These findings indicate that engagement in meaningful activity decreasedslightly over the course of the first year of the pandemic, and thatthis decrease occurred mostly from T2 to T3. Further, productivity timeand boredom did not significantly increase or decrease over the firstyear of the COVID-19 pandemic even though meaningful activity decreasedover time.EMAS scores were significantly different across time points. Inspection of the median values showed anincrease in PHQ-9 scores from T1  to T2  and a decrease from T2 to T3 . Post-hoctests confirm that PHQ-9 scores increased significantly from T1 to T2 and decreased significantlyfrom T2 to T3  both with largeeffect sizes . There were nostatistically significant changes in PHQ-9 scores overall from T1 to T3.Similarly, GAD-7 (anxiety) scores were significantly different across T1to T3 . Inspection of the median values showed anincrease in anxiety at T2 , while these values werethe same at T1 and T3. Post-hoc tests confirm that GAD-7 scoresincreased significantly from T1 to T2  and decreased significantly from T2 to T3 both with large effect sizes. UCLA-LS scores were significantlydifferent across T1 to T3 . Median values increased from T1 to T2  and then decreased fromT2 to T3 . Post-hoc tests confirm that UCLA-LSscores increased significantly from T1 to T2  and decreased significantly from T2 toT3  both with large effectsizes . Brief H-Pos (hopelessness)scores were not significantly different across T1 to T3 . These findings suggestthat there was a similar pattern for depression (PHQ-9), anxiety(GAD-7), and loneliness (UCLA-LS) in that all increased significantly atT2, falling back to baseline levels by T3. PHQ-9 (depression) scores were significantly different across timepoints .Inspection of the median values showed a decrease in median AUDIT-10scores from T1  to T2  and anincrease at T3 . Post-hoc tests revealed a significantmedian difference from T1 to T2 , T2 to T3  and a significant increase from T1 to T3 with medium to large effectsizes . DAST-10 (drug use)scores were not significantly different across T1–T3 . While alcohol use increasedover T1 to T3, it should be noted that a score of “8” or higher on theAUDIT-10 is considered to be a “hazardous” level of drinking accordingto the test authors  scores were significantly different across T1 toT3 . Activities that they performed with easeprior to the pandemic were made more difficult as they tried to avoidcontracting the COVID-19 virus. Participants noted that they could notafford to have groceries delivered, and that having to go out to storesplaced their health at risk more than individuals who could affordgrocery delivery: “I have to get groceries. I have to eat…soit's venturing out that's quite stressful for me because noteverybody is careful” [Sharon]. The experience of this wasdescribed by participants as a sense of loss: “I’ve lostcreative time” [Stephen]; “I’ve lost social time,exercise time, and mental health time” [Elaine]. Manydescribed how the presence of physical distancing policies, which weredescribed by participants as “ableist,” were responsible for creating orentrenching disability: “Quarantine has very much affected theway that disabled people get around the world” [Thomas].The loss of amenities that enabled participants to engage in meaningfulactivities easily in the community before the pandemic were no longeravailable due to physical distancing policies and led to ever-increasingisolation: “I would love for them to figure out how I could takepublic transit. I would love to be able to go to places”[Tova].Overall, participants at T1 described how physical distancing policiesprevented them from engaging in necessary daily activities that promotedwellbeing: “Ihave not been able to feel like I’m really contributing much ofanything at all…and that's not particularly good for my mentalwell-being” [Dara]. Some participants expressed that havingadditional free time enabled them to slow down and finish projects thatwere challenging to complete prior to the onset of the pandemic:“I have time to just stay home and not be running aroundlike a chicken with my head cut off” [Adelita]. Others usedunoccupied time to learn new hobbies or reconnect with activities thatwere meaningful to them in the past, but in which they had been unableto engage for a long time: [I am] “trying to read books for funbecause I have a bit more time, and I haven’t read books for fun inabout five years” [Tova].The loss of activities that were necessary for participants to engage inpreviously were longed after by participants. In their absence,participants sought to find meaning in what they could do whilefollowing physical distancing protocols. Many were driven to engage inproductivity activities specifically, as having fewer opportunities tocontribute engendered negative impacts on mental wellbeing: “I feel like I’m in jail because I’min my room by myself” [Lee]; “I feel like I’mtethered on a short leash, and I don’t like it” [Michelle].These changes in routines came on suddenly: “it's like night andday. A complete change” [John]. The suddenness with whichphysical distancing policies were implemented caused an immediate haltand suspension of regular activities. This, combined with supply chainissues, made it feel to participants like Sharon like the end of the world:This feels like an apocalypse…Like when I went into the grocerystore the first time and seen the bare shelves, I cried…Icouldn’t wrap my head around how I couldn’t buy my kids toiletpaper…like “oh my God. We’re gonna run out of diapers.”[Sharon]Some participants lived with health conditions thatincreased vulnerability to contracting the virus and experiencingcomplications associated with COVID-19. This caused them to isolate intheir apartments, without seeing anyone or leaving to perform necessary activities:It has extremely affected my life. I am disabled andimmunocompromised…it extremely affected my mental health when wefirst went into quarantine. So I went into extreme lockdown inmy own apartment. I didn’t even leave to do laundry. I don’thave a balcony that's useable. [Thomas]Severe limitations on participants’ time use caused some to feel likethey had been imprisoned: “The essence of our analysis of T3 qualitative interviews was that afterthe pandemic wore on over time, participants felt a sense that physicaldistancing protocols added an extra layer of burden that made everythingmore difficult than it was before. These narratives were particularlypowerful as most participants already lived with disabilities thatchallenged them in their daily lives prior to the onset of the pandemic,and ongoing changes to physical distancing restrictions createdconfusion and generated additional emotional and cognitive burdens. Thisessence was expressed through three themes generated in our analysis:(1) finding meaning through relationships with activity; (2) COVID-19has magnified the inequities I live with; and (3) Classist and ableistpandemic policies have made daily life so much harder.my life was really busybefore…I didn’t always take time for myself. And now I have too muchtime for myself” [Elaine]. Having little to do, however,continued to motivate participants to find new activities to fill time.They saw activities as a way of coping by “weathering” the storm ofCOVID-19: “I bought a set of bongos, which I’ve always wanted todo, and started to teach myself a little bit” [Karen];“I do a lot more meditation and mindfulness than I everhave” [Stuart].As the year progressed, participants endured a range of physicaldistancing restrictions that ebbed and flowed as COVID-19 case numbersfluctuated and public health officials responded. Physical distancingrules evolved constantly, causing confusion for participants about howthey could spend their time in community spaces. Participants haddifferent experiences over the year, but most continued to struggle tofill time in meaningful ways and maintaining a sense balance inactivities continued to be a problem: “I can’t afford tohave groceries delivered. That means that I have to go out”[Elaine]. Participants indicated that this situation was compounded bythe fact that the cost of food and other necessary resources hadincreased: “a lot of things have gone up” [Karen].However, despite record levels of inflation driving up the cost of basicneeds, income support benefits had not followed suit, and placedparticipants in ever-increasing precarity: “I just go furtherand further in debt each month” [Lynn]. Participantsrecognized that they needed to perform activities differently to respondto growing income inequality, and they expressed frustration over thischallenging situation: “How can you have a functioning societywhen so many people are hanging on by their fingernails like this?It's madness” [Dara].Participants discussed how living in low income was an additional barrierthat made it challenging to cope with physical distancing restrictionsimposed during the first year of the pandemic. They indicated that aninadequate income forced them to make decisions when performing dailyactivities that placed them at greater risk of contracting COVID-19 thanindividuals living on more adequate incomes: “my lifehas not really been impacted by social distancing restrictions, it'sbeen impacted by the fact that we are treated like…dogs to be putdown at worst” [Jeane]. This point was emphasized as theycompared the introduction of the CERB, a benefit available toindividuals who had lost employment due to the pandemic. The amount forCERB was set to $2,000/month, while funding allotted to individualsliving on the ODSP  was set toapproximately $1,200/month, and Ontario Works  at just over $600/month: “when they decided lastyear that $2,000 was the amount for people that were off work fromthe pandemic. We get half that. It's just a slap in theface” [Karen]. The poverty in which participants lived asthey observed this growing inequality restricted their ability tofunction in daily life to such an extent that it caused them to consideropting for medical assistance in dying:You know how many people I know who are thinking of takingmedical assistance in dying because they’re living on the sameODSP income that they’ve always lived on? $1,169 a month. Andthey live alone. And they can’t get any more money, and everyoneelse who lost money or lost a job got $2,000 a month each.[Lynn]Further, some participants highlighted that the challengesfaced by persons living in low income and with disabilities during thepandemic were unacceptable and hoped that inequities revealed during theCOVID-19 experience would lead to needed changes after the pandemicended: “If anything good comes out of the COVID pandemic, itwill be the fact that we’re now more willing to question those basicassumptions to a greater extent than we were before. Because‘normal’ wasn’t working” [Dara].As the pandemic wore on, participants described how there seemed to be noend in sight, and physical distancing policies made everything they didwith their time more emotionally and cognitively taxing. As many wereliving with disabilities prior to the pandemic, activities were alreadymore difficult to perform, and participants noted that physicaldistancing policies failed to account for their specific needs, makingthem feel as though their needs simply did not matter. They emphasizedthat this tiered system existed prior to the pandemic: “We conducted this study to explore: (1) how individuals living in low incomeexperienced meaningful activity during the first year of the COVID-19 pandemic; (2)how indices of meaningful activity engagement and psychosocial wellbeing wereassociated; and (3) meaningful activity and psychosocial wellbeing evolved duringthis time period. Our findings reveal that physical distancing policies, which havebeen necessary for controlling the spread of the COVID-19 virus, have imposedunintended, negative influences on the ability of persons living in low income toparticipate in meaningful activity and attain psychosocial wellbeing. Approximately75% of participants in our study identified as living with health conditions, andmost participants in our qualitative sample identified as living with disabilities.As they reflected back on experiences over the first year of the pandemic, theyexpressed anger and frustration that public health policies failed to account fortheir specific needs. They continued to live in poverty as the prices of goods andservices increased and income support rates did not. Participants had limitedopportunities for meaningful activity, and this meant that they were less likely toexperience improvements in psychosocial wellbeing as greater engagement inmeaningful activity and lower boredom were associated across all three time pointswith decreased hopelessness, anxiety, and depression. Over half of participants inboth the survey and qualitative interviews identified as women, and from anintersectional  lens, thOur quantitative findings reveal that indices of meaningful activity engagement werepositively associated with several measures of psychosocial wellbeing over the firstyear of the pandemic and that meaningful activity decreased over time. Participantsconfirmed these findings in qualitative interviews and indicated that access tomeaningful activity was limited in their lives both by living in poverty and theneed to follow physical distancing protocols. Psychosocial wellbeing declinedsignificantly at T2, and meaningful activity engagement followed. This decrease inpsychosocial wellbeing has been observed in other studies exploring the mentalhealth impacts of the COVID-19 pandemic for a range of populations . We canOur findings reinforce the findings of recent existing research indicating thatmeaningful activity and psychosocial wellbeing are closely associated, and thatindividuals have faced barriers to meaningful activity participation during theCOVID-19 pandemic . While sThe findings of this research underscore the critical importance of meaningfulactivity for psychosocial wellbeing. Occupational therapists and occupationaltherapy researchers should work together to explore these relationships further,with a particular focus on influencing policy, and developing and evaluatinginterventions tailored to meeting the activity needs of persons limited by lowincomes as public health policies continue to evolve. Co-designing interventionsalongside persons with lived experience may provide opportunities for developingapproaches that are relevant and feasible for persons living in poverty . ResearcThe findings of this research emphasize the ways in which necessary public healthpolicies that help limit the spread of disease can impose other unintendedconsequences for human health. While we did not intend for our research to focusspecifically on disability, the high rates of poverty among persons living withdisabilities resulted in a sample that lived with a high prevalence of healthconditions, and most participants in our qualitative sample identified asdisabled. As such, they faced barriers to engagement in meaningful activityprior to the pandemic, and physical distancing restrictions imposed anadditional layer that limited participation. Our research emphasizes the needfor public policy that mitigates the unintended impacts of physical distancingon the meaningful activities of persons who experience both poverty anddisability to reduce harms that limiting engagement in meaningful activity maycause. Allocating funding for public health initiatives that support theimplementation of programs that address barriers to meaningful activityengagement during pandemic restrictions need to be employed in concert withemergency measures. Policymakers may consider consulting both with persons withlived experiences of poverty and occupational therapists in the development ofsuch policies . FinallyThis research was conducted with individuals living in poverty in one province ina high-income country. Sample sizes in our quantitative analyses were smallgiven the high rate of attrition over the three data collection periods in thisstudy. In terms of race, gender, and sexual orientation, participants in thisstudy were mostly White, more than 60% were women or nonbinary, and fewidentified as 2SLGBTQ + . Further, most of the participants in our qualitativesample were women, and as such, the reader should be aware that our qualitativefindings reflect a distinctly feminine perspective. The composition of oursamples should be accounted for when interpreting our findings, and we recommendthat future research be undertaken with more diverse samples with respect torace, gender, and sexual orientation.During the time of preparing this article, the pandemic is continuing to unfold.While physical distancing restrictions have recently been lifted in Ontario, Canada,the risk of contracting the COVID-19 virus continues to fluctuate . Scholar


Our study shows a new role for G protein signaling in the mechanism of α7 nAChR-associated breast cancer growth.Chronic smoking is a primary risk factor for breast cancer due to the presence of various toxins and carcinogens within tobacco products. Nicotine is the primary addictive component of tobacco products and has been shown to promote breast cancer cell proliferation and metastases. Nicotine activates nicotinic acetylcholine receptors (nAChRs) that are expressed in cancer cell lines. Here, we examine the role of the α7 nAChR in coupling to heterotrimeric G proteins within breast cancer MCF-7 cells. Pharmacological activation of the α7 nAChR using choline or nicotine was found to increase proliferation, motility, and calcium signaling in MCF-7 cells. This effect of α7 nAChR on cell proliferation was abolished by application of Gαi/o and Gαq protein blockers. Specifically, application of the Gαi/o inhibitor pertussis toxin was found to abolish choline-mediated cell proliferation and intracellular calcium transient response. These findings were corroborated by expression of a G protein binding dominant negative nAChR subunit (α7 Epidemiological studies show that smoking of tobacco products can significantly increase a woman’s risk of developing breast cancer –4. Thus,The nAChR channel is a pentameric protein consisting of combinations of 16 isoforms of subunits including a subunits α1–α10, β1–β4, γ, δ, and/or ε , 10. Hom2 and 95% humidity. MCF-7 is a human breast cancer cell line with estrogen, progesterone and glucocorticoid receptors and is derived from the pleural effusion of a 69-year-old metastatic adenocarcinoma. MCF-7 cells were transfected with constructs encoding human α7345-348A or the control human α7 nAChR in pEYFP-C1 (Addgene)  reagent (Promega) (0.5 mg/ml) was added to each well and incubated at 37°C for 30 min before the addition of 1 ml acidic isopropanol then vigorous re-suspension of the converted blue crystals. Cells were optically counted with a hemocytometer (Thermo Fisher) or the absorbance of the suspension was measured at 595 nm with background subtraction at 650 nm. Results are expressed as mean ± standard error of the mean (S.E.M.).Approximately 10Cells were transfected with GCaMP5G  and the 2. Cell motility was determined by calculating the width of the scratch at 24 h as a percentage of 0 h.Cells were plated on 6-well plates at 80–90% confluence with complete DMEM containing vehicle or drug. The following day, a scratch was created in the cell monolayer using a sterile p1000 pipette tip. A photograph of the scratched area was taken immediately (0 h) and after a 24 h incubation in a 37°C, 5% COStudent’s two-tailed unpaired t-test, or one-way ANOVA test followed by Bonferroni post hoc test were used to compare means of individual groups with p < 0.05 as statistically significant.Nicotine has been shown promote cancer cell proliferation within various cell lines and in animal systems , 7, 20. Nicotine can activate calcium signaling and lead to cell proliferation and the regulation of apoptosis within cancer cells . We invein vitro Reviewers' comments:Reviewer's Responses to Questions  Comments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?  The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: PartlyReviewer #2: Yes**********  2. Has the statistical analysis been performed appropriately and rigorously?   Reviewer #1: I Don't KnowReviewer #2: Yes**********  3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.  The Reviewer #1: YesReviewer #2: No**********  4. Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********  5. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The experiment in figure 7B should be repeated with a control group for α7345-348a that was not exposed to choline to show that transfection with α7345-348a does not alter proliferation by itself.The results in Figure 4 are not mentioned in the abstract or the discussion. It would be good if the authors discuss how the increase in α7 nAChR expression might affect the proliferation, motility, and/or calcium signaling of cancer cells. Additionally, the authors did not show if these effects could be blocked by MLA or another antagonist, or whether this upregulation is related to g-protein mediated signaling via α7 nAChRs. Further experiments to answer these questions would help to tie these results into the rest of the paper.YM 254890 is mentioned in the abstract as a G protein blocker, but in the results section of the manuscript, the authors never define what specifically YM 254890 is or why it is being used.The proliferation assay in Figure 7 plots Cell count x 105, whereas the other proliferation assays measure Net OD. Could the authors please explain why this assay was quantified differently?There are two “B” panels in figure 5The deltaF/F scales are not consistent across figures. For example, in Figure 5, A and C plot deltaF/F (x100), whereas panel B1 writes out the 100s, and the second panel B just has deltaF/F without the x100 clarification. Similarly, in Figure 7, panel A, the first graph is x100, while the second graph is not.Scale bars should be added to Figure 3A and Figure 4AScale bar should be defined in Figure 7B.In the figure legend for Figure 6 it is noted that the “Asterix denotes significant difference from control,” whereas the figure seems to indicate that the Asterix represents significant difference from the choline treated group. Could the authors clarify what comparisons are being measured in this figure, and what is significantly different from what?The figure legend for Figure 2 states “Asterix denoted significant difference from control” but the figure seems to indicate that significance is measured as difference from the choline group.Figure 7 has only 2 panels, A and B, but the figure legend has A, B, and C.Figure 7 states “statistical significance relative to the control or α7 transfected group.” This is confusing. Could the authors clarify what comparisons are being made and what significance is being denoted. Does this mean that the α7345-348a group is significantly different from both the control and α7 group? If so, this should be denoted by two different symbols.In the text, the mutant α7 is called “α7345-348a” whereas in the figure legend and figure it is “α7345-8a”, this nomenclature should be consistent throughout the paperIn the figure legend for Figure 5, the definition of a double Asterix is given, but there is no double Asterix in Figure 5Reviewer #2: The paper by Oz et al, shows that in MCF-7 cells activation by choline of α7 receptor increasesproliferation, motility, and calcium signaling and this is partially blocked by the application of G protein blocker, Gαi/o inhibitor and by the presence of a G protein binding dominant negative α7 subunit (α7345-348A).The work is interesting and well done, and it demonstrated that the α7 subtype is involved in mediating choline induced proliferation, motility, and calcium signalling. However the effect of choline was blocked using antagonists that act on both α7 and α9 subtypes. Why the authors did not used the α7 selective antagonist AR  and the α9 selective antagonist RGIA4  ? This certainly will help in clarifying the subtypes involved and their contribution to the effects reportedMinor points:In the abstract it is written "Nicotine activates various nicotinic acetylcholine receptors (nAChRs)" and in the introduction it is written"Mammalian nAChRs assemble from α (α1–α6) and β (β2–β4) subunit combinations forming homo- or hetero-pentameric channels .Nicotine does not activates a1 containing receptors and nicotine activates various nAChRsthat assemble from α  and β (β2–β4) subunit combinations.Fig 7: Please add C to the figure**********  6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.  Reviewer #1: NoReviewer #2: No**********https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  7 Jul 2023Please find the revision of our manuscript entitled “α7 nicotinic acetylcholine receptor interaction with G proteins mediates breast cancer cell proliferation, motility, and calcium signaling” for consideration as a research article in PLOS One. We have taken into consideration the comments of both reviewers and have addressed them throughout the revised manuscript. This is enumerated in a point-by-point response letter to the reviewers showing specific changes in the revised submission:Reviewer #1: • The experiment in figure 7B should be repeated with a control group for α7345-348a that was not exposed to choline to show that transfection with α7345-348a does not alter proliferation by itself.RESPONSE: We thank the reviewer for this comment. In fact, the experiment was conducted as a control however it was not included in the original submission. Therefore, the revised manuscript shows data on mutant receptor subunit transfection within Figure 7 and corresponding text in Results page 8 (last sentences of the section) .• The results in Figure 4 are not mentioned in the abstract or the discussion. It would be good if the authors discuss how the increase in α7 nAChR expression might affect the proliferation, motility, and/or calcium signaling of cancer cells. Additionally, the authors did not show if these effects could be blocked by MLA or another antagonist, or whether this upregulation is related to g-protein mediated signaling via α7 nAChRs. Further experiments to answer these questions would help to tie these results into the rest of the paper.RESPONSE: We thank the reviewer for pointing this out and we have now incorporated a discussion of this on Page 9 (end of the second paragraph). As stated, alteration in nicotinic receptor expression at the cell surface is likely an important driver of calcium and other signaling responses that can support cancer cell growth, and the experiments suggested by the reviewer are clearly important. However, due to limitation in experimental resources, we are not able to perform these experiments currently. Furthermore, we would like to suggest that studies on the mechanisms that participate in the regulation of nAChR at the cell surface, fall outside of the scope of the current manuscript. We now mention this as an important direction in future study in the revised manuscript in the Discussion on Page 9 (end of the second paragraph).• YM 254890 is mentioned in the abstract as a G protein blocker, but in the results section of the manuscript, the authors never define what specifically YM 254890 is or why it is being used.RESPONSE: The correction is now included on Page 7, last sentences of the 3rd paragraph within the Results section. The clarification is made that YM254890 is a Gq inhibitor and used to confirm Gq involvement.• The proliferation assay in Figure 7 plots Cell count x 105, whereas the other proliferation assays measure Net OD. Could the authors please explain why this assay was quantified differently?RESPONSE: Proliferation assays in the manuscript were performed in the laboratory of Dr. Oz however those presented in Figure 7 were performed in the lab of Dr. Kabbani. The two assays are virtually identical . The results are also highly robust and show a comparable effect of choline on MCF-7 cells proliferation when comparing % change in cell count relative to the control group. To clarify this in the revised manuscript a newly added Figure 7 C shows cell count results as “% control (vehicle)” as done in earlier figures.• There are two “B” panels in figure 5 Response: This is now corrected. • The deltaF/F scales are not consistent across figures. For example, in Figure 5, A and C plot deltaF/F (x100), whereas panel B1 writes out the 100s, and the second panel B just has deltaF/F without the x100 clarification. Similarly, in Figure 7, panel A, the first graph is x100, while the second graph is not. Scale bar should be defined in Figure 7B.Response: These figures are significantly revised to correct for these errors. • Scale bars should be added to Figure 3A and Figure 4AResponse: The scale bars are now added into Figs. 3 and 4.• In the figure legend for Figure 6 it is noted that the “Asterix denotes significant difference from control,” whereas the figure seems to indicate that the Asterix represents significant difference from the choline treated group. Could the authors clarify what comparisons are being measured in this figure, and what is significantly different from what?Response: Thank you for pointing out this error. We have revised the legends for figures 2, 6, and 7 with the new legends clearly stating which groups are used for statistical comparison.• The figure legend for Figure 2 states “Asterix denoted significant difference from control” but the figure seems to indicate that significance is measured as difference from the choline group.Response: This is now corrected.• Figure 7 has only 2 panels, A and B, but the figure legend has A, B, and C.Response: This is now corrected. • Figure 7 states “statistical significance relative to the control or α7 transfected group.” This is confusing. Could the authors clarify what comparisons are being made and what significance is being denoted. Does this mean that the α7345-348a group is significantly different from both the control and α7 group? If so, this should be denoted by two different symbols.In the text, the mutant α7 is called “α7345-348a” whereas in the figure legend and figure it is “α7345-8a”, this nomenclature should be consistent throughout the paperResponse: This is now corrected. • In the figure legend for Figure 5, the definition of a double Asterix is given, but there is no double Asterix in Figure 5Response: This is now corrected. Reviewer #2: The paper by Oz et al, shows that in MCF-7 cells activation by choline of α7 receptor increasesproliferation, motility, and calcium signaling and this is partially blocked by the application of G protein blocker, Gαi/o inhibitor and by the presence of a G protein binding dominant negative α7 subunit (α7345-348A). The work is interesting and well done, and it demonstrated that the α7 subtype is involved in mediating choline induced proliferation, motility, and calcium signalling. • However the effect of choline was blocked using antagonists that act on both α7 and α9 subtypes. Why the authors did not used the α7 selective antagonist AR  and the α9 selective antagonist RGIA4  ? This certainly will help in clarifying the subtypes involved and their contribution to the effects report.Response: α-Conotoxin RgIA has higher potency for α9/α10 than α7 nAChRs , and was thus chosen in complementary experiments to α bungarotoxin. The use of additional pharmacological ligands with greater selectivity, as suggested by the reviewer, is definitely important and to that end this point is now stated in the Discussion on Page 10, last two sentences.Minor points: In the abstract it is written "Nicotine activates various nicotinic acetylcholine receptors (nAChRs)" and in the introduction it is written"Mammalian nAChRs assemble from α (α1–α6) and β (β2–β4) subunit combinations forming homo- or hetero-pentameric channels .• Nicotine does not activates a1 containing receptors and nicotine activates various nAChRsthat assemble from α  and β (β2–β4) subunit combinations.• Fig 7: Please add C to the figureResponse: We thank the reviewer for pointing these mistakes and have corrected them within the revised manuscript.AttachmentReviewer_Comments.docxSubmitted filename: Click here for additional data file. 12 Jul 2023α7 nicotinic acetylcholine receptor interaction with G proteins in breast cancer cell proliferation, motility, and calcium signalingPONE-D-23-15038R1Dear Dr. Kabbani,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Israel SilmanAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments:Reviewer's Responses to Questions  Comments to the Author  1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressed**********  2. Is the manuscript technically sound, and do the data support the conclusions?  The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. 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Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: (No Response)**********  6. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: (No Response)**********  7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). 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