Dramatic microbiota changes and loss of commensal anaerobic bacteria are associated with adverse outcomes in hematopoietic cell transplantation (HCT) recipients. In this study, we demonstrate these dynamic changes at high resolution through daily stool sampling and assess the impact of individual antibiotics on those changes. Dramatic microbiota changes and loss of commensal anaerobic bacteria are associated with adverse outcomes in hematopoietic cell transplantation (HCT) recipients. In this study, we demonstrate these dynamic changes at high resolution through daily stool sampling and assess the impact of individual antibiotics on those changes. We collected 272 longitudinal stool samples (with mostly daily frequency) from 18 patients undergoing HCT and determined their composition by multiparallel 16S rRNA gene sequencing as well as the density of bacteria in stool by quantitative PCR (qPCR). We calculated microbiota volatility to quantify rapid shifts and developed a new dynamic systems inference method to assess the specific impact of antibiotics. The greatest shifts in microbiota composition occurred between stem cell infusion and reconstitution of healthy immune cells. Piperacillin-tazobactam caused the most severe declines among obligate anaerobes. Our approach of daily sampling, bacterial density determination, and dynamic systems modeling allowed us to infer the independent effects of specific antibiotics on the microbiota of HCT patients. Clostridia and Bacteroidetes negatively influences HCT outcomes, as shown in both animal models and humans . Prior to HCT, chemotherapy and/or total body irradiation is performed to deplete the cancerous cells. These treatments, combined with simultaneous antibiotic administration, compromise immune defenses, damage the mucosal epithelium, and deplete the native intestinal microbiota, facilitating the emergence of antibiotic-resistant organisms and increasing the risk of infections , 2. Micr4–d humans , 8.Yet the relative degree and manner in which various antibiotics and conditioning regimens contribute to microbiota disruption is still not well described. In previous studies examining the changes in the microbiota of HCT patients, stool samples were collected either approximately once per week or at a limited number of time points –5, 9, 10–In this study, we collected near-daily stool samples from 18 HCT recipients, for which we analyzed total species abundance by combining 16S sequencing in conjunction with quantitative PCR (qPCR) of the 16S gene. We leveraged classical models of microbial growth with Bayesian regression techniques to quantify the impact of specific classes of antibiotics on anaerobic microbes representative of a healthy gut. Importantly, our model can be extrapolated to clinically guide sequential drug treatments that minimize detrimental effects on commensal bacteria. Our results reveal how important commensal anaerobic microbial species are lost during HCT.Our cohort consisted of 18 patients who underwent auto- or allo-HCT at Memorial Sloan Kettering Cancer Center (MSKCC) between July 2015 and January 2016. Clinical characteristics and stool microbiome data for each patient are shown in Clostridia/Negativicutes and the phyla Fusobacteria/Bacteroidetes  .A single subject’s timeline (patient 15) is presented in To quantify day-to-day community shifts, we assessed the compositional volatility of the microbiota between daily intervals, reflecting the overall degree of compositional change over time , albeit with limited credibility, whereas fluoroquinolones, vancomycin (i.v.), and trimethoprim-sulfamethoxazole had very little impact  as well as of coadministered antibiotics .Under normal circumstances, the human intestinal microbiota is relatively stable over time and largely consists of obligate anaerobic bacteria . In cont3–Here, we show that patients can differ in terms of the rapidity, magnitude, and quality of microbiota alterations, which likely reflect differences in baseline microbiota composition, exposure to antibiotics, and degrees of immune compromise and epithelial damage. The frequent stool sampling coupled with 16S qPCR and detailed clinical data allowed us to now quantify the impact of specific antibiotics on microbiota composition. In our modeling approach, we incorporated absolute measures of 16S abundance and therefore were able to study microbiome dynamics as rate changes. This would be impossible with 16S relative abundance, and the resulting covariance bias could make it impossible to disentangle loss of anaerobes from increases in other taxa . In someClostridia, Bacteroidetes, Negativicutes, and Fusobacteria), given their ties to healthy immunity and colonization resistance . Although not traditionally used to treat anaerobic infections, ceftriaxone and cefazolin have been shown to have some activity against ium spp. . The kilIndeed, we observed significant anaerobic loss during the time window of phase II, i.e., postconditioning and HCT infusion but prior to neutrophil engraftment day. Independent of antibiotic effects, these results may encapsulate direct HCT treatment- and immune suppression-related effects, including the cytotoxic effects of chemotherapy and/or radiation. We hypothesize that these factors contribute to microbiota disruption, either directly by the killing of anaerobic bacteria or indirectly by impairing host mucosal mechanisms for intestinal homeostasis.HCT exposes the intestinal microbiota to a wide variety of environmental changes and creates a complex ecosystem that is difficult to model. However, despite this being a pilot study of HCT patients, we feel that our model performed well and provided promising results largely consistent with our clinical impressions. Discerning the individual effects of different antibiotics and chemotherapy on the microbiota was a challenge as simultaneous drug administrations are common, but we are encouraged by our model estimations for individual antibiotic effects. Our complex patient population and small sample size meant that some of our results consisted of wide credibility intervals, which estimate population parameters with lower precision. Our model therefore predicted the time courses of patients qualitatively, capturing inflection points of major anaerobe loss rather than predicting time courses with high quantitative accuracy. To bypass these potential limitations, we will continue to accumulate high-frequency, quantitative microbiome data in conjunction with detailed clinical metadata to better predict the individual effects of each drug.Understanding collateral damage to the microbiota is relevant to prevent not only microbiome dysbiosis-related disease but also the rise of antibiotic-resistant pathogens , 24. A bWe followed 18 adult patients undergoing auto-HCT or allo-HCT at Memorial Sloan Kettering Cancer Center (MSKCC) from July 2015 to January 2016. There were 7 female and 11 male patients; their ages ranged from 40 to 75 years. Fecal samples were collected longitudinally from each patient during their transplant hospitalization using a prospective institutional fecal biospecimen collection protocol (described previously ). For thper os [p.o.]) ciprofloxacin 2 days prior to hematopoietic cell infusion as prophylaxis against Gram-negative bacterial infections. Allo-HCT recipients are also given intravenous (i.v.) vancomycin as prophylaxis against viridans-group streptococci  varied. In the event of a new fever during times of neutropenia, patients were usually started on empirical antibiotics, such as piperacillin-tazobactam, cefepime, or meropenem.At MSKCC, antimicrobial prophylaxis is given routinely to patients undergoing HCT. Subjects undergoing either auto- or allo-HCT are given oral  is the relative abundance of taxon i at time t. The inverse time scaling allows volatility to be interpreted as average change in composition over time. We calculated volatility using relative abundances of microbes taxonomically grouped at the genus level. Theoretically, the most volatile points (V ≈ 1) would correspond to complete microbiota replacements between two time-adjacent samples, whereby previously abundant genera would be completely replaced by different genera.We developed and employed a metric of compositional volatility to quantify the rate of overall change in microbiota composition across adjacent samples in time. The metric assesses overall community change by calculating the Manhattan distance between microbiota compositions and ranges between 0 and 1. It can be interpreted as the fraction of community turnover when pairs of consecutive samples within a single patient are compared. The volatility, o) from which each individual prophylactic antibiotic  could deviate . Finally, and with highest resolution, our model included independent variables for empirical antibiotics: piperacillin-tazobactam, meropenem, metronidazole, cephalosporins (generations 1 to 3), vancomycin (p.o.), cefepime, and linezolid were considered without pooling.The total abundances of anaerobes were calculated by multiplying the summed relative abundances of obligate anaerobic taxa obtained by 16S sequencing  with the total copy numbers of 16S genes obtained via qPCR. To estimate the effects of different antibiotics on specific microbial groups, we calculated the log-difference of absolute anaerobe cell counts per gram of stool (wet weight) between two samples (deltas) which were at most 2 days apart and within the first hospitalization. We used Bayesian regression techniques to parameterize a model of the logistic growth of the obligate anaerobe community, used similarly by Stein et al. . AntibioP). Finally, we included a term that limits the otherwise exponential growth of anaerobes at high densities . Changes in the anaerobe abundance (N) were modeled as:r), the effects of phase I (βp1) and phase II (βp2) and the growth rate-changing effects, βai, of empirical antibiotics (iA) and antibiotic prophylaxis , with the residual uncaptured variance of the model, σm). As for phase I and II, we constructed binary antibiotic covariate indicators .We accounted for repeated samples from the same patient by including a random intercept term (1 | 2)] for the growth rate, empirical antibiotics, and the HCT treatment phases and regularizing priors [𝒩] for the other parameters. This analysis produced posterior distributions for each parameter after “no U-turn” sampling of 10,000 samples from 3 traces , and other coadministered antibiotics. We then repeatedly chose a random antibiotic course from this list, with replacement, and assigned parameters chosen jointly from the posterior parameter value distributions to our model. Then, starting from an initial, normalized density set to 1, we used the model to calculate the predicted fold change of anaerobe density at the end of each antibiotic course. Aggregating all of these fold change values allowed us to calculate the average residual fraction of anaerobes after a typical course of specific antibiotics.


We report details of a unique association of hadrosaur and therizinosaur tracks found in the Late Cretaceous lower Cantwell Formation, Denali National Park, central Alaska Range, Alaska. This rock unit is now well-documented as a source of thousands of fossil footprints of vertebrates such as fishes, pterosaurs, and avialan and non-avialan dinosaurs. The lower Cantwell Formation in this area consists of numerous fining-upward successions of conglomerates and pebbly sandstones, cross-stratified and massive sandstones, interbedded sandstones and siltstones, organic-rich siltstones and shales, and rare, thin, bentonites, typically bounded by thin coal seams, and it contains a diverse fossil flora. We report the first North American co-occurrence of tracks attributable to hadrosaurs and therizinosaurs in the lower Cantwell Formation. Although previously un-reported in North America, this association of hadrosaur and therizinosaur tracks is more characteristic of the correlative Nemegt Formation in central Asia, perhaps suggesting that parameters defining the continental ecosystem of central Asia were also present in this part of Alaska during the Latest Cretaceous. Here we document the co-occurrence of tracks attributable to hadrosaurs (Ornithischia) and therizinosaurs (Saurischia) in the lower Cantwell Formation exposed in the Big Creek drainage of DENA. The tracks at this site are preserved in debris blocks of various sizes. Field observations confirm that the blocks eroded from a single sandstone layer farther up slope. Tracks preserved in the in-situ sandstone are only viewable in cross-section. While most specimens are single tracks of either hadrosaurs or therizinosaurs exposed on small blocks, one very large block confirms the tracks of both types of dinosaurs on the same bedding plane  were deposited onto channel floors at the front or sides of migrating channel bars. Channelized conglomerate and pebbly sandstones are interpreted as vertically accreted channel and bar complexes characteristic of a predominantly sandy braided river9. Tabular, fining-upward, trough cross-bedded sandstones are interpreted as shallow distributary channels. Shallow channel-fills and tabular sandstones abruptly overlying siltstones and mudstones suggest a recurrent pattern of frequent avulsion and unconfined flow27. Mud drapes and desiccation cracks indicate rapid abandonment and periodic drying out of sediments as channels avulsed across distal fan lobes and adjacent basin marginal floodplains22.Coarsest-grained deposits constitute 2–10 m thick successions bounded by thick mudstone. Average maximum clast size is 12 cm. Medium- and fine-grained sandstones are present in both fining- and coarsening-upward cycles. These units (~10 to 50 m thick) consist of recurrent intervals of tabular fine- to medium - pebbly sandstones and mudstones. Well-stratified pebble conglomerates and sandstones are interpreted as traction-flow deposits onto gravelly channel floors and sand barsOverbank deposits include laterally extensive, thin, fine- to very fine-grained sandstones interbedded with siltstones, mudstones and coaly shales Fig. . Some sa19. Coaly shales and laminated shales represent backswamp deposits and small ponds or lakes in distal fan settings away from active fan lobes or on adjacent floodplains , shoots, cones and seeds of the deciduous conifers Metasequoia sp., , Parataxodium sp. (P. wigginsii?), Glyptostrobus sp., Tumion gracilis, Cephalotaxopsis heterophylla, and Larix sp. Angiosperm leaves and conifer shoots often form leaf mats pointing to synchronous leaf loss and a deciduous habit. Angiosperms are represented by a relatively diverse assemblage of broad-leaved and linear-bladed monocotyledonous and woody dicotyledonous leaf forms. Dicot leaf fossils are of menispermoid, trochodendroid, platanoid and higher hamamelid affinities. Palmately veined menispermoid  and trochodendroid leaves , and leaves of betulaceous form (e.g. Corylites sp. and an Alnus-like leaf) are most abundant and typically occur in fine-grained floodplain environments in association with Metasequoia sp. and possibly Parataxodium sp. Platanoid types, such as Platanites sp. and Pseudoprotophyllum borealis, are more common in coarser-grained sediments, suggesting a taphonomic bias or it may indicate a preference for riparian environments or more proximal alluvial fan settings28.Paleoflora from the lower Cantwell Formation has been studied in detail at two localities: Sable Mountain and upper Riley CreekEquisetum arcticum, and fern frond fossils. This implies the growth site may be a semi-open moist habitat in a groundwater-fed or frequently inundated low-lying floodplain that retained water in shallow lakes, backwater ponds, marshes, and abandoned channels. In contrast, reed-like monocot leaf impression and Equisetum sp. fossils associated with finer-grained fluvial or overbank sands and muds may extend the habitat interpretation to a riparian setting29. As drainage improved over time, wet sandy soils became more amendable for other plants to succeed. Sandstone with large-sized root horizons indicates periods of non-deposition between episodic high discharge events. The dark color of the finer-grained facies, sparse burrowing, coalification of wood, concretions, and iron oxide nodules suggest water tables remained close to the surface, while shallow lakes, ponds, and abandoned channels accumulated fine-grained sediments and supported a shallow water aquatic plant and lake margin forest community26.Other slumped blocks incorporate large pieces of fossilized and partly coalified conifer wood, leafy shoots of taxodioid-cupressaceous conifers, rhizome and stem segments and tuberli of Nuphar sp. (water lily). The Nymphaeaceae may date to as early as the Early Cretaceous, and leaves resembling extant Nuphar sp. have been named from Early Late Cretaceous outcrops along the Yukon-Koyukuk Rivers, and Paleocene of the Rocky Mountains32. The Nymphaeaceae are an aquatic plant group characterized by thin floating leaves that grow across still water ponds and shallow lakes, and sedimentary data indicate that the aquatic growth habit may be ancestral to this plant group33. The low-relief of the leaf fossil impression indicates that in life the specimen was thin-bladed. The relative integrity of this delicate leaf indicates it was not transported far, and transport by streams can be excluded. Most likely, this leaf floated on the surface of a quiet, shallow water body distal from main channels. Our taphonomic interpretation suggests the leaf was encased in rapidly settling overbank sediment while still suspended in water. This water-lily-like leaf fossil supports the assumption that the hadrosaur and therizinosaur tracks at Sable Mountain were made in shallow standing water prior to deposition of a crevasse-sand body that was deposited into a shallow pond or lake, preserving them.A small fossil leaf with a deeply cordate base, entire margin, a broad and tapered multistrand midvein and pinnate-brochidodromous venation is found at Sable Mountain in massive fine-grained sandstone that preserved the hadrosaur and therizinosaur tracks Fig. . The lea34. Mudstones were deposited outside of the main active depositional lobe or in abandoned channels. Deposition from unconfined overbank flow occurred when channels shifted or where floodwaters overtopped banks while passing through a network of smaller, sediment-choked, distributary channels. Sheet-flow is common on alluvial fans, involving an entire active lobe and becoming unconfined across the distal fan and on the adjacent alluvial plain35.Paleobotanical evidence indicates wetland and possibly riparian plant communities in the area. The study area was either a distal wet alluvial fan on a low-gradient slope, or an interfan and/or fan fringe interfingering with an adjacent axial valley floodplain39) analysis of leaf material and stable isotopic analysis of organic matter and wood28. CLAMP results for the Maastrichtian lower Cantwell Formation at Sable Mountain indicate a mean annual temperature of 7.4 +/− 2.4 °C, a warmest month mean temperature of 17.1 +/− 3.2 °C, and a coldest month mean temperature of −2.3 +/− 3.8 °C. CLAMP results also indicate growing season precipitation of 229.4 +/− 671.8 mm, three wettest months precipitation of 176.5 +/− 280.2 mm, three driest months precipitation of 141 +/− 186 mm and a growing season that was 4.8 +/− 1.4 months long. The relative humidity, calculated from CLAMP was 73.9 +/− 7.4%40.Paleoclimate during deposition of the lower Cantwell Formation was reconstructed from CLAMP  data were determined for bulk organic matter and wood fragments from the lower Cantwell Formation at the East Fork of the Toklat River at a site ~9 km west of the study area. Bulk organic matter values were used to determine values of δ13Catm, and then these values and values for δ13Cwood were used to determine isotopic fractionation of C3 plants during carbon assimilation41. This calculated value was then substituted into an equation42 to determine mean annual precipitation (MAP) for the lower Cantwell Formation. Sampling at the East Fork of the Toklat River surrounded a bentonite with a radiometric age of 69.5 +/− 0.7 Ma23, so MAP values were calculated for the Middle-Maastrichtian Event (MME), an intense greenhouse episode at ~ 69 Ma43, as well as for pre- and post-MME time. Calculated MAP estimates range from 353–1050 mm/yr before the MME, 168–470 mm/yr during the MME, and 475–1451 mm/yr after the MME23. Calculated temperature values are consistent with other Maastrichtian high-latitude paleobotanical temperature estimates, but paleoprecipitation values are lower than those reported from near-coastal high-latitude Maastrichtian environments elsewhere46.Carbon stable isotope  and the Asian oviraptorid Khaan mckennai,  with a small first digit like most non-avian theropod dinosaurs60. Derived therizinosaurs, the Therizinosauridae, have greatly modified foot structures. Therizinosaurids such as Segnosaurus galbienensis and Therizinosaurus cheloniformis have a functionally tetradactyl foot61 with digit I as robust as digits II-IV. The pedal digits are almost equally robust, and pedal phalanges are much wider than high, unlike in basal therizinosaurs and other theropods. The distal end of metatarsal I diverges medially in Nothronychus graffami, Neimongosaurus yangi, Segnosaurus galbienensis, and Therizinosaurus cheloniformis and is medially rotated in distal view. Because of its divergence and rotation, the angle between digits I and II is wider than that in basal therizinosaurs. Taken together, derived therizinosaurids from Asia  and North America (Nothronychus grafammi and Nothronychus mckinleyi) have a unique combination of pedal features , which is different from basal therizinosaurs and other non-avian dinosaurs63. Therefore, the tracks found in this study site are consistent with the known skeletal anatomy of therizinosaurs.In contrast, the feet of derived Late Cretaceous Therizinosauridae have four large weight-bearing toes64. It is particularly intriguing given that the hadrosaurids likely had a complex social dynamic5, thereby prompting hypotheses of scenarios to explain this rare co-occurrence of taxa. The first scenario is that although the tracks are spatially connected, the taxa were separated temporally. In other words, a herd of hadrosaurids and the therizinosaurids walked across this landscape at different times, and did not encounter each another in doing so. Alternatively, this co-occurrence was biologically linked, and these taxa co-existed when and where conditions were right. Such a scenario warrants some speculation about the paleobiological significance of this co-occurrence of fossil taxa. Extant taxa provide clues to the possible interaction, because different species of extant taxa can co-exist for beneficial reasons, such as improving resource acquisition or reducing predation risks.The association of hadrosaurid and therizinosaurid tracks in Late Cretaceous sediments of south-central Alaska/Beringia is noteworthy because it is not reported elsewhere in North America. Rather, this faunal association is more characteristic of correlative rocks in central Asia66, but further observation and study suggested instead that predator avoidance played as significant a role66. It is now recognized that predator avoidance is complex, as enhanced sensory perception of one herbivore species verses another can offer benefits for co-existence67. Landscape heterogeneity can also play a role and can contribute specifically to the dynamics in the case of wildebeests and zebras68 mentioned above.The co-existence of African zebras and wildebeests has received a great deal of scientific attention, though it remains to be fully understood. Traditional views stemming from studies of the 1960s and 1970s suggested that interspecific competition was a dominant influence that shaped this co-existence69. More derived Late Cretaceous therizinosaurids such as Erlikosaurus andrewsi and Segnosaurus galbinensis had a reduced bite force compared to earlier therizinosaurs such as Falcarius utahensis69. Another examination that modeled the bite force in Erlikosaurus andrewsi suggested that the bite force in the hadrosaur Edmontosaurus was greater than that for Erlikosaurus70. The lesser bite force for Erlikosaurus better served in stripping and cropping leaves, rather than active mastication70. While Erlikosaurus and Segnosaurus are from rocks older than the lower Cantwell Formation, they are the only derived therizinosaurids with described jaws within the clade that includes Therizinosaurus, the therizinosaurid correlative with this Alaskan rock unit15. Given this evolutionary relationship, it is reasonable to speculate that Therizinosaurus had a similarly lesser bit force.Recent work on jaw mechanics and endocranial anatomy of therizinosaurs allows for comparison of some attributes between this clade and the better-known hadrosaurs. A study of evolutionary trends in jaw mechanics of therizinosaurs noticed a change in bite force through timeEdmontosaurus, suggested hadrosaurs were actively chewing grazers rather than browsers71. It is tempting to conclude that these two kinds of herbivorous dinosaurs co-existed in a mixed-taxonomic herd because of reduced interspecific competition for food resources. However, this ecological process has fallen out of favor among workers studying modern ecosystem processes and interactions68, so caution must be exercised before uncritically applying this phenomenon to an example from the fossil record.Hadrosaur tooth microwear, specifically in 72. Such sensory attributes almost assuredly served an important role in activities such as foraging, predator evasion, and/or social complexity72. In contrast, while increased olfaction was proposed for at least some members of the Lambeosaurinae73 a reevaluation of the nasal cavity in this group of hadrosaurs suggested instead that the nasal region of hadrosaurs was conservative74. Again, it is tempting to consider the differences in sensory adaptations and capabilities in these taxa that might have served a role as a mutually beneficial predatory avoidance mechanism for the more inclusive herd. However, if co-existence for predator avoidance was the reason for this co-occurrence of taxa and their tracks, then one would expect that the demographic profile of the two taxa to be similar, as expressed by the length-width measurements of the tracks for each taxon. Measurements of the tracks at the site do not plot to the same sort of herd demographic pattern  and therizinosaurids (Therizinosaurus chelonifomis), and there are footprint localities dominated by hadrosaurid tracks77. To account for the stratigraphic distribution of hadrosauroids in the Mongolian sequence of sediments, it was offered that the presence or absence of hadrosauroids in the Late Cretaceous rock units of Mongolia may be linked to the climatic conditions under which each rock unit was deposited76. More specifically a shift from more arid to more mesic conditions may account for the immigration of derived hadrosaurids from North America76.The correlative Nemegt Formation of Mongolia is thought to have been deposited under more humid conditions than either the older Cretaceous Djadokhta or Baruungoyot formations in the same area78. In addition to channel and splay deposits throughout the area, the presence of nymphaeaceous leaf fossils near the Big Creek track site shows that rivers and still-water ponds and lakes existed in this part of DENA at the time. The co-occurrence of tracks of hadrosaurids and therizinosaurs here, as well as body fossils of both taxa in the relatively wet paleoenvironment of the Nemegt Formation of Mongolia, seems more likely to be linked by an aspect of environment  rather than sophisticated multi-taxonomic herd behavior  an epoxy cast made from the mold was used for modeling. Photogrammetric models presented in Fig. 83.The surface morphology of each track was captured using photogrammetry utilizing molds made in the fieldSupplementary information


Pygoscelis antarctica) from three breeding locations in the northern Antarctic Peninsula region during the austral winter of 2017. The satellite tracking data revealed overlap of individuals over continental shelf areas during autumn months (Mar-May), shared outbound corridors that track the southern Antarctic circumpolar current front, followed by occupancy of progressively colder, deeper, and ice-free waters that spanned the entire western hemisphere south of the Polar Front. Despite broadly similar physical environments used by individuals from different colonies, the proportion of birds from each colony that remained within 500km of their colony was positively correlated with their local population trends. This suggests that local migration strategies near the Antarctic Peninsula may benefit breeding populations. However, the magnitude of inter-colony and intra-colony overlap was generally low given the broad scale of habitats occupied. High individual variation in winter movements suggests that habitat selection among chinstrap penguins is more opportunistic, without clear colony-specific preference for fine-scale foraging hotspots. Mixing of individuals from multiple colonies across broad regions of the Southern Ocean would expose chinstrap penguins from the Antarctic Peninsula to a shared environmental experience that helps explain the regional decline in their abundance.A goal of tracking migratory animals is to characterize the habitats they use and to interpret population processes with respect to conditions experienced en route to, and within, overwintering areas. For migratory seabirds with broad breeding ranges, inferring population-level effects of environmental conditions that are experienced during migratory periods would benefit by directly comparing how birds from different breeding aggregations disperse, characterizing the physical conditions of areas they use, and determining whether they occupy shared foraging areas. We therefore tracked 41 adult and juvenile chinstrap penguins ( Migration links disjunct habitats that are vital to the success of many species. Regular movement between, and occupation of, such different areas is generally thought to arise because fitness benefits accrue in different habitats at different times. For example, conditions encountered within foraging areas during the non-breeding period (hereafter winter) are hypothesized to affect survival and future reproductive success of many migratory animals ,2, ultimWhile the distribution of summer and winter habitats used by some species are well known and leveraged effectively in conservation and management efforts , informaPygoscelis antarctica), a migratory seabird with a circumpolar breeding distribution that is centered primarily on the island archipelagos in the south Atlantic sector of the Southern Ocean. Worldwide, the IUCN rates the conservation status of chinstrap penguins as ‘least concern’ with a declining population currently estimated around 8 million mature individuals [Here, we consider the chinstrap penguin , fish, and squid, which form the majority of the prey consumed by chinstrap penguins [We focus our analysis on the spatial distribution of the chinstrap penguins during winter and the environmental conditions encountered by them: sea ice, sea-surface temperature, and surface currents. Chinstrap penguins are considered an ice-avoiding species, generally being observed in open waters seaward of the edge of sea ice , thus icpenguins . Our aimResearch was permitted under U.S. Antarctic Conservation Act Permits (Permit #2017–012), the Polish Permitting Authority IBB PAS (Permit #05/2016), and the Argentine Dirección Nacional del Antártico Environmental Office (Permit 2017–010). Field protocols were approved by the University of California San Diego Institutional Animal Care and Use Committee (S05480).We conducted our study at Cape Shirreff and Admiralty Bay, in the South Shetland Islands and at Cierva Cove, along the western Antarctic Peninsula . Over thPost-molt adult and fully-fledged juvenile chinstrap penguins were captured for instrumentation between 18 February 2017 and 9 March 2017 . We assu2) to produce habitat utilization distributions (HUD) using the R package ‘crawlr’ [The raw location data collected by the ARGOS satellite system were processed to remove erroneous location estimates as indicated by “Z” quality codes, unspecified ellipse errors, and as indicated by speed filters with a conservative constant swim speed of 2.5 m/s. We arbitrarily restricted our data set to deployments with at least one week of location estimates to minimize over-representing near-colony habitat use immediately following molt or fledging. This restriction removed 15% of all adult tracks and 30% of all juvenile tracks . All ret‘crawlr’ . This reTo assess movement of birds on a larger scale, we classified each deployment into western, local or eastern bins to assess the frequency of different, large-scale migration patterns within colonies. The classification for each deployment was based on the net direction traveled and maximum distance achieved from its tagging location. We assigned a track to the local bin if it remained within a 500 km radius of its tagging location. This arbitrary radius was based on assessments of the maximum distance attained from each tag’s origin . It is eAverage, monthly environmental conditions encountered during the study period were extracted from data layers characterizing habitat covariates (see below) using the areal extent of each monthly HUD. Monthly indices were selected to provide conservative estimates of environmental conditions given inherent uncertainty in location estimates and to limit over-interpretation of environmental conditions experienced by the few animals tracked in such remote locations. The covariates considered here included bathymetry, zonal (west-to-east) surface currents, sea-surface temperature (SST), and sea-ice concentration (SIC). We used the bathymetry data from ETOPO1  to extraWe also matched raw position estimates with daily estimates of SST and SIC. These along-track indices were created to complement the monthly composites from the HUDs and to examine near real-time experience of SST and SIC that the monthly composites may smooth. We used daily Multi-scale Ultra-high Resolution (MUR) SST resolved on a 1 km grid  and dailFinally, we used the locations of the Polar Front (PF), southern Antarctic circumpolar current front (SACCF), and southern boundary of the Antarctic circumpolar current (SBACC) , availabGiven the wide range of ocean areas used by the tagged penguins , we creaData with ≥1 week of at-sea position estimates were collected from 34 adults and 7 juveniles, representing 90% of all deployments . On aver2 = 22.4, df = 2, p<0.001). Due to small sample sizes and short durations of juvenile penguin deployments  when sea ice extent was greatest, chinstrap penguins were distributed across a wide longitudinal range near the ice edge . As ice During the winter, individuals occupied areas from roughly 170°W to 25°W, spanning a distance of roughly 8000 km at 60°S. For the western-most observation, the nearest point of land was Cape Adare on the northwest coast of the Ross Sea, roughly 1080 km to the southwest. The nearest known chinstrap breeding colonies, in the Balleny Islands, are similarly 1100 km to the southwest . The nearest point of land to the eastern-most observation was roughly 215 km to the southwest at Zavadoski Island , in the South Sandwich Islands, home to the world’s largest known chinstrap breeding colony . Thus, cAcross this wide expanse of Southern Ocean, the birds generally remained in cold (≤2°C) waters south of the PF, even as sea ice advanced north . The opeDespite the decrease in general habitat availability across the broad longitudinal range of areas that chinstrap penguins occupied, overlap of the monthly HUDs was low. Inter-colony overlap by birds from the three colonies was highest from March through June, covering roughly 10–13% of the total monthly HUD area each month . During Tracking the winter migrations of adult and juvenile chinstrap penguins from multiple breeding locations within the northern Antarctic Peninsula region revealed shared east-west migration corridors along the SACCF but relatively little overlap of wintering areas within or across colonies. Rather, chinstrap penguins distributed themselves broadly between the sea ice edge and the PF, occupying progressively generally colder (<2° C), ice-free, and deeper physical habitats that spanned the western hemisphere of the Southern Ocean. Across this broad area, inter-colony and intra-colony overlap was generally low except in the months immediately following tagging over shelf areas in the vicinity of the study colonies. We interpret the patterns of overlap and wide distribution of birds across the Southern Ocean to suggest that the availability of suitable physical habitat for chinstrap penguins is widespread throughout the winter.P. papua) are increasing in the Antarctic Peninsula region in contrast to their migratory congeners, the chinstrap and Adélie (P. adeliae) penguins [At a colony level, the tracking data support expectations that colony location influenced the general direction of travel during outbound migration . For exapenguins . Alternapenguins  suggest Nonetheless, the limited degree of spatial and temporal inter-colony and intra-colony overlap suggests that individual variations in movement are the primary factor driving the ultimate spatial patterns of habitat occupancy across the Southern Ocean during winter. From each colony, some adults and juveniles remained relatively local, while others rapidly moved thousands of kilometers along relatively narrow corridors, with individuals choosing unique stopover locations along the way. Such high levels of individual variability in movement patterns can make unambiguous identification of colony-specific wintering areas problematic . Multi-yDespite the similarity of general physical habitats used by chinstrap penguins during winter, smaller-scale processes undoubtedly inform individual-level selection of foraging areas. For example, local hydrographic variation and frontal zones influence the distribution of foraging areas by individual penguins during the breeding season ,49,50, a15N signatures in tail feather tissues of chinstraps that migrated west [We assume that fine-scale habitat use during winter is also driven by heterogeneity in local prey distributions. However, such distributions are virtually unknown across the extent of areas occupied. A prior study of the stable isotopic niches occupied by chinstrap penguins during winter revealed elevated ted west  highlighted west , suggestMulti-colony studies of some wide-ranging seabird species have highlighted convergence of individuals from multiple colonies on relatively small-scale, specific locations ,51. SuchConservation and management efforts for chinstrap penguins may therefore be prioritized by focusing on these coastal foraging habitats over the shelf of the Antarctic Peninsula region. There, spatial and functional overlap with the Antarctic krill fishery occurs , and colThe long-term decline in abundance of chinstrap penguins is the predominant trend observed at multiple locations in the Antarctic Peninsula and Scotia Sea region , though S1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S4 Fig(PDF)Click here for additional data file.S5 Fig(PDF)Click here for additional data file.S6 Fig(PDF)Click here for additional data file.S7 Fig(PDF)Click here for additional data file.S1 Data(ZIP)Click here for additional data file.


Given that obesity and associated disorder type II diabetes mellitus have reached epidemic proportions worldwide, the development of efficient prevention and therapeutic interventions is a global public health interest. There is now a large body of evidence suggesting that the micro-organisms colonizing the human gut, known as gut microbiota, play a central role in human physiology and metabolism. Understanding how gut microbiota affects and regulates key metabolic functions such as glucose regulation and insulin resistance is an important health issue. The present review summarizes recent advances in our understanding of how gut bacterial species interfere with host metabolic phenotype. We will examine key biological molecular mechanisms underlying the impact of gut microbiota on host glycemic control including: incretin secretion, short-chain fatty acid production, bile acid metabolism, and adipose tissue regulation. We will highlight how prebiotic/probiotic interventions affect these bacterial processes and are now considered as promising approaches to treat obese and diabetic patients. Obesity is a chronic, complex, and multifactorial disease representing the fifth leading cause of death in the world and accounting for almost 3.4 million deaths each year .2. Epidemiological studies indicate that more than 2.1 billion people are currently overweight or obese worldwide. If current trends continue, estimations show that 38% of the world's adult population will be overweight and another 20% will be obese by the year 2030 , which is the hallmark of the disease. Hyperglycemia is due to concomitant insulin resistance and insufficient insulin secretion due to beta-cell function impairment over time, resulting in failure to control blood glucose levels. Even if the precise mechanisms by which obesity leads to insulin resistance affecting skeletal muscle and liver, but also adipose tissue and brain, are not fully understood, epidemiological studies have established that T2DM is the result of complex gene-environment interactions. Excess caloric intake and reduced energy expenditure are important predictors of obesity and T2DM. Recent experimental and clinical evidence suggests that another key endogenous factor may be considered as a critical host metabolism regulator: the gut microbiota. Although still debated, it is estimated that up to 100 trillion micro-organisms reside throughout our body and that the collective gene set of our gut microbes is about 150 times larger than our own human genome , 9. MicrBacteroidetes and Firmicutes, including species of the Ruminococcus, Lactobacillus, and Clostridium genera, constitute over 90% of the known phylogenetic categories and dominate the healthy intestinal microbiota , with a 50% reduction in the abundance of Bacteroidetes, and a proportional increase in Firmicutes compared to their lean siblings  and gastric inhibitory polypeptide (GIP), are gut peptides released from enteroendocrine cells. They are secreted into blood stream and rapidly stimulate insulin secretion from beta cells in response to nutrients in order to control meal-related glycemic excursions . Oral glSeveral studies have attempted to decipher how gut microbiota regulates and interferes with incretion secretion. Notably, authors have showed that the fermentation action of gut microbiota in the colon could impact the number of enteroendocrine cells. The addition of non-digestible carbohydrates, such as oligofructose, in the diet has been shown to improve glucose tolerance, insulin response, and to reduce food intake in mice and humans. These beneficial metabolic effects have been linked to higher plasma GLP-1 levels –36. To c2S), a bioactive gas metabolite abundantly produced in the colon by sulfate-reducing bacteria, can directly stimulate intestinal GLP-1 response  are organic fatty acids containing two to six atoms of carbon. They are produced in the colon and the caecum of the host following the anaerobic fermentation of non-digestible dietary fibers by saccarolytic bacteria . Acetateynthesis . Short cIn addition to being an important source of energy for the host, SCFA contribute to many biological pathways including amelioration of the host metabolic health. Notably, they are involved in intestinal health by impacting colonocytes proliferation, differentiation, and inflammation , 52. MorAt a local level, propionate and butyrate have been described to stimulate intestinal gluconeogenesis, via different mechanisms . IntestiThe discovery of SCFA receptors in many different tissues has highlighted SCFA as important signaling molecules involved in the metabolic crosstalk between the gut and peripheral tissues. Notably, two G protein-coupled receptors have been described to be activated by SCFA and identified as modulators of microbiota-host interaction: GPR41 and GPR43, also known as the free fatty acid receptors FFAR3 and FFAR2, respectively . They hain vivo. Inconsistently, in another study, high fat diet-fed GPR43—deficient mice were shown to have lower body fat mass associated with improved glucose control and insulin sensitivity as well as increased energy expenditure compared to normal diet-fed mice  in hepatocytes. Alternatively, the interaction bile acids/FXR in ileal enterocytes induces the expression of fibroblast growth factor  which enters the circulation and further inhibits bile acid synthesis through activation of hepatic fibroblast growth factor receptor 4 (FGFR4) .For in-depth reviews on bile acid synthesis and feedback regulation, the reader is referred to following reviews: , 80. TheBile acids and gut microbiota are mutually linked and closely affect each other. Bile acids that escape from ileal reabsorption enter the colon where they are transformed into secondary bile acids by the resident gut microbiota . EnzymatSeveral studies have highlighted the importance of bile acid modification genes in the gut microbiome in host metabolic status by quantifying the abundance of bile salt hydrogenase (BSH) gene, 7 alpha-dehydroxylase (ADH) gene, and 7-alpha hydroxysteroid dehydrogenase (HSDH) gene in fecal samples from T2DM patients. They showed that gut microbiota of T2DM patients was characterized by a significant reduction in firmicute-derived BSH. Reduction of ADH and HSDH genes was also found in T2DM patients relative to healthy controls .Lactobacillus reuteri NCIMB 30242 daily was shown to increase circulating bile acids by >2-fold as a result of enhanced intestinal bile acid deconjugation, which was associated with an increase of FGF19 secretion  markedly modulated the gut microbiome leading to an activation of TGR5/GLP-1 signaling to effectively improve insulin sensitivity and glucose tolerance . FurtherThe expression and production of the entero-hormone FGF19 are also directly controlled by bile acids, and recent reports revealed that besides its well-known action in the feed-back regulation of hepatic bile acid production, FGF19 circulates in the body, and exerts important metabolic actions. For example, FGF19 has been described to stimulate hepatic glycogen synthesis in postprandial state, hence contributing to reduce blood concentrations of glucose . In miceInterestingly, a growing body of evidence suggests that microbiota-bile acids interactions play also a role in the rapid improvement of glycemic control after bariatric surgery , since aAlthough it is complex and not fully understood, bile acid homeostasis is another piece in the puzzle linking microbiota, and host glycemic control. Modulation of the gut microbiota-bile acids axis may offer a future therapeutic approach in obesity and T2DM.Emerging evidence suggests that microbes resident in the human intestine are involved in host glycemic regulation through adipose tissue regulation , 107. AdLactobacillus fermentum MTCC5689 for a period of 6 months has been shown to reduce pro-inflammatory gene markers TNFα and IL-6 in visceral fat of high fat diet fed mice  by acquiring features of brown adipose tissue. This transition takes usually place under certain conditions such as cold exposure or chronic endurance exercise, and transforms white adipose tissue into beige adipose tissue. Beige adipose tissue exhibits higher thermogenesis rate and enhanced capacity to dissipate energy through UCP1-mediated mitochondrial uncoupling . BecauseSeveral studies have indeed highlighted that adipose tissue browning promoted a lean and healthy metabolic phenotype including by improving insulin sensitivity. In 2015, Suarez-Zamorano et al. uncovered a mechanism linking gut microbiota, beige fat development, and metabolic disorders . They poLactobacillus reuteri 263 mediates its anti-obesity effect through energy metabolism remodeling of white adipose tissue in a model of obese rats (Lactobacillus reuteri 263 enhanced oxygen consumption in white adipose tissue after 8 weeks of daily treatment. The mRNA expressions of thermogenesis genes were up-regulated in the white adipose tissue of treated group compared to the control group. Furthermore, Lactobacillus reuteri 263 induced browning of white adipose tissue due to an upregulation of browning-related genes mRNA levels. The analysis of a human cohort has reinforced data showing a link between gut bacteria and adipose tissue browning; 34 morbidly obese women and men have been analyzed in order to identify a potential relationship among gene expression markers of adipose tissue browning and gut microbiota composition (Firmicutes relative abundance is positively associated with markers of brown adipose adipocytes in subcutaneous adipose tissue and insulin sensitivity. Geurts et al. provided evidence that the endocannabinoid system might also have a role in the interplay between gut microbiota, adipose tissue browning, and glucose tolerance (More recently, Chen et al. have identified that probiotic strain ese rats . Authorsposition . Authorsolerance . Severalolerance .In connection with previous section, bile acids have been described to activate thermogenesis and adipose tissue browning, therefore improve metabolic control . The admFirmicutes to Bacteroidetes and increased Akkermansia muciniphila abundance in the gut microbiota, together with and increased amount of brown adipocytes in high fat diet-fed mice (Numerous compounds, such as gypenosides from jiaogulan tea or Danshensu Bingpian Zhi, a synthetic derivative of natural compounds used in traditional Chinese medicine, have been lately described to modulate both gut microbiota composition and adipose thermogenesis leading to a better host glycemic response , 134. Nofed mice . These cThe gut microbiota has become the subject of considerable investigation in recent years and our knowledge of its composition and functions is rapidly growing.It is becoming increasingly clear that gut microbiota has profound impact on host physiological and pathophysiological processes. Notably, it is now well-established that imbalanced gut microbiota is linked to host glycemic control impairment and T2DM development, as showed by the findings we have reviewed.Although the precise role of gut microbiota remains incompletely understood, as suggested by multiple studies that remain controversial, several key molecular mechanisms linking gut bacterial residents, and host glucose homeostasis have been highlighted and include: intestinal incretin secretion, SCFA production, bile acid metabolism, and adipose tissue regulation. Some of these bacterial processes can be targeted to improve the treatment of T2DM patients, suggesting that these approaches appear as a promising avenue for the treatment of glycemic disorders. As a matter of fact, despite a large therapeutic arsenal, the treatment of this complex chronic disease is far from being optimal since in a majority of patients, T2DM remains poorly controlled over time. Using pre/probiotics in order to modulate blood glucose has been considered for a long time, and the discovery of the key roles of gut bacteria in T2DM has boosted research efforts in this field. However, the low efficacy of currently available pre/probiotic strategies highlights the lack of well-defined and standardized methodology to identify and select compounds and bacterial strains with proven antidiabetic properties. This is probably the challenge of the next 5 years. A better understanding of the mechanisms by which gut microbiota impacts host physiology will help defining innovative and efficient strategies to identify probiotic strains with antidiabetic activities or nutritional interventions increasing their abundance in the gut. Although preclinical models will probably result in the rapid identification of new and efficient probiotic strains, the transfer of these data to the human situation will require large and well performed clinical trials in the next few years. Therefore, a deeper understanding of the tight interplay between gut microbiota and host glycemic control and a validation of this knowledge in humans are still needed to optimize and individualize gut microbiota manipulation to combat metabolic diseases and improve overall host metabolic health.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The primary objective of this study was to determine the surgical team’s learning curve for robotic-arm assisted TKA through assessments of operative times, surgical team comfort levels, accuracy of implant positioning, limb alignment, and postoperative complications. Secondary objectives were to compare accuracy of implant positioning and limb alignment in conventional jig-based TKA versus robotic-arm assisted TKA.This prospective cohort study included 60 consecutive conventional jig-based TKAs followed by 60 consecutive robotic-arm assisted TKAs performed by a single surgeon. Independent observers recorded surrogate markers of the learning curve including operative times, stress levels amongst the surgical team using the state-trait anxiety inventory (STAI) questionnaire, accuracy of implant positioning, limb alignment, and complications within 30 days of surgery. Cumulative summation (CUSUM) analyses were used to assess learning curves for operative time and STAI scores in robotic TKA.p = 0.01) and surgical team anxiety levels (p = 0.02). Cumulative robotic experience did not affect accuracy of implant positioning (n.s.) limb alignment (n.s.) posterior condylar offset ratio (n.s.) posterior tibial slope (n.s.) and joint line restoration (n.s.). Robotic TKA improved accuracy of implant positioning (p < 0.001) and limb alignment (p < 0.001) with no additional risk of postoperative complications compared to conventional manual TKA.Robotic-arm assisted TKA was associated with a learning curve of seven cases for operative times (Implementation of robotic-arm assisted TKA led to increased operative times and heightened levels of anxiety amongst the surgical team for the initial seven cases but there was no learning curve for achieving the planned implant positioning. Robotic-arm assisted TKA improved accuracy of implant positioning and limb alignment compared to conventional jig-based TKA. The findings of this study will enable clinicians and healthcare professionals to better understand the impact of implementing robotic TKA on the surgical workflow, assist the safe integration of this procedure into surgical practice, and facilitate theatre planning and scheduling of operative cases during the learning phase.II. Total knee arthroplasty (TKA) is an established and cost-effective treatment for patients with symptomatic end-stage knee osteoarthritis . HoweverExisting studies on the learning curve of robotic-arm assisted TKA have used operative times as exclusive markers of surgical competence, and found surgical proficiency may be achieved by high-volume arthroplasty surgeons within a few months , 20. It The primary objective of this study was to determine the surgical team’s learning curve for robotic-arm assisted TKA through assessments of operative times, surgical team comfort levels, accuracy of implant positioning, limb alignment, and postoperative complications. The hypothesis was that cumulative experience with robotic-arm assisted TKA would lead to improved operative times and surgical team comfort levels but there would be no learning effect for accuracy of implant positioning or limb alignment. The secondary objectives were to compare accuracy of implant positioning and limb alignment in patients undergoing robotic-arm assisted TKA versus conventional jig-based TKA.This prospective cohort study included 120 patients with symptomatic knee osteoarthritis undergoing primary TKA between 2016 and 2017. This included 60 consecutive patients undergoing conventional jig-based TKA followed by 60 consecutive patients receiving robotic-arm assisted TKA. Patients were allocated to their treatment group based on the date of their surgery relative to installation of the robotic device into the study institution. Conventional jig-based TKA was performed prior to installation of the robotic device, and robotic-arm assisted TKA performed after its installation. Patients were not randomized but this enabled assessment of learning curves associated with complete transition from conventional jig-based TKA to robotic-arm assisted TKA. All operative procedures were performed by the senior author who is experienced in performing conventional jig-based TKA and had undergone cadaveric training on robotic-arm assisted TKA. The robotic group was the first cohort of patients undergoing robotic-arm assisted TKA under the operating surgeon.n = 6); prior infection of knee joint (n = 1); arthroplasty for fracture or previous osteotomy (n = 2); and underlying neurological dysfunction compromising mobility (n = 1). Patients undergoing conventional jig-based TKA and robotic-arm assisted TKA were well matched for baseline characteristics  with plain radiographs to preoperatively template implant sizes and positions. Full-length hip-to-ankle radiographs were used to guide femoral and tibial resection angles to achieve neutral mechanical alignment. Lateral knee radiograph was used to select the femoral component size and position to restore the patient’s native posterior condylar offset ratio whilst avoiding overhang or notching of the femur. Tibial implant position and size were selected to restore native posterior tibial slope and avoid any anteroposterior overhang. On the anteroposterior knee radiograph, femoral and tibial implant positons and sizes were selected to achieve maximum mediolateral contact whilst avoiding overhang. In patients undergoing robotic-arm assisted TKA, preoperative CT scan and CAD model were used to select the optimal implant positioning and implant sizes for achieving the desired bone coverage and limb alignment.Conventional jig-based TKA was performed using standard instrumentation with alignment jigs to guide bone resection. Extramedullary referencing was used to perform tibial bone resection perpendicular to the mechanical axis of the tibia in the coronal plane with the aim of matching anatomical anteroposterior slope in the sagittal plane. The femur was prepared using an intramedullary alignment jig with the distal cutting block positioned so that the distal femoral cut was at 5°–7° valgus angle depending on the pre-existing deformity. The distal femoral cutting block was positioned in 3° or greater of external rotation using the transepicondylar axis. Flexion and extension gaps were checked and appropriate soft tissue releases performed to ensure the knee was balanced. No further intraoperative adjustments or tailoring of implant positioning were performed to account for individual patient anatomy.In patients undergo robotic-arm assisted TKA, distal femoral and proximal tibial bicortical registration pins were inserted and fixed arrays mounted onto these to enable intraoperative dynamic referencing. Bone registration was performed by intraoperatively mapping radiological landmarks displayed on the computer screen to verify anatomy and establish bone geometry. Joint balancing captured femoral and tibial poses with corrective forces, assessed kinematics through the arc of motion, and enabled fine tuning of implant positioning based on laxity of the soft tissue envelope. An intraoperative surgeon-controlled robotic arm with visual, tactile, and audio feedback was then used to execute the preoperative plan to within 2 mm of the planned bone resection. Tibial and femoral osteotomies in the coronal plane were performed perpendicular to the tibial and femoral mechanical axes, respectively, to achieve neutral overall alignment. In the sagittal plane, 0°–5° of femoral component flexion were used to optimise implant sizing whilst preventing notching. The tibial slope was initially set to zero degrees and then adjusted as required based on intraoperative assessment of the flexion gap and range of motion. Optical motion capture technology was used to assess limb alignment, range of motion, flexion and extension gaps, and arc of motion with trial implants prior to definitive selection and cement implantation of final components.All radiological measurements were recorded by each observer at 28 days apart and findings compared to assess for intra-observer agreement. Radiological measurements were compared between the two observers to assess for inter-observer agreement. Interclass correlation coefficient was 0.9 (95% CI 0.8–1.0) for intra-observer agreement and 0.9 (95% CI 0.8–0.9) for inter-observer agreement in all study outcomes, which indicated good agreement on all radiological parameters assessed by the two independent observers.Operative time was defined as time from initial surgical incision to final wound closure. In robotic-arm assisted TKA, surgical times for the following parts of the procedure were recorded: Set up of surgical tray, robotic device, and instruments; surgical approach and insertion of registration pins; bone registration; joint balancing; bone preparation; implant trialling; cement implantation of final prosthesis; and overall operative time.The Spielberger State-Trait Anxiety Inventory (STAI) questionnaire is a validated subjective assessment tool for quantifying an individual’s stress levels with individual traits arising from the clinical environment . The sixAll patients underwent postoperative anteroposterior weight-bearing and lateral knee radiographs, and full-length hip-to-ankle weight-bearing radiographs. Accuracy of implant positioning and limb alignment were assessed by comparing the values achieved in the postoperative radiographs to the planned values in the corresponding preoperative radiographs. Femoral and tibial axes were used as reference markers as described by Bell et al. . AccuracAll patients were reviewed in outpatient clinic at 30 days following surgery by the independent observers for clinical assessment and full weight-bearing radiographs performed. Any postoperative complications and their respective treatments during this follow-up period were recorded for analysis.Hospital review board approval was acquired from the host institution  before commencement of the study. Further Research Ethics Committee (REC) or Health Research Authority (HRA) approval was not required for this study.t tests with a power of 80% and significance level of 5%. Due to the limited follow-up time, no further adjustments were made to the sample size calculation to account for sample size attrition during follow-up.Sample size calculation was performed using operative time as the primary outcome measure and published data on operative times with similar surgical techniques for TKA. The minimal clinical difference was set at 5 min and standard deviation at 10 min . This stt tests for unpaired variables, paired t test for paired (matched) variables, and one-way ANOVA for multiple variables, The Mann–Whitney test was used for non-parametric data. Statistical significance was set at p < 0.05 for all statistical tests. All statistical analyses were performed using SPSS software version 21 .The CUSUM sequential analysis tool was used to assess learning curves in robotic-arm assisted TKA for operative time and surgical team stress levels as assessed using the STAI questionnaire. Standardised target values for the CUSUM analyses were set using the overall mean values for these outcome measures from the robotic-arm assisted TKA group. CUSUM values represent a running total of the differences between the value of each data point and the standardised target values for each outcome. Learning curves for accuracy of implant position and limb alignment in robotic-arm assisted TKA were assessed by calculating root mean square error values for radiological outcomes and assessing progression in groups of ten patients. Categorical data were compared using the chi square test and Fisher’s exact test where greater than 25% of cells had less than five cases. Normally distributed continuous variables were compared using independent p = 0.01) with no differences in baseline characteristics compared to phase 2  in a pattern similar to operative times in robotic-arm assisted TKA . During this stage, the surgeon assessed knee kinematics through the arc of motion, flexion and extension gaps, range of movement, and stability using optical motion technology. Using this intraoperative data, the surgeon was able to fine-tune femoral and tibial bone resections to balance flexion and extension gaps without having to perform more extensive soft tissue releases as may often be required in conventional jig-based TKA [–12 min. The findings of this study complement those of Sodhi et al.  that expImplementation of robotic-arm assisted TKA was associated with heightened levels of anxiety amongst the surgical team during the initial learning phase. This is important as higher levels of stress and mental strain are associated with diminished operative performance, poor decision-making, and reduced technical skills . In thisCumulative robotic experience did not impact the accuracy of achieving the planned implant positioning, limb alignment, posterior condylar offset ratio, posterior tibial slope, or native joint line restoration. Robotic-arm assisted TKA uses bone registration to confirm intraoperative spatial orientation of the limb and fixed arrays accurately track the femoral and tibial bone resection windows throughout the procedure. Stereotactic boundaries also confine bone resection to the limits of the haptic windows, which helps to reduce manual errors in bone resection and iatrogenic soft tissue injury from the handheld sawblade used in conventional TKA , 12. Thep < 0.001) [Robotic-arm assisted TKA was associated with improved accuracy in implant positioning and limb alignment compared to conventional jig-based TKA, which is important as these outcomes affect functional recovery, clinical outcomes, and long-term implant survivorship , 19, 22.< 0.001) . Improve< 0.001) , 10.There are several limitations of this study that must be appreciated when interpreting the findings. First, accuracy of implant positioning and limb alignment was measured using plain radiographs, which are not as accurate as CT scans. Second, different preoperative planning techniques were used in each treatment group, which may have affected the accuracy of implant positioning achieved with each treatment technique. Third, the surgical team in this study are all experienced in working with both conventional and navigated TKA in a high-volume arthroplasty centre, and therefore, their learning curve may not be directly transferrable to other less experienced teams. Fourth, follow-up time was limited to 30 days following surgery and so long-term data on functional outcomes, implant survivorship and revision rates were not available. Fifth, additional costs and impact on other operative cases due to increased operating times during the learning phase were not assessed.The findings of this study will enable healthcare professionals to better understand the impact of implementing robotic-arm assisted TKA on the surgical workflow. Theatre planning and scheduling of operative cases should consider increased operative times and heightened levels of anxiety amongst the surgical team during this initial learning phase. As team members become more familiar and adept with robotic technology, comfort levels improve and theatre efficiency increases thereafter. After the initial learning phase of robotic-arm assisted TKA, operative times with robotic TKA will be comparable to those with conventional manual TKA. There is no impact of cumulative experience with robotic-arm assisted TKA on accuracy of implant positioning or limb alignment, which is important for the safe implementation of this procedure into routine surgical practice. Robotic-arm assisted TKA improves accuracy of implant positioning with no additional risk of postoperative complications at short-term follow-up compared to conventional manual TKA.Implementation of robotic-arm assisted TKA alters the surgical workflow with increased operative times and heightened levels of anxiety amongst the surgical team for the initial seven cases but this does not translate to any compromise in the accuracy of implant positioning. Robotic-arm assisted TKA improved accuracy of implant positioning and limb alignment compared to conventional jig-based TKA.


In recent decades large fires have affected communities throughout central and southern Chile with great social and ecological consequences. Despite this high fire activity, the controls and drivers and the spatiotemporal pattern of fires are not well understood. To identify the large-scale trends and drivers of recent fire activity across six regions in south-central Chile (~32–40° S Latitude) we evaluated MODIS satellite-derived fire detections and compared this data with Chilean Forest Service records for the period 2001–2017. MODIS burned area estimates provide a spatially and temporally comprehensive record of fire activity across an important bioclimatic transition zone between dry Mediterranean shrublands/sclerophyllous forests and wetter deciduous-broadleaf evergreen forests. Results suggest fire activity was highly variable in any given year, with no statistically significant trend in the number of fires or mean annual area burned. Evaluation of the variables associated with spatiotemporal patterns of fire for the 2001–2017 period indicate vegetation type, biophysical conditions , mean annual and seasonal climatic conditions  and mean population density have the greatest influence on the probability of fire occurrence and burned area for any given year. Both the number of fires and annual area burned were greatest in warmer, biomass-rich lowland Bío-Bío and Araucanía regions. Resource selection analyses indicate fire ‘preferentially’ occurs in exotic plantation forests, mixed native-exotic forests, native sclerophyll forests, pasture lands and matorral, vegetation types that all provide abundant, flammable and connected biomass for burning. Structurally and compositionally homogenous exotic plantation forests may promote fire spread greater than native deciduous-Nothofagaceae forests which were once widespread in the southern parts of the study area. In the future, the coincidence of warmer and drier conditions in landscapes dominated by flammable and fuel-rich forest plantations and mixed native-exotic and sclerophyll forests are likely to further promote large fires in south-central Chile. In recent decades, surges in wildfire activity in many ecosystems worldwide, even where fuel conditions and natural ignitions historically limited fire activity, have prompted questions of whether climate change, human ignitions, land-use change, and/or altered vegetation are responsible , 2. ManyIn south-central Chile (32–40° S. Latitude), Mediterranean shrublands and sclerophyllous forests co-occur with temperate deciduous forests. Here, abundant vegetative biomass and seasonal desiccation support some of the highest levels of fire activity in South America , 12. RecEucalyptus and Pinus spp.) have expanded throughout south-central Chile in areas previously occupied by a more heterogeneous matrix of native forests, agricultural lands and degraded open forest/shrublands . Th. Th2/yr)Lithraea caustica, Peumus boldus, Quillaja saponaria, Cryptocarya alba, Beilschmiedia miersii. An open savanna community known as espinal (Acacia caven) cover the low-flat areas of the central valley [Nothofagus spp.) in more mesic areas (south-facing slopes) and steppe vegetation occur at higher elevations [Nothofagus forests  which are mixed at different altitudes with broadleaf evergreen taxa  and coniferous podocarps [Araucaria araucana, a long-lived conifer is the dominant Andean forest (above 1000 masl) in the Araucanía region, pure or mixed with N. dombeyi, N. pumilio or N. antarctica [In south-central Chile the dominant geographic controls on the distribution of vegetation include elevational gradients associated with north to south mountain ranges including the coastal cordillera and the Andes and east-west ranges, tectonically and erosionally created lowlands and valleys , seasonal temperatures and the distribution of precipitation . Additiol valley . Moreoveevations –40. The evations , 33, 41.odocarps . Araucartarctica To identify the primary controls on fire activity across the large spatial area of south-central Chile we evaluated a number of local to regional scale variables including variables that operate at finer spatial resolution than those considered by Holz et al. . These ist to June 30th. Hence, the fire year 2001–2002 represents fire activity beginning July 1st, 2001 and ending June 30th, 2002. The Bío-Bío and Araucanía regions experience the highest number of fires annually [http://www.conaf.cl/) and fire detections primarily rely on the presence and spatial distribution of mobile and fixed ground and aerial operators which are complemented by satellite derived fire detections. CONAF fire data includes forested areas and large portions of other vegetation types but does not record prescribed fires in agricultural and pasture lands. Here we focus our analyses on satellite-derived fire detections which provide comprehensive spatial and temporal coverage across all forested and non-forest lands and validation of fire detections with a time-series of satellite derived surface reflectance values. We also compare satellite derived versus CONAF burned area estimates to evaluate fire activity recorded by the different approaches.Historically, wildfire occurrence in south-central Chile was most common during the warm and dry summer season (January-March) although fires in recent decades have been recorded throughout the year in many parts of the study area , 14. Theannually . For CON2 burned pixel. We used the MODIS Collection 6 burned area product to first, characterize fire activity over the 2001–2017 interval, second, to identify key drivers of the spatial distribution of burned area in the six central Chilean regions and third, to model the probability of fire occurrence across the study area using generalized linear, generalized additive and decision tree models. The MODIS Collection 6 product uses a synergistic approach that includes both abrupt changes in surface reflection and information from 1km MODIS active fire data [We used fire detections from satellite derived MODIS Collection 6 burned area product MCD64A1, ) obtaineA1,  obtaire data , 46. TheWe used generalized linear models , generaThe multi-model approach used here provides complementary information useful for better understanding the relationship between fire activity and predictor values. GLMs estimate univariate relationships between factors known to influence fire activity  yet this approach assumes the relationship between the response and predictor variables is linear. Generalized additive models are more flexible, allowing the relationship to be determined by the data but can often result in overfitting. Random Forests decision tree models are less sensitive to correlated variables, have strong predictive power and estimate the importance of each variable in contributing to model performance .In addition to identifying models that best predict the spatial distribution of fire occurrence, we employed resource selection functions to determine whether the probability of fire occurrence in each vegetation type was higher or lower than expected based on the availability of each vegetation type. We used the Murdoch’s Index and the R-package ‘Resource Selection Function’ , 55–57 tCONAF and MODIS satellite-derived fire records indicate strong year-to-year variability in both the frequency of fires and total area burned and no significant trends over time . MODIS dFires burned a higher proportion of the Araucanía region compared to other regions except for the 2016–2017 fire season when large percentages of the Maule, O’Higgins, Bío-Bío and Metropolitana regions burned . Annual Results from pre-screening of model variables and generalized linear and generalized additive model selection indicate elevation, growing season precipitation, population density, slope and vegetation type best explain the probability of fire occurrence in south-central Chile  Tables. The relationship between univariate biophysical, climatic and population density variables and the probability of fire occurrence suggests that the probability of fire decreases as elevation increases . The proThe probability of fire occurrence estimated by the best GLM, GAM and Random Forests models was greatest in coastal mountain matorral and plantation forests in the North bioclimatic zone and coastal plantation forests, pasture lands and lowest in agricultural lands, higher elevations and the far northern matorral shrublands , S1 Fig.Results from resource selection function analyses for the North bioclimatic zone show strong fire preference for plantation forests, mixed native-exotic forests, native sclerophyll forests, and matorral, and show avoidance in agriculture and unvegetated lands , 2) abundant sources of accidental and intentional anthropogenic ignitions adjacent to exotic plantation forests, and 3) the fuel structure and fire-prone characteristics of Eucalyptus and Pinus plantations and native sclerophyllous forests [Diostea juncea, Lomatia hirsuta) and nonnative  plant taxa have been shown to facilitate fire spread and alter characteristics of fires that occur [Strong selective preference for fire occurrence in matorral, exotic plantation forests and dry sclerophyll forests more than would be expected in relation to their availability across the landscape can best be understood by examining the role that fuel structure, availability and condition contribute to fire occurrence and spread. All vegetation types where fire shows strong preference are characterized by abundant and connected fuels that are capable of promoting fire spread during warm, hot and dry conditions. Fire preference for exotic plantation and mixed native-exotic forests is likely a result of a combination of factors including: 1) the relatively homogenous and highly connected forest patch structure of exotic plantation forests compared to some native deciduous forests  and land cover (vegetation type) factors that influence the abundance, structure, continuity and condition of fuels and human factors (population density) that influences the distribution of ignitions.Drier areas of the North bioclimatic zone support fewer fires and lower mean annual area burned compared to the more productive, biomass-rich areas of the wetter South bioclimatic zone. Fuel-rich Araucanía and Bío-Bío regions account for 60% of all area burned across the study area even though these two areas account for only 46% of the entire study area.Matorral, pasture lands, exotic plantation forests and native sclerophyll forests represent a large proportion of the annual area burned in the North bioclimatic zone, likely a result of a mix of natural factors related to the spatial distribution of natural and human-caused ignitions and conditions driving fire spread . These vegetation types all provide abundant, flammable and continuous fuels that support fire spread.quemas agrícolas” to remove post-harvest agricultural and cereal crop stubble. Accidental spread of these fires may increasingly lead to large fires in adjacent, biomass-rich native and exotic plantation forests.Exotic plantation forests and pasture lands and annual crops represent the largest proportion of annual area burned in the wetter South bioclimatic zone. Exotic plantation forests provide abundant, structurally homogenous, connected and flammable fuels that can promote fire spread. The increase in the extent of plantation forests may interact with changing climatic conditions to promote large fires in south-central Chile. High mean annual area burned in pasture lands and annual crops is likely a result of the use of prescribed fires or “Agricultural lands account for a low amount of annual area burned in the North bioclimatic zone compared to the availability of this vegetation type to burn. This is likely due to fire management aimed at protecting agricultural production and the fragmented distribution of fuels in these areas.Fire occurrence shows strong selective ‘preference’ for exotic plantation forests in both bioclimatic zones. This result highlights an important question—whether inherent flammability, land-use practices, natural, accidental or intentional ignitions or other factors are responsible for the disproportionately high occurrence of fire in plantation forests. The relative homogeneity and continuity of woody fuels associated with plantation forests may facilitate fire spread compared to other cover types where fuel structure is more heterogenous and discontinuous.Human activity in south-central Chile can either promote  or inhibit (through increased suppression effectiveness) fire activity. Our results suggest fire activity generally decreases with population density in both bioclimatic zones, however this relationship is weaker in the South bioclimatic zone where accidental/intentional fires in rural areas may contribute to fire occurrence and spread when extreme conditions promote fuel drying.During extreme fire conditions, hot, dry and windy conditions can lead to large fires in all vegetation types, including normally mesic deciduous forests that dominate the southern regions of the study area. Warming and drying trends that are projected to continue into the future for much of south-central Chile will further promote large fires in these fuel-rich forests that are often slow to recover from fires. This may result in a further decline in the abundance of native forest assemblages.In summary, shifts in the fundamental controls on fire could portend a future with large increases in the frequency and extent of fires in south-central Chile. In light of recent large fires in Chile, efforts to reestablish more structurally and compositionally heterogeneous and less flammable native forests would likely buffer changes that are occurring in the climate system by reducing overall landscape flammability. With these anticipated changes, policymakers, managers and communities should prepare to accommodate more frequent and larger wildfires in the years to come. Policymakers and managers should also consider the role that fires in exotic plantation forests and pasture lands and annual crops may play in facilitating the spread of accidental fires into adjacent more fire-sensitive forests that may not readily recover following widespread fires. Clarifying the factors promoting large fires is becoming increasingly urgent as warmer temperatures and drier fire seasons provide conditions favorable for the occurrence of large fires throughout much of south-central Chile.S1 Fig(EPS)Click here for additional data file.S2 Fig(EPS)Click here for additional data file.S1 TableHighly correlated variables (Pearson’s correlation coefficient > 0.60) and variables with importance values < 0.05 were not included in model comparison.(DOCX)Click here for additional data file.S2 TableVariables ranked according to their Random Forests variable importance values shown as the estimated mean decrease in accuracy (MDA).(DOCX)Click here for additional data file.S3 TableModel AIC, delta AIC between best model and model shown, % deviance explained, model r-squared, degrees of freedom and predictor variables included in each model. All continuous variables were significant at the p < 0.0001 significance level.(DOCX)Click here for additional data file.S1 File(JPG)Click here for additional data file.


Pseudomonas sp. and Sphingomonas sp. were more abundant after touching standard, non-enriched sand materials, while only the relative abundance of Chryseobacterium sp. increased after touching the inoculant-enriched materials. As Chryseobacterium is harmless for healthy persons, and as standard landscaping materials and normal skin contain genera that include severe pathogens, the inoculant-enriched materials can be considered safe. Microbial inoculants could be specifically created to increase the proportion of non-pathogenic bacterial taxa and minimize the transfer of pathogenic taxa. We recommend further study into the usability of inoculant-enriched materials and their effects on the bacterial community composition of human skin and on the immune response.Human activities typically lead to simplified urban diversity, which in turn reduces microbial exposure and increases the risk to urban dwellers from non-communicable diseases. To overcome this, we developed a microbial inoculant from forest and agricultural materials that resembles microbiota in organic soils. Three different sand materials  commonly used in playgrounds and other public spaces were enriched with 5% of the inoculant. Skin microbiota on fingers  was compared after touching non-enriched and microbial inoculant-enriched sands. Exposure to the non-enriched materials changed the skin bacterial community composition in distinct ways. When the inoculant was added to the materials, the overall shift in community composition was larger and the differences between different sand materials almost disappeared. Inoculant-enriched sand materials increased bacterial diversity and richness but did not affect evenness at the OTU level on skin. The Firmicutes/Bacteroidetes ratio was higher after touching inoculant-enriched compared to non-enriched sand materials. The relative abundance of opportunistic pathogens on skin was 40–50% before touching sand materials, but dropped to 14 and 4% after touching standard and inoculant-enriched sand materials, respectively. When individual genera were analyzed,  Disconnection of man from soil is a major problem in developed countries . CoupledSkin bacterial diversity is lower among people who have an immune-mediated disease . We receper se are typically related to occupational health, i.e., frequent long-term daily exposure to specific dust-bound particles or pathogens .Three different mineral soil materials were received from Rudus Oy : sieved sand (<8 mm), safety sand used in children’s playgrounds (1–8 mm) and sandbox sand (<4 mm), hereafter, jointly referred to as sands. These sands are commonly used as surface soil materials in public parks, schools and kindergartens. Each material was divided in two parts. The first part was used unaltered, and the second part was mixed with freeze-dried organic material (ratio 1:20). This organic material is the microbiologically rich and diverse mixture of plant and soil-based materials  previously described and tested by Five urban volunteers  tested the three sand materials with and without the microbial inoculant in July 2017. First, volunteers washed their hands with soap in tap water for 20 s and patted their hands dry with a towel. Next, an assistant took skin swab samples from two fingers, identically from both hands, to collect the before samples. Each finger was stroked five times from the tip to the lowest joint with a sterile nylon swab  dipped in sterile 0.15M NaCl+ 0.1% Tween 20 solution. Volunteers then rubbed one of the fingers in sand for 20 s and the other finger in the same material mixed with the microbial inoculant . The assistant took the second round of skin swab samples, the after samples, 5 min after participants washed their hands. The procedure was repeated for all test materials separately and materials were tested in a random order. No more than one material was tested on any day and there was at least a 1-day interval between the tests. Four persons touched each mineral soil material. Fingers and persons were randomized. Skin swab samples were stored in a sterile polyethene tube in a deep freezer (<-70°C) until the DNA extraction.1 under accession number SAMN10371562 – SAMN10371609.DNA was extracted from the samples using the Fast DNA spin kit for soil  following manufacturer’s instructions. DNA samples were prepared for sequencing as in Ethical approval was received from the ethics committee of Tampere University Hospital (case number: ETL R15081). The study was carried out in accordance with the relevant guidelines and regulations in Finland and the volunteers signed informed consents.Paired-end sequence data (.fastq) were processed using mothur version 1.35.1 . BacteriBacterial sequences were aligned against a SILVA reference database, preclustered to remove erroneous reads , and scrIf the abundance of an OTU was ≤10 sequences across all experimental units, it was excluded from statistical analysis as most of the low-abundance OTUs are PCR or sequencing artifacts . We estiTo identify potential human pathogens in our dataset, we used a list of bacterial genera that include potentially pathogenic species (opportunistic + facultative) published in Appendix A by 2 to analyze pathways associated with OTUs on skin (3). The resulting OTU biom table was then used for microbial community metagenome prediction with PICRUSt on the online Galaxy interface4. PICRUSt was then used to derive relative Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway benchmarks.OTU data was inserted to KEGG: Kyoto Encyclopedia of Genes and Genomes on skin  followin on skin , which penvfit function in the vegan package) and the Bray-Curtis coefficient was used as the dissimilarity measure.All statistical analyses were performed in R  phylum after touching the microbial inoculant-enriched sand materials, while Actinobacteria (41.7%) was the most abundant bacterial phylum after touching non-enriched sand materials. Among the five most common bacterial phyla, the relative abundance of Firmicutes was higher and the relative abundances of Acidobacteria, Actinobacteria, and Proteobacteria were lower in the inoculant-enriched samples compared to the non-enriched sand samples . Within Caldalkalibacillus, Conexibacter, Marmoricola, Plaromonas, Pseudomonas, Ralstonia, and Staphylococcus) out of the nine most abundant bacterial genera were higher in skin samples taken after touching non-modified sand materials as compared to samples taken after touching inoculant-enriched sand materials . The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In organisms as diverse as worms, flies, and mice, oocyte precursors, oogonia, are generated in excess of the number of fully grown oocytes produced for fertilization. This surfeit is culled by apoptosis, also called programmed cell death –3, whichCaenorhabditis elegans, more than half of all female germ cells undergo apoptosis [PLOS Genetics reports a tour-de-force analysis of early events in the cell biology of germline apoptosis using multiple microscopic modalities, including live-cell imaging conducted in the wild-type and engulfment-defective mutants [In poptosis ,5. A key mutants . The breRaiders and colleagues used a combination of live imaging and an examination of fixed samples by fluorescence and transmission electron microscopy (TEM) to elucidate cellular events occurring during the execution stage of the apoptotic program. They noticed that dying germ cells were devoid of mitochondria. Using live-cell imaging, they observed the selective export of mitochondria from doomed germ cells into the cytoplasmic core of the germline . MitochoDuring apoptotic execution, Raiders and colleagues observed two stages of cell shrinkage. The first, referred to as “fast shrinkage,” commences approximately 80 min before the dying germ cell exhibits optical refractility. By contrast, “slow shrinkage” occurs following the closure of the ring channels . During Upon closure of the ring channels, the dying cell extensively remodels its cytoskeleton. Microtubule “cocoons,” closely apposed to the cell cortex and the nucleus, form rings in the apoptotic cells soon after ring channel closure. The apoptotic cells also extensively reorganize their actin cytoskeletons by forming large cofilin-actin rods approximately 40–70 min after ring channel closure. Interestingly, cofilin-actin rods have been observed in several neurodegenerative diseases including Alzheimers and Huntingtons disease. Thus, not only does the dying cell actively participate in its own demise, but it erects cytoskeletal elements that are defining features of the process. These cytoskeletal changes may reinforce the structure of the dying cell to protect the germline or the engulfing cell from degradative activities, including activated caspases.An unexpected finding of the study is that binucleate and trinucleate germ cells appear to form as byproducts of morphogenesis of the syncytium. These aberrant multinucleate germ cells are eliminated by apoptosis. This observation documents a clear role for germline apoptosis in serving a quality control mechanism. The mechanisms that surveil and recognize multinucleate germ cells and trigger CED-3 caspase activation remain to be determined.The work of Raiders and colleagues illustrates the continued power of descriptive studies in developmental biology. New microfluidic methods may enable longer term observation of the apoptotic process . These i