Macrophages are a major component of the tumor microenvironment and orchestrate various aspects of immunity. Within tumors, macrophages can reversibly alter their endotype in response to environmental cues, including hypoxia and stimuli derived from other immune cells, as well as the extracellular matrix. Depending on their activation status, macrophages can exert dual influences on tumorigenesis by either antagonizing the cytotoxic activity immune cells or by enhancing antitumor responses. In most solid cancers, increased infiltration with tumor-associated macrophages (TAMs) has long been associated with poor patient prognosis, highlighting their value as potential diagnostic and prognostic biomarkers in cancer. A number of macrophage-centered approaches to anticancer therapy have been investigated, and include strategies to block their tumor-promoting activities or exploit their antitumor effector functions. Integrating therapeutic strategies to target TAMs to complement conventional therapies has yielded promising results in preclinical trials and warrants further investigation to determine its translational benefit in human cancer patients. In this review, we discuss the molecular mechanisms underlying the pro-tumorigenic programming of macrophages and provide a comprehensive update of macrophage-targeted therapies for the treatment of solid cancers. Tumors are complex tissues where cancer cells maintain intricate interactions with their surrounding stroma. Important components of the tumor stroma include macrophages, which are intimately involved in tumor rejection, promotion, and metastasis. In some cases, macrophages can comprise up to 50% of the tumor mass, and their abundance is associated with a poor clinical outcome in most cancers. Tumor-associated macrophages (TAMs) promote tumor growth by facilitating angiogenesis, immunosuppression, and inflammation, and can also influence tumor relapse after conventional anticancer therapies. Strategies aimed at targeting TAMs have shown great promise in mouse models, and a number of these agents are currently under clinical investigation. Here, we review current understanding of how TAMs regulate tumor progression and provide a comprehensive update of therapies targeting macrophages for the treatment of solid cancers. We also evaluate the contribution of TAMs in moderating the effectiveness of different anticancer treatment modalities and reflect on the challenges that need to be addressed to successfully incorporate the targeting of TAMs into current anticancer regimens.Macrophages are required to maintain homeostasis in the organs they occupy. Given the specific needs of each tissue microenvironment, there are many different types of macrophages with morphologically and functionally distinct characteristics. Prototypical examples include liver Kupffer cells, brain microglia, and lung alveolar macrophages, which together reflect the versatility of the mononuclear phagocytic system.via self-renewal  receptor TIE2 . The differentiation of inflammatory Ly6Cignaling . Geneticr growth . A smalltor TIE2 . These Ttor TIE2 . MDSCs mendotype . Since try cells .Cx3cr1 in the host microenvironment facilitated the recruitment of Ly6CHigh “inflammatory monocytes” into tumor tissues, which were responsible for increased tumor incidence and shorter survival times in glioma-bearing mice. By contrast, selective ablation of Cx3cr1 in microglia had no impact on glioma growth  or “alternatively activated M2” (AAM) endotypes. Much our understanding of macrophage polarization has relied on  signals . For M1  signals . Changes signals , 13.The current classification of CAM or M1 macrophages is in part based on their response to stimulation with bacterial LPS, TNFα, and/or IFNγ Table , 40. OncAlternatively activated M2 macrophages are broadly characterized by their anti-inflammatory and wound-healing endotype . While tin vitro  in mice susceptible to mammary carcinoma delayed metastasis and decreased tumor growth, while the transgenic expression of the corresponding CSF1 protein accelerated cancer progression and promoted pulmonary metastasis  and irritants (cigarette smoke) creates a mutagenic environment in the sub-epithelial stroma. These transformed neoplastic cells consequently produce inflammatory mediators including TNFα   , 73. Thind ll13) . Likewisntiation .+ T-cell infiltration -L1 on the surface of monocytes and TAMs . Althougltration , 77. Theltration . More reltration . Anotherltration . Macrophltration , 81.α is constitutively expressed in macrophages and acts as a major regulator of hypoxic stress by inducing a switch from aerobic to anaerobic metabolism , which are recruited by CCL2, have been identified . Activat by MAMs . CollectThe extent of macrophage infiltration serves as an important diagnostic and prognostic biomarker in many human cancers. The identification and quantification of TAMs can be performed through various methods, ranging from morphological discrimination to gene expression analysis and cell-surface marker profiling. Human TAMs are typically identified by CD68 expression; however, CD163, CD206, and CD204 are also commonly used to distinguish those of the AAM endotype , 110. By+ macrophages was also negatively correlated with survival and secondary treatment outcome  may be used to impair macrophage recruitment , 160. In+ T-cell expansion. Administration of emactuzumab to patients similarly led to a striking reduction of macrophages in tumor tissue, which translated to a marked clinical benefit for patients with diffuse-type giant cell tumors  protein, for example, is a histone 3 Lys27 demethylase that has been implicated in AAM activation . Loss ofnfection . The rolnfection . IncreasSTAT3 and STAT6 play an important role in tumor-promoting macrophage polarization. A small-molecule inhibitor of STAT3 significantly reduced AAM polarization in patients with malignant glioma , while u+ T-cell-mediated antitumor immune responses  macrophages compared with non-responder patients. These results were consistent with a decrease in Treg cell numbers following immune checkpoint inhibition (Inhibition of CTLA4, an inhibitory receptor expressed on the surface of T-cells, has emerged as an effective therapy for metastatic melanoma. Analysis of the mechanism by which anti-CTLA4 therapy exerts its antitumor effects has revealed an important role of macrophages in driving these responses . In melahibition .in vivo experiments and have contributed significantly to our understanding of human immunology. Comparative analysis of the mouse and human genome has revealed a striking level of conservation. Despite this, there are major discrepancies between our innate and adaptive immune systems in terms of development, activation and function. Such differences are unsurprising since the divergence of mice and humans occurred more than 60 million years ago, resulting in the evolution of both species under different ecological niches and environmental pressures. Thus, while there are many parallels between mouse and human biology, it is also important to recognize the fundamental differences, especially when translating preclinical findings from bench to bedside. For example, expression of the cell-surface marker F4/80 is exclusively found in mouse macrophages and is undetectable on human cells (Mice provide a mainstay of an cells . An altean cells .in vitro. For example, polarization of mouse macrophages toward an immunosuppressive AAM endotype is usually modeled by stimulation with IL4 and/or IL13. This results in the upregulation of M2-associated markers including FIZZ1, ARG1, and YM1; however, this response is not observed in human AAMs (Differences also exist when comparing the transcriptional profile of mouse and human macrophages following exposure to stimulating cytokines man AAMs . Likewisman AAMs . Thus, m+ T-cell responses and stimulate immunological memory. Likewise, TAM-targeting strategies may also complement the efficacy of immune checkpoint inhibitors by removing additional inhibitory factors that may further restrict T-cell function. In preclinical models of PDAC, anti-PD1 and anti-CTLA4 antagonists showed limited efficacy as monotherapies to restrain tumor growth, but the use of these agents in combination with CSF1R blockade resulted in tumor regression (Whether macrophage-targeting therapies will be most efficacious as monotherapies or as a combinatorial approach with chemotherapy and immunotherapy is still unclear. Considering that antigens are released by dying tumor cells following chemotherapy , the crogression .Since macrophage-targeted approaches elicit distinct effects based on tumor type, another aspect that should be considered is the identification of cancers and stratification of patient cohorts that are most likely to respond to treatment. In one study, high TAM density in metastatic lymph nodes predicted better disease-free survival in stage III colorectal cancer patients undergoing 5-fluorouracil adjuvant therapy . On the The development of localized treatment options for the primary tumor represents a significant hurdle, since the systemic depletion of macrophages in an immunocompromised patient undergoing chemotherapy may increase their vulnerability to infections. Furthermore, long-term depletion may also perturb the behavior of other immune cells that rely on macrophages to guide their functions. For instance, systemic inflammation has been observed as a result of excessive neutrophil infiltration in the absence of macrophages . LikewisMacrophage-targeting strategies currently encompass a range of antibodies and small-molecule inhibitors; however, these two classes of drugs exhibit major differences in their pharmacological properties. Owing to their larger molecule weight, monoclonal antibodies often have a reduced efficiency for tissue penetration, but extended tumor retention and clearance from the blood compared with small-molecule inhibitors . HoweverMacrophages are a major component of solid cancers and can promote tumorigenesis by facilitating angiogenesis, immunosuppression, invasion, and metastasis. Given the association between high macrophage infiltration and poor survival in most cancers, these cells represent promising targets for anticancer therapy. Strategies aimed at targeting TAMs have shown success in clinical trials and include macrophage depletion, modifying macrophage recruitment, and the reprogramming of macrophages away from an AAM endotype. These macrophage-directed therapies have also shown complementary effects when combined with chemo- and immunotherapies, suggesting the additive benefit of targeting TAMs alongside other cell populations to augment antitumor immunity. For this reason, a greater understanding of the complex interactions between TAMs and their surrounding microenvironment is vital to identify additional pathways that can be targeted in parallel.One major hurdle of targeting TAMs is to minimize the occurrence of negative side effects in the patient. Given their multifaceted roles of maintaining homeostasis, the systemic depletion of macrophages may lead to increased infections or impaired ability of tissue-resident cells to carry out their normal function. Thus, the identification of TAM-specific markers or molecules that are predominantly produced by AAMs and/or MAMs will enable the development of more sophisticated therapies that can be targeted specifically to tumors without affecting the function of other tissue-resident immune cells. In the same way, strategies aimed at reprogramming macrophages should also aim to conserve the ability of these cells to carry out phagocytosis and wound healing in non-tumor tissues.AP and ME wrote the manuscript and designed the figures.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.


A 52-year-old male underwent cardiac catheterization for abnormal stress test. Trans-radial coronary angiography revealed a severe proximal left anterior descending artery (LAD) lesion. LAD angioplasty was performed with two drug-eluting stents. This resulted in dissection of the proximal LAD, the circumflex artery and the left main coronary artery (LMCA) extending back into the coronary sinus. A diagnosis of type 3 coronary dissection was made. The circumflex artery and the left coronary artery were stented, and then the LMCA was stented. Repeat intravascular ultrasound showed resolution of the dissection and TIMI-3 flow was achieved in all vessels. He underwent follow-up angiography in 1 month, which revealed patent stents with resolution of the aorto-coronary dissection. We report a rare case of iatrogenic aorto-coronary dissection that was successfully treated with unprotected left main percutaneous coronary intervention strategy alone and review the pertinent literature. Iatrogenic retrograde aorto-coronary dissection is a rare and potentially disastrous complication of percutaneous coronary intervention (PCI). The incidence of left main coronary artery (LMCA) dissection is reported at less than 0.1% in the published literature , 3. LMCAA 52-year-old male with past medical history of hyperlipidemia and a remote 6-year smoking history presented with 2 weeks of chest pain and dyspnea on exertion. His family history was significant for myocardial infarction in his father at the age of 54 years. He was referred to the cardiac catheterization lab on an urgent basis from his cardiologist’s office, following a markedly abnormal stress MIBI test, which showed extensive anterior wall ischemia. Trans-radial coronary angiography revealed a subtotal occlusion proximal left anterior descending artery (LAD) lesion . The resIatrogenic coronary artery dissection results from various mechanisms including mechanical injury to the arterial wall due to extensive catheter manipulation, passage or deployment of an interventional device or inadvertent contrast administration when the tip of the catheter is scraping against the wall of the coronary artery during the injection. Many risk factors have also been identified including unusual/small coronary anatomy or location , 4, operAorto-coronary dissection should be suspected in any patient undergoing a percutaneous coronary artery intervention who develops otherwise unexplained hypotension and hemodynamic compromise. Once dissection occurs, the clinical picture differs depending on the remaining antegrade coronary flow, and can range from an asymptomatic patient with preserved TIMI-3 flow, to a patient in refractory cardiogenic shock whose LMCA is completely compromised. While iatrogenic aorto-coronary artery dissection is obvious on coronary angiography, it may under estimate the extent of aortic involvement. Physical exam findings such as a murmur of aortic regurgitation and diminished peripheral pulses are less prevalent. Even in cases of initially preserved TIMI-3 flow with stable hemodynamics, deterioration may acutely occur because of compromise to flow from a progressive dissection or a superimposed thrombus formation . Hence, Coronary dissections are classified using the National Heart, Lung, and Blood Institute (NHLBI) diagnostic criteria-NHLBI. The NHLBI has six types of dissections classified based on the extent and location of radiolucent areas within the coronary lumen during contrast injection and persistence of contrast. The simplified classification scheme defines three types of coronary dissections involving the left main artery. Type 1 is a localized dissection without extension into the LAD or LCx. Extension of LMCA dissection into LAD or LCx is defined as type 2, and if extension involves the aortic root then it is type 3 [Importance of prompt and timely recognition of this complication to prevent both retrograde and antegrade extension cannot be overemphasized. Conservative therapy, bailout stent implantation and emergent CABG have all been described extensively in literature as potential strategies for the management of iatrogenic aorto-coronary dissection. Given the unpredictable nature of the dissection and the potential for catastrophic sequelae, conservative therapy is rarely considered as a therapeutic option for aorto-coronary dissection. In the setting of aorto-coronary dissection and hemodynamic collapse, IABP alone will not provide hemodynamic stability , 8, and Dunning et al  have sugThe stent must be delivered to the coronary ostium, protruding 1 - 2 mm into the aortic lumen, with the intention of sealing the aortic dissection. The flaring of the proximal end of the stent should be done to avoid in-stent restenosis, and to facilitate later catheter engagements. Intracoronary stenting of the LAD and LCx can be accomplished using various bifurcation stenting techniques. Literature review cites that mostly DES has been used although bare metal stents have also been used in iatrogenic aorto-coronary dissection treated with LMCA stenting. Initial LMCA stenting experiences were described by Hokken et al in 2002 , where 1Surgical repair, given the setting of full anticoagulation/antiplatelet therapy and acute coronary ischemia, might have a higher overall risk than bail-out-stenting . In instProblems do remain with LMCA stenting, as stated in the study by Onsea et al , uncontrOur patient was discharged home the day after the procedure without any complications. The patient underwent surveillance angiography in 1 month from initial cardiac catheterization date. This was technically not difficult and showed full patency of original stents without any extension of the dissection plane. We report a rare case of iatrogenic aorto-coronary dissection that was successfully treated with PCI strategy alone.


Somatic mutation rates in cancer differ across the genome in a cancer cell-type specific manner. Although key factors that contribute to the differences were identified, the major cancer progression stage when these factors associate with the mutation variance remained poorly investigated. Here, we analyzed whole-genome sequencing data of pre-cancerous and matching cancer tissues from 173 individuals and 423 normal tissue chromatin features to determine the critical stage of these features contributing to shaping the somatic mutation landscape. Our data showed that the establishment of somatic mutation landscape inferred by chromatin features occur early in the process of cancer progression, and gastric acid reflux environmental exposure-mediated epigenetic changes, represented as gastric metaplasia, at early stage can dramatically impact the somatic mutation landscape. We suggest a possible crucial role of chromatin features during the mutation landscape establishment at early stage of progression in a cancer-type specific manner. Environmental insults that change how DNA is packaged could lead to mutations responsible for the earliest stages of cancer. Hwajin Lee and colleagues at Seoul National University analyzed whole-genome sequencing data from precancerous tissues (B-cell and esophagus) and the matching cancer types  from 173 individuals. They cross checked the mutational profiles against the epigenetic features that shape how DNA is wound into chromosomes, and found that these chromatin marks serve a central role in driving the overall mutation landscape. The authors suggest that gastric acid reflux, which is known to cause a precancerous condition known as Barrett’s esophagus, could be shifting the esophageal cells to become more stomach-like, and the resulting change in chromatin features might be triggering major mutation accumulations that affect subsequent cancer progression. Beyond these gene-focused approaches, systematic analyses of mechanisms that could explain genomic regional variations in mutation rates across various cancer types could significantly extend our understanding about common contributors to the establishment of mutation landscapes before and during cancer progression. To this end, a number of studies have examined relationships between regional mutation frequencies across the genome and several types of features, including gene expression level, DNA sequence context, mutation profiles of nucleotide excision and mismatch repair genes, histone post-translational modifications, and open chromatin marks such as DNase1-seq profiles.15 Although these factors display high correlation with regional mutation rates, somatic mutation profiles used for the studies were limited to fully progressed tumors. Thus, it remains unknown whether the correlations between regional mutation frequencies and cell-of-origin chromatin marks are established either gradually during cancer progression or during a specific critical time period, either pre-or post-malignancy. Analyzing the mutation landscapes of precancerous, non-neoplastic tissues alongside matching cancer tissues could help to determine the major time points where chromatin marks shape the mutation landscape.Recent advances in cancer genomics have so far revealed numerous somatic mutation landscapes for various cancer types, leading to a number of key findings. Identification of new driver gene mutations, deciphering clonal evolution structure, and profiling tumor heterogeneity within and among different patients through examination of mutations, mainly at the gene level,Here, we analyzed a total of 38 precancerous lesions including monoclonal B cell lymphocytosis (MBL) and Barrett’s esophagus (BE) (methods). Representative matching cancer types were also analyzed, corresponding to a total of 144 tumor samples from chronic lymphocytic leukemia (CLL) and esophageal adenocarcinoma (EAC). In addition, a total of 14 esophageal squamous cell carcinoma (ESCC) samples were analyzed to represent cancer without any defined precancerous stages during progression with a matching cell-of-origin.17 were reflected in the level of 1-megabase window regional mutation frequencies. Consistent with the differences in average mutation frequency, both MBL samples and CLL samples were indistinguishably located and formed separate clusters based on immunoglobulin heavy chain variable region (IGHV) mutation status, a key marker for distinguishing either naive-B cells or memory B cell origin for both MBL and CLL.18 These results indicate that cell-of-origin differences might contribute to the differences in regional mutation frequencies, rather than cancer progression-based status alone  to test whether the average mutation rate differences reported previouslyone Fig. . In contone Fig. . Collect10 Based on the IGHV mutation status-based clustering of MBL and CLL tissues in PCOA, we hypothesized that differential IGHV mutation status would correlate with distinct chromatin features explaining the regional mutation variation, and similar chromatin features would come up as significant when comparing IGHV mutation type-matching MBL and CLL genomes. To confirm the former part of the hypothesis, we first employed a random forest regression-based chromatin feature selection algorithm to identify significant chromatin features explaining the variance in regional mutation rates for different sample groups. Indeed, significant chromatin features explaining regional mutation variations were different between IGHV mutant and unmutant groups  . These results imply a distinct process of mutation landscape establishment for these cancer types that varies depending on the presence of precancerous tissues with cell-type shifts.To ensure that the chromatin features shaping the mutation landscape of BE and EAC were not common for any esophageal cancer type, we analyzed the genome of ESCC, another cancer type derived from the esophageal squamous epithelium without any precancerous stages going through cell type shift during the progression. Although the regional mutation frequency of ESCC displayed univariate correlation with histone modification marks from stomach and esophagus tissues in a similar manner  and matching cancer types  combined with 423 epigenomic features derived from normal tissues to elucidate the major time point at which these features play a role in establishing mutation landscape of cancer at early-stage of the progression. These analyses were important to investigate the possible role of chromatin features on shaping cancer somatic mutation landscape at early stage of progression along with possibly inferring previously uncovered intermediate stage of precancerous tissue development in terms of somatic mutation accumulations.One of the major findings in our work is that the major time point for the establishment of the mutation landscape shaped by chromatin marks could be early, even prior to the phenotypic emergence of precancerous tissues. This finding was consistent for both of the precancerous tissues, MBL, and BE. Although additional whole-genome sequencing data on other types of precancerous tissues might further confirm our findings, these two tissue types do represent two major categories of pre-cancerous tissues, one with metaplasia and one without it.One thing to note is that our results display non-universal chromatin features identified as significant in different cancer types. The reason for these differences in the extent of variance explaining values for any distinct chromatin feature could be complex, and the reason might be due to the tissue type-dependent differences in the mechanisms of epigenetic regulation plus the differences in major contributing chromatin features serving as either euchromatin or heterochromatin marks. One mechanistic approach to assess the extent of chromatin features contributing to mutation landscape is using CRISPR-Cas9 system to incorporate mutations on chromatin enzymes leading to global epigenetic changes, and then inducing somatic mutations using various types of mutagens to examine the effect of different epigenetic features on shaping mutation landscape, which could be one of the strong candidates for any follow-up research.Finally, analyses results from BE and EAC also raise the possibility that epigenetic changes due to environmental insults, represented as a cell type shift, could serve as a primary role for establishing the mutation landscape of at early stage of cancer progression. Although there are possibilities that esophagus tissue chromatin features could still be involved in shaping the mutation landscape of BE in a minor manner, our analyses demonstrated that the stomach tissue chromatin features serve as a key factor shaping regional variations in somatic mutation frequency of BE.Taken together, this study provides novel insights to the mechanisms acting on shaping somatic mutation landscape at early-stage cancer progression, as well as suggesting possible dynamic contributions of chromatin features in this process. Based on our findings, we propose that the mutation accumulation process at early stage of the cancer progression could be non-gradual with possible intermediate stage depending on the presence of metaplasia . In the case of BE, EAC, and ESCC, data use were authorized from ICGC (http://icgc.org) and BGI (http://www.genomics.cn/) before use. A total of 23 pairs of BE and matching EAC genomics data17 were authorized from ICGC and genome data of 14 ESCC samples23 were acquired from BGI. These data sets were subsequently analyzed following the standard GATK pipeline (https://www.broadinstitute.org/gatk/) and somatic variants were called using the MuTect algorithm24 (https://www.broadinstitute.org/cancer/cga/mutect).For the purposes of our project, we used somatic mutation data from CLL, MBL, BE, EAC, and ESCC tissues. In the case of CLL and MBL genome data, total mutations were acquired from Supplementary Table 25 and ENCODE.26 NIH Roadmap Epigenomics data were accessible from the NCBI GEO series GSE18927, referring to the University of Washington Human Reference Epigenome Mapping Project.A total of 423 epigenomics and chromatin data were from the NIH Roadmap Epigenomics Mapping Consortium27 was employed to calculate the frequency and scores per each 1 Mbp region.To calculate the regional mutation density and mean signal of chromatin features, all autosomes were split in 1-Mbp regions followed by filtering out regions containing centromeres, telomeres, and low quality unique mappable base pairs. To determine regional mutation density and histone modification profiles, we counted the total number of somatic mutations or ChIP-seq reads per each 1-megabase region. For analyzing the DNase I hypersensitivity and Repli-seq data, scores of DNase I peaks and replication were calculated per each 1-megabase region. For somatic mutations, ChIP-seq data and DNase I hypersensitivity data, BEDOPSPCOA was used to represent differences in mutation frequency distribution among the individual samples. A dissimilarity matrix was built using 1—Pearson correlation coefficient across all samples. Each sample location was assigned in a two-dimensional space using this matrix.10 with modifications. Briefly, the training set for each tree was constructed, followed by using out-of-bag data to estimate the mean squared error. Thus, there was no need to perform additional tests for error evaluation. Out-of-bag data were also used to estimate the importance of each variable. In each out-of-bag case, the values corresponding to each variable were randomly permuted, then tested to each tree. Subtracting the score of the mean squared error between the untouched out-of-bag data cases and the variable-m-permuted cases, the raw importance score of variable m was measured. By calculating the average score of variable m in the entire tree, the rank of importance for each variable was determined. A total of 1000 random forest trees were employed to predict mutation density using a total of 423 chromatin features. Every random forest model was repeated 1000 times.A random forest regression-based feature selection algorithm was performed as described20 were removed prior to the analysis. To perform feature selection classified by differential dysplasia states  displaying top 5% in term of the residual values, (2) showing higher H3K4me1 levels in esophagus than stomach mucosa. Subsequently, we built two separate regression models, and then applied the model to predict the regional mutation frequencies for the 92 regions. One regression model was between observed mutation frequencies in BE with no dysplasia and H3K4me1 level of stomach mucosa, and the other one was between observed mutation frequencies in BE with no dysplasia and H3K4me1 level of esophagus.Our core analysis code utilizing the random forest feature selection algorithm is available on GitHub (code name: Random_forest_Ha_mutation_epi).https://doi.org/10.1101/074724).The preprint version of our manuscript is currently online at bioarxiv (Supplementary Information


However, apparent differences attributed to biogeography (ocean basin effect) and phylogeny (family/tribe effect) were highly correlated with methodological differences in tag type, model type, habitat type and study duration, thereby confounding biological interpretations and complicating efforts to use many current survival estimates in population assessments. Our results highlight the importance of evaluating sources of heterogeneity when interpreting patterns among similar demographic studies and directly inform efforts to identify research priorities for marine turtles globally.Comparative syntheses of key demographic parameters are critical not only for identifying data gaps, but also for evaluating sources of heterogeneity among estimates. Because demographic studies frequently exhibit heterogeneity, evaluating sources of heterogeneity among estimates can inform biological patterns and conservation actions more broadly. To better understand adult survival in marine turtles and avoid drawing inaccurate conclusions from current estimates, we conducted a comprehensive meta-analysis to test how heterogeneity among estimates was partitioned among phylogenetic, biogeographic and methodological factors. Fifty-nine studies from five marine turtle species met the minimum selection criteria for inclusion in our meta-analysis. Heterogeneity among survival estimates was first partitioned between differences in ocean basin (Indo-Pacific  However, estimates of key demographic parameters, such as survival and recruitment, viewed in isolation often provide limited and/or potentially biased inferences. In this regard, comparative syntheses of similar demographic studies are critical not only for identifying data gaps, but also for evaluating sources of heterogeneity among estimates. Because demographic studies frequently exhibit heterogeneity due to system-specific nature of biological phenomena2 and study-specific differences in methodology, identifying important sources of heterogeneity can inform biological patterns and conservation actions more broadly4. Conversely, comparative studies that fail to evaluate sources of heterogeneity risk drawing inaccurate conclusions and misleading management decisions.Demographic studies in ecology and conservation biology form the basis for assessing population viability and managing ecological risk6 of annual survival rates for adult marine turtles to generate precision-weighted, species-specific estimates and prediction intervals from existing data7 and to explicitly model sources of heterogeneity among estimates2. In theory, because all marine turtles exhibit conserved life history patterns, including slow growth and delayed sexual maturity8, adult survival rates should be high (>0.90) and exhibit limited natural heterogeneity among estimates. Our goal was to quantify heterogeneity among survival estimates and test how heterogeneity is influenced by (a) phylogeny, (b) biogeography and (c) methodology. If heterogeneity is influenced by phylogeny or biogeography, then biological differences in survival among species/populations may exist. In this case, survival estimates that are lower than expected would highlight important species- or region-specific hotspots in adult mortality – areas of conservation concern. However, if heterogeneity is also strongly influenced by methodological differences, then statistical biases related to certain methodologies introduce artificial variation and mask important biological differences. In this case, the use of survival estimates that are lower than expected may mislead management decisions if methodological biases are not accounted for. We expect the findings of this synthesis to highlight the importance of evaluating sources of heterogeneity when interpreting demographic estimates2 and directly inform efforts to identify research priorities for marine turtles globally12.We conducted a systematic review and comprehensive meta-analysis6. Specifically, we conducted a two-tiered literature search to compile annual survival probability estimates for adult marine turtles. A structured search was conducted in Google Scholar, Sea Turtle Document Library (seaturtle.org) and Sea Turtle Online Bibliography  using the following Boolean search terms: survival, survivorship, mortality, and the names of the seven marine turtle genera. Then, an unstructured literature search was conducted by reviewing the reference lists of all the relevant publications and reports from the structured search. References compiled from the structured and unstructured search were reviewed and only those that estimated annual survival probabilities for adult turtles were retained . Seventy-eight survival estimates were found in the global literature review with 59 meeting the minimum selection criteria for inclusion in the meta-analysis  is sister to Chelonidae, which includes Chelonini (flatback and green turtles) and Carettini . The measure of effect size and precision of each estimate was the study-specific inverse-precision weighted annual survival probability and the associated standard error, respectively.We followed the PRISMA protocols for assembling a dataset suitable for meta-analytic evaluationet al.15. Details on covariate characterization can be found in the Supplementary Methods. Study duration and publication year were also used to account for various forms of publication bias17.The following potentially informative covariates (or moderators) were compiled for all survival estimates: specific publication ID, research group (based on common authors), type of publication , publication year, taxonomic group , study site, geographic region with subgrouping for two oceans (Indo-Pacific and Atlantic), study duration (years), habitat type (nesting or foraging), tag type and statistical estimation type with subgrouping for modeling procedures versus enumeration calculations. Each estimate was categorized by whether tag loss, imperfect detection and temporary emigration were explicitly accounted for or not. The population of interest in each study was also characterized in terms of population size, population trend, direct harvest history and fisheries bycatch impact using primarily Wallace 19. In this 2-level analysis, the random effect was the specific study. Each study-specific survival estimate was a response variable soft-bound between 0–1. Response variables were therefore logit-transformed prior to fitting the random-effects models to ensure the predicted estimates were also between 0–120 and then back-transformed for any predicted summaries. Species-specific random-effects models were fitted using the metafor package for R21 and displayed in a subgroup forest plot that was augmented with the species-specific random effects estimates and the prediction intervals for those estimates7.We used a precision-weighted random-effects model approach to summarize the 59 survival estimates into species-specific subgroups before accounting for informative covariates23 to explore underlying patterns among the potential effects of 12 correlated covariates on the 59 survival estimates. The conditional inference tree model was fitted and then displayed using the partykit package for R24 with a minimum split criterion of 0.95 . Because the conditional inference tree approach does not account for the precision of survival estimates, we also tested a series of meta-regression models using metafor to explore other potentially informative covariates when estimate precision was explicitly considered. Models with different predictors were compared based on Akaike Information Criterion (AICc).Because many of the potentially informative covariates in our meta-analysis were highly correlated, we could not isolate individual effects or explicitly model interactions among covariates simultaneously. Therefore, we first used a recursive partitioning or conditional inference regression tree approach25 to model annual survival rates conditioned on the main interaction effect – ‘ocean by family/tribe’ – identified within the conditional inference tree and four additional moderators identified by exploratory meta-regression modeling – tag type, model type, habitat type and study duration. We also included a 3-level hierarchical structure27 to test for potential non-independence between studies conducted by the same research group (based on common authors), an important assumption to account for in meta-analytic studies28. In this 3-level hierarchical analysis, the random effects were study within research group. The mixed effects meta-regression models were fitted using a multivariate parameterization to accommodate assessment of random effect structures29. The model-predicted study-specific inverse-precision weighted annual survival estimates and covariate effects were summarized as covariate-specific boxplots. Continuous variables, like study duration, were modeled using B-splines (splines package)30 to account for potential nonlinear functional forms29 and predicted estimates were summarized using a cubic regression spline GAM-based smoother31 implemented within the ggplots2 package for R32.We then used a mixed-effects meta-regression approach2 statistic33 was used to assess the level of unexplained heterogeneity estimated in the 3-level hierarchical meta-regression model fit to the 59 studies, and a simple R2 measure appropriate for the multivariate parameterization of a meta-regression model was used as a metric of the overall model fit. The Cochrane QE test was used as a formal test of residual heterogeneity34, while an omnibus F-test was used to test for significance of the set of all covariates included in the meta-regression model35. Lastly, we explored potential publication bias17 using a contour-enhanced funnel plot36 of the model predicted study-specific survival estimates using metafor.The IThe dataset supporting this article has been uploaded as part of the electronic supplementary material.4, geographic and methodological covariates. We have also included the species-specific prediction intervals in the subgroup forest plot, which shows for instance that a new flatback adult survival rate study would be expected to provide an annual estimate ca. 0.93 . On the other hand, for leatherbacks it would be 0.85 .The 59 species-specific survival rate estimates derived from the random-effects model are summarized in Fig. The conditional inference tree approach identified two significant nodes at a minimum split criterion of 0.95: (Node 1) Atlantic versus Indo-Pacific oceans and Node 2) Chelonini versus Carettini and Dermochelidae nested within the Indo-Pacific Ocean . However, ca. 97% of unaccounted variance was due to residual heterogeneity , and only ca. 37% of the residual heterogeneity in the accepted model was accounted for by inclusion of the six moderators (R2 = 0.37). This high level of residual heterogeneity was significant  and apparently typical of ecological studies28.The 3-level hierarchical meta-regression model (random effects = study within research group) was a better fit than a 2-level model (random effect = study) . The 3-level model with a nonlinear functional form for study duration was a better fit than the same model with a linear functional form . The inclusion of the six moderators in the accepted 3-level, nonlinear regression model led to a significant improvement in overall model fit , ocean (2 levels), tag type (4 levels), method type (5 levels), habitat type (2 levels) and the study duration by tag type interaction term Fig.  and (5) A contour-enhanced funnel plot of the predicted study-specific survival estimates derived from the 3-level hierarchical meta-regression model fit to the 59 studies showed no evidence of any form of publication bias , then by differences among family/tribe within the Indo-Pacific (Chelonini versus Carettini and Dermochelidae). Though often ignored, phylogenetic non-independence can change the results of ecological meta-analyses4. However, in this case, differences were not associated with phylogenetic similarity – Carettini is more closely related to Chelonini (both in Chelonidae) than to Dermochelidae13. Therefore, survival estimates in Carettini and Dermochelidae are likely similar and lower than Chelonini due to other biological or methodological factors, not phylogenetic history. Estimates for Indo-Pacific Chelonini might be higher because this group includes flatback turtles, which are endemic to the Indo-Pacific, exhibit different and potentially less vulnerable habitat-use patterns (exclusively neritic versus both neritic and oceanic), and have been consistently monitored with robust methodologies (see below)37. Estimates specifically from the Northwest Atlantic (as there are no estimates from the Northeast or South Atlantic) are lower than the Indo-Pacific. However, this is not consistent with any apparent differences in natural or anthropogenic mortality rates or any known differences in life-history behavior among populations in different oceans. Predictors that might be indicative of differences in adult mortality among turtle populations such as harvest history and fisheries bycatch impact15 were not found to contribute to heterogeneity among survival estimates . Similar concerns with respect to tag loss may apply to inconel tags, although to a lesser extent than monel. Second, our results show that early attempts to estimate survival via enumeration methods that rely on time-series counts of individuals violate far more CMR assumptions than statistical modeling procedures such as CJSRE and MSORD, which are designed to estimate and account for biases including imperfect detection and temporary emigration43. Although robust statistical modeling procedures are well accepted and almost universally used, the accuracy of estimates will always depend on the quality of CMR data to which the models are applied. Third, our results suggest that CMR data collected in foraging areas may be less prone to statistical biases than data collected on nesting beaches. Because marine turtles spend considerably more time in foraging areas, estimates from foraging areas may be more robust to statistical biases associated with temporary, as well as permanent, emigration. Methodological differences clearly contribute to heterogeneity among survival estimates.The ocean and family/tribe predictors were highly correlated with methodological predictors, including tag type, method/model type, habitat type and study duration. Results from exploratory meta-regression modeling showed that these four factors, in addition to ocean and species, were consistently found within the best-fitting models. Direct monitoring of marine turtles in the wild is inherently difficult and CMR studies remain the most reliable tool for estimating annual survival rates. However, such efforts are clearly vulnerable to statistical biases when methodologies cannot account for complexities inherent to the biology and study of marine turtles such as imperfect detection, tag loss, and temporary and permanent emigration. First, our results highlight the importance of tag type and its ramifications on tag loss on survival estimates. We found that estimates generated from monel tags were consistently lower than estimates generated primarily from inconel, titanium and PIT tags. Estimates generated from monel tags are likely biased low and effected by study duration Fig.  due to f15, more work is needed to generate new, more comparable estimates that will improve the accuracy of assessments of the status and trends in marine turtle populations44 and help guide conservation measures and management in the future.Patterns among different methodologies and their associated biases are highly correlated with biological patterns: more low estimates come from the Atlantic Ocean, Carettini and Dermochelidae, monel tags, enumeration calculations and nesting beaches, while more high estimates come from the Indo-Pacific ocean, Chelonini, titanium tags, statistical modeling procedures and foraging areas Figs  and 4. W12. At the region-level for all applicable species, there is a noticeable lack of estimates from the eastern North Atlantic (including the Mediterranean Sea), South Atlantic, western and northern Indian Ocean (including the Red Sea and Persian Gulf), western North Pacific and eastern South Pacific  were excluded for not meeting the minimum selection criteria for inclusion in the meta-analysis. Because these estimates were not deemed sufficiently robust and all are at least two decades old, new estimates for ridleys should be a research priority, especially given their susceptibility to overexploitation from human threats such as fisheries bycatch45. Globally, estimates from nesting beaches are far more frequent than estimates from foraging habitats, which are primarily from eastern Australia . Meta-analytic comparisons of key parameters and threats associated with the biology and conservation of marine turtles − such as breeding and recruitment rates, population and individual growth rates, and fisheries bycatch and plastic ingestion rates − will reveal novel patterns and valuable insights, while accounting for important sources of heterogeneity that may obscure important interpretations28. Such analyses serve to guide research and conservation priorities for marine turtles into the future.Global research on marine turtles is poised to benefit from the application of meta-analysis. The accumulation of demographic and biological information from decades of research across all species and biogeographic regions has elicited global assessments and numerous review articles in recent years (e.g.Supplementary materialsTable S1


The indicating biomarkers specific to chronic wounds include blood pressure, temperature, oxygen, pH, lactate, glucose, interleukin-6 (IL-6), and infection status. A wound monitoring device would help decrease prolonged hospitalization, multiple doctors' visits, and the expensive lab testing associated with the diagnosis and treatment of chronic wounds. A device capable of monitoring the wound status and stimulating the healing process is highly desirable. In this review, we discuss the impaired physiological states of chronic wounds and explain the current treatment methods. Specifically, we focus on improvements in materials, platforms, fabrication methods for wearable devices, and quantitative analysis of various biomarkers vital to wound healing progress.Chronic non-healing wounds challenge tissue regeneration and impair infection regulation for patients afflicted with this condition. Next generation wound care technology capable of  Chronic wounds, those that exceed a 3-month healing process or that fail to demonstrate improvement through treatment under the normal physiological tissue repair mechanism in a timely manner, present severe difficulties for individuals afflicted with this condition and a substantial financial burden for the healthcare industry  hemostasis and inflammation, (2) proliferation, and (3) remodeling Figures  Witte a.Immediately after tissue damage occurs, hemostasis initiates. The blood vessels exposed to the injury site constrict, platelets aggregate at the site and form a platelet clot, followed by a fibrin matrix which is cleaved from fibrinogen during the coagulation of blood  remains around 5–20 mmHg in the exudate of chronic wounds, whereas healthy tissue exhibits 30–50 mmHg  and monocyte chemoattractant protein-2 (MCP-2), which recruits monocytes to maintain the inflammatory response and modify the immune system respectively. Therefore, elevated IL-6 levels in wound tissue can correlate to markers of the inflammatory phase Gabay, . AdditioThe second stage, proliferation, occurs 2–10 days after injury  and Staphylococcus aureus (S. aureus) developing into a biofilm and infecting the wound tissue   per gram of tissue has been shown to induce trauma at the wound, whereas more than 106 CFUs results in the inability to heal through normal physiological mechanisms  system on a wearable platform has the potential to improve current treatment options. In developing a wound monitoring microsystem, current wound dressing research and materials can indeed be incorporated into sensor substrates or platforms.Although both passive and active strategies for wound treatments and biocompatible materials have been studied, the current care system lacks a feedback mechanism that monitors the dynamics of the physiochemical microenvironment so treatment can be improved. A multifunctional Biosensor technology is advancing at an exponential rate. Engineering flexible biosensors capable of monitoring physiological information and assisting in proper treatment while laminating the device on the skin or an organ are technologically possible due to current advancements in the field  and polyimide (PI), are the staple materials for wearable technology because they form the skin to sensor contact primarily due to their high flexibility. For transparent flexible electronics, PET constitutes one of the commonly used substrates exhibiting robust mechanical properties (moduli 3.5–11 GPa), solvent resistant properties, tolerance to temperature (Tg ~100°C) , and higher glass transition temperature (Tg ~300°C)   and polyurethane-polyurea (10% spandex) provide sensor systems with physically tough, yet flexible and breathable support while providing an increase in strain. Of note, nylon fabric substrates have shown to be rugged and breathable substrates for noninvasive Unlike other substrates, paper offers a unique set of advantages that are completely distinct from polymers or other conventional materials. Paper substrates are highly accessible, inexpensive, and readily obtainable. Paper's inherent properties including flexible, light, thin, porous, breathable, and easily tear-able advances flexible electronics by making them an inexpensive disposable option compared to the alternatives. However, paper-based electronics have several limitations: (1) repeated folding results in thin circuit wires tearing, leading to circuit failure, (2) during laser engraving the stencil and paper contact makes it difficult to fabricate advanced pattern features of which require a dimension less than 50 μm  by the body's own fluids. Common biodegradable polymers used as substrate materials are polylactic acid (PLA), polycaprolactone (PCL), poly(lactic-co-glycolic acid) (PLGA), and silk. These electronics can fully degrade while maintaining a sensor performance for a specific time, which can be altered through the synthesis of the substrate polymer ratio concentration and circuit nanomembrane doping levels Figure  Hwang e. The re-As state of the art, flexible electronics are emerging at an abundant rate, rapid advancements in sensing platforms have paved the way for a new class of wearable technology. Epidermal platforms, often referred to as temporary tattoo electronics, give rise to a new emergence of next generation technology for flexible and stretchable electronics. The overall engineering of the system allows for a much thinner, lighter, and “skin-like” flexible device providing a nonirritating and long-lived interface with the human epidermis  Madou, . The resThe technique of soft lithography uses a combination of steps to design 3D patterns applied to flexible substrates, such as micro-channels and reservoirs. The master design is produced using conventional photolithography techniques, and PDMS—soft silicone-based elastomeric polymer—is coated over the master and cured , a polymer of interest is exposed to an ultra-fast laser focused through a transparent membrane. This focusing results in two or more photons absorbed simultaneously and can control the depth and location of where the polymerization occurs, rendering 3D objects without layer-by-layer fabrication or masks  on the electrode surface breaking down glucose into gluconic acid Wang, . Variousin vivo monitoring, and silica nanoparticles encapsulating organic dye on PMMA for glucose monitoring in tear-based contact lens sensors  enzymatic reactions by lactate dehydrogenase and diaphorase producing a color change of a chromogenic reagent  to decrease abnormal collagen formation, increase fibroblast activity, slow metalloproteinase enzyme degradation rates, and yield a harsh environmental condition to decrease bacterial viability and infection at the site  on the polyimide film, constructed to measure or influence pH , phenol red, and naphtholphthalein. This colorimetric approach immobilizes dye on a flexible substrate, using various recording techniques  in wound exudate ranges from 5 to 20 mmHg, whereas healthy tissue exhibits levels from 30 to 50 mmHg  vs. unbound (660 nm) Baura, . Pulse oRecent oxygen sensors have been developed using chronoamperometry. Luo et al. reports encasing a gold electrode in a PDMS-solid state Nafion electrolyte composite for oxygen dissolved in a microfluidic system , using glutaraldehyde and chitosan to immobilize the anti-IL-6-antibody in a photoelectrochemical sensor  bind to the antigen and then enzyme label secondary antibody (Ab2) bioconjugate interacts to the antigen  electromagnetic waves. Measure IR power using pyroelectric materials generate a voltage due to a change in temperature correlates with body temperature Baura, . Ota et Normal blood pressure levels are defined as having a systolic pressure (SP) below 120 mmHg and diastolic pressure (DP) lower than 80 mmHg  biosensor , whereas the non-covalent method yielded a higher limit of detection (107 CFU/mL) and higher sensitivity (1.52 mV/Decade). In another study, Suaifan et al. reported a colorimetric paper-based biosensor reacting to the affinity of magnetic nanobeads to the proteolytic activity of S. aureus,  (Singh et al., in situ wound monitoring device, a synergistic research effort of incorporating therapeutic agents to assist in wound repair would improve the overall efficacy of the device. Pharmaceutical enhancements, distinct drugs able to not only increase and induce improved wound healing but also administer antibiotics to eradicate biofilms present on the wound bed. However, in instances where there is an absence of a bacterial biofilm the device should not elicit an antibiotic treatment since antibiotics have been shown to disrupt the natural healing process and promote necrosis of the tissue in wounds not cultured with bacteria (Lo et al., In parallel with developing an To fabricate such a device, future research should focus on the integration of sensors able to monitor physiological information and assist in providing proper treatment while worn. Individual works cited throughout this review have provided new solutions to engineering flexible and stretchable sensors to be used in the fabrication of a POC device applicable to improving wound care technology.MB and AK conceived and developed the framework for the outline and focus of the review paper. MB and BA drafted the article and created tables and figures. MB constructed the manuscript. MB, BA, and AK participated in the revision process of the article and gave final approval of the submitted version.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.


Whether bisphosphonates could enhance the effect of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) in non-small-cell lung cancer (NSCLC) patients with EGFR mutation and bone metastases (BM) remains unknown. EGFR mutation status were collected from 1560 patients with NSCLC and BM. 356 NSCLC patients with EGFR mutation and BM were identified. Among them, 91 patients received EGFR-TKIs alone and 105 patients received EGFR-TKIs plus bisphosphonates as first-line therapy. Comparing to TKIs alone, EGFR-TKIs plus bisphosphonates had a statistically significant longer progression-free survival , while a similar overall survival  in patients with EGFR-mutant NSCLC and BM. The incidence of skeletal-related events in combined group was numerically lower than that in EGFR-TKIs alone group . In multivariate analysis, EGFR mutation was found to be a significant independent prognostic factor for OS in NSCLC patients with BM . In conclusion, EGFR mutation was the significant independent prognostic factor for OS and the addition of bisphosphonates to EGFR-TKIs could enhance the antitumor effect of EGFR-TKIs in patients with EGFR-mutant NSCLC and BM. Lung cancer is one of the most common cancers as well as the leading cause of cancer-related death worldwide14557in vitro and in vivoCurrently, the therapeutic strategies to manage BM are still limited. Systemic therapies that block osteoclast activity including bisphosphonates  and Receptor Activator of Nuclear factor Kappa B Ligand (RANKL) inhibitors (denosumab) can reduce the incidence of SREs91012141516Thus, we analyzed this large cohort of 1560 patients with BM and advanced NSCLC to investigate whether bisphosphonates affect the outcome of first-line EGFR-TKIs therapy in Chinese NSCLC patients with EGFR mutation and BM. Meanwhile, we also assessed the role of bisphosphonates in advanced NSCLC patients who receiving chemotherapy as the first-line setting. In addition, the epidemiology and clinical characteristics of NSCLC patients with BM were analyzed.A total of 2975 NSCLC patients with M1b stage were initially identified and 1560 NSCLC patients with BM enrolled into further analysis in this study from February 2012 to May 2015 . Of them552 patients underwent the EGFR detection . There aIn EGFR mutation group, 94 patients with BM received EGFR-TKIs and 111 patients received EGFR-TKIs plus bisphosphonates . 91 patiIn univariate analysis of 552 patients with BM, patients without SREs had significantly better OS than those with SREs . Patients with ECOG PS 0–1 had significantly better OS than those presenting with ECOG PS > 1  . No signTo our best knowledge, the current study is the first large-scale observational study to investigate the epidemiology and role of the third-generation bisphosphonates in NSCLC patients with BM. 1560 NSCLC patients with BM were included into this study and 552 cases entered the epidemiological analysis of EGFR mutation and survival analysis. We found that EGFR mutation was a significant independent prognostic factor for OS in BM patients with NSCLC. More importantly, the addition of bisphosphonates to EGFR-TKIs had longer PFS, while similar OS than TKIs alone in BM patients with EGFR mutations. However, bisphosphonates showed no additional PFS or OS benefit when combined with chemotherapy as the first line setting in patients with NSCLC and BM.in vitro and in vivo1818Bisphosphonates are the frequently used for preventing SRE in NSCLC patients with BM5Systemic chemotherapy is still the main therapeutic choice for advanced NSCLC without driver mutations. Several preclinical studies indicated that bisphosphonates could induce tumor cells apoptosis, inhibit tumor cell invasion and metastasis, affect immune microenvironment and therefore have antitumor effects in a variety of tumors, including NSCLC181921Comprehensive understanding the process of BM formation could help to develop potential novel therapeutic compounds for BM. Bone metastasis is a continuous and complicated process and several features of the bone marrow microenvironment involve, including interaction with osteoclasts and osteoblasts promoting bone degradation releasing extracellular matrix (ECM) bound growth factors, which could also promote the development of lung cancer micrometastases258Our study has several limitations that should be acknowledged. Firstly, despite the fact that the initial population was large, the number of patients who entered the final analysis was relatively small. Therefore, the findings in this study need to be further validated in prospective trials with large scale. Secondly, this study is a retrospective study, which will inevitably have selection bias. Due to the side effects of bisphosphonates, it was not recommended to some patients with renal dysfunction or dental diseases. Thirdly, all of patients in this study received the third-generation bisphosphonates (zoledronic acid and ibandronic acid). Therefore, whether other bisphosphonates could improve patient’s survival combined with EGFR-TKIs needs further investigation.In conclusion, this study demonstrated that EGFR mutation was a significant independent prognostic factor for OS in patients with advanced NSCLC and BM. The addition of bisphosphonates to EGFR-TKIs could enhance the antitumor effect of EGFR-TKIs in patients with EGFR mutant NSCLC and BM, which suggested that third generation of bisphosphonates should be recommended in patients with advanced EGFR mutant NSCLC and BM who received EGFR-TKIs as the first-line setting.Patients with pathologically confirmed lung cancer at the Department of Medical Oncology, Shanghai Pulmonary Hospital and Henan Cancer Hospital from February 2012 to May 2015 were retrospectively collected. The lung cancer diagnosis was confirmed pathologically according to World Health Organization (WHO) pathology classification. Firstly, NSCLC patients with BM were selected. Then, patients received EGFR mutation test were chosen for the subsequent analysis. The major clinicopathological characteristics including demographic information, Eastern Cooperative Oncology Group performance status (ECOG PS), smoking history, lung cancer histology . EGFR mutations were tested by amplification refractory mutation system (ARMS) as described in our previous studies 313233342), vinorebine  or gemcitabine  was administered in combination with platinum-based chemotherapy every 3 weeks for 4–6 cycles until progressive disease (PD) or unacceptable toxic effect. Patients achieving complete response (CR), partial response (PR), stable disease (SD) would receive maintenance therapy. The decision whether to start bisphosphonates in NSCLC patients with BM were at the discretion of the treating physician. Zoledronic acid (4 mg) and ibandronic acid (6 mg) were administrated every 3–4 weeks according to the guidelines up to 2 years or until unacceptable toxic effect36The EGFR-TKIs used in this study included gefitinib , erlotinib  and icotinib . Pemetrexed  and corresponding 95% confidence intervals (CI). OS was calculated from the date of lung cancer diagnosis to death from any cause or was censored at the last follow-up date. PFS was defined as the time from the date of first-line treatment initiation to the date of systemic progression or death and was censored at the date of last tumor assessment (when carried out). Disease progression was defined in accordance with the RECIST version 1.1. P values were two-sided and considered significant if less than 0.05. All statistical analyses were performed using the SPSS statistical software, version 20.0 .How to cite this article: Zhang, G. et al. Bisphosphonates enhance antitumor effect of EGFR-TKIs in patients with advanced EGFR mutant NSCLC and bone metastases. Sci. Rep.7, 42979; doi: 10.1038/srep42979 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Ecological processes are generally scale-dependent and there is little consensus about the relative importance of deterministic versus stochastic processes in driving patterns of biological diversity. We investigated how the relationship between functional dispersion and environmental gradients changes with spatial scale in subtropical freshwater lakes. The functional alpha and beta dispersions of all the tested traits were significantly under-dispersed across spatial scales and along environmental gradients. Results showed more functional similarity within communities in leaf dry mass content and flowering duration but less functional turnover among communities in all the tested traits at regional scales (Yunnan-Guizhou plateau and the middle and low reaches of the Yangtze River). The strengths and directions of environmental effects on the functional alpha and beta dispersions depended on the selected traits, diversity metrics and spatial scales. Surprisingly, broad-scale factors - elevation and water transparency - decreased the functional turnover for most traits along the gradients, whereas fine-scale factors - water depth - produced the opposite patterns along the gradient, depending on the trait selected. Our study highlights the dominant role of deterministic assembly processes in structuring the local functional composition and governing the spatial functional turnover of macrophyte communities across multiple spatial scales. For example, a community may have high taxonomic α-diversity, but low functional α-diversity because these species exhibit functional similarity within a given habitat2. Similarly, there may be complete species turnover between two communities (i.e. taxonomic β-diversity) but little functional turnover, because these species exhibit functional similarity at different habitats3. Therefore, investigating the determinants of functional diversity - which characterizes the physiological dimension of biodiversity omitted by purely taxonomic analyses - will increase our understanding the mechanisms driving the diversity patterns.The majority of research into biological diversity has focused on determining the factors that drive species richness within a community (taxonomic α-diversity) and species turnover between communities (taxonomic β-diversity), However, species-level analysis of biodiversity are limited, because they treat all species within a community as ecologically equivalent. This ignores the inherent functional variation among species that arise from different life-history strategies within the same environment8. These studies have tested the relative importance of deterministic vs. stochastic processes in structuring functional diversity using measures of how far the functional α-diversity of each community diverges from a null model10. For example, theoretical and empirical analyses suggest that abiotic filtering creates communities with species that are more similar in their functional traits than expected by chance (under-dispersion/convergence). Conversely, biotic interactions are thought to create communities where functional traits are more different than expected by chance (over-dispersion/divergence). Furthermore, recent studies on functional beta diversity have shown that deterministic processes play a more important role in structuring local communities and governing spatial turnover in communities13. For example, if the co-occurring species in the nearby communities are more functional divergent than the null expectation given the observed species turnover, a higher functional turnover than expected would be detected among communities2.Recent analyses have focused on the degree to which the functional diversity of ecological communities is driven by either deterministic process (such as abiotic filtering and biotic competition), or stochastic processes (such as vicariance and random dispersion)19. This scale-dependency will necessarily affect the results of previous studies that focused on a single spatial scale21. A relatively well-accepted hierarchical model of community assembly suggests that environmental factors act as a series of filters  sequentially sorting species being favorable to local habitats from the regional pool22. These hierarchical assembly processes filter species according to sets of functional traits23. Firstly, broad-scale environmental factors such as annual rainfall should result in functional similar co-occurring species within large regions , with little functional turnover among neighboring communities within a large area of homogeneous habitat. Secondly, fine-scale environmental factors such as topography should filter species pool into several subsets with more functionally similar traits along the gradients . A substantial functional turnover between assemblages may exist because of the turnover in the environmental gradient . Finally, the finest-scale  is characterized by high individual density and low habitat heterogeneity. With decreasing spatial scales, generally, deterministic processes become less important while stochastic processes become more important in determining community assembly20. The scale-dependency of assembly processes are largely attributed to the fact that25: (1) the range and extent of environmental filter would change with scale, and (2) the dominant environmental factors would change with scale. For example, elevation or altitude would be important factors driving diversity patterns at regional scale, while local environment  would determine the abundance and distributions of local macrophyte communities26. Given the inherent interaction effects of scaling and environment on the assembly processes, few studies have simultaneously focused on the assembly mechanisms along environmental gradients and across multiple spatial scales.The assembly mechanisms inferred from the observed patterns of functional diversity will be influenced by the spatial scale of analysisWe analyzed how the relationship between functional diversity and environmental gradients changed across four nested spatial scales in south China - 1008 plots, along the water depth gradients within 24 lakes across two regions. We quantified functional alpha and beta dispersion to determine whether the observed functional alpha and beta diversity differs from that expected by chance. We applied a general linear mixed model to decompose the total variance of functional alpha and beta dispersion across spatial scales. Subsequently, we analyzed the significance of environmental effects on functional alpha and beta dispersion at each of three spatial scales . We test three questions: First, how do functional alpha and beta dispersion vary across the four spatial scales? Second, how do functional alpha and beta dispersion vary along environmental gradients at each spatial scale? Third, do these diversity patterns related to spatial scale, or environmental gradients differ among functional traits?P < 0.05). Results showed that functional alpha and beta diversity were significantly clustered (under-dispersion) for multiple trait metric and most individual traits across all four spatial scales  and beta dispersion (SES Dpw and SES Dnn) were quantified using pairwise and nearest-neighbor metrics. Non-random functional alpha and beta dispersion was found for all the traits across all four spatial scales  at broader scales Fig. . For lifThe partitioning of variance in functional alpha and beta dispersion reveals relatively un-balanced distributions of variance across spatial scales Fig. . Among tAt the depth scale, the water depth gradient was considered as the primary environmental factor influencing community dynamics in this study. Significant trends in the SES values of alpha and beta metrics were found along the water depth gradient, although these trends varied in direction, depending upon the metric or traits used Table . PairwisAt the lake scale, the water transparency (Secchi depth in this study) was the most important environmental factor according to PCA from the six measured physical and chemical parameters of water. Pairwise functional alpha diversity was more clustered for multi-trait metric and three individual traits - life history, specific leaf area and leaf dry mass content - at lakes with higher transparency Table , Fig. 5.At the regional scale, elevation was considered as the major environmental factor influencing community dynamics in this study. Pairwise functional alpha dispersion was more clustered for life history and leaf dry mass content at higher elevation Table , Fig. 7.Here we quantified the functional alpha and beta diversity of macrophyte communities along environmental gradients at multiple spatial scales in 24 freshwater lakes of south China. We found that the patterns of functional diversity within community as well as functional turnover among communities were strongly nonrandom across all four spatial scales. Furthermore, the strength of nonrandom effects on the functional composition of macrophyte significantly varied with spatial scale and along the environmental gradients at each spatial scale. Our results provide strong support for the deterministic processes that drive macrophyte community assembly from the local to regional scales.27. Variations of the functional alpha dispersion across spatial scales largely depend on the selected traits. For example, the strengths of abiotic filtering effects on functional diversity within a community were relatively lower in some functional axes  but higher in other functional axes  with decreasing spatial scale. This result suggests that deterministic assembly processes shape the functional composition of local community in multidimensional functional space, and are strongly related to the trade-offs among functional traits 28. By contrast, the variations in functional beta dispersion across spatial scales were highly consistent for the metrics of multi-trait and all individual traits. The strength of abiotic filtering effects on functional turnover among communities was shown to be lower at finer spatial scales. This study highlighted that there are generally more functionally similar co-occurring species within community with less functional turnover among communities at broader scales.The first goal of this study was to estimate how functional alpha and beta dispersion vary across spatial scales, given the observed species alpha and beta diversity. Our results showed that the observed functional alpha and beta diversities were generally lower than that the null expectation given the species richness and turnover, as indicated by the significant clustering of functional alpha and beta dispersion in most cases. This result indicated that niche-based deterministic processes are relatively more important than stochastic processes in structuring the macrophyte community across spatial scales, which is consistent with previous studies on terrestrial plant communities29, we can decompose the studied spatial scales into external  and internal  filtering processes. The present study demonstrated that the functional diversity patterns across spatial scales for multiple trait metrics and individual traits were greatly affected by internal filtering processes (>50%), implying that the environmental heterogeneity in micro-habitat and biotic interactions were highly important in determining functional compositions of macrophyte community. Overall, regional and lake scale explained more variations of functional beta dispersion, while plot scale accounted for more variations of functional alpha dispersion.Variance partitioning of functional dispersion demonstrated that the spatial structure of total variance was largely dependent on scale and trait metrics. This result suggests that environmental gradients in different scales may have different roles in shaping functional diversity patterns across spatial scales. As previous study suggested31, freshwater32 and marsh plant communities33, even in tropical forests9 that may be driven by neutral assembly processes. Freshwater macrophytes generally show broad distributional ranges from the local to regional scales, which is largely attributed to their high trait plasticity  in various freshwater habitats34. Freshwater habitats represent a stressful environment for plants, characterized by low carbon availability, shaded conditions, sediment anoxia, mechanical damage by currents and waves and a limited nutrient supply35. Furthermore, the primary environmental factors influencing macrophyte communities would change from broad scales  to fine scales 29. According to the hierarchical assembly processes, the three nested environmental gradients  in the present study should have sequentially filtered species being favorable to local habitats from the regional species pool.The second goal of this study was to estimate how functional alpha and beta dispersion vary along environmental gradients at specific spatial scales, given the observed species alpha and beta diversity. In the present study, we focused on one major environmental gradient for each of three spatial scales, namely, elevation at the regional scale, water transparency at the lake scale and water depth at the depth scale. Study results showed that the observed functional alpha and beta diversities were generally lower than the null expectations along the three environmental gradients given the species richness and turnover, as indicated by the significant clustering of functional alpha and beta dispersion in most cases. This result firstly demonstrated that there were significant deterministic assembly processes that structure the functional composition of macrophyte communities along each of the three environmental gradients across three nested spatial scales. Several previous studies on the mechanisms of community assembly have focused on a specific scale, although deterministic assembly has been observed in terrestrial29. Abiotic filtering effects are usually weakened when environmental conditions become favorable for plants at broad scales; thus, nearby communities should become more functionally similar. For this point, less functional turnover was observed in benign habitats than in adverse ones at the two scales . However, the trait distribution at the local scale should be shaped by the hierarchical effects of abiotic and biotic filters33. Our recent study demonstrated that niche differentiation  has a structuring role in the macrophyte community assembly along the water depth gradient; the effects of abiotic and biotic filters may act strongly on some traits but weakly on others, linking the intrinsic trade-offs among different sets of traits along the gradient5. Thus, the combined effects of abiotic and biotic filters may be responsible for the opposite patterns of functional turnover among the tested traits along the water depth gradient.Surprisingly, the strengths and directions of environmental effects depend on the selected traits, diversity metrics and spatial scales. For example, macrophyte species tend to be more functionally similar within communities for life history at deeper water , lakes with higher transparency  and regions with higher elevation , while be less functionally similar for shoot height at deeper water. This result suggests that abiotic filtering effects increased for life history but decreased for shoot height along water depth gradients, associated with the intrinsic trade-offs among different sets of traits along the gradients. On the other hand, functional beta dispersions were generally lower than the null expectations across scales; nearby communities increased functional turnover - less departure from the null expectation - for leaf dry mass content along the water depth gradient, while decreased functional turnover for life history and specific leaf area toward deep waters. With increased water transparency and elevation, however, nearby communities decreased functional turnover for multi-trait metric and two individual traits - specific leaf area and leaf dry mass content. Results indicated that broad-scale environmental factors - elevation and water transparency - resulted in decreased functional turnover for most traits along the gradients, and fine-scale environmental factors - water depth - lead to two completely opposite patterns along the gradient, depending on the trait selected. In this study, the regions with higher elevation in the Yunnan-Guizhou plateau and the lakes with higher water transparency are relatively favorable to the growth of macrophytes. The former showed a longer growth period, higher light radiation intensity and constant annual temperature, while the latter had a higher light availabilityet al.5 indicated that biotic interactions played a structuring role on macrophyte community assembly at local scale, and that including intraspecific trait variability into functional alpha diversity greatly enhanced the detections of non-random biotic effects. Spasojevic, et al.36 highlighted that the integration of intraspecific trait variability into functional beta diversity would better explain the diversity patterns across spatial scales. The present study measured the metrics of functional alpha and beta diversity based on the interspecific trait variability, and thus important information might have been lost from intraspecific trait variability37.However, we also found no significant effects of environmental gradients - water depth, water transparency and elevation - on functional alpha and beta dispersions for several tested traits, thereby implying that the strength of deterministic processes in these functional axes did not vary with environmental gradients. Furthermore, no significant biotic effects  on the functional composition of macrophyte communities were found in most tested traits of this study. Fu, To our knowledge, this study is the first to focus on the effects of spatial scale on the functional alpha and beta dispersion for aquatic macrophytes. Results provide fresh insights into the mechanisms that drive macrophyte diversity patterns across spatial scales and in relation to environmental gradients. Overall, the present study leads to three important conclusions. Firstly, the functional alpha and beta dispersion of most traits was clustered across all four spatial scales, thereby highlighting the dominant role of deterministic processes at the scales of this study. Secondly, the effects of spatial scale on functional alpha dispersion depended on the selected traits; the strength of abiotic filtering effects increased for some traits but decreased for others as the spatial scale increased. For functional beta dispersion, the strength of abiotic filtering effects largely decreased  from the regional to local scale. Finally, the strengths and directions of environmental effects on the functional alpha and beta dispersions depended on the selected traits, diversity metrics and spatial scales. Surprisingly, broad-scale abiotic factors - elevation and water transparency - resulted in decreased functional turnover for most traits along the gradients. Fine-scale abiotic factors - water depth - produced two completely opposite patterns along the gradient, depending on the trait selected. Overall, the deterministic assembly processes would drive functional diversity patterns by shaping the multi-dimensional functional space, which is constructed from functional traits representing major axes of plant strategy.2 plots in 3 -45 (in a larger lake) sites of these lakes . All the species in these plots were identified and recorded. Fifty species including 27 submerged macrophytes, 12 floating-leaved macrophytes and 11 emergent macrophytes were recorded in the 1008 sampling plots along the water depth gradients of 24 lakes across 2 regions , shoot height, specific leaf area, leaf dry mass content and flowering duration. The life history and flowering duration for each species were collected from regional floras. Flowering duration describe the earliest and latest months that a species is in flower. The details of the trait measurements were described in Fu et al.39.Five key functional traits were measured, and two traits (life history and flowering duration) were collected from the literature for the 50 macrophyte species following standardised protocols41. Leaf dry mass content reflects the fundamental trade-off in investing resources in structural tissues vs. liquid-phase processes and therefore has been argued to be the root variable that governs the correlations among the traits in the leaf economic spectrum42. Shoot height (cm) is often allometrically related to overall plant size and competitive interactions for light43.We measured the mean values of the following three functional traits from 50 individuals of each species: shoot height, specific leaf area, leaf dry mass content. Specific leaf area is part of the leaf economic spectrum and is closely correlated with photosynthetic capacity, nitrogen content per mass and leaf life spann = 1008), depth scale (n = 135), lake scale (n = 24), and regional scale (n = 2). The plots were nested within different depth strata, the depth strata were nested within different lakes, and the lakes were nested within different region. We defined ecological communities at four nested spatial scales. Firstly, the plot scale was defined as four quadrats pooled into a 25 m2 plot  was used to extract orthogonal axes of lake from the six measured physical and chemical parameters of water  and to reduce information redundancy Table . Prior t44. The distances between individuals were calculated from a trait dendrogram, which is the mean distance of all species to the weighted centroid of the community in the trait space44. The trait dendrogram was generated by first generating a trait Euclidean distance matrix for the continuous data, and a trait Gower distance matrix for the discrete or mixed data . Hierarchical clustering was then applied to these matrices to generate the dendrogram. We generated six trait dendrograms, including ten for each trait (single trait) and one for all the traits combined (multi-trait metric).Functional alpha and beta diversities of macrophyte communities were calculated using two dendrogram-based metrics: mean pairwise and nearest-neighbor trait distance, respectively44.To calculate the functional alpha diversity, the mean pairwise trait distance (PW) and nearest-neighbor trait distance (NN) were weighted by abundance and quantified from the functional trait dendrogram for all the individuals in a community Fig. 44.et al.2. The first metric calculated the mean pairwise functional dissimilarity (Dpw) between two communities. The second metric calculated the mean nearest functional neighbor dissimilarity (Dnn) between two communities. We used these two metrics of functional beta diversity because they represent the two main mathematically independent classes of functional dissimilarity metrics, which avoid the redundancy of calculating other identical metrics44.To quantify the functional beta diversity, two abundance weighted metrics were measured according the approach of Swenson, n = 135), we pooled all quadrats within each plot, and calculated functional dissimilarity among all plots at each depth stratum of each lake , we pooled all depth stratum within each lake and calculated the functional dissimilarity among the depth strata of each lake. To quantify the functional beta diversity within each region (n = 2), we all pooled all lakes within each region and calculated the functional dissimilarity among the lakes of each region. To measure the functional beta diversity among both regions, we calculated functional dissimilarity among the two studied regions.To quantify the functional beta diversity  within each depth stratum  within communities for alpha diversity, and functional clustering among communities for beta diversity. If functional diversity values were higher than expected by chance, this indicated a functional over-dispersion within communities for alpha diversity, and a functional over-dispersion among communities for beta diversity.At each spatial scale, we tested whether the observed functional alpha and beta diversity metrics differed from those expected by chance, using a null model. The null model was generated by randomly assigning the taxa names to the tips of the trait dendrogram for 999 times45  to assess the standard deviation of the observed trait distribution from the null trait distributionequation :1\docume47.To test how functional alpha  and beta dispersions  varied with spatial scales, we fitted a general linear mixed model to the total variance of functional alpha and beta dispersion across four scales nested one into another (i.e. nested ANOVA with random effects) in this increasing order: plot, depth, lake and region. A variance component analysis was performed on this model using the ‘varcomp’ function of Ret al.48, which contains four major steps: (1) identify the optimal error structure (using AICc); (2) identify the optimal fixed-effect structure for the given random-effect structure through likelihood ratio tests; (3) check the final model assumptions ; (4) present the final model using restricted maximum likelihood estimation (REML) as the likelihood estimator, as it is considered to be a less biased estimator48. The P-values of the models were obtained by the likelihood ratio test. If the SES values of a trait metric become more negative than the null expectation along the gradient, we can expect a stronger effect of abiotic filtering effects on this trait; if the SES values of a trait metric become more positive than the null expectation along the gradient, we can expect a stronger effect of biotic filtering effects on this trait.To test how functional alpha and beta dispersion varied with environmental gradient of each spatial scale, a linear mixed effects model was generated for the three spatial scales , with the SES values of each metric for each scale as the dependent variables. To quantify the optimal structure of fixed-effect and random-effect in linear mixed effect models, we followed the top-down approach described by Zuur, 51. The figures were obtained using ArcGis 10.0 and the R packages “ggplot2”53.All analyses were performed in R using the packages “vegan”, “picante”, “coin” and “lme4”Supplementary Information


While less appreciated than the ubiquitous process of cell fission (division), cell fusion events play crucial roles in all walks of life. In vertebrates, the multinucleated product of cell—cell fusion, referred to as a syncytium, is central to the structure and function of tissue types like skeletal muscle fibers and the fetal—maternal barrier in the placenta . SyncytiA major functional component of HIV and related retroviruses is the Envelope glycoprotein (Env), which is embedded in the viral lipid bilayer membrane and is used for attachment to surface receptors on host cells. Env also encodes the machinery necessary to carry out the virus—cell fusion sequence. In addition to its role in initiating infection, Env protein synthesized de novo in the infected cell is trafficked to the plasma membrane to allow incorporation into assembling virus particles. As a result, infected cells are decorated with non-negligible amounts of viral Env protein. Early reports characterizing the behavior of the AIDS virus in tissue culture systems demonstrated that cell surface-associated Env can engage receptors on neighboring cells and trigger cell—cell fusion events, giving rise to giant, multinucleated cells , 3. ThusAt the turn of the century, the first direct evidence emerged that HIV-positive lymphocytes can fuse in vivo. In histological studies of lymphoid tissues rich in densely packed lymphocytes, multinucleated T cells showing signs of productive HIV-1 infection were observed . ImportaFurther work documented and quantified small, elongated syncytia in an HIV-1 infected humanized mouse model and provided important functional characterization in an in vitro system in which these structures could be reproduced . Here, sTogether, these publications suggest that small, virus-producing syncytia may be more common in the lymph nodes of infected humans than previously thought. Of all the HIV-1 infected T cells observed in situ, approximately 20% were multinucleated, and most contained only two nuclei. Interestingly, larger syncytia were observed at later time points following infection . Thus, HStudies of virus infection in living cells and tissues unveil a number of important insights regarding the behavior of infected cells, but they are equally informative for what they do not reveal. T cell syncytia can form and persist in the setting of HIV-1 infection, yet they remain a minority among the totality of infected T cells. Moreover, the transitory contacts that form between syncytia and uninfected lymphocytes indicate that Env-mediated fusion is subject to temporospatial regulation.It has long been recognized that, in tightly packed environments, HIV-infected T cells engage neighboring cells and form a “virological synapse,” named as such because it resembles the immunological synapse that T cells form with antigen-presenting cells  reviewe 16]. Ce. Ce16]. While certain processes controlling glycoprotein fusion of other viruses do not pertain to HIV (such as pH-dependent triggering), another mechanism of fusion regulation is hard-wired into HIV-1 virions. In immature particles, the structural Gag precursor protein inhibits Env-mediated fusion by interacting with the cytoplasmic tail of the gp41 subunit. Once Gag is cleaved during virion budding and maturation, Env fusion activity is restored –23. MoreWhile processes governing virus-mediated cell—cell fusion are affected by extracellular factors, such as Env-specific antibodies, they are also subject to a cellular landscape that changes once virus infection is detected or “sensed.” Every cell is equipped with a cell-autonomous innate immune system consisting of nucleic acid sensors and antiviral effector proteins that are mobilized in response to invading viruses . SeveralThe interferon-induced transmembrane (IFITM) proteins occupy cellular membranes and inhibit virus—cell fusion by altering the properties of lipid bilayers in which they reside and also inhibit the fusogenicity of HIV-1 particles , 29. AccBy combining intravital imaging of mice with advancements in gene modification and immunotherapy, the identification of host factors that control the formation or behavior of multinucleated cells will be possible. Furthermore, the perturbation or enhancement of small, mobile syncytia will define their ultimate importance to HIV dissemination. Adapting the same living systems for use with other virus strains with different origins and host tropisms (such as simian immunodeficiency virus [SIV]) may also reveal the extent to which the induction of cell—cell fusion is conserved during lentivirus evolution. Likewise, the in vivo study of other viruses known to induce syncytia in vitro, such as nonlentiviral retroviruses (T lymphotropic virus and foamy virus)  and RNA