Acute lymphoblastic leukemia (ALL) is the most common type of cancer diagnosed in children and Glucocorticoids (GCs) form an essential component of the standard chemotherapy in most treatment regimens. The category of infant ALL patients carrying a translocation involving the mixed lineage leukemia (MLL) gene (gene KMT2A) is characterized by resistance to GCs and poor clinical outcome. Although some studies examined GC-resistance in infant ALL patients, the understanding of this phenomenon remains limited and impede the efforts to improve prognosis.This study integrates differential co-expression (DC) and protein-protein interaction (PPI) networks to find active protein modules associated with GC-resistance in MLL-rearranged infant ALL patients. A network was constructed by linking differentially co-expressed gene pairs between GC-resistance and GC-sensitive samples and later integrated with PPI networks by keeping the links that are also present in the PPI network. The resulting network was decomposed into two sub-networks, specific to each phenotype. Finally, both sub-networks were clustered into modules using weighted gene co-expression network analysis (WGCNA) and further analyzed with functional enrichment analysis.Through the integration of DC analysis and PPI network, four protein modules were found active under the GC-resistance phenotype but not under the GC-sensitive. Functional enrichment analysis revealed that these modules are related to proteasome, electron transport chain, tRNA-aminoacyl biosynthesis, and peroxisome signaling pathways. These findings are in accordance with previous findings related to GC-resistance in other hematological malignancies such as pediatric ALL.Differential co-expression analysis is a promising approach to incorporate the dynamic context of gene expression profiles into the well-documented protein interaction networks. The approach allows the detection of relevant protein modules that are highly enriched with DC gene pairs. Functional enrichment analysis of detected protein modules generates new biological hypotheses and may help in explaining the GC-resistance in MLL-rearranged infant ALL patients.The online version of this article (10.1186/s10020-019-0106-1) contains supplementary material, which is available to authorized users. Acute lymphoblastic leukemia (ALL) is a malignant disease of the bone marrow characterized by the overproduction of immature white blood cells that accumulate and inhibit the production of normal cells. ALL is the most common type of leukemia in children  analysis has emerged as an alternative approach to differential expression analysis , the resulting network is decomposed into two sub-networks depending on the sign of the difference in co-expression between the two conditions. Finally, each sub-network is clustered into modules. Examining these modules using functional enrichment analysis reveal which of them are highly enriched with gene ontology (GO) terms. Active modules in each condition are specified by extracting genes of modules which are highly enriched in the same category of GO terms and form a connected sub-graph in the corresponding module. Our results demonstrate that protein modules related to signaling pathways such as proteasome, electron transport chain, tRNA-aminoacyl biosynthesis and peroxisome are active under the GC-resistance condition in MLL-rearranged infant ALL patients.50 value), such that LC50 < 0.1 μg/ml of prednisolone indicates prednisolone-sensitive and LC50 > 150 μg/ml of prednisolone indicates prednisolone-resistant  database under the series accession number GSE32962  database  and B (sensitive) separately. Pearson’s correlation coefficient between genes x and y under condition A is defined asx and y under condition A, nA is the number of samples under condition A, and k is the sample index. The correlation values were transformed using Fisher’s Z transformation such that  such that  for each individual gene pair and only links with assigned p-values< 0.01 are deemed significant and remain in the DC network while the remaining links are removed from the network. The resulting DC network represents links between gene pairs that are differentially co-expressed between GC-resistant and GC-sensitive samples with high confidence. To identify active protein modules, the DC network was modified such that all the links that are absent in the experimentally validated PPI network are removed from the DC network. In other words, the links of the DC network are pruned or trimmed by the experimentally validated protein-protein interactions. Combining the gene expression data and PPI networks in this step is reasonable given the moderate concordance between messenger RNA (mRNA) and protein abundances  for individual gene pairs. In the DCresistant sub-network, only the links that satisfy both of the two conditions rA- rB > 0.5 and rA > 0.5 are included. Similarly, in the DCsensitive sub-network, only links that satisfy both of the two conditions rA- rB < − 0.5 and rB > 0.5 are included. These conditions ensure that selected links represent high or moderate co-expression between the respective genes under the condition of interest but not under the second condition. Decomposing the DC network in this way allows easier biological interpretation for detected modules under each condition, as only genes with homogeneous changes between conditions are highlighted in each sub-network.The DC network is further decomposed into two sub-networks, DCresistant and DCsensitive were constructed to represent active links under each condition. Each sub-network was clustered into modules to identify active protein modules under each condition (resistant and sensitive). We used the generalized version of Topological Overlap Measure (TOM), as implemented in the WGCNA R package  tool  remained in the network. To identify active protein modules, the resulting network was integrated into the PPI network obtained from the HIPPIE database, such that only links available in the PPI network remain. As a result of integrating with the PPI network, a DC network with 4053 links across 3551 nodes (genes or proteins) was obtained. To identify active protein modules in each condition separately, the resulting DC network was decomposed into two DCresistant and DCsensitive sub-networks, as described in the Methods section. The DCresistant sub-network had 1511 links and 1449 nodes, and the DCsensitive sub-network had 739 links and 1075 nodes.To detect which gene pairs are differentially co-expressed with significance between resistant and sensitive samples, a weighted differential co-expression network was constructed and only significant links (DCresistant represents protein links with their associated genes having moderate or high co-expression (correlation) in resistant samples that is also higher than what is observed in sensitive samples. Clustering the DCresistant sub-network into modules revealed 8 gene modules, with 385 genes, which are active under the resistant condition but not the sensitive condition . The turquoise module has ~ 38 out of 85 genes playing key roles in the regulation of protein ubiquitination, ubiquitin-protein ligase activity in mitotic cell cycle, ubiquitin-dependent protein catabolic process and proteolysis, and most of them are highly enriched (FDR = 1.47 × 10− 48) in the proteasome KEGG pathway. These genes belong to the proteasome subunit (PSM) family and PSMC4 with 34 differentially co-expressed links with the rest of the module members is a hub gene in this module. Two other important genes of the same module are PSMD2 and PSMD1 with 27 and 22 differentially co-expressed links, respectively. The brown module is highly enriched with some close BP GO terms including mitochondrial adenosine triphosphate (ATP) synthesis coupled electron transport, respiratory electron transport chain and oxidative phosphorylation. Twelve genes of this module are different subunits of NADH:ubiquinone oxidoreductase (complex I), which is the first enzyme complex located in the inner membrane of the mitochondrion and plays a key role in the electron transport chain. In Table NDUFA9 was introduced as a hub gene of the brown module. NDUFA9 is differentially co-expressed with other members of the module encoding different subunits of mitochondrial complex I. The brown module was also found significantly enriched with members of the REACTOME Complex I biogenesis and respiratory electron transport pathways. These findings are concordant with earlier studies which associated the up-regulation of oxidative phosphorylation with GC-resistant  is a gene encoding protein kinase, which is differentially co-expressed with 11 members of the yellow module associated with MAPKKK cascade and also response to stress. Protein kinase C delta (PRKCD) is a member of the yellow module that is differentially co-expressed with 9 other members of the module, and is the second hub in the module. Human studies demonstrate that this gene encodes a kinase which is involved in B cell signaling and the regulation of growth and apoptosis.Another module seen in the PDHB, PDHA1 and DLAT) are highly enriched in the acetyl-CoA biosynthetic process, but none of them is a hub gene within the module. Gene ABCE1 has the highest connectivity within the green module, but ABCE1 shares no common biological function with its neighbors in the green module.Some distinct categories of BP GO terms were found in the green module. Respectively, 8 and 7 out of 43 genes were associated with RNA splicing and response to DNA damage. Only 3 genes of this module . PEX5 which plays an essential role in peroxisome, has the highest connectivity within the pink module, and most of its immediate neighbors, including PEX6, ACOX3, ACOT8, EHHADH, HMGCL, HACL1, ECI2 and MPV17, are also involved in Peroxisome KEGG pathway.Although the pink module is the smallest module in the on Table . Genes oTo determine whether the genes associated with biological functions are connected in their corresponding modules, we extract sub-graphs comprising these genes. We observed that the genes associated with proteasome, respiratory electron transport, peroxisome and aminoacyl-tRNA biosynthesis pathways, respectively in the turquoise, brown, pink and red modules are connected within these modules. This indicates that the genes involved in these biological functions are significantly DC between resistant and sensitive condition. This result suggests that the pathways connecting these genes are active pathways where regulatory relationships under one condition are disrupted under another. As indicated in Fig. DCsensitive sub-network are highly enriched in BP GO terms (FDR < 0.01). In the blue module, 10 genes are involved with protein ubiquitination and proteolysis and ~ 10 genes of the yellow module are involved in RNA splicing and spliceosome KEGG pathway. Although the blue module of DCsensitive sub-network is involved in proteolysis similar to the turquoise module of DCresistant sub-network, there are only two genes (PSMC2 and PSMD6) in the intersection of the two modules. Moreover, after extracting the genes associated with proteolysis from the blue module under the sensitive sub-network, no connectivity was observed among them. We also extracted the genes associated with the spliceosome pathway from the yellow module of the DCsensitive sub-network, and observed that these genes are connected within the module. Hence, the spliceosome can be suggested as an active pathway in sensitive condition as compared to the resistant condition.We performed similar functional enrichment analysis and sub-graph extraction steps to find out whether the detected active modules under the sensitive condition are enriched with BP GO terms. Table To check the hypothesis that the detected modules in the present study are possibly confounded by differences in prednisolone responsiveness in addition to differences related to GC-resistance, we checked the intersection between the list of 51 transcriptionally-regulated genes by prednisolone reported in  and fatty acid oxidation mediate glucocorticoid resistance in chronic lymphoblastic leukemia (CLL) , the hub gene of the pink module detected in the resistant sub-network, is associated with fatty acid beta oxidation, peroxisome pathway, and glucose metabolism. Also gene ABCE1 (ATP Binding Cassette Subfamily E Member 1), the hub gene of the green module detected in the resistant sub-network, is associated with glucose transport. The recent work by Chan et al.  as central effectors of B-lymphoid restriction of glucose and energy supply. More specific to MLL-rearranged infant ALL, the data reported in -positive MLL-rearranged infant ALL samples. Hence, the literature already presents possible mechanisms  by which glucose metabolism alterations and energy deprivation could be associated with MLL-rearranged infant ALL cells. Although Chan et al. did not conduct their study using MLL-rearranged infant samples, the similarities between their findings and the current study are within the general characterization of B-cell ALL with transcriptional repression of glucose metabolism and energy supply. In addition to the pink module, the brown module found in resistant sub-network is rich with genes related to ATP synthesis by chemiosmotic coupling, adding additional indication to energy deprivation in B-cell ALL.Another important active protein module observed in DCmyc proto-oncogene  that affect its interaction with ataxia-telangiectasia mutated (ATM) kinases and ability to activate p53 (a tumor suppressor protein) have been reported in human chronic myeloid leukemia patients  are essential house-keeping enzymes that provide the substrates for protein synthesis


Trauma and hemorrhagic shock can lead to acute traumatic coagulopathy (ATC) that is not fully reversed by prehospital resuscitation as simulated with a limited volume of fresh whole blood (FWB) in a rat model. Tranexamic Acid (TXA) is used as an anti-fibrinolytic agent to reduce surgical bleeding if administered prior to or during surgery, and to improve survival in trauma if given early after trauma. It is not clear from the existing clinical literature whether TXA has the same mechanism of action in both settings. This study sought to explore the molecular mechanisms of TXA activity in trauma and determine whether administration of TXA as a supplement to FWB resuscitation could attenuate the established ATC in a rat model simulating prehospital resuscitation of polytrauma and hemorrhagic shock. In a parallel in-vitro study, the effects on clotting assays of adding plasmin at varying doses along with either simultaneous addition of TXA or pre-incubation with TXA were measured, and the results suggested that maximum anti-fibrinolytic effect of TXA on plasmin-induced fibrinolysis required pre-incubation of TXA and plasmin prior to clot initiation. In the rat model, ATC was induced by polytrauma followed by 40% hemorrhage. One hour after trauma, the rats were resuscitated with FWB collected from donor rats. Vehicle or TXA (10mg/kg) was given as bolus either before trauma (TXA-BT), or 45min after trauma prior to resuscitation (TXA-AT). The TXA-BT group was included to contrast the coagulation effects of TXA when used as it is in elective surgery vs. what is actually feasible in real trauma patients (TXA-AT group). A single dose of TXA prior to trauma significantly delayed the onset of ATC from 30min to 120min after trauma as measured by a rise in prothrombin time (PT). The plasma d-dimer as well as plasminogen/fibrinogen ratio in traumatized liver of TXA-BT were significantly lower as compared to vehicle and TXA-AT. Wet/dry weight ratio and leukocytes infiltration of lungs were significantly decreased only if TXA was administrated later, prior to resuscitation (TXA-AT). In conclusion: Limited prehospital trauma resuscitation that includes FWB and TXA may not correct established systemic ATC, but rather may improve overall outcomes of resuscitation by attenuation of acute lung injury. By contrast, TXA given prior to trauma reduced levels of fibrinolysis at the site of tissue injury and circulatory d-dimer, and delayed development of coagulopathy independent of reduction of fibrinogen levels following trauma. These findings highlight the importance of early administration of TXA in trauma, and suggest that further optimization of dosing protocols in trauma to exploit TXA’s various sites and modes of action may further improve patient outcomes. Trauma induced hemorrhage is a leading cause of mortality and morbidity in both civilian and military casualties , 2. AcutRecent evidence in both animal and clinical studies has shown that ATC has a fibrinolytic component. Trauma patients show an elevation in plasma d-dimers , 8, tissTranexamic acid (TXA) is a lysine derivative that exerts anti-fibrinolytic activity by blocking the lysine binding site of plasminogen or plasmin . TXA redPlasmin causes not only fibrinolysis but also up-regulation of inflammatory responses and activation of bradykinin signaling which leads to damaged vascular integrity and increased vascular permeability . Based oIn a rat model with ATC induced by polytrauma and hemorrhage , we prevwww.criver.com) were male, and were group housed before the experiment. The light/dark cycle was 12 hours light/12 hours dark. The rats ate Laboratory Rodent Diet 5001 (www.LabDiet.com). Food and water were given ad libitum. Thirty rats were randomly and evenly assigned to three study groups: vehicle, TXA given before trauma (TXA-BT), and TXA given after trauma (TXA-AT). Our power analysis determined that a significant difference  in prolongation of PT  could be detected with groups of 6 to 7 rats at 2hr after trauma without or with FWB resuscitation [The animal study was approved by the Institutional Animal Care and Use Committee of the U.S. Army Institute of Surgical Research, and conducted in compliance with the Animal Welfare Act, the implementing Animal Welfare Regulations, and the principles of the “Guide for the Care and Use of Laboratory Animals”. All experiments were started between 0800–0900 hours in a room separated from home caging. All rats  treated with plasmin, TXA or plasmin/TXA. This study was conducted under a protocol reviewed and approved by the US Army Medical Research and Materiel Command Institutional Review Board and in accordance with the approved protocol. Human whole blood was collected from healthy volunteers with both verbal and written consent.®)), or plasmin with TXA. For combination treatment of plasmin and TXA, the plasmin and TXA were either pre-incubated for 10min (TXA-PI) or added simultaneously (TXA-S) immediately prior to assay. Whole blood without any treatment was used as a baseline (control) for all groups. Prothrombin time (PT), and activated partial thromboplastin time (aPTT) was measured by Start-4 . Coagulation Time (CT), Maximum Clot Firmness (MCF) and Lysis Index (LI) were measured by rotational thromboelastography .Coagulation properties in-vitro: human whole blood was collected in 3.8% sodium citrate. The whole blood was treated with either plasmin , TXA  was given intravenously as a bolus  before trauma  or 45min after trauma . The dose of TXA was determined from the CRASH-2 study using 1g TXA bolus administration for trauma patients (10-15mg/kg bolus based on a subject with 70-100kg body weight) [Resuscitation with FWB and administration of TXA: Rats were resuscitated 60min after completion of trauma with FWB collected from donor rats. Donors were anesthetized and cannulated as above, then exsanguinated under anesthesia. FWB was collected in CPD (citrate phosphate dextrose) and was ready for transfusion within 1hr from collection . Tranexamic acid  had not changed for three consecutive days. The wet/dry weight ratio was calculated, representing the lung water content as an indicator of lung injury. The left lobe of lung and the liver tissue (included the site of injury) were processed for immunohistochemistry as described in detail below.Tissue collection and procession: The lung and traumatized liver were harvested at the end of the experiment. The right inferior lobe of the right lung was taken for wet weight, and then kept in a drying oven at 60 Plasmin activity and D-dimer in the plasma: Plasmin activity was measured by chromogenic substrate . Prior to adding the chromogenic substrate, both plasmin standard and samples were treated with hirudin  to avoid cross reaction with thrombin. Human plasmin  was used to generate the standard curve by measuring the absorbance change over time at 405nm by a spectrophotometer . The change of absorbance over time in the samples was then measured and the plasmin activity was determined by standard curve. D-dimer was measured by ELISA kit  following manufacture’s instruction.Immunohistochemistry: The liver and lung tissues were fixed in 4% paraformaldehyde overnight, followed by 20% sucrose for 24 hours. Following fixation, the tissues were then embedded in Optimal Cutting Temperature Compound  and frozen in liquid nitrogen for cryosectioning at 5μm thickness respectively. The liver sections were treated with goat polyclonal anti-rat plasminogen  and rabbit polyclonal anti-rat fibrinogen , followed by treatment with secondary Alexa 594 conjugated anti-goat IgG, and Alexa 488 conjugated anti-rabbit IgG  respectively. Both anti-fibrinogen and anti-plasminogen antibodies did not specifically differentiate fibrinogen and fibrin or plasminogen and plasmin so that the positive stain in the section of traumatized liver tissue represented the amount of fibrinogen or fibrin (fibrin(ogen)) and plasminogen or plasmin (plasmin(ogen)) in the clot respectively. Since there is little free fibrinogen left in the clot, the positive stain of anti-fibrinogen antibody was taken to approximate fibrin content in the clot. The lung sections were treated with goat polyclonal anti-rat plasminogen and mouse anti-rat CD11b , followed by treatment with secondary Alexa 594 conjugated anti-goat IgG, and Alexa 488 conjugated anti-mouse IgG  respectively. All sections were completed with co-stained with 4',6-diamidino-2-phenylindole (DAPI) for nuclear staining and analyzed under inverted fluorescence microscopy . The plasmin(ogen) and fibrin(ogen) stain at the injured area of the liver sections were quantified using ImageJ software , Rockville, MD) to calculate the plasmin(ogen)/fibrin(ogen) ratio, which approximates the proportional amount of plasminogen binding to the fibrin and thus suggests the degree of or potential for fibrinolysis in the tissue. The ratio of plasmin(ogen)/DAPI and CD11b/DAPI in the lung were also quantified by ImageJ to present the leukocytes infiltration, and the co-localization of plasminogen/CD11b was also observed.Data analysis: The data analysis was performed by SigmaPlot . All variables were tested for normality using the Shapiro-Wilk test. For in vitro study  and in vIn-vitro assay in human whole blood: Plasmin at 250μg/ml, and 100μg/ml alone completely inhibited coagulation  and heart rate (HR)  at 30minProcoagulant activity: PT was significantly elevated from the baseline by 30min after trauma . AdminisPlasmin(ogen)/Fibrin(ogen) ratio in traumatized liver: Immunostaining for plasmin(ogen) and fibrin(ogen) was performed at the injured site in the liver for each of the three groups  and fibrin(ogen) distribution at injured site of tissue. TXA given as a single bolus either prior to trauma or at 45min after trauma  has no effect on the systemic coagulopathy status at 120min after trauma with FWB resuscitation in this model. On the other hand, TXA given at 45min after trauma, but not prior to trauma attenuates the development of acute lung injury.The in-vitro study conceptually suggested that the maximum anti-fibrinolytic effect of TXA on plasmin-induced fibrinolysis required competitive binding of TXA and plasmin(ogen) prior to clot initiation so that the plasmin(ogen)-TXA complex was not able to bind to fibrin strands to initiate fibrinolysis. Without pre-incubation of plasmin and TXA prior to initiation of clot formation, the anti-fibrinolytic effect of TXA on plasmin-induced fibrinolysis was diminished, suggesting that the degree of fibrinolysis was likely determined by the binding capacity of plasmin or plasminogen to fibrin during clot initiation. This was consistent with the in vivo study showing a reduced plasmin(ogen)/fibrin(ogen) ratio in damaged tissue of TXA-BT as compared to TXA-AT. By contrast, if TXA is given after trauma, it is not able to reverse the binding of plasmin(ogen) that has already bound to the fibrin clot to initiate fibrinolysis.Using a rat model with ATC, we previously demonstrated that giving FWB at 60min after trauma in a limited volume  is not capable of fully restoring hemostatic function  as measuThe results of this study add to the body of evidence showing that prophylactic administration of TXA is beneficial for reducing blood loss during major surgical procedures , predomiIn this study, there was no significant difference in systemically measured plasmin activity among vehicle and TXA treated groups (TXA-BT or TXA-AT), suggesting that TXA might not necessarily alter the conversion of plasminogen to plasmin by tPA in circulating blood. The plasmin activity was significantly reduced to baseline at 120min after trauma in all three groups, which was more likely due to addition of plasmin inhibitors from FWB transfusion . However, in contrast to unchanged plasmin activity in plasma, the TXA did prevent elevation of d-dimer in the plasma, especially in the group with TXA prior to trauma, suggesting that prevention of plasminogen binding to forming clot is the principle mechanism of action of TXA. Since changes in plasma fibrinolytic indices beside D-dimer did not detect the activity of TXA, it may be misleading to depend on them to guide TXA therapy clinically.This study explains the degree to which the molecular mechanism of TXA activity (namely prevention of plasminogen binding to forming fibrin stands) drives changes in clinically relevant coagulation parameters. In our model, we previously were not able to measure an increase in systemic fibrinolytic activity by ROTEM ; however+ cells) if given 45min after trauma (prior to resuscitation). We previously demonstrated that TXA reduced acute lung injury, which was associated with less vascular permeability, reduction of leukocyte and platelet infiltration, and attenuation of neutrophil activity and complement activation in the lung after trauma and hemorrhagic shock [+ leukocytes infiltrated into the lung after trauma and hemorrhagic shock were mostly plasmin(ogen) positive; and TXA given at 45min after trauma (TXA-AT) significantly reduced CD11b+/Plasmin(ogen)+ leukocytes infiltration into the lung, which was, at least in part, contributed to attenuation of acute lung injury. However, current study was not able to fully define whether the mechanism for inhibition CD11b+/Plasmin(ogen)+ leukocytes extravascular infiltration was due to the action of TXA on affecting circulatory plasminogen binding to plasminogen receptors or inhibiting plasminogen converting to plasmin by tPA on the surface of activated leukocyte after trauma followed by hemorrhagic shock. It is also interesting to notice that TXA-BT had no effect on reduction in wet/dry weight ratio and CD11b/plamin(ogen) content in the lung, which could be due to the possibility that TXA was consumed in the clot, lost during hemorrhage, or couldn’t preferably affect non-activated leukocytes prior to trauma.Our study did not identify any adverse effect of a single dose TXA administration within a very limited acute time window after trauma. There was no additional consumption of RBCs and platelets in either TXA treatment group suggesting no additional inappropriate thrombosis formation . By contrast, TXA treatment might lead to better outcomes in terms of attenuating development of acute lung injury, as characterized by a significant reduction in vascular permeability (lower wet/dry weight ratio) and leukocyte infiltration  followed by limited FWB resuscitation is not capable of correction of established systemic ATC by preventing the elevation of PT, but rather may improve overall outcomes of FWB resuscitation by attenuation of acute lung injury, as characterized by a reduction in vascular permeability and leukocytes infiltration. TXA given prior to trauma reduced levels of fibrinolysis at the site of tissue injury and circulatory d-dimer levels, and delayed development of coagulopathy independent of reduction of fibrinogen levels following trauma, which explains the effectiveness of TXA given prior to elective surgery in reducing bleeding but does not fully explain the observed clinical benefit in trauma patients. However, this study suggests that, without any other intervention, a single dose of TXA administered immediately at the point of injury is thought to be capable of inhibition of fibrinolysis in the clot, which is considered beneficial in reducing bleeding from acute surgical procedures after trauma. On the other hand, the reductions in observed biomarkers of tissue injury in this study and others suggest that, at least within one hour timeframe observed in CRASH-2 and in this rodent study, TXA may provide clinical benefit through mechanisms other than simply clot stabilization.S1 FigThere was no significant different of the change in PT, aPTT and fibrinogen between the groups of Vehicle (n = 10) and TXA-AT-0min (n = 4). TXA-AT-0min: TXA was administered immediately after completion of trauma. #: significant difference compared to BL; &: significant difference compared to 30min.(TIF)Click here for additional data file.S2 Fig1, &1 and $1: significant difference compared to baseline (BL); #2, &2 and $2: significant difference compared to 30min.The hematocrit was significantly declined at 30min and restored at 120min after trauma (n = 10 per group). The hematocrit was not significant different among the groups. #: Vehicle; &: TXA-BT; $: TXA-AT. #(TIF)Click here for additional data file.S3 FigLI30 and LI60 were measured by ROTEM (EXTEM) at 2hr after trauma. LI30 or LI60 was not significant different among the groups of Sham (n = 3), Non-R (n = 10), and FWB (n = 10). Non-R: Trauma/hemorrhage without resuscitation; FWB: Trauma/hemorrhage with fresh whole blood resuscitation. *: Significant difference between LI60 and LI30.(TIF)Click here for additional data file.


We report a case of meningioma with both secretory and lipomatous features in an advanced middle aged female patient with a 3-month history of headaches and convulsions. Radiological findings are revised and compared to other reported cases in the literature. Meningioma is a central nervous system tumor arising from the arachnoid cells present in the arachnoid mater. It is the most common primary tumor of the brain; 33.8% of all primary central nervous system tumors are reported in the United States between 2002 and 2006 . SecretoA 65-year-old female patient was admitted to the hospital complaining of headaches and convulsions over the previous three months. The patient was conscious and alert with stable vital signs. Computer tomography (CT) scan showed a well-defined left-temporal extra-axial lesion of mixed density, predominantly hypodense (fat density), causing calvarian bone hyperostosis with a localized mass effect on the adjacent temporal lobe. Significant vasogenic edema with associated effacement of the left hemispheric sulci, compression of the ipsilateral ventricle, early left uncal herniation, and a rightward midline shift also were noted. MRI showed a dural-based focal mass in the left-temporal lobe exhibiting a mass effect on the adjacent parenchyma and a large area of perifocal edema (delete vasogenic) causing compression of the ipsilateral ventricle and approximately 6mm midline shift towards the right. Evidence of a high fat component (high T1 and T2 mass) showing avid enhancement with a dural tail sign was present Figures . As a reUpon examination in our laboratory, we found a firm, well-circumscribed, white/tan mass attached to the dura. The cut surface showed yellowish fatty tissue interwoven with firm fibrous tissue. Microscopically, the tumor was composed of meningotheliomatous tumor cells with classic whorls in addition to hyaline inclusion bodies scattered throughout the examined tissue, representing the secretory component Figures . These hAlthough meningothelial meningioma is quite common, the presence of secretory and lipomatous features in the same tumor is exceptional and deserves studying and reporting. Secretory meningioma is identified radiologically by predominantly hypo-to iso-signal T1 weighted and hypersignal T2 weighted (T2 flair) MR images. These findings have been related to soft tissue consistency and the severe peritumoral brain edema. The predominant finding on MR images is a strongly enhanced, homogeneous tumor. Dai-Jun Wang and his colleagues call this enhancement, “xenon light” like enhancement comparable to the enhancement of secretory meningiomas . HistoloOur case demonstrates both secretory and lipomatous elements within conventional meningioma, as demonstrated by both radiological and pathological studies. It shows mixed density on CT scan. MRI revealed evidence of both peritumoral brain edema and fat components. The key features of our case in comparison with the previous reported cases are summarized in the table . Each of


During the evolution of multicellular eukaryotes, gene duplication occurs frequently to generate new genes and/or functions. A duplicated gene may have a similar function to its ancestral gene. Therefore, it may be expected that duplicated genes are less likely to be critical for the survival of an organism, since there are multiple copies of the gene rendering each individual copy redundant. In this study, we explored the developmental expression patterns of duplicate gene pairs and the relationship between development co-expression and phenotypes resulting from the knockout of duplicate genes in the mouse. We define genes that generate lethal phenotypes in single gene knockout experiments as essential genes. We found that duplicate gene pairs comprised of two essential genes tend to be expressed at different stages of development, compared to duplicate gene pairs with at least one non-essential member, showing that the timing of developmental expression affects the ability of one paralogue to compensate for the loss of the other. Gene essentiality, developmental expression and gene duplication are thus closely linked. It can generate new genes , retaining sequence similarity to the ancestral gene, but performing new biological functions3. Duplication events can be small scale, involving regions containing a single gene, or encompass the entire genome. Evolutionary pressures can cause duplicated genes that are no longer useful to the organism to acquire loss-of-function mutations and become non-functional pseudogenes4. For a gene to be retained in the genome following duplication, it has been proposed that the gene must undergo neofunctionalisation  or subfunctionalisation 7. The preservation of duplicate genes may also be driven through functional conservation8  and neosubfunctionalisation10 . Subfunctionalisation can arise from partitioning of the expression pattern of duplicated genes, such that individual duplicate genes are expressed within a subset of the temporal and morphological expression domains of the ancestral gene15. A study of duplicated genes in the human genome identified subfunctionalisation of gene expression as a rare event, which occurs after the duplicated genes have been segregated to different chromosomal locations and acquire divergence in their expression patterns16.Gene duplication is a key evolutionary event in multicellular eukaryotes19, although this phenomenon may be rare. Moreover, genome-wide gene knockdown or knockout experiments in Caenorhabditis elegans21 and Saccharomyces cerevisiae17 showed that duplicate genes are considerably less likely to be essential than singletons (single-copy genes). However, studies of mouse knockout phenotypes reported that the proportion of essential genes between singletons and duplicates is similar; therefore, mouse duplicate genes are just as essential as singletons23. Duplicate gene essentiality was attributed to connectivity in protein-protein interaction networks (PINs), based on the finding that mouse duplicate genes are highly connected within PINs, whereas duplicated yeast genes, which are less likely to be essential, are not highly interconnected within PINs22. The over-representation of mouse developmental genes in the dataset of genes that have been knocked out has also been proposed as an explanation for the high frequency of essential duplicate genes in mouse knockout experiments, since developmental genes would be more likely to generate a lethal knockout phenotype24. Further studies have reported that recently duplicated genes are under-represented in the mouse knockout dataset, but after correction for this bias singletons were more likely to be essential than duplicates26, and within a given evolutionary age group, singletons are more likely to be essential27.Given that selective pressures will influence gene retention within a genome after a duplication event, it may be assumed that duplicates retained as active genes each perform functions that are required within the organism. Prior studies reported that the functional loss of deleting a duplicate gene could be compensated by the existence of its close paralogue in the same genome if the paralogue retains overlapping functions and expression patterns28. Highly expressed developmental genes were more likely to be essential, suggesting a positive association between singleton developmental genes and essentiality28. However, to our knowledge no previous studies have examined the developmental co-expression of duplicate gene pairs and the correlation of expression patterns with essentiality phenotype in mouse knockout experiments. When we examined the phenotypes that result from published mouse knockout experiments29, we found that there are duplicate gene pairs whereby each member of the pair is individually essential , duplicate pairs where one member is essential and the other is not, and duplicate pairs where neither member is essential. We hypothesised that developmental co-expression patterns are an important factor in determining the essentiality status of duplicated genes in mouse knockout experiments, since genes with overlapping developmental expression patterns are more likely to provide functional compensation for one member of a duplicate gene pair. In this study we analyse the mouse knockout data in the context of gene duplication status. We identified mouse duplicate gene pairs based on protein sequence conservation, and determined the essentiality status of these duplicated genes from published knockout experiments. Using mouse EST expression data covering 13 developmental stages, we discovered that duplicate pairs containing two essential genes tend to have greater divergence in developmental expression patterns than duplicate pairs comprised of two non-essential genes, demonstrating that developmental co-expression is an additional factor that contributes to the essentiality status of duplicated genes in the mouse.Genes expressed during early mouse development were more likely to revert to a single copy following whole genome duplication events22, we did not include genes causing infertility within our essential gene dataset, but have analysed genes causing infertility as a separate group. From the knockout mouse phenotype data in the Mouse Genome Informatics (MGI) database30, we identified a total of 1,301 essential and 3,451 non-essential mouse genes29. In agreement with other reports of mouse knockout phenotypes32, our dataset shows that non-essential genes are more common than essential genes in the mouse29  in mouse knockout experiments. Because we wished to test the hypothesis that developmental co-expression would be a key factor to determine whether or not deletion of a duplicate gene produces an embryonic lethal phenotype, we defined essentiality based on the requirement for the gene in embryonic survival. Thus, in contrast to other studies of essential genes27. Previously it was reported that the mouse knockout literature is highly enriched with evolutionarily older genes, thus underrepresenting recently duplicated genes25. To determine if this bias persists in the knockout dataset we utilise in this study, we compared the evolutionary ages of genes assayed in mouse knockout experiments to the ages of genes in the mouse genome as a whole  are less frequent than those that are singletons (33.10%) . Non-essential genes are more likely to be duplicates  from UniGene EST data33 for all essential and non-essential genes in our datasets across 13 stages of mouse development. We found that a greater proportion of genes expressed at a particular stage of development are singletons rather than duplicates  when knocked out individually (E-E), those that are both non-essential (producing a viable phenotype) when knocked out individually (NE-NE), and those where one member is essential and one is non-essential (E-NE). We hypothesised that overlapping developmental expression patterns (co-expression) could be an important factor in determining the essentiality of duplicate gene pairs, because genes that are expressed at different times are less likely to compensate for each other if one is knocked out. Therefore, we analysed duplicate pair developmental gene expression patterns to test our hypothesis.34. We computed the degree of developmental co-expression between each mouse duplicate gene and its paralogue from expression data across 13 developmental stages using the Manhattan distance method . Because we identified the genes that are members of duplicate pairs in two ways, we wished to determine if the method of duplicate identification had an effect on the outcome of our study. Co-expression of the duplicate gene pairs identified from the Blast search only  with E-NE pairs in between. Analysing mouse duplicate gene pairs defined by being orthologues of human duplicate gene pairs34 confirmed these conclusions: NE-NE duplicate gene pairs are more likely to have similar developmental co-expression patterns, as calculated using the Manhattan distance .Larger Manhattan and Euclidean distances indicate lower co–expression values. We observed that E-E gene pairs tend to have higher distances and thus lower co–expression compared to NE-NE and E-NE pairs -(NE-I) duplicate pairs. (NE-I)-(NE-I) duplicate gene pairs were obtained after excluding all the I-I pairs from the total NE-NE pairs. We observed that I-I duplicate pairs tend to have higher co–expression compared to E-E gene pairs and lower co-expression than (NE-I)-(NE-I) pairs . Analysis of developmental co-expression of the duplicate gene pairs identified by the Blast search confirmed that co-expression values of I-I duplicate pairs tend to fall in between of E-E and (NE-I)-(NE-I) co-expression values . Furthermore, co-expression analysis of all mouse orthologues of human duplicate gene pairs34 showed that E-E duplicate pairs are more likely to have greater divergence of expression . Since genes associated with infertility may be required at different stages of an organism’s life (e.g. puberty) than developmental essential genes, the requirement for each paralogue in a pair of duplicated infertility genes to have overlapping developmental expression patterns may be relaxed.Since genes associated with infertility have been considered essential from an evolutionary perspectiveion Fig.  compared34. We found that both SSD and WGD genes followed the trend that E-E duplicate pairs tended to have more divergent developmental expression patterns than NE-NE gene pairs . In total 194 E-E, 520 E-NE and 343 NE-NE whole genome duplication (WGD) mouse gene pairs were found within our dataset by identifying mouse duplicate gene pairs which are the orthologues of previously reported human duplicate gene pairs27. In agreement with prior studies27, we have found that mouse singleton genes are more likely to be essential than mouse duplicate genes. Although others have found that duplicate genes are as essential as singletons23, the inclusion of genes causing infertility as essential genes in their datasets may have influenced the relative proportions of essential singletons and duplicates. It was previously predicted that when the mouse knockout experimental dataset increased it would be confirmed that singletons are more likely to be essential as compared to duplicated genes24. The increased size of the mouse knockout experimental dataset since 2007 (approximately 1.5 times larger now than 2007) confirms this prediction, as we have identified that a greater proportion of singleton rather than duplicate genes are essential   were obtained from published reports27. This list of infertility causing genes was compared with our essential and non-essential genes lists. Genes within our NE dataset that were annotated as I in other publications were removed from the NE dataset for analyses  as those that cause lethality prior to postnatal day 1 in a single gene knockout (targeted deletion) experiment. We used the prenatal (MP:0002080), perinatal (MP:0002081), and postnatal (MP:0002082) lethal mouse knockout phenotype annotations from the MGI database40 on our local computer to detect mouse duplicate gene pairs within our own duplicate datasets. We identified three categories of duplicate gene pairs: (i) essential-essential (E-E), (ii) non-essential-non-essential (NE-NE), and (iii) essential-non-Essential (E-NE). Two all-against-all BLAST searches were performed on the essential duplicate and non-essential duplicate datasets to generate the E-E and NE-NE gene pairs respectively. The genes in the essential duplicate dataset were then searched against the database of the non-essential duplicate dataset using BLAST to generate the E-NE gene pairs. In accordance with prior studies34, we identified duplicate partners of a mouse gene within our datasets by considering sequence similarity scores and E-values (<10−7) from the BLAST search. The best match from the BLAST output was then considered to be the closest paralogue for a mouse duplicate gene. In addition, we used human duplicate gene pairs listed in Makino and MyLysaght34 as another means to define parologous genes. Mouse orthologues of these human duplicate genes were obtained from the Ensembl BioMart data-mining tool41 (http://www.ensembl.org/biomart/martview/) with the Ensembl release 75 dataset of the Homo sapiens genes (GRCh37.p13). We included only one-to-one mouse orthologues of these human duplicate genes.We used Ensembl (release 75) gene trees of mouse gene families to categorise and label all mouse protein-coding genes into two groups: singletons and duplicates. Essentiality status was assigned to these singleton and duplicate genes by analysing their knockout phenotype annotations from the MGI database. Genes without confirmed essentiality status from MGI were removed from the dataset for subsequent analysis. This resulted in four datasets: (i) essential singletons, (ii) non-essential singletons, (iii) essential duplicates, and iv) non-essential duplicates. The paralogues of the mouse genes present in the mouse essential and non-essential duplicate datasets were then identified, by measuring protein sequence similarity based on BLAST search. We downloaded the BLAST+ software package from the NCBI database and performed Blast search34. The rest of the mouse duplicate genes in our datasets were classified as small–scale duplicates.A mouse duplicate gene was further classified as either a small–scale duplicate (SSD) or a whole–genome duplicate (WGD). A gene was defined as a WGD if its human orthologue was found within the 9,059 human WGD duplicate pairs listed in Makino and MyLysaght30 (http://www.informatics.jax.org/phenotypes.shtml). All essential and non-essential genes that we examined29 in this study were also included in the whole mouse gene dataset. Mouse genes that were not classified as either essential or non-essential were classified as genes with unknown essentiality status.All genes in the mouse genome were obtained from the Mouse Genome Informatics (MGI) database29. We assigned two evolutionary ages to each duplicated gene in our datasets: the age of the most recent duplication (MRD) event and the age of the evolutionarily most distantly related species, i.e., the age of the duplicate common ancestor (DCA) that has an identified orthologue of that gene. For singletons, we used the age of their single common ancestor (SCA). Evolutionary ages are reported in millions of years (MYA).Evolutionary ages of mouse protein coding genes were retrieved from Ensembl (release 75) gene trees, which represent the evolutionary processes by which genes diverged from their common ancestors, as previously described29, raw expression data of mouse essential and viable genes were obtained directly from the NCBI UniGene database33 as expressed sequence tag (EST) clusters using UniGene IDs. We extracted EST clusters from 13 developmental stages: oocyte, unfertilized ovum, zygote, cleavage, morula, blastocyst, egg cylinder, gastrula, organogenesis, fetus, neonate, juvenile and adult. Since the total number of ESTs for a particular gene varies greatly between different developmental stages, the raw data in UniGene have been normalised to get gene expression in the form of transcripts per million (TPM), and we utilised the TPM values in this study. Every gene with a minimum Transcript per Million (TPM) value of 1 was defined as expressed at a particular stage. Eq. ith gene at jth developmental stage33.Using a methodology we have previously describedTPMs were also transformed to their corresponding log values using Eq. TPMs were also normalised within the range  using Eq. We used the Euclidean and the Manhattan distance methods to calculate numerical scores representing gene co-expression. These numerical distance values are used to compare gene expression between every gene pair during development. If entclass1pt{minima42 method was used to test the co-expression patterns of duplicate gene pairs. This statistical test was used because our co-expression datasets did not show a normal distribution. This statistical test was carried out using the statistical software package SPSS43 version 22. The Chi–square (χ2) test was carried out to investigate whether singleton and duplicate genes are differentially expressed across different developmental stages. The null hypothesis tested by the Chi-square test was “the frequencies of singleton and duplicate genes expressed at one developmental stage are equal.” To calculate expected values for each developmental stage, the total number of genes expressed at that stage  was divided by the total of all genes in our dataset and the relative proportion of singleton and duplicate genes expressed at that particular stage was calculated. The total number of singletons in our dataset was then multiplied by this gene proportion value to determine the expected singleton frequency at that stage. The same procedure was used to calculate the expected frequency of duplicate genes. Thus by simple proportions from the totals we found an expected number to compare each observed number. We then used the observed and expected frequencies to calculate the Chi-square test statistic. The Bonferroni correction44 was applied to calculate corrected p–values.The nonparametric Kruskal-WallisSupplementary InformationSupplementary Dataset


Innate immune cells including macrophages, dendritic cells, and natural killer cells are key mediators of the radiation-induced immune response. They regulate the sensing of radiation-mediated damage and subsequent radiation-induced inflammation. Given the importance of innate immune cells as determinants of the post-radiation anti-tumor immune response, much research has been devoted to identify ways to both enhance the innate immune response and prevent their ability to suppress ongoing immune responses. In this review, we will discuss how the innate immune system shapes anti-tumor immunity following radiation and highlight key strategies directed at the innate immune response to enhance the efficacy of radiation.Radiation continues to play a major role in the treatment of almost every cancer type. Traditional radiation studies focused on its ability to damage DNA, but recent evidence has demonstrated that a key mechanism driving the efficacy of radiation  Radiation (RT) continues to play a major role in the treatment of cancer with more than 50% of all cancer patients receiving RT sometime during their treatment course . TraditiEarly work from Stone et al. demonstrated that mice lacking T and B cells required more RT to control the same size tumor compared to immune intact animals . Other gcontext for an immune response through a specialized set of receptors designed to distinguish when a given target poses a danger and should be eliminated by the immune system  cells provide the e system . Upon ree system . Cells oe system . Thus, gAmong cancer therapies, RT possesses unique biology as a result of its ubiquity in the environment. Given the omnipresent nature of radiation from natural sources such as naturally occurring isotopes and cosmic radiation, all organisms from bacteria to humans have had to develop methods to deal with cells damaged by irradiation. Activation of the innate immune system is one of those methods and likely serves as one of the main mechanisms driving the extraordinary efficacy of RT. Evidence of the importance of innate immunity in the response to RT come from studies that demonstrate reduced efficacy for RT in preclinical models of cancer which are deficient in innate immune cells including NK cells , macrophAs previously mentioned, one of the primary functions of the innate immune system is to regulate the initiation of an immune response. In the sterile environment of most tumors, innate immune cells initiate an immune response following detection of signals that indicate the presence of cell damage or danger. Radiation activates the innate immune system by inducing both tumor and normal cells to release specific danger signals that leads to activation of multiple inflammatory pathways in innate immune cells. These danger signals include high-mobility group B-1 (HMGB1), calreticulin, complement, and cytosolic DNA all of which act upon receptors on innate immune cells and lead to release of mediators such as cytokine and chemokines that trigger an immune response –30 Figu.The HMGB1 protein is a nuclear protein that is released by damaged cells and binds to toll-like receptor 4 (TLR4), the main receptor for lipopolysaccharide (LPS). Thus, HMGB1, like its bacterial counterpart LPS, can stimulate macrophages and dendritic cells which express high levels of TLR4 leading to cytokine production and upregulation of molecules  that lead to activation of T cells. It was one of the first inflammatory molecules identified in the setting of RT. Apetoh et al. demonstrated that RT releases HMGB1 and that depletion of HMGB1 or loss of TLR4 reduced the efficacy of RT . Interes−/−)  , 41. Oth−/−) .*3) did not induce higher levels of Trex1, rather it induced more IFN-β production and activation of Batf3-dependent DCs, leading to enhanced anti-tumor T cells responses. The induction of Trex1 by a single fraction of high-dose radiation dose but not with a short-course of fractionated radiation suggests that it may be essential to fractionate the radiation doses to improve the immunogenicity of RT and its synergy with immunotherapy. Preclinical studies and a recently reported clinical trial support this notion demonstrating synergy between fractionated RT and anti-CTLA (*3) induced an abscopal systemic immune response when given in conjunction with anti-CTLA-4 leading to prolonged/sustained tumor regression. Fractionated lower doses (8 Gy*3) induced the production of IFN-I stimulated genes in mice followed by enhanced number of CD8α+ tumor infiltrating DCs (with high CD70) within the tumors and IFNβ in TSA cells in vitro but interestingly 20 Gy did not in part through in the induction of Trex1 by high-dose single fraction RT. Trex1 knockdown in TSA cells restored Type I interferon production with high doses of radiation (20 Gy*2) suggesting that induction of Trex1 is a key mediator of RT-induced inflammation. Thus, to ensure an optimal anti-tumor responses, short-course fractionated RT may need to be employed in part to prevent Trex1 induction leading to optimal sensing of the cytosolic DNA produced by RT.Recent observations have shown that a DNA exonuclease called 3′ repair exonuclease 1 (Trex1) regulates RT-induced activation of the cGAS-STING-IFN pathway. Using paired RT-sensitive and resistant orthotopic breast cancers it was revealed that RT-sensitivity depends in part on Trex1 levels. Mechanistically, Trex1 cleaves the DNA that accumulates in the cytosol following RT thereby abrogating IFN-β production through the STING-cGAS pathway. Thus, high levels of Trex1 prevent radiation-induced Type I interferon induced inflammation thereby reducing the efficacy of RT . Interesnti-CTLA . In the By sensing an array of danger signals produced by irradiated cells, innate immune cells serve as the primary sentinels of the body to identify cells that have been damaged by radiation Figure . As suchMost of the strategies directed at augmenting the innate immune response have focused on increasing signals that mimic the danger signal sensed by the innate immune system. In preclinical models, these strategies have shown much promise and are beginning to be tested clinically. The oldest and most common strategy that has been utilized to enhance the early innate immune response typically targets toll signaling. While RT naturally leads to release of HMGB1 which binds TLR4, other toll agonists have also been utilized to augment the inflammatory response triggered by RT. For example, addition of CpG, a TLR9 agonist, showed synergy when combined with RT  in a murOther strategies to improve innate immunity have focused on the calreticulin pathway. As mentioned previously, calreticulin expression is induced by RT and is an important signal for phagocytosis by macrophages . This prOne of the most promising newer strategies to augment the RT-mediated activation of innate immunity has been to target type I interferon production through the use of STING agonists. Mostly structured as cyclic dinucleotides, multiple groups have shown the efficacy of STING agonists in combination with chemotherapy and various immunotherapies –55. STINWhile limited clinical information exists, there is substantial preclinical data suggesting that augmenting the innate immune activation triggered by RT can significantly enhance the anti-tumor immunity produced following RT Figure . However−/− mice consistent with other observations demonstrating the critical role of Batf3 DC in regulating RT-induced anti-tumor immune responses . Activation of the adaptive immune system requires maturation of dendritic cells or macrophages into antigen-presenting cells (APC) which requires appropriate expression of MHC molecules and co-stimulatory signals. Interestingly, RT has been shown to upregulate MHC class I and stimulate presentation of unique antigens , 8, 58 aesponses –62. In aesponses , 64.Following innate recognition, one of the first proinflammatory molecules activated by RT is complement, soluble effector proteins that are produced by and regulate innate immune cell function , 66. SurIn addition to expression of complement, RT has been shown to increase the expression of a number of cytokines and chemokines. Aside from the previously mentioned type I interferons, RT has been shown to induce immune cells within the tumor including TAMs and CD8+ T cells and NK cells and others to produce inflammatory cytokines including tumor necrosis factor alpha (TNF-α) , interleThrough the expression of various inflammatory molecules, the innate immune system translates the danger signals they sense in irradiated tissue into an anti-tumor immune response. Multiple strategies have been employed combining RT with various agents in attempt to enhance the innate immune response to RT as we discuss below.In addition to targeting the danger signaling induced by immunogenic cell death, multiple groups have sought to make the downstream responses of the innate immune cells more productive. Strategies to enhance the magnitude and efficiency of antigen presentation and inflammation induced by RT are currently being explored.The primary target of the strategies to augment the innate immune response following RT has been focused on dendritic cells as they are the primary APC within tumors. Several groups have shown that they can improve the response to RT in murine models and early human trials by increasing the growth and differentiation of dendritic cells. One way to increase the number of DC is the cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) which has been shown to be a crucial pathway for the growth, maturation and migration of DC , 84. SevAnother cytokine for DC-specific growth similar to GM-CSF that has been shown to enhance the response to RT is the FS-like tyrosine kinase 3 ligand (FLT3L) –90. FLT3Instead of encouraging the creation of more or better DCs, others have taken a more direct approach and have tested combining dendritic cell vaccines with RT , 95. In While none of these strategies have had tremendous clinical responses to date, the advent of newer immunotherapy approaches particularly those targeting tumor immunosuppression such as checkpoint inhibitors have generated renewed interest in RT and DC vaccination combinations.The recent success of agents known as checkpoint inhibitors that block immunosuppressive pathways within tumors highlight the importance of targeting the immunosuppressive tumor microenvironment to foster anti-tumor immunity. Cells of the innate immune system particularly macrophages in conjunction with tumor cells participate in establishing the suppressive environment of tumors. Macrophages play a complex dual role in the context of tumor immunobiology. They have pro-inflammatory roles as outlined above, but more often exhibit a pro-tumor phenotype that suppresses anti-tumor immunity and supports tumor growth , 99. In With the recent recognition of the need to alleviate the intrinsic tumor immunosuppression to allow anti-tumor immunity to progress, much activity has been devoted to targeting the pathways and cells that mediate immunosuppression. Interestingly, many of the cellular targets are innate immune cells such as macrophages. Since RT generates both an anti-tumor immune response and the corresponding suppressive immune control mechanisms, combinations of RT with agents that target intratumoral immune suppression are thought to allow for an enhanced anti-tumor immune response following RT. Preclinical models strongly support this notion and clinical data is just emerging that suggests that this strategy may also be efficacious in the clinical setting.One of the most successful regimens targeting intratumoral immunosuppression has been targeting immune suppression with checkpoint inhibitors which are agents that target the PD-1/PD-L1 and CTLA-4 pathways. Innate immune cells are one of the key sources of signal for the PD-1/PD-L1 pathway with dendritic cells and macrophage serving as one of the primary, non-tumor sources of PD-L1 in the tumor microenvironment. Thus, the underlying mechanism of checkpoint blockade likely involves disrupting the effects of innate immune cells on immune response in tumors. To date, an increasingly large amount of data has demonstrated the efficacy of using checkpoint inhibitors in the preclinical and clinical setting in combination with RT. As several excellent recent reviews have examined the role of combining checkpoint blockade with RT in detail, we will not discuss combinations with checkpoint blockade further here though it should be recognized that including one of these agents as a part of any immune-directed therapeutic regimen will be an important consideration for the foreseeable future , 107.Beyond checkpoint blockade, macrophages serve as the main source of immunosuppression within the tumor microenvironment following RT. As evidence of the importance of macrophages, various studies have revealed a strong negative correlation between the presence of macrophages and survival in various solid tumors including breast, colon, bladder, and lung cancer –12, 108.Given the successful preclinical models showing enhanced responses to RT in combination with agents that target macrophages including CSF-1R inhibitors and CD11b, several trials are currently underway to test the validity of this observation in human trials. Based on the work of Stafford et al. a trial using the small molecule inhibitor of CSF-1R  in newly diagnosed glioblastoma in combination with standard chemotherapy and RT was opened and accruing . Another group is also testing the CSF-1R inhibitor in combination with concurrent standard dose RT and androgen deprivation for localized unfavorable risk prostate cancer . Interestingly, agents targeting tumor-associated macrophages such as the CCL2 inhibitor carlumab have had limited effect as single-agents  and in fIn order to preserve the macrophage capacity to activate anti-tumor immunity while preventing their differentiation into pro-tumor, immunosuppressive phenotypes, several groups including our own have examined the potential of targeting the pathways that lead to pro-tumor phenotypes in macrophages including IL-4 , TGF-β , and TyrThe findings from these preclinical studies targeting macrophage phenotype in combination with radiation are just beginning to be explored in the clinical trial setting. One promising target is TGF-β a cytokine for which several inhibitors have been developed. Though TGF-β has pleiotropic effects, its upregulation post-RT is one of the primary drivers of immunosuppression in the irradiated tumor microenvironment particular effects on the development of regulatory macrophages and T cells. Using an agent that binds all isoforms of TGF-β  in combination with SBRT for patients with metastatic breast cancer , Formenti et al. found that the highest dose combination led to improved survival and systemic immune responses compared to lower doses . Other cThe innate immune system plays a critical role in regulating the response to RT from the recognition of RT-mediated tissue damage to shaping of the RT-mediated anti-tumor immune response. Strategies to augment the innate immune response have met with varying success clinically, however promising new strategies based on our improved understanding of innate immune biology such as STING agonists, adjuvants to enhance DC activity and anti-macrophage agents will undoubtedly shape future therapeutic approaches to combination therapies with RT.TD and SS conceived this article. TD, RH, and SS wrote the article 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.


In vitro crystallization of struvite was performed in the presence of two bacteria that were originally isolated from the kidney stone patients. Morphological evaluation was carried out using SR-μCT as well as FESEM, XRD and FT-IR. Characteristic internal 3-D morphology and porosity of the stones were studied. For comparison, patient derived struvite stones were used. From the results obtained, we report that the presence of bacteria enhances the crystallization process of struvite in vitro. A series of time-resolved experiments revealed that struvite crystals experienced a significant morphologic evolution from pin pointed structure to X-shaped and tabular morphologies. These X-shaped and unusual tabular habits of struvite resembled biogenic morphologies of struvite. SR-μCT showed similarities between the patient derived and the in vitro derived struvite crystals. In conclusion, these experiments revealed that the bacteria play a major role in the specific morphogenesis of struvite and can able to control the nucleation, modulate crystalline phases, and shape of the growing crystal.Pathological biomineralization in the urinary system leads to urolithiasis. Formation of kidney stones involves a series of events during which they undergo morphological and mineralogical changes. We investigated the mineralization of biogenic struvite ( It is associated with infection caused by urease-producing microorganisms . Th. Th19]. software . Quantitin vitro struvite crystallization. Based on 16S rRNA gene sequencing, the isolates YU22S and YU27S were identified respectively as P. aeruginosa and E. cloacae. The NCBI GenBank accession numbers for the sequences are MH021663 and MH021673 respectively. The cultures were deposited at Microbial Culture Collection Center  with culture collection numbers; YU22S as MCC 3101 and YU27S as MCC 3111.Two urease positive strains namely, YU22S and YU27S isolated from the stone culture of the patients with struvite stones were used for The early stage (10 min- 48 h) crystallization of struvite revealed by the initial experiment is given in The time-resolved experiments revealed the growth of small dendritic type struvite crystals immediately after the addition of supernatant solution, at the gel-liquid interface. The initially grown pinpoint crystal tubes tend to nucleate randomly throughout the test tube and on the gel surface . In the P. aeruginosa and E. cloacae X-shaped dendrite crystals were observed the end of the fifth day, with high accumulation of crystals compared to control. The aggregation of crystals was rapid in the presence of bacteria compared to the control sets. At pH greater than 9, the hopper like crystals were also observed coexisting with dendrite-like crystals.At the end of third-day, the crystals grown in all the conditions appeared as single crystals exhibiting coffin-like habit with well-defined planes. In the presence of At the initial stages of struvite mineralization, crystals displayed well-defined faces . The arrThe percentage porosity showed a distinct variation at different stages of struvite formation in the presence and absence of bacteria . The meaThe FESEM images from single struvite crystals showed well-defined faces, and the porous nature of struvite was distinctly seen in all the struvite crystals . The por-1 due to the absorption of PO43- (v3 mode) antisymmetric stretch. The absorption peaks at 1469, 1435 and 1400 cm-1 attributed to (v4) NH4+ antisymmetric bending were also present.The crystals showed characteristic IR spectrum with a strong peak at 1010 cmThe XRD pattern revealed the appearance of struvite crystallizes in the orthorhombic Pmn21 space group . Representative XRD patterns for the crystals obtained with and without bacteria are shown in in vitro in the presence of two urease positive kidney stone associated bacteria. Presence of bacteria during early crystallization influenced the morphology and growth pattern of crystals. Previous study from our group reported that struvite stones can be present as pure type or along with other minerals such as calcium oxalate and calcium phosphate [in vitro [Proteus mirabilis has been widely known for its role in biogenic struvite mineralization [P. aeruginosa and E. cloacae are limited because majority of these strains are not urease producing.The study revealed the events during the crystallization of struvite hosphate . Struvitin vitro , 22. Amolization . Howeverin vitro struvite can exhibit various morphologies like pyramidal type, prismatic type, coffin shaped, needle type and dendritic type. Large dendritic structures of struvite can be formed rapidly in short time and can easily retain in the urinary tract. It can damage the epithelium of internal renal walls and enhance the crystal growth and also can easily trap bacteria [Precise information of micro-structure during the early stages of struvite is also limited. To best of our knowledge, the present study is the first to report on struvite mineralization using these bacteria and to report the morphological transformation during the early stages crystallization using SR-μCT based imaging technique to examine the nature of bacterially induced struvite crystals. Struvite stones formed in the human kidney tend to be staghorn-like structures; and similar dendrites also appeared in bacterially induced mineralization experiments . Chauhanbacteria .Urease producing bacteria cause ammonia-induced cytotoxicity of the renal epithelium, and the increase in pH triggers the precipitation of struvite in the urinary tract . The pH P. mirabilis induced struvite crystals also show the similar morphology and habits [4+ groups, while (00Ῑ) face is rich in PO43- groups. Present results also suggest the intrinsic dipole-dipole interactions from the arrowhead-shaped crystals that drive them to orient towards the crystallographic directions to form quadrangular tubular architectures.Our time-resolved crystallization experiments suggest that in the presence or absence of bacteria, a variety morphological evolution exist and these mainly involve the formation of pin pointed-like crystals through the prismatic type to rectangular platelet type crystals, X-shape, and the flatter tabular structure with a blurred X on its surface. These characteristic X-shapes have been reported by several researchers when struvite is crystallized in the presence of urease-producing bacteria , 28. P. d habits . After td habits . Prywer d habits  suggeste2+ and Mg2+ ions to promote crystallization process [In addition to urease, bacteria can produce other metabolites and organic macromolecules that may also contribute to the promotion of crystal growth. In the absence of bacteria, relatively low amount of crystals formed, and the crystals formed in the presence of bacteria were sometimes relatively complex. Polysaccharides and proteins present in the extracellular matrices of bacteria also play a crucial role in the struvite structuration . Bacteri process . Also, iMorphological evolution of struvite crystals as observed from SR-μCT revealed that, in the presence of bacteria, struvite crystal exhibit coffin-like morphology and these are the typical hemimorphic morphology, i.e., the two ends of a crystallographic axis are not related by symmetry. It is suggested that the biogenic X-shaped and unusual tabular struvite may represent two different growth stages . We founP. aeruginosa and E. cloacae play a major role in the specific morphogenesis of struvite and these results demonstrate that the bacteria can control the nucleation, modulate crystalline phases and shape of the growing crystal. The biogenic struvite initially displayed a small arrowhead-shaped morphology subsequently evolving into large X-shaped tabular structures. Presence of bacteria can also induce transformations in crystal morphology.In conclusion, a series of time-course experiments with and without bacteria revealed that urease-producing bacteria such as S1 Fig(TIF)Click here for additional data file.S2 FigSR-μCT images of patient derived struvite showing the layered pattern and void spaces with cracks inwards from the outer surfaces (a) projection image, (b) 2-D slice of projection.(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


The American College of Surgeons National Quality Improvement Program started a “Geriatric Pilot” in January 2014. This project has already collected 19 additional older adult specialty variables in more than 60,000 patients undergoing operations. Twenty-six medical centers participate from across North America. The variables collect information in the domains of cognition, function, mobility and decision-making. Variables are collected in both the pre- and post-operative settings. It is clear that the quality of surgical care cannot be limited to the immediate hospitalization. The pilot has recently expanded its use of longer-term outcomes and has begun collecting 30-day outcomes of functional status and living location.


Advanced thermal management methods have been the key issues for the rapid development of the electronic industry following Moore’s law. Droplet-based microfluidic cooling technologies are considered as promising solutions to conquer the major challenges of high heat flux removal and nonuniform temperature distribution in confined spaces for high performance electronic devices. In this paper, we review the state-of-the-art droplet-based microfluidic cooling methods in the literature, including the basic theory of electrocapillarity, cooling applications of continuous electrowetting (CEW), electrowetting (EW) and electrowetting-on-dielectric (EWOD), and jumping droplet microfluidic liquid handling methods. The droplet-based microfluidic cooling methods have shown an attractive capability of microscale liquid manipulation and a relatively high heat flux removal for hot spots. Recommendations are made for further research to develop advanced liquid coolant materials and the optimization of system operation parameters. It gradid metal .As illustrated in 2 by forced-air convection up to 790 W/cm2. The compact size of microchannels enables the feasibility of the direct integration of cooling units with electronic packages, which is believed to be a potential solution to the rapid increment of waste heat dissipation in advanced integrated circuit development. However, coolants require external pumps generating large pressure driving force in the microchannels. In order to further enhance the heat removal capacity of microchannel heat sinks, the flow rates of coolants need to be increased, which inevitably results in increased power consumption and an increased pump size. The same challenge is faced by microjet impingement cooling and liquid slug/plug cooling techniques. Discrete droplet cooling techniques driven by surface-tension modulation provide an energy-friendly option for an integrated on-chip cooling system. Without the requirement of powerful liquid pump and complex tubing connections, a high coolant flow rate can be achieved by periodic modulation of the surface tensions of the front and back menisci of each discrete microdroplet according to external applied fields [Currently, microfluidic thermal management methods normally consist of two types: a continuous liquid phase and a discrete liquid phase. Microchannel cooling and microjet impingement cooling continuously supply liquid convective flow or liquid jets into the hot zones, respectively, and waste heat is dissipated out of the chip as liquid flows out after the heat transfer process. Droplet-based microfluidic cooling techniques utilize discrete droplets ,20 and ld fields . Differed fields . The eleIn this work, we review the fundamental theory of droplet-based microfluidic thermal management methods and recent developments that are promising for integrated/embedded thermal management systems of high-performance electronic devices. Emphasis is placed on the electrocapillary-principle-related methods and other droplet-based methods based on surface-tension modulation. Technologies employing microdroplets in spray cooling are generally not covered, as they require a relatively high-power conventional mechanical actuator for droplet generation and transport. Relevant information is recommended to refer to previous reviews ,25. SectIn 1875, Gabriel Lippmann, a Nobel laureate in Physics 1908, first discovered electrocapillarity, a process by which the interfacial tension of a liquid metal  suspended in an inert electrolyte can be changed under an electrical potential applied to a liquid metal . As showc is the capacitance per unit area of EDL for CEW and EW, or the dielectric layer for EWOD. It should be noted that the interfacial tension , electrowetting (EW), and electrowetting on dielectric (EWOD), as illustrated in shown in a, while This section presents research on active droplet-based microfluidic cooling methods based on electrocapillary phenomena. It is divided by two subsections: CEW-based and EW- and EWOD-based applications.In 2000, Lee and Kim  demonstrDue to its fluidic property at room temperature and high thermal conductivity, mercury has been frequently used to demonstrate CEW-based electrical control of discrete droplet motion and DHT for compact thermal management applications. However, mercury is a toxic heavy metal which is not appropriate for general use in cooling applications. The liquid alloys have low melting points below or near room temperature and a good thermal property, as shown in After Lippmann discovered the electrocapillarity , numerous works have been performed on liquid metal  suspended in different aqueous electrolytes. Further development of CEW in practical applications has been impeded by its intrinsic disadvantage of the electrolytic decomposition of water. Water would easily decompose under an applied electrical potential of more than a few hundred millivolts . Until t® AF on the PCB board to ensure surface hydrophobicity. Conducting liquid droplets  were placed on the Teflon® AF coating layer and electrostatically actuated to transport across the hot spot (65 °C) at a switching frequency of 32 Hz, and the hot spot was cooled by 20 °C within 0.24 s [Chakrabarty’s research group from Duke University  are the n 0.24 s . Siliconn 0.24 s . Using tn 0.24 s , switchin 0.24 s . Based on 0.24 s , includin 0.24 s ) and pron 0.24 s ). A flown 0.24 s  also useAfter the EWOD-based cooling was successfully demonstrated by Pamula and Chakrabarty  in 2003,4). The overall heat transfer performance of the ionic liquids was not improved compared to that of DI water due to their low thermal conductivity and high viscosity. However, the ionic liquids demonstrated excellent thermal stability, as no evaporation occurred during the cooling process, while DI water showed vigorous evaporation under the same heat load. An attempt to increase the thermal conductivity of the ionic liquids was made by adding multiwall carbon nanotubes (MWCNTs) to the liquid droplets. Besides work on liquid coolants, efforts have also been made with respect to the fabrication of EWOD-based cooling devices. Cheng and Chen [At around the same period as Chakrabarty et al. in 2008, Kim’s research group from UCLA proposed and demonstrated the thermal switch cooling scheme using water and glycerin droplets actuated by coplanar EWOD chip as shown in and Chen  designedUnlike the single liquid phase heat transfer of the EWOD-based flow-through cooling schemes mentioned aforementioned, Park et al. ,51 utiliWith the aforementioned attractive cooling performances achieved by the EWOD-based methods, it is worth mentioning that all of these methods face serious failure issues of EWOD-based droplet actuation, such as dielectric breakdown and charging . In EWODApart from the active electrocapillary-based droplet-based techniques, a passive droplet-based liquid handling technology has recently been suggested for electronics cooling. It is called the planar jumping-droplet thermal diode, which was proposed by Chen’s group from Duke University . It consWith the rapid increase in packaging density and continuous reduction in device size, cooling issues have become a vital problem for extending the progression of Moore’s law and the further development of high-performance electronic devices. High heat flux, non-uniform temperature distribution, and space constraints in compact packaging are three major challenges that advanced thermal management methods must conquer. In terms of emerging cooling techniques, droplet-based microfluidic thermal management methods were first proposed in 2003 and have recently been vigorously investigated. In this review, we focus on droplet-based microfluidic cooling techniques based on surface-tension modulation, especially using the electrocapillary principle. Compared with other macroscale droplet-based cooling methods such as spray cooling, the surface-tension modulation-related microfluidic methods have the advantage of low energy consumption, easy integration with compact size, and selective cooling for hot spots. Among these droplet-based techniques, electrocapillary-based cooling techniques have been suggested as one of the most promising integrated/embedded thermal management approaches, due to their fast liquid actuation response under a low-power electrical field and the precise control of droplet motion with digital manipulation. Three types of electrocapillary-based active cooling techniques have been reviewed: continuous electrowetting (CEW), electrowetting (EW), and electrowetting on dielectric (EWOD).A passive cooling method was also introduced: the planar jumping-droplet thermal diode, whereby droplet actuation  does not require external energy input but uses the released excess surface energy during the coalescence process of the liquid droplet condensate on the superhydrophobic surface. Based on all analyses, droplet-based microfluidic thermal management methods have demonstrated an attractive potential for high performance electronic devices. Lastly, several future research directions are recommended: (1) The development of liquid coolant materials with good thermal property and controllable wettability under electrical field is highly encouraged. (2) Intelligent route design and feedback control for droplet transport based on temperature sensing for hot spots are key to improving system effectiveness. (3) More attention should be paid to the reliability of EWOD-based cooling devices, and further investigations on the mechanisms of dielectric breakdown and droplet coalescence at elevated temperatures are highly recommended for the long-term performance of EWOD-based cooling devices. (4) Investigations on the interference between the electric driving signal for electrocapillary-based cooling system and the digital information signal of the electronic devices are required since the cooling unit is required to be integrated into 3D stacked chips. Further reduction of the driving voltage of EWOD-based cooling techniques is also suggested.


Understanding how regulatory elements control mammalian gene expression is a challenge of post-genomic era. We previously reported that size of proximal promoter architecture predicted the breadth of expression (fraction of tissues in which a gene is expressed). Herein, the contributions of individual transcription factors (TFs) were quantified. Several technologies of statistical modelling were utilized and compared: tree models, generalized linear models , Bayesian GLMs and random forest. Both linear and non-linear modelling strategies were explored. Encouragingly, different models led to similar statistical conclusions and biological interpretations. The majority of ENCODE TFs correlated positively with housekeeping expression, a minority correlated negatively. Thus, housekeeping expression can be understood as a cumulative effect of many types of TF binding sites. This is accompanied by the exclusion of fewer types of binding sites for TFs which are repressors, or support cell lineage commitment or temporarily inducible or spatially-restricted expression. Quasi-likelihood was used to compensate for over-dispersion of the linear model . The GLMs produced vectors of correlation coefficients θ1-N (for N TFs which were the inputs for the model) plus the estimate for the intercept (θ0). Model parameters were by default returned on the scale defined by the reverse of the link function. These values could be transformed into the scale of model inputs by a reverse logit transformation. Standardized coefficients were the result of variant analyses where variances of independent and dependent variables were standardized to one. As all independent variables were on the same scale (TF counts), standardization was not essential. Unless otherwise stated, interaction terms were not included in models.GLMs are a family of models which generalize linear regression to response variables for which errors are not normally distributed. To specify a model one specifies the family of distributions from which errors derive and a link function. The link function can be non-linear and describes the relation between the mean of and the linear combination of the predictive variables in the model . BoE wasglmnet [glmnet is regularization which facilitates variable selection and shrinkage among the groups of correlated explanatory variables. This makes glmnet the method of choice for genomics applications (where the number of features tends to be high and the number of observations may be limited). The authors of the package use the metaphor of the fishing net catching “big fish”. The net ensures that only significant variables are selected to have non-zero coefficients in the final model [glmnet will favor either the lasso  or the ridge . The elastic net  is a compromise between lasso and ridge. The ridge penalty tends to shrink the coefficients of correlated variables so that they become more similar. In contrast, the lasso tends to promote one of the variables in a correlated group and discard the others. Both lasso and ridge were invoked through the function glmnet. Lambda is the parameter of regularization controlling the penalty imposed on maximum likelihood. The glmnet algorithm constructs a sequence of lambda values and plots the correlation coefficients of the model along this sequence  for both the regression coefficients (θ1–148) and the intercept (θ). The model was defined with an identical formula to the one used for glm and glmnet. The MCMC sampler was invoked using Rstanarm’s function stan_glm. Four MCMC chains were run for 1,000 iterations (split evenly between warm-up and sampling).For our Bayesian model, we used weak non-informative Gaussian priors The convergence between the chains was estimated using k-means implementation of the core R was used, namely the function kmeans. The option of the Forgy algorithm was specified. The clusters were defined in two dimensions. These clusters were used to construct a non-linear-response model with multinomial regression that was fitted with the glmnet package using the lasso penalty .The Rstanarm implementations of GLMs do not implement multinomial regression. Therefore, the response variable of multinomial regression had to be recoded as a binary variable (cluster II versus the other two clusters).The core R and the randomForest. Cross-validation was performed using 10-folds.A 148-variable random forest was built using R package S1 FigThis supplementary figure shows the correlogram of TFs color-coded by the strength and significance of their Spearman’s pairwise correlation coefficients.(EPS)Click here for additional data file.S2 FigThis supplementary figure contains a plot visualizing the random expectation of TF-correlations compared with the observed distribution. The determined thresholds of statistical significance are also visualized.(EPS)Click here for additional data file.S3 FigRNA Polymerase II, TAF1 and S2-phosphorylated Pol II sites were the most significant sources of variability.(EPS)Click here for additional data file.S4 FigThe regularization paths of: lasso, ridge, and the elastic net for the linear-response (A-C) and non-linear-response models (D-F) models are visualized in this supplementary figure.(EPS)Click here for additional data file.S5 FigGlmnet performs leave-one-out cross-validation after the data-set is grouped into ten folds (random partitions). The value of lambda.min reported by cross-validation is the value in the lambda sequence  which minimizes the cross-validated binomial deviance  and was used to report the values of the coefficients of the model. Panel A shows the cross-validation results for the lasso, panel B for the ridge, and panel C for the elastic net version of the GLM regression. Panel D shows cross-validation for the multinomial lasso of the non-linear-response model.(EPS)Click here for additional data file.S1 Dataset(TXT)Click here for additional data file.S2 DatasetNote this dataset contains redundant RefSeqs. Please, contact the corresponding author for details on post-processing and R scripts.(TXT)Click here for additional data file.S1 TableAll pairs of correlated TFs are given in this supplementary table.(TXT)Click here for additional data file.S2 TableModel terms correspond to ENCODE TFs cut off at the significance level of 0.05 . The table also lists pairwise TF interactions. The intercept is also shown on the logit scale.(TXT)Click here for additional data file.S3 TableCorrelation coefficients of different models were compared in this supplementary table.(TXT)Click here for additional data file.S4 Table(TXT)Click here for additional data file.