Endovascular therapy in the management of de novo common femoral disease remains controversial. Considerable interest has been generated in recent years due to recent technological advancement in the design of vascular stents. In particular, SUPERA  stents are designed to offer increased flexibility and less adverse interactions with the arterial wall, thus making it potentially better suited for common femoral lesions. However, despite such theoretical advantages, there is lack of data in its use in clinical practice. This study provides illustrative examples of SUPERA stents in different clinical settings and contributes to important clinical data for the overall efficacy and safety profile of endovascular interventions in common femoral artery (CFA) disease.Retrospective analysis of all endovascular CFA procedures between January 1, 2011, and December 31, 2019, was conducted. Data collected included demographics, clinical symptoms, medical comorbidities, procedural characteristics, and immediate and short-term complications. Detailed analysis was performed on the stenting cohort.During our study period, a total of 69 patients underwent endovascular interventions involving the CFA at our institution, of which 16 patients had stenting procedures for a total of 18 stent deployments. Technical success was achieved in all stenting procedures. A total of 15 SUPERA stents were placed in 13 patients. No stent fractures were observed. Overall primary patency rate of SUPERA stents at the time of 12-month follow-up was 100% in patients who had a follow-up assessment (n = 12 stents).Endovascular intervention of the CFA is an evolving topic in the interventional radiology and vascular surgery community. Recent development of newer generation of devices such as SUPERA peripheral stents offers significant potential benefits given their inherent design. Despite the theoretically promising design of the SUPERA, there is a lack of data to support its use. This study contributes important patient-level data for SUPERA stent deployments. Potential fears include stent kinking, fracture, or development of neointimal hyperplasia leading to occlusion. Furthermore, CFA stent placement risks jailing the profunda femoris artery, a major collateral vessel for the leg. Hypothetically, stenting may also preclude future endovascular or surgical access to the CFA.The role of endovascular therapy for common femoral artery (CFA) atherosclerotic disease has been much debated, with femoral endarterectomy currently considered the gold standard with primary patency rates approaching 90% at 5 years. In addition, these stents may preserve future endovascular accessibility of the CFA. Recently, data from a randomized controlled trial  comparing the safety and efficacy of stenting vs open surgery for de novo CFA stenosis found that perioperative morbidity and mortality was lower among patients who underwent endovascular therapy with stenting compared to surgery. Consequently, endovascular treatment of the CFA is gaining more consideration as an alternative treatment to surgery or in patients who are not surgical candidates. Given the availability of a large vascular database at our center which collects data on each endovascular procedure, this study examines our experience with CFA endovascular stenting with focus on SUPERA stents with regard to safety and clinical efficacy over a 9-year period.In recent years, evidence for endovascular CFA treatment has evolved, showing high rates of technical success with emerging data for primary/secondary patency and freedom from target lesion/extremity revascularization. Technological developments such as vascular mimetic stents  may be better suited to deal with the eccentric calcified plaques and crush risk attributed to the CFA.Institutional Research Ethics Board approval (UHN Research CAPCR Study ID #19-6174.0) was obtained to perform a retrospective review of all patients who had an endovascular CFA intervention between January 1, 2011, and December 31, 2019. Requirement for informed consent was waived. Eligible patients were identified using the centralized Vascular Quality Initiative database, a clinical registry which prospectively collects robust data from patients treated by vascular specialists in academic and community hospitals across North America. Patients were included if intervention was performed for CFA stenosis or occlusive disease. Exclusion criteria included interventions performed for non-atherosclerotic disease including iatrogenic dissection or bleeding.Each eligible patient was reviewed for age; gender; presenting symptoms; lesion type; pre-procedural duplex and anklebrachial indexes; and intervention characteristics including access, type of stenting, technical success, and complications. Perioperative morbidity and mortality within 30 days of the procedure included death from any cause.Common femoral artery lesions were classified into 4 categories . Type I Follow-up information included post-procedural duplex and anklebrachial indexes and symptoms. Patients were deemed lost to follow-up when no further follow-up visits or evaluations were available at our institution at time of data extraction.All patients were seen and assessed by a staff vascular surgeon and/or interventional radiologist prior to the procedure. All patients included in this study were declined for surgery and referred to endovascular treatment as it is local practice to perform endarterectomy for significant common femoral artery stenoses. Local anesthesia with conscious sedation was provided. Arterial access into the common femoral artery or brachial artery was achieved using ultrasound guidance. Following vascular sheath placement, a digital subtraction angiogram was performed to visualize the CFA and the bifurcation. Various catheters and guidewires were used to navigate to the target lesion. Pre-stenting angioplasties were performed in all patients, and stents were inserted when the residual stenosis was more than 30% of the native artery diameter following angioplasty. In such cases, patients received SUPERA stents  or self-expandable stents . Stent sizing selection was based on the vessel diameter, and was equal to or 1 mm less than the pre-stenting angioplasty balloon size. Post-stent deployment angiograms were performed to ensure satisfactory post-stenting results.Procedural success was defined as the ability to traverse the lesion and deploy a stent. The primary endpoint of primary patency at 12 months was defined as lack of restenosis or need for re-intervention of the symptomatic target CFA lesion. Follow-up information included clinical and hemodynamical assessments based on clinical symptoms, duplex evaluation, and anklebrachial index measurements as appropriate. CT angiograms were performed in cases of worsening clinical symptoms and/or findings suggestive of hemodynamic changes on duplex scans.During our study period, a total of 69 patients underwent endovascular interventions involving the common femoral artery at our institution. Of the 69 endovascular procedures performed at our institution, endovascular stent placements were performed in 16 patients with a total of 18 stent deployments. Individual cases including patient demographics, presenting symptoms, CFA vessel characteristics, stent type, pre- and post-procedural duplex, complications, and outcomes are outlined in One patient died within 30 days of the intervention to a cause deemed unrelated to the intervention, while another patient died within 12 months of the procedure due to natural causes. Major complications in 30 days following endovascular stenting were NSTEMI (n = 1), osteomyelitis (n= 1), and gastrointestinal bleeding (n = 1). Baseline duplex stenotic peak velocity ratio decreased from 3.74 ± 7.11 to 1.12 ± 0.56 (P = .11) following intervention. Overall improvements in symptoms were documented in 9 patients, while 1 patient did not notice any changes in overall clinical symptoms. Three patients experienced worsening symptoms within 12 months, with documented elevated peak systolic velocity compared to baseline duplex that required further nonCFA-related interventions. Further analysis of each of these 3 patients revealed preserved patency of the CFA stents but had interventions relating to stenoses involving non-CFA lesions. At the time of 12-month follow-up, all patients who returned for reassessment had preserved patency of the in-situ endovascular stent with a primary patency of 100% (n = 15 stents). Specifically, the overall primary patency rate of the SUPERA stent at the time of 12-month follow-up was 100% in our cohort (n = 12 stents).Peripheral artery disease is a major cause of morbidity and mortality worldwide. In recent years, advancements have been made in the therapeutic options for management of patients requiring lower extremity revascularization. Traditionally, open surgical approaches were considered the gold standard; however, the advent of new technologies and techniques has led to the rapid growth and widespread use of endovascular techniques for treatment of infrainguinal disease. The role of endovascular therapy in the management of de novo common femoral disease remains controversial. Given the significant morphological changes of shortening, twisting, and bending during the dynamic flexion at the hip, the common femoral artery has long been viewed as a hostile environment for endovascular revascularization given its inherent risk of stent fractures, occlusions, and distal embolization. Beside the primary concerns of perceived inferiority in patency rates compared to open surgical managements, stent placements may limit future surgical or endovascular treatment or access options and potentially compromise the profunda femoral artery. However, in recent years, there has been an emergence of studies examining the overall technical feasibility and clinical outcomes of endovascular interventions of the common femoral artery. This shift in momentum toward minimally invasive techniques is in part because open surgical endarterectomy is not as benign as previously believed and carries complication rates as high as 15% including a 3.4% death rate.Common femoral artery lesions are challenging and differ from other infrainguinal segments due to their unique anatomical and mechanical properties. During flexion, parts of the legs may be subjected to multiaxial deformations of up to 60% rotation and 20% contraction. In this study, a total of 117 patients with de novo CFA disease were randomized to the stenting group (n = 56) and endarterectomy group (n = 61). The primary outcome of morbidity and mortality rate within 30 days occurred in 26% of patients in the surgery group and 12.5% in the endovascular group. In particular, there was a higher percentage of local complications including delayed healing (16.4%), paresthesia (6.5%), hematoma (5%), and local infection (5%) in the surgical group. At 24 months, there was no demonstrated difference in the overall sustained clinical improvement, primary patency rate, target lesion, and extremity revascularization rates between the 2 groups.The TECCO trial published in 2017 was the first multicenter randomized controlled trial comparing surgery to stainless-steel stenting for CFA de novo atherosclerotic lesions.4922 A major propeller for this momentum change is the invention of newer generations of stents which aim to address the unique challenges of the dynamic forces and atherosclerotic issues of the common femoral artery. Osteoid metaplasia is the formation of lamellar bone-like arterial calcification, characterized by formation of extracellular osteoid matrix composed of osteoblast- and osteoclast-like cells, regulatory osseous cytokines, macrophages, and pericytes. Due to the high prevalence of osteoid metaplasia in the common femoral artery, especially compared to other vessels such as the common carotid artery, stents must be able to sustain high radial forces while maintaining a high degree of flexibility. In particular, the SUPERA peripheral stent , a helical interwoven Nitinol self-expandable device, has been of great interest recently. In a study conducted by Maleckis et al. comparing different Nitinol stents, the SUPERA device was shown to have the highest torsional stiffness (959.2 µN·m/°) and radial compressive response while maintaining relatively low axial stiffness (94 N/m) which allows for increased flexibility and potentially less adverse interactions with the arterial wall. Such stent design characteristics theoretically make these devices more attractive as the device of choice given its ability to withstand the flexion forces in this vessel segment. To our knowledge, there is one ongoing study with interim data published on the use of SUPERA stents for de novo common femoral lesions. In this study, the cumulative primary patency rate and cumulative freedom from target lesion revascularization rate was 100% at the 6-month follow-up.In our study, analysis was performed to examine outcomes of endovascular stent implantation in the common femoral artery. Traditionally, stent placements were reserved for suboptimal angioplasties or in the setting of angioplasty-related complications. In recent years, there is growing evidence to suggest that percutaneous stents may be a valid option for CFA stenoses .4-6,9-22Since the FDA approval of SUPERA stents for peripheral vascular disease in 2014, there has been an upward trend of their usage for selected patients at our institution. Of the 16 patients who had stents implanted, a total of 15 SUPERA stents were placed into the common femoral artery over the study period, all after 2017. In this cohort, technical success was achieved in all cases, and there were no stent-associated complications including fractures or kinking. Complex lesions involving the femoral bifurcation were treated with variety of stenting techniques and can be summarized as single stent, jailed SFA; single stent, jailed profunda femoral artery; single stent, isolated common femoral artery; and double kissing stents. Most cases done at our institution were single stents isolated to the common femoral arteries, while 4 patients had single stented, jailed profunda femoral artery; 2 patients with kissing stents; and 2 with single stented, jailed superficial femoral artery. Examples of each scenario are depicted in Implantation of SUPERA stents in the common femoral artery did not preclude or limit future endovascular or surgical revascularization procedures. One patient had multiple re-punctures into the SUPERA stent with placement of vascular sheaths (4-Fr and 6-Fr) and 5-Fr Exoseal vascular closure devices  during subsequent endovascular interventions with no peri-procedural or subsequent stent compromise . AdditioGiven the retrospective nature of this study, a major limitation is its inherent vulnerability to various biases and confounding variables. Additional limitations include its relatively small sample size and the single institutional nature. Despite such limitations, our study particularly highlights the utility and efficacy of SUPERA stents in the CFA and contributes to an area of research which is quite limited in the current literature. Given the significant complexity and heterogeneity in CFA lesions, more robust long-term data are needed to better support this evolving field. At such, endarterectomies remain the mainstay therapeutic option for CFA lesions, whereas endovascular techniques are typically reserved for patients who are poor surgical candidates at our institution. The VMI-CFA (NCT-02804113) and SUPERSURG (NCT-04349657) trials are both ongoing prospective randomized control trials investigating the overall safety and efficacy of endovascular treatment of common femoral artery lesions using SUPERA peripheral stenting systems. These studies will hopefully provide further clarifications on the most appropriate applications and long-term outcomes of endovascular techniques for management of atherosclerotic CFA disease in the future.Endovascular revascularization of the common femoral artery is an evolving and highly debated topic in the interventional radiology and vascular surgery community. Despite the recent excitement, there is limited published literature on the overall efficacy of CFA stenting particularly with newer generation stents. Our study provides patient-level data on the outcomes of SUPERA stenting in the common femoral artery.


Accurate predictions of ecological restoration outcomes are needed across the increasingly large landscapes requiring treatment following disturbances. However, observational studies often fail to account for nonrandom treatment application, which can result in invalid inference. Examining a spatiotemporally extensive management treatment involving post-fire seeding of declining sagebrush shrubs across semiarid areas of the western USA over two decades, we quantify drivers and consequences of selection biases in restoration using remotely sensed data. From following more than 1,500 wildfires, we find treatments were disproportionately applied in more stressful, degraded ecological conditions. Failure to incorporate unmeasured drivers of treatment allocation led to the conclusion that costly, widespread seedings were unsuccessful; however, after considering sources of bias, restoration positively affected sagebrush recovery. Treatment effects varied with climate, indicating prioritization criteria for interventions. Our findings revise the perspective that post-fire sagebrush seedings have been broadly unsuccessful and demonstrate how selection biases can pose substantive inferential hazards in observational studies of restoration efficacy and the development of restoration theory. Postfire sagebrush seeding treatments are widely applied across the western USA but evidence for the success of this restoration approach has been variable. Examining >1500 wildfires, this study shows that positive treatment effects were only detected after considering systematic differences between treated and untreated sites due to effects of selection biases in restoration. The lack of predictive power resulting from this variability has inhibited the development of theoretical frameworks in restoration ecology2. Given escalating local and global stressors and the limited resources available to do restoration, there is an urgent need to be able to predict more broadly which treatments will be successful, as well as understand where and when restoration results in the greatest ecological gains5.Restoration is an essential tool for counteracting losses in habitat, biodiversity, and other ecological attributes that are threatened by global change drivers, such as changing disturbance regimes and species invasions. However, outcomes of restoration treatments can be highly variable–even across similar sites and treatments7. Recent advances in the remote sensing of certain plant types have allowed for estimation of population recovery across broader spatial and temporal extents, presenting an opportunity to explore restoration outcomes at a larger scale12. However, the inferences from this approach have a contrasting limitation: conservation actions, including restoration treatments, are rarely randomly distributed, due to variation in ecological value, conservation need, social willingness, costs, and institutional resources across heterogenous landscapes16.Randomized, manipulative experiments, in which treatments are applied and assessed against comparable control plots, are frequently used to study restoration efficacy. These efforts are costly and typically do not match the spatiotemporal scope of actual management efforts, which can occur over 10’s to 1000’s of hectares or across decades20. A key assumption of these statistical approaches is that no confounding, unobserved factors are correlated both with the response and the treatment effect of interest20. Thus, as large-scale remotely sensed products and aggregated datasets become more readily available, selection biases have the potential to hinder inference about restoration successes or failures from these observational datasets. Recent meta-analyses have explored the efficacy of several of the world’s most common restoration efforts, including soil recovery following agricultural conversion21, active forest regeneration following deforestation22, or the control of invasive plants23. Notably, many assessments of restoration have failed to observe widespread benefits or full ecosystem recovery associated with treatments, a pattern potentially attributable to the inferential hurdles faced by observational analyses24.This nonrandom, often strategic, deployment of restoration treatments can lead to statistical bias (referred to as “selection bias”) and spurious inference about the effectiveness of management actions when classic regression approaches are used20. Researchers may include additional covariates in regression analyses to consider possible confounding factors, or similarly, “propensity score matching” accounts for observed drivers of selection bias by matching observations with similar probabilities of treatment and different treatment statuses based on a set of measured covariates. However, each of these approaches assume that all factors influencing treatment allocation have been observed25. When repeated observations from before and after the treatment are available (such as in Before-After Control-Impact designs (BACI)), “difference-in-differences” estimation can leverage repeated observations to account for time-invariant measured and unmeasured sources of bias26. Difference-in-differences (DiD) estimation identifies: (a) the persistent differences between treated and untreated groups (which may arise from nonrandom deployment of treatments), (b) the expected changes in these groups over time , and (c) the treatment effect, identified as the average observation’s departure from its expected temporal trajectory when treatment is applied (identified using an interaction term between an observation’s group and time period). Within-estimator panel regression extends the DiD regression structure to consider additional sources of bias, such as numerous post-treatment time points, multiple groups, or time-varying sources of heterogeneity included as covariates. Though these before-after control-impact designs can be employed in small-scale assessments of treatment efficacy, repeated measurements are often costly, impractical, or impossible to collect 19. Thus, only a small proportion of ecological impact studies, including assessments of restoration efficacy, typically apply these approaches28.Statistical approaches can minimize the effects of selection biases when inferring treatment effects from large, observational datasets2 of western North America29 but are now one of the continent’s most threatened vegetation types. The foundational species of these habitats, sagebrushes , have been challenged by climate change, conifer encroachment, and the invasion of an invasive annual grass, Bromus tectorum or ‘cheatgrass’, which has contributed to more frequent and larger wildfire occurrence in this region31. Altered fire regimes have locally eradicated fire-sensitive sagebrush, as most sagebrushes do not resprout, have short seed longevities (<~2 years), and disperse over short distances (<~2 m)32. This has led to propagule limitation in increasingly large burned patches and necessitated widespread investments in restoration seeding treatments  to facilitate post-fire regeneration6.We examined how statistical approaches that differentially address selection biases influence our estimation of the efficacy of one of the most widely deployed restoration treatments globally––post-fire seeding of fire-intolerant shrubs. Sagebrush-steppe ecosystems once covered 620,000 km2 of the Great Basin over the last century6. Yet, like many other widely deployed restoration treatments, evidence for the broad “success” of these treatments is variable from regionwide observational studies37 and from investigations targeting specific ecoregions or fires42. Whether these seeding treatments have been broadly successful and how effectiveness can be quantified has been a long-standing administrative question43. An analysis based on field observations of nearly 100 historic post-fire sagebrush seedings and paired unseeded sites concluded that seeding was ineffective34. A larger-scale observational field study found that probability of A. tridentata occurrence among treated areas increased with repeated seeding actions, although the study did not compare impacts in seeded and unseeded locations35. Other research using region-wide, plot-based vegetation cover data found positive correlations between a variety of restoration actions  and Artemisia spp. occurrence (but not abundance), although the authors cautioned that possible differences in the biophysical characteristics of treated and untreated sites had not been considered in the analysis44.Since 1990, the Bureau of Land Management (BLM), which manages more than half of the land area within the Great Basin, has invested more than $100 million in sagebrush seed for restoration actions, impacting more than 6000 km47. However, due to the unpredictable nature of wildfire events, interannual climatic variation, the potentially stochastic availability of economic and biological resources, and heterogeneity in regional and local interpretation of frameworks, the extent to which on-the-ground restoration implementation has historically aligned with these conceptual guidelines remains unclear.Recent restoration planning frameworks provide general recommendations for the prioritization of treatment sites based upon their resistance to cheatgrass invasion, their resilience to wildfire events, and their value as sage-grouse habitatIn this work, we quantify how observed and unobserved sources of selection bias (emerging from the nonrandom deployment of treatments) affect widespread inferences of restoration “success” by examining post-fire sagebrush seedings following more than 1500 wildfires occurring over a 20-year period between 1985 and 2005 across the western U.S. . We then examined the biophysical correlates of treatment deployment and treatment effect sizes identified by three comparative approaches, relative to a null “naïve” model in which neither observed nor unobserved sources of selection bias are considered , a long-term catalog of more than 50,000 management actions on BLM land across the western U.S.50. Remotely sensed data products and other large-scale observational datasets that monitor plant populations are increasingly accessible. Thus, explicit consideration of nonrandom application of treatments, including the ecological, social, and economic factors shaping these decisions, is essential to advancing restoration theory over broad spatiotemporal extents and prioritizing treatment sites, given limited management resources and accelerating anthropogenic threats.Our results provide evidence that widespread post-fire sagebrush seeding efforts may have been more successful in increasing plant cover than previously quantified over broad spatial extents, and that there is significant variation in treatment efficacy across climatic gradients relevant to the global change ecology of this foundational dryland shrub. Invasive annual grasses are expected to further spread across western North America, and their roles as wildfire fuels, in addition to changing climatic conditions, will continue to accelerate fire frequencies and expand the total area requiring restoration interventionIn the dataset of randomly selected burned sagebrush habitat locations, treated and untreated sites systematically differed in their biophysical properties, indicating substantial potential for selection bias in the assessment of restoration treatment effects using observational datasets, such as RCMAP and LTDL Fig. , 2. WithThe probability of areas receiving seeding also decreased in larger burned areas Fig.  and was 52, resulted in a subset of the data in which seeded and unseeded locations were similar in terms of these biophysical characteristics , with significant variation in efficacy across climatic gradients  allocation of funding, regional-level  coordination of emergency stabilization and restoration resources, and local implementation , influenced by individual practitioners’ interpretations of prioritization guidelines. Further, wildfires occur unpredictably in space and time. Thus, the implementation of restoration may be further shaped by other stochastic or opportunistic factors, including interannual variation in seed availability, contractor availability, timing of funding availability relative to sagebrush phenology, suitability of weather conditions, and social factors that vary across the range of sagebrush steppe. Thus, it is critical to document possible gaps between where restoration is recommended and where treatments are actually completed, and then identify whether the locations receiving management represent an efficient use of limited financial, sociopolitical, and biological resources.Our results also explicitly quantify the environmental correlates of restoration implementation in a widespread dryland ecosystem. Though several frameworks outline recommendations for prioritization of restoration sites in sagebrush steppe5.The shift in treatment effects across our analyses may be best explained by the biophysical and anthropogenic factors that were associated with the probability of a burned location receiving restoration, as identified in the propensity score model. Over several decades, treatments on BLM land recorded in the LTDL database have been systematically applied in areas characterized by more stressful climatic conditions and smaller pre- and post-fire surviving sagebrush populations, compared to the broader range of conditions in sagebrush steppe ecosystems Figs. , 3. Sele51 or in areas with the largest pre-fire or surviving post-fire populations (which may exhibit more stable population dynamics4), where sagebrush may be perceived more capable of recovering without interventions. Simultaneously, practitioners may be marginally less likely to apply treatments in areas with smaller pre-fire populations, if these areas are perceived to be suboptimal sagebrush habitat. Currently, similar temperature and moisture regime characteristics estimated by the US National Resource Conservation Service soil survey provide guidance for prioritization of restoration treatments46. These regimes have been demonstrated as indicators of post-fire resilience in sagebrush steppe ecosystems, with warmer, more xeric soil regimes resulting in decreased plant community resilience to disturbance and decreased resistance to post-fire cheatgrass invasion5.We hypothesize that these correlates of restoration occurrence may reflect a combination of the perceived environmental requirements for sagebrush recovery, the narrower range of conditions that may exist on BLM lands, and the cost-benefit relationships faced by practitioners. For instance, restoration practitioners may be less likely to apply treatments in the wettest or coolest sites47. Greater sage-grouse (Centrocercus urophasianus), a sagebrush-dependent species that has experienced large declines or local eradication across the western U.S. due to loss of the sagebrush-steppe habitat, may preferentially occupy areas of moderate sagebrush cover55. Extremely dense sagebrush stands can result from overgrazing and depletion of perennial grasses; when these dense stands with depauperate understories burn, lack of native resprouting perennials can result in increased invasion by exotic annual grasses56. Thus, selection toward sagebrush stands with moderate density before fire may also reflect practitioners’ prioritization of seeding investments into known wildlife habitat. Additional surveys, which specifically investigate the preferences, resources, institutional constraints, and ecological criteria that shape decisions made by restoration practitioners and organizations, are required to confirm whether these mechanisms drive biophysical differences in treated and untreated areas.Selection against sites with large pre-fire sagebrush populations may also relate to practitioner perceptions of wildlife attributes or other ecological values in these stands. Critical habitat for listed or candidate threatened and endangered species is a key selection criteria outlined by the BLM Emergency Stabilization and Rehabilitation program, which plans and implements the post-fire seedings we evaluated39. The disproportionate allocation of treatments toward sites that are more climatically stressful, more degraded by fire, or generally more ecologically “difficult” to restore  may underestimate effects of restoration if additional, unobserved characteristics differ between treated and untreated sites.Yet, analyses that considered observed environmental sources of selection bias (via propensity matching or multiple regression) also did not detect clearly positive treatment effects, even after the inclusion of a set of biophysical characteristics that have been frequently integrated into past observational studies of restoration efficacy in sagebrush steppe ecosystems57. While the spring temperature, spring precipitation, and soil variables that we included in our analyses may influence the phenology of spring snowmelt, soil moisture, and recharge, they may not correlate perfectly with fine-scale soil-water potential. Another ecologically relevant, but omitted factor was systematic differences in cheatgrass invasion and biotic interactions at treated and untreated sites; for instance, competition with invasive cheatgrass determine trajectories of sagebrush recovery and further alter soil water availability58. Similarly, pre- and post-fire livestock grazing, which varies in pressure across BLM lands, may correlate with treatment application and sagebrush recovery59. However, to our knowledge, no existing datasets accurately summarize grazing history across this broad spatiotemporal extent.Ecologically relevant but unobserved sources of bias in our analyses may include finer scale environmental factors, such as soil microsite conditions, or biotic interactions influencing treatment allocation. Mean temperatures, precipitation, soil texture and water retention (i.e. soil percent clay), and late-winter snowpack retention have all been correlated with survival and growth of sagebrush in past field studies, suggesting that soil-water availability in the early stages of sagebrush development, when seedlings are most susceptible to drought, may play a key role in restoration efficacy64, including in sagebrush systems66. Time-invariant mean climatic variables imperfectly capture the specific weather conditions that occurred in the years following restoration. Further, the extent of interannual climatic variation may differ between hotter, drier and cooler, moister sites, suggesting that the strength of weather fluctuations may also correlate with treatment assignment.DiD estimation, which considered both observed and unobserved time-invariant sources of bias associated with systematic differences between treated and untreated groups, suggested that post-fire seeding treatments generated small (5.7%) improvements in sagebrush cover in treated areas Fig. . The est52. In contrast, DiD and within-estimator panel regression methods are limited by the assumptions that in the absence of treatment, the differences between treated and untreated groups are constant, that the predictors are exogenous, and that treatment effects are static over time68. In particular, we expect treatment effects to be heterogenous across the range of sagebrush steppe and explored this variation in a subsequent form of our DiD model  vary across these biophysical characteristics of sites (though see refs. 38).Recent discussions of restoration efficacy in sagebrush steppe ecosystems have called for flexible management, such as planning that can integrate near-term weather forecasts to capitalize on years with particularly favorable conditions for establishment38. We propose that flexible management plans may use similar analysis of observational datasets to predict where treatment effects will be greatest (in contrast to where plant population recovery is most likely) to expend limited restoration resources most efficiently, given intensifying species invasions, rapidly changing climates, and accelerating fire cycles50. Over the historical range examined in this study, restoration was applied in many areas that were predicted to experience large gains in sagebrush cover; however, treatments were also likely to occur in areas where treatment effect sizes were minimal , as illustrated by the interaction terms between the DiD estimates and biophysical variables in subsequent analysis , given limitations associated with land ownership or the obvious need for practitioners to make strategic decisions about the allocation of limited management resources.This variation in treatment effect sizes along gradients of precipitation and temperature Fig.  may furt12. As we have demonstrated, if sources of bias (including those introduced by humans’ perceptions of or preferences for restoration sites) are not statistically incorporated when working with non-experimental datasets, correlations between treatment application and the characteristics of sites may cloud inference of restoration efficacy under both changing climatic conditions and anthropogenic pressures.Massive restoration efforts, such as post-fire seeding of dryland shrubs, span regions and encompass environmental variability at a scale that is difficult to capture in traditional smaller control–impact studies. Quasi-experimental approaches are not intended to be a replacement for planned, randomized field experiments. However, long-term observational datasets, including those derived from satellite imagery, are increasingly accessible to researchers and may represent powerful tools for both improving management and advancing restoration theory, while capturing broad spatiotemporal extents69, information campaigns to reduce water consumption70, and payments or land protections to prevent deforestation18); however, they have been noticeably absent from large observational studies of restoration outcomes14, suggesting a need for interdisciplinary research that examines social and ecological motivations that underlie the nonrandom application of restoration treatments.Each of the inferential approaches in this analysis has comparative limitations, and we caution against the application of any single treatment effect or singular adoption of any statistical model. However, this analysis of remotely sensed data clearly illustrates that selection bias may be a key hurdle to understanding and predicting treatment effects across a broad spatial and temporal extent and suggests that post-fire seeding may be more broadly beneficial than previously documented. Quasi-experimental approaches are regularly applied in studies examining the ecological or socioeconomic impacts of other public environmental programs  a naïve “null model” comparing the mean sagebrush cover at treated and untreated sites, in which neither observed or unobserved sources of selection bias are considered; (2) analyses that incorporated observed sources of selection bias, using one of two approaches ; and (3) using Difference-in-Differences (DiD) estimation to consider time-invariant sources of unobserved and observed bias; and (4) using within-estimator panel regression to consider unobserved time-invariant and timepoint-specific heterogeneities, along with measured time-varying covariates. We then identified apparent environmental drivers of where restoration treatments are implemented and compared the gains in estimates of sagebrush cover achieved by post-fire seeding efforts along gradients of several biophysical characteristics of sites that shape selection of post-fire treatment locations.Artemisia tridentata), with lesser occurrences of three-tip sagebrush (Artemisia tripartita), low sagebrush (Artemisia arbuscula), or other Artemisia species. Herbs, perennial bunchgrasses, or annual grasses can dominate in these ecosystems as a result of historic fire, some types of grazing, or management actions such as herbicides and seeding56. Fire severity can be highly variable, ranging from complete removal of aboveground biomass over large areas, to mosaics of unburned patches within more severely burned areas. Post-fire restoration seedings of sagebrush typically occur either in the fall or early spring following a wildfire via ground broadcast seeding or aerial broadcast from aircraft. Sagebrush seeds germinate in early spring, during the transition from low temperature to water limitation71. Many studies have sought to understand the environmental drivers of sagebrush’s post-fire establishment and population recovery, primarily focusing on climate and weather effects during this critical spring period. In this arid ecosystem, site elevation, temperature and precipitation72, spring soil water potential , and the occurrence of spring freezing events73 have all been associated with sagebrush establishment, survival, or growth.The sagebrush steppe ecosystem is defined by presence of one or multiple taxa within the big sagebrush complex (48). Using the LTDL, we extracted 10,000 randomized locations, in which at least one (and up to four) Artemisia species or subspecies was seeded  in the fall or spring following the fire. These burned, treated areas were identified by the overlap between treated and fire perimeter polygons from 1985 to 2005 . Areas that burned more than once during the focal time period were excluded from the analysis, and burned locations were randomly selected using the spsample function in the sp package in R75. We then randomly extracted a series of 10,000 burned, untreated locations using the same fire perimeter polygons. The randomly selected set of treated and untreated datapoints were located within the perimeters of 1539 fires occurring between 1986 and 2001.We compared post-fire sagebrush recovery for treated and untreated locations across the Great Basin, identified using historical fire perimeters, the National Land Cover Databases’ historical sagebrush cover product, and the Land Treatment Digital Library, a catalog of management actions on BLM lands across the western U.S.  the year preceding wildfire to establish the site’s pre-fire sagebrush population size; (2) one year post-fire to establish the “pre-seeding-treatment” population size , and (3) each of the 10 years following treatment to quantify the “success” of reseeding treatments. We selected a 10 year timepoint to ensure that the stand was beyond the point at which the remotely sensed signal for cover was likely to fluctuate strongly (previously identified as ~6 years after fire)76. The results of our analysis did not qualitatively differ if we examined longer (15-year) or shorter (8-year) timepoints , which is based on Landsat, Quickbird, and AWiFS imagery for each year from 1984-2018 across the Great Basin longer 1-year or 52. For each location, using the raster package in R78, we extracted or calculated elevation79, soil percent clay and sand (using a product aggregating the USDA-NCSS SSURGO and STATSGO datasets)80, heatload81, the U.S. Environmental Protection Agency’s Level III ecoregion, fire size, and distance to a major road from the U.S. Census Bureau’s TIGER database. We calculated November-January (winter) and February-April (spring) mean temperatures and mean total precipitation for the period for between 1984 and 2014 for each location, using the gridMet modeled meteorological dataset82. GridMet contains daily, high-spatial resolution (4-km) climate estimates for the contiguous U.S. from 1979 to present.We identified biophysical characteristics that we thought may influence treatment location or restoration success, based on covariates that appear in recent frameworks for the prioritization of sagebrush restoration sites or variables that have been commonly included as “control” variables in previously-published studies of post-fire recovery of sagebrush84. Further, because PSM relies on narrowing observations to a region of common support between groups, the treatment effect estimated from this model may focus upon a narrower range of possible conditions, relative to the “unmatched” dataset.Propensity score matching (PSM) attempts to estimate an accurate treatment effect by accounting for included measured covariates that may influence the probability of an observation receiving the treatment, as these covariates can generate bias if they also influence the response variable. Propensity score matching uses logistic regression to estimate each observation’s probability of receiving treatment based on the suite of observed covariates, and then pairs treated and untreated observations with similar treatment probabilities, including only matched sets below a given threshold for similarity, defined by the investigator. This approach relies upon the assumption that matching simulates randomization of treatment assignmentMatchIt R package’s nearest neighbor method85  equivalent to a fifth of the standard deviation of the mean propensity score86. The matching protocol resulted in 11,012 paired treated and untreated pixels in the reduced dataset, within 940 fires.We matched treated and untreated observations based on their propensity for receiving treatment, using the To infer relationships between sites’ biophysical characteristics and treatment probabilities, we also constructed a Bayesian Bernoulli glmm (with a logit link) containing treatment occurrence as the response variable and each of the covariates included in the matching procedure as independent variables, with a varying intercept for ecoregion. The full list of variables included in this model is displayed in Fig. To compare how inferences on restoration efficacy may vary depending on how selection biases are considered, we developed five Bayesian negative binomial generalized linear models and mixed models with sagebrush cover 10 years following fire as the response variable 52.The second and third models accounted for measured sources of bias, either analyzing the subset of locations remaining following the propensity score (referred to as the “matched” dataset) or analyzing the full, unmatched dataset, using a regression that contained environmental variables that represented factors that have been commonly incorporated as “control” covariates in past studies of sagebrush recoveryA key limitation of using “control” variables or propensity score matching is that it only addresses observed sources of bias in treatment location, which the researcher is both aware of and has measured covariates for. Difference-in-differences and within-estimator panel regression approaches may overcome this limitation by comparing observations from before and after a treatment was applied to remove omitted sources of time-invariant and time-varying bias, respectively. DiD uses a binary variable for whether a treatment was applied to a given individual or location to account for persistent differences between treated and untreated groups (group), and a binary variable for whether an observation describes the status of an individual or location before or after treatment (time). The effect of the treatment is identified using the parameter estimate associated with the interaction between group and time variables. Within-estimator panel regression extends this structure to incorporate multiple post-treatment observations, with time-varying indicator variables that capture unobserved heterogeneity that is distinct to each observation timepoint.67. Both models contained a varying intercept for location identity (to account for unmeasured differences between sites and autocorrelation between repeated measures) and a varying intercept for the identity of the fire impacting the site . The panel regression also contained a time-varying covariate for each observation year’s spring mean temperature and total precipitation to assess the extent to which these annual deviations from time-invariant mean climatic conditions further impacted sagebrush recovery.To assess how accounting for unobserved sources of bias may influence inference of restoration success, we developed multilevel DiD and within-estimator panel regression models, which examined sagebrush cover  and three biophysical characteristics of sites, including February-April mean temperature, November-April total precipitation, and soil percent clay, to identify how gains in sagebrush cover achieved by post-fire seeding varied under different conditions. Though other variables may influence treatment success, we selected these covariates based on their relevance in the propensity score analysis and to the climate mechanisms highlighted in past studies of sagebrush recoverybrms, rstan, and cmdstanr packages in R (Version 4.1.1), using weakly informative priors and a Markov Chain Monte Carlo sampler with four chains, each with 2000 iterations and 1000 warmup iterations90. We assessed effective sample size and model convergence, indicated by Gelman-Rubin statistics close to 1 and stable-well mixed chains89. Parameter estimates with 95% credible intervals that did not contain zero were considered to have “non-zero” effects on the response variable89. Model fit was assessed by calculating the mean absolute error and using graphical posterior predictive checks, which compare the observed data to draws from the posterior predictive distribution generated by the model (Supplementary Fig. 94.In all models, continuous variables were centered and scaled by 1 standard deviation. Models were estimated using the language Stan and the  Version .1.1, usiFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Traditionally, hand hygiene (HH) interventions do not identify the observed healthcare workers (HWCs) and therefore, reflect HH compliance only at population level. Intensive care units (ICUs) in seven European hospitals participating in the “Prevention of Hospital Infections by Intervention and Training” (PROHIBIT) study provided individual HH compliance levels. We analysed these to understand the determinants and dynamics of individual change in relation to the overall intervention effect.We included HCWs who contributed at least two observation sessions before and after intervention. Improving, non-changing, and worsening HCWs were defined with a threshold of 20% compliance change. We used multivariable linear regression and spearman’s rank correlation to estimate determinants for the individual response to the intervention and correlation to overall change. Swarm graphs visualized ICU-specific patterns.In total 280 HCWs contributed 17,748 HH opportunities during 2677 observation sessions. Overall, pooled HH compliance increased from 43.1 to 58.7%. The proportion of improving HCWs ranged from 33 to 95% among ICUs. The median HH increase per improving HCW ranged from 16 to 34 percentage points. ICU wide improvement correlated significantly with both the proportion of improving HCWs . Multilevel regression demonstrated that individual improvement was significantly associated with nurse profession, lower activity index, higher nurse-to-patient ratio, and lower baseline compliance.Both the proportion of improving HCWs and their median individual improvement differed substantially among ICUs but correlated with the ICUs’ overall HH improvement. With comparable overall means the range in individual HH varied considerably between some hospitals, implying different transmission risks. Greater insight into improvement dynamics might help to design more effective HH interventions in the future.The online version contains supplementary material available at 10.1186/s13756-022-01148-1. Healthcare-associated infections (HAIs) affect on average 6% of hospitalized patients in Europe , 2. PatiAll but a few small studies –17 on HHThe PROHIBIT intervention study tested two interventions to prevent central venous catheter bloodstream infection (CRBSI) in Intensive Care Units (ICUs) in European acute care hospitals: a central venous catheter (CVC) insertion strategy, and a HH improvement strategy. Several other work packages addressed the topic of HAI prevention more widely –22. Aftehttp://www.who.int/gpsc/5may/tools/en/). Hand hygiene promotion included educational sessions and bedside training. In addition, the ICUs displayed posters and/or other reminders in the workplace and participants came up with various additional promotion activities. Hand hygiene compliance was measured by direct observation according to the WHO observation method   was the only one in which the activity index was not negatively associated with HH compliance. This suggests that the nurse-to-patient ratio is a relevant variable to target as a risk for low HH compliance. The negative effect of a high workload on HH compliance has been reported before –28. ScheOur study reveals considerable variability in HH compliance between individual HCWs, in some ICUs more than in others. The few previous studies that have employed individualized observation found similar between-HCW variability –17, 31. Data on the level of HH compliance needed to prevent cross-transmission are limited to modelling studies. Three reports identified a “threshold” of mean HH compliance above which pathogen transmission and infections would start to decline to be 48%, 66% and 87%, respectively, always assuming that each HH action results in a total eradication of pathogen transmission–40. ModeThis study has limitations. First, not all observed HCWs could be included in the analysis due to the required number of observations. This could have led to an overrepresentation of permanent staff. Both the pooled baseline and intervention compliance were, however, comparable between the group of study HCWs and the excluded HCWs.Improving HCWs as those with ≥ 20% HH improvement precluded the inclusion of HCWs with > 80% compliance at baseline in this category. To circumvent this problem, we evaluated the possibility of using the change in non-compliance, rather than compliance to distinguish HCWs. This resulted in slightly higher correlations and similar effect estimates in the univariable regression model. We therefore decided to remain with the traditional definition of HH compliance. Third, the chosen cut-off value of 20% to distinguish HCWs into the three HH compliance change categories was somewhat arbitrary. However, a multivariable model with a cut-off value of 10% provided similar results (data not shown). Fourth, some of the observed between-HCW variability could be explained by chance due to a limited number of HH observation sessions per HCW and a limited number of opportunities per session. However, our study is the largest of its kind to date and demonstrates the feasibility and benefit of this approach. It might take an advanced automatic HH monitoring system to collect a larger number of opportunities per identified HCW. Finally, like other HH observation studies, observer and observation biases cannot be entirely excluded, especially a desirability bias by the observers also being involved in the promotion of the intervention, and observation bias, also known as Hawthorne effect [Second, the definition of e effect –48. HoweBoth the proportion of improving HCWs and the median of individual HH improvement differed substantially among hospitals. Both measures were associated with the overall success of the intervention. However, the patterns and dynamics of individual HH compliance varied considerably among ICUs, and could potentially result in different risk of pathogen transmission. Being a nurse, a low individual baseline HH compliance, a lower ICU-level activity index, and a favourable nurse-to-patient ratio were associated with a higher individual HH compliance improvement. Data on individual HH compliance could advance our understanding of improvement dynamics and inform better intervention strategies. Collecting individual level HH data should be seriously considered in future HH research, especially in the design of interventions.Additional file 1: Table S1. Association between hand hygiene and activity index during baseline and intervention; Table S2. Overall  hand hygiene compliance per hospital, during baseline and the intervention period; Figure S1. Boxplot  of individual HH compliance both during baseline and intervention period; Figure S2. Boxplot  of hand hygiene increase (in percentage points) in the group of improving HCWs; Figure S3. Variability within improving HCWs, measured as the range between the observation session with the lowest compliance and the session with the highest compliance for each HCW.


Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements.The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications.ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses.A model-based platform consisting of an EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus.Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications. Characterization of the agreement between MC models of EWDRS and empirical measurements establishes the basis for more complex or nuanced future studies to guide the development of EWDRS, and a representative example of MC simulations of an EWDRS measurement scenario involving detection of a pelvic nerve plexus is included in this work.In this paper, we report a model-based characterization platform for EWDRS that includes demonstration of measurements from an 22.1The EWDRS system  was crea2.2All data preprocessing is implemented in MATLAB (MathWorks) and includes spectral referencing. InGaAs array fixed pattern noise reduction and the calculation of a spectral matching factor2.3,Dissection of the femoral NVB in fresh chicken thighs is a common microsurgical model due to the similar size and structure as the human digital artery and nerve,2.4,The processed spectra were classified with a Bayesian machine learning algorithm, sparse multinomial logistic regression (SMLR).2.5Two-layer tissue simulating optical phantoms, shown in Optical measurements were performed on one- and two-layer phantoms with different thicknesses of the NM layer. At each measurement location, five repeated measurements were collected. The acquisition time of the probe was 50 ms in the VIS/NIR range and 800 ms in the SWIR range. During the measurement, the probe was held by hand perpendicular to the surface of each two-layer phantom with light pressure. A total of five phantoms (two one-layer phantom and three two-layer phantoms) were analyzed for 25 measured spectra.2.6The optical properties of all dissected tissue types, as well as each tissue-mimicking optical phantom layer were determined using measurements of reflectance and transmittance collected via an integrating sphere . Inverse adding-doubling (IAD)2.7MC models used here were created using the open-source Monte Carlo eXtreme (MCX) software package.Simulations were performed from 500 to 1500 nm. The light source and detectors were set up based on the fiber optic probe , which lComparison of simulated spectra with measurements required each spectrum be normalized to account for scalar differences between simulation output units and those of measured spectra. Both simulated and measured spectra were normalized to area under the curve, and the difference between the two is then plotted and compared against the 95% confidence interval  was performed using SMLR, using spectra collected across the full EWDRS range as well as with spectra collected with the VIS/NIR spectral channel alone . The ove3.2,,,Supplemental Material). The SWIR peak ratio of NM phantom was Tissue-mimicking optical phantoms have been widely used in VIS/NIR spectroscopy for evaluation of specific parameters influence on measurements, such as feature depth, layer thickness, and precise compositional changes within tissues since these factors can be difficult to precisely control in tissue specimens. Here, tissue-mimicking optical phantoms were developed with chromophores in both the VIS/NIR and SWIR spectral ranges to evaluate agreement between measurements and MC simulations across the EWDRS spectral range. Phantoms were designed to produce spectral line shapes similar to those observed from the tissues of interest in the nerve dissection model. Both the MM and NM layers from the optical phantom were compared with spectra collected during dissection . PreviouThe simulated heme spectral feature in MM layer phantom was achieved with the red and green food dye, whose absorption maxima at 630 nm was similar with the certain heme proteins including myoglobin and met-hemoglobin.3.3ex vivo tissues.MC simulations offer the capability of closely characterizing the influence of sample composition, architecture, and illumination/collection geometry on spectroscopic measurements. Evaluating the relative agreement between computational models of simplified samples such as optical phantoms against empirical measurements is a critically important step prior to moving forward with more in-depth MC model-based studies of EWDRS. Here, a comparison of empirical EWDRS measurements and identically configured MC simulations is reported in single-layer homogeneous phantoms, two-layer phantoms, and finally dissected 3.3.1A comparison of homogeneous, one-layer, NM phantom and MM phantom measurements 1and MC simulated measurements from tissue models is shown in The MC simulation of the EWDRS spectra is based on the geometric configuration of the fiber-optic probe as well as the optical properties of the phantom. Comparison between the measured and simulated diffuse reflectance across the entire wavelength range was evaluated. The difference between simulation and measurement spectra  was with3.3.2Further comparison of the measured spectra with simulated spectra was performed using an incrementally more complex two-layer phantom, which simulates the presence of nerve tissue with various thicknesses over background muscle tissue. Representative simulated and measured spectra from 1- to 3 mm-thick superficial NM layer are shown in Alternatively, the comparison of spectra in the SWIR range, both measured and modeled spectra, indicated a more prominent local minima in the lipid feature around 1210 nm, which indicates a reduced contribution from the underlying tissue layer. Agreement in the trends in the VIS/NIR and SWIR peak ratios used for EWDRS tissue characterization with changes in sample structural composition . The VIS,In this paper, we developed a two-layer EWDRS phantoms with various thickness of superficial layer, which successfully mimicked a lipid-rich NM layer on top of a blood-rich MM layer with optical properties close to that of biological tissues across the entire EWDRS range. To our knowledge, NM optical phantoms including chromophores across the EWDRS (VIS/NIR/SWIR) spectral range have yet to be reported. Measurements and simulations from the superficial NM layer diverged at thickness’ under 1 mm, however, trends in spectral ratios persisted. Further studies using NVB phantoms should take care to measure and characterize optical properties carefully, as well as to improve phantom fabrication techniques to generate precise multilayer or 3D printed materials with thin geometries. Additional issues that may contribute to mismatch between simulation and measurement include errors between 900 and 1100 nm, where reduced spectrometer throughput and sensitivity in both the VIS/NIR and SWIR channels is reduced. Moreover, discussion of methods for merging spectra from the two spectrometer channels is limited,Overall, comparison between measured and simulated spectra across the entire wavelength range indicates an excellent MC model agreed with both homogeneous and two-layer phantom measurements, which confirms the ability of the MC models of fiber-optic probe-based EWDRS to agree with measured diffuse reflectance spectra given appropriate construction of MC tissue model and fiber-probe configuration. These results provide the necessary support for future quantitative MC-based studies, which use simulations to investigate more complex scenarios such as a scale of changes in spectral features corresponding to depth-dependent changes in observed EWDRS spectra, changes in EWDRS spectra with varying tissue microstructure and composition, as well as more detailed analysis of fiber-probe design/configuration.3.3.3In addition to performing a comparison of simulations and measurements in optical phantoms, a comparison of empirical measurements obtained from tissues observed in the microsurgical dissection model against MC simulations of homogeneous tissues with identical optical properties was performed, with the purpose of further evaluating the agreement between simulation and measurement. Again, simulated spectra agreed with measured data. Comparison of muscle and NVB simulated versus measured spectra are shown in 3.4ex vivo and in vivo animal models provide critical feasibility data to support the development of optical technologies; however, uncertainty over the precise morphological and compositional makeup of the sample can limit fundamental insight. Alternatively, optical phantom models are valuable in establishing objective fundamental characterization but can be difficult to fabricate with morphological and compositional variations that mimic the full complexity of biological tissues. As a result, MC simulations offer a critically unique path toward further analyses in some cases.Finally, preliminary MC simulations of measurements of a nerve plexus were performed to provide a representative example of possible model-based MC simulations to study potential measurement scenarios in EWDRS. Empirical measurements from ,,One example of MC simulations that offer insight into translational scenarios is an evaluation of the depth dependency of changes in spectral signatures associated with a neurovascular plexus beneath adjacent tissues. A pelvic nerve plexus structure was created with dimensions and geometry informed from the microstructural anatomy typically encountered in laparoscopic surgeries of the prostate or uterus4ex vivo chicken femoral nerve microsurgical dissection model and unique two-layer nonbiological phantom phantoms were used to demonstrate spectral agreement between MC simulations and empirical measures across the entire spectral range and in important spectral VIS/NIR and SWIR ratios previously used for tissue characterization. Optical phantoms included major biological chromophore features across EWDRS spectral windows, including pigments VIS/NIR blood mimicking pigments, scattering, and SWIR absorbances from lipids, collagen, and water. Empirical measurements from the chicken thigh femoral nerve microsurgical dissection model produced spectra representative that re-affirmed prior reports of tissue classification and could serve as a simple preclinical model for future studies. Overall, these results provide a basis for further utilization of model systems for the development of EWDRS applications, such as the preliminary investigation of the depth-dependence of signal changes in neurovascular plexus identification shown here, along with the theoretical comparison of different EWDRS fiber-probe designs and more.Evaluation of the agreement between EWDRS MC simulations and measurements across model systems is a critical step toward their expanded utilization for application development. This study sought to complement prior reports investigate the agreement between MC models of fiber-optic EWDRS in both optical phantoms and dissected tissues.Click here for additional data file.


Human beings and their indigenous microbial communities have coexisted for centuries, which led to the development of co-evolutionary mechanisms of communication and cooperation. Such communication machineries are governed by sophisticated multi-step feedback loops, which typically begin with the recognition of microbes by pattern recognition receptors (PRRs), followed by a host transcriptional response leading to the release of effector molecules. Our gastrointestinal tract being the main platform for this interaction, a variety of host intestinal cells tightly regulate these loops to establish tolerance towards the microbial communities of the gut and maintain homeostasis. The transcription factor, nuclear factor kappa B (NF-κB) is an integral component of such a communication apparatus, which plays a critical role in determining the state of homeostasis or inflammation associated with dysbiosis in the host. Here we outline the crucial role of NF-κB in host response to microbial cues in the context of ageing and associated diseases. The recent realization that microbiota, which colonizes multiple niches of our body is an essential and integral part of us has revolutionized modern biology. The past decades have dramatically enriched our understanding of the holobiont concept, a mutual co-evolutionary relationship between the eukaryotic, prokaryotic and viral counterparts of an organism. The fundamentals of this concept of symbiotic co-existence rely on mutual requirements of the host and its microbiome and is regulated tightly by complex interactions. Of the distinct niches colonized by our microbiota within or on us, the gastro-intestinal tract harbours the most complex microbiota, consisting of bacteria, fungi, viruses, archaea and protozoa, and acts as a hotspot for host-microbe interactions . The hosOur gut microbiota is composed of a complex array of microorganisms, especially the commensals and mutualists, which exist in a symbiotic relationship with the host and have co-evolved to serve multiple roles and responsibilities . They plThe composition of gut microbiota varies amongst individuals or within the same individual across age, playing distinct functional roles. It has the capacity to integrate external and intrinsic signals such as diet, geography, season, health status and age of the host and respond accordingly by changing its composition and community structure . In addiDrosophila melanogaster and African Turquoise Killifish, ageing was found to be associated with an increased abundance of Proteobacteria and reduction in Firmicutes, leading to an increase in the levels of inflammatory markers and loss of intestinal integrity , reversed the effect, implicating bacterial folate synthesis as a regulator of longevity  homoserine lactone  has provided a clearer picture about the process and gave a better understanding of the fundamentals of innate immunity . TLRs arOnce TLRs recognize the respective PAMPs, they recruit a set of TIR domain-containing adaptor proteins, such as myeloid differentiation primary response-88 (MyD88), TIRAP, TRIF, or TRAM and initiate downstream signaling pathways that finally lead to inflammatory responses through recruitment of immune cells and release of cytokines . A key pAnother major arm of PRRs that play an important role in host response to microbiota is the oligomerization domain containing NOD-like receptors (NLRs). There are 22 different NLRs in humans and amongst them NOD1 (NLRC1) and NOD2 (NLRC2), the founding members of the NLRs, sense bacterial peptidoglycans and play a pivotal role in tissue homeostasis and host defense against bacterial pathogens . NotablyNF-κB is activated by a wide range of stimuli and is a key regulator of cellular responses in both physiological and pathological conditions. Almost all the receptors of innate and adaptive immune systems activate NF-κB transcription factors to mediate host responses . On one The canonical pathway of NF-κB signaling is activated by tumour necrosis factor, IL-1, and TLR ligands such as LPS. It plays an important role in the expression of genes involved in inflammation, cell proliferation, invasiveness, survival, angiogenesis, and metastasis . WhereasUnder normal physiological conditions, NF-κB plays a dual role. It directs the immune cells to elicit a response against any foreign element. At the same time, it protects the non-immune cells like the epithelial and stromal cells from the innate immune responses that are activated. Thereby, it ensures that tissue integrity and homeostasis are maintained and restores the ability of the immune system to respond to potential stressors . For insThe intestinal epithelium being directly exposed to the gut microbiota acts as a protective barrier by producing mucus and antimicrobial peptides and plays a vital role in maintaining immune homeostasis . They exAnother organ in direct contact with a complex microbiota is our skin, where homeostasis is maintained by the cross-talk between epidermal keratinocytes and dermal immune cells. NF-κB inhibition in mouse epidermis disturbs skin homeostasis and triggers TNF-dependent skin inflammation, epidermal hyperplasia, and the development of squamous cell carcinoma. Moreover, NF-κB signaling blockade perturbs the communication between the epidermis and the dermis and initiates an inflammatory response that resembles a wound-healing reaction .It is therefore evident that NF-κB is highly beneficial for the survival of cells and also for conferring protection against infection and trauma. However, prolonged or uncontrolled activation of NF-κB signaling could be detrimental and requires timely termination. Even though NF-κB activity is tightly regulated by feedback mechanisms, constitutively elevated levels of NF-κB are associated with several chronic inflammatory diseases and many types of cancers. Hence for persistent homeostasis, it is crucial to maintain this delicate balance in order to remain tolerant towards our endogenous symbiotic microbiota, while retaining the capacity to elicit appropriate immune responses towards pathogens . TogetheBacteroides fragilis have been shown to accumulate during ageing in humans, which can stimulate IL-8 secretion via NF-κB activation  and Parkinson’s disease (PD). AD involves increased intracranial activity of inflammatory cytokines like IL-1β, IL-6, and TNF-α due to amyloid-β (Aβ) stimulation of NF-κB activity in the microglia . Interes process .PD is another neurodegenerative condition with increased inflammation and cytokine signaling in both the brain and CSF. Inflammation derived oxidative stress and cytokine toxicity leads to the misfolding of the protein, α-synuclein (syn) and its aggregation in the brain of PD patients . The rolAkkermansia muciniphila exerted antidiabetic effects , involves autoimmune destruction of β-cells, which is mediated by cytokines like IL-1. Upon increased exposure to IL-1, NF-κB is activated, which translocates into the nucleus to further activate several genes responsible for β-cell destruction and death by apoptosis. Gut dysbiosis related NF-κB activation is also one of the key features associated with T1DM, leading to deregulated immune responses that further cause loss of intestinal integrity and increased microbial passage into circulation . This ac effects . The inv effects . NF-κB i effects . The fun effects . Moreove effects . Further effects .Hyperactivity of NF-κB signaling is one of the main etiologies of several cardiovascular disorders. Increased NF-κB activity has been observed in unstable atherosclerotic plaques of the coronary artery . In a baOsteoporosis, one of the major age-related problems is associated with decreased bone density, increased fragility of bones, and accelerated osteoclast formation due to the hyper-activity of NF-κB driven inflammatory cytokines such as IL-6, TNF-α, and IL-1 . It has Helicobacter pylori is the potential cause of gastric cancer, established the initial link between bacteria and oncogenesis. Subsequent reports by several groups, including ours, demonstrated that NF-κB signaling is one of the main pathways that potentiate the bacteria mediated gastric oncogenesis  pks+, Peptostreptococcus and enterotoxigenic (LT+) B. fragilis (ETBF)  . An incrs (ETBF) . For insal cells . The anaintegrin . Fusobaccontrols . AdditioIt is well established that dysbiosis of gut microbiota is associated with ageing and age-related pathologies. Hence, a better understanding of the age-related dynamic changes in gut microbiota and its effect on various cellular signaling pathways is essential for the development of therapeutic strategies that could delay the process of ageing or promote healthy ageing. Considering the difficulties in pursuing mechanistic studies in human subjects, studies involving germ-free, transgenic mice mimicking human ageing and associated diseases, where the gut microbiome could be manipulated are highly encouraged. Such studies will significantly enrich our current understanding on microbial involvement in the host ageing process and help decode the underlying molecular mechanisms. Much work has been done over the recent years to understand and characterize the interactions between the innate immune system and microbial pathogens and the crosstalk between gut microbiota and NF-κB signaling pathway has been implicated as one of the major determining factors of ageing and age-related diseases. Targeting the NF-κB signaling by exploiting the flexibility of the gut microbiome could therefore have a great potential in developing safe and effective clinical options for the treatment of several age-related pathologies. However, further studies are required to assess the risk-benefit ratio of NF-κB signaling manipulation.Selective inhibition of NF-κB signaling could be utilized to develop potential anti-ageing or anti-cancer agents. Proteasomal inhibitors are one such class of compounds that prevent the degradation of IκB and thereby block NF-κB pathway, as exemplified by the drug bortezomib, which is being effectively used in the treatment of multiple myeloma . SeveralBacteroides thetaiotaomicron, known to prevent the activation of NF-κB by promoting the nuclear export of NF-κB subunit RelA through a PPARγ dependent pathway (There is much scope to develop potential futuristic NF-κB signaling “modulators” by manipulating the gut microbiota using specific microbes of potential biological importance, which could reshape the microbiome-NF-κB axis and emerge as an effective therapeutic strategy to delay the ageing process or protect against age-related pathologies. For example,  pathway  can be a


The presence of tumor cell clusters in pleural effusion may be a signal of cancer metastasis. The instance segmentation of single cell from cell clusters plays a pivotal role in cluster cell analysis. However, current cell segmentation methods perform poorly for cluster cells due to the overlapping/touching characters of clusters, multiple instance properties of cells, and the poor generalization ability of the models.APmask is > 90%, a more than 10% increase compared with state-of-the-art semantic segmentation algorithms. From the qualitative results, we can observe that our method rarely has segmentation errors.In this article, we propose a contour constraint instance segmentation framework (CC framework) for cluster cells based on a cluster cell combination enhancement module. The framework can accurately locate each instance from cluster cells and realize high-precision contour segmentation under a few samples. Specifically, we propose the contour attention constraint module to alleviate over- and under-segmentation among individual cell-instance boundaries. In addition, to evaluate the framework, we construct a pleural effusion cluster cell dataset including 197 high-quality samples. The quantitative results show that the numeric result of  The comprehensive segmentation of cells are core analysis steps in many histopathology image analysis tasks  without prior knowledge based on cluster cell combination enhancement (CCCE). First, to alleviate the demand for a large amount of data in the network framework, we constructed a data enhancement module CCCE, which can enrich cluster cell information through the small number of discrete cells. Secondly, to avoid false detection and missed detection in intertwined complex cell regions, inspired by keypoints detection , which are used to synthesize aggregated pleural effusion cells and labels; Synthetic pleural effusion cluster cells, which consist of 200 samples as the training set in our framework; Real pleural effusion cluster cells, which consist of 129 labeled images as the testing set in our framework. This dataset provides great challenges in medical image segmentation, such as overlapping, touching, low contrast and complex background.We propose a cluster cell instance segmentation framework that only requires unlabeled synthetic dataset as the training set and achieves an high-quality cell boundaries instance segmentation close to fully supervised methods on real pleural effusion tumor cluster cell dataset. The framework includes three modules: CCCE, KD and contour attention constraint segmentation (CACS). The CCCE module can simulate the clusters cells image by using only a few discrete cells images, which greatly reduces the dependence of the network on the dataset. The KD and CACS module can be applied to various medical segmentation images, especially the cluster cell images of complex scenes.APmask (averaged over Mask IoU thresholds). In metric We compare with five state-of-the-art (SOTA) algorithms on two datasets. Our algorithm achieves a 13% increase compared with other segmentation algorithms and attains >97% on metric 1.1.1Data augmentation enhances the size and quality of training datasets that are widely used in deep learning networks. For example, some scholars have proposed regularization methods .Conflict of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.The data underlying this article will be shared on reasonable request to the corresponding author.